{"pageNumber":"581","pageRowStart":"14500","pageSize":"25","recordCount":46689,"records":[{"id":70045440,"text":"ds755 - 2013 - Quantitative determination of selenium and mercury, and an ICP-MS semi-quantitative scan of other elements in samples of eagle tissues collected from the Pacific Northwest--Summer 2011","interactions":[],"lastModifiedDate":"2013-04-16T12:58:21","indexId":"ds755","displayToPublicDate":"2013-04-16T00:00:00","publicationYear":"2013","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":"755","title":"Quantitative determination of selenium and mercury, and an ICP-MS semi-quantitative scan of other elements in samples of eagle tissues collected from the Pacific Northwest--Summer 2011","docAbstract":"Eagle tissues from dead eagle carcasses were collected by U.S. Fish and Wildlife Service personnel at various locations in the Pacific Northwest as part of a study to document the occurrence of metal and metalloid contaminants. A group of 182 eagle tissue samples, consisting of liver, kidney, brain, talon, feather, femur, humerus, and stomach contents, were quantitatively analyzed for concentrations of selenium and mercury by atomic absorption techniques, and for other elements by semi-quantitative scan with an inductively coupled plasma-mass spectrometer. For the various tissue matrices analyzed by an ICP-MS semiquantitative scan, some elemental concentrations (micrograms per gram dry weight) were quite variable within a particular matrix; notable observations were as follows: lead concentrations ranged from 0.2 to 31 in femurs, 0.1 to 29 in humeri, 0.1 to 54 in talons, less than (<) 0.05 to 120 in livers, <0.05 to 34 in kidneys, and 0.05 to 8 in brains; copper concentrations ranged from 5 to 9 in feathers, 8 to 47 in livers, 7 to 43 in kidneys, and 7 to 28 in brains; cadmium concentrations ranged from 0.1 to 10 in kidneys. In stomach contents, concentrations of vanadium ranged from 0.08 to 5, chromium 2 to 34, manganese 1 to 57, copper 2 to 69, arsenic <0.05 to 6, rubidium 1 to 13, and barium <0.5 to 18. Selenium concentrations from highest to lowest based on the matrix mean were as follows: kidney, liver, feather, brain, stomach content, talon, femur, and humerus. For mercury, the highest to lowest concentrations were feather, liver, talon, brain, stomach content, femur, and humerus.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds755","usgsCitation":"May, T., Walther, M., and Brumbaugh, W., 2013, Quantitative determination of selenium and mercury, and an ICP-MS semi-quantitative scan of other elements in samples of eagle tissues collected from the Pacific Northwest--Summer 2011: U.S. Geological Survey Data Series 755, iii, 3 p.; Tables, https://doi.org/10.3133/ds755.","productDescription":"iii, 3 p.; Tables","numberOfPages":"12","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2011-06-21","temporalEnd":"2011-09-22","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":270997,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds755.gif"},{"id":270995,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/755/ds755_web.pdf"},{"id":270996,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/755/downloads/ds755_tables.xls"},{"id":270994,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/755/"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.7857,32.53 ], [ -124.7857,49.0 ], [ -111.04,49.0 ], [ -111.04,32.53 ], [ -124.7857,32.53 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"516e64dae4b00154e4368b67","contributors":{"authors":[{"text":"May, Thomas","contributorId":39259,"corporation":false,"usgs":true,"family":"May","given":"Thomas","affiliations":[],"preferred":false,"id":477503,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Walther, Mike","contributorId":9137,"corporation":false,"usgs":true,"family":"Walther","given":"Mike","affiliations":[],"preferred":false,"id":477502,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brumbaugh, William","contributorId":48462,"corporation":false,"usgs":true,"family":"Brumbaugh","given":"William","affiliations":[],"preferred":false,"id":477504,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70045456,"text":"ofr20131073 - 2013 - Residential and service-population exposure to multiple natural hazards in the Mount Hood region of Clackamas County, Oregon","interactions":[],"lastModifiedDate":"2013-04-16T16:17:45","indexId":"ofr20131073","displayToPublicDate":"2013-04-16T00:00:00","publicationYear":"2013","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":"2013-1073","title":"Residential and service-population exposure to multiple natural hazards in the Mount Hood region of Clackamas County, Oregon","docAbstract":"The objective of this research is to document residential and service-population exposure to natural hazards in the rural communities of Clackamas County, Oregon, near Mount Hood. The Mount Hood region of Clackamas County has a long history of natural events that have impacted its small, tourism-based communities. To support preparedness and emergency-management planning in the region, a geospatial analysis of population exposure was used to determine the number and type of residents and service populations in flood-, wildfire-, and volcano-related hazard zones. Service populations are a mix of residents and tourists temporarily benefitting from local services, such as retail, education, or recreation. In this study, service population includes day-use visitors at recreational sites, overnight visitors at hotels and resorts, children at schools, and community-center visitors. Although the heavily-forested, rural landscape suggests few people are in the area, there are seasonal peaks of thousands of visitors to the region. “Intelligent” dasymetric mapping efforts using 30-meter resolution land-cover imagery and U.S. Census Bureau data proved ineffective at adequately capturing either the spatial distribution or magnitude of population at risk. Consequently, an address-point-based hybrid dasymetric methodology of assigning population to the physical location of buildings mapped with a global positioning system was employed. The resulting maps of the population (1) provide more precise spatial distributions for hazard-vulnerability assessments, (2) depict appropriate clustering due to higher density structures, such as apartment complexes and multi-unit commercial buildings, and (3) provide new information on the spatial distribution and temporal variation of people utilizing services within the study area.\n\nEstimates of population exposure to flooding, wildfire, and volcanic hazards were determined by using overlay analysis in a geographic information system. Population exposure to flood hazards is low (less than 10 percent of residents) and does not vary substantially between 100-year and 500-year flood-hazard scenarios. Moderate, moderate-to-high, and high wildfire-risk areas within the study region account for 72 percent of residents, 62 percent of employees, and 60 percent of daytime visitors to recreation sites. Fifteen percent of businesses in the study area are in moderate-to-high or high wildfire-risk areas but these businesses represent 51 percent of the local workforce. A volcanic event at Mount Hood could directly impact up to 60 percent of residents in their homes and 87 percent of employees at their workplaces. The proximal volcanic-hazard zone alone includes 65 percent of employees, 80 percent of schools and community facilities, more than 60 percent of overnight visitors in peak seasons, and 82–100 percent of daytime visitors to recreation sites during the summer and winter months, respectively. The number of day-use visitors to recreation sites in the region is greatest during winter months (averaging 129,300 people per month), whereas overnight visitors are greatest during summer months (averaging 34,000 per month). This analysis of residential and service-population exposure to natural hazards supports the development of targeted risk-reduction efforts in the region, while also expanding the discourse on characterizing and assessing population dynamics in tourist-frequented areas.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131073","collaboration":"Prepared in cooperation with the Clackamas County Emergency Management Department","usgsCitation":"Mathie, A., and Wood, N., 2013, Residential and service-population exposure to multiple natural hazards in the Mount Hood region of Clackamas County, Oregon: U.S. Geological Survey Open-File Report 2013-1073, iv, 48 p., https://doi.org/10.3133/ofr20131073.","productDescription":"iv, 48 p.","numberOfPages":"54","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":271018,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131073.jpg"},{"id":271017,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1073/pdf/ofr20131073.pdf"},{"id":271016,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1073/"}],"country":"United States","state":"Oregon","county":"Clackamas County","otherGeospatial":"Mount Hood","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.868,44.8857 ], [ -122.868,45.4617 ], [ -121.651,45.4617 ], [ -121.651,44.8857 ], [ -122.868,44.8857 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"516e64dbe4b00154e4368b6b","contributors":{"authors":[{"text":"Mathie, Amy M.","contributorId":82803,"corporation":false,"usgs":true,"family":"Mathie","given":"Amy M.","affiliations":[],"preferred":false,"id":477522,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wood, Nathan 0000-0002-6060-9729 nwood@usgs.gov","orcid":"https://orcid.org/0000-0002-6060-9729","contributorId":71151,"corporation":false,"usgs":true,"family":"Wood","given":"Nathan","email":"nwood@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":false,"id":477521,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70045399,"text":"cir1383A - 2013 - U.S. Geological Survey Climate and Land Use Change Science Strategy—A Framework for Understanding and Responding to Global Change","interactions":[],"lastModifiedDate":"2023-02-23T21:18:35.601132","indexId":"cir1383A","displayToPublicDate":"2013-04-15T17:35:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":307,"text":"Circular","code":"CIR","onlineIssn":"2330-5703","printIssn":"1067-084X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1383","chapter":"A","displayTitle":"U.S. Geological Survey climate and land use change science strategy—A framework for understanding and responding to global change","title":"U.S. Geological Survey Climate and Land Use Change Science Strategy—A Framework for Understanding and Responding to Global Change","docAbstract":"

Executive Summary

The U.S. Geological Survey (USGS), a nonregulatory Federal science agency with national scope and responsibilities, is uniquely positioned to serve the Nation’s needs in understanding and responding to global change, including changes in climate, water availability, sea level, land use and land cover, ecosystems, and global biogeochemical cycles. Global change is among the most challenging and formidable issues confronting our Nation and society. Scientists agree that global environmental changes during this century will have far-reaching societal implications (Intergovernmental Panel on Climate Change, 2007; U.S. Global Change Research Program, 2009). In the face of these challenges, the Nation can benefit greatly by using natural science information in decisionmaking.

Since the passage of the U.S. Global Change Research Act of 1990, the USGS has made substantial scientific contributions to understanding the interactive living and nonliving components of the Earth system. USGS natural science activities have led to fundamental advances in observing and understanding climate and land-cover change and the effects these changes have on ecosystems, natural-resource availability, and societal sustainability. Most of these major advances were pursued in partnership with other organizations within and outside the Department of the Interior. The inherent value of partnerships with other U.S. Global Change Research Program agencies and natural-resource managers is emphasized in all aspects of the planning and implementation of this Science Strategy for the coming decade.

Over the next 10 years, the USGS will make substantial contributions to understanding how Earth systems interact, respond to, and cause global change. The USGS will work with science partners, decisionmakers, and resource managers at local to international levels (including Native American tribes) to improve understanding of past and present change; develop relevant forecasts; and identify those lands, resources, and communities most vulnerable to global change processes. Science will play an essential role in helping communities and land and resource managers understand local to global implications, anticipate effects, prepare for changes, and reduce the risks associated with decisionmaking in a changing environment. USGS partners and stakeholders will benefit from the data, predictive models, and decision-support products and services resulting from the implementation of this strategy.

This Science Strategy recognizes core USGS strengths that are applied to key societal problems. It establishes seven goals for USGS global change science and strategic actions that may be implemented in the short term (1–5 years) and the longer term (5–10 years) to improve our understanding of the following areas of inquiry:

  1. Rates, causes, and impacts of past global changes;
  2. The global carbon cycle;
  3. Biogeochemical cycles and their coupled interactions;
  4. Land-use and land-cover change rates, causes, and consequences;
  5. Droughts, floods, and water availability under changing land-use and climatic conditions;
  6. Coastal response to sea-level rise, climatic change, and human development; and
  7. Biological responses to global change.

In addition to the seven thematic goals, we address the central role of monitoring in accordance with the USGS Science Strategy recommendation that global change research should rely on existing “…decades of observational data and long-term records to interpret consequences of climate variability and change to the Nation’s biological populations, ecosystems, and land and water resources” (U.S. Geological Survey, 2007, p. 19). We also briefly describe specific needs and opportunities for coordinating USGS global change science among USGS Mission Areas and address the need for a comprehensive and sustained communications strategy.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1383A","usgsCitation":"Burkett, V.R., Kirtland, D.A., Taylor, I.L., Belnap, Jayne, Cronin, T.M., Dettinger, M.D., Frazier, E.L., Haines, J.W., Loveland, T.R., Milly, P.C.D., O’Malley, Robin, Thompson, R.S., Maule, A.G., McMahon, Gerard, and Striegl, R.G., 2013, U.S. Geological Survey climate and land use change science strategy—A framework for understanding and responding to global change: U.S. Geological Survey Circular 1383–A, 43 p.","productDescription":"viii, 43 p.","numberOfPages":"56","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":270884,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/circ/1383a/images/coverthb.gif"},{"id":270883,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1383a/circ1383-A.pdf","text":"Report","size":"20.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"CIR 1383-A"}],"country":"United States","contact":"

Land Resources
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192

","tableOfContents":"","publishedDate":"2013-04-15","noUsgsAuthors":false,"publicationDate":"2013-04-15","publicationStatus":"PW","scienceBaseUri":"516d135de4b0411d430a89b1","contributors":{"authors":[{"text":"Burkett, Virginia R. 0000-0003-4746-2862","orcid":"https://orcid.org/0000-0003-4746-2862","contributorId":80229,"corporation":false,"usgs":true,"family":"Burkett","given":"Virginia","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":477378,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kirtland, David A. dakirtland@usgs.gov","contributorId":265,"corporation":false,"usgs":true,"family":"Kirtland","given":"David","email":"dakirtland@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":477362,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Taylor, Ione L. itaylor@usgs.gov","contributorId":322,"corporation":false,"usgs":true,"family":"Taylor","given":"Ione","email":"itaylor@usgs.gov","middleInitial":"L.","affiliations":[],"preferred":true,"id":477363,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Belnap, Jayne 0000-0001-7471-2279 jayne_belnap@usgs.gov","orcid":"https://orcid.org/0000-0001-7471-2279","contributorId":1332,"corporation":false,"usgs":true,"family":"Belnap","given":"Jayne","email":"jayne_belnap@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":477366,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cronin, Thomas M. 0000-0002-2643-0979 tcronin@usgs.gov","orcid":"https://orcid.org/0000-0002-2643-0979","contributorId":2579,"corporation":false,"usgs":true,"family":"Cronin","given":"Thomas","email":"tcronin@usgs.gov","middleInitial":"M.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":477367,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dettinger, Michael D. 0000-0002-7509-7332","orcid":"https://orcid.org/0000-0002-7509-7332","contributorId":31743,"corporation":false,"usgs":true,"family":"Dettinger","given":"Michael D.","affiliations":[],"preferred":false,"id":477372,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Frazier, Eldrich L. efrazier@usgs.gov","contributorId":5214,"corporation":false,"usgs":true,"family":"Frazier","given":"Eldrich","email":"efrazier@usgs.gov","middleInitial":"L.","affiliations":[],"preferred":true,"id":477370,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Haines, John W. 0000-0002-6475-8924 jhaines@usgs.gov","orcid":"https://orcid.org/0000-0002-6475-8924","contributorId":509,"corporation":false,"usgs":true,"family":"Haines","given":"John","email":"jhaines@usgs.gov","middleInitial":"W.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":477365,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Loveland, Thomas R. 0000-0003-3114-6646 loveland@usgs.gov","orcid":"https://orcid.org/0000-0003-3114-6646","contributorId":3005,"corporation":false,"usgs":true,"family":"Loveland","given":"Thomas R.","email":"loveland@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":477369,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Milly, Paul C.D.","contributorId":60503,"corporation":false,"usgs":true,"family":"Milly","given":"Paul C.D.","affiliations":[],"preferred":false,"id":477375,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"O'Malley, Robin","contributorId":202833,"corporation":false,"usgs":true,"family":"O'Malley","given":"Robin","affiliations":[{"id":477,"text":"North Central Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":772050,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Thompson, Robert S. 0000-0001-9287-2954 rthompson@usgs.gov","orcid":"https://orcid.org/0000-0001-9287-2954","contributorId":891,"corporation":false,"usgs":true,"family":"Thompson","given":"Robert","email":"rthompson@usgs.gov","middleInitial":"S.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":772051,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Maule, Alec G. amaule@usgs.gov","contributorId":2606,"corporation":false,"usgs":true,"family":"Maule","given":"Alec","email":"amaule@usgs.gov","middleInitial":"G.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":477368,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"McMahon, Gerard 0000-0001-7675-777X gmcmahon@usgs.gov","orcid":"https://orcid.org/0000-0001-7675-777X","contributorId":191488,"corporation":false,"usgs":true,"family":"McMahon","given":"Gerard","email":"gmcmahon@usgs.gov","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":477364,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Striegl, Robert G. 0000-0002-8251-4659 rstriegl@usgs.gov","orcid":"https://orcid.org/0000-0002-8251-4659","contributorId":1630,"corporation":false,"usgs":true,"family":"Striegl","given":"Robert","email":"rstriegl@usgs.gov","middleInitial":"G.","affiliations":[{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":false,"id":477371,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}} ,{"id":70045418,"text":"ds752 - 2013 - Estimated annual agricultural pesticide use for counties of the conterminous United States, 1992--2009","interactions":[],"lastModifiedDate":"2013-04-15T15:19:30","indexId":"ds752","displayToPublicDate":"2013-04-15T00:00:00","publicationYear":"2013","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":"752","title":"Estimated annual agricultural pesticide use for counties of the conterminous United States, 1992--2009","docAbstract":"This report provides estimated annual agricultural pesticide use for counties of the conterminous United States for 459 compounds from 1992 through 2009 following the methods described in Thelin and Stone (2013). As described in Thelin and Stone (2013), U.S. Department of Agriculture county-level data for harvested-crop acreage were used in conjunction with proprietary Crop Reporting District (CRD)-level pesticide-use data to estimate county-level pesticide use. Estimated pesticide use (EPest) values were calculated with both the EPest-high and EPest-low methods. The distinction between the EPest-high method and the EPest-low method is that there are more counties with estimated pesticide use for EPest-high compared to EPest-low (Thelin and Stone, 2013). The estimates of annual agricultural pesticide use are provided in tab-delimited files and organized by compound, year, state Federal Information Processing Standard (FIPS) code, county FIPS code, and kg (amount in kilograms).\n\nEPest-high county pesticide-use estimates were divided into tables 1 through 7 by pesticide name:\n\nTable 1: 2, 4-D through Chlordimeform\nTable 2: Chlorethoxyfos through Diflufenzopyr\nTable 3: Dimethenamid through Gibberellic acid\nTable 4: Glufosinate through Metriam\nTable 5: Metolachlor through Propazine\nTable 6: Propiconazole through Triazamate\nTable 7: Tribenuron methyl through Zoxamide\n\nEPest-low county pesticide-use estimates were divided into tables 8 through 14 by pesticide name:\n\nTable 8: 2, 4-D through Chlordimeform\nTable 9: Chlorethoxyfos through Diflufenzopyr\nTable 10: Dimethenamid through Gibberellic acid\nTable 11: Glufosinate through Metriam\nTable 12: Metolachlor through Propazine\nTable 13: Propiconazole through Triazamate\nTable 14: Tribenuron methyl through Zoxamide","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds752","usgsCitation":"Stone, W.W., 2013, Estimated annual agricultural pesticide use for counties of the conterminous United States, 1992--2009: U.S. Geological Survey Data Series 752, Pamphlet: iii, 1 p.; 14 Tables, https://doi.org/10.3133/ds752.","productDescription":"Pamphlet: iii, 1 p.; 14 Tables","additionalOnlineFiles":"Y","temporalStart":"1992-01-01","temporalEnd":"2009-12-31","costCenters":[{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":270941,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds752.png"},{"id":270926,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/752/pdf/ds752.pdf"},{"id":270925,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/752/"},{"id":270927,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/752/EPest.high.county.estimates.table1.txt"},{"id":270928,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/752/EPest.high.county.estimates.table2.txt"},{"id":270929,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/752/EPest.high.county.estimates.table3.txt"},{"id":270930,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/752/EPest.high.county.estimates.table4.txt"},{"id":270931,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/752/EPest.high.county.estimates.table5.txt"},{"id":270932,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/752/EPest.high.county.estimates.table6.txt"},{"id":270933,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/752/EPest.high.county.estimates.table7.txt"},{"id":270934,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/752/EPest.low.county.estimates.table8.txt"},{"id":270935,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/752/EPest.low.county.estimates.table9.txt"},{"id":270936,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/752/EPest.low.county.estimates.table10.txt"},{"id":270937,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/752/EPest.low.county.estimates.table11.txt"},{"id":270938,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/752/EPest.low.county.estimates.table12.txt"},{"id":270939,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/752/EPest.low.county.estimates.table13.txt"},{"id":270940,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/752/EPest.low.county.estimates.table14.txt"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.79,24.52 ], [ -124.79,49.0 ], [ -66.95,49.0 ], [ -66.95,24.52 ], [ -124.79,24.52 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"516d135ae4b0411d430a899d","contributors":{"authors":[{"text":"Stone, Wesley W. 0000-0003-0239-2063 wwstone@usgs.gov","orcid":"https://orcid.org/0000-0003-0239-2063","contributorId":1496,"corporation":false,"usgs":true,"family":"Stone","given":"Wesley","email":"wwstone@usgs.gov","middleInitial":"W.","affiliations":[{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true}],"preferred":true,"id":477470,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70045416,"text":"sir20135009 - 2013 - Estimation of annual agricultural pesticide use for counties of the conterminous United States, 1992-2009","interactions":[],"lastModifiedDate":"2017-05-26T09:37:34","indexId":"sir20135009","displayToPublicDate":"2013-04-15T00:00:00","publicationYear":"2013","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":"2013-5009","subseriesTitle":"National Water-Quality Assessment Program","title":"Estimation of annual agricultural pesticide use for counties of the conterminous United States, 1992-2009","docAbstract":"A method was developed to calculate annual county level pesticide use for selected herbicides, insecticides, and fungicides applied to agricultural crops grown in the conterminous United States from 1992 through 2009. Pesticide-use data compiled by proprietary surveys of farm operations located within Crop Reporting Districts were used in conjunction with annual harvested-crop acreage reported by the U.S. Department of Agriculture National Agricultural Statistics Service (NASS) to calculate use rates per harvested crop acre, or an 'estimated pesticide use' (EPest) rate, for each crop by year. Pesticide-use data were not available for all Crop Reporting Districts and years. When data were unavailable for a Crop Reporting District in a particular year, EPest extrapolated rates were calculated from adjoining or nearby Crop Reporting Districts to ensure that pesticide use was estimated for all counties that reported harvested-crop acreage. EPest rates were applied to county harvested-crop acreage differently to obtain EPest-low and EPest-high estimates of pesticide-use for counties and states, with the exception of use estimates for California, which were taken from annual Department of Pesticide Regulation Pesticide Use Reports. Annual EPest-low and EPest-high use totals were compared with other published pesticide-use reports for selected pesticides, crops, and years. EPest-low and EPest-high national totals for five of seven herbicides were in close agreement with U.S. Environmental Protection Agency and National Pesticide Use Data estimates, but greater than most NASS national totals. A second set of analyses compared EPest and NASS annual state totals and state-by-crop totals for selected crops. Overall, EPest and NASS use totals were not significantly different for the majority of crop-stateyear combinations evaluated. Furthermore, comparisons of EPest and NASS use estimates for most pesticides had rank correlation coefficients greater than 0.75 and median relative errors of less than 15 percent. Of the 48 pesticide-by-crop combinations with 10 or more state-year combinations, 12 of the EPest-low and 17 of the EPest-high totals showed significant differences (p < 0.05) from NASS use estimates. The differences between EPest and NASS estimates did not follow consistent patterns related to particular crops, years, or states, and most correlation coefficients were greater than 0.75. EPest values from this study are suitable for making national, regional, and watershed assessments of annual pesticide use from 1992 to 2009. Although estimates are provided by county to facilitate estimation of watershed pesticide use for a wide variety of watersheds, there is a greater degree of uncertainty in individual county-level estimates when compared to Crop Reporting District or state-level estimates because (1) EPest crop-use rates were developed on the basis of pesticide use on harvested acres in multi-county areas (Crop Reporting Districts) and then allocated to county harvested cropland; (2) pesticide-by-crop use rates were not available for all Crop Reporting Districts in the conterminous United States, and extrapolation methods were used to estimate pesticide use for some counties; and (3) it is possible that surveyed pesticide-by-crop use rates do not reflect all agricultural use on all crops grown. The methods developed in this study also are applicable to other agricultural pesticides and years.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135009","usgsCitation":"Thelin, G.P., and Stone, W.W., 2013, Estimation of annual agricultural pesticide use for counties of the conterminous United States, 1992-2009: U.S. Geological Survey Scientific Investigations Report 2013-5009, Report: viii, 54 p.; Appendix 1: XLSX file; Appendix 2: XLSX file; Companion Report, https://doi.org/10.3133/sir20135009.","productDescription":"Report: viii, 54 p.; Appendix 1: XLSX file; Appendix 2: XLSX file; Companion Report","numberOfPages":"66","additionalOnlineFiles":"Y","temporalStart":"1992-01-01","temporalEnd":"2009-12-31","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":270924,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135009.jpg"},{"id":270919,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5009/"},{"id":270920,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5009/pdf/sir20135009.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"}},{"id":270921,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2013/5009/sir20135009_appendix1.xlsx","text":"Appendix 1","linkFileType":{"id":3,"text":"xlsx"}},{"id":270922,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2013/5009/sir20135009_appendix2.xlsx","text":"Appendix 2","linkFileType":{"id":3,"text":"xlsx"}},{"id":270923,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/ds/752/","text":"Estimated Annual Agricultural Pesticide Use for Counties of the Conterminous United States, 1992–2009 (USGS Data Series 752)"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.8,24.5 ], [ -124.8,49.383333 ], [ -66.95,49.383333 ], [ -66.95,24.5 ], [ -124.8,24.5 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"516d135be4b0411d430a89a1","contributors":{"authors":[{"text":"Thelin, Gail P.","contributorId":75178,"corporation":false,"usgs":true,"family":"Thelin","given":"Gail","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":477469,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stone, Wesley W. 0000-0003-0239-2063 wwstone@usgs.gov","orcid":"https://orcid.org/0000-0003-0239-2063","contributorId":1496,"corporation":false,"usgs":true,"family":"Stone","given":"Wesley","email":"wwstone@usgs.gov","middleInitial":"W.","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true},{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":477468,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70045467,"text":"70045467 - 2013 - The influence of regional hydrology on nesting behavior and nest fate of the American alligator","interactions":[],"lastModifiedDate":"2013-04-18T09:11:58","indexId":"70045467","displayToPublicDate":"2013-04-15T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"The influence of regional hydrology on nesting behavior and nest fate of the American alligator","docAbstract":"Hydrologic conditions are critical to the nesting behavior and reproductive success of crocodilians. In South Florida, USA, growing human settlement has led to extensive surface water management and modification of historical water flows in the wetlands, which have affected regional nesting of the American alligator (Alligator mississippiensis). Although both natural and anthropogenic factors are considered to determine hydrologic conditions, the aspects of hydrological patterns that affect alligator nest effort, flooding (partial and complete), and failure (no hatchling) are unclear. We deconstructed annual hydrological patterns using harmonic models that estimated hydrological matrices including mean, amplitude, timing of peak, and periodicity of surface water depth and discharge and examined their effects on alligator nesting using survey data from Shark Slough, Everglades National Park, from 1985 to 2005. Nest effort increased in years with higher mean and lesser periodicity of water depth. A greater proportion of nests were flooded and failed when peak discharge occurred earlier in the year. Also, nest flooding rates were greater in years with greater periodicity of water depth, and nest failure rate was greater when mean discharge was higher. This study guides future water management decisions to mitigate negative impacts on reproduction of alligators and provides wildlife managers with a tool for assessing and modifying annual water management plans to conserve crocodilians and other wetland species.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Wildlife Management","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","publisherLocation":"Hoboken, NJ","doi":"10.1002/jwmg.463","usgsCitation":"Ugarte, C.A., Bass, O.L., Nuttle, W., Mazzotti, F., Rice, K.G., Fujisaki, I., and Whelan, K.R., 2013, The influence of regional hydrology on nesting behavior and nest fate of the American alligator: Journal of Wildlife Management, v. 77, no. 1, p. 192-199, https://doi.org/10.1002/jwmg.463.","productDescription":"8 p.","startPage":"192","endPage":"199","numberOfPages":"8","ipdsId":"IP-026739","costCenters":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"links":[{"id":271050,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/jwmg.463"},{"id":271051,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Shark Slough Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -81,5.555555555555556E-4 ], [ -81,5.555555555555556E-4 ], [ -80.00694444444444,5.555555555555556E-4 ], [ -80.00694444444444,5.555555555555556E-4 ], [ -81,5.555555555555556E-4 ] ] ] } } ] }","volume":"77","issue":"1","noUsgsAuthors":false,"publicationDate":"2012-09-27","publicationStatus":"PW","scienceBaseUri":"517115e2e4b005316063424d","contributors":{"authors":[{"text":"Ugarte, Cristina A.","contributorId":11913,"corporation":false,"usgs":true,"family":"Ugarte","given":"Cristina","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":477560,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bass, Oron L.","contributorId":108004,"corporation":false,"usgs":true,"family":"Bass","given":"Oron","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":477565,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nuttle, William","contributorId":63685,"corporation":false,"usgs":true,"family":"Nuttle","given":"William","affiliations":[],"preferred":false,"id":477563,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mazzotti, Frank J.","contributorId":100018,"corporation":false,"usgs":false,"family":"Mazzotti","given":"Frank J.","affiliations":[{"id":12557,"text":"University of Florida, FLREC","active":true,"usgs":false}],"preferred":false,"id":477564,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rice, Kenneth G. 0000-0001-8282-1088 krice@usgs.gov","orcid":"https://orcid.org/0000-0001-8282-1088","contributorId":117,"corporation":false,"usgs":true,"family":"Rice","given":"Kenneth","email":"krice@usgs.gov","middleInitial":"G.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":477559,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fujisaki, Ikuko","contributorId":31108,"corporation":false,"usgs":false,"family":"Fujisaki","given":"Ikuko","email":"","affiliations":[{"id":12557,"text":"University of Florida, FLREC","active":true,"usgs":false}],"preferred":false,"id":477561,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Whelan, Kevin R.T.","contributorId":53894,"corporation":false,"usgs":true,"family":"Whelan","given":"Kevin","email":"","middleInitial":"R.T.","affiliations":[],"preferred":false,"id":477562,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70118022,"text":"70118022 - 2013 - Modeling mountain pine beetle disturbance in Glacier National Park using multiple lines of evidence","interactions":[],"lastModifiedDate":"2014-07-25T09:24:04","indexId":"70118022","displayToPublicDate":"2013-04-13T09:10:24","publicationYear":"2013","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":18,"text":"Abstract or summary"},"title":"Modeling mountain pine beetle disturbance in Glacier National Park using multiple lines of evidence","docAbstract":"Temperate forest ecosystems are subject to various disturbances which contribute to ecological legacies that can have profound effects on the structure of the ecosystem. Impacts of disturbance can vary widely in extent, duration and severity over space and time. Given that global climate change is expected to increase rates of forest disturbance, an understanding of these events are critical in the interpretation of contemporary forest patterns and those of the near future. We seek to understand the impact of the 1970s mountain pine beetle outbreak on the landscape of Glacier National Park and investigate any connection between this event and subsequent decades of extensive wildfire. The lack of spatially explicit data on the mountain pine beetle disturbance represents a major data gap and inhibits our ability to test for correlations between outbreak severity and fire severity. To overcome this challenge, we utilized multiple lines of evidence to model forest canopy mortality as a proxy for outbreak severity. We used historical aerial and landscape photos, reports, aerial survey data, a six year collection of Landsat imagery and abiotic data in combination with regression analysis. The use of remotely sensed data is critical in large areas where subsequent disturbance (fire) has erased some of the evidence from the landscape. Results indicate that this method is successful in capturing the spatial heterogeneity of the outbreak in a topographically complex landscape. Furthermore, this study provides an example on the use of existing data to reduce levels of uncertainty associated with an historic disturbance.","conferenceTitle":"Association of American Geographers Annual Meeting","conferenceDate":"2013-04-13T00:00:00","conferenceLocation":"Chicago, IL","language":"English","publisher":"Association of American Geographers","publisherLocation":"Washington, D.C.","usgsCitation":"Assal, T., and Sibold, J., 2013, Modeling mountain pine beetle disturbance in Glacier National Park using multiple lines of evidence, Association of American Geographers Annual Meeting, Chicago, IL, 2013-04-13T00:00:00.","costCenters":[],"links":[{"id":290971,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57f7f314e4b0bc0bec0a0779","contributors":{"authors":[{"text":"Assal, Timothy","contributorId":87864,"corporation":false,"usgs":true,"family":"Assal","given":"Timothy","affiliations":[],"preferred":false,"id":496140,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sibold, Jason","contributorId":10724,"corporation":false,"usgs":false,"family":"Sibold","given":"Jason","affiliations":[],"preferred":false,"id":496139,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70156584,"text":"70156584 - 2013 - Delineation of fractures, foliation, and groundwater-flow zones of the bedrock at the Harlem River Tunnel in northern New York County, New York","interactions":[],"lastModifiedDate":"2022-11-08T19:21:19.951485","indexId":"70156584","displayToPublicDate":"2013-04-13T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Delineation of fractures, foliation, and groundwater-flow zones of the bedrock at the Harlem River Tunnel in northern New York County, New York","docAbstract":"

Advanced borehole-geophysical methods were used to investigate the hydrogeology of the crystalline bedrock in 36 boreholes on the northernmost part of New York County, New York, for the construction of a utilities tunnel beneath the Harlem River. The borehole-logging techniques were used to delineate bedrock fractures, foliation, and groundwater-flow zones in test boreholes at the site. Fracture indexes of the deep boreholes ranged from 0.65 to 0.76 per foot. Most of the fracture populations had either northwest to southwest or east to southeast dip azimuths with moderate dip angles. The mean foliation dip azimuth ranged from 100º to 124º southeast with dip angles of 52º to 60º. Groundwater appears to flow through an interconnected network of fractures that are affected by tidal variations from the nearby Harlem River and tunnel construction dewatering operations. The transmissivities of the 3 boreholes tested (USGS-1, USGS-3, and USGS-4), calculated from specific capacity data, were 2, 48, and 30 feet squared per day (ft2/d), respectively. The highest transmissivities were observed in wells north and west of the secant ring. Three borehole-radar velocity tomograms were collected. In the USGS-1 and USGS-4 velocity tomogram there are two areas of low radar velocity. The first is at the top of the tomogram and runs from 105 ft below land surface (BLS) at USGS-4 and extends to 125 ft BLS at USGS-1, the second area is centered at a depth of 150 ft BLS at USGS-1 and 135 to 150 ft BLS at USGS-4. Field measurements of specific conductance of 14 boreholes under ambient conditions at the site indicate an increase in conductivity toward the southwest part of the site (nearest the Harlem River). Specific conductance ranged from 107 microsiemens per centimeter (μS/cm) (borehole 63C) to 11,000 μS/cm (borehole 79B). The secant boreholes had the highest specific conductance.

","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"20th Conference on the geology of Long Island and metropolitan New York","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"20th Conference on the Geology of Long Island and Metropolitan New York","conferenceDate":"April 13, 2013","conferenceLocation":"Stony Brook, New York, United States","language":"English","usgsCitation":"Stumm, F., Chu, A., Joesten, P.K., Noll, M.L., and Como, M.D., 2013, Delineation of fractures, foliation, and groundwater-flow zones of the bedrock at the Harlem River Tunnel in northern New York County, New York, in 20th Conference on the geology of Long Island and metropolitan New York, Stony Brook, New York, United States, April 13, 2013, 12 p.","productDescription":"12 p.","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":307345,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Harlem River Tunnel","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -73.91962970636514,\n 40.87368620296553\n ],\n [\n -73.9184101328308,\n 40.87295613540937\n ],\n [\n -73.91099106049475,\n 40.869901291739524\n ],\n [\n -73.90847569007956,\n 40.86920960945341\n ],\n [\n -73.90677336868755,\n 40.87334038249534\n ],\n [\n -73.90621439748416,\n 40.87476207732257\n ],\n [\n -73.90629062082988,\n 40.87649112448045\n ],\n [\n -73.90662092199535,\n 40.87668323804374\n ],\n [\n -73.90710366985304,\n 40.87741326449918\n ],\n [\n -73.90796753443999,\n 40.87823933735811\n ],\n [\n -73.90875517568126,\n 40.878796450442564\n ],\n [\n -73.91035586594568,\n 40.880121976516676\n ],\n [\n -73.91063535154734,\n 40.880544602437624\n ],\n [\n -73.91142299278862,\n 40.8801796074828\n ],\n [\n -73.91236308072129,\n 40.87933434828133\n ],\n [\n -73.9140399943314,\n 40.87833539167303\n ],\n [\n -73.91536119899413,\n 40.87795117357837\n ],\n [\n -73.91607261688893,\n 40.87800880643462\n ],\n [\n -73.91663158809229,\n 40.87785511870598\n ],\n [\n -73.91785116162741,\n 40.87725957538848\n ],\n [\n -73.91787656940933,\n 40.8762797989169\n ],\n [\n -73.91919777407206,\n 40.8746852297337\n ],\n [\n -73.91962970636514,\n 40.87368620296553\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55dc402de4b0518e354d10e7","contributors":{"authors":[{"text":"Stumm, Frederick 0000-0002-5388-8811 fstumm@usgs.gov","orcid":"https://orcid.org/0000-0002-5388-8811","contributorId":1077,"corporation":false,"usgs":true,"family":"Stumm","given":"Frederick","email":"fstumm@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":569582,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chu, Anthony 0000-0001-8623-2862 achu@usgs.gov","orcid":"https://orcid.org/0000-0001-8623-2862","contributorId":2517,"corporation":false,"usgs":true,"family":"Chu","given":"Anthony","email":"achu@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":569583,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Joesten, Peter K. pjoesten@usgs.gov","contributorId":1929,"corporation":false,"usgs":true,"family":"Joesten","given":"Peter","email":"pjoesten@usgs.gov","middleInitial":"K.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true},{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true}],"preferred":true,"id":569584,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Noll, Michael L. 0000-0003-2050-3134 mnoll@usgs.gov","orcid":"https://orcid.org/0000-0003-2050-3134","contributorId":4652,"corporation":false,"usgs":true,"family":"Noll","given":"Michael","email":"mnoll@usgs.gov","middleInitial":"L.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":569585,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Como, Michael D. 0000-0002-7911-5390 mcomo@usgs.gov","orcid":"https://orcid.org/0000-0002-7911-5390","contributorId":4651,"corporation":false,"usgs":true,"family":"Como","given":"Michael","email":"mcomo@usgs.gov","middleInitial":"D.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":569586,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70045394,"text":"70045394 - 2013 - Distribution of Pacific lamprey Entosphenus tridentatus in watersheds of Puget Sound Based on smolt monitoring data","interactions":[],"lastModifiedDate":"2016-05-04T15:46:28","indexId":"70045394","displayToPublicDate":"2013-04-13T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2900,"text":"Northwest Science","onlineIssn":"2161-9859","printIssn":"0029-344X","active":true,"publicationSubtype":{"id":10}},"title":"Distribution of Pacific lamprey Entosphenus tridentatus in watersheds of Puget Sound Based on smolt monitoring data","docAbstract":"

Lamprey populations are in decline worldwide and the status of Pacific lamprey (Entosphenus tridentatus) is a topic of current interest. They and other lamprey species cycle nutrients and serve as prey in riverine ecosystems. To determine the current distribution of Pacific lamprey in major watersheds flowing into Puget Sound, Washington, we sampled lamprey captured during salmonid smolt monitoring that occurred from late winter to mid-summer. We found Pacific lamprey in 12 of 18 watersheds and they were most common in southern Puget Sound watersheds and in watersheds draining western Puget Sound (Hood Canal). Two additional species, western brook lamprey (Lampetra richardsoni) and river lamprey (L. ayresii) were more common in eastern Puget Sound watersheds. Few Pacific lamprey macrophthalmia were found, suggesting that the majority of juveniles migrated seaward during other time periods. In addition, “dwarf” adult Pacific lamprey (< 300 mm) were observed in several watersheds and may represent an alternate life history for some Puget Sound populations. Based on genetic data, the use of visual techniques to identify lamprey ammocoetes as Entosphenus or Lampetra was successful for 97% (34 of 35) of the samples we evaluated.

","language":"English","publisher":"Northwest Scientific Association","doi":"10.3955/046.087.0202","usgsCitation":"Hayes, M.C., Hays, R., Rubin, S.P., Chase, D., Hallock, M., Cook-Tabor, C., Luzier, C.W., and Moser, M., 2013, Distribution of Pacific lamprey Entosphenus tridentatus in watersheds of Puget Sound Based on smolt monitoring data: Northwest Science, v. 87, no. 2, p. 95-105, https://doi.org/10.3955/046.087.0202.","productDescription":"11 p.","startPage":"95","endPage":"105","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-040130","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":270873,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Puget Sound","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.7513,47.7495 ], [ -122.7513,48.2117 ], [ -122.3315,48.2117 ], [ -122.3315,47.7495 ], [ -122.7513,47.7495 ] ] ] } } ] }","volume":"87","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd5580e4b0b290850f6571","contributors":{"authors":[{"text":"Hayes, Michael C. 0000-0002-9060-0565 mhayes@usgs.gov","orcid":"https://orcid.org/0000-0002-9060-0565","contributorId":3017,"corporation":false,"usgs":true,"family":"Hayes","given":"Michael","email":"mhayes@usgs.gov","middleInitial":"C.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":477343,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hays, Richard","contributorId":59320,"corporation":false,"usgs":true,"family":"Hays","given":"Richard","email":"","affiliations":[],"preferred":false,"id":477349,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rubin, Stephen P. 0000-0003-3054-7173","orcid":"https://orcid.org/0000-0003-3054-7173","contributorId":38037,"corporation":false,"usgs":true,"family":"Rubin","given":"Stephen","email":"","middleInitial":"P.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":477347,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chase, Dorothy M.","contributorId":59319,"corporation":false,"usgs":true,"family":"Chase","given":"Dorothy M.","affiliations":[],"preferred":false,"id":477348,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hallock, Molly","contributorId":24251,"corporation":false,"usgs":true,"family":"Hallock","given":"Molly","email":"","affiliations":[],"preferred":false,"id":477344,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cook-Tabor, Carrie","contributorId":31649,"corporation":false,"usgs":true,"family":"Cook-Tabor","given":"Carrie","affiliations":[],"preferred":false,"id":477345,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Luzier, Christina W.","contributorId":37616,"corporation":false,"usgs":true,"family":"Luzier","given":"Christina","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":477346,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Moser, Mary L.","contributorId":83412,"corporation":false,"usgs":true,"family":"Moser","given":"Mary L.","affiliations":[],"preferred":false,"id":477350,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70045398,"text":"ds758 - 2013 - Digital database of the Holocene tephras of the Mono-Inyo Craters, California","interactions":[],"lastModifiedDate":"2013-04-12T21:41:14","indexId":"ds758","displayToPublicDate":"2013-04-12T00:00:00","publicationYear":"2013","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":"758","title":"Digital database of the Holocene tephras of the Mono-Inyo Craters, California","docAbstract":"This digital product comprises a collection of age and isopach data for the Holocene tephras of the Mono-Inyo Craters, California. Data on the most recent eruptions from this volcanic chain are relatively comprehensive, getting less so the further back in time. For the most recent eruptions to about 1,500 years ago, tephra beds within separate eruptive sequences have been studied and isopached. Before this, from about 2,000 years ago to about 5,000 years ago, there are insufficient data for isopaching. However, one isolated tephra of about 9,000 years ago was studied and isopached in detail.\n\nRegarding ages, there are many tens of radiocarbon ages that have been obtained on the Holocene Mono-Inyo volcanic products. The vast majority of these radiocarbon dates are associated with tephras at locales that can be considered distal (basically where the primary tephra is less than several centimeters (cm) thick). These dates represent carbon that was sequestered perhaps within several hundred years of the eruption but do not represent the ages of separate eruptive pulses. There are two reasons for this. In some cases, it is clear that the dated material is not associated with the eruption products. This is the case in some lake strata where carbon is either not physically close to a given tephra layer or where an age for a tephra layer was obtained by interpolation assuming a sedimentation rate. In other cases, it is not clear that a given tephra layer represents a primary tephra; in such cases the layer could instead be redeposited. At most distal localities (beyond about 5 kilometers (km) from the chain), there was no record made of whether tephra was primary or redeposited, and at these distances where tephra is thin, it is generally redeposited during later events such as fires or thunderstorms. These age data are not appropriate for use in dating the eruptive history of the volcanic chain, and are therefore not included in the present contribution.\n\nThe carbon age data in the present contribution were obtained by careful consideration of the material being collected. In the best instances, carbon was collected from new growth on plants that were probably killed by an eruption event through burning and burial. Slightly poorer data were collected from burned and buried forest duff that is renewed frequently. Finally, some dates for older Holocene tephra layers at Black Lake, Nevada, downwind of the Mono-Inyo Craters, appear to allow correlation of the layers to proximal occurrences. In cases where these poorer data were collected but yielded ages statistically indistinguishable from better data, the poorer data were included in the analysis. In the most difficult cases, usually the furthest back in time, poorer data that were nevertheless statistically indistinguishable were weighted together to generate the age estimate.\n\nThere are some known Holocene eruptions from the Mono-Inyo Craters that are not included in this tabulation, as so far a tephra has not been associated with the eruptions. A good example of this is the Java blocks. The Java block eruption, from a vent underlying the northwestern corner of Negit Island in Mono Lake, expelled numerous blocks that were rafted within the lake and that are mostly deposited on the southwestern and northern lakeshore. No tephra that can be correlated to this deposit has been found, and therefore the eruption is not included in this tabulation.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds758","usgsCitation":"Bursik, M., and Sieh, K., 2013, Digital database of the Holocene tephras of the Mono-Inyo Craters, California: U.S. Geological Survey Data Series 758, iv, 6 p.; Data Table; All Data, https://doi.org/10.3133/ds758.","productDescription":"iv, 6 p.; Data Table; All Data","numberOfPages":"10","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":270871,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds758.gif"},{"id":270867,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/758/"},{"id":270870,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/758/data/1_all_data.zip"},{"id":270868,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/758/ds758_text.pdf"},{"id":270869,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/758/data/monoinyodates.html"}],"country":"United States","state":"California","otherGeospatial":"Mono-inyo Craters","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.4,32.5 ], [ -124.4,42.0 ], [ -114.0,42.0 ], [ -114.0,32.5 ], [ -124.4,32.5 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd54f9e4b0b290850f6109","contributors":{"authors":[{"text":"Bursik, Marcus","contributorId":36030,"corporation":false,"usgs":true,"family":"Bursik","given":"Marcus","affiliations":[],"preferred":false,"id":477360,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sieh, Kerry","contributorId":103945,"corporation":false,"usgs":true,"family":"Sieh","given":"Kerry","affiliations":[],"preferred":false,"id":477361,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70045385,"text":"ofr20111127 - 2013 - Construction of a 3-arcsecond digital elevation model for the Gulf of Maine","interactions":[],"lastModifiedDate":"2022-11-22T14:13:35.002513","indexId":"ofr20111127","displayToPublicDate":"2013-04-12T00:00:00","publicationYear":"2013","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":"2011-1127","title":"Construction of a 3-arcsecond digital elevation model for the Gulf of Maine","docAbstract":"A system-wide description of the seafloor topography is a basic requirement for most coastal oceanographic studies. The necessary detail of the topography obviously varies with application, but for many uses, a nominal resolution of roughly 100 m is sufficient. Creating a digital bathymetric grid with this level of resolution can be a complex procedure due to a multiplicity of data sources, data coverages, datums and interpolation procedures. This report documents the procedures used to construct a 3-arcsecond (approximately 90-meter grid cell size) digital elevation model for the Gulf of Maine (71°30' to 63° W, 39°30' to 46° N). We obtained elevation and bathymetric data from a variety of American and Canadian sources, converted all data to the North American Datum of 1983 for horizontal coordinates and the North American Vertical Datum of 1988 for vertical coordinates, used a combination of automatic and manual techniques for quality control, and interpolated gaps using a surface-fitting routine.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20111127","usgsCitation":"Twomey, E.R., and Signell, R.P., 2013, Construction of a 3-arcsecond digital elevation model for the Gulf of Maine: U.S. Geological Survey Open-File Report 2011-1127, HTML Document, https://doi.org/10.3133/ofr20111127.","productDescription":"HTML Document","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":270856,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20111127.bmp"},{"id":270854,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2011/1127/","linkFileType":{"id":5,"text":"html"}},{"id":270855,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2011/1127/titlepage.html","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Maine","otherGeospatial":"Gulf Of Maine","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -71.5,\n 46\n ],\n [\n -71.5,\n 39.5\n ],\n [\n -63,\n 39.5\n ],\n [\n -63,\n 46\n ],\n [\n -71.5,\n 46\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd52a0e4b0b290850f4a33","contributors":{"authors":[{"text":"Twomey, Erin R.","contributorId":44860,"corporation":false,"usgs":true,"family":"Twomey","given":"Erin","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":477325,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Signell, Richard P. rsignell@usgs.gov","contributorId":1435,"corporation":false,"usgs":true,"family":"Signell","given":"Richard","email":"rsignell@usgs.gov","middleInitial":"P.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":477324,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70045384,"text":"ofr20131083 - 2013 - Louisiana Barrier Island Comprehensive Monitoring (BICM) Program Summary Report: Data and Analyses 2006 through 2010","interactions":[],"lastModifiedDate":"2023-04-05T13:18:14.881422","indexId":"ofr20131083","displayToPublicDate":"2013-04-12T00:00:00","publicationYear":"2013","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":"2013-1083","title":"Louisiana Barrier Island Comprehensive Monitoring (BICM) Program Summary Report: Data and Analyses 2006 through 2010","docAbstract":"The Barrier Island Comprehensive Monitoring (BICM) program was implemented under the Louisiana Coastal Area Science and Technology (LCA S&T) office as a component of the System Wide Assessment and Monitoring (SWAMP) program. The BICM project was developed by the State of Louisiana (Coastal Protection Restoration Authority [CPRA], formerly Department of Natural Resources [DNR]) to complement other Louisiana coastal monitoring programs such as the Coastwide Reference Monitoring System-Wetlands (CRMS-Wetlands) and was a collaborative research effort by CPRA, University of New Orleans (UNO), and the U.S. Geological Survey (USGS). The goal of the BICM program was to provide long-term data on the barrier islands of Louisiana that could be used to plan, design, evaluate, and maintain current and future barrier-island restoration projects. The BICM program used both historical and newly acquired (2006 to 2010) data to assess and monitor changes in the aerial and subaqueous extent of islands, habitat types, sediment texture and geotechnical properties, environmental processes, and vegetation composition. BICM datasets included aerial still and video photography (multiple time series) for shoreline positions, habitat mapping, and land loss; light detection and ranging (lidar) surveys for topographic elevations; single-beam and swath bathymetry; and sediment grab samples. Products produced using BICM data and analyses included (but were not limited to) storm-impact assessments, rate of shoreline and bathymetric change, shoreline-erosion and accretion maps, high-resolution elevation maps, coastal-shoreline and barrier-island habitat-classification maps, and coastal surficial-sediment characterization maps. Discussions in this report summarize the extensive data-collection efforts and present brief interpretive analyses for four coastal Louisiana geographic regions. In addition, several coastal-wide and topical themes were selected that integrate the data and analyses within a broader coastal context: (1) barrier-shoreline evolution driven by rapid relative sea-level rise (RSLR), (2) hurricane impacts to the Chandeleur Islands and likelihood of island recovery, (3) impact of tropical storms on barrier shorelines, (4) Barataria Bay tidal-inlet management, and (5) habitat changes related to RSLR. The final theme addresses potential future goals of the BICM program, including rotational annual to semi-decadal monitoring, proposed new-data collection, how to incorporate technological advances with previous data-collection and monitoring protocols, and standardizing methods and quality-control assessments for continued coastal monitoring and restoration.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131083","usgsCitation":"Kindinger, J.L., Buster, N.A., Flocks, J.G., Bernier, J., and Kulp, M., 2013, Louisiana Barrier Island Comprehensive Monitoring (BICM) Program Summary Report: Data and Analyses 2006 through 2010: U.S. Geological Survey Open-File Report 2013-1083, xii, 86 p., https://doi.org/10.3133/ofr20131083.","productDescription":"xii, 86 p.","numberOfPages":"100","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":270851,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131083.gif"},{"id":270850,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1083/pdf/ofr2013-1083.pdf"},{"id":270849,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1083/"}],"country":"United States","state":"Louisiana","otherGeospatial":"Acadiana Bays, Chenier Plain, Mississippi River Delta Plain, Pontchartrain Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -93.72283095158805,\n 30.195489802441173\n ],\n [\n -93.92316014269579,\n 29.80663794050693\n ],\n [\n -93.81263369242943,\n 29.65667474997356\n ],\n [\n -93.63993611388814,\n 29.710687319156023\n ],\n [\n -93.17710660339773,\n 29.698687034477473\n ],\n [\n -92.28598709812483,\n 29.46439536022504\n ],\n [\n -91.33269646457647,\n 29.17529191430168\n ],\n [\n -90.31032679961224,\n 29.024393407178422\n ],\n [\n -89.43302310062232,\n 28.861174998204078\n ],\n [\n -88.97710149327335,\n 29.07270499115147\n ],\n [\n -89.23269390951455,\n 30.093937319227948\n ],\n [\n -89.58499696973861,\n 30.159659686308487\n ],\n [\n -89.65407600115556,\n 30.35656389863381\n ],\n [\n -90.14453712421245,\n 30.511422052760707\n ],\n [\n -90.60045873156137,\n 30.350602907818654\n ],\n [\n -90.83532743837759,\n 29.632659850727023\n ],\n [\n -91.0701961451938,\n 29.95039138912159\n ],\n [\n -91.82315758763387,\n 30.14771341947055\n ],\n [\n -92.12710532586651,\n 30.046111770642014\n ],\n [\n -93.1011196688393,\n 30.195489802441173\n ],\n [\n -93.72283095158805,\n 30.195489802441173\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd6505e4b0b290850ffd46","contributors":{"authors":[{"text":"Kindinger, Jack L. jkindinger@usgs.gov","contributorId":815,"corporation":false,"usgs":true,"family":"Kindinger","given":"Jack","email":"jkindinger@usgs.gov","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":477319,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Buster, Noreen A. 0000-0001-5069-9284 nbuster@usgs.gov","orcid":"https://orcid.org/0000-0001-5069-9284","contributorId":3750,"corporation":false,"usgs":true,"family":"Buster","given":"Noreen","email":"nbuster@usgs.gov","middleInitial":"A.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":477322,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Flocks, James G. 0000-0002-6177-7433 jflocks@usgs.gov","orcid":"https://orcid.org/0000-0002-6177-7433","contributorId":816,"corporation":false,"usgs":true,"family":"Flocks","given":"James","email":"jflocks@usgs.gov","middleInitial":"G.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":477320,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bernier, Julie 0000-0002-9918-5353 jbernier@usgs.gov","orcid":"https://orcid.org/0000-0002-9918-5353","contributorId":3549,"corporation":false,"usgs":true,"family":"Bernier","given":"Julie","email":"jbernier@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":477321,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kulp, Mark A.","contributorId":16113,"corporation":false,"usgs":true,"family":"Kulp","given":"Mark A.","affiliations":[],"preferred":false,"id":477323,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70045365,"text":"sim3254 - 2013 - California State Waters Map Series — Offshore of Ventura, California","interactions":[],"lastModifiedDate":"2022-04-15T21:04:23.508233","indexId":"sim3254","displayToPublicDate":"2013-04-11T00:00:00","publicationYear":"2013","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":"3254","title":"California State Waters Map Series — Offshore of Ventura, California","docAbstract":"In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within the 3-nautical-mile limit of California’s State Waters. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data, acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow (to about 100 m) subsurface geology.\n\nThe Offshore of Ventura map area lies within the Santa Barbara Channel region of the Southern California Bight. This geologically complex region forms a major biogeographic transition zone, separating the cold-temperate Oregonian province north of Point Conception from the warm-temperate California province to the south. The map area is in the Ventura Basin, in the southern part of the Western Transverse Ranges geologic province, which is north of the California Continental Borderland. Significant clockwise rotation—at least 90°—since the early Miocene has been proposed for the Western Transverse Ranges, and the region is presently undergoing north-south shortening.\n\nThe city of Ventura is the major cultural center in the map area. The Ventura River cuts through Ventura, draining the Santa Ynez Mountains and the coastal hills north of Ventura. Northwest of Ventura, the coastal zone is a narrow strip containing highway and railway transportation corridors and a few small residential clusters. Rincon Island, an island constructed for oil and gas production, lies offshore of Punta Gorda. Southeast of Ventura, the coastal zone consists of the mouth and broad, alluvial plains of the Santa Clara River, and the region is characterized by urban and agricultural development. Ventura Harbor sits just north of the mouth of the Santa Clara River, in an area formerly occupied by lagoons and marshes.\n\nThe Offshore of Ventura map area lies in the eastern part of the Santa Barbara littoral cell, whose littoral drift is to the east-southeast. Drift rates of about 700,000 to 1,150,000 tons/yr have been reported at Ventura Harbor. At the east end of the littoral cell, eastward-moving sediment is trapped by Hueneme and Mugu Canyons and then transported into the deep-water Santa Monica Basin. The largest sediment source to this littoral cell (and the largest in all of southern California) is the Santa Clara River, which has an estimated annual sediment flux of 3.1 million tons. In addition, the Ventura River yields about 270,000 tons of sediment annually. Despite the large local sediment supply, coastal erosion problems are ongoing in the map area. Riprap, revetments, and seawalls variably protect the coast within and north of Ventura.\n\nThe offshore part of the map area mainly consists of relatively flat, shallow continental shelf, which dips so gently (about 0.2° to 0.4°) that water depths at the 3-nautical-mile limit of California’s State Waters are just 20 to 40 m. This part of the Santa Barbara Channel is relatively well protected from large Pacific swells from the north and west by Point Conception and the Channel Islands; long-period swells affecting the area are mainly from the south-southwest. Fair-weather wave base is typically shallower than 20-m water depth, but winter storms are capable of resuspending fine-grained sediments in 30 m of water, and so shelf sediments in the map area probably are remobilized on an annual basis. The shelf is underlain by tens of meters of interbedded upper Quaternary shelf, estuarine, and fluvial sediments deposited as sea level fluctuated up and down in the last several hundred thousand years.\n\nSeafloor habitats in the broad Santa Barbara Channel region consist of significant amounts of soft sediment and isolated areas of rocky habitat that support kelp-forest communities nearshore and rocky-reef communities in deep water. The potential marine benthic habitat types mapped in the Offshore of Ventura map area are directly related to its Quaternary geologic history, geomorphology, and active sedimentary processes. These potential habitats lie within the Shelf (continental shelf) megahabitat, dominated by a flat seafloor and substrates formed from deposition of fluvial and marine sediment during sea-level rise. This flat, fairly homogeneous seafloor, composed primarily of unconsolidated sand and mud and local deposits of gravel, cobbles, and pebbles, provides promising habitat for groundfish, crabs, shrimp, and other marine benthic organisms. The only significant interruptions to this homogeneous habitat type are exposures of hard, irregular sedimentary bedrock and coarse-grained sediment where potential habitats for rockfish and related species exist.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3254","usgsCitation":"Johnson, S.Y., Dartnell, P., Cochrane, G.R., Golden, N., Phillips, E., Ritchie, A.C., Kvitek, R.G., Greene, H., Krigsman, L., Endris, C.A., Seitz, G., Gutierrez, C.I., Sliter, R.W., Erdey, M.D., Wong, F.L., Yoklavich, M.M., Draut, A.E., and Hart, P.E., 2013, California State Waters Map Series — Offshore of Ventura, California: U.S. Geological Survey Scientific Investigations Map 3254, Report: iv, 42 p.; 11 Sheets: 53.00 × 36.00 inches or smaller; Metadata; Data Catalog, https://doi.org/10.3133/sim3254.","productDescription":"Report: iv, 42 p.; 11 Sheets: 53.00 × 36.00 inches or smaller; Metadata; Data 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Gary","affiliations":[],"preferred":false,"id":477302,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Krigsman, Lisa M.","contributorId":43642,"corporation":false,"usgs":true,"family":"Krigsman","given":"Lisa M.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":477299,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Endris, Charles A.","contributorId":87824,"corporation":false,"usgs":true,"family":"Endris","given":"Charles","email":"","middleInitial":"A.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":477301,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Seitz, Gordon G.","contributorId":17303,"corporation":false,"usgs":false,"family":"Seitz","given":"Gordon G.","affiliations":[{"id":7099,"text":"Calif. Geol. Survey","active":true,"usgs":false}],"preferred":false,"id":477297,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Gutierrez, Carlos I.","contributorId":32799,"corporation":false,"usgs":true,"family":"Gutierrez","given":"Carlos","email":"","middleInitial":"I.","affiliations":[],"preferred":false,"id":477298,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Sliter, Ray W. 0000-0003-0337-3454 rsliter@usgs.gov","orcid":"https://orcid.org/0000-0003-0337-3454","contributorId":1992,"corporation":false,"usgs":true,"family":"Sliter","given":"Ray","email":"rsliter@usgs.gov","middleInitial":"W.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":477290,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Erdey, Mercedes D. merdey@usgs.gov","contributorId":5411,"corporation":false,"usgs":true,"family":"Erdey","given":"Mercedes","email":"merdey@usgs.gov","middleInitial":"D.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":477296,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Wong, Florence L. 0000-0002-3918-5896 fwong@usgs.gov","orcid":"https://orcid.org/0000-0002-3918-5896","contributorId":1990,"corporation":false,"usgs":true,"family":"Wong","given":"Florence","email":"fwong@usgs.gov","middleInitial":"L.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":477289,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Yoklavich, Mary M.","contributorId":96167,"corporation":false,"usgs":true,"family":"Yoklavich","given":"Mary","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":477304,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Draut, Amy E.","contributorId":92215,"corporation":false,"usgs":true,"family":"Draut","given":"Amy","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":477303,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Hart, Patrick E. 0000-0002-5080-1426 hart@usgs.gov","orcid":"https://orcid.org/0000-0002-5080-1426","contributorId":2879,"corporation":false,"usgs":true,"family":"Hart","given":"Patrick","email":"hart@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":477294,"contributorType":{"id":1,"text":"Authors"},"rank":18}]}} ,{"id":70045356,"text":"ofr20131069 - 2013 - Forecasting the impact of storm waves and sea-level rise on Midway Atoll and Laysan Island within the Papahānaumokuākea Marine National Monument—a comparison of passive versus dynamic inundation models","interactions":[],"lastModifiedDate":"2013-04-11T07:50:43","indexId":"ofr20131069","displayToPublicDate":"2013-04-11T00:00:00","publicationYear":"2013","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":"2013-1069","title":"Forecasting the impact of storm waves and sea-level rise on Midway Atoll and Laysan Island within the Papahānaumokuākea Marine National Monument—a comparison of passive versus dynamic inundation models","docAbstract":"Two inundation events in 2011 underscored the potential for elevated water levels to damage infrastructure and affect terrestrial ecosystems on the low-lying Northwestern Hawaiian Islands in the Papahānaumokuākea Marine National Monument. The goal of this study was to compare passive \"bathtub\" inundation models based on geographic information systems (GIS) to those that include dynamic water levels caused by wave-induced set-up and run-up for two end-member island morphologies: Midway, a classic atoll with islands on the shallow (2-8 m) atoll rim and a deep, central lagoon; and Laysan, which is characterized by a deep (20-30 m) atoll rim and an island at the center of the atoll. Vulnerability to elevated water levels was assessed using hindcast wind and wave data to drive coupled physics-based numerical wave, current, and water-level models for the atolls. The resulting model data were then used to compute run-up elevations using a parametric run-up equation under both present conditions and future sea-level-rise scenarios. In both geomorphologies, wave heights and wavelengths adjacent to the island shorelines increased more than three times and four times, respectively, with increasing values of sea-level rise, as more deep-water wave energy could propagate over the atoll rim and larger wind-driven waves could develop on the atoll. Although these increases in water depth resulted in decreased set-up along the islands’ shorelines, the larger wave heights and longer wavelengths due to sea-level rise increased the resulting wave-induced run-up. Run-up values were spatially heterogeneous and dependent on the direction of incident wave direction, bathymetry, and island configuration. Island inundation was modeled to increase substantially when wave-driven effects were included, suggesting that inundation and impacts to infrastructure and terrestrial habitats will occur at lower values of predicted sea-level rise, and thus sooner in the 21st century, than suggested by passive GIS-based \"bathtub\" inundation models. Lastly, observations and the modeling results suggest that classic atolls with islands on a shallow atoll rim are more susceptible to the combined effects of sea-level rise and wave-driven inundation than atolls characterized by a deep atoll rim.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, Virginia","doi":"10.3133/ofr20131069","usgsCitation":"Storlazzi, C., Berkowitz, P., Reynolds, M.H., and Logan, J., 2013, Forecasting the impact of storm waves and sea-level rise on Midway Atoll and Laysan Island within the Papahānaumokuākea Marine National Monument—a comparison of passive versus dynamic inundation models: U.S. Geological Survey Open-File Report 2013-1069, v, 78 p., https://doi.org/10.3133/ofr20131069.","productDescription":"v, 78 p.","numberOfPages":"83","onlineOnly":"Y","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":270806,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131069.gif"},{"id":270794,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1069/of2013-1069.pdf"},{"id":270795,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1069/"}],"country":"United States","state":"Hawai'i","otherGeospatial":"Papahanaumokuakea Marine National Monument","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -159.91,18.91 ], [ -159.91,22.86 ], [ -154.81,22.86 ], [ -154.81,18.91 ], [ -159.91,18.91 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5167cd59e4b0ec0efb666ee5","contributors":{"authors":[{"text":"Storlazzi, Curt D. 0000-0001-8057-4490","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":77889,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt D.","affiliations":[],"preferred":false,"id":477282,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Berkowitz, Paul pberkowitz@usgs.gov","contributorId":4642,"corporation":false,"usgs":true,"family":"Berkowitz","given":"Paul","email":"pberkowitz@usgs.gov","affiliations":[],"preferred":true,"id":477280,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reynolds, Michelle H. 0000-0001-7253-8158 mreynolds@usgs.gov","orcid":"https://orcid.org/0000-0001-7253-8158","contributorId":3871,"corporation":false,"usgs":true,"family":"Reynolds","given":"Michelle","email":"mreynolds@usgs.gov","middleInitial":"H.","affiliations":[{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true},{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":477279,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Logan, Joshua B.","contributorId":34470,"corporation":false,"usgs":true,"family":"Logan","given":"Joshua B.","affiliations":[],"preferred":false,"id":477281,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70045373,"text":"sir20135023 - 2013 - Methods, quality assurance, and data for assessing atmospheric deposition of pesticides in the Central Valley of California","interactions":[],"lastModifiedDate":"2013-04-11T15:35:47","indexId":"sir20135023","displayToPublicDate":"2013-04-11T00:00:00","publicationYear":"2013","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":"2013-5023","title":"Methods, quality assurance, and data for assessing atmospheric deposition of pesticides in the Central Valley of California","docAbstract":"The U.S. Geological Survey monitored atmospheric deposition of pesticides in the Central Valley of California during two studies in 2001 and 2002–04. The 2001 study sampled wet deposition (rain) and storm-drain runoff in the Modesto, California, area during the orchard dormant-spray season to examine the contribution of pesticide concentrations to storm runoff from rainfall. In the 2002–04 study, the number and extent of collection sites in the Central Valley were increased to determine the areal distribution of organophosphate insecticides and other pesticides, and also five more sample types were collected. These were dry deposition, bulk deposition, and three sample types collected from a soil box: aqueous phase in runoff, suspended sediment in runoff, and surficial-soil samples. This report provides concentration data and describes methods and quality assurance of sample collection and laboratory analysis for pesticide compounds in all samples collected from 16 sites. Each sample was analyzed for 41 currently used pesticides and 23 pesticide degradates, including oxygen analogs (oxons) of 9 organophosphate insecticides. Analytical results are presented by sample type and study period.\n\nThe median concentrations of both chloryprifos and diazinon sampled at four urban (0.067 micrograms per liter [μg/L] and 0.515 μg/L, respectively) and four agricultural sites (0.079 μg/L and 0.583 μg/L, respectively) during a January 2001 storm event in and around Modesto, Calif., were nearly identical, indicating that the overall atmospheric burden in the region appeared to be fairly similar during the sampling event. Comparisons of median concentrations in the rainfall to those in the McHenry storm-drain runoff showed that, for some compounds, rainfall contributed a substantial percentage of the concentration in the runoff; for other compounds, the concentrations in rainfall were much greater than in the runoff. For example, diazinon concentrations in rainfall were about 70 percent of the diazinon concentration in the runoff, whereas the chlorpyrifos concentration in the rain was 1.8 times greater than in the runoff. The more water-soluble pesticides—carbaryl, metolachlor, napropamide, and simazine—followed the same pattern as diazinon and had lower concentrations in rain compared to runoff. Similar to chlorpyrifos,compounds with low water solubilities and higher soil-organic carbon partition coefficients, including dacthal, pendimethalin, and trifluralin, were found to have higher concentrations in rain than in runoff water and were presumed to partition to the suspended sediments and organic matter on the ground.\n\nDuring the 2002–04 study period, the herbicide dacthal had the highest detection frequencies for all sample types collected from the Central Valley sites (67–100 percent). The most frequently detected compounds in the wet-deposition samples were dacthal, diazinon, chlorpyrifos, and simazine (greater than 90 percent). The median wet-deposition amounts for these compounds were 0.044 micrograms per square meter per day (μg/m2/day), 0.209 μg/m2/day, 0.079 μg/m2/day, and 0.172 μg/m2/day, respectively. For the dry-deposition samples, detection frequencies were greater than 73 percent for the compounds dacthal, metolachor, and chlorpyrifos, and median deposition amounts were an order of magnitude less than for wet deposition. The differences between wet deposition and dry deposition appeared to be closely related to the Henry’s Law (H) constant of each compound, although the mass deposited by dry deposition takes place over a much longer time frame.\n\nPesticides detected in rainfall usually were detected in the aqueous phase of the soil-box runoff water, and the runoff concentrations were generally similar to those in the rainfall. For compounds detected in the aqueous phase and suspended-sediment samples of soil-box runoff, concentrations of pesticides in the aqueous phase generally were detected in low concentrations and had few corresponding detections in the suspended- sediment samples. Dacthal, diazinon, chlorpyrifos, and simazine were the most frequently detected pesticides (greater than 83 percent) in the aqueous-phase samples, with median concentrations of 0.010 μg/L, 0.045 μg/L, 0.016 μg/L, and 0.077 μg/L, respectively. Simazine was the most frequently detected compound in the suspended-sediment samples (69 percent), with a median concentration of 0.232 μg/L.\n\nResults for compounds detected in the surficial-soil samples collected throughout the study period showed that there was an increase in concentration for some compounds, indicating atmospheric deposition of these compounds onto the soil-box surface. In the San Joaquin Valley, the compounds chlorpyrifos, dacthal, and iprodione were detected at higher concentrations (between 1.4 and 2 times greater) than were found in the background samples collected from the San Joaquin Valley soil-box sites. In the Sacramento Valley, the compounds chlorpyrifos, dacthal, iprodione, parathionmethyl, and its oxygen analog, paraoxon-methyl, were detected in samples collected during the study period in low concentrations, but were not detected in the background concentration of the Sacramento Valley soil mix.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135023","usgsCitation":"Zamora, C., Majewski, M.S., and Foreman, W., 2013, Methods, quality assurance, and data for assessing atmospheric deposition of pesticides in the Central Valley of California: U.S. Geological Survey Scientific Investigations Report 2013-5023, xi, 180 p., https://doi.org/10.3133/sir20135023.","productDescription":"xi, 180 p.","numberOfPages":"195","additionalOnlineFiles":"N","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":270844,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135023.jpg"},{"id":270843,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5023/pdf/sir20135023.pdf"},{"id":270842,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5023/"}],"country":"United States","state":"California","otherGeospatial":"Central Valley","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.78,35.0 ], [ -122.78,40.74 ], [ -118.8,40.74 ], [ -118.8,35.0 ], [ -122.78,35.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5167cd5be4b0ec0efb666ee9","contributors":{"authors":[{"text":"Zamora, Celia 0000-0003-1456-4360 czamora@usgs.gov","orcid":"https://orcid.org/0000-0003-1456-4360","contributorId":1514,"corporation":false,"usgs":true,"family":"Zamora","given":"Celia","email":"czamora@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"preferred":true,"id":477313,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Majewski, Michael S. majewski@usgs.gov","contributorId":440,"corporation":false,"usgs":true,"family":"Majewski","given":"Michael","email":"majewski@usgs.gov","middleInitial":"S.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":477311,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Foreman, William T. wforeman@usgs.gov","contributorId":1473,"corporation":false,"usgs":true,"family":"Foreman","given":"William T.","email":"wforeman@usgs.gov","affiliations":[{"id":452,"text":"National Water Quality Laboratory","active":true,"usgs":true}],"preferred":false,"id":477312,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70045360,"text":"sir20135052 - 2013 - Use of surrogate technologies to estimate suspended sediment in the Clearwater River, Idaho, and Snake River, Washington, 2008-10","interactions":[],"lastModifiedDate":"2013-04-10T21:52:21","indexId":"sir20135052","displayToPublicDate":"2013-04-10T00:00:00","publicationYear":"2013","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":"2013-5052","title":"Use of surrogate technologies to estimate suspended sediment in the Clearwater River, Idaho, and Snake River, Washington, 2008-10","docAbstract":"Elevated levels of fluvial sediment can reduce the biological productivity of aquatic systems, impair freshwater quality, decrease reservoir storage capacity, and decrease the capacity of hydraulic structures. The need to measure fluvial sediment has led to the development of sediment surrogate technologies, particularly in locations where streamflow alone is not a good estimator of sediment load because of regulated flow, load hysteresis, episodic sediment sources, and non-equilibrium sediment transport. An effective surrogate technology is low maintenance and sturdy over a range of hydrologic conditions, and measured variables can be modeled to estimate suspended-sediment concentration (SSC), load, and duration of elevated levels on a real-time basis. Among the most promising techniques is the measurement of acoustic backscatter strength using acoustic Doppler velocity meters (ADVMs) deployed in rivers. The U.S. Geological Survey, in cooperation with the U.S. Army Corps of Engineers, Walla Walla District, evaluated the use of acoustic backscatter, turbidity, laser diffraction, and streamflow as surrogates for estimating real-time SSC and loads in the Clearwater and Snake Rivers, which adjoin in Lewiston, Idaho, and flow into Lower Granite Reservoir. The study was conducted from May 2008 to September 2010 and is part of the U.S. Army Corps of Engineers Lower Snake River Programmatic Sediment Management Plan to identify and manage sediment sources in basins draining into lower Snake River reservoirs.\n\nCommercially available acoustic instruments have shown great promise in sediment surrogate studies because they require little maintenance and measure profiles of the surrogate parameter across a sampling volume rather than at a single point. The strength of acoustic backscatter theoretically increases as more particles are suspended in the water to reflect the acoustic pulse emitted by the ADVM. ADVMs of different frequencies (0.5, 1.5, and 3 Megahertz) were tested to target various sediment grain sizes. Laser diffraction and turbidity also were tested as surrogate technologies. Models between SSC and surrogate variables were developed using ordinary least-squares regression. Acoustic backscatter using the high frequency ADVM at each site was the best predictor of sediment, explaining 93 and 92 percent of the variability in SSC and matching sediment sample data within +8.6 and +10 percent, on average, at the Clearwater River and Snake River study sites, respectively. Additional surrogate models were developed to estimate sand and fines fractions of suspended sediment based on acoustic backscatter. Acoustic backscatter generally appears to be a better estimator of suspended sediment concentration and load over short (storm event and monthly) and long (annual) time scales than transport curves derived solely from the regression of conventional sediment measurements and streamflow. Changing grain sizes, the presence of organic matter, and aggregation of sediments in the river likely introduce some variability in the model between acoustic backscatter and SSC.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135052","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Wood, M.S., and Teasdale, G.N., 2013, Use of surrogate technologies to estimate suspended sediment in the Clearwater River, Idaho, and Snake River, Washington, 2008-10: U.S. Geological Survey Scientific Investigations Report 2013-5052, vi, 30 p., https://doi.org/10.3133/sir20135052.","productDescription":"vi, 30 p.","numberOfPages":"40","additionalOnlineFiles":"N","temporalStart":"2008-01-01","temporalEnd":"2010-12-31","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":270796,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5052/"},{"id":270797,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5052/pdf/sir20135052.pdf"},{"id":270798,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135052.jpg"}],"country":"United States","state":"Idaho;Washington","otherGeospatial":"Clearwater River;Snake River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.8,42.0 ], [ -124.8,49.0 ], [ -111.0,49.0 ], [ -111.0,42.0 ], [ -124.8,42.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51667bdae4b0bba30b388bae","contributors":{"authors":[{"text":"Wood, Molly S. 0000-0002-5184-8306 mswood@usgs.gov","orcid":"https://orcid.org/0000-0002-5184-8306","contributorId":788,"corporation":false,"usgs":true,"family":"Wood","given":"Molly","email":"mswood@usgs.gov","middleInitial":"S.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true},{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":true,"id":477285,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Teasdale, Gregg N.","contributorId":77440,"corporation":false,"usgs":true,"family":"Teasdale","given":"Gregg","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":477286,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70044978,"text":"70044978 - 2013 - Avian influenza in shorebirds: experimental infection of ruddy turnstones (Arenaria interpres) with avian influenza virus","interactions":[],"lastModifiedDate":"2018-01-03T14:41:36","indexId":"70044978","displayToPublicDate":"2013-04-10T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1990,"text":"Influenza and Other Respiratory Viruses","active":true,"publicationSubtype":{"id":10}},"title":"Avian influenza in shorebirds: experimental infection of ruddy turnstones (Arenaria interpres) with avian influenza virus","docAbstract":"Background: Low pathogenic avian influenza viruses (LPAIV) have been reported in shorebirds, especially at Delaware Bay, USA, during spring migration. However, data on patterns of virus excretion, minimal infectious doses, and clinical outcome are lacking. The ruddy turnstone (Arenaria interpres) is the shorebird species with the highest prevalence of influenza virus at Delaware Bay.\n\nObjectives: The primary objective of this study was to experimentally assess the patterns of influenza virus excretion, minimal infectious doses, and clinical outcome in ruddy turnstones.\n\nMethods: We experimentally challenged ruddy turnstones using a common LPAIV shorebird isolate, an LPAIV waterfowl isolate, or a highly pathogenic H5N1 avian influenza virus. Cloacal and oral swabs and sera were analyzed from each bird.\n\nResults: Most ruddy turnstones had pre-existing antibodies to avian influenza virus, and many were infected at the time of capture. The infectious doses for each challenge virus were similar (103·6–104·16 EID50), regardless of exposure history. All infected birds excreted similar amounts of virus and showed no clinical signs of disease or mortality. Influenza A-specific antibodies remained detectable for at least 2 months after inoculation.\n\nConclusions: These results provide a reference for interpretation of surveillance data, modeling, and predicting the risks of avian influenza transmission and movement in these important hosts.","language":"English","publisher":"Wiley","publisherLocation":"Hoboken, NJ","doi":"10.1111/j.1750-2659.2012.00358.x","usgsCitation":"Hall, J.S., Krauss, S., Franson, J., TeSlaa, J.L., Nashold, S.W., Stallknecht, D.E., Webby, R., and Webster, R.G., 2013, Avian influenza in shorebirds: experimental infection of ruddy turnstones (Arenaria interpres) with avian influenza virus: Influenza and Other Respiratory Viruses, v. 7, no. 1, p. 85-92, https://doi.org/10.1111/j.1750-2659.2012.00358.x.","productDescription":"8 p.","startPage":"85","endPage":"92","ipdsId":"IP-029445","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":473881,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/j.1750-2659.2012.00358.x","text":"Publisher Index Page"},{"id":270800,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":270799,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/j.1750-2659.2012.00358.x"}],"volume":"7","issue":"1","noUsgsAuthors":false,"publicationDate":"2012-04-12","publicationStatus":"PW","scienceBaseUri":"51667bd8e4b0bba30b388ba6","contributors":{"authors":[{"text":"Hall, Jeffrey S. 0000-0001-5599-2826 jshall@usgs.gov","orcid":"https://orcid.org/0000-0001-5599-2826","contributorId":2254,"corporation":false,"usgs":true,"family":"Hall","given":"Jeffrey","email":"jshall@usgs.gov","middleInitial":"S.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":476557,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Krauss, Scott","contributorId":43250,"corporation":false,"usgs":true,"family":"Krauss","given":"Scott","affiliations":[],"preferred":false,"id":476561,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Franson, J. Christian 0000-0002-0251-4238","orcid":"https://orcid.org/0000-0002-0251-4238","contributorId":95002,"corporation":false,"usgs":true,"family":"Franson","given":"J. Christian","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":false,"id":476564,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"TeSlaa, Joshua L. 0000-0001-7802-3454 jteslaa@usgs.gov","orcid":"https://orcid.org/0000-0001-7802-3454","contributorId":46813,"corporation":false,"usgs":true,"family":"TeSlaa","given":"Joshua","email":"jteslaa@usgs.gov","middleInitial":"L.","affiliations":[],"preferred":false,"id":476562,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nashold, Sean W. 0000-0002-8869-6633 snashold@usgs.gov","orcid":"https://orcid.org/0000-0002-8869-6633","contributorId":3611,"corporation":false,"usgs":true,"family":"Nashold","given":"Sean","email":"snashold@usgs.gov","middleInitial":"W.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":false,"id":476558,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stallknecht, David E.","contributorId":20230,"corporation":false,"usgs":true,"family":"Stallknecht","given":"David","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":476560,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Webby, Richard J.","contributorId":80156,"corporation":false,"usgs":true,"family":"Webby","given":"Richard J.","affiliations":[],"preferred":false,"id":476563,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Webster, Robert G.","contributorId":11089,"corporation":false,"usgs":true,"family":"Webster","given":"Robert","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":476559,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70044568,"text":"70044568 - 2013 - A quantitative assessment of the conservation benefits of the Wetlands Reserve Program to amphibians","interactions":[],"lastModifiedDate":"2013-04-10T22:36:56","indexId":"70044568","displayToPublicDate":"2013-04-10T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3271,"text":"Restoration Ecology","active":true,"publicationSubtype":{"id":10}},"title":"A quantitative assessment of the conservation benefits of the Wetlands Reserve Program to amphibians","docAbstract":"The Mississippi Alluvial Valley (MAV) originally consisted of nearly contiguous bottomland hardwood (BLH) forest encompassing approximately 10 million hectares. Currently, only 20–25% of the historical BLH forests remain in small patches fragmented by agricultural lands. The Wetlands Reserve Program (WRP) was established to restore and protect the functions and values of wetlands in agricultural landscapes. To assess the potential benefit of WRP restoration to amphibians, we surveyed 30 randomly selected WRP sites and 20 nearby agricultural sites in the Mississippi Delta. We made repeat visits to each site from May to August 2008 and performed both visual encounter and vocalization surveys. We analyzed the encounter history data for 11 anuran species using a Bayesian hierarchical occupancy model that estimated detection probability and probability of occurrence simultaneously for each species. Nine of the 11 species had higher probabilities of occurrence at WRP sites compared to agriculture. Derived estimates of species richness were also higher for WRP sites. Five anuran species were significantly more likely to occur in WRP than in agriculture, four of which were among the most aquatic species. It appears that the restoration of a more permanent hydrology at the WRP sites may be the primary reason for this result. Although amphibians represent only one group of wildlife species, they are useful for evaluating restoration benefits for wildlife because of their intermediate trophic position. The methods used in this study to evaluate the benefit of restoration could be used in other locations and with other groups of indicator species.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Restoration Ecology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","publisherLocation":"Hoboken, NJ","doi":"10.1111/j.1526-100X.2012.00881.x","usgsCitation":"Waddle, J., Glorioso, B.M., and Faulkner, S.P., 2013, A quantitative assessment of the conservation benefits of the Wetlands Reserve Program to amphibians: Restoration Ecology, v. 21, no. 2, p. 200-206, https://doi.org/10.1111/j.1526-100X.2012.00881.x.","productDescription":"7 p.","startPage":"200","endPage":"206","ipdsId":"IP-029595","costCenters":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"links":[{"id":269264,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/j.1526-100X.2012.00881.x"},{"id":270803,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Mississippi","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -91.66,30.17 ], [ -91.66,35.0 ], [ -88.1,35.0 ], [ -88.1,30.17 ], [ -91.66,30.17 ] ] ] } } ] }","volume":"21","issue":"2","noUsgsAuthors":false,"publicationDate":"2012-07-05","publicationStatus":"PW","scienceBaseUri":"51667bcfe4b0bba30b388b9e","contributors":{"authors":[{"text":"Waddle, J. Hardin 0000-0003-1940-2133","orcid":"https://orcid.org/0000-0003-1940-2133","contributorId":89982,"corporation":false,"usgs":true,"family":"Waddle","given":"J. Hardin","affiliations":[],"preferred":false,"id":475877,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Glorioso, Brad M. 0000-0002-5400-7414 gloriosob@usgs.gov","orcid":"https://orcid.org/0000-0002-5400-7414","contributorId":4241,"corporation":false,"usgs":true,"family":"Glorioso","given":"Brad","email":"gloriosob@usgs.gov","middleInitial":"M.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":475876,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Faulkner, Stephen P. 0000-0001-5295-1383 faulkners@usgs.gov","orcid":"https://orcid.org/0000-0001-5295-1383","contributorId":374,"corporation":false,"usgs":true,"family":"Faulkner","given":"Stephen","email":"faulkners@usgs.gov","middleInitial":"P.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":475875,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70045353,"text":"sir20135031 - 2013 - Emergent sandbar dynamics in the lower Platte River in eastern Nebraska: methods and results of pilot study, 2011","interactions":[],"lastModifiedDate":"2018-01-08T12:22:23","indexId":"sir20135031","displayToPublicDate":"2013-04-10T00:00:00","publicationYear":"2013","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":"2013-5031","title":"Emergent sandbar dynamics in the lower Platte River in eastern Nebraska: methods and results of pilot study, 2011","docAbstract":"The lower Platte River corridor provides important habitats for two State- and federally listed bird species: the interior least tern (terns; Sternula antillarum athallassos) and the piping plover (plovers; Charadrius melodus). However, many of the natural morphological and hydrological characteristics of the Platte River have been altered substantially by water development, channelization, hydropower operations, and invasive vegetation encroachment, which have decreased the abundance of high-quality nesting and foraging habitat for terns and plovers. The lower Platte River (LPR), defined as 103 miles (mi) of the Platte River between its confluence with the Loup River and its confluence with the Missouri River, has narrowed since the late-19th and early-20th centuries, yet it partially retains many geomorphologic and hydrologic characteristics important to terns and plovers. These birds nest on the sandbars in the river and along shorelines at sand- and gravel-pit lakes in the adjacent valley. The need to balance continued economic, infrastructure, and resource development with the conservation of important physical and aquatic habitat resources requires increased understanding of the physical and biological dynamics of the lower Platte River. Spatially and temporally rich datasets for emergent sandbar habitats are necessary to quantify emergent sandbar dynamics relative to hypothesized controls and stressors. In cooperation with the Lower Platte South Natural Resources District, the U.S. Geological Survey initiated a pilot study of emergent sandbar dynamics along a 22-mi segment of the LPR downstream from its confluence with Salt Creek, near Ashland, Nebraska. The purposes of the study were to: (1) develop methods to rapidly assess sandbar geometries and locations in a wide, sand-bed river, and (2) apply and validate the method to assess emergent sandbar dynamics over three seasons in 2011. An examination of the height of sandbars relative to the local stage of the formative discharge event, and how subsequent river discharges, of both high and low magnitude, alter sandbar geometries and abundance within the LPR was of particular interest. A “rapid-assessment” method was developed with the goal of characterizing the spatial distribution and habitat-relevant geometries of the complete population of sandbars along the study segment. Three primary measures were used to assess emergent sandbar dynamics in the study segment: sandbar area, sandbar height, and sandbar location. Data to derive these measures were collected during three, week-long survey periods in 2011, herein named “spring survey period,” “summer survey period,” and “fall survey period.” Emergent sandbars were grouped into one of three generalized types: (1) bank-attached, (2) island-attached, and (3) mid-channel.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135031","collaboration":"Prepared in cooperation with the Lower Platte South Natural Resources District","usgsCitation":"Alexander, J.S., Schultze, D.M., and Zelt, R.B., 2013, Emergent sandbar dynamics in the lower Platte River in eastern Nebraska: methods and results of pilot study, 2011: U.S. Geological Survey Scientific Investigations Report 2013-5031, vi, 42 p., https://doi.org/10.3133/sir20135031.","productDescription":"vi, 42 p.","numberOfPages":"54","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2011-01-01","temporalEnd":"2011-12-31","ipdsId":"IP-043639","costCenters":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"links":[{"id":270773,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135031.gif"},{"id":270771,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5031/"},{"id":270772,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5031/sir13_5031.pdf"}],"scale":"100000","projection":"Universal Transverse Mercator projection, Zone 15","datum":"North American Datum of 1983","country":"United States","state":"Nebraska","county":"Cass;Sarpy;Saunders","otherGeospatial":"Platte River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -96.416667,40.966667 ], [ -96.416667,41.166667 ], [ -95.916667,41.166667 ], [ -95.916667,40.966667 ], [ -96.416667,40.966667 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51667bd9e4b0bba30b388baa","contributors":{"authors":[{"text":"Alexander, Jason S. 0000-0002-1602-482X jalexand@usgs.gov","orcid":"https://orcid.org/0000-0002-1602-482X","contributorId":2802,"corporation":false,"usgs":true,"family":"Alexander","given":"Jason","email":"jalexand@usgs.gov","middleInitial":"S.","affiliations":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"preferred":false,"id":477277,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schultze, Devin M.","contributorId":90191,"corporation":false,"usgs":true,"family":"Schultze","given":"Devin","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":477278,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zelt, Ronald B. 0000-0001-9024-855X rbzelt@usgs.gov","orcid":"https://orcid.org/0000-0001-9024-855X","contributorId":300,"corporation":false,"usgs":true,"family":"Zelt","given":"Ronald","email":"rbzelt@usgs.gov","middleInitial":"B.","affiliations":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":477276,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70169084,"text":"70169084 - 2013 - Characterizing the thermal suitability of instream habitat for salmonids: A cautionary example from the Rocky Mountains","interactions":[],"lastModifiedDate":"2016-03-16T13:05:07","indexId":"70169084","displayToPublicDate":"2013-04-09T14:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Characterizing the thermal suitability of instream habitat for salmonids: A cautionary example from the Rocky Mountains","docAbstract":"

Understanding a species’ thermal niche is becoming increasingly important for management and conservation within the context of global climate change, yet there have been surprisingly few efforts to compare assessments of a species’ thermal niche across methods. To address this uncertainty, we evaluated the differences in model performance and interpretations of a species’ thermal niche when using different measures of stream temperature and surrogates for stream temperature. Specifically, we used a logistic regression modeling framework with three different indicators of stream thermal conditions (elevation, air temperature, and stream temperature) referenced to a common set of Brook Trout Salvelinus fontinalis distribution data from the Boise River basin, Idaho. We hypothesized that stream temperature predictions that were contemporaneous with fish distribution data would have stronger predictive performance than composite measures of stream temperature or any surrogates for stream temperature. Across the different indicators of thermal conditions, the highest measure of accuracy was found for the model based on stream temperature predictions that were contemporaneous with fish distribution data (percent correctly classified = 71%). We found considerable differences in inferences across models, with up to 43% disagreement in the amount of stream habitat that was predicted to be suitable. The differences in performance between models support the growing efforts in many areas to develop accurate stream temperature models for investigations of species’ thermal niches.

","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Transactions of the American Fisheries Socitey","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Fisheries Society","publisherLocation":"Lawrence, KS","doi":"10.1080/00028487.2013.778900","usgsCitation":"Al-Chokhachy, R.K., Wegner, S.J., Isaak, D.J., and Kershner, J.L., 2013, Characterizing the thermal suitability of instream habitat for salmonids: A cautionary example from the Rocky Mountains: Transactions of the American Fisheries Society, v. 142, no. 3, p. 793-801, https://doi.org/10.1080/00028487.2013.778900.","productDescription":"9 p.","startPage":"793","endPage":"801","numberOfPages":"9","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-033925","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":318912,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"Boise River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.4111328125,\n 43.24520272203356\n ],\n [\n -116.4111328125,\n 45.5679096098613\n ],\n [\n -112.91748046874999,\n 45.5679096098613\n ],\n [\n -112.91748046874999,\n 43.24520272203356\n ],\n [\n -116.4111328125,\n 43.24520272203356\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"142","issue":"3","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2013-04-09","publicationStatus":"PW","scienceBaseUri":"56ea83abe4b0f59b85d90cd2","contributors":{"authors":[{"text":"Al-Chokhachy, Robert K. 0000-0002-2136-5098 ral-chokhachy@usgs.gov","orcid":"https://orcid.org/0000-0002-2136-5098","contributorId":1674,"corporation":false,"usgs":true,"family":"Al-Chokhachy","given":"Robert","email":"ral-chokhachy@usgs.gov","middleInitial":"K.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":622832,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wegner, Seth J.","contributorId":167607,"corporation":false,"usgs":false,"family":"Wegner","given":"Seth","email":"","middleInitial":"J.","affiliations":[{"id":24776,"text":"Trout Unlimited, 322 East Front Street, Suite 401, Boise, ID","active":true,"usgs":false}],"preferred":false,"id":622834,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Isaak, Daniel J.","contributorId":57202,"corporation":false,"usgs":true,"family":"Isaak","given":"Daniel","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":622833,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kershner, Jeffrey L. 0000-0002-7093-9860 jkershner@usgs.gov","orcid":"https://orcid.org/0000-0002-7093-9860","contributorId":310,"corporation":false,"usgs":true,"family":"Kershner","given":"Jeffrey","email":"jkershner@usgs.gov","middleInitial":"L.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":622831,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70045337,"text":"ds69Z - 2013 - Map of assessed shale gas in the United States, 2012","interactions":[],"lastModifiedDate":"2013-04-09T19:52:53","indexId":"ds69Z","displayToPublicDate":"2013-04-09T00:00:00","publicationYear":"2013","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":"69","chapter":"Z","title":"Map of assessed shale gas in the United States, 2012","docAbstract":"The U.S. Geological Survey has compiled a map of shale-gas assessments in the United States that were completed by 2012 as part of the National Assessment of Oil and Gas Project. Using a geology-based assessment methodology, the U.S. Geological Survey quantitatively estimated potential volumes of undiscovered gas within shale-gas assessment units. These shale-gas assessment units are mapped, and square-mile cells are shown to represent proprietary shale-gas wells. The square-mile cells include gas-producing wells from shale intervals. In some cases, shale-gas formations contain gas in deeper parts of a basin and oil at shallower depths (for example, the Woodford Shale and the Eagle Ford Shale). Because a discussion of shale oil is beyond the scope of this report, only shale-gas assessment units and cells are shown. The map can be printed as a hardcopy map or downloaded for interactive analysis in a Geographic Information System data package using the ArcGIS map document (file extension MXD) and published map file (file extension PMF). Also available is a publications access table with hyperlinks to current U.S. Geological Survey shale gas assessment publications and web pages. Assessment results and geologic reports are available as completed at the U.S. Geological Survey Energy Resources Program Web Site, http://energy.usgs.gov/OilGas/AssessmentsData/NationalOilGasAssessment.aspx. A historical perspective of shale gas activity in the United States is documented and presented in a video clip included as a PowerPoint slideshow.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds69Z","collaboration":"National Assessment of Oil and Gas Project","usgsCitation":"U.S. Geological Survey National Assessment of Oil and Gas Resources Team, and Biewick, L., 2013, Map of assessed shale gas in the United States, 2012: U.S. Geological Survey Data Series 69, iii, 16 p.; Map: 1 Sheet: 37 x 27 inches; Table 1; Shale Gas Slideshow 2012; Downloads Directory, https://doi.org/10.3133/ds69Z.","productDescription":"iii, 16 p.; Map: 1 Sheet: 37 x 27 inches; Table 1; Shale Gas Slideshow 2012; Downloads Directory","additionalOnlineFiles":"Y","temporalStart":"2012-01-01","temporalEnd":"2012-12-31","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":270760,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds69z.gif"},{"id":270756,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov//dds/dds-069/dds-069-z/downloads/DDS-69-Z_plate1.pdf"},{"id":270757,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov//dds/dds-069/dds-069-z/downloads/Table1.pdf"},{"id":270754,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov//dds/dds-069/dds-069-z/"},{"id":270755,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov//dds/dds-069/dds-069-z/DDS-69-Z_pamphlet.pdf"},{"id":270758,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov//dds/dds-069/dds-069-z/downloads/DDS-69-Z_ShaleGasSlideshow2012.pps"},{"id":270759,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov//dds/dds-069/dds-069-z/downloads/"}],"otherGeospatial":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 172.5,18.9 ], [ 172.5,71.4 ], [ -66.9,71.4 ], [ -66.9,18.9 ], [ 172.5,18.9 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51652a5fe4b077fa94dadf4f","contributors":{"authors":[{"text":"U.S. Geological Survey National Assessment of Oil and Gas Resources Team","contributorId":128233,"corporation":true,"usgs":false,"organization":"U.S. Geological Survey National Assessment of Oil and Gas Resources Team","id":535481,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Biewick, Laura R. H. (compiler) lbiewick@usgs.gov","contributorId":92561,"corporation":false,"usgs":true,"family":"Biewick","given":"Laura R. H.","suffix":"(compiler)","email":"lbiewick@usgs.gov","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":477264,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70045305,"text":"ofr20131012 - 2013 - Simplified stratigraphic cross sections of the Eocene Green River Formation in the Piceance Basin, northwestern Colorado","interactions":[],"lastModifiedDate":"2013-04-09T09:45:33","indexId":"ofr20131012","displayToPublicDate":"2013-04-09T00:00:00","publicationYear":"2013","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":"2013-1012","title":"Simplified stratigraphic cross sections of the Eocene Green River Formation in the Piceance Basin, northwestern Colorado","docAbstract":"Thirteen stratigraphic cross sections of the Eocene Green River Formation in the Piceance Basin of northwestern Colorado are presented in this report. Originally published in a much larger and more detailed form by Self and others (2010), they are shown here in simplified, page-size versions that are easily accessed and used for presentation purposes. Modifications to the original versions include the elimination of the detailed lithologic columns and oil-yield histograms from Fischer assay data and the addition of ground-surface lines to give the depth of the various oil shale units shown on the cross section.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131012","usgsCitation":"Dietrich, J.D., and Johnson, R.C., 2013, Simplified stratigraphic cross sections of the Eocene Green River Formation in the Piceance Basin, northwestern Colorado: U.S. Geological Survey Open-File Report 2013-1012, iii, 20 p., https://doi.org/10.3133/ofr20131012.","productDescription":"iii, 20 p.","numberOfPages":"23","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":270682,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131012.gif"},{"id":270680,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1012/"},{"id":270681,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1012/OF13-1012.pdf"}],"country":"United States","state":"Colorado","otherGeospatial":"Piceance Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -109.0,37.0 ], [ -109.0,41.0 ], [ -102.0,41.0 ], [ -102.0,37.0 ], [ -109.0,37.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51652a5fe4b077fa94dadf53","contributors":{"authors":[{"text":"Dietrich, John D.","contributorId":53841,"corporation":false,"usgs":true,"family":"Dietrich","given":"John","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":477204,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Ronald C. 0000-0002-6197-5165 rcjohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-6197-5165","contributorId":1550,"corporation":false,"usgs":true,"family":"Johnson","given":"Ronald","email":"rcjohnson@usgs.gov","middleInitial":"C.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":477203,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70043720,"text":"70043720 - 2013 - Automated cloud and shadow detection and filling using two-date Landsat imagery in the United States","interactions":[],"lastModifiedDate":"2013-04-09T20:09:58","indexId":"70043720","displayToPublicDate":"2013-04-09T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2068,"text":"International Journal of Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Automated cloud and shadow detection and filling using two-date Landsat imagery in the United States","docAbstract":"A simple, efficient, and practical approach for detecting cloud and shadow areas in satellite imagery and restoring them with clean pixel values has been developed. Cloud and shadow areas are detected using spectral information from the blue, shortwave infrared, and thermal infrared bands of Landsat Thematic Mapper or Enhanced Thematic Mapper Plus imagery from two dates (a target image and a reference image). These detected cloud and shadow areas are further refined using an integration process and a false shadow removal process according to the geometric relationship between cloud and shadow. Cloud and shadow filling is based on the concept of the Spectral Similarity Group (SSG), which uses the reference image to find similar alternative pixels in the target image to serve as replacement values for restored areas. Pixels are considered to belong to one SSG if the pixel values from Landsat bands 3, 4, and 5 in the reference image are within the same spectral ranges. This new approach was applied to five Landsat path/rows across different landscapes and seasons with various types of cloud patterns. Results show that almost all of the clouds were captured with minimal commission errors, and shadows were detected reasonably well. Among five test scenes, the lowest producer's accuracy of cloud detection was 93.9% and the lowest user's accuracy was 89%. The overall cloud and shadow detection accuracy ranged from 83.6% to 99.3%. The pixel-filling approach resulted in a new cloud-free image that appears seamless and spatially continuous despite differences in phenology between the target and reference images. Our methods offer a straightforward and robust approach for preparing images for the new 2011 National Land Cover Database production.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"International Journal of Remote Sensing","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Taylor & Francis","publisherLocation":"Philadelphia, PA","doi":"10.1080/01431161.2012.720045","usgsCitation":"Jin, S., Homer, C.G., Yang, L., Xian, G., Fry, J., Danielson, P., and Townsend, P., 2013, Automated cloud and shadow detection and filling using two-date Landsat imagery in the United States: International Journal of Remote Sensing, v. 34, no. 5, p. 1540-1560, https://doi.org/10.1080/01431161.2012.720045.","productDescription":"21 p.","startPage":"1540","endPage":"1560","ipdsId":"IP-024783","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":270762,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":270761,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1080/01431161.2012.720045"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 172.5,18.9 ], [ 172.5,71.4 ], [ -66.9,71.4 ], [ -66.9,18.9 ], [ 172.5,18.9 ] ] ] } } ] }","volume":"34","issue":"5","noUsgsAuthors":false,"publicationDate":"2012-10-16","publicationStatus":"PW","scienceBaseUri":"51652a5de4b077fa94dadf43","contributors":{"authors":[{"text":"Jin, Suming 0000-0001-9919-8077 sjin@usgs.gov","orcid":"https://orcid.org/0000-0001-9919-8077","contributorId":4397,"corporation":false,"usgs":true,"family":"Jin","given":"Suming","email":"sjin@usgs.gov","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":474167,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Homer, Collin G. 0000-0003-4755-8135 homer@usgs.gov","orcid":"https://orcid.org/0000-0003-4755-8135","contributorId":2262,"corporation":false,"usgs":true,"family":"Homer","given":"Collin","email":"homer@usgs.gov","middleInitial":"G.","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":474163,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yang, Limin 0000-0002-2843-6944 lyang@usgs.gov","orcid":"https://orcid.org/0000-0002-2843-6944","contributorId":4305,"corporation":false,"usgs":true,"family":"Yang","given":"Limin","email":"lyang@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":474166,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Xian, George 0000-0001-5674-2204","orcid":"https://orcid.org/0000-0001-5674-2204","contributorId":76589,"corporation":false,"usgs":true,"family":"Xian","given":"George","affiliations":[],"preferred":false,"id":474169,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fry, Joyce 0000-0002-8466-9582 jfry@usgs.gov","orcid":"https://orcid.org/0000-0002-8466-9582","contributorId":3147,"corporation":false,"usgs":true,"family":"Fry","given":"Joyce","email":"jfry@usgs.gov","affiliations":[],"preferred":true,"id":474164,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Danielson, Patrick 0000-0002-2990-2783 pdanielson@usgs.gov","orcid":"https://orcid.org/0000-0002-2990-2783","contributorId":3551,"corporation":false,"usgs":true,"family":"Danielson","given":"Patrick","email":"pdanielson@usgs.gov","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}],"preferred":true,"id":474165,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Townsend, Philip A.","contributorId":47664,"corporation":false,"usgs":true,"family":"Townsend","given":"Philip A.","affiliations":[],"preferred":false,"id":474168,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70044142,"text":"70044142 - 2013 - Assessment of spectral band impact on intercalibration over desert sites using simulation based on EO-1 Hyperion data","interactions":[],"lastModifiedDate":"2013-04-09T13:47:15","indexId":"70044142","displayToPublicDate":"2013-04-09T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1944,"text":"IEEE Transactions on Geoscience and Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Assessment of spectral band impact on intercalibration over desert sites using simulation based on EO-1 Hyperion data","docAbstract":"Since the beginning of the 1990s, stable desert sites have been used for the calibration monitoring of many different sensors. Many attempts at sensor intercalibration have been also conducted using these stable desert sites. As a result, site characterization techniques and the quality of intercalibration techniques have gradually improved over the years. More recently, the Committee on Earth Observation Satellites has recommended a list of reference pseudo-invariant calibration sites for frequent image acquisition by multiple agencies. In general, intercalibration should use well-known or spectrally flat reference. The reflectance profile of desert sites, however, might not be flat or well characterized (from a fine spectral point of view). The aim of this paper is to assess the expected accuracy that can be reached when using desert sites for intercalibration. In order to have a well-mastered estimation of different errors or error sources, this study is performed with simulated data from a hyperspectral sensor. Earth Observing-1 Hyperion images are chosen to provide the simulation input data. Two different cases of intercalibration are considered, namely, Landsat 7 Enhanced Thematic Mapper Plus with Terra Moderate Resolution Imaging Spectroradiometer (MODIS) and Environmental Satellite MEdium Resolution Imaging Spectrometer (MERIS) with Aqua MODIS. The simulation results have confirmed that intercalibration accuracy of 1% to 2% can be achieved between sensors, provided there are a sufficient number of available measurements. The simulated intercalibrations allow explaining results obtained during real intercalibration exercises and to establish some recommendations for the use of desert sites for intercalibration.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"IEEE Transactions on Geoscience and Remote Sensing","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"IEEE","publisherLocation":"Washington, D.C.","doi":"10.1109/TGRS.2012.2228210","usgsCitation":"Henry, P., Chander, G., Fougnie, B., Thomas, C., and Xiong, X., 2013, Assessment of spectral band impact on intercalibration over desert sites using simulation based on EO-1 Hyperion data: IEEE Transactions on Geoscience and Remote Sensing, v. 51, no. 3, p. 1297-1308, https://doi.org/10.1109/TGRS.2012.2228210.","productDescription":"12 p.","startPage":"1297","endPage":"1308","ipdsId":"IP-040537","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":270700,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1109/TGRS.2012.2228210"},{"id":270701,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"51","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51652a52e4b077fa94dadf3b","contributors":{"authors":[{"text":"Henry, P.","contributorId":91599,"corporation":false,"usgs":true,"family":"Henry","given":"P.","email":"","affiliations":[],"preferred":false,"id":474889,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chander, G.","contributorId":51449,"corporation":false,"usgs":true,"family":"Chander","given":"G.","affiliations":[],"preferred":false,"id":474888,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fougnie, B.","contributorId":12346,"corporation":false,"usgs":true,"family":"Fougnie","given":"B.","email":"","affiliations":[],"preferred":false,"id":474886,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thomas, C.","contributorId":7443,"corporation":false,"usgs":true,"family":"Thomas","given":"C.","affiliations":[],"preferred":false,"id":474885,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Xiong, Xiaoxiong","contributorId":15088,"corporation":false,"usgs":true,"family":"Xiong","given":"Xiaoxiong","email":"","affiliations":[],"preferred":false,"id":474887,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70042906,"text":"70042906 - 2013 - An isotope-dilution standard GC/MS/MS method for steroid hormones in water","interactions":[],"lastModifiedDate":"2021-05-27T16:01:28.036606","indexId":"70042906","displayToPublicDate":"2013-04-08T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"An isotope-dilution standard GC/MS/MS method for steroid hormones in water","docAbstract":"An isotope-dilution quantification method was developed for 20 natural and synthetic steroid hormones and additional compounds in filtered and unfiltered water. Deuterium- or carbon-13-labeled isotope-dilution standards (IDSs) are added to the water sample, which is passed through an octadecylsilyl solid-phase extraction (SPE) disk. Following extract cleanup using Florisil SPE, method compounds are converted to trimethylsilyl derivatives and analyzed by gas chromatography with tandem mass spectrometry. Validation matrices included reagent water, wastewater-affected surface water, and primary (no biological treatment) and secondary wastewater effluent. Overall method recovery for all analytes in these matrices averaged 100%; with overall relative standard deviation of 28%. Mean recoveries of the 20 individual analytes for spiked reagent-water samples prepared along with field samples analyzed in 2009–2010 ranged from 84–104%, with relative standard deviations of 6–36%. Detection levels estimated using ASTM International’s D6091–07 procedure range from 0.4 to 4 ng/L for 17 analytes. Higher censoring levels of 100 ng/L for bisphenol A and 200 ng/L for cholesterol and 3-beta-coprostanol are used to prevent bias and false positives associated with the presence of these analytes in blanks. Absolute method recoveries of the IDSs provide sample-specific performance information and guide data reporting. Careful selection of labeled compounds for use as IDSs is important because both inexact IDS-analyte matches and deuterium label loss affect an IDS’s ability to emulate analyte performance. Six IDS compounds initially tested and applied in this method exhibited deuterium loss and are not used in the final method.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Evaluating Veterinary Pharmaceutical Behavior in the Environment: ACS Symposium Series","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"ACS Publications","publisherLocation":"Washington, D.C.","doi":"10.1021/bk-2013-1126.ch004","usgsCitation":"Foreman, W., Gray, J.L., ReVello, R., Lindley, C.E., and Losche, S.A., 2013, An isotope-dilution standard GC/MS/MS method for steroid hormones in water, chap. of Evaluating Veterinary Pharmaceutical Behavior in the Environment: ACS Symposium Series, v. 1126, p. 57-136, https://doi.org/10.1021/bk-2013-1126.ch004.","productDescription":"80 p.","startPage":"57","endPage":"136","ipdsId":"IP-038162","costCenters":[{"id":140,"text":"Branch of Analytical Serv (National Water Quality Laboratory)","active":false,"usgs":true},{"id":452,"text":"National Water Quality Laboratory","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":270671,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":270670,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1021/bk-2013-1126.ch004"}],"volume":"1126","noUsgsAuthors":false,"publicationDate":"2013-03-14","publicationStatus":"PW","scienceBaseUri":"5163d8dae4b0b7010f820135","contributors":{"authors":[{"text":"Foreman, William T. wforeman@usgs.gov","contributorId":1473,"corporation":false,"usgs":true,"family":"Foreman","given":"William T.","email":"wforeman@usgs.gov","affiliations":[{"id":452,"text":"National Water Quality Laboratory","active":true,"usgs":true}],"preferred":false,"id":472561,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gray, James L. 0000-0002-0807-5635 jlgray@usgs.gov","orcid":"https://orcid.org/0000-0002-0807-5635","contributorId":1253,"corporation":false,"usgs":true,"family":"Gray","given":"James","email":"jlgray@usgs.gov","middleInitial":"L.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":452,"text":"National Water Quality Laboratory","active":true,"usgs":true},{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true}],"preferred":true,"id":472560,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"ReVello, Rhiannon C. rcrevell@usgs.gov","contributorId":4128,"corporation":false,"usgs":true,"family":"ReVello","given":"Rhiannon C.","email":"rcrevell@usgs.gov","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":472563,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lindley, Chris E. clindley@usgs.gov","contributorId":2337,"corporation":false,"usgs":true,"family":"Lindley","given":"Chris","email":"clindley@usgs.gov","middleInitial":"E.","affiliations":[],"preferred":true,"id":472562,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Losche, Scott A. salosche@usgs.gov","contributorId":4694,"corporation":false,"usgs":true,"family":"Losche","given":"Scott","email":"salosche@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":472564,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ]}