Hurricane Sandy made landfall in Barnegat Bay, October, 29, 2012, damaging shorelines and infrastructure. Estuarine sediment chemistry and toxicity were investigated before and after to evaluate potential environmental health impacts and to establish post-event baseline sediment-quality conditions. Trace element concentrations increased throughout Barnegat Bay up to two orders of magnitude, especially north of Barnegat Inlet, consistent with northward redistribution of silt. Loss of organic compounds, clay, and organic carbon is consistent with sediment winnowing and transport through the inlets and sediment transportmodeling results. The number of sites exceeding sediment quality guidance levels for trace elements tripled post-Sandy. Sediment toxicity post-Sandy was mostly unaffected relative to pre-Sandy conditions, but at the site with the greatest relative increase for trace elements, survival rate of the test amphipod decreased (indicating degradation). This study would not have been possible without comprehensive baseline data enabling the evaluation of storm-derived changes in sediment quality.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.marpolbul.2016.04.018","usgsCitation":"Romanok, K., Szabo, Z., Reilly, T.J., Defne, Z., and Ganju, N., 2016, Sediment chemistry and toxicity in Barnegat Bay, New Jersey: Pre- and post-Hurricane Sandy, 2012–13: Marine Pollution Bulletin, v. 107, no. 2, p. 472-488, https://doi.org/10.1016/j.marpolbul.2016.04.018.","productDescription":"17 p.","startPage":"472","endPage":"488","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068252","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":321463,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Jersey","otherGeospatial":"Barnegat Bay estuary","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.97894287109375,\n 39.14710270770074\n ],\n [\n -74.97894287109375,\n 40.41349604970198\n ],\n [\n -74.00390625,\n 40.41349604970198\n ],\n [\n -74.00390625,\n 39.14710270770074\n ],\n [\n -74.97894287109375,\n 39.14710270770074\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"107","issue":"2","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57403559e4b07e28b65e9705","contributors":{"authors":[{"text":"Romanok, Kristin M. 0000-0002-8472-8765 kromanok@usgs.gov","orcid":"https://orcid.org/0000-0002-8472-8765","contributorId":169543,"corporation":false,"usgs":true,"family":"Romanok","given":"Kristin M. ","email":"kromanok@usgs.gov","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":false,"id":629965,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Szabo, Zoltan 0000-0002-0760-9607 zszabo@usgs.gov","orcid":"https://orcid.org/0000-0002-0760-9607","contributorId":138827,"corporation":false,"usgs":true,"family":"Szabo","given":"Zoltan","email":"zszabo@usgs.gov","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":629966,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reilly, Timothy J. 0000-0002-2939-3050 tjreilly@usgs.gov","orcid":"https://orcid.org/0000-0002-2939-3050","contributorId":1858,"corporation":false,"usgs":true,"family":"Reilly","given":"Timothy","email":"tjreilly@usgs.gov","middleInitial":"J.","affiliations":[{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true},{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":629967,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Defne, Zafer 0000-0003-4544-4310 zdefne@usgs.gov","orcid":"https://orcid.org/0000-0003-4544-4310","contributorId":5520,"corporation":false,"usgs":true,"family":"Defne","given":"Zafer","email":"zdefne@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":629968,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ganju, Neil K. 0000-0002-1096-0465 nganju@usgs.gov","orcid":"https://orcid.org/0000-0002-1096-0465","contributorId":149613,"corporation":false,"usgs":true,"family":"Ganju","given":"Neil K.","email":"nganju@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":629969,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70170609,"text":"sir20165056 - 2016 - Evaluation of background concentrations of selected chemical and radiochemical constituents in water from the eastern Snake River Plain aquifer at and near the Idaho National Laboratory, Idaho","interactions":[],"lastModifiedDate":"2016-10-24T13:54:47","indexId":"sir20165056","displayToPublicDate":"2016-05-05T18:00:00","publicationYear":"2016","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":"2016-5056","title":"Evaluation of background concentrations of selected chemical and radiochemical constituents in water from the eastern Snake River Plain aquifer at and near the Idaho National Laboratory, Idaho","docAbstract":"The U.S. Geological Survey and Idaho Department of Environmental Quality Idaho National Laboratory (INL) Oversight Program in cooperation with the U.S. Department of Energy determined background concentrations of selected chemical and radiochemical constituents in the eastern Snake River Plain aquifer to aid with ongoing cleanup efforts at the INL. Chemical and radiochemical constituents including calcium, magnesium, sodium, potassium, silica, chloride, sulfate, fluoride, bicarbonate, chromium, nitrate, tritium, strontium-90, chlorine-36, iodine-129, plutonium-238, plutonium-239, -240 (undivided), americium-241, technetium-99, uranium-234, uranium-235, and uranium-238 were selected for the background study because they were either not analyzed in earlier studies or new data became available to give a more recent determination of background concentrations. Samples of water collected from wells and springs at and near the INL that were not believed to be influenced by wastewater disposal were used to identify background concentrations. Groundwater in the eastern Snake River Plain aquifer at and near the INL was divided into two major water types (western tributary and eastern regional) based on concentrations of lithium less than and greater than 5 micrograms per liter (μg/L). Median concentrations for each constituent were used to define the upper limit of background.
\nThe upper limit of background concentrations for inorganic chemicals for western tributary water was 40.7 milligrams per liter (mg/L) for calcium, 15.3 mg/L for magnesium, 8.30 mg/L for sodium, 2.32 mg/L for potassium, 23.1 mg/L for silica, 11.8 mg/L for chloride, 21.4 mg/L for sulfate, 0.20 mg/L for fluoride, 176 mg/L for bicarbonate, 4.00 μg/L for chromium, and 0.655 mg/L for nitrate.
\nThe upper limit of background concentrations for inorganic chemicals for eastern regional water was 34.05 mg/L for calcium, 13.85 mg/L for magnesium, 14.85 mg/L for sodium, 3.22 mg/L for potassium, 31.0 mg/L for silica, 14.15 mg/L for chloride, 20.2 mg/L for sulfate, 0.4675 mg/L for fluoride, 165 mg/L for bicarbonate, 3.00 μg/L for chromium, and 0.995 mg/L for nitrate.
\nThe upper limit of background concentrations for radiochemical constituents for western tributary water was 34.15 ±2.35 picocuries per liter (pCi/L) for tritium, 0.00098 ±0.00006 pCi/L for chlorine-36, 0.000011 ±0.000005 pCi/L for iodine-129, <0.0000054 pCi/L for technetium-99, 0 pCi/L for strontium-90, plutonium-238, plutonium-239, -240 (undivided), and americium-241, 1.36 pCi/L with undetermined uncertainty for uranium-234, 0.025 ±0.001 pCi/L for uranium-235, and 0.541 ±0.001 pCi/L for uranium-238.
\nThe upper limit of background concentrations for radiochemical constituents for eastern regional water was 5.43 ±0.574 pCi/L for tritium, 0.0002048 ±0.0000054 pCi/L for chlorine-36, 0.000000865 ±0.000000015 pCi/L for iodine-129, <0.0000054 pCi/L for technetium-99, 0 pCi/L for strontium-90, plutonium-238, plutonium-239, -240 (undivided), and americium-241, 1.32 ±0.77 pCi/L for uranium-234, 0.016 ±0.012 pCi/L for uranium-235, and 0.477 ±0.044 pCi/L for uranium-238.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165056","collaboration":"Prepared in cooperation with the U.S. Department of Energy","usgsCitation":"Bartholomay, R.C., and Hall, L.F., 2016, Evaluation of background concentrations of selected chemical and radiochemical constituents in water from the eastern Snake River Plain aquifer at and near the Idaho National Laboratory, Idaho: U.S. Geological Survey Scientific Investigations Report 2016–5056, (DOE/ID-22237), 19 p.,\nhttps://dx.doi.org/10.3133/sir20165056.","productDescription":"Report: v, 19 p.; Appendixes A-C","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-065188","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":321010,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5056/sir20165056.pdf","text":"Report","size":"1.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5056 Report PDF"},{"id":321011,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5056/sir20165056_appendixa.xlsx","text":"Appendix A","size":"36 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2016-5056 Appendix A"},{"id":321009,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5056/coverthb.jpg"},{"id":321012,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5056/sir20165056_appendixb.xlsx","text":"Appendix B","size":"75 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2016-5056 Appendix B"},{"id":321013,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5056/sir20165056_appendixc.xlsx","text":"Appendix C","size":"81 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2016-5056 Appendix C"}],"country":"United States","state":"Idaho","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -113.75,\n 44.25\n ],\n [\n -113.75,\n 43.30\n ],\n [\n -112.25,\n 43.30\n ],\n [\n -112.25,\n 44.25\n ],\n [\n -113.75,\n 44.25\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Idaho Water Science Center
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A groundwater-flow model was developed to improve understanding of water resources on the Kitsap Peninsula. The Kitsap Peninsula is in the Puget Sound lowland of west-central Washington, is bounded by Puget Sound on the east and by Hood Canal on the west, and covers an area of about 575 square miles. The peninsula encompasses all of Kitsap County, Mason County north of Hood Canal, and part of Pierce County west of Puget Sound. The peninsula is surrounded by saltwater, and the hydrologic setting is similar to that of an island. The study area is underlain by a thick sequence of unconsolidated glacial and interglacial deposits that overlie sedimentary and volcanic bedrock units that crop out in the central part of the study area. Twelve hydrogeologic units consisting of aquifers, confining units, and an underlying bedrock unit form the basis of the groundwater-flow model.
Groundwater flow on the Kitsap Peninsula was simulated using the groundwater-flow model, MODFLOW‑NWT. The finite difference model grid comprises 536 rows, 362 columns, and 14 layers. Each model cell has a horizontal dimension of 500 by 500 feet, and the model contains a total of 1,227,772 active cells. Groundwater flow was simulated for transient conditions. Transient conditions were simulated for January 1985–December 2012 using annual stress periods for 1985–2004 and monthly stress periods for 2005–2012. During model calibration, variables were adjusted within probable ranges to minimize differences between measured and simulated groundwater levels and stream baseflows. As calibrated to transient conditions, the model has a standard deviation for heads and flows of 47.04 feet and 2.46 cubic feet per second, respectively.
Simulated inflow to the model area for the 2005–2012 period from precipitation and secondary recharge was 585,323 acre-feet per year (acre-ft/yr) (93 percent of total simulated inflow ignoring changes in storage), and simulated inflow from stream and lake leakage was 43,905 acre-ft/yr (7 percent of total simulated inflow). Simulated outflow from the model primarily was through discharge to streams, lakes, springs, seeps, and Puget Sound (594,595 acre-ft/yr; 95 percent of total simulated outflow excluding changes in storage) and through withdrawals from wells (30,761 acre-ft/yr; 5 percent of total simulated outflow excluding changes in storage).
Six scenarios were formulated with input from project stakeholders and were simulated using the calibrated model to provide representative examples of how the model could be used to evaluate the effects on water levels and stream baseflows of potential changes in groundwater withdrawals, in consumptive use, and in recharge. These included simulations of a steady-state system, no-pumping and return flows, 15-percent increase in current withdrawals in all wells, 80-percent decrease in outdoor water to simulate effects of conservation efforts, 15-percent decrease in recharge from precipitation to simulate a drought, and particle tracking to determine flow paths.
Changes in water-level altitudes and baseflow amounts vary depending on the stress applied to the system in these various scenarios. Reducing recharge by 15 percent between 2005 and 2012 had the largest effect, with water-level altitudes declining throughout the model domain and baseflow amounts decreasing by as much as 18 percent compared to baseline conditions. Changes in pumping volumes had a smaller effect on the model. Removing all pumping and resulting return flows caused increased water-level altitudes in many areas and increased baseflow amounts of between 1 and 3 percent.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165052","collaboration":"Prepared in cooperation with Public Utility District No. 1 of Kitsap County","usgsCitation":"Frans, L.M. and Olsen, T.D., 2016, Numerical simulation of the groundwater-flow system of the Kitsap Peninsula, west-central Washington (ver. 1.1, October 2016): U.S. Geological Survey Scientific Investigations Report 2016–5052, 63 p., https://dx.doi.org/10.3133/sir20165052.","productDescription":"vi, 63 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-071099","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":329281,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2016/5052/versionHist.txt","size":"544 bytes","linkFileType":{"id":2,"text":"txt"},"description":"SIR 2016-5052 Version 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U.S. Geological Survey
934 Broadway, Suite 300
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http://wa.water.usgs.gov
Streams and adjacent terrestrial ecosystems are characterized by permeable boundaries that are crossed by resource subsidies. Although the importance of these subsidies for riverine ecosystems is increasingly recognized, little is known about how they may be influenced by global environmental change. Drawing from available evidence, in this review we propose a conceptual framework to evaluate the effects of global change on the quality and spatiotemporal dynamics of stream–terrestrial subsidies. We illustrate how changes to hydrological and temperature regimes, atmospheric CO2 concentration, land use and the distribution of nonindigenous species can influence subsidy fluxes by affecting the biology and ecology of donor and recipient systems and the physical characteristics of stream–riparian boundaries. Climate-driven changes in the physiology and phenology of organisms with complex life cycles will influence their development time, body size and emergence patterns, with consequences for adjacent terrestrial consumers. Also, novel species interactions can modify subsidy dynamics via complex bottom-up and top-down effects. Given the seasonality and pulsed nature of subsidies, alterations of the temporal and spatial synchrony of resource availability to consumers across ecosystems are likely to result in ecological mismatches that can scale up from individual responses, to communities, to ecosystems. Similarly, altered hydrology, temperature, CO2 concentration and land use will modify the recruitment and quality of riparian vegetation, the timing of leaf abscission and the establishment of invasive riparian species. Along with morphological changes to stream–terrestrial boundaries, these will alter the use and fluxes of allochthonous subsidies associated with stream ecosystems. Future research should aim to understand how subsidy dynamics will be affected by key drivers of global change, including agricultural intensification, increasing water use and biotic homogenization. Our conceptual framework based on the match–mismatch between donor and recipient organisms may facilitate understanding of the multiple effects of global change and aid in the development of future research questions.
","language":"English","publisher":"Wiley","doi":"10.1111/gcb.13182","usgsCitation":"Larsen, S., Muehlbauer, J.D., and Marti Roca, M.E., 2016, Resource subsidies between stream and terrestrial ecosystems under global change: Global Change Biology, v. 22, no. 7, p. 2489-2504, https://doi.org/10.1111/gcb.13182.","productDescription":"16 p.","startPage":"2489","endPage":"2504","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-067749","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":320998,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"22","issue":"7","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-04-25","publicationStatus":"PW","scienceBaseUri":"572c609ce4b09acee752ef96","contributors":{"authors":[{"text":"Larsen, Stefano","contributorId":169188,"corporation":false,"usgs":false,"family":"Larsen","given":"Stefano","email":"","affiliations":[{"id":13099,"text":"German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany","active":true,"usgs":false}],"preferred":false,"id":628833,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Muehlbauer, Jeffrey D. 0000-0003-1808-580X jmuehlbauer@usgs.gov","orcid":"https://orcid.org/0000-0003-1808-580X","contributorId":5045,"corporation":false,"usgs":true,"family":"Muehlbauer","given":"Jeffrey","email":"jmuehlbauer@usgs.gov","middleInitial":"D.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":628832,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Marti Roca, Maria Eugenia","contributorId":169189,"corporation":false,"usgs":false,"family":"Marti Roca","given":"Maria","email":"","middleInitial":"Eugenia","affiliations":[{"id":25434,"text":"Centre d'Estudis Avancats de Blanes","active":true,"usgs":false}],"preferred":false,"id":628834,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70170799,"text":"70170799 - 2016 - Contamination with bacterial zoonotic pathogen genes in U.S. streams influenced by varying types of animal agriculture","interactions":[],"lastModifiedDate":"2018-09-12T17:04:25","indexId":"70170799","displayToPublicDate":"2016-05-05T11:45:00","publicationYear":"2016","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}},"title":"Contamination with bacterial zoonotic pathogen genes in U.S. streams influenced by varying types of animal agriculture","docAbstract":"Animal waste, stream water, and streambed sediment from 19 small (< 32 km2) watersheds in 12 U.S. states having either no major animal agriculture (control, n = 4), or predominantly beef (n = 4), dairy (n = 3), swine (n = 5), or poultry (n = 3) were tested for: 1) cholesterol, coprostanol, estrone, and fecal indicator bacteria (FIB) concentrations, and 2) shiga-toxin producing and enterotoxigenic Escherichia coli, Salmonella, Campylobacter, and pathogenic and vancomycin-resistant enterococci by polymerase chain reaction (PCR) on enrichments, and/or direct quantitative PCR. Pathogen genes were most frequently detected in dairy wastes, followed by beef, swine and poultry wastes in that order; there was only one detection of an animal-source-specific pathogen gene (stx1) in any water or sediment sample in any control watershed. Post-rainfall pathogen gene numbers in stream water were significantly correlated with FIB, cholesterol and coprostanol concentrations, and were most highly correlated in dairy watershed samples collected from 3 different states. Although collected across multiple states and ecoregions, animal-waste gene profiles were distinctive via discriminant analysis. Stream water gene profiles could also be discriminated by the watershed animal type. Although pathogen genes were not abundant in stream water or streambed samples, PCR on enrichments indicated that many genes were from viable organisms, including several (shiga-toxin producing or enterotoxigenic E. coli, Salmonella, vancomycin-resistant enterococci) that could potentially affect either human or animal health. Pathogen gene numbers and types in stream water samples were influenced most by animal type, by local factors such as whether animals had stream access, and by the amount of local rainfall, and not by studied watershed soil or physical characteristics. Our results indicated that stream water in small agricultural U.S. watersheds was susceptible to pathogen gene inputs under typical agricultural practices and environmental conditions. Pathogen gene profiles may offer the potential to address both source of, and risks associated with, fecal pollution.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2016.04.087","usgsCitation":"Haack, S.K., Duris, J., Kolpin, D.W., Focazio, M.J., Meyer, M.T., Johnson, H., Oster, R.J., and Foreman, W., 2016, Contamination with bacterial zoonotic pathogen genes in U.S. streams influenced by varying types of animal agriculture: Science of the Total Environment, v. 563-564, p. 340-350, https://doi.org/10.1016/j.scitotenv.2016.04.087.","productDescription":"11 p.","startPage":"340","endPage":"350","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059123","costCenters":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":320993,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, Indiana, Iowa, Kentucky, Maryland, Michigan, New York, North Carolina, Ohio, Pennsylvania, 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\"}}]}","volume":"563-564","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"572c609ae4b09acee752ef84","contributors":{"authors":[{"text":"Haack, Sheridan K. skhaack@usgs.gov","contributorId":1982,"corporation":false,"usgs":true,"family":"Haack","given":"Sheridan","email":"skhaack@usgs.gov","middleInitial":"K.","affiliations":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true}],"preferred":true,"id":628463,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Duris, Joseph W. jwduris@usgs.gov","contributorId":169110,"corporation":false,"usgs":true,"family":"Duris","given":"Joseph W.","email":"jwduris@usgs.gov","affiliations":[],"preferred":false,"id":628464,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kolpin, Dana W. 0000-0002-3529-6505 dwkolpin@usgs.gov","orcid":"https://orcid.org/0000-0002-3529-6505","contributorId":1239,"corporation":false,"usgs":true,"family":"Kolpin","given":"Dana","email":"dwkolpin@usgs.gov","middleInitial":"W.","affiliations":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"preferred":true,"id":628465,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Focazio, Michael J. 0000-0003-0967-5576 mfocazio@usgs.gov","orcid":"https://orcid.org/0000-0003-0967-5576","contributorId":1276,"corporation":false,"usgs":true,"family":"Focazio","given":"Michael","email":"mfocazio@usgs.gov","middleInitial":"J.","affiliations":[{"id":5056,"text":"Office of the AD Energy and Minerals, and Environmental Health","active":true,"usgs":true},{"id":38175,"text":"Toxics Substances Hydrology Program","active":true,"usgs":true}],"preferred":true,"id":628466,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Meyer, Michael T. 0000-0001-6006-7985 mmeyer@usgs.gov","orcid":"https://orcid.org/0000-0001-6006-7985","contributorId":866,"corporation":false,"usgs":true,"family":"Meyer","given":"Michael","email":"mmeyer@usgs.gov","middleInitial":"T.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":628467,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Johnson, Heather E.","contributorId":207837,"corporation":false,"usgs":false,"family":"Johnson","given":"Heather E.","affiliations":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true},{"id":12456,"text":"former USGS scientist","active":true,"usgs":false}],"preferred":false,"id":744847,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Oster, Ryan J. roster@usgs.gov","contributorId":5483,"corporation":false,"usgs":true,"family":"Oster","given":"Ryan","email":"roster@usgs.gov","middleInitial":"J.","affiliations":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true}],"preferred":true,"id":628469,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Foreman, William T. wforeman@usgs.gov","contributorId":1473,"corporation":false,"usgs":true,"family":"Foreman","given":"William T.","email":"wforeman@usgs.gov","affiliations":[{"id":452,"text":"National Water Quality Laboratory","active":true,"usgs":true}],"preferred":false,"id":628470,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70170861,"text":"70170861 - 2016 - Modeling suitable habitat of invasive red lionfish Pterois volitans (Linnaeus, 1758) in North and South America’s coastal waters","interactions":[],"lastModifiedDate":"2016-07-07T10:09:23","indexId":"70170861","displayToPublicDate":"2016-05-05T11:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":868,"text":"Aquatic Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Modeling suitable habitat of invasive red lionfish Pterois volitans (Linnaeus, 1758) in North and South America’s coastal waters","docAbstract":"We used two common correlative species-distribution models to predict suitable habitat of invasive red lionfish Pterois volitans (Linnaeus, 1758) in the western Atlantic and eastern Pacific Oceans. The Generalized Linear Model (GLM) and the Maximum Entropy (Maxent) model were applied using the Software for Assisted Habitat Modeling. We compared models developed using native occurrences, using non-native occurrences, and using both native and non-native occurrences. Models were trained using occurrence data collected before 2010 and evaluated with occurrence data collected from the invaded range during or after 2010. We considered a total of 22 marine environmental variables. Models built with non-native only or both native and non-native occurrence data outperformed those that used only native occurrences. Evaluation metrics based on the independent test data were highest for models that used both native and non-native occurrences. Bathymetry was the strongest environmental predictor for all models and showed increasing suitability as ocean floor depth decreased, with salinity ranking the second strongest predictor for models that used native and both native and non-native occurrences, indicating low habitat suitability for salinities <30. Our model results also suggest that red lionfish could continue to invade southern latitudes in the western Atlantic Ocean and may establish localized populations in the eastern Pacific Ocean. We reiterate the importance in the choice of the training data source (native, non-native, or native/non-native) used to develop correlative species distribution models for invasive species.
\nIt is commonly recognized that suspended-sediment concentrations in rivers can change rapidly in time and independently of water discharge during important sediment‑transporting events (for example, during floods); thus, suspended-sediment measurements at closely spaced time intervals are necessary to characterize suspended‑sediment loads. Because the manual collection of sufficient numbers of suspended-sediment samples required to characterize this variability is often time and cost prohibitive, several “surrogate” techniques have been developed for in situ measurements of properties related to suspended-sediment characteristics (for example, turbidity, laser-diffraction, acoustics). Herein, we present a new physically based method for the simultaneous measurement of suspended-silt-and-clay concentration, suspended-sand concentration, and suspended‑sand median grain size in rivers, using multi‑frequency arrays of single-frequency side‑looking acoustic-Doppler profilers. The method is strongly grounded in the extensive scientific literature on the incoherent scattering of sound by random suspensions of small particles. In particular, the method takes advantage of theory that relates acoustic frequency, acoustic attenuation, acoustic backscatter, suspended-sediment concentration, and suspended-sediment grain-size distribution. We develop the theory and methods, and demonstrate the application of the method at six study sites on the Colorado River and Rio Grande, where large numbers of suspended-sediment samples have been collected concurrently with acoustic attenuation and backscatter measurements over many years. The method produces acoustical measurements of suspended-silt-and-clay and suspended-sand concentration (in units of mg/L), and acoustical measurements of suspended-sand median grain size (in units of mm) that are generally in good to excellent agreement with concurrent physical measurements of these quantities in the river cross sections at these sites. In addition, detailed, step-by-step procedures are presented for the general river application of the method.
Quantification of errors in sediment-transport measurements made using this acoustical method is essential if the measurements are to be used effectively, for example, to evaluate uncertainty in long-term sediment loads and budgets. Several types of error analyses are presented to evaluate (1) the stability of acoustical calibrations over time, (2) the effect of neglecting backscatter from silt and clay, (3) the bias arising from changes in sand grain size, (4) the time-varying error in the method, and (5) the influence of nonrandom processes on error. Results indicate that (1) acoustical calibrations can be stable for long durations (multiple years), (2) neglecting backscatter from silt and clay can result in unacceptably high bias, (3) two frequencies are likely required to obtain sand-concentration measurements that are unbiased by changes in grain size, depending on site-specific conditions and acoustic frequency, (4) relative errors in silt-and-clay- and sand-concentration measurements decrease substantially as concentration increases, and (5) nonrandom errors may arise from slow changes in the spatial structure of suspended sediment that affect the relations between concentration in the acoustically ensonified part of the cross section and concentration in the entire river cross section. Taken together, the error analyses indicate that the two-frequency method produces unbiased measurements of suspended-silt-and-clay and sand concentration, with errors that are similar to, or larger than, those associated with conventional sampling methods.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1823","usgsCitation":"Topping, D.J., and Wright, S.A., 2016, Long-term continuous acoustical suspended-sediment measurements in rivers—Theory, application, bias, and error: U.S. Geological Survey Professional Paper 1823, 98 p.,\nhttps://dx.doi.org/10.3133/pp1823.","productDescription":"xii, 97 p.","numberOfPages":"114","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062803","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":320792,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1823/coverthb.jpg"},{"id":320827,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1823/pp1823.pdf","text":"Report","size":"6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1823 Report PDF"}],"country":"United States","state":"Arizona, Texas","otherGeospatial":"Colorado River, Grand Canyon National Park; Rio Grande, Big Bend National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.5384521484375,\n 36.01578220325809\n ],\n [\n -112.5384521484375,\n 36.41907231092499\n ],\n [\n -111.86553955078124,\n 36.41907231092499\n ],\n [\n -111.86553955078124,\n 36.01578220325809\n ],\n [\n -112.5384521484375,\n 36.01578220325809\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -103.76174926757812,\n 28.96489485992114\n ],\n [\n -103.76174926757812,\n 29.410890376109\n ],\n [\n -102.82241821289062,\n 29.410890376109\n ],\n [\n -102.82241821289062,\n 28.96489485992114\n ],\n [\n -103.76174926757812,\n 28.96489485992114\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"SBSC staff, Southwest Biological Science Center
U.S. Geological Survey
2255 N. Gemini Drive
Flagstaff, AZ 86001
http://sbsc.wr.usgs.gov/
","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2016-05-04","noUsgsAuthors":false,"publicationDate":"2016-05-04","publicationStatus":"PW","scienceBaseUri":"572b0f1ae4b0b13d391a83f7","contributors":{"authors":[{"text":"Topping, David J. 0000-0002-2104-4577 dtopping@usgs.gov","orcid":"https://orcid.org/0000-0002-2104-4577","contributorId":715,"corporation":false,"usgs":true,"family":"Topping","given":"David","email":"dtopping@usgs.gov","middleInitial":"J.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":false,"id":626542,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wright, Scott 0000-0002-0387-5713 sawright@usgs.gov","orcid":"https://orcid.org/0000-0002-0387-5713","contributorId":1536,"corporation":false,"usgs":true,"family":"Wright","given":"Scott","email":"sawright@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":626543,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70169399,"text":"ofr20161054 - 2016 - Evaluation of the Storm 3 data logger manufactured by WaterLOG/Xylem Incorporated—Results of bench, temperature, and field deployment testing","interactions":[],"lastModifiedDate":"2016-05-04T15:49:10","indexId":"ofr20161054","displayToPublicDate":"2016-05-04T15:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-1054","title":"Evaluation of the Storm 3 data logger manufactured by WaterLOG/Xylem Incorporated—Results of bench, temperature, and field deployment testing","docAbstract":"
The Storm 3 is a browser-based data logger manufactured by WaterLOG/Xylem Incorporated that operates over a temperature range of −40 to 60 degrees Celsius (°C). A Storm logger with no built-in telemetry (Storm3-00) and a logger with built-in cellular modem (Storm3-03) were evaluated by the U.S. Geological Survey (USGS) Hydrologic Instrumentation Facility (HIF) for conformance to the manufacturer’s specifications with bench tests, for recording data over the device’s operating temperature range with temperature chamber tests, and for field performance with an outdoor deployment test.
\nThe procedures followed and the results obtained from the testing are described in this publication. The device met most of the manufacturer’s stated specifications. An exception was power consumption, which was about 10 percent above the manufacturer’s specifications. It was also observed that enabling WiFi doubles the Storm 3’s power consumption. In addition, several logging errors were made by two units during deployment testing, but it could not be determined whether these errors were the fault of the Storm or of an attached sensor.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161054","usgsCitation":"Kunkle, G.A., 2016, Evaluation of the Storm 3 data logger manufactured by Waterlog/Xylem Incorporated—Results of Bench, Temperature, and Field Deployment Testing: U.S. Geological Survey Open-File Report 2016–1054, 9 p., https://dx.doi.org/10.3133/ofr20161054.","productDescription":"iii, 9 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-069059","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":320970,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1054/ofr20161054.pdf","text":"Report","size":"373 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1054"},{"id":320969,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1054/coverthb.jpg","description":"OFR 2016-1054"}],"contact":"Chief, Hydrologic Instrumentation Facility
U.S. Geological Survey
Building 2101
Stennis Space Center, MS 39529
http://water.usgs.gov/hif/
Although initially viewed as oases within a barren deep ocean, hydrothermal vent and methane seep communities are now recognized to interact with surrounding ecosystems on the sea floor and in the water column, and to affect global geochemical cycles. The importance of understanding these interactions is growing as the potential rises for disturbance from oil and gas extraction, seabed mining and bottom trawling. Here we synthesize current knowledge of the nature, extent and time and space scales of vent and seep interactions with background systems. We document an expanded footprint beyond the site of local venting or seepage with respect to elemental cycling and energy flux, habitat use, trophic interactions, and connectivity. Heat and energy are released, global biogeochemical and elemental cycles are modified, and particulates are transported widely in plumes. Hard and biotic substrates produced at vents and seeps are used by “benthic background” fauna for attachment substrata, shelter, and access to food via grazing or through position in the current, while particulates and fluid fluxes modify planktonic microbial communities. Chemosynthetic production provides nutrition to a host of benthic and planktonic heterotrophic background species through multiple horizontal and vertical transfer pathways assisted by flow, gamete release, animal movements, and succession, but these pathways remain poorly known. Shared species, genera and families indicate that ecological and evolutionary connectivity exists among vents, seeps, organic falls and background communities in the deep sea; the genetic linkages with inactive vents and seeps and background assemblages however, are practically unstudied. The waning of venting or seepage activity generates major transitions in space and time that create links to surrounding ecosystems, often with identifiable ecotones or successional stages. The nature of all these interactions is dependent on water depth, as well as regional oceanography and biodiversity. Many ecosystem services are associated with the interactions and transitions between chemosynthetic and background ecosystems, for example carbon cycling and sequestration, fisheries production, and a host of non-market and cultural services. The quantification of the sphere of influence of vents and seeps could be beneficial to better management of deep-sea environments in the face of growing industrialization.
","language":"English","publisher":"Frontiers","doi":"10.3389/fmars.2016.00072","usgsCitation":"Levin, L.A., Baco, A., Bowden, D., Colaco, A., Cordes, E.E., Cunha, M., Demopoulos, A.W., Gobin, J., Grupe, B., Le, J., Metaxas, A., Netburn, A., Rouse, G., Thurber, A., Tunnicliffe, V., Van Dover, C., Vanreusel, A., and Watling, L., 2016, Hydrothermal vents and methane seeps: Rethinking the sphere of influence: Frontiers in Marine Science, v. 3, art72: 23 p., https://doi.org/10.3389/fmars.2016.00072.","productDescription":"art72: 23 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-073011","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":471022,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fmars.2016.00072","text":"Publisher Index Page"},{"id":320952,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"3","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-19","publicationStatus":"PW","scienceBaseUri":"572b0f1ae4b0b13d391a83f4","contributors":{"authors":[{"text":"Levin, Lisa A.","contributorId":12372,"corporation":false,"usgs":true,"family":"Levin","given":"Lisa","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":628684,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baco, Amy","contributorId":120023,"corporation":false,"usgs":true,"family":"Baco","given":"Amy","email":"","affiliations":[],"preferred":false,"id":628685,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bowden, David","contributorId":10864,"corporation":false,"usgs":true,"family":"Bowden","given":"David","email":"","affiliations":[],"preferred":false,"id":628686,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Colaco, Ana","contributorId":169152,"corporation":false,"usgs":false,"family":"Colaco","given":"Ana","email":"","affiliations":[{"id":25423,"text":"Univ. of the Azores","active":true,"usgs":false}],"preferred":false,"id":628687,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cordes, Erik E.","contributorId":37623,"corporation":false,"usgs":false,"family":"Cordes","given":"Erik","email":"","middleInitial":"E.","affiliations":[{"id":16710,"text":"Temple University, Department of Biology","active":true,"usgs":false}],"preferred":false,"id":628688,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cunha, Marina","contributorId":169153,"corporation":false,"usgs":false,"family":"Cunha","given":"Marina","email":"","affiliations":[{"id":25424,"text":"Univ. de Aveiro","active":true,"usgs":false}],"preferred":false,"id":628689,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Demopoulos, Amanda W.J. 0000-0003-2096-4694 ademopoulos@usgs.gov","orcid":"https://orcid.org/0000-0003-2096-4694","contributorId":145681,"corporation":false,"usgs":true,"family":"Demopoulos","given":"Amanda","email":"ademopoulos@usgs.gov","middleInitial":"W.J.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"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":628683,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Gobin, Judith","contributorId":169154,"corporation":false,"usgs":false,"family":"Gobin","given":"Judith","email":"","affiliations":[{"id":25425,"text":"Univ. West Indies","active":true,"usgs":false}],"preferred":false,"id":628690,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Grupe, Ben","contributorId":169155,"corporation":false,"usgs":false,"family":"Grupe","given":"Ben","affiliations":[{"id":6728,"text":"Scripps Inst Oceanography","active":true,"usgs":false}],"preferred":false,"id":628691,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Le, Jennifer","contributorId":169163,"corporation":false,"usgs":false,"family":"Le","given":"Jennifer","email":"","affiliations":[],"preferred":false,"id":628692,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Metaxas, Anna","contributorId":169156,"corporation":false,"usgs":false,"family":"Metaxas","given":"Anna","email":"","affiliations":[{"id":24650,"text":"Dalhousie University","active":true,"usgs":false}],"preferred":false,"id":628693,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Netburn, Amanda","contributorId":169157,"corporation":false,"usgs":false,"family":"Netburn","given":"Amanda","affiliations":[{"id":6728,"text":"Scripps Inst Oceanography","active":true,"usgs":false}],"preferred":false,"id":628694,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Rouse, Greg","contributorId":169158,"corporation":false,"usgs":false,"family":"Rouse","given":"Greg","email":"","affiliations":[{"id":6728,"text":"Scripps Inst Oceanography","active":true,"usgs":false}],"preferred":false,"id":628695,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Thurber, Andrew","contributorId":169159,"corporation":false,"usgs":false,"family":"Thurber","given":"Andrew","affiliations":[{"id":25426,"text":"OSU","active":true,"usgs":false}],"preferred":false,"id":628696,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Tunnicliffe, Verena","contributorId":169160,"corporation":false,"usgs":false,"family":"Tunnicliffe","given":"Verena","email":"","affiliations":[{"id":25427,"text":"Univ. of Victoria","active":true,"usgs":false}],"preferred":false,"id":628697,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Van Dover, Cindy L.","contributorId":95341,"corporation":false,"usgs":true,"family":"Van Dover","given":"Cindy L.","affiliations":[],"preferred":false,"id":628698,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Vanreusel, Ann","contributorId":169161,"corporation":false,"usgs":false,"family":"Vanreusel","given":"Ann","email":"","affiliations":[{"id":25428,"text":"Ghent Univ.","active":true,"usgs":false}],"preferred":false,"id":628699,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Watling, Les","contributorId":54755,"corporation":false,"usgs":false,"family":"Watling","given":"Les","email":"","affiliations":[{"id":16143,"text":"University of Hawaii at Manoa, Honolulu, Hawaii","active":true,"usgs":false}],"preferred":false,"id":628714,"contributorType":{"id":1,"text":"Authors"},"rank":18}]}} ,{"id":70170821,"text":"70170821 - 2016 - Vegetation of semi-stable rangeland dunes of the Navajo Nation, Southwestern USA","interactions":[],"lastModifiedDate":"2016-07-28T10:53:13","indexId":"70170821","displayToPublicDate":"2016-05-04T11:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":904,"text":"Arid Land Research and Management","active":true,"publicationSubtype":{"id":10}},"title":"Vegetation of semi-stable rangeland dunes of the Navajo Nation, Southwestern USA","docAbstract":"Dune destabilization and increased mobility is a worldwide issue causing ecological, economic, and health problems for the inhabitants of areas with extensive dune fields. Dunes cover nearly a third of the Navajo Nation within the Colorado Plateau of southwestern USA. There, higher temperatures and prolonged drought beginning in 1996 have produced significant increases in dune mobility. Vegetation plays an important role in dune stabilization, but there are few studies of the plants of the aeolian surfaces of this region. We examined plant species and their attributes within a moderately vegetated dune field of the Navajo Nation to understand the types and characteristics of plants that stabilize rangeland dunes. These dunes supported a low cover of mixed grass-scrubland with fifty-two perennial and annual species including extensive occurrence of non-native annual Salsola spp. Perennial grass richness and shrub cover were positively associated with increased soil sand composition. Taprooted shrubs were more common on sandier substrates. Most dominant grasses had C4 photosynthesis, suggestive of higher water-use efficiencies and growth advantage in warm arid environments. Plant cover was commonly below the threshold of dune stabilization. Increasing sand movement with continued aridity will select for plants adapted to burial, deflation, and abrasion. The study indicates plants tolerant of increased sand mobility and burial but more investigation is needed to identify the plants adapted to establish and regenerate under these conditions. In addition, the role of Salsola spp. in promoting decline of perennial grasses and shrubs needs clarification.
","language":"English","publisher":"Taylor and Francis","doi":"10.1080/15324982.2016.1138157","usgsCitation":"Thomas, K.A., and Redsteer, M.H., 2016, Vegetation of semi-stable rangeland dunes of the Navajo Nation, Southwestern USA: Arid Land Research and Management, v. 30, no. 4, p. 400-411, https://doi.org/10.1080/15324982.2016.1138157.","productDescription":"12 p.","startPage":"400","endPage":"411","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063167","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":502595,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"text":"External Repository"},{"id":320950,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, Colorado, New Mexico, Utah","otherGeospatial":"Navajo Nation","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.3134765625,\n 34.56085936708387\n ],\n [\n -111.3134765625,\n 38.22091976683121\n ],\n [\n -107.29248046875,\n 38.22091976683121\n ],\n [\n -107.29248046875,\n 34.56085936708387\n ],\n [\n -111.3134765625,\n 34.56085936708387\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"30","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-04-27","publicationStatus":"PW","scienceBaseUri":"572b0f1ce4b0b13d391a8407","contributors":{"authors":[{"text":"Thomas, Kathryn A. 0000-0002-7131-8564 kathryn_a_thomas@usgs.gov","orcid":"https://orcid.org/0000-0002-7131-8564","contributorId":167,"corporation":false,"usgs":true,"family":"Thomas","given":"Kathryn","email":"kathryn_a_thomas@usgs.gov","middleInitial":"A.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":628554,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Redsteer, Margaret H.","contributorId":9123,"corporation":false,"usgs":true,"family":"Redsteer","given":"Margaret","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":628555,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70170814,"text":"70170814 - 2016 - Drivers of barotropic and baroclinic exchange through an estuarine navigation channel in the Mississippi River Delta Plain","interactions":[],"lastModifiedDate":"2016-05-04T10:03:24","indexId":"70170814","displayToPublicDate":"2016-05-04T11:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Drivers of barotropic and baroclinic exchange through an estuarine navigation channel in the Mississippi River Delta Plain","docAbstract":"Estuarine navigation channels have long been recognized as conduits for saltwater intrusion into coastal wetlands. Salt flux decomposition and time series measurements of velocity and salinity were used to examine salt flux components and drivers of baroclinic and barotropic exchange in the Houma Navigation Channel, an estuarine channel located in the Mississippi River delta plain that receives substantial freshwater inputs from the Mississippi-Atchafalaya River system at its inland extent. Two modes of vertical current structure were identified from the time series data. The first mode, accounting for 90% of the total flow field variability, strongly resembled a barotropic current structure and was coherent with alongshelf wind stress over the coastal Gulf of Mexico. The second mode was indicative of gravitational circulation and was linked to variability in tidal stirring and the horizontal salinity gradient along the channel’s length. Tidal oscillatory salt flux was more important than gravitational circulation in transporting salt upestuary, except over equatorial phases of the fortnightly tidal cycle during times when river inflows were minimal. During all tidal cycles sampled, the advective flux, driven by a combination of freshwater discharge and wind-driven changes in storage, was the dominant transport term, and net flux of salt was always out of the estuary. These findings indicate that although human-made channels can effectively facilitate inland intrusion of saline water, this intrusion can be minimized or even reversed when they are subject to significant freshwater inputs.
","language":"English","publisher":"MDPI","doi":"10.3390/w8050184","usgsCitation":"Snedden, G., 2016, Drivers of barotropic and baroclinic exchange through an estuarine navigation channel in the Mississippi River Delta Plain: Water, v. 8, no. 5, Article 184: 15 p., https://doi.org/10.3390/w8050184.","productDescription":"Article 184: 15 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069649","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":471023,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w8050184","text":"Publisher Index Page"},{"id":320948,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Houma Navigation Canal","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.74844360351562,\n 29.216904948184734\n ],\n [\n -90.74844360351562,\n 29.58898286696141\n ],\n [\n -90.604248046875,\n 29.58898286696141\n ],\n [\n -90.604248046875,\n 29.216904948184734\n ],\n [\n -90.74844360351562,\n 29.216904948184734\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","issue":"5","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2016-04-30","publicationStatus":"PW","scienceBaseUri":"572b0f19e4b0b13d391a83ec","contributors":{"authors":[{"text":"Snedden, Gregg 0000-0001-7821-3709 sneddeng@usgs.gov","orcid":"https://orcid.org/0000-0001-7821-3709","contributorId":140235,"corporation":false,"usgs":true,"family":"Snedden","given":"Gregg","email":"sneddeng@usgs.gov","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":628526,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70170954,"text":"70170954 - 2016 - Trace elements in stormflow, ash, and burned soil following the 2009 station fire in southern California","interactions":[],"lastModifiedDate":"2016-05-13T09:18:39","indexId":"70170954","displayToPublicDate":"2016-05-04T10:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Trace elements in stormflow, ash, and burned soil following the 2009 station fire in southern California","docAbstract":"Most research on the effects of wildfires on stream water quality has focused on suspended sediment and nutrients in streams and water bodies, and relatively little research has examined the effects of wildfires on trace elements. The purpose of this study was two-fold: 1) to determine the effect of the 2009 Station Fire in the Angeles National Forest northeast of Los Angeles, CA on trace element concentrations in streams, and 2) compare trace elements in post-fire stormflow water quality to criteria for aquatic life to determine if trace elements reached concentrations that can harm aquatic life. Pre-storm and stormflow water-quality samples were collected in streams located inside and outside of the burn area of the Station Fire. Ash and burned soil samples were collected from several locations within the perimeter of the Station Fire. Filtered concentrations of Fe, Mn, and Hg and total concentrations of most trace elements in storm samples were elevated as a result of the Station Fire. In contrast, filtered concentrations of Cu, Pb, Ni, and Se and total concentrations of Cu were elevated primarily due to storms and not the Station Fire. Total concentrations of Se and Zn were elevated as a result of both storms and the Station Fire. Suspended sediment in stormflows following the Station Fire was an important transport mechanism for trace elements. Cu, Pb, and Zn primarily originate from ash in the suspended sediment. Fe primarily originates from burned soil in the suspended sediment. As, Mn, and Ni originate from both ash and burned soil. Filtered concentrations of trace elements in stormwater samples affected by the Station Fire did not reach levels that were greater than criteria established for aquatic life. Total concentrations for Fe, Pb, Ni, and Zn were detected at concentrations above criteria established for aquatic life.
","language":"English","publisher":"Public Library of Science","publisherLocation":"San Francisco, CA","doi":"10.1371/journal.pone.0153372","collaboration":"Amphibian Research and Monitoring Initiative (BRD) Mineral Resources Program (USGS)","usgsCitation":"Burton, C.A., Hoefen, T.M., Plumlee, G.S., Baumberger, K., Backlin, A.R., Gallegos, E., and Fisher, R.N., 2016, Trace elements in stormflow, ash, and burned soil following the 2009 station fire in southern California: PLoS ONE, v. 11, no. 5, https://doi.org/10.1371/journal.pone.0153372.","productDescription":"26 p.","startPage":"e0153372","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-051778","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":471024,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0153372","text":"Publisher Index Page"},{"id":321203,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":321176,"type":{"id":15,"text":"Index Page"},"url":"https://dx.doi.org/10.1371/journal.pone.0153372."}],"country":"United States","state":"California","otherGeospatial":"Angeles National Forest","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.466667,\n 34.625\n ],\n [\n -118.466667,\n 34.125\n ],\n [\n -117.6875,\n 34.125\n ],\n [\n -117.6875,\n 34.625\n ],\n [\n -118.466667,\n 34.625\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","issue":"5","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-04","publicationStatus":"PW","scienceBaseUri":"5736fae1e4b0dae0d5e03ebb","contributors":{"authors":[{"text":"Burton, Carmen A. 0000-0002-6381-8833 caburton@usgs.gov","orcid":"https://orcid.org/0000-0002-6381-8833","contributorId":444,"corporation":false,"usgs":true,"family":"Burton","given":"Carmen","email":"caburton@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":629205,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hoefen, Todd M. 0000-0002-3083-5987 thoefen@usgs.gov","orcid":"https://orcid.org/0000-0002-3083-5987","contributorId":403,"corporation":false,"usgs":true,"family":"Hoefen","given":"Todd","email":"thoefen@usgs.gov","middleInitial":"M.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":629206,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Plumlee, Geoffrey S. 0000-0002-9607-5626 gplumlee@usgs.gov","orcid":"https://orcid.org/0000-0002-9607-5626","contributorId":960,"corporation":false,"usgs":true,"family":"Plumlee","given":"Geoffrey","email":"gplumlee@usgs.gov","middleInitial":"S.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":629207,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Baumberger, Katherine L. kbaumberger@usgs.gov","contributorId":5870,"corporation":false,"usgs":true,"family":"Baumberger","given":"Katherine L.","email":"kbaumberger@usgs.gov","affiliations":[],"preferred":true,"id":629208,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Backlin, Adam R. 0000-0001-5618-8426 abacklin@usgs.gov","orcid":"https://orcid.org/0000-0001-5618-8426","contributorId":3802,"corporation":false,"usgs":true,"family":"Backlin","given":"Adam","email":"abacklin@usgs.gov","middleInitial":"R.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":629209,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gallegos, Elizabeth 0000-0002-8402-2631 egallegos@usgs.gov","orcid":"https://orcid.org/0000-0002-8402-2631","contributorId":1528,"corporation":false,"usgs":true,"family":"Gallegos","given":"Elizabeth","email":"egallegos@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":629210,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Fisher, Robert N. 0000-0002-2956-3240 rfisher@usgs.gov","orcid":"https://orcid.org/0000-0002-2956-3240","contributorId":1529,"corporation":false,"usgs":true,"family":"Fisher","given":"Robert","email":"rfisher@usgs.gov","middleInitial":"N.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":629211,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70170139,"text":"sir20165046 - 2016 - Simulation of deep ventilation in Crater Lake, Oregon, 1951–2099","interactions":[],"lastModifiedDate":"2021-10-12T17:00:16.258141","indexId":"sir20165046","displayToPublicDate":"2016-05-04T10:00:00","publicationYear":"2016","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":"2016-5046","title":"Simulation of deep ventilation in Crater Lake, Oregon, 1951–2099","docAbstract":"The frequency of deep ventilation events in Crater Lake, a caldera lake in the Oregon Cascade Mountains, was simulated in six future climate scenarios, using a 1-dimensional deep ventilation model (1DDV) that was developed to simulate the ventilation of deep water initiated by reverse stratification and subsequent thermobaric instability. The model was calibrated and validated with lake temperature data collected from 1994 to 2011. Wind and air temperature data from three general circulation models and two representative concentration pathways were used to simulate the change in lake temperature and the frequency of deep ventilation events in possible future climates. The lumped model air2water was used to project lake surface temperature, a required boundary condition for the lake model, based on air temperature in the future climates.
The 1DDV model was used to simulate daily water temperature profiles through 2099. All future climate scenarios projected increased water temperature throughout the water column and a substantive reduction in the frequency of deep ventilation events. The least extreme scenario projected the frequency of deep ventilation events to decrease from about 1 in 2 years in current conditions to about 1 in 3 years by 2100. The most extreme scenario considered projected the frequency of deep ventilation events to be about 1 in 7.7 years by 2100. All scenarios predicted that the temperature of the entire water column will be greater than 4 °C for increasing lengths of time in the future and that the conditions required for thermobaric instability induced mixing will become rare or non-existent.
The disruption of deep ventilation by itself does not provide a complete picture of the potential ecological and water quality consequences of warming climate to Crater Lake. Estimating the effect of warming climate on deep water oxygen depletion and water clarity will require careful modeling studies to combine the physical mixing processes affected by the atmosphere with the multitude of factors affecting the growth of algae and corresponding water clarity.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165046","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Wood, T.M., Wherry, S.A., Piccolroaz, S., and Girdner, S.F., 2016, Simulation of deep ventilation in Crater Lake, Oregon, 1951–2099: U.S. Geological Survey Scientific Investigations Report 2016–5046, 43 p. https://doi.org/10.3133/sir20165046","productDescription":"vii, 43 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-066051","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":320860,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5046/sir20165046.pdf","text":"Report","size":"3.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-5046 Report PDF"},{"id":320859,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5046/coverthb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Crater Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.18616485595703,\n 42.892567248047285\n ],\n [\n -122.18616485595703,\n 42.986065036562955\n ],\n [\n -122.03922271728514,\n 42.986065036562955\n ],\n [\n -122.03922271728514,\n 42.892567248047285\n ],\n [\n -122.18616485595703,\n 42.892567248047285\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.1: February 2020; Version 1.0: October 2016","contact":"Director, Oregon Water Science Center
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http://or.water.usgs.gov
The one-dimensional hydrodynamic ice model, DYRESM-WQ-I, was modified to simulate ice cover and thermal structure of dimictic Lake Mendota, Wisconsin, USA, over a continuous 104-year period (1911–2014). The model results were then used to examine the drivers of changes in ice cover and water temperature, focusing on the responses to shifts in air temperature, wind speed, and water clarity at multiyear timescales. Observations of the drivers include a change in the trend of warming air temperatures from 0.081 °C per decade before 1981 to 0.334 °C per decade thereafter, as well as a shift in mean wind speed from 4.44 m s−1 before 1994 to 3.74 m s−1 thereafter. Observations show that Lake Mendota has experienced significant changes in ice cover: later ice-on date(9.0 days later per century), earlier ice-off date (12.3 days per century), decreasing ice cover duration (21.3 days per century), while model simulations indicate a change in maximum ice thickness (12.7 cm decrease per century). Model simulations also show changes in the lake thermal regime of earlier stratification onset (12.3 days per century), later fall turnover (14.6 days per century), longer stratification duration (26.8 days per century), and decreasing summer hypolimnetic temperatures (−1.4 °C per century). Correlation analysis of lake variables and driving variables revealed ice cover variables, stratification onset, epilimnetic temperature, and hypolimnetic temperature were most closely correlated with air temperature, whereas freeze-over water temperature, hypolimnetic heating, and fall turnover date were more closely correlated with wind speed. Each lake variable (i.e., ice-on and ice-off dates, ice cover duration, maximum ice thickness, freeze-over water temperature, stratification onset, fall turnover date, stratification duration, epilimnion temperature, hypolimnion temperature, and hypolimnetic heating) was averaged for the three periods (1911–1980, 1981–1993, and 1994–2014) delineated by abrupt changes in air temperature and wind speed. Average summer hypolimnetic temperature and fall turnover date exhibit significant differences between the third period and the first two periods. Changes in ice cover (ice-on and ice-off dates, ice cover duration, and maximum ice thickness) exhibit an abrupt change after 1994, which was related in part to the warm El Niño winter of 1997–1998. Under-ice water temperature, freeze-over water temperature, hypolimnetic temperature, fall turnover date, and stratification duration demonstrate a significant difference in the third period (1994–2014), when air temperature was warmest and wind speeds decreased rather abruptly. The trends in ice cover and water temperature demonstrate responses to both long-term and abrupt changes in meteorological conditions that can be complemented with numerical modeling to better understand how these variables will respond in a future climate.
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Resources","active":true,"usgs":false}],"preferred":false,"id":639533,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wu, Chin H","contributorId":172076,"corporation":false,"usgs":false,"family":"Wu","given":"Chin","email":"","middleInitial":"H","affiliations":[{"id":7122,"text":"University of Wisconsin","active":true,"usgs":false}],"preferred":false,"id":639534,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Magee, Madeline R.","contributorId":172077,"corporation":false,"usgs":false,"family":"Magee","given":"Madeline","middleInitial":"R.","affiliations":[{"id":5083,"text":"University of British Columbia, Department of Zoology, Biodiversity Research Centre and Beaty Biodiversity Museum","active":true,"usgs":false}],"preferred":false,"id":639535,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hamilton, David P.","contributorId":166840,"corporation":false,"usgs":false,"family":"Hamilton","given":"David P.","affiliations":[{"id":24543,"text":"Environmental Research Institute, University of Waikato, Private Bag 3015, Hamilton 3240, New Zealand.","active":true,"usgs":false}],"preferred":false,"id":639536,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70169135,"text":"ds984 - 2016 - Pesticide concentrations in wetlands on the Lake Traverse Indian Reservation, South and North Dakota, July 2015","interactions":[],"lastModifiedDate":"2017-10-12T19:58:33","indexId":"ds984","displayToPublicDate":"2016-05-04T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"984","title":"Pesticide concentrations in wetlands on the Lake Traverse Indian Reservation, South and North Dakota, July 2015","docAbstract":"During July 2015, water samples were collected from 18 wetlands on the Lake Traverse Indian Reservation in northeastern South Dakota and southeastern North Dakota and analyzed for physical properties and 54 pesticides. This study by the U.S. Geological Survey in cooperation with the Sisseton-Wahpeton Oyate was designed to provide an update on pesticide concentrations of the same 18 wetlands that were sampled for a reconnaissance-level assessment during July 2006. The purpose of this report is to present the results of the assessment of pesticide concentrations in selected Lake Traverse Indian Reservation wetlands during July 2015 and provide a comparison of pesticide concentrations between 2006 and 2015.
Of the 54 pesticides that were analyzed for in the samples collected during July 2015, 47 pesticides were not detected in any samples. Seven pesticides—2-chloro-4-isopropylamino-6-amino-s-triazine (CIAT); 2,4–D; acetachlor; atrazine; glyphosate; metolachlor; and prometon—were detected in the 2015 samples with estimated concentrations or concentrations greater than the laboratory reporting level, and most pesticides were detected at low concentrations in only a few samples. Samples from all wetlands contained at least one detected pesticide. The maximum number of pesticides detected in a wetland sample was six, and the median number of pesticides detected was three.
The most commonly detected pesticides in the 2015 samples were atrazine and the atrazine degradate CIAT (also known as deethylatrazine), which were detected in 14 and 13 of the wetlands sampled, respectively. Glyphosate was detected in samples from 11 wetlands, and metolachlor was detected in samples from 10 wetlands. The other detected pesticides were 2,4–D (4 wetlands), acetochlor (3 wetlands), and prometon (1 wetland).
The same pesticides that were detected in the 2006 samples were detected in the 2015 samples, with the exception of simazine, which was detected only in one sample in 2006. Atrazine and CIAT were the most commonly detected pesticides in both sampling years; however, atrazine and CIAT were detected in fewer wetlands in 2015 (14 and 13 wetlands, respectively) than in 2006 (17 wetlands for both pesticides). The pesticides 2,4–D and prometon also were detected in fewer wetlands in 2015 than 2006, and simazine was only detected in 2006. In contrast, acetochlor, glyphosate, and metolachlor were detected in samples from more wetlands in 2015 than in 2006. In samples from individual wetlands, the number of pesticides detected was similar between 2006 and 2015. At least one pesticide was detected in all wetlands in 2015, and all but one wetland had pesticide detections in 2006.
Concentrations of pesticides detected in samples from wetlands were compared to selected water-quality (human-health and aquatic-life) benchmarks. None of the concentrations in either 2006 or 2015 were greater than water-quality benchmarks, with the exception of atrazine. All detections of atrazine in the 2006 and 2015 samples were greater than the acute benchmark of 0.001 microgram per liter (μg/L) for vascular plants. In addition, some concentrations of 2,4–D and atrazine were within an order of magnitude of a water-quality benchmark. The 2,4–D concentrations in the 2015 samples from three wetlands were within an order of magnitude of the U.S. Environmental Protection Agency’s Maximum Contaminant Level of 70 μg/L (that is, sample concentrations were greater than 7.0 μg/L). The maximum dissolved atrazine concentration of 0.185 μg/L in the 2015 samples along with the concentrations in 2006 samples from two wetlands were within an order of magnitude of the acute benchmark of less than 1 μg/L for nonvascular plants (that is, concentrations were greater than 0.1 μg/L).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds984","collaboration":"Prepared in cooperation with the Sisseton-Wahpeton Oyate","usgsCitation":"Carter, J.M., and Thompson, R.F., 2016, Pesticide concentrations in wetlands on the Lake Traverse Indian Reservation, South and North Dakota, July 2015: U.S. Geological Survey Data Series Report 984, 32 p., https://dx.doi.org/10.3133/ds984.","productDescription":"vi, 32 p.","numberOfPages":"42","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-072207","costCenters":[{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":320926,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/0984/coverthb.jpg"},{"id":320927,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0984/ds984.pdf","text":"Report","size":"1.54 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 984"}],"country":"United States","state":"North Dakota, South Dakota","otherGeospatial":"Lake Traverse Indian Reservation","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96.56021118164062,\n 45.93778073466329\n ],\n [\n -97.5146484375,\n 46.02462129598765\n ],\n [\n -97.18505859374999,\n 44.97645666320777\n ],\n [\n -96.85272216796875,\n 45.60058738537025\n ],\n [\n -96.85684204101562,\n 45.622682153628226\n ],\n [\n -96.84173583984374,\n 45.64188792039229\n ],\n [\n -96.78543090820312,\n 45.68123916702059\n ],\n [\n -96.70989990234374,\n 45.71864517367924\n ],\n [\n -96.66320800781249,\n 45.74261022090537\n ],\n [\n -96.61102294921875,\n 45.79625461321962\n ],\n [\n -96.5753173828125,\n 45.84602106744846\n ],\n [\n -96.56021118164062,\n 45.93778073466329\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, South Dakota Water Science Center
U.S. Geological Survey
1608 Mountain View Road
Rapid City, South Dakota 57702
The goal of this study was to map rainfed and irrigated rice-fallow cropland areas across South Asia, using MODIS 250 m time-series data and identify where the farming system may be intensified by the inclusion of a short-season crop during the fallow period. Rice-fallow cropland areas are those areas where rice is grown during the kharif growing season (June–October), followed by a fallow during the rabi season (November–February). These cropland areas are not suitable for growing rabi-season rice due to their high water needs, but are suitable for a short -season (≤3 months), low water-consuming grain legumes such as chickpea (Cicer arietinum L.), black gram, green gram, and lentils. Intensification (double-cropping) in this manner can improve smallholder farmer’s incomes and soil health via rich nitrogen-fixation legume crops as well as address food security challenges of ballooning populations without having to expand croplands. Several grain legumes, primarily chickpea, are increasingly grown across Asia as a source of income for smallholder farmers and at the same time providing rich and cheap source of protein that can improve the nutritional quality of diets in the region. The suitability of rainfed and irrigated rice-fallow croplands for grain legume cultivation across South Asia were defined by these identifiers: (a) rice crop is grown during the primary (kharif) crop growing season or during the north-west monsoon season (June–October); (b) same croplands are left fallow during the second (rabi) season or during the south-east monsoon season (November–February); and (c) ability to support low water-consuming, short-growing season (≤3 months) grain legumes (chickpea, black gram, green gram, and lentils) during rabi season. Existing irrigated or rainfed crops such as rice or wheat that were grown during kharif were not considered suitable for growing during the rabi season, because the moisture/water demand of these crops is too high. The study established cropland classes based on the every 16-day 250 m normalized difference vegetation index (NDVI) time series for one year (June 2010–May 2011) of Moderate Resolution Imaging Spectroradiometer (MODIS) data, using spectral matching techniques (SMTs), and extensive field knowledge. Map accuracy was evaluated based on independent ground survey data as well as compared with available sub-national level statistics. The producers’ and users’ accuracies of the cropland fallow classes were between 75% and 82%. The overall accuracy and the kappa coefficient estimated for rice classes were 82% and 0.79, respectively. The analysis estimated approximately 22.3 Mha of suitable rice-fallow areas in South Asia, with 88.3% in India, 0.5% in Pakistan, 1.1% in Sri Lanka, 8.7% in Bangladesh, 1.4% in Nepal, and 0.02% in Bhutan. Decision-makers can target these areas for sustainable intensification of short-duration grain legumes.
","language":"English","doi":"10.1080/17538947.2016.1168489","usgsCitation":"Gumma, M., Thenkabail, P.S., Teluguntla, P.G., Rao, M.N., Mohammed, I., and Whitbread, A.M., 2016, Mapping rice-fallow cropland areas for short-season grain legumes intensification in South Asia using MODIS 250 m time-series data: International Journal of Digital Earth, v. 9, no. 10, p. 981-1003, https://doi.org/10.1080/17538947.2016.1168489.","productDescription":"23 p.","startPage":"981","endPage":"1003","ipdsId":"IP-070335","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":471026,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/17538947.2016.1168489","text":"Publisher Index Page"},{"id":330906,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Bangladesh, Bhutan, India, Nepal, Pakistan, Sri Lanka","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 83.97949218750001,\n 15.284185114076433\n ],\n [\n 82.3095703125,\n 11.996338401936226\n ],\n [\n 83.32031250000001,\n 7.754537346539373\n ],\n [\n 81.78222656250001,\n 5.266007882805485\n ],\n [\n 79.365234375,\n 5.747174076651375\n ],\n [\n 76.81640625,\n 7.406047717076271\n ],\n [\n 72.59765625,\n 12.382928338487396\n ],\n [\n 66.4013671875,\n 25.64152637306577\n ],\n [\n 80.4638671875,\n 29.11377539511439\n ],\n [\n 95.61523437500003,\n 30.34192736497245\n ],\n [\n 91.62597656250001,\n 20.67390526467282\n ],\n [\n 83.97949218750001,\n 15.284185114076433\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"9","issue":"10","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-04","publicationStatus":"PW","scienceBaseUri":"582443f5e4b09065cdf30528","contributors":{"authors":[{"text":"Gumma, Murali Krishna","contributorId":50426,"corporation":false,"usgs":true,"family":"Gumma","given":"Murali Krishna","affiliations":[],"preferred":false,"id":653404,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thenkabail, Prasad S. 0000-0002-2182-8822 pthenkabail@usgs.gov","orcid":"https://orcid.org/0000-0002-2182-8822","contributorId":570,"corporation":false,"usgs":true,"family":"Thenkabail","given":"Prasad","email":"pthenkabail@usgs.gov","middleInitial":"S.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":653405,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Teluguntla, Pardhasaradhi G. 0000-0001-8060-9841 pteluguntla@usgs.gov","orcid":"https://orcid.org/0000-0001-8060-9841","contributorId":5275,"corporation":false,"usgs":true,"family":"Teluguntla","given":"Pardhasaradhi","email":"pteluguntla@usgs.gov","middleInitial":"G.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":653406,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rao, Mahesh N.","contributorId":127588,"corporation":false,"usgs":false,"family":"Rao","given":"Mahesh","email":"","middleInitial":"N.","affiliations":[{"id":7067,"text":"Humboldt State University","active":true,"usgs":false}],"preferred":false,"id":653407,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mohammed, Irshad A.","contributorId":176755,"corporation":false,"usgs":false,"family":"Mohammed","given":"Irshad A.","affiliations":[{"id":7069,"text":"International Crops Research Institute for the Semi Arid Tropics (ICRISAT)","active":true,"usgs":false}],"preferred":false,"id":653408,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Whitbread, Anthony M.","contributorId":176756,"corporation":false,"usgs":false,"family":"Whitbread","given":"Anthony","email":"","middleInitial":"M.","affiliations":[{"id":7069,"text":"International Crops Research Institute for the Semi Arid Tropics (ICRISAT)","active":true,"usgs":false}],"preferred":false,"id":653409,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70174051,"text":"70174051 - 2016 - Effect of diet quality on chronic toxicity of aqueous lead to the amphipod Hyalella azteca","interactions":[],"lastModifiedDate":"2018-08-07T12:26:29","indexId":"70174051","displayToPublicDate":"2016-05-03T13:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Effect of diet quality on chronic toxicity of aqueous lead to the amphipod Hyalella azteca","docAbstract":"The authors investigated the chronic toxicity of aqueous Pb to the amphipod Hyalella azteca (Hyalella) in 42-d tests using 2 different diets: 1) the yeastþcereal leafþtrout pellet (YCT) diet, fed at the uniform low ration used in standard methods for sediment toxicity tests; and 2) a new diet of diatomsþTetraMin flakes (DT), fed at increasing rations over time, that has been optimized for use in Hyalella water-only tests. Test endpoints included survival, weight, biomass, fecundity, and total young. Lethal effects of Pb were similar for the DT and YCT tests (20% lethal concentration [LC20]¼13 mg/L and 15mg/L, respectively, as filterable Pb). In contrast, weight and fecundity endpoints were not significantly affected in the DT test at Pb concentrations up to 63 mg/L, but these endpoints were significantly reduced by Pb in the YCT test—and in a 2005 test in the same laboratory with a diet of conditioned Rabbit Chow (RC-2005). The fecundity and total young endpoints from the YCT and RC-2005 tests were considered unreliable because fecundity in controls did not meet test acceptability criteria, but both of these tests still produced lower Pb effect concentrations (for weight or biomass) than the test with the DT diet. The lowest biotic ligand model–normalized effect concentrations for the 3 tests ranged from 3.7mg/L (weight 20% effect concentration [EC20] for the RC-2005 test) to 8.2 mg/L (total young EC20 for the DT test), values that would rank Hyalella as the second or third most sensitive of 13 genera in a species sensitivity distribution for chronic Pb toxicity. These results demonstrate that toxicity tests with Hyalella fed optimal diets can meet more stringent test acceptability criteria for control performance, but suggest that results of these tests may underestimate sublethal toxic effects of Pb to Hyalella under suboptimal feeding regimes.
","language":"English","publisher":"Setac Press","doi":"10.1002/etc.3341","usgsCitation":"Besser, J.M., Ivey, C.D., Brumbaugh, W.G., and Ingersoll, C.G., 2016, Effect of diet quality on chronic toxicity of aqueous lead to the amphipod Hyalella azteca: Environmental Toxicology and Chemistry, v. 35, p. 1825-1834, https://doi.org/10.1002/etc.3341.","productDescription":"10 p.","startPage":"1825","endPage":"1834","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063482","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":324365,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"35","edition":"7","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-18","publicationStatus":"PW","scienceBaseUri":"576e59aee4b07657d1a43c55","contributors":{"authors":[{"text":"Besser, John M. 0000-0002-9464-2244 jbesser@usgs.gov","orcid":"https://orcid.org/0000-0002-9464-2244","contributorId":2073,"corporation":false,"usgs":true,"family":"Besser","given":"John","email":"jbesser@usgs.gov","middleInitial":"M.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":640705,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ivey, Chris D. 0000-0002-0485-7242 civey@usgs.gov","orcid":"https://orcid.org/0000-0002-0485-7242","contributorId":3308,"corporation":false,"usgs":true,"family":"Ivey","given":"Chris","email":"civey@usgs.gov","middleInitial":"D.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":640706,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brumbaugh, William G. 0000-0003-0081-375X bbrumbaugh@usgs.gov","orcid":"https://orcid.org/0000-0003-0081-375X","contributorId":493,"corporation":false,"usgs":true,"family":"Brumbaugh","given":"William","email":"bbrumbaugh@usgs.gov","middleInitial":"G.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":640707,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ingersoll, Christopher G. 0000-0003-4531-5949 cingersoll@usgs.gov","orcid":"https://orcid.org/0000-0003-4531-5949","contributorId":2071,"corporation":false,"usgs":true,"family":"Ingersoll","given":"Christopher","email":"cingersoll@usgs.gov","middleInitial":"G.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":640708,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70170803,"text":"70170803 - 2016 - Flow management for hydropower extirpates aquatic insects, undermining river food webs","interactions":[],"lastModifiedDate":"2016-07-07T10:06:15","indexId":"70170803","displayToPublicDate":"2016-05-02T11:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":997,"text":"BioScience","active":true,"publicationSubtype":{"id":10}},"title":"Flow management for hydropower extirpates aquatic insects, undermining river food webs","docAbstract":"Dams impound the majority of rivers and provide important societal benefits, especially daily water releases that enable on-peak hydroelectricity generation. Such “hydropeaking” is common worldwide, but its downstream impacts remain unclear. We evaluated the response of aquatic insects, a cornerstone of river food webs, to hydropeaking using a life history–hydrodynamic model. Our model predicts that aquatic-insect abundance will depend on a basic life-history trait—adult egg-laying behavior—such that open-water layers will be unaffected by hydropeaking, whereas ecologically important and widespread river-edge layers, such as mayflies, will be extirpated. These predictions are supported by a more-than-2500-sample, citizen-science data set of aquatic insects from the Colorado River in the Grand Canyon and by a survey of insect diversity and hydropeaking intensity across dammed rivers of the Western United States. Our study reveals a hydropeaking-related life history bottleneck that precludes viable populations of many aquatic insects from inhabiting regulated rivers.
","language":"English","publisher":"American Institute of Biological Sciences","publisherLocation":"Washington, D.C.","doi":"10.1093/biosci/biw059","usgsCitation":"Kennedy, T.A., Muehlbauer, J.D., Yackulic, C.B., Lytle, D., Miller, S., Dibble, K.L., Kortenhoeven, E.W., Metcalfe, A.N., and Baxter, C., 2016, Flow management for hydropower extirpates aquatic insects, undermining river food webs: BioScience, v. 66, no. 7, p. 561-575, https://doi.org/10.1093/biosci/biw059.","productDescription":"15 p.","startPage":"561","endPage":"575","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069041","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":471029,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/biosci/biw059","text":"Publisher Index Page"},{"id":438616,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7WM1BH4","text":"USGS data release","linkHelpText":"Flow management for hydropower extirpates aquatic insects, undermining river food websData"},{"id":320875,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"66","issue":"7","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-02","publicationStatus":"PW","scienceBaseUri":"5729cbb2e4b0b13d3919a342","contributors":{"authors":[{"text":"Kennedy, Theodore A. 0000-0003-3477-3629 tkennedy@usgs.gov","orcid":"https://orcid.org/0000-0003-3477-3629","contributorId":167537,"corporation":false,"usgs":true,"family":"Kennedy","given":"Theodore","email":"tkennedy@usgs.gov","middleInitial":"A.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":628488,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Muehlbauer, Jeffrey D. 0000-0003-1808-580X jmuehlbauer@usgs.gov","orcid":"https://orcid.org/0000-0003-1808-580X","contributorId":5045,"corporation":false,"usgs":true,"family":"Muehlbauer","given":"Jeffrey","email":"jmuehlbauer@usgs.gov","middleInitial":"D.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":628490,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yackulic, Charles B. 0000-0001-9661-0724 cyackulic@usgs.gov","orcid":"https://orcid.org/0000-0001-9661-0724","contributorId":4662,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","email":"cyackulic@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":628489,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lytle, D.A.","contributorId":85422,"corporation":false,"usgs":true,"family":"Lytle","given":"D.A.","email":"","affiliations":[],"preferred":false,"id":628491,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Miller, S.A.","contributorId":66389,"corporation":false,"usgs":true,"family":"Miller","given":"S.A.","email":"","affiliations":[],"preferred":false,"id":628492,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dibble, Kimberly L. 0000-0003-0799-4477 kdibble@usgs.gov","orcid":"https://orcid.org/0000-0003-0799-4477","contributorId":5174,"corporation":false,"usgs":true,"family":"Dibble","given":"Kimberly","email":"kdibble@usgs.gov","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":628500,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kortenhoeven, Eric W. ekortenhoeven@usgs.gov","contributorId":5046,"corporation":false,"usgs":true,"family":"Kortenhoeven","given":"Eric","email":"ekortenhoeven@usgs.gov","middleInitial":"W.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":628493,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Metcalfe, Anya N. 0000-0002-6286-4889 ametcalfe@usgs.gov","orcid":"https://orcid.org/0000-0002-6286-4889","contributorId":5271,"corporation":false,"usgs":true,"family":"Metcalfe","given":"Anya","email":"ametcalfe@usgs.gov","middleInitial":"N.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":628494,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Baxter, Colden V.","contributorId":47334,"corporation":false,"usgs":false,"family":"Baxter","given":"Colden V.","affiliations":[{"id":13656,"text":"Idaho State Univ.","active":true,"usgs":false}],"preferred":false,"id":628501,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70170755,"text":"70170755 - 2016 - Preface: Land subsidence processes","interactions":[],"lastModifiedDate":"2019-09-06T11:12:11","indexId":"70170755","displayToPublicDate":"2016-05-02T11:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1923,"text":"Hydrogeology Journal","active":true,"publicationSubtype":{"id":10}},"title":"Preface: Land subsidence processes","docAbstract":"No abstract available.
","language":"English","publisher":"Springer","doi":"10.1007/s10040-016-1386-y","usgsCitation":"Galloway, D.L., Erkens, G., Kuniansky, E.L., and Rowland, J.C., 2016, Preface: Land subsidence processes: Hydrogeology Journal, v. 24, no. 3, p. 547-550, https://doi.org/10.1007/s10040-016-1386-y.","productDescription":"3 p.","startPage":"547","endPage":"550","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-072759","costCenters":[{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":471031,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10040-016-1386-y","text":"Publisher Index Page"},{"id":320814,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"24","issue":"3","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-03-04","publicationStatus":"PW","scienceBaseUri":"57286c1be4b0b13d3917ce10","contributors":{"authors":[{"text":"Galloway, Devin L. 0000-0003-0904-5355 dlgallow@usgs.gov","orcid":"https://orcid.org/0000-0003-0904-5355","contributorId":679,"corporation":false,"usgs":true,"family":"Galloway","given":"Devin","email":"dlgallow@usgs.gov","middleInitial":"L.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true},{"id":5078,"text":"Southwest Regional Director's Office","active":true,"usgs":true},{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true},{"id":5058,"text":"Office of the Chief Scientist for Water","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":628277,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Erkens, Gilles","contributorId":169045,"corporation":false,"usgs":false,"family":"Erkens","given":"Gilles","email":"","affiliations":[{"id":25398,"text":"Deltares Research Institute, The Netherlands","active":true,"usgs":false}],"preferred":false,"id":628278,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kuniansky, Eve L. 0000-0002-5581-0225 elkunian@usgs.gov","orcid":"https://orcid.org/0000-0002-5581-0225","contributorId":932,"corporation":false,"usgs":true,"family":"Kuniansky","given":"Eve","email":"elkunian@usgs.gov","middleInitial":"L.","affiliations":[{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true},{"id":5064,"text":"Southeast Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":628279,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rowland, Joel C.","contributorId":169046,"corporation":false,"usgs":false,"family":"Rowland","given":"Joel","email":"","middleInitial":"C.","affiliations":[{"id":13447,"text":"Los Alamos National Laboratory","active":true,"usgs":false}],"preferred":false,"id":628280,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70170759,"text":"70170759 - 2016 - Hydrologic exchanges and baldcypress water use on deltaic hummocks, Louisiana, USA","interactions":[],"lastModifiedDate":"2016-12-09T16:35:39","indexId":"70170759","displayToPublicDate":"2016-05-02T11:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1447,"text":"Ecohydrology","active":true,"publicationSubtype":{"id":10}},"title":"Hydrologic exchanges and baldcypress water use on deltaic hummocks, Louisiana, USA","docAbstract":"Coastal forested hummocks support clusters of trees in the saltwater–freshwater transition zone. To examine how hummocks support trees in mesohaline sites that are beyond physiological limits of the trees, we used salinity and stable isotopes (2H and 18O) of water as tracers to understand water fluxes in hummocks and uptake by baldcypress (Taxodium distichum (L.) Rich.), which is the most abundant tree species in coastal freshwater forests of the southeastern U.S. Hummocks were always partially submerged and were completely submerged 1 to 8% of the time during the two studied growing seasons, in association with high water in the estuary. Salinity, δ18O, and δ2H varied more in the shallow open water than in groundwater. Surface water and shallow groundwater were similar to throughfall in isotopic composition, which suggested dominance by rainfall. Salinity of groundwater in hummocks increased with depth, was higher than in swales, and fluctuated little over time. Isotopic composition of xylem water in baldcypress was similar to the vadose zone and unlike other measured sources, indicating that trees preferentially use unsaturated hummock tops as refugia from higher salinity and saturated soil in swales and the lower portions of hummocks. Sustained upward gradients of salinity from groundwater to surface water and vadose water, and low variation in groundwater salinity and isotopic composition, suggested long residence time, limited exchange with surface water, and that the shallow subsurface of hummocks is characterized by episodic salinization and slow dilution.
","language":"English","publisher":"Wiley","doi":"10.1002/eco.1738","usgsCitation":"Hsueh, Y., Chambers, J., Krauss, K.W., Allen, S.T., and Keim, R., 2016, Hydrologic exchanges and baldcypress water use on deltaic hummocks, Louisiana, USA: Ecohydrology, v. 9, no. 8, p. 1452-1463, https://doi.org/10.1002/eco.1738.","productDescription":"12 p.","startPage":"1452","endPage":"1463","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-067366","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":320812,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Jean Lafitte National Historical Park and Preserve","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.14,\n 29.75\n ],\n [\n -90.14,\n 29.76\n ],\n [\n -90.15,\n 29.76\n ],\n [\n -90.15,\n 29.75\n ],\n [\n -90.14,\n 29.75\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"9","issue":"8","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2016-04-28","publicationStatus":"PW","scienceBaseUri":"57286c1be4b0b13d3917ce0e","contributors":{"authors":[{"text":"Hsueh, Yu-Hsin","contributorId":169051,"corporation":false,"usgs":false,"family":"Hsueh","given":"Yu-Hsin","email":"","affiliations":[],"preferred":false,"id":628310,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chambers, Jim L.","contributorId":16498,"corporation":false,"usgs":true,"family":"Chambers","given":"Jim L.","affiliations":[],"preferred":false,"id":628311,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":628298,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Allen, Scott T.","contributorId":168409,"corporation":false,"usgs":false,"family":"Allen","given":"Scott","email":"","middleInitial":"T.","affiliations":[{"id":25282,"text":"School of Renewable Natural Resources, Louisiana State University, Baton Rouge, LA","active":true,"usgs":false}],"preferred":false,"id":628312,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Keim, Richard F.","contributorId":21858,"corporation":false,"usgs":true,"family":"Keim","given":"Richard F.","affiliations":[],"preferred":false,"id":628313,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70162383,"text":"sir20165008 - 2016 - Geology of tight oil and potential tight oil reservoirs in the lower part of the Green River Formation, Uinta, Piceance, and Greater Green River Basins, Utah, Colorado, and Wyoming","interactions":[],"lastModifiedDate":"2016-05-02T10:42:55","indexId":"sir20165008","displayToPublicDate":"2016-05-02T10:00:00","publicationYear":"2016","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":"2016-5008","title":"Geology of tight oil and potential tight oil reservoirs in the lower part of the Green River Formation, Uinta, Piceance, and Greater Green River Basins, Utah, Colorado, and Wyoming","docAbstract":"The recent successful development of a tight oil play in the Eocene-age informal Uteland Butte member of the lacustrine Green River Formation in the Uinta Basin, Utah, using modern horizontal drilling and hydraulic fracturing techniques has spurred a renewed interest in the tight oil potential of lacustrine rocks. The Green River Formation was deposited by two large lakes, Lake Uinta in the Uinta and Piceance Basins and Lake Gosiute in the Greater Green River Basin. These three basins contain the world’s largest in-place oil shale resources with recent estimates of 1.53 trillion, 1.33 trillion, and 1.44 trillion barrels of oil in place in the Piceance, Uinta, and Greater Green River Basins, respectively. The Uteland Butte member was deposited during an early freshwater stage of the lake in the Uinta Basin prior to deposition of the assessed oil shale intervals. This report only presents information on the early freshwater interval and overlying brackish-water interval in all three basins because these intervals are most likely to have tight oil potential. Burial histories of the three basins were reconstructed to study (1) variations in subsidence and lake development, and (2) post deposition burial that led to the development of a petroleum system in only the Uinta Basin. The Uteland Butte member is a successful tight oil play because it is thermally mature for hydrocarbon generation and contains organic-rich shale, brittle carbonate, and porous dolomite. Abnormally high pressure in parts of the Uteland Butte is also important to production. Variations in organic richness of the Uteland Butte were studied using Fischer assay analysis from oil shale assessments, and pressures were studied using drill-stem tests. Freshwater lacustrine intervals in the Piceance and Greater Green River Basins are immature for hydrocarbon generation and contain much less carbonate than the Uteland Butte member. The brackish-water interval in the Uinta Basin is thermally mature for hydrocarbon generation but is clay-rich and contains little carbonate, and thus is a poor prospect for tight oil development.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165008","usgsCitation":"Johnson, R.C., Birdwell, J.E., Mercier, T.J., and Brownfield, M.E., 2016, Geology of tight oil and potential tight oil reservoirs in the lower part of the Green River Formation, Uinta, Piceance, and Greater Green River Basins, Utah, Colorado, and Wyoming: U.S. Geological Survey Scientific Investigations Report 2016–5008, 63 p., https://dx.doi.org/10.3133/sir20165008.","productDescription":"Report: vii, 63 p.; Table 1; Figure 29","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-059890","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":320649,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5008/coverthb.jpg"},{"id":320650,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5008/sir20165008.pdf","text":"Report","size":"53.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5008"},{"id":320651,"rank":3,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/sir/2016/5008/sir20165008_fig29.pdf","text":"Figure 29","size":"1.02 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5008 Figure 29"},{"id":320672,"rank":4,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2016/5008/sir20165008_Table1UtelandFischerassay.xlsx","text":"Table 1","size":"68.0 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2016-5008 Table 1"}],"country":"United States","state":"Colorado, Utah, Wyoming","otherGeospatial":"Green River Basin, Piceance River Basin, Uinta River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.566162109375,\n 38.62545397209084\n ],\n [\n -111.566162109375,\n 43.30119623257966\n ],\n [\n -106.336669921875,\n 43.30119623257966\n ],\n [\n -106.336669921875,\n 38.62545397209084\n ],\n [\n -111.566162109375,\n 38.62545397209084\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Center Director, USGS Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver Federal Center
Denver, CO 80225-0046
Taiyangshan is a poorly studied copper–molybdenum deposit located in the Triassic Western Qinling collisional belt of northwest China. The intrusions exposed in the vicinity of the Taiyangshan deposit record episodic magmatism over 20–30 million years. Pre-mineralization quartz diorite porphyries, which host some of the deposit, were emplaced at 226.6 ± 6.2 Ma. Syn-collisional monzonite and quartz monzonite porphyries, which also host mineralization, were emplaced at 218.0 ± 6.1 Ma and 215.0 ± 5.8 Ma, respectively. Mineralization occurred during the transition from a syn-collisional to a post-collisional setting at ca. 208 Ma. A barren post-mineralization granite porphyry marked the end of post-collisional magmatism at 200.7 ± 5.1 Ma. The ore-bearing monzonite and quartz monzonite porphyries have a εHf(t) range from − 2.0 to + 12.5, which is much more variable than that of the slightly older quartz diorite porphyries, with TDM2 of 1.15–1.23 Ga corresponding to the positive εHf(t) values and TDM1 of 0.62–0.90 Ga corresponding to the negative εHf(t) values. Molybdenite in the Taiyangshan deposit with 27.70 to 38.43 ppm Re suggests metal sourced from a mantle–crust mixture or from mafic and ultramafic rocks in the lower crust. The δ34S values obtained for pyrite, chalcopyrite, and molybdenite from the deposit range from + 1.3‰ to + 4.0‰, + 0.2‰ to + 1.1‰, and + 5.3‰ to + 5.9‰, respectively, suggesting a magmatic source for the sulfur. Calculated δ18Ofluid values for magmatic K-feldspar from porphyries (+ 13.3‰), hydrothermal K-feldspar from stockwork veins related to potassic alteration (+ 11.6‰), and hydrothermal sericite from quartz–pyrite veins (+ 8.6 to + 10.6‰) indicate the Taiyangshan deposit formed dominantly from magmatic water. Hydrogen isotope values for hydrothermal sericite ranging from − 85 to − 50‰ may indicate that magma degassing progressively depleted residual liquid in deuterium during the life of the magmatic–hydrothermal system. Alternatively, δD variability may have been caused by a minor amount of mixing with meteoric waters. We propose that the ore-related magma was derived from partial melting of the ancient Mesoproterozoic to Neoproterozoic middle to lower continental crust. This crust was likely metasomatized during earlier subduction, and the crustal magmas may have been contaminated with lithospheric mantle derived magma triggered by MASH (e.g., melting, assimilation, storage, and homogenization) processes during collisional orogeny. In addition, a significant proportion of the metals and sulfur supplied from mafic magma were simultaneously incorporated into the resultant hybrid magmas.
","language":"English","publisher":"International Association for Gondwana Research","doi":"10.1016/j.gr.2016.03.014","usgsCitation":"Kun-Feng Qiu, Taylor, R.D., Song, Y., Yu, H., Kai-Rui Song, and Li, N., 2016, Geologic and geochemical insights into the formation of the Taiyangshan porphyry copper–molybdenum deposit, Western Qinling Orogenic Belt, China: Gondwana Research, v. 35, p. 40-58, https://doi.org/10.1016/j.gr.2016.03.014.","productDescription":"19 p.","startPage":"40","endPage":"58","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-072464","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":322044,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"China","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 102,\n 32\n ],\n [\n 102,\n 36\n ],\n [\n 107,\n 36\n ],\n [\n 107,\n 32\n ],\n [\n 102,\n 32\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"35","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57500763e4b0ee97d51bb609","contributors":{"authors":[{"text":"Kun-Feng Qiu","contributorId":169784,"corporation":false,"usgs":false,"family":"Kun-Feng Qiu","affiliations":[{"id":24737,"text":"China University of Geosciences, Beijing","active":true,"usgs":false}],"preferred":false,"id":631055,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Taylor, Ryan D. 0000-0002-8845-5290 rtaylor@usgs.gov","orcid":"https://orcid.org/0000-0002-8845-5290","contributorId":3412,"corporation":false,"usgs":true,"family":"Taylor","given":"Ryan","email":"rtaylor@usgs.gov","middleInitial":"D.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":631054,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Song, Yao-Hui","contributorId":169785,"corporation":false,"usgs":false,"family":"Song","given":"Yao-Hui","email":"","affiliations":[{"id":24737,"text":"China University of Geosciences, Beijing","active":true,"usgs":false}],"preferred":false,"id":631056,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Yu, Hao-Cheng","contributorId":169788,"corporation":false,"usgs":false,"family":"Yu","given":"Hao-Cheng","email":"","affiliations":[{"id":24737,"text":"China University of Geosciences, Beijing","active":true,"usgs":false}],"preferred":false,"id":631059,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kai-Rui Song","contributorId":169786,"corporation":false,"usgs":false,"family":"Kai-Rui Song","affiliations":[{"id":24737,"text":"China University of Geosciences, Beijing","active":true,"usgs":false}],"preferred":false,"id":631057,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Li, Nan","contributorId":169787,"corporation":false,"usgs":false,"family":"Li","given":"Nan","email":"","affiliations":[{"id":24737,"text":"China University of Geosciences, Beijing","active":true,"usgs":false}],"preferred":false,"id":631058,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70174339,"text":"70174339 - 2016 - A millennial-scale record of Pb and Hg contamination in peatlands of the Sacramento-San Joaquin Delta of California, USA","interactions":[],"lastModifiedDate":"2016-07-08T13:22:05","indexId":"70174339","displayToPublicDate":"2016-05-01T14:30:00","publicationYear":"2016","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}},"title":"A millennial-scale record of Pb and Hg contamination in peatlands of the Sacramento-San Joaquin Delta of California, USA","docAbstract":"In this paper, we provide the first record of millennial patterns of Pb and Hg concentrations on the west coast of the United States. Peat cores were collected from two micro-tidal marshes in the Sacramento-San Joaquin Delta of California. Core samples were analyzed for Pb, Hg, and Ti concentrations and dated using radiocarbon, 210Pb, and 137Cs. Pre-anthropogenic concentrations of Pb and Hg in peat ranged from 0.60 to 13.0 µg g-1and from 6.9 to 71 ng g-1, respectively. For much of the past 6000+ years, the Delta was free from anthropogenic pollution, however, beginning in ~1425 CE, Hg and Pb concentrations, Pb/Ti ratios, Pb enrichment factors (EFs), and HgEFs all increased. Pb isotope compositions of the peat suggest that this uptick was likely caused by smelting activities originating in Asia. The next increases in Pb and Hg contamination occurred during the California Gold Rush (beginning ~1850 CE), when concentrations reached their highest levels (74 µg g-1 Pb, 990 ng g-1 Hg; PbEF = 12 and HgEF = 28). Lead concentrations increased again beginning in the ~1920s with the incorporation of Pb additives in gasoline. The phase-out of lead additives in the late 1980s was reflected in Pb isotope ratios and reductions in Pb concentrations in the surface layers of the peat. The rise and fall of Hg contamination was also tracked by the peat archive, with the highest Hg concentrations occurring just before 1963 CE and then decreasing during the post-1963 period. Overall, the results show that the Delta was a pristine region for most of its ~6700-year existence; however, since ~1425 CE, it has received Pb and Hg contamination from both global and regional sources.
","language":"English","publisher":"Elsevier B.V.","doi":"10.1016/j.scitotenv.2016.01.201","collaboration":"(REPEAT II project)","usgsCitation":"Drexler, J.Z., Alpers, C.N., Neymark, L., Paces, J.B., Taylor, H.E., and Fuller, C.C., 2016, A millennial-scale record of Pb and Hg contamination in peatlands of the Sacramento-San Joaquin Delta of California, USA: Science of the Total Environment, v. 551-552, p. 738-751, https://doi.org/10.1016/j.scitotenv.2016.01.201.","productDescription":"13 p.","startPage":"738","endPage":"751","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-071457","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":324937,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento–San Joaquin Delta of California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.25537109375,\n 41.94314874732696\n ],\n [\n -124.3212890625,\n 41.73852846935917\n ],\n [\n -124.20043945312499,\n 41.65649719441145\n ],\n [\n -124.178466796875,\n 41.36856413680967\n ],\n [\n -124.31030273437499,\n 41.16211393939692\n ],\n [\n -124.222412109375,\n 40.95501133048621\n ],\n [\n -124.53002929687499,\n 40.463666324587685\n ],\n [\n -124.45312499999999,\n 40.245991504199026\n ],\n [\n -123.90380859374999,\n 39.69873414348139\n ],\n [\n -123.914794921875,\n 39.317300373271024\n ],\n [\n -123.85986328124999,\n 38.89103282648846\n ],\n [\n -123.6181640625,\n 38.7283759182398\n ],\n [\n -123.11279296875001,\n 38.08268954483802\n ],\n [\n -123.07983398437499,\n 37.94419750075404\n ],\n [\n -122.84912109375,\n 37.90953361677018\n ],\n [\n -122.78320312499999,\n 37.57070524233116\n ],\n [\n -122.56347656249999,\n 37.59682400108367\n ],\n [\n -121.10229492187501,\n 37.75334401310656\n ],\n [\n -121.322021484375,\n 38.59970036588819\n ],\n [\n -121.79443359375,\n 39.78321267821705\n ],\n [\n -121.728515625,\n 40.830436877649255\n ],\n [\n -121.89331054687499,\n 41.623655390686395\n ],\n [\n -121.92626953124999,\n 41.97582726102573\n ],\n [\n -124.25537109375,\n 41.94314874732696\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"551-552","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5780ceaee4b0811616822296","contributors":{"authors":[{"text":"Drexler, Judith Z. 0000-0002-0127-3866 jdrexler@usgs.gov","orcid":"https://orcid.org/0000-0002-0127-3866","contributorId":167492,"corporation":false,"usgs":true,"family":"Drexler","given":"Judith","email":"jdrexler@usgs.gov","middleInitial":"Z.","affiliations":[{"id":5044,"text":"National Research Program - 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This study evaluated the potential to map riverbed composition based on in situ and/or remote measurements of reflectance. Field spectra and substrate photos from the Snake River, Wyoming, USA, were used to identify different sediment facies and degrees of algal development and to quantify their optical characteristics. We hypothesized that accounting for the effects of depth and water column attenuation to isolate the reflectance of the streambed would enhance distinctions among bottom types and facilitate substrate classification. A bottom reflectance retrieval algorithm adapted from coastal research yielded realistic spectra for the 450 to 700 nm range; but bottom reflectance-based substrate classifications, generated using a random forest technique, were no more accurate than classifications derived from above-water field spectra. Additional hypothesis testing indicated that a combination of reflectance magnitude (brightness) and indices of spectral shape provided the most accurate riverbed classifications. Convolving field spectra to the response functions of a multispectral satellite and a hyperspectral imaging system did not reduce classification accuracies, implying that high spectral resolution was not essential. Supervised classifications of algal density produced from hyperspectral data and an inferred bottom reflectance image were not highly accurate, but unsupervised classification of the bottom reflectance image revealed distinct spectrally based clusters, suggesting that such an image could provide additional river information. We attribute the failure of bottom reflectance retrieval to yield more reliable substrate maps to a latent correlation between depth and bottom type. Accounting for the effects of depth might have eliminated a key distinction among substrates and thus reduced discriminatory power. Although further, more systematic study across a broader range of fluvial environments is needed to substantiate our initial results, this case study suggests that bed composition in shallow, clear-flowing rivers potentially could be mapped remotely.
","language":"English","publisher":"Elsevier Science Pub. Co.","publisherLocation":"New York, NY","doi":"10.1016/j.geomorph.2016.04.006","usgsCitation":"Legleiter, C.J., Stegman, T.K., and Overstreet, B.T., 2016, Spectrally based mapping of riverbed composition: Geomorphology, v. 264, p. 61-79, https://doi.org/10.1016/j.geomorph.2016.04.006.","productDescription":"19 p.","startPage":"61","endPage":"79","numberOfPages":"19","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-073537","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":471034,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.geomorph.2016.04.006","text":"Publisher Index Page"},{"id":320883,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"264","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5729cbbae4b0b13d3919a3c6","contributors":{"authors":[{"text":"Legleiter, Carl J. 0000-0003-0940-8013 cjl@usgs.gov","orcid":"https://orcid.org/0000-0003-0940-8013","contributorId":169002,"corporation":false,"usgs":true,"family":"Legleiter","given":"Carl","email":"cjl@usgs.gov","middleInitial":"J.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":628405,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stegman, Tobin K.","contributorId":169087,"corporation":false,"usgs":false,"family":"Stegman","given":"Tobin","email":"","middleInitial":"K.","affiliations":[{"id":6656,"text":"University of Wyoming, Renewable Resources","active":true,"usgs":false}],"preferred":false,"id":628406,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Overstreet, Brandon T. 0000-0001-7845-6671","orcid":"https://orcid.org/0000-0001-7845-6671","contributorId":63257,"corporation":false,"usgs":true,"family":"Overstreet","given":"Brandon","email":"","middleInitial":"T.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":false,"id":628407,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70171438,"text":"70171438 - 2016 - Regional patterns of total nitrogen concentrations in the National Rivers and Streams Assessment","interactions":[],"lastModifiedDate":"2017-01-18T09:20:26","indexId":"70171438","displayToPublicDate":"2016-05-01T01:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2456,"text":"Journal of Soil and Water Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Regional patterns of total nitrogen concentrations in the National Rivers and Streams Assessment","docAbstract":"Patterns of nitrogen (N) concentrations in streams sampled by the National Rivers and Streams Assessment (NRSA) were examined semiquantitatively to identify regional differences in stream N levels. The data were categorized and analyzed by watershed size classes to reveal patterns of the concentrations that are consistent with the spatial homogeneity in natural and anthropogenic characteristics associated with regional differences in N levels. Ecoregions and mapped information on human activities including agricultural practices were used to determine the resultant regions. Marked differences in N levels were found among the nine aggregations of ecoregions used to report the results of the NRSA. We identified distinct regional patterns of stream N concentrations within the reporting regions that are associated with the characteristics of specific Level III ecoregions, groups of Level III ecoregions, groups of Level IV ecoregions, certain geographic characteristics within ecoregions, and/or particular watershed size classes. We described each of these regions and illustrated their areal extent and median and range in N concentrations. Understanding the spatial variability of nutrient concentrations in flowing waters and the apparent contributions that human and nonhuman factors have on different sizes of streams and rivers is critical to the development of effective water quality assessment and management plans. This semi-quantitative analysis is also intended to identify areas within which more detailed quantitative work can be conducted to determine specific regional factors associated with variations in stream N concentrations.
","language":"English","publisher":"Soil and Water Conservation Society","doi":"10.2489/jswc.71.3.167","usgsCitation":"Omernik, J.M., Paulsen, S.G., Griffith, G.E., and Weber, M.H., 2016, Regional patterns of total nitrogen concentrations in the National Rivers and Streams Assessment: Journal of Soil and Water Conservation, v. 71, no. 3, p. 167-181, https://doi.org/10.2489/jswc.71.3.167.","productDescription":"15 p.","startPage":"167","endPage":"181","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057215","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":322053,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"71","issue":"3","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-09","publicationStatus":"PW","scienceBaseUri":"57500771e4b0ee97d51bb70e","contributors":{"authors":[{"text":"Omernik, James M.","contributorId":169740,"corporation":false,"usgs":false,"family":"Omernik","given":"James","email":"","middleInitial":"M.","affiliations":[{"id":25578,"text":"USGS -Volunteer","active":true,"usgs":false}],"preferred":false,"id":630982,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Paulsen, Steven G.","contributorId":169741,"corporation":false,"usgs":false,"family":"Paulsen","given":"Steven","email":"","middleInitial":"G.","affiliations":[{"id":13529,"text":"US Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":630983,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Griffith, Glenn E. 0000-0001-7966-4720 ggriffith@usgs.gov","orcid":"https://orcid.org/0000-0001-7966-4720","contributorId":4053,"corporation":false,"usgs":true,"family":"Griffith","given":"Glenn","email":"ggriffith@usgs.gov","middleInitial":"E.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":630981,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Weber, Marc H.","contributorId":169742,"corporation":false,"usgs":false,"family":"Weber","given":"Marc","email":"","middleInitial":"H.","affiliations":[{"id":13529,"text":"US Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":630984,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ]}