{"pageNumber":"696","pageRowStart":"17375","pageSize":"25","recordCount":40790,"records":[{"id":70039844,"text":"sir20125065 - 2012 - Predicted nitrate and arsenic concentrations in basin-fill aquifers of the Southwestern United States","interactions":[],"lastModifiedDate":"2019-12-30T14:29:12","indexId":"sir20125065","displayToPublicDate":"2012-09-07T00:00:00","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":"2012-5065","title":"Predicted nitrate and arsenic concentrations in basin-fill aquifers of the Southwestern United States","docAbstract":"<p>The National Water-Quality Assessment (NAWQA) Program of the U.S. Geological Survey (USGS) is conducting a regional analysis of water quality in the principal aquifer systems across the United States. The Southwest Principal Aquifers (SWPA) study is building a better understanding of the susceptibility and vulnerability of basin-fill aquifers in the region to groundwater contamination by synthesizing baseline knowledge of groundwater-quality conditions in 16 basins previously studied by the NAWQA Program. The improved understanding of aquifer susceptibility and vulnerability to contamination is assisting in the development of tools that water managers can use to assess and protect the quality of groundwater resources.</p><p>Human-health concerns and economic considerations associated with meeting drinking-water standards motivated a study of the vulnerability of basin-fill aquifers to nitrate con­tamination and arsenic enrichment in the southwestern United States. Statistical models were developed by using the random forest classifier algorithm to predict concentrations of nitrate and arsenic across a model grid that represents about 190,600 square miles of basin-fill aquifers in parts of Arizona, California, Colorado, Nevada, New Mexico, and Utah. The statistical models, referred to as classifiers, reflect natural and human-related factors that affect aquifer vulnerability to contamina­tion and relate nitrate and arsenic concentrations to explana­tory variables representing local- and basin-scale measures of source, aquifer susceptibility, and geochemical conditions. The classifiers were unbiased and fit the observed data well, and misclassifications were primarily due to statistical sampling error in the training datasets.</p><p>The classifiers were designed to predict concentrations to be in one of six classes for nitrate, and one of seven classes for arsenic. Each classification scheme allowed for identification of areas with concentrations that were equal to or exceeding the U.S. Environmental Protection Agency drinking-water standard. Whereas 2.4 percent of the area underlain by basin-fill aquifers in the study area was predicted to equal or exceed this standard for nitrate (10 milligrams per liter as N; mg/L), 42.7 percent was predicted to equal or exceed the standard for arsenic (10 micrograms per liter; μg/L). Areas predicted to equal or exceed the drinking-water standard for nitrate include basins in central Arizona near Phoenix; the San Joaquin, Inland, and San Jacinto basins of California; and the San Luis Valley of Colorado. Much of the area predicted to equal or exceed the drinking-water standard for arsenic is within a belt of basins along the western portion of the Basin and Range Physiographic Province in Nevada, California, and Arizona. Predicted nitrate and arsenic concentrations are substantially lower than the drinking-water standards in much of the study area—about 93.0 percent of the area underlain by basin-fill aquifers was less than one-half the standard for nitrate (5.0 mg/L), and 50.2 percent was less than one-half the standard for arsenic (5.0 μg/L).</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125065","usgsCitation":"Anning, D.W., Paul, A.P., McKinney, T., Huntington, J.M., Bexfield, L.M., and Thiros, S.A., 2012, Predicted nitrate and arsenic concentrations in basin-fill aquifers of the Southwestern United States: U.S. Geological Survey Scientific Investigations Report 2012-5065, Report: viii, 115 p.; Metadata; Appendices 1, 2, 8-17, https://doi.org/10.3133/sir20125065.","productDescription":"Report: viii, 115 p.; Metadata; Appendices 1, 2, 8-17","numberOfPages":"128","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true},{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true},{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true},{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":261754,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5065.jpg"},{"id":261752,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5065/","linkFileType":{"id":5,"text":"html"}},{"id":332846,"rank":9,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2012/5065/pdf/sir20125065LandUse.pdf","text":"Appendix 11","size":"10.5 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":332847,"rank":10,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2012/5065/pdf/sir20125065Population.pdf","text":"Appendix 12","size":"9.6 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":332848,"rank":11,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2012/5065/pdf/sir20125065Geology.pdf","text":"Appendix 13","size":"8.2 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":332850,"rank":13,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2012/5065/pdf/sir20125065Soil.pdf","text":"Appendix 15","size":"11 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":261753,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5065/pdf/sir20125065.pdf","size":"9.6 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":273232,"type":{"id":16,"text":"Metadata"},"url":"https://water.usgs.gov/GIS/metadata/usgswrd/XML/ds698_SWPA_NO3_As_prediction.xml"},{"id":332842,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2012/5065/pdf/sir20125065Appendix1and2.xlsx","text":"Appendixes 1 and 2","size":"36 MB","linkFileType":{"id":3,"text":"xlsx"}},{"id":332852,"rank":15,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2012/5065/pdf/sir20125065Recharge.pdf","text":"Appendix 17","size":"9 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":332849,"rank":12,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2012/5065/pdf/sir20125065LandSurface.pdf","text":"Appendix 14","size":"8.2 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":332843,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2012/5065/pdf/sir20125065Nitrate.pdf","text":"Appendix 8","size":"7 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":332844,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2012/5065/pdf/sir20125065Arsenic.pdf","text":"Appendix 9","size":"7 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":332845,"rank":8,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2012/5065/pdf/sir20125065Nitrogen.pdf","text":"Appendix 10","size":"11 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":332851,"rank":14,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2012/5065/pdf/sir20125065Water.pdf","text":"Appendix 16","size":"9.6 MB","linkFileType":{"id":1,"text":"pdf"}}],"projection":"Albers Equal Area Conic projection","datum":"North American Datum of 1983","country":"United States","state":"Arizona, California, Colorado, Nevada, New Mexico, 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,{"id":70039842,"text":"ds698 - 2012 - Digital spatial data for predicted nitrate and arsenic concentrations in basin-fill aquifers of the Southwest Principal Aquifers study area","interactions":[],"lastModifiedDate":"2017-09-20T12:18:45","indexId":"ds698","displayToPublicDate":"2012-09-07T00:00:00","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":"698","title":"Digital spatial data for predicted nitrate and arsenic concentrations in basin-fill aquifers of the Southwest Principal Aquifers study area","docAbstract":"This product \"Digital spatial data for predicted nitrate and arsenic concentrations in basin-fill aquifers of the Southwest Principal Aquifers study area\" is a 1:250,000-scale vector spatial dataset developed as part of a regional Southwest Principal Aquifers (SWPA) study (Anning and others, 2012). The study examined the vulnerability of basin-fill aquifers in the southwestern United States to nitrate contamination and arsenic enrichment. Statistical models were developed by using the random forest classifier algorithm to predict concentrations of nitrate and arsenic across a model grid that represents local- and basin-scale measures of source, aquifer susceptibility, and geochemical conditions.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds698","collaboration":"National Water-Quality Assessment Program","usgsCitation":"McKinney, T., and Anning, D.W., 2012, Digital spatial data for predicted nitrate and arsenic concentrations in basin-fill aquifers of the Southwest Principal Aquifers study area: U.S. Geological Survey Data Series 698, iv, 2 p., https://doi.org/10.3133/ds698.","productDescription":"iv, 2 p.","numberOfPages":"10","costCenters":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":261757,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds_698.jpg"},{"id":261750,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/698/","linkFileType":{"id":5,"text":"html"}},{"id":261751,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/698/pdf/ds698.pdf","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Arizona, California, Colorado, Idaho, Nevada, New Mexico, Oregon, Utah","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.4,31.333333333333332 ], [ -124.4,43 ], [ -105,43 ], [ -105,31.333333333333332 ], [ -124.4,31.333333333333332 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a018be4b0c8380cd4fc4d","contributors":{"authors":[{"text":"McKinney, Tim S.","contributorId":66792,"corporation":false,"usgs":true,"family":"McKinney","given":"Tim S.","affiliations":[],"preferred":false,"id":467035,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anning, David W. dwanning@usgs.gov","contributorId":432,"corporation":false,"usgs":true,"family":"Anning","given":"David","email":"dwanning@usgs.gov","middleInitial":"W.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":467034,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70039841,"text":"ds697 - 2012 - Digital spatial data for observed, predicted, and misclassification errors for observations in the training dataset for nitrate and arsenic concentrations in basin-fill aquifers in the Southwest Principal Aquifers study area","interactions":[],"lastModifiedDate":"2017-09-20T12:17:59","indexId":"ds697","displayToPublicDate":"2012-09-07T00:00:00","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":"697","title":"Digital spatial data for observed, predicted, and misclassification errors for observations in the training dataset for nitrate and arsenic concentrations in basin-fill aquifers in the Southwest Principal Aquifers study area","docAbstract":"This product \"Digital spatial data for observed, predicted, and misclassification errors for observations in the training dataset for nitrate and arsenic concentrations in basin-fill aquifers in the Southwest Principal Aquifers study area\" is a 1:250,000-scale point spatial dataset developed as part of a regional Southwest Principal Aquifers (SWPA) study (Anning and others, 2012). The study examined the vulnerability of basin-fill aquifers in the southwestern United States to nitrate contamination and arsenic enrichment. Statistical models were developed by using the random forest classifier algorithm to predict concentrations of nitrate and arsenic across a model grid that represents local- and basin-scale measures of source, aquifer susceptibility, and geochemical conditions.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds697","collaboration":"National Water-Quality Assessment Program","usgsCitation":"McKinney, T., and Anning, D.W., 2012, Digital spatial data for observed, predicted, and misclassification errors for observations in the training dataset for nitrate and arsenic concentrations in basin-fill aquifers in the Southwest Principal Aquifers study area: U.S. Geological Survey Data Series 697, Report: iv, 2 p.; Metadata, https://doi.org/10.3133/ds697.","productDescription":"Report: iv, 2 p.; Metadata","numberOfPages":"10","costCenters":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":261756,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds_697.jpg"},{"id":273229,"type":{"id":16,"text":"Metadata"},"url":"https://water.usgs.gov/GIS/metadata/usgswrd/XML/ds697_SWPA_NO3_As_training.xml"},{"id":261748,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/697/","linkFileType":{"id":5,"text":"html"}},{"id":261749,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/697/pdf/ds697.pdf","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Arizona, California, Colorado, Idaho, Nevada, New Mexico, Oregon, Utah","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.4,31.333333333333332 ], [ -124.4,43 ], [ -105,43 ], [ -105,31.333333333333332 ], [ -124.4,31.333333333333332 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a018ae4b0c8380cd4fc4a","contributors":{"authors":[{"text":"McKinney, Tim S.","contributorId":66792,"corporation":false,"usgs":true,"family":"McKinney","given":"Tim S.","affiliations":[],"preferred":false,"id":467033,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anning, David W. dwanning@usgs.gov","contributorId":432,"corporation":false,"usgs":true,"family":"Anning","given":"David","email":"dwanning@usgs.gov","middleInitial":"W.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":467032,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70039840,"text":"sir20125137 - 2012 - Development of a flood-warning system and flood-inundation mapping in Licking County, Ohio","interactions":[],"lastModifiedDate":"2012-09-07T17:16:30","indexId":"sir20125137","displayToPublicDate":"2012-09-07T00:00:00","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":"2012-5137","title":"Development of a flood-warning system and flood-inundation mapping in Licking County, Ohio","docAbstract":"Digital flood-inundation maps for selected reaches of South Fork Licking River, Raccoon Creek, North Fork Licking River, and the Licking River in Licking County, Ohio, were created by the U.S. Geological Survey (USGS), in cooperation with the Ohio Department of Transportation; U.S. Department of Transportation, Federal Highway Administration; Muskingum Watershed Conservancy District; U.S. Department of Agriculture, Natural Resources Conservation Service; and the City of Newark and Village of Granville, Ohio. The inundation maps depict estimates of the areal extent of flooding corresponding to water levels (stages) at the following USGS streamgages: South Fork Licking River at Heath, Ohio (03145173); Raccoon Creek below Wilson Street at Newark, Ohio (03145534); North Fork Licking River at East Main Street at Newark, Ohio (03146402); and Licking River near Newark, Ohio (03146500). The maps were provided to the National Weather Service (NWS) for incorporation into a Web-based flood-warning system that can be used in conjunction with NWS flood-forecast data to show areas of predicted flood inundation associated with forecasted flood-peak stages. As part of the flood-warning streamflow network, the USGS re-installed one streamgage on North Fork Licking River, and added three new streamgages, one each on North Fork Licking River, South Fork Licking River, and Raccoon Creek. Additionally, the USGS upgraded a lake-level gage on Buckeye Lake. Data from the streamgages and lake-level gage can be used by emergency-management personnel, in conjunction with the flood-inundation maps, to help determine a course of action when flooding is imminent. Flood profiles for selected reaches were prepared by calibrating steady-state step-backwater models to selected, established streamgage rating curves. The step-backwater models then were used to determine water-surface-elevation profiles for up to 10 flood stages at a streamgage with corresponding streamflows ranging from approximately the 50 to 0.2-percent chance annual-exceedance probabilities for each of the 4 streamgages that correspond to the flood-inundation maps. The computed flood profiles were used in combination with digital elevation data to delineate flood-inundation areas. Maps of Licking County showing flood-inundation areas overlain on digital orthophotographs are presented for the selected floods. The USGS also developed an unsteady-flow model for a reach of South Fork Licking River for use by the NWS to enhance their ability to provide advanced flood warning in the region north of Buckeye Lake, Ohio. The unsteady-flow model was calibrated based on data from four flooding events that occurred from June 2008 to December 2011. Model calibration was approximate due to the fact that there were unmeasured inflows to the river that were not able to be considered during the calibration. Information on unmeasured inflow derived from NWS hydrologic models and additional flood-event data could enable the NWS to further refine the unsteady-flow model.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125137","collaboration":"39 plates (PDF and JPEG formats) available through the index page link displayed at the top of this record. Prepared in cooperation with the Ohio Department of Transportation; U.S. Department of Transportation, Federal Highway Administration; Muskingum Watershed Conservancy District; U.S. Department of Agriculture, Natural Resources Conservation Service; and the City of Newark and Village of Granville, Ohio","usgsCitation":"Ostheimer, C.J., 2012, Development of a flood-warning system and flood-inundation mapping in Licking County, Ohio: U.S. Geological Survey Scientific Investigations Report 2012-5137, vii, 13 p.; 39 Plates (PDF and JPEG format): 13 x 13 inches or smaller; Downloads Directory, https://doi.org/10.3133/sir20125137.","productDescription":"vii, 13 p.; 39 Plates (PDF and JPEG format): 13 x 13 inches or smaller; Downloads Directory","numberOfPages":"26","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":513,"text":"Ohio Water Science 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,{"id":70039839,"text":"ofr20121178 - 2012 - Profile measurements and data from the 2011 Optics, Acoustics, and Stress In Situ (OASIS) project at the Martha's Vineyard Coastal Observatory","interactions":[],"lastModifiedDate":"2012-09-07T17:16:30","indexId":"ofr20121178","displayToPublicDate":"2012-09-07T00:00:00","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":"2012-1178","title":"Profile measurements and data from the 2011 Optics, Acoustics, and Stress In Situ (OASIS) project at the Martha's Vineyard Coastal Observatory","docAbstract":"This report documents data collected by the U.S. Geological Survey (USGS) for the Coastal Model Applications and Field Measurements project under the auspices of the U.S. Navy Office of Naval Research Optics, Acoustics, and Stress In Situ (OASIS) Project. The objective of the measurements was to relate optical and acoustic properties of suspended particles to changes in particle size, concentration, and vertical distribution in the bottom boundary layer near the seafloor caused by wave- and current-induced stresses. This information on the physics of particle resuspension and aggregation and light penetration and water clarity will help improve models of sediment transport, benthic primary productivity, and underwater visibility. There is well-established technology for acoustic profiling, but optical profiles are more difficult to obtain because of the rapid attenuation of light in water. A specially modified tripod with a moving arm was designed to solve this problem by moving instruments vertically in the bottom boundary layer, between the bottom and about 2 meters above the seafloor. The profiling arm was designed, built, and tested during spring and summer 2011 by a team of USGS scientists, engineers, and technicians. To accommodate power requirements and the large data files recorded by some of the optical instruments, the tripod was connected via underwater cable to the Martha's Vineyard Coastal Observatory, operated by the Woods Hole Oceanographic Institution (WHOI). This afforded real-time Internet communication with the embedded computers aboard the tripod. Instruments were mounted on the profiling arm, and additional instruments were mounted elsewhere on the tripod and nearby on the seafloor. The tripod and a small mooring for a profiling current meter were deployed on September 17, 2011, at the Martha's Vineyard Coastal Observatory 12-meter-deep underwater node about 2 kilometers south of Martha's Vineyard, Massachusetts. Divers assisted in the deployment and cleaned the instrument surfaces on the tripod approximately once per week until the tripod and current meter were recovered on October 23, 2011. There was a range of wave and current conditions during the 36-day deployment, including the distant passage of Hurricane Ophelia, several moderate wave events, and a significant local gale that generated wave heights greater than 4 meters at the 12-meter site and knocked over the tripod 3 days before it was recovered. All but one of the instruments functioned well and provided complete datasets. The details of these data and the location of files containing the best basic version of the data are described in this report.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121178","usgsCitation":"Sherwood, C.R., Dickhudt, P., Martini, M.A., Montgomery, E., and Boss, E.S., 2012, Profile measurements and data from the 2011 Optics, Acoustics, and Stress In Situ (OASIS) project at the Martha's Vineyard Coastal Observatory: U.S. Geological Survey Open-File Report 2012-1178, HTML Document, https://doi.org/10.3133/ofr20121178.","productDescription":"HTML Document","onlineOnly":"Y","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":261706,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1178.jpg"},{"id":261704,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1178/","linkFileType":{"id":5,"text":"html"}},{"id":261705,"rank":200,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1178/title_page.html","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Massachusetts","otherGeospatial":"Martha's Vineyard","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -70.83333333333333,41.25 ], [ -70.83333333333333,41.5 ], [ -70.33333333333333,41.5 ], [ -70.33333333333333,41.25 ], [ -70.83333333333333,41.25 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a8dffe4b0c8380cd7ef6a","contributors":{"authors":[{"text":"Sherwood, Christopher R. 0000-0001-6135-3553 csherwood@usgs.gov","orcid":"https://orcid.org/0000-0001-6135-3553","contributorId":2866,"corporation":false,"usgs":true,"family":"Sherwood","given":"Christopher","email":"csherwood@usgs.gov","middleInitial":"R.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":467027,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dickhudt, Patrick J.","contributorId":48302,"corporation":false,"usgs":true,"family":"Dickhudt","given":"Patrick J.","affiliations":[],"preferred":false,"id":467028,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Martini, Marinna A. 0000-0002-7757-5158 mmartini@usgs.gov","orcid":"https://orcid.org/0000-0002-7757-5158","contributorId":2456,"corporation":false,"usgs":true,"family":"Martini","given":"Marinna","email":"mmartini@usgs.gov","middleInitial":"A.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":467026,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Montgomery, Ellyn T.","contributorId":78038,"corporation":false,"usgs":true,"family":"Montgomery","given":"Ellyn T.","affiliations":[],"preferred":false,"id":467030,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Boss, Emmanuel S.","contributorId":48811,"corporation":false,"usgs":true,"family":"Boss","given":"Emmanuel","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":467029,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70039828,"text":"ofr20121200 - 2012 - Survival and migration route probabilities of juvenile Chinook salmon in the Sacramento-San Joaquin River Delta during the winter of 2009-10","interactions":[],"lastModifiedDate":"2016-05-03T16:12:39","indexId":"ofr20121200","displayToPublicDate":"2012-09-06T00:00:00","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":"2012-1200","title":"Survival and migration route probabilities of juvenile Chinook salmon in the Sacramento-San Joaquin River Delta during the winter of 2009-10","docAbstract":"<p>Juvenile Chinook salmon (<i>Oncorhynchus tshawytscha</i>) emigrating from natal tributaries of the Sacramento River may use a number of migration routes to negotiate the Sacramento-San Joaquin River Delta (hereafter, \"the Delta\"), each of which may influence their probability of surviving. We applied a mark-recapture model to data from acoustically tagged juvenile late-fall Chinook salmon that migrated through the Delta during the winter of 2009-10 (hereafter, 2010). This report presents findings from our fourth year of research. We estimated route-specific survival for four release groups: two release groups that migrated through the Delta in December 2009 and January 2010, and two release groups that migrated during February 2010. Population-level survival through the Delta (<i>S</i><sub>Delta</sub>) ranged from 0.374 (SE = 0.040) to 0.524 (SE = 0.034) among releases. Although river flows for the February release groups were substantially higher (20,000-40,000 ft<sup>3</sup>/s at Freeport) than for the December release groups (about 10,000 ft<sup>3</sup>/s), <i>S</i><sub>Delta</sub> did not differ considerably between release groups. Among migration routes, fish migrating through the Sacramento River exhibited the highest survival, and fish entering the interior Delta exhibited the lowest survival. Fish entering Sutter and Steamboat Sloughs had lower survival than fish entering the Sacramento River during December, but similar survival during February. These patterns were consistent among release groups, and strikingly similar to patterns observed in previous years. Migration routing varied among release groups partly because of differences in river discharge between releases. For the two December release groups, 26.5 and 28.9 percent of fish entered the interior Delta; for the two February release groups, 10.4 and 17.9 percent of fish entered the interior Delta. Differences in routing probabilities between December and February are partly related to the inverse relationship between flow and the fraction of discharge entering the interior Delta. The proportion of fish diverted into the interior Delta also can be affected by the status of the Delta Cross Channel's gates. The fraction of fish entering Sutter and Steamboat Sloughs also varied considerably among release groups from 22.1 to 44.7 percent, and did not appear correlated to river discharge. For example, the lowest and highest proportion of fish entering Sutter and Steamboat Sloughs occurred during February. Because fish entering Sutter and Steamboat Sloughs bypass the entrance to the interior Delta, a high proportion of fish migrating into this route reduces the proportion of fish entering the interior Delta.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121200","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service. Other contributors: U.S. Army Corps of Engineers and University of California at Davis","usgsCitation":"Perry, R.W., Romine, J.G., Brewer, S.J., LaCivita, P.E., Brostoff, W.N., and Chapman, E.D., 2012, Survival and migration route probabilities of juvenile Chinook salmon in the Sacramento-San Joaquin River Delta during the winter of 2009-10: U.S. Geological Survey Open-File Report 2012-1200, iv, 30 p., https://doi.org/10.3133/ofr20121200.","productDescription":"iv, 30 p.","numberOfPages":"38","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":261696,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1200.jpg"},{"id":261691,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1200/","linkFileType":{"id":5,"text":"html"}},{"id":261692,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1200/pdf/ofr20121200.pdf","text":"Report","size":"2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"country":"United States","state":"California","city":"Sacramento","otherGeospatial":"Sacramento-San Joaquin River Delta","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.25,37.75 ], [ -122.25,38.583333333333336 ], [ -121.36666666666666,38.583333333333336 ], [ -121.36666666666666,37.75 ], [ -122.25,37.75 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505ba2b3e4b08c986b31f8c8","contributors":{"authors":[{"text":"Perry, Russell W. 0000-0003-4110-8619 rperry@usgs.gov","orcid":"https://orcid.org/0000-0003-4110-8619","contributorId":2820,"corporation":false,"usgs":true,"family":"Perry","given":"Russell","email":"rperry@usgs.gov","middleInitial":"W.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":467006,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Romine, Jason G. 0000-0002-6938-1185 jromine@usgs.gov","orcid":"https://orcid.org/0000-0002-6938-1185","contributorId":2823,"corporation":false,"usgs":true,"family":"Romine","given":"Jason","email":"jromine@usgs.gov","middleInitial":"G.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":467007,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brewer, Scott J. sbrewer@usgs.gov","contributorId":4407,"corporation":false,"usgs":true,"family":"Brewer","given":"Scott","email":"sbrewer@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":true,"id":467008,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"LaCivita, Peter E.","contributorId":101507,"corporation":false,"usgs":true,"family":"LaCivita","given":"Peter","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":467011,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brostoff, William N.","contributorId":52828,"corporation":false,"usgs":true,"family":"Brostoff","given":"William","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":467010,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Chapman, Eric D.","contributorId":34377,"corporation":false,"usgs":true,"family":"Chapman","given":"Eric","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":467009,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70041445,"text":"70041445 - 2012 - 2011 Georgiana Slough non-physical barrier performance evaluation project report","interactions":[],"lastModifiedDate":"2022-11-10T16:00:46.568563","indexId":"70041445","displayToPublicDate":"2012-09-05T02:30:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"2011 Georgiana Slough non-physical barrier performance evaluation project report","docAbstract":"<p>The Sacramento River and its tributaries support populations of anadromous fish species including winter-run, spring-run, fall-run, and late fall&ndash;run Chinook salmon (<i>Oncorhynchus tshawytscha</i>); and steelhead (<i>O. mykiss</i>). Several of these species are listed as threatened or endangered under the California Endangered Species Act (CESA), federal Endangered Species Act (ESA), or both. These species spawn and rear in Sacramento River tributaries; adults use the mainstem Sacramento River for primarily upstream migration and juveniles use it for downstream migration. Juvenile Chinook salmon and steelhead migrate through the lower river during winter and spring. During their downstream migration, juvenile salmonids encounter alternative pathways, such as Sutter and Steamboat Sloughs, the Sacramento&ndash;San Joaquin Delta (Delta), Delta Cross Channel (DCC), and Georgiana Slough. Likewise, sturgeon juveniles migrate downstream in the Sacramento River basin to the Delta, utilizing the distributary channels to rear within and migrate through the system.</p>\n<p>Georgiana Slough is a natural channel that allows water and fish to move into the interior Delta. Previous studies have demonstrated that juvenile Chinook salmon experience greater mortality when migrating into Georgiana Slough than those juveniles that continue to migrate downstream in the Sacramento River (Perry 2010). Movement and/or diversion of these fish into the interior and south Delta increases the likelihood of losses through predation, entrainment into non-project Delta diversions, and mortality associated with the State Water Project (SWP) and Central Valley Project (CVP) pumping facilities in the south Delta (Perry 2010; NMFS 2009). Figure ES-1 shows the migration pathways in the lower Sacramento River and Delta for outmigrating anadromous salmonids, and the location of the DCC, and the SWP and CVP pumping facilities in the south Delta.</p>\n<p>Passage of juvenile salmonids from the Sacramento River into the interior Delta through the DCC can be reduced through seasonal closure of the radial gates (February through May); however, no similar protection is available to reduce the movement of juvenile salmonids from the Sacramento River into the interior Delta through Georgiana Slough. Flows into Georgiana Slough improve water quality and flushing in the interior Delta and free access encourages use by recreational boaters. Because of these benefits, alternatives to the installation of a physical barrier (i.e. radial gates), are being investigated.</p>\n<p>Under the ESA, the National Marine Fisheries Service (NMFS) issued the 2009 <i>Biological and Conference Opinion for the Long‐Term Operations of the Central Valley Project and State Water Project</i> (BO) for Chinook salmon and other listed anadromous fish species (NMFS 2009). Reasonable and Prudent Alternative (RPA) Action IV.1.3 of the BO requires the California Department of Water Resources (DWR) and the U.S. Bureau of Reclamation (Reclamation) to consider engineering solutions to reduce the diversion of juvenile salmonids from the Sacramento River into the interior and south Delta. DWR implemented the 2011 Georgiana Slough NonPhysical Barrier (GSNPB) Study to test the effectiveness of using a non-physical barrier, referred to as a behavioral Bio-Acoustic Fish Fence (BAFF), that combines three stimuli to deter juvenile Chinook salmon from entering Georgiana Slough: sound, high-intensity modulated light (previously known as stroboscopic light), and a bubble curtain. This report presents the results of the experimental tests conducted in 2011.</p>","language":"English","publisher":"California Department of Water Resources","usgsCitation":"Reeves, R.R., McQuirk, J., Ameri, K., Perry, R.W., Romine, J.G., Liedtke, T.L., Burau, J.R., Blake, A.R., Fitzer, C., Smith, N., Pagliughi, S., Johnston, S., Kumagai, K., and Cash, K., 2012, 2011 Georgiana Slough non-physical barrier performance evaluation project report, 228 p.","productDescription":"228 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-037369","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":320940,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":320939,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://data.ca.gov/dataset/2011-and-2012-georgiana-slough-non-physical-barrier-performance-evaluation-gsnpb-11_legacy_repo/resource/a0f2e749-df6b-4690-82ca-ee287750479a"}],"country":"United States","state":"California","otherGeospatial":"Georgiana Slough, Sacramento River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -121.76010131835938,\n              37.95286091815649\n            ],\n            [\n              -121.76010131835938,\n              38.34704152882895\n            ],\n            [\n              -121.4154052734375,\n              38.34704152882895\n            ],\n            [\n              -121.4154052734375,\n              37.95286091815649\n            ],\n            [\n              -121.76010131835938,\n              37.95286091815649\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","tableOfContents":"<p>ES EXECUTIVE SUMMARY</p>\n<p style=\"padding-left: 30px;\">ES.1 Introduction</p>\n<p style=\"padding-left: 30px;\">ES.2 Study Purpose, Objectives, and Overview</p>\n<p style=\"padding-left: 30px;\">ES.3 Study Results and Findings</p>\n<p style=\"padding-left: 30px;\">ES.4 Study Conclusions</p>\n<p style=\"padding-left: 30px;\">ES.5 Recommendations and Future Directions</p>\n<p>1 INTRODUCTION</p>\n<p style=\"padding-left: 30px;\">1.1 Background</p>\n<p style=\"padding-left: 30px;\">1.1 Study Purpose, Objectives, and Overview</p>\n<p>2 STUDY APPROACH AND METHODS</p>\n<p style=\"padding-left: 30px;\">2.1 Overview of Experimental Design</p>\n<p style=\"padding-left: 30px;\">2.2 Hypothesis Testing</p>\n<p style=\"padding-left: 30px;\">2.3 Statistical Basis and Fish Sample Sizes for the Experimental Design</p>\n<p style=\"padding-left: 30px;\">2.4 Experiment Implementation</p>\n<p style=\"padding-left: 30px;\">2.5 Monitoring and Data Collection</p>\n<p style=\"padding-left: 30px;\">2.6 Experimental Barrier Operations</p>\n<p style=\"padding-left: 30px;\">2.7 Statistical Analysis of Barrier Efficiency and Variables Affecting Fish Fates</p>\n<p>3 RESULTS AND DISCUSSION</p>\n<p style=\"padding-left: 30px;\">3.1 Environmental Conditions</p>\n<p style=\"padding-left: 30px;\">3.2 Fish Transport, Tagging, and Release</p>\n<p style=\"padding-left: 30px;\">3.3 Barrier Operations</p>\n<p style=\"padding-left: 30px;\">3.4 Barrier Deterrence, Protection, and Overall Efficiency</p>\n<p style=\"padding-left: 30px;\">3.5 Generalized Linear Model</p>\n<p style=\"padding-left: 30px;\">3.6 Survival and Route Entrainment Probabilities</p>\n<p style=\"padding-left: 30px;\">3.7 Predation</p>\n<p>4 SUMMARY OF FINDINGS AND CONCLUSIONS</p>\n<p style=\"padding-left: 30px;\">4.1 Study Findings</p>\n<p style=\"padding-left: 30px;\">4.2 Study Conclusions</p>\n<p>5 RECOMMENDATIONS AND FUTURE DIRECTIONS</p>\n<p>6 REFERENCES</p>\n<p>&nbsp;</p>","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5729cbaae4b0b13d3919a2d7","contributors":{"authors":[{"text":"Reeves, Ryan R. rreeves@usgs.gov","contributorId":4993,"corporation":false,"usgs":true,"family":"Reeves","given":"Ryan","email":"rreeves@usgs.gov","middleInitial":"R.","affiliations":[],"preferred":true,"id":628653,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McQuirk, Jacob","contributorId":169143,"corporation":false,"usgs":false,"family":"McQuirk","given":"Jacob","email":"","affiliations":[],"preferred":false,"id":628654,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ameri, Khalid","contributorId":169144,"corporation":false,"usgs":false,"family":"Ameri","given":"Khalid","email":"","affiliations":[],"preferred":false,"id":628655,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Perry, Russell W. 0000-0003-4110-8619 rperry@usgs.gov","orcid":"https://orcid.org/0000-0003-4110-8619","contributorId":2820,"corporation":false,"usgs":true,"family":"Perry","given":"Russell","email":"rperry@usgs.gov","middleInitial":"W.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":628656,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Romine, Jason G. 0000-0002-6938-1185 jromine@usgs.gov","orcid":"https://orcid.org/0000-0002-6938-1185","contributorId":2823,"corporation":false,"usgs":true,"family":"Romine","given":"Jason","email":"jromine@usgs.gov","middleInitial":"G.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":628657,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Liedtke, Theresa L. 0000-0001-6063-9867 tliedtke@usgs.gov","orcid":"https://orcid.org/0000-0001-6063-9867","contributorId":2999,"corporation":false,"usgs":true,"family":"Liedtke","given":"Theresa","email":"tliedtke@usgs.gov","middleInitial":"L.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":628658,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Burau, Jon R. 0000-0002-5196-5035 jrburau@usgs.gov","orcid":"https://orcid.org/0000-0002-5196-5035","contributorId":1500,"corporation":false,"usgs":true,"family":"Burau","given":"Jon","email":"jrburau@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":628659,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Blake, Aaron R. 0000-0001-7348-2336 ablake@usgs.gov","orcid":"https://orcid.org/0000-0001-7348-2336","contributorId":5059,"corporation":false,"usgs":true,"family":"Blake","given":"Aaron","email":"ablake@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":628660,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Fitzer, Chris","contributorId":169147,"corporation":false,"usgs":false,"family":"Fitzer","given":"Chris","affiliations":[{"id":13386,"text":"AECOM","active":true,"usgs":false}],"preferred":false,"id":628661,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Smith, Natalie","contributorId":169145,"corporation":false,"usgs":false,"family":"Smith","given":"Natalie","email":"","affiliations":[{"id":13386,"text":"AECOM","active":true,"usgs":false}],"preferred":false,"id":628662,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Pagliughi, Steve","contributorId":169146,"corporation":false,"usgs":false,"family":"Pagliughi","given":"Steve","affiliations":[{"id":13386,"text":"AECOM","active":true,"usgs":false}],"preferred":false,"id":628663,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Johnston, Sam","contributorId":169148,"corporation":false,"usgs":false,"family":"Johnston","given":"Sam","email":"","affiliations":[],"preferred":false,"id":628664,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Kumagai, Kevin","contributorId":169149,"corporation":false,"usgs":false,"family":"Kumagai","given":"Kevin","affiliations":[],"preferred":false,"id":628665,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Cash, Kenneth","contributorId":169150,"corporation":false,"usgs":false,"family":"Cash","given":"Kenneth","email":"","affiliations":[],"preferred":false,"id":628666,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}}
,{"id":70040327,"text":"ds709B - 2012 - Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Balkhab mineral district in Afghanistan: Chapter B in <i>Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan</i>","interactions":[],"lastModifiedDate":"2013-02-01T11:14:10","indexId":"ds709B","displayToPublicDate":"2012-09-05T00:00:00","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":"709","chapter":"B","title":"Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Balkhab mineral district in Afghanistan: Chapter B in <i>Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan</i>","docAbstract":"The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Balkhab mineral district, which has copper deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (&copy;JAXA,2007,2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. Therefore, it was necessary to (1) register the 10-m AVNIR multispectral imagery to a well-controlled Landsat image base, (2) mosaic the individual multispectral images into a single image of the entire area of interest, (3) register each panchromatic image to the registered multispectral image base, and (4) mosaic the individual panchromatic images into a single image of the entire area of interest. The two image-registration steps were facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band's picture element based on the digital values of all picture elements within a 315-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area's local zone (42 for Balkhab) and the WGS84 datum. The final image mosaics were subdivided into two overlapping tiles or quadrants because of the large size of the target area. The two image tiles (or quadrants) for the Balkhab area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image. Within the Balkhab study area, one subarea was designated for detailed field investigations (that is, the Balkhab Prospect subarea); this subarea was extracted from the area's image mosaic and is provided as separate embedded geotiff images.","largerWorkTitle":"Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan (DS 709)","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds709B","collaboration":"Prepared in cooperation with the U.S. Department of Defense <a href=\"http://tfbso.defense.gov/www/\" target=\"_blank\">Task Force for Business and Stability Operations</a> and the <a href=\"http://www.bgs.ac.uk/AfghanMinerals/\" target=\"_blank\">Afghanistan Geological Survey</a>. This report is Chapter B in <i>Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan</i>. For more information, see: <a href=\"http://pubs.er.usgs.gov/publication/ds709\" target=\"_blank\">DS 709</a>.","usgsCitation":"Davis, P.A., and Cagney, L.E., 2012, Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Balkhab mineral district in Afghanistan: Chapter B in <i>Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan</i>: U.S. Geological Survey Data Series 709, Readme; 2 Maps: 11 x 8.5 inches and 46.68 x 35.61 inches; 6 Image Files; 6 Metadata Files; Shapefiles; DS 709, https://doi.org/10.3133/ds709B.","productDescription":"Readme; 2 Maps: 11 x 8.5 inches and 46.68 x 35.61 inches; 6 Image Files; 6 Metadata Files; Shapefiles; DS 709","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"links":[{"id":262587,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds_709_B.jpg"},{"id":262584,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/709/b/","linkFileType":{"id":5,"text":"html"}},{"id":262586,"rank":400,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/b/index_maps/Balkhab_Image_Index_Map.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":262585,"rank":400,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/b/index_maps/Balkhab_Area-of-Interest_Index_Map.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":263621,"type":{"id":14,"text":"Image"},"url":"https://pubs.usgs.gov/ds/709/b/image_files/image_files.html"},{"id":263620,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/ds/709/b/1_readme.txt"},{"id":263622,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/ds/709/b/metadata/metadata.html"},{"id":263623,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/709/b/shapefiles/shapefiles.html"},{"id":263624,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/ds/709/"}],"country":"Afghanistan","state":"Balkh;Samangan;Sari-Pul","otherGeospatial":"Balkhab Mineral District","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 66.25,35.25 ], [ 66.25,35.916667 ], [ 67.25,35.916667 ], [ 67.25,35.25 ], [ 66.25,35.25 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"507d2378e4b0905c2a76c025","contributors":{"authors":[{"text":"Davis, Philip A. pdavis@usgs.gov","contributorId":692,"corporation":false,"usgs":true,"family":"Davis","given":"Philip","email":"pdavis@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":468095,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cagney, Laura E. 0000-0003-3282-2458 lcagney@usgs.gov","orcid":"https://orcid.org/0000-0003-3282-2458","contributorId":4744,"corporation":false,"usgs":true,"family":"Cagney","given":"Laura","email":"lcagney@usgs.gov","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":468096,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70039814,"text":"sir20125161 - 2012 - Groundwater flow and water budget in the surficial and Floridan aquifer systems in east-central Florida","interactions":[{"subject":{"id":70038861,"text":"ofr20121132 - 2012 - Groundwater flow and water budget in the surficial and Floridan aquifer systems in east-central Florida","indexId":"ofr20121132","publicationYear":"2012","noYear":false,"title":"Groundwater flow and water budget in the surficial and Floridan aquifer systems in east-central Florida"},"predicate":"SUPERSEDED_BY","object":{"id":70039814,"text":"sir20125161 - 2012 - Groundwater flow and water budget in the surficial and Floridan aquifer systems in east-central Florida","indexId":"sir20125161","publicationYear":"2012","noYear":false,"title":"Groundwater flow and water budget in the surficial and Floridan aquifer systems in east-central Florida"},"id":1}],"lastModifiedDate":"2018-04-02T15:33:30","indexId":"sir20125161","displayToPublicDate":"2012-09-05T00:00:00","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":"2012-5161","title":"Groundwater flow and water budget in the surficial and Floridan aquifer systems in east-central Florida","docAbstract":"A numerical transient model of the surficial and Floridan aquifer systems in east-central Florida was developed to (1) increase the understanding of water exchanges between the surficial and the Floridan aquifer systems, (2) assess the recharge rates to the surficial aquifer system from infiltration through the unsaturated zone and (3) obtain a simulation tool that could be used by water-resource managers to assess the impact of changes in groundwater withdrawals on spring flows and on the potentiometric surfaces of the hydrogeologic units composing the Floridan aquifer system. The hydrogeology of east-central Florida was evaluated and used to develop and calibrate the groundwater flow model, which simulates the regional fresh groundwater flow system. The U.S. Geological Survey three-dimensional groundwater flow model, MODFLOW-2005, was used to simulate transient groundwater flow in the surficial, intermediate, and Floridan aquifer systems from 1995 to 2006. The East-Central Florida Transient model encompasses an actively simulated area of about 9,000 square miles. Although the model includes surficial processes-rainfall, irrigation, evapotranspiration (ET), runoff, infiltration, lake water levels, and stream water levels and flows-its primary purpose is to characterize and refine the understanding of groundwater flow in the Floridan aquifer system. Model-independent estimates of the partitioning of rainfall into ET, streamflow, and aquifer recharge are provided from a water-budget analysis of the surficial aquifer system. The interaction of the groundwater flow system with the surface environment was simulated using the Green-Ampt infiltration method and the MODFLOW-2005 Unsaturated-Zone Flow, Lake, and Streamflow-Routing Packages. The model is intended to simulate the part of the groundwater system that contains freshwater. The bottom and lateral boundaries of the model were established at the estimated depths where the chloride concentration is 5,000 milligrams per liter in the Floridan aquifer system. Potential flow across the interface represented by this chloride concentration is simulated by the General Head Boundary Package. During 1995 through 2006, there were no major groundwater withdrawals near the freshwater and saline-water interface, making the general head boundary a suitable feature to estimate flow through the interface.  The east-central Florida transient model was calibrated using the inverse parameter estimation code, PEST. Steady-state models for 1999 and 2003 were developed to estimate hydraulic conductivity (K) using average annual heads and spring flows as observations. The spatial variation of K was represented using zones of constant values in some layers, and pilot points in other layers. Estimated K values were within one order of magnitude of aquifer performance test data. A simulation of the final two years (2005-2006) of the 12-year model, with the K estimates from the steady-state calibration, was used to guide the estimation of specific yield and specific storage values. The final model yielded head and spring-flow residuals that met the calibration criteria for the 12-year transient simulation. The overall mean residual for heads, defining residual as simulated minus measured value, was -0.04 foot. The overall root-mean square residual for heads was less than 3.6 feet for each year in the 1995 to 2006 simulation period. The overall mean residual for spring flows was -0.3 cubic foot per second. The spatial distribution of head residuals was generally random, with some minor indications of bias. Simulated average ET over the 1995 to 2006 period was 34.47 inches per year, compared to the calculated average ET rate of 36.39 inches per year from the model-independent water-budget analysis. Simulated average net recharge to the surficial aquifer system was 3.58 inches per year, compared with the calculated average of 3.39 inches per year from the model-independent water-budget analysis. Groundwater withdrawals from the Floridan aquifer system averaged about 920 million gallons per day, which is equivalent to about 2 inches per year over the model area and slightly more than half of the simulated average net recharge to the surficial aquifer system over the same period. Annual net simulated recharge rates to the surficial aquifer system were less than the total groundwater withdrawals from the Floridan aquifer system only during the below-average rainfall years of 2000 and 2006.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125161","collaboration":"Prepared in cooperation with the St. Johns River Water Management District, South Florida Water Management District, and Southwest Florida Water Management District","usgsCitation":"Sepulveda, N., Tiedeman, C.R., O’Reilly, A.M., Davis, J.B., and Burger, P., 2012, Groundwater flow and water budget in the surficial and Floridan aquifer systems in east-central Florida: U.S. Geological Survey Scientific Investigations Report 2012-5161, xiii, 214 p., https://doi.org/10.3133/sir20125161.","productDescription":"xiii, 214 p.","onlineOnly":"Y","costCenters":[{"id":285,"text":"Florida Water Science Center","active":false,"usgs":true}],"links":[{"id":260178,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5161.jpg"},{"id":260176,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5161/pdf/2012-5161.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":260177,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5161/","linkFileType":{"id":5,"text":"html"}}],"projection":"Universal Transverse Mercator, zone 17","country":"United States","state":"Florida","county":"Lake;Osceola;Orange;Polk;Seminole","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -82,27.5 ], [ -82,29 ], [ -80.5,29 ], [ -80.5,27.5 ], [ -82,27.5 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a2da0e4b0c8380cd5bf67","contributors":{"authors":[{"text":"Sepulveda, Nicasio 0000-0002-6333-1865 nsepul@usgs.gov","orcid":"https://orcid.org/0000-0002-6333-1865","contributorId":1454,"corporation":false,"usgs":true,"family":"Sepulveda","given":"Nicasio","email":"nsepul@usgs.gov","affiliations":[{"id":5051,"text":"FLWSC-Orlando","active":true,"usgs":true}],"preferred":true,"id":466979,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tiedeman, Claire R. 0000-0002-0128-3685 tiedeman@usgs.gov","orcid":"https://orcid.org/0000-0002-0128-3685","contributorId":196777,"corporation":false,"usgs":true,"family":"Tiedeman","given":"Claire","email":"tiedeman@usgs.gov","middleInitial":"R.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":466982,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"O’Reilly, Andrew M. 0000-0003-3220-1248 aoreilly@usgs.gov","orcid":"https://orcid.org/0000-0003-3220-1248","contributorId":2184,"corporation":false,"usgs":true,"family":"O’Reilly","given":"Andrew","email":"aoreilly@usgs.gov","middleInitial":"M.","affiliations":[{"id":5051,"text":"FLWSC-Orlando","active":true,"usgs":true}],"preferred":true,"id":466980,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Davis, Jeffrey B.","contributorId":50168,"corporation":false,"usgs":true,"family":"Davis","given":"Jeffrey","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":466981,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Burger, Patrick","contributorId":90976,"corporation":false,"usgs":true,"family":"Burger","given":"Patrick","email":"","affiliations":[],"preferred":false,"id":466983,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70039807,"text":"sim3226 - 2012 - Flood-inundation maps for Suwanee Creek from the confluence of Ivy Creek to the Noblin Ridge Drive bridge, Gwinnett County, Georgia","interactions":[],"lastModifiedDate":"2017-01-13T09:40:31","indexId":"sim3226","displayToPublicDate":"2012-09-04T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3226","title":"Flood-inundation maps for Suwanee Creek from the confluence of Ivy Creek to the Noblin Ridge Drive bridge, Gwinnett County, Georgia","docAbstract":"Digital flood-inundation maps for a 6.9-mile reach of Suwanee Creek, from the confluence of Ivy Creek to the Noblin Ridge Drive bridge, were developed by the U.S. Geological Survey (USGS) in cooperation with Gwinnett County, Georgia. The inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at <a href=\"http://water.usgs.gov/osw/flood_inundation/\">http://water.usgs.gov/osw/flood_inundation/</a>, depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage at Suwanee Creek at Suwanee, Georgia (02334885). Current stage at this USGS streamgage may be obtained at <a href=\"http://waterdata.usgs.gov/\">http://waterdata.usgs.gov/</a> and can be used in conjunction with these maps to estimate near real-time areas of inundation. The National Weather Service (NWS) is incorporating results from this study into the Advanced Hydrologic Prediction Service (AHPS) flood-warning system (<a href=\"http://water.weather.gov/ahps/\">http://water.weather.gov/ahps/</a>). The NWS forecasts flood hydrographs at many places that commonly are collocated at USGS streamgages. The forecasted peak-stage information for the USGS streamgage at Suwanee Creek at Suwanee (02334885), available through the AHPS Web site, may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation. A one-dimensional step-backwater model was developed using the U.S. Army Corps of Engineers HEC-RAS software for Suwanee Creek and was used to compute flood profiles for a 6.9-mile reach of the creek. The model was calibrated using the most current stage-discharge relations at the Suwanee Creek at Suwanee streamgage (02334885). The hydraulic model was then used to determine 19 water-surface profiles for flood stages at the Suwanee Creek streamgage at 0.5-foot intervals referenced to the streamgage. The profiles ranged from just above bankfull stage (7.0 feet) to approximately 1.7 feet above the highest recorded water level at the streamgage (16.0 feet). The simulated water-surface profiles were then combined with a geographic information system digital elevation model - derived from light detection and ranging (LiDAR) data having a 5.0-foot horizontal resolution - to delineate the area flooded for each 0.5-foot increment of stream stage. The availability of these maps, when combined with real-time stage information from USGS streamgages and forecasted stream stage from the NWS, provides emergency management personnel and residents with critical information during flood-response activities, such as evacuations and road closures, as well as for post-flood recovery efforts.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3226","collaboration":"Prepared in cooperation with Gwinnett County, Georgia","usgsCitation":"Musser, J.W., 2012, Flood-inundation maps for Suwanee Creek from the confluence of Ivy Creek to the Noblin Ridge Drive bridge, Gwinnett County, Georgia: U.S. Geological Survey Scientific Investigations Map 3226, Report: v, 8 p.; 19 Sheets: 34 x 24 inches; Downloads Directory, https://doi.org/10.3133/sim3226.","productDescription":"Report: v, 8 p.; 19 Sheets: 34 x 24 inches; Downloads Directory","numberOfPages":"18","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":260164,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim_3226.jpg"},{"id":260158,"rank":416,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3226/sheets/Sheet17_flood_inundation_map_SuwaneeCr.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":260143,"rank":401,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3226/sheets/Sheet2_flood_inundation_map_SuwaneeCr.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":260141,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3226/pdf/sim3226.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":260142,"rank":400,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3226/sheets/Sheet1_flood_inundation_map_SuwaneeCr.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":260140,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3226/","linkFileType":{"id":5,"text":"html"}},{"id":260144,"rank":402,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3226/sheets/Sheet3_flood_inundation_map_SuwaneeCr.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":260145,"rank":403,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3226/sheets/Sheet4_flood_inundation_map_SuwaneeCr.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":260146,"rank":404,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3226/sheets/Sheet5_flood_inundation_map_SuwaneeCr.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":260147,"rank":405,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3226/sheets/Sheet6_flood_inundation_map_SuwaneeCr.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":260148,"rank":406,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3226/sheets/Sheet7_flood_inundation_map_SuwaneeCr.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":260149,"rank":407,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3226/sheets/Sheet8_flood_inundation_map_SuwaneeCr.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":260150,"rank":408,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3226/sheets/Sheet9_flood_inundation_map_SuwaneeCr.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":260151,"rank":409,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3226/sheets/Sheet10_flood_inundation_map_SuwaneeCr.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":260152,"rank":410,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3226/sheets/Sheet11_flood_inundation_map_SuwaneeCr.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":260153,"rank":411,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3226/sheets/Sheet12_flood_inundation_map_SuwaneeCr.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":260154,"rank":412,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3226/sheets/Sheet13_flood_inundation_map_SuwaneeCr.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":260155,"rank":413,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3226/sheets/Sheet14_flood_inundation_map_SuwaneeCr.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":260156,"rank":414,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3226/sheets/Sheet15_flood_inundation_map_SuwaneeCr.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":260157,"rank":415,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3226/sheets/Sheet16_flood_inundation_map_SuwaneeCr.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":260159,"rank":417,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3226/sheets/Sheet18_flood_inundation_map_SuwaneeCr.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":260160,"rank":418,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3226/sheets/Sheet19_flood_inundation_map_SuwaneeCr.pdf","linkFileType":{"id":1,"text":"pdf"}}],"scale":"24000","country":"United States","state":"Georgia","county":"Gwinnett County","otherGeospatial":"Suwanee Creek","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -84.11666666666666,34 ], [ -84.11666666666666,34.083333333333336 ], [ -84.03333333333333,34.083333333333336 ], [ -84.03333333333333,34 ], [ -84.11666666666666,34 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a1166e4b0c8380cd53fa0","contributors":{"authors":[{"text":"Musser, Jonathan W. 0000-0002-3543-0807 jwmusser@usgs.gov","orcid":"https://orcid.org/0000-0002-3543-0807","contributorId":2266,"corporation":false,"usgs":true,"family":"Musser","given":"Jonathan","email":"jwmusser@usgs.gov","middleInitial":"W.","affiliations":[{"id":13634,"text":"South Atlantic Water Science 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,{"id":70039874,"text":"ofr20121193 - 2012 - Demographics and run timing of adult Lost River (<i>Deltistes luxatus</i>) and shortnose (<i>Chasmistes brevirostris</i>) suckers in Upper Klamath Lake, Oregon, 2011","interactions":[],"lastModifiedDate":"2016-05-03T13:24:05","indexId":"ofr20121193","displayToPublicDate":"2012-09-03T15:56:00","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":"2012-1193","title":"Demographics and run timing of adult Lost River (<i>Deltistes luxatus</i>) and shortnose (<i>Chasmistes brevirostris</i>) suckers in Upper Klamath Lake, Oregon, 2011","docAbstract":"<h1>Executive Summary</h1>\n<p>Data from a long-term capture-recapture program were used to assess the status and dynamics of populations of two long-lived, federally endangered catostomids in Upper Klamath Lake, Oregon. Lost River suckers (<i>Deltistes luxatus</i>) and shortnose suckers (<i>Chasmistes brevirostris</i>) have been captured and tagged with passive integrated transponder (PIT) tags during their spawning migrations in each year since 1995. In addition, beginning in 2005, individuals that had been previously PIT-tagged were re-encountered on remote underwater antennas deployed throughout sucker spawning areas. Captures and remote encounters during spring 2011 were used to describe the spawning migrations in that year and also were incorporated into capture-recapture analyses of population dynamics.</p>\n<p>Cormack-Jolly-Seber (CJS) open population capture-recapture models were used to estimate annual survival probabilities, and a reverse-time analog of the CJS model was used to estimate recruitment of new individuals into the spawning populations. In addition, data on the size composition of captured fish was examined to provide corroborating evidence of recruitment. Survival and recruitment estimates were used to derive estimates of changes in population size over time and to determine the status of the populations in 2010. Separate analyses were conducted for each species and also for each subpopulation of Lost River suckers (LRS). One subpopulation of LRS migrates into tributaries to spawn, similar to shortnose suckers (SNS), whereas the other subpopulation spawns at upwelling areas along the eastern shoreline of the lake.</p>\n<p>In 2011, we captured, tagged, and released 806 LRS at four lakeshore spawning areas and recaptured an additional 1,006 individuals that had been tagged in previous years. Across all four areas, the remote antennas detected 6,547 individual LRS during the spawning season. Spawning activity peaked in April and most individuals were encountered at Sucker Springs and Cinder Flats. In the Williamson River, we captured, tagged, and released 2,742 LRS and 123 SNS, and recaptured 376 LRS and 58 SNS that had been tagged in previous years. Remote PIT tag antennas in the traps at the weir on the Williamson River and remote antenna systems that spanned the river at four different locations on the Williamson and Sprague Rivers detected a total of 16,494 LRS and 5,450 SNS. Most LRS passed upstream between mid-April and mid-May when water temperatures were rising and near or greater than 10 &deg;C. In contrast, the largest peaks in upstream passage of SNS occurred in early and mid-May when water temperatures were rising and near or greater than 12 &deg;C. Finally, an additional 875 LRS and 1,600 SNS were captured in trammel net sampling at pre-spawn staging areas in the northeastern portion of the lake. Of these, 191of the LRS and 571 of the SNS had been PIT-tagged in previous years. For LRS, encounter histories showed that more than 90 percent of the fish captured at the staging areas were members of the subpopulation that spawns in the tributaries.</p>\n<p>Capture-recapture analyses for the LRS subpopulation that spawns at the shoreline areas included encounter histories for more than 10,500 individuals, and analyses for the subpopulation that spawns in the tributaries included more than 22,000 encounter histories. With a few exceptions, the survival of males and females in both subpopulations was high (greater than 0.9) between 1999 and 2009. Notably lower survival occurred for both sexes from the tributaries in 2000, for both sexes from the shoreline areas in 2002, and for males from the tributaries in 2006. Between 2001 and 2010, the abundance of males in the lakeshore spawning subpopulation decreased by 50&ndash;60 percent and the abundance of females decreased by 29&ndash;44 percent. Capture-recapture models suggested that the abundance of the river spawning subpopulation of LRS has increased substantially since 2006. The increase over this period was largely due to large estimated recruitment events in 2003, 2006, and 2008. We know that the estimate in 2006 is substantially biased in favor of recruitment due to a sampling issue. We are skeptical of the magnitude of recruitment indicated by the 2003 and 2008 estimates as well because very few small individuals that would indicate the presence of new recruits were captured in those years. If we assume that little or no recruitment has occurred, the abundance of both sexes in the river spawning subpopulation decreased by more than 40 percent between 2002 and 2010.</p>\n<p>Capture-recapture analyses for SNS included encounter histories for more than 15,500 individuals. The majority of annual survival estimates between 2001 and 2009 were high (greater than 0.8), but SNS did experience more years of low survival than either LRS subpopulation. The survival of both sexes was particularly low in both 2001 and 2004, and male survival also was somewhat low in 2002 and 2006. Capture-recapture models and size composition data indicated that recruitment of new individuals into the SNS spawning population was trivial in nearly all years between 2001 and 2009. As a result, the abundance of males decreased by 64&ndash;82 percent and the abundance of females decreased by 62&ndash;76 percent between 2001 and 2010.</p>\n<p>Despite relatively high survival in most years, both species have experienced substantial declines in the abundance of spawning fish because losses from mortality have not been balanced by recruitment of new individuals. Although capture-recapture data indicate substantial recruitment of new individuals into the adult spawning populations for SNS and river spawning LRS in some years, size data do not corroborate these estimates. In fact, fork length data indicate that all populations are largely comprised of fish that were present in the late 1990s and early 2000s. As a result, the status of the endangered sucker populations in Upper Klamath Lake remains worrisome, and the situation is most dire for shortnose suckers. Future investigations should explore the connections between sucker recruitment and survival and various environmental factors, such as water quality and disease. Our monitoring program provides a robust platform for estimating vital population parameters, evaluating the status of the populations, and assessing the effectiveness of conservation and recovery efforts.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121193","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Hewitt, D.A., Janney, E.C., Hayes, B., and Harris, A., 2012, Demographics and run timing of adult Lost River (<i>Deltistes luxatus</i>) and shortnose (<i>Chasmistes brevirostris</i>) suckers in Upper Klamath Lake, Oregon, 2011: U.S. Geological Survey Open-File Report 2012-1193, vii, 42 p., https://doi.org/10.3133/ofr20121193.","productDescription":"vii, 42 p.","numberOfPages":"52","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":261836,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1193.jpg"},{"id":261832,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1193/pdf/ofr20121193.pdf","text":"Report","size":"2.25 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":261831,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1193/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"California, Oregon","otherGeospatial":"Klamath River Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.16666666666667,42.166666666666664 ], [ -122.16666666666667,42.666666666666664 ], [ -121.75,42.666666666666664 ], [ -121.75,42.166666666666664 ], [ -122.16666666666667,42.166666666666664 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059fe86e4b0c8380cd4ed8b","contributors":{"authors":[{"text":"Hewitt, David A. 0000-0002-5387-0275 dhewitt@usgs.gov","orcid":"https://orcid.org/0000-0002-5387-0275","contributorId":3767,"corporation":false,"usgs":false,"family":"Hewitt","given":"David","email":"dhewitt@usgs.gov","middleInitial":"A.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":467113,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Janney, Eric C. 0000-0002-0228-2174","orcid":"https://orcid.org/0000-0002-0228-2174","contributorId":83629,"corporation":false,"usgs":true,"family":"Janney","given":"Eric","email":"","middleInitial":"C.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":false,"id":467115,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hayes, Brian S. 0000-0001-8229-4070","orcid":"https://orcid.org/0000-0001-8229-4070","contributorId":37022,"corporation":false,"usgs":true,"family":"Hayes","given":"Brian S.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":false,"id":467114,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Harris, Alta C. 0000-0002-2123-3028 aharris@usgs.gov","orcid":"https://orcid.org/0000-0002-2123-3028","contributorId":3490,"corporation":false,"usgs":true,"family":"Harris","given":"Alta C.","email":"aharris@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":467112,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70158993,"text":"70158993 - 2012 - Validation of the ASTER Global Digital Elevation Model Version 2 over the conterminous United States","interactions":[],"lastModifiedDate":"2017-04-25T16:27:48","indexId":"70158993","displayToPublicDate":"2012-09-03T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Validation of the ASTER Global Digital Elevation Model Version 2 over the conterminous United States","docAbstract":"<p><span>The ASTER Global Digital Elevation Model Version 2 (GDEM v2) was evaluated over the conterminous United States in a manner similar to the validation conducted for the original GDEM Version 1 (v1) in 2009. The absolute vertical accuracy of GDEM v2 was calculated by comparison with more than 18,000 independent reference geodetic ground control points from the National Geodetic Survey. The root mean square error (RMSE) measured for GDEM v2 is 8.68 meters. This compares with the RMSE of 9.34 meters for GDEM v1. Another important descriptor of vertical accuracy is the mean error, or bias, which indicates if a DEM has an overall vertical offset from true ground level. The GDEM v2 mean error of -0.20 meters is a significant improvement over the GDEM v1 mean error of -3.69 meters. The absolute vertical accuracy assessment results, both mean error and RMSE, were segmented by land cover to examine the effects of cover types on measured errors. The GDEM v2 mean errors by land cover class verify that the presence of aboveground features (tree canopies and built structures) cause a positive elevation bias, as would be expected for an imaging system like ASTER. In open ground classes (little or no vegetation with significant aboveground height), GDEM v2 exhibits a negative bias on the order of 1 meter. GDEM v2 was also evaluated by differencing with the Shuttle Radar Topography Mission (SRTM) dataset. In many forested areas, GDEM v2 has elevations that are higher in the canopy than SRTM.</span></p>","largerWorkType":{"id":24,"text":"Conference Paper"},"largerWorkTitle":"Imaging a sustainable future, 22nd Congress","conferenceTitle":"Imaging a sustainable future, 22nd Congress","conferenceDate":"August 24 - September 3 2012","conferenceLocation":"Melbourne, Australia","language":"English","publisher":"International Society for Photogrammetry and Remote Sensing","publisherLocation":"August 24 - September 3 2012","doi":"10.5194/isprsarchives-XXXIX-B4-281-2012","usgsCitation":"Gesch, D.B., Oimoen, M.J., Zhang, Z., Meyer, D.J., and Danielson, J.J., 2012, Validation of the ASTER Global Digital Elevation Model Version 2 over the conterminous United States, <i>in</i> Imaging a sustainable future, 22nd Congress, Melbourne, Australia, August 24 - September 3 2012, p. 281-286, https://doi.org/10.5194/isprsarchives-XXXIX-B4-281-2012.","productDescription":"6 p.","startPage":"281","endPage":"286","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-037242","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":474368,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/isprsarchives-xxxix-b4-281-2012","text":"Publisher Index Page"},{"id":309817,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2012-07-31","publicationStatus":"PW","scienceBaseUri":"5618e535e4b0cdb063e3fef4","contributors":{"authors":[{"text":"Gesch, Dean B. 0000-0002-8992-4933 gesch@usgs.gov","orcid":"https://orcid.org/0000-0002-8992-4933","contributorId":2956,"corporation":false,"usgs":true,"family":"Gesch","given":"Dean","email":"gesch@usgs.gov","middleInitial":"B.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":577174,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Oimoen, Michael J. 0000-0003-3611-6227 oimoen@usgs.gov","orcid":"https://orcid.org/0000-0003-3611-6227","contributorId":4757,"corporation":false,"usgs":true,"family":"Oimoen","given":"Michael","email":"oimoen@usgs.gov","middleInitial":"J.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":577175,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zhang, Zhen 0000-0003-0899-1139","orcid":"https://orcid.org/0000-0003-0899-1139","contributorId":149173,"corporation":false,"usgs":false,"family":"Zhang","given":"Zhen","email":"","affiliations":[],"preferred":false,"id":577176,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Meyer, David J.","contributorId":149174,"corporation":false,"usgs":false,"family":"Meyer","given":"David","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":577177,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Danielson, Jeffrey J. 0000-0003-0907-034X daniels@usgs.gov","orcid":"https://orcid.org/0000-0003-0907-034X","contributorId":3996,"corporation":false,"usgs":true,"family":"Danielson","given":"Jeffrey","email":"daniels@usgs.gov","middleInitial":"J.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":577178,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70200749,"text":"70200749 - 2012 - Problem of the Love‐Gannon relation between the asymmetric disturbance field and Dst","interactions":[],"lastModifiedDate":"2018-10-30T15:42:42","indexId":"70200749","displayToPublicDate":"2012-09-01T15:42:35","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2313,"text":"Journal of Geophysical Research A: Space Physics","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Problem of the Love‐Gannon relation between the asymmetric disturbance field and <i>Dst</i>","title":"Problem of the Love‐Gannon relation between the asymmetric disturbance field and Dst","docAbstract":"<p><span>Love and Gannon (2009) discovered that statistically, over a fifty year period the difference in the dawn and dusk disturbance‐field&nbsp;</span><i>H</i><span>&nbsp;component at low latitudes (hourly averaged) is linearly proportional to&nbsp;</span><i>Dst.</i><span>&nbsp;If the difference is designated by&nbsp;</span><i>δ</i><sub><i>DD</i></sub><span>&nbsp;in units of nT/R</span><sub>E</sub><span>, then the Love‐Gannon (L‐G) relation is&nbsp;</span><i>δ</i><sub><i>DD</i></sub><span>&nbsp;=&nbsp;</span><i>−</i><span>0.2&nbsp;</span><i>Dst.</i><span>&nbsp;At any time departures from the relation can be large. Nonetheless, the relation is evident for all values of&nbsp;</span><i>Dst</i><span>&nbsp;and persists throughout magnetic storms, both the main phase and the recovery phase. The Love‐Gannon discovery presents a problem to current understanding of the relation between the causes of&nbsp;</span><i>δ</i><sub><i>DD</i></sub><span>&nbsp;and&nbsp;</span><i>Dst</i><span>&nbsp;because the dawn dusk asymmetry in the disturbance field is presumably governed by a long‐established magnetosphere‐ionosphere coupling theory which predicts a characteristic time scale (the shielding time) of less than an hour whereas the characteristic time scale for&nbsp;</span><i>Dst</i><span>&nbsp;(the ring current decay time) is more like ten hours. Thus, without forcing both time scales toward each other to the limits of their ranges, a linear proportionality between&nbsp;</span><i>δ</i><sub><i>DD</i></sub><span>&nbsp;and&nbsp;</span><i>Dst</i><span>&nbsp;cannot be derived from the current understanding of the causes of the asymmetry and the ring current. This conclusion is the paper's main contribution. In addition, we attempt to get around the conflict of time scales by looking at other possibilities for generating&nbsp;</span><i>δ</i><sub><i>DD</i></sub><span>&nbsp;that depend directly on the ring current. The most promising of these is the possibility that the ring current decay mechanism creates a quasi‐permanent, local‐time modification of the ring current compared to what it would be in the absence of the decay mechanism and that this modification causes a field‐aligned current that closes through the ionosphere and generates the asymmetry&nbsp;</span><i>δ</i><sub><i>DD</i></sub><span>. This idea has the virtue of coupling the asymmetry directly to the ring current and of accounting for the persistence of the L‐G proportionality through the recovery phase of magnetic storms.</span></p>","language":"English","publisher":"AGU","doi":"10.1029/2012JA017879","usgsCitation":"Siscoe, G.L., Love, J.J., and Gannon, J., 2012, Problem of the Love‐Gannon relation between the asymmetric disturbance field and Dst: Journal of Geophysical Research A: Space Physics, v. 117, no. A9, A09216; 11 p., https://doi.org/10.1029/2012JA017879.","productDescription":"A09216; 11 p.","ipdsId":"IP-039196 ","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":358987,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"117","issue":"A9","noUsgsAuthors":false,"publicationDate":"2012-09-06","publicationStatus":"PW","scienceBaseUri":"5c10bd73e4b034bf6a7efe19","contributors":{"authors":[{"text":"Siscoe, G. L.","contributorId":210281,"corporation":false,"usgs":false,"family":"Siscoe","given":"G.","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":750359,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":750360,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gannon, J.L.","contributorId":78275,"corporation":false,"usgs":true,"family":"Gannon","given":"J.L.","email":"","affiliations":[],"preferred":false,"id":750361,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70150345,"text":"70150345 - 2012 - Effects of flow dynamics on the aquatic-terrestrial transition zone (ATTZ) of lower Missouri river sandbars with implications for selected biota","interactions":[],"lastModifiedDate":"2015-06-29T10:06:03","indexId":"70150345","displayToPublicDate":"2012-09-01T11:15:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3301,"text":"River Research and Applications","active":true,"publicationSubtype":{"id":10}},"title":"Effects of flow dynamics on the aquatic-terrestrial transition zone (ATTZ) of lower Missouri river sandbars with implications for selected biota","docAbstract":"<p>Sandbars are an important aquatic terrestrial transition zone (ATTZ) in the active channel of rivers that provide a variety of habitat conditions for riverine biota. Channelization and flow regulation in many large rivers have diminished sandbar habitats and their rehabilitation is a priority. We developed sandbar-specific models of discharge-area relationships to determine how changes in flow regime affect the area of different habitat types within the submerged sandbar ATTZ (depth) and exposed sandbar ATTZ (elevation) for a representative sample of Lower Missouri River sandbars. We defined six different structural habitat types within the sandbar ATTZ based on depth or exposed elevation ranges that are important to different biota during at least part of their annual cycle for either survival or reproduction. Scenarios included the modelled natural flow regime, current managed flow regime and two environmental flow options, all modelled within the contemporary river active channel. Thirteen point and wing-dike sandbars were evaluated under four different flow scenarios to explore the effects of flow regime on seasonal habitat availability for foraging of migratory shorebirds and wading birds, nesting of softshell turtles and nursery of riverine fishes. Managed flows provided more foraging habitat for shorebirds and wading birds and more nursery habitat for riverine fishes within the channelized reach sandbar ATTZ than the natural flow regime or modelled environmental flows. Reduced summer flows occurring under natural and environmental flow alternatives increased exposed sandbar nesting habitat for softshell turtle hatchling emergence. Results reveal how management of channelized and flow regulated large rivers could benefit from a modelling framework that couples hydrologic and geomorphic characteristics to predict habitat conditions for a variety of biota.</p>","language":"English","publisher":"John Wiley & Sons","publisherLocation":"Chichester, West Sussex, UK","doi":"10.1002/rra.1492","usgsCitation":"Tracy-Smith, E., Galat, D.L., and Jacobson, R.B., 2012, Effects of flow dynamics on the aquatic-terrestrial transition zone (ATTZ) of lower Missouri river sandbars with implications for selected biota: River Research and Applications, v. 28, no. 7, p. 793-813, https://doi.org/10.1002/rra.1492.","productDescription":"21 p.","startPage":"793","endPage":"813","numberOfPages":"21","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-021713","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":305428,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"28","issue":"7","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2011-02-25","publicationStatus":"PW","scienceBaseUri":"55926c9de4b0b6d21dd67783","contributors":{"authors":[{"text":"Tracy-Smith, Emily","contributorId":145409,"corporation":false,"usgs":false,"family":"Tracy-Smith","given":"Emily","email":"","affiliations":[],"preferred":false,"id":556720,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Galat, David L.","contributorId":13711,"corporation":false,"usgs":true,"family":"Galat","given":"David","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":563901,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jacobson, Robert B. 0000-0002-8368-2064 rjacobson@usgs.gov","orcid":"https://orcid.org/0000-0002-8368-2064","contributorId":1289,"corporation":false,"usgs":true,"family":"Jacobson","given":"Robert","email":"rjacobson@usgs.gov","middleInitial":"B.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":563902,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70040983,"text":"70040983 - 2012 - Using mark-recapture models to estimate survival from telemetry data: Chapter 9.2","interactions":[{"subject":{"id":70040983,"text":"70040983 - 2012 - Using mark-recapture models to estimate survival from telemetry data: Chapter 9.2","indexId":"70040983","publicationYear":"2012","noYear":false,"title":"Using mark-recapture models to estimate survival from telemetry data: Chapter 9.2"},"predicate":"IS_PART_OF","object":{"id":70198150,"text":"70198150 - 2012 - Telemetry techniques: A user guide for fisheries research","indexId":"70198150","publicationYear":"2012","noYear":false,"title":"Telemetry techniques: A user guide for fisheries research"},"id":1}],"isPartOf":{"id":70198150,"text":"70198150 - 2012 - Telemetry techniques: A user guide for fisheries research","indexId":"70198150","publicationYear":"2012","noYear":false,"title":"Telemetry techniques: A user guide for fisheries research"},"lastModifiedDate":"2022-12-21T15:24:29.732869","indexId":"70040983","displayToPublicDate":"2012-09-01T09:15:00","publicationYear":"2012","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Using mark-recapture models to estimate survival from telemetry data: Chapter 9.2","docAbstract":"<p>Analyzing telemetry data within a mark–recapture framework is a powerful approach for estimating demographic parameters (e.g., survival and movement probabilities) that might otherwise be difficult to measure. Yet many studies using telemetry techniques focus on fish behavior and fail to recognize the potential of telemetry data to provide information about fish survival. The sophistication of both mark–recapture modeling and telemetry has dramatically improved since the 1980s, largely due to technological advancements in computing power (for mark–recapture models) and electronic components (for telemetry). Such advances now allow mark–recapture models to take advantage of the detailed information that telemetry techniques can provide.</p><p>The key feature of mark–recapture models is simultaneous estimation of detection and survival probabilities. With telemetry, a “capture” event consists of detecting a given tag code one or more times at a specific location or time. By contrast, in some studies interest may focus on the probability of detecting a single tag transmission (see Sections 7.2 and 9.1). Compared to conventional mark and recapture methods, telemetry methods often have greater detection probabilities due to large detection ranges, increased “effort” (i.e., continuous monitoring with autonomous receivers), and ability to simultaneously monitor multiple locations. Nonetheless, perfect detectability is rare in telemetry studies because both random (e.g., from electronic noise) and nonrandom processes (e.g., receiver loses power temporarily) can allow a fish to pass a receiver undetected. Failure to account for imperfect detection can lead to serious bias in survival estimates. When using telemetry to estimate survival, it is therefore critical to explicitly estimate detection probabilities to ensure unbiased estimates of survival (see Section 7.2). Fortunately, using telemetry techniques and mark–recapture models together yields the best of both worlds: Well-designed telemetry systems deliver high detection probabilities that result in precise estimates from small sample sizes. Mark–recapture models ensure estimates of the demographic parameters are unbiased with respect to the detection process.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Telemetry techniques: A user guide for fisheries research","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"American Fisheries Society","publisherLocation":"Bethesda, MD","doi":"10.47886/9781934874264.ch19","usgsCitation":"Perry, R.W., Castro-Santos, T.R., Holbrook, C., and Sandford, B., 2012, Using mark-recapture models to estimate survival from telemetry data: Chapter 9.2, chap. <i>of</i> Telemetry techniques: A user guide for fisheries research, p. 453-475, https://doi.org/10.47886/9781934874264.ch19.","productDescription":"23 p.","startPage":"453","endPage":"475","numberOfPages":"518","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-037563","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":319642,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56fd062fe4b0a6037df2d077","contributors":{"editors":[{"text":"Adams, Noah","contributorId":91604,"corporation":false,"usgs":true,"family":"Adams","given":"Noah","affiliations":[],"preferred":false,"id":625682,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Beeman, John W. jbeeman@usgs.gov","contributorId":2646,"corporation":false,"usgs":true,"family":"Beeman","given":"John","email":"jbeeman@usgs.gov","middleInitial":"W.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":625683,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Eiler, John H.","contributorId":146952,"corporation":false,"usgs":false,"family":"Eiler","given":"John","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":625684,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Perry, Russell W. 0000-0003-4110-8619 rperry@usgs.gov","orcid":"https://orcid.org/0000-0003-4110-8619","contributorId":2820,"corporation":false,"usgs":true,"family":"Perry","given":"Russell","email":"rperry@usgs.gov","middleInitial":"W.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":625658,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Castro-Santos, Theodore R. 0000-0003-2575-9120 tcastrosantos@usgs.gov","orcid":"https://orcid.org/0000-0003-2575-9120","contributorId":3321,"corporation":false,"usgs":true,"family":"Castro-Santos","given":"Theodore","email":"tcastrosantos@usgs.gov","middleInitial":"R.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":625659,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Holbrook, Christopher M. 0000-0001-8203-6856 cholbrook@usgs.gov","orcid":"https://orcid.org/0000-0001-8203-6856","contributorId":4198,"corporation":false,"usgs":true,"family":"Holbrook","given":"Christopher M.","email":"cholbrook@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":625660,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sandford, Benjamin P.","contributorId":118178,"corporation":false,"usgs":true,"family":"Sandford","given":"Benjamin P.","affiliations":[],"preferred":false,"id":515037,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70044110,"text":"70044110 - 2012 - Time-to-event analysis as a framework for quantifying fish passage performance","interactions":[],"lastModifiedDate":"2022-12-27T16:31:22.906306","indexId":"70044110","displayToPublicDate":"2012-09-01T09:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"chapter":"9.1","title":"Time-to-event analysis as a framework for quantifying fish passage performance","docAbstract":"<p>Fish passage is the result of a sequence of processes, whereby fish must approach, enter, and pass a structure. Each of these processes takes time, and fishway performance is best quantified in terms of the rates at which each process is completed. Optimal performance is achieved by maximizing the rates of approach, entry, and passage through safe and desirable routes. Sometimes, however, it is necessary to reduce rates of passage through less desirable routes in order to increase proportions passing through the preferred route. Effectiveness of operational or structural modifications for achieving either of these goals is best quantified by applying time-to-event analysis, commonly known as survival analysis methods, to telemetry data. This set of techniques allows for accurate estimation of passage rates and covariate effects on those rates. Importantly, it allows researchers to quantify rates that vary over time, as well as the effects of covariates that also vary over time. Finally, these methods are able to control for competing risks, i.e., the presence of alternate passage routes, failure to pass, or other fates that remove fish from the pool of candidates available to pass through a particular route. In this chapter, we present a model simulation of telemetered fish passing a hydroelectric dam, and provide step-by-step guidance and rationales for performing time-to-event analysis on the resulting data. We demonstrate how this approach removes bias from performance estimates that can result from using methods that focus only on proportions passing each route. Time-to-event analysis, coupled with multinomial models for measuring survival, provides a comprehensive set of techniques for quantifying fish passage, and a framework from which performance among different sites can be better understood.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Telemetry techniques: A user guide for fisheries research","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"American Fisheries Society","publisherLocation":"Bethesda, MD","usgsCitation":"Castro-Santos, T.R., and Perry, R.W., 2012, Time-to-event analysis as a framework for quantifying fish passage performance, chap. 9.1 <i>of</i> Telemetry techniques: A user guide for fisheries research, p. 427-452.","productDescription":"26 p.","startPage":"427","endPage":"452","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-032289","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":319637,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":319636,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://fisheries.org/bookstore/all-titles/professional-and-trade/55068c/"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56fd0587e4b0a6037df2cf7e","contributors":{"editors":[{"text":"Adams, Noah S. 0000-0002-8354-0293 nadams@usgs.gov","orcid":"https://orcid.org/0000-0002-8354-0293","contributorId":3521,"corporation":false,"usgs":true,"family":"Adams","given":"Noah","email":"nadams@usgs.gov","middleInitial":"S.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":625655,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Beeman, John W. jbeeman@usgs.gov","contributorId":2646,"corporation":false,"usgs":true,"family":"Beeman","given":"John","email":"jbeeman@usgs.gov","middleInitial":"W.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":625656,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Eiler, John H.","contributorId":146952,"corporation":false,"usgs":false,"family":"Eiler","given":"John","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":625657,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Castro-Santos, Theodore R. 0000-0003-2575-9120 tcastrosantos@usgs.gov","orcid":"https://orcid.org/0000-0003-2575-9120","contributorId":3321,"corporation":false,"usgs":true,"family":"Castro-Santos","given":"Theodore","email":"tcastrosantos@usgs.gov","middleInitial":"R.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":625653,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Perry, Russell W. 0000-0003-4110-8619 rperry@usgs.gov","orcid":"https://orcid.org/0000-0003-4110-8619","contributorId":2820,"corporation":false,"usgs":true,"family":"Perry","given":"Russell","email":"rperry@usgs.gov","middleInitial":"W.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":625654,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70040972,"text":"70040972 - 2012 - Design and performance of radio telemetry systems for assessing juvenile fish passage at three hydroelectric dams","interactions":[{"subject":{"id":70040972,"text":"70040972 - 2012 - Design and performance of radio telemetry systems for assessing juvenile fish passage at three hydroelectric dams","indexId":"70040972","publicationYear":"2012","noYear":false,"chapter":"6.5","title":"Design and performance of radio telemetry systems for assessing juvenile fish passage at three hydroelectric dams"},"predicate":"IS_PART_OF","object":{"id":70198150,"text":"70198150 - 2012 - Telemetry techniques: A user guide for fisheries research","indexId":"70198150","publicationYear":"2012","noYear":false,"title":"Telemetry techniques: A user guide for fisheries research"},"id":1}],"isPartOf":{"id":70198150,"text":"70198150 - 2012 - Telemetry techniques: A user guide for fisheries research","indexId":"70198150","publicationYear":"2012","noYear":false,"title":"Telemetry techniques: A user guide for fisheries research"},"lastModifiedDate":"2022-12-20T17:40:21.604896","indexId":"70040972","displayToPublicDate":"2012-09-01T06:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"6.5","title":"Design and performance of radio telemetry systems for assessing juvenile fish passage at three hydroelectric dams","docAbstract":"<p>Studies of the effects of hydroelectric dams on fish populations are common (Williams 2008). Dams block passage of migratory and resident fish, alter habitats from free-flowing to lacustrine, and can alter water temperatures both upstream and downstream. At some dams, structures or operations are modified to reduce their effects on fish populations. In these cases, it is recommended that a series of studies be conducted before and after the alterations to help assess the effectiveness of the actions. We will describe three studies at hydroelectric dams on the Columbia and Snake rivers in the Pacific Northwest of the United States prompted by a need to reduce their effects on fishes, primarily salmonids, listed under the Endangered Species Act (ESA 1973).</p><p>Hydroelectric development on the Columbia and Snake rivers occurred chiefly between the early 1930s and the late 1970s. Fish originating in the upper portions of the Columbia and Snake rivers must pass as many as eight dams on these rivers during their seaward migration and again on their trip back to their natal waters. Small changes in passage survival at each dam can be important, due to the multiplicative effects of the series of dams. For example, if downstream passage survival at each of eight dams and reservoirs was 90% and it was increased by only 3% per dam, the numbers of fish surviving through the entire hydro system would increase from 43% to 56%. Thus, precisely measuring small changes in passage survival are important to the overall program. This has been achieved by designing efficient telemetry systems and releasing large numbers of tagged fish.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Telemetry techniques: A user guide for fisheries research","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"American Fisheries Society","publisherLocation":"Bethesda, MD","doi":"10.47886/9781934874264.ch12","usgsCitation":"Beeman, J.W., Hockersmith, E., and Stevenson, J.R., 2012, Design and performance of radio telemetry systems for assessing juvenile fish passage at three hydroelectric dams, chap. 6.5 <i>of</i> Telemetry techniques: A user guide for fisheries research, p. 281-304, https://doi.org/10.47886/9781934874264.ch12.","productDescription":"24 p.","startPage":"281","endPage":"304","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-026883","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":319633,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56fcfac3e4b0a6037df2bbae","contributors":{"editors":[{"text":"Adams, Noah S. 0000-0002-8354-0293 nadams@usgs.gov","orcid":"https://orcid.org/0000-0002-8354-0293","contributorId":3521,"corporation":false,"usgs":true,"family":"Adams","given":"Noah","email":"nadams@usgs.gov","middleInitial":"S.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":625638,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Beeman, John W. jbeeman@usgs.gov","contributorId":2646,"corporation":false,"usgs":true,"family":"Beeman","given":"John","email":"jbeeman@usgs.gov","middleInitial":"W.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":625639,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Eiler, John H.","contributorId":146952,"corporation":false,"usgs":false,"family":"Eiler","given":"John","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":625640,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Beeman, John W. jbeeman@usgs.gov","contributorId":2646,"corporation":false,"usgs":true,"family":"Beeman","given":"John","email":"jbeeman@usgs.gov","middleInitial":"W.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":625637,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hockersmith, Eric","contributorId":56781,"corporation":false,"usgs":true,"family":"Hockersmith","given":"Eric","email":"","affiliations":[],"preferred":false,"id":515018,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stevenson, John R.","contributorId":147936,"corporation":false,"usgs":false,"family":"Stevenson","given":"John","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":515019,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70043666,"text":"70043666 - 2012 - Atlas of nonindigenous marine and estuarine species in the North Pacific","interactions":[],"lastModifiedDate":"2016-05-03T14:51:29","indexId":"70043666","displayToPublicDate":"2012-09-01T03:45:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Atlas of nonindigenous marine and estuarine species in the North Pacific","docAbstract":"<h1>Executive Summary</h1>\n<p>Marine and estuarine nonindigenous species (NIS) are found across the world&rsquo;s oceans, and designing effective management strategies to mitigate this economic, ecological and human health threat requires a basic understanding of the existing invasion patterns at regional to global scales. However, to date, syntheses at ocean basin scales have essentially been nonexistent. To fill the gap for the North Pacific, we synthesized the distributions, invasion history, environmental tolerances, and natural history of the near-coastal nonindigenous species (NIS) reported from the member countries of the North Pacific Marine Science Organization (PICES; United States, Canada, China, Republic of Korea, Japan, and Russia). The hierarchical &ldquo;Marine Ecoregions of the World&rdquo; (MEOW) biogeographic schema was used as the framework for assessing species&rsquo; distributions, with the modification that we added a &ldquo;region&rdquo; level to differentiate eastern and western sides of oceans. The two North Pacific regions are the Northeast Pacific (NEP), which extends from the Gulf of California to the Aleutian Islands, and the Northwest Pacific (NWP), which extends from the East China Sea to the Kamchatka Shelf. To have complete coverage of the United States, we included the MEOW Hawaii Ecoregion as a separate reporting unit. To have complete coverage of Japan and China, we combined five MEOW ecoregions in southern China and Japan into the North Central-Indo Pacific (NCIP) Region. The various types of information were synthesized in a Microsoft Access database, the &ldquo;PICES Nonindigenous Species Information System&rdquo;, which is further described in the &ldquo;User&rsquo;s Guide and Metadata for the PICES Nonindigenous Species Information System&rdquo; (Lee et al., 2012). The PICES database was then used to generate two-page &ldquo;species profiles&rdquo; that map the native and introduced distributions of each species and provide a standardized summary of its invasion history, environmental tolerances, and natural history. These species profiles form the bulk of the &ldquo;Atlas of Nonindigenous Marine and Estuarine Species in the North Pacific&rdquo;.</p>\n<p>A total of 747 near-coastal nonindigenous species were identified in the PICES countries, with four phyla (Arthropoda, Chordata, Mollusca, and Annelida) constituting more than 70% of these invaders. The NEP and Hawaii have similar numbers of reported nonindigenous species, 368 and 347, respectively. In comparison, the NWP has about 60% of the number of reported NIS, 208. The NCIP contains only 73 NIS, though there is limited information for these ecoregions. When evaluated at an individual MEOW ecoregion scale, the Hawaii Ecoregion was the most invaded with 347 invaders, followed by the Northern California Ecoregion, which includes the San Francisco Estuary, with 287 NIS. The most invaded ecoregion in the NWP was the Central Kuroshio Current Ecoregion, which includes Tokyo Bay, with 87 reported NIS. Eight potential reasons for this geographical discrepancy in the extent of invasion were considered. The two most important appear to be: 1) the milder temperature regimes in the NEP and Hawaii are more conducive for NWP species to invade the NEP and Hawaii than the reverse and 2) there has been a greater search effort for NIS in Hawaii and the NEP at least for certain taxonomic groups.</p>\n<p>In terms of how the NIS were transported, hull fouling was potentially the most important vector in the NEP, NWP, and Hawaii, with ballast water discharges the second most important in all three regions. Intentional stocking and aquaculture escapees were relatively more important in the NWP than the NEP or Hawaii, reflecting the extensive aquaculture in Asia. Aquaculture associated species (i.e., aquaculture hitchhikers) was relatively important in the NEP, reflecting the historical influx of invaders with the importation of Atlantic and Pacific oysters.&nbsp;</p>","language":"English","publisher":"U.S. Environmental Protection Agency","usgsCitation":"Lee, and Reusser, D.A., 2012, Atlas of nonindigenous marine and estuarine species in the North Pacific, xxv,1915.","productDescription":"xxv,1915","numberOfPages":"1943","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-040943","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":320909,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":320903,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://nepis.epa.gov/Exe/ZyNET.exe/P100FXIS.txt?ZyActionD=ZyDocument&Client=EPA&Index=2011%20Thru%202015&Docs=&Query=Atlas%20nonindigenous%20marine%20estuarine%20species%20North%20Pacific%20&Time=&EndTime=&SearchMethod=2&TocRestrict=n&Toc=&TocEntry=&QField=&QFieldYear=&QFieldMonth=&QFieldDay=&UseQField=&IntQFieldOp=0&ExtQFieldOp=0&XmlQuery=&File=D%3A%5CZYFILES%5CINDEX%20DATA%5C11THRU15%5CTXT%5C00000006%5CP100FXIS.txt&User=ANONYMOUS&Password=anonymous&SortMethod=-%7Ch&MaximumDocuments=15&FuzzyDegree=0&ImageQuality=r85g16/r85g16/x150y150g16/i500&Display=hpfr&DefSeekPage=x&SearchBack=ZyActionL&Back=ZyActionS&BackDesc=Results%20page&MaximumPages=1&ZyEntry=1&SeekPage=x"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5729cbade4b0b13d3919a2e3","contributors":{"authors":[{"text":"Lee, Henry II","contributorId":115628,"corporation":false,"usgs":true,"family":"Lee","suffix":"Henry II","affiliations":[],"preferred":false,"id":516730,"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":628559,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70040973,"text":"70040973 - 2012 - A history of telemetry in fishery research","interactions":[{"subject":{"id":70040973,"text":"70040973 - 2012 - A history of telemetry in fishery research","indexId":"70040973","publicationYear":"2012","noYear":false,"chapter":"2","title":"A history of telemetry in fishery research"},"predicate":"IS_PART_OF","object":{"id":70198150,"text":"70198150 - 2012 - Telemetry techniques: A user guide for fisheries research","indexId":"70198150","publicationYear":"2012","noYear":false,"title":"Telemetry techniques: A user guide for fisheries research"},"id":1}],"isPartOf":{"id":70198150,"text":"70198150 - 2012 - Telemetry techniques: A user guide for fisheries research","indexId":"70198150","publicationYear":"2012","noYear":false,"title":"Telemetry techniques: A user guide for fisheries research"},"lastModifiedDate":"2022-12-20T17:41:08.073877","indexId":"70040973","displayToPublicDate":"2012-09-01T02:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"2","title":"A history of telemetry in fishery research","docAbstract":"<p>Biotelemetry has been defined as “the instrumental technique for gaining and transmitting information from a living organism and its environment to a remote observer” (Slater 1965). Biotelemetry typically utilizes wireless transmission of either an audible signal or electronic data to determine location of a tagged animal. Fisheries researchers use location information to gain a variety of insights into migration, habitat use, behavior, productivity, or survival of fish. Biotelemetry can be divided into two basic categories, acoustic or radio, based on mode of transmission, mechanical or electromagnetic energy, and operating frequency. Most acoustic systems in use today transmit at low frequency, between 30 and 300 kHz, while most radio systems transmit at very high frequency, between 30 and 300 MHz (Sisak and Lotimer 1998).</p><p>Acoustic telemetry is based on the principals of sonar (sound navigation and ranging), which was developed to detect submarines during World War I. The properties of acoustic systems favor their use in deep waters with high conductivity and low turbulence (Winter 1996). Radio telemetry is based on the principals of wireless radio communication, which were first demonstrated by Nikola Tesla in 1893. Radio systems are best suited in shallow waters with relatively low conductivity but have the added benefit of improved signal detection in turbulent conditions and with aerial antennas. Advances in both technologies have resulted in highly efficient transmitter and receiving systems.</p><p>Advancements in products used for animal telemetry over the past 50 years have generally followed those in the electronics field (Figure 1). Bell Laboratories1 ushered in the age of digital electronics with the invention of the transistor in 1947 (Mann 2000). Today transistors are common in everyday items such as radios, televisions, hearing aids, computers, cell phones and even MP3 players. Consumer demand for inexpensive small electronic devices with increased functionality has continually driven advancements in the field of electronics. These advancements have subsequently led to improvements in biotelemetry transmitters and receivers such as miniaturization of components, increased battery performance, and more powerful micro-processing.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Telemetry techniques: A user guide for fisheries research","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"American Fisheries Society","publisherLocation":"Bethesda, MD","doi":"10.47886/9781934874264.ch2","usgsCitation":"Hockersmith, E., and Beeman, J.W., 2012, A history of telemetry in fishery research, chap. 2 <i>of</i> Telemetry techniques: A user guide for fisheries research, p. 7-19, https://doi.org/10.47886/9781934874264.ch2.","productDescription":"13 p.","startPage":"7","endPage":"19","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-026746","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":313833,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"568cf73ae4b0e7a44bc0f123","contributors":{"editors":[{"text":"Adams, Noah S. 0000-0002-8354-0293 nadams@usgs.gov","orcid":"https://orcid.org/0000-0002-8354-0293","contributorId":3521,"corporation":false,"usgs":true,"family":"Adams","given":"Noah","email":"nadams@usgs.gov","middleInitial":"S.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":625599,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Beeman, John W. jbeeman@usgs.gov","contributorId":2646,"corporation":false,"usgs":true,"family":"Beeman","given":"John","email":"jbeeman@usgs.gov","middleInitial":"W.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":625600,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Eiler, John H.","contributorId":146952,"corporation":false,"usgs":false,"family":"Eiler","given":"John","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":625601,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Hockersmith, Eric","contributorId":56781,"corporation":false,"usgs":true,"family":"Hockersmith","given":"Eric","email":"","affiliations":[],"preferred":false,"id":515021,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Beeman, John W. jbeeman@usgs.gov","contributorId":2646,"corporation":false,"usgs":true,"family":"Beeman","given":"John","email":"jbeeman@usgs.gov","middleInitial":"W.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":587636,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70044023,"text":"70044023 - 2012 - Tidal and groundwater fluxes to a shallow, microtidal estuary: Constraining inputs through field observations and hydrodynamic modeling","interactions":[],"lastModifiedDate":"2013-05-30T14:08:52","indexId":"70044023","displayToPublicDate":"2012-09-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1584,"text":"Estuaries and Coasts","active":true,"publicationSubtype":{"id":10}},"title":"Tidal and groundwater fluxes to a shallow, microtidal estuary: Constraining inputs through field observations and hydrodynamic modeling","docAbstract":"Increased nutrient loading to estuaries has led to eutrophication, degraded water quality, and ecological transformations. Quantifying nutrient loads in systems with significant groundwater input can be difficult due to the challenge of measuring groundwater fluxes. We quantified tidal and freshwater fluxes over an 8-week period at the entrance of West Falmouth Harbor, Massachusetts, a eutrophic, groundwater-fed estuary. Fluxes were estimated from velocity and salinity measurements and a total exchange flow (TEF) methodology. Intermittent cross-sectional measurements of velocity and salinity were used to convert point measurements to cross-sectionally averaged values over the entire deployment (index relationships). The estimated mean freshwater flux (0.19 m<sup>3</sup>/s) for the 8-week period was mainly due to groundwater input (0.21 m<sup>3</sup>/s) with contributions from precipitation to the estuary surface (0.026 m<sup>3</sup>/s) and removal by evaporation (0.048 m<sup>3</sup>/s). Spring–neap variations in freshwater export that appeared in shorter-term averages were mostly artifacts of the index relationships. Hydrodynamic modeling with steady groundwater input demonstrated that while the TEF methodology resolves the freshwater flux signal, calibration of the index–salinity relationships during spring tide conditions only was responsible for most of the spring–neap signal. The mean freshwater flux over the entire period estimated from the combination of the index-velocity, index–salinity, and TEF calculations were consistent with the model, suggesting that this methodology is a reliable way of estimating freshwater fluxes in the estuary over timescales greater than the spring–neap cycle. Combining this type of field campaign with hydrodynamic modeling provides guidance for estimating both magnitude of groundwater input and estuarine storage of freshwater and sets the stage for robust estimation of the nutrient load in groundwater.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Estuaries and Coasts","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","doi":"10.1007/s12237-012-9515-x","usgsCitation":"Ganju, N., Hayn, M., Chen, S., Howarth, R.W., Dickhudt, P., Aretxabaleta, A., and Marino, R., 2012, Tidal and groundwater fluxes to a shallow, microtidal estuary: Constraining inputs through field observations and hydrodynamic modeling: Estuaries and Coasts, v. 35, no. 5, p. 1285-1298, https://doi.org/10.1007/s12237-012-9515-x.","productDescription":"14 p.","startPage":"1285","endPage":"1298","ipdsId":"IP-036919","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":474373,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hdl.handle.net/1912/5383","text":"External Repository"},{"id":273025,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":273024,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s12237-012-9515-x"}],"country":"United States","state":"Massachusetts","otherGeospatial":"West Falmouth Harbor","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -70.66,41.593 ], [ -70.66,41.613 ], [ -70.63,41.613 ], [ -70.63,41.593 ], [ -70.66,41.593 ] ] ] } } ] }","volume":"35","issue":"5","noUsgsAuthors":false,"publicationDate":"2012-05-30","publicationStatus":"PW","scienceBaseUri":"51a874ebe4b082d85d5ed8ff","contributors":{"authors":[{"text":"Ganju, Neil K. 0000-0002-1096-0465","orcid":"https://orcid.org/0000-0002-1096-0465","contributorId":93543,"corporation":false,"usgs":true,"family":"Ganju","given":"Neil K.","affiliations":[],"preferred":false,"id":474649,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hayn, Melanie","contributorId":57754,"corporation":false,"usgs":false,"family":"Hayn","given":"Melanie","email":"","affiliations":[{"id":13003,"text":"Department of Ecology and Evolutionary Biology, Cornell University, Ithaca, New York","active":true,"usgs":false}],"preferred":false,"id":474648,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chen, Shih-Nan","contributorId":7166,"corporation":false,"usgs":true,"family":"Chen","given":"Shih-Nan","affiliations":[],"preferred":false,"id":474644,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Howarth, Robert W.","contributorId":32066,"corporation":false,"usgs":false,"family":"Howarth","given":"Robert","email":"","middleInitial":"W.","affiliations":[{"id":13003,"text":"Department of Ecology and Evolutionary Biology, Cornell University, Ithaca, New York","active":true,"usgs":false}],"preferred":false,"id":474645,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dickhudt, Patrick J.","contributorId":48302,"corporation":false,"usgs":true,"family":"Dickhudt","given":"Patrick J.","affiliations":[],"preferred":false,"id":474647,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Aretxabaleta, Alfredo L.","contributorId":41311,"corporation":false,"usgs":true,"family":"Aretxabaleta","given":"Alfredo L.","affiliations":[],"preferred":false,"id":474646,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Marino, Roxanne","contributorId":105627,"corporation":false,"usgs":true,"family":"Marino","given":"Roxanne","affiliations":[],"preferred":false,"id":474650,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70044380,"text":"70044380 - 2012 - Reading the climate record of the martian polar layered deposits","interactions":[],"lastModifiedDate":"2018-11-14T10:50:33","indexId":"70044380","displayToPublicDate":"2012-09-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1963,"text":"Icarus","active":true,"publicationSubtype":{"id":10}},"title":"Reading the climate record of the martian polar layered deposits","docAbstract":"The martian polar regions have layered deposits of ice and dust. The stratigraphy of these deposits is exposed within scarps and trough walls and is thought to have formed due to climate variations in the past. Insolation has varied significantly over time and caused dramatic changes in climate, but it has remained unclear whether insolation variations could be linked to the stratigraphic record. We present a model of layer formation based on physical processes that expresses polar deposition rates of ice and dust in terms of insolation. In this model, layer formation is controlled by the insolation record, and dust-rich layers form by two mechanisms: (1) increased summer sublimation during high obliquity, and (2) variations in the polar deposition of dust modulated by obliquity variations. The model is simple, yet physically plausible, and allows for investigations of the climate control of the polar layered deposits (PLD). We compare the model to a stratigraphic column obtained from the north polar layered deposits (NPLD) (Fishbaugh, K.E., Hvidberg, C.S., Byrne, S., Russel, P.S., Herkenhoff, K.E., Winstrup, M., Kirk, R. [2010a]. Geophys. Res. Lett., 37, L07201) and show that the model can be tuned to reproduce complex layer sequences. The comparison with observations cannot uniquely constrain the PLD chronology, and it is limited by our interpretation of the observed stratigraphic column as a proxy for NPLD composition. We identified, however, a set of parameters that provides a chronology of the NPLD tied to the insolation record and consistently explains layer formation in accordance with observations of NPLD stratigraphy. This model dates the top 500 m of the NPLD back to ∼1 million years with an average net deposition rate of ice and dust of 0.55 mm a−1. The model stratigraphy contains a quasi-periodic ∼30 m cycle, similar to a previously suggested cycle in brightness profiles from the NPLD (Laskar, J., Levrard, B., Mustard, F. [2002]. Nature, 419, 375–377; Milkovich, S., Head, J.W. [2005]. J. Geophys. Res. 110), but here related to half of the obliquity cycles of 120 and 99 kyr and resulting from a combination of the two layer formation mechanisms. Further investigations of the non-linear insolation control of PLD formation should consider data from other geographical locations and include radar data and other stratigraphic datasets that can constrain the composition and stratigraphy of the NPLD layers.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Icarus","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.icarus.2012.08.009","usgsCitation":"Hvidberg, C., Fishbaugh, K., Winstrup, M., Svensson, A., Byrne, S., and Herkenhoff, K.E., 2012, Reading the climate record of the martian polar layered deposits: Icarus, v. 221, no. 1, p. 405-419, https://doi.org/10.1016/j.icarus.2012.08.009.","productDescription":"15 p.","startPage":"405","endPage":"419","ipdsId":"IP-022313","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":273716,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":273715,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.icarus.2012.08.009"}],"volume":"221","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51bc3b68e4b0c04034a01cc6","contributors":{"authors":[{"text":"Hvidberg, C.S.","contributorId":104737,"corporation":false,"usgs":true,"family":"Hvidberg","given":"C.S.","email":"","affiliations":[],"preferred":false,"id":475477,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fishbaugh, K.E.","contributorId":102692,"corporation":false,"usgs":true,"family":"Fishbaugh","given":"K.E.","email":"","affiliations":[],"preferred":false,"id":475476,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Winstrup, M.","contributorId":73036,"corporation":false,"usgs":true,"family":"Winstrup","given":"M.","affiliations":[],"preferred":false,"id":475474,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Svensson, A.","contributorId":76628,"corporation":false,"usgs":true,"family":"Svensson","given":"A.","email":"","affiliations":[],"preferred":false,"id":475475,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Byrne, S.","contributorId":105083,"corporation":false,"usgs":true,"family":"Byrne","given":"S.","email":"","affiliations":[],"preferred":false,"id":475478,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Herkenhoff, Kenneth E. 0000-0002-3153-6663 kherkenhoff@usgs.gov","orcid":"https://orcid.org/0000-0002-3153-6663","contributorId":2275,"corporation":false,"usgs":true,"family":"Herkenhoff","given":"Kenneth","email":"kherkenhoff@usgs.gov","middleInitial":"E.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":475473,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70039801,"text":"fs20123105 - 2012 - A climate trend analysis of Mali","interactions":[],"lastModifiedDate":"2012-09-05T01:01:46","indexId":"fs20123105","displayToPublicDate":"2012-09-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-3105","subseriesTitle":"Informing Climate Change Adaptation Series","title":"A climate trend analysis of Mali","docAbstract":"This brief report, drawing from a multi-year effort by the U.S. Agency for International Development (USAID) Famine Early Warning Systems Network (FEWS NET), identifies modest declines in rainfall, accompanied by increases in air temperatures. These analyses are based on quality-controlled station observations. Conclusions: * Summer rains have remained relatively steady for the past 20 years, but are 12 percent below the 1920-1969 average. * Temperatures have increased by 0.8&deg; Celsius since 1975, amplifying the effect of droughts. * Cereal yields are low but have been improving. * Current population and agricultural trends indicate that increased yields have offset population expansion, keeping per capita cereal production steady.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20123105","collaboration":"Famine Early Warning Systems Network&ndash;Informing Climate Change Adaptation Series","usgsCitation":"Funk, C.C., Rowland, J., Adoum, A., Eilerts, G., and White, L., 2012, A climate trend analysis of Mali: U.S. Geological Survey Fact Sheet 2012-3105, 4 p., https://doi.org/10.3133/fs20123105.","productDescription":"4 p.","numberOfPages":"4","additionalOnlineFiles":"N","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":260125,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs_2012_3105.gif"},{"id":260118,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2012/3105/","linkFileType":{"id":5,"text":"html"}},{"id":260119,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2012/3105/fs2012-3105.pdf","linkFileType":{"id":1,"text":"pdf"}}],"country":"Mali","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd4988e4b0b290850ef410","contributors":{"authors":[{"text":"Funk, Christopher C. 0000-0002-9254-6718 cfunk@usgs.gov","orcid":"https://orcid.org/0000-0002-9254-6718","contributorId":721,"corporation":false,"usgs":true,"family":"Funk","given":"Christopher","email":"cfunk@usgs.gov","middleInitial":"C.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":466946,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rowland, Jim 0000-0003-4837-3511","orcid":"https://orcid.org/0000-0003-4837-3511","contributorId":22891,"corporation":false,"usgs":true,"family":"Rowland","given":"Jim","email":"","affiliations":[],"preferred":false,"id":466947,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Adoum, Alkhalil","contributorId":59670,"corporation":false,"usgs":true,"family":"Adoum","given":"Alkhalil","email":"","affiliations":[],"preferred":false,"id":466949,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Eilerts, Gary","contributorId":31101,"corporation":false,"usgs":true,"family":"Eilerts","given":"Gary","email":"","affiliations":[],"preferred":false,"id":466948,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"White, Libby","contributorId":61680,"corporation":false,"usgs":true,"family":"White","given":"Libby","email":"","affiliations":[],"preferred":false,"id":466950,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70043123,"text":"70043123 - 2012 - Inland fields of dispersed cobbles and boulders as evidence for a tsunami on Anegada, British Virgin Islands","interactions":[],"lastModifiedDate":"2018-03-23T12:06:03","indexId":"70043123","displayToPublicDate":"2012-09-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2822,"text":"Natural Hazards","active":true,"publicationSubtype":{"id":10}},"title":"Inland fields of dispersed cobbles and boulders as evidence for a tsunami on Anegada, British Virgin Islands","docAbstract":"Marine overwash from the north a few centuries ago transported hundreds of angular cobbles and boulders tens to hundreds of meters southward from limestone outcrops in the interior of Anegada, 140 km east–northeast of Puerto Rico. We examined two of several cobble and boulder fields as part of an effort to interpret whether the overwash resulted from a tsunami or a storm in a location where both events are known to occur. One of the cobble and boulder field extends 200 m southward from limestone outcrops that are 300 m inland from the island’s north shore. The other field extends 100 m southward from a limestone knoll located 800 m from the nearest shore. In the two fields, we measured the size, orientation, and spatial distribution of a total of 161 clasts and determined their stratigraphic positions with respect to an overwash sand and shell sheet deposit. In both fields, we found the spacing between clasts increased southward and that clast long-axis orientations are consistent with a transport trending north–south. Almost half the clasts are partially buried in a landward thinning and fining overwash sand and none were found embedded in the shelly mud of a pre-overwash marine pond. The two cobble and boulder fields resemble modern tsunami deposits in which dispersed clasts extend inland as a single layer. The fields contrast with coarse clast storm deposits that often form wedge-shaped shore-parallel ridges. These comparisons suggest that the overwash resulted from a tsunami and not from a storm.","language":"English","publisher":"Springer","doi":"10.1007/s11069-011-9848-y","usgsCitation":"Jaffe, B.E., Watt, S., and Buckley, M., 2012, Inland fields of dispersed cobbles and boulders as evidence for a tsunami on Anegada, British Virgin Islands: Natural Hazards, v. 63, no. 1, p. 119-131, https://doi.org/10.1007/s11069-011-9848-y.","productDescription":"23 p.","startPage":"119","endPage":"131","ipdsId":"IP-023899","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":267977,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":267976,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s11069-011-9848-y"}],"country":"British Virgin Islands","volume":"63","issue":"1","noUsgsAuthors":false,"publicationDate":"2011-05-31","publicationStatus":"PW","scienceBaseUri":"5129f32ee4b04edf7e93f8f0","contributors":{"authors":[{"text":"Jaffe, Bruce E. 0000-0002-8816-5920 bjaffe@usgs.gov","orcid":"https://orcid.org/0000-0002-8816-5920","contributorId":2049,"corporation":false,"usgs":true,"family":"Jaffe","given":"Bruce","email":"bjaffe@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":473008,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Watt, Steve swatt@usgs.gov","contributorId":4451,"corporation":false,"usgs":true,"family":"Watt","given":"Steve","email":"swatt@usgs.gov","affiliations":[],"preferred":true,"id":473009,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Buckley, Mark","contributorId":6695,"corporation":false,"usgs":true,"family":"Buckley","given":"Mark","affiliations":[],"preferred":false,"id":473010,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70042984,"text":"70042984 - 2012 - Calcite growth-rate inhibition by fulvic acid and magnesium ion—Possible influence on biogenic calcite formation","interactions":[],"lastModifiedDate":"2013-02-14T14:13:28","indexId":"70042984","displayToPublicDate":"2012-09-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2236,"text":"Journal of Crystal Growth","active":true,"publicationSubtype":{"id":10}},"title":"Calcite growth-rate inhibition by fulvic acid and magnesium ion—Possible influence on biogenic calcite formation","docAbstract":"Increases in ocean surface water dissolved carbon dioxide (CO2) concentrations retard biocalcification by reducing calcite supersaturation (Ωc). Reduced calcification rates may influence growth-rate dependent magnesium ion (Mg) incorporation into biogenic calcite modifying the use of calcifying organisms as paleoclimate proxies. Fulvic acid (FA) at biocalcification sites may further reduce calcification rates. Calcite growth-rate inhibition by FA and Mg, two common constituents of seawater and soil water involved in the formation of biogenic calcite, was measured separately and in combination under identical, highly reproducible experimental conditions. Calcite growth rates (pH=8.5 and Ωc=4.5) are reduced by FA (0.5 mg/L) to 47% and by Mg (10−4 M) to 38%, compared to control experiments containing no added growth-rate inhibitor. Humic acid (HA) is twice as effective a calcite growth-rate inhibitor as FA. Calcite growth rate in the presence of both FA (0.5 mg/L) and Mg (10−4 M) is reduced to 5% of the control rate. Mg inhibits calcite growth rates by substitution for calcium ion at the growth site. In contrast, FA inhibits calcite growth rates by binding multiple carboxylate groups on the calcite surface. FA and Mg together have an increased affinity for the calcite growth sites reducing calcite growth rates.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Crystal Growth","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.jcrysgro.2011.12.069","usgsCitation":"Reddy, M.M., 2012, Calcite growth-rate inhibition by fulvic acid and magnesium ion—Possible influence on biogenic calcite formation: Journal of Crystal Growth, v. 352, no. 1, p. 151-154, https://doi.org/10.1016/j.jcrysgro.2011.12.069.","startPage":"151","endPage":"154","ipdsId":"IP-031613","costCenters":[{"id":145,"text":"Branch of Regional Research-Central Region","active":false,"usgs":true}],"links":[{"id":267413,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":267412,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.jcrysgro.2011.12.069"}],"country":"United States","volume":"352","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"511e1579e4b071e86a19a42a","contributors":{"authors":[{"text":"Reddy, Michael M. mmreddy@usgs.gov","contributorId":684,"corporation":false,"usgs":true,"family":"Reddy","given":"Michael","email":"mmreddy@usgs.gov","middleInitial":"M.","affiliations":[{"id":145,"text":"Branch of Regional Research-Central Region","active":false,"usgs":true}],"preferred":true,"id":472737,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70192479,"text":"70192479 - 2012 - Estimating rate uncertainty with maximum likelihood: differences between power-law and flicker–random-walk models","interactions":[],"lastModifiedDate":"2017-10-26T14:53:40","indexId":"70192479","displayToPublicDate":"2012-09-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2303,"text":"Journal of Geodesy","active":true,"publicationSubtype":{"id":10}},"title":"Estimating rate uncertainty with maximum likelihood: differences between power-law and flicker–random-walk models","docAbstract":"<p><span>Recent studies have documented that global positioning system (GPS) time series of position estimates have temporal correlations which have been modeled as a combination of power-law and white noise processes. When estimating quantities such as a constant rate from GPS time series data, the estimated uncertainties on these quantities are more realistic when using a noise model that includes temporal correlations than simply assuming temporally uncorrelated noise. However, the choice of the specific representation of correlated noise can affect the estimate of uncertainty. For many GPS time series, the background noise can be represented by either: (1) a sum of flicker and random-walk noise or, (2) as a power-law noise model that represents an average of the flicker and random-walk noise. For instance, if the underlying noise model is a combination of flicker and random-walk noise, then incorrectly choosing the power-law model could underestimate the rate uncertainty by a factor of two. Distinguishing between the two alternate noise models is difficult since the flicker component can dominate the assessment of the noise properties because it is spread over a significant portion of the measurable frequency band. But, although not necessarily detectable, the random-walk component can be a major constituent of the estimated rate uncertainty. None the less, it is possible to determine the upper bound on the random-walk noise.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s00190-012-0556-5","usgsCitation":"Langbein, J.O., 2012, Estimating rate uncertainty with maximum likelihood: differences between power-law and flicker–random-walk models: Journal of Geodesy, v. 86, no. 9, p. 775-783, https://doi.org/10.1007/s00190-012-0556-5.","productDescription":"9 p.","startPage":"775","endPage":"783","ipdsId":"IP-034632","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":474372,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s00190-012-0556-5","text":"Publisher Index Page"},{"id":347500,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"86","issue":"9","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2012-04-11","publicationStatus":"PW","scienceBaseUri":"5a07f115e4b09af898c8cda9","contributors":{"authors":[{"text":"Langbein, John O. 0000-0002-7821-8101 langbein@usgs.gov","orcid":"https://orcid.org/0000-0002-7821-8101","contributorId":3293,"corporation":false,"usgs":true,"family":"Langbein","given":"John","email":"langbein@usgs.gov","middleInitial":"O.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":716047,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
]}