The spread of tamarisk (Tamarix spp., also known as saltcedar) is a significant ecological disturbance in western North America and has long been targeted for control, leading to the importation of the northern tamarisk beetle (Diorhabda carinulata) as a biological control agent. Following its initial release along the Colorado River near Moab, Utah in 2004, the beetle has successfully established and defoliated tamarisk across much of the upper Colorado River Basin. However, the spatial distribution and seasonal timing of defoliation are complex and difficult to quantify over large areas. To address this challenge, we tested and compared two remote sensing approaches to mapping tamarisk defoliation: Disturbance Index (DI) and a decision tree method called Random Forest (RF). Based on multitemporal Landsat 5 TM imagery for 2006-2010, changes in DI and defoliation probability from RF were calculated to detect tamarisk defoliation along the banks of Green, Colorado, Dolores and San Juan rivers within the Colorado Plateau area. Defoliation mapping accuracy was assessed based on field surveys partitioned into 10 km sections of river and on regions of interest created for continuous riparian vegetation. The DI method detected 3711 ha of defoliated area in 2007, 7350 ha in 2008, 10,457 ha in 2009 and 5898 ha in 2010. The RF method detected much smaller areas of defoliation but proved to have higher accuracy, as demonstrated by accuracy assessment and sensitivity analysis, with 784 ha in 2007, 960 ha in 2008, 934 ha in 2009, and 1008 ha in 2010. Results indicate that remote sensing approaches are likely to be useful for studying spatiotemporal patterns of tamarisk defoliation as the tamarisk leaf beetle spreads throughout the western United States.
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In this study, VNIRS (350–2500 nm) was employed to analyze 227 air-dried soil samples of Ultisols from a soil chronosequence in western Kenya and assess 16 SQ indicators. Partial least squares regression (PLSR) was validated using the full-site cross-validation method by grouping samples from each farm or forest site. Most suitable models successfully predicted SQ indicators (R2 ≥ 0.80; ratio of performance to deviation [RPD] ≥ 2.00) including soil organic matter (OMLOI), active C, Ca, cation exchange capacity (CEC), and clay. Moderately-well predicted indicators (0.50 ≤ R2 < 0.80; 1.40 ≤ RPD < 2.00) were water stable aggregation (WSA), Cu, silt, Mg, pH, sand, water content at permanent wilting point (Θpwp), and field capacity (Θfc). Poorly predicted indicators (R2 < 0.50; RPD < 1.40) were EC, S, P, available water capacity (AWC), K, Zn, and penetration resistance. Combining VNIRS with selected field- and laboratory-measured SQ indicator values increased predictability. Furthermore, VNIRS showed moderate to substantial agreement in predicting interpretive SQ scores and a composite soil quality index (CSQI) especially when combined with directly measured SQ indicator values. In conclusion, VNIRS has good potential for low cost, rapid assessment of physical and biological SQ indicators but conventional soil chemical tests may need to be retained to provide comprehensive SQ assessments.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Soil Science Society of America Journal","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Soil Science Society of America","doi":"10.2136/sssaj2011.0307","usgsCitation":"Kinoshita, R., Moebius-Clune, B.N., van Es, H.M., Hively, W., and Bilgilis, A.V., 2012, Strategies for soil quality assessment using VNIR gyperspectral spectroscopy in a western Kenya Chronosequence: Soil Science Society of America Journal, v. 76, no. 5, p. 1776-1788, https://doi.org/10.2136/sssaj2011.0307.","productDescription":"13 p.","startPage":"1776","endPage":"1788","numberOfPages":"13","ipdsId":"IP-033379","costCenters":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"links":[{"id":474097,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2136/sssaj2011.0307","text":"Publisher Index Page"},{"id":272032,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":272030,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.2136/sssaj2011.0307"}],"country":"Kenya","otherGeospatial":"Western Kenya","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 33.91,-4.68 ], [ 33.91,5.05 ], [ 37.51,5.05 ], [ 37.51,-4.68 ], [ 33.91,-4.68 ] ] ] } } ] }","volume":"76","issue":"5","noUsgsAuthors":false,"publicationDate":"2012-09-12","publicationStatus":"PW","scienceBaseUri":"518a1460e4b061e1bd53335b","contributors":{"authors":[{"text":"Kinoshita, Rintaro","contributorId":34800,"corporation":false,"usgs":true,"family":"Kinoshita","given":"Rintaro","email":"","affiliations":[],"preferred":false,"id":477644,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moebius-Clune, Bianca N.","contributorId":62104,"corporation":false,"usgs":true,"family":"Moebius-Clune","given":"Bianca","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":477645,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"van Es, Harold M.","contributorId":97800,"corporation":false,"usgs":true,"family":"van Es","given":"Harold","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":477646,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hively, W. 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Our perception is that interested members of the public and some managers believe that harvest influences North American duck populations based on calls for more conservative harvest regulations. A recent review of harvest and population dynamics of North American mallard (Anas platyrhynchos) populations (Pöysä et al. 2004) reached similar conclusions. Because of the importance of this issue, we reviewed the evidence for an impact of harvest on duck populations. Our understanding of the effects of harvest is limited because harvest effects are typically confounded with those of population density; regulations are typically most liberal when populations are greatest. This problem also exists in the current Adaptive Harvest Management Program (Conn and Kendall 2004). Consequently, even where harvest appears additive to other mortality, this may be an artifact of ignoring effects of population density. 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We undertook a novel cross-basin comparison of trophic position in two ecologically well-characterized and different groups of dominant mid-water fish consumers using amino acid nitrogen isotope compositions. We found that trophic positions estimated from the δ15N values of individual amino acids are nearly uniform within both families of these fishes across five global regions despite great variability in bulk tissue δ15N values. Regional differences in the δ15N values of phenylalanine confirmed that bulk tissue δ15N values reflect region-specific water mass biogeochemistry controlling δ15N values at the base of the food web. Trophic positions calculated from amino acid isotopic analyses (AA-TP) for lanternfishes (family Myctophidae) (AA-TP ~2.9) largely align with expectations from stomach content studies (TP ~3.2), while AA-TPs for dragonfishes (family Stomiidae) (AA-TP ~3.2) were lower than TPs derived from stomach content studies (TP~4.1). 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This report contains geophysical data collected by the USGS on three cruises conducted in 2009, 2010, and 2011, and additional bathymetry data collected by the National Oceanic and Atmospheric Administration in 2004. The geophysical data include (1) swath bathymetry using interferometric sonar and multibeam echosounder systems, (2) acoustic backscatter from sidescan sonar, and (3) seismic-reflection profiles from a chirp subbottom profiler. 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assessment algorithms","docAbstract":"The upcoming launch of the Operational Land Imager (OLI) will start the next era of the Landsat program. However, the Automated Cloud-Cover Assessment (CCA) (ACCA) algorithm used on Landsat 7 requires a thermal band and is thus not suited for OLI. There will be a thermal instrument on the Landsat Data Continuity Mission (LDCM)-the Thermal Infrared Sensor-which may not be available during all OLI collections. This illustrates a need for CCA for LDCM in the absence of thermal data. To research possibilities for full-resolution OLI cloud assessment, a global data set of 207 Landsat 7 scenes with manually generated cloud masks was created. It was used to evaluate the ACCA algorithm, showing that the algorithm correctly classified 79.9% of a standard test subset of 3.95 109 pixels. The data set was also used to develop and validate two successor algorithms for use with OLI data-one derived from an off-the-shelf machine learning package and one based on ACCA but enhanced by a simple neural network. These comprehensive CCA algorithms were shown to correctly classify pixels as cloudy or clear 88.5% and 89.7% of the time, respectively.","language":"English","publisher":"Institute of Electrical and Electronics Engineers","doi":"10.1109/TGRS.2011.2164087","usgsCitation":"Scaramuzza, P., Bouchard, M., and Dwyer, J.L., 2012, Development of the Landsat Data Continuity Mission cloud-cover assessment algorithms: IEEE Transactions on Geoscience and Remote Sensing, v. 50, no. 4, p. 1140-1154, https://doi.org/10.1109/TGRS.2011.2164087.","productDescription":"15 p.","startPage":"1140","endPage":"1154","ipdsId":"IP-020443","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":270623,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"50","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5180d9d9e4b0df838b924d29","contributors":{"authors":[{"text":"Scaramuzza, Pat 0000-0002-2616-8456 pscar@usgs.gov","orcid":"https://orcid.org/0000-0002-2616-8456","contributorId":3970,"corporation":false,"usgs":true,"family":"Scaramuzza","given":"Pat","email":"pscar@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":473298,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bouchard, M.A. 0000-0002-6353-3491","orcid":"https://orcid.org/0000-0002-6353-3491","contributorId":13023,"corporation":false,"usgs":true,"family":"Bouchard","given":"M.A.","affiliations":[],"preferred":false,"id":473300,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dwyer, John L. 0000-0002-8281-0896","orcid":"https://orcid.org/0000-0002-8281-0896","contributorId":6136,"corporation":false,"usgs":true,"family":"Dwyer","given":"John","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":473299,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70045696,"text":"ds739 - 2012 - Bathymetry and acoustic backscatter data collected in 2010 from Cat Island, Mississippi","interactions":[],"lastModifiedDate":"2013-04-30T08:48:15","indexId":"ds739","displayToPublicDate":"2013-04-22T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"739","title":"Bathymetry and acoustic backscatter data collected in 2010 from Cat Island, Mississippi","docAbstract":"Scientists from the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center (SPCMSC), in collaboration with the U.S. Army Corps of Engineers (USACE), conducted geophysical and sedimentological surveys around Cat Island, the westernmost island in the Mississippi-Alabama barrier island chain (fig. 1). The objectives of the study were to understand the geologic evolution of Cat Island relative to other barrier islands in the northern Gulf of Mexico and to identify relationships between the geologic history, present day morphology, and sediment distribution. This report contains data from the bathymetry and side-scan sonar portion of the study collected during two geophysical cruises. Interferometric swath bathymetry and side-scan sonar data were collected aboard the RV G.K. Gilbert September 7-15, 2010. Single-beam bathymetry was collected in shallow water around the island (< 2 meter (m)) from the RV Streeterville from September 28 to October 2, 2010, to cover the data gap between the landward limit of the previous cruise and the shoreline. This report serves as an archive of processed interferometric swath and single-beam bathymetry and side scan sonar data. GIS data products include a 50-m cell size interpolated gridded bathymetry surface, trackline maps, and an acoustic side-scan sonar image. Additional files include error analysis maps, Field Activity Collection System (FACS) logs, and formal Federal Geographic Data Committee (FDGC) metadata.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds739","usgsCitation":"Buster, N.A., Pfeiffer, W.R., Miselis, J.L., Kindinger, J.L., Wiese, D.S., and Reynolds, B., 2012, Bathymetry and acoustic backscatter data collected in 2010 from Cat Island, Mississippi: U.S. Geological Survey Data Series 739, HTML Document: Abstract; Introduction; Survey Overview; Data Acquisition; Data Processing; Error Analysis; Survey Products; Data Downloads; Logs; Acronyms; Acknowledgements; References, https://doi.org/10.3133/ds739.","productDescription":"HTML Document: Abstract; Introduction; Survey Overview; Data Acquisition; Data Processing; Error Analysis; Survey Products; Data Downloads; Logs; Acronyms; Acknowledgements; References","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":271622,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":271621,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/739/index.html"}],"country":"United States","state":"Alabama;Mississippi","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -89.25,30.15 ], [ -89.25,30.3 ], [ -89,30.3 ], [ -89,30.15 ], [ -89.25,30.15 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5180e7e4e4b0df838b924d55","contributors":{"authors":[{"text":"Buster, Noreen A. 0000-0001-5069-9284 nbuster@usgs.gov","orcid":"https://orcid.org/0000-0001-5069-9284","contributorId":3750,"corporation":false,"usgs":true,"family":"Buster","given":"Noreen","email":"nbuster@usgs.gov","middleInitial":"A.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":478064,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pfeiffer, William R. wpfeiffer@usgs.gov","contributorId":3725,"corporation":false,"usgs":true,"family":"Pfeiffer","given":"William","email":"wpfeiffer@usgs.gov","middleInitial":"R.","affiliations":[],"preferred":true,"id":478063,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miselis, Jennifer L. 0000-0002-4925-3979 jmiselis@usgs.gov","orcid":"https://orcid.org/0000-0002-4925-3979","contributorId":3914,"corporation":false,"usgs":true,"family":"Miselis","given":"Jennifer","email":"jmiselis@usgs.gov","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":478065,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kindinger, Jack L. jkindinger@usgs.gov","contributorId":815,"corporation":false,"usgs":true,"family":"Kindinger","given":"Jack","email":"jkindinger@usgs.gov","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":478061,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wiese, Dana S. dwiese@usgs.gov","contributorId":2476,"corporation":false,"usgs":true,"family":"Wiese","given":"Dana","email":"dwiese@usgs.gov","middleInitial":"S.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":478062,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Reynolds, B.J.","contributorId":47874,"corporation":false,"usgs":true,"family":"Reynolds","given":"B.J.","email":"","affiliations":[],"preferred":false,"id":478066,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70045154,"text":"70045154 - 2012 - Credible occurrence probabilities for extreme geophysical events: earthquakes, volcanic eruptions, magnetic storms","interactions":[],"lastModifiedDate":"2013-05-06T10:36:12","indexId":"70045154","displayToPublicDate":"2013-04-22T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Credible occurrence probabilities for extreme geophysical events: earthquakes, volcanic eruptions, magnetic storms","docAbstract":"Statistical analysis is made of rare, extreme geophysical events recorded in historical data -- counting the number of events $k$ with sizes that exceed chosen thresholds during specific durations of time $\\tau$. Under transformations that stabilize data and model-parameter variances, the most likely Poisson-event occurrence rate, $k/\\tau$, applies for frequentist inference and, also, for Bayesian inference with a Jeffreys prior that ensures posterior invariance under changes of variables. Frequentist confidence intervals and Bayesian (Jeffreys) credibility intervals are approximately the same and easy to calculate: $(1/\\tau)[(\\sqrt{k} - z/2)^{2},(\\sqrt{k} + z/2)^{2}]$, where $z$ is a parameter that specifies the width, $z=1$ ($z=2$) corresponding to $1\\sigma$, $68.3\\%$ ($2\\sigma$, $95.4\\%$). If only a few events have been observed, as is usually the case for extreme events, then these \"error-bar\" intervals might be considered to be relatively wide. From historical records, we estimate most likely long-term occurrence rates, 10-yr occurrence probabilities, and intervals of frequentist confidence and Bayesian credibility for large earthquakes, explosive volcanic eruptions, and magnetic storms.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Geophysical Research Letters","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"AGU","publisherLocation":"Washington, D.C.","doi":"10.1029/2012GL051431","usgsCitation":"Love, J.J., 2012, Credible occurrence probabilities for extreme geophysical events: earthquakes, volcanic eruptions, magnetic storms: Geophysical Research Letters, v. 39, no. 10, L10301, https://doi.org/10.1029/2012GL051431.","productDescription":"L10301","ipdsId":"IP-037733","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":474100,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2012gl051431","text":"Publisher Index Page"},{"id":271365,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":271364,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1029/2012GL051431"}],"volume":"39","issue":"10","noUsgsAuthors":false,"publicationDate":"2012-05-18","publicationStatus":"PW","scienceBaseUri":"51764ddbe4b0f989f99e008e","contributors":{"authors":[{"text":"Love, Jeffrey J. 0000-0002-3324-0348 jlove@usgs.gov","orcid":"https://orcid.org/0000-0002-3324-0348","contributorId":760,"corporation":false,"usgs":true,"family":"Love","given":"Jeffrey","email":"jlove@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":476944,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70045472,"text":"ofr20121263 - 2012 - Monitoring storm tide and flooding from Hurricane Isaac along the Gulf Coast of the United States, August 2012","interactions":[],"lastModifiedDate":"2017-02-03T12:14:22","indexId":"ofr20121263","displayToPublicDate":"2013-04-19T00:00:00","publicationYear":"2012","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":"2012-1263","title":"Monitoring storm tide and flooding from Hurricane Isaac along the Gulf Coast of the United States, August 2012","docAbstract":"The U.S. Geological Survey (USGS) deployed a temporary monitoring network of water-level and barometric pressure sensors at 127 locations along the gulf coast from Alabama to Louisiana to record the timing, areal extent, and magnitude of hurricane storm tide and coastal flooding generated by Hurricane Isaac. This deployment was undertaken as part of a coordinated federal emergency response as outlined by the Stafford Act under a directed mission assignment by the Federal Emergency Management Agency. Storm tide, as defined by National Oceanic and Atmospheric Administration (NOAA; National Oceanic and Atmospheric Administration, 2008), is the water-level rise generated by a combination of storm surge and astronomical tide during a coastal storm. Hurricane Isaac initially made landfall on the coast of Louisiana in Plaquemines Parish on August 28, 2012, as a Category 1 hurricane on the Saffir–Simpson Hurricane Wind Scale (National Weather Service, 1974) and then stalled over southern Louisiana for several days, causing prolonged storm-tide impacts. A total of 188 water-level and wave-height sensors were deployed at 127 locations during August 27–28 prior to landfall. More than 90 percent of the sensors and all high-water marks (HWMs) were recovered and surveyed to North American Vertical Datum of 1988 (NAVD 88) within 7 days of the Isaac landfall. Only a handful of sensors in the Plaquemines Parish area of Louisiana could not be retrieved until weeks later due to prolonged flooding in the area. Data collected from this event can be used to evaluate the performance of storm-tide models for maximum and incremental water level and flood extent and the site-specific effects of storm tide on natural and anthropogenic features of the environment.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121263","collaboration":"Prepared under a mission assignment with the Federal Emergency Management Agency","usgsCitation":"McCallum, B.E., McGee, B.D., Kimbrow, D.R., Runner, M.S., Painter, J.A., Frantz, E.R., and Gotvald, A.J., 2012, Monitoring storm tide and flooding from Hurricane Isaac along the Gulf Coast of the United States, August 2012: U.S. Geological Survey Open-File Report 2012-1263, Report: ii, 26 p.; 6 Tables, https://doi.org/10.3133/ofr20121263.","productDescription":"Report: ii, 26 p.; 6 Tables","numberOfPages":"30","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-042625","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":271140,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20121263.JPG"},{"id":271126,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1263/"},{"id":271129,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1263/pdf/ofr2012-1263.pdf","text":"Report"},{"id":271131,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2012/1263/downloads/Table1-Isaac.xlsx","text":"Table 1 - Number of monitoring sites, by state"},{"id":271133,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2012/1263/downloads/Table2-Isaac.xlsx","text":"Table 2 - GNSS/NGS elevation differences"},{"id":271134,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2012/1263/downloads/Table3-Isaac.xlsx","text":"Table 3 - Storm tides-temporary sites"},{"id":271136,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2012/1263/downloads/Table5-Isaac.xlsx","text":"Table 5 - Storm tides-NOAA sites"},{"id":271137,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2012/1263/downloads/Table6-Isaac.xlsx","text":"Table 6 - High-water marks"},{"id":271135,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2012/1263/downloads/Table4-Isaac.xlsx","text":"Table 4 - Storm tides-USGS sites"}],"country":"United States","state":"Alabama, Louisiana, Mississippi","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.28515625,\n 28.719496107557465\n ],\n [\n -92.28515625,\n 30.883369321692268\n ],\n [\n -87.286376953125,\n 30.883369321692268\n ],\n [\n -87.286376953125,\n 28.719496107557465\n ],\n [\n -92.28515625,\n 28.719496107557465\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5172595ce4b0c173799e78ea","contributors":{"authors":[{"text":"McCallum, Brian E. 0000-0002-8935-0343 bemccall@usgs.gov","orcid":"https://orcid.org/0000-0002-8935-0343","contributorId":1591,"corporation":false,"usgs":true,"family":"McCallum","given":"Brian","email":"bemccall@usgs.gov","middleInitial":"E.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":477581,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McGee, Benton D. bdmcgee@usgs.gov","contributorId":2899,"corporation":false,"usgs":true,"family":"McGee","given":"Benton","email":"bdmcgee@usgs.gov","middleInitial":"D.","affiliations":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":477583,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kimbrow, Dustin R. dkimbrow@usgs.gov","contributorId":3915,"corporation":false,"usgs":true,"family":"Kimbrow","given":"Dustin","email":"dkimbrow@usgs.gov","middleInitial":"R.","affiliations":[{"id":105,"text":"Alabama Water Science Center","active":true,"usgs":true}],"preferred":true,"id":477585,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Runner, Michael S. msrunner@usgs.gov","contributorId":3497,"corporation":false,"usgs":true,"family":"Runner","given":"Michael","email":"msrunner@usgs.gov","middleInitial":"S.","affiliations":[],"preferred":true,"id":477584,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Painter, Jaime A. 0000-0001-8883-9158 jpainter@usgs.gov","orcid":"https://orcid.org/0000-0001-8883-9158","contributorId":1466,"corporation":false,"usgs":true,"family":"Painter","given":"Jaime","email":"jpainter@usgs.gov","middleInitial":"A.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":477580,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Frantz, Eric R. 0000-0002-1867-886X efrantz@usgs.gov","orcid":"https://orcid.org/0000-0002-1867-886X","contributorId":41573,"corporation":false,"usgs":true,"family":"Frantz","given":"Eric","email":"efrantz@usgs.gov","middleInitial":"R.","affiliations":[],"preferred":false,"id":477586,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gotvald, Anthony J. 0000-0002-9019-750X agotvald@usgs.gov","orcid":"https://orcid.org/0000-0002-9019-750X","contributorId":1970,"corporation":false,"usgs":true,"family":"Gotvald","given":"Anthony","email":"agotvald@usgs.gov","middleInitial":"J.","affiliations":[{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":477582,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70045036,"text":"70045036 - 2012 - Expansion of an exotic species and concomitant disease outbreaks: Pigeon paramyxovirus in free-ranging Eurasian collared doves","interactions":[],"lastModifiedDate":"2023-10-23T10:52:33.080799","indexId":"70045036","displayToPublicDate":"2013-04-16T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1443,"text":"EcoHealth","active":true,"publicationSubtype":{"id":10}},"title":"Expansion of an exotic species and concomitant disease outbreaks: Pigeon paramyxovirus in free-ranging Eurasian collared doves","docAbstract":"Eurasian collared doves (Streptopelia decaocto) have expanded their range across the United States since their introduction several decades ago. Recent mortality events in Eurasian collared doves in Arizona and Montana, USA, during the winter of 2009–2010 were the result of pigeon paramyxovirus (PPMV), a novel disease agent. The first instance of mortality by this emerging infectious disease in this species occurred in Florida in 2001 with subsequent disease events in 2006 and 2008. Full diagnostic necropsies were performed on carcasses from the three states. PPMV was identified by RT-PCR and virus isolation and was sequenced to the VIb genotype of avian paramyxovirus-1 (APMV). Other APMVs are common in a variety of free-ranging birds, but concern is warranted because of the potential for commingling of this species with native birds, virus evolution, and threats to domestic poultry. Improved surveillance for wildlife mortality events and efforts to prevent introduction of non-native animals could reduce the threat of introducing new pathogens.
A bacilliform virus was isolated from diseased fathead minnows (Pimephales promelas). Analysis of the complete genome coding for the polyprotein (pp1ab), spike (S), membrane (M) and nucleocapsid (N) proteins revealed that the virus was most like white bream virus (WBV), another bacilliform virus isolated from white bream (Blicca bjoerkna L.) and the type species of the genus Bafinivirus within the order Nidovirales. In addition to similar gene order and size, alignment of deduced amino acid sequences of the pp1ab, M, N and S proteins of the fathead minnow nidovirus (FHMNV) with those of WBV showed 46, 44, 39 and 15 % identities, respectively. Phylogenetic analysis using the conserved helicase domain of the replicase showed FHMNV was distinct from WBV, yet the closest relative identified to date. Thus, FHMNV appears to represent a second species in the genus Bafinivirus. A PCR assay was developed for the identification of future FHMNV-like isolates.
","language":"English","publisher":"Society for General Microbiology","doi":"10.1099/vir.0.041210-0","usgsCitation":"Batts, W.N., Goodwin, A., and Winton, J.R., 2012, Genetic analysis of a novel nidovirus from fathead minnows: Journal of General Virology, v. 93, no. 6, p. 1247-1252, https://doi.org/10.1099/vir.0.041210-0.","productDescription":"6 p.","startPage":"1247","endPage":"1252","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-019989","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":474102,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1099/vir.0.041210-0","text":"Publisher Index Page"},{"id":270437,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"93","issue":"6","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"515a9e5fe4b0105540728a22","contributors":{"authors":[{"text":"Batts, William N. 0000-0002-6469-9004 bbatts@usgs.gov","orcid":"https://orcid.org/0000-0002-6469-9004","contributorId":3815,"corporation":false,"usgs":true,"family":"Batts","given":"William","email":"bbatts@usgs.gov","middleInitial":"N.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":474517,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Goodwin, Andrew E.","contributorId":99848,"corporation":false,"usgs":true,"family":"Goodwin","given":"Andrew E.","affiliations":[],"preferred":false,"id":474518,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Winton, James R. 0000-0002-3505-5509 jwinton@usgs.gov","orcid":"https://orcid.org/0000-0002-3505-5509","contributorId":1944,"corporation":false,"usgs":true,"family":"Winton","given":"James","email":"jwinton@usgs.gov","middleInitial":"R.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":false,"id":474516,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70043062,"text":"70043062 - 2012 - GeoChip-based analysis of microbial functional gene diversity in a landfill leachate-contaminated aquifer","interactions":[],"lastModifiedDate":"2013-04-01T22:08:49","indexId":"70043062","displayToPublicDate":"2013-04-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"GeoChip-based analysis of microbial functional gene diversity in a landfill leachate-contaminated aquifer","docAbstract":"The functional gene diversity and structure of microbial communities in a shallow landfill leachate-contaminated aquifer were assessed using a comprehensive functional gene array (GeoChip 3.0). Water samples were obtained from eight wells at the same aquifer depth immediately below a municipal landfill or along the predominant downgradient groundwater flowpath. Functional gene richness and diversity immediately below the landfill and the closest well were considerably lower than those in downgradient wells. Mantel tests and canonical correspondence analysis (CCA) suggested that various geochemical parameters had a significant impact on the subsurface microbial community structure. That is, leachate from the unlined landfill impacted the diversity, composition, structure, and functional potential of groundwater microbial communities as a function of groundwater pH, and concentrations of sulfate, ammonia, and dissolved organic carbon (DOC). Historical geochemical records indicate that all sampled wells chronically received leachate, and the increase in microbial diversity as a function of distance from the landfill is consistent with mitigation of the impact of leachate on the groundwater system by natural attenuation mechanisms.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Environmental Science and Technology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Chemical Society","publisherLocation":"Washington, D.C.","doi":"10.1021/es300478j","usgsCitation":"Lu, Z., He, Z., Parisi, V.A., Kang, S., Deng, Y., Van Nostrand, J.D., Masoner, J.R., Cozzarelli, I.M., Suflita, J.M., and Zhou, J., 2012, GeoChip-based analysis of microbial functional gene diversity in a landfill leachate-contaminated aquifer: Environmental Science & Technology, v. 46, no. 11, p. 5824-5833, https://doi.org/10.1021/es300478j.","productDescription":"10 p.","startPage":"5824","endPage":"5833","ipdsId":"IP-035013","costCenters":[{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true}],"links":[{"id":270439,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":270438,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1021/es300478j"}],"country":"United States","state":"Oklahoma","county":"Cleveland","city":"Norman","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -97.57,35.0 ], [ -97.57,35.38 ], [ -97.1,35.38 ], [ -97.1,35.0 ], [ -97.57,35.0 ] ] ] } } ] }","volume":"46","issue":"11","noUsgsAuthors":false,"publicationDate":"2012-05-23","publicationStatus":"PW","scienceBaseUri":"515a9e60e4b0105540728a26","contributors":{"authors":[{"text":"Lu, Zhenmei","contributorId":9931,"corporation":false,"usgs":true,"family":"Lu","given":"Zhenmei","email":"","affiliations":[],"preferred":false,"id":472890,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"He, Zhili","contributorId":9145,"corporation":false,"usgs":true,"family":"He","given":"Zhili","email":"","affiliations":[],"preferred":false,"id":472889,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Parisi, Victoria A.","contributorId":55706,"corporation":false,"usgs":true,"family":"Parisi","given":"Victoria","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":472892,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kang, Sanghoon","contributorId":60096,"corporation":false,"usgs":true,"family":"Kang","given":"Sanghoon","email":"","affiliations":[],"preferred":false,"id":472893,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Deng, Ye","contributorId":92133,"corporation":false,"usgs":true,"family":"Deng","given":"Ye","email":"","affiliations":[],"preferred":false,"id":472896,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Van Nostrand, Joy D.","contributorId":62485,"corporation":false,"usgs":true,"family":"Van Nostrand","given":"Joy","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":472894,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Masoner, Jason R. 0000-0002-4829-6379 jmasoner@usgs.gov","orcid":"https://orcid.org/0000-0002-4829-6379","contributorId":3193,"corporation":false,"usgs":true,"family":"Masoner","given":"Jason","email":"jmasoner@usgs.gov","middleInitial":"R.","affiliations":[{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":472888,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Cozzarelli, Isabelle M. 0000-0002-5123-1007 icozzare@usgs.gov","orcid":"https://orcid.org/0000-0002-5123-1007","contributorId":1693,"corporation":false,"usgs":true,"family":"Cozzarelli","given":"Isabelle","email":"icozzare@usgs.gov","middleInitial":"M.","affiliations":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":472887,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Suflita, Joseph M.","contributorId":82997,"corporation":false,"usgs":true,"family":"Suflita","given":"Joseph","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":472895,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Zhou, Jizhong","contributorId":26594,"corporation":false,"usgs":true,"family":"Zhou","given":"Jizhong","email":"","affiliations":[],"preferred":false,"id":472891,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70043571,"text":"70043571 - 2012 - Transcriptional profiling of the parr–smolt transformation in Atlantic salmon","interactions":[],"lastModifiedDate":"2017-05-06T16:15:31","indexId":"70043571","displayToPublicDate":"2013-03-26T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1290,"text":"Comparative Biochemistry and Physiology, Part D: Genomics and Proteomics","active":true,"publicationSubtype":{"id":10}},"title":"Transcriptional profiling of the parr–smolt transformation in Atlantic salmon","docAbstract":"The parr–smolt transformation in Atlantic salmon (Salmo salar) is a complex developmental process that culminates in the ability to migrate to and live in seawater. We used GRASP 16K cDNA microarrays to identify genes that are differentially expressed in the liver, gill, hypothalamus, pituitary, and olfactory rosettes of smolts compared to parr. Smolts had higher levels of gill Na+/K+-ATPase activity, plasma cortisol and plasma thyroid hormones relative to parr. Across all five tissues, stringent microarray analyses identified 48 features that were differentially expressed in smolts compared to parr. Using a less stringent method we found 477 features that were differentially expressed at least 1.2-fold in smolts, including 172 features in the gill. Smolts had higher mRNA levels of genes involved in transcription, protein biosynthesis and folding, electron transport, oxygen transport, and sensory perception and lower mRNA levels for genes involved in proteolysis. Quantitative RT-PCR was used to confirm differential expression in select genes identified by microarray analyses and to quantify expression of other genes known to be involved in smolting. This study expands our understanding of the molecular processes that underlie smolting in Atlantic salmon and identifies genes for further investigation.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.cbd.2012.07.003","usgsCitation":"Robertson, L.S., and McCormick, S., 2012, Transcriptional profiling of the parr–smolt transformation in Atlantic salmon: Comparative Biochemistry and Physiology, Part D: Genomics and Proteomics, v. 7, no. 4, p. 351-360, https://doi.org/10.1016/j.cbd.2012.07.003.","productDescription":"10 p.","startPage":"351","endPage":"360","ipdsId":"IP-038773","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":474103,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.419.4332","text":"External Repository"},{"id":270212,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5152b565e4b01197b08e9bed","contributors":{"authors":[{"text":"Robertson, Laura S. lrobertson@usgs.gov","contributorId":2288,"corporation":false,"usgs":true,"family":"Robertson","given":"Laura","email":"lrobertson@usgs.gov","middleInitial":"S.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":473859,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCormick, Stephen D. 0000-0003-0621-6200 smccormick@usgs.gov","orcid":"https://orcid.org/0000-0003-0621-6200","contributorId":39666,"corporation":false,"usgs":true,"family":"McCormick","given":"Stephen D.","email":"smccormick@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":473860,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70043555,"text":"70043555 - 2012 - Carbon dioxide stripping in aquaculture -- part II: development of gas transfer models","interactions":[],"lastModifiedDate":"2013-03-25T15:46:16","indexId":"70043555","displayToPublicDate":"2013-03-25T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":852,"text":"Aquacultural Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Carbon dioxide stripping in aquaculture -- part II: development of gas transfer models","docAbstract":"The basic mass transfer equation for gases such as oxygen and carbon dioxide can be derived from integration of the driving force equation. Because of the physical characteristics of the gas transfer processes, slightly different models are used for aerators tested under the non steady-state procedures, than for packed columns, or weirs. It is suggested that the standard condition for carbon dioxide should be 20 °C, 1 atm, CCO2=20 mg/kg, and XCO2=0.000285. The selection of the standard condition for carbon dioxide based on a fixed mole fraction ensures that standardized carbon dioxide transfer rates will be comparable even though the value of C*CO2 in the atmosphere is increasing with time. The computation of mass transfer for carbon dioxide is complicated by the impact of water depth and gas phase enrichment on the saturation concentration within the unit, although the importance of either factor depends strongly on the specific type of aerator. For some types of aerators, the most accurate gas phase model remains to be determined for carbon dioxide. The assumption that carbon dioxide can be treated as a non-reactive gas in packed columns may apply for cold acidic waters but not for warm alkaline waters.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Aquacultural Engineering","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.aquaeng.2011.12.002","usgsCitation":"Colt, J., Watten, B., and Pfeiffer, T., 2012, Carbon dioxide stripping in aquaculture -- part II: development of gas transfer models: Aquacultural Engineering, v. 47, p. 38-46, https://doi.org/10.1016/j.aquaeng.2011.12.002.","productDescription":"9 p.","startPage":"38","endPage":"46","ipdsId":"IP-036709","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":270027,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":270026,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.aquaeng.2011.12.002"}],"volume":"47","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"515163dce4b087909f0bbe2f","contributors":{"authors":[{"text":"Colt, John","contributorId":63695,"corporation":false,"usgs":true,"family":"Colt","given":"John","email":"","affiliations":[],"preferred":false,"id":473825,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Watten, Barnaby 0000-0002-2227-8623","orcid":"https://orcid.org/0000-0002-2227-8623","contributorId":97788,"corporation":false,"usgs":true,"family":"Watten","given":"Barnaby","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":473826,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pfeiffer, Tim","contributorId":34792,"corporation":false,"usgs":true,"family":"Pfeiffer","given":"Tim","email":"","affiliations":[],"preferred":false,"id":473824,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70042531,"text":"70042531 - 2012 - Influence of water temperature on rainbow smelt spawning and early life history dynamics in St. Martin Bay, Lake Huron","interactions":[],"lastModifiedDate":"2013-03-25T16:18:32","indexId":"70042531","displayToPublicDate":"2013-03-25T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Influence of water temperature on rainbow smelt spawning and early life history dynamics in St. Martin Bay, Lake Huron","docAbstract":"Rainbow smelt are an important prey species for native and introduced salmonines in the Great Lakes. In Lake Huron, rainbow smelt populations are characterized by variable recruitment and year-class strength. To understand the influence of water temperature on reproduction, growth, and survival during larval-fish stages, we sampled spawning tributaries and larval-fish habitats during 2008 and 2009 in St. Martin Bay, Lake Huron. Spawning by rainbow smelt occurred primarily when stream temperatures were between 3 and 10 °C, which resulted in a 7–10-day spawning period during 2008, and a 15–20-day spawning period during 2009. Regardless of these differences in spawning temperatures and duration, peak larval-fish densities during 2008 were double those observed during 2009. Length–frequency analysis of larval-fish populations during both years revealed stream-hatched fish during May and a later emergence of larval rainbow smelt during summer, presumably originating from lake spawning. Warmer bay water temperatures led to earlier emergence of lake-spawned rainbow smelt larvae during 2009. Stream-hatched fish larvae experienced large-scale mortality during May 2008 resulting in a bay population consisting primarily of lake-spawned rainbow smelt larvae, but during 2009 both stream- and lake-hatched cohorts experienced higher survival concomitant with significantly higher mean population growth rates. Higher larval-fish growth rates during 2009 appeared to be density-dependent and facilitated by warmer water temperatures during late June and cooler water temperatures during July. Temperature-mediated differences in annual growth rates and irregular contributions from stream- and lake-hatched fish larvae are important factors affecting survival and abundance of young-of-the-year rainbow smelt in Lake Huron.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Great Lakes Research","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.jglr.2012.09.017","usgsCitation":"O’Brien, T.P., Taylor, W., Briggs, A., and Roseman, E., 2012, Influence of water temperature on rainbow smelt spawning and early life history dynamics in St. Martin Bay, Lake Huron: Journal of Great Lakes Research, v. 38, no. 4, p. 776-785, https://doi.org/10.1016/j.jglr.2012.09.017.","productDescription":"10 p.","startPage":"776","endPage":"785","ipdsId":"IP-041203","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":270037,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":270036,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.jglr.2012.09.017"}],"country":"United States","state":"Michigan","otherGeospatial":"St. Martin Bay","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -84.69958,45.950468 ], [ -84.69958,46.049267 ], [ -84.538156,46.049267 ], [ -84.538156,45.950468 ], [ -84.69958,45.950468 ] ] ] } } ] }","volume":"38","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"515163e3e4b087909f0bbe43","contributors":{"authors":[{"text":"O’Brien, Timothy P. 0000-0003-4502-5204 tiobrien@usgs.gov","orcid":"https://orcid.org/0000-0003-4502-5204","contributorId":2662,"corporation":false,"usgs":true,"family":"O’Brien","given":"Timothy","email":"tiobrien@usgs.gov","middleInitial":"P.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":471711,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Taylor, William W.","contributorId":49735,"corporation":false,"usgs":false,"family":"Taylor","given":"William W.","affiliations":[],"preferred":false,"id":471713,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Briggs, Andrew S.","contributorId":32796,"corporation":false,"usgs":true,"family":"Briggs","given":"Andrew S.","affiliations":[],"preferred":false,"id":471712,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Roseman, Edward F.","contributorId":100334,"corporation":false,"usgs":true,"family":"Roseman","given":"Edward F.","affiliations":[],"preferred":false,"id":471714,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70142795,"text":"70142795 - 2012 - Status and trends in the fish community of Lake Superior, 2012","interactions":[],"lastModifiedDate":"2017-04-24T13:03:42","indexId":"70142795","displayToPublicDate":"2013-03-20T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":9,"text":"Other Report"},"title":"Status and trends in the fish community of Lake Superior, 2012","docAbstract":"The Great Lakes Science Center has conducted daytime nearshore bottom trawl surveys of Lake Superior (15-80 m bathymetric depth zone) each spring since 1978 and an offshore survey (>80 m) since 2011 to provide long-term trends of relative abundance and biomass of the fish community. In 2012, 72 nearshore and 34 offshore stations were sampled with a 12-m Yankee bottom trawl.
\nThe 2012 estimate of lake-wide nearshore fish community biomass was 1.14 kg/ha, second lowest in the 35-year survey history, down from 3.63 kg/ha observed in the 2011 survey. Dominant species in the catch, in order of relative biomass, were bloater, rainbow smelt, lake whitefish, pygmy whitefish, and shortjaw cisco. Compared to 2011 levels, biomass of all species decreased. Year-class strengths for the 2011 cisco and bloater cohorts were well below average and ranked as the second weakest year-classes in the past 35 years. Year-class strength of rainbow smelt was the weakest in the survey record, continuing a decline that began in 2008. As in 2011, densities of hatchery lake trout remained near zero in 2012, while densities of wild (lean) lake trout and siscowet lake trout decreased. Proportions of total lake trout density in 2012 that were hatchery, wild, and siscowet were 5, 74, and 21%, respectively.
\nThe 2012 estimate of lake-wide offshore fish community biomass was 6.9 kg/ha, down from 9.0 kg/ha in 2011. Deepwater sculpin, kiyi, and siscowet lake trout represented 98% of the fish caught in terms of both density and biomass. Community composition, number of species collected and densities and biomass for most species were similar to that observed in 2011.
\nDue to ship mechanical failures, nearshore sampling was delayed from mid-May to mid-June to mid-June to late August. The shift to summer sampling when the lake was stratified may have affected our estimates, thus our estimates of status and trends for the nearshore fish community in 2012 are tentative, pending results of future surveys. However, the results of the 2012 survey are comparable with those during 2009 and 2010 when lake-wide fish biomass declined to < 1.40 kg/ha. Declines in prey fish biomass since the late 1990s can be attributed to a combination of increased predation by recovered lake trout populations and infrequent and weak recruitment by the principal prey fishes, cisco and bloater. In turn declines in lake trout biomass since the mid-2000s are likely linked to declines in prey fish biomass. If lean and siscowet lake trout populations in nearshore waters continue to remain at current levels, predation mortality will likely maintain the relatively low prey fish biomass observed in recent years. Alternatively, if lake trout populations show a substantial decline in abundance in upcoming years, prey fish populations may rebound in a fashion reminiscent to what occurred in the late 1970s to mid-1980s. However, this scenario depends on substantial increases in harvest of lake trout, which seems unlikely given that levels of lake trout harvest have been flat or declining in many regions of Lake Superior since 2000.
","conferenceTitle":"Great Lakes Fishery Commission, Lake Superior Committee Meeting","conferenceDate":"March 20, 2013","conferenceLocation":"Duluth, MN","language":"English","usgsCitation":"Gorman, O.T., Evrard, L.M., Cholwek, G.A., and Vinson, M., 2012, Status and trends in the fish community of Lake Superior, 2012, 13 p.","productDescription":"13 p.","numberOfPages":"13","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-044797","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":300312,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":300311,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://www.glsc.usgs.gov/sites/default/files/product_files/2012LakeSuperiorPreyfish.pdf","size":"344.34 KB"}],"country":"Canada, United States","otherGeospatial":"Lake Superior","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n 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gcholwek@usgs.gov","contributorId":2719,"corporation":false,"usgs":true,"family":"Cholwek","given":"Gary","email":"gcholwek@usgs.gov","middleInitial":"A.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":542171,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vinson, Mark R. 0000-0001-5256-9539 mvinson@usgs.gov","orcid":"https://orcid.org/0000-0001-5256-9539","contributorId":3800,"corporation":false,"usgs":true,"family":"Vinson","given":"Mark","email":"mvinson@usgs.gov","middleInitial":"R.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":542173,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70044632,"text":"ds744 - 2012 - Summary of suspended-sediment concentration data, San Francisco Bay, California, water year 2009","interactions":[],"lastModifiedDate":"2013-03-16T11:58:07","indexId":"ds744","displayToPublicDate":"2013-03-16T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"744","title":"Summary of suspended-sediment concentration data, San Francisco Bay, California, water year 2009","docAbstract":"Suspended-sediment concentration data were collected by the U.S. Geological Survey in San Francisco Bay during water year 2009 (October 1, 2008–September 30, 2009). Optical sensors and water samples were used to monitor suspended-sediment concentration at two sites in Suisun Bay, one site in San Pablo Bay, two sites in Central San Francisco Bay, and one site in South San Francisco Bay. Sensors were positioned at two depths at most sites to help define the vertical variability of suspended sediments. Water samples were collected periodically and analyzed for concentrations of suspended sediment. The results of the analyses were used to calibrate the output of the optical sensors so that a record of suspended-sediment concentrations could be derived. This report presents the data-collection methods used and summarizes, in graphs, the suspended-sediment concentration data collected from October 2008 through September 2009. Calibration curves and plots of the processed data for each sensor also are presented.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds744","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers, San Francisco District","usgsCitation":"Buchanan, P.A., and Morgan, T., 2012, Summary of suspended-sediment concentration data, San Francisco Bay, California, water year 2009: U.S. Geological Survey Data Series 744, viii, 26 p., https://doi.org/10.3133/ds744.","productDescription":"viii, 26 p.","numberOfPages":"38","additionalOnlineFiles":"N","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":269443,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds744.png"},{"id":269441,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/744/"},{"id":269442,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/744/pdf/ds744.pdf"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.5946,37.4346 ], [ -122.5946,38.0 ], [ -122.0,38.0 ], [ -122.0,37.4346 ], [ -122.5946,37.4346 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51458658e4b0c47b5d322a6b","contributors":{"authors":[{"text":"Buchanan, Paul A. 0000-0002-4796-4734 buchanan@usgs.gov","orcid":"https://orcid.org/0000-0002-4796-4734","contributorId":1018,"corporation":false,"usgs":true,"family":"Buchanan","given":"Paul","email":"buchanan@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":476084,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Morgan, Tara L. 0000-0001-5632-5232","orcid":"https://orcid.org/0000-0001-5632-5232","contributorId":29124,"corporation":false,"usgs":true,"family":"Morgan","given":"Tara L.","affiliations":[],"preferred":false,"id":476085,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70044631,"text":"ds717 - 2012 - Data from a thick unsaturated zone in Joshua Tree, San Bernardino County, California, 2007--09","interactions":[],"lastModifiedDate":"2013-03-16T11:45:04","indexId":"ds717","displayToPublicDate":"2013-03-16T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"717","title":"Data from a thick unsaturated zone in Joshua Tree, San Bernardino County, California, 2007--09","docAbstract":"Data were collected on the physical properties of unsaturated alluvial deposits, the chemical composition of leachate extracted from unsaturated alluvial deposits, the chemical and isotopic composition of groundwater and unsaturated-zone water, and the chemical composition of unsaturated-zone gas at four monitoring sites in the southwestern part of the Mojave Desert in the town of Joshua Tree, San Bernardino County, California. The presence of denitrifying and nitrate-reducing bacteria from unsaturated alluvial deposits was evaluated for two of these monitoring sites that underlie unsewered residential development.\n\nFour unsaturated-zone monitoring sites were installed in the Joshua Tree area—two in an unsewered residential development and two adjacent to a proposed artificial-recharge site in an undeveloped area. The two boreholes in residential development areas were installed by using the ODEX air-hammer method. One borehole was drilled through the unsaturated zone to a depth of 541 ft (feet) below land surface; a well screened across the water table was installed. Groundwater was sampled from this well. The second borehole was drilled to a depth of 81 ft below land surface. Drilling procedures, lithologic and geophysical data, construction details, and instrumentation placed in these boreholes are described. Core material was analyzed for water content, bulk density, matric potential, particle size, and water retention. The leachate from over 500 subsamples of cores and cuttings was analyzed for soluble anions, including fluoride, sulfate, bromide, chloride, nitrate, nitrite, and orthophosphate. Groundwater was analyzed for major ions, inorganic compounds, select trace elements, and isotopic composition. Unsaturated-zone water from suction-cup lysimeters was analyzed for major ions, inorganic compounds, select trace elements, and isotopic composition. Unsaturated-zone gas samples were analyzed for argon, oxygen, nitrogen, methane, carbon dioxide, ethane, nitrous oxide, and carbon monoxide. Drill cuttings were analyzed for denitrifying and nitrate-reducing bacteria.\n\nOne of the boreholes installed adjacent to the Joshua Basin Water District proposed groundwater-recharge facility was installed by using the ODEX air-hammer method and the other was installed by using a 7.875-inch hollow-stem auger. Drilling procedures, lithologic and geophysical data, construction details, and instrumentation placed in these boreholes are described; however, geochemical data were not available at the time of publication.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds717","collaboration":"Prepared in cooperation with the Joshua Basin Water District","usgsCitation":"Burgess, M., Izbicki, J., Teague, N., O’Leary, D.R., Clark, D., and Land, M., 2012, Data from a thick unsaturated zone in Joshua Tree, San Bernardino County, California, 2007--09: U.S. Geological Survey Data Series 717, vii, 103 p., https://doi.org/10.3133/ds717.","productDescription":"vii, 103 p.","numberOfPages":"114","additionalOnlineFiles":"N","temporalStart":"2007-01-01","temporalEnd":"2009-12-31","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":269438,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds717.jpg"},{"id":269439,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/717/"},{"id":269440,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/717/pdf/ds717.pdf"}],"country":"United States","state":"California","county":"San Bernardino County","city":"Joshua Tree","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -116.351526,34.104018 ], [ -116.351526,34.149356 ], [ -116.290866,34.149356 ], [ -116.290866,34.104018 ], [ -116.351526,34.104018 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5145864fe4b0c47b5d322a67","contributors":{"authors":[{"text":"Burgess, Matthew","contributorId":17112,"corporation":false,"usgs":true,"family":"Burgess","given":"Matthew","affiliations":[],"preferred":false,"id":476079,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Izbicki, John 0000-0003-0816-4408","orcid":"https://orcid.org/0000-0003-0816-4408","contributorId":91905,"corporation":false,"usgs":true,"family":"Izbicki","given":"John","affiliations":[],"preferred":false,"id":476083,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Teague, Nicholas 0000-0001-5289-1210","orcid":"https://orcid.org/0000-0001-5289-1210","contributorId":20229,"corporation":false,"usgs":true,"family":"Teague","given":"Nicholas","affiliations":[],"preferred":false,"id":476080,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"O’Leary, David R. 0000-0001-9888-1739 doleary@usgs.gov","orcid":"https://orcid.org/0000-0001-9888-1739","contributorId":2143,"corporation":false,"usgs":true,"family":"O’Leary","given":"David","email":"doleary@usgs.gov","middleInitial":"R.","affiliations":[],"preferred":false,"id":476078,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Clark, Dennis","contributorId":40099,"corporation":false,"usgs":true,"family":"Clark","given":"Dennis","affiliations":[],"preferred":false,"id":476081,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Land, Michael 0000-0001-5141-0307","orcid":"https://orcid.org/0000-0001-5141-0307","contributorId":56613,"corporation":false,"usgs":true,"family":"Land","given":"Michael","affiliations":[],"preferred":false,"id":476082,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70043106,"text":"70043106 - 2012 - Simulating the effect of climate extremes on groundwater flow through a lakebed","interactions":[],"lastModifiedDate":"2013-05-07T09:48:42","indexId":"70043106","displayToPublicDate":"2013-03-13T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1861,"text":"Ground Water","active":true,"publicationSubtype":{"id":10}},"title":"Simulating the effect of climate extremes on groundwater flow through a lakebed","docAbstract":"Groundwater exchanges with lakes resulting from cyclical wet and dry climate extremes maintain lake levels in the environment in ways that are not well understood, in part because they remain difficult to simulate. To better understand the atypical groundwater interactions with lakes caused by climatic extremes, an original conceptual approach is introduced using MODFLOW-2005 and a kinematic-wave approximation to variably saturated flow that allows lake size and position in the basin to change while accurately representing the daily lake volume and three-dimensional variably saturated groundwater flow responses in the basin. Daily groundwater interactions are simulated for a calibrated lake basin in Florida over a decade that included historic wet and dry departures from the average rainfall. The divergent climate extremes subjected nearly 70% of the maximum lakebed area and 75% of the maximum shoreline perimeter to both groundwater inflow and lake leakage. About half of the lakebed area subject to flow reversals also went dry. A flow-through pattern present for 73% of the decade caused net leakage from the lake 80% of the time. Runoff from the saturated lake margin offset the groundwater deficit only about half of that time. A centripetal flow pattern present for 6% of the decade was important for maintaining the lake stage and generated 30% of all net groundwater inflow. Pumping effects superimposed on dry climate extremes induced the least frequent but most cautionary flow pattern with leakage from over 90% of the actual lakebed area.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ground Water","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1111/j.1745-6584.2012.00969.x","usgsCitation":"Virdi, M.L., Lee, T.M., Swancar, A., and Niswonger, R., 2012, Simulating the effect of climate extremes on groundwater flow through a lakebed: Ground Water, v. 51, no. 2, p. 203-218, https://doi.org/10.1111/j.1745-6584.2012.00969.x.","productDescription":"16 p.","startPage":"203","endPage":"218","numberOfPages":"16","ipdsId":"IP-012958","costCenters":[{"id":285,"text":"Florida Water Science Center","active":false,"usgs":true},{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":271915,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":271912,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/j.1745-6584.2012.00969.x"}],"country":"United States","state":"Florida","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -88,5.555555555555556E-4 ], [ -88,8.333333333333334E-4 ], [ -79,8.333333333333334E-4 ], [ -79,5.555555555555556E-4 ], [ -88,5.555555555555556E-4 ] ] ] } } ] }","volume":"51","issue":"2","noUsgsAuthors":false,"publicationDate":"2012-08-14","publicationStatus":"PW","scienceBaseUri":"518a2279e4b061e1bd5334b2","contributors":{"authors":[{"text":"Virdi, Makhan L.","contributorId":84246,"corporation":false,"usgs":true,"family":"Virdi","given":"Makhan","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":472970,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lee, Terrie M. tmlee@usgs.gov","contributorId":2461,"corporation":false,"usgs":true,"family":"Lee","given":"Terrie","email":"tmlee@usgs.gov","middleInitial":"M.","affiliations":[],"preferred":true,"id":472968,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Swancar, Amy aswancar@usgs.gov","contributorId":450,"corporation":false,"usgs":true,"family":"Swancar","given":"Amy","email":"aswancar@usgs.gov","affiliations":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"preferred":false,"id":472967,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Niswonger, Richard G.","contributorId":45402,"corporation":false,"usgs":true,"family":"Niswonger","given":"Richard G.","affiliations":[],"preferred":false,"id":472969,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70044957,"text":"70044957 - 2012 - Parasites of fishes in the Colorado River and selected tributaries in Grand Canyon, Arizona.","interactions":[],"lastModifiedDate":"2018-01-24T10:37:16","indexId":"70044957","displayToPublicDate":"2013-03-04T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2414,"text":"Journal of Parasitology","active":true,"publicationSubtype":{"id":10}},"title":"Parasites of fishes in the Colorado River and selected tributaries in Grand Canyon, Arizona.","docAbstract":"As part of the endangered humpback chub (HBC; Gila cypha) Adaptive Management Program, a parasite survey was conducted from 28 June to 17 July 2006 in 8 tributaries and 7 adjacent sections of the main stem of the Colorado River, U.S.A. In total, 717 fish were caught, including 24 HBC. Field necropsies yielded 19 parasite species, 5 of which (Achtheres sp., Kathlaniidae gen. sp., Caryophyllaidae gen. sp., Myxidium sp., and Octomacrum sp.) are new records for Grand Canyon, Arizona, U.S.A. Spearman's correlation coefficient analyses showed no correlations between parasite burden and fork length for various combinations of fish and parasite species. Regression analyses suggest that no parasite species had a strong effect on fish length. The most diverse parasite community (n=14) was at river kilometer (Rkm) 230, near the confluence of Kanab Creek. The most diverse parasite infracommunity (n=12) was found in the non-native channel catfish (CCF; Ictaluris punctatus). Overall parasite prevalence was highest in CCF (85%) followed by that in HBC (58%). The parasite fauna of humpback chub was mainly composed of Bothriocephalus acheilognathi and Ornithodiplostomum sp. metacercariae.
","language":"English","publisher":"Allen Press Publishing Services","publisherLocation":"Lawrence, KS","doi":"10.1645/GE-2538.1","usgsCitation":"Cole, R.A., Sterner, M.C., Linder, C., Hoffnagle, T.L., Persons, B., Choudhury, A., and Haro, R., 2012, Parasites of fishes in the Colorado River and selected tributaries in Grand Canyon, Arizona.: Journal of Parasitology, v. 98, no. 1, p. 117-127, https://doi.org/10.1645/GE-2538.1.","productDescription":"11 p.","startPage":"117","endPage":"127","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-018339","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":270407,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":270406,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1645/GE-2538.1"}],"country":"United States","state":"Arizona","volume":"98","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"515aac70e4b0105540728a5c","contributors":{"authors":[{"text":"Cole, Rebecca A. 0000-0003-2923-1622 rcole@usgs.gov","orcid":"https://orcid.org/0000-0003-2923-1622","contributorId":2873,"corporation":false,"usgs":true,"family":"Cole","given":"Rebecca","email":"rcole@usgs.gov","middleInitial":"A.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":476517,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sterner, Mauritz C. msterner@usgs.gov","contributorId":3229,"corporation":false,"usgs":true,"family":"Sterner","given":"Mauritz","email":"msterner@usgs.gov","middleInitial":"C.","affiliations":[],"preferred":true,"id":476518,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Linder, Chad","contributorId":25053,"corporation":false,"usgs":true,"family":"Linder","given":"Chad","email":"","affiliations":[],"preferred":false,"id":476519,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hoffnagle, Timothy L.","contributorId":30523,"corporation":false,"usgs":true,"family":"Hoffnagle","given":"Timothy","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":476520,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Persons, Bill","contributorId":45599,"corporation":false,"usgs":true,"family":"Persons","given":"Bill","email":"","affiliations":[],"preferred":false,"id":476521,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Choudhury, Anindo 0000-0001-7553-4179","orcid":"https://orcid.org/0000-0001-7553-4179","contributorId":82268,"corporation":false,"usgs":false,"family":"Choudhury","given":"Anindo","affiliations":[],"preferred":false,"id":476523,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Haro, Roger","contributorId":53260,"corporation":false,"usgs":true,"family":"Haro","given":"Roger","affiliations":[],"preferred":false,"id":476522,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70044356,"text":"ofr20121243 - 2012 - The role of the U.S. Geological Survey in Lake Michigan Diversion Accounting in Illinois, 1984-2010","interactions":[],"lastModifiedDate":"2013-03-04T13:01:55","indexId":"ofr20121243","displayToPublicDate":"2013-03-04T00:00:00","publicationYear":"2012","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":"2012-1243","title":"The role of the U.S. Geological Survey in Lake Michigan Diversion Accounting in Illinois, 1984-2010","docAbstract":"The State of Illinois' annual withdrawl from Lake Michigan is limited by a U.S. Supreme Court decree. The U.S. Geological Survey (USGS) is responsible for monitoring flows in the Chicago area waterway system (CAWS) as part of the Lake Michigan Diversion Accounting (LMDA) overseen by the U.S. Army Corps of Engineers, Chicago District. Every five years, the USGS streamgage practices in the CAWS are reviewed by a committee of practicing engineers and academics to ensure that the best engineering practices are implemented in accordance with the U.S. Supreme Court decree and as part of LMDA. This report provides a perspective on the role of the USGS in LMDA from 1984 to 2010 including the responses to the review committees. Six technical review committees have been convened by the U.S. Corps of Engineers to evaluate the key components of LMDA especially the USGS streamgages within the CAWS. Any changes in streamgaging practices at CAWS gaging stations require detailed analysis to ensure the change will not adversely affect the ability of the USGS to accurately monitor flows.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121243","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers-Chicago District","usgsCitation":"Johnson, K.K., Duncker, J.J., and Jackson, P., 2012, The role of the U.S. Geological Survey in Lake Michigan Diversion Accounting in Illinois, 1984-2010: U.S. Geological Survey Open-File Report 2012-1243, viii, 73 p., https://doi.org/10.3133/ofr20121243.","productDescription":"viii, 73 p.","numberOfPages":"84","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"1984-01-01","temporalEnd":"2010-12-31","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":268708,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1243.jpg"},{"id":268706,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1243/"},{"id":268707,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1243/pdf/ofr2012-1243.pdf"}],"scale":"100000","projection":"Albers Equal-Area Conic","country":"United States","state":"Illinois","city":"Chicago","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -88.25,41.5 ], [ -88.25,42.25 ], [ -87.5,42.25 ], [ -87.5,41.5 ], [ -88.25,41.5 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5135c26be4b03b8ec4025b34","contributors":{"authors":[{"text":"Johnson, Kevin K. 0000-0003-2703-5994 johnsonk@usgs.gov","orcid":"https://orcid.org/0000-0003-2703-5994","contributorId":4220,"corporation":false,"usgs":true,"family":"Johnson","given":"Kevin","email":"johnsonk@usgs.gov","middleInitial":"K.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":475358,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Duncker, James J. 0000-0001-5464-7991 jduncker@usgs.gov","orcid":"https://orcid.org/0000-0001-5464-7991","contributorId":4316,"corporation":false,"usgs":true,"family":"Duncker","given":"James","email":"jduncker@usgs.gov","middleInitial":"J.","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true}],"preferred":true,"id":475359,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jackson, P. Ryan","contributorId":68571,"corporation":false,"usgs":true,"family":"Jackson","given":"P. Ryan","affiliations":[],"preferred":false,"id":475360,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70044265,"text":"ofr20121274 - 2012 - Potential climate-induced runoff changes and associated uncertainty in four Pacific Northwest estuaries","interactions":[],"lastModifiedDate":"2013-03-01T10:18:17","indexId":"ofr20121274","displayToPublicDate":"2013-03-01T00:00:00","publicationYear":"2012","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":"2012-1274","title":"Potential climate-induced runoff changes and associated uncertainty in four Pacific Northwest estuaries","docAbstract":"As part of a larger investigation into potential effects of climate change on estuarine habitats in the Pacific Northwest, we estimated changes in freshwater inputs into four estuaries: Coquille River estuary, South Slough of Coos Bay, and Yaquina Bay in Oregon, and Willapa Bay in Washington. We used the U.S. Geological Survey's Precipitation Runoff Modeling System (PRMS) to model watershed hydrological processes under current and future climatic conditions. This model allowed us to explore possible shifts in coastal hydrologic regimes at a range of spatial scales. All modeled watersheds are located in rainfall-dominated coastal areas with relatively insignificant base flow inputs, and their areas vary from 74.3 to 2,747.6 square kilometers. The watersheds also vary in mean elevation, ranging from 147 meters in the Willapa to 1,179 meters in the Coquille. The latitudes of watershed centroids range from 43.037 degrees north latitude in the Coquille River estuary to 46.629 degrees north latitude in Willapa Bay. We calibrated model parameters using historical climate grid data downscaled to one-sixteenth of a degree by the Climate Impacts Group, and historical runoff from sub-watersheds or neighboring watersheds. Nash Sutcliffe efficiency values for daily flows in calibration sub-watersheds ranged from 0.71 to 0.89. After calibration, we forced the PRMS models with four North American Regional Climate Change Assessment Program climate models: Canadian Regional Climate Model-(National Center for Atmospheric Research) Community Climate System Model version 3, Canadian Regional Climate Model-Canadian Global Climate Model version 3, Hadley Regional Model version 3-Hadley Centre Climate Model version 3, and Regional Climate Model-Canadian Global Climate Model version 3. These are global climate models (GCMs) downscaled with regional climate models that are embedded within the GCMs, and all use the A2 carbon emission scenario developed by the Intergovernmental Panel on Climate Change. With these climate-forcing outputs, we derived the mean change in flow from the period encompassing the 1980s (1971-1995) to the period encompassing the 2050s (2041-2065). Specifically, we calculated percent change in mean monthly flow rate, coefficient of variation, top 5 percent of flow, and 7-day low flow. The trends with the most agreement among climate models and among watersheds were increases in autumn mean monthly flows, especially in October and November, decreases in summer monthly mean flow, and increases in the top 5 percent of flow. We also estimated variance in PRMS outputs owing to parameter uncertainty and the selection of climate model using Latin hypercube sampling. This analysis showed that PRMS low-flow simulations are more uncertain than medium or high flow simulations, and that variation among climate models was a larger source of uncertainty than the hydrological model parameters. These results improve our understanding of how climate change may affect the saltwater-freshwater balance in Pacific Northwest estuaries, with implications for their sensitive ecosystems.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121274","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency and the Oregon Climate Change Research Institute","usgsCitation":"Steele, M.O., Chang, H., Reusser, D.A., Brown, C.A., and Jung, I., 2012, Potential climate-induced runoff changes and associated uncertainty in four Pacific Northwest estuaries: U.S. Geological Survey Open-File Report 2012-1274, Report: ix, 52 p., https://doi.org/10.3133/ofr20121274.","productDescription":"Report: ix, 52 p.","numberOfPages":"63","onlineOnly":"Y","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":268612,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1274.jpg"},{"id":268610,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1274/index.html"},{"id":268611,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1274/pdf/ofr2012-1274.pdf"}],"country":"United States","state":"Oregon;Washington","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.61,41.99 ], [ -124.61,47.26 ], [ -122.0,47.26 ], [ -122.0,41.99 ], [ -124.61,41.99 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5131cdf1e4b0140546f53bad","contributors":{"authors":[{"text":"Steele, Madeline O.","contributorId":19048,"corporation":false,"usgs":true,"family":"Steele","given":"Madeline","email":"","middleInitial":"O.","affiliations":[],"preferred":false,"id":475209,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chang, Heejun","contributorId":14705,"corporation":false,"usgs":true,"family":"Chang","given":"Heejun","email":"","affiliations":[],"preferred":false,"id":475208,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reusser, Deborah A. dreusser@usgs.gov","contributorId":2423,"corporation":false,"usgs":true,"family":"Reusser","given":"Deborah","email":"dreusser@usgs.gov","middleInitial":"A.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":475207,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brown, Cheryl A.","contributorId":69284,"corporation":false,"usgs":true,"family":"Brown","given":"Cheryl","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":475211,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jung, Il-Won","contributorId":38865,"corporation":false,"usgs":true,"family":"Jung","given":"Il-Won","email":"","affiliations":[],"preferred":false,"id":475210,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70043890,"text":"ofr20121112 - 2012 - Shipboard surveys track magnetic sources in marine sediments--geophysical studies of the Stono and North Edisto Inlets near Charleston, South Carolina","interactions":[],"lastModifiedDate":"2013-02-26T08:51:56","indexId":"ofr20121112","displayToPublicDate":"2013-02-26T00:00:00","publicationYear":"2012","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":"2012-1112","title":"Shipboard surveys track magnetic sources in marine sediments--geophysical studies of the Stono and North Edisto Inlets near Charleston, South Carolina","docAbstract":"Magnetic field data are traditionally used to analyze igneous and metamorphic rocks, but recent efforts have shown that magnetic sources within sediments may be detectable, suggesting new applications for high-resolution magnetic field surveys. Candidates for sedimentary sources include heavy mineral sand concentrations rich in magnetite or hematite, alteration-induced glauconite, or biogenic magnetite. Magnetic field surveys can be used to map the distributions of such sources with much denser and more widespread coverage than possible by sampling. These data can then provide constraints on the composition history of local sediments. Mapping such sediments requires the sensor to be relatively close to the source, and filtering approaches may be needed to distinguish signals from both system noise and deeper basement features. Marine geophysical surveys conducted in July, 2010, over the Stono and North Edisto River inlets and their riverine inputs south of Charleston, South Carolina, showed 10- to 40-m-wide, 1- to 6-nT magnetic anomalies associated with shallow, sand-covered seabed. These anomalies are distinct from system noise but are too narrow to represent basement features. The anomalies are present mostly in shallow areas where river sediments originating from upland areas enter the inlets. Surface grab samples from the North Edisto River contain trace amounts of heavy mineral sediments including hematite, maghemite, ilmenite, and magnetite, as well as garnet, epidote, zircon, and rutile. Previous stream sediment analyses show enhanced titanium over much of the Atlantic Coastal Plain. The combined data suggest that the anomalies are generated by titanium- and iron-rich heavy mineral sands ultimately originating from the Piedmont and Blue Ridge provinces, which are then reworked and concentrated by tidal currents.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121112","usgsCitation":"Shah, A.K., and Harris, M., 2012, Shipboard surveys track magnetic sources in marine sediments--geophysical studies of the Stono and North Edisto Inlets near Charleston, South Carolina: U.S. Geological Survey Open-File Report 2012-1112, 1 p.: 1 Sheet: 73 x 43 inches, https://doi.org/10.3133/ofr20121112.","productDescription":"1 p.: 1 Sheet: 73 x 43 inches","startPage":"1","endPage":"1","numberOfPages":"1","additionalOnlineFiles":"N","ipdsId":"IP-036671","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":268278,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1112.png"},{"id":268276,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1112/"},{"id":268277,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1112/OF12-1112.pdf"}],"country":"United States","state":"South Carolina","city":"Charleston","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -83.35,32.03 ], [ -83.35,35.22 ], [ -78.54,35.22 ], [ -78.54,32.03 ], [ -83.35,32.03 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd729fe4b0b290851086d2","contributors":{"authors":[{"text":"Shah, Anjana K. 0000-0002-3198-081X ashah@usgs.gov","orcid":"https://orcid.org/0000-0002-3198-081X","contributorId":2297,"corporation":false,"usgs":true,"family":"Shah","given":"Anjana","email":"ashah@usgs.gov","middleInitial":"K.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":474399,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harris, M. Scott","contributorId":7795,"corporation":false,"usgs":true,"family":"Harris","given":"M. Scott","affiliations":[],"preferred":false,"id":474400,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70044061,"text":"sir20125228 - 2012 - Organic contaminants, trace and major elements, and nutrients in water and sediment sampled in response to the Deepwater Horizon oil spill","interactions":[],"lastModifiedDate":"2019-12-03T14:33:22","indexId":"sir20125228","displayToPublicDate":"2013-02-26T00:00:00","publicationYear":"2012","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":"2012-5228","title":"Organic contaminants, trace and major elements, and nutrients in water and sediment sampled in response to the Deepwater Horizon oil spill","docAbstract":"Beach water and sediment samples were collected along the Gulf of Mexico coast to assess differences in contaminant concentrations before and after landfall of Macondo-1 well oil released into the Gulf of Mexico from the sinking of the British Petroleum Corporation's Deepwater Horizon drilling platform. Samples were collected at 70 coastal sites between May 7 and July 7, 2010, to document baseline, or \"pre-landfall\" conditions. A subset of 48 sites was resampled during October 4 to 14, 2010, after oil had made landfall on the Gulf of Mexico coast, called the \"post-landfall\" sampling period, to determine if actionable concentrations of oil were present along shorelines. Few organic contaminants were detected in water; their detection frequencies generally were low and similar in pre-landfall and post-landfall samples. Only one organic contaminant--toluene--had significantly higher concentrations in post-landfall than pre-landfall water samples. No water samples exceeded any human-health benchmarks, and only one post-landfall water sample exceeded an aquatic-life benchmark--the toxic-unit benchmark for polycyclic aromatic hydrocarbons (PAH) mixtures. In sediment, concentrations of 3 parent PAHs and 17 alkylated PAH groups were significantly higher in post-landfall samples than pre-landfall samples. One pre-landfall sample from Texas exceeded the sediment toxic-unit benchmark for PAH mixtures; this site was not sampled during the post-landfall period. Empirical upper screening-value benchmarks for PAHs in sediment were exceeded at 37 percent of post-landfall samples and 22 percent of pre-landfall samples, but there was no significant difference in the proportion of samples exceeding benchmarks between paired pre-landfall and post-landfall samples. Seven sites had the largest concentration differences between post-landfall and pre-landfall samples for 15 alkylated PAHs. Five of these seven sites, located in Louisiana, Mississippi, and Alabama, had diagnostic geochemical evidence of Macondo-1 oil in post-landfall sediments and tarballs. For trace and major elements in water, analytical reporting levels for several elements were high and variable. No human-health benchmarks were exceeded, although these were available for only two elements. Aquatic-life benchmarks for trace elements were exceeded in 47 percent of water samples overall. The elements responsible for the most exceedances in post-landfall samples were boron, copper, and manganese. Benchmark exceedances in water could be substantially underestimated because some samples had reporting levels higher than the applicable benchmarks (such as cobalt, copper, lead and zinc) and some elements (such as boron and vanadium) were analyzed in samples from only one sampling period. For trace elements in whole sediment, empirical upper screening-value benchmarks were exceeded in 57 percent of post-landfall samples and 40 percent of pre-landfall samples, but there was no significant difference in the proportion of samples exceeding benchmarks between paired pre-landfall and post-landfall samples. Benchmark exceedance frequencies could be conservatively high because they are based on measurements of total trace-element concentrations in sediment. In the less than 63-micrometer sediment fraction, one or more trace or major elements were anthropogenically enriched relative to national baseline values for U.S. streams for all sediment samples except one. Sixteen percent of sediment samples exceeded upper screening-value benchmarks for, and were enriched in, one or more of the following elements: barium, vanadium, aluminum, manganese, arsenic, chromium, and cobalt. These samples were evenly divided between the sampling periods. Aquatic-life benchmarks were frequently exceeded along the Gulf of Mexico coast by trace elements in both water and sediment and by PAHs in sediment. For the most part, however, significant differences between pre-landfall and post-landfall samples were limited to concentrations of PAHs in sediment. At five sites along the coast, the higher post-landfall concentrations of PAHs were associated with diagnostic geochemical evidence of Deepwater Horizon Macondo-1 oil.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125228","usgsCitation":"Nowell, L.H., Ludtke, A.S., Mueller, D.K., and Scott, J.C., 2012, Organic contaminants, trace and major elements, and nutrients in water and sediment sampled in response to the Deepwater Horizon oil spill: U.S. Geological Survey Scientific Investigations Report 2012-5228, Report: x, 96 p.; 5 Tables; 17 Appendices , https://doi.org/10.3133/sir20125228.","productDescription":"Report: x, 96 p.; 5 Tables; 17 Appendices ","additionalOnlineFiles":"Y","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":268297,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2012/5228/pdf/sir20125228_app1_refs.pdf","text":"Appendix 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