Since the mid-1980s, fish-killing blooms of Prymnesium parvum spread throughout the USA. In the south central USA, P. parvum blooms have commonly spanned hundreds of kilometers. There is much evidence that physiological stress brought on by inorganic nutrient limitation enhances toxicity. Other factors influence toxin production as well, such as stress experienced at low salinity and temperature. A better understanding of toxin production by P. parvum remains elusive and the identities and functions of chemicals produced are unclear. This limits our understanding of factors that facilitated the spread of P. parvum blooms. In the south central USA, not only is there evidence that the spread of blooms was controlled, in part, by migration limitation. But there are also observations that suggest changed environmental conditions, primarily salinity, facilitated the spread of blooms. Other factors that might have played a role include altered hydrology and nutrient loading. Changes in water hardness, herbicide use, system pH, and the presence of toxin-resistant and/or P. parvum-inhibiting plankton may also have played a role. Management of P. parvum in natural systems has yet to be attempted, but may be guided by successes achieved in small impoundments and mesocosm experiments that employed various chemical and hydraulic control approaches.
","language":"English","publisher":"Springer","doi":"10.1007/s10750-015-2273-6","usgsCitation":"Roelke, D.L., Barkoh, A., Brooks, B.W., Grover, J.P., Hambright, K.D., LaClaire, J.W., Moeller, P.D., and Patino, R., 2015, A chronicle of a killer alga in the west: Ecology, assessment, and management of Prymnesium parvum blooms: Hydrobiologia, v. 764, p. 29-50, https://doi.org/10.1007/s10750-015-2273-6.","productDescription":"22 p.","startPage":"29","endPage":"50","numberOfPages":"22","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061394","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":305644,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"764","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2015-04-08","publicationStatus":"PW","scienceBaseUri":"57f7ef48e4b0bc0bec09f00f","contributors":{"authors":[{"text":"Roelke, D. L.","contributorId":28342,"corporation":false,"usgs":true,"family":"Roelke","given":"D.","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":564562,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barkoh, Aaron","contributorId":145542,"corporation":false,"usgs":false,"family":"Barkoh","given":"Aaron","email":"","affiliations":[],"preferred":false,"id":564563,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brooks, Bryan W. 0000-0002-6277-9852","orcid":"https://orcid.org/0000-0002-6277-9852","contributorId":198868,"corporation":false,"usgs":false,"family":"Brooks","given":"Bryan","email":"","middleInitial":"W.","affiliations":[{"id":35352,"text":"Department of Environmental Science, Baylor University, Waco, TX, USA","active":true,"usgs":false}],"preferred":false,"id":564564,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Grover, J. P.","contributorId":20453,"corporation":false,"usgs":true,"family":"Grover","given":"J.","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":564565,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hambright, K. D.","contributorId":25793,"corporation":false,"usgs":true,"family":"Hambright","given":"K.","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":564566,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"LaClaire, John W. II","contributorId":145543,"corporation":false,"usgs":false,"family":"LaClaire","given":"John","suffix":"II","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":564567,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Moeller, Peter D. R.","contributorId":145544,"corporation":false,"usgs":false,"family":"Moeller","given":"Peter","email":"","middleInitial":"D. R.","affiliations":[],"preferred":false,"id":564568,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Patino, Reynaldo 0000-0002-4831-8400 r.patino@usgs.gov","orcid":"https://orcid.org/0000-0002-4831-8400","contributorId":2311,"corporation":false,"usgs":true,"family":"Patino","given":"Reynaldo","email":"r.patino@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":564276,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70146557,"text":"70146557 - 2015 - USGS National Wildlife Health Center quarterly mortality report","interactions":[],"lastModifiedDate":"2023-10-13T14:18:39.520524","indexId":"70146557","displayToPublicDate":"2015-04-08T10:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3769,"text":"Wildlife Disease Association Newsletter","active":true,"publicationSubtype":{"id":10}},"title":"USGS National Wildlife Health Center quarterly mortality report","docAbstract":"No abstract available.
","language":"English","publisher":"Wildlife Disease Association","usgsCitation":"Chipault, J.G., Ballmann, A., Bodenstein, B., and Dusek, R., 2015, USGS National Wildlife Health Center quarterly mortality report: Wildlife Disease Association Newsletter, no. April 2015, p. 4-5.","productDescription":"2 p.","startPage":"4","endPage":"5","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064251","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":299772,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://www.wildlifedisease.org/PersonifyEbusiness/Resources/Publications/Newsletter/Archive"},{"id":299773,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"issue":"April 2015","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5536234be4b0b22a15807ac4","contributors":{"authors":[{"text":"Chipault, Jennifer G. 0000-0002-1368-622X jchipault@usgs.gov","orcid":"https://orcid.org/0000-0002-1368-622X","contributorId":4765,"corporation":false,"usgs":true,"family":"Chipault","given":"Jennifer","email":"jchipault@usgs.gov","middleInitial":"G.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":false,"id":545142,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ballmann, Anne 0000-0002-0380-056X aballmann@usgs.gov","orcid":"https://orcid.org/0000-0002-0380-056X","contributorId":140319,"corporation":false,"usgs":true,"family":"Ballmann","given":"Anne","email":"aballmann@usgs.gov","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":545143,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bodenstein, Barbara L. 0000-0001-7946-0103 bbodenstein@usgs.gov","orcid":"https://orcid.org/0000-0001-7946-0103","contributorId":139354,"corporation":false,"usgs":true,"family":"Bodenstein","given":"Barbara L.","email":"bbodenstein@usgs.gov","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":false,"id":545144,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dusek, Robert J. 0000-0001-6177-7479 rdusek@usgs.gov","orcid":"https://orcid.org/0000-0001-6177-7479","contributorId":140066,"corporation":false,"usgs":true,"family":"Dusek","given":"Robert J.","email":"rdusek@usgs.gov","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":false,"id":545145,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70139404,"text":"sir20145224 - 2015 - Hydrogeologic framework, hydrology, and refined conceptual model of groundwater flow for Coastal Plain aquifers at the Standard Chlorine of Delaware, Inc. Superfund Site, New Castle County, Delaware, 2005-12","interactions":[],"lastModifiedDate":"2018-03-21T15:43:13","indexId":"sir20145224","displayToPublicDate":"2015-04-08T10:30:00","publicationYear":"2015","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":"2014-5224","title":"Hydrogeologic framework, hydrology, and refined conceptual model of groundwater flow for Coastal Plain aquifers at the Standard Chlorine of Delaware, Inc. Superfund Site, New Castle County, Delaware, 2005-12","docAbstract":"From 1966 to 2002, activities at the Standard Chlorine of Delaware chemical facility in New Castle County, Delaware resulted in the contamination of groundwater, soils, and wetland sediment. In 2005, the U.S. Geological Survey (USGS), in partnership with the U.S. Environmental Protection Agency, Region 3, and the Delaware Department of Natural Resources and Environmental Control began a multi-year investigation of the hydrogeologic framework and hydrology of the confined aquifer system. The goals of the ongoing study at the site (the Potomac Aquifer Study) are to determine the hydraulic connection between the Columbia and Potomac aquifers, determine the direction of groundwater flow in the Potomac aquifer, and identify factors affecting the fate of contaminated groundwater. This report describes progress made towards these goals based on available data collected through September 2012.
\nThe regional hydrogeologic framework indicates that the site is underlain by Coastal Plain sediments of the Columbia, Merchantville, and Potomac Formations. Two primary aquifers underlying the site, the Columbia and the upper Potomac, are separated by the Merchantville Formation confining unit. Local groundwater flow in the surficial (Columbia) aquifer is controlled by topography and generally flows northward and discharges to nearby surface water. Regional flow within the Potomac aquifer is towards the southeast, and is strongly influenced by major water withdrawals locally. Previous investigations at the site indicated that contaminants, primarily benzene and chlorinated benzene compounds, were present in the Columbia aquifer in most locations; however, there were only limited detections in the upper Potomac aquifer as of 2004. From 2005 through 2012, the USGS designed a monitoring network, assisted with exploratory drilling, collected data at monitoring wells, conducted geophysical surveys, evaluated water-level responses in wells during pumping of a production well, and evaluated major aquifer withdrawals. Data collected through these efforts were used to refine the local conceptual flow system. The refined conceptual flow system for the site includes: (a) identification of gaps in confining units in the study area, (b) identification and correlation of multiple water-bearing sand intervals within the upper Potomac Formation, (c) connections between groundwater and surface water, (d) connections between shallow and deeper groundwater, (e) new water-level (or potentiometric surface) maps and inferred flow directions, and (f) identification of major local pumping well influences. The implications of the revised conceptual flow system on the occurrence and movement of site contaminants are that the resulting detection of contaminants in the upper Potomac aquifer at specific well locations can be attributed primarily to either advective lateral transport, direct vertical contaminant transport, or a combination of vertical and lateral movement resulting from changes in water withdrawal rates over time.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145224","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency","usgsCitation":"Brayton, M.J., Cruz, R.M., Myers, L., Degnan, J.R., and Raffensperger, J.P., 2015, Hydrogeologic framework, hydrology, and refined conceptual model of groundwater flow for Coastal Plain aquifers at the Standard Chlorine of Delaware, Inc. Superfund Site, New Castle County, Delaware, 2005-12: U.S. Geological Survey Scientific Investigations Report 2014-5224, vii, 61 p., https://doi.org/10.3133/sir20145224.","productDescription":"vii, 61 p.","numberOfPages":"74","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"2005-01-01","temporalEnd":"2012-09-30","ipdsId":"IP-059549","costCenters":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"links":[{"id":299486,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145224.jpg"},{"id":299484,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5224/"},{"id":299485,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5224/pdf/sir2014-5224.pdf","text":"Report","size":"3.94 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"projection":"State Plane Delaware Projection","datum":"North American Datum of 1983","country":"United States","state":"Delaware","county":"New Castle County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.60430526733398,\n 39.63187001350982\n ],\n [\n -75.65872192382812,\n 39.637422462817\n ],\n [\n -75.70489883422852,\n 39.60886226158157\n ],\n [\n -75.71365356445311,\n 39.59464387992515\n ],\n [\n -75.65108299255371,\n 39.55554482419571\n ],\n [\n -75.59306144714355,\n 39.571623755318214\n ],\n [\n -75.58670997619629,\n 39.579231826349016\n ],\n [\n -75.58653831481934,\n 39.5808856443388\n ],\n [\n -75.59864044189453,\n 39.58935257415456\n ],\n [\n -75.60842514038085,\n 39.59484229602979\n ],\n [\n -75.61426162719727,\n 39.60463011823322\n ],\n [\n -75.61134338378906,\n 39.6109782362526\n ],\n [\n -75.61408996582031,\n 39.617325772242175\n ],\n [\n -75.61031341552734,\n 39.625788248139436\n ],\n [\n -75.60636520385742,\n 39.6265815522009\n ],\n [\n -75.60430526733398,\n 39.63187001350982\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5526431de4b026915857c634","contributors":{"authors":[{"text":"Brayton, Michael J. mbrayton@usgs.gov","contributorId":2993,"corporation":false,"usgs":true,"family":"Brayton","given":"Michael","email":"mbrayton@usgs.gov","middleInitial":"J.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":539388,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cruz, Roberto M. 0000-0003-1235-3295 rmcruz@usgs.gov","orcid":"https://orcid.org/0000-0003-1235-3295","contributorId":5757,"corporation":false,"usgs":true,"family":"Cruz","given":"Roberto","email":"rmcruz@usgs.gov","middleInitial":"M.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":539389,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Myers, Luke lmyers@usgs.gov","contributorId":5758,"corporation":false,"usgs":true,"family":"Myers","given":"Luke","email":"lmyers@usgs.gov","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":539390,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Degnan, James R. 0000-0002-5665-9010 jrdegnan@usgs.gov","orcid":"https://orcid.org/0000-0002-5665-9010","contributorId":498,"corporation":false,"usgs":true,"family":"Degnan","given":"James","email":"jrdegnan@usgs.gov","middleInitial":"R.","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":539391,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Raffensperger, Jeff P. 0000-0001-9275-6646 jpraffen@usgs.gov","orcid":"https://orcid.org/0000-0001-9275-6646","contributorId":199119,"corporation":false,"usgs":true,"family":"Raffensperger","given":"Jeff","email":"jpraffen@usgs.gov","middleInitial":"P.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":539392,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70141848,"text":"sir20155024 - 2015 - Hydrologic effects of potential changes in climate, water use, and land cover in the Upper Scioto River Basin, Ohio","interactions":[],"lastModifiedDate":"2015-04-15T08:44:40","indexId":"sir20155024","displayToPublicDate":"2015-04-08T10:00:00","publicationYear":"2015","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":"2015-5024","title":"Hydrologic effects of potential changes in climate, water use, and land cover in the Upper Scioto River Basin, Ohio","docAbstract":"This report presents the results of a study to provide information on the hydrologic effects of potential 21st-century changes in climate, water use, and land cover in the Upper Scioto River Basin, Ohio (from Circleville, Ohio, to the headwaters). A precipitation-runoff model, calibrated on the basis of historical climate and streamflow data, was used to simulate the effects of climate change on streamflows and reservoir water levels at several locations in the basin. Two levels of simulations were done. The first level of simulation (level 1) accounted only for anticipated 21st-century changes in climate and operations of three City of Columbus upground reservoirs located in northwest Delaware County, Ohio. The second level of simulation (level 2) accounted for development-driven changes in land cover and water use in addition to changes in climate and reservoir operations.
\nA statistical change-factor approach was used to construct future climate time series that were used in the precipitation-runoff model to compute time series of future streamflows and reservoir water levels. Monthly change factors were computed by determining differences or fractional changes between baseline historical climate time series and future climate time series consisting of outputs from selected global climate models that were included in the World Climate Research Programme’s Coupled Model Intercomparison Project phase 3 (CMIP3). Eight sets of change factors were determined on the basis of outputs from four global climate models, each of which was run under two greenhouse-gas scenarios (the “A1b” and “A2” scenarios from the Intergovernmental Panel on Climate Change’s 4th assessment). The 4 global climate models whose data were used in this study were selected to represent a wide range of potential climate outcomes as compared to the entire range of potential climate outcomes associated with the 16 global climate models represented in the CMIP3 multimodel dataset.
\nFuture land-cover and water-use data were estimated for use in the level-2 precipitation-runoff simulations to account for development-driven changes in land cover and water use. Future land-cover characteristics were estimated for selected future years based on population projections and zoning plans for communities in the basin. Future water-use data for major water suppliers and wastewater-treatment facilities were estimated from current per capita water use, population projections for 2035, and population projections for 2090 assuming full build-out. A statistical change-factor-based approach was used to estimate future water-use characteristics by major water suppliers and wastewater-treatment facilities on the basis of reference-period historical water uses. Annual change factors that were determined for future years other than 2035 and 2090 (when the change factors could be explicitly computed) were estimated by interpolating or extrapolating linearly in time. Water uses by entities other than major water suppliers and wastewater-treatment facilities were assumed to remain unchanged because of uncertainty about if and (or) how they might change.
\nResults from the level-1 simulations were analyzed primarily to facilitate evaluation of climate-driven temporal changes in annual, seasonal, and monthly streamflow and water-level characteristics, as well as in maximum and minimum 7-, 30-, and 180-day average streamflow and reservoir water levels. Results from the level-2 simulations were analyzed to help evaluate and contrast (relative to level-1 results) the effects of the added development-related factors on maximums and minimum 7-, 30-, and 180-day average streamflows and reservoir water levels and duration characteristics of 7- and 30-day average streamflows and reservoir water levels. Results for 12 stream locations and 5 reservoirs in the Upper Scioto River Basin are presented primarily as a series of plots.
\nAlthough it is beyond the scope of this study to address results in detail for each model-output location, selected results are discussed to illustrate potential uses and interpretations of the graph products provided in this report. In addition, general trends and patterns in streamflow and water-level characteristics are identified where possible.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155024","collaboration":"Prepared in cooperation with the Mid-Ohio Regional Planning Commission; the Ohio Water Development Authority; the City of Columbus, Ohio; and Del-Co Water Company","usgsCitation":"Ebner, A.D., Koltun, G., and Ostheimer, C., 2015, Hydrologic effects of potential changes in climate, water use, and land cover in the Upper Scioto River Basin, Ohio: U.S. Geological Survey Scientific Investigations Report 2015-5024, Report: vii, 34 p.; Appendixes A-G; Downloads Directory, https://doi.org/10.3133/sir20155024.","productDescription":"Report: vii, 34 p.; Appendixes A-G; Downloads Directory","numberOfPages":"46","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-060946","costCenters":[{"id":513,"text":"Ohio Water Science 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quantile."},{"id":299478,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5024/appendix/sir2015-5024_appendixd.pdf","text":"Appendix D","size":"905 KB","linkFileType":{"id":1,"text":"pdf"},"description":"Appendix D","linkHelpText":"Plots of maximum and minimum 7-, 30-, and 180-day average streamflows and water levels as a function of plotting year."},{"id":299481,"rank":9,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5024/appendix/sir2015-5024_appendixg.pdf","text":"Appendix G","size":"226 KB","linkFileType":{"id":1,"text":"pdf"},"description":"Appendix G","linkHelpText":"Plots of simulated level-2 30-day running average streamflows and water levels as a function of exceedance quantile."},{"id":299482,"rank":10,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5024/downloads","text":"Downloads Directory","size":"5.44 MB","description":"Downloads Directory","linkHelpText":"Contains Appendixes A-G ZIP 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Bisphenol A (BPA) is an estrogenic chemical commonly found in a variety of habitats. In this study, we used painted turtles (Chrysemys picta), which have temperature-dependent sex determination (TSD), as an animal model for ontogenetic endocrine disruption by BPA. We hypothesized that BPA would override TSD and disrupt sexual development. We incubated farm-raised turtle eggs at the male-producing temperature (26 °C), randomly assigned individuals to treatment groups: control, vehicle control, 17β-estradiol (E2, 20 ng/g-egg) or 0.01, 1.0, 100 μg BPA/g-egg and harvested tissues at hatch. Typical female gonads were present in 89% of the E2-treated “males”, but in none of the control males (n = 35). Gonads of BPA-exposed turtles had varying amounts of ovarian-like cortical (OLC) tissue and disorganized testicular tubules in the medulla. Although the percentage of males with OLCs increased with BPA dose (BPA-low = 30%, BPA-medium = 33%, BPA-high = 39%), this difference was not significant (p = 0.85). In all three BPA treatments, SOX9 patterns revealed disorganized medullary testicular tubules and β-catenin expression in a thickened cortex. Liver vitellogenin, a female-specific liver protein commonly used as an exposure biomarker, was not induced by any of the treatments. Notably, these results suggest that developmental exposure to BPA disrupts sexual differentiation in painted turtles. Further examination is necessary to determine the underlying mechanisms of sex reversal in reptiles and how these translate to EDC exposure in wild populations.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ygcen.2015.04.003","usgsCitation":"Jandegian, C.M., Deem, S.L., Bhandari, R.K., Holliday, C.M., Nicks, D., Rosenfeld, C.S., Selcer, K., Tillitt, D.E., vom Saal, F.S., Velez, V., Yang, Y., and Holliday, D.K., 2015, Developmental exposure to bisphenol A (BPA) alters sexual differentiation in painted turtles (Chrysemys picta): General and Comparative Endocrinology, v. 216, p. 77-85, https://doi.org/10.1016/j.ygcen.2015.04.003.","productDescription":"9 p.","startPage":"77","endPage":"85","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061239","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":306671,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"216","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55cdbfafe4b08400b1fe13e4","contributors":{"authors":[{"text":"Jandegian, Caitlin M. cjandegian@usgs.gov","contributorId":5941,"corporation":false,"usgs":true,"family":"Jandegian","given":"Caitlin","email":"cjandegian@usgs.gov","middleInitial":"M.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":567436,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Deem, Sharon L.","contributorId":139277,"corporation":false,"usgs":false,"family":"Deem","given":"Sharon","email":"","middleInitial":"L.","affiliations":[{"id":12719,"text":"Whitney R. 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The goals of this study were to predict and map patterns of fish biomass as a proxy for the availability of catchable fish for anglers in rivers and to identify the strongest landscape constraints on fish productivity. We examined hypotheses about fish responses to total phosphorus (TP), as TP is a growth-limiting nutrient known to cause increases (subsidy response) and/or decreases (stress response) in fish biomass depending on its concentration and the species being considered. Boosted regression trees were used to define nonlinear functions that predicted the standing crops of Brook Trout Salvelinus fontinalis, Brown Trout Salmo trutta, Smallmouth Bass Micropterus dolomieu, panfishes (seven centrarchid species), and Walleye Sander vitreus by using landscape and modeled local-scale predictors. Fitted models were highly significant and explained 22–56% of the variation in validation data sets. Nonlinear and threshold responses were apparent for numerous predictors, including TP concentration, which had significant effects on all except the Walleye fishery. Brook Trout and Smallmouth Bass exhibited both subsidy and stress responses, panfish biomass exhibited a subsidy response only, and Brown Trout exhibited a stress response. Maps of reach-specific standing crop predictions showed patterns of predicted fish biomass that corresponded to spatial patterns in catchment area, water temperature, land cover, and nutrient availability. Maps illustrated predictions of higher trout biomass in coldwater streams draining glacial till in northern Michigan, higher Smallmouth Bass and panfish biomasses in warmwater systems of southern Michigan, and high Walleye biomass in large main-stem rivers throughout the state. Our results allow fisheries managers to examine the biomass potential of streams, describe geographic patterns of fisheries, explore possible nutrient management targets, and identify habitats that are candidates for species management.
","language":"English","publisher":"American Fisheries Society","publisherLocation":"Lawrence, KS","doi":"10.1080/02755947.2014.987887","usgsCitation":"Esselman, P.C., Stevenson, R.J., Lupi, F., Riseng, C.M., and Wiley, M., 2015, Landscape prediction and mapping of game fish biomass, an ecosystem service of Michigan rivers: North American Journal of Fisheries Management, v. 35, no. 2, p. 302-320, https://doi.org/10.1080/02755947.2014.987887.","productDescription":"19 p.","startPage":"302","endPage":"320","numberOfPages":"19","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057022","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":472157,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://figshare.com/articles/journal_contribution/Landscape_Prediction_and_Mapping_of_Game_Fish_Biomass_an_Ecosystem_Service_of_Michigan_Rivers/1378927","text":"External Repository"},{"id":306583,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Michigan","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.3515625,\n 46.604167162931844\n ],\n [\n -90.087890625,\n 46.45299704748289\n ],\n [\n -89.9560546875,\n 46.30140615437332\n ],\n [\n -88.79150390625,\n 46.042735653846506\n ],\n [\n -88.30810546875,\n 45.98169518512228\n ],\n [\n -88.00048828124999,\n 45.73685954736049\n ],\n [\n -87.64892578125,\n 45.166547157856016\n ],\n [\n -87.099609375,\n 45.67548217560647\n ],\n [\n -86.68212890625,\n 45.62940492064501\n ],\n [\n -85.7373046875,\n 45.935870621190546\n ],\n [\n -85.14404296875,\n 45.98169518512228\n ],\n [\n -84.9462890625,\n 45.84410779560204\n ],\n [\n -85.1220703125,\n 45.61403741135093\n ],\n [\n -85.517578125,\n 45.22848059584359\n ],\n [\n -86.28662109375,\n 44.68427737181225\n ],\n [\n -86.572265625,\n 43.77109381775651\n ],\n [\n -86.24267578125,\n 42.924251753870685\n ],\n [\n -86.37451171875,\n 42.342305278572816\n ],\n [\n -86.77001953125,\n 41.934976500546604\n ],\n [\n -86.7919921875,\n 41.80407814427237\n ],\n [\n -83.34228515625,\n 41.705728515237524\n ],\n [\n -83.056640625,\n 42.147114459220994\n ],\n [\n -82.81494140625,\n 42.48830197960227\n ],\n [\n -82.4853515625,\n 42.827638636242284\n ],\n [\n -82.44140625,\n 43.11702412135048\n ],\n [\n -82.59521484375,\n 43.78695837311561\n ],\n [\n -82.79296874999999,\n 44.05601169578525\n ],\n [\n -83.25439453125,\n 44.43377984606825\n ],\n [\n -83.27636718749999,\n 44.85586880735725\n ],\n [\n -83.38623046875,\n 45.321254361171476\n ],\n [\n -84.26513671875,\n 45.73685954736049\n ],\n [\n -84.0234375,\n 45.90529985724796\n ],\n [\n -83.6279296875,\n 46.08847179577592\n ],\n [\n -84.13330078125,\n 46.46813299215554\n ],\n [\n -84.79248046875,\n 46.81509864599243\n ],\n [\n -86.1328125,\n 46.73986059969267\n ],\n [\n -87.12158203125,\n 46.619261036171515\n ],\n [\n -87.6708984375,\n 46.90524554642923\n ],\n [\n -88.0224609375,\n 47.11499982620772\n ],\n [\n -87.5390625,\n 47.428087261714275\n ],\n [\n -88.2861328125,\n 47.56170075451973\n ],\n [\n -89.18701171875,\n 47.15984001304432\n ],\n [\n -90.3515625,\n 46.604167162931844\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"35","issue":"2","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2015-04-07","publicationStatus":"PW","scienceBaseUri":"55cb1caee4b08400b1fdd477","contributors":{"authors":[{"text":"Esselman, Peter C. 0000-0002-0085-903X pesselman@usgs.gov","orcid":"https://orcid.org/0000-0002-0085-903X","contributorId":5965,"corporation":false,"usgs":true,"family":"Esselman","given":"Peter","email":"pesselman@usgs.gov","middleInitial":"C.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":540045,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stevenson, R. 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These data were used to characterize current water-quality conditions, to establish a baseline for future comparisons, and to describe trends in surface-water quality. The data also were used to assess the effects of watershed characteristics on surface-water quality and to inform future watershed management.
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\nIn response to the uncertainty surrounding the status of mineral projects in Guinea, Liberia, and Sierra Leone, the National Minerals Information Center compiled information on the distribution of mines, mineral facilities, and mineral projects under development in the three countries. This fact sheet provides information on the role that the mineral sector plays in their respective economies, on the operating status of mining projects through yearend 2014, and on the coordinated actions by mining companies to support governments and international relief organizations in their efforts to contain the EVD outbreak.
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(v1.15)","interactions":[],"lastModifiedDate":"2017-10-12T20:04:28","indexId":"70145259","displayToPublicDate":"2015-04-07T11:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1818,"text":"Geoscientific Model Development","active":true,"publicationSubtype":{"id":10}},"title":"RRAWFLOW: Rainfall-Response Aquifer and Watershed Flow Model (v1.15)","docAbstract":"The Rainfall-Response Aquifer and Watershed Flow Model (RRAWFLOW) is a lumped-parameter model that simulates streamflow, spring flow, groundwater level, or solute transport for a measurement point in response to a system input of precipitation, recharge, or solute injection. I introduce the first version of RRAWFLOW available for download and public use and describe additional options. The open-source code is written in the R language and is available at http://sd.water.usgs.gov/projects/RRAWFLOW/RRAWFLOW.html along with an example model of streamflow. RRAWFLOW includes a time-series process to estimate recharge from precipitation and simulates the response to recharge by convolution, i.e., the unit-hydrograph approach. Gamma functions are used for estimation of parametric impulse-response functions (IRFs); a combination of two gamma functions results in a double-peaked IRF. A spline fit to a set of control points is introduced as a new method for estimation of nonparametric IRFs. Several options are included to simulate time-variant systems. For many applications, lumped models simulate the system response with equal accuracy to that of distributed models, but moreover, the ease of model construction and calibration of lumped models makes them a good choice for many applications (e.g., estimating missing periods in a hydrologic record). RRAWFLOW provides professional hydrologists and students with an accessible and versatile tool for lumped-parameter modeling.
","language":"English","publisher":"European Geosciences Union","publisherLocation":"Katlenburg-Lindau, Germany","doi":"10.5194/gmd-8-865-2015","usgsCitation":"Long, A.J., 2015, RRAWFLOW: Rainfall-Response Aquifer and Watershed Flow Model (v1.15): Geoscientific Model Development, v. 8, p. 865-880, https://doi.org/10.5194/gmd-8-865-2015.","productDescription":"16 p.","startPage":"865","endPage":"880","numberOfPages":"16","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056483","costCenters":[{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":472158,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/gmd-8-865-2015","text":"Publisher Index Page"},{"id":299446,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2015-03-30","publicationStatus":"PW","scienceBaseUri":"5524f19ce4b027f0aee3d45d","contributors":{"authors":[{"text":"Long, Andrew J. 0000-0001-7385-8081 ajlong@usgs.gov","orcid":"https://orcid.org/0000-0001-7385-8081","contributorId":989,"corporation":false,"usgs":true,"family":"Long","given":"Andrew","email":"ajlong@usgs.gov","middleInitial":"J.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true},{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":544130,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70140114,"text":"sir20155017 - 2015 - Physical subdivision and description of the water-bearing sediments of the Santa Clara Valley, California","interactions":[],"lastModifiedDate":"2015-04-07T08:39:02","indexId":"sir20155017","displayToPublicDate":"2015-04-07T09:30:00","publicationYear":"2015","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":"2015-5017","title":"Physical subdivision and description of the water-bearing sediments of the Santa Clara Valley, California","docAbstract":"A thick Quaternary alluvial section fills a sedimentary basin beneath the Santa Clara Valley, California, located within the San Andreas Fault system at the south end of San Francisco Bay. This section consists of an upper sequence about 1,000 feet thick containing eight sedimentary cycles and a lower fine-grained unit as thick as several hundred feet. Together these constitute the Quaternary Santa Clara Basin. The section overlies an irregular unconformity with more than 1,200 feet of relief cut into the underlying bedrock. This stratigraphy is determined through study of new wells and seismic reflection profiles, together with a sample of the many thousands of water wells in the valley. It represents a major change and improvement in understanding of the basin, particularly with regard to the upper cyclic sequence, which forms a large groundwater system that is an important resource in the San Francisco Bay region.
\nEach of the eight sedimentary cycles consists of a coarse-grained bottom interval overlain by a fine-grained top, with the coarse bottom forming a permeable sheet that is more or less continuous around the basin and the fine top forming a similarly extensive, relatively impermeable confining layer. This stratigraphic organization contrasts with most previous views, which have considered the coarse sediment in the basin to occur as scattered, discrete lenses and (or) sinuous channel sands, all embedded in a predominantly fine-grained section. Temperature logs in several wells demonstrate that the fine cycle tops do limit vertical movement of groundwater, although this may not be the case where those tops are thin to perhaps locally absent around parts of the basin margin.
\nAge control has been obtained from previous work, in which the sedimentary cycles were correlated with the marine oxygen isotope record and the ages of two deeper Quaternary unconformities were estimated, and from detailed paleomagnetic study of cores from the new wells by E.A. Mankinen. Despite careful search of the cores, very few fossils were found, and none that are helpful in subdividing the section. No tephra (volcanic ash) was recovered, and the few carbon samples found and dated radiometrically are limited to the upper 120 feet of the section. The upper cyclic section ranges in age from 0 to somewhat older than 718 thousand years (ka), and the lower fine-grained section lies between unconformities with estimated ages of 950 and 1500 ka.
\nReflections in the seismic profiles indicate that layering in the basin is subparallel to the ground surface, and this fact, together with the continuous stratigraphic detail provided by geophysical logs of the new wells, allows the confident interwell correlation required to delineate the sedimentary cycles. The sequence of layers within any one cycle tends to persist laterally between the wells in the dataset, which are spaced 1 to 3 km apart, with most changes occurring gradually. The eight cycles, in contrast, tend to differ from each other in the details of their internal organization.
\nMaps and cross sections show the elevations of cycle boundaries and the underlying bedrock surface, the varying thicknesses of the cycles and of their fine tops and coarse bottoms, and the aggregate thickness of coarse layers in those bottom intervals. Coarse sediment is more abundant toward some parts of the basin margin and in the southern part of the basin. Cycle boundary surfaces are relatively smooth, and their shapes are consistent with having been intercycle topographic surfaces. The underlying bedrock surface has a relief of more than 1,200 feet and deepens toward the center of the basin and the west edge of the fault-bounded Evergreen Basin, which is concealed beneath the east side of the Quaternary basin. The absence of consistent abrupt changes in thicknesses or boundary elevations across the basin or in cross section indicates that the interior of the basin is largely unfaulted, with the Silver Creek strand of the San Andreas system at the west edge of the Evergreen Basin being the sole exception. The east and west margins of the Santa Clara Basin, in contrast, are marked by reverse and thrust fault systems.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155017","usgsCitation":"Wentworth, C.M., Jachens, R.C., Williams, R., Tinsley, J., and Hanson, R.T., 2015, Physical subdivision and description of the water-bearing sediments of the Santa Clara Valley, California: U.S. Geological Survey Scientific Investigations Report 2015-5017, Report: x, 73 p.; 2 Plates: 43.43 x 31.60 inches and 19.76 x 19.60 inches; ReadMe; 10 ZIP files, https://doi.org/10.3133/sir20155017.","productDescription":"Report: x, 73 p.; 2 Plates: 43.43 x 31.60 inches and 19.76 x 19.60 inches; ReadMe; 10 ZIP files","numberOfPages":"84","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-049605","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science 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\nThis project provides datasets acquired on August 7 and 8, 2012, for a portion of the Chandeleur Islands, Louisiana. An innovative airborne lidar system, known as the second-generation Experimental Advanced Airborne Research Lidar (EAARL-B), was used during data acquisition. The EAARL-B system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometers) lidar designed to map nearshore bathymetry, topography, and vegetation structure simultaneously.
\nFor more information about similar projects, please visit the Lidar for Science and Resource Management Web site.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds913","usgsCitation":"Wright, C.W., Klipp, E.S., Kranenburg, C., Troche, R.J., Fredericks, X., Masessa, M.L., and Nagle, D.B., 2015, EAARL-B coastal topography: Chandeleur Islands, Louisiana, 2012: seamless (bare earth and submerged): U.S. Geological Survey Data Series 913, HTML Document, https://doi.org/10.3133/ds913.","productDescription":"HTML Document","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2012-01-01","temporalEnd":"2012-12-31","ipdsId":"IP-059846","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":299417,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds913.jpg"},{"id":299416,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0913/html/ds_home.html","linkFileType":{"id":5,"text":"html"}},{"id":299415,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0913/"}],"country":"United States","state":"Louisiana","otherGeospatial":"Chandeleur Islands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.88076782226562,\n 30.05720849081894\n ],\n [\n -88.86154174804688,\n 30.045915969180676\n ],\n [\n -88.84368896484375,\n 30.0286775329042\n ],\n [\n -88.82789611816405,\n 30.00073301042315\n ],\n [\n -88.8189697265625,\n 29.9793233715619\n ],\n [\n -88.81484985351562,\n 29.952554831950962\n ],\n [\n -88.81072998046875,\n 29.931134809868713\n ],\n [\n -88.81004333496094,\n 29.903758071027738\n ],\n [\n -88.81278991699219,\n 29.881136828132842\n ],\n [\n -88.81553649902344,\n 29.859701442126756\n ],\n [\n -88.82308959960938,\n 29.832900734318393\n ],\n [\n -88.83819580078125,\n 29.798346993042582\n ],\n [\n -88.84780883789062,\n 29.774509870772462\n ],\n [\n -88.8629150390625,\n 29.7470901645232\n ],\n [\n -88.88076782226562,\n 29.719066630304063\n ],\n [\n -88.9068603515625,\n 29.6880527498568\n ],\n [\n -88.92951965332031,\n 29.66180275761379\n ],\n [\n -88.95904541015625,\n 29.639723597620257\n ],\n [\n -88.98513793945312,\n 29.622414924968727\n ],\n [\n -89.00505065917969,\n 29.621221113784504\n ],\n [\n -89.00436401367188,\n 29.628980633662827\n ],\n [\n -88.98788452148438,\n 29.634949088440198\n ],\n [\n -88.9679718017578,\n 29.651658880141365\n ],\n [\n -88.95355224609375,\n 29.66597935109997\n ],\n [\n -88.93844604492188,\n 29.68328053373362\n ],\n [\n -88.92196655273438,\n 29.701771608904792\n ],\n [\n -88.90274047851562,\n 29.727414884638474\n ],\n [\n -88.890380859375,\n 29.75364773335698\n ],\n [\n -88.87664794921875,\n 29.78523727825047\n ],\n [\n -88.86909484863281,\n 29.806688644587354\n ],\n [\n -88.85398864746094,\n 29.827539729697882\n ],\n [\n -88.84506225585938,\n 29.858510452312036\n ],\n [\n -88.84162902832031,\n 29.886494954894626\n ],\n [\n -88.83750915527344,\n 29.920423069383865\n ],\n [\n -88.84300231933592,\n 29.95552947018257\n ],\n [\n -88.84506225585938,\n 29.97753902660092\n ],\n [\n -88.85467529296875,\n 30.00965233044293\n ],\n [\n -88.87390136718749,\n 30.035811042667792\n ],\n [\n -88.88282775878906,\n 30.050670872077248\n ],\n [\n -88.88076782226562,\n 30.05720849081894\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5524f198e4b027f0aee3d459","contributors":{"authors":[{"text":"Wright, C. Wayne wwright@usgs.gov","contributorId":2973,"corporation":false,"usgs":true,"family":"Wright","given":"C.","email":"wwright@usgs.gov","middleInitial":"Wayne","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":544167,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Klipp, Emily S. eklipp@usgs.gov","contributorId":2754,"corporation":false,"usgs":true,"family":"Klipp","given":"Emily","email":"eklipp@usgs.gov","middleInitial":"S.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":544168,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kranenburg, Christine J. ckranenburg@usgs.gov","contributorId":3924,"corporation":false,"usgs":true,"family":"Kranenburg","given":"Christine J.","email":"ckranenburg@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":544169,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Troche, Rodolfo J. rtroche@usgs.gov","contributorId":4304,"corporation":false,"usgs":true,"family":"Troche","given":"Rodolfo","email":"rtroche@usgs.gov","middleInitial":"J.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":544170,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fredericks, Xan 0000-0001-7186-6555 afredericks@usgs.gov","orcid":"https://orcid.org/0000-0001-7186-6555","contributorId":2972,"corporation":false,"usgs":true,"family":"Fredericks","given":"Xan","email":"afredericks@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":544171,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Masessa, Melanie L. mmasessa@usgs.gov","contributorId":5903,"corporation":false,"usgs":true,"family":"Masessa","given":"Melanie","email":"mmasessa@usgs.gov","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":544172,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Nagle, David B. 0000-0002-2306-6147 dnagle@usgs.gov","orcid":"https://orcid.org/0000-0002-2306-6147","contributorId":3380,"corporation":false,"usgs":true,"family":"Nagle","given":"David","email":"dnagle@usgs.gov","middleInitial":"B.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":544173,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70139629,"text":"sir20155014 - 2015 - Occurrence of pesticides in groundwater underlying areas of high-density row-crop production in Alabama, 2009-2013","interactions":[],"lastModifiedDate":"2015-04-20T15:09:00","indexId":"sir20155014","displayToPublicDate":"2015-04-06T15:00:00","publicationYear":"2015","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":"2015-5014","title":"Occurrence of pesticides in groundwater underlying areas of high-density row-crop production in Alabama, 2009-2013","docAbstract":"The U.S. Geological Survey, in cooperation with the Alabama Department of Agriculture and Industries, sampled a network of 15 wells for up to 167 pesticides and pesticide degradates from 2009 through 2013 in three areas of high-density row-crop agriculture in Alabama. Eighteen herbicides, 2 fungicides, and 9 degradates were detected in water from the sampled wells. The highest concentration of a detected pesticide was 4.49 micrograms per liter of bentazon in Baldwin County, Alabama, which was well below the lifetime health advisory level of 200 micrograms per liter. None of the measured pesticide concentrations exceeded a human-health benchmark. Insecticides were not detected.
\nRelatively flat land and permeable soils prevalent in each of the three areas facilitate the transport of pesticides through the unsaturated zone into the underlying aquifers. Pesticides and the degradate, deethylatrazine, were more frequently detected in groundwater from wells located in northern Alabama than in southeastern Alabama and Baldwin County, Alabama. Greater amounts of pesticide usage and shallow well depths in northern Alabama likely explain the detection of pesticides in that area. Pesticides were detected in two of the shallowest sampled wells in southeastern Alabama, and the detected pesticides have been extensively used on the crops grown in this area. Total pesticide use among the three areas was lowest in Baldwin County; however, fungicides were detected more often in Baldwin County, which is indicative of peanut crops planted in that area.
\nConcentrations of metolachlor and atrazine have substantially decreased in the northern Alabama wells since 2000. A decline in use of metolachlor and atrazine from a high in the late-1990s and a high in 2004, respectively, in northern Alabama could account for the lower concentrations. Fluometuron use has also declined since 1998, but the relation between time and concentrations differed in the five northern Alabama wells. Fluometuron concentrations in three of the five wells have been decreasing over time, while concentrations in the remaining two wells have been increasing.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155014","collaboration":"Prepared in cooperation with the Alabama Department of Agriculture and Industries","usgsCitation":"Welch, H.L., 2015, Occurrence of pesticides in groundwater underlying areas of high-density row-crop production in Alabama, 2009-2013: U.S. Geological Survey Scientific Investigations Report 2015-5014, Report: iv, 35 p.; 2 Appendices, https://doi.org/10.3133/sir20155014.","productDescription":"Report: iv, 35 p.; 2 Appendices","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2009-01-01","ipdsId":"IP-060255","costCenters":[{"id":105,"text":"Alabama Water Science Center","active":true,"usgs":true}],"links":[{"id":299398,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20155014.jpg"},{"id":299395,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2015/5014/"},{"id":299396,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5014/pdf/sir2015-5014.pdf","text":"Report","size":"888 KB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":299397,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5014/download","text":"Appendix 2","size":"167 KB","linkFileType":{"id":1,"text":"pdf"},"description":"Appendix 2","linkHelpText":"Concentrations of detected compounds in groundwater samples from wells located in areas of high-density row-crop production in Alabama, 2000-2013."}],"country":"United States","state":"Alabama","county":"Baldwin County, Colbert County, Geneva County, Henry County, Houston County, Lauderdale County, Limestone County, Madison County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.53700256347656,\n 30.40471180080158\n ],\n [\n -87.76771545410156,\n 30.39656853856939\n ],\n [\n -87.90435791015625,\n 30.53860787885458\n ],\n [\n -87.89920806884764,\n 30.55132212123368\n ],\n [\n -87.81543731689453,\n 30.593592390615303\n ],\n [\n -87.77938842773438,\n 30.584430469735068\n ],\n [\n -87.73441314697266,\n 30.427065265208352\n ],\n [\n -87.53734588623047,\n 30.42144037217422\n ],\n [\n -87.53700256347656,\n 30.40471180080158\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.63107299804688,\n 34.728069689872285\n ],\n [\n -87.6324462890625,\n 34.69307382947489\n ],\n [\n -87.57888793945312,\n 34.6704879985043\n ],\n [\n -86.8414306640625,\n 34.65919277297455\n ],\n [\n -86.48574829101562,\n 34.820567967282706\n ],\n [\n -86.396484375,\n 34.99062863827382\n ],\n [\n -86.50772094726562,\n 34.99287873327227\n ],\n [\n -86.572265625,\n 34.82282272723702\n ],\n [\n -86.82083129882812,\n 34.728069689872285\n ],\n [\n -87.63107299804688,\n 34.728069689872285\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -85.37200927734375,\n 31.007628489931207\n ],\n [\n -85.68511962890624,\n 31.065286288898164\n ],\n [\n -85.72288513183594,\n 31.19107061829726\n ],\n [\n -85.39192199707031,\n 31.36946776371185\n ],\n [\n -85.28205871582031,\n 31.371812843961937\n ],\n [\n -85.37200927734375,\n 31.007628489931207\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5523a017e4b027f0aee3d115","contributors":{"authors":[{"text":"Welch, Heather L. 0000-0001-8370-7711 hllott@usgs.gov","orcid":"https://orcid.org/0000-0001-8370-7711","contributorId":552,"corporation":false,"usgs":true,"family":"Welch","given":"Heather","email":"hllott@usgs.gov","middleInitial":"L.","affiliations":[{"id":105,"text":"Alabama Water Science Center","active":true,"usgs":true}],"preferred":true,"id":539455,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70144431,"text":"sir20155038 - 2015 - Potential groundwater recharge for the State of Minnesota using the Soil-Water-Balance model, 1996-2010","interactions":[],"lastModifiedDate":"2015-04-06T15:06:47","indexId":"sir20155038","displayToPublicDate":"2015-04-06T15:00:00","publicationYear":"2015","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":"2015-5038","title":"Potential groundwater recharge for the State of Minnesota using the Soil-Water-Balance model, 1996-2010","docAbstract":"Groundwater recharge is one of the most difficult components of a water budget to ascertain, yet is an important boundary condition necessary for the quantification of water resources. In Minnesota, improved estimates of recharge are necessary because approximately 75 percent of drinking water and 90 percent of agricultural irrigation water in Minnesota are supplied from groundwater. The water that is withdrawn must be supplied by some combination of (1) increased recharge, (2) decreased discharge to streams, lakes, and other surface-water bodies, and (3) removal of water that was stored in the system. Recent pressure on groundwater resources has highlighted the need to provide more accurate recharge estimates for various tools that can assess the sustainability of long-term water use. As part of this effort, the U.S. Geological Survey, in cooperation with the Minnesota Pollution Control Agency, used the Soil-Water-Balance model to calculate gridded estimates of potential groundwater recharge across Minnesota for 1996‒2010 at a 1-kilometer (0.621-mile) resolution. The potential groundwater recharge estimates calculated for Minnesota from the Soil-Water Balance model included gridded values (1-kilometer resolution) of annual mean estimates (that is, the means for individual years from 1996 through 2010) and mean annual estimates (that is, the mean for the 15-year period 1996−2010).
\nThe Soil-Water-Balance model uses a modified Thornthwaite-Mather soil-water-balance approach, with components of the soil-water balance calculated on a daily basis. A key advantage of this approach includes the use of commonly available geographic information system data layers that incorporate land cover, soil properties, and daily meteorological data to produce temporally and spatially variable gridded estimates of potential recharge. The Soil-Water-Balance model was calibrated by using a combination of parameter estimation techniques, making manual adjustments of model parameters, and using parameter values from previously published Soil-Water-Balance models. Each calibration simulation compared the potential recharge estimate from the model against base-flow estimates derived from three separate hydrograph separation techniques. A total of 35 Minnesota watersheds were selected for the model calibration.
\nMeteorological data necessary for the model included daily precipitation, minimum daily temperature, and maximum daily temperature. All of the meteorological data were provided by the Daymet dataset, which included daily continuous surfaces of key climatological data. Land-cover data were provided by the 2001 and 2006 National Land Cover Database: the 2001 classification was used from 1994 through 2003, and the 2006 classification was used from 2004 through 2010. Soil data used in the model included hydrologic soils group and the available soil-water capacity. These soil data were obtained from the Natural Resources Conservation Service Soil Survey Geographic (SSURGO) database and the State Soil Geographic (STATSGO) database.
\nThe statewide mean annual potential recharge rate from 1996–2010 was 4.9 inches per year. Potential recharge estimates increased from west to east across Minnesota. The mean annual potential recharge estimates across Minnesota at a 1-km resolution for the overall simulation period (1996–2010) ranged from less than 0.1 to 17.8 inches per year. Some of the lowest potential recharge rates for the simulation period were in the Red River of the North Basin of northwestern Minnesota, and generally were between 1.0 and 1.5 inches per year. The highest potential recharge rates were in northeastern Minnesota and the Anoka Sand Plain in central Minnesota. Eighty-eight percent of the potential recharge rates (by grid cell) were between 2 and 8 inches per year from 1996–2010. Only about 3 percent of all the potential recharge estimates (by grid cell) were less than 2 inches per year, and 9 percent of estimates were greater than 8 inches per year.
\nOn an annual basis, however, potential recharge rates were as high as 27.2 inches per year. The highest annual mean recharge estimate across the State was for 2010, and the lowest mean recharge estimate was for 2003. Although precipitation variability partially explained the annual differences in potential recharge estimates, precipitation alone did not account for these differences, and other factors such as antecedent moisture conditions likely were important. Also, because precipitation gradients across the State can vary from year to year, the dominant land-cover class and hydrologic soil group combinations for a particular region had a large effect on the resulting potential recharge value. During 1996–2010, April had the greatest monthly mean potential recharge compared to all other months, accounting for a mean of 30 percent of annual potential recharge in this single month.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155038","collaboration":"Prepared in cooperation with the Minnesota Pollution Control Agency","usgsCitation":"Smith, E.A., and Westenbroek, S.M., 2015, Potential groundwater recharge for the State of Minnesota using the Soil-Water-Balance model, 1996-2010: U.S. Geological Survey Scientific Investigations Report 2015-5038, vii, 85 p., https://doi.org/10.3133/sir20155038.","productDescription":"vii, 85 p.","startPage":"85","numberOfPages":"98","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"1996-01-01","temporalEnd":"2010-12-31","ipdsId":"IP-034584","costCenters":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"links":[{"id":299402,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20155038.jpg"},{"id":299399,"type":{"id":15,"text":"Index 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,{"id":70143271,"text":"sim3322 - 2015 - Using satellite images to monitor glacial-lake outburst floods: Lago Cachet Dos drainage, Chile","interactions":[],"lastModifiedDate":"2015-04-06T13:00:00","indexId":"sim3322","displayToPublicDate":"2015-04-06T12:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3322","title":"Using satellite images to monitor glacial-lake outburst floods: Lago Cachet Dos drainage, Chile","docAbstract":"The U.S. Geological Survey (USGS) is monitoring and analyzing glacial-lake outburst floods (GLOFs) in the Colonia valley in the Patagonia region of southern Chile. A GLOF is a type of flood that occurs when water impounded by a glacier or a glacial moraine is released catastrophically. In the Colonia valley, GLOFs originating from Lago Cachet Dos, which is dammed by the Colonia Glacier, have recurred periodically since 2008. The water discharged during these GLOFs flows under or through the Colonia Glacier, into Lago Colonia and then the Río Colonia, and finally into the Río Baker—Chile's largest river in terms of volume of water.
\nThis report presents a GeoEye-1 image collected December 1, 2011 and a WorldView-2 image collected September 27, 2013. The 2011 image shows Lago Cachet Dos when the water level was near its maximum extent. The 2013 image shows the drained lake four days after a GLOF event. The images were used to delineate the differences in water surface area prior to, and immediately following, a GLOF event. The imagery shown here highlights the dramatic changes that typically occur during GLOFs from Lago Cachet Dos. The lake area decreased from 4.84 km2 in 2011 (pre-GLOF) to only 0.30 km2 in September 2013 (post-GLOF). The water surface lowered approximately 90 m between the pre- and post-GLOF satellite images, yielding a change in volume of approximately 217,000,000 m3; this value is similar to previous estimates (about 200 million m3) of the volume of flood water that flowed down the Río Colonia during some previous GLOFs.
\nDuring 2008–2013, 14 GLOFs were released from Lago Cachet Dos and created environmental and safety concerns for downstream residents and to infrastructure. If GLOFs and the consequent headward erosion continue, the moraine that creates Lago Cachet Uno could be destabilized and breached, and the two lakes could merge. If the two lakes become connected, the volume of future GLOFs likely would be greater and thus cause longer and (or) more extensive flooding downstream. Additional GLOFs from Lago Cachet Dos are expected in the future, and continued environmental monitoring could provide an early warning system as well as scientific information that could increase our understanding of GLOFs and their consequences. GLOFs occur in glaciated areas around the world and remote sensing technologies can allow researchers to better understand—and potentially predict—future GLOF events.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3322","usgsCitation":"Friesen, B.A., Cole, C.J., Nimick, D.A., Wilson, E.M., Fahey, M., McGrath, D.J., and Leidich, J., 2015, Using satellite images to monitor glacial-lake outburst floods: Lago Cachet Dos drainage, Chile: U.S. Geological Survey Scientific Investigations Map 3322, 44.17 x 41.0 inches, https://doi.org/10.3133/sim3322.","productDescription":"44.17 x 41.0 inches","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-053416","costCenters":[{"id":573,"text":"Special Applications Science Center","active":true,"usgs":true}],"links":[{"id":299392,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim3322.jpg"},{"id":299390,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3322/"},{"id":299391,"rank":2,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3322/pdf/sim3322.pdf","text":"Map 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Center","active":true,"usgs":true}],"preferred":true,"id":540486,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cahan, Steven M. 0000-0002-4776-3668 scahan@usgs.gov","orcid":"https://orcid.org/0000-0002-4776-3668","contributorId":4529,"corporation":false,"usgs":true,"family":"Cahan","given":"Steven","email":"scahan@usgs.gov","middleInitial":"M.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":540487,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Warwick, Peter D. 0000-0002-3152-7783 pwarwick@usgs.gov","orcid":"https://orcid.org/0000-0002-3152-7783","contributorId":762,"corporation":false,"usgs":true,"family":"Warwick","given":"Peter","email":"pwarwick@usgs.gov","middleInitial":"D.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":540488,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70176906,"text":"70176906 - 2015 - Are conservation organizations configured for effective adaptation to global change?","interactions":[],"lastModifiedDate":"2016-10-13T08:53:04","indexId":"70176906","displayToPublicDate":"2015-04-03T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1701,"text":"Frontiers in Ecology and the Environment","active":true,"publicationSubtype":{"id":10}},"title":"Are conservation organizations configured for effective adaptation to global change?","docAbstract":"Conservation organizations must adapt to respond to the ecological impacts of global change. Numerous changes to conservation actions (eg facilitated ecological transitions, managed relocations, or increased corridor development) have been recommended, but some institutional restructuring within organizations may also be needed. Here we discuss the capacity of conservation organizations to adapt to changing environmental conditions, focusing primarily on public agencies and nonprofits active in land protection and management in the US. After first reviewing how these organizations anticipate and detect impacts affecting target species and ecosystems, we then discuss whether they are sufficiently flexible to prepare and respond by reallocating funding, staff, or other resources. We raise new hypotheses about how the configuration of different organizations enables them to protect particular conservation targets and manage for particular biophysical changes that require coordinated management actions over different spatial and temporal scales. Finally, we provide a discussion resource to help conservation organizations assess their capacity to adapt.
","language":"English","publisher":"Ecological Society of America","publisherLocation":"Washington, D.C.","doi":"10.1890/130352","usgsCitation":"Armsworth, P.R., Larson, E.R., Jackson, S.T., Sax, D.F., Simonin, P.W., Blossey, B., Green, N., Lester, L., Klein, M.L., Ricketts, T.H., Runge, M.C., and Shaw, M.R., 2015, Are conservation organizations configured for effective adaptation to global change?: Frontiers in Ecology and the Environment, v. 13, no. 3, p. 163-169, https://doi.org/10.1890/130352.","startPage":"163","endPage":"169","numberOfPages":"7","ipdsId":"IP-057333","costCenters":[{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true}],"links":[{"id":329514,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57ffdf00e4b0824b2d179cfc","contributors":{"authors":[{"text":"Armsworth, Paul R.","contributorId":175280,"corporation":false,"usgs":false,"family":"Armsworth","given":"Paul","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":650736,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Larson, Eric R.","contributorId":175281,"corporation":false,"usgs":false,"family":"Larson","given":"Eric","email":"","middleInitial":"R.","affiliations":[{"id":16989,"text":"University of Tennessee, Knoxville, TN","active":true,"usgs":false}],"preferred":false,"id":650737,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jackson, Stephen T. 0000-0002-1487-4652 stjackson@usgs.gov","orcid":"https://orcid.org/0000-0002-1487-4652","contributorId":344,"corporation":false,"usgs":true,"family":"Jackson","given":"Stephen","email":"stjackson@usgs.gov","middleInitial":"T.","affiliations":[{"id":560,"text":"South Central Climate Science Center","active":true,"usgs":true},{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":650670,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sax, Dov F.","contributorId":175300,"corporation":false,"usgs":false,"family":"Sax","given":"Dov","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":650738,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Simonin, Paul W.","contributorId":171499,"corporation":false,"usgs":false,"family":"Simonin","given":"Paul","email":"","middleInitial":"W.","affiliations":[{"id":18160,"text":"Rubenstein School of Environment and Natural Resources, University of Vermont","active":true,"usgs":false}],"preferred":false,"id":650739,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Blossey, Bernd","contributorId":175301,"corporation":false,"usgs":false,"family":"Blossey","given":"Bernd","email":"","affiliations":[],"preferred":false,"id":650740,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Green, Nancy","contributorId":147691,"corporation":false,"usgs":false,"family":"Green","given":"Nancy","email":"","affiliations":[{"id":16902,"text":"U.S. Fish and Wildlife Service, Ecological Services Program, Washington, D.C., 20240, USA","active":true,"usgs":false}],"preferred":false,"id":650741,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Klein, Mary L.","contributorId":175302,"corporation":false,"usgs":false,"family":"Klein","given":"Mary","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":650742,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Lester, Liza","contributorId":175303,"corporation":false,"usgs":false,"family":"Lester","given":"Liza","email":"","affiliations":[],"preferred":false,"id":650743,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Ricketts, Taylor H.","contributorId":175304,"corporation":false,"usgs":false,"family":"Ricketts","given":"Taylor","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":650744,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Runge, Michael C. 0000-0002-8081-536X mrunge@usgs.gov","orcid":"https://orcid.org/0000-0002-8081-536X","contributorId":3358,"corporation":false,"usgs":true,"family":"Runge","given":"Michael","email":"mrunge@usgs.gov","middleInitial":"C.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":650671,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Shaw, M. Rebecca","contributorId":175305,"corporation":false,"usgs":false,"family":"Shaw","given":"M.","email":"","middleInitial":"Rebecca","affiliations":[],"preferred":false,"id":650745,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70145260,"text":"70145260 - 2015 - Conceptual models of the formation of acid-rock drainage at road cuts in Tennessee","interactions":[],"lastModifiedDate":"2015-11-23T15:30:52","indexId":"70145260","displayToPublicDate":"2015-04-03T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":18,"text":"Abstract or summary"},"title":"Conceptual models of the formation of acid-rock drainage at road cuts in Tennessee","docAbstract":"Pyrite and other minerals containing sulfur and trace metals occur in several rock formations throughout Middle and East Tennessee. Pyrite (FeS2) weathers in the presence of oxygen and water to form iron hydroxides and sulfuric acid. The weathering and interaction of the acid on the rocks and other minerals at road cuts can result in drainage with low pH (< 4) and high concentrations of trace metals. Acid-rock drainage can cause environmental problems and damage transportation infrastructure. The formation and remediation of acid-drainage from roads cuts has not been researched as thoroughly as acid-mine drainage. The U.S Geological Survey, in cooperation with the Tennessee Department of Transportation, is conducting an investigation to better understand the geologic, hydrologic, and biogeochemical factors that control acid formation at road cuts. Road cuts with the potential for acid-rock drainage were identifed and evaluated in Middle and East Tennessee. The pyrite-bearing formations evaluated were the Chattanooga Shale (Devonian black shale), the Fentress Formation (coal-bearing), and the Precambrian Anakeesta Formation and similar Precambrian rocks. Conceptual models of the formation and transport of acid-rock drainage (ARD) from road cuts were developed based on the results of a literature review, site reconnaissance, and the initial rock and water sampling. The formation of ARD requires a combination of hydrologic, geochemical, and microbial interactions which affect drainage from the site, acidity of the water, and trace metal concentrations. The basic modes of ARD formation from road cuts are; 1 - seeps and springs from pyrite-bearing formations and 2 - runoff over the face of a road cut in a pyrite-bearing formation. Depending on site conditions at road cuts, the basic modes of ARD formation can be altered and the additional modes of ARD formation are; 3 - runoff over and through piles of pyrite-bearing material, either from construction or breakdown material weathered from shale, and 4 - the deposition of secondary-sulfate minerals can store trace metals and, during rainfall, result in increased acidity and higher concentrations of trace metals in storm runoff. Understanding the factors that control ARD formation and transport are key to addressing the problems associated with the movement of ARD from the road cuts to the environment. The investigation will provide the Tennessee Department of Transportation with a regional characterization of ARD and provide insights into the geochemical and biochemical attributes for the control and remediation of ARD from road cuts.
","largerWorkTitle":"Proceedings of the 2015 Tennessee Water Resources Symposium","conferenceTitle":"2015 Tennessee Water Resources Symposium","conferenceDate":"April 1-3, 2015","conferenceLocation":"Montgomery Bell State Park Burns, Tennessee","language":"English","publisher":"Tennessee Section of the American Water Resources Association","collaboration":"Tenn. Department of Transportation","usgsCitation":"Bradley, M., Worland, S., and Byl, T., 2015, Conceptual models of the formation of acid-rock drainage at road cuts in Tennessee, in Proceedings of the 2015 Tennessee Water Resources Symposium, Montgomery Bell State Park Burns, Tennessee, April 1-3, 2015, p. 2C-8-2C-9.","productDescription":"1 p.","startPage":"2C-8","endPage":"2C-9","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062621","costCenters":[{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true}],"links":[{"id":311666,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":299403,"type":{"id":15,"text":"Index Page"},"url":"https://tnawra.er.usgs.gov/Library/Proceedings24th.pdf"}],"country":"United States","state":"Tennessee","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -86.748046875,\n 36.677230602346214\n ],\n [\n -87.56103515625,\n 36.075742215627\n ],\n [\n -87.593994140625,\n 35.53222622770337\n ],\n [\n -87.220458984375,\n 35.0120020431607\n ],\n [\n -86.81396484375,\n 35.110921809704756\n ],\n [\n -86.484375,\n 35.29943548054545\n ],\n [\n -85.98999023437499,\n 35.951329861522666\n ],\n [\n -86.28662109375,\n 36.5184659896759\n ],\n [\n -86.572265625,\n 36.659606226479696\n ],\n [\n -86.748046875,\n 36.677230602346214\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.836669921875,\n 36.60670888641815\n ],\n [\n -84.74853515625,\n 36.27085020723905\n ],\n [\n -85.23193359375,\n 35.7019167328534\n ],\n [\n -85.462646484375,\n 35.22767235493586\n ],\n [\n -85.484619140625,\n 35.02099970111467\n ],\n [\n -85.1220703125,\n 34.94899072578227\n ],\n [\n -84.891357421875,\n 35.003003395276714\n ],\n [\n -84.3310546875,\n 35.755428369259626\n ],\n [\n -83.726806640625,\n 36.33282808737917\n ],\n [\n -83.5400390625,\n 36.56260003738548\n ],\n [\n -83.836669921875,\n 36.60670888641815\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.2216796875,\n 36.58024660149866\n ],\n [\n -84.649658203125,\n 35.16482750605027\n ],\n [\n -84.385986328125,\n 35.038992046780784\n ],\n [\n -84.19921875,\n 35.27253175660236\n ],\n [\n -83.8037109375,\n 35.48751102385376\n ],\n [\n -83.16650390625,\n 35.69299463209881\n ],\n [\n -82.5732421875,\n 36.04021586880111\n ],\n [\n -82.3974609375,\n 36.13787471840729\n ],\n [\n -81.990966796875,\n 36.19995805932895\n ],\n [\n -81.63940429687499,\n 36.62434536776987\n ],\n [\n -82.2216796875,\n 36.58024660149866\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"565446bde4b071e7ea53d4a6","contributors":{"authors":[{"text":"Bradley, Mike 0000-0002-2979-265X mbradley@usgs.gov","orcid":"https://orcid.org/0000-0002-2979-265X","contributorId":582,"corporation":false,"usgs":true,"family":"Bradley","given":"Mike","email":"mbradley@usgs.gov","affiliations":[{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":544131,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Worland, Scott","contributorId":150038,"corporation":false,"usgs":false,"family":"Worland","given":"Scott","affiliations":[],"preferred":false,"id":580500,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Byl, Tom","contributorId":150039,"corporation":false,"usgs":false,"family":"Byl","given":"Tom","affiliations":[],"preferred":false,"id":580501,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70142541,"text":"sir20155042 - 2015 - Multilevel groundwater monitoring of hydraulic head and temperature in the eastern Snake River Plain aquifer, Idaho National Laboratory, Idaho, 2011-13","interactions":[],"lastModifiedDate":"2015-04-02T16:56:44","indexId":"sir20155042","displayToPublicDate":"2015-04-02T17:45:00","publicationYear":"2015","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":"2015-5042","title":"Multilevel groundwater monitoring of hydraulic head and temperature in the eastern Snake River Plain aquifer, Idaho National Laboratory, Idaho, 2011-13","docAbstract":"From 2011 to 2013, the U.S. Geological Survey’s Idaho National Laboratory (INL) Project Office, in cooperation with the U.S. Department of Energy, collected depth-discrete measurements of fluid pressure and temperature in 11 boreholes located in the eastern Snake River Plain aquifer. Each borehole was instrumented with a multilevel monitoring system (MLMS) consisting of a series of valved measurement ports, packer bladders, casing segments, and couplers.
\nMultilevel monitoring at the INL has been ongoing since 2006 and this report summarizes data collected from 2011 to 2013 in 11 multilevel monitoring wells. Hydraulic head (head) and groundwater temperature data were collected from 11 multilevel monitoring wells, including 177 hydraulically isolated depth intervals from 448.0 to 1,377.6 feet below land surface. One port (port 3) within borehole USGS 134 was not monitored because of a valve failure.
\nHead and temperature profiles reveal unique patterns for vertical examination of the aquifer’s complex basalt and sediment stratigraphy, proximity to aquifer recharge and discharge, and groundwater flow. These features contribute to some of the localized variability even though the general profile shape remained consistent over the period of record. Twenty-two major head inflections were described for 9 of 11 MLMS boreholes and almost always coincided with low‑permeability sediment layers and occasionally thick layers of dense basalt. However, the presence of a sediment layer or dense basalt layer was insufficient for identifying the location of a major head change within a borehole without knowing the true areal extent and relative transmissivity of the lithologic unit. Temperature profiles for boreholes completed within the Big Lost Trough indicate linear conductive trends; whereas, temperature profiles for boreholes completed within volcanic rift zones and near the southern boundary of the Idaho National Laboratory, indicate mostly convective heat transfer. Select boreholes along the southern boundary show a temperature reversal and cooler water deeper in the aquifer resulting from the vertical movement of groundwater.
\nVertical head and temperature change were quantified for each of the 11 multilevel monitoring systems. Vertical head gradients defined for the major inflections in the head profiles were as high as 2.9 feet per foot. In general, fractured basalt zones displayed relatively small vertical head differences and show a high occurrence within volcanic rift zones. Poor connectivity between fractures and higher vertical gradients were generally attributed to sediment layers and layers of dense basalt, or both. Groundwater temperatures in all boreholes ranged from 10.8 to 16.3 °C.
\nNormalized mean head values were analyzed for all 11 multilevel monitoring wells for the period of record (2007–13). The mean head values suggest a moderately positive correlation among all boreholes and generally reflect regional fluctuations in water levels in response to seasonal climatic changes. Boreholes within volcanic rift zones and near the southern boundary (USGS 103, USGS 105, USGS 108, USGS 132, USGS 135, USGS 137A) display a temporal correlation that is strongly positive. Boreholes in the Big Lost Trough display some variations in temporal correlations that may result from proximity to the mountain front to the northwest and episodic flow in the Big Lost River drainage system. For example, during June 2012, boreholes MIDDLE 2050A and MIDDLE 2051 showed head buildup within the upper zones when compared to the June 2010 profile event, which correlates to years when surface water was reported for the Big Lost River several months preceding the measurement period. With the exception of borehole USGS 134, temporal correlation between MLMS wells completed within the Big Lost Trough is generally positive. Temporal correlation for borehole USGS 134 shows the least agreement with other MLMS boreholes located within the Big Lost Trough; however, borehole USGS 134 is close to the mountain front where tributary valley subsurface inflow is suspected.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155042","collaboration":"Prepared in cooperation with the U.S. Department of Energy","usgsCitation":"Twining, B.V., and Fisher, J.C., 2015, Multilevel groundwater monitoring of hydraulic head and temperature in the eastern Snake River Plain aquifer, Idaho National Laboratory, Idaho, 2011-13: U.S. Geological Survey Scientific Investigations Report 2015-5042, Report: vii, 49 p.; 8 Appendices, https://doi.org/10.3133/sir20155042.","productDescription":"Report: vii, 49 p.; 8 Appendices","numberOfPages":"62","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2011-01-01","temporalEnd":"2013-12-31","ipdsId":"IP-056607","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":299324,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20155042.jpg"},{"id":299323,"rank":10,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5042/pdf/sir20155042_AppH.pdf","text":"Appendix H","size":"161 KB","linkFileType":{"id":1,"text":"pdf"}},{"id":299314,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2015/5042/"},{"id":299315,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5042/pdf/sir2015-5042.pdf","size":"4.1 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":299316,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5042/pdf/sir20155042_AppA.pdf","text":"Appendix A","size":"98 KB","linkFileType":{"id":1,"text":"pdf"}},{"id":299317,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5042/pdf/sir20155042_AppB.pdf","text":"Appendix B","size":"202 KB","linkFileType":{"id":1,"text":"pdf"}},{"id":299318,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5042/pdf/sir20155042_AppC.pdf","text":"Appendix C","size":"125 KB","linkFileType":{"id":1,"text":"pdf"}},{"id":299319,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5042/pdf/sir20155042_AppD.pdf","text":"Appendix D","size":"109 KB","linkFileType":{"id":1,"text":"pdf"}},{"id":299320,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5042/pdf/sir20155042_AppE.pdf","text":"Appendix E","size":"592 KB","linkFileType":{"id":1,"text":"pdf"}},{"id":299321,"rank":8,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5042/pdf/sir20155042_AppF.pdf","text":"Appendix F","size":"103 KB","linkFileType":{"id":1,"text":"pdf"}},{"id":299322,"rank":9,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5042/pdf/sir20155042_AppG.pdf","text":"Appendix G","size":"148 KB","linkFileType":{"id":1,"text":"pdf"}}],"scale":"24000","projection":"Universal Transverse Mercator projection","datum":"North American Datum of 1927","country":"United States","state":"Idaho","otherGeospatial":"Eastern Snake River Plain aquifer","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -113.104248046875,\n 43.52664646047308\n ],\n [\n -113.104248046875,\n 43.880077621969065\n ],\n [\n -112.61123657226562,\n 43.880077621969065\n ],\n [\n -112.61123657226562,\n 43.52664646047308\n ],\n [\n -113.104248046875,\n 43.52664646047308\n ]\n ]\n ]\n }\n }\n ]\n}","publicComments":"DOE/ID-22235","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"551e5a1fe4b027f0aee3b87d","contributors":{"authors":[{"text":"Twining, Brian V. 0000-0003-1321-4721 btwining@usgs.gov","orcid":"https://orcid.org/0000-0003-1321-4721","contributorId":2387,"corporation":false,"usgs":true,"family":"Twining","given":"Brian","email":"btwining@usgs.gov","middleInitial":"V.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":543938,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fisher, Jason C. 0000-0001-9032-8912 jfisher@usgs.gov","orcid":"https://orcid.org/0000-0001-9032-8912","contributorId":2523,"corporation":false,"usgs":true,"family":"Fisher","given":"Jason","email":"jfisher@usgs.gov","middleInitial":"C.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":543939,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70142609,"text":"ofr20151044 - 2015 - Mass-movement deposits in the lacustrine Eocene Green River Formation, Piceance Basin, western Colorado","interactions":[],"lastModifiedDate":"2015-04-02T11:21:47","indexId":"ofr20151044","displayToPublicDate":"2015-04-02T12:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-1044","title":"Mass-movement deposits in the lacustrine Eocene Green River Formation, Piceance Basin, western Colorado","docAbstract":"The Eocene Green River Formation was deposited in two large Eocene saline lakes, Lake Uinta in the Uinta and Piceance Basins and Lake Gosiute in the Greater Green River Basin. Here we will discuss mass-movement deposits in just the Piceance Basin part of Lake Uinta.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151044","usgsCitation":"Johnson, R.C., Birdwell, J.E., Brownfield, M.E., and Mercier, T.J., 2015, Mass-movement deposits in the lacustrine Eocene Green River Formation, Piceance Basin, western Colorado: U.S. Geological Survey Open-File Report 2015-1044, 42 p., https://doi.org/10.3133/ofr20151044.","productDescription":"42 p.","numberOfPages":"42","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-059898","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":299310,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20151044.jpg"},{"id":299308,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2015/1044/"},{"id":299309,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1044/pdf/ofr2015-1044.pdf","size":"30.2 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Colorado","otherGeospatial":"Eocene Green River Formation, Piceance Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.819580078125,\n 39.2832938689385\n ],\n [\n -108.819580078125,\n 40.30466538259176\n ],\n [\n -107.720947265625,\n 40.30466538259176\n ],\n [\n -107.720947265625,\n 39.2832938689385\n ],\n [\n -108.819580078125,\n 39.2832938689385\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"551e5a1fe4b027f0aee3b87b","contributors":{"authors":[{"text":"Johnson, Ronald C. 0000-0002-6197-5165 rcjohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-6197-5165","contributorId":1550,"corporation":false,"usgs":true,"family":"Johnson","given":"Ronald","email":"rcjohnson@usgs.gov","middleInitial":"C.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":543917,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Birdwell, Justin E. 0000-0001-8263-1452 jbirdwell@usgs.gov","orcid":"https://orcid.org/0000-0001-8263-1452","contributorId":3302,"corporation":false,"usgs":true,"family":"Birdwell","given":"Justin","email":"jbirdwell@usgs.gov","middleInitial":"E.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":543918,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brownfield, Michael E. 0000-0003-3633-1138 mbrownfield@usgs.gov","orcid":"https://orcid.org/0000-0003-3633-1138","contributorId":1548,"corporation":false,"usgs":true,"family":"Brownfield","given":"Michael","email":"mbrownfield@usgs.gov","middleInitial":"E.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":543919,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mercier, Tracey J. 0000-0002-8232-525X tmercier@usgs.gov","orcid":"https://orcid.org/0000-0002-8232-525X","contributorId":2847,"corporation":false,"usgs":true,"family":"Mercier","given":"Tracey","email":"tmercier@usgs.gov","middleInitial":"J.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":543920,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70144294,"text":"ofr20151058 - 2015 - An evaluation of the accuracy of modeled and computed streamflow time-series data for the Ohio River at Hannibal Lock and Dam and at a location upstream from Sardis, Ohio","interactions":[],"lastModifiedDate":"2015-04-09T08:31:36","indexId":"ofr20151058","displayToPublicDate":"2015-04-02T11:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-1058","title":"An evaluation of the accuracy of modeled and computed streamflow time-series data for the Ohio River at Hannibal Lock and Dam and at a location upstream from Sardis, Ohio","docAbstract":"Between July 2013 and June 2014, the U.S. Geological Survey (USGS) made 10 streamflow measurements on the Ohio River about 1.5 miles (mi) downstream from the Hannibal Lock and Dam (near Hannibal, Ohio) and 11 streamflow measurements near the USGS Sardis gage (station number 03114306) located approximately 2.4 mi upstream from Sardis, Ohio. The measurement results were used to assess the accuracy of modeled or computed instantaneous streamflow time series created and supplied by the USGS, U.S. Army Corps of Engineers (USACE), and National Weather Service (NWS) for the Ohio River at Hannibal Lock and Dam and (or) at the USGS streamgage. Hydraulic or hydrologic models were used to create the modeled time series; index-velocity methods or gate-opening ratings coupled with hydropower operation data were used to create the computed time series. The time step of the various instantaneous streamflow time series ranged from 15 minutes to 24 hours (once-daily values at 12:00 Coordinated Universal Time [UTC]). The 15-minute time-series data, computed by the USGS for the Sardis gage, also were downsampled to 1-hour and 24-hour time steps to permit more direct comparisons with other streamflow time series.
\nTo facilitate comparisons between measurement results and time-series data, streamflows corresponding to the times of the streamflow measurements were computed from the time-series data by time-based linear interpolation. Prior to doing interpolations, measurement times for the Hannibal Lock and Dam location were adjusted for traveltime to account for the fact that the streamflow measurements were made about 1.5 mi downstream from the location corresponding to the modeled/computed time-series data. Measured and interpolated streamflows were tabulated along with residuals (the difference between measured and interpolated streamflows) and selected summary statistics.
\nOverall, streamflows interpolated from the USGS computed 15-minute time-series data (hereafter referred to as the USGS 15-minute time-series data) had the smallest root-mean-square error (RMSE) (3,939 cubic feet per second [ft3/s]) and the second smallest mean absolute residual (2,636 ft3/s), whereas streamflows interpolated from the USACE 12 UTC time series had the largest RMSE (14,590 ft3/s) and the largest mean absolute residual (10,800 ft3/s). The larger RMSEs for streamflows interpolated from the USACE 12 UTC time series likely resulted in part from the coarser time step of that time series. Streamflows interpolated from the USGS downsampled 1-hour time series had the second smallest RMSE (4,025 ft3/s) and the smallest mean absolute residual (2,600 ft3/s). Somewhat surprisingly, streamflows interpolated from the NWS 6-hour model time series had the third smallest RMSE (4,483 ft3/s) and mean absolute residual (4,050 ft3/s) in spite of being determined from a time series with a coarser time step than the USACE 1-hour modeled and computed time series.
\nMeasured streamflows at the Sardis gage and at the Hannibal Lock and Dam measurement location were plotted versus residuals (expressed as a percentage of the measured streamflows) of corresponding interpolated time-series streamflow values. Results for each of the time series exhibited some anomaly, possibly indicating the need and (or) potential for improvement in the streamflow computational/modeling processes.
\nStreamflow hydrographs were plotted for modeled/computed time series for the Ohio River near the USGS Sardis gage and the Ohio River at the Hannibal Lock and Dam. In general, the time series at these two locations compared well. Some notable differences include the exclusive presence of short periods of negative streamflows in the USGS 15-minute time-series data for the gage on the Ohio River above Sardis, Ohio, and the occurrence of several peak streamflows in the USACE gate/hydropower time series for the Hannibal Lock and Dam that were appreciably larger than corresponding peaks in the other time series, including those modeled/computed for the downstream Sardis gage
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151058","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Koltun, G., 2015, An evaluation of the accuracy of modeled and computed streamflow time-series data for the Ohio River at Hannibal Lock and Dam and at a location upstream from Sardis, Ohio: U.S. Geological Survey Open-File Report 2015-1058, viii, 23 p., https://doi.org/10.3133/ofr20151058.","productDescription":"viii, 23 p.","numberOfPages":"32","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-063449","costCenters":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"links":[{"id":299300,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20151058.jpg"},{"id":299296,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2015/1058/"},{"id":299297,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1058/pdf/ofr2015-1058.pdf","text":"Report","size":"1.20 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"country":"United States","state":"Ohio","otherGeospatial":"Ohio River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.96099853515624,\n 39.57817336212527\n ],\n [\n -80.96099853515624,\n 39.68182601089365\n ],\n [\n -80.82092285156249,\n 39.68182601089365\n ],\n [\n -80.82092285156249,\n 39.57817336212527\n ],\n [\n -80.96099853515624,\n 39.57817336212527\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"551e5a1be4b027f0aee3b86b","contributors":{"authors":[{"text":"Koltun, G. F. 0000-0003-0255-2960 gfkoltun@usgs.gov","orcid":"https://orcid.org/0000-0003-0255-2960","contributorId":1852,"corporation":false,"usgs":true,"family":"Koltun","given":"G. F.","email":"gfkoltun@usgs.gov","affiliations":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"preferred":false,"id":543454,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70144432,"text":"70144432 - 2015 - Do management actions to restore rare habitat benefit native fish conservation? Distribution of juvenile native fish among shoreline habitats of the Colorado River","interactions":[],"lastModifiedDate":"2015-12-07T10:14:29","indexId":"70144432","displayToPublicDate":"2015-04-02T10:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3301,"text":"River Research and Applications","active":true,"publicationSubtype":{"id":10}},"title":"Do management actions to restore rare habitat benefit native fish conservation? Distribution of juvenile native fish among shoreline habitats of the Colorado River","docAbstract":"Many management actions in aquatic ecosystems are directed at restoring or improving specific habitats to benefit fish populations. In the Grand Canyon reach of the Colorado River, experimental flow operations as part of the Glen Canyon Dam Adaptive Management Program have been designed to restore sandbars and associated backwater habitats. Backwaters can have warmer water temperatures than other habitats, and native fish, including the federally endangered humpback chub Gila cypha, are frequently observed in backwaters, leading to a common perception that this habitat is critical for juvenile native fish conservation. However, it is unknown how fish densities in backwaters compare with that in other habitats or what proportion of juvenile fish populations reside in backwaters. Here, we develop and fit multi-species hierarchical models to estimate habitat-specific abundances and densities of juvenile humpback chub, bluehead suckerCatostomus discobolus, flannelmouth sucker Catostomus latipinnis and speckled dace Rhinichthys osculus in a portion of the Colorado River. Densities of all four native fish were greatest in backwater habitats in 2009 and 2010. However, backwaters are rare and ephemeral habitats, so they contain only a small portion of the overall population. For example, the total abundance of juvenile humpback chub in this study was much higher in talus than in backwater habitats. Moreover, when we extrapolated relative densities based on estimates of backwater prevalence directly after a controlled flood, the majority of juvenile humpback chub were still found outside of backwaters. This suggests that the role of controlled floods in influencing native fish population trends may be limited in this section of the Colorado River.
","language":"English","publisher":"Wiley","doi":"10.1002/rra.2842","usgsCitation":"Dodrill, M.J., Yackulic, C.B., Gerig, B., Pine, W.E., Korman, J., and Finch, C., 2015, Do management actions to restore rare habitat benefit native fish conservation? Distribution of juvenile native fish among shoreline habitats of the Colorado River: River Research and Applications, v. 31, no. 10, p. 1203-1217, https://doi.org/10.1002/rra.2842.","productDescription":"15 p.","startPage":"1203","endPage":"1217","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-052358","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":299274,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Colorado River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.8902587890625,\n 36.097938036628065\n ],\n [\n -111.8902587890625,\n 36.289670126842225\n ],\n [\n -111.74057006835936,\n 36.289670126842225\n ],\n [\n -111.74057006835936,\n 36.097938036628065\n ],\n [\n -111.8902587890625,\n 36.097938036628065\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"31","issue":"10","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2014-10-08","publicationStatus":"PW","scienceBaseUri":"551e5a1ee4b027f0aee3b873","contributors":{"authors":[{"text":"Dodrill, Michael J. 0000-0002-7038-7170 mdodrill@usgs.gov","orcid":"https://orcid.org/0000-0002-7038-7170","contributorId":5468,"corporation":false,"usgs":true,"family":"Dodrill","given":"Michael","email":"mdodrill@usgs.gov","middleInitial":"J.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":543579,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yackulic, Charles B. 0000-0001-9661-0724 cyackulic@usgs.gov","orcid":"https://orcid.org/0000-0001-9661-0724","contributorId":4662,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","email":"cyackulic@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":543580,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gerig, Brandon","contributorId":139958,"corporation":false,"usgs":false,"family":"Gerig","given":"Brandon","affiliations":[{"id":13331,"text":"University of Florida, Dept. of Wildlife Ecology and Conservation","active":true,"usgs":false}],"preferred":false,"id":543581,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pine, William E. III","contributorId":139959,"corporation":false,"usgs":false,"family":"Pine","given":"William","suffix":"III","email":"","middleInitial":"E.","affiliations":[{"id":13332,"text":"Uni. of Florida Department of Wildlife Ecology and Conservation","active":true,"usgs":false}],"preferred":false,"id":543582,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Korman, Josh","contributorId":139960,"corporation":false,"usgs":false,"family":"Korman","given":"Josh","email":"","affiliations":[{"id":13333,"text":"Ecometric Research Inc.","active":true,"usgs":false}],"preferred":false,"id":543583,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Finch, Colton","contributorId":139961,"corporation":false,"usgs":false,"family":"Finch","given":"Colton","affiliations":[{"id":13334,"text":"Uni. of Florida, Department of Wildlife Ecology and Conservation","active":true,"usgs":false}],"preferred":false,"id":543584,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70144936,"text":"70144936 - 2015 - Not putting all their eggs in one basket: bet-hedging despite extraordinary annual reproductive output of desert tortoises","interactions":[],"lastModifiedDate":"2015-04-27T13:40:37","indexId":"70144936","displayToPublicDate":"2015-04-02T10:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1019,"text":"Biological Journal of the Linnean Society","active":true,"publicationSubtype":{"id":10}},"title":"Not putting all their eggs in one basket: bet-hedging despite extraordinary annual reproductive output of desert tortoises","docAbstract":"Bet-hedging theory makes the counter-intuitive prediction that, if juvenile survival is low and unpredictable, organisms should consistently reduce short-term reproductive output to minimize the risk of reproductive failure in the long-term. We investigated the long-term reproductive output of an Agassiz's desert tortoise (Gopherus agassizii) population and conformance to a bet-hedging strategy of reproduction in an unpredictable but comparatively productive environment. Most females reproduced every year, even during periods of low precipitation and poor germination of food plants, and the mean percentage of reproducing females did not differ significantly on an annual basis. Although mean annual egg production (clutch size × clutch frequency) differed significantly among years, mean clutch size and mean clutch frequency remained relatively constant. During an El Niño year, mean annual egg production and mean annual clutch frequency were the highest ever reported for this species. Annual egg production was positively influenced by maternal body size but clutch size and clutch frequency were not. Our long-term results confirm earlier conclusions based on short-term research that desert tortoises have a bet-hedging strategy of producing small clutches almost every year. The risk of long-term reproductive failure is minimized in unpredictable environments, both through time by annually producing multiple small clutches over a long reproductive lifespan, even in years of low resource availability, and through space by depositing multiple annual clutches in different locations. The extraordinary annual reproductive output of this population appears to be the result of a typically high but unpredictable biomass of annual food plants at the site relative to tortoise habitat in dryer regions. Under the comparatively productive but unpredictable conditions, tortoises conform to predictions of a bet-hedging strategy of reproduction with relatively small but consistent clutch sizes.
","language":"English","publisher":"The Linnean Society of London","doi":"10.1111/bij.12505","usgsCitation":"Lovich, J.E., Ennen, J., Yackulic, C.B., Meyer-Wilkins, K., Agha, M., Loughran, C.L., Bjurlin, C., Austin, M., and Madrak, S.V., 2015, Not putting all their eggs in one basket: bet-hedging despite extraordinary annual reproductive output of desert tortoises: Biological Journal of the Linnean Society, v. 115, no. 2, p. 399-410, https://doi.org/10.1111/bij.12505.","productDescription":"12 p.","startPage":"399","endPage":"410","numberOfPages":"12","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059628","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":472160,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/bij.12505","text":"Publisher Index Page"},{"id":299271,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"115","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-03-19","publicationStatus":"PW","scienceBaseUri":"551e5a20e4b027f0aee3b87f","chorus":{"doi":"10.1111/bij.12505","url":"http://dx.doi.org/10.1111/bij.12505","publisher":"Oxford University Press (OUP)","authors":"Lovich Jeffrey E., Ennen Joshua R., Yackulic Charles B., Meyer-Wilkins Kathie, Agha Mickey, Loughran Caleb, Bjurlin Curtis, Austin Meaghan, Madrak Sheila","journalName":"Biological Journal of the Linnean Society","publicationDate":"3/19/2015","auditedOn":"7/24/2015"},"contributors":{"authors":[{"text":"Lovich, Jeffrey E. 0000-0002-7789-2831 jeffrey_lovich@usgs.gov","orcid":"https://orcid.org/0000-0002-7789-2831","contributorId":458,"corporation":false,"usgs":true,"family":"Lovich","given":"Jeffrey","email":"jeffrey_lovich@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":543848,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ennen, Joshua R.","contributorId":60368,"corporation":false,"usgs":false,"family":"Ennen","given":"Joshua R.","affiliations":[{"id":13216,"text":"Tennessee Aquarium Conservation Institute","active":true,"usgs":false}],"preferred":false,"id":543849,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yackulic, Charles B. 0000-0001-9661-0724 cyackulic@usgs.gov","orcid":"https://orcid.org/0000-0001-9661-0724","contributorId":4662,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","email":"cyackulic@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":543856,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Meyer-Wilkins, Kathie","contributorId":8742,"corporation":false,"usgs":false,"family":"Meyer-Wilkins","given":"Kathie","affiliations":[],"preferred":false,"id":543850,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Agha, Mickey","contributorId":22235,"corporation":false,"usgs":false,"family":"Agha","given":"Mickey","email":"","affiliations":[{"id":12425,"text":"University of Kentucky","active":true,"usgs":false},{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":543851,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Loughran, Caleb L.","contributorId":26599,"corporation":false,"usgs":true,"family":"Loughran","given":"Caleb","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":543852,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bjurlin, Curtis","contributorId":90183,"corporation":false,"usgs":false,"family":"Bjurlin","given":"Curtis","affiliations":[],"preferred":false,"id":543853,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Austin, Meaghan","contributorId":37244,"corporation":false,"usgs":true,"family":"Austin","given":"Meaghan","affiliations":[],"preferred":false,"id":543854,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Madrak, Sheila V.","contributorId":7403,"corporation":false,"usgs":true,"family":"Madrak","given":"Sheila","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":543855,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70144136,"text":"ofr20151051 - 2015 - Efficacy of Pseudomonas fluorescens strain CL145A spray dried powder for controlling zebra mussels adhering to native unionid mussels within field enclosures","interactions":[],"lastModifiedDate":"2015-04-02T08:37:22","indexId":"ofr20151051","displayToPublicDate":"2015-04-02T09:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-1051","title":"Efficacy of Pseudomonas fluorescens strain CL145A spray dried powder for controlling zebra mussels adhering to native unionid mussels within field enclosures","docAbstract":"The efficacy of a commercially prepared spray dried powder (SDP) formulation of Pseudomonas fluorescens (strain CL145A) was evaluated for removing zebra mussels (Dreissena polymorpha) adhering to a population of unionid mussels in Lake Darling (Alexandria, Minnesota). Two groups of unionid mussels were used in the study. Unionid mussels were collected near the test area, weighed, photographed, individually tagged, and randomly allocated to one of nine test enclosures in equal proportions and then divided into two groups. The first group of unionid mussels (Group 1, n = 5 per test enclosure) were indiscriminately selected from each test enclosure and used to estimate the number of zebra mussels adhering to unionid mussels prior to exposure. The second group of unionid mussels (Group 2, n = 22 per test enclosure) were used to evaluate the efficacy of SDP for removal of adhering zebra mussels. Both Group 1 and Group 2 mussels were used to evaluate the effects of SDP exposure on unionid mussel survival.
\nTreatment was assigned to each test enclosure by using a randomized block design. The three treatment groups were tested in triplicate and included an untreated control group and groups that received a single application of 50 or 100 milligrams per liter (mg/L) of SDP based on active ingredient. All treatment concentrations are reported as active ingredient of SDP. Test enclosures were removed at the 8-hour exposure termination. Both Group 1 and Group 2 mussels remained in their assigned exposure location during the postexposure holding period. The number of zebra mussels adhering to Group 2 mussels (live and dead) was assessed 18 to 20 days postexposure in addition to assessing the survival of Group 1 and Group 2 unionid mussels.
\nSDP, administered as a single treatment, significantly (p < 0.01) reduced the number of adhering zebra mussels when compared to the untreated controls. The number of zebra mussels adhering to unionid mussels (Group 2) was reduced 53 percent in the 50-mg/L treatment group and 68 percent in the 100-mg/L treatment group. The number of adhering zebra mussels did not differ (p = 0.79) between the 50- and 100-mg/L treatment groups after exposure. When standardized to the amount of SDP applied per square meter, each gram (g) of SDP applied in the 50-mg/L treatment reduced the number of adhering zebra mussel 59.8 percent more than the 100-mg/L treatment group.
\nGroup 1 mussel survival did not differ between treatment groups (p > 0.05); however, a difference was detected (p < 0.01) in the survival of Group 2 mussels. The survival of Group 2 mussels did not differ (p > 0.23) between control and treated groups. A difference in Group 2 mussel survival was detected (p = 0.03; odds ratio [OR] = 0.290) between the 50- and 100-mg/L treatment groups (that is, the survival was highest in the 50-mg/L treatment group and lowest in the 100-mg/L treatment group), however, the biological significance of the difference is indeterminate.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151051","usgsCitation":"Luoma, J.A., Weber, K.L., Severson, T.J., and Mayer, D., 2015, Efficacy of Pseudomonas fluorescens strain CL145A spray dried powder for controlling zebra mussels adhering to native unionid mussels within field enclosures: U.S. Geological Survey Open-File Report 2015-1051, viii, 302 p., https://doi.org/10.3133/ofr20151051.","productDescription":"viii, 302 p.","numberOfPages":"310","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-064301","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":299266,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20151051.jpg"},{"id":299264,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2015/1051/"},{"id":299265,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1051/pdf/ofr2015-1051.pdf","size":"8.11 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Minnesota","county":"Alexandria","otherGeospatial":"Lake Darling","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -95.38699150085449,\n 45.93131891375231\n ],\n [\n -95.38546800613403,\n 45.93160247365145\n ],\n [\n -95.38422346115112,\n 45.93169201858156\n ],\n [\n -95.38304328918457,\n 45.93152785276592\n ],\n [\n -95.3817343711853,\n 45.9312293682198\n ],\n [\n -95.38059711456299,\n 45.930647318734614\n ],\n [\n -95.37937402725218,\n 45.929975715584696\n ],\n [\n -95.37909507751465,\n 45.9295429003568\n ],\n [\n -95.37868738174438,\n 45.92870710966921\n ],\n [\n -95.37868738174438,\n 45.927617577899674\n ],\n [\n -95.37911653518677,\n 45.92700563971238\n ],\n [\n -95.38003921508788,\n 45.92630414129035\n ],\n [\n -95.38053274154663,\n 45.92611010824568\n ],\n [\n -95.3811764717102,\n 45.92576681735024\n ],\n [\n -95.38190603256226,\n 45.925602633997094\n ],\n [\n -95.38709878921509,\n 45.93133383799366\n ],\n [\n -95.38699150085449,\n 45.93131891375231\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"551e5a1ee4b027f0aee3b875","contributors":{"authors":[{"text":"Luoma, James A. 0000-0003-3556-0190 jluoma@usgs.gov","orcid":"https://orcid.org/0000-0003-3556-0190","contributorId":4449,"corporation":false,"usgs":true,"family":"Luoma","given":"James","email":"jluoma@usgs.gov","middleInitial":"A.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":543881,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Weber, Kerry L. klweber@usgs.gov","contributorId":4750,"corporation":false,"usgs":true,"family":"Weber","given":"Kerry","email":"klweber@usgs.gov","middleInitial":"L.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":543882,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Severson, Todd J. 0000-0001-5282-3779 tseverson@usgs.gov","orcid":"https://orcid.org/0000-0001-5282-3779","contributorId":4749,"corporation":false,"usgs":true,"family":"Severson","given":"Todd","email":"tseverson@usgs.gov","middleInitial":"J.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":543883,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mayer, Denise A.","contributorId":98772,"corporation":false,"usgs":true,"family":"Mayer","given":"Denise A.","affiliations":[],"preferred":false,"id":543884,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ]}