This is the fifty-fourth in a series of annual reports that describe groundwater conditions in Utah. Reports in this series, published cooperatively by the U.S. Geological Survey and the Utah Department of Natural Resources, Division of Water Rights, and the Utah Department of Environmental Quality, Division of Water Quality, provide data to enable interested parties to maintain awareness of changing groundwater conditions.
This report, like the others in the series, contains information on well construction, groundwater withdrawals from wells, water-level changes, precipitation, streamflow, and chemical quality of water. Information on well construction included in this report refers only to new wells constructed for withdrawal of groundwater. Supplementary data are included in reports of this series only for those years or areas that are important to a discussion of changing groundwater conditions and for which applicable data are available.
This report includes individual discussions of selected significant areas of groundwater development in the State for calendar year 2016. Most of the reported data were collected by the U.S. Geological Survey in cooperation with the Utah Department of Natural Resources, Division of Water Rights, and the Utah Department of Environmental Quality, Division of Water Quality. This report is also available online at http://www.waterrights.utah.gov/techinfo/ and http://ut.water.usgs.gov/publications/GW2017.pdf.
Groundwater conditions in Utah for calendar year 2015 are reported in Burden and others (2016) and are available online at http://ut.water.usgs.gov/publications/GW2016.pdf.
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\"}}]}","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fbeee4b06e28e9c237a6","contributors":{"authors":[{"text":"Burden, Carole B. cburden@usgs.gov","contributorId":852,"corporation":false,"usgs":true,"family":"Burden","given":"Carole","email":"cburden@usgs.gov","middleInitial":"B.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":718085,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70190700,"text":"70190700 - 2017 - Inter-nesting movements and habitat-use of adult female Kemp’s ridley turtles in the Gulf of Mexico","interactions":[],"lastModifiedDate":"2017-09-12T15:09:37","indexId":"70190700","displayToPublicDate":"2017-04-01T00:00:00","publicationYear":"2017","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":"Inter-nesting movements and habitat-use of adult female Kemp’s ridley turtles in the Gulf of Mexico","docAbstract":"Species vulnerability is increased when individuals congregate in restricted areas for breeding; yet, breeding habitats are not well defined for many marine species. Identification and quantification of these breeding habitats are essential to effective conservation. Satellite telemetry and switching state-space modeling (SSM) were used to define inter-nesting habitat of endangered Kemp’s ridley turtles (Lepidochelys kempii) in the Gulf of Mexico. Turtles were outfitted with satellite transmitters after nesting at Padre Island National Seashore, Texas, USA, from 1998 through 2013 (n = 60); Rancho Nuevo, Tamaulipas, Mexico, during 2010 and 2011 (n = 11); and Tecolutla, Veracruz, Mexico, during 2012 and 2013 (n = 11). These sites span the range of nearly all nesting by this species. Inter-nesting habitat lies in a narrow band of nearshore western Gulf of Mexico waters in the USA and Mexico, with mean water depth of 14 to 19 m within a mean distance to shore of 6 to 11 km as estimated by 50% kernel density estimate, α-Hull, and minimum convex polygon methodologies. Turtles tracked during the inter-nesting period moved, on average, 17.5 km/day and a mean total distance of 398 km. Mean home ranges occupied were 725 to 2948 km2. Our results indicate that these nearshore western Gulf waters represent critical inter-nesting habitat for this species, where threats such as shrimp trawling and oil and gas platforms also occur. Up to half of all adult female Kemp’s ridleys occupy this habitat for weeks to months during each nesting season. Because inter-nesting habitat for this species is concentrated in nearshore waters of the western Gulf of Mexico in both Mexico and the USA, international collaboration is needed to protect this essential habitat and the turtles occurring within it.
","language":"English","publisher":"PLOS ONE","doi":"10.1371/journal.pone.0174248","usgsCitation":"Shaver, D.J., Hart, K.M., Fujisaki, I., Bucklin, D.N., Iverson, A., Rubio, C., Backof, T.F., Burchfield, P.M., Gonzales Diaz Miron, R.D., Dutton, P.H., Frey, A., Peña, J., Gamez, D.G., Martinez, H.J., and Ortiz, J., 2017, Inter-nesting movements and habitat-use of adult female Kemp’s ridley turtles in the Gulf of Mexico: PLoS ONE, v. 12, no. 3, e0174248; 27 p., https://doi.org/10.1371/journal.pone.0174248.","productDescription":"e0174248; 27 p.","ipdsId":"IP-074667","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":469969,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0174248","text":"Publisher Index Page"},{"id":345671,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico, United States","otherGeospatial":"Gulf of Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -98.3056640625,\n 18.771115062337024\n ],\n [\n -95.29541015625,\n 18.771115062337024\n ],\n [\n -95.29541015625,\n 28.998531814051795\n ],\n [\n -98.3056640625,\n 28.998531814051795\n ],\n [\n -98.3056640625,\n 18.771115062337024\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"12","issue":"3","noUsgsAuthors":false,"publicationDate":"2017-03-20","publicationStatus":"PW","scienceBaseUri":"59b8f21fe4b08b1644e0aee5","contributors":{"authors":[{"text":"Shaver, Donna J.","contributorId":11104,"corporation":false,"usgs":true,"family":"Shaver","given":"Donna","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":710208,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hart, Kristen M. 0000-0002-5257-7974 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M.","contributorId":47676,"corporation":false,"usgs":true,"family":"Burchfield","given":"Patrick","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":710215,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Gonzales Diaz Miron, Raul de Jesus","contributorId":168393,"corporation":false,"usgs":false,"family":"Gonzales Diaz Miron","given":"Raul","email":"","middleInitial":"de Jesus","affiliations":[],"preferred":false,"id":710216,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Dutton, Peter H.","contributorId":98029,"corporation":false,"usgs":true,"family":"Dutton","given":"Peter","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":710217,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Frey, Amy","contributorId":196390,"corporation":false,"usgs":false,"family":"Frey","given":"Amy","email":"","affiliations":[],"preferred":false,"id":710218,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Peña, Jaime","contributorId":34810,"corporation":false,"usgs":true,"family":"Peña","given":"Jaime","affiliations":[],"preferred":false,"id":710219,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Gamez, Daniel Gomez","contributorId":32065,"corporation":false,"usgs":true,"family":"Gamez","given":"Daniel","email":"","middleInitial":"Gomez","affiliations":[],"preferred":false,"id":710220,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Martinez, Hector J.","contributorId":168394,"corporation":false,"usgs":false,"family":"Martinez","given":"Hector","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":710221,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Ortiz, 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widely utilized in natural gas systems for distinguishing microbial and thermogenic methane and for delineating methanogenic pathways (acetoclastic, hydrogenotrophic, and/or methylotrophic methanogenesis). Recent studies of coal and shale gas systems have characterized in situ microbial communities and provided stable isotope data (δD-CH4, δD-H2O, δ13C-CH4, and δ13C-CO2) from a wider range of environments than available previously. Here we review the principal biogenic methane-yielding pathways in coal beds and shales and the isotope effects imparted on methane, document the uncertainties and inconsistencies in established isotopic fingerprinting techniques, and identify the knowledge gaps in understanding the subsurface processes that govern H and C isotope signatures of biogenic methane. We also compare established isotopic interpretations with recent microbial community characterization techniques, which reveal additional inconsistencies in the interpretation of microbial metabolic pathways in coal beds and shales. Collectively, the re-assessed data show that widely-utilized isotopic fingerprinting techniques neglect important complications in coal beds and shales.
Isotopic fingerprinting techniques that combine δ13C-CH4 with δD-CH4 and/or δ13C-CO2have significant limitations: (1) The consistent ~ 160‰ offset between δD-H2O and δD-CH4 could imply that hydrogenotrophic methanogenesis is the dominant metabolic pathway in microbial gas systems. However, hydrogen isotopes can equilibrate between methane precursors and coexisting water, yielding a similar apparent H isotope signal as hydrogenotrophic methanogenesis, regardless of the actual methane formation pathway. (2) Non-methanogenic processes such as sulfate reduction, Fe oxide reduction, inputs of thermogenic methane, anaerobic methane oxidation, and/or formation water interaction can cause the apparent carbon isotope fractionation between δ13C-CH4 and δ13C-CO2(α13CCO2-CH4) to differ from the true methanogenic fractionation, complicating interpretation of methanogenic pathways. (3) Where little-fractionating non-methanogenic bacterial processes compete with highly-fractionating methanogenesis, the mass balance between CH4 and CO2 is affected. This has implications for δ13C values and provides an alternative interpretation for net C isotope signatures than solely the pathways used by active methanogens. (4) While most of the reviewed values of δD-H2O - δD-CH4 and α13CCO2-CH4 are apparently consistent with hydrogenotrophic methanogenesis as the dominant pathway in coal beds and shales, recent microbial community characterization techniques suggest a possible role for acetoclastic or methylotrophic methanogenesis in some basins.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.chemgeo.2017.01.027","usgsCitation":"Vinson, D.S., Blair, N.E., Martini, A.M., Larter, S., Orem, W.H., and McIntosh, J.C., 2017, Microbial methane from in situ biodegradation of coal and shale: A review and reevaluation of hydrogen and carbon isotope signatures: Chemical Geology, v. 453, p. 128-145, https://doi.org/10.1016/j.chemgeo.2017.01.027.","productDescription":"18 p.","startPage":"128","endPage":"145","ipdsId":"IP-073590","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":469977,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.chemgeo.2017.01.027","text":"Publisher Index Page"},{"id":342186,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"453","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5937bf2de4b0f6c2d0d9c756","contributors":{"authors":[{"text":"Vinson, David S.","contributorId":172390,"corporation":false,"usgs":false,"family":"Vinson","given":"David","email":"","middleInitial":"S.","affiliations":[{"id":25392,"text":"Department of Geography and Earth Science, University of North Carolina at Charlotte, North Carolina, USA","active":true,"usgs":false}],"preferred":false,"id":697341,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Blair, Neal E.","contributorId":192674,"corporation":false,"usgs":false,"family":"Blair","given":"Neal","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":697342,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Martini, Anna M.","contributorId":192675,"corporation":false,"usgs":false,"family":"Martini","given":"Anna","email":"","middleInitial":"M.","affiliations":[{"id":35249,"text":"Department of Geology, Amherst College","active":true,"usgs":false}],"preferred":false,"id":697343,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Larter, Steve","contributorId":192676,"corporation":false,"usgs":false,"family":"Larter","given":"Steve","email":"","affiliations":[],"preferred":false,"id":697344,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Orem, William H. 0000-0003-4990-0539 borem@usgs.gov","orcid":"https://orcid.org/0000-0003-4990-0539","contributorId":577,"corporation":false,"usgs":true,"family":"Orem","given":"William","email":"borem@usgs.gov","middleInitial":"H.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":697340,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McIntosh, Jennifer C.","contributorId":139870,"corporation":false,"usgs":false,"family":"McIntosh","given":"Jennifer","email":"","middleInitial":"C.","affiliations":[{"id":13301,"text":"Department of Hydrology and Water Resources, University of Arizona, Tucson, Arizona","active":true,"usgs":false}],"preferred":false,"id":697345,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70187329,"text":"70187329 - 2017 - A software tool to assess uncertainty in transient-storage model parameters using Monte Carlo simulations","interactions":[],"lastModifiedDate":"2017-04-28T15:43:43","indexId":"70187329","displayToPublicDate":"2017-04-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1699,"text":"Freshwater Science","active":true,"publicationSubtype":{"id":10}},"title":"A software tool to assess uncertainty in transient-storage model parameters using Monte Carlo simulations","docAbstract":"Researchers and practitioners alike often need to understand and characterize how water and solutes move through a stream in terms of the relative importance of in-stream and near-stream storage and transport processes. In-channel and subsurface storage processes are highly variable in space and time and difficult to measure. Storage estimates are commonly obtained using transient-storage models (TSMs) of the experimentally obtained solute-tracer test data. The TSM equations represent key transport and storage processes with a suite of numerical parameters. Parameter values are estimated via inverse modeling, in which parameter values are iteratively changed until model simulations closely match observed solute-tracer data. Several investigators have shown that TSM parameter estimates can be highly uncertain. When this is the case, parameter values cannot be used reliably to interpret stream-reach functioning. However, authors of most TSM studies do not evaluate or report parameter certainty. Here, we present a software tool linked to the One-dimensional Transport with Inflow and Storage (OTIS) model that enables researchers to conduct uncertainty analyses via Monte-Carlo parameter sampling and to visualize uncertainty and sensitivity results. We demonstrate application of our tool to 2 case studies and compare our results to output obtained from more traditional implementation of the OTIS model. We conclude by suggesting best practices for transient-storage modeling and recommend that future applications of TSMs include assessments of parameter certainty to support comparisons and more reliable interpretations of transport processes.
","language":"English","publisher":"University of Chicago Press","doi":"10.1086/690444","usgsCitation":"Ward, A.S., Kelleher, C.A., Mason, S.J., Wagener, T., McIntyre, N., McGlynn, B.L., Runkel, R.L., and Payn, R.A., 2017, A software tool to assess uncertainty in transient-storage model parameters using Monte Carlo simulations: Freshwater Science, v. 36, no. 1, p. 195-217, https://doi.org/10.1086/690444.","productDescription":"23 p.","startPage":"195","endPage":"217","ipdsId":"IP-074821","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":461661,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://research-information.bris.ac.uk/en/publications/2ec1a71e-046a-4faa-ad85-2f323af51119","text":"External Repository"},{"id":340632,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"36","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"590454a1e4b022cee40dc222","contributors":{"authors":[{"text":"Ward, Adam S.","contributorId":11508,"corporation":false,"usgs":true,"family":"Ward","given":"Adam","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":693393,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kelleher, Christa A.","contributorId":46417,"corporation":false,"usgs":true,"family":"Kelleher","given":"Christa","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":693394,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mason, Seth J. K.","contributorId":191535,"corporation":false,"usgs":false,"family":"Mason","given":"Seth","email":"","middleInitial":"J. K.","affiliations":[],"preferred":false,"id":693395,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wagener, Thorsten","contributorId":176323,"corporation":false,"usgs":false,"family":"Wagener","given":"Thorsten","email":"","affiliations":[],"preferred":false,"id":693396,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McIntyre, Neil","contributorId":191602,"corporation":false,"usgs":false,"family":"McIntyre","given":"Neil","email":"","affiliations":[],"preferred":false,"id":693397,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McGlynn, Brian L.","contributorId":83012,"corporation":false,"usgs":true,"family":"McGlynn","given":"Brian","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":693398,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Runkel, Robert L. 0000-0003-3220-481X runkel@usgs.gov","orcid":"https://orcid.org/0000-0003-3220-481X","contributorId":685,"corporation":false,"usgs":true,"family":"Runkel","given":"Robert","email":"runkel@usgs.gov","middleInitial":"L.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":693392,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Payn, Robert A.","contributorId":36461,"corporation":false,"usgs":true,"family":"Payn","given":"Robert","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":693399,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70188157,"text":"70188157 - 2017 - The role of uplift and erosion in the persistence of saline groundwater in the shallow subsurface","interactions":[],"lastModifiedDate":"2018-03-29T11:22:31","indexId":"70188157","displayToPublicDate":"2017-04-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"The role of uplift and erosion in the persistence of saline groundwater in the shallow subsurface","docAbstract":"In many regions of the world, the shallow (<300 m) subsurface is replenished with meteoric recharge within a few centuries or millennia, but in some regions saline groundwater persists despite abundant rainfall. Analyses of the flushing rate of shallow groundwater usually consider the permeability and recharge rate and a static landscape. The influence of landscape evolution can become important over millions of years, however. Here we present numerical simulations of fluid flow and transport in the top 1 km of a sedimentary foreland basin dominated by aquitards, where the rate of uplift and erosion (20 m Ma−1) balances that of meteoric flushing. Paleozoic age saline groundwater and brine persist at shallow depths that might otherwise have contained potable water. Similar hydrogeologic conditions, and uplift and erosion rates, likely exist in many other regions of the world, where a moving landscape has probably never been considered as an important contributor to groundwater quality.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2017GL072980","usgsCitation":"Yager, R.M., McCoy, K.J., Voss, C.I., Sanford, W.E., and Winston, R.B., 2017, The role of uplift and erosion in the persistence of saline groundwater in the shallow subsurface: Geophysical Research Letters, v. 44, no. 8, p. 3672-3681, https://doi.org/10.1002/2017GL072980.","productDescription":"10 p.","startPage":"3672","endPage":"3681","ipdsId":"IP-074589","costCenters":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true}],"links":[{"id":469971,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2017gl072980","text":"Publisher Index Page"},{"id":352930,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"44","issue":"8","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2017-04-30","publicationStatus":"PW","scienceBaseUri":"5afee8abe4b0da30c1bfc48d","contributors":{"authors":[{"text":"Yager, Richard M. 0000-0001-7725-1148 ryager@usgs.gov","orcid":"https://orcid.org/0000-0001-7725-1148","contributorId":950,"corporation":false,"usgs":true,"family":"Yager","given":"Richard","email":"ryager@usgs.gov","middleInitial":"M.","affiliations":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true},{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":696942,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCoy, Kurt J. 0000-0002-9756-8238 kjmccoy@usgs.gov","orcid":"https://orcid.org/0000-0002-9756-8238","contributorId":1391,"corporation":false,"usgs":true,"family":"McCoy","given":"Kurt","email":"kjmccoy@usgs.gov","middleInitial":"J.","affiliations":[{"id":37280,"text":"Virginia and West Virginia Water Science Center ","active":true,"usgs":true}],"preferred":true,"id":696943,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Voss, Clifford I. 0000-0001-5923-2752 cvoss@usgs.gov","orcid":"https://orcid.org/0000-0001-5923-2752","contributorId":1559,"corporation":false,"usgs":true,"family":"Voss","given":"Clifford","email":"cvoss@usgs.gov","middleInitial":"I.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":696944,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sanford, Ward E. 0000-0002-6624-0280 wsanford@usgs.gov","orcid":"https://orcid.org/0000-0002-6624-0280","contributorId":2268,"corporation":false,"usgs":true,"family":"Sanford","given":"Ward","email":"wsanford@usgs.gov","middleInitial":"E.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":696945,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Winston, Richard B. 0000-0002-6287-8834 rbwinst@usgs.gov","orcid":"https://orcid.org/0000-0002-6287-8834","contributorId":3567,"corporation":false,"usgs":true,"family":"Winston","given":"Richard","email":"rbwinst@usgs.gov","middleInitial":"B.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":696946,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70182811,"text":"70182811 - 2017 - Inner-shelf ocean dynamics and seafloor morphologic changes during Hurricane Sandy","interactions":[],"lastModifiedDate":"2018-07-23T12:49:07","indexId":"70182811","displayToPublicDate":"2017-04-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1333,"text":"Continental Shelf Research","active":true,"publicationSubtype":{"id":10}},"title":"Inner-shelf ocean dynamics and seafloor morphologic changes during Hurricane Sandy","docAbstract":"Hurricane Sandy was one of the most destructive hurricanes in US history, making landfall on the New Jersey coast on Oct 30, 2012. Storm impacts included several barrier island breaches, massive coastal erosion, and flooding. While changes to the subaerial landscape are relatively easily observed, storm-induced changes to the adjacent shoreface and inner continental shelf are more difficult to evaluate. These regions provide a framework for the coastal zone, are important for navigation, aggregate resources, marine ecosystems, and coastal evolution. Here we provide unprecedented perspective regarding regional inner continental shelf sediment dynamics based on both observations and numerical modeling over time scales associated with these types of large storm events. Oceanographic conditions and seafloor morphologic changes are evaluated using both a coupled atmospheric-ocean-wave-sediment numerical modeling system and observation analysis from a series of geologic surveys and oceanographic instrument deployments focused on a region offshore of Fire Island, NY. The geologic investigations conducted in 2011 and 2014 revealed lateral movement of sedimentary structures of distances up to 450 m and in water depths up to 30 m, and vertical changes in sediment thickness greater than 1 m in some locations. The modeling investigations utilize a system with grid refinement designed to simulate oceanographic conditions with progressively increasing resolutions for the entire US East Coast (5-km grid), the New York Bight (700-m grid), and offshore of Fire Island, NY (100-m grid), allowing larger scale dynamics to drive smaller scale coastal changes. Model results in the New York Bight identify maximum storm surge of up to 3 m, surface currents on the order of 2 ms-1 along the New Jersey coast, waves up to 8 m in height, and bottom stresses exceeding 10 Pa. Flow down the Hudson Shelf Valley is shown to result in convergent sediment transport and deposition along its axis. Modeled sediment redistribution along Fire Island showed erosion across the crests of inner shelf sand ridges and sedimentation in adjacent troughs, consistent with the geologic observations.","language":"English","publisher":"Elsevier ","doi":"10.1016/j.csr.2017.02.003","usgsCitation":"Warner, J., Schwab, W.C., List, J.H., Safak, I., Liste, M., and Baldwin, W.E., 2017, Inner-shelf ocean dynamics and seafloor morphologic changes during Hurricane Sandy: Continental Shelf Research, v. 138, p. 1-18, https://doi.org/10.1016/j.csr.2017.02.003.","productDescription":"18 p.","startPage":"1","endPage":"18","ipdsId":"IP-072875","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":37273,"text":"Advanced Research Computing (ARC)","active":true,"usgs":true}],"links":[{"id":469976,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.csr.2017.02.003","text":"Publisher Index Page"},{"id":336758,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"138","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58e60271e4b09da6799ac67f","chorus":{"doi":"10.1016/j.csr.2017.02.003","url":"http://dx.doi.org/10.1016/j.csr.2017.02.003","publisher":"Elsevier BV","authors":"Warner John C., Schwab William C., List Jeffrey H., Safak Ilgar, Liste Maria, Baldwin Wayne","journalName":"Continental Shelf Research","publicationDate":"4/2017"},"contributors":{"authors":[{"text":"Warner, John C. 0000-0002-3734-8903 jcwarner@usgs.gov","orcid":"https://orcid.org/0000-0002-3734-8903","contributorId":2681,"corporation":false,"usgs":true,"family":"Warner","given":"John C.","email":"jcwarner@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":673847,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schwab, William C. 0000-0001-9274-5154 bschwab@usgs.gov","orcid":"https://orcid.org/0000-0001-9274-5154","contributorId":417,"corporation":false,"usgs":true,"family":"Schwab","given":"William","email":"bschwab@usgs.gov","middleInitial":"C.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":673848,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"List, Jeffrey H. 0000-0001-8594-2491 jlist@usgs.gov","orcid":"https://orcid.org/0000-0001-8594-2491","contributorId":174581,"corporation":false,"usgs":true,"family":"List","given":"Jeffrey","email":"jlist@usgs.gov","middleInitial":"H.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":673849,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Safak, Ilgar 0000-0001-7675-0770 isafak@usgs.gov","orcid":"https://orcid.org/0000-0001-7675-0770","contributorId":5522,"corporation":false,"usgs":true,"family":"Safak","given":"Ilgar","email":"isafak@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":673850,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Liste, Maria","contributorId":190581,"corporation":false,"usgs":false,"family":"Liste","given":"Maria","email":"","affiliations":[],"preferred":false,"id":673851,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Baldwin, Wayne E. 0000-0001-5886-0917 wbaldwin@usgs.gov","orcid":"https://orcid.org/0000-0001-5886-0917","contributorId":1321,"corporation":false,"usgs":true,"family":"Baldwin","given":"Wayne","email":"wbaldwin@usgs.gov","middleInitial":"E.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":673852,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70192945,"text":"70192945 - 2017 - Classification of California streams using combined deductive and inductive approaches: Setting the foundation for analysis of hydrologic alteration","interactions":[],"lastModifiedDate":"2025-12-23T14:37:28.701523","indexId":"70192945","displayToPublicDate":"2017-04-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1447,"text":"Ecohydrology","active":true,"publicationSubtype":{"id":10}},"title":"Classification of California streams using combined deductive and inductive approaches: Setting the foundation for analysis of hydrologic alteration","docAbstract":"Regional classification of streams is an early step in the Ecological Limits of Hydrologic Alteration framework. Many stream classifications are based on an inductive approach using hydrologic data from minimally disturbed basins, but this approach may underrepresent streams from heavily disturbed basins or sparsely gaged arid regions. An alternative is a deductive approach, using watershed climate, land use, and geomorphology to classify streams, but this approach may miss important hydrological characteristics of streams. We classified all stream reaches in California using both approaches. First, we used Bayesian and hierarchical clustering to classify reaches according to watershed characteristics. Streams were clustered into seven classes according to elevation, sedimentary rock, and winter precipitation. Permutation-based analysis of variance and random forest analyses were used to determine which hydrologic variables best separate streams into their respective classes. Stream typology (i.e., the class that a stream reach is assigned to) is shaped mainly by patterns of high and mean flow behavior within the stream's landscape context. Additionally, random forest was used to determine which hydrologic variables best separate minimally disturbed reference streams from non-reference streams in each of the seven classes. In contrast to stream typology, deviation from reference conditions is more difficult to detect and is largely defined by changes in low-flow variables, average daily flow, and duration of flow. Our combined deductive/inductive approach allows us to estimate flow under minimally disturbed conditions based on the deductive analysis and compare to measured flow based on the inductive analysis in order to estimate hydrologic change.
","language":"English","publisher":"Wiley","doi":"10.1002/eco.1802","usgsCitation":"Pyne, M.I., Carlisle, D.M., Konrad, C.P., and Stein, E.D., 2017, Classification of California streams using combined deductive and inductive approaches: Setting the foundation for analysis of hydrologic alteration: Ecohydrology, v. 10, no. 3, e1802, 14 p; Data Release, https://doi.org/10.1002/eco.1802.","productDescription":"e1802, 14 p; Data Release","ipdsId":"IP-073147","costCenters":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"links":[{"id":348846,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F70R9MJ7","text":"USGS data release","description":"USGS data release","linkHelpText":"Select watershed attributes for California stream segments (NHDPlus V.1)"},{"id":348662,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.er.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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Center","active":false,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":717395,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Konrad, Christopher P. 0000-0002-7354-547X cpkonrad@usgs.gov","orcid":"https://orcid.org/0000-0002-7354-547X","contributorId":1716,"corporation":false,"usgs":true,"family":"Konrad","given":"Christopher","email":"cpkonrad@usgs.gov","middleInitial":"P.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":717397,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stein, Eric D.","contributorId":198848,"corporation":false,"usgs":false,"family":"Stein","given":"Eric","email":"","middleInitial":"D.","affiliations":[{"id":12704,"text":"Southern California Coastal Water Research Project","active":true,"usgs":false}],"preferred":false,"id":717398,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70204148,"text":"70204148 - 2017 - 2016 status of the Lake Ontario Lower Trophic levels","interactions":[],"lastModifiedDate":"2019-09-24T08:47:40","indexId":"70204148","displayToPublicDate":"2017-03-31T13:15:24","publicationYear":"2017","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"16","displayTitle":"2016 Status of the Lake Ontario Lower Trophic Levels","title":"2016 status of the Lake Ontario Lower Trophic levels","docAbstract":"Significant Findings for Year 2016:\n1) Offshore spring total phosphorus (TP) in 2016 was 6.2 μg/L, higher than 2014 and 2015 (4.0 and 4.2 μg/L); there was no significant decline 2001 - 2016. Offshore soluble reactive phosphorus (SRP) was very low in 2016; Apr/May – Oct mean values were <1 μg/L. SRP has been stable in nearshore and offshore habitats since 1998 (range, 0.4 – 3.3 μg/L). Apr/May – Oct mean TP concentrations were low at both nearshore and offshore locations (range 5.2 – 9.9 μg/L). TP and SRP concentrations were significantly higher in nearshore compared to offshore habitats (7.6 μg/L vs 6.0 μg/L, TP; 1.4 μg/L vs 0.8 μg/L, SRP).\n2) Chlorophyll-a and Secchi depth values are indicative of oligotrophic conditions in nearshore and offshore habitats. Offshore summer chlorophyll-a declined significantly 2000 - 2016. Nearshore chlorophyll-a increased 1995 - 2004 but then declined 2005 - 2016. Epilimnetic chlorophyll-a averaged between 1.4 and 2.5 μg/L across sites, and offshore and nearshore Apr/May – Oct concentrations were the same (1.9 μg/L). Summer Secchi depth increased significantly in the offshore 2000 - 2016 and showed no trend in the nearshore, 1995 – 2016. Apr/May – Oct Secchi depth ranged from 5.0 m to 13.0 m at individual sites and was significantly higher in the offshore (10.0 m) than nearshore (6.5 m).\n3) In 2016, Apr/May – Oct epilimnetic zooplankton density and biomass were not different between the offshore and the nearshore, but calanoid copepod and Limnocalanus biomass were higher in the offshore (4.7 mg/m3 vs 2.6 mg/m3 and 0.7 mg/m3 vs 0.1 mg/m3), and bosminid biomass was higher in the nearshore (1.1 mg/m3 vs 0.3 mg/m3). Zooplankton size was significantly higher in the offshore than the nearshore (0.66 mm vs 0.49 mm).\n4) Peak (July) epilimnetic biomass of Cercopagis was 1.0 mg/m3 in the nearshore and 1.4 mg/m3 in the offshore. Peak (October) epilimnetic biomass of Bythotrephes was 1.8 mg/m3 in the nearshore and 0.6 mg/m3 in the offshore. Bythotrephes biomass has increased significantly in the nearshore, 1995 – 2016. Bythotrephes was more abundant in 2016 than in the previous two years and the zooplankton community responded accordingly with a decrease in bosminds and cyclopoids.\n5) Summer nearshore zooplankton density and biomass declined significantly 1995 – 2004 and then remained stable 2005 – 2016. The decline was due to reductions in bosminids and cyclopoids.\n6) Summer epilimnetic offshore zooplankton density and biomass increased significantly 2005 – 2016. In 2016, offshore summer epilimnetic zooplankton biomass was 22 mg/m3--less than half that observed in 2015--but still slightly higher than the mean from 2005 – 2015 (21 mg/m3).\n7) Most offshore zooplankton biomass was found in the metalimnion in July and September, and in the hypolimnion in October. Limnocalanus dominated the metalimnion in July while other calanoids and daphnids comprised most of the biomass in September. Limnocalanus and other calanoids dominated the October hypolimnion. Whole water column samples taken show a stable zooplankton biomass but changing community composition since 2010. Cyclopoids increased 2013 – 2015 and declined in 2016, while the calanoid pattern was the opposite. Daphnids declined 2014 – 2015 but rebounded in 2016.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Annual Report Bureau of Fisheries Lake Ontario Unit and St. Lawrence River Unit to Great Lakes Fishery Commission’s Lake Ontario Committee.","largerWorkSubtype":{"id":9,"text":"Other Report"},"language":"English","publisher":"New York State Department of Environmental Conservation","usgsCitation":"Holeck, K.T., Lars G. Rudstam, Christopher Hotaling, McCullough, R., Dave Lemon, Pearsall, W., Jana Lantry, Connerton, M., LaPan, S., Zy Biesinger, Lantry, B.F., Walsh, M., and Weidel, B., 2017, 2016 status of the Lake Ontario Lower Trophic levels, chap. 16 of Annual Report Bureau of Fisheries Lake Ontario Unit and St. Lawrence River Unit to Great Lakes Fishery Commission’s Lake Ontario Committee., p. 16-1-16-30.","productDescription":"30 p.","startPage":"16-1","endPage":"16-30","ipdsId":"IP-089248","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":367610,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":365376,"type":{"id":15,"text":"Index Page"},"url":"https://www.dec.ny.gov/outdoor/27068.html"}],"country":"Canada, United States","otherGeospatial":"Lake Ontario","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -79.925537109375,\n 43.265206318396025\n ],\n [\n -79.8101806640625,\n 43.281204464332745\n ],\n [\n -79.5904541015625,\n 43.18515250937298\n ],\n [\n -79.3597412109375,\n 43.16512263158296\n ],\n [\n -79.1839599609375,\n 43.193162620926074\n ],\n [\n -78.9532470703125,\n 43.27320591705845\n ],\n [\n -78.6236572265625,\n 43.329173667843904\n ],\n [\n -78.4259033203125,\n 43.369119087738554\n ],\n [\n -78.189697265625,\n 43.35713822211053\n ],\n [\n -78.123779296875,\n 43.35713822211053\n ],\n [\n -77.95898437499999,\n 43.35314407444698\n ],\n [\n -77.750244140625,\n 43.32517767999296\n ],\n [\n -77.596435546875,\n 43.23719944365308\n ],\n [\n -77.51953125,\n 43.197167282501276\n ],\n [\n -77.5140380859375,\n 43.241201214257885\n ],\n [\n -77.3602294921875,\n 43.26920624914964\n ],\n [\n -77.14050292968749,\n 43.27720532212024\n ],\n [\n -77.01416015625,\n 43.26120612479979\n ],\n [\n -76.89880371093749,\n 43.213183300738876\n ],\n [\n -76.904296875,\n 43.26920624914964\n ],\n [\n -76.7340087890625,\n 43.32517767999296\n ],\n [\n -76.6461181640625,\n 43.37311218382002\n ],\n [\n -76.5966796875,\n 43.42898792344155\n ],\n [\n -76.48681640625,\n 43.48082639482503\n ],\n [\n -76.4208984375,\n 43.50872101129684\n ],\n [\n -76.365966796875,\n 43.52465500687185\n ],\n [\n -76.31103515625,\n 43.51270490464819\n ],\n [\n -76.2396240234375,\n 43.51270490464819\n ],\n [\n -76.17919921875,\n 43.624147145668076\n ],\n [\n -76.1407470703125,\n 43.6599240747891\n ],\n [\n -76.1846923828125,\n 43.691707903073805\n ],\n [\n -76.1956787109375,\n 43.78299262890581\n ],\n [\n -76.201171875,\n 43.8503744993026\n ],\n [\n -76.0968017578125,\n 43.91768033000405\n ],\n [\n -75.9979248046875,\n 44.008620115415354\n ],\n [\n -76.1297607421875,\n 44.08363928284644\n ],\n [\n -76.300048828125,\n 44.14279782818058\n ],\n [\n -76.3934326171875,\n 44.17826452922573\n ],\n [\n -76.453857421875,\n 44.25700308645885\n ],\n [\n -76.629638671875,\n 44.25700308645885\n ],\n [\n -76.8109130859375,\n 44.17038488259618\n ],\n [\n -76.97021484375,\n 44.08758502824516\n ],\n [\n -77.069091796875,\n 44.071800467511565\n ],\n [\n -77.069091796875,\n 43.96514454266273\n ],\n [\n -77.080078125,\n 43.88997537383687\n ],\n [\n -77.3162841796875,\n 43.96119063892024\n ],\n [\n -77.4151611328125,\n 43.96909818325171\n ],\n [\n -77.574462890625,\n 44.06390660801779\n ],\n [\n -77.7337646484375,\n 44.040218713142146\n ],\n [\n -78.01391601562499,\n 44.004669106432225\n ],\n [\n -78.33251953125,\n 43.95328204198018\n ],\n [\n -78.5137939453125,\n 43.90185050527358\n ],\n [\n -78.7664794921875,\n 43.88997537383687\n ],\n [\n -78.9862060546875,\n 43.862257524417934\n ],\n [\n -79.1015625,\n 43.81471121600004\n ],\n [\n -79.2279052734375,\n 43.723474896114794\n ],\n [\n -79.3377685546875,\n 43.65197548731187\n ],\n [\n -79.4805908203125,\n 43.644025847699496\n ],\n [\n -79.5684814453125,\n 43.56845179881218\n ],\n [\n -79.617919921875,\n 43.52465500687185\n ],\n [\n -79.6343994140625,\n 43.464880828929545\n ],\n [\n -79.7113037109375,\n 43.37710501700073\n ],\n [\n -79.82666015625,\n 43.329173667843904\n ],\n [\n -79.925537109375,\n 43.265206318396025\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Holeck, Kristen T.","contributorId":197985,"corporation":false,"usgs":false,"family":"Holeck","given":"Kristen","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":765713,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lars G. 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Since 1990, cyanobacterial blooms have been present occasionally in Cheney Reservoir, resulting in increased treatment costs and decreased recreational use. Cyanobacteria, the cyanotoxin microcystin, and the taste-and-odor compounds geosmin and 2-methylisoborneol have been measured in Cheney Reservoir by the U.S. Geological Survey, in cooperation with the city of Wichita, for about 16 years. The purpose of this report is to describe the occurrence of cyanobacteria, microcystin, and taste-and-odor compounds in Cheney Reservoir during May 2001 through June 2016 and to update previously published logistic regression models that used continuous water-quality data to estimate the probability of microcystin and geosmin occurrence above relevant thresholds.
Cyanobacteria, microcystin, and geosmin were detected in about 84, 52, and 31 percent of samples collected in Cheney Reservoir during May 2001 through June 2016, respectively. 2-methylisoborneol was less common, detected in only 3 percent of samples. Microcystin and geosmin concentrations exceeded advisory values of concern more frequently than cyanobacterial abundance; therefore, cyanobacteria are not a good indicator of the presence of these taste-and-odor compounds in Cheney Reservoir. Broad seasonal patterns in cyanobacteria and microcystin were evident, though abundance and concentration varied by orders of magnitude across years. Cyanobacterial abundances generally peaked in late summer or early fall (August through October), and smaller peaks were observed in winter (January through February). In a typical year, microcystin was first detected in June or July, increased to its seasonal maxima in the summer (July through September), and then decreased. Seasonal patterns in geosmin were less consistent than cyanobacteria and microcystin, but geosmin typically had a small peak during winter (January through March) during most years and a large peak during summer (July through September) during some years. Though the relation between cyanobacterial abundance and microcystin and geosmin concentrations was positive, overall correlations were weak, likely because production is strain-specific and cyanobacterial strain composition may vary substantially over time. Microcystin often was present without taste-and-odor compounds. By comparison, where taste-and-odor compounds were present, microcystin frequently was detected. Taste-and-odor compounds, therefore, may be used as indicators that microcystin may be present; however, microcystin was present without taste-and-odor compounds, so taste or odor alone does not provide sufficient warning to ensure human-health protection.
Logistic regression models that estimate the probability of microcystin occurrence at concentrations greater than or equal to 0.1 micrograms per liter and geosmin occurrence at concentrations greater than or equal to 5 nanograms per liter were developed. Models were developed using the complete dataset (January 2003 through June 2016 for microcystin [14-year dataset]; May 2001 through June 2016 for geosmin [16-year dataset]) and an abbreviated 4-year dataset (January 2013 through June 2016 for microcystin and geosmin). Performance of the newly developed models was compared with previously published models that were developed using data collected during May 2001 through December 2009. A seasonal component and chlorophyll fluorescence (a surrogate for algal biomass) were the explanatory variables for microcystin occurrence at concentrations greater than or equal to 0.1 micrograms per liter in all models. All models were relatively robust, though the previously published and 14-year models performed better over time; however, as a tool to estimate microcystin occurrence at concentrations greater than or equal to 0.1 micrograms per liter in a real-time notification system near the Cheney Dam, the 4-year model is most representative of recent (2013 through 2016) conditions. All models for geosmin occurrence at concentrations greater than or equal to 5 nanograms per liter had different explanatory variables and model forms. The previously published and 16-year models were not robust over time, likely because of changing environmental conditions and seasonal patterns in geosmin occurrence. By comparison, the abbreviated 4-year model may be a useful tool to estimate geosmin occurrence at concentrations greater than or equal to 5 nanograms per liter in a real-time notification system near the Cheney Dam. The better performance of the abbreviated 4-year geosmin model during 2013 through 2016 relative to the previously published and 16-year models demonstrates the need for continuous reevaluation of models estimating the probability of occurrence.
Director, Kansas Water Science Center
U.S. Geological Survey
4821 Quail Crest Place
Lawrence, KS 66049
Since 1996, the U.S. Geological Survey (USGS), in cooperation with the City of Wichita, has done studies in the Cheney Reservoir watershed to understand environmental effects on water-quality conditions. Early studies (1996–2001) determined subwatershed sources of contaminants, nutrient and sediment loading to Cheney Reservoir, changes in reservoir sediment quality over time, and watershed sources of phosphorus. Later studies (2001–present) focused on nutrient and sediment concentrations and mass transport from the watershed; the presence of cyanobacteria, cyanotoxins, and taste-and-odor compounds in the reservoir; and development of regression models for real-time computations of water-quality constituents of interest that may affect drinking-water treatment. This fact sheet summarizes key results from studies done by the USGS during 1996–2016 in the Cheney Reservoir watershed and Cheney Reservoir.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20173019","collaboration":"Prepared in cooperation with the City of Wichita, Kansas","usgsCitation":"Graham, J.L., Foster, G.M., and Kramer, A.R., 2017, Twenty years of water-quality studies in the Cheney Reservoir watershed, Kansas, 1996–2016: U.S. Geological Survey Fact Sheet 2017–3019, 4 p., https://doi.org/10.3133/fs20173019.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-080288","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":338840,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2017/3019/fs20173019.pdf","text":"Fact Sheet","size":"1.01 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2017–3019"},{"id":338839,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2017/3019/coverthb.jpg"},{"id":338841,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://doi.org/10.3133/sir20175016","text":"SIR 2017–5016","description":"SIR 2017–5016","linkHelpText":"Occurrence of cyanobacteria, microcystin, and taste-and-odor compounds in Cheney Reservoir, Kansas, 2001-16"}],"country":"United States","state":"Kansas","otherGeospatial":"Cheney Reservoir","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.74,\n 38.1\n ],\n [\n -99.25,\n 38.1\n ],\n [\n -99.25,\n 37.5\n ],\n [\n -97.74,\n 37.5\n ],\n [\n -97.74,\n 38.1\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Kansas Water Science Center
U.S. Geological Survey
4821 Quail Crest Place
Lawrence, KS 66049
A partnership established between the European Space Agency (ESA) and the U.S. Geological Survey (USGS) allows for USGS storage and redistribution of images acquired by the MultiSpectral Instrument (MSI) on the European Union's Sentinel-2 satellite mission. The MSI data are acquired from a pair of satellites, Sentinel-2A and Sentinel-2B, which are part of a larger set of ESA missions focusing on different aspects of Earth observation. The primary purpose of the Sentinel-2 series is to collect multispectral imagery over the Earth’s land surfaces, large islands, and inland and coastal waters. Sentinel-2A was launched in 2015 and Sentinel-2B launched in 2017.
The collaborative effort between ESA and USGS provides for public access and redistribution of global acquisitions of Sentinel-2 data at no cost, which allows users to download the MSI imagery from USGS access systems such as Earth- Explorer, in addition to the ESA Sentinels Scientific Data Hub. The MSI sensor acquires 13 spectral bands that are highly complementary to data acquired by the USGS Landsat 8 Operational Land Imager (OLI) and Landsat 7 Enhanced Thematic Mapper Plus (ETM+). The product options from USGS include a Full-Resolution Browse (FRB) image product generated by USGS, along with a 100-kilometer (km) by 100-km tile-based Level-1C top-of-atmosphere (TOA) reflectance product that is very similar (but not identical) to the currently (2017) distributed ESA Level 1C product.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20173026","usgsCitation":"Pieschke, R.L., 2017, U.S. Geological Survey distribution of European Space Agency's Sentinel-2 data: U.S. Geological Survey Fact Sheet 2017–3026, 2 p., https://doi.org/10.3133/fs20173026.\n","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","ipdsId":"IP-082585","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":338860,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2017/3026/fs20173026.pdf","text":"Fact Sheet","size":"1.54 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2017–3026"},{"id":338859,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2017/3026/coverthb.jpg"}],"contact":"Director, Earth Resources Observation and Science (EROS) Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, SD 57198–0001
The Prairie Pothole Region (PPR) of north-central United States and south-central Canada supports greater than half of all breeding mallards (Anas platyrhynchos) annually counted in North America and is the focus of widespread conservation and research efforts. Allocation of conservation resources for this socioeconomically important population would benefit from an understanding of the nature of spatiotemporal variation in distribution of breeding mallards throughout the 850,000 km2 landscape. We used mallard counts from the Waterfowl Breeding Population and Habitat Survey to test for spatial heterogeneity and identify high- and low-abundance regions of breeding mallards over a 50-year time series. We found strong annual spatial heterogeneity in all years: 90% of mallards counted annually were on an average of only 15% of surveyed segments. Using a local indicator of spatial autocorrelation, we found a relatively static distribution of low-count clusters in northern Montana, USA, and southern Alberta, Canada, and a dynamic distribution of high-count clusters throughout the study period. Distribution of high-count clusters shifted southeast from northwestern portions of the PPR in Alberta and western Saskatchewan, Canada, to North and South Dakota, USA, during the latter half of the study period. This spatial redistribution of core mallard breeding populations was likely driven by interactions between environmental variation that created favorable hydrological conditions for wetlands in the eastern PPR and dynamic land-use patterns related to upland cropping practices and government land-retirement programs. Our results highlight an opportunity for prioritizing relatively small regions within the PPR for allocation of wetland and grassland conservation for mallard populations. However, the extensive spatial heterogeneity in core distributions over our study period suggests such spatial prioritization will have to overcome challenges presented by dynamic land-use and climate patterns in the region, and thus merits additional monitoring and empirical research to anticipate future population distribution. Published 2017. This article is a U.S. Government work and is in the public domain in the USA.
","language":"English","publisher":"Wiley","doi":"10.1002/wsb.747","usgsCitation":"Janke, A.K., Anteau, M.J., and Stafford, J.D., 2017, Long-term spatial heterogeneity in mallard distribution in the Prairie pothole region: Wildlife Society Bulletin, v. 41, no. 1, p. 116-124, https://doi.org/10.1002/wsb.747.","productDescription":"9 p.","startPage":"116","endPage":"124","ipdsId":"IP-066605","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":469979,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://lib.dr.iastate.edu/nrem_pubs/208","text":"External Repository"},{"id":338982,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"41","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-03-22","publicationStatus":"PW","scienceBaseUri":"58df6abee4b02ff32c6aea25","contributors":{"authors":[{"text":"Janke, Adam K. 0000-0003-2781-7857","orcid":"https://orcid.org/0000-0003-2781-7857","contributorId":130959,"corporation":false,"usgs":false,"family":"Janke","given":"Adam","email":"","middleInitial":"K.","affiliations":[{"id":7176,"text":"Dept of Natl Res Mgmt, SDSU, Brookings, SD","active":true,"usgs":false}],"preferred":false,"id":687899,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anteau, Michael J. 0000-0002-5173-5870 manteau@usgs.gov","orcid":"https://orcid.org/0000-0002-5173-5870","contributorId":3427,"corporation":false,"usgs":true,"family":"Anteau","given":"Michael","email":"manteau@usgs.gov","middleInitial":"J.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":687903,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stafford, Joshua D. jstafford@usgs.gov","contributorId":4267,"corporation":false,"usgs":true,"family":"Stafford","given":"Joshua","email":"jstafford@usgs.gov","middleInitial":"D.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":687904,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70190184,"text":"70190184 - 2017 - Quantifying acoustic doppler current profiler discharge uncertainty: A Monte Carlo based tool for moving-boat measurements","interactions":[],"lastModifiedDate":"2017-08-23T10:10:56","indexId":"70190184","displayToPublicDate":"2017-03-31T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":18,"text":"Abstract or summary"},"title":"Quantifying acoustic doppler current profiler discharge uncertainty: A Monte Carlo based tool for moving-boat measurements","docAbstract":"This paper presents a method using Monte Carlo simulations for assessing uncertainty of moving-boat acoustic Doppler current profiler (ADCP) discharge measurements using a software tool known as QUant, which was developed for this purpose. Analysis was performed on 10 data sets from four Water Survey of Canada gauging stations in order to evaluate the relative contribution of a range of error sources to the total estimated uncertainty. The factors that differed among data sets included the fraction of unmeasured discharge relative to the total discharge, flow nonuniformity, and operator decisions about instrument programming and measurement cross section. As anticipated, it was found that the estimated uncertainty is dominated by uncertainty of the discharge in the unmeasured areas, highlighting the importance of appropriate selection of the site, the instrument, and the user inputs required to estimate the unmeasured discharge. The main contributor to uncertainty was invalid data, but spatial inhomogeneity in water velocity and bottom-track velocity also contributed, as did variation in the edge velocity, uncertainty in the edge distances, edge coefficients, and the top and bottom extrapolation methods. To a lesser extent, spatial inhomogeneity in the bottom depth also contributed to the total uncertainty, as did uncertainty in the ADCP draft at shallow sites. The estimated uncertainties from QUant can be used to assess the adequacy of standard operating procedures. They also provide quantitative feedback to the ADCP operators about the quality of their measurements, indicating which parameters are contributing most to uncertainty, and perhaps even highlighting ways in which uncertainty can be reduced. Additionally, QUant can be used to account for self-dependent error sources such as heading errors, which are a function of heading. The results demonstrate the importance of a Monte Carlo method tool such as QUant for quantifying random and bias errors when evaluating the uncertainty of moving-boat ADCP measurements.
The invasive Asian clam Corbicula fluminea was introduced to North America in the 1930s and now inhabits most regions of the conterminous United States; however, the distribution and ecology of C. fluminea in the Columbia River Basin is poorly understood. During 2013 and 2014, 5 Columbia-Snake River reservoirs were sampled monthly from May through September, along with 23 additional lakes and reservoirs sampled once each summer. Associations among C. fluminea veligers, other components of the plankton, and environmental variables were analyzed using non-metric multidimensional scaling and canonical correspondence analysis. Corbicula fluminea veligers were found in high abundances in all mainstem Columbia-Snake River reservoirs, with an annual mean abundance of 71.2 individuals per cubic meter (inds./m3). Only 3 of 23 lakes and (non-mainstem) reservoirs contained C. fluminea, with abundances considerably lower (maximum = 21.2 inds./m3) than in the mainstem reservoirs. A diatom-dominated community preceded the spawning of C. fluminea in early summer at all sites. Corbicula fluminea veligers characterized the plankton community in late summer and were associated with cyanobacteria and high water temperatures. A third community, characterized by cyanobacteria, was apparent in non-mainstem sites in July and August. Our analyses describe the relationship of C. fluminea to the plankton community and environment, which contributes to our understanding of the possible effects of C. fluminea infestations and which waterbodies in the Columbia River Basin are at risk for infestation. Understanding the effects and environmental determinants of invasive mollusks will be increasingly important in the future with the possible arrival of zebra (Dreissena polymorpha) or quagga (D. bugensis) mussels to the region.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/10402381.2017.1294218","usgsCitation":"Hassett, W., Bollens, S.M., Counihan, T.D., Rollwagen-Bollens, G., Zimmerman, J., and Emerson, J.E., 2017, Veligers of the invasive Asian clam Corbicula fluminea in the Columbia River Basin: Broadscale distribution, abundance, and ecological associations: Lake and Reservoir Management, v. 33, no. 3, p. 234-248, https://doi.org/10.1080/10402381.2017.1294218.","productDescription":"15 p.","startPage":"234","endPage":"248","ipdsId":"IP-072926","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":338810,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"33","issue":"3","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-03-24","publicationStatus":"PW","scienceBaseUri":"58de194ae4b02ff32c699c7b","contributors":{"authors":[{"text":"Hassett, Whitney","contributorId":190161,"corporation":false,"usgs":false,"family":"Hassett","given":"Whitney","email":"","affiliations":[],"preferred":false,"id":687434,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bollens, Stephen M. 0000-0001-9214-9037","orcid":"https://orcid.org/0000-0001-9214-9037","contributorId":148958,"corporation":false,"usgs":false,"family":"Bollens","given":"Stephen","email":"","middleInitial":"M.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":687435,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Counihan, Timothy D. 0000-0003-4967-6514 tcounihan@usgs.gov","orcid":"https://orcid.org/0000-0003-4967-6514","contributorId":4211,"corporation":false,"usgs":true,"family":"Counihan","given":"Timothy","email":"tcounihan@usgs.gov","middleInitial":"D.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":687433,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rollwagen-Bollens, Gretchen","contributorId":190162,"corporation":false,"usgs":false,"family":"Rollwagen-Bollens","given":"Gretchen","email":"","affiliations":[],"preferred":false,"id":687436,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zimmerman, Julie","contributorId":190163,"corporation":false,"usgs":false,"family":"Zimmerman","given":"Julie","affiliations":[],"preferred":false,"id":687437,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Emerson, Joshua E.","contributorId":148957,"corporation":false,"usgs":false,"family":"Emerson","given":"Joshua","email":"","middleInitial":"E.","affiliations":[{"id":17602,"text":"School of the Environment, Washington State University, Vancouver, WA 98686","active":true,"usgs":false}],"preferred":false,"id":687438,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70186040,"text":"70186040 - 2017 - Species composition, timing, and weather correlates of autumn open-water crossings by raptors migrating along the East-Asian Oceanic Flyway","interactions":[],"lastModifiedDate":"2017-11-22T17:03:36","indexId":"70186040","displayToPublicDate":"2017-03-30T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2442,"text":"Journal of Raptor Research","active":true,"publicationSubtype":{"id":10}},"title":"Species composition, timing, and weather correlates of autumn open-water crossings by raptors migrating along the East-Asian Oceanic Flyway","docAbstract":"Raptor migration rarely involves long-distance movements across open oceans. One exception occurs along the East-Asian Oceanic Flyway. We collected migration data at two terrestrial hawkwatch sites along this flyway to better understand open-ocean movements along this largely overwater corridor. At the northern end of the Philippines, at Basco on the island of Batan, we recorded 7587 migratory raptors in autumn 2014. Near the southern end of the Philippines, at Cape San Agustin on the island of Mindanao, we recorded 27,399 raptors migrating in autumn 2012. Chinese Sparrowhawks (Accipiter soloensis) were the most common raptors observed, making up approximately 89% and 92% of total records for Basco and Cape San Agustin, respectively. The Grey-faced Buzzard (Butastur indicus) was the second most common raptor migrant, accounting for 8% of the total counts at both watch sites. The migration period was about 1–2 wk earlier at Basco, the more northerly site, than at Cape San Agustin. Overwater flights at Basco peaked in both the morning and late afternoon, whereas at Cape San Agustin there was only a morning peak. In general, the rate of migration passage at both sites was highest with clear skies when winds were blowing from the northwest. However, we observed interspecific differences in migration behavior at both sites, with Accipiters more likely to be observed with tailwinds and eastward winds, and Grey-faced Buzzards more likely observed with headwinds. These results help to characterize poorly known aspects of raptor biology and to identify potential migratory bottlenecks or key sites for raptor conservation in little-studied Philippine tropical ecosystems.
","language":"English","publisher":"The Raptor Research Foundation","doi":"10.3356/JRR-16-00001.1","usgsCitation":"Concepcion, C.B., Dumandan, P., Silvosa, M.R., Bildstein, K.L., and Katzner, T., 2017, Species composition, timing, and weather correlates of autumn open-water crossings by raptors migrating along the East-Asian Oceanic Flyway: Journal of Raptor Research, v. 51, no. 1, p. 25-37, https://doi.org/10.3356/JRR-16-00001.1.","productDescription":"13 p.","startPage":"25","endPage":"37","ipdsId":"IP-071451","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":469982,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://www.bioone.org/doi/10.3356/JRR-16-00001.1","text":"External Repository"},{"id":338780,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"East-Asian Oceanic Flyway","volume":"51","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58de1949e4b02ff32c699c79","contributors":{"authors":[{"text":"Concepcion, Camille B.","contributorId":190164,"corporation":false,"usgs":false,"family":"Concepcion","given":"Camille","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":687440,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dumandan, Patricia T.","contributorId":190165,"corporation":false,"usgs":false,"family":"Dumandan","given":"Patricia T.","affiliations":[],"preferred":false,"id":687441,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Silvosa, Medel R.","contributorId":190166,"corporation":false,"usgs":false,"family":"Silvosa","given":"Medel","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":687442,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bildstein, Keith L.","contributorId":150854,"corporation":false,"usgs":false,"family":"Bildstein","given":"Keith","email":"","middleInitial":"L.","affiliations":[{"id":18119,"text":"Hawk Mountain Sanctuary, Acopian Center for Conservation Learning","active":true,"usgs":false}],"preferred":false,"id":687443,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Katzner, Todd E. 0000-0003-4503-8435 tkatzner@usgs.gov","orcid":"https://orcid.org/0000-0003-4503-8435","contributorId":5979,"corporation":false,"usgs":true,"family":"Katzner","given":"Todd E.","email":"tkatzner@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":false,"id":687439,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70186031,"text":"70186031 - 2017 - Spatial and temporal dynamics of suspended particle characteristics and composition in Navigation Pool 19 of the Upper Mississippi River","interactions":[],"lastModifiedDate":"2017-07-10T16:20:01","indexId":"70186031","displayToPublicDate":"2017-03-30T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3301,"text":"River Research and Applications","active":true,"publicationSubtype":{"id":10}},"title":"Spatial and temporal dynamics of suspended particle characteristics and composition in Navigation Pool 19 of the Upper Mississippi River","docAbstract":"Suspended particles are an essential component of large rivers influencing channel geomorphology, biogeochemical cycling of nutrients, and food web resources. The Upper Mississippi River is a large floodplain river that exhibits pronounced spatiotemporal variation in environmental conditions and biota, providing an ideal environment for investigating dynamics of suspended particles in large river ecosystems. Here we investigated two questions: (i) How do suspended particle characteristics (e.g. size and morphology) vary temporally and spatially? and (ii) What environmental variables have the strongest association with particle characteristics? Water sampling was conducted in June, August, and September of 2013 and 2014 in Navigation Pool 19 of the Upper Mississippi River. A FlowCAM® (Flow Cytometer and Microscope) particle imaging system was used to enumerate and measure particles 53–300 μm in diameter for size and shape characteristics (e.g. volume, elongation, and symmetry). Suspended particle characteristics varied considerably over space and time and were strongly associated with discharge and concentrations of nitrate + nitrite (NO3−) and soluble reactive phosphorus. Particle characteristics in backwaters were distinct from those in other habitats for most of the study period, likely due to reduced hydrologic connectivity and higher biotic production in backwaters. During low discharge, phytoplankton and zooplankton made up relatively greater proportions of the observed particles. Concurrently during low discharge, concentrations of chlorophyll, volatile suspended solids, and total phosphorus were higher. Our results suggest that there are complex interactions among space, time, discharge, and other environmental variables (e.g. water nutrients), which drive suspended particle dynamics in large rivers.
","language":"English","publisher":"Wiley","doi":"10.1002/rra.3131","usgsCitation":"Milde, A.S., Richardson, W.B., Strauss, E.A., Larson, J.H., Vallazza, J.M., and Knights, B.C., 2017, Spatial and temporal dynamics of suspended particle characteristics and composition in Navigation Pool 19 of the Upper Mississippi River: River Research and Applications, v. 33, no. 5, p. 740-752, https://doi.org/10.1002/rra.3131.","productDescription":"13 p.","startPage":"740","endPage":"752","ipdsId":"IP-076602","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":338814,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":343530,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F70Z7250","text":"Spatial and temporal dynamics of suspended particle characteristics and composition in Navigation Pool 19 of the Upper Mississippi River"}],"country":"United 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amilde@usgs.gov","orcid":"https://orcid.org/0000-0001-5854-9184","contributorId":5877,"corporation":false,"usgs":true,"family":"Milde","given":"Amanda","email":"amilde@usgs.gov","middleInitial":"S.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":687402,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Richardson, William B. 0000-0002-7471-4394 wrichardson@usgs.gov","orcid":"https://orcid.org/0000-0002-7471-4394","contributorId":3277,"corporation":false,"usgs":true,"family":"Richardson","given":"William","email":"wrichardson@usgs.gov","middleInitial":"B.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":687403,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Strauss, Eric A.","contributorId":190148,"corporation":false,"usgs":false,"family":"Strauss","given":"Eric","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":687404,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Larson, James H. 0000-0002-6414-9758 jhlarson@usgs.gov","orcid":"https://orcid.org/0000-0002-6414-9758","contributorId":4250,"corporation":false,"usgs":true,"family":"Larson","given":"James","email":"jhlarson@usgs.gov","middleInitial":"H.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":687405,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vallazza, Jonathan M. 0000-0003-2367-4887 jvallazza@usgs.gov","orcid":"https://orcid.org/0000-0003-2367-4887","contributorId":149362,"corporation":false,"usgs":true,"family":"Vallazza","given":"Jonathan","email":"jvallazza@usgs.gov","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":687406,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Knights, Brent C. 0000-0001-8526-8468 bknights@usgs.gov","orcid":"https://orcid.org/0000-0001-8526-8468","contributorId":2906,"corporation":false,"usgs":true,"family":"Knights","given":"Brent","email":"bknights@usgs.gov","middleInitial":"C.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":687407,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70186028,"text":"70186028 - 2017 - Live transport of Yellow Perch and Nile Tilapia in AQUI-S 20E (10% Eugenol) at high loading densities","interactions":[],"lastModifiedDate":"2017-03-30T11:56:43","indexId":"70186028","displayToPublicDate":"2017-03-30T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2885,"text":"North American Journal of Aquaculture","active":true,"publicationSubtype":{"id":10}},"title":"Live transport of Yellow Perch and Nile Tilapia in AQUI-S 20E (10% Eugenol) at high loading densities","docAbstract":"Fish transport costs are a substantial portion of the operational expenses for aquaculture facilities in the USA. Safely transporting higher loading densities of fish would benefit haulers by increasing efficiency and reducing costs, but research evaluating transport for individual species is generally lacking. In this study, Yellow Perch Perca flavescens and Nile Tilapia Oreochromis niloticus were transported for 6 h immersed in water containing AQUI-S 20E (10% eugenol) at fish loading densities of 240 g/L (2 lb/gal) for perch and 480 g/L (4 lb/gal) for tilapia. Survival was quantified for fish transported in AQUI-S 20E concentrations of (1) control or 0 mg/L of water, (2) 100 mg/L, or (3) 200 mg/L. Yellow Perch had 98–100% survival, and Nile Tilapia had 100% survival up to through 14 d after transport across all AQUI-S 20E levels, including the control. Eugenol concentrations decreased rapidly in transport tank water, and fish showed no signs of sedation by the end of transport. We conclude that live transport of Yellow Perch and Nile Tilapia at higher loading densities resulted in high survival regardless of the AQUI-S 20E concentrations we tested.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/15222055.2017.1281853","usgsCitation":"Cupp, A.R., Schreier, T.M., and Schleis, S.M., 2017, Live transport of Yellow Perch and Nile Tilapia in AQUI-S 20E (10% Eugenol) at high loading densities: North American Journal of Aquaculture, v. 79, no. 2, p. 176-182, https://doi.org/10.1080/15222055.2017.1281853.","productDescription":"7 p.","startPage":"176","endPage":"182","ipdsId":"IP-078019","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":338816,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"79","issue":"2","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2017-03-02","publicationStatus":"PW","scienceBaseUri":"58de194be4b02ff32c699c81","contributors":{"authors":[{"text":"Cupp, Aaron R. 0000-0001-5995-2100 acupp@usgs.gov","orcid":"https://orcid.org/0000-0001-5995-2100","contributorId":5162,"corporation":false,"usgs":true,"family":"Cupp","given":"Aaron","email":"acupp@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":687390,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schreier, Theresa M. 0000-0001-7722-6292 tschreier@usgs.gov","orcid":"https://orcid.org/0000-0001-7722-6292","contributorId":3344,"corporation":false,"usgs":true,"family":"Schreier","given":"Theresa","email":"tschreier@usgs.gov","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":687391,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schleis, Susan M. 0000-0002-9396-7856 sschleis@usgs.gov","orcid":"https://orcid.org/0000-0002-9396-7856","contributorId":2858,"corporation":false,"usgs":true,"family":"Schleis","given":"Susan","email":"sschleis@usgs.gov","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":687392,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70186019,"text":"70186019 - 2017 - Spatial and temporal relationships between the invasive snail Bithynia tentaculata and submersed aquatic vegetation in Pool 8 of the Upper Mississippi River","interactions":[],"lastModifiedDate":"2017-06-07T10:23:14","indexId":"70186019","displayToPublicDate":"2017-03-30T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3301,"text":"River Research and Applications","active":true,"publicationSubtype":{"id":10}},"title":"Spatial and temporal relationships between the invasive snail Bithynia tentaculata and submersed aquatic vegetation in Pool 8 of the Upper Mississippi River","docAbstract":"Bithynia tentaculata is an invasive snail that was first reported in Lake Michigan in 1871 and has since spread throughout a number of freshwater systems of the USA. This invasion has been extremely problematic in the Upper Mississippi River as the snails serve as intermediate hosts for several trematode parasites that have been associated with waterfowl mortality in the region. This study was designed to assess the abundance and distribution of B. tentaculata relative to submersed aquatic vegetation as macrophytes provide important nesting and food resources for migrating waterfowl. Temporal changes in both vegetation and snail densities were compared between 2007 and 2015. Between these years, B. tentaculata densities have nearly quadrupled despite minor changes in vegetation abundance, distribution and composition. Understanding the spatial distribution of B. tentaculata in relation to other habitat features, including submersed vegetation, and quantifying any further changes in the abundance and distribution of B. tentaculata over time will be important for better identifying areas of risk for disease transmission to waterfowl.
","language":"English","publisher":"Wiley","doi":"10.1002/rra.3123","usgsCitation":"Weeks, A.M., De Jager, N.R., Haro, R.J., and Sandland, G., 2017, Spatial and temporal relationships between the invasive snail Bithynia tentaculata and submersed aquatic vegetation in Pool 8 of the Upper Mississippi River: River Research and Applications, v. 33, no. 5, p. 729-739, https://doi.org/10.1002/rra.3123.","productDescription":"11 p.","startPage":"729","endPage":"739","ipdsId":"IP-079774","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":338845,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"33","issue":"5","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58de194ce4b02ff32c699c87","contributors":{"authors":[{"text":"Weeks, Alicia M.","contributorId":190136,"corporation":false,"usgs":false,"family":"Weeks","given":"Alicia","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":687360,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"De Jager, Nathan R. 0000-0002-6649-4125 ndejager@usgs.gov","orcid":"https://orcid.org/0000-0002-6649-4125","contributorId":3717,"corporation":false,"usgs":true,"family":"De Jager","given":"Nathan","email":"ndejager@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":687359,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haro, Roger J.","contributorId":139538,"corporation":false,"usgs":false,"family":"Haro","given":"Roger","email":"","middleInitial":"J.","affiliations":[{"id":12793,"text":"University of Wisconsin-La Crosse","active":true,"usgs":false}],"preferred":false,"id":687361,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sandland, Greg J.","contributorId":190137,"corporation":false,"usgs":false,"family":"Sandland","given":"Greg J.","affiliations":[],"preferred":false,"id":687362,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70186017,"text":"70186017 - 2017 - Effects of the biopesticide Zequanox® on reproduction and early development of the fathead minnow (Pimephales promelas)","interactions":[],"lastModifiedDate":"2017-03-30T15:24:17","indexId":"70186017","displayToPublicDate":"2017-03-30T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2655,"text":"Management of Biological Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Effects of the biopesticide Zequanox® on reproduction and early development of the fathead minnow (Pimephales promelas)","docAbstract":"The biopesticide, Zequanox®, is registered for dreissenid mussel control in open water systems in the United States. Previous toxicity trials with nontarget organisms, including several young-of-the-year fish species and invertebrates, demonstrated selectivity of Zequanox for dreissenid mussels, but data are lacking on the treatment-related effects on reproduction and early life stage development of fish. The present study evaluated the effects of Zequanox on spawning and early life stages of the fathead minnow, Pimephales promelas, after exposure to the maximum approved concentration [100 mg active ingredient (AI)/L] and exposure duration (8h) for open water application. The results showed no significant treatment-related effect of Zequanox on survival, condition, or cumulative egg production (21 d) in adult fathead minnow. Eggs (≤24 h old) exposed to Zequanox developed to the eyed-stage at a similar rate to that of untreated eggs. Additionally, Zequanox did not have a significant effect on survival and growth (90 d) of newly hatched larvae (≤24-h old). Zequanox may be an option for control of dreissenid mussels in localized open water habitats where concerns exist regarding reproduction and recruitment of cyprinids and related species.
","language":"English","publisher":"Regional Euro-Asian Biological Invasions Centre","doi":"10.3391/mbi.2017.8.1.12","usgsCitation":"Waller, D.L., and Luoma, J.A., 2017, Effects of the biopesticide Zequanox® on reproduction and early development of the fathead minnow (Pimephales promelas): Management of Biological Invasions, v. 8, no. 1, p. 125-135, https://doi.org/10.3391/mbi.2017.8.1.12.","productDescription":"11 p.","startPage":"125","endPage":"135","ipdsId":"IP-079839","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":469983,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3391/mbi.2017.8.1.12","text":"Publisher Index Page"},{"id":338846,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"1","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58de194ce4b02ff32c699c89","contributors":{"authors":[{"text":"Waller, Diane L. 0000-0002-6104-810X dwaller@usgs.gov","orcid":"https://orcid.org/0000-0002-6104-810X","contributorId":5272,"corporation":false,"usgs":true,"family":"Waller","given":"Diane","email":"dwaller@usgs.gov","middleInitial":"L.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":687356,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Luoma, James A. 0000-0003-3556-0190 jluoma@usgs.gov","orcid":"https://orcid.org/0000-0003-3556-0190","contributorId":4449,"corporation":false,"usgs":true,"family":"Luoma","given":"James","email":"jluoma@usgs.gov","middleInitial":"A.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":687357,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70185601,"text":"ofr20171034 - 2017 - Landsat and agriculture—Case studies on the uses and benefits of Landsat imagery in agricultural monitoring and production","interactions":[],"lastModifiedDate":"2017-03-30T12:15:26","indexId":"ofr20171034","displayToPublicDate":"2017-03-29T17:45:00","publicationYear":"2017","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":"2017-1034","title":"Landsat and agriculture—Case studies on the uses and benefits of Landsat imagery in agricultural monitoring and production","docAbstract":"The use of Landsat satellite imagery for global agricultural monitoring began almost immediately after the launch of Landsat 1 in 1972, making agricultural monitoring one of the longest-standing operational applications for the Landsat program. More recently, Landsat imagery has been used in domestic agricultural applications as an input for field-level production management. The enactment of the U.S. Geological Survey’s free and open data policy in 2008 and the launch of Landsat 8 in 2013 have both influenced agricultural applications. This report presents two primary sets of case studies on the applications and benefits of Landsat imagery use in agriculture. The first set examines several operational applications within the U.S. Department of Agriculture (USDA) and the second focuses on private sector applications for agronomic management.
Information on the USDA applications is provided in the U.S. Department of Agriculture Uses of Landsat Imagery for Global and Domestic Agricultural Monitoring section of the report in the following subsections:
Private sector applications using Landsat imagery for agricultural management are discussed in the Landsat Imagery Use and Benefits in Field-Level Agricultural Production Management section of the report in the following subsections:
Director, Fort Collins Science Center
U.S. Geological Survey
2150 Centre Ave., Bldg. C
Fort Collins, CO 80526-8118
Podostemum ceratophyllum, commonly called Hornleaf Riverweed, occurs in mid-order montane and piedmont rivers of eastern North America, where the plant grows submerged and attached to rocks and stable substrates in swift, aerated water. Multiple studies, mostly conducted in the southern portions of the plant’s range, have shown that Podostemum can variously influence benthic communities in flowing waters. However, a synthetic review of the biology and ecology of the plant is needed to inform conservation, particularly because P. ceratophyllum is reported to be in decline in much of its range, for mostly unknown reasons. We have thus summarized the literature showing that Podostemum provides substantial habitat for invertebrates and fish, may be consumed by invertebrates, turtles, and other vertebrates, removes and sequesters dissolved elements (i.e., nitrogen, phosphorus, calcium, zinc, etc.) from the water column, and contributes organic matter to the detrital pool. Podostemum may be tolerant to some forms of pollution but appears vulnerable to sedimentation, epiphytic over-growth, and hydrologic changes that result in desiccation, and possibly increased herbivory pressure. Much remains unknown about Podostemum, including aspects of morphological variation, seed dispersal, and tolerance to changes in temperature and water chemistry. Nonetheless, Podostemum may be considered a foundation species, whose loss from eastern North American rivers is likely to affect higher trophic levels and ecosystem processes.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.aquabot.2017.02.009","usgsCitation":"Wood, J., and Freeman, M., 2017, Ecology of the macrophyte Podostemum ceratophyllum Michx. (Hornleaf riverweed), a widespread foundation species of eastern North American rivers: Aquatic Botany, v. 139, p. 65-74, https://doi.org/10.1016/j.aquabot.2017.02.009.","productDescription":"10 p.","startPage":"65","endPage":"74","ipdsId":"IP-084003","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":338537,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"139","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58dcc7d3e4b02ff32c685667","contributors":{"authors":[{"text":"Wood, James","contributorId":174400,"corporation":false,"usgs":false,"family":"Wood","given":"James","affiliations":[],"preferred":false,"id":686750,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Freeman, Mary 0000-0001-7615-6923 mcfreeman@usgs.gov","orcid":"https://orcid.org/0000-0001-7615-6923","contributorId":3528,"corporation":false,"usgs":true,"family":"Freeman","given":"Mary","email":"mcfreeman@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":686578,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70181024,"text":"ofr20171016 - 2017 - Numerical modeling of the effects of Hurricane Sandy and potential future hurricanes on spatial patterns of salt marsh morphology in Jamaica Bay, New York City","interactions":[],"lastModifiedDate":"2017-03-29T15:19:26","indexId":"ofr20171016","displayToPublicDate":"2017-03-29T00:00:00","publicationYear":"2017","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":"2017-1016","title":"Numerical modeling of the effects of Hurricane Sandy and potential future hurricanes on spatial patterns of salt marsh morphology in Jamaica Bay, New York City","docAbstract":"The salt marshes of Jamaica Bay, managed by the New York City Department of Parks & Recreation and the Gateway National Recreation Area of the National Park Service, serve as a recreational outlet for New York City residents, mitigate flooding, and provide habitat for critical wildlife species. Hurricanes and extra-tropical storms have been recognized as one of the critical drivers of coastal wetland morphology due to their effects on hydrodynamics and sediment transport, deposition, and erosion processes. However, the magnitude and mechanisms of hurricane effects on sediment dynamics and associated coastal wetland morphology in the northeastern United States are poorly understood. In this study, the depth-averaged version of the Delft3D modeling suite, integrated with field measurements, was utilized to examine the effects of Hurricane Sandy and future potential hurricanes on salt marsh morphology in Jamaica Bay, New York City. Hurricane Sandy-induced wind, waves, storm surge, water circulation, sediment transport, deposition, and erosion were simulated by using the modeling system in which vegetation effects on flow resistance, surge reduction, wave attenuation, and sedimentation were also incorporated. Observed marsh elevation change and accretion from a rod surface elevation table and feldspar marker horizons and cesium-137- and lead-210-derived long-term accretion rates were used to calibrate and validate the wind-waves-surge-sediment transport-morphology coupled model.
The model results (storm surge, waves, and marsh deposition and erosion) agreed well with field measurements. The validated modeling system was then used to detect salt marsh morphological change due to Hurricane Sandy across the entire Jamaica Bay over the short-term (for example, 4 days and 1 year) and long-term (for example, 5 and 10 years). Because Hurricanes Sandy (2012) and Irene (2011) were two large and destructive tropical cyclones which hit the northeast coast, the validated coupled model was run to predict the effects of Sandy-like and Irene-like hurricanes with different storm tracks and wind intensities on wetland morphology in Jamaica Bay. Model results indicate that, in Jamaica Bay salt marshes, the morphological changes (greater than 5 millimeters [mm] determined by the long-term marsh accretion rate) caused by Hurricane Sandy were complex and spatially heterogeneous. Most of the erosion (5–40 mm) and deposition (5–30 mm) were mainly characterized by fine sand for channels and bay bottoms and by mud for marsh areas. Hurricane Sandy-generated deposition and erosion were generated locally. The storm-induced net sediment input through Rockaway Inlet was only about 1 percent of the total amount of the sediment reworked by the hurricane. Salt marshes inside the western part of the bay showed erosion overall while marshes inside the eastern part showed deposition from Hurricane Sandy. Model results indicated that most of the marshes could recover from Hurricane Sandy-induced erosion after 1 year and demonstrated continued marsh accretion after the hurricane over the course of long simulation periods although the effect (accretion) was diminished. Local waves and currents generated by Hurricane Sandy appeared to play a critical role in sediment transport and associated wetland morphological change in Jamaica Bay. Hypothetical hurricanes, depending on their track and intensity, cause variable responses in spatial patterns of sediment deposition and erosion compared to simulations without the hurricane. In general, hurricanes passing west of the Jamaica Bay estuary appear to be more destructive to the salt marshes than those passing the east. Consequently, marshes inside the western part of the bay were likely to be more vulnerable to hurricanes than marshes inside the eastern part of the bay.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171016","usgsCitation":"Wang, H., Chen, Q., Hu, K., Snedden, G.A., Hartig, E.K., Couvillion, B.R., Johnson, C.L., and Orton, P.M., 2017, Numerical modeling of the effects of Hurricane Sandy and potential future hurricanes on spatial patterns of salt marsh morphology in Jamaica Bay, New York City: U.S. Geological Survey Open-File Report 2017–1016, 43 p., https://doi.org/10.3133/ofr20171016.","productDescription":"vii, 43 p.","numberOfPages":"56","onlineOnly":"Y","ipdsId":"IP-079827","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":338515,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1016/coverthb.jpg"},{"id":338516,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1016/ofr20171016.pdf","text":"Report","size":"30.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017–1016"}],"country":"United States","state":"New York","city":"New York City","otherGeospatial":"Jamaica Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.95687103271484,\n 40.539112438263516\n ],\n [\n -73.72684478759766,\n 40.539112438263516\n ],\n [\n -73.72684478759766,\n 40.658503716866974\n ],\n [\n -73.95687103271484,\n 40.658503716866974\n ],\n [\n -73.95687103271484,\n 40.539112438263516\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"
Director, Wetland and Aquatic Research Center
U.S. Geological Survey
7920 NW 71st Street
Gainesville, FL 32653
https://www.usgs.gov/centers/wetland-and-aquatic-research-center-warc
","tableOfContents":"Recent investigations of demersal fish communities in deepwater (>50 m) habitats have considerably increased our knowledge of the factors that influence the assemblage structure of fishes across mesophotic to deep-sea depths. While different habitat types influence deepwater fish distribution, whether different types of rugged seafloor features provide functionally equivalent habitat for fishes is poorly understood. In the northeastern Caribbean, different types of rugged features (e.g., seamounts, banks, canyons) punctuate insular margins, and thus create a remarkable setting in which to compare demersal fish communities across various features. Concurrently, several water masses are vertically layered in the water column, creating strong stratification layers corresponding to specific abiotic conditions. In this study, we examined differences among fish assemblages across different features (e.g., seamount, canyon, bank/ridge) and water masses at depths ranging from 98 to 4060 m in the northeastern Caribbean. We conducted 26 remotely operated vehicle dives across 18 sites, identifying 156 species of which 42% of had not been previously recorded from particular depths or localities in the region. While rarefaction curves indicated fewer species at seamounts than at other features in the NE Caribbean, assemblage structure was similar among the different types of features. Thus, similar to seamount studies in other regions, seamounts in the Anegada Passage do not harbor distinct communities from other types of rugged features. Species assemblages, however, differed among depths, with zonation generally corresponding to water mass boundaries in the region. High species turnover occurred at depths <1200 m, and may be driven by changes in water mass characteristics including temperature (4.8–24.4 °C) and dissolved oxygen (2.2–9.5 mg per l). Our study suggests the importance of water masses in influencing community structure of benthic fauna, while considerably adding to the knowledge of mesophotic and deep-sea fish biogeography.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.dsr.2017.03.009","usgsCitation":"Quattrini, A.M., Demopoulos, A., Singer, R., Roa-Varon, A., and Chaytor, J., 2017, Demersal fish assemblages on seamounts and other rugged features in the northeastern Caribbean: Deep-Sea Research Part I: Oceanographic Research Papers, v. 123, p. 90-104, https://doi.org/10.1016/j.dsr.2017.03.009.","productDescription":"15 p.","startPage":"90","endPage":"104","ipdsId":"IP-083697","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":469984,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://hdl.handle.net/1912/9076","text":"Publisher Index Page"},{"id":438403,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7HQ3X4M","text":"USGS data release","linkHelpText":"Demersal fish assemblages on seamounts and other rugged features in the northeastern Caribbean"},{"id":338541,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"123","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58dcc7d4e4b02ff32c68566b","contributors":{"authors":[{"text":"Quattrini, Andrea M. aquattrini@usgs.gov","contributorId":149346,"corporation":false,"usgs":true,"family":"Quattrini","given":"Andrea","email":"aquattrini@usgs.gov","middleInitial":"M.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":false,"id":686500,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Demopoulos, Amanda W.J. 0000-0003-2096-4694 ademopoulos@usgs.gov","orcid":"https://orcid.org/0000-0003-2096-4694","contributorId":371,"corporation":false,"usgs":true,"family":"Demopoulos","given":"Amanda W.J.","email":"ademopoulos@usgs.gov","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":false,"id":686499,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Singer, Randal","contributorId":189929,"corporation":false,"usgs":false,"family":"Singer","given":"Randal","email":"","affiliations":[],"preferred":false,"id":686501,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Roa-Varon, Adela","contributorId":189930,"corporation":false,"usgs":false,"family":"Roa-Varon","given":"Adela","affiliations":[],"preferred":false,"id":686502,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chaytor, Jason D. jchaytor@usgs.gov","contributorId":4961,"corporation":false,"usgs":true,"family":"Chaytor","given":"Jason D.","email":"jchaytor@usgs.gov","affiliations":[{"id":6706,"text":"Woods Hole Oceanographic Institution,","active":true,"usgs":false},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":686503,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70185743,"text":"70185743 - 2017 - Ecosystem variability along the estuarine salinity gradient: Examples from long-term study of San Francisco Bay","interactions":[],"lastModifiedDate":"2017-11-29T16:42:03","indexId":"70185743","displayToPublicDate":"2017-03-29T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2620,"text":"Limnology and Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"Ecosystem variability along the estuarine salinity gradient: Examples from long-term study of San Francisco Bay","docAbstract":"The salinity gradient of estuaries plays a unique and fundamental role in structuring spatial patterns of physical properties, biota, and biogeochemical processes. We use variability along the salinity gradient of San Francisco Bay to illustrate some lessons about the diversity of spatial structures in estuaries and their variability over time. Spatial patterns of dissolved constituents (e.g., silicate) can be linear or nonlinear, depending on the relative importance of river-ocean mixing and internal sinks (diatom uptake). Particles have different spatial patterns because they accumulate in estuarine turbidity maxima formed by the combination of sinking and estuarine circulation. Some constituents have weak or no mean spatial structure along the salinity gradient, reflecting spatially distributed sources along the estuary (nitrate) or atmospheric exchanges that buffer spatial variability of ecosystem metabolism (dissolved oxygen). The density difference between freshwater and seawater establishes stratification in estuaries stronger than the thermal stratification of lakes and oceans. Stratification is strongest around the center of the salinity gradient and when river discharge is high. Spatial distributions of motile organisms are shaped by species-specific adaptations to different salinity ranges (shrimp) and by behavioral responses to environmental variability (northern anchovy). Estuarine spatial patterns change over time scales of events (intrusions of upwelled ocean water), seasons (river inflow), years (annual weather anomalies), and between eras separated by ecosystem disturbances (a species introduction). Each of these lessons is a piece in the puzzle of how estuarine ecosystems are structured and how they differ from the river and ocean ecosystems they bridge.
","language":"English","publisher":"ASLO","doi":"10.1002/lno.10537","usgsCitation":"Cloern, J.E., Jassby, A.D., Schraga, T., Kress, E.S., and Martin, C.A., 2017, Ecosystem variability along the estuarine salinity gradient: Examples from long-term study of San Francisco Bay: Limnology and Oceanography, v. 62, no. S1, p. S272-S291, https://doi.org/10.1002/lno.10537.","productDescription":"20 p.","startPage":"S272","endPage":"S291","ipdsId":"IP-081785","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":461689,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/lno.10537","text":"Publisher Index Page"},{"id":438405,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7TQ5ZPR","text":"USGS data release","linkHelpText":"USGS Measurements of Water Quality in San Francisco Bay (CA), 1969-2015 (ver. 4.0, March 2023)"},{"id":338536,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.52365112304688,\n 37.40943717748788\n ],\n [\n -121.64886474609375,\n 37.40943717748788\n ],\n [\n -121.64886474609375,\n 38.190704293996504\n ],\n [\n -122.52365112304688,\n 38.190704293996504\n ],\n [\n -122.52365112304688,\n 37.40943717748788\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"62","issue":"S1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-03-25","publicationStatus":"PW","scienceBaseUri":"58dcc7d3e4b02ff32c685663","chorus":{"doi":"10.1002/lno.10537","url":"http://dx.doi.org/10.1002/lno.10537","publisher":"Wiley-Blackwell","authors":"Cloern James E., Jassby Alan D., Schraga Tara S., Nejad Erica, Martin Charles","journalName":"Limnology and Oceanography","publicationDate":"3/2017","publiclyAccessibleDate":"3/25/2017"},"contributors":{"authors":[{"text":"Cloern, James E. 0000-0002-5880-6862 jecloern@usgs.gov","orcid":"https://orcid.org/0000-0002-5880-6862","contributorId":1488,"corporation":false,"usgs":true,"family":"Cloern","given":"James","email":"jecloern@usgs.gov","middleInitial":"E.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":686612,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jassby, Alan D.","contributorId":66403,"corporation":false,"usgs":true,"family":"Jassby","given":"Alan","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":686613,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schraga, Tara 0000-0002-2108-5846 tschraga@usgs.gov","orcid":"https://orcid.org/0000-0002-2108-5846","contributorId":1118,"corporation":false,"usgs":true,"family":"Schraga","given":"Tara","email":"tschraga@usgs.gov","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":686616,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kress, Erica S. 0000-0001-8204-6368 ekress@usgs.gov","orcid":"https://orcid.org/0000-0001-8204-6368","contributorId":4859,"corporation":false,"usgs":true,"family":"Kress","given":"Erica","email":"ekress@usgs.gov","middleInitial":"S.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":686614,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Martin, Charles A. 0000-0003-3576-2585 camartin@usgs.gov","orcid":"https://orcid.org/0000-0003-3576-2585","contributorId":4860,"corporation":false,"usgs":true,"family":"Martin","given":"Charles","email":"camartin@usgs.gov","middleInitial":"A.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":686615,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70185702,"text":"70185702 - 2017 - Neonicotinoid insecticide removal by prairie strips in row-cropped watersheds with historical seed coating use","interactions":[],"lastModifiedDate":"2017-03-29T10:07:00","indexId":"70185702","displayToPublicDate":"2017-03-29T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":682,"text":"Agriculture, Ecosystems and Environment","active":true,"publicationSubtype":{"id":10}},"title":"Neonicotinoid insecticide removal by prairie strips in row-cropped watersheds with historical seed coating use","docAbstract":"Neonicotinoids are a widely used class of insecticides that are commonly applied as seed coatings for agricultural crops. Such neonicotinoid use may pose a risk to non-target insects, including pollinators and natural enemies of crop pests, and ecosystems. This study assessed neonicotinoid residues in groundwater, surface runoff water, soil, and native plants adjacent to corn and soybean crop fields with a history of being planted with neonicotinoid-treated seeds from 2008-2013. Data from six sites with the same crop management history, three with and three without in-field prairie strips, were collected in 2015-2016, 2-3 years after neonicotinoid (clothianidin and imidacloprid) seed treatments were last used. Three of the six neonicotinoids analyzed were detected in at least one environmental matrix: the two applied as seed coatings on the fields (clothianidin and imidacloprid) and another widely used neonicotinoid (thiamethoxam). Sites with prairie strips generally had lower concentrations of neonicotinoids: groundwater and footslope soil neonicotinoid concentrations were significantly lower in the sites with prairie strips than those without; mean concentrations for groundwater were 11 and 20 ng/L (p = 0.048) and <1 and 6 ng/g (p = 0.0004) for soil, respectively. Surface runoff water concentrations were not significantly (p = 0.38) different for control sites (44 ng/L) or sites with prairie strips (140 ng/L). Consistent with the decreased inputs of neonicotinoids, concentrations tended to decrease over the sampling timeframe. Two sites recorded concentration increases, however, potentially due to disturbance of previous applications or influence from nearby fields where use of seed treatments continued. There were no detections (limit of detection: 1 ng/g) of neonicotinoids in the foliage or roots of plants comprising prairie strips, indicating a low likelihood of exposure to pollinators and other insects visiting these plants following the cessation of seed coating use. Offsite transport of neonicotinoids to aquatic systems through the groundwater and surface water were furthermore reduced with prairie strips. This study demonstrates the potential for prairie strips comprising 10% of an agricultural catchment to mitigate the non-target impacts of neonicotinoids.","language":"English","publisher":"Elsevier","doi":"10.1016/j.agee.2017.03.015","usgsCitation":"Hladik, M., Bradbury, S., Schulte, L.A., Helmers, M., Witte, C., Kolpin, D.W., Garrett, J.D., and Harris, M., 2017, Neonicotinoid insecticide removal by prairie strips in row-cropped watersheds with historical seed coating use: Agriculture, Ecosystems and Environment, v. 241, p. 160-167, https://doi.org/10.1016/j.agee.2017.03.015.","productDescription":"8 p.","startPage":"160","endPage":"167","ipdsId":"IP-083340","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":488600,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://lib.dr.iastate.edu/nrem_pubs/209","text":"External Repository"},{"id":338539,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"241","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58dcc7d4e4b02ff32c68566d","contributors":{"authors":[{"text":"Hladik, Michelle L. 0000-0002-0891-2712 mhladik@usgs.gov","orcid":"https://orcid.org/0000-0002-0891-2712","contributorId":189904,"corporation":false,"usgs":true,"family":"Hladik","given":"Michelle L.","email":"mhladik@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":686445,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bradbury, Steven","contributorId":177603,"corporation":false,"usgs":false,"family":"Bradbury","given":"Steven","email":"","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":686446,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schulte, Lisa A.","contributorId":177987,"corporation":false,"usgs":false,"family":"Schulte","given":"Lisa","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":686447,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Helmers, Matthew","contributorId":189905,"corporation":false,"usgs":false,"family":"Helmers","given":"Matthew","email":"","affiliations":[],"preferred":false,"id":686448,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Witte, Christopher","contributorId":189906,"corporation":false,"usgs":false,"family":"Witte","given":"Christopher","email":"","affiliations":[],"preferred":false,"id":686449,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"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":686450,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Garrett, Jessica D. 0000-0002-4466-3709 jgarrett@usgs.gov","orcid":"https://orcid.org/0000-0002-4466-3709","contributorId":4229,"corporation":false,"usgs":true,"family":"Garrett","given":"Jessica","email":"jgarrett@usgs.gov","middleInitial":"D.","affiliations":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":686452,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Harris, Mary","contributorId":189907,"corporation":false,"usgs":false,"family":"Harris","given":"Mary","email":"","affiliations":[],"preferred":false,"id":686451,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ]}