Saltwater intrusion in southern Florida poses a potential threat to the public drinking-water supply that is typically monitored using water samples and electromagnetic induction logs collected from a network of wells. Transient electromagnetic (TEM) soundings are a complementary addition to the monitoring program because of their ease of use, low cost, and ability to fill in data gaps between wells. TEM soundings have been used to map saltwater intrusion in the Biscayne aquifer over a large part of south Florida including eastern Miami-Dade County and the Everglades. These two areas are very different with one being urban and the other undeveloped. Each poses different conditions that affect data collection and data quality. In the developed areas, finding sites large enough to make soundings is difficult. The presence of underground pipes further restricts useable locations. Electromagnetic noise, which reduces data quality, is also an issue. In the Everglades, access to field sites is difficult and working in water-covered terrain is challenging. Nonetheless, TEM soundings are an effective tool for mapping saltwater intrusion. Direct estimates of water quality can be obtained from the inverted TEM data using a formation factor determined for the Biscayne aquifer. This formation factor is remarkably constant over Miami-Dade County owing to the uniformity of the aquifer and the absence of clay. Thirty-six TEM soundings were collected in the Model Land area of southeast Miami-Dade County to aid in calibration of a helicopter electromagnetic (HEM) survey. The soundings and HEM survey revealed an area of saltwater intrusion aligned with canals and drainage ditches along U.S. Highway 1 and the Card Sound Road. These canals and ditches likely reduced freshwater levels through unregulated drainage and provided pathways for seawater to flow at least 12.4 km inland.
","language":"English","publisher":"Environmental and Engineering Geophysical","doi":"10.2113/JEEG19.1.33","usgsCitation":"Fitterman, D.V., 2014, Mapping saltwater intrusion in the Biscayne Aquifer, Miami-Dade County, Florida using transient electromagnetic sounding: Journal of Environmental & Engineering Geophysics, v. 19, no. 1, p. 33-43, https://doi.org/10.2113/JEEG19.1.33.","productDescription":"11 p.","startPage":"33","endPage":"43","ipdsId":"IP-044880","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":343166,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","county":"Miami-Dade County","otherGeospatial":"Biscayne Aquifer","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.243896484375,\n 25.088086383542663\n ],\n [\n -80.0848388671875,\n 25.088086383542663\n ],\n [\n -80.0848388671875,\n 25.958044673317843\n ],\n [\n -81.243896484375,\n 25.958044673317843\n ],\n [\n -81.243896484375,\n 25.088086383542663\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"19","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"595611c2e4b0d1f9f05067b0","contributors":{"authors":[{"text":"Fitterman, David V. dfitterman@usgs.gov","contributorId":1106,"corporation":false,"usgs":true,"family":"Fitterman","given":"David","email":"dfitterman@usgs.gov","middleInitial":"V.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":702815,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70187387,"text":"70187387 - 2014 - How much Is enough? Minimal responses of water quality and stream biota to partial retrofit stormwater management in a suburban neighborhood","interactions":[],"lastModifiedDate":"2017-05-01T12:34:52","indexId":"70187387","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"How much Is enough? Minimal responses of water quality and stream biota to partial retrofit stormwater management in a suburban neighborhood","docAbstract":"Decentralized stormwater management approaches (e.g., biofiltration swales, pervious pavement, green roofs, rain gardens) that capture, detain, infiltrate, and filter runoff are now commonly used to minimize the impacts of stormwater runoff from impervious surfaces on aquatic ecosystems. However, there is little research on the effectiveness of retrofit, parcel-scale stormwater management practices for improving downstream aquatic ecosystem health. A reverse auction was used to encourage homeowners to mitigate stormwater on their property within the suburban, 1.8 km2 Shepherd Creek catchment in Cincinnati, Ohio (USA). In 2007–2008, 165 rain barrels and 81 rain gardens were installed on 30% of the properties in four experimental (treatment) subcatchments, and two additional subcatchments were maintained as controls. At the base of the subcatchments, we sampled monthly baseflow water quality, and seasonal (5×/year) physical habitat, periphyton assemblages, and macroinvertebrate assemblages in the streams for the three years before and after treatment implementation. Given the minor reductions in directly connected impervious area from the rain barrel installations (11.6% to 10.4% in the most impaired subcatchment) and high total impervious levels (13.1% to 19.9% in experimental subcatchments), we expected minor or no responses of water quality and biota to stormwater management. There were trends of increased conductivity, iron, and sulfate for control sites, but no such contemporaneous trends for experimental sites. The minor effects of treatment on streamflow volume and water quality did not translate into changes in biotic health, and the few periphyton and macroinvertebrate responses could be explained by factors not associated with the treatment (e.g., vegetation clearing, drought conditions). Improvement of overall stream health is unlikely without additional treatment of major impervious surfaces (including roads, apartment buildings, and parking lots). Further research is needed to define the minimum effect threshold and restoration trajectories for retrofitting catchments to improve the health of stream ecosystems.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0085011","usgsCitation":"Roy, A.H., Rhea, L.K., Mayer, A.L., Shuster, W.D., Beaulieu, J.J., Hopton, M.E., Morrison, M.A., and St. Amand, A.E., 2014, How much Is enough? Minimal responses of water quality and stream biota to partial retrofit stormwater management in a suburban neighborhood: PLoS ONE, v. 9, no. 1, p. 1-14, https://doi.org/10.1371/journal.pone.0085011.","productDescription":"e85011; 14 p.","startPage":"1","endPage":"14","ipdsId":"IP-042659","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":473275,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0085011","text":"Publisher Index Page"},{"id":340670,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Ohio","city":"Cincinnati","volume":"9","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2014-01-17","publicationStatus":"PW","scienceBaseUri":"59084934e4b0fc4e448ffd88","contributors":{"authors":[{"text":"Roy, Allison H. 0000-0002-8080-2729 aroy@usgs.gov","orcid":"https://orcid.org/0000-0002-8080-2729","contributorId":4240,"corporation":false,"usgs":true,"family":"Roy","given":"Allison","email":"aroy@usgs.gov","middleInitial":"H.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":693724,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rhea, Lee K.","contributorId":191662,"corporation":false,"usgs":false,"family":"Rhea","given":"Lee","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":693745,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mayer, Audrey L.","contributorId":191663,"corporation":false,"usgs":false,"family":"Mayer","given":"Audrey","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":693746,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shuster, William D.","contributorId":139413,"corporation":false,"usgs":false,"family":"Shuster","given":"William","email":"","middleInitial":"D.","affiliations":[{"id":12772,"text":"USEPA","active":true,"usgs":false}],"preferred":false,"id":693747,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Beaulieu, Jake J.","contributorId":191664,"corporation":false,"usgs":false,"family":"Beaulieu","given":"Jake","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":693748,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hopton, Matthew E.","contributorId":189133,"corporation":false,"usgs":false,"family":"Hopton","given":"Matthew","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":693749,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Morrison, Matthew A.","contributorId":191665,"corporation":false,"usgs":false,"family":"Morrison","given":"Matthew","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":693750,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"St. Amand, Ann E.","contributorId":146962,"corporation":false,"usgs":false,"family":"St. Amand","given":"Ann","email":"","middleInitial":"E.","affiliations":[{"id":16763,"text":"PhycoTech, Inc.","active":true,"usgs":false}],"preferred":false,"id":693751,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70189207,"text":"70189207 - 2014 - Evaluation of statistically downscaled GCM output as input for hydrological and stream temperature simulation in the Apalachicola–Chattahoochee–Flint River Basin (1961–99)","interactions":[],"lastModifiedDate":"2017-07-05T16:20:39","indexId":"70189207","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1421,"text":"Earth Interactions","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of statistically downscaled GCM output as input for hydrological and stream temperature simulation in the Apalachicola–Chattahoochee–Flint River Basin (1961–99)","docAbstract":"The accuracy of statistically downscaled general circulation model (GCM) simulations of daily surface climate for historical conditions (1961–99) and the implications when they are used to drive hydrologic and stream temperature models were assessed for the Apalachicola–Chattahoochee–Flint River basin (ACFB). The ACFB is a 50 000 km2 basin located in the southeastern United States. Three GCMs were statistically downscaled, using an asynchronous regional regression model (ARRM), to ⅛° grids of daily precipitation and minimum and maximum air temperature. These ARRM-based climate datasets were used as input to the Precipitation-Runoff Modeling System (PRMS), a deterministic, distributed-parameter, physical-process watershed model used to simulate and evaluate the effects of various combinations of climate and land use on watershed response. The ACFB was divided into 258 hydrologic response units (HRUs) in which the components of flow (groundwater, subsurface, and surface) are computed in response to climate, land surface, and subsurface characteristics of the basin. Daily simulations of flow components from PRMS were used with the climate to simulate in-stream water temperatures using the Stream Network Temperature (SNTemp) model, a mechanistic, one-dimensional heat transport model for branched stream networks.
The climate, hydrology, and stream temperature for historical conditions were evaluated by comparing model outputs produced from historical climate forcings developed from gridded station data (GSD) versus those produced from the three statistically downscaled GCMs using the ARRM methodology. The PRMS and SNTemp models were forced with the GSD and the outputs produced were treated as “truth.” This allowed for a spatial comparison by HRU of the GSD-based output with ARRM-based output. Distributional similarities between GSD- and ARRM-based model outputs were compared using the two-sample Kolmogorov–Smirnov (KS) test in combination with descriptive metrics such as the mean and variance and an evaluation of rare and sustained events. In general, precipitation and streamflow quantities were negatively biased in the downscaled GCM outputs, and results indicate that the downscaled GCM simulations consistently underestimate the largest precipitation events relative to the GSD. The KS test results indicate that ARRM-based air temperatures are similar to GSD at the daily time step for the majority of the ACFB, with perhaps subweekly averaging for stream temperature. Depending on GCM and spatial location, ARRM-based precipitation and streamflow requires averaging of up to 30 days to become similar to the GSD-based output.
Evaluation of the model skill for historical conditions suggests some guidelines for use of future projections; while it seems correct to place greater confidence in evaluation metrics which perform well historically, this does not necessarily mean those metrics will accurately reflect model outputs for future climatic conditions. Results from this study indicate no “best” overall model, but the breadth of analysis can be used to give the product users an indication of the applicability of the results to address their particular problem. Since results for historical conditions indicate that model outputs can have significant biases associated with them, the range in future projections examined in terms of change relative to historical conditions for each individual GCM may be more appropriate.
","language":"English","publisher":"American Meteorological Society","doi":"10.1175/2013EI000554.1","usgsCitation":"Hay, L.E., LaFontaine, J.H., and Markstrom, S.L., 2014, Evaluation of statistically downscaled GCM output as input for hydrological and stream temperature simulation in the Apalachicola–Chattahoochee–Flint River Basin (1961–99): Earth Interactions, v. 18, p. 1-32, https://doi.org/10.1175/2013EI000554.1.","productDescription":"32 p.","startPage":"1","endPage":"32","ipdsId":"IP-052922","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":473306,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1175/2013ei000554.1","text":"Publisher Index Page"},{"id":343366,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida, Georgia","otherGeospatial":"Apalachicola–Chattahoochee–Flint River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -85.60546875,\n 29.6594160549124\n ],\n [\n -83.7158203125,\n 29.6594160549124\n ],\n [\n -83.7158203125,\n 34.470335121217474\n ],\n [\n -85.60546875,\n 34.470335121217474\n ],\n [\n -85.60546875,\n 29.6594160549124\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"18","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2014-04-14","publicationStatus":"PW","scienceBaseUri":"595dfab7e4b0d1f9f056a7a6","contributors":{"authors":[{"text":"Hay, Lauren E. 0000-0003-3763-4595 lhay@usgs.gov","orcid":"https://orcid.org/0000-0003-3763-4595","contributorId":1287,"corporation":false,"usgs":true,"family":"Hay","given":"Lauren","email":"lhay@usgs.gov","middleInitial":"E.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":703494,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"LaFontaine, Jacob H. 0000-0003-4923-2630 jlafonta@usgs.gov","orcid":"https://orcid.org/0000-0003-4923-2630","contributorId":2258,"corporation":false,"usgs":true,"family":"LaFontaine","given":"Jacob","email":"jlafonta@usgs.gov","middleInitial":"H.","affiliations":[{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":703495,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Markstrom, Steven L. 0000-0001-7630-9547 markstro@usgs.gov","orcid":"https://orcid.org/0000-0001-7630-9547","contributorId":146553,"corporation":false,"usgs":true,"family":"Markstrom","given":"Steven","email":"markstro@usgs.gov","middleInitial":"L.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":703496,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70189074,"text":"70189074 - 2014 - Spectroscopy from Space","interactions":[],"lastModifiedDate":"2020-11-05T16:48:04.612491","indexId":"70189074","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3281,"text":"Reviews in Mineralogy and Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Spectroscopy from Space","docAbstract":"This chapter reviews detection of materials on solid and liquid (lakes and ocean) surfaces in the solar system using ultraviolet to infrared spectroscopy from space, or near space (high altitude aircraft on the Earth), or in the case of remote objects, earth-based and earth-orbiting telescopes. Point spectrometers and imaging spectrometers have been probing the surfaces of our solar system for decades. Spacecraft carrying imaging spectrometers are currently in orbit around Mercury, Venus, Earth, Mars, and Saturn, and systems have recently visited Jupiter, comets, asteroids, and one spectrometer-carrying spacecraft is on its way to Pluto. Together these systems are providing a wealth of data that will enable a better understanding of the composition of condensed matter bodies in the solar system.
Minerals, ices, liquids, and other materials have been detected and mapped on the Earth and all planets and/or their satellites where the surface can be observed from space, with the exception of Venus whose thick atmosphere limits surface observation. Basaltic minerals (e.g., pyroxene and olivine) have been detected with spectroscopy on the Earth, Moon, Mars and some asteroids. The greatest mineralogic diversity seen from space is observed on the Earth and Mars. The Earth, with oceans, active tectonic and hydrologic cycles, and biological processes, displays the greatest material diversity including the detection of amorphous and crystalline inorganic materials, organic compounds, water and water ice.
Water ice is a very common mineral throughout the Solar System and has been unambiguously detected or inferred in every planet and/or their moon(s) where good spectroscopic data has been obtained.
In addition to water ice, other molecular solids have been observed in the solar system using spectroscopic methods. Solid carbon dioxide is found on all systems beyond the Earth except Pluto, although CO2 sometimes appears to be trapped in other solids rather than as an ice on some objects. The largest deposits of carbon dioxide ice are found on Mars. Sulfur dioxide ice is found in the Jupiter system. Nitrogen and methane ices are common beyond the Uranian system.
Saturn’s moon Titan probably has the most complex active extra-terrestrial surface chemistry involving organic compounds. Some of the observed or inferred compounds include ices of benzene (C6H6), cyanoacetylene (HC3N), toluene (C7H8), cyanogen (C2N2), acetonitrile (CH3CN), water (H2O), carbon dioxide (CO2), and ammonia (NH3). Confirming compounds on Titan is hampered by its thick smoggy atmosphere, where in relative terms the atmospheric interferences that hamper surface characterization lie between that of Venus and Earth.
In this chapter we exclude discussion of the planets Jupiter, Saturn, Uranus, and Neptune because their thick atmospheres preclude observing the surface, even if surfaces exist. However, we do discuss spectroscopic observations on a number of the extra-terrestrial satellite bodies. Ammonia was predicted on many icy moons but is notably absent among the definitively detected ices with possible exceptions on Charon and possible trace amounts on some of the Saturnian satellites. Comets, storehouses of many compounds that could exist as ices in their nuclei, have only had small amounts of water ice definitively detected on their surfaces from spectroscopy. Only two asteroids have had a direct detection of surface water ice, although its presence can be inferred in others.
","language":"English","publisher":"Mineralogical Society of America","doi":"10.2138/rmg.2014.78.10","usgsCitation":"Clark, R.N., Swayze, G.A., Carlson, R.R., Grundy, W., and Noll, K., 2014, Spectroscopy from Space: Reviews in Mineralogy and Geochemistry, v. 78, no. 1, p. 399-446, https://doi.org/10.2138/rmg.2014.78.10.","productDescription":"48 p.","startPage":"399","endPage":"446","ipdsId":"IP-036673","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":343176,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"78","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2014-02-27","publicationStatus":"PW","scienceBaseUri":"595611b9e4b0d1f9f0506772","contributors":{"authors":[{"text":"Clark, Roger N. 0000-0002-7021-1220 rclark@usgs.gov","orcid":"https://orcid.org/0000-0002-7021-1220","contributorId":515,"corporation":false,"usgs":true,"family":"Clark","given":"Roger","email":"rclark@usgs.gov","middleInitial":"N.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":702780,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Swayze, Gregg A. 0000-0002-1814-7823 gswayze@usgs.gov","orcid":"https://orcid.org/0000-0002-1814-7823","contributorId":518,"corporation":false,"usgs":true,"family":"Swayze","given":"Gregg","email":"gswayze@usgs.gov","middleInitial":"A.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":702779,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Carlson, Robert R.","contributorId":71944,"corporation":false,"usgs":true,"family":"Carlson","given":"Robert","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":702931,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Grundy, Will","contributorId":156333,"corporation":false,"usgs":false,"family":"Grundy","given":"Will","email":"","affiliations":[],"preferred":false,"id":702932,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Noll, Keith","contributorId":193877,"corporation":false,"usgs":false,"family":"Noll","given":"Keith","email":"","affiliations":[],"preferred":false,"id":702933,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70190450,"text":"70190450 - 2014 - Geochemistry of a marine phosphate deposit: A signpost to phosphogenesis","interactions":[],"lastModifiedDate":"2017-09-05T15:01:01","indexId":"70190450","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Geochemistry of a marine phosphate deposit: A signpost to phosphogenesis","docAbstract":"The Permian age Phosphoria Formation in southeastern Idaho and adjoining states represents possibly the largest marine phosphate deposit in the world. The Meade Peak Member, which contains the highest concentrations and amount of carbonate fluorapatite in the formation, was not significantly altered by mechanical reworking during deposition or subsequently by chemical weathering. Thus, its present composition reflects properties of the Phosphoria Sea that were critical to its accumulation and possibly to the accumulation of most major marine phosphate deposits. These properties included the chemistry of the water column, the hydrography, and the level of primary productivity. Calculated accumulation rates of the PO43− and trace nutrients – Cd, Cu, Ni, and Zn – recorded a dynamic upwelling rate of c.30 m year−1 that supported primary productivity of 2g C m−2day−1. High accumulation rates of the hydrogenous redox-sensitive trace metals – Cr, Mo, U, and V – reflect bottom-water redox conditions that were dominantly suboxic, maintained by a balance between the oxidation of ~ 8% of the organic detritus that settled out of the photic zone and advection of bottom water with a residence time of c.10 years. A limited flux into the basin of siliciclastic lithogenous debris contributed further to elevated concentrations of the seawater-derived sediment fractions.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Treatise on geochemistry","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Elsevier","doi":"10.1016/B978-0-08-095975-7.01112-8","usgsCitation":"Piper, D.Z., and Perkins, R., 2014, Geochemistry of a marine phosphate deposit: A signpost to phosphogenesis, chap. of Treatise on geochemistry, v. 13, p. 293-312, https://doi.org/10.1016/B978-0-08-095975-7.01112-8.","productDescription":"20 p.","startPage":"293","endPage":"312","ipdsId":"IP-027826","costCenters":[{"id":662,"text":"Western Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":345471,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59afb79ee4b0e9bde135113b","contributors":{"authors":[{"text":"Piper, David Z. dzpiper@usgs.gov","contributorId":2452,"corporation":false,"usgs":true,"family":"Piper","given":"David","email":"dzpiper@usgs.gov","middleInitial":"Z.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":709223,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Perkins, R.B.","contributorId":49501,"corporation":false,"usgs":true,"family":"Perkins","given":"R.B.","email":"","affiliations":[],"preferred":false,"id":709224,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70189135,"text":"70189135 - 2014 - Carbonate rocks of the Seward Peninsula, Alaska: Their correlation and paleogeographic significance","interactions":[],"lastModifiedDate":"2018-05-07T21:00:10","indexId":"70189135","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1727,"text":"GSA Special Papers","active":true,"publicationSubtype":{"id":10}},"title":"Carbonate rocks of the Seward Peninsula, Alaska: Their correlation and paleogeographic significance","docAbstract":"Paleozoic carbonate strata deposited in shallow platform to off-platform settings occur across the Seward Peninsula and range from unmetamorphosed Ordovician–Devonian(?) rocks of the York succession in the west to highly deformed and metamorphosed Cambrian–Devonian units of the Nome Complex in the east. Faunal and lithologic correlations indicate that early Paleozoic strata in the two areas formed as part of a single carbonate platform.\n\nThe York succession makes up part of the York terrane and consists of Ordovician, lesser Silurian, and limited, possibly Devonian rocks. Shallow-water facies predominate, but subordinate graptolitic shale and calcareous turbidites accumulated in deeper water, intraplatform basin environments, chiefly during the Middle Ordovician. Lower Ordovician strata are mainly lime mudstone and peloid-intraclast grainstone deposited in a deepening upward regime; noncarbonate detritus is abundant in lower parts of the section. Upper Ordovician and Silurian rocks include carbonate mudstone, skeletal wackestone, and coral-stromatoporoid biostromes that are commonly dolomitic and accumulated in warm, shallow to very shallow settings with locally restricted circulation.\n\nThe rest of the York terrane is mainly Ordovician and older, variously deformed and metamorphosed carbonate and siliciclastic rocks intruded by early Cambrian (and younger?) metagabbros. Older (Neoproterozoic–Cambrian) parts of these units are chiefly turbidites and may have been basement for the carbonate platform facies of the York succession; younger, shallow- and deep-water strata likely represent previously unrecognized parts of the York succession and its offshore equivalents. Intensely deformed and altered Mississippian carbonate strata crop out in a small area at the western edge of the terrane.\n\nMetacarbonate rocks form all or part of several units within the blueschist- and greenschist-facies Nome Complex. The Layered sequence includes mafic meta¬igneous rocks and associated calcareous metaturbidites of Ordovician age as well as shallow-water Silurian dolostones. Scattered metacarbonate rocks are chiefly Cambrian, Ordovician, Silurian, and Devonian dolostones that formed in shallow, warm-water settings with locally restricted circulation and marbles of less constrained Paleozoic age. Carbonate metaturbidites occur on the northeast and southeast coasts and yield mainly Silurian and lesser Ordovician and Devonian conodonts; the northern succession also includes debris flows with meter-scale clasts and an argillite interval with Late Ordovician graptolites and lenses of radiolarian chert. Mafic igneous rocks at least partly of Early Devonian age are common in the southern succession.\n\nCarbonate rocks on Seward Peninsula experienced a range of deformational and thermal histories equivalent to those documented in the Brooks Range. Conodont color alteration indices (CAIs) from Seward Peninsula, like those from the Brooks Range, define distinct thermal provinces that likely reflect structural burial. Penetratively deformed high-pressure metamorphic rocks of the Nome Complex (CAIs ≥5) correspond to rocks of the Schist belt in the southern Brooks Range; both record subduction during early stages of the Jurassic–Cretaceous Brooks Range orogeny. Weakly metamorphosed to unmetamorphosed strata of the York terrane (CAIs mainly 2–5), like Brooks Range rocks in the Central belt and structural allochthons to the north, experienced moderate to shallow burial during the main phase of the Brooks Range orogeny. The nature of the contact between the York terrane and the Nome Complex is uncertain; it may be a thrust fault, an extensional surface, or a thrust fault later reactivated as an extensional fault.\n\nLithofacies and biofacies data indicate that, in spite of their divergent Mesozoic histories, rocks of the York terrane and protoliths of the Nome Complex formed as part of the same lower Paleozoic carbonate platform. Stratigraphies in both","language":"English","publisher":"Geological Society of America","doi":"10.1130/2014.2506(03)","usgsCitation":"Dumoulin, J.A., Harris, A., and Repetski, J.E., 2014, Carbonate rocks of the Seward Peninsula, Alaska: Their correlation and paleogeographic significance: GSA Special Papers, v. 506, p. 59-110, https://doi.org/10.1130/2014.2506(03).","productDescription":"52 p.","startPage":"59","endPage":"110","ipdsId":"IP-046076","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":343246,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"506","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59576338e4b0d1f9f051b544","contributors":{"authors":[{"text":"Dumoulin, Julie A. 0000-0003-1754-1287 dumoulin@usgs.gov","orcid":"https://orcid.org/0000-0003-1754-1287","contributorId":203209,"corporation":false,"usgs":true,"family":"Dumoulin","given":"Julie","email":"dumoulin@usgs.gov","middleInitial":"A.","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":703118,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harris, Alta aharris@usgs.gov","contributorId":148394,"corporation":false,"usgs":true,"family":"Harris","given":"Alta","email":"aharris@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":703120,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Repetski, John E. 0000-0002-2298-7120 jrepetski@usgs.gov","orcid":"https://orcid.org/0000-0002-2298-7120","contributorId":2596,"corporation":false,"usgs":true,"family":"Repetski","given":"John","email":"jrepetski@usgs.gov","middleInitial":"E.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":703119,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70189669,"text":"70189669 - 2014 - Transcriptomic effects-based monitoring for endocrine active chemicals: Assessing relative contribution of treated wastewater to downstream pollution","interactions":[],"lastModifiedDate":"2018-09-14T16:02:33","indexId":"70189669","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","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":"Transcriptomic effects-based monitoring for endocrine active chemicals: Assessing relative contribution of treated wastewater to downstream pollution","docAbstract":"The present study investigated whether a combination of targeted analytical chemistry information with unsupervised, data-rich biological methodology (i.e., transcriptomics) could be utilized to evaluate relative contributions of wastewater treatment plant (WWTP) effluents to biological effects. The effects of WWTP effluents on fish exposed to ambient, receiving waters were studied at three locations with distinct WWTP and watershed characteristics. At each location, 4 d exposures of male fathead minnows to the WWTP effluent and upstream and downstream ambient waters were conducted. Transcriptomic analyses were performed on livers using 15 000 feature microarrays, followed by a canonical pathway and gene set enrichment analyses. Enrichment of gene sets indicative of teleost brain–pituitary–gonadal–hepatic (BPGH) axis function indicated that WWTPs serve as an important source of endocrine active chemicals (EACs) that affect the BPGH axis (e.g., cholesterol and steroid metabolism were altered). The results indicated that transcriptomics may even pinpoint pertinent adverse outcomes (i.e., liver vacuolization) and groups of chemicals that preselected chemical analytes may miss. Transcriptomic Effects-Based monitoring was capable of distinguishing sites, and it reflected chemical pollution gradients, thus holding promise for assessment of relative contributions of point sources to pollution and the efficacy of pollution remediation.
","language":"English","publisher":"ACS","doi":"10.1021/es404027n","usgsCitation":"Martinovic-Weigelt, D., Mehinto, A.C., Ankley, G., Denslow, N., Barber, L.B., Lee, K., King, R.J., Schoenfuss, H.L., Schroeder, A.L., and Villeneuve, D.L., 2014, Transcriptomic effects-based monitoring for endocrine active chemicals: Assessing relative contribution of treated wastewater to downstream pollution: Environmental Science & Technology, v. 48, no. 4, p. 2385-2394, https://doi.org/10.1021/es404027n.","productDescription":"10 p.","startPage":"2385","endPage":"2394","ipdsId":"IP-053126","costCenters":[{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":344075,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"48","issue":"4","noUsgsAuthors":false,"publicationDate":"2014-01-10","publicationStatus":"PW","scienceBaseUri":"59706fbce4b0d1f9f065a911","contributors":{"authors":[{"text":"Martinovic-Weigelt, Dalma","contributorId":173655,"corporation":false,"usgs":false,"family":"Martinovic-Weigelt","given":"Dalma","affiliations":[{"id":6748,"text":"University of St. Thomas","active":true,"usgs":false}],"preferred":false,"id":705708,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mehinto, Alvine C.","contributorId":104387,"corporation":false,"usgs":true,"family":"Mehinto","given":"Alvine","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":705709,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ankley, Gerald T.","contributorId":177970,"corporation":false,"usgs":false,"family":"Ankley","given":"Gerald T.","affiliations":[{"id":13485,"text":"U.S. Environmental Protection Agency, Duluth, MN","active":true,"usgs":false}],"preferred":false,"id":705710,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Denslow, Nancy D.","contributorId":72831,"corporation":false,"usgs":true,"family":"Denslow","given":"Nancy D.","affiliations":[],"preferred":false,"id":705711,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Barber, Larry B. 0000-0002-0561-0831 lbbarber@usgs.gov","orcid":"https://orcid.org/0000-0002-0561-0831","contributorId":921,"corporation":false,"usgs":true,"family":"Barber","given":"Larry","email":"lbbarber@usgs.gov","middleInitial":"B.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":705712,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lee, Kathy 0000-0002-7683-1367 klee@usgs.gov","orcid":"https://orcid.org/0000-0002-7683-1367","contributorId":2538,"corporation":false,"usgs":true,"family":"Lee","given":"Kathy","email":"klee@usgs.gov","affiliations":[{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":705713,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"King, Ryan J.","contributorId":194914,"corporation":false,"usgs":false,"family":"King","given":"Ryan","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":705714,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Schoenfuss, Heiko L.","contributorId":76409,"corporation":false,"usgs":false,"family":"Schoenfuss","given":"Heiko","email":"","middleInitial":"L.","affiliations":[{"id":13317,"text":"Saint Cloud State University","active":true,"usgs":false}],"preferred":false,"id":705715,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Schroeder, Anthony L.","contributorId":173596,"corporation":false,"usgs":false,"family":"Schroeder","given":"Anthony","email":"","middleInitial":"L.","affiliations":[{"id":12503,"text":"University of Minnesota - Saint Paul","active":true,"usgs":false},{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":705716,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Villeneuve, Daniel L.","contributorId":32091,"corporation":false,"usgs":false,"family":"Villeneuve","given":"Daniel","email":"","middleInitial":"L.","affiliations":[{"id":13485,"text":"U.S. Environmental Protection Agency, Duluth, MN","active":true,"usgs":false}],"preferred":false,"id":705717,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70188032,"text":"70188032 - 2014 - Detecting emergence, growth, and senescence of wetland vegetation with polarimetric synthetic aperture radar (SAR) data","interactions":[],"lastModifiedDate":"2017-05-31T15:19:27","indexId":"70188032","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Detecting emergence, growth, and senescence of wetland vegetation with polarimetric synthetic aperture radar (SAR) data","docAbstract":"Wetlands provide ecosystem goods and services vitally important to humans. Land managers and policymakers working to conserve wetlands require regularly updated information on the statuses of wetlands across the landscape. However, wetlands are challenging to map remotely with high accuracy and consistency. We investigated the use of multitemporal polarimetric synthetic aperture radar (SAR) data acquired with Canada’s Radarsat-2 system to track within-season changes in wetland vegetation and surface water. We speculated, a priori, how temporal and morphological traits of different types of wetland vegetation should respond over a growing season with respect to four energy-scattering mechanisms. We used ground-based monitoring data and other ancillary information to assess the limits and consistency of the SAR data for tracking seasonal changes in wetlands. We found the traits of different types of vertical emergent wetland vegetation were detected well with the SAR data and corresponded with our anticipated backscatter responses. We also found using data from Landsat’s optical/infrared sensors in conjunction with SAR data helped remove confusion of wetland features with upland grasslands. These results suggest SAR data can provide useful monitoring information on the statuses of wetlands over time.
","language":"English","publisher":"MDPI","doi":"10.3390/w6030694","usgsCitation":"Gallant, A.L., Kaya, S.G., White, L., Brisco, B., Roth, M.F., Sadinski, W.J., and Rover, J., 2014, Detecting emergence, growth, and senescence of wetland vegetation with polarimetric synthetic aperture radar (SAR) data: Water, v. 6, no. 3, p. 694-722, https://doi.org/10.3390/w6030694.","productDescription":"29 p.","startPage":"694","endPage":"722","ipdsId":"IP-053361","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":473304,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w6030694","text":"Publisher Index Page"},{"id":341958,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","issue":"3","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2014-03-24","publicationStatus":"PW","scienceBaseUri":"592fd640e4b0e9bd0ea8970a","contributors":{"authors":[{"text":"Gallant, Alisa L. 0000-0002-3029-6637 gallant@usgs.gov","orcid":"https://orcid.org/0000-0002-3029-6637","contributorId":2940,"corporation":false,"usgs":true,"family":"Gallant","given":"Alisa","email":"gallant@usgs.gov","middleInitial":"L.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":696252,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kaya, Shannon G.","contributorId":192330,"corporation":false,"usgs":false,"family":"Kaya","given":"Shannon","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":696253,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"White, Lori","contributorId":192557,"corporation":false,"usgs":false,"family":"White","given":"Lori","email":"","affiliations":[],"preferred":false,"id":696254,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brisco, Brian","contributorId":37665,"corporation":false,"usgs":true,"family":"Brisco","given":"Brian","email":"","affiliations":[],"preferred":false,"id":696255,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Roth, Mark F. 0000-0001-5095-1865 mroth@usgs.gov","orcid":"https://orcid.org/0000-0001-5095-1865","contributorId":3286,"corporation":false,"usgs":true,"family":"Roth","given":"Mark","email":"mroth@usgs.gov","middleInitial":"F.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":696256,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sadinski, Walter J. wsadinski@usgs.gov","contributorId":3287,"corporation":false,"usgs":true,"family":"Sadinski","given":"Walter","email":"wsadinski@usgs.gov","middleInitial":"J.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":696257,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rover, Jennifer 0000-0002-3437-4030 jrover@usgs.gov","orcid":"https://orcid.org/0000-0002-3437-4030","contributorId":192333,"corporation":false,"usgs":true,"family":"Rover","given":"Jennifer","email":"jrover@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":696258,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70187711,"text":"70187711 - 2014 - Estuarine removal of glacial iron and implications for iron fluxes to the ocean","interactions":[],"lastModifiedDate":"2017-05-15T21:45:19","indexId":"70187711","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Estuarine removal of glacial iron and implications for iron fluxes to the ocean","docAbstract":"While recent work demonstrates that glacial meltwater provides a substantial and relatively labile flux of the micronutrient iron to oceans, the role of high-latitude estuary environments as a potential sink of glacial iron is unknown. Here we present the first quantitative description of iron removal in a meltwater-dominated estuary. We find that 85% of “dissolved” Fe is removed in the low-salinity region of the estuary along with 41% of “total dissolvable” iron associated with glacial flour. We couple these findings with hydrologic and geochemical data from Gulf of Alaska (GoA) glacierized catchments to calculate meltwater-derived fluxes of size and species partitioned Fe to the GoA. Iron flux data indicate that labile iron in the glacial flour and associated Fe minerals dominate the meltwater contribution to the Fe budget of the GoA. As such, GoA nutrient cycles and related ecosystems could be strongly influenced by continued ice loss in its watershed.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2014GL060199","usgsCitation":"Schroth, A.W., Crusius, J., Hoyer, I., and Campbell, R., 2014, Estuarine removal of glacial iron and implications for iron fluxes to the ocean: Geophysical Research Letters, v. 41, no. 11, p. 3951-3958, https://doi.org/10.1002/2014GL060199.","productDescription":"8 p.","startPage":"3951","endPage":"3958","ipdsId":"IP-055771","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":473420,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2014gl060199","text":"Publisher Index Page"},{"id":341327,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"41","issue":"11","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2014-06-06","publicationStatus":"PW","scienceBaseUri":"591abe39e4b0a7fdb43c8bff","contributors":{"authors":[{"text":"Schroth, Andrew W.","contributorId":192042,"corporation":false,"usgs":false,"family":"Schroth","given":"Andrew","email":"","middleInitial":"W.","affiliations":[{"id":17809,"text":"University of Vermont, Burlington","active":true,"usgs":false}],"preferred":false,"id":695218,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Crusius, John 0000-0003-2554-0831 jcrusius@usgs.gov","orcid":"https://orcid.org/0000-0003-2554-0831","contributorId":2155,"corporation":false,"usgs":true,"family":"Crusius","given":"John","email":"jcrusius@usgs.gov","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":695216,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hoyer, Ian","contributorId":192041,"corporation":false,"usgs":false,"family":"Hoyer","given":"Ian","email":"","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":695217,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Campbell, Robert","contributorId":192043,"corporation":false,"usgs":false,"family":"Campbell","given":"Robert","affiliations":[{"id":13600,"text":"Prince William Sound Science Center","active":true,"usgs":false}],"preferred":false,"id":695219,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70186564,"text":"70186564 - 2014 - Self-recognition in corals facilitates deep-sea habitat engineering","interactions":[],"lastModifiedDate":"2017-04-05T16:16:26","indexId":"70186564","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"Self-recognition in corals facilitates deep-sea habitat engineering","docAbstract":"The ability of coral reefs to engineer complex three-dimensional habitats is central to their success and the rich biodiversity they support. In tropical reefs, encrusting coralline algae bind together substrates and dead coral framework to make continuous reef structures, but beyond the photic zone, the cold-water coral Lophelia pertusa also forms large biogenic reefs, facilitated by skeletal fusion. Skeletal fusion in tropical corals can occur in closely related or juvenile individuals as a result of non-aggressive skeletal overgrowth or allogeneic tissue fusion, but contact reactions in many species result in mortality if there is no ‘self-recognition’ on a broad species level. This study reveals areas of ‘flawless’ skeletal fusion in Lophelia pertusa, potentially facilitated by allogeneic tissue fusion, are identified as having small aragonitic crystals or low levels of crystal organisation, and strong molecular bonding. Regardless of the mechanism, the recognition of ‘self’ between adjacent L. pertusa colonies leads to no observable mortality, facilitates ecosystem engineering and reduces aggression-related energetic expenditure in an environment where energy conservation is crucial. The potential for self-recognition at a species level, and subsequent skeletal fusion in framework-forming cold-water corals is an important first step in understanding their significance as ecological engineers in deep-seas worldwide.
","language":"English","publisher":"Nature","doi":"10.1038/srep06782","usgsCitation":"Hennige, S.J., Morrison, C.L., Form, A.U., Buscher, J., Kamenos, N.A., and Roberts, J.M., 2014, Self-recognition in corals facilitates deep-sea habitat engineering: Scientific Reports, v. 4, p. 1-7, https://doi.org/10.1038/srep06782.","productDescription":"Article 6782; 7 p.","startPage":"1","endPage":"7","ipdsId":"IP-052554","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":473433,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/srep06782","text":"Publisher Index Page"},{"id":339271,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"4","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2014-10-27","publicationStatus":"PW","scienceBaseUri":"58e60273e4b09da6799ac68b","contributors":{"authors":[{"text":"Hennige, Sebastian J","contributorId":190561,"corporation":false,"usgs":false,"family":"Hennige","given":"Sebastian","email":"","middleInitial":"J","affiliations":[],"preferred":false,"id":689593,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Morrison, Cheryl L. 0000-0001-9425-691X cmorrison@usgs.gov","orcid":"https://orcid.org/0000-0001-9425-691X","contributorId":146488,"corporation":false,"usgs":true,"family":"Morrison","given":"Cheryl","email":"cmorrison@usgs.gov","middleInitial":"L.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":689592,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Form, Armin U.","contributorId":190562,"corporation":false,"usgs":false,"family":"Form","given":"Armin","email":"","middleInitial":"U.","affiliations":[],"preferred":false,"id":689594,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Buscher, Janina","contributorId":190563,"corporation":false,"usgs":false,"family":"Buscher","given":"Janina","email":"","affiliations":[],"preferred":false,"id":689595,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kamenos, Nicholas A.","contributorId":190564,"corporation":false,"usgs":false,"family":"Kamenos","given":"Nicholas","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":689596,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Roberts, J. Murray","contributorId":190565,"corporation":false,"usgs":false,"family":"Roberts","given":"J.","email":"","middleInitial":"Murray","affiliations":[],"preferred":false,"id":689597,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70187359,"text":"70187359 - 2014 - The temperature-productivity squeeze: Constraints on brook trout growth along an Appalachian river continuum","interactions":[],"lastModifiedDate":"2017-05-04T12:34:08","indexId":"70187359","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1919,"text":"Hydrobiologia","onlineIssn":"1573-5117","printIssn":"0018-8158","active":true,"publicationSubtype":{"id":10}},"title":"The temperature-productivity squeeze: Constraints on brook trout growth along an Appalachian river continuum","docAbstract":"We tested the hypothesis that brook trout growth rates are controlled by a complex interaction of food availability, water temperature, and competitor density. We quantified trout diet, growth, and consumption in small headwater tributaries characterized as cold with low food and high trout density, larger tributaries characterized as cold with moderate food and moderate trout density, and large main stems characterized as warm with high food and low trout density. Brook trout consumption was highest in the main stem where diets shifted from insects in headwaters to fishes and crayfish in larger streams. Despite high water temperatures, trout growth rates also were consistently highest in the main stem, likely due to competitively dominant trout monopolizing thermal refugia. Temporal changes in trout density had a direct negative effect on brook trout growth rates. Our results suggest that competition for food constrains brook trout growth in small streams, but access to thermal refugia in productive main stem habitats enables dominant trout to supplement growth at a watershed scale. Brook trout conservation in this region should seek to relieve the “temperature-productivity squeeze,” whereby brook trout productivity is constrained by access to habitats that provide both suitable water temperature and sufficient prey.
","language":"English","publisher":"Springer","doi":"10.1007/s10750-013-1794-0","usgsCitation":"Petty, J.T., Thorne, D., Huntsman, B.M., and Mazik, P.M., 2014, The temperature-productivity squeeze: Constraints on brook trout growth along an Appalachian river continuum: Hydrobiologia, v. 727, no. 1, p. 151-166, https://doi.org/10.1007/s10750-013-1794-0.","productDescription":"16 p.","startPage":"151","endPage":"166","ipdsId":"IP-042627","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":340823,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"West Virginia","otherGeospatial":"Upper Shaver's Fork","volume":"727","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2013-12-31","publicationStatus":"PW","scienceBaseUri":"590c3dcbe4b0e541a038dd2d","contributors":{"authors":[{"text":"Petty, J. Todd","contributorId":166749,"corporation":false,"usgs":false,"family":"Petty","given":"J.","email":"","middleInitial":"Todd","affiliations":[{"id":24497,"text":"West Virginia University, Morgantown, WV","active":true,"usgs":false}],"preferred":false,"id":693608,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thorne, David","contributorId":191765,"corporation":false,"usgs":false,"family":"Thorne","given":"David","email":"","affiliations":[{"id":24498,"text":"West Virginia Division of Natural Resources, Point Pleasant, WV","active":true,"usgs":false},{"id":25281,"text":"West Virginia University, WV","active":true,"usgs":false}],"preferred":false,"id":694167,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Huntsman, Brock M. 0000-0003-4090-1949","orcid":"https://orcid.org/0000-0003-4090-1949","contributorId":166748,"corporation":false,"usgs":false,"family":"Huntsman","given":"Brock","email":"","middleInitial":"M.","affiliations":[{"id":24497,"text":"West Virginia University, Morgantown, WV","active":true,"usgs":false}],"preferred":false,"id":694168,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mazik, Patricia M. 0000-0002-8046-5929 pmazik@usgs.gov","orcid":"https://orcid.org/0000-0002-8046-5929","contributorId":2318,"corporation":false,"usgs":true,"family":"Mazik","given":"Patricia","email":"pmazik@usgs.gov","middleInitial":"M.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":694169,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70188057,"text":"70188057 - 2014 - Land cover characterization and mapping of South America for the year 2010 using Landsat 30 m satellite data","interactions":[],"lastModifiedDate":"2017-05-30T13:33:33","indexId":"70188057","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Land cover characterization and mapping of South America for the year 2010 using Landsat 30 m satellite data","docAbstract":"Detailed and accurate land cover and land cover change information is needed for South America because the continent is in constant flux, experiencing some of the highest rates of land cover change and forest loss in the world. The land cover data available for the entire continent are too coarse (250 m to 1 km) for resource managers, government and non-government organizations, and Earth scientists to develop conservation strategies, formulate resource management options, and monitor land cover dynamics. We used Landsat 30 m satellite data of 2010 and prepared the land cover database of South America using state-of-the-science remote sensing techniques. We produced regionally consistent and locally relevant land cover information by processing a large volume of data covering the entire continent. Our analysis revealed that in 2010, 50% of South America was covered by forests, 2.5% was covered by water, and 0.02% was covered by snow and ice. The percent forest area of South America varies from 9.5% in Uruguay to 96.5% in French Guiana. We used very high resolution (<5 m) satellite data to validate the land cover product. The overall accuracy of the 2010 South American 30-m land cover map is 89% with a Kappa coefficient of 79%. Accuracy of barren areas needs to improve possibly using multi-temporal Landsat data. An update of land cover and change database of South America with additional land cover classes is needed. The results from this study are useful for developing resource management strategies, formulating biodiversity conservation strategies, and regular land cover monitoring and forecasting.
","language":"English","publisher":"MDPI","doi":"10.3390/rs6109494","usgsCitation":"Giri, C., and Long, J., 2014, Land cover characterization and mapping of South America for the year 2010 using Landsat 30 m satellite data: Remote Sensing, v. 6, no. 10, p. 9494-9510, https://doi.org/10.3390/rs6109494.","productDescription":"17 p.","startPage":"9494","endPage":"9510","ipdsId":"IP-059806","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":473301,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs6109494","text":"Publisher Index Page"},{"id":341862,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"South America","volume":"6","issue":"10","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2014-10-08","publicationStatus":"PW","scienceBaseUri":"592e84c6e4b092b266f10d9f","contributors":{"authors":[{"text":"Giri, Chandra cgiri@usgs.gov","contributorId":189128,"corporation":false,"usgs":true,"family":"Giri","given":"Chandra","email":"cgiri@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":696340,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Long, Jordan 0000-0002-4814-464X jlong@usgs.gov","orcid":"https://orcid.org/0000-0002-4814-464X","contributorId":3609,"corporation":false,"usgs":true,"family":"Long","given":"Jordan","email":"jlong@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":696341,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70186518,"text":"70186518 - 2014 - USGS48 Puerto Rico precipitation - A new isotopic reference material for δ2H and δ18O measurements of water","interactions":[],"lastModifiedDate":"2017-04-05T08:52:41","indexId":"70186518","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2114,"text":"Isotopes in Environmental and Health Studies","active":true,"publicationSubtype":{"id":10}},"title":"USGS48 Puerto Rico precipitation - A new isotopic reference material for δ2H and δ18O measurements of water","docAbstract":"A new secondary isotopic reference material has been prepared from Puerto Rico precipitation, which was filtered, homogenised, loaded into glass ampoules, sealed with a torch, autoclaved to eliminate biological activity, and calibrated by dual-inlet isotope-ratio mass spectrometry. This isotopic reference material, designated as USGS48, is intended to be one of two isotopic reference waters for daily normalisation of stable hydrogen (δ2H) and stable oxygen (δ18O) isotopic analysis of water with a mass spectrometer or a laser absorption spectrometer. The δ2H and δ18O values of this reference water are−2.0±0.4 and−2.224±0.012 ‰, respectively, relative to Vienna Standard Mean Ocean Water on scales normalised such that the δ2H and δ18O values of Standard Light Antarctic Precipitation reference water are−428 and−55.5 ‰, respectively. Each uncertainty is an estimated expanded uncertainty (U=2uc) about the reference value that provides an interval that has about a 95 % probability of encompassing the true value. This isotopic reference water is available by the case of 144 glass ampoules containing 5 mL of water in each ampoule.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/10256016.2014.905555","usgsCitation":"Qi, H., Coplen, T.B., Tarbox, L.V., Lorenz, J.M., and Scholl, M.A., 2014, USGS48 Puerto Rico precipitation - A new isotopic reference material for δ2H and δ18O measurements of water: Isotopes in Environmental and Health Studies, v. 50, no. 4, p. 442-447, https://doi.org/10.1080/10256016.2014.905555.","productDescription":"6 p.","startPage":"442","endPage":"447","ipdsId":"IP-052742","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":339182,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Puerto Rico","volume":"50","issue":"4","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2014-04-16","publicationStatus":"PW","scienceBaseUri":"58e60273e4b09da6799ac68d","contributors":{"authors":[{"text":"Qi, Haiping 0000-0002-8339-744X haipingq@usgs.gov","orcid":"https://orcid.org/0000-0002-8339-744X","contributorId":507,"corporation":false,"usgs":true,"family":"Qi","given":"Haiping","email":"haipingq@usgs.gov","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":688558,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coplen, Tyler B. 0000-0003-4884-6008 tbcoplen@usgs.gov","orcid":"https://orcid.org/0000-0003-4884-6008","contributorId":508,"corporation":false,"usgs":true,"family":"Coplen","given":"Tyler","email":"tbcoplen@usgs.gov","middleInitial":"B.","affiliations":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"preferred":true,"id":688559,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tarbox, Lauren V. 0000-0002-4126-1851 ltarbox@usgs.gov","orcid":"https://orcid.org/0000-0002-4126-1851","contributorId":5319,"corporation":false,"usgs":true,"family":"Tarbox","given":"Lauren","email":"ltarbox@usgs.gov","middleInitial":"V.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":688560,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lorenz, Jennifer M. 0000-0002-5826-7264 jlorenz@usgs.gov","orcid":"https://orcid.org/0000-0002-5826-7264","contributorId":3558,"corporation":false,"usgs":true,"family":"Lorenz","given":"Jennifer","email":"jlorenz@usgs.gov","middleInitial":"M.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":688561,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Scholl, Martha A. 0000-0001-6994-4614 mascholl@usgs.gov","orcid":"https://orcid.org/0000-0001-6994-4614","contributorId":1920,"corporation":false,"usgs":true,"family":"Scholl","given":"Martha","email":"mascholl@usgs.gov","middleInitial":"A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":688562,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70189913,"text":"70189913 - 2014 - Geophysical and hydrologic studies of lake seepage variability","interactions":[],"lastModifiedDate":"2017-08-01T08:32:18","indexId":"70189913","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3825,"text":"Groundwater","active":true,"publicationSubtype":{"id":10}},"title":"Geophysical and hydrologic studies of lake seepage variability","docAbstract":"Variations in lake seepage were studied along a 130 m shoreline of Mirror Lake NH. Seepage was downward from the lake to groundwater; rates measured from 28 seepage meters varied from 0 to −282 cm/d. Causes of this variation were investigated using electrical resistivity surveys and lakebed sediment characterization. Two-dimensional (2D) resistivity surveys showed a transition in lakebed sediments from outwash to till that correlated with high- and low-seepage zones, respectively. However, the 2D survey was not able to predict smaller scale variations within these facies. In the outwash, fast seepage was associated with permeability variations in a thin (2 cm) layer of sediments at the top of the lakebed. In the till, where seepage was slower than that in the outwash, a three-dimensional resistivity survey mapped a point of high seepage associated with heterogeneity (lower resistivity and likely higher permeability). Points of focused flow across the sediment–water interface are difficult to detect and can transmit a large percentage of total exchange. Using a series of electrical resistivity geophysical methods in combination with hydrologic data to locate heterogeneities that affect seepage rates can help guide seepage meter placement. Improving our understanding of the causes and types of heterogeneity in lake seepage will provide better data for lake budgets and prediction of mass transfer of solutes or contaminants between lakes and groundwater.
","language":"English","publisher":"Wiley","doi":"10.1111/gwat.12309","usgsCitation":"Toran, L., Nyquist, J.E., Rosenberry, D.O., Gagliano, M.P., Mitchell, N., and Mikochik, J., 2014, Geophysical and hydrologic studies of lake seepage variability: Groundwater, v. 53, no. 6, p. 841-850, https://doi.org/10.1111/gwat.12309.","productDescription":"10 p.","startPage":"841","endPage":"850","ipdsId":"IP-057392","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":344490,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"53","issue":"6","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2014-12-31","publicationStatus":"PW","scienceBaseUri":"59819316e4b0e2f5d463b7a5","contributors":{"authors":[{"text":"Toran, Laura","contributorId":81622,"corporation":false,"usgs":false,"family":"Toran","given":"Laura","email":"","affiliations":[{"id":34225,"text":"Temple University, Philadelphia, Pa.","active":true,"usgs":false}],"preferred":false,"id":706753,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nyquist, Jonathan E.","contributorId":101801,"corporation":false,"usgs":false,"family":"Nyquist","given":"Jonathan","email":"","middleInitial":"E.","affiliations":[{"id":34225,"text":"Temple University, Philadelphia, Pa.","active":true,"usgs":false}],"preferred":false,"id":706754,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rosenberry, Donald O. 0000-0003-0681-5641 rosenber@usgs.gov","orcid":"https://orcid.org/0000-0003-0681-5641","contributorId":1312,"corporation":false,"usgs":true,"family":"Rosenberry","given":"Donald","email":"rosenber@usgs.gov","middleInitial":"O.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":706752,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gagliano, Michael P.","contributorId":176822,"corporation":false,"usgs":false,"family":"Gagliano","given":"Michael","email":"","middleInitial":"P.","affiliations":[{"id":34225,"text":"Temple University, Philadelphia, Pa.","active":true,"usgs":false}],"preferred":false,"id":706755,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mitchell, Natasha","contributorId":195321,"corporation":false,"usgs":false,"family":"Mitchell","given":"Natasha","email":"","affiliations":[{"id":34225,"text":"Temple University, Philadelphia, Pa.","active":true,"usgs":false}],"preferred":false,"id":706756,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mikochik, James","contributorId":195322,"corporation":false,"usgs":false,"family":"Mikochik","given":"James","email":"","affiliations":[{"id":34225,"text":"Temple University, Philadelphia, Pa.","active":true,"usgs":false}],"preferred":false,"id":706757,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70188035,"text":"70188035 - 2014 - A universal Model-R Coupler to facilitate the use of R functions for model calibration and analysis","interactions":[],"lastModifiedDate":"2017-05-31T14:15:41","indexId":"70188035","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1551,"text":"Environmental Modelling and Software","active":true,"publicationSubtype":{"id":10}},"title":"A universal Model-R Coupler to facilitate the use of R functions for model calibration and analysis","docAbstract":"Mathematical models are useful in various fields of science and engineering. However, it is a challenge to make a model utilize the open and growing functions (e.g., model inversion) on the R platform due to the requirement of accessing and revising the model's source code. To overcome this barrier, we developed a universal tool that aims to convert a model developed in any computer language to an R function using the template and instruction concept of the Parameter ESTimation program (PEST) and the operational structure of the R-Soil and Water Assessment Tool (R-SWAT). The developed tool (Model-R Coupler) is promising because users of any model can connect an external algorithm (written in R) with their model to implement various model behavior analyses (e.g., parameter optimization, sensitivity and uncertainty analysis, performance evaluation, and visualization) without accessing or modifying the model's source code.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.envsoft.2014.08.012","usgsCitation":"Wu, Y., Liu, S., and Yan, W., 2014, A universal Model-R Coupler to facilitate the use of R functions for model calibration and analysis: Environmental Modelling and Software, v. 62, p. 65-69, https://doi.org/10.1016/j.envsoft.2014.08.012.","productDescription":"5 p.","startPage":"65","endPage":"69","ipdsId":"IP-054920","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":341952,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"62","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"592fd640e4b0e9bd0ea89707","contributors":{"authors":[{"text":"Wu, Yiping ywu@usgs.gov","contributorId":987,"corporation":false,"usgs":true,"family":"Wu","given":"Yiping","email":"ywu@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":696283,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Liu, Shuguang 0000-0002-6027-3479 sliu@usgs.gov","orcid":"https://orcid.org/0000-0002-6027-3479","contributorId":147403,"corporation":false,"usgs":true,"family":"Liu","given":"Shuguang","email":"sliu@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":696804,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yan, Wende","contributorId":192438,"corporation":false,"usgs":false,"family":"Yan","given":"Wende","email":"","affiliations":[],"preferred":false,"id":696805,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70187636,"text":"70187636 - 2014 - Combined global change effects on ecosystem processesin nine U.S. topographically complex areas","interactions":[],"lastModifiedDate":"2018-03-16T10:20:44","indexId":"70187636","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1007,"text":"Biogeochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Combined global change effects on ecosystem processesin nine U.S. topographically complex areas","docAbstract":"Concurrent changes in climate, atmospheric nitrogen (N) deposition, and increasing levels of atmospheric carbon dioxide (CO2) affect ecosystems in complex ways. The DayCent-Chem model was used to investigate the combined effects of these human-caused drivers of change over the period 1980–2075 at seven forested montane and two alpine watersheds in the United States. Net ecosystem production (NEP) increased linearly with increasing N deposition for six out of seven forested watersheds; warming directly increased NEP at only two of these sites. Warming reduced soil organic carbon storage at all sites by increasing heterotrophic respiration. At most sites, warming together with high N deposition increased nitrous oxide (N2O) emissions enough to negate the greenhouse benefit of soil carbon sequestration alone, though there was a net greenhouse gas sink across nearly all sites mainly due to the effect of CO2 fertilization and associated sequestration by plants. Over the simulation period, an increase in atmospheric CO2 from 350 to 600 ppm was the main driver of change in net ecosystem greenhouse gas sequestration at all forested sites and one of two alpine sites, but an additional increase in CO2 from 600 to 760 ppm produced smaller effects. Warming either increased or decreased net greenhouse gas sequestration, depending on the site. The N contribution to net ecosystem greenhouse gas sequestration averaged across forest sites was only 5–7 % and was negligible for the alpine. Stream nitrate (NO3−) fluxes increased sharply with N-loading, primarily at three watersheds where initial N deposition values were high relative to terrestrial N uptake capacity. The simulated results displayed fewer synergistic responses to warming, N-loading, and CO2 fertilization than expected. Overall, simulations with DayCent-Chem suggest individual site characteristics and historical patterns of N deposition are important determinants of forest or alpine ecosystem responses to global change.
","language":"English","publisher":"Springer","doi":"10.1007/s10533-014-9950-9","usgsCitation":"Hartman, M.D., Baron, J., Ewing, H.A., and Weathers, K., 2014, Combined global change effects on ecosystem processesin nine U.S. topographically complex areas: Biogeochemistry, v. 119, no. 1, p. 85-108, https://doi.org/10.1007/s10533-014-9950-9.","productDescription":"24 p.","startPage":"85","endPage":"108","ipdsId":"IP-071832","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":341157,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"119","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2014-01-25","publicationStatus":"PW","scienceBaseUri":"5915495fe4b01a342e691301","contributors":{"authors":[{"text":"Hartman, Melannie D.","contributorId":98836,"corporation":false,"usgs":true,"family":"Hartman","given":"Melannie","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":694872,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baron, Jill S. 0000-0002-5902-6251 jill_baron@usgs.gov","orcid":"https://orcid.org/0000-0002-5902-6251","contributorId":174080,"corporation":false,"usgs":true,"family":"Baron","given":"Jill S.","email":"jill_baron@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":694871,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ewing, Holly A.","contributorId":191962,"corporation":false,"usgs":false,"family":"Ewing","given":"Holly","email":"","middleInitial":"A.","affiliations":[{"id":33413,"text":"Bates College","active":true,"usgs":false}],"preferred":false,"id":694874,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Weathers, Kathleen","contributorId":191961,"corporation":false,"usgs":false,"family":"Weathers","given":"Kathleen","affiliations":[{"id":7188,"text":"Cary Institute of Ecosystem Studies, Millbrook, NY, USA","active":true,"usgs":false}],"preferred":false,"id":694873,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70189677,"text":"70189677 - 2014 - 1.13 – Emerging contaminants","interactions":[],"lastModifiedDate":"2017-07-19T16:21:53","indexId":"70189677","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"1.13 – Emerging contaminants","docAbstract":"Since the Industrial Revolution, a diversity of large-scale chemical innovations has impacted aquatic systems in urban environments. Beginning in the 1990s, there has been a growing scientific interest and public awareness of the effects of the chemicals used in domestic, commercial, industrial, and agricultural applications, referred to in this article as ‘emerging contaminants’ (ECs), on ecosystem and human health. The growing global population and its increasing demands on water supplies in conjunction with climate-induced changes in hydrologic regimes place stress on freshwater resources, resulting in a greater reliance on reuse of reclaimed municipal wastewater treatment plant (WWTP) effluents to meet human and environmental needs. WWTP effluents are a major source of ECs, and it is important to have an understanding of the chemical composition of the reclaimed water, because many ECs are biologically active and the effects of chronic exposure to low concentration complex mixtures are unknown. Several classes of ECs that have been shown to be widespread in the aquatic environment are discussed in this chapter, including surfactants, complexing agents, fragrances, antimicrobials, industrial chemicals, pharmaceuticals, natural and synthetic estrogens, and disinfection byproducts. All of these compounds are biologically active via a variety of modes of action, and can occur in aquatic systems at concentrations ranging from <0.001 to >100 μg l−1.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Comprehensive water quality and purification","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Elsevier","doi":"10.1016/B978-0-12-382182-9.00015-3","usgsCitation":"Barber, L.B., 2014, 1.13 – Emerging contaminants, chap. of Comprehensive water quality and purification, v. 1, p. 245-266, https://doi.org/10.1016/B978-0-12-382182-9.00015-3.","productDescription":"22 p.","startPage":"245","endPage":"266","ipdsId":"IP-042295","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":344083,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59706fbce4b0d1f9f065a903","contributors":{"authors":[{"text":"Barber, Larry B. 0000-0002-0561-0831 lbbarber@usgs.gov","orcid":"https://orcid.org/0000-0002-0561-0831","contributorId":921,"corporation":false,"usgs":true,"family":"Barber","given":"Larry","email":"lbbarber@usgs.gov","middleInitial":"B.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":705747,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70185705,"text":"70185705 - 2014 - Resolving terrestrial ecosystem processes along a subgrid topographic gradient for an earth-system model","interactions":[],"lastModifiedDate":"2017-03-28T09:58:08","indexId":"70185705","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","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":"Resolving terrestrial ecosystem processes along a subgrid topographic gradient for an earth-system model","docAbstract":"Soil moisture is a crucial control on surface water and energy fluxes, vegetation, and soil carbon cycling. Earth-system models (ESMs) generally represent an areal-average soil-moisture state in gridcells at scales of 50–200 km and as a result are not able to capture the nonlinear effects of topographically-controlled subgrid heterogeneity in soil moisture, in particular where wetlands are present. We addressed this deficiency by building a subgrid representation of hillslope-scale topographic gradients, TiHy (Tiled-hillslope Hydrology), into the Geophysical Fluid Dynamics Laboratory (GFDL) land model (LM3). LM3-TiHy models one or more representative hillslope geometries for each gridcell by discretizing them into land model tiles hydrologically coupled along an upland-to-lowland gradient. Each tile has its own surface fluxes, vegetation, and vertically-resolved state variables for soil physics and biogeochemistry. LM3-TiHy simulates a gradient in soil moisture and water-table depth between uplands and lowlands in each gridcell. Three hillslope hydrological regimes appear in non-permafrost regions in the model: wet and poorly-drained, wet and well-drained, and dry; with large, small, and zero wetland area predicted, respectively. Compared to the untiled LM3 in stand-alone experiments, LM3-TiHy simulates similar surface energy and water fluxes in the gridcell-mean. However, in marginally wet regions around the globe, LM3-TiHy simulates shallow groundwater in lowlands, leading to higher evapotranspiration, lower surface temperature, and higher leaf area compared to uplands in the same gridcells. Moreover, more than four-fold larger soil carbon concentrations are simulated globally in lowlands as compared with uplands. We compared water-table depths to those simulated by a recent global model-observational synthesis, and we compared wetland and inundated areas diagnosed from the model to observational datasets. The comparisons demonstrate that LM3-TiHy has the capability to represent some of the controls of these hydrological variables, but also that improvement in parameterization and input datasets are needed for more realistic simulations. We found large sensitivity in model-diagnosed wetland and inundated area to the depth of conductive soil and the parameterization of macroporosity. With improved parameterization and inclusion of peatland biogeochemical processes, the model could provide a new approach to investigating the vulnerability of Boreal peatland carbon to climate change in ESMs.
","language":"English","publisher":"European Geosciences Union","doi":"10.5194/hessd-11-8443-2014","usgsCitation":"Subin, Z., Milly, P., Sulman, B.N., Malyshev, S., and Shevliakova, E., 2014, Resolving terrestrial ecosystem processes along a subgrid topographic gradient for an earth-system model: Hydrology and Earth System Sciences, v. 11, p. 8443-8492, https://doi.org/10.5194/hessd-11-8443-2014.","productDescription":"50 p.","startPage":"8443","endPage":"8492","ipdsId":"IP-056981","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":473315,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.5194/hessd-11-8443-2014","text":"External Repository"},{"id":338439,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58db7631e4b0ee37af29e4a4","contributors":{"authors":[{"text":"Subin, Z M","contributorId":189918,"corporation":false,"usgs":false,"family":"Subin","given":"Z M","affiliations":[],"preferred":false,"id":686473,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Milly, Paul C.D. 0000-0003-4389-3139 cmilly@usgs.gov","orcid":"https://orcid.org/0000-0003-4389-3139","contributorId":2119,"corporation":false,"usgs":true,"family":"Milly","given":"Paul C.D.","email":"cmilly@usgs.gov","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":false,"id":686472,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sulman, B N","contributorId":189919,"corporation":false,"usgs":false,"family":"Sulman","given":"B","email":"","middleInitial":"N","affiliations":[],"preferred":false,"id":686474,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Malyshev, Sergey","contributorId":189177,"corporation":false,"usgs":false,"family":"Malyshev","given":"Sergey","affiliations":[],"preferred":false,"id":686475,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Shevliakova, E","contributorId":189920,"corporation":false,"usgs":false,"family":"Shevliakova","given":"E","affiliations":[],"preferred":false,"id":686476,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70189372,"text":"70189372 - 2014 - Equations for calculating hydrogeochemical reactions of minerals and gases such as CO2 at high pressures and temperatures","interactions":[],"lastModifiedDate":"2017-07-12T09:20:32","indexId":"70189372","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","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}},"displayTitle":"Equations for calculating hydrogeochemical reactions of minerals and gases such as CO2 at high pressures and temperatures","title":"Equations for calculating hydrogeochemical reactions of minerals and gases such as CO2 at high pressures and temperatures","docAbstract":"Calculating the solubility of gases and minerals at the high pressures of carbon capture and storage in geological reservoirs requires an accurate description of the molar volumes of aqueous species and the fugacity coefficients of gases. Existing methods for calculating the molar volumes of aqueous species are limited to a specific concentration matrix (often seawater), have been fit for a limited temperature (below 60 °C) or pressure range, apply only at infinite dilution, or are defined for salts instead of individual ions. A more general and reliable calculation of apparent molar volumes of single ions is presented, based on a modified Redlich–Rosenfeld equation. The modifications consist of (1) using the Born equation to calculate the temperature dependence of the intrinsic volumes, following Helgeson–Kirkham–Flowers (HKF), but with Bradley and Pitzer’s expression for the dielectric permittivity of water, (2) using the pressure dependence of the extended Debye–Hückel equation to constrain the limiting slope of the molar volume with ionic strength, and (3) adopting the convention that the proton has zero volume at all ionic strengths, temperatures and pressures. The modifications substantially reduce the number of fitting parameters, while maintaining or even extending the range of temperature and pressure over which molar volumes can be accurately estimated. The coefficients in the HKF-modified-Redlich–Rosenfeld equation were fitted by least-squares on measured solution densities.
The limiting volume and attraction factor in the Van der Waals equation of state can be estimated with the Peng–Robinson approach from the critical temperature, pressure, and acentric factor of a gas. The Van der Waals equation can then be used to determine the fugacity coefficients for pure gases and gases in a mixture, and the solubility of the gas can be calculated from the fugacity, the molar volume in aqueous solution, and the equilibrium constant. The coefficients for the Peng–Robinson equations are readily available in the literature.
The required equations have been implemented in PHREEQC, version 3, and the parameters for calculating the partial molar volumes and fugacity coefficients have been added to the databases that are distributed with PHREEQC. The ease of use and power of the formulation are illustrated by calculating the solubility of CO2 at high pressures and temperatures, and comparing with well-known examples from the geochemical literature. The equations and parameterizations are suitable for wide application in hydrogeochemical systems, especially in the field of carbon capture and storage.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.gca.2013.10.003","usgsCitation":"Appelo, C., Parkhurst, D.L., and Post, V., 2014, Equations for calculating hydrogeochemical reactions of minerals and gases such as CO2 at high pressures and temperatures: Geochimica et Cosmochimica Acta, v. 125, p. 49-67, https://doi.org/10.1016/j.gca.2013.10.003.","productDescription":"19 p.","startPage":"49","endPage":"67","ipdsId":"IP-041823","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":343643,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"125","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59673544e4b0d1f9f05dd7e1","contributors":{"authors":[{"text":"Appelo, C.A.J.","contributorId":106539,"corporation":false,"usgs":true,"family":"Appelo","given":"C.A.J.","email":"","affiliations":[],"preferred":false,"id":704412,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Parkhurst, David L. 0000-0003-3348-1544 dlpark@usgs.gov","orcid":"https://orcid.org/0000-0003-3348-1544","contributorId":1088,"corporation":false,"usgs":true,"family":"Parkhurst","given":"David","email":"dlpark@usgs.gov","middleInitial":"L.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":704411,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Post, V.E.A.","contributorId":56078,"corporation":false,"usgs":true,"family":"Post","given":"V.E.A.","email":"","affiliations":[],"preferred":false,"id":704445,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70188320,"text":"70188320 - 2014 - Detecting the influence of best management practices on vegetation near ephemeral streams with Landsat data","interactions":[],"lastModifiedDate":"2017-06-06T14:00:55","indexId":"70188320","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3228,"text":"Rangeland Ecology and Management","onlineIssn":"1551-5028","printIssn":"1550-7424","active":true,"publicationSubtype":{"id":10}},"title":"Detecting the influence of best management practices on vegetation near ephemeral streams with Landsat data","docAbstract":"Various best management practices (BMPs) have been implemented on rangelands with the goals of controlling nonpoint source pollution, reducing the impact of livestock in ecologically important riparian areas, and improving grazing distribution. Providing off-stream water sources to livestock in pastures, cross-fencing, and rotational grazing are common rangeland BMPs that have demonstrated success in drawing livestock grazing pressure away from streams. We evaluated the effects of rangeland BMP implementation with six commercial-scale pastures in the northern mixed-grass prairie. Four pastures received a BMP suite consisting of off-stream water, cross-fencing, and deferred-rotation grazing, and two pastures did not receive BMPs. We hypothesized that the BMPs increased the quantity of riparian vegetation cover relative to the conditions in these pastures during the pre-BMP period and to the two pastures that did not receive BMPs. We used a series of 30-m Landsat normalized difference vegetation index (NDVI) images to track the spatial and temporal changes (1984–2010, n = 24) in vegetation cover, to which NDVI has been well correlated. Validation indicated that the remotely sensed signal from in-channel vegetation was representative of ground conditions. The BMP suite was associated with a 15% increase in the in-channel NDVI (0–30 m from stream centerline) and 18% increase in the riparian NDVI (30–180 m from stream center line). Conversely, the in-channel and riparian NDVI of non-BMP pastures declined 30% and 18% over the study period. The majority of change occurred within 2 yr of BMP implementation. The patterns of in-channel NDVI among pastures suggested that BMP implementation likely altered grazing distribution by decreasing the preferential use of riparian and in-channel areas. We demonstrated that satellite imagery time series are useful in retrospectively evaluating the efficacy of conservation practices, providing critical information to guide adaptive management and decision makers.
","language":"English","publisher":"Elsevier","doi":"10.2111/REM-D-12-00185.1","usgsCitation":"Rigge, M.B., Smart, A., Wylie, B.K., and de Van Kamp, K., 2014, Detecting the influence of best management practices on vegetation near ephemeral streams with Landsat data: Rangeland Ecology and Management, v. 67, no. 1, p. 1-8, https://doi.org/10.2111/REM-D-12-00185.1.","productDescription":"8 p.","startPage":"1","endPage":"8","ipdsId":"IP-035745","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":342160,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"67","issue":"1","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5937bf2fe4b0f6c2d0d9c781","contributors":{"authors":[{"text":"Rigge, Matthew B. 0000-0003-4471-8009 mrigge@usgs.gov","orcid":"https://orcid.org/0000-0003-4471-8009","contributorId":751,"corporation":false,"usgs":true,"family":"Rigge","given":"Matthew","email":"mrigge@usgs.gov","middleInitial":"B.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":697194,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smart, Alexander","contributorId":24262,"corporation":false,"usgs":true,"family":"Smart","given":"Alexander","affiliations":[],"preferred":false,"id":697310,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wylie, Bruce K. 0000-0002-7374-1083 wylie@usgs.gov","orcid":"https://orcid.org/0000-0002-7374-1083","contributorId":750,"corporation":false,"usgs":true,"family":"Wylie","given":"Bruce","email":"wylie@usgs.gov","middleInitial":"K.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":697311,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"de Van Kamp, Kendall","contributorId":192662,"corporation":false,"usgs":false,"family":"de Van Kamp","given":"Kendall","email":"","affiliations":[],"preferred":false,"id":697312,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70189562,"text":"70189562 - 2014 - Spatial distribution of mercury in southeastern Alaskan streams influenced by glaciers, wetlands, and salmon","interactions":[],"lastModifiedDate":"2018-10-11T16:38:32","indexId":"70189562","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1555,"text":"Environmental Pollution","active":true,"publicationSubtype":{"id":10}},"title":"Spatial distribution of mercury in southeastern Alaskan streams influenced by glaciers, wetlands, and salmon","docAbstract":"Southeastern Alaska is a remote coastal-maritime ecosystem that is experiencing increased deposition of mercury (Hg) as well as rapid glacier loss. Here we present the results of the first reported survey of total and methyl Hg (MeHg) concentrations in regional streams and biota. Overall, streams draining large wetland areas had higher Hg concentrations in water, mayflies, and juvenile salmon than those from glacially-influenced or recently deglaciated watersheds. Filtered MeHg was positively correlated with wetland abundance. Aqueous Hg occurred predominantly in the particulate fraction of glacier streams but in the filtered fraction of wetland-rich streams. Colonization by anadromous salmon in both glacier and wetland-rich streams may be contributing additional marine-derived Hg. The spatial distribution of Hg in the range of streams presented here shows that watersheds are variably, yet fairly predictably, sensitive to atmospheric and marine inputs of Hg.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.envpol.2013.07.040","usgsCitation":"Nagorski, S.A., Engstrom, D.R., Hudson, J.P., Krabbenhoft, D.P., Hood, E., DeWild, J.F., and Aiken, G.R., 2014, Spatial distribution of mercury in southeastern Alaskan streams influenced by glaciers, wetlands, and salmon: Environmental Pollution, v. 184, p. 62-72, https://doi.org/10.1016/j.envpol.2013.07.040.","productDescription":"11 p.","startPage":"62","endPage":"72","ipdsId":"IP-046100","costCenters":[{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":343945,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -137.274169921875,\n 58.03718871323224\n ],\n [\n -133.79150390625,\n 58.03718871323224\n ],\n [\n -133.79150390625,\n 59.80063426102869\n ],\n [\n -137.274169921875,\n 59.80063426102869\n ],\n [\n -137.274169921875,\n 58.03718871323224\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"184","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"596dcca4e4b0d1f9f062756b","contributors":{"authors":[{"text":"Nagorski, Sonia A.","contributorId":32940,"corporation":false,"usgs":true,"family":"Nagorski","given":"Sonia","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":705191,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Engstrom, Daniel R.","contributorId":82665,"corporation":false,"usgs":true,"family":"Engstrom","given":"Daniel","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":705192,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hudson, John P.","contributorId":171887,"corporation":false,"usgs":false,"family":"Hudson","given":"John","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":705193,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Krabbenhoft, David P. 0000-0003-1964-5020 dpkrabbe@usgs.gov","orcid":"https://orcid.org/0000-0003-1964-5020","contributorId":1658,"corporation":false,"usgs":true,"family":"Krabbenhoft","given":"David","email":"dpkrabbe@usgs.gov","middleInitial":"P.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":705194,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hood, Eran","contributorId":106802,"corporation":false,"usgs":false,"family":"Hood","given":"Eran","affiliations":[],"preferred":false,"id":705195,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"DeWild, John F. 0000-0003-4097-2798 jfdewild@usgs.gov","orcid":"https://orcid.org/0000-0003-4097-2798","contributorId":2525,"corporation":false,"usgs":true,"family":"DeWild","given":"John","email":"jfdewild@usgs.gov","middleInitial":"F.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":705196,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Aiken, George R. 0000-0001-8454-0984 graiken@usgs.gov","orcid":"https://orcid.org/0000-0001-8454-0984","contributorId":1322,"corporation":false,"usgs":true,"family":"Aiken","given":"George","email":"graiken@usgs.gov","middleInitial":"R.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":705197,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70189202,"text":"70189202 - 2014 - Distributed Evaluation of Local Sensitivity Analysis (DELSA), with application to hydrologic models","interactions":[],"lastModifiedDate":"2017-07-05T16:57:14","indexId":"70189202","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Distributed Evaluation of Local Sensitivity Analysis (DELSA), with application to hydrologic models","docAbstract":"This paper presents a hybrid local-global sensitivity analysis method termed the Distributed Evaluation of Local Sensitivity Analysis (DELSA), which is used here to identify important and unimportant parameters and evaluate how model parameter importance changes as parameter values change. DELSA uses derivative-based “local” methods to obtain the distribution of parameter sensitivity across the parameter space, which promotes consideration of sensitivity analysis results in the context of simulated dynamics. This work presents DELSA, discusses how it relates to existing methods, and uses two hydrologic test cases to compare its performance with the popular global, variance-based Sobol' method. The first test case is a simple nonlinear reservoir model with two parameters. The second test case involves five alternative “bucket-style” hydrologic models with up to 14 parameters applied to a medium-sized catchment (200 km2) in the Belgian Ardennes. Results show that in both examples, Sobol' and DELSA identify similar important and unimportant parameters, with DELSA enabling more detailed insight at much lower computational cost. For example, in the real-world problem the time delay in runoff is the most important parameter in all models, but DELSA shows that for about 20% of parameter sets it is not important at all and alternative mechanisms and parameters dominate. Moreover, the time delay was identified as important in regions producing poor model fits, whereas other parameters were identified as more important in regions of the parameter space producing better model fits. The ability to understand how parameter importance varies through parameter space is critical to inform decisions about, for example, additional data collection and model development. The ability to perform such analyses with modest computational requirements provides exciting opportunities to evaluate complicated models as well as many alternative models.
","language":"English","publisher":"AGU","doi":"10.1002/2013WR014063","usgsCitation":"Rakovec, O., Hill, M.C., Clark, M., Weerts, A.H., Teuling, A.J., and Uijlenhoet, R., 2014, Distributed Evaluation of Local Sensitivity Analysis (DELSA), with application to hydrologic models: Water Resources Research, v. 50, no. 1, p. 409-426, https://doi.org/10.1002/2013WR014063.","productDescription":"18 p.","startPage":"409","endPage":"426","ipdsId":"IP-053395","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":487085,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/1808/19328","text":"External Repository"},{"id":343373,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"50","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2014-01-17","publicationStatus":"PW","scienceBaseUri":"595dfab7e4b0d1f9f056a7aa","contributors":{"authors":[{"text":"Rakovec, O.","contributorId":194218,"corporation":false,"usgs":false,"family":"Rakovec","given":"O.","email":"","affiliations":[],"preferred":false,"id":703468,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hill, Mary C. mchill@usgs.gov","contributorId":974,"corporation":false,"usgs":true,"family":"Hill","given":"Mary","email":"mchill@usgs.gov","middleInitial":"C.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":703467,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Clark, M.P.","contributorId":194219,"corporation":false,"usgs":false,"family":"Clark","given":"M.P.","email":"","affiliations":[],"preferred":false,"id":703469,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Weerts, A. H.","contributorId":194220,"corporation":false,"usgs":false,"family":"Weerts","given":"A.","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":703470,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Teuling, A. J.","contributorId":138517,"corporation":false,"usgs":false,"family":"Teuling","given":"A.","email":"","middleInitial":"J.","affiliations":[{"id":6920,"text":"Wageningen University, The Netherlands","active":true,"usgs":false}],"preferred":false,"id":703471,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Uijlenhoet, R.","contributorId":138518,"corporation":false,"usgs":false,"family":"Uijlenhoet","given":"R.","email":"","affiliations":[{"id":6920,"text":"Wageningen University, The Netherlands","active":true,"usgs":false}],"preferred":false,"id":703472,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70189226,"text":"70189226 - 2014 - Effects of iron on optical properties of dissolved organic matter","interactions":[],"lastModifiedDate":"2018-04-02T16:50:30","indexId":"70189226","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","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":"Effects of iron on optical properties of dissolved organic matter","docAbstract":"Iron is a source of interference in the spectroscopic analysis of dissolved organic matter (DOM); however, its effects on commonly employed ultraviolet and visible (UV–vis) light adsorption and fluorescence measurements are poorly defined. Here, we describe the effects of iron(II) and iron(III) on the UV–vis absorption and fluorescence of solutions containing two DOM fractions and two surface water samples. In each case, regardless of DOM composition, UV–vis absorption increased linearly with increasing iron(III). Correction factors were derived using iron(III) absorption coefficients determined at wavelengths commonly used to characterize DOM. Iron(III) addition increased specific UV absorbances (SUVA) and decreased the absorption ratios (E2:E3) and spectral slope ratios (SR) of DOM samples. Both iron(II) and iron(III) quenched DOM fluorescence at pH 6.7. The degree and region of fluorescence quenching varied with the iron:DOC concentration ratio, DOM composition, and pH. Regions of the fluorescence spectra associated with greater DOM conjugation were more susceptible to iron quenching, and DOM fluorescence indices were sensitive to the presence of both forms of iron. Analyses of the excitation–emission matrices using a 7- and 13-component parallel factor analysis (PARAFAC) model showed low PARAFAC sensitivity to iron addition.
","language":"English","publisher":"ACS Publications","doi":"10.1021/es502670r","usgsCitation":"Poulin, B., Ryan, J.N., and Aiken, G.R., 2014, Effects of iron on optical properties of dissolved organic matter: Environmental Science & Technology, v. 48, no. 17, p. 10098-10106, https://doi.org/10.1021/es502670r.","productDescription":"9 p.","startPage":"10098","endPage":"10106","ipdsId":"IP-058675","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":343391,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"48","issue":"17","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2014-08-13","publicationStatus":"PW","scienceBaseUri":"595f4c42e4b0d1f9f057e362","contributors":{"authors":[{"text":"Poulin, Brett 0000-0002-5555-7733 bpoulin@usgs.gov","orcid":"https://orcid.org/0000-0002-5555-7733","contributorId":194253,"corporation":false,"usgs":true,"family":"Poulin","given":"Brett","email":"bpoulin@usgs.gov","affiliations":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":703600,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ryan, Joseph N.","contributorId":54290,"corporation":false,"usgs":false,"family":"Ryan","given":"Joseph","email":"","middleInitial":"N.","affiliations":[{"id":604,"text":"University of Colorado- Boulder","active":false,"usgs":true}],"preferred":false,"id":703602,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Aiken, George R. 0000-0001-8454-0984 graiken@usgs.gov","orcid":"https://orcid.org/0000-0001-8454-0984","contributorId":1322,"corporation":false,"usgs":true,"family":"Aiken","given":"George","email":"graiken@usgs.gov","middleInitial":"R.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":703601,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70189671,"text":"70189671 - 2014 - Identifying non-point sources of endocrine active compounds and their biological impacts in freshwater lakes","interactions":[],"lastModifiedDate":"2018-09-04T16:40:37","indexId":"70189671","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":887,"text":"Archives of Environmental Contamination and Toxicology","active":true,"publicationSubtype":{"id":10}},"title":"Identifying non-point sources of endocrine active compounds and their biological impacts in freshwater lakes","docAbstract":"Contaminants of emerging concern, particularly endocrine active compounds (EACs), have been identified as a threat to aquatic wildlife. However, little is known about the impact of EACs on lakes through groundwater from onsite wastewater treatment systems (OWTS). This study aims to identify specific contributions of OWTS to Sullivan Lake, Minnesota, USA. Lake hydrology, water chemistry, caged bluegill sunfish (Lepomis macrochirus), and larval fathead minnow (Pimephales promelas) exposures were used to assess whether EACs entered the lake through OWTS inflow and the resultant biological impact on fish. Study areas included two OWTS-influenced near-shore sites with native bluegill spawning habitats and two in-lake control sites without nearby EAC sources. Caged bluegill sunfish were analyzed for plasma vitellogenin concentrations, organosomatic indices, and histological pathologies. Surface and porewater was collected from each site and analyzed for EACs. Porewater was also collected for laboratory exposure of larval fathead minnow, before analysis of predator escape performance and gene expression profiles. Chemical analysis showed EACs present at low concentrations at each study site, whereas discrete variations were reported between sites and between summer and fall samplings. Body condition index and liver vacuolization of sunfish were found to differ among study sites as did gene expression in exposed larval fathead minnows. Interestingly, biological exposure data and water chemistry did not match. Therefore, although results highlight the potential impacts of seepage from OWTS, further investigation of mixture effects and life history factor as well as chemical fate is warranted.
","language":"English","publisher":"Springer","doi":"10.1007/s00244-014-0052-4","usgsCitation":"Baker, B.H., Martinovic-Weigelt, D., Ferrey, M.L., Barber, L.B., Writer, J.H., Rosenberry, D.O., Kiesling, R.L., Lundy, J.R., and Schoenfuss, H.L., 2014, Identifying non-point sources of endocrine active compounds and their biological impacts in freshwater lakes: Archives of Environmental Contamination and Toxicology, v. 67, no. 3, p. 374-388, https://doi.org/10.1007/s00244-014-0052-4.","productDescription":"15 p.","startPage":"374","endPage":"388","ipdsId":"IP-057586","costCenters":[{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":344078,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota","county":"Wright County","city":"Maple Lake Township","otherGeospatial":"Sullivan Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.94999265670776,\n 45.217084825093266\n ],\n [\n -93.93267631530762,\n 45.217084825093266\n ],\n [\n -93.93267631530762,\n 45.22789121544507\n ],\n [\n -93.94999265670776,\n 45.22789121544507\n ],\n [\n -93.94999265670776,\n 45.217084825093266\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"67","issue":"3","noUsgsAuthors":false,"publicationDate":"2014-06-29","publicationStatus":"PW","scienceBaseUri":"59706fbce4b0d1f9f065a905","contributors":{"authors":[{"text":"Baker, Beth H.","contributorId":194915,"corporation":false,"usgs":false,"family":"Baker","given":"Beth","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":705718,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Martinovic-Weigelt, Dalma","contributorId":173655,"corporation":false,"usgs":false,"family":"Martinovic-Weigelt","given":"Dalma","affiliations":[{"id":6748,"text":"University of St. Thomas","active":true,"usgs":false}],"preferred":false,"id":705719,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ferrey, Mark L.","contributorId":59912,"corporation":false,"usgs":true,"family":"Ferrey","given":"Mark","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":705720,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barber, Larry B. 0000-0002-0561-0831 lbbarber@usgs.gov","orcid":"https://orcid.org/0000-0002-0561-0831","contributorId":921,"corporation":false,"usgs":true,"family":"Barber","given":"Larry","email":"lbbarber@usgs.gov","middleInitial":"B.","affiliations":[{"id":438,"text":"National Research Program - 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2014 - Bacterial pathogen gene abundance and relation to recreational water quality at seven Great Lakes beaches","interactions":[],"lastModifiedDate":"2017-11-16T16:52:57","indexId":"70194120","displayToPublicDate":"2014-01-01T00:00:00","publicationYear":"2014","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":"Bacterial pathogen gene abundance and relation to recreational water quality at seven Great Lakes beaches","docAbstract":"Quantitative assessment of bacterial pathogens, their geographic variability, and distribution in various matrices at Great Lakes beaches are limited. Quantitative PCR (qPCR) was used to test for genes from E. coli O157:H7 (eaeO157), shiga-toxin producing E. coli (stx2), Campylobacter jejuni (mapA), Shigella spp. (ipaH), and a Salmonella enterica-specific (SE) DNA sequence at seven Great Lakes beaches, in algae, water, and sediment. Overall, detection frequencies were mapA>stx2>ipaH>SE>eaeO157. Results were highly variable among beaches and matrices; some correlations with environmental conditions were observed for mapA, stx2, and ipaH detections. Beach seasonal mean mapA abundance in water was correlated with beach seasonal mean log10E. coli concentration. At one beach, stx2 gene abundance was positively correlated with concurrent daily E. coli concentrations. Concentration distributions for stx2, ipaH, and mapA within algae, sediment, and water were statistically different (Non-Detect and Data Analysis in R). Assuming 10, 50, or 100% of gene copies represented viable and presumably infective cells, a quantitative microbial risk assessment tool developed by Michigan State University indicated a moderate probability of illness for Campylobacter jejuni at the study beaches, especially where recreational water quality criteria were exceeded. Pathogen gene quantification may be useful for beach water quality management.
","language":"English","publisher":"ACS Publications","doi":"10.1021/es5038657","usgsCitation":"Oster, R.J., Wijesinghe, R.U., Fogarty, L.R., Haack, S.K., Fogarty, L.R., Tucker, T.R., and Riley, S., 2014, Bacterial pathogen gene abundance and relation to recreational water quality at seven Great Lakes beaches: Environmental Science & Technology, v. 48, no. 24, p. 14148-14157, https://doi.org/10.1021/es5038657.","productDescription":"10 p.","startPage":"14148","endPage":"14157","ipdsId":"IP-052094","costCenters":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true}],"links":[{"id":349032,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Great Lakes","volume":"48","issue":"24","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2014-11-25","publicationStatus":"PW","scienceBaseUri":"5a6100c8e4b06e28e9c25411","contributors":{"authors":[{"text":"Oster, Ryan J. roster@usgs.gov","contributorId":5483,"corporation":false,"usgs":true,"family":"Oster","given":"Ryan","email":"roster@usgs.gov","middleInitial":"J.","affiliations":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true}],"preferred":true,"id":722157,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wijesinghe, Rasanthi U. rwijesinghe@usgs.gov","contributorId":5484,"corporation":false,"usgs":true,"family":"Wijesinghe","given":"Rasanthi","email":"rwijesinghe@usgs.gov","middleInitial":"U.","affiliations":[],"preferred":true,"id":722158,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fogarty, Lisa Reynolds 0000-0003-0329-3251 lrfogart@usgs.gov","orcid":"https://orcid.org/0000-0003-0329-3251","contributorId":150958,"corporation":false,"usgs":true,"family":"Fogarty","given":"Lisa","email":"lrfogart@usgs.gov","middleInitial":"Reynolds","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":722159,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Haack, Sheridan K. skhaack@usgs.gov","contributorId":1982,"corporation":false,"usgs":true,"family":"Haack","given":"Sheridan","email":"skhaack@usgs.gov","middleInitial":"K.","affiliations":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true}],"preferred":true,"id":722160,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fogarty, Lisa R. 0000-0003-0329-3251 lrfogart@usgs.gov","orcid":"https://orcid.org/0000-0003-0329-3251","contributorId":2053,"corporation":false,"usgs":true,"family":"Fogarty","given":"Lisa","email":"lrfogart@usgs.gov","middleInitial":"R.","affiliations":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true}],"preferred":false,"id":722571,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Tucker, Taaja R. 0000-0003-1534-4677 trtucker@usgs.gov","orcid":"https://orcid.org/0000-0003-1534-4677","contributorId":5172,"corporation":false,"usgs":true,"family":"Tucker","given":"Taaja","email":"trtucker@usgs.gov","middleInitial":"R.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":722161,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Riley, Stephen 0000-0002-8968-8416 sriley@usgs.gov","orcid":"https://orcid.org/0000-0002-8968-8416","contributorId":169479,"corporation":false,"usgs":true,"family":"Riley","given":"Stephen","email":"sriley@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":722162,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ]}