1000lnαCO2(ACID)-calcite=3.48(103/T)-1.471000lnαCO2(ACID)-calcite=3.48(103/T)-1.47\n![\"\"](\"http://www.sciencedirect.com/sd/blank.gif\")
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\nIn October 2012, the U.S. Geological Survey (USGS), in cooperation with the Central Texas Groundwater Conservation District, began an assessment to better understand if and where groundwater from the Ellenburger-San Saba aquifer is discharging to the Colorado River, and if and where Colorado River streamflow is recharging the Ellenburger-San Saba aquifer in the study area. Discharge measurements were made to determine if different reaches of the Colorado River in northwestern Burnet and southeastern San Saba Counties are gaining or losing streamflow, the locations and quantities of gains and losses, and whether the gains and losses can be attributed to interaction between the river and the Ellenbuger-San Saba aquifer. To assess streamflow gains and losses, two sets of synoptic gain-loss discharge measurements representing different streamflow conditions were completed. In the first gain-loss streamflow survey during December 3–6, 2012 (hereinafter the fall 2012 gain-loss survey), discharge measurements were made at low-flow conditions ranging from about 30 to 60 cubic feet per second (ft3/s) at seven locations along the Colorado River. In the second gain-loss streamflow survey during May 31–June 1, 2014 (hereinafter the spring 2014 gain-loss survey), discharge measurements were made at high-flow conditions ranging from about 660 to 900 ft3/s at 12 locations along the Colorado River.
\nDuring the fall 2012 gain-loss survey, verifiable gains or losses of streamflow were identified in 4 of 6 reaches (the difference in measured discharge between the upstream and downstream boundaries of the reach was larger than the sum of potential errors associated with the two discharge measurements). The two reaches with a verifiable gain in streamflow cross areas where the Ellenburger-San Saba aquifer crops out. The more upstream of the two reaches with verifiable losses crosses a small part of the Ellenburger-San Saba aquifer outcrop and confining units (Point Peak Member and Morgan Creek Limestone); it is possible streamflow losses in this reach are in the form of recharge to the Ellenburger-San Saba aquifer; little streamflow is likely lost to the underlying formations in the downstream part of the reach, which consists of relatively impermeable aquifer confining units exposed at land surface. The more downstream of the two reaches where a verifiable loss of streamflow was measured also flows across relatively impermeable confining units before crossing the Mid-Cambrian aquifer outcrop in the lower part of the reach; most of the streamflow losses in this reach were likely a result of water infiltrating into the subsurface from the streambed and providing recharge to the relatively permeable Mid-Cambrian aquifer.
\nDuring the spring 2014 gain-loss survey, 11 reaches were combined into 3 in an attempt to consolidate gains and losses as well as group reaches within the same hydrogeologic units. An unverifiable loss was measured in the reach farthest upstream, which crosses a combination of alluvium and Ellenburger-San Saba aquifer outcrop, whereas an unverifiable gain was measured in the middle reach, which crosses each of the different hydrogeologic units represented in the study area. The reach farthest downstream crosses an area where only the Ellenburger-San Saba aquifer crops out; a streamflow gain of 123 ft3/s was measured in this reach, exceeding the potential error of 93.9 ft3/s. The verifiable streamflow gain in this downstream reach implies the Ellenburger-San Saba aquifer was discharging groundwater to the Colorado River in this part of the study area under the hydrologic conditions of the spring 2014 gain-loss survey.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155098","collaboration":"Prepared in cooperation with the Central Texas Groundwater Conservation District","usgsCitation":"Braun, C.L., and Grzyb, S.D., 2015, Streamflow gains and losses in the Colorado River in northwestern Burnet and southeastern San Saba Counties, Texas, 2012–14: U.S. Geological Survey Scientific Investigations Report 2015–5098, 32 p., https://dx.doi.org/10.3133/sir20155098.","productDescription":"v, 32 p.","numberOfPages":"41","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-062274","costCenters":[{"id":105,"text":"Alabama Water Science Center","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":306566,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5098/coverthb.jpg"},{"id":306567,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5098/sir20155098.pdf","text":"Report","size":"6.48 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5098"}],"country":"United States","state":"Texas","county":"Burnet County, San Saba County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -98.48075866699219,\n 30.918131046738022\n ],\n [\n -98.48075866699219,\n 31.0376384361344\n ],\n [\n -98.38085174560547,\n 31.0376384361344\n ],\n [\n -98.38085174560547,\n 30.918131046738022\n ],\n [\n -98.48075866699219,\n 30.918131046738022\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, Texas 78754–4501
http://tx.usgs.gov/
The North Platte Natural Resources District (NPNRD) has been actively collecting data and studying groundwater resources because of concerns about the future availability of the highly inter-connected surface-water and groundwater resources. This report, prepared by the U.S. Geological Survey in cooperation with the North Platte Natural Resources District, describes a groundwater-flow model of the North Platte River valley from Bridgeport, Nebraska, extending west to 6 miles into Wyoming. The model was built to improve the understanding of the interaction of surface-water and groundwater resources, and as an optimization tool, the model is able to analyze the effects of water-management options on the simulated stream base flow of the North Platte River. The groundwater system and related sources and sinks of water were simulated using a newton formulation of the U.S. Geological Survey modular three-dimensional groundwater model, referred to as MODFLOW–NWT, which provided an improved ability to solve nonlinear unconfined aquifer simulations with wetting and drying of cells. Using previously published aquifer-base-altitude contours in conjunction with newer test-hole and geophysical data, a new base-of-aquifer altitude map was generated because of the strong effect of the aquifer-base topography on groundwater-flow direction and magnitude. The largest inflow to groundwater is recharge originating from water leaking from canals, which is much larger than recharge originating from infiltration of precipitation. The largest component of groundwater discharge from the study area is to the North Platte River and its tributaries, with smaller amounts of discharge to evapotranspiration and groundwater withdrawals for irrigation. Recharge from infiltration of precipitation was estimated with a daily soil-water-balance model. Annual recharge from canal seepage was estimated using available records from the Bureau of Reclamation and then modified with canal-seepage potentials estimated using geophysical data. Groundwater withdrawals were estimated using land-cover data, precipitation data, and published crop water-use data. For fields irrigated with surface water and groundwater, surface-water deliveries were subtracted from the estimated net irrigation requirement, and groundwater withdrawal was assumed to be equal to any demand unmet by surface water.
\nThe groundwater-flow model was calibrated to measured groundwater levels and stream base flows estimated using the base-flow index method. The model was calibrated through automated adjustments using statistical techniques through parameter estimation using the parameter estimation suite of software (PEST). PEST was used to adjust 273 parameters, grouped as hydraulic conductivity of the aquifer, spatial multipliers to recharge, temporal multipliers to recharge, and two specific recharge parameters. Base flow of the North Platte River at Bridgeport, Nebraska, streamgage near the eastern, downstream end of the model was one of the primary calibration targets. Simulated base flow reasonably matched estimated base flow for this streamgage during 1950–2008, with an average difference of 15 percent. Overall, 1950–2008 simulated base flow followed the trend of the estimated base flow reasonably well, in cases with generally increasing or decreasing base flow from the start of the simulation to the end. Simulated base flow also matched estimated base flow reasonably well for most of the North Platte River tributaries with estimated base flow. Average simulated groundwater budgets during 1989–2008 were nearly three times larger for irrigation seasons than for non-irrigation seasons.
\nThe calibrated groundwater-flow model was used with the Groundwater-Management Process for the 2005 version of the U.S. Geological Survey modular three-dimensional groundwater model, MODFLOW–2005, to provide a tool for the NPNRD to better understand how water-management decisions could affect stream base flows of the North Platte River at Bridgeport, Nebr., streamgage in a future period from 2008 to 2019 under varying climatic conditions. The simulation-optimization model was constructed to analyze the maximum increase in simulated stream base flow that could be obtained with the minimum amount of reductions in groundwater withdrawals for irrigation. A second analysis extended the first to analyze the simulated base-flow benefit of groundwater withdrawals along with application of intentional recharge, that is, water from canals being released into rangeland areas with sandy soils. With optimized groundwater withdrawals and intentional recharge, the maximum simulated stream base flow was 15–23 cubic feet per second (ft3/s) greater than with no management at all, or 10–15 ft3/s larger than with managed groundwater withdrawals only. These results indicate not only the amount that simulated stream base flow can be increased by these management options, but also the locations where the management options provide the most or least benefit to the simulated stream base flow. For the analyses in this report, simulated base flow was best optimized by reductions in groundwater withdrawals north of the North Platte River and in the western half of the area. Intentional recharge sites selected by the optimization had a complex distribution but were more likely to be closer to the North Platte River or its tributaries. Future users of the simulation-optimization model will be able to modify the input files as to type, location, and timing of constraints, decision variables of groundwater withdrawals by zone, and other variables to explore other feasible management scenarios that may yield different increases in simulated future base flow of the North Platte River.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155093","collaboration":"Prepared in cooperation with the North Platte Natural Resources District","usgsCitation":"Peterson, S.M, Flynn, A.T., Vrabel, Joseph, and Ryter, D.W., 2015, Simulation of groundwater flow and analysis of the effects of water-management options in the North Platte Natural Resources District, Nebraska: U.S. Geological Survey Scientific Investigations Report 2015–5093, 67 p., https://dx.doi.org/10.3133/sir20155093.","productDescription":"ix, 67 p.","numberOfPages":"82","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-055438","costCenters":[{"id":464,"text":"Nebraska Water Science 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U.S. Geological Survey
5231 South 19th Street
Lincoln, Nebraska 68512
http://ne.water.usgs.gov/
Hydraulically fractured shales are becoming an increasingly important source of natural gas production in the United States. This process has been known to create up to 420 gallons of produced water (PW) per day, but the volume varies depending on the formation, and the characteristics of individual hydraulic fracture. PW from hydraulic fracturing of shales are comprised of injected fracturing fluids and natural formation waters in proportions that change over time. Across the state of Pennsylvania, shale gas production is booming; therefore, it is important to assess the variability in PW chemistry and microbiology across this geographical span. We quantified the inorganic and organic chemical composition and microbial communities in PW samples from 13 shale gas wells in north central Pennsylvania. Microbial abundance was generally low (66–9400 cells/mL). Non-volatile dissolved organic carbon (NVDOC) was high (7–31 mg/L) relative to typical shallow groundwater, and the presence of organic acid anions (e.g., acetate, formate, and pyruvate) indicated microbial activity. Volatile organic compounds (VOCs) were detected in four samples (∼1 to 11.7 μg/L): benzene and toluene in the Burket sample, toluene in two Marcellus samples, and tetrachloroethylene (PCE) in one Marcellus sample. VOCs can be either naturally occurring or from industrial activity, making the source of VOCs unclear. Despite the addition of biocides during hydraulic fracturing, H2S-producing, fermenting, and methanogenic bacteria were cultured from PW samples. The presence of culturable bacteria was not associated with salinity or location; although organic compound concentrations and time in production were correlated with microbial activity. Interestingly, we found that unlike the inorganic chemistry, PW organic chemistry and microbial viability were highly variable across the 13 wells sampled, which can have important implications for the reuse and handling of these fluids
","language":"English","publisher":"Oxford","publisherLocation":"New York, NY","doi":"10.1016/j.apgeochem.2015.04.011","usgsCitation":"Akob, D.M., Cozzarelli, I.M., Dunlap, D.S., Rowan, E.L., and Lorah, M.M., 2015, Organic and inorganic composition and microbiology of produced waters from Pennsylvania shale gas wells: Applied Geochemistry, v. 60, p. 116-125, https://doi.org/10.1016/j.apgeochem.2015.04.011.","productDescription":"10 p.","startPage":"116","endPage":"125","numberOfPages":"10","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061928","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":306602,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Pennsylvania","county":"Lycoming, 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Center","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":566590,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dunlap, Darren S. 0000-0001-5595-6817 ddunlap@usgs.gov","orcid":"https://orcid.org/0000-0001-5595-6817","contributorId":5260,"corporation":false,"usgs":true,"family":"Dunlap","given":"Darren","email":"ddunlap@usgs.gov","middleInitial":"S.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":566591,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rowan, Elisabeth L. 0000-0001-5753-6189 erowan@usgs.gov","orcid":"https://orcid.org/0000-0001-5753-6189","contributorId":2075,"corporation":false,"usgs":true,"family":"Rowan","given":"Elisabeth","email":"erowan@usgs.gov","middleInitial":"L.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":566592,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lorah, Michelle M. 0000-0002-9236-587X mmlorah@usgs.gov","orcid":"https://orcid.org/0000-0002-9236-587X","contributorId":1437,"corporation":false,"usgs":true,"family":"Lorah","given":"Michelle","email":"mmlorah@usgs.gov","middleInitial":"M.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":566593,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70155846,"text":"70155846 - 2015 - Normalization of stable isotope data for carbonate minerals: implementation of IUPAC guideline","interactions":[],"lastModifiedDate":"2015-08-12T08:49:16","indexId":"70155846","displayToPublicDate":"2015-08-12T08:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1759,"text":"Geochimica et Cosmochimica Acta","active":true,"publicationSubtype":{"id":10}},"title":"Normalization of stable isotope data for carbonate minerals: implementation of IUPAC guideline","docAbstract":"Carbonate minerals provide a rich source of geochemical information because their δ13C and δ18O values provide information about surface and subsurface Earth processes. However, a significant problem is that the same δ18O value is not reported for the identical carbonate sample when analyzed in different isotope laboratories in spite of the fact that the International Union of Pure and Applied Chemistry (IUPAC) has provided reporting guidelines for two decades. This issue arises because (1) the δ18O measurements are performed on CO2 evolved by reaction of carbonates with phosphoric acid, (2) the acid-liberated CO2 is isotopically fractionated (enriched in 18O) because it contains only two-thirds of the oxygen from the solid carbonate, (3) this oxygen isotopic fractionation factor is a function of mineralogy, temperature, concentration of the phosphoric acid, and δ18O value of water in the phosphoric acid, (4) researchers may use any one of an assortment of oxygen isotopic fractionation factors that have been published for various minerals at various reaction temperatures, and (5) it sometimes is not clear how one should calculate δ18OVPDB values on a scale normalized such that the δ18O value of SLAP reference water is −55.5 ‰ relative to VSMOW reference water.
\nTo enable researchers worldwide to publish the same δ18O value (within experimental uncertainty) for the same carbonate sample, we have re-evaluated reported acid fractionation factors for calcite at 25, 50, and 75 °C and propose a revised relation for the temperature dependence of oxygen isotopic acid fractionation factor, αCO2(ACID)-calciteαCO2(ACID)-calcite, of
\nwhere T is temperature in kelvin. At 25 °C, αCO2(ACID)-calcite=1.01025αCO2(ACID)-calcite=1.01025, the most commonly accepted value for this quantity. We propose a normalization protocol in which (1) the internationally distributed carbonate isotopic reference materials NBS 18 and NBS 19 are interspersed among carbonate samples analyzed by treatment with phosphoric acid, (2) the δ18O values of the calcite reference materials and the carbonate samples are calculated, respectively, by using the αCO2(ACID)-calciteαCO2(ACID)-calcite relation above and oxygen-isotope acid fractionation factors appropriate for the sample mineralogy and reaction temperature, (3) the δ18O values of solid carbonate samples are determined on the VPDB scale (δ18OVPDB) with IUPAC-recommended scale expansion such that the δ18O of SLAP reference water is −55.5 ‰ relative to VSMOW reference water by normalizing δ18O values of carbonate samples with 2014-IUPAC-recommended δ18O values of NBS 18 and NBS 19, and (4) δ18O values on the VPDB scale are converted to δ18O values on the VSMOW-SLAP scale by using IUPAC recommendations.
\nTo ease calculations in the protocol, a software application titled “Carbon and Oxygen Isotopic Normalization Tool for Carbonates” is available that relies upon IUPAC-recommended δ13C and δ18O values of carbonate isotopic reference materials
\n(http://isotopes.usgs.gov/research/topics/carbonatesnormalizationtool.html).
","language":"English","publisher":"Elsevier","publisherLocation":"New York, NY","doi":"10.1016/j.gca.2015.02.011","usgsCitation":"Kim, S., Coplen, T.B., and Horita, J., 2015, Normalization of stable isotope data for carbonate minerals: implementation of IUPAC guideline: Geochimica et Cosmochimica Acta, v. 158, p. 276-289, https://doi.org/10.1016/j.gca.2015.02.011.","productDescription":"14 p.","startPage":"276","endPage":"289","numberOfPages":"14","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062909","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":306604,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"158","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55cc6022e4b08400b1fe0fb7","contributors":{"authors":[{"text":"Kim, Sang-Tae","contributorId":146204,"corporation":false,"usgs":false,"family":"Kim","given":"Sang-Tae","email":"","affiliations":[{"id":16624,"text":"School of Geography and Earth Sciences, McMaster University, ON, Canada","active":true,"usgs":false}],"preferred":false,"id":566587,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coplen, Tyler B. 0000-0003-4884-6008 tbcoplen@usgs.gov","orcid":"https://orcid.org/0000-0003-4884-6008","contributorId":508,"corporation":false,"usgs":true,"family":"Coplen","given":"Tyler","email":"tbcoplen@usgs.gov","middleInitial":"B.","affiliations":[{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":566586,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Horita, Juske","contributorId":146205,"corporation":false,"usgs":false,"family":"Horita","given":"Juske","email":"","affiliations":[{"id":16625,"text":"Department of Geosciences, Texas Tech University, Lubbock, Texas","active":true,"usgs":false}],"preferred":false,"id":566588,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70148090,"text":"sir20155075 - 2015 - Median nitrate concentrations in groundwater in the New Jersey Highlands Region estimated using regression models and land-surface characteristics","interactions":[],"lastModifiedDate":"2015-09-03T13:16:16","indexId":"sir20155075","displayToPublicDate":"2015-08-12T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-5075","title":"Median nitrate concentrations in groundwater in the New Jersey Highlands Region estimated using regression models and land-surface characteristics","docAbstract":"Nitrate-concentration data are used in conjunction with land-use and land-cover data to estimate median nitrate concentrations in groundwater underlying the New Jersey (NJ) Highlands Region. Sources of data on nitrate in 19,670 groundwater samples are from the U.S. Geological Survey (USGS) National Water Information System (NWIS) and the NJ Private Well Testing Act (PWTA).
\nIn a study conducted by the USGS, in cooperation with the New Jersey Department of Environmental Protection, logistic regression was used to relate measured nitrate concentrations to five explanatory variables (percent urban and agricultural land use, septic-system density, total length of streams, and number of known contaminated sites) quantified in 610-meter-square grid cells. A method for calculating the median concentrations of nitrate from a series of logistic regression models was developed. Two calibration and two validation procedures showed that the logistic-regression-based method can estimate groundwater-nitrate concentrations in the Highlands Region accurately to within 0.1 milligram per liter as nitrogen (mg/L as N). Limitations of the logistic-regression-based method include the inability to select a logistic model with exactly 0.5 probability of exceeding the threshold value and lack of an algorithm to directly calculate the median value. Quantile regression was evaluated as a suitable alternative and was slightly less accurate than the logistic-regression method in estimating median groundwater nitrate concentrations in the Highlands Region.
\nMultiple-linear regression with log-transformed nitrate-concentration data and the same five explanatory values was less accurate than either logistic or quantile regression in estimating median nitrate concentrations. On the basis of 4,516 2000 x 2000 foot grid cells that contain wells with data stored in NWIS and the PWTA database, the estimated median nitrate concentration for the entire Highlands Region is about 1.25 mg/L as N, and estimated median concentrations range from about 1.05 to 1.78 mg/L as N among 11 smaller administratively defined areas within the Highlands Region that vary in percentages of urban land use, agricultural land use, and septic-system density.
\nThe Kaplan-Meier method of estimating summary statistics from left-censored data was applied in order to include nondetects (left-censored data) in median nitrate-concentration calculations. Median concentrations also were determined using three alternative methods of handling nondetects. Treatment of the 23 percent of samples that were nondetects had little effect on estimated median nitrate concentrations because method detection limits were mostly less than median values.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155075","collaboration":"Prepared in cooperation with the New Jersey Department of Environmental Protection","usgsCitation":"Baker, R.J., Chepiga, M., and Cauller, S.J., 2015, Median nitrate concentrations in groundwater in the New Jersey Highlands Region estimated using regression models and land-surface characteristics: U.S. Geological Survey Scientific Investigations Report 2015-5075, Report: vii, 26 p.; 2 Appendices, https://doi.org/10.3133/sir20155075.","productDescription":"Report: vii, 26 p.; 2 Appendices","numberOfPages":"39","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-060925","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":305639,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5075/support/sir20155075_appendix01.xlsx","text":"Appendix 1","size":"17.2 MB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2015-5075 Appendix 1","linkHelpText":"Example spreadsheet for calculating median nitrate concentrations with logistic-regression models"},{"id":305637,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2015/5075/"},{"id":305638,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5075/support/sir20155075.pdf","text":"Report","size":"16.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5075 Report"},{"id":305640,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5075/support/sir20155075_appendix02.pdf","text":"Appendix 2","size":"180 KB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5075 Appendix 2","linkHelpText":"Geographic and environmental characteristics evaluated as possible explanatory variables in models of median nitrate concentrations in groundwater in the NJ Highlands Region"},{"id":305641,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20155075.jpg"}],"projection":"Universal Transverse Mercator projection","country":"United States","state":"New Jersey","otherGeospatial":"New Jersey Highlands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.0531005859375,\n 40.86783384138491\n ],\n [\n -74.9212646484375,\n 41.03793062246529\n ],\n [\n -74.805908203125,\n 41.03793062246529\n ],\n [\n -74.5697021484375,\n 41.290189955885644\n ],\n [\n -74.2236328125,\n 41.13315883477399\n ],\n [\n -74.3115234375,\n 40.94671366508002\n ],\n [\n -74.4049072265625,\n 40.77638178482896\n ],\n [\n -74.5806884765625,\n 40.643135583312805\n ],\n [\n -74.72351074218749,\n 40.51379915504413\n ],\n [\n -74.9212646484375,\n 40.47202439692057\n ],\n [\n -75.08056640625,\n 40.44694705960048\n ],\n [\n -75.069580078125,\n 40.53050177574321\n ],\n [\n -75.146484375,\n 40.56389453066509\n ],\n [\n -75.1904296875,\n 40.538851525354666\n ],\n [\n -75.2288818359375,\n 40.62646106367355\n ],\n [\n -75.234375,\n 40.693134153308094\n ],\n [\n -75.223388671875,\n 40.751418432997454\n ],\n [\n -75.16845703124999,\n 40.78885994449482\n ],\n [\n -75.135498046875,\n 40.772221877329024\n ],\n [\n -75.091552734375,\n 40.82212357516945\n ],\n [\n -75.1190185546875,\n 40.863679665481676\n ],\n [\n -75.0531005859375,\n 40.86783384138491\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"560bb6cbe4b058f706e53d66","contributors":{"authors":[{"text":"Baker, Ronald J. rbaker@usgs.gov","contributorId":1436,"corporation":false,"usgs":true,"family":"Baker","given":"Ronald","email":"rbaker@usgs.gov","middleInitial":"J.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":547539,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chepiga, Mary M. mchepiga@usgs.gov","contributorId":888,"corporation":false,"usgs":true,"family":"Chepiga","given":"Mary M.","email":"mchepiga@usgs.gov","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":false,"id":547540,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cauller, Stephen J. 0000-0002-1823-8813 sjcaulle@usgs.gov","orcid":"https://orcid.org/0000-0002-1823-8813","contributorId":3641,"corporation":false,"usgs":true,"family":"Cauller","given":"Stephen","email":"sjcaulle@usgs.gov","middleInitial":"J.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":false,"id":564557,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70155837,"text":"70155837 - 2015 - Introduction to this special issue on ocean acidification: the pathway from science to policy","interactions":[],"lastModifiedDate":"2015-08-11T15:30:16","indexId":"70155837","displayToPublicDate":"2015-08-11T16:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2929,"text":"Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"Introduction to this special issue on ocean acidification: the pathway from science to policy","docAbstract":"Ocean acidification (OA) is a progressive decrease in the pH of seawater over decades, caused primarily by uptake of excess atmospheric CO2 and accompanied by changes in seawater carbonate chemistry. Scientific studies designed to examine the effects of anthropogenic carbon dioxide (CO2) emissions on global carbon fluxes have also led to the detection of OA. During the last decade, this phenomenon has surged to the attention of not only scientists but also policymakers and the public. OA chemistry is well understood and follows first principles of acid-base chemistry (e.g., Gattuso and Hansson, 2011; Box 1 in McLaughlin et al.). Today, total anthropogenic release of CO2 exceeds nine petagrams of carbon annually, with ~85% coming directly from industrial sources and ~15% from changes in land use. The three major sinks for this CO2 are: ~46% of CO2 emitted remains in the atmosphere, ~29% is absorbed by the terrestrial biosphere, and the ocean absorbs the remaining ~26% (Le Quéré et al., 2014), resulting in OA. Since the Industrial Revolution, global average surface ocean pH has dropped 0.1 unit (about a 30% increase in acidity; IPCC, 2013), and it is expected to drop another 0.3 to 0.4 units by 2100 (100-150% increase in acidity) if CO2 emissions continue in a business-as-usual scenario (Orr et al., 2005; IPCC, 2013). Some areas of the ocean, such as coastal regions, upwelling zones, and polar seas, may be subjected to much greater chemical perturbations from OA than indicated by such globally averaged values (e.g., Feely et al., 2008; Mathis et al.).
","language":"English","publisher":"Oceanography Society","publisherLocation":"Rockville, MD","doi":"10.5670/oceanog.2015.26","usgsCitation":"Mathis, J.T., Cooley, S.R., Yates, K.K., and Williamson, P., 2015, Introduction to this special issue on ocean acidification: the pathway from science to policy: Oceanography, v. 28, no. 2, p. 10-15, https://doi.org/10.5670/oceanog.2015.26.","productDescription":"i, 6 p.","startPage":"10","endPage":"15","numberOfPages":"7","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066110","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":471884,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5670/oceanog.2015.26","text":"Publisher Index Page"},{"id":306588,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"28","issue":"2","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55cb0ea3e4b08400b1fdd457","contributors":{"authors":[{"text":"Mathis, Jeremy T.","contributorId":146187,"corporation":false,"usgs":false,"family":"Mathis","given":"Jeremy","email":"","middleInitial":"T.","affiliations":[{"id":12641,"text":"NOAA NMFS","active":true,"usgs":false}],"preferred":false,"id":566554,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cooley, Sarah R.","contributorId":145518,"corporation":false,"usgs":false,"family":"Cooley","given":"Sarah","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":566555,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yates, Kimberly K. 0000-0001-8764-0358 kyates@usgs.gov","orcid":"https://orcid.org/0000-0001-8764-0358","contributorId":420,"corporation":false,"usgs":true,"family":"Yates","given":"Kimberly","email":"kyates@usgs.gov","middleInitial":"K.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":566553,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Williamson, Phillip","contributorId":146188,"corporation":false,"usgs":false,"family":"Williamson","given":"Phillip","email":"","affiliations":[{"id":16617,"text":"University of East Anglia","active":true,"usgs":false}],"preferred":false,"id":566556,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70155838,"text":"70155838 - 2015 - Transdisciplinary science: A path to understanding the interactions among ocean acidification, ecosystems, and society","interactions":[],"lastModifiedDate":"2026-01-26T14:24:49.438181","indexId":"70155838","displayToPublicDate":"2015-08-11T16:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2929,"text":"Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"Transdisciplinary science: A path to understanding the interactions among ocean acidification, ecosystems, and society","docAbstract":"The global nature of ocean acidification (OA) transcends habitats, ecosystems, regions, and science disciplines. The scientific community recognizes that the biggest challenge in improving understanding of how changing OA conditions affect ecosystems, and associated consequences for human society, requires integration of experimental, observational, and modeling approaches from many disciplines over a wide range of temporal and spatial scales. Such transdisciplinary science is the next step in providing relevant, meaningful results and optimal guidance to policymakers and coastal managers. We discuss the challenges associated with integrating ocean acidification science across funding agencies, institutions, disciplines, topical areas, and regions, and the value of unifying science objectives and activities to deliver insights into local, regional, and global scale impacts. We identify guiding principles and strategies for developing transdisciplinary research in the ocean acidification science community.
","language":"English","publisher":"Oceanography Society","publisherLocation":"Rockville, MD","doi":"10.5670/oceanog.2015.43","usgsCitation":"Yates, K.K., Turley, C., Hopkinson, B.M., Todgham, A.E., Cross, J.N., Greening, H., Williamson, P., Van Hooidonk, R., Deheyn, D.D., and Johnson, Z., 2015, Transdisciplinary science: A path to understanding the interactions among ocean acidification, ecosystems, and society: Oceanography, v. 28, no. 2, p. 212-225, https://doi.org/10.5670/oceanog.2015.43.","productDescription":"i, 14 p.","startPage":"212","endPage":"225","numberOfPages":"15","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060179","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":471885,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5670/oceanog.2015.43","text":"Publisher Index Page"},{"id":306587,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"28","issue":"2","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55cb0ea4e4b08400b1fdd45d","contributors":{"authors":[{"text":"Yates, Kimberly K. 0000-0001-8764-0358 kyates@usgs.gov","orcid":"https://orcid.org/0000-0001-8764-0358","contributorId":420,"corporation":false,"usgs":true,"family":"Yates","given":"Kimberly","email":"kyates@usgs.gov","middleInitial":"K.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":566557,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Turley, Carol","contributorId":146189,"corporation":false,"usgs":false,"family":"Turley","given":"Carol","email":"","affiliations":[{"id":16618,"text":"Plymouth Marine Laboratory - UK","active":true,"usgs":false}],"preferred":false,"id":566558,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hopkinson, Brian M.","contributorId":146190,"corporation":false,"usgs":false,"family":"Hopkinson","given":"Brian","email":"","middleInitial":"M.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":566559,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Todgham, Anne E.","contributorId":146191,"corporation":false,"usgs":false,"family":"Todgham","given":"Anne","email":"","middleInitial":"E.","affiliations":[{"id":6690,"text":"San Francisco State University","active":true,"usgs":false}],"preferred":false,"id":566560,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cross, Jessica N.","contributorId":146192,"corporation":false,"usgs":false,"family":"Cross","given":"Jessica","email":"","middleInitial":"N.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":566562,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Greening, Holly","contributorId":64299,"corporation":false,"usgs":true,"family":"Greening","given":"Holly","email":"","affiliations":[],"preferred":false,"id":566561,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Williamson, Phillip","contributorId":146188,"corporation":false,"usgs":false,"family":"Williamson","given":"Phillip","email":"","affiliations":[{"id":16617,"text":"University of East Anglia","active":true,"usgs":false}],"preferred":false,"id":566564,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Van Hooidonk, Ruben","contributorId":146193,"corporation":false,"usgs":false,"family":"Van Hooidonk","given":"Ruben","email":"","affiliations":[{"id":12641,"text":"NOAA NMFS","active":true,"usgs":false}],"preferred":false,"id":566563,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Deheyn, Dimitri D.","contributorId":146194,"corporation":false,"usgs":false,"family":"Deheyn","given":"Dimitri","email":"","middleInitial":"D.","affiliations":[{"id":16619,"text":"UCSD","active":true,"usgs":false}],"preferred":false,"id":566565,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Johnson, Zackary","contributorId":229396,"corporation":false,"usgs":false,"family":"Johnson","given":"Zackary","affiliations":[{"id":12643,"text":"Duke University","active":true,"usgs":false}],"preferred":false,"id":954394,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70155836,"text":"70155836 - 2015 - How well can wave runup be predicted? comment on Laudier et al. (2011) and Stockdon et al. (2006)","interactions":[],"lastModifiedDate":"2015-08-11T15:55:32","indexId":"70155836","displayToPublicDate":"2015-08-11T16:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1262,"text":"Coastal Engineering","active":true,"publicationSubtype":{"id":10}},"title":"How well can wave runup be predicted? comment on Laudier et al. (2011) and Stockdon et al. (2006)","docAbstract":"Laudier et al. (2011) suggested that there may be a systematic bias error in runup predictions using a model developed by Stockdon et al. (2006). Laudier et al. tested cases that sampled beach and wave conditions that differed from those used to develop the Stockdon et al. model. Based on our re-analysis, we found that in two of the three Laudier et al. cases observed overtopping was actually consistent with the Stockdon et al. predictions. In these cases, the revised predictions indicated substantial overtopping with, in one case, a freeboard deficit of 1 m. In the third case, the revised prediction had a low likelihood of overtopping, which reflected a large uncertainty due to wave conditions that included a broad and bi-modal frequency distribution. The discrepancy between Laudier et al. results and our re-analysis appear to be due, in part, to simplifications made by Laudier et al. when they implemented a reduced version of the Stockdon et al. model.
","language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam","doi":"10.1016/j.coastaleng.2015.05.001","usgsCitation":"Plant, N.G., and Stockdon, H.F., 2015, How well can wave runup be predicted? comment on Laudier et al. (2011) and Stockdon et al. (2006): Coastal Engineering, v. 102, no. 2015, p. 44-48, https://doi.org/10.1016/j.coastaleng.2015.05.001.","productDescription":"5 p.","startPage":"44","endPage":"48","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065141","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":471886,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.coastaleng.2015.05.001","text":"Publisher Index Page"},{"id":306590,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"102","issue":"2015","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55cb0ea3e4b08400b1fdd455","chorus":{"doi":"10.1016/j.coastaleng.2015.05.001","url":"http://dx.doi.org/10.1016/j.coastaleng.2015.05.001","publisher":"Elsevier BV","authors":"Plant Nathaniel G., Stockdon Hilary F.","journalName":"Coastal Engineering","publicationDate":"8/2015","auditedOn":"7/24/2015"},"contributors":{"authors":[{"text":"Plant, Nathaniel G. 0000-0002-5703-5672 nplant@usgs.gov","orcid":"https://orcid.org/0000-0002-5703-5672","contributorId":3503,"corporation":false,"usgs":true,"family":"Plant","given":"Nathaniel","email":"nplant@usgs.gov","middleInitial":"G.","affiliations":[{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":566551,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stockdon, Hilary F. 0000-0003-0791-4676 hstockdon@usgs.gov","orcid":"https://orcid.org/0000-0003-0791-4676","contributorId":2153,"corporation":false,"usgs":true,"family":"Stockdon","given":"Hilary","email":"hstockdon@usgs.gov","middleInitial":"F.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":566552,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70155211,"text":"fs20153050 - 2015 - Assessment of undiscovered oil and gas resources in sandstone reservoirs of the Cotton Valley Group, U.S. Gulf Coast, 2015","interactions":[],"lastModifiedDate":"2015-08-12T08:51:28","indexId":"fs20153050","displayToPublicDate":"2015-08-11T16:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-3050","title":"Assessment of undiscovered oil and gas resources in sandstone reservoirs of the Cotton Valley Group, U.S. Gulf Coast, 2015","docAbstract":"Using a geology-based assessment methodology, the U.S. Geological Survey estimated undiscovered mean volumes of 14 million barrels of conventional oil, 430 billion cubic feet of conventional gas, 34,028 billion cubic feet of continuous gas, and a mean total of 391 million barrels of natural gas liquids in sandstone reservoirs of the Upper Jurassic–Lower Cretaceous Cotton Valley Group in onshore lands and State waters of the U.S. Gulf Coast region.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20153050","collaboration":"National and Global Petroleum Assessment","usgsCitation":"Eoff, J.D., Biewick, L.R.H., Brownfield, M.E., Burke, Lauri, Charpentier, R.R., Dubiel, R.F., Gaswirth, S.B., Gianoutsos, N.J., Kinney, S.A., Klett, T.R., Leathers, H.M., Mercier, T.J., Paxton, S.T., Pearson, O.N., Pitman, J.K., Schenk, C.J., Tennyson, M.E., and Whidden, K.J., 2015, Assessment of undiscovered oil and gas resources in sandstone reservoirs of the Cotton Valley Group, U.S. Gulf Coast, 2015: U.S. Geological Survey Fact Sheet 2015-3050, 2 p., https://dx.doi.org/10.3133/fs20153050.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066205","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":306556,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2015/3050/coverthb.jpg"},{"id":306558,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2015/3050/fs20153050.pdf","text":"Report","size":"1.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2015-3050"}],"country":"United States","otherGeospatial":"Cotton Valley Group, Gulf Coast","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.08935546875,\n 30.164126343161097\n ],\n [\n -84.24316406249999,\n 30.845647420182598\n ],\n [\n -84.72656249999999,\n 31.203404950917395\n ],\n [\n -85.20996093749999,\n 31.034108344903512\n ],\n [\n -86.06689453125,\n 30.996445897426373\n ],\n [\n -87.25341796875,\n 31.989441837922904\n ],\n [\n -88.681640625,\n 32.43561304116276\n ],\n [\n -89.84619140625,\n 33.26624989076275\n ],\n [\n -90.63720703125,\n 33.96158628979907\n ],\n [\n -91.1865234375,\n 33.97980872872457\n ],\n [\n -91.99951171875,\n 33.706062655101206\n ],\n [\n -93.14208984375,\n 33.578014746143985\n ],\n [\n -94.54833984375,\n 33.797408767572485\n ],\n [\n -95.25146484374999,\n 33.97980872872457\n ],\n [\n -96.17431640625,\n 33.815666308702774\n ],\n [\n -96.7236328125,\n 33.687781758439364\n ],\n [\n -97.58056640625,\n 32.99023555965106\n ],\n [\n -97.93212890625,\n 32.008075959291055\n ],\n [\n -98.02001953125,\n 31.27855085894653\n ],\n [\n -98.0859375,\n 30.543338954230222\n ],\n [\n -98.28369140625,\n 29.954934549656144\n ],\n [\n -99.052734375,\n 29.38217507514529\n ],\n [\n -100.17333984375,\n 29.0945770775118\n ],\n [\n -100.83251953125,\n 29.248063243796576\n ],\n [\n -100.37109375,\n 28.57487404744697\n ],\n [\n -100.08544921874999,\n 27.97499795326776\n ],\n [\n -99.4482421875,\n 27.586197857692664\n ],\n [\n -98.7451171875,\n 27.994401411046173\n ],\n [\n -97.646484375,\n 28.57487404744697\n ],\n [\n -96.9873046875,\n 29.439597566602902\n ],\n [\n -96.30615234375,\n 30.107117887092382\n ],\n [\n -96.08642578125,\n 30.65681556429287\n ],\n [\n -95.5810546875,\n 31.18460913574325\n ],\n [\n -94.6142578125,\n 31.541089879585808\n ],\n [\n -93.3837890625,\n 31.541089879585808\n ],\n [\n -92.548828125,\n 31.93351676190369\n ],\n [\n -91.38427734374999,\n 31.653381399664\n ],\n [\n -90.1318359375,\n 31.57853542647338\n ],\n [\n -89.736328125,\n 31.015278981711266\n ],\n [\n -89.80224609374999,\n 30.619004797647808\n ],\n [\n -89.62646484375,\n 30.240086360983426\n ],\n [\n -88.76953125,\n 30.4297295750316\n ],\n [\n -88.08837890625,\n 30.29701788337205\n ],\n [\n -87.29736328125,\n 30.391830328088137\n ],\n [\n -85.95703125,\n 30.29701788337205\n ],\n [\n -85.5615234375,\n 30.14512718337613\n ],\n [\n -85.31982421875,\n 29.611670115197377\n ],\n [\n -84.8583984375,\n 29.66896252599253\n ],\n [\n -84.375,\n 29.954934549656144\n ],\n [\n -84.08935546875,\n 30.164126343161097\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver Federal Center
Denver, CO 80225-0046
http://energy.usgs.gov/
Gas emissions at the Yellowstone Plateau Volcanic Field (YPVF) reflect open-system mixing of gas species originating from diverse rock types, magmas, and crustal fluids, all combined in varying proportions at different thermal areas. Gases are not necessarily in chemical equilibrium with the waters through which they vent, especially in acid sulfate terrain where bubbles stream through stagnant acid water. Gases in adjacent thermal areas often can be differentiated by isotopic and gas ratios, and cannot be tied to one another solely by shallow processes such as boiling-induced fractionation of a parent liquid. Instead, they inherit unique gas ratios (e.g., CH4/He) from the dominant rock reservoirs where they originate, some of which underlie the Quaternary volcanic rocks. Steam/gas ratios (essentially H2O/CO2) of Yellowstone fumaroles correlate with Ar/He and N2/CO2, strongly suggesting that H2O/CO2 is controlled by addition of steam boiled from water rich in atmospheric gases. Moreover, H2O/CO2 varies systematically with geographic location, such that boiling is more enhanced in some areas than others. The δ13C and 3He/CO2 of gases reflect a dominant mantle origin for CO2 in Yellowstone gas. The mantle signature is most evident at Mud Volcano, which hosts gases with the lowest H2O/CO2, lowest CH4 concentrations and highest He isotope ratios (~16Ra), consistent with either a young subsurface intrusion or less input of crustal and meteoric gas than any other location at Yellowstone. Across the YPVF, He isotope ratios (3He/4He) inversely vary with He concentrations, and reflect varied amounts of long- stored, radiogenic He added to the magmatic endmember within the crust. Similarly, addition of CH4 from organic-rich sediments is common in the eastern thermal areas at Yellowstone. Overall, Yellowstone gases reflect addition of deep, high-temperature magmatic gas (CO2-rich), lower-temperatures crustal gases (4He- and CH4-bearing), and those gases (N2, Ne, Ar) added principally through boiling of the meteoric-water-derived geothermal liquid found in the upper few kilometers. We also briefly explore the pathways by which Cl, F, and S, move through the crust.
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This investigation aims to quantify population and infrastructure exposure within the conterminous U.S. that are subjected to varying levels of earthquake ground motions by systematically analyzing the last four cycles of the U.S. Geological Survey's (USGS) National Seismic Hazard Models (published in 1996, 2002, 2008 and 2014). Using the 2013 LandScan data, we estimate the numbers of people who are exposed to potentially damaging ground motions (peak ground accelerations at or above 0.1g). At least 28 million (~9% of the total population) may experience 0.1g level of shaking at relatively frequent intervals (annual rate of 1 in 72 years or 50% probability of exceedance (PE) in 50 years), 57 million (~18% of the total population) may experience this level of shaking at moderately frequent intervals (annual rate of 1 in 475 years or 10% PE in 50 years), and 143 million (~46% of the total population) may experience such shaking at relatively infrequent intervals (annual rate of 1 in 2,475 years or 2% PE in 50 years). We also show that there is a significant number of critical infrastructure facilities located in high earthquake-hazard areas (Modified Mercalli Intensity ≥ VII with moderately frequent recurrence interval).
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S.","email":"kjaiswal@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":565670,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Petersen, Mark D. 0000-0001-8542-3990 mpetersen@usgs.gov","orcid":"https://orcid.org/0000-0001-8542-3990","contributorId":1163,"corporation":false,"usgs":true,"family":"Petersen","given":"Mark","email":"mpetersen@usgs.gov","middleInitial":"D.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":565671,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rukstales, Kenneth S. 0000-0003-2818-078X rukstales@usgs.gov","orcid":"https://orcid.org/0000-0003-2818-078X","contributorId":775,"corporation":false,"usgs":true,"family":"Rukstales","given":"Kenneth","email":"rukstales@usgs.gov","middleInitial":"S.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":565672,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Leith, William S. 0000-0002-3463-3119 wleith@usgs.gov","orcid":"https://orcid.org/0000-0002-3463-3119","contributorId":2248,"corporation":false,"usgs":true,"family":"Leith","given":"William","email":"wleith@usgs.gov","middleInitial":"S.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":565673,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70155823,"text":"70155823 - 2015 - Understory vegetation as an indicator for floodplain forest restoration in the Mississippi River Alluvial Valley, U.S.A.","interactions":[],"lastModifiedDate":"2017-01-11T15:38:09","indexId":"70155823","displayToPublicDate":"2015-08-11T13:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3271,"text":"Restoration Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Understory vegetation as an indicator for floodplain forest restoration in the Mississippi River Alluvial Valley, U.S.A.","docAbstract":"In the Mississippi River Alluvial Valley (MAV), complete alteration of river-floodplain hydrology allowed for widespread
conversion of forested bottomlands to intensive agriculture, resulting in nearly 80% forest loss. Governmental programs have
attempted to restore forest habitat and functions within this altered landscape by the methods of tree planting (afforestation)
and local hydrologic enhancement on reclaimed croplands. Early assessments identified factors that influenced whether
planting plus tree colonization could establish an overstory community similar to natural bottomland forests. The extent
to which afforested sites develop typical understory vegetation has not been evaluated, yet understory composition may be
indicative of restored site conditions. As part of a broad study quantifying the ecosystem services gained from restoration
efforts, understory vegetation was compared between 37 afforested sites and 26 mature forest sites. Differences in vegetation
attributes for species growth forms, wetland indicator classes, and native status were tested with univariate analyses;
floristic composition data were analyzed by multivariate techniques. Understory vegetation of restoration sites was generally
hydrophytic, but species composition differed from that of mature bottomland forest because of young successional age and
differing responses of plant growth forms. Attribute and floristic variation among restoration sites was related to variation
in canopy development and local wetness conditions, which in turn reflected both intrinsic site features and outcomes of
restoration practices. Thus, understory vegetation is a useful indicator of functional progress in floodplain forest restoration.
Chemoreception is hypothesized to influence spawning site selection, mate search, and synchronization of gamete release in chars (Salvelinus spp.), but behavioral evidence is generally lacking. Here, we provide a survey of the behavioral responses of reproductive male and female lake trout (Salvelinus namaycush) to natural conspecific chemosensory stimuli. A flow-through laboratory assay with side-by-side artificial spawning reefs was used to evaluate behavioral preferences of spawning-phase males and females for chemosensory stimuli from juveniles and from spawning-phase males and females. Males and females preferred male and juvenile stimuli over no stimuli, but only had weak preferences for female stimuli. Only females had a preference for male over juvenile stimuli when given a direct choice between the two. The unexpected observation of male attraction to male stimuli, even when offered female stimuli, indicates a fundamental difference from the existing models of chemical communication in fishes. We discuss our results from the perspectives of prespawning aggregation, mate evaluation, and spawning synchronization. Identification of specific components of the stimuli will allow confirmation of the function and may have management implications for native and invasive populations of lake trout that are ecologically and economically important.
","language":"English","publisher":"National Research Council Canada","publisherLocation":"Ottawa","doi":"10.1139/cjfas-2015-0351","collaboration":"Tyler J. Buchinger; Weiming Li","usgsCitation":"Buchinger, T.J., Li, W., and Johnson, N., 2015, Behavioral evidence for a role of chemoreception during reproduction in lake trout: Canadian Journal of Fisheries and Aquatic Sciences, v. 72, no. 12, p. 1847-1852, https://doi.org/10.1139/cjfas-2015-0351.","productDescription":"6 p.","startPage":"1847","endPage":"1852","numberOfPages":"6","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-067693","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":313092,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"72","issue":"12","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56850e57e4b0a04ef49337f5","contributors":{"authors":[{"text":"Buchinger, Tyler J.","contributorId":40508,"corporation":false,"usgs":true,"family":"Buchinger","given":"Tyler","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":583937,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Li, Weiming","contributorId":126748,"corporation":false,"usgs":false,"family":"Li","given":"Weiming","email":"","affiliations":[{"id":6590,"text":"Department of Fisheries and Wildlife, Michigan State University","active":true,"usgs":false}],"preferred":false,"id":583938,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Nicholas S. 0000-0002-7419-6013 njohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-7419-6013","contributorId":150983,"corporation":false,"usgs":true,"family":"Johnson","given":"Nicholas S.","email":"njohnson@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":583936,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70148270,"text":"ds942 - 2015 - Geochemical, modal, and geochronologic data for 1.4 Ga A-type granitoid intrusions of the conterminous United States","interactions":[],"lastModifiedDate":"2016-06-29T13:23:03","indexId":"ds942","displayToPublicDate":"2015-08-10T11:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"942","title":"Geochemical, modal, and geochronologic data for 1.4 Ga A-type granitoid intrusions of the conterminous United States","docAbstract":"The purpose of this report is to present available geochemical, modal, and geochronologic data for approximately 1.4 billion year (Ga) A-type granitoid intrusions of the United States and to make those data available to ongoing petrogenetic investigations of these rocks. A-type granites, as originally defined by Loiselle and Wones (1979), are iron-enriched granitoids (synonymous with the ferroan granitoids of Frost and Frost, 2011) that occur in an anorogenic, within-continent setting. Relative to other granitic rocks, A-type granites have high FeO*/(FeO*+MgO), high K2O and K2O/Na2O, are metaluminous to weakly peraluminous, and are enriched in incompatible trace elements. Loiselle and Wones (1979) further suggested that A-type granites are relatively anhydrous. Anderson (1983) provides an early compilation of data for the products of 1.4 Ga magmatism in North America and notes the spatial and temporal association of a trio of rock types, which includes gabbro to anorthosite, intermediate composition mangerite, and granitic rapakivi rocks. In North America, the majority of known A-type intrusions were emplaced between 1.5 and 1.3 Ga and are predominantly of the granitic variety (Anderson, 1983).
\nThis report addresses the broadly Mesoproterozoic-age granitic rocks of the conterminous United States. Constituents of this group of intrusive rocks were defined using a variety of spatial, compositional, and geochronologic metrics. Thomas and others (2012) provided an updated synthesis, largely based on new isotopic and geochronologic data (for example, Fisher and others, 2010), for the large-scale geologic and tectonic evolution of the eastern United States. Their findings suggest that the basement rocks of the central and southern Appalachian region are allochthonous relative to the remainder of Laurentia and were accreted along the Grenville front between 1.25 and 1.0 Ga. Accordingly, Mesoproterozoic rocks east of the Grenville front and south of the approximate latitude of New York City do not represent North American magmatism. Consequently, geochemical, modal, and geochronologic data for these rocks are not included in the compilation described herein. Further, the structural styles and compositions of granitoid rocks east of the Grenville front, mostly highly deformed gneissic rocks, are dissimilar to those characteristic of the A-type granitoid rocks described herein.
\nA variety of compositional and age information further characterizes the 1.4 Ga A-type granitoid rocks in the conterminous United States. Most samples included in this compilation have felsic compositions, although some extend to intermediate compositions. SiO2 contents range from 56 to almost 78 weight percent, and median and mean SiO2 contents are 72.0 and 71.1 weight percent, respectively. The majority of these rocks for which modal data are available are composed of monzogranite (Streckeisen, 1976), although the dataset also contains many samples composed of granodiorite and syenogranite. A smaller group of the granitoid rocks in this dataset are composed of quartz monzodiorite and quartz monzonite, and a very small subset of samples is composed of alkali-feldspar granite, tonalite, alkali-feldspar quartz syenite, and quartz syenite (fig. 1). Many of the 1.4 Ga granitoid rocks are further characterized by medium- to coarse-grain size and are also conspicuously porphyritic; alkali feldspar phenocrysts or megacrysts (2–10 cm), often with rapakivi overgrowths, are a common feature of many of these rocks (Anderson, 1983; Anderson and Bender, 1989; Anderson and Cullers, 1978; Condie and Budding, 1979). The age of A-type magmatism in North America ranges from about 1.8 to 1.0 Ga, although Anderson (1983) suggests that more than 70 percent (by volume) of A-type magmatism in this region occurred between 1.49 and 1.41 Ga. In the conterminous United States, ages of A-type granitoid rocks are restricted to the period between about 1.49 and 1.33 Ga (Anderson, 1983; Bauer and Pollock, 1993; Bickford and Mose, 1975; Bickford, Harrower, and others, 1981; Bickford and others, 1989; Dewane and Van Schmus, 2007; Hoppe and others, 1983; Peterman and Hedge, 1968; Van Schmus and Bickford, 1981; Van Schmus and others, 1975). Using these recognition criteria, we identified A-type granitoid intrusions of the conterminous United States; for those intrusions, we compiled available geochemical, modal, isotopic (Sr and Nd) and geochronologic data for inclusion in the databases described herein.
\nThe significance of 1.4 Ga granitoid rocks relative to the geologic evolution of the conterminous United States remains unclear, despite Anderson’s (1983) compilation and synthesis of compositional data pertinent to these rocks. The large-volume magmatic events indicated by these rocks, as well as their broad geographic distribution, tectonic significance, and association with mineral deposits, underscore their importance. The broad distribution of these rocks, from the northern mid-continent to the southwestern United States (in New Mexico, Arizona, California, and southernmost Nevada), throughout the Rocky Mountains in New Mexico and Colorado (and sporadically in southern Wyoming and central Idaho), and beneath much of the Plains region (as indicated by drilling), has led to the large-scale tectonic and magmatic processes responsible for genesis of the associated magmas being actively studied.
\nIn addition, Kisvarsanyi (1972) suggests that iron-copper deposits in the St. Francois Mountains of southeastern Missouri are petrogenetically associated with 1.4 Ga A-type granitoids that occur in that region. Similarly, Dall’Agnol and others (2012) summarize important global associations between A-type granitoid rocks and a variety of important ore deposit types, particularly tin, high-field-strength elements (Zr, Hf, Nb, Ta), rare-earth elements, and iron oxide-copper-gold deposits. Consequently, the need to better understand relations between A-type granitoid rocks, tectonic setting, and magma petrogenesis, as well as their genetic associations with important types of ore deposits, suggests that developing a definitive geochemical, modal, and geochronologic database for these rocks in the conterminous United States is of considerable value.
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U.S. Geological Survey
Box 25046, Mail Stop 973
Denver, CO 80225
http://minerals.cr.usgs.gov/
This report, prepared for the National Earthquake Prediction Evaluation Council (NEPEC), is intended as a step toward improving communications about earthquake hazards between information providers and users who coordinate emergency-response activities in the Cascadia region of the Pacific Northwest. NEPEC charged a subcommittee of scientists with writing this report about forewarnings of increased probabilities of a damaging earthquake. We begin by clarifying some terminology; a “prediction” refers to a deterministic statement that a particular future earthquake will or will not occur. In contrast to the 0- or 100-percent likelihood of a deterministic prediction, a “forecast” describes the probability of an earthquake occurring, which may range from >0 to <100 percent. When the time window is short (days to months) and the forecast is formulated for operational utility, this term may be “operational earthquake forecasting.” The subcommittee considered short-term forecasts only, herein referred to as “forewarnings,” but not their formulation into messages or their applications, which will be addressed by NEPEC in subsequent activities.
The subcommittee considered “direct” and “indirect” forewarnings. Direct forewarnings originate with observed changes in geologic processes or conditions, which may include
Indirect forewarnings are based largely on model predictions of increased earthquake-occurrence probabilities. In this context, “models” refers to simulations of the processes believed to affect earthquake occurrence, as implemented in computer software, laboratory experiments, or some analog natural system. These indirect forewarnings likely will be more uncertain and difficult to interpret than direct forewarnings. This report also highlights the challenges of assessing the significance of forewarnings, which mostly will be extraordinary events with little or no historical precedent in the Cascadia region.
\n","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151151","usgsCitation":"Gomberg, J., Atwater, B., Beeler, N., Bodin, P., Davis, E., Frankel, A., Hayes, G., McConnell, V., Melbourne, T., Oppenheimer, D., Parrish, J., Roeloffs, E., Rogers, G., Sherrod, B., Vidale, J., Walsh, T., Weaver, C., and Whitmore, P., 2015, Earthquake forewarning in the Cascadia region: U.S. Geological Survey Open-File Report 2015–1151, 8 p., https://dx.doi.org/10.3133/ofr20151151.","productDescription":"iii, 8 p.","numberOfPages":"11","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-064402","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":306462,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1151/coverthb.gif"},{"id":306463,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1151/ofr20151151.pdf","text":"Report","size":"230 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1151"}],"country":"Canada, United States","otherGeospatial":"Cascadia region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.0576171875,\n 40.58058466412764\n ],\n [\n -122.4755859375,\n 41.1455697310095\n ],\n [\n -121.37695312499999,\n 42.00032514831621\n ],\n [\n -120.14648437499999,\n 42.553080288955826\n ],\n [\n -117.72949218749999,\n 42.16340342422401\n ],\n [\n -116.630859375,\n 41.83682786072714\n ],\n [\n -114.78515624999999,\n 41.672911819602085\n ],\n [\n -111.181640625,\n 42.00032514831621\n ],\n [\n -109.6875,\n 42.52069952914966\n ],\n [\n -109.9072265625,\n 43.51668853502909\n ],\n [\n -111.0498046875,\n 44.59046718130883\n ],\n [\n -113.37890625,\n 45.02695045318546\n ],\n [\n -112.8076171875,\n 45.9511496866914\n ],\n [\n -113.4228515625,\n 46.800059446787316\n ],\n [\n -116.45507812500001,\n 49.724479188713005\n ],\n [\n -118.21289062499999,\n 52.64306343665892\n ],\n [\n -121.025390625,\n 54.41892996865827\n ],\n [\n -129.7265625,\n 58.63121664342478\n ],\n [\n -134.912109375,\n 59.977005492196\n ],\n [\n -137.373046875,\n 60.15244221438077\n ],\n [\n -139.21874999999997,\n 60.37042901631508\n ],\n [\n -141.064453125,\n 60.413852350464914\n ],\n [\n -141.591796875,\n 59.88893689676585\n ],\n [\n -140.09765625,\n 59.66774058164963\n ],\n [\n -138.25195312499997,\n 58.99531118795094\n ],\n [\n -135.17578125,\n 56.36525013685606\n ],\n [\n -132.451171875,\n 52.32191088594773\n ],\n [\n -129.0234375,\n 50.62507306341435\n ],\n [\n -125.94726562499999,\n 49.095452162534826\n ],\n [\n -124.365234375,\n 48.04870994288686\n ],\n [\n -124.27734374999999,\n 44.84029065139799\n ],\n [\n -124.71679687499999,\n 42.81152174509788\n ],\n [\n -124.0576171875,\n 40.58058466412764\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"
Earthquake Science Center—Seattle, Washington Field Office
\nU.S. Geological Survey
\nDept. Earth & Space Sciences
\nUniversity of Washington, Box 351310
\nSeattle, WA 98195-1310
\n","tableOfContents":"In drylands, climate change is predicted to cause chronic reductions in water availability (press-droughts) through reduced precipitation and increased temperatures as well as increase the frequency and intensity of short-term extreme droughts (pulse-droughts). These changes in precipitation patterns may have profound ecosystem effects, depending on the sensitivities of the dominant plant functional types (PFTs). Here we present the responses of four Colorado Plateau PFTs to an experimentally imposed, 4-year, press-drought during which a natural pulse-drought occurred. Our objectives were to (1) identify the drought sensitivities of the PFTs, (2) assess the additive effects of the press- and pulse-drought, and (3) examine the interactive effects of soils and drought. Our results revealed that the C3 grasses were the most sensitive PFT to drought, the C3shrubs were the most resistant, and the C4 grasses and shrubs had intermediate drought sensitivities. Although we expected the C3 grasses would have the greatest response to drought, the higher resistance of C3 shrubs relative to the C4 shrubs was contrary to our predictions based on the higher water use efficiency of C4 photosynthesis. Also, the additive effects of press- and pulse-droughts caused high morality in C3 grasses, which has large ecological and economic ramifications for this region. Furthermore, despite predictions based on the inverse texture hypothesis, we observed no interactive effects of soils with the drought treatment on cover or mortality. These results suggest that plant responses to droughts in drylands may differ from expectations and have large ecological effects if press- and pulse-droughts push species beyond physiological and mortality thresholds.
","language":"English","publisher":"Springer-Verlag","publisherLocation":"Berlin","doi":"10.1007/s00442-015-3414-3","usgsCitation":"Hoover, D.L., Duniway, M.C., and Belnap, J., 2015, Pulse-drought atop press-drought: unexpected plant responses and implications for dryland ecosystems: Oecologia, v. 179, no. 4, p. 1211-1221, https://doi.org/10.1007/s00442-015-3414-3.","productDescription":"11 p.","startPage":"1211","endPage":"1221","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059648","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":306798,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"179","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-08-08","publicationStatus":"PW","scienceBaseUri":"55d305b9e4b0518e35468d1c","contributors":{"authors":[{"text":"Hoover, David L. dlhoover@usgs.gov","contributorId":5843,"corporation":false,"usgs":true,"family":"Hoover","given":"David","email":"dlhoover@usgs.gov","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":false,"id":567890,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Duniway, Michael C. 0000-0002-9643-2785 mduniway@usgs.gov","orcid":"https://orcid.org/0000-0002-9643-2785","contributorId":4212,"corporation":false,"usgs":true,"family":"Duniway","given":"Michael","email":"mduniway@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":567891,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Belnap, Jayne 0000-0001-7471-2279 jayne_belnap@usgs.gov","orcid":"https://orcid.org/0000-0001-7471-2279","contributorId":1332,"corporation":false,"usgs":true,"family":"Belnap","given":"Jayne","email":"jayne_belnap@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":567892,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70189705,"text":"70189705 - 2015 - Eruptive and environmental processes recorded by diatoms in volcanically-dispersed lake sediments from the Taupo Volcanic Zone, New Zealand","interactions":[],"lastModifiedDate":"2017-07-21T10:45:52","indexId":"70189705","displayToPublicDate":"2015-08-08T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2411,"text":"Journal of Paleolimnology","active":true,"publicationSubtype":{"id":10}},"title":"Eruptive and environmental processes recorded by diatoms in volcanically-dispersed lake sediments from the Taupo Volcanic Zone, New Zealand","docAbstract":"Late Pleistocene diatomaceous sediment was widely dispersed along with volcanic ash (tephra) across and beyond New Zealand by the 25.4 ka Oruanui supereruption from Taupo volcano. We present a detailed analysis of the diatom populations in the Oruanui tephra and the newly discovered floras in two other eruptions from the same volcano: the 28.6 ka Okaia and 1.8 ka Taupo eruptions. For comparison, the diatoms were also examined in Late Pleistocene and Holocene lake sediments from the Taupo Volcanic Zone (TVZ). Our study demonstrates how these microfossils provide insights into the lake history of the TVZ since the Last Glacial Maximum. Morphometric analysis of Aulacoseira valve dimensions provides a useful quantitative tool to distinguish environmental and eruptive processes within and between individual tephras. The Oruanui and Okaia diatom species and valve dimensions are highly consistent with a shared volcanic source, paleolake and eruption style (involving large-scale magma-water interaction). They are distinct from lacustrine sediments sourced elsewhere in the TVZ. Correspondence analysis shows that small, intact samples of erupted lake sediment (i.e., lithic clasts in ignimbrite) contain heterogeneous diatom populations, reflecting local variability in species composition of the paleolake and its shallowly-buried sediments. Our analysis also shows a dramatic post-Oruanui supereruption decline in Cyclostephanos novaezelandiae, which likely reflects a combination of (1) reorganisation of the watershed in the aftermath of the eruption, and (2) overall climate warming following the Last Glacial Maximum. This decline is reflected in substantially lower proportions of C. novaezelandiae in the 1.8 ka Taupo eruption deposits, and even fewer in post-1.8 ka sediments from modern (Holocene) Lake Taupo. Our analysis highlights how the excellent preservation of siliceous microfossils in volcanic tephra may fingerprint the volcanic source region and retain a valuable record of volcanically-influenced environmental change.","language":"English","publisher":"Springer","doi":"10.1007/s10933-015-9851-5","usgsCitation":"Harper, M.A., Pledger, S.A., Smith, E.G., Van Eaton, A.R., and Wilson, C., 2015, Eruptive and environmental processes recorded by diatoms in volcanically-dispersed lake sediments from the Taupo Volcanic Zone, New Zealand: Journal of Paleolimnology, v. 54, no. 4, p. 263-277, https://doi.org/10.1007/s10933-015-9851-5.","productDescription":"14 p. ","startPage":"263","endPage":"277","ipdsId":"IP-066862","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":344152,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"New Zealand","otherGeospatial":"Taupo Volcanic Zone","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 173.1884765625,\n -40.27952566881291\n ],\n [\n 178.87939453125,\n -40.27952566881291\n ],\n [\n 178.87939453125,\n -37.63163475580644\n ],\n [\n 173.1884765625,\n -37.63163475580644\n ],\n [\n 173.1884765625,\n -40.27952566881291\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"54","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-08-08","publicationStatus":"PW","scienceBaseUri":"5971c1c3e4b0ec1a4885dada","contributors":{"authors":[{"text":"Harper, Margaret A.","contributorId":194941,"corporation":false,"usgs":false,"family":"Harper","given":"Margaret","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":705874,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pledger, Shirley A.","contributorId":194942,"corporation":false,"usgs":false,"family":"Pledger","given":"Shirley","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":705875,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, Euan G. C.","contributorId":194943,"corporation":false,"usgs":false,"family":"Smith","given":"Euan","email":"","middleInitial":"G. C.","affiliations":[],"preferred":false,"id":705876,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Van Eaton, Alexa R. 0000-0001-6646-4594 avaneaton@usgs.gov","orcid":"https://orcid.org/0000-0001-6646-4594","contributorId":184079,"corporation":false,"usgs":true,"family":"Van Eaton","given":"Alexa","email":"avaneaton@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":705873,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wilson, Colin J. N.","contributorId":194944,"corporation":false,"usgs":false,"family":"Wilson","given":"Colin J. N.","affiliations":[],"preferred":false,"id":705877,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70155242,"text":"70155242 - 2015 - Muskellunge growth potential in northern Wisconsin: implications for trophy management","interactions":[],"lastModifiedDate":"2016-06-01T11:56:54","indexId":"70155242","displayToPublicDate":"2015-08-07T12:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Muskellunge growth potential in northern Wisconsin: implications for trophy management","docAbstract":"The growth potential of Muskellunge Esox masquinongy was evaluated by back-calculating growth histories from cleithra removed from 305 fish collected during 1995–2011 to determine whether it was consistent with trophy management goals in northern Wisconsin. Female Muskellunge had a larger mean asymptotic length (49.8 in) than did males (43.4 in). Minimum ultimate size of female Muskellunge (45.0 in) equaled the 45.0-in minimum length limit, but was less than the 50.0-in minimum length limit used on Wisconsin's trophy waters, while the minimum ultimate size of male Muskellunge (34.0 in) was less than the statewide minimum length limit. Minimum reproductive sizes for both sexes were less than Wisconsin's trophy minimum length limits. Mean growth potential of female Muskellunge in northern Wisconsin appears to be sufficient for meeting trophy management objectives and angler expectations. Muskellunge in northern Wisconsin had similar growth potential to those in Ontario populations, but lower growth potential than Minnesota's populations, perhaps because of genetic and environmental differences.
","language":"English","publisher":"American Fisheries Society","doi":"10.1080/02755947.2015.1044627","usgsCitation":"Faust, M.D., Isermann, D.A., Luehring, M.A., and Hansen, M.J., 2015, Muskellunge growth potential in northern Wisconsin: implications for trophy management: North American Journal of Fisheries Management, v. 35, no. 4, p. 766-774, https://doi.org/10.1080/02755947.2015.1044627.","productDescription":"9 p.","startPage":"766","endPage":"774","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062107","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":306498,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 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Among the many challenges faced by parks is management of wildlife populations that occupy larger landscapes than individual park units but that concentrate within park lands both seasonally and opportunistically. Great Sand Dunes National Park and Preserve in south-central Colorado is currently developing an Ungulate Management Plan to address management of elk and bison populations within the park. Execution of the Ungulate Management Plan will require monitoring and assessment of habitat conditions in areas that appear sensitive to ungulate use or heavily used by elk and bison. Several sources of information on the various habitats within the park and their use and response to foraging elk and bison exist from recent and on-going research in Great Sand Dunes National Park and Preserve as well as from studies in other regions of the Intermountain West. All of this data can be used to inform the planning process. This report provides background on vegetation types that make up the primary bison and elk ranges in Great Sand Dunes National Park and Preserve and on the potential effects of ungulate grazing and browsing in these specific vegetation communities (both locally and regionally). The report also provides a review of the elements necessary to develop a long-term monitoring program for Great Sand Dunes National Park and Preserve that addresses both the responses to ungulate herbivory seen in important habitats in the park and the amount and patterns of ungulate habitat use.
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Storms following wildfires are known to impair drinking water supplies in the southwestern United States, yet our understanding of the role of precipitation in post-wildfire water quality is far from complete. We quantitatively assessed water-quality impacts of different hydrologic events in the Colorado Front Range and found that for a three-year period, substantial hydrologic and geochemical responses downstream of a burned area were primarily driven by convective storms with a 30 min rainfall intensity >10 mm h−1. These storms, which typically occur several times each year in July–September, are often small in area, short-lived, and highly variable in intensity and geographic distribution. Thus, a rain gage network with high temporal resolution and spatial density, together with high-resolution stream sampling, are required to adequately characterize post-wildfire responses. We measured total suspended sediment, dissolved organic carbon (DOC), nitrate, and manganese concentrations that were 10–156 times higher downstream of a burned area compared to upstream during relatively common (50% annual exceedance probability) rainstorms, and water quality was sufficiently impaired to pose water-treatment concerns. Short-term water-quality impairment was driven primarily by increased surface runoff during higher intensity convective storms that caused erosion in the burned area and transport of sediment and chemical constituents to streams. Annual sediment yields downstream of the burned area were controlled by storm events and subsequent remobilization, whereas DOC yields were closely linked to annual runoff and thus were more dependent on interannual variation in spring runoff. Nitrate yields were highest in the third year post-wildfire. Results from this study quantitatively demonstrate that water quality can be altered for several years after wildfire. Because the southwestern US is prone to wildfires and high-intensity rain storms, the role of storms in post-wildfire water-quality impacts must be considered when assessing water-quality vulnerability.
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Branch","active":true,"usgs":true}],"preferred":true,"id":567541,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Writer, Jeffrey H. jwriter@usgs.gov","contributorId":1393,"corporation":false,"usgs":true,"family":"Writer","given":"Jeffrey","email":"jwriter@usgs.gov","middleInitial":"H.","affiliations":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"preferred":false,"id":567542,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McCleskey, R. Blaine 0000-0002-2521-8052 rbmccles@usgs.gov","orcid":"https://orcid.org/0000-0002-2521-8052","contributorId":147399,"corporation":false,"usgs":true,"family":"McCleskey","given":"R.","email":"rbmccles@usgs.gov","middleInitial":"Blaine","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true}],"preferred":true,"id":567543,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Martin, Deborah A. 0000-0001-8237-0838 damartin@usgs.gov","orcid":"https://orcid.org/0000-0001-8237-0838","contributorId":1900,"corporation":false,"usgs":true,"family":"Martin","given":"Deborah","email":"damartin@usgs.gov","middleInitial":"A.","affiliations":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"preferred":false,"id":567544,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70156027,"text":"70156027 - 2015 - Age of the Lava Creek supereruption and magma chamber assembly at Yellowstone based on 40Ar/39Ar and U-Pb dating of sanidine and zircon crystals","interactions":[],"lastModifiedDate":"2018-03-21T10:24:22","indexId":"70156027","displayToPublicDate":"2015-08-07T04:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1757,"text":"Geochemistry, Geophysics, Geosystems","active":true,"publicationSubtype":{"id":10}},"title":"Age of the Lava Creek supereruption and magma chamber assembly at Yellowstone based on 40Ar/39Ar and U-Pb dating of sanidine and zircon crystals","docAbstract":"The last supereruption from the Yellowstone Plateau formed Yellowstone caldera and ejected the >1000 km3 of rhyolite that composes the Lava Creek Tuff. Tephra from the Lava Creek eruption is a key Quaternary chronostratigraphic marker, in particular for dating the deposition of mid Pleistocene glacial and pluvial deposits in western North America. To resolve the timing of eruption and crystallization history for the Lava Creek magma, we performed (1) 40Ar/39Ar dating of single sanidine crystals to delimit eruption age and (2) ion microprobe U-Pb and trace-element analyses of the crystal faces and interiors of single zircons to date the interval of zircon crystallization and characterize magmatic evolution. Sanidines from the two informal members composing Lava Creek Tuff yield a preferred 40Ar/39Ar isochron date of 631.3 ± 4.3 ka. Crystal faces on zircons from both members yield a weighted mean 206Pb/238U date of 626.5 ± 5.8 ka, and have trace element concentrations that vary with the eruptive stratigraphy. Zircon interiors yield a mean 206Pb/238U date of 659.8 ± 5.5 ka, and reveal reverse and/or oscillatory zoning of trace element concentrations, with many crystals containing high U concentration cores that likely grew from highly evolved melt. The occurrence of distal Lava Creek tephra in stratigraphic sequences marking the Marine Isotope Stage 16–15 transition supports the apparent eruption age of ∼631 ka. The combined results reveal that Lava Creek zircons record episodic heating, renewed crystallization, and an overall up-temperature evolution for Yellowstone's subvolcanic reservoir in the 103−104 year interval before eruption.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2015GC005881","usgsCitation":"Matthews, N.E., Vazquez, J.A., and Calvert, A.T., 2015, Age of the Lava Creek supereruption and magma chamber assembly at Yellowstone based on 40Ar/39Ar and U-Pb dating of sanidine and zircon crystals: Geochemistry, Geophysics, Geosystems, v. 16, no. 8, p. 2508-2528, https://doi.org/10.1002/2015GC005881.","productDescription":"21 p.","startPage":"2508","endPage":"2528","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065261","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":306756,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Yellowstone National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.4013671875,\n 42.204107493733176\n ],\n [\n -111.4013671875,\n 45.158800738352134\n ],\n [\n -103.260498046875,\n 45.158800738352134\n ],\n [\n -103.260498046875,\n 42.204107493733176\n ],\n [\n -111.4013671875,\n 42.204107493733176\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"16","issue":"8","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-08-07","publicationStatus":"PW","scienceBaseUri":"55fbe435e4b05d6c4e5028d5","contributors":{"authors":[{"text":"Matthews, Naomi E. nmatthews@usgs.gov","contributorId":4990,"corporation":false,"usgs":true,"family":"Matthews","given":"Naomi","email":"nmatthews@usgs.gov","middleInitial":"E.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":567734,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vazquez, Jorge A. 0000-0003-2754-0456 jvazquez@usgs.gov","orcid":"https://orcid.org/0000-0003-2754-0456","contributorId":4458,"corporation":false,"usgs":true,"family":"Vazquez","given":"Jorge","email":"jvazquez@usgs.gov","middleInitial":"A.","affiliations":[{"id":501,"text":"Office of Science Quality and Integrity","active":true,"usgs":true},{"id":5056,"text":"Office of the AD Energy and Minerals, and Environmental Health","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":567733,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Calvert, Andrew T. 0000-0001-5237-2218 acalvert@usgs.gov","orcid":"https://orcid.org/0000-0001-5237-2218","contributorId":2694,"corporation":false,"usgs":true,"family":"Calvert","given":"Andrew","email":"acalvert@usgs.gov","middleInitial":"T.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":567735,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70188565,"text":"70188565 - 2015 - Estimating rates of debris flow entrainment from ground vibrations","interactions":[],"lastModifiedDate":"2017-06-15T13:38:05","indexId":"70188565","displayToPublicDate":"2015-08-07T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Estimating rates of debris flow entrainment from ground vibrations","docAbstract":"Debris flows generate seismic waves as they travel downslope and can become more dangerous\nas they entrain sediment along their path. We present field observations that show a systematic relation\nbetween the magnitude of seismic waves and the amount of erodible sediment beneath the flow. Specifically,\nwe observe that a debris flow traveling along a channel filled initially with sediment 0.34m thick generates\nabout 2 orders of magnitude less spectral power than a similar-sized flow over the same channel without\nsediment fill.We adapt amodel fromfluvial seismology to explain this observation and then invert it to estimate\nthe level of bed sediment (and rate of entrainment) beneath a passing series of surges. Our estimates compare\nfavorably with previous direct measurements of entrainment rates at the site, suggesting the approach may be\na new indirect way to obtain rare field constraints needed to test models of debris flow entrainment.","language":"English","publisher":"AGU","doi":"10.1002/2015GL064811","usgsCitation":"Kean, J.W., Coe, J.A., Coviello, V., Smith, J.B., McCoy, S., and Arattano, M., 2015, Estimating rates of debris flow entrainment from ground vibrations: Geophysical Research Letters, v. 42, no. 15, p. 6365-6372, https://doi.org/10.1002/2015GL064811.","productDescription":"8 p. 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The measure of total dissolved solids is the sum of all the major ion concentrations in solution and in this case, the dominant ions are sodium (Na) and sulfate (SO4), which can form salts like thenardite (Na2SO4) and mirabilite (Na2SO4⋅H2O). The Utah Department of Environmental Quality (2010) classified the contamination as natural background and from nonpoint sources related to regional lithology and irrigation practices. Although the daily loads of the constituents of concern and water chemistry have been characterized for parts of the watershed, little is known about the controls that bedrock and soil mineralogy have on salt, Se, and B storage and the water-rock interactions that influence the mobility of these components in ground and surface waters. Studies in the Uncompahgre River watershed in Colorado by Tuttle and others (2014a, 2014b) show that salt derived from weathering of shale in a semiarid climate is stored in a variety of minerals that contribute solutes to runoff and surface waters based on a complex set of conditions such as water availability, geomorphic position (for example, topography controls the depth of salt accumulation in soils), water-table fluctuations, redox conditions, mineral dissolution kinetics, ion-exchange reactions, and secondary mineral formation. Elements like Se and B commonly reside in soluble salt phases, so knowledge of the behavior of salt minerals also sheds light on the behavior of associated contaminants.
\nThe goal of this study was to establish a process-based understanding of salt, Se, and B behavior to address whether these contaminants can be better managed, or if uncontrollable natural processes will overwhelm any attempts to bring Pariette Draw into compliance with respect to recently established total maximum daily limits (TMDLs). We collected data to refine our knowledge about the role of rock weathering and soil formation in the transport and storage of salt in the watershed and to show how salt is cycled under irrigated and natural conditions. Our approach was to sample rock, soils, and sediment on irrigated and natural terrain for mineralogical analysis to determine the residence of salt and associated Se and B, classify minerals as primary (related to rock formation) or secondary weathering products, and characterize mineral dissolution kinetics. Mineral and chemical analyses and selective extractions of rocks and soils provide useful information in understanding solute movement and mineral dissolution/ formation. The resulting data are critical in determining residence of salt, Se, and B in weathered rock and soil and understanding the mobility during water-rock-soil interactions. This report summarizes our methods for sample and data collection and tabulates the mineral, chemical, and isotopic data collected.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151132","collaboration":"U.S. Geological Survey Mineral Resources Program, prepared in cooperation with Bureau of Reclamation, Bureau of Land Management, and Utah Department of Environmental Quality Division of Water Quality","usgsCitation":"Morrison, J.M., Tuttle, M.L.W., and Fahy, J.W., 2015, Results of mineral, chemical, and sulfate isotopic analyses\nof water, soil, rocks, and soil extracts from the Pariette Draw Watershed, Uinta Basin, Utah: U.S. Geological Survey\nOpen-File Report 2015–1132, 10 p., https://dx.doi.org/10.3133/ofr20151132.","productDescription":"Report: vii, 9 p.; 1 Appendix","numberOfPages":"21","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-060327","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":306414,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2015/1132/downloads","text":"Appendix Tables","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2015-1132 Appendix Tables"},{"id":306413,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1132/ofr20151132.pdf","text":"Report","size":"10.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1132"},{"id":306412,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1132/coverthb.jpg"}],"country":"United States","state":"Utah","otherGeospatial":"Uinta Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.18188476562499,\n 39.825413103424786\n ],\n [\n -110.18188476562499,\n 40.12429084831405\n ],\n [\n -109.434814453125,\n 40.12429084831405\n ],\n [\n -109.434814453125,\n 39.825413103424786\n ],\n [\n -110.18188476562499,\n 39.825413103424786\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Crustal Geophysics and Geochemistry Science Center
U.S. Geological Survey
Box 25046, MS 964
Denver, CO 80225
http://crustal.usgs.gov/
Isolated patches of native vegetation in human-modified landscapes are important reservoirs of biological diversity because they may be the only places in which rare or native species can persist. Manassas National Battlefield Park, Virginia, is an island embedded in a matrix of intensively modified lands; it is becoming increasingly isolated due to growth of the greater Washington, D.C. area. A series of cliffs along Bull Run support an eastern white pine community disjunct from its more typical range in the Appalachian Mountains. Cliffs frequently support vegetation communities that differ from surrounding habitat. In this ecological context, the cliffs along Bull Run are islands of specialized habitat within an island of natural and semi-natural communities (the park), surrounded by a human-dominated landscape. A floral survey of these cliffs was a top priority identified by the National Park Service National Capital Region via the National Resource Preservation Program; in 2014, we completed a floral survey of 11 cliffs in the park. We recorded 282 species in 194 genera and 83 families, including 23 newly documented species for the park.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds940","usgsCitation":"Stroh, E.D., Struckhoff, M.A., and Grabner, K.W., 2015, A floral survey of cliff habitats along Bull Run at Manassas National Battlefield Park, Virginia, 2014: U.S. Geological Survey Data Series 940, 20 p., https://dx.doi.org/10.3133/ds940.","productDescription":"Report: iv, 20 p.; Database; ReadMe","numberOfPages":"28","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2014-01-01","ipdsId":"IP-063929","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":306469,"rank":4,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/ds/0940/ReadMe.txt","text":"ReadMe File","size":"5.47 kB","linkFileType":{"id":2,"text":"txt"}},{"id":306409,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/0940/coverthb.jpg"},{"id":306410,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0940/ds940.pdf","text":"Report","size":"1.53 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 940"},{"id":306411,"rank":3,"type":{"id":9,"text":"Database"},"url":"https://dx.doi.org/10.5066/F7NS0RXN","text":"Manassas Bluff Flora Database"}],"country":"United States","state":"Virginia","otherGeospatial":"Bull Run, Manassas National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.62424468994139,\n 38.79369731838258\n ],\n [\n -77.61566162109375,\n 38.80654039080489\n ],\n [\n -77.60948181152344,\n 38.819916129801314\n ],\n [\n -77.60261535644531,\n 38.830614912420565\n ],\n [\n -77.59471893310547,\n 38.849066533608884\n ],\n [\n -77.58956909179688,\n 38.85414657465764\n ],\n [\n -77.58922576904297,\n 38.86083028642411\n ],\n [\n -77.57377624511719,\n 38.85708748522446\n ],\n [\n -77.57068634033203,\n 38.85468129471517\n ],\n [\n -77.552490234375,\n 38.850938169890064\n ],\n [\n -77.54528045654297,\n 38.84505571861154\n ],\n [\n -77.53429412841797,\n 38.841579496043266\n ],\n [\n -77.52399444580078,\n 38.83837052447013\n ],\n [\n -77.50991821289062,\n 38.84345132929943\n ],\n [\n -77.50373840332031,\n 38.83837052447013\n ],\n [\n -77.50099182128906,\n 38.833556795784745\n ],\n [\n -77.50614166259766,\n 38.83034746244922\n ],\n [\n -77.50030517578125,\n 38.82473078093276\n ],\n [\n -77.50133514404297,\n 38.81777618035695\n ],\n [\n -77.4972152709961,\n 38.81536866036827\n ],\n [\n -77.48451232910156,\n 38.81028585091164\n ],\n [\n -77.486572265625,\n 38.80225962384825\n ],\n [\n -77.48485565185547,\n 38.79931644737651\n ],\n [\n -77.47318267822266,\n 38.80225962384825\n ],\n [\n -77.48846054077148,\n 38.79543661993626\n ],\n [\n -77.51644134521484,\n 38.79008478723166\n ],\n [\n -77.5224494934082,\n 38.79704209139086\n ],\n [\n -77.53961563110352,\n 38.793831112316646\n ],\n [\n -77.54631042480467,\n 38.791556581282244\n ],\n [\n -77.54287719726562,\n 38.783795870358176\n ],\n [\n -77.57240295410156,\n 38.77710492428489\n ],\n [\n -77.62046813964844,\n 38.77041335043523\n ],\n [\n -77.62424468994139,\n 38.79369731838258\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Columbia Environmental Research Center
U.S. Geological Survey
4200 New Haven Road
Columbia, MO 65201
http://www.cerc.usgs.gov/
In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within the 3-nautical-mile limit of California’s State Waters. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data, acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow subsurface geology.
\nThe Offshore of Bodega Head map area is located in northern California, about 70 km north of San Francisco and about 80 km south of Point Arena. The onshore part of the map area is largely undeveloped, used primarily for recreation, farms and ranches, and a few wineries. The small town of Bodega Bay, located on the east side of Bodega Harbor, is the largest cultural center. Bodega Harbor is an important commercial fishing base and, in season, an active sport fishing and recreation harbor. Much of the coastline from Bodega Head north to about 6 km north of the Russian River is part of Sonoma Coast State Park. The Offshore of Bodega Head map area includes two California Marine Protected Areas, the Bodega Head State Marine Reserve and the northern part of the Bodega Head State Marine Conservation Area. Additionally, the inland parts of two large estuaries in the map area, Estero Americano and Estero de San Antonio, have been designated as State Marine Recreational Management Areas.
\nThe map area is cut by the northwest-striking San Andreas Fault, the right-lateral transform boundary between the North American and Pacific plates. This fault juxtaposes rocks of the Jurassic and Cretaceous Franciscan Complex on the northeast with Cretaceous granitic rocks on the southwest, and it has an estimated slip rate of about 17 to 25 mm/yr in this area. The devastating great 1906 California earthquake (M7.8) is thought to have nucleated on the San Andreas Fault offshore of San Francisco, about 80 km south of Bodega Head, with the rupture extending northward through the Offshore of Bodega Head map area and an additional 220 km to the south flank of Cape Mendocino.
\nNorth of the mouth of Salmon Creek, the coast and shoreline are rugged and scenic, characterized by flights of uplifted marine terraces, rocky promontories, nearshore sea stacks, kelp-rich coves, and both pocket beaches and longer beach strands, the latter of which include Wrights Beach and Portuguese Beach. The coast has lower relief between the mouth of Salmon Creek and Mussel Point, where South Salmon Creek Beach is backed by a large (about 4 km2) complex of coastal sand dunes. The enormous volume of sand on the beach and in the dune field is derived by southward littoral drift from the Russian River, Salmon Creek, and smaller coastal watersheds. The sediment is trapped by protruding bedrock at Mussel Point, which represents the south end of the Russian River littoral cell.
\nBodega Head is underlain by Cretaceous granitic rocks, and its shoreline is variously characterized by relatively low-lying terraces, steep and high bluffs, and a few pocket beaches. East of Bodega Head, Doran Beach (part of Doran Regional Park) is a 1.7-km-long sand spit that forms the north boundary of Bodega Bay and the south boundary of Bodega Harbor. The coast south of Doran Beach on the east flank of Bodega Bay is composed of rocky bluffs, hummocky marine terraces, and a few small pocket beaches. The bluffs are underlain by sheared rocks of the Franciscan Complex and are highly susceptible to landslides. This section of coast includes two prominent watersheds, Estero Americano and Estero de San Antonio, which drain westward into Bodega Bay.
\nThe offshore part of the Offshore of Bodega Head map area is characterized by an extensive, rugged and rocky shelf underlain by Cretaceous granitic rocks. This rocky terrain, centered offshore of Bodega Head, extends northwestward for about 15 km, from the south edge of the map area (where it forms the west boundary of Bodega Bay) to the northern-central part of the map area offshore of the mouth of Salmon Creek. This rocky seafloor reaches water depths of 40 to 80 m and is overlain by young sediment.
\nCirculation over the shelf and seafloor in the map area (and in the broader central California region) is dominated by the southward-flowing California Current, the eastern boundary current of the North Pacific Gyre. Associated upwelling brings cool, nutrient-rich waters to the surface, resulting in high biological productivity. Persistent northwest winds are sometimes weak or absent during the fall and winter, causing the California Current to move farther offshore so that the shelf is affected by the Davidson Current, a weaker northward-flowing countercurrent. As a result, net flow over the continental shelf is commonly southeastward during the spring and summer and northwestward during the fall and winter.
\nThroughout the year, this part of the northern California coast is exposed to four wave climate regimes: the north Pacific swell, the southern swell, northwest wind waves, and local wind waves. The north Pacific swell dominates in winter months (typically November through March). During summer months, the largest waves come from the southern swell, generated by storms in the south Pacific and offshore of Central America. Northwest wind waves affect the coast throughout the year, whereas local wind waves are most common from October to April.
\nPotential marine benthic habitats in the Offshore of Bodega Head map area include unconsolidated continental-shelf sediments, mixed continental-shelf substrate, and hard continental-shelf substrate. Rocky-shelf outcrops and rubble are considered to be promising potential habitats for rockfish and lingcod, both of which are recreationally and commercially important species.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151140","usgsCitation":"Johnson, S.Y., Dartnell, P., Golden, N.E., Hartwell, S.R., Erdey, M.D., Greene, H.G., Cochrane, G.R., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, B.E., Watt, J.T., Krigsman, L.M., Sliter, R.W., Lowe, E.N., and Chin, J.L. (S.Y. Johnson and S.A. Cochran, eds.), 2015, California State Waters Map Series—Offshore of Bodega Head, California: U.S. Geological Survey Open-File Report 2015–1140, pamphlet 39 p., 10 sheets, scale 1:24,000, https://dx.doi.org/10.3133/ofr20151140.","productDescription":"Report: iv, 39 p.; 10 Plates: 46.0 x 36.0 inches or smaller; Metadata; Data Catalog","numberOfPages":"43","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-055943","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":399007,"rank":20,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_102290.htm"},{"id":306403,"rank":19,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1140/coverthb.jpg"},{"id":306402,"rank":18,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/of/2015/1114/","text":"Open-File Report 2015–1114","description":"Open-File Report 2015–1114","linkHelpText":"California State Waters Map Series—Offshore of Point Reyes and Vicinity, California, by Janet T. 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Watt and others."},{"id":306416,"rank":14,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/ds/781/","text":"Data Series 781","description":"Data Series 781","linkHelpText":"California State Waters Map Series Data Catalog"},{"id":306398,"rank":13,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/of/2015/1140/ofr20151140_metadata.html","text":"Metadata","linkFileType":{"id":5,"text":"html"}},{"id":306397,"rank":12,"type":{"id":28,"text":"Dataset"},"url":"https://pubs.usgs.gov/ds/781/OffshoreBodegaHead/data_catalog_OffshoreBodegaHead.html","text":"Data Catalog","linkFileType":{"id":5,"text":"html"},"linkHelpText":"The GIS data layers for this map are accessible from “Data Catalog—Offshore of Bodega Head, California,” which is part of California State Waters Map Series Data Catalog (Data Series 781). Each GIS data file is listed with a brief description, a small image, and links to the metadata files and the downloadable data files."},{"id":306396,"rank":11,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2015/1140/ofr20151140_sheet10.pdf","text":"Sheet 10","linkFileType":{"id":1,"text":"pdf"},"description":"Sheet 10","linkHelpText":"Offshore and Onshore Geology and Geomorphology, Offshore of Bodega Head Map Area, California By Samuel Y. Johnson, Stephen R. Hartwell, and Michael W. Manson"},{"id":306395,"rank":10,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2015/1140/ofr20151140_sheet9.pdf","text":"Sheet 9","linkFileType":{"id":1,"text":"pdf"},"description":"Sheet 9","linkHelpText":"Local (Offshore of Bodega Head Map Area) and Regional (Offshore from Salt Point to Drakes Bay) Shallow-Subsurface Geology and Structure, California By Samuel Y. Johnson, Stephen R. Hartwell, Janet T. Watt, and Ray W. Sliter"},{"id":306394,"rank":9,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2015/1140/ofr20151140_sheet8.pdf","text":"Sheet 8","linkFileType":{"id":1,"text":"pdf"},"description":"Sheet 8","linkHelpText":"Seismic-Reflection Profiles, Offshore of Bodega Head Map Area, California by Samuel Y. Johnson, Ray W. Sliter, Stephen R. Hartwell, and John L. Chin"},{"id":306389,"rank":4,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2015/1140/ofr20151140_sheet3.pdf","text":"Sheet 3","linkFileType":{"id":1,"text":"pdf"},"description":"Sheet 3","linkHelpText":"Acoustic Backscatter, Offshore of Bodega Head Map Area, California By Peter Dartnell, Mercedes D. Erdey, and Rikk G. 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Kvitek"},{"id":306386,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1140/ofr20151140_pamphlet.pdf","text":"Pamphlet","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1140 Pamphlet"},{"id":306393,"rank":8,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2015/1140/ofr20151140_sheet7.pdf","text":"Sheet 7","linkFileType":{"id":1,"text":"pdf"},"description":"Sheet 7","linkHelpText":"Potential Marine Benthic Habitats, Offshore of Bodega Head Map Area, California By Bryan E. Dieter, H. Gary Greene, Charles A. Endris, and Erik N . Lowe"},{"id":306392,"rank":7,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2015/1140/ofr20151140_sheet6.pdf","text":"Sheet 6","linkFileType":{"id":1,"text":"pdf"},"description":"Sheet 6","linkHelpText":"Ground-Truth Studies, Offshore of Bodega Head Map Area, California By Nadine E. Golden, Guy R. Cochrane, and Lisa M. Krigsman"},{"id":306391,"rank":6,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2015/1140/ofr20151140_sheet5.pdf","text":"Sheet 5","linkFileType":{"id":1,"text":"pdf"},"description":"Sheet 5","linkHelpText":"Seafloor Character, Offshore of Bodega Head Map Area, California By Mercedes D. Erdey and Guy R. Cochrane"},{"id":306390,"rank":5,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2015/1140/ofr20151140_sheet4.pdf","text":"Sheet 4","linkFileType":{"id":1,"text":"pdf"},"description":"Sheet 4","linkHelpText":"Data Integration and Visualization, Offshore of Bodega Head Map Area, California By Peter Dartnell"}],"country":"United States","state":"California","otherGeospatial":"Bodega Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.1719,\n 38.2611\n ],\n [\n -123.1719,\n 38.4122\n ],\n [\n -122.9703,\n 38.4122\n ],\n [\n -122.9703,\n 38.2611\n ],\n [\n -123.1719,\n 38.2611\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contact Information
Pacific Coastal & Marine Science Center
U.S. Geological Survey
Pacific Science Center
2885 Mission St.
Santa Cruz, CA 95060
http://walrus.wr.usgs.gov/