Automated generalization software must accommodate multi-scale representations of hydrographic networks across a variety of geographic landscapes, because scale-related hydrography differences are known to vary in different physical conditions. While generalization algorithms have been tailored to specific regions and landscape conditions by several researchers in recent years, the selection and characterization of regional conditions have not been formally defined nor statistically validated. This paper undertakes a systematic classification of landscape types in the conterminous United States to spatially subset the country into workable units, in preparation for systematic tailoring of generalization workflows that preserve hydrographic characteristics. The classification is based upon elevation, standard deviation of elevation, slope, runoff, drainage and bedrock density, soil and bedrock permeability, area of inland surface water, infiltration-excess of overland flow, and a base flow index. A seven class solution shows low misclassification rates except in areas of high landscape diversity such as the Appalachians, Rocky Mountains, and Western coastal regions.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/23729333.2018.1443759","usgsCitation":"Stanislawski, L.V., Finn, M.P., and Buttenfield, B.P., 2018, Classifying physiographic regimes on terrain and hydrologic factors for adaptive generalization of stream networks: International Journal of Cartography, v. 1, p. 4-21, https://doi.org/10.1080/23729333.2018.1443759.","productDescription":"18 p.","startPage":"4","endPage":"21","ipdsId":"IP-096031","costCenters":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"links":[{"id":356386,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"1","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-20","publicationStatus":"PW","scienceBaseUri":"5b6fc3c4e4b0f5d57878e8d7","contributors":{"authors":[{"text":"Stanislawski, Larry V. 0000-0002-9437-0576 lstan@usgs.gov","orcid":"https://orcid.org/0000-0002-9437-0576","contributorId":3386,"corporation":false,"usgs":true,"family":"Stanislawski","given":"Larry","email":"lstan@usgs.gov","middleInitial":"V.","affiliations":[{"id":404,"text":"NGTOC Rolla","active":true,"usgs":true},{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":742028,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Finn, Michael P. 0000-0003-0415-2194 mfinn@usgs.gov","orcid":"https://orcid.org/0000-0003-0415-2194","contributorId":2657,"corporation":false,"usgs":true,"family":"Finn","given":"Michael","email":"mfinn@usgs.gov","middleInitial":"P.","affiliations":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true},{"id":5047,"text":"NGTOC Denver","active":true,"usgs":true}],"preferred":true,"id":742029,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Buttenfield, Barbara P.","contributorId":184069,"corporation":false,"usgs":false,"family":"Buttenfield","given":"Barbara","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":742030,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70198581,"text":"70198581 - 2018 - Stream‐centric methods for determining groundwater contributions in karst mountain watersheds","interactions":[],"lastModifiedDate":"2018-10-23T16:57:20","indexId":"70198581","displayToPublicDate":"2018-08-10T11:28:02","publicationYear":"2018","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":"Stream‐centric methods for determining groundwater contributions in karst mountain watersheds","docAbstract":"Climate change influences on mountain hydrology are uncertain, but likely to be mediated through changes in subsurface hydrologic residence times and flowpaths. The heterogeneity of karst aquifers add complexity in assessing the resiliency of these water sources to perturbation, suggesting a clear need to quantify contributions from and losses to these aquifers. Here we develop a stream centric method that combines mass and flow balances to quantify net and gross gains and losses at different spatial scales. We then extend these methods to differentiate between karst conduit and matrix contributions from the aquifer. In the Logan River watershed in Northern Utah we found significant amounts of the river water repeatedly gained and then lost through a 35 km study reach. Further, the direction and amount of water exchanged varied over space, time, and discharge. Streamflow was dominated by discharge of karst conduit groundwater after runoff with increasing, yet still small, fractions of matrix water later in the summer. These findings were combined with geologic information, prior subsurface dye tracing, and chemical sampling to provide additional lines of evidence that repeated groundwater exchanges are likely occurring and river flows are highly dependent on karst aquifer recharge and discharge. Given the large population dependent on karst aquifers throughout the world, there is a continued need to develop simple methods, like those presented here, for determining the resiliency of karst groundwater resources.
","language":"English","publisher":"AGU","doi":"10.1029/2018WR022664","usgsCitation":"Neilson, B., Tennant, H., Barnes, M., Stout, T., Miller, M.P., Gabor, R.S., Jameel, Y., Millington, M., Gelderloos, A., Bowen, G.J., and Brooks, P.D., 2018, Stream‐centric methods for determining groundwater contributions in karst mountain watersheds: Water Resources Research, v. 54, no. 9, p. 6708-6724, https://doi.org/10.1029/2018WR022664.","productDescription":"17 p.","startPage":"6708","endPage":"6724","ipdsId":"IP-094388","costCenters":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":468507,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2018wr022664","text":"Publisher Index Page"},{"id":356385,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"54","issue":"9","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2018-09-22","publicationStatus":"PW","scienceBaseUri":"5b6fc3c4e4b0f5d57878e8d9","contributors":{"authors":[{"text":"Neilson, Bethany","contributorId":178798,"corporation":false,"usgs":false,"family":"Neilson","given":"Bethany","affiliations":[],"preferred":false,"id":742017,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tennant, Hyrum","contributorId":206880,"corporation":false,"usgs":false,"family":"Tennant","given":"Hyrum","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":742018,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barnes, Michelle","contributorId":206881,"corporation":false,"usgs":false,"family":"Barnes","given":"Michelle","email":"","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":742019,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stout, Trinity","contributorId":206882,"corporation":false,"usgs":false,"family":"Stout","given":"Trinity","email":"","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":742020,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Miller, Matthew P. 0000-0002-2537-1823 mamiller@usgs.gov","orcid":"https://orcid.org/0000-0002-2537-1823","contributorId":3919,"corporation":false,"usgs":true,"family":"Miller","given":"Matthew","email":"mamiller@usgs.gov","middleInitial":"P.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":742016,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gabor, Rachel S.","contributorId":177335,"corporation":false,"usgs":false,"family":"Gabor","given":"Rachel","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":742021,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jameel, Yusef","contributorId":206883,"corporation":false,"usgs":false,"family":"Jameel","given":"Yusef","email":"","affiliations":[{"id":13252,"text":"University of Utah","active":true,"usgs":false}],"preferred":false,"id":742022,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Millington, Mallory","contributorId":206884,"corporation":false,"usgs":false,"family":"Millington","given":"Mallory","email":"","affiliations":[{"id":13252,"text":"University of Utah","active":true,"usgs":false}],"preferred":false,"id":742023,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Gelderloos, Andrew","contributorId":206885,"corporation":false,"usgs":false,"family":"Gelderloos","given":"Andrew","email":"","affiliations":[{"id":13252,"text":"University of Utah","active":true,"usgs":false}],"preferred":false,"id":742024,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Bowen, Gabriel J.","contributorId":138889,"corporation":false,"usgs":false,"family":"Bowen","given":"Gabriel","email":"","middleInitial":"J.","affiliations":[{"id":12566,"text":"Department of Geology and Geophysics, Unviersity of Utah","active":true,"usgs":false}],"preferred":false,"id":742025,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Brooks, Paul D.","contributorId":139471,"corporation":false,"usgs":false,"family":"Brooks","given":"Paul","email":"","middleInitial":"D.","affiliations":[{"id":12566,"text":"Department of Geology and Geophysics, Unviersity of Utah","active":true,"usgs":false}],"preferred":false,"id":742026,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70198576,"text":"70198576 - 2018 - Effect of spatial and temporal scale on simulated groundwater recharge investigations","interactions":[],"lastModifiedDate":"2018-08-10T11:25:15","indexId":"70198576","displayToPublicDate":"2018-08-10T11:21:51","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":664,"text":"Advances in Water Resources","active":true,"publicationSubtype":{"id":10}},"title":"Effect of spatial and temporal scale on simulated groundwater recharge investigations","docAbstract":"Hydrologic model input datasets such as climate, land use, elevation, soil, and geology information are available in a range of scales for use in water resources investigations. Smaller spatial and temporal scale input data allow groundwater recharge models to simulate more physically realistic processes and presumably result in more accurate estimates of groundwater recharge. Projected climate data are, therefore, often downscaled to smaller spatial and temporal scales for use in these models. It is unknown, however, if increasingly smaller-scale climate data produce substantially different simulated recharge results, either in magnitude or trend. Also, even if simulated recharge results are different at a higher space and time resolution, simulation at coarser resolution might be adequate to provide recharge information at decision scales (e.g., meeting Colorado River compact requirements on a ten-year moving average basis). Historical climate datasets at three spatial (∼800 m, ∼4 km, and ∼12 km) and two temporal (daily and monthly) scales were used in a Soil Water Balance (SWB) model of the upper Colorado River basin (UCRB) to simulate groundwater recharge over the water-year 1982–2014 time period. The magnitude of annual and moving ten-year annual average recharge results for daily climate data were within 5% and 7% of ∼4 km results for ∼800 m and ∼12 km climate data, respectively, with deviations from 1982 to 2014 means within 1% and 3% (median), respectively. Comparison of simulated recharge results using the coarsest spatial and temporal climate data with results from the finest scale data indicated similar small differences over ten-year moving annual averages, over water years, and during high recharge months. While differences in simulated groundwater recharge magnitude, which may be important for groundwater-flow simulations, were substantial during some seasonal comparisons, trends in recharge were almost identical across scales, leading to similar conclusions about change from “normal”. Considering the uncertainty inherent in projected climate data, coarser spatial and longer temporal scale input data may be sufficient for water resources managers who need to understand changes in trends in groundwater recharge over water-year or longer time periods.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.advwatres.2018.07.014","usgsCitation":"Tillman, F.D., Pruitt, T., and Gangopadhyay, S., 2018, Effect of spatial and temporal scale on simulated groundwater recharge investigations: Advances in Water Resources, v. 119, p. 257-270, https://doi.org/10.1016/j.advwatres.2018.07.014.","productDescription":"14 p.","startPage":"257","endPage":"270","ipdsId":"IP-087425","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":356384,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Upper Colorado River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.77490234375,\n 36.66841891894786\n ],\n [\n -105.62255859375,\n 36.66841891894786\n ],\n [\n -105.62255859375,\n 43.35713822211053\n ],\n [\n -111.77490234375,\n 43.35713822211053\n ],\n [\n -111.77490234375,\n 36.66841891894786\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"119","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b6fc3c5e4b0f5d57878e8db","contributors":{"authors":[{"text":"Tillman, Fred D. 0000-0002-2922-402X ftillman@usgs.gov","orcid":"https://orcid.org/0000-0002-2922-402X","contributorId":147809,"corporation":false,"usgs":true,"family":"Tillman","given":"Fred","email":"ftillman@usgs.gov","middleInitial":"D.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":741994,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pruitt, Tom 0000-0002-3543-1324","orcid":"https://orcid.org/0000-0002-3543-1324","contributorId":173440,"corporation":false,"usgs":false,"family":"Pruitt","given":"Tom","email":"","affiliations":[{"id":27228,"text":"Reclamation","active":true,"usgs":false}],"preferred":false,"id":741996,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gangopadhyay, Subhrendu 0000-0003-3864-8251","orcid":"https://orcid.org/0000-0003-3864-8251","contributorId":173439,"corporation":false,"usgs":false,"family":"Gangopadhyay","given":"Subhrendu","affiliations":[{"id":7183,"text":"U.S. Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":741995,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70196724,"text":"sir20185063 - 2018 - Mercury methylation and bioaccumulation in Sinclair Inlet, Kitsap County, Washington","interactions":[],"lastModifiedDate":"2019-07-17T13:20:46","indexId":"sir20185063","displayToPublicDate":"2018-08-09T14:30:55","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-5063","title":"Mercury methylation and bioaccumulation in Sinclair Inlet, Kitsap County, Washington","docAbstract":"The U.S. Geological Survey evaluated the transformation of mercury to bioavailable methylmercury in Sinclair Inlet, Kitsap County, Washington, and assessed the effect of the transformation processes on the mercury burden in marine organisms and sediment. In August 2008, samples of sediment, water, and biota from six sites in Sinclair Inlet and three bays representative of Puget Sound embayments were collected. The extensive sediment sampling included analysis of methylmercury in sediment and porewater, estimates of methylation production potential, and analyses of ancillary constituents associated with organic carbon and reduction-oxidation (redox) conditions to assist in interpreting the mercury results. Analyses of methylmercury in water overlying incubated cores provided an estimate of the release of methylmercury to the water column. Collection of samples for mercury species in the aqueous, particulate (suspended solids), and biological phases, and for ancillary carbon and nitrogen constituents in surface water, continued, on about a monthly schedule, at four stations through August 2009. In February, June, and August 2009, seasonal sediment samples were collected at 20 stations distributed between greater Sinclair Inlet and Operable Unit B Marine of the Bremerton naval complex, Bremerton, Washington, to examine geographical and seasonal patterns of mercury biogeochemistry of sediment in Sinclair Inlet. At six of these seasonal sediment stations, porewater was collected and triplicate core incubation experiments were done.
Median sediment-methylmercury concentrations were not statistically different between the representative bays and Sinclair Inlet. The percentage of sediment methylmercury (relative to total mercury) was actually lower in the Sinclair Inlet sites compared with the representative bays, reflecting the higher sediment total mercury concentration for the Sinclair Inlet stations compared with the representative bays. Likewise, median sediment methylmercury concentrations were not statistically different between the greater Sinclair Inlet stations and the Bremerton naval complex stations; whereas the percentage of sediment methylmercury to total mercury was lower in the Bremerton naval complex due to higher sediment total mercury concentrations than the greater Sinclair Inlet stations. The biogeochemical characteristics of each station, measured by redox, organic carbon, and the seasonal availability of nutrients controlled methylmercury biogeochemistry. Mercury methylation production potential was a function of temperature, concentration of total mercury in sediment, and the percentage of ferrous iron (relative to total measured iron) across all sites. Methylmercury porewater concentrations were best described by using concentrations of dissolved organic carbon and reduction-oxidation conditions. Likewise, the variable fluxes of methylmercury from incubated cores were best described using dissolved organic carbon and reduction-oxidation conditions.
Sinclair Inlet exhibited the classic Puget Sound biological cycle, with spring and autumn phytoplankton blooms resulting in depletion of nitrate, orthophosphate, and silicate in the surface water. Although variable in timing between 2008 and 2009, a strong corresponding seasonal trend of increased availability, incorporation, and bioaccumulation of methylmercury into the food web of Sinclair Inlet occurred during the early spring and summer growing season.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185063","collaboration":"Prepared in cooperation with Naval Facilities Engineering Command","usgsCitation":"Paulson, A.J., Marvin-DiPasquale, M.C., Moran, P.W., Stewart, A.R., DeWild, J.F., Toft, J., Agee, J.L., Kakouros, E., Kieu, L.H., Carter, B., Sheibley, R.W., Cordell, J., and Krabbenhoft, D.P., 2018, Mercury methylation and bioaccumulation in Sinclair Inlet, Kitsap County, Washington: U.S. Geological Survey Scientific Investigations Report 2018–5063, 63 p., 1 app., https://doi.org/10.3133/sir20185063.","productDescription":"Report: x, 66 p.; Appendix Tables","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-080527","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":356359,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5063/coverthb.jpg"},{"id":356360,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5063/sir20185063.pdf","text":"Report","size":"7.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5063"},{"id":356361,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2018/5063/sir20185063_appendix01_tables.xls","text":"Tables","size":"111 KB xls","description":"SIR 2018-5063 Appendix Tables"}],"country":"United States","state":"Washington","county":"Kitsap County","otherGeospatial":"Sinclair Inlet","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124,\n 47\n ],\n [\n -122,\n 47\n ],\n [\n -122,\n 49\n ],\n [\n -124,\n 49\n ],\n [\n -124,\n 47\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402
Using a geology-based assessment methodology, the U.S. Geological Survey assessed mean undiscovered, technically recoverable continuous
resources of 1.5 billion barrels of oil and 4.6 trillion cubic feet of gas in the Upper Cretaceous Tuscaloosa marine shale in onshore and State waters of
Louisiana, Mississippi, Alabama, and Florida in the U.S. Gulf Coast region.
Director, Eastern Energy Resources Science Center
U.S. Geological Survey
12201 Sunrise Valley Drive, MS-954
Reston, VA 20192
Understanding changing nutrient concentrations in surface waters requires quantitative information on changing nutrient sources in contributing watersheds. For example, the proportion of nutrient inputs reaching streams and rivers is directly affected by when and where those nutrients enter the landscape. The goal of this report is to contribute to the U.S. Geological Survey’s efforts to describe spatial and temporal patterns in nutrient inputs to the landscape in the Chesapeake Bay watershed, thereby informing efforts to understand changes in riverine and estuarine conditions. The magnitude, spatial variability, and changes over time in nutrient inputs from manure and fertilizer were evaluated in the context of changes in land use and agricultural practices from 1950 through 2012 at three spatial scales: the entire Chesapeake Bay watershed, the 53 8-digit hydrologic units (HUC8s) that are contained within the watershed, and a set of 7 regions that were determined by aggregating geographically similar HUC8s. The expected effect of agricultural best management practices (BMPs) on agricultural nutrient inputs from 1985 through 2012 was also investigated. Nitrogen (N) and phosphorus (P) inputs from manure increased gradually over time at the scale of the entire watershed. Fertilizer-N inputs showed steeper increases, with greater inter-annual fluctuations. Fertilizer-P inputs were less variable, increasing moderately from 1950 through the mid-1970s, and declining thereafter. Nutrient inputs and farming practices varied geographically within the watershed, with implications for the potential impact of these inputs on downstream water quality and ecosystem health. Both temporal and spatial patterns in the intensity of agricultural nutrient inputs were consistent with the magnitude and concentration of livestock and poultry populations and the intensity of row crop agriculture. Reported implementation of the animal and land-use change BMPs that were evaluated were expected to have little effect on agricultural N inputs. Animal BMPs were expected to have a more measurable impact on manure-P inputs, particularly in areas with large poultry populations. Understanding these patterns is important for explaining the changes that have been observed in nutrient loads to the rivers and streams of the Chesapeake Bay watershed, and their impacts on the water quality and ecosystem health of Chesapeake Bay itself.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185022","collaboration":" ","usgsCitation":"Keisman, J.L.D., Devereux, O.H., LaMotte, A.E., Sekellick, A.J., and Blomquist, J.D., 2018, Manure and fertilizer inputs to land in the Chesapeake Bay watershed, 1950–2012: U.S. Geological Survey Scientific Investigations Report 2018–5022, 37 p., https://doi.org/10.3133/sir20185022.","productDescription":"vii, 37 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-081775","costCenters":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"links":[{"id":356307,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5022//sir20185022.pdf","text":"Report","size":"8.29 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5022"},{"id":356306,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5022/coverthb.jpg"}],"country":"United 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U.S. Geological Survey
5522 Research Park Drive
Baltimore, MD 21228
Director, Upper Midwest Water Science Center
U.S. Geological Survey
8505 Research Way
Middleton, WI 53562
Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
Rapid population growth and declining annual recharge to aquifers in the upper Santa Cruz Basin area of southern Arizona, have increased the demand for additional groundwater resources. This demand is predicted to escalate in the future because of higher temperatures, longer droughts, less aquifer recharge, and decreased river and stream base flow. We conducted geologic studies to help evaluate and better understand groundwater resources in the basin. Results of these studies are presented in this report, which summarizes the basin geologic framework and hydrogeology, and presents a threedimensional (3D) hydrogeologic model for the Rio Rico and Nogales 7.5′ quadrangles. Three major hydrogeologic units are displayed in the 3D model; a lower basement confining unit, consisting of Jurassic, Cretaceous, and Tertiary (Paleocene and Oligocene) rocks; a middle unit composed entirely of the Miocene Nogales Formation; and an upper unit consisting of late Miocene to Holocene surficial deposits. The Nogales Formation and the late Miocene to Holocene sediments are the main aquifers in the upper Santa Cruz Basin. The 3D model integrates the hydrogeologic units and faults to define the geometry, structure, and thickness of the aquifer system that provides water to Nogales and surrounding communities of southernmost Arizona. The report includes an EarthVision 3D Viewer, consisting of software enabling the user to view data interactively in 3D space to help explain the internal complexities of the basin geometry, structure, stratigraphy, and hydrology. The 3D model is a synthesis of geologic data from geologic maps, cross sections, and lithologic descriptions and interpretations; and geophysical data including gravity, magnetic data, and airborne electromagnetic data.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185062","usgsCitation":"Page, W.R., Bultman, M.W., VanSistine, D.P., Menges, C.M., Gray, Floyd, and Pantea, M.P., 2018, Geologic framework and hydrogeology of the Rio Rico and Nogales 7.5’ quadrangles, upper Santa Cruz Basin, Arizona, with three-dimensional hydrogeologic model: U.S. Geological Survey Scientific Investigations Report 2018–5062, 34 p., https://doi.org/10.3133/sir20185062.","productDescription":"Report: vi, 34 p.; Data release","onlineOnly":"Y","ipdsId":"IP-085666","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":356167,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5062/coverthb.jpg"},{"id":356184,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7QJ7GHT","text":"USGS data release","linkHelpText":"Data Release for Geologic Framework and Hydrogeology of the Rico Rico and Nogales 7.5' quadrangles, Upper Santa Cruz basin, Arizona, with 3-Dimensional hydrogeologic model"},{"id":356168,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5062/sir20185062.pdf","text":"Report","size":"23.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5062"}],"country":"United States","state":"Arizona","otherGeospatial":"Rio Rico and Nogales 7.5’ Quadrangles, Upper Santa Cruz Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111,\n 31.33\n ],\n [\n -110.875,\n 31.33\n ],\n [\n -110.875,\n 31.5\n ],\n [\n -111,\n 31.5\n ],\n [\n -111,\n 31.33\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Geosciences and Environmental Change Science Center
U.S. Geological Survey
Box 25046, MS 980
Denver, CO 80225
Digital flood-inundation maps for an 8-mile (mi) reach of the Huron River near Hamburg, Michigan (station number 04172000), from downstream of Rickett Road to Strawberry Lake, were created by the U.S. Geological Survey (USGS), in cooperation with Green Oak and Hamburg Townships, Michigan, and the U.S. Army Corps of Engineers. The flood-inundation maps also include a 1.16-mi reach of the Ore Lake Tributary until it joins the Huron River, approximately 2.22 mi downstream of Rickett Road. The flood-inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science website at http://water.usgs.gov/osw/flood_inundation/, depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage on the Huron River near Hamburg, Michigan (station number 04172000). Near real-time stages at this streamgage may be obtained on the Internet from the USGS National Water Information System at http://waterdata.usgs.gov/ or the National Weather Service (NWS) Advanced Hydrologic Prediction Service at http:/water.weather.gov/ahps/. The NWS Advanced Hydrologic Prediction Service also provides forecasted flood hydrographs at this website.
Flood profiles were computed for the stream reach by means of a one-dimensional step-backwater model. The hydraulic model was calibrated by using the current stage-discharge relation at the Huron River near Hamburg, Mich., streamgage and was calibrated to water levels determined with stage sensors (pressure transducers) temporarily deployed along the stream reach. The hydraulic model was used to compute a set of water-surface profiles for flood stages ranging from 7.0 to 10.5 feet (ft). This range represents stages just above 6.0 (bankfull) to 2.04 ft above the maximum recorded stage at the USGS streamgage on the Huron River near Hamburg, Mich. (station number 04172000). The computed water-surface profiles were then combined with a Geographic Information System digital elevation model (derived from light detection and ranging [lidar] data having a 0.49-ft vertical accuracy and 3.8-ft horizontal resolution) to delineate the area flooded at each water level.
The availability of these maps, along with Internet information regarding current stage and forecasted high-flow stages from the NWS, will provide emergency management personnel and residents with information critical for flood-response activities such as evacuations, road closures, and postflood recovery efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185048","collaboration":"Prepared in cooperation with Green Oak and Hamburg Townships, Michigan and the U.S. Army Corps of Engineers","usgsCitation":"Prokopec, J.G., 2018, Hydraulic modeling and flood-inundation mapping for the Huron River and Ore Lake Tributary, Livingston County, Michigan: U.S. Geological Survey Scientific Investigations Report 2018–5048, 13 p., https://doi.org/10.3133/sir20185048.","productDescription":"Report: vii, 13 p.; 2 Data releases","numberOfPages":"24","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-084641","costCenters":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true}],"links":[{"id":437793,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9H1TX91","text":"USGS data release","linkHelpText":"Geospatial data for a Flood-Inundation Mapping Study of the Huron River near Hamburg, Michigan"},{"id":362849,"rank":4,"type":{"id":30,"text":"Data Release"},"url":" https://www.sciencebase.gov/catalog/item/5c953d27e4b09388245a6d33 ","text":"USGS data release","description":"USGS data release","linkHelpText":"Geospatial data for a Flood-Inundation Mapping Study of the Huron River near Hamburg, Michigan"},{"id":356059,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5048/coverthb.jpg"},{"id":356060,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5048/sir20185048.pdf","text":"Report","size":"1.51 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5048"},{"id":356061,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F79G5M11","text":"USGS data release","description":"USGS data release","linkHelpText":"Huron River near Hamburg, Michigan, flood-inundation model and field data"}],"country":"United States","state":"Michigan","county":"Livingston County","otherGeospatial":"Huron River, Ore Lake Tributary","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.84233474731445,\n 42.4333\n ],\n [\n -83.7667,\n 42.4333\n ],\n [\n -83.7667,\n 42.490960223200396\n ],\n [\n -83.84233474731445,\n 42.490960223200396\n ],\n [\n -83.84233474731445,\n 42.4333\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Upper Midwest Water Science Center
U.S. Geological Survey
6520 Mercantile Way
Suite 5
Lansing, MI 48911
Review of previous investigations indicates that potential decreases in groundwater recharge and increased groundwater extraction in the vicinity of the Lower Des Plaines River Valley in Will County, Illinois, may reduce the amount of groundwater flow in the Silurian aquifer in this area. Groundwater discharge from the Silurian aquifer to wetlands in the Lower Des Plaines River Valley plays an important role in sustaining the habitat of the endangered Hine’s emerald dragonfly (Somatochlora hineana). Groundwater modeling performed by previous investigators indicates that increasing the amount of water pumped from the aquifer in support of expanded quarry operations near the Lockport Prairie Nature Preserve has the potential to reduce groundwater discharge to the most productive Hine’s emerald dragonfly habitats in Illinois, potentially degrading the habitat. Model simulations indicate that mitigation procedures designed to artificially enhance groundwater recharge in the vicinity of dragonfly habitats near the Lockport Prairie Nature Preserve are likely to offset the effects of increased pumping. Several areas with smaller, often intermittent populations of Hine’s emerald dragonflies have been identified in other parts of the Lower Des Plaines River Valley and elsewhere in Illinois. Human activities have the potential to produce changes in hydrology and water quality that can threaten all of these habitats.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185074","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Kay, R.T., Gahala, A.M., and Bailey, C., 2018, Assessment of water resources in areas that affect the habitat of the endangered Hine’s emerald dragonfly in the Lower Des Plaines River Valley, Illinois: U.S. Geological Survey Scientific Investigations Report 2018–5074, 104 p., https://doi.org/10.3133/sir20185074.","productDescription":"ix, 104 p.","numberOfPages":"118","onlineOnly":"Y","ipdsId":"IP-084365","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":356231,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5074/coverthb.jpg"},{"id":356232,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5074/sir20185074.pdf","text":"Report","size":"14.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5074"}],"country":"United States","state":"Illinois","otherGeospatial":"Lower Des Plaines River Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.15,\n 41.55\n ],\n [\n -88.05,\n 41.55\n ],\n [\n -88.05,\n 41.65\n ],\n [\n -88.15,\n 41.65\n ],\n [\n -88.15,\n 41.55\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
405 N. Goodwin
Urbana, IL 61801
Calcareous microfossil assemblages in late Holocene sediments from the western Arctic continental shelf provide an important baseline for evaluating the impacts of today’s changing Arctic oceanography. This study compares 14C-dated late Holocene microfaunal assemblages of sediment cores SWERUS-L2-2-PC1, 2-MC4 and 2-KL1 (57 mwd), which record the last 4200 years in the Herald Canyon (Chukchi Sea shelf), and HLY1302-JPC-32, GGC-30, MC-29 (60 mwd), which record the last 3000 years in the Beaufort Sea shelf off the coast of Canada. Foraminiferal and ostracode assemblages are typical of Arctic continental shelf environments with annual sea-ice cover and show relatively small changes in terms of variability of dominant species. Important microfaunal changes in the Beaufort site include a spike in Spiroplectammina biformis coinciding with a decrease in Cassidulina reniforme in the last few centuries suggesting an increase of Pacific Water influence and decreased sea-ice. There is low-amplitude centennial-scale variability in proportions of benthic foraminiferal species, such as C. reniforme. In addition to these species, Cassidulina teretis s.l., Elphidium excavatum clavatum and Stainforthia feylingi are also common at this site. At the Herald Canyon site in the last few centuries, C. reniforme peaks around 150 years BP and then decreases while Spiroplectammina earlandi spikes and Acanthocythereis dunelmensis decreases also suggesting an increase in Pacific Water influence and decreased sea-ice at this site. This site also includes Buccella spp. and Elphidium excavatum clavatum. Differences in benthic foraminifera and ostracode species dominance between the two sites may be due to a greater influence of Pacific Water in the Chukchi shelf, compared to the more distal Beaufort shelf, which is also affected by the Beaufort Gyre and the Mackenzie River.
","language":"English","publisher":"Springer Link","doi":"10.1007/s41063-018-0058-7","usgsCitation":"Seidenstein, J.L., Cronin, T.M., Gemery, L., Keigwin, L., Pearce, C., Jakobsson, M., Coxall, H.K., Wei, E., and Driscoll, N., 2018, Late Holocene paleoceanography in the Chukchi and Beaufort Seas, Arctic Ocean, based on benthic foraminifera and ostracodes: Arktos: The Journal of Arctic Geosciences, v. 4, no. 1, p. 1-17, https://doi.org/10.1007/s41063-018-0058-7.","productDescription":"17 p.","startPage":"1","endPage":"17","ipdsId":"IP-138468","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":399666,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, Russia, United States","otherGeospatial":"Arctic Ocean, Beaufort Sea, Chukchi Sea","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -179.9,\n 69\n ],\n [\n -105.46875,\n 69\n ],\n [\n -105.46875,\n 81.72318761821155\n ],\n [\n -179.9,\n 81.72318761821155\n ],\n [\n -179.9,\n 69\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -178.9453125,\n 64\n ],\n [\n -161.015625,\n 64\n ],\n [\n -161.015625,\n 69\n ],\n [\n -178.9453125,\n 69\n ],\n [\n -178.9453125,\n 64\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"4","issue":"1","noUsgsAuthors":false,"publicationDate":"2018-08-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Seidenstein, Julia Lynn 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Sweden","active":true,"usgs":false}],"preferred":false,"id":841424,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jakobsson, Martin","contributorId":166854,"corporation":false,"usgs":false,"family":"Jakobsson","given":"Martin","email":"","affiliations":[{"id":24562,"text":"Stockholm University","active":true,"usgs":false}],"preferred":false,"id":841425,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Coxall, Helen K","contributorId":290629,"corporation":false,"usgs":false,"family":"Coxall","given":"Helen","email":"","middleInitial":"K","affiliations":[{"id":62460,"text":"Stockholm University, Stockholm Sweden","active":true,"usgs":false}],"preferred":false,"id":841426,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wei, Emily A","contributorId":290630,"corporation":false,"usgs":false,"family":"Wei","given":"Emily A","affiliations":[{"id":62462,"text":"University of California San Diego, La Jolla, CA","active":true,"usgs":false}],"preferred":false,"id":841427,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Driscoll, Neal W.","contributorId":261210,"corporation":false,"usgs":false,"family":"Driscoll","given":"Neal W.","affiliations":[{"id":38264,"text":"Scripps Institution of Oceanography","active":true,"usgs":false}],"preferred":false,"id":841428,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70198562,"text":"70198562 - 2018 - Effects of local shoreline and subestuary watershed condition on waterbird community integrity: Influences of geospatial scale and season in the Chesapeake Bay","interactions":[],"lastModifiedDate":"2018-08-07T16:31:13","indexId":"70198562","displayToPublicDate":"2018-08-07T16:31:09","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1584,"text":"Estuaries and Coasts","active":true,"publicationSubtype":{"id":10}},"title":"Effects of local shoreline and subestuary watershed condition on waterbird community integrity: Influences of geospatial scale and season in the Chesapeake Bay","docAbstract":"In many coastal regions throughout the world, there is increasing pressure to harden shorelines to protect human infrastructures against sea level rise, storm surge, and erosion. This study examines waterbird community integrity in relation to shoreline hardening and land use characteristics at three geospatial scales: (1) the shoreline scale characterized by seven shoreline types: bulkhead, riprap, developed, natural marsh, Phragmites-dominated marsh, sandy beach, and forest; (2) the local subestuary landscape scale including land up to 500 m inland of the shoreline; and (3) the watershed scale >500 m from the shoreline. From 2010 to 2014, we conducted waterbird surveys along the shoreline and open water within 21 subestuaries throughout the Chesapeake Bay during two seasons to encompass post-breeding shorebirds and colonial waterbirds in late summer and migrating and wintering waterfowl in late fall. We employed an Index of Waterbird Community Integrity (IWCI) derived from mean abundance of individual waterbird species and scores of six key species attributes describing each species’ sensitivity to human disturbance, and then used this index to characterize communities in each subestuary and season. IWCI scores ranged from 14.3 to 19.7. Multivariate regression model selection showed that the local shoreline scale had the strongest influence on IWCI scores. At this scale, percent coverage of bulkhead and Phragmites along shorelines were the strongest predictors of IWCI, both with negative relationships. Recursive partitioning revealed that when subestuary shoreline coverage exceeded thresholds of approximately 5% Phragmites or 8% bulkhead, IWCI scores decreased. Our results indicate that development at the shoreline scale has an important effect on waterbird community integrity, and that shoreline hardening and invasive Phragmites each have a negative effect on waterbirds using subestuarine systems.
","language":"English","publisher":"Springer","doi":"10.1007/s12237-017-0288-0","usgsCitation":"Prosser, D.J., Nagel, J.L., Howlin, S., Marban, P., Day, D.D., and Erwin, R., 2018, Effects of local shoreline and subestuary watershed condition on waterbird community integrity: Influences of geospatial scale and season in the Chesapeake Bay: Estuaries and Coasts, v. 41, no. Supplement 1, p. 207-222, https://doi.org/10.1007/s12237-017-0288-0.","productDescription":"16 p.","startPage":"207","endPage":"222","ipdsId":"IP-080893","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":460865,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s12237-017-0288-0","text":"Publisher Index Page"},{"id":437798,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ENV0R9","text":"USGS data release","linkHelpText":"Shoreline delineations for 21 Subestuaries in the Chesapeake Bay 2010-2014."},{"id":437797,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7QR4V9M","text":"USGS data release","linkHelpText":"Effects of local shoreline and subestuary watershed condition on waterbird use: influences of geography, scale, and season in the Chesapeake Bay"},{"id":356317,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Chesapeake Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.1734619140625,\n 36.90597988519294\n ],\n [\n -75.43212890625,\n 36.90597988519294\n ],\n [\n -75.43212890625,\n 39.6606850221923\n ],\n [\n -77.1734619140625,\n 39.6606850221923\n ],\n [\n -77.1734619140625,\n 36.90597988519294\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"41","issue":"Supplement 1","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2017-07-26","publicationStatus":"PW","scienceBaseUri":"5b6fc3d0e4b0f5d57878e8f1","contributors":{"authors":[{"text":"Prosser, Diann J. 0000-0002-5251-1799 dprosser@usgs.gov","orcid":"https://orcid.org/0000-0002-5251-1799","contributorId":2389,"corporation":false,"usgs":true,"family":"Prosser","given":"Diann","email":"dprosser@usgs.gov","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":741933,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nagel, Jessica L. 0000-0002-4437-0324 jnagel@usgs.gov","orcid":"https://orcid.org/0000-0002-4437-0324","contributorId":3976,"corporation":false,"usgs":true,"family":"Nagel","given":"Jessica","email":"jnagel@usgs.gov","middleInitial":"L.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":741934,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Howlin, Shay","contributorId":206848,"corporation":false,"usgs":false,"family":"Howlin","given":"Shay","email":"","affiliations":[{"id":37415,"text":"Western EcoSystems Technology, Cheyenne, WY","active":true,"usgs":false}],"preferred":false,"id":741935,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Marban, Paul 0000-0002-4910-6565 pmarban@usgs.gov","orcid":"https://orcid.org/0000-0002-4910-6565","contributorId":196581,"corporation":false,"usgs":true,"family":"Marban","given":"Paul","email":"pmarban@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":741936,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Day, Daniel D. 0000-0001-9070-7170 dday@usgs.gov","orcid":"https://orcid.org/0000-0001-9070-7170","contributorId":3985,"corporation":false,"usgs":true,"family":"Day","given":"Daniel","email":"dday@usgs.gov","middleInitial":"D.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":741937,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Erwin, R. Michael 0000-0003-2108-9502","orcid":"https://orcid.org/0000-0003-2108-9502","contributorId":196583,"corporation":false,"usgs":false,"family":"Erwin","given":"R. Michael","affiliations":[],"preferred":false,"id":741938,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70198557,"text":"70198557 - 2018 - Impacts of coastal land use and shoreline armoring on estuarine ecosystems: An introduction to a special issue","interactions":[],"lastModifiedDate":"2018-08-07T16:08:25","indexId":"70198557","displayToPublicDate":"2018-08-07T16:08:22","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1584,"text":"Estuaries and Coasts","active":true,"publicationSubtype":{"id":10}},"title":"Impacts of coastal land use and shoreline armoring on estuarine ecosystems: An introduction to a special issue","docAbstract":"The nearshore land-water interface is an important ecological zone that faces anthropogenic pressure from development in coastal regions throughout the world. Coastal waters and estuaries like Chesapeake Bay receive and process land discharges loaded with anthropogenic nutrients and other pollutants that cause eutrophication, hypoxia, and other damage to shallow-water ecosystems. In addition, shorelines are increasingly armored with bulkhead (seawall), riprap, and other structures to protect human infrastructure against the threats of sea-level rise, storm surge, and erosion. Armoring can further influence estuarine and nearshore marine ecosystem functions by degrading water quality, spreading invasive species, and destroying ecologically valuable habitat. These detrimental effects on ecosystem function have ramifications for ecologically and economically important flora and fauna. This special issue of Estuaries and Coasts explores the interacting effects of coastal land use and shoreline armoring on estuarine and coastal marine ecosystems. The majority of papers focus on the Chesapeake Bay region, USA, where 50 major tributaries and an extensive watershed (~ 167,000 km2), provide an ideal model to examine the impacts of human activities at scales ranging from the local shoreline to the entire watershed. The papers consider the influence of watershed land use and natural versus armored shorelines on ecosystem properties and processes as well as on key natural resources.
","language":"English","publisher":"Springer","doi":"10.1007/s12237-017-0331-1","usgsCitation":"Prosser, D.J., Jordan, T.E., Nagel, J.L., Seitz, R.D., Weller, D.E., and Whigham, D.F., 2018, Impacts of coastal land use and shoreline armoring on estuarine ecosystems: An introduction to a special issue: Estuaries and Coasts, v. 41, no. Supplement 1, p. 2-18, https://doi.org/10.1007/s12237-017-0331-1.","productDescription":"17 p.","startPage":"2","endPage":"18","ipdsId":"IP-080892","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":460867,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s12237-017-0331-1","text":"Publisher Index Page"},{"id":356312,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"41","issue":"Supplement 1","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2017-12-18","publicationStatus":"PW","scienceBaseUri":"5b6fc3d3e4b0f5d57878e8f9","contributors":{"authors":[{"text":"Prosser, Diann J. 0000-0002-5251-1799 dprosser@usgs.gov","orcid":"https://orcid.org/0000-0002-5251-1799","contributorId":2389,"corporation":false,"usgs":true,"family":"Prosser","given":"Diann","email":"dprosser@usgs.gov","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":741906,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jordan, Thomas E.","contributorId":206832,"corporation":false,"usgs":false,"family":"Jordan","given":"Thomas","email":"","middleInitial":"E.","affiliations":[{"id":13510,"text":"Smithsonian Environmental Research Center","active":true,"usgs":false}],"preferred":false,"id":741908,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nagel, Jessica L. 0000-0002-4437-0324 jnagel@usgs.gov","orcid":"https://orcid.org/0000-0002-4437-0324","contributorId":3976,"corporation":false,"usgs":true,"family":"Nagel","given":"Jessica","email":"jnagel@usgs.gov","middleInitial":"L.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":741907,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Seitz, Rochelle D.","contributorId":206833,"corporation":false,"usgs":false,"family":"Seitz","given":"Rochelle","email":"","middleInitial":"D.","affiliations":[{"id":37406,"text":"College of William & Mary","active":true,"usgs":false}],"preferred":false,"id":741909,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Weller, Donald E.","contributorId":206834,"corporation":false,"usgs":false,"family":"Weller","given":"Donald","email":"","middleInitial":"E.","affiliations":[{"id":13510,"text":"Smithsonian Environmental Research Center","active":true,"usgs":false}],"preferred":false,"id":741910,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Whigham, Dennis F.","contributorId":206835,"corporation":false,"usgs":false,"family":"Whigham","given":"Dennis","email":"","middleInitial":"F.","affiliations":[{"id":13510,"text":"Smithsonian Environmental Research Center","active":true,"usgs":false}],"preferred":false,"id":741911,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70197345,"text":"70197345 - 2018 - Examination of contaminant exposure and reproduction of ospreys (Pandion haliaetus) nesting in Delaware Bay and River in 2015","interactions":[],"lastModifiedDate":"2018-08-07T12:26:43","indexId":"70197345","displayToPublicDate":"2018-08-07T12:26:40","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Examination of contaminant exposure and reproduction of ospreys (Pandion haliaetus) nesting in Delaware Bay and River in 2015","title":"Examination of contaminant exposure and reproduction of ospreys (Pandion haliaetus) nesting in Delaware Bay and River in 2015","docAbstract":"A study of ospreys (Pandion haliaetus) nesting in the coastal Inland Bays of Delaware, and the Delaware Bay and Delaware River in 2015 examined spatial and temporal trends in contaminant exposure, food web transfer and reproduction. Concentrations of organochlorine pesticides and metabolites, polychlorinated biphenyls (PCBs), coplanar PCB toxic equivalents, polybrominated diphenyl ethers (PBDEs) and other flame retardants in sample eggs were generally greatest in the Delaware River. Concentrations of legacy contaminants in 2015 Delaware Bay eggs were lower than values observed in the 1970s through early 2000s. Several alternative brominated flame retardants were rarely detected, with only TBPH [bis(2-ethylhexyl)-tetrabromophthalate)] present in 5 of 27 samples at <5 ng/g wet weight. No relation was found between p,p′-DDE, total PCBs or total PBDEs in eggs with egg hatching, eggs lost from nests, nestling loss, fledging and nest success. Osprey eggshell thickness recovered to pre-DDT era values, and productivity was adequate to sustain a stable population. Prey fish contaminant concentrations were generally less than those in osprey eggs, with detection frequencies and concentrations greatest in white perch (Morone americana) from Delaware River compared to the Bay. Biomagnification factors from fish to eggs for p,p′-DDE and total PCBs were generally similar to findings from several Chesapeake Bay tributaries. Overall, findings suggest that there have been improvements in Delaware Estuary waterbird habitat compared to the second half of the 20th century. This trend is in part associated with mitigation of some anthropogenic contaminant threats.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2018.05.068","usgsCitation":"Rattner, B.A., Lazarus, R.S., Bean, T.G., McGowan, P.C., Callahan, C.R., Erickson, R.A., and Hale, R., 2018, Examination of contaminant exposure and reproduction of ospreys (Pandion haliaetus) nesting in Delaware Bay and River in 2015: Science of the Total Environment, v. 639, p. 596-607, https://doi.org/10.1016/j.scitotenv.2018.05.068.","productDescription":"12 p.","startPage":"596","endPage":"607","ipdsId":"IP-095078","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":356282,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Delaware Bay and River ","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.69030761718749,\n 38.46219172306828\n ],\n [\n -74.83062744140625,\n 38.46219172306828\n ],\n [\n -74.83062744140625,\n 40.113789191575236\n ],\n [\n -75.69030761718749,\n 40.113789191575236\n ],\n [\n -75.69030761718749,\n 38.46219172306828\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"639","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b6fc3d4e4b0f5d57878e8fd","contributors":{"authors":[{"text":"Rattner, Barnett A. 0000-0003-3676-2843 brattner@usgs.gov","orcid":"https://orcid.org/0000-0003-3676-2843","contributorId":4142,"corporation":false,"usgs":true,"family":"Rattner","given":"Barnett","email":"brattner@usgs.gov","middleInitial":"A.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":736774,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lazarus, Rebecca S. 0000-0003-1731-6469 rlazarus@usgs.gov","orcid":"https://orcid.org/0000-0003-1731-6469","contributorId":205286,"corporation":false,"usgs":false,"family":"Lazarus","given":"Rebecca","email":"rlazarus@usgs.gov","middleInitial":"S.","affiliations":[{"id":27571,"text":"USGS volunteer","active":true,"usgs":false}],"preferred":false,"id":736775,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bean, Thomas G. 0000-0002-3577-1994 tbean@usgs.gov","orcid":"https://orcid.org/0000-0002-3577-1994","contributorId":205287,"corporation":false,"usgs":false,"family":"Bean","given":"Thomas","email":"tbean@usgs.gov","middleInitial":"G.","affiliations":[{"id":33433,"text":"University of Maryland, College Park","active":true,"usgs":false}],"preferred":false,"id":736776,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McGowan, Peter C.","contributorId":13867,"corporation":false,"usgs":false,"family":"McGowan","given":"Peter","email":"","middleInitial":"C.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":736777,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Callahan, Carl R.","contributorId":205289,"corporation":false,"usgs":false,"family":"Callahan","given":"Carl","email":"","middleInitial":"R.","affiliations":[{"id":37073,"text":"USFWS, Annapolis MD","active":true,"usgs":false}],"preferred":false,"id":736780,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Erickson, Richard A. 0000-0003-4649-482X rerickson@usgs.gov","orcid":"https://orcid.org/0000-0003-4649-482X","contributorId":5455,"corporation":false,"usgs":true,"family":"Erickson","given":"Richard","email":"rerickson@usgs.gov","middleInitial":"A.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":736778,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hale, Robert","contributorId":205288,"corporation":false,"usgs":false,"family":"Hale","given":"Robert","affiliations":[{"id":37072,"text":"College of William and Mary, VA","active":true,"usgs":false}],"preferred":false,"id":736779,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70198523,"text":"70198523 - 2018 - Mechanisms of earthquake‐induced chemical and fluid transport to carbonate groundwater springs after earthquakes","interactions":[],"lastModifiedDate":"2018-09-28T09:09:43","indexId":"70198523","displayToPublicDate":"2018-08-06T16:56:13","publicationYear":"2018","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":"Mechanisms of earthquake‐induced chemical and fluid transport to carbonate groundwater springs after earthquakes","docAbstract":"Mechanisms by which hydrochemical changes occur after earthquakes are not well documented. We use the 2016–2017 central Italy seismic sequence, which caused notable hydrochemical transient variations in groundwater springs to address this topic, with special reference to effects on fractured carbonate aquifers. Hydrochemistry measured before and after the earthquakes at four springs at varying distances from the epicenters all showed immediate postmainshock peaks in trace element concentrations but little change in major elements. Most parameters returned to preearthquake values before the last events of the seismic sequence. The source of solutes, particularly trace elements, is longer residence time pore water stored in slow‐moving fractures or abandoned karstic flow paths. These fluids were expelled into the main flow paths after an increase in pore pressure, hydraulic conductivity, and shaking from coseismic aquifer stress. The weak response to the later earthquakes is explained by progressive depletion of high solute fluids as earlier shocks flushed out the stored fluids in the fractures. Spring δ13CDIC values closest to a deep magma source to the west became enriched relative to preearthquake values following the 24 August event. This enrichment indicates input from deeply sourced dissolved CO2 gas after dilation of specific fault conduits. Differences in carbon isotopic responses between springs are attributed to proximity to the deep gaseous CO2 source. Most of the transient chemical changes seen in the three fractured carbonate aquifers are attributed to local shaking and emptying of isolated pores and fractures and are not from rapid upward movement of deep fluids.
","language":"English","publisher":"AGU","doi":"10.1029/2017WR022097","usgsCitation":"Rosen, M.R., Binda, G., Archer, C., Pozzi, A., Michetti, A., and Noble, P., 2018, Mechanisms of earthquake‐induced chemical and fluid transport to carbonate groundwater springs after earthquakes: Water Resources Research, v. 54, no. 8, p. 5225-5244, https://doi.org/10.1029/2017WR022097.","productDescription":"20 p.","startPage":"5225","endPage":"5244","ipdsId":"IP-091568","costCenters":[{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true}],"links":[{"id":468516,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2017wr022097","text":"Publisher Index Page"},{"id":356228,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Italy","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 12.623291015625,\n 42.039094188385945\n ],\n [\n 13.82354736328125,\n 42.039094188385945\n ],\n [\n 13.82354736328125,\n 43.00665566595925\n ],\n [\n 12.623291015625,\n 43.00665566595925\n ],\n [\n 12.623291015625,\n 42.039094188385945\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"54","issue":"8","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-08-06","publicationStatus":"PW","scienceBaseUri":"5b6fc3d4e4b0f5d57878e8ff","contributors":{"authors":[{"text":"Rosen, Michael R. 0000-0003-3991-0522 mrosen@usgs.gov","orcid":"https://orcid.org/0000-0003-3991-0522","contributorId":495,"corporation":false,"usgs":true,"family":"Rosen","given":"Michael","email":"mrosen@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":741777,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Binda, Gilberto 0000-0001-5530-3939","orcid":"https://orcid.org/0000-0001-5530-3939","contributorId":206790,"corporation":false,"usgs":false,"family":"Binda","given":"Gilberto","email":"","affiliations":[{"id":37402,"text":"Università degli Studi dell’Insubria","active":true,"usgs":false}],"preferred":false,"id":741778,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Archer, Claire","contributorId":198952,"corporation":false,"usgs":false,"family":"Archer","given":"Claire","email":"","affiliations":[{"id":33648,"text":"Department of Geological Sciences and Engineering, University of Nevada","active":true,"usgs":false}],"preferred":false,"id":741779,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pozzi, Andrea","contributorId":206791,"corporation":false,"usgs":false,"family":"Pozzi","given":"Andrea","email":"","affiliations":[{"id":37402,"text":"Università degli Studi dell’Insubria","active":true,"usgs":false}],"preferred":false,"id":741780,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Michetti, Alessandro 0000-0002-1775-1340","orcid":"https://orcid.org/0000-0002-1775-1340","contributorId":206792,"corporation":false,"usgs":false,"family":"Michetti","given":"Alessandro","email":"","affiliations":[{"id":37402,"text":"Università degli Studi dell’Insubria","active":true,"usgs":false}],"preferred":false,"id":741781,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Noble, Paula","contributorId":198953,"corporation":false,"usgs":false,"family":"Noble","given":"Paula","affiliations":[{"id":33648,"text":"Department of Geological Sciences and Engineering, University of Nevada","active":true,"usgs":false}],"preferred":false,"id":741782,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70198508,"text":"70198508 - 2018 - The confluences of ideas leading to, and the flow of ideas emerging from, individual-based modeling of riverine fishes","interactions":[],"lastModifiedDate":"2018-08-06T14:53:30","indexId":"70198508","displayToPublicDate":"2018-08-06T14:53:26","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"title":"The confluences of ideas leading to, and the flow of ideas emerging from, individual-based modeling of riverine fishes","docAbstract":"In this review article, we trace the history of events leading to the development of individual-based models (IBMs) to represent aquatic organisms in rivers and streams. As a metaphor, we present this history as a series of confluences between individual scientists (tributaries) sharing ideas. We describe contributions of these models to science and management. One iconic feature of river IBMs is the linkage between flow and the physical habitat experienced by individual animals, and the first model that focused on this linkage is briefly described. We continue by reviewing the contributions of riverine IBMs to eight broad areas of scientific inquiry. The first four areas include research to understand 1) the effects of flow regimes on fish populations, 2) species interactions (e.g., size-mediated competition and predation), 3) fish movement and habitat selection, and 4) contaminant and water quality impacts on populations. Next, we review research using IBMs 5) to guide conservation biology of imperiled taxa through population viability analysis, including research 6) to understand river fragmentation by dams and reconnection, 7) to understand genetic outcomes for riverine metapopulations, and 8) to anticipate the future effects of temperature and climate change. This rich body of literature has contributed to both theoretical insights (e.g., about animal behavior and life history) and applied insights (e.g., population-level effects of flow regimes, temperature, and the effects of hydropower and other industries that share rivers with aquatic biota). We finish by exploring promising branches that lie ahead in the braided, downstream channel that represents future river modeling research.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolmodel.2018.06.013","usgsCitation":"Jager, H.I., and DeAngelis, D.L., 2018, The confluences of ideas leading to, and the flow of ideas emerging from, individual-based modeling of riverine fishes: Ecological Modelling, v. 384, p. 341-352, https://doi.org/10.1016/j.ecolmodel.2018.06.013.","productDescription":"12 p.","startPage":"341","endPage":"352","ipdsId":"IP-095746","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":468517,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.osti.gov/biblio/1461059","text":"Publisher Index Page"},{"id":356209,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"384","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b6fc3d6e4b0f5d57878e901","contributors":{"authors":[{"text":"Jager, Henriette I.","contributorId":206774,"corporation":false,"usgs":false,"family":"Jager","given":"Henriette","email":"","middleInitial":"I.","affiliations":[{"id":37400,"text":"Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee","active":true,"usgs":false}],"preferred":false,"id":741717,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"DeAngelis, Donald L. 0000-0002-1570-4057 don_deangelis@usgs.gov","orcid":"https://orcid.org/0000-0002-1570-4057","contributorId":148065,"corporation":false,"usgs":true,"family":"DeAngelis","given":"Donald","email":"don_deangelis@usgs.gov","middleInitial":"L.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":741716,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70198422,"text":"sir20185053 - 2018 - An exploratory Bayesian network for estimating the magnitudes and uncertainties of selected water-quality parameters at streamgage 03374100 White River at Hazleton, Indiana, from partially observed data","interactions":[],"lastModifiedDate":"2018-08-07T13:33:46","indexId":"sir20185053","displayToPublicDate":"2018-08-06T12:30:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-5053","title":"An exploratory Bayesian network for estimating the magnitudes and uncertainties of selected water-quality parameters at streamgage 03374100 White River at Hazleton, Indiana, from partially observed data","docAbstract":"An exploratory discrete Bayesian network (BN) was developed to assess the potential of this type of model for estimating the magnitudes and uncertainties of an arbitrary subset of unmeasured water-quality parameters given the measured complement of parameters historically measured at a U.S. Geological Survey streamgage. Water-quality data for 27 water-quality parameters from 596 discrete measurements at U.S. Geological Survey streamgage 03374100 White River at Hazleton, Indiana, were used to develop this BN. Data for each of the water-quality parameters were discretized into five intervals based on the quintiles of the measured values. The 596 discrete measurements were randomly partitioned into a training set with 80 percent of the data and a testing set with 20 percent of the data to identify, estimate, and assess the training and testing accuracy of the Bayesian network.
A BN with 28 nodes was formed from the 27 water-quality parameters and the month of sample collection. Based on data in the training set, a network with 53 directed edges and month as the target node was identified by minimizing the negative log-likelihood function for all nodes treated, in turn, as the target variable. The edge structure determines the number and magnitude of elements in conditional probability tables associated with all nodes.
The effectiveness of the BN was assessed on the basis of correct classification rates to one of the five discrete intervals, which were computed separately for the training and testing datasets and for two conditioning variable sets. The selected sets of conditioning variables represent two of many possible sets of measured parameters on which to base estimates of unmeasured parameters. The first set includes only the month of sample collection (month), and an expanded set includes month and six other continuously measurable parameters, referred to as the ContMeasSet, all of which were obtained from the discrete data.
Results indicated that the training dataset had average correct classification rates of 41.7- and 61.2-percent rates conditioned on the month and ContMeasSet sets, respectively. The testing dataset had somewhat lower average correct classification rates of 40.8 and 56.5 percent for the two conditioning variable sets. When conditioned on month only, the average correct classification rate for the testing dataset was only slightly lower than the average correct classification rate in the training dataset, indicating little model overfitting. When using the ContMeasSet, however, the average decrease in accuracy between training and testing sets was 4.9 percent. The training and testing datasets and both sets of conditioning variables, however, indicate that the BN would substantially outperform a random assignment model, which would be expected to have a 20-percent correct classification rate. In addition, the edge structure of the BN depicts how information can flow through the network, which may help prioritize parameters for measurement to facilitate estimation of unmeasured parameters. Finally, extension of a static BN, like the one developed in this report, to a dynamic BN may provide a basis for using high-frequency or continuous water-quality data to extend information in time between discrete water-quality samples, and this integration could mitigate some of the limitations of high-frequency and discrete water-quality sampling methods.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185053","collaboration":"National Water-Quality Program","usgsCitation":"Holtschlag, D.J., 2018, An exploratory Bayesian network for estimating the magnitudes and uncertainties of selected water-quality parameters at streamgage 03374100 White River at Hazleton, Indiana, from partially observed data: U.S. Geological Survey Scientific Investigations ReportDirector, Michigan Water Science Center
U.S. Geological Survey
6520 Mercantile Way, Suite 5
Lansing, MI 48911
With rising sea levels, mortality of glycophytes can be caused by water and nutrient stress under increasing salinity. However, the relative effects of these two stressors may vary by species-specific functional traits. For example, deciduous species, with leaves typically emerging during low salinity periods of the year, may suffer less from water stress than evergreen species. We sampled two woody species with contrasting functional traits: the evergreen and N2-fixing waxmyrtle (Morella cerifera), and the deciduous and non-N2 fixing baldcypress (Taxodium distichum) along a coastal river (South Carolina, USA) showing an increasing pattern of plant mortality along a salinity gradient. We first analyzed oxygen and hydrogen isotope ratios of plant stem water and river water to determine changes in plant source water at different sites. Then we analyzed foliar carbon and nitrogen isotope ratios (δ13C and δ15N) along with nitrogen and phosphorous content (%N and %P) as proxies for the water and nutrient stress. Results showed that: (1) the two species had different water sources at the higher salinity sites; (2) foliar δ15N values of baldcypress decreased with higher salinity while retaining a constant δ13C value, and both of these isotope values were positively related with foliar %P, suggesting greater nutrient stress but minor water stress under high salinity; and (3) foliar δ13C values of waxmyrtle increased with higher salinity while retaining a constant foliar δ15N value, and neither of the values was significantly related to foliar nutrients, suggesting greater water stress but minor nutrient stress under high salinity. The different responses of the two species to high salinity may be related to their differences in leaf phenology and N2-fixation. Our results suggest that nutrient stress, particularly of P, can contribute to stress and eventual high mortality of baldcypress exposed to salt water intrusion.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.envexpbot.2018.07.023","usgsCitation":"Zhai, L., Krauss, K.W., Liu, X., Duberstein, J., Conner, W.H., DeAngelis, D., and Sternberg, L.D., 2018, Growth stress response to sea level rise in species with contrasting functional traits: A case study in tidal freshwater forested wetlands: Environmental and Experimental Botany, v. 155, p. 378-386, https://doi.org/10.1016/j.envexpbot.2018.07.023.","productDescription":"9 p.","startPage":"378","endPage":"386","ipdsId":"IP-098771","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":468521,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envexpbot.2018.07.023","text":"Publisher Index Page"},{"id":356186,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"South Carolina","otherGeospatial":"Sampit River, Waccamaw River","volume":"155","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b6fc3e0e4b0f5d57878e913","contributors":{"authors":[{"text":"Zhai, Lu","contributorId":202653,"corporation":false,"usgs":false,"family":"Zhai","given":"Lu","email":"","affiliations":[{"id":5112,"text":"University of Miami","active":true,"usgs":false}],"preferred":false,"id":741583,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Krauss, Ken W. 0000-0003-2195-0729 kraussk@usgs.gov","orcid":"https://orcid.org/0000-0003-2195-0729","contributorId":2017,"corporation":false,"usgs":true,"family":"Krauss","given":"Ken","email":"kraussk@usgs.gov","middleInitial":"W.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":741582,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Liu, Xin","contributorId":146527,"corporation":false,"usgs":false,"family":"Liu","given":"Xin","email":"","affiliations":[{"id":16715,"text":"Nanjing Forestry University, Nanjing, China","active":true,"usgs":false}],"preferred":false,"id":741584,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Duberstein, Jamie A.","contributorId":91007,"corporation":false,"usgs":false,"family":"Duberstein","given":"Jamie A.","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":741585,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Conner, William H.","contributorId":79376,"corporation":false,"usgs":false,"family":"Conner","given":"William","email":"","middleInitial":"H.","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":741586,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"DeAngelis, Donald L. 0000-0002-1570-4057 don_deangelis@usgs.gov","orcid":"https://orcid.org/0000-0002-1570-4057","contributorId":147289,"corporation":false,"usgs":true,"family":"DeAngelis","given":"Donald L.","email":"don_deangelis@usgs.gov","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":false,"id":741587,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sternberg, Leonel d.S.L","contributorId":67051,"corporation":false,"usgs":true,"family":"Sternberg","given":"Leonel","email":"","middleInitial":"d.S.L","affiliations":[],"preferred":false,"id":741588,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70198419,"text":"70198419 - 2018 - The influence of angler values, involvement, catch orientation, satisfaction, agency trust, and demographics on support for habitat protection and restoration versus stocking in publicly managed waters","interactions":[],"lastModifiedDate":"2018-09-20T16:27:00","indexId":"70198419","displayToPublicDate":"2018-08-03T14:07:28","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1547,"text":"Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"The influence of angler values, involvement, catch orientation, satisfaction, agency trust, and demographics on support for habitat protection and restoration versus stocking in publicly managed waters","docAbstract":"Resource managers benefit from knowledge of angler support for fisheries management strategies. Factors including angler values (protection, utilitarian, and dominance), involvement (attraction, centrality, social, identity affirmation, and expression), catch-related motivations (catching some, many, and big fish, and keeping fish), satisfaction, agency trust, and demographics may relate to fisheries management preferences. Using results from a mail survey of Minnesota resident anglers, we explored how these factors were related to budget support for fish stocking relative to habitat protection/restoration. Results suggest that values, angler involvement, catch orientation, satisfaction, total and recent years fishing, age, and education influence relative support for stocking versus habitat protection/restoration. Utilitarian values, angling centrality, an orientation to catch many fish, satisfaction with the number of fish caught, number of recent years fishing, and age positively related to support for stocking over habitat management, while protection values, attraction to angling, total years fishing, and education level were negatively related to relative support for stocking.
","language":"English","publisher":"Springer","doi":"10.1007/s00267-018-1067-9","usgsCitation":"Schroeder, S., Fulton, D.C., Altena, E., Baird, H., Dieterman, D.J., and Jennings, M., 2018, The influence of angler values, involvement, catch orientation, satisfaction, agency trust, and demographics on support for habitat protection and restoration versus stocking in publicly managed waters: Environmental Management, v. 62, no. 4, p. 665-677, https://doi.org/10.1007/s00267-018-1067-9.","productDescription":"13 p.","startPage":"665","endPage":"677","ipdsId":"IP-083735","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":356151,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"62","issue":"4","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-05-23","publicationStatus":"PW","scienceBaseUri":"5b6fc3e4e4b0f5d57878e919","contributors":{"authors":[{"text":"Schroeder, Susan A.","contributorId":78235,"corporation":false,"usgs":true,"family":"Schroeder","given":"Susan A.","affiliations":[],"preferred":false,"id":741576,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fulton, David C. 0000-0001-5763-7887 dcf@usgs.gov","orcid":"https://orcid.org/0000-0001-5763-7887","contributorId":2208,"corporation":false,"usgs":true,"family":"Fulton","given":"David","email":"dcf@usgs.gov","middleInitial":"C.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":741376,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Altena, Eric","contributorId":206734,"corporation":false,"usgs":false,"family":"Altena","given":"Eric","email":"","affiliations":[],"preferred":false,"id":741577,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Baird, Heather","contributorId":206735,"corporation":false,"usgs":false,"family":"Baird","given":"Heather","email":"","affiliations":[],"preferred":false,"id":741578,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dieterman, Douglas J.","contributorId":147846,"corporation":false,"usgs":false,"family":"Dieterman","given":"Douglas","email":"","middleInitial":"J.","affiliations":[{"id":6754,"text":"University of Missouri","active":true,"usgs":false}],"preferred":false,"id":741579,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jennings, Martin","contributorId":206736,"corporation":false,"usgs":false,"family":"Jennings","given":"Martin","affiliations":[],"preferred":false,"id":741580,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70195660,"text":"fs20183010 - 2018 - Brackish groundwater and its potential as a resource in the southwestern United States","interactions":[],"lastModifiedDate":"2018-09-18T11:00:37","indexId":"fs20183010","displayToPublicDate":"2018-08-03T10:55:04","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-3010","title":"Brackish groundwater and its potential as a resource in the southwestern United States","docAbstract":"Secure, reliable, and sustainable water resources are fundamental to food production, energy independence, and the health of humans and ecosystems. But the large-scale development of fresh groundwater resources has stressed aquifers in some areas, causing declines in the amount of groundwater in storage and decreases in discharge to surface-water bodies like rivers and springs (Reilly and others, 2008). In some parts of the southwestern United States, the water supply is not adequate to meet demand without substantial effects on groundwater storage or surface discharge, and severe drought intensifies the stresses affecting water resources.
In support of the national census of water resources, the U.S. Geological Survey (USGS) completed the national brackish groundwater assessment to provide information about brackish groundwater as a potential resource to augment or replace freshwater supplies (Stanton and others, 2017). The objectives of the brackish groundwater assessment were to consolidate available data into a comprehensive database of brackish groundwater resources in the United States and to produce a summary report about the distribution, physical and chemical characteristics, and use of brackish groundwater. This fact sheet summarizes the occurrence of brackish groundwater and factors affecting its usability in the southwestern United States (specifically the Southwest Basins region) reported for the national study. The map below (fig. 1) summarizes the brackish zones for the five largest principal aquifers within the southwestern United States, along with groundwater resources in the remaining part of the region (Reilly and others, 2008).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20183010","usgsCitation":"Anning, D.W., Beisner, K.R., Paul, A.P., Stanton, J.S., and Thiros, S.A., 2018, Brackish groundwater and its potential as a resource in the southwestern United States: U.S. Geological Survey Fact Sheet 2018–3010, 6 p., https://doi.org/10.3133/fs20183010.","productDescription":"6 p.","numberOfPages":"6","ipdsId":"IP-093411","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":356134,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2018/3010/fs20183010_.pdf","text":"Report","size":"6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Fact Sheet 2018-3010"},{"id":356133,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2018/3010/coverthb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.45312499999999,\n 28.998531814051795\n ],\n [\n -102.6123046875,\n 28.998531814051795\n ],\n [\n -102.6123046875,\n 42.00032514831621\n ],\n [\n -124.45312499999999,\n 42.00032514831621\n ],\n [\n -124.45312499999999,\n 28.998531814051795\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Arizona Water Science Center
U.S. Geological Survey
520 N. Park Avenue
Tucson, AZ 85719
Nitrate concentrations in the Cedar River in Iowa and Minnesota have increased from an average of less than 1.0 milligram per liter in the early 1900s to more than 5.0 milligrams per liter in the 2000s and have resulted in periodic water-quality impairment of the river. Spatial differences and temporal changes in nitrogen and phosphorus transport in the Cedar River Basin are described for the period from 2000 to 2015. Data used to estimate nitrogen and phosphorus transport were collected by the U.S. Geological Survey as part of six base-flow synoptic studies and by the Minnesota Pollution Control Agency and the Iowa Department of Natural Resources as part of their long-term stream and river monitoring programs. The Cedar River transported an annual average of 53,100 tons of total nitrogen and 2,510 tons of total phosphorus during 2000–15. Three subbasins yielded an annual average of more than 30 pounds per acre (lb/acre) of nitrogen to the Cedar River, whereas two subbasins yielded an annual average of less than 20 lb/acre of nitrogen. The average annual total phosphorus yield from the Little Cedar River subbasin (0.35 lb/acre) was only about 16 percent of the yield from the greatest total phosphorus yielding Lower Cedar River subbasin (more than 1.0 lb/acre). The annual total nitrogen and total phosphorus loads did not change significantly during the study. The relation between annual stream runoff and annual total nitrogen and total phosphorus yields was not spatially uniform across the Cedar River Basin. The Beaver Creek, Black Hawk Creek, and Wolf Creek subbasins yielded the most, and the Main Stem Middle Cedar River, the Lower Cedar River, and the Little Cedar River subbasins yielded the least amount of nitrogen for a given amount of runoff. The Lower Cedar River and Wolf Creek subbasins yielded the most and the West Fork Cedar River and the Little Cedar River subbasins yielded the least phosphorus for a given amount of runoff. The results of this study describe nutrient transport during 2000–15 that can be used to evaluate future progress of nutrient reduction strategies in the Cedar River Basin.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185090","collaboration":"Prepared in cooperation with the City of Cedar Rapids, Iowa","usgsCitation":"Kalkhoff, S.J., 2018, Transport of nitrogen and phosphorus in the Cedar River Basin, Iowa and Minnesota, 2000–15: U.S. Geological Survey Scientific Investigations Report 2018–5090, 44 p., https://doi.org/10.3133/sir20185090.","productDescription":"ix, 44 p.","numberOfPages":"58","onlineOnly":"N","ipdsId":"IP-090101","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":355857,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5090/sir20185090.pdf","text":"Report","size":"18.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5090"},{"id":355856,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5090/coverthb.jpg"}],"country":"United States","state":"Iowa, Minnesota","otherGeospatial":"Cedar River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.75,\n 41.25\n ],\n [\n -90.5,\n 41.25\n ],\n [\n -90.5,\n 44\n ],\n [\n -93.75,\n 44\n ],\n [\n -93.75,\n 41.25\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
400 South Clinton Street
Room 269
Iowa City, Iowa 52240-4105
Fine sediment (particles <2 mm in diameter) in stream beds has wide-ranging effects on hydraulics, geomorphology, and ecology and is a primary focus for stream quality management in many regions. We identify reach- and basin-scale factors associated with fine sediment in the beds of 83 stream reaches in the Midwestern United States using recursive partitioning of sand-bed and gravel-bed streams and a generalized linear model for the fraction of a stream bed covered by fine sediment. A water-surface gradient of 0.00075 is the best single determinant (80% correct classification) distinguishing sand-bed streams (lower gradient) from gravel-bed streams (higher gradient). In the higher gradient category, sand-bed streams generally had more variable monthly precipitation than gravel-bed streams. The fractional response model indicated that the proportion of a stream bed composed of fine sediment is related to high sediment supply and low transport capacity but also high gravel transport capacity. This result is consistent with both theory and observations that bed material can be transported indiscriminately with respect to particle size under high shear stress, which will drive the particle size distribution of bed material toward the distribution of supply. Management of fine sediment in Midwestern streams has been approached largely by focusing on sediment supply, which may be immutable in some places due to the landscape position or glacial history. Retention of coarse sediment is an alternative management approach to reduce the fraction of fine sediment in the beds of some Midwestern streams.
","language":"English","publisher":"ACSESS","doi":"10.2134/jeq2018.02.0060","usgsCitation":"Konrad, C.P., and Gellis, A.C., 2018, Factors influencing fine sediment on stream beds in the Midwestern United States: Journal of Environmental Quality, v. 47, no. 5, p. 1214-1222, https://doi.org/10.2134/jeq2018.02.0060.","productDescription":"9 p.","startPage":"1214","endPage":"1222","ipdsId":"IP-084623","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":468526,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2134/jeq2018.02.0060","text":"Publisher Index Page"},{"id":357839,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -98.7451171875,\n 36.59788913307022\n ],\n [\n -82.28759765625,\n 36.59788913307022\n ],\n [\n -82.28759765625,\n 45.36758436884978\n ],\n [\n -98.7451171875,\n 45.36758436884978\n ],\n [\n -98.7451171875,\n 36.59788913307022\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"47","issue":"5","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5bc02fc0e4b0fc368eb53975","contributors":{"authors":[{"text":"Konrad, Christopher P. 0000-0002-7354-547X cpkonrad@usgs.gov","orcid":"https://orcid.org/0000-0002-7354-547X","contributorId":1716,"corporation":false,"usgs":true,"family":"Konrad","given":"Christopher","email":"cpkonrad@usgs.gov","middleInitial":"P.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":746505,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gellis, Allen C. 0000-0002-3449-2889 agellis@usgs.gov","orcid":"https://orcid.org/0000-0002-3449-2889","contributorId":197684,"corporation":false,"usgs":true,"family":"Gellis","given":"Allen","email":"agellis@usgs.gov","middleInitial":"C.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":746506,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70198376,"text":"70198376 - 2018 - Volcanic eruptions and threats to respiratory health","interactions":[],"lastModifiedDate":"2018-08-02T11:48:54","indexId":"70198376","displayToPublicDate":"2018-08-02T11:48:24","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5724,"text":"American Journal of Respiratory and Critical Care Medicine","active":true,"publicationSubtype":{"id":10}},"title":"Volcanic eruptions and threats to respiratory health","docAbstract":"In early May 2018, Kīlauea volcano became increasingly active, posing an increase in threat to respiratory health. The emission of gases such as sulfur dioxide from Kīlauea produces large amounts of respirable acid particles as the gases react with water vapor and sunlight, resulting in a visible haze called “vog”. Additionally, the lava lake at Kīlauea’s summit crater has fallen, leading to explosions of “ash” that have reached as high up as 30,000 feet above sea level. Finally, lava entering the Pacific Ocean boils sea water to dryness, creating thick clouds of “laze” that is filled with hydrochloric acid and tiny shards of glass. Depending on your location and wind direction and speed, vog, ash, and laze can reach hazardous levels of air pollution that are toxic to humans. This fact sheet serves to inform you of potential adverse health effects following exposure to these airborne products of volcanic activity. This outdoor air quality issue is relevant to other locations worldwide at risk for volcanic activity.","language":"English","publisher":"American Thoracic Society","doi":"10.1164/rccm.19712P21","usgsCitation":"Carlos, W.G., Gross, J.E., Jamil, S., Dela Cruz, C.S., Damby, D., and Tam, E.K., 2018, Volcanic eruptions and threats to respiratory health: American Journal of Respiratory and Critical Care Medicine, v. 197, no. 12, p. P21-P22, https://doi.org/10.1164/rccm.19712P21.","productDescription":"2 p.","startPage":"P21","endPage":"P22","ipdsId":"IP-098924","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":468528,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1164/rccm.19712p21","text":"Publisher Index Page"},{"id":356111,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"197","issue":"12","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b6fc3e8e4b0f5d57878e929","contributors":{"authors":[{"text":"Carlos, W. Graham","contributorId":206615,"corporation":false,"usgs":false,"family":"Carlos","given":"W.","email":"","middleInitial":"Graham","affiliations":[{"id":37145,"text":"Indiana University","active":true,"usgs":false}],"preferred":false,"id":741291,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gross, Jane E.","contributorId":206616,"corporation":false,"usgs":false,"family":"Gross","given":"Jane","email":"","middleInitial":"E.","affiliations":[{"id":36955,"text":"National Jewish Health","active":true,"usgs":false}],"preferred":false,"id":741292,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jamil, Shazia","contributorId":206617,"corporation":false,"usgs":false,"family":"Jamil","given":"Shazia","email":"","affiliations":[{"id":37349,"text":"Scripps Clinic and University of California San Diego School of Medicine","active":true,"usgs":false}],"preferred":false,"id":741293,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dela Cruz, Charles S.","contributorId":206618,"corporation":false,"usgs":false,"family":"Dela Cruz","given":"Charles","email":"","middleInitial":"S.","affiliations":[{"id":37350,"text":"Yale School of Medicine","active":true,"usgs":false}],"preferred":false,"id":741294,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Damby, David 0000-0002-3238-3961 ddamby@usgs.gov","orcid":"https://orcid.org/0000-0002-3238-3961","contributorId":177453,"corporation":false,"usgs":true,"family":"Damby","given":"David","email":"ddamby@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":741290,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Tam, Elizabeth K.","contributorId":173742,"corporation":false,"usgs":false,"family":"Tam","given":"Elizabeth","email":"","middleInitial":"K.","affiliations":[{"id":27286,"text":"John A. Burns School of Medicine, University of Hawaii","active":true,"usgs":false}],"preferred":false,"id":741295,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70199225,"text":"70199225 - 2018 - Metal reactivity in laboratory burned wood from a watershed affected by wildfires","interactions":[],"lastModifiedDate":"2018-09-11T16:36:52","indexId":"70199225","displayToPublicDate":"2018-08-01T16:36:47","publicationYear":"2018","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":"Metal reactivity in laboratory burned wood from a watershed affected by wildfires","docAbstract":"We investigated interfacial processes affecting metal mobility by wood ash under laboratory-controlled conditions using aqueous chemistry, microscopy, and spectroscopy. The Valles Caldera National Preserve in New Mexico experiences catastrophic wildfires of devastating effects. Wood samples of Ponderosa Pine, Colorado Blue Spruce, and Quaking Aspen collected from this site were exposed to temperatures of 60, 350, and 550 °C. The 350 °C Pine ash had the highest content of Cu (4997 ± 262 mg kg–1), Cr (543 ± 124 mg kg–1), and labile dissolved organic carbon (DOC, 11.3 ± 0.28 mg L–1). Sorption experiments were conducted by reacting 350 °C Pine, Spruce, and Aspen ashes separately with 10 μM Cu(II) and Cr(VI) solutions. Up to a 94% decrease in Cu(II) concentration was observed in solution while Cr(VI) concentration showed a limited decrease (up to 13%) after 180 min of reaction. X-ray photoelectron spectroscopy (XPS) analyses detected increased association of Cu(II) on the near surface region of the reacted 350 °C Pine ash from the sorption experiments compared to the unreacted ash. The results suggest that dissolution and sorption processes should be considered to better understand the potential effects of metals transported by wood ash on water quality that have important implications for postfire recovery and response strategies.
","language":"English","publisher":"ACS","doi":"10.1021/acs.est.8b00530","usgsCitation":"Rahman, A., El Hayek, E., Blake, J.M., Bixby, R.J., Ali, A., Spilde, M., Otieno, A.A., Miltenberger, K., Ridgeway, C., Artyushkova, K., Atudorei, V., and Ceratto, J.M., 2018, Metal reactivity in laboratory burned wood from a watershed affected by wildfires: Environmental Science & Technology, v. 52, no. 15, p. 8115-8123, https://doi.org/10.1021/acs.est.8b00530.","productDescription":"9 p.","startPage":"8115","endPage":"8123","ipdsId":"IP-094540","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":357233,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"52","issue":"15","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2018-07-18","publicationStatus":"PW","scienceBaseUri":"5b98a28ae4b0702d0e842f57","contributors":{"authors":[{"text":"Rahman, Asifur","contributorId":207796,"corporation":false,"usgs":false,"family":"Rahman","given":"Asifur","email":"","affiliations":[{"id":36307,"text":"University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":744753,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"El Hayek, Eliane","contributorId":207797,"corporation":false,"usgs":false,"family":"El Hayek","given":"Eliane","email":"","affiliations":[{"id":36307,"text":"University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":744754,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Blake, Johanna M. 0000-0003-4667-0096 jmtblake@usgs.gov","orcid":"https://orcid.org/0000-0003-4667-0096","contributorId":169698,"corporation":false,"usgs":true,"family":"Blake","given":"Johanna","email":"jmtblake@usgs.gov","middleInitial":"M.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":744752,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bixby, Rebecca J.","contributorId":147389,"corporation":false,"usgs":false,"family":"Bixby","given":"Rebecca","email":"","middleInitial":"J.","affiliations":[{"id":16834,"text":"Dept. of Biology and Museum of Southwestern Biology, Univ of NM","active":true,"usgs":false}],"preferred":false,"id":744755,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ali, Abdul-Mehdi","contributorId":207798,"corporation":false,"usgs":false,"family":"Ali","given":"Abdul-Mehdi","affiliations":[{"id":36307,"text":"University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":744756,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Spilde, Michael","contributorId":207799,"corporation":false,"usgs":false,"family":"Spilde","given":"Michael","affiliations":[{"id":36307,"text":"University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":744757,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Otieno, Amanda A.","contributorId":207800,"corporation":false,"usgs":false,"family":"Otieno","given":"Amanda","email":"","middleInitial":"A.","affiliations":[{"id":36307,"text":"University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":744758,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Miltenberger, Keely","contributorId":207801,"corporation":false,"usgs":false,"family":"Miltenberger","given":"Keely","affiliations":[{"id":36307,"text":"University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":744759,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Ridgeway, Cyrena","contributorId":207802,"corporation":false,"usgs":false,"family":"Ridgeway","given":"Cyrena","email":"","affiliations":[{"id":36307,"text":"University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":744760,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Artyushkova, Kateryna","contributorId":207803,"corporation":false,"usgs":false,"family":"Artyushkova","given":"Kateryna","email":"","affiliations":[{"id":36307,"text":"University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":744761,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Atudorei, Viorel","contributorId":207804,"corporation":false,"usgs":false,"family":"Atudorei","given":"Viorel","email":"","affiliations":[{"id":36307,"text":"University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":744762,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Ceratto, Jose M.","contributorId":207805,"corporation":false,"usgs":false,"family":"Ceratto","given":"Jose","email":"","middleInitial":"M.","affiliations":[{"id":36307,"text":"University of New Mexico","active":true,"usgs":false}],"preferred":false,"id":744763,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ]}