The Younger Dryas (YD, 12.9–11.7 ka) is the most recent, near-global interval of abrupt climate change with rates similar to modern global warming. Understanding the causes and biodiversity effects of YD climate changes requires determining the spatial fingerprints of past temperature changes. Here we build pollen-based and branched glycerol dialkyl glycerol tetraether-based temperature reconstructions in eastern North America (ENA) to better understand deglacial temperature evolution. YD cooling was pronounced in the northeastern United States and muted in the north central United States. Florida sites warmed during the YD, while other southeastern sites maintained a relatively stable climate. This fingerprint is consistent with an intensified subtropical high during the YD and demonstrates that interhemispheric responses were more complex spatially in ENA than predicted by the bipolar seesaw model. Reduced-amplitude or antiphased millennial-scale temperature variability in the southeastern United States may support regional hotspots of biodiversity and endemism.
Declining water levels and reduced natural discharge at springs, seeps, and phreatophyte areas primarily are the result of decades of groundwater development in the Death Valley regional flow system, in Nevada and California. A calibrated groundwater-flow model was used to simulate potential future effects of groundwater pumping on water levels and natural groundwater discharge in the study area. Effects of climate change on future groundwater pumping were not considered and were beyond the scope of the study. Four groundwater-pumping scenarios were developed by stakeholders to predict and compare (1) the extent of regional water-level declines; (2) drawdown at Devils Hole; and (3) reductions in natural discharge at select discharge areas, including the Amargosa Wild and Scenic River, the Ash Meadows discharge area, the Furnace Creek area, and Stump Spring. Scenarios were simulated from 1913 to 2120, with historical pumping occurring from 1913 to 2010, historical 2010 pumping rates projected from 2010 to 2020, and scenario pumping beginning in 2020. Pumping scenarios included a base case and scenarios A, B, and C. The base case projected 2010 pumping rates from 2010 to 2120, and scenarios A, B, and C projected base case pumping plus additional pumping at various locations from 2020 to 2120. By 2020, historical (1913–2020) pumping resulted in the propagation of simulated drawdown of 1 foot (ft) or more westward from Pahrump Valley to areas north of Shoshone in the Pahrump to Death Valley South (PDVS) groundwater basin and the merging of simulated 1-ft drawdown contours between the Alkali Flat–Furnace Creek Ranch (AFFCR) and Ash Meadows groundwater basins. In the base case scenario, extent and magnitude of simulated drawdown continued to increase in the Ash Meadows and AFFCR groundwater basins from 2020 to 2120. In the base case, the magnitude of simulated drawdown continued to increase in western Pahrump Valley from 2020 to 2120, whereas simulated water levels rose in eastern Pahrump Valley from 2020 to 2070 and then stabilized from 2070 to 2120. Scenarios A and B primarily affected the PDVS and AFFCR groundwater basins by increasing the magnitude of drawdown in 2120, compared to the base case. In scenario C, drawdown propagated throughout a high-transmissivity part of the carbonate aquifer known as the megachannel, greatly affecting water levels in the Ash Meadows discharge area. Scenario C resulted in an additional 10–100 ft of drawdown (compared to the base case) throughout the southeastern part of the Ash Meadows groundwater basin by 2120. Simulated drawdowns in Devils Hole in 2120 were 3.2, 3.4, 3.8, and 25.4 ft for the base case and scenarios A, B, and C, respectively. The federally mandated minimum water level for Devils Hole is 2.7 ft below a reference point. In 2020, the simulated water level in Devils Hole was above the minimum water level, at 1.7 ft below the reference. Simulated water levels in Devils Hole fell below the federally mandated water level by 2078, 2073, 2058, and 2025 for the base case and scenarios A, B, and C, respectively, assuming a hypothetical recharge scenario of constant natural recharge. Simulated reductions in predevelopment (natural) discharge at select discharge areas ranged from 3 to 38 percent by 2120 for all scenarios. Amargosa Wild and Scenic River was the least affected discharge area with simulated capture rates ranging from 3 to 4 percent of predevelopment discharge by 2120. Ash Meadows discharge area was greatly affected by groundwater pumping in scenario C with a simulated capture rate of 38 percent, compared to simulated capture rates of 8, 8, and 9 percent for the base case, scenario A, and scenario B, respectively, in 2120. Simulated capture rates in the Furnace Creek area ranged from 10 to 11 percent for all scenarios in 2120. Simulated capture rates at Stump Spring ranged from 32 to 36 percent for all scenarios in 2120.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205103","collaboration":"Prepared in cooperation with the Bureau of Land Management; National Park Service; Nevada Division of Wildlife; Nye County, Nevada; and U.S. Fish and Wildlife Service","usgsCitation":"Nelson, N.C., and Jackson, T.R., 2020, Simulated effects of pumping in the Death Valley Regional Groundwater Flow System, Nevada and California—Selected management scenarios projected to 2120: U.S. Geological Survey Scientific Investigations Report 2020–5103, 30 p., https://doi.org/10.3133/sir20205103.","productDescription":"Report: vii, 30 p.; Data Releases","onlineOnly":"Y","ipdsId":"IP-112177","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":379438,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5103/coverthb.jpg"},{"id":379439,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5103/sir20205103.pdf","text":"Report","size":"6.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020-5103"},{"id":379440,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9OBUPXU","text":"USGS data release","description":"USGS Data Release","linkHelpText":"MODFLOW-2005 models used to simulate effects of pumping in the Death Valley Regional Groundwater Flow System, Nevada and California—Selected management scenarios projected to 2120"},{"id":379476,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F75H7FH3","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Update to the groundwater withdrawals database for the Death Valley regional groundwater flow system, Nevada and California, 1913 -2010"},{"id":379477,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9HIYVG2","text":"USGS data release","description":"USGS Data Release","linkHelpText":"MODFLOW-2005 model and supplementary data used to characterize groundwater flow and effects of pumping in the Death Valley regional groundwater flow system, Nevada and California, with special reference to Devils Hole"}],"country":"United States","state":"California, Nevada","otherGeospatial":"Death Valley Regional Groundwater Flow System","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.3779296875,\n 33.62376800118811\n ],\n [\n -114.08203125,\n 33.62376800118811\n ],\n [\n -114.08203125,\n 38.62545397209084\n ],\n [\n -117.3779296875,\n 38.62545397209084\n ],\n [\n -117.3779296875,\n 33.62376800118811\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Nevada Water Science Center
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2730 N. Deer Run Road
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In 2015, about 84,600 million gallons per day (Mgal/d) of groundwater were withdrawn in the United States for various uses including public supply, self-supplied domestic, industrial, mining, thermoelectric power, aquaculture, livestock, and irrigation. Of this total, about 94 percent (79,200 Mgal/d) was withdrawn from principal aquifers, which are defined as regionally extensive aquifers or aquifer systems that have the potential to be used as sources of water of suitable quality and quantity to meet various needs. The remaining 6 percent (5,400 Mgal/d) was withdrawn from other, nonprincipal aquifers in the United States.
Sixty-six principal aquifers belonging to 5 major lithologic groups have been identified and delineated in the United States, including Puerto Rico and the U.S. Virgin Islands. Of the water withdrawn from principal aquifers in 2015, 81 percent (63,900 Mgal/d) was from the unconsolidated and semiconsolidated sand and gravel lithologic group, 7.1 percent (5,630 Mgal/d) was from the igneous and metamorphic-rock lithologic group, 6.8 percent (5,360 Mgal/d) was from the carbonate-rock lithologic group, 3.4 percent (2,680 Mgal/d) was from the sandstone lithologic group, and 2.2 percent (1,710 Mgal/d) was from the sandstone and carbonate-rock lithologic group.
The most heavily pumped of the 24 principal aquifers and aquifer systems within the unconsolidated and semiconsolidated sand and gravel lithologic group were the High Plains aquifer (12,300 Mgal/d), Mississippi River Valley alluvial aquifer (12,100 Mgal/d), Central Valley aquifer system (11,100 Mgal/d), and Basin and Range basin-fill aquifers (7,390 Mgal/d). Withdrawals for irrigation were 48,100 Mgal/d and accounted for 75 percent of the total withdrawals from this lithologic group. Although unconsolidated sand and gravel aquifers are widely distributed and were used as sources of water in all States except Hawaii and the U.S. Virgin Islands, 56 percent of the total withdrawn from unconsolidated and semiconsolidated sand and gravel aquifers was in just four States: California (15,600 Mgal/d), Arkansas (9,560 Mgal/d), Nebraska (5,570 Mgal/d), and Texas (4,830 Mgal/d).
The most heavily pumped of the seven principal aquifers within the igneous and metamorphic-rock lithologic group were the Snake River Plain (2,930 Mgal/d) and Columbia Plateau basaltic-rock aquifers (1,080 Mgal/d), which are located in the northwestern United States and together accounted for 71 percent of the water withdrawn from this lithologic group. Withdrawals for irrigation were 4,190 Mgal/d and accounted for more than 74 percent of the total withdrawals from this lithologic group. Seventy-eight percent of the withdrawals from igneous and metamorphic-rock aquifers were in three States: Idaho (3,230 Mgal/d), Washington (614 Mgal/d), and Oregon (528 Mgal/d).
The most heavily pumped of the 15 principal aquifers and aquifer systems within the carbonate-rock lithologic group were the Floridan aquifer system (3,180 Mgal/d) and the Biscayne aquifer (679 Mgal/d), which are in the southeastern United States and together accounted for almost 72 percent of the withdrawals from this lithologic group. Withdrawals for public supply (2,440 Mgal/d) and irrigation (1,610 Mgal/d) together accounted for almost 76 percent of the total withdrawals from this lithologic group. Although water was withdrawn from carbonate-rock aquifers in 35 States, 71 percent of the total withdrawn was in Florida (3,020 Mgal/d) and Georgia (785 Mgal/d).
The most heavily pumped of the 15 principal aquifers within the sandstone lithologic group was the Cambrian-Ordovician aquifer system (921 Mgal/d), which is in the north-central United States and accounted for 34 percent of the water withdrawn from this lithologic group. Withdrawals for public supply were 1,030 Mgal/d and accounted for 38 percent of the total withdrawals from this lithologic group. Although sandstone aquifers were used as sources of water in 32 States, 45 percent of the total withdrawn from sandstone aquifers was in five States: Minnesota (321 Mgal/d), Wisconsin (319 Mgal/d), Kansas (193 Mgal/d), Illinois (187 Mgal/d), and Pennsylvania (179 Mgal/d).
The most heavily pumped of the five principal aquifers and aquifer systems within the sandstone and carbonate-rock lithologic group were the Edwards-Trinity aquifer system (661 Mgal/d) in the south-central United States and the Valley and Ridge aquifers (551 Mgal/d) of the eastern United States, which together accounted for 71 percent of total withdrawals from this lithologic group. Withdrawals from sandstone and carbonate-rock aquifers for public-supply (713 Mgal/d), irrigation (469 Mgal/d), and self-supplied domestic (253 Mgal/d) uses accounted for about 84 percent of the total withdrawals from this lithologic group. Although water was withdrawn from sandstone and carbonate-rock aquifers in 25 States, 65 percent of the total withdrawn was in Texas (651 Mgal/d), Pennsylvania (238 Mgal/d), and Florida (223 Mgal/d).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1464","usgsCitation":"Lovelace, J.K., Nielsen, M.G., Read, A.L., Murphy, C.J., and Maupin, M.A., 2020, Estimated groundwater withdrawals from principal aquifers in the United States, 2015 (ver. 1.2, October 2020): U.S. Geological Survey Circular 1464, 70 p., https://doi.org/10.3133/cir1464.","productDescription":"Report: vii, 70 p.; Data Release","numberOfPages":"82","onlineOnly":"N","ipdsId":"IP-107784","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":374027,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/circ/1464/coverthb3.jpg"},{"id":375193,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/circ/1464/versionHist.txt","text":"Version History","description":"CIR 1464 Version 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U.S. Geological Survey
640 Grassmere Park, Suite 100
Nashville, Tennessee 37211
The Utica and Marcellus Shale Plays in the Appalachian Basin are the fourth and first largest natural gas producing plays in the United States, respectively. Hydrocarbon production generates large volumes of brine (“produced water”) that must be disposed of, treated, or reused. Though Marcellus brines have been studied extensively, there are few studies from the Utica Shale Play. This study presents new brine chemical analyses from 16 Utica Shale Play wells in Ohio and Pennsylvania. Results from Na–Cl–Br systematics and stable and radiogenic isotopes suggest that the Utica Shale Play brines are likely residual pore water concentrated beyond halite saturation during the formation of the Ordovician Beekmantown evaporative sequence. The narrow range of chemistry for the Utica Shale Play produced waters (e.g., total dissolved solids = 214–283 g/L) over both time and space implies a consistent composition for disposal and reuse planning. The amount of salt produced annually from the Utica Shale Play is equivalent to 3.4% of the annual U.S. halite production. Utica Shale Play brines have radium activities 580 times the EPA maximum contaminant level and are supersaturated with respect to barite, indicating the potential for surface and aqueous radium hazards if not properly disposed of.
This geologic map includes a trove of stratigraphic and geomorphic information that chronicles the inception and evolution of the lower Colorado River. The map area is located near the south end of the Lake Mead National Recreation Area about 80 km (50 mi) downstream from Hoover Dam. It spans parts of northwestern Arizona and southern Nevada near the south end of Cottonwood Valley. The map includes the Spirit Mountain SE 7.5' quadrangle and the southern part of the Spirit Mountain NE 7.5' quadrangle. The map area contains well-exposed Neogene and Quaternary strata and associated geomorphic features that record and are critical in dating the arrival of the Colorado River in the early Pliocene and the subsequent history of the river and its landscape through the Holocene. The valley is bounded on the west by the Newberry Mountains (Nevada) and on the east by the Black Mountains (Arizona) and includes part of Lake Mohave, a reservoir created by the completion of Davis Dam in 1951. This map does not include the geology of the reservoir floor and focuses only on surficial deposits.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3448","collaboration":"Prepared in cooperation with Nevada Bureau of Mines and Geology; Arizona Geological Survey; University of Nevada, Las Vegas, Department of Geoscience; University of Oklahoma School of Geosciences; and National Park Service","usgsCitation":"House, P.K., Crow, R.S., Pearthree, P.A., Brock-Hon, A.L., Schwing, J., Thacker, J.O., and Gootee, B.F., 2020, Surficial geologic map of the Spirit Mountain SE and part of the Spirit Mountain NE 7.5' quadrangles, Nevada and Arizona: U.S. Geological Survey Scientific Investigations Map 3448, pamphlet 30 p., scale 1:24,000, https://doi.org/10.3133/sim3448.","productDescription":"Pamphlet: iv, 30 p.; 1 Sheet: 38.50 x 43.00 inches; Database; Metadata; Readme file","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-094912","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":379010,"rank":5,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sim/3448/sim3448_metadata.xml","size":"18 KB","linkFileType":{"id":8,"text":"xml"},"description":"SIM 3448 metadata xml"},{"id":379009,"rank":4,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sim/3448/sim3448_metadata.txt","size":"16 KB","linkFileType":{"id":2,"text":"txt"},"description":"SIM 3448 metadata txt"},{"id":379008,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3448/sim3448_pamphlet.pdf","text":"Pamphlet","size":"18.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3448 Pamphlet"},{"id":379007,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3448/sim3448.pdf","text":"Map","size":"22.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3448"},{"id":495225,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_110667.htm","linkFileType":{"id":5,"text":"html"}},{"id":379011,"rank":6,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sim/3448/sim3448_readme.txt","size":"3 KB","linkFileType":{"id":2,"text":"txt"},"description":"SIM 3448 readme"},{"id":379012,"rank":7,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/sim/3448/sim3448_database.zip","size":"73.8 MB","linkFileType":{"id":6,"text":"zip"},"description":"SIM 3448 database (.zip)"},{"id":379006,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3448/coverthb.jpg"}],"country":"United States","state":"Arizona, Nevada","otherGeospatial":"Spirit Mountain quadrangle","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.61212158203124,\n 35.21420969483077\n ],\n [\n -114.33197021484375,\n 35.21420969483077\n ],\n [\n -114.33197021484375,\n 35.641673184600585\n ],\n [\n -114.61212158203124,\n 35.641673184600585\n ],\n [\n -114.61212158203124,\n 35.21420969483077\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contact Information, Geology, Minerals, Energy, & Geophysics Science Center
U.S. Geological Survey
2255 N. Gemini Drive
Flagstaff, AZ 86001-1600
Soil respiration is a primary component of the terrestrial carbon cycle. However, predicting the response of soil respiration to climate change remains a challenge due to the complex interactions between environmental drivers, especially plant phenology, temperature, and soil moisture. In this study, we use a 1‐D diffusion‐reaction model to calculate depth‐resolved CO2 production rates from soil CO2 concentrations and surface efflux observations in a subalpine meadow in the East River watershed, CO. Modeled rates are compared to in situ soil temperature and moisture conditions and MODIS satellite enhanced vegetation index (EVI) representing plant phenology across three hydrologically distinct growing seasons from 2016–2018. While soil respiration correlated with temperature on diel timescales (p < 0.05), seasonal variability was dominated by soil moisture and plant phenology (p < 0.05). We observed significant respiration increases in response to precipitation events; however, magnitude and duration were significantly higher in 2017 than 2016 despite similar wetting characteristics. Based on MODIS EVI, we suggest that the respiration response to rainfall is controlled by plant phenology, which in turn reflects the capacity of plants to respond to precipitation via increased photosynthesis and autotrophic respiration, behavior that is not captured in typical soil respiration pulse models. Projected changes in montane climate such as earlier snowmelt and prolonged fore‐summer drought may decrease soil respiration fluxes by decreasing the overlap between peak productivity and the summer monsoon. Finally, we observed significant late season CO2 fluxes from the deep subsoil (>165 cm) that support growing evidence for the importance of subsoil processes in driving integrated respiration fluxes.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020JG005924","usgsCitation":"Winnick, M., Lawrence, C.R., McCormick, M., Druhan, J., and Maher, K., 2020, Soil respiration response to rainfall modulated by plant phenology in a montane meadow, East River, Colorado, USA: Journal of Geophysical Research Biogeosciences, v. 125, no. 10, e2020JG005924, 20 p., https://doi.org/10.1029/2020JG005924.","productDescription":"e2020JG005924, 20 p.","ipdsId":"IP-108485","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":455072,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.osti.gov/biblio/1664387","text":"External Repository"},{"id":381100,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"East River watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -107.061767578125,\n 38.50626606567193\n ],\n [\n -106.82968139648436,\n 38.50626606567193\n ],\n [\n -106.82968139648436,\n 38.922023851268925\n ],\n [\n -107.061767578125,\n 38.922023851268925\n ],\n [\n -107.061767578125,\n 38.50626606567193\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"125","issue":"10","noUsgsAuthors":false,"publicationDate":"2020-10-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Winnick, Mathew","contributorId":245458,"corporation":false,"usgs":false,"family":"Winnick","given":"Mathew","affiliations":[{"id":36396,"text":"University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":806219,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lawrence, Corey R. 0000-0001-6143-7781","orcid":"https://orcid.org/0000-0001-6143-7781","contributorId":202390,"corporation":false,"usgs":true,"family":"Lawrence","given":"Corey","email":"","middleInitial":"R.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":806220,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McCormick, Maeve","contributorId":245459,"corporation":false,"usgs":false,"family":"McCormick","given":"Maeve","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":806221,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Druhan, Jennifer","contributorId":245460,"corporation":false,"usgs":false,"family":"Druhan","given":"Jennifer","affiliations":[{"id":36403,"text":"University of Illinois","active":true,"usgs":false}],"preferred":false,"id":806222,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Maher, Kate","contributorId":245461,"corporation":false,"usgs":false,"family":"Maher","given":"Kate","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":806223,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70215178,"text":"70215178 - 2020 - Estimating the net costs of brine production and disposal to expand pressure-limited dynamic capacity for basin-scale CO2 storage in a saline formation","interactions":[],"lastModifiedDate":"2020-10-09T12:45:17.757956","indexId":"70215178","displayToPublicDate":"2020-10-09T07:39:43","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2049,"text":"International Journal of Greenhouse Gas Control","active":true,"publicationSubtype":{"id":10}},"title":"Estimating the net costs of brine production and disposal to expand pressure-limited dynamic capacity for basin-scale CO2 storage in a saline formation","docAbstract":"If carbon capture and storage (CCS) needs to be deployed at basin- or larger-scale, it is likely that multiple sites will be injecting carbon dioxide (CO2) into the same geologic formation. This could lead to excessive pressure buildup, overlapping induced pressure fronts, and pressure interference with neighboring uses of the subsurface. Extracting the in situ brine from the storage formation could be necessary to relieve pressure constraints; control migration of the CO2 plume, displaced brine, and the induced pressure front; and sequester more CO2 while reducing potential risks. Such active pressure management could be very costly, and it could present a formidable economic constraint on the feasible scale of deployment of CCS. Alternatively, there may be high-injectivity zones (“storage sweet spots”) where a significant volume of CO2 could be stored without producing brine. For simulated deployment of CO2 storage sites across the Illinois Basin, the results of this study suggest that brine production could be required to sequester 20 % or more of the regional CO2 emissions of major stationary sources in the Mount Simon Sandstone saline formation. In some cases, brine production could expand pressure-limited CO2 storage capacity enough to more than compensate for the additional costs of pressure management, but only if produced brine could be cheaply reinjected onsite for disposal in an overlying geologic formation. With or without brine production, this study found that the lowest-cost deployment option was to inject CO2 only into a potential storage sweet spot of the Mount Simon Sandstone.
Azimuthal variations in receiver function conversions can image lithospheric structural contrasts and anisotropic fabrics that together compose tectonic grain. We apply this method to data from EarthScope Transportable Array in Alaska and additional stations across the northern Cordillera. The best‐resolved quantities are the strike and depth of dipping fabric contrasts or interfaces. We find a strong geographic gradient in such anomalies, with large amplitudes extending inboard from the present‐day subduction margin, the Aleutian arc, and an influence of flat‐slab subduction of the Yakutat microplate north of the Denali fault. An east–west band across interior Alaska shows low‐amplitude crustal anomalies. Anomaly amplitudes correlate with structural intensity (density of aligned geological elements), but are the highest in areas of strong Cenozoic deformation, raising the question of an influence of current stress state. Imaged subsurface strikes show alignment with surface structures. We see concentric strikes around arc volcanoes implying dipping magmatic structures and fabric into the middle crust. Regions with present‐day weaker deformation show lower anomaly amplitudes but structurally aligned strikes, suggesting pre‐Cenozoic fabrics may have been overprinted or otherwise modified. We observe general coherence of the signal across the brittle‐plastic transition. Imaged crustal fabrics are aligned with major faults and shear zones, whereas intrafault blocks show imaged strikes both parallel to and at high angles to major block‐bounding faults. High‐angle strikes are subparallel to neotectonic deformation, seismicity, fault lineaments, and prominent metallogenic belts, possibly due to overprinting and/or co‐evolution with fault‐parallel fabrics. We suggest that the underlying tectonic grain in the northern Cordillera is broadly distributed rather than strongly localized. Receiver functions thus reveal key information about the nature and continuity of tectonic fabrics at depth and can provide unique insights into the deformation history and distribution of regional strain in complex orogenic belts.
Methods were developed for measuring immune function in Micropterus dolomieu (smallmouth bass). The ultimate objective is to monitor and evaluate changes over time in immune status and disease resistance in conjunction with other characteristics of fish health and environmental stressors. To test these methods for utility in ecotoxicological studies, 192 smallmouth bass, age 2 years and older, were collected from three sites within the Susquehanna River Basin and one site in the Ohio River Basin during spring and fall 2016 and 2017. The anterior kidney was aseptically removed and homogenized for leukocyte isolation. Leukocytes were tested for bactericidal activity against two species of bacteria; respiratory burst activity when stimulated with phorbol 12-myristate 13-acetate; and mitogenesis activity when stimulated with concanavalin A, phytohemagglutinin, and lipopolysaccharide. Tissues were preserved for histopathological analyses.
Two of the sites were part of a monitoring program at which surface-water samples were collected monthly (bimonthly in spring) for chemical contaminants. Significant seasonal and (or) site differences in all three immune function tests were observed. Interpretations of seasonal trends in immune function of wild fish or correlations with environmental variables and other factors are difficult to make owing to the complex nature of the immune response and the environment. Differences in immune function could potentially be related to a variety of confounding factors; therefore, additional endpoints and repeated sampling over an extended period are essential to draw conclusions on the immune status of wild fish.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201077","collaboration":"Prepared in cooperation with Pennsylvania Department of Environmental Protection","usgsCitation":"Smith, C.R., Ottinger, C.A., Walsh, H.L., and Blazer, V.S., 2020, Development of a suite of functional immune assays and initial assessment of their utility in wild smallmouth bass health assessments: U.S. Geological Survey Open-File Report 2020–1077, 23 p., https://doi.org/10.3133/ofr20201077.","productDescription":"vii, 23 p.","numberOfPages":"23","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-118051","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":379041,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1077/ofr20201077.pdf","text":"Report","size":"13.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1077"},{"id":379040,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1077/coverthb.jpg"}],"country":"United States","state":"Pennsylvania","otherGeospatial":"Tionesta Lake, Pine Creek, Upper Juniata River, West Branch Mahantango Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -79.79919433593749,\n 41.30257109430557\n ],\n [\n -77.38220214843749,\n 41.30257109430557\n ],\n [\n -77.38220214843749,\n 42.00032514831621\n ],\n [\n -79.79919433593749,\n 42.00032514831621\n ],\n [\n -79.79919433593749,\n 41.30257109430557\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Eastern Ecological Science Center
U.S. Geological Survey
11649 Leetown Road
Kearneysville, WV 25430
Shallowly dipping (<30°) low‐angle normal faults (LANFs) have been documented globally; however, examples of active LANFs in continental settings are limited. The western margin of the Panamint Range in eastern California is defined by a LANF that dips west beneath Panamint Valley and has evidence of Quaternary motion. In addition, high‐angle dextral‐oblique normal faults displace middle to late Quaternary alluvial fans near the range front. To image shallow (<1 km depth), crosscutting relationships between the low‐ and high‐angle faults along the range front, we acquired two high‐resolution P wave seismic reflection profiles. The northern, 4.6‐km‐long profile crosses the 2‐km‐wide Wildrose graben and the southern, 0.8‐km‐long profile extends onto the Panamint Valley playa, ~7.5 km S of Ballarat, CA. The profile across the Wildrose graben reveals a robust, low‐angle reflector interpreted to represent the LANF separating Plio‐Pleistocene alluvial fanglomerate and Proterozoic metasedimentary deposits. High‐angle faults interpreted in the seismic profile correspond to fault scarps on Quaternary alluvial fan surfaces. Interpretation of the reflection data suggests that the high‐angle faults vertically displace the LANF up to 80 m within the Wildrose graben. Similarly, the profile south of Ballarat reveals a low‐angle reflector, which appears both rotated and displaced up to 260 m by high‐angle faults. These results suggest that near the Panamint range front, the high‐angle faults are the dominant active structures. We conclude that at least at shallow (<1 km) depths, the LANF we imaged is not active today.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2020JB020243","usgsCitation":"Gold, R.D., Stephenson, W.J., Briggs, R.W., DuRoss, C., Kirby, E., Woolery, E.W., Delano, J., and Odum, J., 2020, Seismic reflection imaging of the low-angle Panamint normal fault system, eastern California: JGR Solid Earth, v. 125, no. 11, e2020JB020243, 18 p., https://doi.org/10.1029/2020JB020243.","productDescription":"e2020JB020243, 18 p.","ipdsId":"IP-122325","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":455104,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://cdr.lib.unc.edu/downloads/gb19fg41w","text":"External Repository"},{"id":436762,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9YY18PF","text":"USGS data release","linkHelpText":"Seismic reflection imaging of the low-angle Panamint normal fault system, eastern California, 2018"},{"id":382016,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Panamint Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.90527343750001,\n 34.95799531086792\n ],\n [\n -116.3671875,\n 34.95799531086792\n ],\n [\n -116.3671875,\n 37.125286284966805\n ],\n [\n -117.90527343750001,\n 37.125286284966805\n ],\n [\n -117.90527343750001,\n 34.95799531086792\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"125","issue":"11","noUsgsAuthors":false,"publicationDate":"2020-11-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Gold, Ryan D. 0000-0002-4464-6394 rgold@usgs.gov","orcid":"https://orcid.org/0000-0002-4464-6394","contributorId":3883,"corporation":false,"usgs":true,"family":"Gold","given":"Ryan","email":"rgold@usgs.gov","middleInitial":"D.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":807815,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stephenson, William J. 0000-0001-8699-0786 wstephens@usgs.gov","orcid":"https://orcid.org/0000-0001-8699-0786","contributorId":695,"corporation":false,"usgs":true,"family":"Stephenson","given":"William","email":"wstephens@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":807816,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Briggs, Richard W. 0000-0001-8108-0046 rbriggs@usgs.gov","orcid":"https://orcid.org/0000-0001-8108-0046","contributorId":139002,"corporation":false,"usgs":true,"family":"Briggs","given":"Richard","email":"rbriggs@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":807817,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"DuRoss, Christopher 0000-0002-6963-7451 cduross@usgs.gov","orcid":"https://orcid.org/0000-0002-6963-7451","contributorId":152321,"corporation":false,"usgs":true,"family":"DuRoss","given":"Christopher","email":"cduross@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":807818,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kirby, Eric 0000-0002-5701-8688","orcid":"https://orcid.org/0000-0002-5701-8688","contributorId":197171,"corporation":false,"usgs":false,"family":"Kirby","given":"Eric","email":"","affiliations":[],"preferred":false,"id":807819,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Woolery, Edward W 0000-0003-3398-5830","orcid":"https://orcid.org/0000-0003-3398-5830","contributorId":192994,"corporation":false,"usgs":false,"family":"Woolery","given":"Edward","email":"","middleInitial":"W","affiliations":[],"preferred":false,"id":807820,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Delano, Jaime 0000-0003-2601-2600","orcid":"https://orcid.org/0000-0003-2601-2600","contributorId":225594,"corporation":false,"usgs":false,"family":"Delano","given":"Jaime","affiliations":[{"id":6605,"text":"USGS","active":true,"usgs":false}],"preferred":false,"id":807821,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Odum, Jackson K. 0000-0003-4697-2430 odum@usgs.gov","orcid":"https://orcid.org/0000-0003-4697-2430","contributorId":1365,"corporation":false,"usgs":true,"family":"Odum","given":"Jackson K.","email":"odum@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":807822,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70215443,"text":"70215443 - 2020 - The eruptive history, magmatic evolution, and influence of glacial ice at long-lived Akutan volcano, eastern Aleutian Islands, Alaska, USA","interactions":[],"lastModifiedDate":"2020-10-20T13:57:30.629194","indexId":"70215443","displayToPublicDate":"2020-10-06T08:49:00","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1723,"text":"GSA Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"The eruptive history, magmatic evolution, and influence of glacial ice at long-lived Akutan volcano, eastern Aleutian Islands, Alaska, USA","docAbstract":"New 40Ar/39Ar and whole-rock geochemical data are used to develop a detailed eruptive chronology for Akutan volcano, Akutan Island, Alaska, USA, in the eastern Aleutian island arc. Akutan Island (166°W, 54.1°N) is the site of long-lived volcanism and the entire island comprises volcanic rocks as old as 3.3 Ma. Our current study is on the 225 km2 western half of the island, where our results show that the focus of volcanism has shifted over the last ∼700 k.y., and that on occasion, multiple volcanic centers have been active over the same period, including within the Holocene. Incremental heating experiments resulted in 56 40Ar/39Ar plateau ages and span 2.3 Ma to 9.2 ka.
Eruptive products of all units are primarily tholeiitic and medium-K, and range from basalt to dacite. Rare calc-alkaline lavas show evidence suggesting their formation via mixing of mafic and evolved magmas, not via crystallization-derived differentiation through the calc-alkaline trend. Earliest lavas are broadly dispersed and are almost exclusively mafic with high and variable La/Yb ratios that are likely the result of low degrees of partial mantle melting. Holocene lavas all fall along a single tholeiitic, basalt-to-dacite evolutionary trend and have among the lowest La/Yb ratios, which favors higher degrees of mantle melting and is consistent with the increased magma flux during this time. A suite of xenoliths, spanning a wide range of compositions, are found in the deposits of the 1.6 ka caldera-forming eruption. They are interpreted to represent completely crystallized liquids or the crystal residuum from tholeiitic fractional crystallization of the active Akutan magma system.
The new geochronologic and geochemical data are used along with existing geodetic and seismic interpretations from the island to develop a conceptual model of the active Akutan magma system. Collectively, these data are consistent with hot, dry magmas that are likely stored at 5−10 km depth prior to eruption. The prolonged eruptive activity at Akutan has also allowed us to evaluate patterns in lava-ice interactions through time as our new data and observations suggest that the influence of glaciation on eruptive activity, and possible magma composition, is more pronounced at Akutan than has been observed for other well-studied Aleutian volcanoes to the west.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/B35667.1","usgsCitation":"Coombs, M.L., and Brian Jicha, 2020, The eruptive history, magmatic evolution, and influence of glacial ice at long-lived Akutan volcano, eastern Aleutian Islands, Alaska, USA: GSA Bulletin, 29 p., https://doi.org/10.1130/B35667.1.","productDescription":"29 p.","ipdsId":"IP-116599","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":379541,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Aleutian Islands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -169.62890625,\n 50.62507306341435\n ],\n [\n -152.9296875,\n 50.62507306341435\n ],\n [\n -152.9296875,\n 58.90464570302001\n ],\n [\n -169.62890625,\n 58.90464570302001\n ],\n [\n -169.62890625,\n 50.62507306341435\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationDate":"2020-10-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Coombs, Michelle L. 0000-0002-6002-6806 mcoombs@usgs.gov","orcid":"https://orcid.org/0000-0002-6002-6806","contributorId":2809,"corporation":false,"usgs":true,"family":"Coombs","given":"Michelle","email":"mcoombs@usgs.gov","middleInitial":"L.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":802217,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brian Jicha","contributorId":243421,"corporation":false,"usgs":false,"family":"Brian Jicha","affiliations":[{"id":34113,"text":"University of Wisconsin Madison","active":true,"usgs":false}],"preferred":false,"id":802218,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70215059,"text":"70215059 - 2020 - Examination of inertinite within immature Eagle Ford Shale at the nanometer-scale using atomic force microscopy-based infrared spectroscopy","interactions":[],"lastModifiedDate":"2020-10-29T15:10:52.865686","indexId":"70215059","displayToPublicDate":"2020-10-05T08:24:54","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":"Examination of inertinite within immature Eagle Ford Shale at the nanometer-scale using atomic force microscopy-based infrared spectroscopy","docAbstract":"The nanoscale molecular composition of sedimentary organic matter is challenging to characterize in situ given the limited tools available that can adequately interrogate its complex chemical structure. This is a particularly relevant issue in source rocks, as kerogen composition will strongly impact its reactivity and so is critical to understanding petroleum generation processes during catagenesis. The recent advent of tip-enhanced analytical methods, such as atomic force microscopy-based infrared spectroscopy (AFM-IR), has allowed for the major compositional features of kerogen and other types of in situ organic matter to be elucidated at spatial resolutions at or below 50 nm. Here AFM-IR was applied to examine inertinite, an important organic matter type, present in a thermally immature Eagle Ford calcareous mudstone. The data show that the nanoscale molecular composition of the examined inertinite is (i) less heterogeneous than solid bitumen in more thermally mature Eagle Ford samples and (ii) more hydrogen- and oxygen-rich than inertinite examined in the New Albany Shale.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.coal.2020.103608","usgsCitation":"Jubb, A., Hackley, P.C., Birdwell, J.E., Hatcherian, J.J., and Qu, J., 2020, Examination of inertinite within immature Eagle Ford Shale at the nanometer-scale using atomic force microscopy-based infrared spectroscopy: International Journal of Coal Geology, v. 231, 103608, 4 p., https://doi.org/10.1016/j.coal.2020.103608.","productDescription":"103608, 4 p.","ipdsId":"IP-120851","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":455138,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.coal.2020.103608","text":"Publisher Index Page"},{"id":379165,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas","otherGeospatial":"Eagle Ford Shale, Bechtel Well","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -98.14773559570312,\n 28.810986808864513\n ],\n [\n -97.88955688476562,\n 28.810986808864513\n ],\n [\n -97.88955688476562,\n 29.012944302424863\n ],\n [\n -98.14773559570312,\n 29.012944302424863\n ],\n [\n -98.14773559570312,\n 28.810986808864513\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"231","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Jubb, Aaron M. 0000-0001-6875-1079","orcid":"https://orcid.org/0000-0001-6875-1079","contributorId":201978,"corporation":false,"usgs":true,"family":"Jubb","given":"Aaron M.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":800664,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hackley, Paul C. 0000-0002-5957-2551 phackley@usgs.gov","orcid":"https://orcid.org/0000-0002-5957-2551","contributorId":592,"corporation":false,"usgs":true,"family":"Hackley","given":"Paul","email":"phackley@usgs.gov","middleInitial":"C.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":800665,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Birdwell, Justin E. 0000-0001-8263-1452 jbirdwell@usgs.gov","orcid":"https://orcid.org/0000-0001-8263-1452","contributorId":3302,"corporation":false,"usgs":true,"family":"Birdwell","given":"Justin","email":"jbirdwell@usgs.gov","middleInitial":"E.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":800666,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hatcherian, Javin J. 0000-0001-9151-6798 jhatcherian@usgs.gov","orcid":"https://orcid.org/0000-0001-9151-6798","contributorId":195770,"corporation":false,"usgs":true,"family":"Hatcherian","given":"Javin","email":"jhatcherian@usgs.gov","middleInitial":"J.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":800667,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Qu, Jing","contributorId":242671,"corporation":false,"usgs":false,"family":"Qu","given":"Jing","affiliations":[{"id":13359,"text":"University of Delaware","active":true,"usgs":false}],"preferred":false,"id":800668,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70215254,"text":"70215254 - 2020 - Linking mesoscale meteorology with extreme landscape response: Effects of narrow cold frontal rainbands (NCFR)","interactions":[],"lastModifiedDate":"2020-10-14T12:30:56.62952","indexId":"70215254","displayToPublicDate":"2020-10-04T07:23:39","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":6454,"text":"Journal of Geophysical Research - Earth Surface","active":true,"publicationSubtype":{"id":10}},"title":"Linking mesoscale meteorology with extreme landscape response: Effects of narrow cold frontal rainbands (NCFR)","docAbstract":"Landscapes evolve in response to prolonged and/or intense precipitation resulting from atmospheric processes at various spatial and temporal scales. Whereas synoptic (large‐scale) features (e.g., atmospheric rivers and hurricanes) govern regional‐scale hydrologic hazards such as widespread flooding, mesoscale features such as thunderstorms or squall lines are more likely to trigger localized geomorphic hazards such as landslides. Thus, to better understand relations between hydrometeorological drivers and landscape response, a knowledge of mesoscale meteorology and its impacts is needed. Here we investigate the extreme geomorphic response associated with one type of mesoscale meteorological feature, the narrow cold frontal rainband (NCFR). Resulting from low‐level convergence and shallow convection along a cold front, NCFRs are narrow bands of high‐intensity rainfall that occur in midlatitude areas of the world. Our study examines an NCFR impacting the Sierra Nevada foothills (California, USA) that initiated over 500 landslides, mobilized ~360,000 metric tons of sediment to the fluvial system (as much as 16 times the local annual sediment yield), and severely damaged local infrastructure and regional water transport facilities. Coupling geomorphological field investigations with meteorological analyses, we demonstrate that precipitation associated with the NCFR was both intense (maximum 15 min intensity of 70 mm/hr) and localized, resulting in a highly concentrated band of shallow landsliding. This meteorological phenomenon likely plays an important role in landscape evolution and hazard initiation. Other types of mesoscale meteorological features also occur globally and offer new avenues for understanding the effects of storms on landscapes.
Eastern oysters have been acknowledged for their important contribution to human well-being by providing goods and services including nitrogen removal from water bodies. In this study, we integrated daily environmental data (2008–2016) and filtration rate model parameter uncertainty to estimate nitrogen removal from denitrification and nitrogen burial services provided by the current extent of oyster (Crassostrea virginica) reefs in Mobile Bay, Alabama. Oyster landing data (2008–2016) in the Bay were also used to estimate nitrogen removal through oyster harvest. A replacement cost method using an engineering solution from wastewater treatment plants was implemented to quantify the economic benefit of the nitrogen removal. The estimated total nitrogen removal services provided by oyster reefs in Mobile Bay was 34,911 ± 5,032 kg N yr−1 (mean ± 1sd), in which 22,095 ± 3,305 kg N yr−1 from denitrification, 11,047 ± 1,652 kg N yr−1 from burial of nitrogen into sediments and 1,769 ± 876 kg N yr−1 by oyster harvest. The mean economic benefit was $76,455 ± 11,020 yr−1 which was estimated as $73.2 ± 11.5 ha−1 yr−1. This method could be used for any time period to estimate the nitrogen removal service in Mobile Bay. With proper modification of model parameters, this method could also be used elsewhere to estimate nitrogen removal services provided by oysters.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2020.106541","usgsCitation":"Lai, Q., Irwin, E.R., and Zhang, Y., 2020, Estimating nitrogen removal services of eastern oyster (Crassostrea virginica) in Mobile Bay, Alabama: Ecological Indicators, v. 117, p. 1-9, https://doi.org/10.1016/j.ecolind.2020.106541.","productDescription":"106541, 9 p.","startPage":"1","endPage":"9","ipdsId":"IP-109626","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":455156,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolind.2020.106541","text":"Publisher Index Page"},{"id":395631,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alabama","otherGeospatial":"Gulf of Mexico, Mobile Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.25042724609374,\n 30.23652704486517\n ],\n [\n -88.06228637695312,\n 30.203300547277813\n ],\n [\n -87.69012451171875,\n 30.22466172703242\n ],\n [\n -87.88375854492186,\n 30.456960567387625\n ],\n [\n -87.85491943359375,\n 30.822063696500948\n ],\n [\n -88.05130004882812,\n 30.86686781614027\n ],\n [\n -88.13232421875,\n 30.657996912582398\n ],\n [\n -88.25042724609374,\n 30.23652704486517\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"117","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lai, Quan","contributorId":204521,"corporation":false,"usgs":false,"family":"Lai","given":"Quan","email":"","affiliations":[{"id":13360,"text":"Auburn University","active":true,"usgs":false}],"preferred":false,"id":833537,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Irwin, Elise R. 0000-0002-6866-4976 eirwin@usgs.gov","orcid":"https://orcid.org/0000-0002-6866-4976","contributorId":2588,"corporation":false,"usgs":true,"family":"Irwin","given":"Elise","email":"eirwin@usgs.gov","middleInitial":"R.","affiliations":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":833538,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zhang, Yaoqi","contributorId":275164,"corporation":false,"usgs":false,"family":"Zhang","given":"Yaoqi","email":"","affiliations":[{"id":13360,"text":"Auburn University","active":true,"usgs":false}],"preferred":false,"id":833750,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70260213,"text":"70260213 - 2020 - Two ensemble approaches for forecasting sulfur dioxide concentrations from Kīlauea volcano","interactions":[],"lastModifiedDate":"2024-10-30T11:58:35.950719","indexId":"70260213","displayToPublicDate":"2020-10-01T06:55:48","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3735,"text":"Weather and Forecasting","active":true,"publicationSubtype":{"id":10}},"title":"Two ensemble approaches for forecasting sulfur dioxide concentrations from Kīlauea volcano","docAbstract":"Kīlauea volcano, located on the island of Hawaii, is one of the most active volcanoes in the world. It was in a state of nearly continuous eruption from 1983 to 2018 with copious emissions of sulfur dioxide (SO2) that affected public health, agriculture, and infrastructure over large portions of the island. Since 2010, the University of Hawaiʻi at Mānoa provides publicly available vog forecasts that began in 2010 to aid in the mitigation of volcanic smog (or “vog”) as a hazard. In September 2017, the forecast system began to produce operational ensemble forecasts. The months that preceded Kīlauea’s historic lower east rift zone eruption of 2018 provide an opportunity to evaluate the newly implemented air quality ensemble prediction system and compare it another approach to the generation of ensemble members. One of the two approaches generates perturbations in the wind field while the other perturbs the sulfur dioxide (SO2) emission rate from the volcano. This comparison has implications for the limits of forecast predictability under the particularly dynamic conditions at Kīlauea volcano. We show that for ensemble forecasts of SO2 generated under these conditions, the uncertainty associated with the SO2 emission rate approaches that of the uncertainty in the wind field. However, the inclusion of a fluctuating SO2 emission rate has the potential to improve the prediction of the changes in air quality downwind of the volcano with suitable postprocessing.
The Mississippi Alluvial Valley (MAV) is a 9 million ha (22-million-acre) floodplain that supports a diverse and ecologically rich bottomland hardwood forest ecosystem – one of the most productive in North America. It extends from roughly Cape Girardeau, Missouri, to the Gulf of Mexico and features a mosaic of ridges, swales, meander belts, and backswamps. Small changes in elevation (<1 foot) in the MAV are associated with large shifts in hydrology, which in turn, strongly affect plant and animal community composition and structure. The resultant diversity contributes to a fertile and productive floodplain. General forest types in the MAV include: Oak-gum-cypress (41%), elm-ash-cottonwood (29%), oakhickory (17%), and the remainder is other forest types (Oswalt 2013). Within the oak-gum-cypress and elm-ash-cottonwood categories, sugarberry-hackberry-elm-green ash and sweetgum-Nuttall oak-willow oak forest types account for close to one-half of MAV bottomland forest acreage, while baldcypress-tupelo forests are about 16 percent (Oswalt 2013). Although we emphasize bottomland hardwood habitat and associated bird species, this planning effort includes analyses based upon all forest types within the MAV. Hence, the term ‘forest’ refers to all forest types in the MAV.
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Our objective was to identify habitat characteristics important to Gag, and their effect on the probability of Gag occurrence. We obtained data from three separate fisheries-independent video surveys that sampled in the eastern GOM from 2010-2017: the National Atmospheric and Oceanic Administration (NOAA) Panama City, FL Office, the NOAA Southeast Area Monitoring and Assessment Program, and the Florida Fish and Wildlife Research Institute. We ran a separate mixed effects logistic regression for each survey, and used Akaike’s Information Criteria to determine the best fitting models. Some variables - percent rock coverage, vertical relief, latitude, and depth - were present in all confidence models. Depth did not have the same relationship with Gag across all surveys, suggesting that shallower habitats (<50 m) might be more suitable for juveniles, whereas deeper habitats (>50 m) might be more suitable for adults. Managers may be able to help Gag and encourage their recovery by using these data to establish or expand protected areas throughout shallower waters.
","conferenceTitle":"Annual Meeting of the American Fisheries Society. Virtual","conferenceDate":"Aug 28 - Sep 3, 2020","language":"English","usgsCitation":"Alvarez, G., Gandy, D., Irwin, B., Jennings, C.A., and Fox, A., 2020, Using video survey to examine the effect of habitat on gag grouper encounter, Annual Meeting of the American Fisheries Society. 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In its efforts to compile information on contaminant indicators in the Gulf of Maine, ESIP identified gaps in monitoring information and worked in partnership with the Gulf of Maine Council and other organizations to fill these gaps. The monitoring and data gaps identified by ESIP indicated that data on contaminants in intertidal/subtidal sediments were lacking for the Bay of Fundy. To address this data gap, the Association of US Delegates to the Gulf of Maine Council on the Marine Environment contracted Eastern Charlotte Waterways Inc., an independent non-governmental organization, to conduct a contaminant monitoring and analysis project funded by Environment and Climate Change Canada . This report summarizes the data produced from this sediment analysis project.","language":"English","publisher":"Gulf of Maine Council","collaboration":"Dalhousie University, US EPA, Bowdoin College, Lawrence LeBlanc Consulting","usgsCitation":"Latimer, J.S., Page, D., Elskus, A., LeBlanc, L., Harding, G., and Wells, P.G., 2020, The collection and analysis of Bay of Fundy sediment under contract between the association of US delegates to the Gulf of Maine Council on the marine environment and eastern Charlotte waterways for contaminant monitoring and analysis, 92 p.","productDescription":"92 p.","ipdsId":"IP-118574","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":371,"text":"Maine Water Science Center","active":true,"usgs":true}],"links":[{"id":378918,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":378842,"type":{"id":15,"text":"Index Page"},"url":"https://gulfofmaine.org/public/gulf-of-maine-council-on-the-marine-environment/publications/"}],"country":"United States, Canada","otherGeospatial":"Gulf of Maine","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -71.982421875,\n 41.65649719441145\n ],\n [\n -63.30322265625001,\n 41.65649719441145\n ],\n [\n -63.30322265625001,\n 46.118941506107056\n ],\n [\n -71.982421875,\n 46.118941506107056\n ],\n [\n -71.982421875,\n 41.65649719441145\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Latimer, James S","contributorId":222883,"corporation":false,"usgs":false,"family":"Latimer","given":"James","email":"","middleInitial":"S","affiliations":[{"id":6784,"text":"US EPA","active":true,"usgs":false}],"preferred":false,"id":799828,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Page, David","contributorId":222884,"corporation":false,"usgs":false,"family":"Page","given":"David","email":"","affiliations":[{"id":33315,"text":"Bowdoin College","active":true,"usgs":false}],"preferred":false,"id":799829,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Elskus, Adria 0000-0003-1192-5124 aelskus@usgs.gov","orcid":"https://orcid.org/0000-0003-1192-5124","contributorId":130,"corporation":false,"usgs":true,"family":"Elskus","given":"Adria","email":"aelskus@usgs.gov","affiliations":[{"id":371,"text":"Maine Water Science Center","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":799830,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"LeBlanc, Lawrence A","contributorId":222882,"corporation":false,"usgs":false,"family":"LeBlanc","given":"Lawrence A","affiliations":[{"id":40617,"text":"Lawrence LeBlanc Consulting","active":true,"usgs":false}],"preferred":false,"id":799831,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Harding, Gareth","contributorId":222885,"corporation":false,"usgs":false,"family":"Harding","given":"Gareth","email":"","affiliations":[{"id":40618,"text":"Fisheries & Oceans, Bedford Institute of Oceanography","active":true,"usgs":false}],"preferred":false,"id":799832,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wells, Peter G","contributorId":222886,"corporation":false,"usgs":false,"family":"Wells","given":"Peter","email":"","middleInitial":"G","affiliations":[{"id":40619,"text":"International Ocean Institute Canada, Dalhousie University","active":true,"usgs":false}],"preferred":false,"id":799833,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70232700,"text":"70232700 - 2020 - Editorial: North American monarch butterfly ecology and conservation","interactions":[],"lastModifiedDate":"2022-07-12T13:14:37.29877","indexId":"70232700","displayToPublicDate":"2020-09-25T08:06:46","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":10963,"text":"Frontiers in Ecology and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Editorial: North American monarch butterfly ecology and conservation","docAbstract":"Spanning Canada, the United States, and Mexico, North America contains two populations of the migratory monarch butterfly (Danaus plexippus). The smaller “western” population overwinters in groves along the California coast and breeds west of the Rocky Mountains, while the much larger “eastern” population breeds east of the Rocky Mountains and overwinters in Oyamel fir forests in central Mexico. Both populations have declined in the last 20 to 30 years, leading to a formal petition in 2014 to list the species as threatened or endangered under the US Endangered Species Act (ESA) and a recommendation in 2016 for listing as endangered under the Canadian Species at Risk act.
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wthogmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":2545,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","email":"wthogmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":846332,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Drum, Ryan G.","contributorId":171941,"corporation":false,"usgs":false,"family":"Drum","given":"Ryan","email":"","middleInitial":"G.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":846333,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schultz, Cheryl B. 0000-0003-3388-8950","orcid":"https://orcid.org/0000-0003-3388-8950","contributorId":292946,"corporation":false,"usgs":false,"family":"Schultz","given":"Cheryl","middleInitial":"B.","affiliations":[{"id":37380,"text":"Washington State University","active":true,"usgs":false}],"preferred":false,"id":846334,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70214091,"text":"sim3461 - 2020 - Geologic framework and hydrostratigraphy of the Edwards and Trinity aquifers within northern Medina County, Texas","interactions":[{"subject":{"id":70214091,"text":"sim3461 - 2020 - Geologic framework and hydrostratigraphy of the Edwards and Trinity aquifers within northern Medina County, Texas","indexId":"sim3461","publicationYear":"2020","noYear":false,"displayTitle":"Geologic Framework and Hydrostratigraphy of the Edwards and Trinity Aquifers Within Northern Medina County, Texas","title":"Geologic framework and hydrostratigraphy of the Edwards and Trinity aquifers within northern Medina County, Texas"},"predicate":"SUPERSEDED_BY","object":{"id":70258397,"text":"sim3526 - 2024 - Geologic framework and hydrostratigraphy of the Edwards and Trinity aquifers within northern Medina County, Texas","indexId":"sim3526","publicationYear":"2024","noYear":false,"title":"Geologic framework and hydrostratigraphy of the Edwards and Trinity aquifers within northern Medina County, Texas"},"id":1}],"supersededBy":{"id":70258397,"text":"sim3526 - 2024 - Geologic framework and hydrostratigraphy of the Edwards and Trinity aquifers within northern Medina County, Texas","indexId":"sim3526","publicationYear":"2024","noYear":false,"title":"Geologic framework and hydrostratigraphy of the Edwards and Trinity aquifers within northern Medina County, Texas"},"lastModifiedDate":"2024-09-20T17:56:40.050301","indexId":"sim3461","displayToPublicDate":"2020-09-24T08:37:02","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":"3461","displayTitle":"Geologic Framework and Hydrostratigraphy of the Edwards and Trinity Aquifers Within Northern Medina County, Texas","title":"Geologic framework and hydrostratigraphy of the Edwards and Trinity aquifers within northern Medina County, Texas","docAbstract":"The karstic Edwards and Trinity aquifers are classified as major sources of water in south-central Texas by the Texas Water Development Board. During 2018–20 the U.S. Geological Survey, in cooperation with the Edwards Aquifer Authority, mapped and described the geologic framework and hydrostratigraphy of the rocks composing the Edwards and Trinity aquifers in northern Medina County from field observations of the surficial expressions of the rocks. The thicknesses of the mapped lithostratigraphic members and hydrostratigraphic units were also estimated from field observations.
The Cretaceous-age rocks (listed in ascending order) in the study area are part of the Trinity Group (lower and upper members of the Glen Rose Limestone), Edwards Group (Kainer Formation [and its stratigraphic equivalent, the Fort Terrett Formation] and Person Formation), Devils River Limestone, Washita Group (Georgetown Formation, Del Rio Clay, and Buda Limestone), Eagle Ford Group, Austin Group, Taylor Group, and Late Cretaceous igneous intrusive rocks. The groups and formations are composed primarily of relatively thick layers of clays, shales, and limestone. The igneous rocks are coarse-grained ultramafic in composition.
The principal structural feature in northern Medina County is the Balcones fault zone, which is the result of late Oligocene and early Miocene extensional faulting and fracturing resulting from the eastern Edwards Plateau uplift. In the Balcones fault zone, most of the faults in the study area are high-angle to vertical, en echelon, normal faults that are predominately downthrown to the southeast.
Hydrostratigraphically, the rocks exposed in the study area (listed in descending order from land surface as they appear in a stratigraphic column) are igneous, the upper confining unit to the Edwards aquifer, the Edwards aquifer, the upper zone of the Trinity aquifer, and the upper part of the middle zone of the Trinity aquifer. The karstic carbonate Edwards and Trinity aquifers developed as a result of their original depositional history, primary and secondary porosity, diagenesis, fracturing, and faulting. These factors have resulted in development of modified porosity, permeability, and transmissivity within and between the aquifers.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3461","collaboration":"Prepared in cooperation with the Edwards Aquifer Authority","usgsCitation":"Clark, A.K., Morris, R.E., and Pedraza, D.E., 2020, Geologic framework and hydrostratigraphy of the Edwards and Trinity aquifers within northern Medina County, Texas: U.S. Geological Survey Scientific Investigations Map 3461, 13 p. pamphlet, 1 pl., scale 1:24,000, https://doi.org/10.3133/sim3461.","productDescription":"Report: vi, 13 p.; Sheet: 48 inches x 36 inches; Data Release","numberOfPages":"23","onlineOnly":"N","ipdsId":"IP-112816","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":378661,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9HHMBX8","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Geospatial dataset of the geologic framework and hydrostratigraphy of the Edwards and Trinity aquifers within northern Medina County, Texas, at 1:24,000 scale"},{"id":378659,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3461/sim3461_pamphlet.pdf","text":"Pamphlet","size":"1.71 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3461 Pamphlet"},{"id":378658,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3461/coverthb1.jpg"},{"id":378660,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3461/sim3461.pdf","text":"Map sheet","size":"30.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3461"}],"country":"United States","state":"Texas","county":"Medina County","otherGeospatial":"Edwards and Trinity Aquifers","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -99.46609497070312,\n 29.31514119318728\n ],\n [\n -98.79867553710936,\n 29.31514119318728\n ],\n [\n -98.79867553710936,\n 29.6510621496229\n ],\n [\n -99.46609497070312,\n 29.6510621496229\n ],\n [\n -99.46609497070312,\n 29.31514119318728\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Oklahoma-Texas Water Science Center
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During winter 2017–18 coastal areas of New England were impacted by the January 4, and March 2–4, 2018, nor’easters. The U.S. Geological Survey (USGS), under an interagency agreement with the Federal Emergency Management Agency (FEMA), collected total water level data (the combination of tide, storm surge, wave runup and setup, and freshwater input) using the North American Vertical Datum of 1988 (NAVD 88) from high-water marks and continuous water-level sensors, to better understand the areal extent, timing, and impact of coastal flooding from strong storms.
During the January 4, 2018, nor’easter the National Oceanic and Atmospheric Administration (NOAA) Boston, Massachusetts, tide gage recorded the highest total water level on record of 9.66 ft. During the March 2–4, 2018, nor’easter, the Boston tide gage recorded its third highest total water level on record of 9.16 ft.
After the January and March 2018 nor’easter storms, the USGS deployed field teams that identified and flagged high-water marks along the coastlines of eastern Massachusetts in January and from Portland, Maine, south to the Connecticut-New York State border in March. In preparation for the approach of the March 2018 nor’easter, the USGS deployed 35 temporary water-level sensors along the coastline of New England to collect total water level data during the storm. Total water level data were also collected at 28 tide gages and 14 coastal streamgages (affected tidally or by tidal backwater during coastal storms) in New England during both nor’easters.
Total water level elevations at 71 high-water marks collected after the January 2018 nor’easter in coastal areas of eastern Massachusetts ranged from 5.8 to 15.1 feet (ft), with an average elevation of 9.4 ft and a median elevation of 9.6 ft. Total water level elevations at 10 tide gages and 7 coastal streamgages from Portland to Cape Cod Bay ranged from 4.8 to 11.2 ft, with an average of 9.1 ft and a median of 9.6 ft. Following the March 2018 nor’easter, 111 high-water marks were collected along the New England coastline. Of the 111 high-water marks, 100 were along the eastern coastline of New England from Portland to Cape Cod and had elevations that ranged from 5.3 to 15.1 ft, with an average of 8.9 ft and a median of 8.6 ft. The remaining 11 high-water marks along the southern coastline of New England in Connecticut, Rhode Island, and Massachusetts had elevations that ranged from 3.1 to 7.5 ft, with an average of 4.3 ft and a median of 4.9 ft. Total water level elevations for 19 USGS temporary water-level sensors from Portland to Cape Cod Bay ranged from 6.2 to 10.4 ft, with an average of 8.4 ft and a median of 8.7 ft. Total water level elevations at 10 tide gages and 6 coastal streamgages from Portland to Cape Cod Bay ranged from 7.8 to 10.8 ft, with an average of 9.1 ft and a median of 9.2 ft.
There were 10 tide gages and 5 coastal streamgages with data from both nor’easters from Portland to Cape Cod Bay; for the January nor’easter, the average and median elevations were about 0.3 and 0.5 ft higher, respectively, than for the March nor’easter. At the 52 high-water mark locations with data for both nor’easters in Massachusetts, the average and median elevations were 0.1 and 0.4 ft higher, respectively, for the January nor’easter than for the March nor’easter.
At 10 tide gages along the coastline from Portland to Cape Cod Bay, the observed peak total water level elevations for the January nor’easter ranged from 1.6 to 3.7 ft higher than the concurrent predicted elevations, with an average of 2.8 ft and a median of 3.0 ft higher. For the March nor’easter, the observed peak total water level elevations ranged from 1.8 to 4.0 ft higher than the concurrent predicted elevations, with an average of 2.7 ft and a median of 3.0 ft higher. This is approximately the amount of storm surge that was experienced during the highest tides of the two nor’easters along the coastline from Portland to Cape Cod Bay.
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U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
Biological conservation often requires an understanding of how environmental conditions affect species occurrence and detection probabilities. We used a hierarchical framework to evaluate these effects for several Appalachian stream fish species of conservation concern: Chrosomus cumberlandensis (BSD; blackside dace), Etheostoma sagitta (CAD; Cumberland arrow darter), and Etheostoma spilotum (KAD; Kentucky arrow darter). Etheostoma susanae (Cumberland darter) also is present in the study area but was too rare to model in this analysis. In this study, conducted by the U.S. Geological Survey in cooperation with the U.S. Fish and Wildlife Service, fish and habitat data were collected from 205 randomly selected stream sites in the upper Cumberland and Kentucky River Basins (120 and 85 sites, respectively) of Kentucky and Tennessee. Sites were sampled with 10 spatial replicates (2 meter x 5 meter electrofishing zones) to enable estimation of detection probabilities and environmental effects. The best models (that is, lowest Akaike information criterion scores) showed the effects of agriculture (negative) on occurrence of BSD and stream conductivity (negative) on occurrence of CAD and KAD. These effects were statistically more important than measures of basin area, elevation, and substrate size. Conductivity and agriculture showed nonlinear effects on species occurrence, and effects of conductivity were more precise above 400 microsiemens per centimeter than below this threshold. Models incorporated detection-level effects of electrofishing time (positive), flow velocity (negative), sand substrate (positive), and gravel/cobble substrate (negative). Models accounting for detection of BSD estimated occupancy rates similar to the observed proportion of occupied sites (0.10), but the best-supported models for CAD and KAD increased expected occupancy by about 4 percent for each species (from 0.17 to 0.21 for CAD and from 0.07 to 0.11 for KAD). Results of this study provide new inferences for modeling stream fish occurrence and detection processes and highlight the importance of continued monitoring and assessment of rare fish species in Appalachian headwater streams.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201100","collaboration":"Prepared in cooperation with U.S. Fish and Wildlife Service","usgsCitation":"Hitt, N.P., Rogers, K.M., Kessler, K., and Macmillan, H., 2020, Modeling occupancy of rare stream fish species in the upper Cumberland and Kentucky River Basins: U.S. Geological Survey Open-File Report 2020–1100, 22 p., https://doi.org/10.3133/ofr20201100.","productDescription":"vi, 22 p.","numberOfPages":"22","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-118746","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":378605,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1100/ofr20201100.pdf","text":"Report","size":"2.02 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1100"},{"id":378604,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1100/coverthb.jpg"}],"country":"United States","state":"Kentucky, Tennessee, Virginia","otherGeospatial":"Cumberland River basin, Kentucky River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.1875,\n 35.88905007936091\n ],\n [\n -81.39770507812499,\n 35.88905007936091\n ],\n [\n -81.39770507812499,\n 38.77121637244273\n ],\n [\n -87.1875,\n 38.77121637244273\n ],\n [\n -87.1875,\n 35.88905007936091\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Eastern Ecological Science Center
U.S. Geological Survey
11649 Leetown Road
Kearneysville, WV 25430
There is an active debate regarding the influence that climate has on the risk of armed conflict, which stems from challenges in assembling unbiased datasets, competing hypotheses on the mechanisms of climate influence, and the difficulty of disentangling direct and indirect climate effects. We use gridded historical non-state conflict records, satellite data, and land surface models in a structural equation modeling approach to uncover the direct and indirect effects of climate on violent conflicts in Africa and the Middle East (ME). We show that climate–conflict linkages in these regions are more complex than previously suggested, with multiple mechanisms at work. Warm temperatures and low rainfall direct effects on conflict risk were stronger than indirect effects through food and water supplies. Warming increases the risk of violence in Africa but unexpectedly decreases this risk in the ME. Furthermore, at the country level, warming decreases the risk of violence in most West African countries. Overall, we find a non-linear response of conflict to warming across countries that depends on the local temperature conditions. We further show that magnitude and sign of the effects largely depend on the scale of analysis and geographical context. These results imply that extreme caution should be exerted when attempting to explain or project local climate–conflict relationships based on a single, generalized theory.
","language":"English","publisher":"IOP Science","doi":"10.1088/1748-9326/aba97d","usgsCitation":"Helman, D., Zaitchik, B., and Funk, C., 2020, Climate has contrasting direct and indirect effects on armed conflicts: Environmental Research Letters, v. 15, 104017, 12 p., https://doi.org/10.1088/1748-9326/aba97d.","productDescription":"104017, 12 p.","ipdsId":"IP-118530","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":455254,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/1748-9326/aba97d","text":"Publisher Index Page"},{"id":421737,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Africa, Middle East","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 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Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":885584,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70219515,"text":"70219515 - 2020 - Unfamiliar territory: Emerging themes for ecological drought research and management","interactions":[],"lastModifiedDate":"2021-04-12T14:49:40.365871","indexId":"70219515","displayToPublicDate":"2020-09-18T09:41:05","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7583,"text":"One Earth","active":true,"publicationSubtype":{"id":10}},"title":"Unfamiliar territory: Emerging themes for ecological drought research and management","docAbstract":"Novel forms of drought are emerging globally, due to climate change, shifting teleconnection patterns, expanding human water use, and a history of human influence on the environment that increases the probability of transformational ecological impacts. These costly ecological impacts cascade to human communities, and understanding this changing drought landscape is one of today’s grand challenges. By using a modified horizon-scanning approach that integrated scientists, managers, and decision-makers, we identified the emerging issues in ecological drought that represent key challenges to timely and effective responses. Here we review the themes that most urgently need attention, including novel drought conditions, the potential for transformational drought impacts, and the need for anticipatory drought management. This horizon scan and review provides a roadmap to facilitate the research and management innovations that will support forward-looking, co-developed approaches to reduce the risk of drought to our socio-ecological systems during the 21st century.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.oneear.2020.08.019","usgsCitation":"Crausbay, S.D., Betancourt, J.L., Bradford, J., Cartwright, J.M., Dennison, W., Dunham, J.B., Enquist, C.A., Frazier, A.G., Hall, K.R., Littell, J., Luce, C.H., Palmer, R., Ramirez, A.R., Rangwala, I., Thompson, L., Walsh, B.M., and Carter, S., 2020, Unfamiliar territory: Emerging themes for ecological drought research and management: One Earth, v. 3, no. 3, p. 337-353, https://doi.org/10.1016/j.oneear.2020.08.019.","productDescription":"17 p.","startPage":"337","endPage":"353","ipdsId":"IP-110891","costCenters":[{"id":107,"text":"Alaska Climate Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern 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York, 2015–17","title":"Use of time domain electromagnetic soundings and borehole electromagnetic induction logs to delineate the freshwater/saltwater interface on southwestern Long Island, New York, 2015–17","docAbstract":"The U.S. Geological Survey, in cooperation with the New York State Department of Environmental Conservation, used surface and borehole geophysical methods to delineate the freshwater/saltwater interface in coastal plain aquifers along the southwestern part of Long Island, New York. Over pumping of groundwater in the early 20th century combined with freshwater/saltwater interfaces at the coastline created saltwater intrusion in the upper glacial, Jameco, Magothy, and Lloyd aquifers. This study documents, for the first time, extensive saltwater intrusion of the Lloyd aquifer along the southwestern coast of Long Island, N.Y. Several public-supply wells in the southern parts of Nassau, Queens, and Kings Counties have been adversely affected by saltwater intrusion causing supply wells to be shutdown and abandoned. Due to the ongoing groundwater pumping in southern Nassau County, the freshwater/saltwater interface requires delineation and monitoring for any inland movement.
In 2015–17, the U.S. Geological Survey collected time domain electromagnetic soundings at 12 locations and borehole electromagnetic induction conductivity logs at 9 wells within the study area to delineate several saltwater intrusion wedges. The upper glacial, Jameco, and Magothy aquifers were grouped into one aquifer complex within the study area to simplify interpretations. The coastal plain sediments increase in thickness from west to east and north to south because of their regional dip toward the southeast. Three separate wedges, shallow, intermediate, and deep, of saltwater intrusion were delineated in the upper glacial, Jameco, and Magothy aquifer complex. In addition, analysis of geophysical logs collected in an open borehole of a test well in southern Queens County in 1989 revealed the Lloyd aquifer was nearly completely intruded by saltwater with an estimated chloride concentration of 15,000 milligrams per liter. The geophysical logs from this well provides, for the first time, definitive proof of saltwater intrusion of the Lloyd aquifer on Long Island’s south shore, suggesting the freshwater/saltwater interface was at the coastline and not miles offshore as theorized by previous studies.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201093","collaboration":"Prepared in cooperation with the New York State Department of Environmental Conservation","usgsCitation":"Stumm, F., Como, M.D., and Zuck, M.A., 2020, Use of time domain electromagnetic soundings and borehole electromagnetic induction logs to delineate the freshwater/saltwater interface on southwestern Long Island, New York, 2015–17: U.S. Geological Survey Open-File Report 2020–1093, 27 p., https://doi.org/10.3133/ofr20201093.","productDescription":"Report: vi, 27 p.; Data Release; Database","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-118303","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":378439,"rank":4,"type":{"id":9,"text":"Database"},"url":"https://doi.org/10.5066/F7X63KT0","linkFileType":{"id":5,"text":"html"},"linkHelpText":"- USGS GeoLog Locator"},{"id":378438,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P90B6OTX","text":"USGS data release","linkFileType":{"id":5,"text":"html"},"linkHelpText":"Time domain electromagnetic surveys collected to estimate the extent of saltwater intrusion in Nassau and Queens County, New York, October–November 2017"},{"id":378437,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1093/ofr20201093.pdf","text":"Report","size":"3.02 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1093"},{"id":378436,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1093/coverthb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Long Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.03961181640625,\n 40.54406959045767\n ],\n [\n -73.32687377929688,\n 40.54406959045767\n ],\n [\n -73.32687377929688,\n 40.77638178482896\n ],\n [\n -74.03961181640625,\n 40.77638178482896\n ],\n [\n -74.03961181640625,\n 40.54406959045767\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New York Water Science Center
U.S. Geological Survey
425 Jordan Road
Troy, NY 12180–8349