We describe a parallel implementation of TRIGRS, the Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability Model for the timing and distribution of rainfall-induced shallow landslides. We have parallelized the four time-demanding execution modes of TRIGRS, namely both the saturated and unsaturated model with finite and infinite soil depth options, within the Message Passing Interface framework. In addition to new features of the code, we outline details of the parallel implementation and show the performance gain with respect to the serial code. Results are obtained both on commercial hardware and on a high-performance multi-node machine, showing the different limits of applicability of the new code. We also discuss the implications for the application of the model on large-scale areas and as a tool for real-time landslide hazard monitoring.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.envsoft.2016.04.002","usgsCitation":"Alvioli, M., and Baum, R., 2016, Parallelization of the TRIGRS model for rainfall-induced landslides using the message passing interface: Environmental Modelling and Software, v. 81, p. 122-135, https://doi.org/10.1016/j.envsoft.2016.04.002.","productDescription":"14 p.","startPage":"122","endPage":"135","ipdsId":"IP-074052","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":438603,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7M044QS","text":"USGS data release","linkHelpText":"TRIGRS version 2.1"},{"id":438602,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F73J3B27","text":"USGS data release","linkHelpText":"Serial and parallel versions of the Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability Model (TRIGRS)"},{"id":438601,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7ZW1J08","text":"USGS data release","linkHelpText":"Map and model input and output data covering N 40.0 40.375 and W 105.25 105.625 in the northern Colorado Front Range for analysis of debris flow initiation resulting from the storm of September 9 13, 2013"},{"id":331019,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"81","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"582c2ce6e4b0c253be072c0a","contributors":{"authors":[{"text":"Alvioli, M.","contributorId":36829,"corporation":false,"usgs":true,"family":"Alvioli","given":"M.","affiliations":[],"preferred":false,"id":653839,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baum, R.L.","contributorId":68752,"corporation":false,"usgs":true,"family":"Baum","given":"R.L.","email":"","affiliations":[],"preferred":false,"id":653840,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70182781,"text":"70182781 - 2016 - The statistical power to detect cross-scale interactions at macroscales","interactions":[],"lastModifiedDate":"2017-03-01T12:46:23","indexId":"70182781","displayToPublicDate":"2016-07-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"The statistical power to detect cross-scale interactions at macroscales","docAbstract":"Macroscale studies of ecological phenomena are increasingly common because stressors such as climate and land-use change operate at large spatial and temporal scales. Cross-scale interactions (CSIs), where ecological processes operating at one spatial or temporal scale interact with processes operating at another scale, have been documented in a variety of ecosystems and contribute to complex system dynamics. However, studies investigating CSIs are often dependent on compiling multiple data sets from different sources to create multithematic, multiscaled data sets, which results in structurally complex, and sometimes incomplete data sets. The statistical power to detect CSIs needs to be evaluated because of their importance and the challenge of quantifying CSIs using data sets with complex structures and missing observations. We studied this problem using a spatially hierarchical model that measures CSIs between regional agriculture and its effects on the relationship between lake nutrients and lake productivity. We used an existing large multithematic, multiscaled database, LAke multiscaled GeOSpatial, and temporal database (LAGOS), to parameterize the power analysis simulations. We found that the power to detect CSIs was more strongly related to the number of regions in the study rather than the number of lakes nested within each region. CSI power analyses will not only help ecologists design large-scale studies aimed at detecting CSIs, but will also focus attention on CSI effect sizes and the degree to which they are ecologically relevant and detectable with large data sets.
","language":"English","publisher":"Wiley","doi":"10.1002/ecs2.1417","usgsCitation":"Wagner, T., Fergus, C.E., Stow, C., Cheruvelil, K.S., and Soranno, P.A., 2016, The statistical power to detect cross-scale interactions at macroscales: Ecosphere, v. 7, no. 7, HTML document , https://doi.org/10.1002/ecs2.1417.","productDescription":"HTML document ","ipdsId":"IP-071692","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":470783,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.1417","text":"Publisher Index Page"},{"id":336753,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"7","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-07-28","publicationStatus":"PW","scienceBaseUri":"58b7eba8e4b01ccd5500bb1b","contributors":{"authors":[{"text":"Wagner, Tyler 0000-0003-1726-016X twagner@usgs.gov","orcid":"https://orcid.org/0000-0003-1726-016X","contributorId":1050,"corporation":false,"usgs":true,"family":"Wagner","given":"Tyler","email":"twagner@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":673735,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fergus, C. Emi","contributorId":150608,"corporation":false,"usgs":false,"family":"Fergus","given":"C.","email":"","middleInitial":"Emi","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":680427,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stow, Craig A.","contributorId":49733,"corporation":false,"usgs":true,"family":"Stow","given":"Craig A.","affiliations":[],"preferred":false,"id":680428,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cheruvelil, Kendra S.","contributorId":172029,"corporation":false,"usgs":false,"family":"Cheruvelil","given":"Kendra","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":680429,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Soranno, Patricia A.","contributorId":172104,"corporation":false,"usgs":false,"family":"Soranno","given":"Patricia","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":680430,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70180261,"text":"70180261 - 2016 - Bayesian nitrate source apportionment to individual groundwater wells in the Central Valley by use of elemental and isotopic tracers","interactions":[],"lastModifiedDate":"2018-08-07T12:34:01","indexId":"70180261","displayToPublicDate":"2016-07-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Bayesian nitrate source apportionment to individual groundwater wells in the Central Valley by use of elemental and isotopic tracers","docAbstract":"Groundwater quality is a concern in alluvial aquifers that underlie agricultural areas, such as in the San Joaquin Valley of California. Shallow domestic wells (less than 150 m deep) in agricultural areas are often contaminated by nitrate. Agricultural and rural nitrate sources include dairy manure, synthetic fertilizers, and septic waste. Knowledge of the relative proportion that each of these sources contributes to nitrate concentration in individual wells can aid future regulatory and land management decisions. We show that nitrogen and oxygen isotopes of nitrate, boron isotopes, and iodine concentrations are a useful, novel combination of groundwater tracers to differentiate between manure, fertilizers, septic waste, and natural sources of nitrate. Furthermore, in this work, we develop a new Bayesian mixing model in which these isotopic and elemental tracers were used to estimate the probability distribution of the fractional contributions of manure, fertilizers, septic waste, and natural sources to the nitrate concentration found in an individual well. The approach was applied to 56 nitrate-impacted private domestic wells located in the San Joaquin Valley. Model analysis found that some domestic wells were clearly dominated by the manure source and suggests evidence for majority contributions from either the septic or fertilizer source for other wells. But, predictions of fractional contributions for septic and fertilizer sources were often of similar magnitude, perhaps because modeled uncertainty about the fraction of each was large. For validation of the Bayesian model, fractional estimates were compared to surrounding land use and estimated source contributions were broadly consistent with nearby land use types.
","language":"English","publisher":"AGU Publications","doi":"10.1002/2015WR018523","usgsCitation":"Ransom, K.M., Grote, M.N., Deinhart, A., Eppich, G., Kendall, C., Sanborn, M.E., Sounders, A.K., Wimpenny, J., Yin, Q., Young, M.B., and Harter, T., 2016, Bayesian nitrate source apportionment to individual groundwater wells in the Central Valley by use of elemental and isotopic tracers: Water Resources Research, v. 52, no. 7, p. 5577-5597, https://doi.org/10.1002/2015WR018523.","productDescription":"21 p.","startPage":"5577","endPage":"5597","ipdsId":"IP-076967","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":470785,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015wr018523","text":"Publisher Index Page"},{"id":334055,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Central Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.52001953124999,\n 38.03078569382294\n ],\n [\n -121.39892578125,\n 37.57070524233116\n ],\n [\n -119.893798828125,\n 35.63051198300061\n ],\n [\n -118.6907958984375,\n 35.652832827451654\n ],\n [\n -119.08630371093749,\n 36.319551259461186\n ],\n [\n -119.55322265624999,\n 36.98500309285596\n ],\n [\n -120.52001953124999,\n 38.03078569382294\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"52","issue":"7","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-07-31","publicationStatus":"PW","scienceBaseUri":"588b1977e4b0ad67323f97e8","contributors":{"authors":[{"text":"Ransom, Katherine M","contributorId":178789,"corporation":false,"usgs":false,"family":"Ransom","given":"Katherine","email":"","middleInitial":"M","affiliations":[],"preferred":false,"id":660979,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grote, Mark N.","contributorId":178790,"corporation":false,"usgs":false,"family":"Grote","given":"Mark","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":660980,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Deinhart, Amanda","contributorId":178791,"corporation":false,"usgs":false,"family":"Deinhart","given":"Amanda","email":"","affiliations":[],"preferred":false,"id":660981,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Eppich, Gary","contributorId":178796,"corporation":false,"usgs":false,"family":"Eppich","given":"Gary","email":"","affiliations":[],"preferred":false,"id":660988,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kendall, Carol 0000-0002-0247-3405 ckendall@usgs.gov","orcid":"https://orcid.org/0000-0002-0247-3405","contributorId":1462,"corporation":false,"usgs":true,"family":"Kendall","given":"Carol","email":"ckendall@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":660982,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sanborn, Matthew E.","contributorId":178792,"corporation":false,"usgs":false,"family":"Sanborn","given":"Matthew","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":660983,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sounders, A. 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Rapid restoration of infrastructure after a large-scale disaster is necessary to sustaining a nation's economy and security, but such long-term restoration has not been investigated as thoroughly as initial rescue and recovery efforts. A model of the Greater Saint Louis Missouri area was created and a disaster scenario simulated. An evolutionary algorithm is used to determine the order in which the bridges should be repaired based on indirect costs. Solutions were evaluated based on the reduction of indirect costs and the restoration of transportation capacity. When compared to a greedy algorithm, the evolutionary algorithm solution reduced indirect costs by approximately 12.4% by restoring automotive travel routes for workers and re-establishing the flow of commodities across the three rivers in the Saint Louis area.
","language":"English","publisher":"Wiley","doi":"10.1002/j.2334-5837.2016.00272.x","usgsCitation":"Corns, S., Long, S.K., and Shoberg, T.G., 2016, Infrastructure system restoration planning using evolutionary algorithms: INCOSE International Symposium, v. 26, no. 1, p. 1947-1956, https://doi.org/10.1002/j.2334-5837.2016.00272.x.","productDescription":"10 p.","startPage":"1947","endPage":"1956","ipdsId":"IP-071024","costCenters":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"links":[{"id":339971,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"26","issue":"1","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2016-09-13","publicationStatus":"PW","scienceBaseUri":"58f877b9e4b0b7ea54521c1a","contributors":{"authors":[{"text":"Corns, Steven","contributorId":146271,"corporation":false,"usgs":false,"family":"Corns","given":"Steven","affiliations":[{"id":16655,"text":"Dept. of Engineering Management and Systems Engineering, Missouri University of Science and Technology, Rolla, MO","active":true,"usgs":false}],"preferred":false,"id":692164,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Long, Suzanna K.","contributorId":146270,"corporation":false,"usgs":false,"family":"Long","given":"Suzanna","email":"","middleInitial":"K.","affiliations":[{"id":16655,"text":"Dept. of Engineering Management and Systems Engineering, Missouri University of Science and Technology, Rolla, MO","active":true,"usgs":false}],"preferred":false,"id":692165,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shoberg, Thomas G. 0000-0003-0173-1246 tshoberg@usgs.gov","orcid":"https://orcid.org/0000-0003-0173-1246","contributorId":3764,"corporation":false,"usgs":true,"family":"Shoberg","given":"Thomas","email":"tshoberg@usgs.gov","middleInitial":"G.","affiliations":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":648905,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70184978,"text":"70184978 - 2016 - Contemporary deformation in the Yakima fold and thrust belt estimated with GPS","interactions":[],"lastModifiedDate":"2017-03-14T16:01:22","indexId":"70184978","displayToPublicDate":"2016-07-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1803,"text":"Geophysical Journal International","active":true,"publicationSubtype":{"id":10}},"title":"Contemporary deformation in the Yakima fold and thrust belt estimated with GPS","docAbstract":"Geodetic, geologic and palaeomagnetic data reveal that Oregon (western USA) rotates clockwise at 0.3 to 1.0° Ma−1 (relative to North America) about an axis near the Idaho–Oregon–Washington border, while northeast Washington is relatively fixed. This rotation has been going on for at least 15 Ma. The Yakima fold and thrust belt (YFTB) forms the boundary between northern Oregon and central Washington where convergence of the clockwise-rotating Oregon block is apparently accommodated. North–south shortening across the YFTB has been thought to occur in a fan-like manner, increasing in rate to the west. We obtained high-accuracy, high-density geodetic GPS measurements in 2012–2014 that are used with earlier GPS measurements from the 1990s to characterize YFTB kinematics. The new results show that the deformation associated with the YFTB starts at the Blue Mountains Anticline in northern Oregon and extends north beyond the Frenchman Hills in Washington, past the epicentre of the 1872 Mw 7.0 Entiat earthquake to 49°N. The north–south strain rate across the region is 2 to 3 × 10−9 yr−1 between the volcanic arc and the eastern edge of the YFTB (241.0°E); east of there it drops to about 10−9 yr−1. At the eastern boundary of the YFTB, faults and earthquake activity are truncated by a north-trending, narrow zone of deformation that runs along the Pasco Basin and Moses Lake regions near 240.9°E. This zone, abutting the Department of Energy Hanford Nuclear Reservation, accommodates about 0.5 mm yr−1 of east to northeast shortening. A similar zone of N-trending transpression is seen along 239.9°E where there is a change in the strike of the Yakima folds. The modern deformation of the YFTB is about 600 km wide from south to north and internally may be controlled by pre-existing crustal structure.
","language":"English","publisher":"Oxford University Press","doi":"10.1093/gji/ggw252","usgsCitation":"McCaffrey, R., King, R.W., Wells, R.E., Lancaster, M., and Miller, M.M., 2016, Contemporary deformation in the Yakima fold and thrust belt estimated with GPS: Geophysical Journal International, v. 207, no. 1, p. 1-11, https://doi.org/10.1093/gji/ggw252.","productDescription":"11 p.","startPage":"1","endPage":"11","ipdsId":"IP-073652","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":470784,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/gji/ggw252","text":"Publisher Index Page"},{"id":337545,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"207","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-07-11","publicationStatus":"PW","scienceBaseUri":"58c90127e4b0849ce97abced","contributors":{"authors":[{"text":"McCaffrey, Robert","contributorId":189078,"corporation":false,"usgs":false,"family":"McCaffrey","given":"Robert","email":"","affiliations":[],"preferred":false,"id":683802,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"King, Robert W.","contributorId":189079,"corporation":false,"usgs":false,"family":"King","given":"Robert","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":683803,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wells, Ray E. 0000-0002-7796-0160 rwells@usgs.gov","orcid":"https://orcid.org/0000-0002-7796-0160","contributorId":149772,"corporation":false,"usgs":true,"family":"Wells","given":"Ray","email":"rwells@usgs.gov","middleInitial":"E.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":683801,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lancaster, Matthew","contributorId":189080,"corporation":false,"usgs":false,"family":"Lancaster","given":"Matthew","email":"","affiliations":[],"preferred":false,"id":683804,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Miller, M. Meghan","contributorId":189081,"corporation":false,"usgs":false,"family":"Miller","given":"M.","email":"","middleInitial":"Meghan","affiliations":[],"preferred":false,"id":683805,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70186193,"text":"70186193 - 2016 - Hydrogeologic controls on groundwater discharge and nitrogen loads in a coastal watershed","interactions":[],"lastModifiedDate":"2017-03-31T10:50:47","indexId":"70186193","displayToPublicDate":"2016-07-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Hydrogeologic controls on groundwater discharge and nitrogen loads in a coastal watershed","docAbstract":"Submarine groundwater discharge (SGD) is a small portion of the global water budget, but a potentially large contributor to coastal nutrient budgets due to high concentrations relative to stream discharge. A numerical groundwater flow model of the Inland Bays Watershed, Delaware, USA, was developed to identify the primary hydrogeologic factors that affect groundwater discharge rates and transit times to streams and bays. The distribution of groundwater discharge between streams and bays is sensitive to the depth of the water table below land surface. Higher recharge and reduced hydraulic conductivity raised the water table and increased discharge to streams relative to bays compared to the Reference case (in which 66% of recharge is discharged to streams). Increases to either factor decreased transit times for discharge to both streams and bays compared to the Reference case (in which mean transit times are 56.5 and 94.3 years, respectively), though sensitivity to recharge is greater. Groundwater-borne nitrogen loads were calculated from nitrogen concentrations measured in discharging fresh groundwater and modeled SGD rates. These loads combined with long SGD transit times suggest groundwater-borne nitrogen reductions and estuarine water quality improvements will lag decades behind implementation of efforts to manage nutrient sources. This work enhances understanding of the hydrogeologic controls on and uncertainties in absolute and relative rates and transit times of groundwater discharge to streams and bays in coastal watersheds.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2016.05.013","usgsCitation":"Russoniello, C.J., Konikow, L.F., Kroeger, K.D., Fernandez, C., Andres, A., and Michael, H.A., 2016, Hydrogeologic controls on groundwater discharge and nitrogen loads in a coastal watershed: Journal of Hydrology, v. 538, p. 783-793, https://doi.org/10.1016/j.jhydrol.2016.05.013.","productDescription":"11 p.","startPage":"783","endPage":"793","ipdsId":"IP-071064","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":470791,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hdl.handle.net/1912/8150","text":"External Repository"},{"id":338942,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"538","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58df6ac0e4b02ff32c6aea2f","contributors":{"authors":[{"text":"Russoniello, Chrtopher J.","contributorId":190221,"corporation":false,"usgs":false,"family":"Russoniello","given":"Chrtopher","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":687831,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Konikow, Leonard F. 0000-0002-0940-3856 lkonikow@usgs.gov","orcid":"https://orcid.org/0000-0002-0940-3856","contributorId":158,"corporation":false,"usgs":true,"family":"Konikow","given":"Leonard","email":"lkonikow@usgs.gov","middleInitial":"F.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":687830,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kroeger, Kevin D. 0000-0002-4272-2349 kkroeger@usgs.gov","orcid":"https://orcid.org/0000-0002-4272-2349","contributorId":1603,"corporation":false,"usgs":true,"family":"Kroeger","given":"Kevin","email":"kkroeger@usgs.gov","middleInitial":"D.","affiliations":[{"id":41100,"text":"Coastal and Marine Hazards and Resources Program","active":true,"usgs":true}],"preferred":true,"id":687832,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fernandez, Cristina","contributorId":190222,"corporation":false,"usgs":false,"family":"Fernandez","given":"Cristina","email":"","affiliations":[],"preferred":false,"id":687833,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Andres, A. Scott","contributorId":64750,"corporation":false,"usgs":true,"family":"Andres","given":"A. Scott","affiliations":[],"preferred":false,"id":687834,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Michael, Holly A.","contributorId":190224,"corporation":false,"usgs":false,"family":"Michael","given":"Holly","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":687835,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70187246,"text":"70187246 - 2016 - Ungulate browsers promote herbaceous layer diversity in logged temperate forests","interactions":[],"lastModifiedDate":"2017-04-28T13:19:54","indexId":"70187246","displayToPublicDate":"2016-07-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Ungulate browsers promote herbaceous layer diversity in logged temperate forests","docAbstract":"Ungulates are leading drivers of plant communities worldwide, with impacts linked to animal density, disturbance and vegetation structure, and site productivity. Many ecosystems have more than one ungulate species; however, few studies have specifically examined the combined effects of two or more species on plant communities. We examined the extent to which two ungulate browsers (moose [Alces americanus]) and white-tailed deer [Odocoileus virginianus]) have additive (compounding) or compensatory (opposing) effects on herbaceous layer composition and diversity, 5–6 years after timber harvest in Massachusetts, USA. We established three combinations of ungulates using two types of fenced exclosures – none (full exclosure), deer (partial exclosure), and deer + moose (control) in six replicated blocks. Species composition diverged among browser treatments, and changes were generally additive. Plant assemblages characteristic of closed canopy forests were less abundant and assemblages characteristic of open/disturbed habitats were more abundant in deer + moose plots compared with ungulate excluded areas. Browsing by deer + moose resulted in greater herbaceous species richness at the plot scale (169 m2) and greater woody species richness at the subplot scale (1 m2) than ungulate exclusion and deer alone. Browsing by deer + moose resulted in strong changes to the composition, structure, and diversity of forest herbaceous layers, relative to areas free of ungulates and areas browed by white-tailed deer alone. Our results provide evidence that moderate browsing in forest openings can promote both herbaceous and woody plant diversity. These results are consistent with the classic grazing-species richness curve, but have rarely been documented in forests.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.2223","usgsCitation":"Faison, E.K., DeStefano, S., Foster, D., Motzkin, G., and Rapp, J., 2016, Ungulate browsers promote herbaceous layer diversity in logged temperate forests: Ecology and Evolution, v. 6, no. 13, p. 4591-4602, https://doi.org/10.1002/ece3.2223.","productDescription":"12 p.","startPage":"4591","endPage":"4602","ipdsId":"IP-069428","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":470795,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.2223","text":"Publisher Index Page"},{"id":340616,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","issue":"13","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-06-12","publicationStatus":"PW","scienceBaseUri":"590454a4e4b022cee40dc23a","contributors":{"authors":[{"text":"Faison, Edward K.","contributorId":191559,"corporation":false,"usgs":false,"family":"Faison","given":"Edward","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":693489,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"DeStefano, Stephen 0000-0003-2472-8373 destef@usgs.gov","orcid":"https://orcid.org/0000-0003-2472-8373","contributorId":166706,"corporation":false,"usgs":true,"family":"DeStefano","given":"Stephen","email":"destef@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":693104,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Foster, David R.","contributorId":149881,"corporation":false,"usgs":false,"family":"Foster","given":"David R.","affiliations":[{"id":16810,"text":"Harvard Univ.","active":true,"usgs":false}],"preferred":false,"id":693490,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Motzkin, Glenn","contributorId":191567,"corporation":false,"usgs":false,"family":"Motzkin","given":"Glenn","email":"","affiliations":[],"preferred":false,"id":693491,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rapp, Josh","contributorId":79757,"corporation":false,"usgs":true,"family":"Rapp","given":"Josh","email":"","affiliations":[],"preferred":false,"id":693492,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70184330,"text":"70184330 - 2016 - Predicting arsenic in drinking water wells of the Central Valley, California","interactions":[],"lastModifiedDate":"2018-09-12T16:43:45","indexId":"70184330","displayToPublicDate":"2016-07-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Predicting arsenic in drinking water wells of the Central Valley, California","docAbstract":"Probabilities of arsenic in groundwater at depths used for domestic and public supply in the Central Valley of California are predicted using weak-learner ensemble models (boosted regression trees, BRT) and more traditional linear models (logistic regression, LR). Both methods captured major processes that affect arsenic concentrations, such as the chemical evolution of groundwater, redox differences, and the influence of aquifer geochemistry. Inferred flow-path length was the most important variable but near-surface-aquifer geochemical data also were significant. A unique feature of this study was that previously predicted nitrate concentrations in three dimensions were themselves predictive of arsenic and indicated an important redox effect at >10 μg/L, indicating low arsenic where nitrate was high. Additionally, a variable representing three-dimensional aquifer texture from the Central Valley Hydrologic Model was an important predictor, indicating high arsenic associated with fine-grained aquifer sediment. BRT outperformed LR at the 5 μg/L threshold in all five predictive performance measures and at 10 μg/L in four out of five measures. BRT yielded higher prediction sensitivity (39%) than LR (18%) at the 10 μg/L threshold–a useful outcome because a major objective of the modeling was to improve our ability to predict high arsenic areas.
","language":"English","publisher":"ACS Publications","doi":"10.1021/acs.est.6b01914","usgsCitation":"Ayotte, J.D., Nolan, B.T., and Gronberg, J.M., 2016, Predicting arsenic in drinking water wells of the Central Valley, California: Environmental Science & Technology, v. 50, no. 14, p. 7555-7563, https://doi.org/10.1021/acs.est.6b01914.","productDescription":"9 p.","startPage":"7555","endPage":"7563","ipdsId":"IP-074943","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":336970,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Central Valley","volume":"50","issue":"14","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2016-07-11","publicationStatus":"PW","scienceBaseUri":"58bfd4f6e4b014cc3a3ba4c8","contributors":{"authors":[{"text":"Ayotte, Joseph D. 0000-0002-1892-2738 jayotte@usgs.gov","orcid":"https://orcid.org/0000-0002-1892-2738","contributorId":149619,"corporation":false,"usgs":true,"family":"Ayotte","given":"Joseph","email":"jayotte@usgs.gov","middleInitial":"D.","affiliations":[{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":681021,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nolan, Bernard T. 0000-0002-6945-9659 btnolan@usgs.gov","orcid":"https://orcid.org/0000-0002-6945-9659","contributorId":2190,"corporation":false,"usgs":true,"family":"Nolan","given":"Bernard","email":"btnolan@usgs.gov","middleInitial":"T.","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"preferred":true,"id":681022,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gronberg, JoAnn M. 0000-0003-4822-7434 jmgronbe@usgs.gov","orcid":"https://orcid.org/0000-0003-4822-7434","contributorId":3548,"corporation":false,"usgs":true,"family":"Gronberg","given":"JoAnn","email":"jmgronbe@usgs.gov","middleInitial":"M.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":681023,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70176820,"text":"70176820 - 2016 - Fault zone characteristics and basin complexity in the southern Salton Trough, California","interactions":[],"lastModifiedDate":"2016-10-11T13:03:55","indexId":"70176820","displayToPublicDate":"2016-07-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1796,"text":"Geology","active":true,"publicationSubtype":{"id":10}},"title":"Fault zone characteristics and basin complexity in the southern Salton Trough, California","docAbstract":"Ongoing oblique slip at the Pacific–North America plate boundary in the Salton Trough produced the Imperial Valley (California, USA), a seismically active area with deformation distributed across a complex network of exposed and buried faults. To better understand the shallow crustal structure in this region and the connectivity of faults and seismicity lineaments, we used data primarily from the Salton Seismic Imaging Project to construct a three-dimensional P-wave velocity model down to 8 km depth and a velocity profile to 15 km depth, both at 1 km grid spacing. A VP = 5.65–5.85 km/s layer of possibly metamorphosed sediments within, and crystalline basement outside, the valley is locally as thick as 5 km, but is thickest and deepest in fault zones and near seismicity lineaments, suggesting a causative relationship between the low velocities and faulting. Both seismicity lineaments and surface faults control the structural architecture of the western part of the larger wedge-shaped basin, where two deep subbasins are located. We estimate basement depths, and show that high velocities at shallow depths and possible basement highs characterize the geothermal areas.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/G38033.1","usgsCitation":"Persaud, P., Ma, Y., Stock, J.M., Hole, J.A., Fuis, G.S., and Han, L., 2016, Fault zone characteristics and basin complexity in the southern Salton Trough, California: Geology, v. 44, no. 9, p. 747-750, https://doi.org/10.1130/G38033.1.","productDescription":"4 p.","startPage":"747","endPage":"750","ipdsId":"IP-078827","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":329437,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Salton Trough","volume":"44","issue":"9","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-09-01","publicationStatus":"PW","scienceBaseUri":"57fe679ee4b0824b2d143711","contributors":{"authors":[{"text":"Persaud, Patricia","contributorId":175210,"corporation":false,"usgs":false,"family":"Persaud","given":"Patricia","email":"","affiliations":[{"id":13711,"text":"Caltech","active":true,"usgs":false}],"preferred":false,"id":650423,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ma, Yiran","contributorId":175211,"corporation":false,"usgs":false,"family":"Ma","given":"Yiran","email":"","affiliations":[{"id":13711,"text":"Caltech","active":true,"usgs":false}],"preferred":false,"id":650424,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stock, Joann M.","contributorId":21057,"corporation":false,"usgs":true,"family":"Stock","given":"Joann","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":650425,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hole, John A.","contributorId":104801,"corporation":false,"usgs":true,"family":"Hole","given":"John","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":650426,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fuis, Gary S. 0000-0002-3078-1544 fuis@usgs.gov","orcid":"https://orcid.org/0000-0002-3078-1544","contributorId":2639,"corporation":false,"usgs":true,"family":"Fuis","given":"Gary","email":"fuis@usgs.gov","middleInitial":"S.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":650422,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Han, Liang","contributorId":49690,"corporation":false,"usgs":true,"family":"Han","given":"Liang","email":"","affiliations":[],"preferred":false,"id":650427,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70193661,"text":"70193661 - 2016 - Slab melting and magma formation beneath the southern Cascade arc","interactions":[],"lastModifiedDate":"2017-11-02T15:21:45","indexId":"70193661","displayToPublicDate":"2016-07-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1427,"text":"Earth and Planetary Science Letters","active":true,"publicationSubtype":{"id":10}},"title":"Slab melting and magma formation beneath the southern Cascade arc","docAbstract":"The processes that drive magma formation beneath the Cascade arc and other warm-slab subduction zones have been debated because young oceanic crust is predicted to largely dehydrate beneath the forearc during subduction. In addition, geochemical variability along strike in the Cascades has led to contrasting interpretations about the role of volatiles in magma generation. Here, we focus on the Lassen segment of the Cascade arc, where previous work has demonstrated across-arc geochemical variations related to subduction enrichment, and H-isotope data suggest that H2O in basaltic magmas is derived from the final breakdown of chlorite in the mantle portion of the slab. We use naturally glassy, olivine-hosted melt inclusions (MI) from the tephra deposits of eight primitive (MgO>7 wt%) basaltic cinder cones to quantify the pre-eruptive volatile contents of mantle-derived melts in this region. The melt inclusions have B concentrations and isotope ratios that are similar to mid-ocean ridge basalt (MORB), suggesting extensive dehydration of the downgoing plate prior to reaching sub-arc depths and little input of slab-derived B into the mantle wedge. However, correlations of volatile and trace element ratios (H2O/Ce, Cl/Nb, Sr/Nd) in the melt inclusions demonstrate that geochemical variability is the result of variable addition of a hydrous subduction component to the mantle wedge. Furthermore, correlations between subduction component tracers and radiogenic isotope ratios show that the subduction component has less radiogenic Sr and Pb than the Lassen sub-arc mantle, which can be explained by melting of subducted Gorda MORB beneath the arc. Agreement between pMELTS melting models and melt inclusion volatile, major, and trace element data suggests that hydrous slab melt addition to the mantle wedge can produce the range in primitive compositions erupted in the Lassen region. Our results provide further evidence that chlorite-derived fluids from the mantle portion of the slab (∼7–9 km below the slab top) cause flux melting of the subducted oceanic crust, producing hydrous slab melts that migrate into the overlying mantle, where they react with peridotite to induce further melting.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.epsl.2016.03.044","usgsCitation":"Walowski, K.J., Wallace, P.J., Clynne, M.A., Rasmussen, D., and Weis, D., 2016, Slab melting and magma formation beneath the southern Cascade arc: Earth and Planetary Science Letters, v. 446, p. 100-112, https://doi.org/10.1016/j.epsl.2016.03.044.","productDescription":"12 p.","startPage":"100","endPage":"112","ipdsId":"IP-066861","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":470787,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.research.ed.ac.uk/en/publications/ac26caa7-78c7-4d82-b689-f1ab62b89bd3","text":"Publisher Index Page"},{"id":348125,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Cascades","volume":"446","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59fc2ea6e4b0531197b27f8b","contributors":{"authors":[{"text":"Walowski, Kristina J.","contributorId":199699,"corporation":false,"usgs":false,"family":"Walowski","given":"Kristina","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":719800,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wallace, Paul J.","contributorId":199700,"corporation":false,"usgs":false,"family":"Wallace","given":"Paul","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":719801,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Clynne, Michael A. 0000-0002-4220-2968 mclynne@usgs.gov","orcid":"https://orcid.org/0000-0002-4220-2968","contributorId":2032,"corporation":false,"usgs":true,"family":"Clynne","given":"Michael","email":"mclynne@usgs.gov","middleInitial":"A.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":719799,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rasmussen, D.J.","contributorId":199701,"corporation":false,"usgs":false,"family":"Rasmussen","given":"D.J.","email":"","affiliations":[],"preferred":false,"id":719802,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Weis, D.","contributorId":199702,"corporation":false,"usgs":false,"family":"Weis","given":"D.","email":"","affiliations":[],"preferred":false,"id":719803,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70193671,"text":"70193671 - 2016 - A long-term study of ecological impacts of river channelization on the population of an endangered fish: Lessons learned for assessment and restoration","interactions":[],"lastModifiedDate":"2017-11-13T14:13:43","indexId":"70193671","displayToPublicDate":"2016-07-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"A long-term study of ecological impacts of river channelization on the population of an endangered fish: Lessons learned for assessment and restoration","docAbstract":"Projects to assess environmental impact or restoration success in rivers focus on project-specific questions but can also provide valuable insights for future projects. Both restoration actions and impact assessments can become “adaptive” by using the knowledge gained from long-term monitoring and analysis to revise the actions, monitoring, conceptual model, or interpretation of findings so that subsequent actions or assessments are better informed. Assessments of impact or restoration success are especially challenging when the indicators of interest are imperiled species and/or the impacts being addressed are complex. From 1997 to 2015, we worked closely with two federal agencies to monitor habitat availability for and population density of Roanoke logperch (Percina rex), an endangered fish, in a 24-km-long segment of the upper Roanoke River, VA. We primarily used a Before-After-Control-Impact analytical framework to assess potential impacts of a river channelization project on the P. rex population. In this paper, we summarize how our extensive monitoring facilitated the evolution of our (a) conceptual understanding of the ecosystem and fish population dynamics; (b) choices of ecological indicators and analytical tools; and (c) conclusions regarding the magnitude, mechanisms, and significance of observed impacts. Our experience with this case study taught us important lessons about how to adaptively develop and conduct a monitoring program, which we believe are broadly applicable to assessments of environmental impact and restoration success in other rivers. In particular, we learned that (a) pre-treatment planning can enhance monitoring effectiveness, help avoid unforeseen pitfalls, and lead to more robust conclusions; (b) developing adaptable conceptual and analytical models early was crucial to organizing our knowledge, guiding our study design, and analyzing our data; (c) catchment-wide processes that we did not monitor, or initially consider, had profound implications for interpreting our findings; and (d) using multiple analytical frameworks, with varying assumptions, led to clearer interpretation of findings than the use of a single framework alone. Broader integration of these guiding principles into monitoring studies, though potentially challenging, could lead to more scientifically defensible assessments of project effects.
","language":"English","publisher":"MDPI","doi":"10.3390/w8060240","usgsCitation":"Roberts, J.H., Anderson, G.B., and Angermeier, P.L., 2016, A long-term study of ecological impacts of river channelization on the population of an endangered fish: Lessons learned for assessment and restoration: Water, v. 8, no. 6, p. 1-38, https://doi.org/10.3390/w8060240.","productDescription":"Article 240; 38 p.","startPage":"1","endPage":"38","ipdsId":"IP-073154","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":470796,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w8060240","text":"Publisher Index Page"},{"id":348710,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"6","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-06-03","publicationStatus":"PW","scienceBaseUri":"5a60fd1fe4b06e28e9c24779","contributors":{"authors":[{"text":"Roberts, James H.","contributorId":83811,"corporation":false,"usgs":true,"family":"Roberts","given":"James","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":721841,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, Gregory B.","contributorId":65988,"corporation":false,"usgs":true,"family":"Anderson","given":"Gregory","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":721842,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Angermeier, Paul L. 0000-0003-2864-170X biota@usgs.gov","orcid":"https://orcid.org/0000-0003-2864-170X","contributorId":166679,"corporation":false,"usgs":true,"family":"Angermeier","given":"Paul","email":"biota@usgs.gov","middleInitial":"L.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":719847,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70159913,"text":"70159913 - 2016 - Rare earths: Market disruption, innovation, and global supply chains","interactions":[],"lastModifiedDate":"2020-12-17T20:33:59.752908","indexId":"70159913","displayToPublicDate":"2016-06-30T15:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5122,"text":"Environment and Resources","active":true,"publicationSubtype":{"id":10}},"title":"Rare earths: Market disruption, innovation, and global supply chains","docAbstract":"Rare earths, sometimes called the vitamins of modern materials, captured public attention when their prices increased more than ten-fold in 2010 and 2011. As prices fell between 2011 and 2016, rare earths receded from public view—but less visibly they became a major focus of innovative activity in companies, government laboratories and universities. Geoscientists worked to better understand the resource base and improve our knowledge about mineral deposits that will be mines in the future. Process engineers carried out research that is making primary production and recycling more efficient. Materials scientists and engineers searched for substitutes that will require fewer or no rare earths while providing properties comparable or superior to those of existing materials. As a result, even though global supply chains are not significantly different now than they were before the market disruption, the innovative activity motivated by the disruption likely will have far-reaching, if unpredictable, consequences for supply chains of rare earths in the future.
","language":"English","publisher":"Annual Reviews","doi":"10.1146/annurev-environ-110615-085700","usgsCitation":"Eggert, R., Wadia, C., Anderson, C., Bauer, D., Fields, F., Meinert, L.D., and Taylor, P., 2016, Rare earths: Market disruption, innovation, and global supply chains: Environment and Resources, v. 41, p. 199-222, https://doi.org/10.1146/annurev-environ-110615-085700.","productDescription":"24 p.","startPage":"199","endPage":"222","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-071063","costCenters":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"links":[{"id":324688,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"41","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5776349de4b07dd077c829cd","contributors":{"authors":[{"text":"Eggert, Roderick","contributorId":172613,"corporation":false,"usgs":false,"family":"Eggert","given":"Roderick","email":"","affiliations":[],"preferred":false,"id":641416,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wadia, Cyrus","contributorId":172614,"corporation":false,"usgs":false,"family":"Wadia","given":"Cyrus","email":"","affiliations":[],"preferred":false,"id":641417,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anderson, Corby","contributorId":172615,"corporation":false,"usgs":false,"family":"Anderson","given":"Corby","email":"","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":641418,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bauer, Diana","contributorId":172616,"corporation":false,"usgs":false,"family":"Bauer","given":"Diana","email":"","affiliations":[],"preferred":false,"id":641419,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fields, Fletcher","contributorId":172617,"corporation":false,"usgs":false,"family":"Fields","given":"Fletcher","email":"","affiliations":[],"preferred":false,"id":641420,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Meinert, Lawrence D. lmeinert@usgs.gov","contributorId":1639,"corporation":false,"usgs":true,"family":"Meinert","given":"Lawrence","email":"lmeinert@usgs.gov","middleInitial":"D.","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"preferred":true,"id":581014,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Taylor, Patrick","contributorId":172618,"corporation":false,"usgs":false,"family":"Taylor","given":"Patrick","email":"","affiliations":[],"preferred":false,"id":641421,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70170965,"text":"sir20165060 - 2016 - Flood-inundation maps for Lake Champlain in Vermont and in northern Clinton County, New York","interactions":[{"subject":{"id":70170965,"text":"sir20165060 - 2016 - Flood-inundation maps for Lake Champlain in Vermont and in northern Clinton County, New York","indexId":"sir20165060","publicationYear":"2016","noYear":false,"title":"Flood-inundation maps for Lake Champlain in Vermont and in northern Clinton County, New York"},"predicate":"SUPERSEDED_BY","object":{"id":70202005,"text":"sir20185169 - 2019 - Flood-inundation maps for Lake Champlain in Vermont and New York","indexId":"sir20185169","publicationYear":"2019","noYear":false,"title":"Flood-inundation maps for Lake Champlain in Vermont and New York"},"id":1}],"supersededBy":{"id":70202005,"text":"sir20185169 - 2019 - Flood-inundation maps for Lake Champlain in Vermont and New York","indexId":"sir20185169","publicationYear":"2019","noYear":false,"title":"Flood-inundation maps for Lake Champlain in Vermont and New York"},"lastModifiedDate":"2022-11-02T14:53:45.691442","indexId":"sir20165060","displayToPublicDate":"2016-06-30T14:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-5060","title":"Flood-inundation maps for Lake Champlain in Vermont and in northern Clinton County, New York","docAbstract":"Digital flood-inundation maps for an approximately100-mile length of Lake Champlain in Addison, Chittenden, Franklin, and Grand Isle Counties in Vermont and northern Clinton County in New York were created by the U.S. Geological Survey (USGS) in cooperation with the International Joint Commission (IJC). The flood-inundationmaps, which can be accessed through the International Joint Commission (IJC) Web site at http://www.ijc.org/en_/, depict estimates of the areal extent flooding correspondingto selected water levels (stages) at the USGS lake gage on the Richelieu River (Lake Champlain) at Rouses Point, N.Y. (station number 04295000). In this study, wind and seiche effects (standing oscillating wave with a long wavelength) were not taken into account and the flood-inundation mapsreflect 11 stages (elevations) for Lake Champlain that are static for the study length of the lake. Near-real-time stages at this lake gage, and others on Lake Champlain, may be obtained on the Internet from the USGS National Water Information System at http://waterdata.usgs.gov/ or the National Weather Service Advanced Hydrologic Prediction Service at http:/water.weather.gov/ahps/, which also forecasts flood hydrographs at the Richelieu River (Lake Champlain) at Rouses Point.
Static flood boundary extents were determined for LakeChamplain in Addison, Chittenden, Franklin, and Grand Isle Counties in Vermont and northern Clinton County in New York using recently acquired (2013–2014) lidar (light detection and ranging) and may be referenced to any of the five USGS lake gages on Lake Champlain. Of these five lakgages, USGS lake gage 04295000, Richelieu River (Lake Champlain) at Rouses Point, N.Y., is the only USGS lake gage that is also a National Weather Service prediction location. Flood boundary extents for the Lake Champlain static flood-inundation map corresponding to the May 201 flood(103.2 feet [ft], National Geodetic Vertical Datum [NGVD] 29) were evaluated by comparing these boundary extents against the inundation area extents determined for the May 2011 flood (which incorporated documented high-water marksfrom the flood of May 201) (Bjerklie and others, 2014).
A digital elevation model (DEM) was created by USGS, within a geographic information system (GIS), from the recently flown and processed light detection and ranging(lidar) data (2013–2014) in Vermont and the lake shore area of northern Clinton County in New York. The lidar data have a vertical accuracy of 0.3 to 0.6-ft (9.6 to 18.0-centimeters [cm]) and a horizontal resolution of 2.3 to 4.6 ft (0.7 to 1.4 meters). This DEM was used in determining the floodboundary for 11 flood stages at 0.5-ft intervals from 100.0 to104.0 ft (NGVD 29) and 1-ft intervals from 104.0 to 106.0 ft (NGVD 29) as referenced to the USGS lake gage 04295000, Richelieu River (Lake Champlain) at Rouses Point, N.Y. In addition, the May 2011 flood-inundation area for elevation103.20 ft (NGVD 29) (102.77 ft, North American Vertical Datum [NAVD] 88) was determined from this DEM. The May 2011 flood is the highest recorded lake water level (stage)at the Rouses Point, N.Y., lake gage. Flood stages greater than 101.5 ft (NGVD 29) exceed the “major flood stage”as defined by the NationalWeather Service for USGS lake gage 04295000.
The availability of these maps, along with Internet information regarding current stage from the USGS lake gage and forecasted high-flow stages from the NationalWeather Service, will provide emergency management personnel and residents with information that is critical for flood responseactivities such as evacuations and road closures, as well as for post-flood recovery eforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165060","collaboration":"Prepared in cooperation with the International Joint Commission","usgsCitation":"Flynn, R.H., and Hayes, Laura, 2016, Flood-inundation maps for Lake Champlain in Vermont and in northern Clinton County, New York: U.S. Geological Survey Scientific Investigations Report 2016–5060, 11 p., https://dx.doi.org/10.3133/sir20165060.","productDescription":"vi, 11 p.","numberOfPages":"22","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-068359","costCenters":[{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true}],"links":[{"id":323821,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5060/sir20165060.pdf","text":"Report","size":"1.54 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5060"},{"id":323820,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5060/coverthb.jpg"}],"country":"United States","state":"New York, Vermont","otherGeospatial":"Lake Champlain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.4600830078125,\n 43.614205328810954\n ],\n [\n -73.4600830078125,\n 45.00753503123719\n ],\n [\n -73.11676025390625,\n 45.00753503123719\n ],\n [\n -73.11676025390625,\n 43.614205328810954\n ],\n [\n -73.4600830078125,\n 43.614205328810954\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
331 Commerce Way, Suite 2
Pembroke, NH 03275
Or visit our Web site at:
http://newengland.water.usgs.gov
Wildfire can significantly alter the hydrologic response of a watershed to the extent that even modest rainstorms can generate dangerous flash floods and debris flows. To reduce public exposure to hazard, the U.S. Geological Survey produces post-fire debris-flow hazard assessments for select fires in the western United States. We use publicly available geospatial data describing basin morphology, burn severity, soil properties, and rainfall characteristics to estimate the statistical likelihood that debris flows will occur in response to a storm of a given rainfall intensity. Using an empirical database and refined geospatial analysis methods, we defined new equations for the prediction of debris-flow likelihood using logistic regression methods. We showed that the new logistic regression model outperformed previous models used to predict debris-flow likelihood.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161106","usgsCitation":"Staley, D.M., Negri, J.A., Kean, J.W., Laber, J.M., Tillery, A.C., and Youberg, A.M., 2016, Updated logistic regression equations for the calculation of post-fire debris-flow likelihood in the western United States: U.S. Geological Survey Open-File Report 2016–1106, 13 p., https://dx.doi.org/ofr20161106.","productDescription":"Report: iv, 13 p.; Appendix 1","numberOfPages":"17","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-076051","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":324673,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1106/ofr20161106.pdf","text":"Report","size":"1.73 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1106 Report"},{"id":324672,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1106/coverthb.jpg"},{"id":324675,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2016/1106/ofr20161106_appx-1.xlsx","text":"Appendix 1","size":"268 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2016-1106 Appendix 1"}],"contact":"Center Director, Geologic Hazards Science Center
U.S. Geological Survey
Box 25046, MS 966
Denver, CO 80225-0046
Understanding spatial variability in contaminant fate and transport is critical to efficient regional water-quality restoration. An approach to capitalize on previously calibrated spatially referenced regression (SPARROW) models to improve the understanding of contaminant fate and transport was developed and applied to the case of nitrogen in the 166,000 km2 Chesapeake Bay watershed. A continuous function of four hydrogeologic, soil, and other landscape properties significant (α = 0.10) to nitrogen transport from uplands to streams was evaluated and compared among each of the more than 80,000 individual catchments (mean area, 2.1 km2) in the watershed. Budgets (including inputs, losses or net change in storage in uplands and stream corridors, and delivery to tidal waters) were also estimated for nitrogen applied to these catchments from selected upland sources. Most (81%) of such inputs are removed, retained, or otherwise processed in uplands rather than transported to surface waters. Combining SPARROW results with previous budget estimates suggests 55% of this processing is attributable to denitrification, 23% to crop or timber harvest, and 6% to volatilization. Remaining upland inputs represent a net annual increase in landscape storage in soils or biomass exceeding 10 kg per hectare in some areas. Such insights are important for planning watershed restoration and for improving future watershed models.
","language":"English","publisher":"American Water Resources Association","doi":"10.1111/1752-1688.12419","usgsCitation":"Ator, S., and Garcia, A.M., 2016, Application of SPARROW modeling to understanding contaminant fate and transport from uplands to streams: JAWRA, v. 52, no. 3, p. 685-704, https://doi.org/10.1111/1752-1688.12419.","productDescription":"20 p.","startPage":"685","endPage":"704","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-071433","costCenters":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"links":[{"id":324676,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"52","issue":"3","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-09","publicationStatus":"PW","scienceBaseUri":"5776349ce4b07dd077c829aa","contributors":{"authors":[{"text":"Ator, Scott 0000-0002-9186-4837 swator@usgs.gov","orcid":"https://orcid.org/0000-0002-9186-4837","contributorId":152414,"corporation":false,"usgs":true,"family":"Ator","given":"Scott","email":"swator@usgs.gov","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":589240,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Garcia, Ana Maria 0000-0002-5388-1281 agarcia@usgs.gov","orcid":"https://orcid.org/0000-0002-5388-1281","contributorId":2035,"corporation":false,"usgs":true,"family":"Garcia","given":"Ana","email":"agarcia@usgs.gov","middleInitial":"Maria","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":589241,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70174223,"text":"70174223 - 2016 - Historical habitat barriers prevent ring-like genetic continuity throughout the distribution of threatened Alameda Striped Racers (Coluber lateralis euryxanthus)","interactions":[],"lastModifiedDate":"2018-11-20T15:45:42","indexId":"70174223","displayToPublicDate":"2016-06-30T11:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1892,"text":"Herpetologica","active":true,"publicationSubtype":{"id":10}},"title":"Historical habitat barriers prevent ring-like genetic continuity throughout the distribution of threatened Alameda Striped Racers (Coluber lateralis euryxanthus)","docAbstract":"We used microsatellites and mtDNA sequences to examine the mixed effects of geophysical, habitat, and contemporary urban barriers on the genetics of threatened Alameda Striped Racers (Coluber lateralis euryxanthus), a species with close ties to declining coastal scrub and chaparral habitat in the eastern San Francisco Bay area of California. We used cluster assignments to characterize population genetic structuring with respect to land management units and approximate Bayesian analysis to rank the ability of five alternative evolutionary hypotheses to explain the inferred structure. Then, we estimated rates of contemporary and historical migration among the major clusters and measured the fit of different historical migration models to better understand the formation of the current population structure. Our results reveal a ring-like pattern of historical connectivity around the Tri-Valley area of the East Bay (i.e., San Ramon, Amador, and Livermore valleys), with clusters largely corresponding to different management units. We found no evidence of continuous gene flow throughout the ring, however, and that the main gap in continuity is centered across the Livermore Valley. Historical migration models support higher rates of gene flow away from the terminal ends of the ring on the north and south sides of the Valley, compared with rates into those areas from western sites that border the interior San Francisco Bay. We attribute the break in ring-like connectivity to the presence of unsuitable habitat within the Livermore Valley that has been reinforced by 20th century urbanization, and the asymmetry in gene flow rates to spatial constraints on movement and east–west environmental gradients influenced by the proximity of the San Francisco Bay.
","language":"English","publisher":"The Herpetologists' League","doi":"10.1655/Herpetologica-D-15-00046.1","usgsCitation":"Richmond, J.Q., Wood, D.A., Swaim, K., Fisher, R.N., and Vandergast, A.G., 2016, Historical habitat barriers prevent ring-like genetic continuity throughout the distribution of threatened Alameda Striped Racers (Coluber lateralis euryxanthus): Herpetologica, v. 72, no. 3, p. 202-213, https://doi.org/10.1655/Herpetologica-D-15-00046.1.","productDescription":"12 p.","startPage":"202","endPage":"213","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066471","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":324669,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Tri-Valley area of the East Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.40280151367188,\n 37.80218877920469\n ],\n [\n -122.20916748046876,\n 37.54457732085582\n ],\n [\n -122.04299926757812,\n 37.42034463389752\n ],\n [\n -121.96746826171875,\n 37.47594794878128\n ],\n [\n -122.20367431640624,\n 37.779398571318765\n ],\n [\n -122.40280151367188,\n 37.80218877920469\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"72","issue":"3","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5776349de4b07dd077c829c3","contributors":{"authors":[{"text":"Richmond, Jonathan Q. 0000-0001-9398-4894 jrichmond@usgs.gov","orcid":"https://orcid.org/0000-0001-9398-4894","contributorId":5400,"corporation":false,"usgs":true,"family":"Richmond","given":"Jonathan","email":"jrichmond@usgs.gov","middleInitial":"Q.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":641399,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wood, Dustin A. 0000-0002-7668-9911 dawood@usgs.gov","orcid":"https://orcid.org/0000-0002-7668-9911","contributorId":4179,"corporation":false,"usgs":true,"family":"Wood","given":"Dustin","email":"dawood@usgs.gov","middleInitial":"A.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":641400,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Swaim, Karen","contributorId":172600,"corporation":false,"usgs":false,"family":"Swaim","given":"Karen","affiliations":[{"id":27065,"text":"Swaim Biological Inc, Livermore, CA","active":true,"usgs":false}],"preferred":false,"id":641401,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fisher, Robert N. 0000-0002-2956-3240 rfisher@usgs.gov","orcid":"https://orcid.org/0000-0002-2956-3240","contributorId":1529,"corporation":false,"usgs":true,"family":"Fisher","given":"Robert","email":"rfisher@usgs.gov","middleInitial":"N.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":641402,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vandergast, Amy G. 0000-0002-7835-6571 avandergast@usgs.gov","orcid":"https://orcid.org/0000-0002-7835-6571","contributorId":3963,"corporation":false,"usgs":true,"family":"Vandergast","given":"Amy","email":"avandergast@usgs.gov","middleInitial":"G.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":641403,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70170927,"text":"sir20165049 - 2016 - Adjusting annual maximum peak discharges at selected stations in northeastern Illinois for changes in land-use conditions","interactions":[],"lastModifiedDate":"2016-07-06T17:17:02","indexId":"sir20165049","displayToPublicDate":"2016-06-30T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-5049","title":"Adjusting annual maximum peak discharges at selected stations in northeastern Illinois for changes in land-use conditions","docAbstract":"The effects of urbanization on annual maximum peak discharges in northeastern Illinois and nearby areas from 1945 to 2009 were analyzed with a two-step longitudinal-quantile linear regression approach. The peak discharges were then adjusted to 2010 land-use conditions. The explanatory variables used were daily precipitation at the time of the peak discharge event and a housing density-based measure of developed land use. The effect of the implementation of stormwater detention was assessed indirectly. Peak discharge records affected by the construction of large reservoirs that affect channel routing were identified and were split into segments at the time of completion of the reservoir. Longitudinal regressions of the peak discharge records on linear and logarithmic transformations of the selected measures of urbanization and precipitation were tested, and the best fitting model was selected for quantile regression and adjustment of the peak discharges.
\nBecause the uncertainties of streamgage-by-streamgage regressions of peak discharges as a function of urbanization are so large, a regional urbanization response was computed. Streamgages used in this study fit the following two criteria: (1) drainage area is at most 200 square miles and, (2) at least 10 consecutive years of peak discharge record are available. In the first step of the regression analysis, linear longitudinal regression models with fixed intercepts estimated for each segment of the peak discharge records were computed. The segment intercepts were then subtracted from the discharge records to homogenize the discharge dataset across the segments in preparation for the quantile regression analysis. From the quantile regression analysis, the effect of urbanization on peak discharge varies strongly with the exceedance probability of the peak discharge event; coefficients monotonically increase from 0.340 to 0.969 over exceedance probabilities from 0.002 to 0.99. The regression analyses yield estimates of the population-wide effect of the explanatory variables on the dependent variables as a function of exceedance probability. These estimates are similar to the coefficients of the regional regression relations in USGS regional flood-frequency studies such as those implemented in the Web application StreamStats; although in the longitudinal analysis used in this study, it is the temporal not the spatial (between-streamgage) variations that are taken into account.
\nThe observed and adjusted values for each streamgage are tabulated. To illustrate the overall effect of the adjustments, differences in the mean, standard deviation, and skewness of the log-transformed observed and urbanization-adjusted peak discharge series by streamgage are computed. For almost every streamgage where an adjustment was applied (no increase in urbanization was reported for a few streamgages), the mean increased and the standard deviation decreased; the effect on skewness values was more variable but usually they increased. Significant positive peak discharge trends were common in the observed values, occurring at 27.3 percent of streamgages at a p-value of 0.05 according to a Kendall’s tau correlation test; in the adjusted values, the incidence of such trends was reduced to 7.0 percent.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165049","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers—Chicago District, the Illinois Center for Transportation, the Illinois Department of Transportation, and the Federal Highway Administration","usgsCitation":"Over, T.M., Saito, R.J., and Soong, D.T., 2016, Adjusting annual maximum peak discharges at selected stations in northeastern Illinois for changes in land-use conditions: U.S. Geological Survey Scientific Investigations Report 2016–5049, 33 p., https://dx.doi.org/10.3133/sir20165049.","productDescription":"Report: viii, 33 p.; Tables; Spatial Data","numberOfPages":"46","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-050378","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":324541,"rank":4,"type":{"id":23,"text":"Spatial 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U.S. Geological Survey
405 North Goodwin Avenue
Urbana, IL 61801
Though characterization of, and understanding determinants of, social structure in bats is increasing, little is known about how bat social groups respond to disturbance resulting in roost loss. Given that many species of bats roost in ephemeral or transitory resources such as plants, it is clear that bat social groups can tolerate some level of roost loss. Understanding responses of bat social groups to roost loss can provide insight into social structure that have applied conservation use. Herein, we review the existing literature on the effects of disturbance on bat social groups, and present a parameterizable agent-based model that can be used to explore the relationships among roost dynamics, population dynamics, and social behavior.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Sociality in bats","language":"English","publisher":"Springer","doi":"10.1007/978-3-319-38953-0_13","usgsCitation":"Silvis, A., Abaid, N., Ford, W., and Britzke, E.R., 2016, Responses of bat social groups to roost loss: More questions than answers, chap. of Sociality in bats, p. 261-280, https://doi.org/10.1007/978-3-319-38953-0_13.","productDescription":"20 p.","startPage":"261","endPage":"280","ipdsId":"IP-066788","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":340718,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-06-08","publicationStatus":"PW","scienceBaseUri":"59099aaee4b0fc4e449157ee","contributors":{"editors":[{"text":"Ortega, Jorge","contributorId":191697,"corporation":false,"usgs":false,"family":"Ortega","given":"Jorge","email":"","affiliations":[],"preferred":false,"id":693882,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"authors":[{"text":"Silvis, Alexander","contributorId":171585,"corporation":false,"usgs":false,"family":"Silvis","given":"Alexander","email":"","affiliations":[{"id":26923,"text":"Virginia Polytechnic Institute, Blacksburg, VA","active":true,"usgs":false}],"preferred":false,"id":693879,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Abaid, Nicole","contributorId":171663,"corporation":false,"usgs":false,"family":"Abaid","given":"Nicole","email":"","affiliations":[],"preferred":false,"id":693880,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ford, W. Mark 0000-0002-9611-594X wford@usgs.gov","orcid":"https://orcid.org/0000-0002-9611-594X","contributorId":172499,"corporation":false,"usgs":true,"family":"Ford","given":"W. Mark","email":"wford@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":693147,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Britzke, Eric R.","contributorId":8327,"corporation":false,"usgs":true,"family":"Britzke","given":"Eric","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":693881,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70173837,"text":"sir20165086 - 2016 - Three-dimensional visualization maps of suspended-sediment concentrations during placement of dredged material in 21st Avenue West Channel Embayment, Duluth-Superior Harbor, Duluth, Minnesota, 2015","interactions":[],"lastModifiedDate":"2016-07-01T11:38:06","indexId":"sir20165086","displayToPublicDate":"2016-06-30T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-5086","title":"Three-dimensional visualization maps of suspended-sediment concentrations during placement of dredged material in 21st Avenue West Channel Embayment, Duluth-Superior Harbor, Duluth, Minnesota, 2015","docAbstract":"Excess sediment in rivers and estuaries poses serious environmental and economic challenges. The U.S. Army Corps of Engineers (USACE) routinely dredges sediment in Federal navigation channels to maintain commercial shipping operations. The USACE initiated a 3-year pilot project in 2013 to use navigation channel dredged material to aid in restoration of shoreline habitat in the 21st Avenue West Channel Embayment of the Duluth-Superior Harbor. Placing dredged material in the 21st Avenue West Channel Embayment supports the restoration of shallow bay aquatic habitat aiding in the delisting of the St. Louis River Estuary Area of Concern.
The U.S. Geological Survey, in cooperation with the USACE, collected turbidity and suspended-sediment concentrations (SSCs) in 2014 and 2015 to measure the horizontal and vertical distribution of SSCs during placement operations of dredged materials. These data were collected to help the USACE evaluate the use of several best management practices, including various dredge material placement techniques and a silt curtain, to mitigate the dispersion of suspended sediment.
Three-dimensional visualization maps are a valuable tool for assessing the spatial displacement of SSCs. Data collection was designed to coincide with four dredged placement configurations that included periods with and without a silt curtain as well as before and after placement of dredged materials. Approximately 230 SSC samples and corresponding turbidity values collected in 2014 and 2015 were used to develop a simple linear regression model between SSC and turbidity. Using the simple linear regression model, SSCs were estimated for approximately 3,000 turbidity values at approximately 100 sampling sites in the 21st Avenue West Channel Embayment of the Duluth-Superior Harbor. The estimated SSCs served as input for development of 12 three-dimensional visualization maps.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165086","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Groten, J.T., Ellison, C.A., and Mahoney, M.H., 2016, Three-dimensional visualization maps of suspended-sediment concentrations during placement of dredged material in 21st Avenue West Channel Embayment, Duluth-Superior Harbor, Duluth, Minnesota, 2015: U.S. Geological Survey Scientific Investigations Report 2016–5086, 26 p., https://dx.doi.org/10.3133/sir20165086.","productDescription":"Report: vi, 26 p.; Appendix Tables: 1-1 through 1-4","startPage":"1","endPage":"26","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-069759","costCenters":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"links":[{"id":324664,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5086/sir20165086_appendix1.xlsx","text":"Appendix Tables 1–1 through 1–4","size":"277 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2016–5086 Appendix Tables"},{"id":324663,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5086/sir20165086.pdf","text":"Report","size":"8.41 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016–5086"},{"id":324662,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5086/coverthb.jpg"}],"country":"United States","state":"Minnesota","city":"Duluth","otherGeospatial":"Duluth-Superior Harbor","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.12679862976073,\n 46.75162347434115\n ],\n [\n -92.12679862976073,\n 46.76626466624822\n ],\n [\n -92.10474014282227,\n 46.76626466624822\n ],\n [\n -92.10474014282227,\n 46.75162347434115\n ],\n [\n -92.12679862976073,\n 46.75162347434115\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Minnesota Water Science Center
U.S. Geological Survey
2280 Woodale Drive
Mounds View, Minnesota 55112
Stonecats Noturus flavus in Vermont conform to a rare distribution pattern (as designated by Rabinowitz 1981) because their known distribution within the state is limited to the LaPlatte and Missisquoi rivers. We focused on Stonecats in the LaPlatte River to predict the stability of the population. During 2012–2014, we captured Stonecats via backpack electrofishing; fish were PIT-tagged (>90 mm TL) and marked with visible implant elastomer. Among the 1,671 Stonecats that were captured, 1,252 were PIT-tagged. Only 156 (12%) of the PIT-tagged fish were recaptured, and only 22 of those individuals were recaptured more than once. The Pradel model in Program MARK was used to estimate apparent survival (Φ) and seniority, which were used to derive the rate of population change (λ) for the Stonecat encounter histories we studied. We examined a total of 64 models in our candidate set, with the following covariates: TL at first capture, maximum temperature, season, maximum discharge, and area sampled. Survival estimates were highest in the spring (range of daily Φ = 0.9993–0.9995) and increased with greater TL at first capture. We also estimated increases in capture probability with increasing area sampled. We derived an annual λ of 0.9794, which indicates a slightly decreasing population. However, our λ estimate contained uncertainty that was likely increased due to the low recapture rates. Additional years of data could increase the accuracy of the λ estimate. In the meantime, we have provided insight into Stonecat population parameters that were otherwise unknown.
","language":"English","publisher":"American Fisheries Society","doi":"10.1080/00028487.2016.1167779","usgsCitation":"Puchala, E.A., Parrish, D.L., and Donovan, T., 2016, Predicting the stability of endangered stonecats in the LaPlatte River, Vermont: Transactions of the American Fisheries Society, v. 145, no. 4, p. 903-912, https://doi.org/10.1080/00028487.2016.1167779.","productDescription":"10 p.","startPage":"903","endPage":"912","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069044","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":324657,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Vermont","otherGeospatial":"LaPlatte River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.21598052978516,\n 44.3795759047351\n ],\n [\n -73.21340560913086,\n 44.37564968766977\n ],\n [\n -73.21134567260742,\n 44.37123237879009\n ],\n [\n -73.21443557739258,\n 44.367305602292426\n ],\n [\n -73.20653915405273,\n 44.36632386703344\n ],\n [\n -73.20430755615234,\n 44.36632386703344\n ],\n [\n -73.20138931274414,\n 44.36546483518457\n ],\n [\n -73.19538116455078,\n 44.36202858181481\n ],\n [\n -73.1964111328125,\n 44.35859212688665\n ],\n [\n -73.19023132324219,\n 44.35834665810766\n ],\n [\n -73.18611145019531,\n 44.3587148608905\n ],\n [\n -73.17838668823242,\n 44.3587148608905\n ],\n [\n -73.17684173583984,\n 44.35662834786087\n ],\n [\n -73.17581176757812,\n 44.35159586369938\n ],\n [\n -73.17649841308594,\n 44.34791328441686\n ],\n [\n -73.17684173583984,\n 44.343984944818594\n ],\n [\n -73.17340850830078,\n 44.343248351836074\n ],\n [\n -73.17014694213867,\n 44.34435323783919\n ],\n [\n -73.16225051879883,\n 44.34300281878521\n ],\n [\n -73.15950393676758,\n 44.34337111797587\n ],\n [\n -73.15023422241211,\n 44.344476001665214\n ],\n [\n -73.14525604248047,\n 44.34435323783919\n ],\n [\n -73.14250946044922,\n 44.34288005187414\n ],\n [\n -73.1224250793457,\n 44.337478053272804\n ],\n [\n -73.1198501586914,\n 44.33477686732845\n ],\n [\n -73.12105178833008,\n 44.331216023015294\n ],\n [\n -73.125,\n 44.328882938821394\n ],\n [\n -73.13203811645508,\n 44.32851454862283\n ],\n [\n -73.14422607421875,\n 44.332689502057086\n ],\n [\n -73.15229415893555,\n 44.332689502057086\n ],\n [\n -73.16413879394531,\n 44.33158439624637\n ],\n [\n -73.17255020141602,\n 44.3329350782982\n ],\n [\n -73.18525314331055,\n 44.33465408319267\n ],\n [\n -73.18902969360352,\n 44.338337495433734\n ],\n [\n -73.18937301635742,\n 44.34668570657191\n ],\n [\n -73.18937301635742,\n 44.35049111420936\n ],\n [\n -73.20602416992188,\n 44.35257784576407\n ],\n [\n -73.20791244506836,\n 44.35797845301104\n ],\n [\n -73.21512222290038,\n 44.358837594637265\n ],\n [\n -73.22233200073242,\n 44.3584693926257\n ],\n [\n -73.22593688964844,\n 44.36092402899763\n ],\n [\n -73.22559356689453,\n 44.36914631155484\n ],\n [\n -73.22628021240234,\n 44.37270485210456\n ],\n [\n -73.22851181030273,\n 44.37614047920012\n ],\n [\n -73.2297134399414,\n 44.37982128456053\n ],\n [\n -73.23022842407227,\n 44.38313381155159\n ],\n [\n -73.22851181030273,\n 44.38583276904476\n ],\n [\n -73.22507858276367,\n 44.38656882676517\n ],\n [\n -73.22319030761719,\n 44.38693685215458\n ],\n [\n -73.21701049804688,\n 44.38436062583777\n ],\n [\n -73.21598052978516,\n 44.3795759047351\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"145","issue":"4","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-06-29","publicationStatus":"PW","scienceBaseUri":"5774e34ae4b07dd077c5fcda","contributors":{"authors":[{"text":"Puchala, Elizabeth A.","contributorId":38862,"corporation":false,"usgs":true,"family":"Puchala","given":"Elizabeth","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":641374,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Parrish, Donna L. 0000-0001-9693-6329 dparrish@usgs.gov","orcid":"https://orcid.org/0000-0001-9693-6329","contributorId":138661,"corporation":false,"usgs":true,"family":"Parrish","given":"Donna","email":"dparrish@usgs.gov","middleInitial":"L.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":621877,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Donovan, Therese M. tdonovan@usgs.gov","contributorId":2653,"corporation":false,"usgs":true,"family":"Donovan","given":"Therese M.","email":"tdonovan@usgs.gov","affiliations":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"preferred":false,"id":641375,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70156604,"text":"70156604 - 2016 - Misapplied survey data and model uncertainty result in incorrect conclusions about the role of predation on alewife population dynamics in Lake Huron: a comment on He et al. (2015)","interactions":[],"lastModifiedDate":"2016-06-29T16:02:13","indexId":"70156604","displayToPublicDate":"2016-06-29T17:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Misapplied survey data and model uncertainty result in incorrect conclusions about the role of predation on alewife population dynamics in Lake Huron: a comment on He et al. (2015)","docAbstract":"Drastic recent and ongoing changes to fish populations and food webs in the Great Lakes have been well-described (Riley et al. 2008; Barbiero et al. 2009; Nalepa et al. 2009; Fahnenstiel et al. 2010;Evans et al. 2011; Gobin et al. 2015), and uncertainty regarding their potential effects on fisheries has caused concern among scientists and fishery managers (e.g., Dettmers et al. 2012). In particular, the relative importance of “bottom-up” (e.g., lower trophic level changes) versus “top-down” (e.g., predation) factors to fish community changes in the Great Lakes have been widely debated (e.g.,Barbiero et al. 2011; Eshenroder and Lantry 2012; Bunnell et al. 2014). In Lake Huron, recent ecosystem changes have been particularly profound, and populations of alewife (Alosa pseudoharengus), an offshore pelagic prey fish, collapsed in 2003 and have yet to recover (Riley et al. 2008, 2014). He et al. (2015) recently used a series of linked ecological models to assess the role of predation in the dynamics of the offshore prey fish community in Lake Huron. While we believe that they provide a novel method for combining bioenergetics and stock assessment modeling, we question the validity of their conclusions because of the misapplication of survey data and the lack of critical interpretation of their modeling efforts. Here we describe how He et al. (2015) have misapplied bottom trawl data from Lake Huron, and we provide examples of how this has resulted in erroneous conclusions regarding the importance of predation to the population dynamics and collapse of alewife in Lake Huron.
","language":"English","publisher":"NRC Research Press","doi":"10.1139/cjfas-2015-0237","usgsCitation":"Riley, S.C., and Dunlop, E.S., 2016, Misapplied survey data and model uncertainty result in incorrect conclusions about the role of predation on alewife population dynamics in Lake Huron: a comment on He et al. (2015): Canadian Journal of Fisheries and Aquatic Sciences, v. 73, no. 5, p. 860-864, https://doi.org/10.1139/cjfas-2015-0237.","productDescription":"5 p.","startPage":"860","endPage":"864","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065429","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":488468,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1139/cjfas-2015-0237","text":"Publisher Index Page"},{"id":324654,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"73","issue":"5","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5774e346e4b07dd077c5fcb3","contributors":{"authors":[{"text":"Riley, Stephen C. 0000-0002-8968-8416 sriley@usgs.gov","orcid":"https://orcid.org/0000-0002-8968-8416","contributorId":2661,"corporation":false,"usgs":true,"family":"Riley","given":"Stephen","email":"sriley@usgs.gov","middleInitial":"C.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":569644,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dunlop, Erin S.","contributorId":146961,"corporation":false,"usgs":false,"family":"Dunlop","given":"Erin","email":"","middleInitial":"S.","affiliations":[{"id":16762,"text":"Ontario Ministry of Natural Resources and Forestry","active":true,"usgs":false}],"preferred":false,"id":569645,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70169334,"text":"70169334 - 2016 - Modeled historical land use and land cover for the conterminous United States","interactions":[],"lastModifiedDate":"2018-03-08T12:52:07","indexId":"70169334","displayToPublicDate":"2016-06-29T16:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2367,"text":"Journal of Land Use Science","active":true,"publicationSubtype":{"id":10}},"title":"Modeled historical land use and land cover for the conterminous United States","docAbstract":"Vibrio is a ubiquitous genus of marine bacteria, typically comprising a small fraction of the total microbial community in surface waters, but capable of becoming a dominant taxon in response to poorly characterized factors. Iron (Fe), often restricted by limited bioavailability and low external supply, is an essential micronutrient that can limit Vibrio growth. Vibrio species have robust metabolic capabilities and an array of Fe-acquisition mechanisms, and are able to respond rapidly to nutrient influx, yet Vibrio response to environmental pulses of Fe remains uncharacterized. Here we examined the population growth of Vibrioafter natural and simulated pulses of atmospherically transported Saharan dust, an important and episodic source of Fe to tropical marine waters. As a model for opportunistic bacterial heterotrophs, we demonstrated that Vibrio proliferate in response to a broad range of dust-Fe additions at rapid timescales. Within 24 h of exposure, strains of Vibrio cholerae and Vibrio alginolyticus were able to directly use Saharan dust–Fe to support rapid growth. These findings were also confirmed with in situ field studies; arrival of Saharan dust in the Caribbean and subtropical Atlantic coincided with high levels of dissolved Fe, followed by up to a 30-fold increase of culturable Vibrio over background levels within 24 h. The relative abundance of Vibrio increased from ∼1 to ∼20% of the total microbial community. This study, to our knowledge, is the first to describe Vibrio response to Saharan dust nutrients, having implications at the intersection of marine ecology, Fe biogeochemistry, and both human and environmental health.
","language":"English","publisher":"PNAS","doi":"10.1073/pnas.1518080113","usgsCitation":"Westrich, J.R., Ebling, A.M., Landing, W.M., Joyner, J.L., Kemp, K.M., Griffin, D.W., and Lipp, E.K., 2016, Saharan dust nutrients promote Vibrio bloom formation in marine surface waters: Proceedings of the National Academy of Sciences of the United States of America, v. 113, no. 21, p. 5964-5969, https://doi.org/10.1073/pnas.1518080113.","productDescription":"6 p.","startPage":"5964","endPage":"5969","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-067140","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":470806,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1073/pnas.1518080113","text":"External Repository"},{"id":324647,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"113","issue":"21","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-09","publicationStatus":"PW","scienceBaseUri":"5774e34ee4b07dd077c5fcef","contributors":{"authors":[{"text":"Westrich, Jason R.","contributorId":168327,"corporation":false,"usgs":false,"family":"Westrich","given":"Jason","email":"","middleInitial":"R.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":625484,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ebling, Alina M.","contributorId":168328,"corporation":false,"usgs":false,"family":"Ebling","given":"Alina","email":"","middleInitial":"M.","affiliations":[{"id":7092,"text":"Florida State University","active":true,"usgs":false}],"preferred":false,"id":625485,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Landing, William M.","contributorId":151019,"corporation":false,"usgs":false,"family":"Landing","given":"William","email":"","middleInitial":"M.","affiliations":[{"id":18104,"text":"Florida State University, Tallahassee","active":true,"usgs":false}],"preferred":false,"id":625488,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Joyner, Jessica L.","contributorId":168329,"corporation":false,"usgs":false,"family":"Joyner","given":"Jessica","email":"","middleInitial":"L.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":625486,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kemp, Keri M.","contributorId":168330,"corporation":false,"usgs":false,"family":"Kemp","given":"Keri","email":"","middleInitial":"M.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":625487,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Griffin, Dale W. 0000-0003-1719-5812 dgriffin@usgs.gov","orcid":"https://orcid.org/0000-0003-1719-5812","contributorId":2178,"corporation":false,"usgs":true,"family":"Griffin","given":"Dale","email":"dgriffin@usgs.gov","middleInitial":"W.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":625483,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lipp, Erin K.","contributorId":73823,"corporation":false,"usgs":true,"family":"Lipp","given":"Erin","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":625489,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70171123,"text":"70171123 - 2016 - Assessing the relationship between groundwater nitrate and animal feeding operations in Iowa (USA)","interactions":[],"lastModifiedDate":"2016-08-12T09:55:23","indexId":"70171123","displayToPublicDate":"2016-06-29T15:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Assessing the relationship between groundwater nitrate and animal feeding operations in Iowa (USA)","docAbstract":"Nitrate-nitrogen is a common contaminant of drinking water in many agricultural areas of the United States of America (USA). Ingested nitrate from contaminated drinking water has been linked to an increased risk of several cancers, specific birth defects, and other diseases. In this research, we assessed the relationship between animal feeding operations (AFOs) and groundwater nitrate in private wells in Iowa. We characterized AFOs by swine and total animal units and type (open, confined, or mixed), and we evaluated the number and spatial intensities of AFOs in proximity to private wells. The types of AFO indicate the extent to which a facility is enclosed by a roof. Using linear regression models, we found significant positive associations between the total number of AFOs within 2 km of a well (p trend < 0.001), number of open AFOs within 5 km of a well (p trend < 0.001), and number of mixed AFOs within 30 km of a well (p trend < 0.001) and the log nitrate concentration. Additionally, we found significant increases in log nitrate in the top quartiles for AFO spatial intensity, open AFO spatial intensity, and mixed AFO spatial intensity compared to the bottom quartile (0.171 log(mg/L), 0.319 log(mg/L), and 0.541 log(mg/L), respectively; all p < 0.001). We also explored the spatial distribution of nitrate-nitrogen in drinking wells and found significant spatial clustering of high-nitrate wells (> 5 mg/L) compared with low-nitrate (≤ 5 mg/L) wells (p = 0.001). A generalized additive model for high-nitrate status identified statistically significant areas of risk for high levels of nitrate. Adjustment for some AFO predictor variables explained a portion of the elevated nitrate risk. These results support a relationship between animal feeding operations and groundwater nitrate concentrations and differences in nitrate loss from confined AFOs vs. open or mixed types.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2016.05.130","usgsCitation":"Zirkle, K.W., Nolan, B.T., Jones, R.R., Weyer, P.J., Ward, M.H., and Wheeler, D.C., 2016, Assessing the relationship between groundwater nitrate and animal feeding operations in Iowa (USA): Science of the Total Environment, v. 566-567, p. 1062-1068, https://doi.org/10.1016/j.scitotenv.2016.05.130.","productDescription":"7 p.","startPage":"1062","endPage":"1068","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-073078","costCenters":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"links":[{"id":470809,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/4980257","text":"External Repository"},{"id":324635,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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,{"id":70173958,"text":"70173958 - 2016 - Isotopically constrained lead sources in fugitive dust from unsurfaced roads in the southeast Missouri mining district","interactions":[],"lastModifiedDate":"2016-10-07T12:56:14","indexId":"70173958","displayToPublicDate":"2016-06-29T15:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1555,"text":"Environmental Pollution","active":true,"publicationSubtype":{"id":10}},"title":"Isotopically constrained lead sources in fugitive dust from unsurfaced roads in the southeast Missouri mining district","docAbstract":"The isotopic composition of lead (Pb) in fugitive dust suspended by a vehicle from 13 unsurfaced roads in Missouri was measured to identify the source of Pb within an established long-term mining area. A three end-member model using 207Pb/206Pb and concentration as tracers resulted in fugitive dust samples plotting in the mixing field of well characterized heterogeneous end members. End members selected for this investigation include the 207Pb/206Pb for 1) a Pb-mixture representing mine tailings, 2) aerosol Pb-impacted soils within close proximity to the Buick secondary recycling smelter, and 3) an average of soils, rock cores and drill cuttings representing the background conditions. Aqua regia total concentrations and 207Pb/206Pb of mining area dust suggest that 35.4–84.3% of the source Pb in dust is associated with the mine tailings mixture, 9.1–52.7% is associated with the smelter mixture, and 0–21.6% is associated with background materials. Isotope ratios varied minimally within the operational phases of sequential extraction suggesting that mixing of all three Pb mixtures occurs throughout. Labile forms of Pb were attributed to all three end members. The extractable carbonate phase had as much as 96.6% of the total concentration associated with mine tailings, 51.8% associated with smelter deposition, and 34.2% with background. The next most labile geochemical phase (Fe + Mn Oxides) showed similar results with as much as 85.3% associated with mine tailings, 56.8% associated with smelter deposition, and 4.2% associated with the background soil.
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