The need for sustainable management of fresh water resources is one of the great challenges of the 21st century. Since most of the planet's liquid fresh water exists as groundwater, it is essential to develop non-invasive geophysical techniques to characterize groundwater aquifers. A field experiment was conducted in the High Plains Aquifer, central United States, to explore the mechanisms governing the non-invasive Surface NMR (SNMR) technology. We acquired both SNMR data and logging NMR data at a field site, along with lithology information from drill cuttings. This allowed us to directly compare the NMR relaxation parameter measured during logging,T2, to the relaxation parameter T2* measured using the SNMR method. The latter can be affected by inhomogeneity in the magnetic field, thus obscuring the link between the NMR relaxation parameter and the hydraulic conductivity of the geologic material. When the logging T2data were transformed to pseudo-T2* data, by accounting for inhomogeneity in the magnetic field and instrument dead time, we found good agreement with T2* obtained from the SNMR measurement. These results, combined with the additional information about lithology at the site, allowed us to delineate the physical mechanisms governing the SNMR measurement. Such understanding is a critical step in developing SNMR as a reliable geophysical method for the assessment of groundwater resources.
","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Geophysical Research Letters","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.1029/2011GL050167","issn":"00948276","usgsCitation":"Knight, R., Grunewald, E., Irons, T., Dlubac, K., Song, Y., Bachman, H., Grau, B., Walsh, D., Abraham, J., and Cannia, J., 2012, Field experiment provides ground truth for surface nuclear magnetic resonance measurement: Geophysical Research Letters, v. 39, no. 3, p. 1-7, https://doi.org/10.1029/2011GL050167.","productDescription":"7 p. ","startPage":"1","endPage":"7","ipdsId":"IP-030935","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":241491,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":213830,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1029/2011GL050167"}],"volume":"39","issue":"3","noUsgsAuthors":false,"publicationDate":"2012-02-04","publicationStatus":"PW","scienceBaseUri":"505a0fb7e4b0c8380cd539bb","contributors":{"authors":[{"text":"Knight, R.","contributorId":22717,"corporation":false,"usgs":true,"family":"Knight","given":"R.","affiliations":[],"preferred":false,"id":437477,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grunewald, E.","contributorId":62820,"corporation":false,"usgs":true,"family":"Grunewald","given":"E.","email":"","affiliations":[],"preferred":false,"id":437478,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Irons, T.","contributorId":95698,"corporation":false,"usgs":true,"family":"Irons","given":"T.","email":"","affiliations":[],"preferred":false,"id":437482,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dlubac, K.","contributorId":70607,"corporation":false,"usgs":true,"family":"Dlubac","given":"K.","affiliations":[],"preferred":false,"id":437480,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Song, Y.","contributorId":92443,"corporation":false,"usgs":true,"family":"Song","given":"Y.","email":"","affiliations":[],"preferred":false,"id":437481,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bachman, H.N.","contributorId":106324,"corporation":false,"usgs":true,"family":"Bachman","given":"H.N.","email":"","affiliations":[],"preferred":false,"id":437483,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Grau, B.","contributorId":70197,"corporation":false,"usgs":true,"family":"Grau","given":"B.","email":"","affiliations":[],"preferred":false,"id":437479,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Walsh, D.","contributorId":7920,"corporation":false,"usgs":true,"family":"Walsh","given":"D.","affiliations":[],"preferred":false,"id":437474,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Abraham, J.D.","contributorId":20686,"corporation":false,"usgs":true,"family":"Abraham","given":"J.D.","email":"","affiliations":[],"preferred":false,"id":437475,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Cannia, J.","contributorId":21358,"corporation":false,"usgs":true,"family":"Cannia","given":"J.","affiliations":[],"preferred":false,"id":437476,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70032386,"text":"70032386 - 2012 - Application of a weighted-averaging method for determining paleosalinity: a tool for restoration of south Florida's estuaries","interactions":[],"lastModifiedDate":"2013-04-08T22:28:07","indexId":"70032386","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1584,"text":"Estuaries and Coasts","active":true,"publicationSubtype":{"id":10}},"title":"Application of a weighted-averaging method for determining paleosalinity: a tool for restoration of south Florida's estuaries","docAbstract":"A molluscan analogue dataset is presented in conjunction with a weighted-averaging technique as a tool for estimating past salinity patterns in south Florida’s estuaries and developing targets for restoration based on these reconstructions. The method, here referred to as cumulative weighted percent (CWP), was tested using modern surficial samples collected in Florida Bay from sites located near fixed water monitoring stations that record salinity. The results were calibrated using species weighting factors derived from examining species occurrence patterns. A comparison of the resulting calibrated species-weighted CWP (SW-CWP) to the observed salinity at the water monitoring stations averaged over a 3-year time period indicates, on average, the SW-CWP comes within less than two salinity units of estimating the observed salinity. The SW-CWP reconstructions were conducted on a core from near the mouth of Taylor Slough to illustrate the application of the method.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Estuaries and Coasts","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","publisherLocation":"Amsterdam, Netherlands","doi":"10.1007/s12237-011-9441-3","issn":"15592723","usgsCitation":"Wingard, G., and Hudley, J., 2012, Application of a weighted-averaging method for determining paleosalinity: a tool for restoration of south Florida's estuaries: Estuaries and Coasts, v. 35, no. 1, p. 262-280, https://doi.org/10.1007/s12237-011-9441-3.","productDescription":"19 p.","startPage":"262","endPage":"280","costCenters":[{"id":563,"text":"South Florida Information Access","active":false,"usgs":true}],"links":[{"id":213780,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s12237-011-9441-3"},{"id":241438,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -87.63,24.52 ], [ -87.63,31.0 ], [ -80.0,31.0 ], [ -80.0,24.52 ], [ -87.63,24.52 ] ] ] } } ] }","volume":"35","issue":"1","noUsgsAuthors":false,"publicationDate":"2011-09-13","publicationStatus":"PW","scienceBaseUri":"5059ec8be4b0c8380cd49325","contributors":{"authors":[{"text":"Wingard, G.L.","contributorId":79981,"corporation":false,"usgs":true,"family":"Wingard","given":"G.L.","email":"","affiliations":[],"preferred":false,"id":435911,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hudley, J.W.","contributorId":18872,"corporation":false,"usgs":true,"family":"Hudley","given":"J.W.","affiliations":[],"preferred":false,"id":435910,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70035521,"text":"70035521 - 2012 - Using multitemporal remote sensing imagery and inundation measures to improve land change estimates in coastal wetlands","interactions":[],"lastModifiedDate":"2020-11-17T12:57:50.879427","indexId":"70035521","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1584,"text":"Estuaries and Coasts","active":true,"publicationSubtype":{"id":10}},"title":"Using multitemporal remote sensing imagery and inundation measures to improve land change estimates in coastal wetlands","docAbstract":"Remote sensing imagery can be an invaluable resource to quantify land change in coastal wetlands. Obtaining an accurate measure of land change can, however, be complicated by differences in fluvial and tidal inundation experienced when the imagery is captured. This study classified Landsat imagery from two wetland areas in coastal Louisiana from 1983 to 2010 into categories of land and water. Tide height, river level, and date were used as independent variables in a multiple regression model to predict land area in the Wax Lake Delta (WLD) and compare those estimates with an adjacent marsh area lacking direct fluvial inputs. Coefficients of determination from regressions using both measures of water level along with date as predictor variables of land extent in the WLD, were higher than those obtained using the current methodology which only uses date to predict land change. Land change trend estimates were also improved when the data were divided by time period. Water level corrected land gain in the WLD from 1983 to 2010 was 1 km2 year−1, while rates in the adjacent marsh remained roughly constant. This approach of isolating environmental variability due to changing water levels improves estimates of actual land change in a dynamic system, so that other processes that may control delta development such as hurricanes, floods, and sediment delivery, may be further investigated.
","language":"English","publisher":"Springer","doi":"10.1007/s12237-011-9437-z","issn":"15592723","usgsCitation":"Allen, Y., Couvillion, B., and Barras, J., 2012, Using multitemporal remote sensing imagery and inundation measures to improve land change estimates in coastal wetlands: Estuaries and Coasts, v. 35, no. 1, p. 190-200, https://doi.org/10.1007/s12237-011-9437-z.","productDescription":"11 p.","startPage":"190","endPage":"200","costCenters":[],"links":[{"id":243907,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Lousianna","otherGeospatial":"Atchafalaya Deltas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.6314697265625,\n 29.703560887190708\n ],\n [\n -91.65481567382812,\n 29.543593066460595\n ],\n [\n -91.51199340820312,\n 29.30077105450428\n ],\n [\n -91.30462646484375,\n 29.31154884819602\n ],\n [\n -91.14257812499999,\n 29.433617570990965\n ],\n [\n -91.6314697265625,\n 29.703560887190708\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"35","issue":"1","noUsgsAuthors":false,"publicationDate":"2011-09-02","publicationStatus":"PW","scienceBaseUri":"505bc019e4b08c986b329f1d","contributors":{"authors":[{"text":"Allen, Y.C.","contributorId":63761,"corporation":false,"usgs":true,"family":"Allen","given":"Y.C.","email":"","affiliations":[],"preferred":false,"id":451066,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Couvillion, B.R. 0000-0001-5323-1687","orcid":"https://orcid.org/0000-0001-5323-1687","contributorId":26540,"corporation":false,"usgs":true,"family":"Couvillion","given":"B.R.","affiliations":[],"preferred":false,"id":451064,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barras, J.A.","contributorId":44260,"corporation":false,"usgs":true,"family":"Barras","given":"J.A.","email":"","affiliations":[],"preferred":false,"id":451065,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70032250,"text":"70032250 - 2012 - Geostatistical modeling of the gas emission zone and its in-place gas content for Pittsburgh-seam mines using sequential Gaussian simulation","interactions":[],"lastModifiedDate":"2018-09-21T12:39:12","indexId":"70032250","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2033,"text":"International Journal of Coal Geology","active":true,"publicationSubtype":{"id":10}},"title":"Geostatistical modeling of the gas emission zone and its in-place gas content for Pittsburgh-seam mines using sequential Gaussian simulation","docAbstract":"Determination of the size of the gas emission zone, the locations of gas sources within, and especially the amount of gas retained in those zones is one of the most important steps for designing a successful methane control strategy and an efficient ventilation system in longwall coal mining. The formation of the gas emission zone and the potential amount of gas-in-place (GIP) that might be available for migration into a mine are factors of local geology and rock properties that usually show spatial variability in continuity and may also show geometric anisotropy. Geostatistical methods are used here for modeling and prediction of gas amounts and for assessing their associated uncertainty in gas emission zones of longwall mines for methane control.
This study used core data obtained from 276 vertical exploration boreholes drilled from the surface to the bottom of the Pittsburgh coal seam in a mining district in the Northern Appalachian basin. After identifying important coal and non-coal layers for the gas emission zone, univariate statistical and semivariogram analyses were conducted for data from different formations to define the distribution and continuity of various attributes. Sequential simulations performed stochastic assessment of these attributes, such as gas content, strata thickness, and strata displacement. These analyses were followed by calculations of gas-in-place and their uncertainties in the Pittsburgh seam caved zone and fractured zone of longwall mines in this mining district. Grid blanking was used to isolate the volume over the actual panels from the entire modeled district and to calculate gas amounts that were directly related to the emissions in longwall mines.
Results indicated that gas-in-place in the Pittsburgh seam, in the caved zone and in the fractured zone, as well as displacements in major rock units, showed spatial correlations that could be modeled and estimated using geostatistical methods. This study showed that GIP volumes may change up to 3 MMscf per acre and, in a multi-panel district, may total 9 Bcf of methane within the gas emission zone. Therefore, ventilation and gas capture systems should be designed accordingly. In addition, rock displacements within the gas emission zone are spatially distributed. From an engineering and practical point of view, spatial distributions of GIP and distributions of rock displacements should be correlated with in-mine emissions and gob gas venthole productions.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.coal.2011.10.010","issn":"01665162","usgsCitation":"Karacan, C.O., Olea, R., and Goodman, G., 2012, Geostatistical modeling of the gas emission zone and its in-place gas content for Pittsburgh-seam mines using sequential Gaussian simulation: International Journal of Coal Geology, v. 90-91, p. 50-71, https://doi.org/10.1016/j.coal.2011.10.010.","productDescription":"22 p.","startPage":"50","endPage":"71","ipdsId":"IP-031033","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":474676,"rank":10000,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/4589251","text":"External Repository"},{"id":242409,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":214664,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.coal.2011.10.010"}],"volume":"90-91","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a28b3e4b0c8380cd5a320","contributors":{"authors":[{"text":"Karacan, Cevat O. 0000-0002-0947-8241","orcid":"https://orcid.org/0000-0002-0947-8241","contributorId":67742,"corporation":false,"usgs":true,"family":"Karacan","given":"Cevat","email":"","middleInitial":"O.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":435243,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Olea, Ricardo A. 0000-0003-4308-0808","orcid":"https://orcid.org/0000-0003-4308-0808","contributorId":26436,"corporation":false,"usgs":true,"family":"Olea","given":"Ricardo A.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":435241,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Goodman, G.","contributorId":29233,"corporation":false,"usgs":true,"family":"Goodman","given":"G.","email":"","affiliations":[],"preferred":false,"id":435242,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70032630,"text":"70032630 - 2012 - Landscape controls on the timing of spring, autumn, and growing season length in mid-Atlantic forests","interactions":[],"lastModifiedDate":"2013-06-20T10:22:30","indexId":"70032630","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"Landscape controls on the timing of spring, autumn, and growing season length in mid-Atlantic forests","docAbstract":"The timing of spring leaf development, trajectories of summer leaf area, and the timing of autumn senescence have profound impacts to the water, carbon, and energy balance of ecosystems, and are likely influenced by global climate change. Limited field-based and remote-sensing observations have suggested complex spatial patterns related to geographic features that influence climate. However, much of this variability occurs at spatial scales that inhibit a detailed understanding of even the dominant drivers. Recognizing these limitations, we used nonlinear inverse modeling of medium-resolution remote sensing data, organized by day of year, to explore the influence of climate-related landscape factors on the timing of spring and autumn leaf-area trajectories in mid-Atlantic, USA forests. We also examined the extent to which declining summer greenness (greendown) degrades the precision and accuracy of observations of autumn offset of greenness. Of the dominant drivers of landscape phenology, elevation was the strongest, explaining up to 70% of the spatial variation in the onset of greenness. Urban land cover was second in importance, influencing spring onset and autumn offset to a distance of 32 km from large cities. Distance to tidal water also influenced phenological timing, but only within ~5 km of shorelines. Additionally, we observed that (i) growing season length unexpectedly increases with increasing elevation at elevations below 275 m; (ii) along gradients in urban land cover, timing of autumn offset has a stronger effect on growing season length than does timing of spring onset; and (iii) summer greendown introduces bias and uncertainty into observations of the autumn offset of greenness. These results demonstrate the power of medium grain analyses of landscape-scale phenology for understanding environmental controls on growing season length, and predicting how these might be affected by climate change.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Global Change Biology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1111/j.1365-2486.2011.02521.x","issn":"13541013","usgsCitation":"Elmore, A., Guinn, S., Minsley, B., and Richardson, A., 2012, Landscape controls on the timing of spring, autumn, and growing season length in mid-Atlantic forests: Global Change Biology, v. 18, no. 2, p. 656-674, https://doi.org/10.1111/j.1365-2486.2011.02521.x.","productDescription":"19 p.","startPage":"656","endPage":"674","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":241560,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":213892,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/j.1365-2486.2011.02521.x"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.8,24.5 ], [ -124.8,49.383333 ], [ -66.95,49.383333 ], [ -66.95,24.5 ], [ -124.8,24.5 ] ] ] } } ] }","volume":"18","issue":"2","noUsgsAuthors":false,"publicationDate":"2011-09-19","publicationStatus":"PW","scienceBaseUri":"505a4408e4b0c8380cd667c5","contributors":{"authors":[{"text":"Elmore, A.J.","contributorId":103095,"corporation":false,"usgs":true,"family":"Elmore","given":"A.J.","email":"","affiliations":[],"preferred":false,"id":437138,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Guinn, S.M.","contributorId":35552,"corporation":false,"usgs":true,"family":"Guinn","given":"S.M.","email":"","affiliations":[],"preferred":false,"id":437136,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Minsley, B. J.","contributorId":52107,"corporation":false,"usgs":true,"family":"Minsley","given":"B. J.","affiliations":[],"preferred":false,"id":437137,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Richardson, A.D.","contributorId":10629,"corporation":false,"usgs":true,"family":"Richardson","given":"A.D.","email":"","affiliations":[],"preferred":false,"id":437135,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70032283,"text":"70032283 - 2012 - The impact of biotic/abiotic interfaces in mineral nutrient cycling: A study of soils of the Santa Cruz chronosequence, California","interactions":[],"lastModifiedDate":"2020-12-03T17:49:49.83412","indexId":"70032283","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","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":"The impact of biotic/abiotic interfaces in mineral nutrient cycling: A study of soils of the Santa Cruz chronosequence, California","docAbstract":"Biotic/abiotic interactions between soil mineral nutrients and annual grassland vegetation are characterized for five soils in a marine terrace chronosequence near Santa Cruz, California. A Mediterranean climate, with wet winters and dry summers, controls the annual cycle of plant growth and litter decomposition, resulting in net above-ground productivities of 280–600 g m−2 yr−1. The biotic/abiotic (A/B) interface separates seasonally reversible nutrient gradients, reflecting biological cycling in the shallower soils, from downward chemical weathering gradients in the deeper soils. The A/B interface is pedologically defined by argillic clay horizons centered at soil depths of about one meter which intensify with soil age. Below these horizons, elevated solute Na/Ca, Mg/Ca and Sr/Ca ratios reflect plagioclase and smectite weathering along pore water flow paths. Above the A/B interface, lower cation ratios denote temporal variability due to seasonal plant nutrient uptake and litter leaching. Potassium and Ca exhibit no seasonal variability beneath the A/B interface, indicating closed nutrient cycling within the root zone, whereas Mg variability below the A/B interface denotes downward leakage resulting from higher inputs of marine aerosols and lower plant nutrient requirements.
The fraction of a mineral nutrient annually cycled through the plants, compared to that lost from pore water discharge, is defined their respective fluxes Fj,plants = qj,plants/(qj,plants + qj,discharge) with average values for K and Ca (FK,plants = 0.99; FCa,plants = 0.93) much higher than for Mg and Na (FMg,plants 0.64; FNa,plants = 0.28). The discrimination against Rb and Sr by plants is described by fractionation factors (KSr/Ca = 0.86; KRb/K = 0.83) which are used in Rayleigh fractionation-mixing calculations to fit seasonal patterns in solute K and Ca cycling. KRb/K and
The application of quantitative real-time PCR (qPCR) technologies for the rapid identification of fecal bacteria in environmental waters is being considered for use as a national water quality metric in the United States. The transition from research tool to a standardized protocol requires information on the reproducibility and sources of variation associated with qPCR methodology across laboratories. This study examines interlaboratory variability in the measurement of enterococci and Bacteroidales concentrations from standardized, spiked, and environmental sources of DNA using the Entero1a and GenBac3 qPCR methods, respectively. Comparisons are based on data generated from eight different research facilities. Special attention was placed on the influence of the DNA isolation step and effect of simplex and multiplex amplification approaches on interlaboratory variability. Results suggest that a crude lysate is sufficient for DNA isolation unless environmental samples contain substances that can inhibit qPCR amplification. No appreciable difference was observed between simplex and multiplex amplification approaches. Overall, interlaboratory variability levels remained low (<10% coefficient of variation) regardless of qPCR protocol.
","language":"English","publisher":"American Chemical Society","doi":"10.1021/es2031455","issn":"0013936X","usgsCitation":"Shanks, O., Sivaganesan, M., Peed, L., Kelty, C., Blackwood, A., Greene, M., Noble, R., Bushon, R.N., Stelzer, E.A., Kinzelman, J., Anan'Eva, T., Sinigalliano, C., Wanless, D., Griffith, J., Cao, Y., Weisberg, S., Harwood, V., Staley, C., Oshima, K., Varma, M., and Haugland, R., 2012, Interlaboratory comparison of real-time pcr protocols for quantification of general fecal indicator bacteria: Environmental Science & Technology, v. 46, no. 2, p. 945-953, https://doi.org/10.1021/es2031455.","productDescription":"9 p.","startPage":"945","endPage":"953","costCenters":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"links":[{"id":242414,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":214668,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1021/es2031455"}],"volume":"46","issue":"2","noUsgsAuthors":false,"publicationDate":"2011-12-16","publicationStatus":"PW","scienceBaseUri":"505a3d24e4b0c8380cd63322","contributors":{"authors":[{"text":"Shanks, O.C.","contributorId":11076,"corporation":false,"usgs":true,"family":"Shanks","given":"O.C.","email":"","affiliations":[],"preferred":false,"id":435544,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sivaganesan, M.","contributorId":83805,"corporation":false,"usgs":true,"family":"Sivaganesan","given":"M.","affiliations":[],"preferred":false,"id":435560,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Peed, L.","contributorId":82192,"corporation":false,"usgs":true,"family":"Peed","given":"L.","affiliations":[],"preferred":false,"id":435559,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kelty, C.A.","contributorId":40091,"corporation":false,"usgs":true,"family":"Kelty","given":"C.A.","email":"","affiliations":[],"preferred":false,"id":435550,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Blackwood, A.D.","contributorId":43237,"corporation":false,"usgs":true,"family":"Blackwood","given":"A.D.","email":"","affiliations":[],"preferred":false,"id":435551,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Greene, M.R.","contributorId":96723,"corporation":false,"usgs":true,"family":"Greene","given":"M.R.","email":"","affiliations":[],"preferred":false,"id":435562,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Noble, R.T.","contributorId":60452,"corporation":false,"usgs":true,"family":"Noble","given":"R.T.","email":"","affiliations":[],"preferred":false,"id":435556,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Bushon, Rebecca N. rnbushon@usgs.gov","contributorId":2304,"corporation":false,"usgs":true,"family":"Bushon","given":"Rebecca","email":"rnbushon@usgs.gov","middleInitial":"N.","affiliations":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"preferred":true,"id":435557,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Stelzer, Erin A. 0000-0001-7645-7603 eastelzer@usgs.gov","orcid":"https://orcid.org/0000-0001-7645-7603","contributorId":1933,"corporation":false,"usgs":true,"family":"Stelzer","given":"Erin","email":"eastelzer@usgs.gov","middleInitial":"A.","affiliations":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":435554,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Kinzelman, J.","contributorId":43584,"corporation":false,"usgs":true,"family":"Kinzelman","given":"J.","affiliations":[],"preferred":false,"id":435552,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Anan'Eva, T.","contributorId":33993,"corporation":false,"usgs":true,"family":"Anan'Eva","given":"T.","affiliations":[],"preferred":false,"id":435549,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Sinigalliano, C.","contributorId":31270,"corporation":false,"usgs":true,"family":"Sinigalliano","given":"C.","email":"","affiliations":[],"preferred":false,"id":435548,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Wanless, D.","contributorId":48836,"corporation":false,"usgs":true,"family":"Wanless","given":"D.","email":"","affiliations":[],"preferred":false,"id":435553,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Griffith, J.","contributorId":6686,"corporation":false,"usgs":true,"family":"Griffith","given":"J.","affiliations":[],"preferred":false,"id":435543,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Cao, Y.","contributorId":29991,"corporation":false,"usgs":true,"family":"Cao","given":"Y.","email":"","affiliations":[],"preferred":false,"id":435547,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Weisberg, S.","contributorId":99775,"corporation":false,"usgs":true,"family":"Weisberg","given":"S.","email":"","affiliations":[],"preferred":false,"id":435563,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Harwood, V.J.","contributorId":58528,"corporation":false,"usgs":true,"family":"Harwood","given":"V.J.","email":"","affiliations":[],"preferred":false,"id":435555,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Staley, C.","contributorId":11077,"corporation":false,"usgs":true,"family":"Staley","given":"C.","email":"","affiliations":[],"preferred":false,"id":435545,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Oshima, K.H.","contributorId":96165,"corporation":false,"usgs":true,"family":"Oshima","given":"K.H.","email":"","affiliations":[],"preferred":false,"id":435561,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Varma, M.","contributorId":26588,"corporation":false,"usgs":true,"family":"Varma","given":"M.","email":"","affiliations":[],"preferred":false,"id":435546,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Haugland, R.A.","contributorId":77010,"corporation":false,"usgs":true,"family":"Haugland","given":"R.A.","affiliations":[],"preferred":false,"id":435558,"contributorType":{"id":1,"text":"Authors"},"rank":21}]}} ,{"id":70032658,"text":"70032658 - 2012 - Verifiable metamodels for nitrate losses to drains and groundwater in the Corn Belt, USA","interactions":[],"lastModifiedDate":"2017-11-21T15:18:55","indexId":"70032658","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Verifiable metamodels for nitrate losses to drains and groundwater in the Corn Belt, USA","docAbstract":"Nitrate leaching in the unsaturated zone poses a risk to groundwater, whereas nitrate in tile drainage is conveyed directly to streams. We developed metamodels (MMs) consisting of artificial neural networks to simplify and upscale mechanistic fate and transport models for prediction of nitrate losses by drains and leaching in the Corn Belt, USA. The two final MMs predicted nitrate concentration and flux, respectively, in the shallow subsurface. Because each MM considered both tile drainage and leaching, they represent an integrated approach to vulnerability assessment. The MMs used readily available data comprising farm fertilizer nitrogen (N), weather data, and soil properties as inputs; therefore, they were well suited for regional extrapolation. The MMs effectively related the outputs of the underlying mechanistic model (Root Zone Water Quality Model) to the inputs (R2 = 0.986 for the nitrate concentration MM). Predicted nitrate concentration was compared with measured nitrate in 38 samples of recently recharged groundwater, yielding a Pearson’s r of 0.466 (p = 0.003). Predicted nitrate generally was higher than that measured in groundwater, possibly as a result of the time-lag for modern recharge to reach well screens, denitrification in groundwater, or interception of recharge by tile drains. In a qualitative comparison, predicted nitrate concentration also compared favorably with results from a previous regression model that predicted total N in streams.
","language":"English","publisher":"ACS","doi":"10.1021/es202875e","issn":"0013936X","usgsCitation":"Nolan, B.T., Malone, R.W., Gronberg, J., Thorp, K., and Ma, L., 2012, Verifiable metamodels for nitrate losses to drains and groundwater in the Corn Belt, USA: Environmental Science & Technology, v. 46, no. 2, p. 901-908, https://doi.org/10.1021/es202875e.","productDescription":"8 p.","startPage":"901","endPage":"908","numberOfPages":"8","ipdsId":"IP-031037","costCenters":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"links":[{"id":241524,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":213859,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1021/es202875e"}],"volume":"46","issue":"2","noUsgsAuthors":false,"publicationDate":"2011-12-22","publicationStatus":"PW","scienceBaseUri":"505bc218e4b08c986b32a905","contributors":{"authors":[{"text":"Nolan, Bernard T. 0000-0002-6945-9659 btnolan@usgs.gov","orcid":"https://orcid.org/0000-0002-6945-9659","contributorId":2190,"corporation":false,"usgs":true,"family":"Nolan","given":"Bernard","email":"btnolan@usgs.gov","middleInitial":"T.","affiliations":[{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":437321,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Malone, Robert W.","contributorId":10347,"corporation":false,"usgs":false,"family":"Malone","given":"Robert","email":"","middleInitial":"W.","affiliations":[{"id":6622,"text":"US Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":437325,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gronberg, Jo Ann M.","contributorId":18342,"corporation":false,"usgs":true,"family":"Gronberg","given":"Jo Ann M.","affiliations":[],"preferred":false,"id":437324,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thorp, K.R.","contributorId":38370,"corporation":false,"usgs":true,"family":"Thorp","given":"K.R.","email":"","affiliations":[],"preferred":false,"id":437323,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ma, Liwang","contributorId":29140,"corporation":false,"usgs":true,"family":"Ma","given":"Liwang","email":"","affiliations":[],"preferred":false,"id":437322,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70032661,"text":"70032661 - 2012 - Climatic forcing of Quaternary deep-sea benthic communities in the North Pacific Ocean","interactions":[],"lastModifiedDate":"2013-04-21T16:54:18","indexId":"70032661","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3001,"text":"Paleobiology","active":true,"publicationSubtype":{"id":10}},"title":"Climatic forcing of Quaternary deep-sea benthic communities in the North Pacific Ocean","docAbstract":"There is growing evidence that changes in deep-sea benthic ecosystems are modulated by climate changes, but most evidence to date comes from the North Atlantic Ocean. Here we analyze new ostracod and published foraminiferal records for the last 250,000 years on Shatsky Rise in the North Pacific Ocean. Using linear models, we evaluate statistically the ability of environmental drivers (temperature, productivity, and seasonality of productivity) to predict changes in faunal diversity, abundance, and composition. These microfossil data show glacial-interglacial shifts in overall abundances and species diversities that are low during glacial intervals and high during interglacials. These patterns replicate those previously documented in the North Atlantic Ocean, suggesting that the climatic forcing of the deep-sea ecosystem is widespread, and possibly global in nature. However, these results also reveal differences with prior studies that probably reflect the isolated nature of Shatsky Rise as a remote oceanic plateau. Ostracod assemblages on Shatsky Rise are highly endemic but of low diversity, consistent with the limited dispersal potential of these animals. Benthic foraminifera, by contrast, have much greater dispersal ability and their assemblages at Shatsky Rise show diversities typical for deep-sea faunas in other regions. Statistical analyses also reveal ostracod-foraminferal differences in relationships between environmental drivers and biotic change. Rarefied diversity is best explained as a hump-shaped function of surface productivity in ostracods, but as having a weak and positive relationship with temperature in foraminifera. Abundance shows a positive relationship with both productivity and seasonality of productivity in foraminifera, and a hump-shaped relationship with productivity in ostracods. Finally, species composition in ostracods is influenced by both temperature and productivity, but only a temperature effect is evident in foraminifera. Though complex in detail, the global-scale link between deep-sea ecosystems and Quaternary climate changes underscores the importance of the interaction between the physical and biological components of paleoceanographical research for better understanding the history of the biosphere.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Paleobiology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"The Paleontological Society","publisherLocation":"http://www.paleosoc.org/","doi":"10.1666/10068.1","issn":"00948373","usgsCitation":"Yasuhara, M., Hunt, G., Cronin, T.M., Hokanishi, N., Kawahata, H., Tsujimoto, A., and Ishitake, M., 2012, Climatic forcing of Quaternary deep-sea benthic communities in the North Pacific Ocean: Paleobiology, v. 38, no. 1, p. 162-179, https://doi.org/10.1666/10068.1.","productDescription":"18 p.","startPage":"162","endPage":"179","costCenters":[],"links":[{"id":213894,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1666/10068.1"},{"id":241562,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Pacific Ocean","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 128.7,-85.6 ], [ 128.7,58.2 ], [ -66.5,58.2 ], [ -66.5,-85.6 ], [ 128.7,-85.6 ] ] ] } } ] }","volume":"38","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059f666e4b0c8380cd4c737","contributors":{"authors":[{"text":"Yasuhara, Moriaki","contributorId":37935,"corporation":false,"usgs":true,"family":"Yasuhara","given":"Moriaki","affiliations":[],"preferred":false,"id":437332,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hunt, G.","contributorId":97699,"corporation":false,"usgs":true,"family":"Hunt","given":"G.","email":"","affiliations":[],"preferred":false,"id":437337,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cronin, T. M. 0000-0002-2643-0979","orcid":"https://orcid.org/0000-0002-2643-0979","contributorId":42613,"corporation":false,"usgs":true,"family":"Cronin","given":"T.","email":"","middleInitial":"M.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":false,"id":437333,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hokanishi, N.","contributorId":34331,"corporation":false,"usgs":true,"family":"Hokanishi","given":"N.","email":"","affiliations":[],"preferred":false,"id":437331,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kawahata, H.","contributorId":90549,"corporation":false,"usgs":true,"family":"Kawahata","given":"H.","email":"","affiliations":[],"preferred":false,"id":437336,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Tsujimoto, Akira","contributorId":58448,"corporation":false,"usgs":true,"family":"Tsujimoto","given":"Akira","email":"","affiliations":[],"preferred":false,"id":437335,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ishitake, M.","contributorId":47988,"corporation":false,"usgs":true,"family":"Ishitake","given":"M.","email":"","affiliations":[],"preferred":false,"id":437334,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70035492,"text":"70035492 - 2012 - An approach to regional wetland digital elevation model development using a differential global positioning system and a custom-built helicopter-based surveying system","interactions":[],"lastModifiedDate":"2020-11-23T16:39:21.889556","indexId":"70035492","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2068,"text":"International Journal of Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"An approach to regional wetland digital elevation model development using a differential global positioning system and a custom-built helicopter-based surveying system","docAbstract":"Accurate topographic data are critical to restoration science and planning for the Everglades region of South Florida, USA. They are needed to monitor and simulate water level, water depth and hydroperiod and are used in scientific research on hydrologic and biologic processes. Because large wetland environments and data acquisition challenge conventional ground-based and remotely sensed data collection methods, the United States Geological Survey (USGS) adapted a classical data collection instrument to global positioning system (GPS) and geographic information system (GIS) technologies. Data acquired with this instrument were processed using geostatistics to yield sub-water level elevation values with centimetre accuracy (±15 cm). The developed database framework, modelling philosophy and metadata protocol allow for continued, collaborative model revision and expansion, given additional elevation or other ancillary data.
","language":"English","publisher":"Taylor & Francis Online","doi":"10.1080/01431161.2010.533212","issn":"01431161","usgsCitation":"Jones, J.W., Desmond, G., Henkle, C., and Glover, R., 2012, An approach to regional wetland digital elevation model development using a differential global positioning system and a custom-built helicopter-based surveying system: International Journal of Remote Sensing, v. 33, no. 2, p. 450-465, https://doi.org/10.1080/01431161.2010.533212.","productDescription":"16 p.","startPage":"450","endPage":"465","costCenters":[],"links":[{"id":242952,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":215170,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1080/01431161.2010.533212"}],"country":"United States","state":"Florida","otherGeospatial":"Everglades National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.14501953125,\n 25.105497373014686\n ],\n [\n -80.22216796875,\n 25.145284610685064\n ],\n [\n -79.8486328125,\n 25.898761936567023\n ],\n [\n -79.9365234375,\n 26.33280692289788\n ],\n [\n -82.0458984375,\n 26.33280692289788\n ],\n [\n -81.14501953125,\n 25.105497373014686\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"33","issue":"2","noUsgsAuthors":false,"publicationDate":"2011-10-28","publicationStatus":"PW","scienceBaseUri":"5059ea0ce4b0c8380cd485db","contributors":{"authors":[{"text":"Jones, J. W.","contributorId":89233,"corporation":false,"usgs":true,"family":"Jones","given":"J.","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":450891,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Desmond, G.B.","contributorId":35014,"corporation":false,"usgs":true,"family":"Desmond","given":"G.B.","email":"","affiliations":[],"preferred":false,"id":450890,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Henkle, C.","contributorId":91319,"corporation":false,"usgs":true,"family":"Henkle","given":"C.","email":"","affiliations":[],"preferred":false,"id":450892,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Glover, R.","contributorId":103106,"corporation":false,"usgs":true,"family":"Glover","given":"R.","email":"","affiliations":[],"preferred":false,"id":450893,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70032694,"text":"70032694 - 2012 - Incidence of adult brain cancers is higher in countries where the protozoan parasite Toxoplasma gondii is common","interactions":[],"lastModifiedDate":"2014-09-18T13:28:00","indexId":"70032694","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1028,"text":"Biology Letters","active":true,"publicationSubtype":{"id":10}},"title":"Incidence of adult brain cancers is higher in countries where the protozoan parasite Toxoplasma gondii is common","docAbstract":"We explored associations between the common protozoan parasite Toxoplasma gondii and brain cancers in human populations. We predicted that T. gondii could increase the risk of brain cancer because it is a long-lived parasite that encysts in the brain, where it provokes inflammation and inhibits apoptosis. We used a medical geography approach based on the national incidence of brain cancers and seroprevalence of T. gondii. We corrected reports of incidence for national gross domestic product because wealth probably increases the ability to detect cancer. We also included gender, cell phone use and latitude as variables in our initial models. Prevalence of T. gondii explained 19 per cent of the residual variance in brain cancer incidence after controlling for the positive effects of gross domestic product and latitude among nations. Infection with T. gondii was associated with a 1.8-fold increase in the risk of brain cancers across the range of T. gondii prevalence in our dataset (4–67%). These results, though correlational, suggest that T. gondii should be investigated further as a possible oncogenic pathogen of humans.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Biology Letters","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"The Royal Society","publisherLocation":"London","doi":"10.1098/rsbl.2011.0588","issn":"17449561","usgsCitation":"Thomas, F., Lafferty, K.D., Brodeur, J., Elguero, E., Gauthier-Clerc, M., and Misse, D., 2012, Incidence of adult brain cancers is higher in countries where the protozoan parasite Toxoplasma gondii is common: Biology Letters, v. 8, no. 1, p. 101-103, https://doi.org/10.1098/rsbl.2011.0588.","productDescription":"3 p.","startPage":"101","endPage":"103","numberOfPages":"3","costCenters":[],"links":[{"id":474734,"rank":10000,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1098/rsbl.2011.0588","text":"External Repository"},{"id":241527,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":213862,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1098/rsbl.2011.0588"}],"volume":"8","issue":"1","noUsgsAuthors":false,"publicationDate":"2011-07-27","publicationStatus":"PW","scienceBaseUri":"505a39d5e4b0c8380cd61a64","contributors":{"authors":[{"text":"Thomas, Frederic","contributorId":57275,"corporation":false,"usgs":true,"family":"Thomas","given":"Frederic","email":"","affiliations":[],"preferred":false,"id":437487,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lafferty, Kevin D. 0000-0001-7583-4593 klafferty@usgs.gov","orcid":"https://orcid.org/0000-0001-7583-4593","contributorId":1415,"corporation":false,"usgs":true,"family":"Lafferty","given":"Kevin","email":"klafferty@usgs.gov","middleInitial":"D.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":437484,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brodeur, Jacques","contributorId":47987,"corporation":false,"usgs":true,"family":"Brodeur","given":"Jacques","email":"","affiliations":[],"preferred":false,"id":437486,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Elguero, Eric","contributorId":80909,"corporation":false,"usgs":true,"family":"Elguero","given":"Eric","email":"","affiliations":[],"preferred":false,"id":437489,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gauthier-Clerc, Michel","contributorId":59639,"corporation":false,"usgs":true,"family":"Gauthier-Clerc","given":"Michel","email":"","affiliations":[],"preferred":false,"id":437488,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Misse, Dorothee","contributorId":29227,"corporation":false,"usgs":true,"family":"Misse","given":"Dorothee","email":"","affiliations":[],"preferred":false,"id":437485,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70032665,"text":"70032665 - 2012 - Occurrence and geochemistry of radium in water from principal drinking-water aquifer systems of the United States","interactions":[],"lastModifiedDate":"2019-09-25T10:51:13","indexId":"70032665","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":835,"text":"Applied Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Occurrence and geochemistry of radium in water from principal drinking-water aquifer systems of the United States","docAbstract":"A total of 1270 raw-water samples (before treatment) were collected from 15 principal and other major aquifer systems (PAs) used for drinking water in 45 states in all major physiographic provinces of the USA and analyzed for concentrations of the Ra isotopes 224Ra, 226Ra and 228Ra establishing the framework for evaluating Ra occurrence. The US Environmental Protection Agency Maximum Contaminant Level (MCL) of 0.185Bq/L (5pCi/L) for combined Ra ( 226Ra plus 228Ra) for drinking water was exceeded in 4.02% (39 of 971) of samples for which both 226Ra and 228Ra were determined, or in 3.15% (40 of 1266) of the samples in which at least one isotope concentration ( 226Ra or 228Ra) was determined. The maximum concentration of combined Ra was 0.755Bq/L (20.4pCi/L) in water from the North Atlantic Coastal Plain quartzose sand aquifer system. All the exceedences of the MCL for combined Ra occurred in water samples from the following 7PAs (in order of decreasing relative frequency of occurrence): the Midcontinent and Ozark Plateau Cambro-Ordovician dolomites and sandstones, the North Atlantic Coastal Plain, the Floridan, the crystalline rocks (granitic, metamorphic) of New England, the Mesozoic basins of the Appalachian Piedmont, the Gulf Coastal Plain, and the glacial sands and gravels (highest concentrations in New England).The concentration of Ra was consistently controlled by geochemical properties of the aquifer systems, with the highest concentrations most likely to be present where, as a consequence of the geochemical environment, adsorption of the Ra was slightly decreased. The result is a slight relative increase in Ra mobility, especially notable in aquifers with poor sorptive capacity (Fe-oxide-poor quartzose sands and carbonates), even if Ra is not abundant in the aquifer solids. The most common occurrence of elevated Ra throughout the USA occurred in anoxic water (low dissolved-O 2) with high concentrations of Fe or Mn, and in places, high concentrations of the competing ions Ca, Mg, Ba and Sr, and occasionally of dissolved solids, K, SO 4 and HCO 3. The other water type to frequently contain elevated concentrations of the Ra radioisotopes was acidic (low pH), and had in places, high concentrations of NO 3 and other acid anions, and on occasion, of the competing divalent cations, Mn and Al. One or the other of these broad water types was commonly present in each of the PAs in which elevated concentrations of combined Ra occurred. Concentrations of 226Ra or 228Ra or combined Ra correlated significantly with those of the above listed water-quality constituents (on the basis of the non-parametric Spearman correlation technique) and loaded on principal components describing the above water types from the entire data set and for samples from the PAs with the highest combined Ra concentrations.Concentrations of 224Ra and 226Ra were significantly correlated to those of 228Ra (Spearman's rank correlation coefficient, +0.236 and +0.326, respectively). Activity ratios of 224Ra/ 228Ra in the water samples were mostly near 1 when concentrations of both isotopes were greater than or equal to 0.037Bq/L (1pCi/L), the level above which analytical results were most reliable. Co-occurrence among these highest concentrations of the Ra radionuclides was most likely in those PAs where chemical conditions are most conducive to Ra mobility (e.g. acidic North Atlantic Coastal Plain). The concentrations of 224Ra were occasionally greater than 0.037Bq/L and the ratios of 224Ra/ 228Ra were generally highest in the PAs composed of alluvial sands and Cretaceous/Tertiary sandstones from the western USA, likely because concentrations of 224Ra are enhanced in solution relative to those of 228Ra by alpha recoil from the aquifer matrix. Rapid adsorption of the two Ra isotopes (controlled by the alkaline and oxic aquifer geochemistry) combined with preferential faster recoil of 224Ra generates a 224Ra/ 228Ra ratio much greater than ","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Applied Geochemistry","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.1016/j.apgeochem.2011.11.002","issn":"08832927","usgsCitation":"Szabo, Z., DePaul, V.T., Fischer, J., Kraemer, T.F., and Jacobsen, E., 2012, Occurrence and geochemistry of radium in water from principal drinking-water aquifer systems of the United States: Applied Geochemistry, v. 27, no. 3, p. 729-752, https://doi.org/10.1016/j.apgeochem.2011.11.002.","startPage":"729","endPage":"752","numberOfPages":"24","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":474677,"rank":10000,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.apgeochem.2011.11.002","text":"Publisher Index Page"},{"id":241597,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":213923,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.apgeochem.2011.11.002"}],"volume":"27","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a6b6ce4b0c8380cd746a9","contributors":{"authors":[{"text":"Szabo, Z. 0000-0002-0760-9607","orcid":"https://orcid.org/0000-0002-0760-9607","contributorId":44302,"corporation":false,"usgs":true,"family":"Szabo","given":"Z.","affiliations":[],"preferred":false,"id":437349,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"DePaul, Vincent T. 0000-0002-7977-5217 vdepaul@usgs.gov","orcid":"https://orcid.org/0000-0002-7977-5217","contributorId":2778,"corporation":false,"usgs":true,"family":"DePaul","given":"Vincent","email":"vdepaul@usgs.gov","middleInitial":"T.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":437351,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fischer, J.M. 0000-0003-2996-9272","orcid":"https://orcid.org/0000-0003-2996-9272","contributorId":74419,"corporation":false,"usgs":true,"family":"Fischer","given":"J.M.","affiliations":[],"preferred":false,"id":437352,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kraemer, T. F.","contributorId":63400,"corporation":false,"usgs":true,"family":"Kraemer","given":"T.","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":437350,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jacobsen, E.","contributorId":101462,"corporation":false,"usgs":true,"family":"Jacobsen","given":"E.","email":"","affiliations":[],"preferred":false,"id":437353,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70035458,"text":"70035458 - 2012 - Geochemical constraints on adakites of different origins and copper mineralization","interactions":[],"lastModifiedDate":"2020-11-13T20:05:13.127307","indexId":"70035458","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2309,"text":"Journal of Geology","active":true,"publicationSubtype":{"id":10}},"title":"Geochemical constraints on adakites of different origins and copper mineralization","docAbstract":"The petrogenesis of adakites holds important clues to the formation of the continental crust and copper ± gold porphyry mineralization. However, it remains highly debated as to whether adakites form by slab melting, by partial melting of the lower continental crust, or by fractional crystallization of normal arc magmas. Here, we show that to form adakitic signature, partial melting of a subducting oceanic slab would require high pressure at depths of >50 km, whereas partial melting of the lower continental crust would require the presence of plagioclase and thus shallower depths and additional water. These two types of adakites can be discriminated using geochemical indexes. Compiled data show that adakites from circum-Pacific regions, which have close affinity to subduction of young hot oceanic plate, can be clearly discriminated from adakites from the Dabie Mountains and the Tibetan Plateau, which have been attributed to partial melting of continental crust, in Sr/Y-versus-La/Yb diagram. Given that oceanic crust has copper concentrations about two times higher than those in the continental crust, whereas the high oxygen fugacity in the subduction environment promotes the release of copper during partial melting, slab melting provides the most efficient mechanism to concentrate copper and gold; slab melts would be more than two times greater in copper (and also gold) concentrations than lower continental crust melts and normal arc magmas. Thus, identification of slab melt adakites is important for predicting exploration targets for copper- and gold-porphyry ore deposits. This explains the close association of ridge subduction with large porphyry copper deposits because ridge subduction is the most favorable place for slab melting.
","language":"English","publisher":"The University of Chicago Press Books","doi":"10.1086/662736","issn":"00221376","usgsCitation":"Sun, W., Ling, M., Chung, S., Ding, X., Yang, X., Liang, H., Fan, W., Goldfarb, R., and Yin, Q., 2012, Geochemical constraints on adakites of different origins and copper mineralization: Journal of Geology, v. 120, no. 1, p. 105-120, https://doi.org/10.1086/662736.","productDescription":"16 p.","startPage":"105","endPage":"120","costCenters":[],"links":[{"id":243369,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":215557,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1086/662736"}],"country":"China","otherGeospatial":"Dabie Mountains and the Tibetan Plateau","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 101.513671875,\n 22.43134015636061\n ],\n [\n 108.720703125,\n 25.958044673317843\n ],\n [\n 107.57812499999999,\n 30.600093873550072\n ],\n [\n 102.65625,\n 31.50362930577303\n ],\n [\n 99.49218749999999,\n 29.152161283318915\n ],\n [\n 99.580078125,\n 25.64152637306577\n ],\n [\n 101.513671875,\n 22.43134015636061\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 107.57812499999999,\n 40.713955826286046\n ],\n [\n 104.765625,\n 35.746512259918504\n ],\n [\n 106.171875,\n 33.137551192346145\n ],\n [\n 112.1484375,\n 32.24997445586331\n ],\n [\n 114.9609375,\n 35.746512259918504\n ],\n [\n 114.9609375,\n 40.17887331434696\n ],\n [\n 112.8515625,\n 42.8115217450979\n ],\n [\n 107.57812499999999,\n 40.713955826286046\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"120","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a15f5e4b0c8380cd54fd6","contributors":{"authors":[{"text":"Sun, W.-D.","contributorId":14658,"corporation":false,"usgs":true,"family":"Sun","given":"W.-D.","email":"","affiliations":[],"preferred":false,"id":450761,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ling, M.-X.","contributorId":69382,"corporation":false,"usgs":true,"family":"Ling","given":"M.-X.","email":"","affiliations":[],"preferred":false,"id":450766,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chung, S.-L.","contributorId":27697,"corporation":false,"usgs":true,"family":"Chung","given":"S.-L.","email":"","affiliations":[],"preferred":false,"id":450762,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ding, X.","contributorId":49990,"corporation":false,"usgs":true,"family":"Ding","given":"X.","email":"","affiliations":[],"preferred":false,"id":450764,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Yang, X.-Y.","contributorId":9489,"corporation":false,"usgs":true,"family":"Yang","given":"X.-Y.","email":"","affiliations":[],"preferred":false,"id":450760,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Liang, H.-Y.","contributorId":88576,"corporation":false,"usgs":true,"family":"Liang","given":"H.-Y.","email":"","affiliations":[],"preferred":false,"id":450767,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Fan, W.-M.","contributorId":100217,"corporation":false,"usgs":true,"family":"Fan","given":"W.-M.","email":"","affiliations":[],"preferred":false,"id":450768,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Goldfarb, R.","contributorId":43113,"corporation":false,"usgs":true,"family":"Goldfarb","given":"R.","email":"","affiliations":[],"preferred":false,"id":450763,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Yin, Q.-Z.","contributorId":64056,"corporation":false,"usgs":true,"family":"Yin","given":"Q.-Z.","email":"","affiliations":[],"preferred":false,"id":450765,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70032540,"text":"70032540 - 2012 - A multi-source satellite data approach for modelling Lake Turkana water level: Calibration and validation using satellite altimetry data","interactions":[],"lastModifiedDate":"2020-11-30T21:58:43.196979","indexId":"70032540","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1928,"text":"Hydrology and Earth System Sciences","active":true,"publicationSubtype":{"id":10}},"title":"A multi-source satellite data approach for modelling Lake Turkana water level: Calibration and validation using satellite altimetry data","docAbstract":"Lake Turkana is one of the largest desert lakes in the world and is characterized by high degrees of inter- and intra-annual fluctuations. The hydrology and water balance of this lake have not been well understood due to its remote location and unavailability of reliable ground truth datasets. Managing surface water resources is a great challenge in areas where in-situ data are either limited or unavailable. In this study, multi-source satellite-driven data such as satellite-based rainfall estimates, modelled runoff, evapotranspiration, and a digital elevation dataset were used to model Lake Turkana water levels from 1998 to 2009. Due to the unavailability of reliable lake level data, an approach is presented to calibrate and validate the water balance model of Lake Turkana using a composite lake level product of TOPEX/Poseidon, Jason-1, and ENVISAT satellite altimetry data. Model validation results showed that the satellite-driven water balance model can satisfactorily capture the patterns and seasonal variations of the Lake Turkana water level fluctuations with a Pearson's correlation coefficient of 0.90 and a Nash-Sutcliffe Coefficient of Efficiency (NSCE) of 0.80 during the validation period (2004–2009). Model error estimates were within 10% of the natural variability of the lake. Our analysis indicated that fluctuations in Lake Turkana water levels are mainly driven by lake inflows and over-the-lake evaporation. Over-the-lake rainfall contributes only up to 30% of lake evaporative demand. During the modelling time period, Lake Turkana showed seasonal variations of 1–2 m. The lake level fluctuated in the range up to 4 m between the years 1998–2009. This study demonstrated the usefulness of satellite altimetry data to calibrate and validate the satellite-driven hydrological model for Lake Turkana without using any in-situ data. Furthermore, for Lake Turkana, we identified and outlined opportunities and challenges of using a calibrated satellite-driven water balance model for (i) quantitative assessment of the impact of basin developmental activities on lake levels and for (ii) forecasting lake level changes and their impact on fisheries. From this study, we suggest that globally available satellite altimetry data provide a unique opportunity for calibration and validation of hydrologic models in ungauged basins.
","language":"English","publisher":"European Geosciences Union","publisherLocation":"Munich, Germany","doi":"10.5194/hess-16-1-2012","issn":"10275606","usgsCitation":"Velpuri, N., Senay, G., and Asante, K., 2012, A multi-source satellite data approach for modelling Lake Turkana water level: Calibration and validation using satellite altimetry data: Hydrology and Earth System Sciences, v. 16, no. 1, p. 1-18, https://doi.org/10.5194/hess-16-1-2012.","productDescription":"18 p.","startPage":"1","endPage":"18","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":474744,"rank":10000,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/hess-16-1-2012","text":"Publisher Index Page"},{"id":241758,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":214070,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.5194/hess-16-1-2012"}],"country":"Kenya","otherGeospatial":"Lake Turkana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 35.79345703125,\n 2.4162756547063857\n ],\n [\n 36.8701171875,\n 2.4162756547063857\n ],\n [\n 36.8701171875,\n 4.718777551249855\n ],\n [\n 35.79345703125,\n 4.718777551249855\n ],\n [\n 35.79345703125,\n 2.4162756547063857\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"16","issue":"1","noUsgsAuthors":false,"publicationDate":"2012-01-03","publicationStatus":"PW","scienceBaseUri":"5059e48be4b0c8380cd466ee","contributors":{"authors":[{"text":"Velpuri, N.M. 0000-0002-6370-1926","orcid":"https://orcid.org/0000-0002-6370-1926","contributorId":66495,"corporation":false,"usgs":true,"family":"Velpuri","given":"N.M.","affiliations":[],"preferred":false,"id":436730,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Senay, Gabriel B. 0000-0002-8810-8539 senay@usgs.gov","orcid":"https://orcid.org/0000-0002-8810-8539","contributorId":152206,"corporation":false,"usgs":true,"family":"Senay","given":"Gabriel B.","email":"senay@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":436729,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Asante, K.O. 0000-0001-5408-1852","orcid":"https://orcid.org/0000-0001-5408-1852","contributorId":17051,"corporation":false,"usgs":true,"family":"Asante","given":"K.O.","affiliations":[],"preferred":false,"id":436728,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70032554,"text":"70032554 - 2012 - Ecological controls on the shell geochemistry of pink and white Globigerinoides ruber in the northern Gulf of Mexico: implications for paleoceanographic reconstruction","interactions":[],"lastModifiedDate":"2014-01-14T10:15:16","indexId":"70032554","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2673,"text":"Marine Micropaleontology","active":true,"publicationSubtype":{"id":10}},"title":"Ecological controls on the shell geochemistry of pink and white Globigerinoides ruber in the northern Gulf of Mexico: implications for paleoceanographic reconstruction","docAbstract":"We evaluate the relationship between foraminiferal test size and shell geochemistry (δ13C, δ18O, and Mg/Ca) for two of the most commonly used planktonic foraminifers for paleoceanographic reconstruction in the subtropical Atlantic Ocean: the pink and white varieties of Globigerinoides ruber. Geochemical analyses were performed on foraminifera from modern core-top samples of high-accumulation rate basins in the northern Gulf of Mexico. Mg/Ca analysis indicates a positive relationship with test size, increasing by 1.1 mmol/mol (~ 2.5 °C) from the smallest (150–212 μm) to largest (> 500 μm) size fractions of G. ruber (pink), but with no significant relationship in G. ruber (white). In comparison, oxygen isotope data indicate a negative relationship with test size, decreasing by 0.6‰ across the size range of both pink and white G. ruber. The observed increase in Mg/Ca and decrease in δ18O are consistent with an increase in calcification temperature of 0.7 °C per 100 μm increase in test size, suggesting differences in the seasonal and/or depth distribution among size fractions. Overall, these results stress the necessity for using a consistent size fraction in downcore paleoceanographic studies. In addition, we compare downcore records of δ18O and Mg/Ca from pink and white G. ruber in a decadal-resolution 1000-year sedimentary record from the Pigmy Basin. Based on this comparison we conclude that pink G. ruber is calcifying in warmer waters than co-occurring white G. ruber, suggesting differences in the relative seasonal distribution and depth habitat of the two varieties.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Marine Micropaleontology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.marmicro.2011.10.002","issn":"03778398","usgsCitation":"Richey, J.N., Poore, R.Z., Flower, B.P., and Hollander, D.J., 2012, Ecological controls on the shell geochemistry of pink and white Globigerinoides ruber in the northern Gulf of Mexico: implications for paleoceanographic reconstruction: Marine Micropaleontology, v. 82-83, p. 28-37, https://doi.org/10.1016/j.marmicro.2011.10.002.","productDescription":"10 p.","startPage":"28","endPage":"37","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":213790,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.marmicro.2011.10.002"},{"id":241449,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Gulf Of Mexico","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -97.9,18.2 ], [ -97.9,30.4 ], [ -81.0,30.4 ], [ -81.0,18.2 ], [ -97.9,18.2 ] ] ] } } ] }","volume":"82-83","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a054de4b0c8380cd50d41","contributors":{"authors":[{"text":"Richey, Julie N. 0000-0002-2319-7980 jrichey@usgs.gov","orcid":"https://orcid.org/0000-0002-2319-7980","contributorId":5182,"corporation":false,"usgs":true,"family":"Richey","given":"Julie","email":"jrichey@usgs.gov","middleInitial":"N.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":436796,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Poore, Richard Z. rpoore@usgs.gov","contributorId":345,"corporation":false,"usgs":true,"family":"Poore","given":"Richard","email":"rpoore@usgs.gov","middleInitial":"Z.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":436795,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Flower, Benjamin P.","contributorId":100620,"corporation":false,"usgs":true,"family":"Flower","given":"Benjamin","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":436798,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hollander, David J.","contributorId":11421,"corporation":false,"usgs":true,"family":"Hollander","given":"David","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":436797,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70032316,"text":"70032316 - 2012 - Intelligent estimation of spatially distributed soil physical properties","interactions":[],"lastModifiedDate":"2020-12-02T21:51:46.727938","indexId":"70032316","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1760,"text":"Geoderma","active":true,"publicationSubtype":{"id":10}},"title":"Intelligent estimation of spatially distributed soil physical properties","docAbstract":"Spatial analysis of soil samples is often times not possible when measurements are limited in number or clustered. To obviate potential problems, we propose a new approach based on the self-organizing map (SOM) technique. This approach exploits underlying nonlinear relation of the steady-state geomorphic concave–convex nature of hillslopes (from hilltop to bottom of the valley) to spatially limited soil textural data. The topographic features are extracted from Shuttle Radar Topographic Mission elevation data; whereas soil textural (clay, silt, and sand) and hydraulic data were collected in 29 spatially random locations (50 to 75 cm depth). In contrast to traditional principal component analysis, the SOM identifies relations among relief features, such as, slope, horizontal curvature and vertical curvature. Stochastic cross-validation indicates that the SOM is unbiased and provides a way to measure the magnitude of prediction uncertainty for all variables. The SOM cross-component plots of the soil texture reveals higher clay proportions at concave areas with convergent hydrological flux and lower proportions for convex areas with divergent flux. The sand ratio has an opposite pattern with higher values near the ridge and lower values near the valley. Silt has a trend similar to sand, although less pronounced. The relation between soil texture and concave–convex hillslope features reveals that subsurface weathering and transport is an important process that changed from loss-to-gain at the rectilinear hillslope point. These results illustrate that the SOM can be used to capture and predict nonlinear hillslope relations among relief, soil texture, and hydraulic conductivity data.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.geoderma.2011.11.002","issn":"00167061","usgsCitation":"Iwashita, F., Friedel, M.J., Ribeiro, G., and Fraser, S.J., 2012, Intelligent estimation of spatially distributed soil physical properties: Geoderma, v. 170, p. 1-10, https://doi.org/10.1016/j.geoderma.2011.11.002.","productDescription":"10 p.","startPage":"1","endPage":"10","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":242483,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":214733,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.geoderma.2011.11.002"}],"volume":"170","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a3c98e4b0c8380cd62e87","contributors":{"authors":[{"text":"Iwashita, F.","contributorId":96912,"corporation":false,"usgs":true,"family":"Iwashita","given":"F.","affiliations":[],"preferred":false,"id":435582,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Friedel, Michael J. 0000-0002-5060-3999 mfriedel@usgs.gov","orcid":"https://orcid.org/0000-0002-5060-3999","contributorId":595,"corporation":false,"usgs":true,"family":"Friedel","given":"Michael","email":"mfriedel@usgs.gov","middleInitial":"J.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":435581,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ribeiro, G.F.","contributorId":60032,"corporation":false,"usgs":true,"family":"Ribeiro","given":"G.F.","email":"","affiliations":[],"preferred":false,"id":435579,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fraser, Stephen J.","contributorId":87769,"corporation":false,"usgs":true,"family":"Fraser","given":"Stephen","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":435580,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70032408,"text":"70032408 - 2012 - Semiochemical compounds of preen secretion reflect genetic make-up in a seabird species","interactions":[],"lastModifiedDate":"2020-11-03T14:32:56.98145","indexId":"70032408","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3174,"text":"Proceedings of the Royal Society B: Biological Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Semiochemical compounds of preen secretion reflect genetic make-up in a seabird species","docAbstract":"Several vertebrates choose their mate according to genetic heterozygosity and relatedness, and use odour cues to assess their conspecifics' genetic make-up. In birds, although several species (including the black-legged kittiwake) exhibit non-random mating according to genetic traits, the cues used to assess genetic characteristics remain unknown. The importance of olfaction in birds' social behaviour is gaining attention among researchers, and it has been suggested that, as in other vertebrates, bird body scent may convey information about genetic traits. Here, we combined gas chromatography data and genetic analyses at microsatellite loci to test whether semiochemical messages in preen secretion of kittiwakes carried information about genetic heterozygosity and relatedness. Semiochemical profile was correlated with heterozygosity in males and females, while semiochemical distance was correlated with genetic distance only in male–male dyads. Our study is the first to demonstrate a link between odour and genetics in birds, which sets the stage for the existence of sophisticated odour-based mechanisms of mate choice also in birds.
","language":"English","publisher":"The Royal Society","doi":"10.1098/rspb.2011.1611","usgsCitation":"Leclaire, S., Merkling, T., Raynaud, C., Mulard, H., Bessiere, J., Lhuillier, E., Hatch, S.A., and Danchin, E., 2012, Semiochemical compounds of preen secretion reflect genetic make-up in a seabird species: Proceedings of the Royal Society B: Biological Sciences, v. 279, no. 1731, p. 1185-1193, https://doi.org/10.1098/rspb.2011.1611.","productDescription":"9 p.","startPage":"1185","endPage":"1193","numberOfPages":"9","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":474627,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/3267147","text":"External Repository"},{"id":241243,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"279","issue":"1731","noUsgsAuthors":false,"publicationDate":"2011-09-21","publicationStatus":"PW","scienceBaseUri":"505b8d12e4b08c986b318256","contributors":{"authors":[{"text":"Leclaire, S.","contributorId":39591,"corporation":false,"usgs":true,"family":"Leclaire","given":"S.","email":"","affiliations":[],"preferred":false,"id":436021,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Merkling, T.","contributorId":26522,"corporation":false,"usgs":true,"family":"Merkling","given":"T.","affiliations":[],"preferred":false,"id":436020,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Raynaud, C.","contributorId":46313,"corporation":false,"usgs":true,"family":"Raynaud","given":"C.","email":"","affiliations":[],"preferred":false,"id":436022,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mulard, Herve","contributorId":104602,"corporation":false,"usgs":false,"family":"Mulard","given":"Herve","email":"","affiliations":[],"preferred":false,"id":436026,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bessiere, J.-M.","contributorId":107107,"corporation":false,"usgs":true,"family":"Bessiere","given":"J.-M.","email":"","affiliations":[],"preferred":false,"id":436027,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lhuillier, E.M.","contributorId":103880,"corporation":false,"usgs":true,"family":"Lhuillier","given":"E.M.","affiliations":[],"preferred":false,"id":436025,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hatch, Scott A. 0000-0002-0064-8187 shatch@usgs.gov","orcid":"https://orcid.org/0000-0002-0064-8187","contributorId":2625,"corporation":false,"usgs":true,"family":"Hatch","given":"Scott","email":"shatch@usgs.gov","middleInitial":"A.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":436023,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Danchin, E.","contributorId":89635,"corporation":false,"usgs":true,"family":"Danchin","given":"E.","affiliations":[],"preferred":false,"id":436024,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70032246,"text":"70032246 - 2012 - A riverscape perspective of Pacific salmonids and aquatic habitats prior to large-scale dam removal in the Elwha River, Washington, USA","interactions":[],"lastModifiedDate":"2017-11-21T14:54:32","indexId":"70032246","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1659,"text":"Fisheries Management and Ecology","active":true,"publicationSubtype":{"id":10}},"title":"A riverscape perspective of Pacific salmonids and aquatic habitats prior to large-scale dam removal in the Elwha River, Washington, USA","docAbstract":"Dam removal has been increasingly proposed as a river restoration technique. In 2011, two large hydroelectric dams will be removed from Washington State’s Elwha River. Ten anadromous fish populations are expected to recolonise historical habitats after dam removal. A key to understanding watershed recolonisation is the collection of spatially continuous information on fish and aquatic habitats. A riverscape approach with an emphasis on biological data has rarely been applied in mid-sized, wilderness rivers, particularly in consecutive years prior to dam removal. Concurrent snorkel and habitat surveys were conducted from the headwaters to the mouth (rkm 65–0) of the Elwha River in 2007 and 2008. This riverscape approach characterised the spatial extent, assemblage structure and patterns of relative density of Pacific salmonids. The presence of dams influenced the longitudinal patterns of fish assemblages, and species richness was the highest downstream of the dams, where anadromous salmonids still have access. The percent composition of salmonids was similar in both years for rainbow trout, Oncorhynchus mykiss (Walbaum), coastal cutthroat trout, Oncorhynchus clarkii clarkii (Richardson) (89%; 88%), Chinook salmon, Oncorhynchus tshawytscha (Walbaum) (8%; 9%), and bull trout, Salvelinus confluentus (Suckley) (3% in both years). Spatial patterns of abundance for rainbow and cutthroat trout (r = 0.76) and bull trout (r = 0.70) were also consistent between years. Multivariate and univariate methods detected differences in habitat structure along the river profile caused by natural and anthropogenic factors. The riverscape view highlighted species-specific biological hotspots and revealed that 60–69% of federally threatened bull trout occurred near or below the dams. Spatially continuous surveys will be vital in evaluating the effectiveness of upcoming dam removal projects at restoring anadromous salmonids.
","language":"English","publisher":"Blackwell Science","doi":"10.1111/j.1365-2400.2011.00815.x","issn":"0969997X","usgsCitation":"Brenkman, S., Duda, J., Torgersen, C., Welty, E., Pess, G., Peters, R., and McHenry, M., 2012, A riverscape perspective of Pacific salmonids and aquatic habitats prior to large-scale dam removal in the Elwha River, Washington, USA: Fisheries Management and Ecology, v. 19, no. 1, p. 36-53, https://doi.org/10.1111/j.1365-2400.2011.00815.x.","productDescription":"18 p.","startPage":"36","endPage":"53","numberOfPages":"18","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":242341,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Elwha River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.56185913085936,\n 48.148679437804546\n ],\n [\n -123.56082916259766,\n 48.14570150746186\n ],\n [\n -123.56185913085936,\n 48.14111973876637\n ],\n [\n -123.55636596679688,\n 48.13974512840794\n ],\n [\n -123.55361938476562,\n 48.13745402934834\n ],\n [\n -123.54949951171876,\n 48.1358501991708\n ],\n [\n -123.54846954345703,\n 48.13172583437477\n ],\n [\n -123.55087280273438,\n 48.127830296770306\n ],\n [\n -123.55121612548828,\n 48.12462198509838\n ],\n [\n -123.54984283447266,\n 48.11912155596991\n ],\n [\n -123.54881286621092,\n 48.11614191094256\n ],\n [\n -123.54812622070311,\n 48.110869807948\n ],\n [\n -123.54675292968749,\n 48.10536790636255\n ],\n [\n -123.55224609375,\n 48.102846004623906\n ],\n [\n -123.55258941650389,\n 48.09848970109192\n ],\n [\n -123.55567932128906,\n 48.092527845402735\n ],\n [\n -123.56117248535155,\n 48.08908799881762\n ],\n [\n -123.55876922607422,\n 48.085418575511966\n ],\n [\n -123.56426239013672,\n 48.08197825339591\n ],\n [\n -123.57112884521483,\n 48.07670264591117\n ],\n [\n -123.5697555541992,\n 48.07372054150283\n ],\n [\n -123.5731887817383,\n 48.07027943703391\n ],\n [\n -123.57181549072264,\n 48.06660867196763\n ],\n [\n -123.57044219970702,\n 48.06362598256743\n ],\n [\n -123.5745620727539,\n 48.05995474295331\n ],\n [\n -123.57868194580078,\n 48.05467687730276\n ],\n [\n -123.58314514160156,\n 48.05123449951945\n ],\n [\n -123.58932495117188,\n 48.050775498427726\n ],\n [\n -123.58932495117188,\n 48.056512718025246\n ],\n [\n -123.58589172363281,\n 48.063167091934076\n ],\n [\n -123.58245849609375,\n 48.06660867196763\n ],\n [\n -123.58142852783203,\n 48.07234412732831\n ],\n [\n -123.57730865478516,\n 48.07532631150696\n ],\n [\n -123.57627868652342,\n 48.080831428223966\n ],\n [\n -123.57215881347656,\n 48.08450117877953\n ],\n [\n -123.56906890869139,\n 48.092069212485605\n ],\n [\n -123.5635757446289,\n 48.09665535758499\n ],\n [\n -123.56151580810547,\n 48.103304541416\n ],\n [\n -123.55945587158203,\n 48.10926514749487\n ],\n [\n -123.55876922607422,\n 48.115683488677305\n ],\n [\n -123.56048583984374,\n 48.12095509778696\n ],\n [\n -123.56323242187499,\n 48.12462198509838\n ],\n [\n -123.5628890991211,\n 48.130121825265675\n ],\n [\n -123.56185913085936,\n 48.13447544771421\n ],\n [\n -123.56666564941406,\n 48.136537561095906\n ],\n [\n -123.5687255859375,\n 48.14111973876637\n ],\n [\n -123.57009887695312,\n 48.14455610362899\n ],\n [\n -123.56941223144531,\n 48.148450372374185\n ],\n [\n -123.56185913085936,\n 48.148679437804546\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"19","issue":"1","noUsgsAuthors":false,"publicationDate":"2011-10-21","publicationStatus":"PW","scienceBaseUri":"5059e564e4b0c8380cd46d23","contributors":{"authors":[{"text":"Brenkman, S.J.","contributorId":106318,"corporation":false,"usgs":true,"family":"Brenkman","given":"S.J.","affiliations":[],"preferred":false,"id":435226,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Duda, J.J. 0000-0001-7431-8634","orcid":"https://orcid.org/0000-0001-7431-8634","contributorId":105073,"corporation":false,"usgs":true,"family":"Duda","given":"J.J.","affiliations":[],"preferred":false,"id":435225,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Torgersen, C.E.","contributorId":34459,"corporation":false,"usgs":true,"family":"Torgersen","given":"C.E.","affiliations":[],"preferred":false,"id":435222,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Welty, E.","contributorId":56464,"corporation":false,"usgs":true,"family":"Welty","given":"E.","email":"","affiliations":[],"preferred":false,"id":435224,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pess, G.R.","contributorId":33037,"corporation":false,"usgs":true,"family":"Pess","given":"G.R.","affiliations":[],"preferred":false,"id":435221,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Peters, R.","contributorId":51875,"corporation":false,"usgs":true,"family":"Peters","given":"R.","email":"","affiliations":[],"preferred":false,"id":435223,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McHenry, M.L.","contributorId":29476,"corporation":false,"usgs":true,"family":"McHenry","given":"M.L.","email":"","affiliations":[],"preferred":false,"id":435220,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70032262,"text":"70032262 - 2012 - Nonlinear effects of group size on the success of wolves hunting elk","interactions":[],"lastModifiedDate":"2020-12-03T19:37:07.184022","indexId":"70032262","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":981,"text":"Behavioral Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Nonlinear effects of group size on the success of wolves hunting elk","docAbstract":"Despite the popular view that social predators live in groups because group hunting facilitates prey capture, the apparent tendency for hunting success to peak at small group sizes suggests that the formation of large groups is unrelated to prey capture. Few empirical studies, however, have tested for nonlinear relationships between hunting success and group size, and none have demonstrated why success trails off after peaking. Here, we use a unique dataset of observations of individually known wolves (Canis lupus) hunting elk (Cervus elaphus) in Yellowstone National Park to show that the relationship between success and group size is indeed nonlinear and that individuals withholding effort (free riding) is why success does not increase across large group sizes. Beyond 4 wolves, hunting success leveled off, and individual performance (a measure of effort) decreased for reasons unrelated to interference from inept hunters, individual age, or size. But performance did drop faster among wolves with an incentive to hold back, i.e., nonbreeders with no dependent offspring, those performing dangerous predatory tasks, i.e., grabbing and restraining prey, and those in groups of proficient hunters. These results suggest that decreasing performance was free riding and that was why success leveled off in groups with >4 wolves that had superficially appeared to be cooperating. This is the first direct evidence that nonlinear trends in group hunting success reflect a switch from cooperation to free riding. It also highlights how hunting success per se is unlikely to promote formation and maintenance of large groups.
","language":"English","doi":"10.1093/beheco/arr159","issn":"10452249","usgsCitation":"MacNulty, D., Smith, D., Mech, L.D., Vucetich, J., and Packer, C., 2012, Nonlinear effects of group size on the success of wolves hunting elk: Behavioral Ecology, v. 23, no. 1, p. 75-82, https://doi.org/10.1093/beheco/arr159.","productDescription":"8 p.","startPage":"75","endPage":"82","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":474823,"rank":10000,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/beheco/arr159","text":"Publisher Index Page"},{"id":242644,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":214888,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1093/beheco/arr159"}],"country":"United States","state":"Idaho, Montana, 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 -112.1484375,\n 43.96119063892024\n ],\n [\n -109.64355468749999,\n 43.96119063892024\n ],\n [\n -109.64355468749999,\n 45.82879925192134\n ],\n [\n -112.1484375,\n 45.82879925192134\n ],\n [\n -112.1484375,\n 43.96119063892024\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"23","issue":"1","noUsgsAuthors":false,"publicationDate":"2011-09-29","publicationStatus":"PW","scienceBaseUri":"505a6783e4b0c8380cd7337f","contributors":{"authors":[{"text":"MacNulty, D.R.","contributorId":7661,"corporation":false,"usgs":true,"family":"MacNulty","given":"D.R.","email":"","affiliations":[],"preferred":false,"id":435317,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, D.W.","contributorId":24726,"corporation":false,"usgs":true,"family":"Smith","given":"D.W.","email":"","affiliations":[],"preferred":false,"id":435318,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mech, L. David 0000-0003-3944-7769 david_mech@usgs.gov","orcid":"https://orcid.org/0000-0003-3944-7769","contributorId":2518,"corporation":false,"usgs":true,"family":"Mech","given":"L.","email":"david_mech@usgs.gov","middleInitial":"David","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":435321,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vucetich, J.A.","contributorId":36098,"corporation":false,"usgs":true,"family":"Vucetich","given":"J.A.","email":"","affiliations":[],"preferred":false,"id":435319,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Packer, C.","contributorId":45532,"corporation":false,"usgs":true,"family":"Packer","given":"C.","email":"","affiliations":[],"preferred":false,"id":435320,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70005993,"text":"70005993 - 2012 - The impact of biotic/abiotic interfaces in mineral nutrient cycling: A study of soils of the Santa Cruz chronosequence, California","interactions":[],"lastModifiedDate":"2020-12-30T19:15:07.348439","indexId":"70005993","displayToPublicDate":"2011-12-25T13:43:00","publicationYear":"2012","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":"The impact of biotic/abiotic interfaces in mineral nutrient cycling: A study of soils of the Santa Cruz chronosequence, California","docAbstract":"Biotic/abiotic interactions between soil mineral nutrients and annual grassland vegetation are characterized for five soils in a marine terrace chronosequence near Santa Cruz, California. A Mediterranean climate, with wet winters and dry summers, controls the annual cycle of plant growth and litter decomposition, resulting in net above-ground productivities of 280–600 g m−2 yr−1. The biotic/abiotic (A/B) interface separates seasonally reversible nutrient gradients, reflecting biological cycling in the shallower soils, from downward chemical weathering gradients in the deeper soils. The A/B interface is pedologically defined by argillic clay horizons centered at soil depths of about one meter which intensify with soil age. Below these horizons, elevated solute Na/Ca, Mg/Ca and Sr/Ca ratios reflect plagioclase and smectite weathering along pore water flow paths. Above the A/B interface, lower cation ratios denote temporal variability due to seasonal plant nutrient uptake and litter leaching. Potassium and Ca exhibit no seasonal variability beneath the A/B interface, indicating closed nutrient cycling within the root zone, whereas Mg variability below the A/B interface denotes downward leakage resulting from higher inputs of marine aerosols and lower plant nutrient requirements.
The fraction of a mineral nutrient annually cycled through the plants, compared to that lost from pore water discharge, is defined their respective fluxes Fj,plants = qj,plants/(qj,plants + qj,discharge) with average values for K and Ca (FK,plants = 0.99; FCa,plants = 0.93) much higher than for Mg and Na (FMg,plants 0.64; FNa,plants = 0.28). The discrimination against Rb and Sr by plants is described by fractionation factors (KSr/Ca = 0.86; KRb/K = 0.83) which are used in Rayleigh fractionation-mixing calculations to fit seasonal patterns in solute K and Ca cycling. KRb/K and
Site-specific temporal trends in algae, benthic invertebrate, and fish assemblages were investigated in 15 streams and rivers draining basins of varying land use in the south-central United States from 1993–2007. A multivariate approach was used to identify sites with statistically significant trends in aquatic assemblages which were then tested for correlations with assemblage metrics and abiotic environmental variables (climate, water quality, streamflow, and physical habitat). Significant temporal trends in one or more of the aquatic assemblages were identified at more than half (eight of 15) of the streams in the study. Assemblage metrics and abiotic environmental variables found to be significantly correlated with aquatic assemblages differed between land use categories. For example, algal assemblages at undeveloped sites were associated with physical habitat, while algal assemblages at more anthropogenically altered sites (agricultural and urban) were associated with nutrient and streamflow metrics. In urban stream sites results indicate that streamflow metrics may act as important controls on water quality conditions, as represented by aquatic assemblage metrics. The site-specific identification of biotic trends and abiotic–biotic relations presented here will provide valuable information that can inform interpretation of continued monitoring data and the design of future studies. In addition, the subsets of abiotic variables identified as potentially important drivers of change in aquatic assemblages provide policy makers and resource managers with information that will assist in the design and implementation of monitoring programs aimed at the protection of aquatic resources.
","language":"English","publisher":"Springer","publisherLocation":"Amsterdam, Netherlands","doi":"10.1007/s10750-011-0950-7","usgsCitation":"Miller, M.P., Kennen, J., Mabe, J.A., and Mize, S.V., 2012, Temporal trends in algae, benthic invertebrate, and fish assemblages in streams and rivers draining basins of varying land use in the south-central United States, 1993-2007: Hydrobiologia, v. 684, no. 1, p. 15-33, https://doi.org/10.1007/s10750-011-0950-7.","productDescription":"19 p.","startPage":"15","endPage":"33","temporalStart":"1993-01-01","temporalEnd":"2007-12-31","costCenters":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":257563,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas, Colorado, Kansas, Kentucky, Louisiana, Mississippi, Missouri, New Mexico, Oklahoma, Texas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.09716796875,\n 25.958044673317843\n ],\n [\n -97.40478515625,\n 25.878994400196202\n ],\n [\n -97.84423828125,\n 26.05678288577881\n ],\n [\n -98.45947265625,\n 26.13571361317392\n ],\n [\n -98.98681640625,\n 26.33280692289788\n ],\n [\n -98.63525390624999,\n 26.82407078047018\n ],\n [\n -99.33837890625,\n 27.605670826465445\n ],\n [\n -99.68994140625,\n 28.304380682962783\n ],\n [\n -99.97558593749999,\n 29.286398892934763\n ],\n [\n -100.72265625,\n 29.477861195816843\n ],\n [\n -101.31591796875,\n 31.522361470421437\n ],\n [\n -103.271484375,\n 32.36140331527543\n ],\n [\n -104.30419921875,\n 34.66935854524543\n ],\n [\n -105.40283203124999,\n 35.7286770448517\n ],\n [\n -104.8974609375,\n 36.40359962073253\n ],\n [\n -105.029296875,\n 37.50972584293751\n ],\n [\n -105.92742919921875,\n 38.756225137839074\n ],\n [\n -103.7548828125,\n 38.35888785866677\n ],\n [\n -102.01904296874999,\n 38.65119833229951\n ],\n [\n -98.8330078125,\n 37.82280243352756\n ],\n [\n -96.8115234375,\n 38.06539235133249\n ],\n [\n -94.921875,\n 37.80544394934271\n ],\n [\n -93.58154296875,\n 36.98500309285596\n ],\n [\n -90.9228515625,\n 37.405073750176925\n ],\n [\n -88.857421875,\n 36.94989178681327\n ],\n [\n -88.30810546875,\n 34.687427949314845\n ],\n [\n -89.56054687499999,\n 33.76088200086917\n ],\n [\n -89.67041015625,\n 32.175612478499325\n ],\n [\n -90.3955078125,\n 31.27855085894653\n ],\n [\n -89.47265625,\n 30.221101852485987\n ],\n [\n -89.36279296875,\n 29.726222319395504\n ],\n [\n -88.9013671875,\n 29.036960648558267\n ],\n [\n -89.93408203124999,\n 29.34387539941801\n ],\n [\n -90.1318359375,\n 28.998531814051795\n ],\n [\n -90.46142578125,\n 29.248063243796576\n ],\n [\n -91.51611328125,\n 29.38217507514529\n ],\n [\n -92.5048828125,\n 29.477861195816843\n ],\n [\n -93.71337890625,\n 29.7453016622136\n ],\n [\n -94.54833984375,\n 29.53522956294847\n ],\n [\n -95.4052734375,\n 28.806173508854776\n ],\n [\n -96.04248046875,\n 28.420391085674304\n ],\n [\n -96.767578125,\n 28.168875180063345\n ],\n [\n -97.27294921875,\n 27.235094607795503\n ],\n [\n -97.119140625,\n 26.175158990178133\n ],\n [\n -97.09716796875,\n 25.958044673317843\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"684","issue":"1","noUsgsAuthors":false,"publicationDate":"2011-11-27","publicationStatus":"PW","scienceBaseUri":"505ba51ae4b08c986b3207f4","contributors":{"authors":[{"text":"Miller, Matthew P. 0000-0002-2537-1823 mamiller@usgs.gov","orcid":"https://orcid.org/0000-0002-2537-1823","contributorId":3919,"corporation":false,"usgs":true,"family":"Miller","given":"Matthew","email":"mamiller@usgs.gov","middleInitial":"P.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":353585,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kennen, Jonathan G. 0000-0002-5426-4445 jgkennen@usgs.gov","orcid":"https://orcid.org/0000-0002-5426-4445","contributorId":574,"corporation":false,"usgs":true,"family":"Kennen","given":"Jonathan G.","email":"jgkennen@usgs.gov","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":353583,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mabe, Jeffrey A.","contributorId":65565,"corporation":false,"usgs":true,"family":"Mabe","given":"Jeffrey","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":353586,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mize, Scott V. 0000-0001-6751-5568 svmize@usgs.gov","orcid":"https://orcid.org/0000-0001-6751-5568","contributorId":2997,"corporation":false,"usgs":true,"family":"Mize","given":"Scott","email":"svmize@usgs.gov","middleInitial":"V.","affiliations":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":353584,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70227333,"text":"70227333 - 2012 - Geochemical modeling of changes in shallow groundwater chemistry observed during the MSU-ZERT CO2 injection experiment","interactions":[],"lastModifiedDate":"2022-01-10T15:36:27.174564","indexId":"70227333","displayToPublicDate":"2011-11-26T09:26:26","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2049,"text":"International Journal of Greenhouse Gas Control","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Geochemical modeling of changes in shallow groundwater chemistry observed during the MSU-ZERT CO2 injection experiment","title":"Geochemical modeling of changes in shallow groundwater chemistry observed during the MSU-ZERT CO2 injection experiment","docAbstract":"A field experiment involving the release of carbon dioxide (CO2) into a shallow aquifer was conducted near Bozeman, Montana, during the summer of 2008, to investigate the potential groundwater quality impacts in the case of leakage of CO2 from deep geological storage. As an essential part of the Montana State University Zero Emission Research and Technology (MSU-ZERT) field program, food-grade CO2 was injected over a 30 day period into a horizontal perforated pipe a few feet below the water table of a shallow aquifer. The impact of elevated CO2 concentrations on groundwater quality was investigated by analyzing water samples taken before, during, and following CO2 injection, from observation wells located in the vicinity of the injection pipe, and from two distant monitoring wells. Field measurements and laboratory analyses showed rapid and systematic changes in pH, alkalinity, and conductance, as well as increases in the aqueous concentrations of naturally occurring major and trace element species.
The geochemical data were evaluated using principal component analysis (PCA) to (1) understand potential correlations between aqueous species, and (2) to identify minerals controlling the chemical composition of the groundwater prior to CO2 injection. These evaluations were used to assess possible geochemical processes responsible for the observed increases in the concentrations of dissolved constituents, and to simulate these processes using a multicomponent reaction path model. Reasonable agreement between observed and modeled data suggests that (1) calcite dissolution was the primary pH buffer, yielding increased Ca+2 concentrations in the groundwater, (2) increases in the concentrations of most major and trace metal cations except Fe could be a result of Ca+2-driven exchange reactions, (3) the release of anions from adsorption sites due to competitive adsorption of carbonate could explain the observed trends of most anions, and (4) the dissolution of reactive Fe minerals (presumed ferrihydrite and fougerite, from thermodynamic analyses) could explain increases in total Fe concentration.
► Because the possibility of CO2 leakage cannot be completely ruled out, the potential impact of CO2 intrusion on the quality of fresh water aquifers overlying CO2 storage sites needs to be investigated. ► Geochemical data from a field experiment involving the release of carbon dioxide (CO2) into a shallow aquifer were evaluated. ► Geochemical model used to assess possible geochemical processes responsible for the observed increases in the concentrations of dissolved constituents. ► Reasonable agreement between observed and modeled data suggests that increases in the concentrations of most major and trace metal cations except Fe could be a result of Ca+2-driven exchange reactions and the release of anions from adsorption sites due to competitive adsorption of carbonate could explain the observed trends of most anions.
We derive point and interval estimates for an urban population of green tree frogs (Hyla cinerea) from capture–mark–recapture field data obtained during the years 2006–2009. We present an infinite-dimensional least-squares approach which compares a mathematical population model to the statistical population estimates obtained from the field data. The model is composed of nonlinear first-order hyperbolic equations describing the dynamics of the amphibian population where individuals are divided into juveniles (tadpoles) and adults (frogs). To solve the least-squares problem, an explicit finite difference approximation is developed. Convergence results for the computed parameters are presented. Parameter estimates for the vital rates of juveniles and adults are obtained, and standard deviations for these estimates are computed. Numerical results for the model sensitivity with respect to these parameters are given. Finally, the above-mentioned parameter estimates are used to illustrate the long-time behavior of the population under investigation.
","language":"English","publisher":"Springer Link","doi":"10.1007/s11538-011-9682-0","usgsCitation":"Ackleh, A.S., Carter, J., Deng, K., Huang, Q., Pal, N., and Yang, X., 2012, Fitting a structured juvenile-adult model for green tree frogs to population estimates from capture-mark-recapture field data: Bulletin of Mathematical Biology, v. 74, no. 3, p. 641-665, https://doi.org/10.1007/s11538-011-9682-0.","productDescription":"25 p.","startPage":"641","endPage":"665","ipdsId":"IP-032520","costCenters":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"links":[{"id":241621,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"74","issue":"3","noUsgsAuthors":false,"publicationDate":"2011-10-13","publicationStatus":"PW","scienceBaseUri":"505a10c6e4b0c8380cd53dd6","contributors":{"authors":[{"text":"Ackleh, Azmy S.","contributorId":119949,"corporation":false,"usgs":true,"family":"Ackleh","given":"Azmy","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":436663,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carter, J. 0000-0003-0110-0284 carterj@usgs.gov","orcid":"https://orcid.org/0000-0003-0110-0284","contributorId":81839,"corporation":false,"usgs":true,"family":"Carter","given":"J.","email":"carterj@usgs.gov","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":436668,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Deng, Keng","contributorId":119746,"corporation":false,"usgs":true,"family":"Deng","given":"Keng","email":"","affiliations":[],"preferred":false,"id":436665,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Huang, Qihua","contributorId":119159,"corporation":false,"usgs":true,"family":"Huang","given":"Qihua","email":"","affiliations":[],"preferred":false,"id":436664,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pal, Nabendu","contributorId":119796,"corporation":false,"usgs":true,"family":"Pal","given":"Nabendu","email":"","affiliations":[],"preferred":false,"id":436667,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Yang, Xing","contributorId":116164,"corporation":false,"usgs":true,"family":"Yang","given":"Xing","email":"","affiliations":[],"preferred":false,"id":436666,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70004913,"text":"70004913 - 2012 - Development and use of a floristic quality index for coastal Louisiana marshes","interactions":[],"lastModifiedDate":"2019-08-27T11:34:45","indexId":"70004913","displayToPublicDate":"2011-06-10T11:30:03","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1552,"text":"Environmental Monitoring and Assessment","onlineIssn":"1573-2959","printIssn":"0167-6369","active":true,"publicationSubtype":{"id":10}},"title":"Development and use of a floristic quality index for coastal Louisiana marshes","docAbstract":"The Floristic Quality Index (FQI) has been used as a tool for assessing the integrity of plant communities and for assessing restoration projects in many regions of the USA. Here, we develop a modified FQI (FQImod) for coastal Louisiana wetlands and verify it using 12 years of monitoring data from a coastal restoration project. Plant species that occur in coastal Louisiana were assigned a coefficient of conservatism (CC) score by a local group with expertise in Louisiana coastal vegetation. Species percent cover and both native and non-native species were included in the FQImod which was scaled from 0?100. The FQImod scores from the long-term monitoring project demonstrated the utility of this index for assessing wetland condition over time, including its sensitivity to a hurricane. Ultimately, the FQI developed for coastal Louisiana will be used in conjunction with other wetland indices (e.g., hydrology and soils) to assess wetland condition coastwide and these indices will aid managers in coastal restoration and management decisions.","language":"English","publisher":"Springer","doi":"10.1007/s10661-011-2125-4","usgsCitation":"Visser, M.J., Cretini, K., Krauss, K.W., and Steyer, G.D., 2012, Development and use of a floristic quality index for coastal Louisiana marshes: Environmental Monitoring and Assessment, v. 184, no. 4, p. 2389-2403, https://doi.org/10.1007/s10661-011-2125-4.","productDescription":"15 p.","startPage":"2389","endPage":"2403","ipdsId":"IP-020272","costCenters":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"links":[{"id":366962,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.80224609374999,\n 30.496017831341284\n ],\n [\n -90.63720703125,\n 30.458144351018078\n ],\n [\n -90.7470703125,\n 30.097613277217132\n ],\n [\n -91.47216796875,\n 30.097613277217132\n ],\n [\n -92.548828125,\n 30.221101852485987\n ],\n [\n -93.69140625,\n 30.211608223816906\n ],\n [\n -93.900146484375,\n 29.754839972510933\n ],\n [\n -93.416748046875,\n 29.735762444449076\n ],\n [\n -93.05419921875,\n 29.735762444449076\n ],\n [\n -92.713623046875,\n 29.563901551414418\n ],\n [\n -92.252197265625,\n 29.48742484748479\n ],\n [\n -92.021484375,\n 29.5830116903775\n ],\n [\n -91.845703125,\n 29.439597566602902\n ],\n [\n -91.549072265625,\n 29.592565403314087\n ],\n [\n -91.56005859375,\n 29.506549442788593\n ],\n [\n -91.351318359375,\n 29.458731185355344\n ],\n [\n -91.38427734374999,\n 29.248063243796576\n ],\n [\n -90.71411132812499,\n 29.142566155107065\n ],\n [\n -90.3955078125,\n 29.34387539941801\n ],\n [\n -90.274658203125,\n 29.0273547804184\n ],\n [\n -89.8681640625,\n 29.23847708592805\n ],\n [\n -89.4287109375,\n 28.8927788645183\n ],\n [\n -88.87939453125,\n 29.152161283318915\n ],\n [\n -89.593505859375,\n 29.5830116903775\n ],\n [\n -89.296875,\n 29.754839972510933\n ],\n [\n -89.088134765625,\n 30.002516938570686\n ],\n [\n -89.307861328125,\n 30.135626231134587\n ],\n [\n -89.593505859375,\n 30.164126343161097\n ],\n [\n -89.80224609374999,\n 30.496017831341284\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"184","issue":"4","noUsgsAuthors":false,"publicationDate":"2011-06-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Visser, M Jenneke Jenneke","contributorId":119531,"corporation":false,"usgs":true,"family":"Visser","given":"M","suffix":"Jenneke","email":"","middleInitial":"Jenneke","affiliations":[],"preferred":false,"id":513238,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cretini, Kari 0000-0003-0419-0748","orcid":"https://orcid.org/0000-0003-0419-0748","contributorId":207226,"corporation":false,"usgs":true,"family":"Cretini","given":"Kari","email":"","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":769360,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Krauss, Ken W. 0000-0003-2195-0729 kraussk@usgs.gov","orcid":"https://orcid.org/0000-0003-2195-0729","contributorId":2017,"corporation":false,"usgs":true,"family":"Krauss","given":"Ken","email":"kraussk@usgs.gov","middleInitial":"W.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":769361,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Steyer, Gregory D. 0000-0001-7231-0110 steyerg@usgs.gov","orcid":"https://orcid.org/0000-0001-7231-0110","contributorId":2856,"corporation":false,"usgs":true,"family":"Steyer","given":"Gregory","email":"steyerg@usgs.gov","middleInitial":"D.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":5064,"text":"Southeast Regional Director's Office","active":true,"usgs":true},{"id":5062,"text":"Office of the Chief Scientist for Ecosystems","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":769362,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70118981,"text":"70118981 - 2012 - MODFLOW-style parameters in underdetermined parameter estimation","interactions":[],"lastModifiedDate":"2024-04-24T16:19:51.813673","indexId":"70118981","displayToPublicDate":"2011-02-25T09:11:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3825,"text":"Groundwater","active":true,"publicationSubtype":{"id":10}},"title":"MODFLOW-style parameters in underdetermined parameter estimation","docAbstract":"In this article, we discuss the use of MODFLOW-Style parameters in the numerical codes MODFLOW_2005 and MODFLOW_2005-Adjoint for the definition of variables in the Layer Property Flow package. Parameters are a useful tool to represent aquifer properties in both codes and are the only option available in the adjoint version. Moreover, for overdetermined parameter estimation problems, the parameter approach for model input can make data input easier. We found that if each estimable parameter is defined by one parameter, the codes require a large computational effort and substantial gains in efficiency are achieved by removing logical comparison of character strings that represent the names and types of the parameters. An alternative formulation already available in the current implementation of the code can also alleviate the efficiency degradation due to character comparisons in the special case of distributed parameters defined through multiplication matrices. The authors also hope that lessons learned in analyzing the performance of the MODFLOW family codes will be enlightening to developers of other Fortran implementations of numerical codes.
","language":"English","publisher":"National Groundwater Association","doi":"10.1111/j.1745-6584.2011.00803.x","usgsCitation":"D’Oria, M.D., and Fienen, M., 2012, MODFLOW-style parameters in underdetermined parameter estimation: Groundwater, v. 50, no. 1, p. 149-153, https://doi.org/10.1111/j.1745-6584.2011.00803.x.","productDescription":"5 p.","startPage":"149","endPage":"153","ipdsId":"IP-016755","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":291560,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"50","issue":"1","noUsgsAuthors":false,"publicationDate":"2011-02-25","publicationStatus":"PW","scienceBaseUri":"53e09e5be4b0beb42bdca469","contributors":{"authors":[{"text":"D’Oria, Marco D.","contributorId":22258,"corporation":false,"usgs":true,"family":"D’Oria","given":"Marco","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":497550,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fienen, Michael N. 0000-0002-7756-4651 mnfienen@usgs.gov","orcid":"https://orcid.org/0000-0002-7756-4651","contributorId":893,"corporation":false,"usgs":true,"family":"Fienen","given":"Michael N.","email":"mnfienen@usgs.gov","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":false,"id":497549,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ]}