Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, national security, recreation, and many others. For the Commonwealth of Pennsylvania, elevation data are critical for natural resources conservation (including the effects of drilling for oil and natural gas), agriculture and precision farming, flood risk management, infrastructure and construction management, water supply and quality, geologic resource assessment and hazard mitigation, and other business uses. Today, high-density light detection and ranging (lidar) data are the primary sources for deriving elevation models and other datasets. Federal, State, and local agencies work in partnership to replace data that are older and of lower quality. A joint goal of Commonwealth and Federal partners is to provide a temporal and density refresh of the current statewide coverage in order to support existing and emerging applications enabled by improved lidar data.
\nThe National Enhanced Elevation Assessment evaluated multiple elevation data acquisition options to determine the optimal data quality and data replacement cycle relative to cost to meet the identified requirements of the user community. The evaluation demonstrated that lidar acquisition at quality level 2 for the conterminous United States and quality level 5 interferometric synthetic aperture radar (ifsar) data for Alaska with a 6- to 10-year acquisition cycle provided the highest benefit/cost ratios. The 3D Elevation Program (3DEP) initiative selected an 8-year acquisition cycle for the respective quality levels. 3DEP, managed by the U.S. Geological Survey, the Office of Management and Budget Circular A–16 lead agency for terrestrial elevation data, responds to the growing need for high-quality topographic data and a wide range of other 3D representations of the Nation’s natural and constructed features.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20153019","usgsCitation":"Carswell, W., 2015, The 3D Elevation Program: summary for Pennsylvania (Version 1: Originally posted March 12, 2015; Version 1.1: June 24, 2015): U.S. Geological Survey Fact Sheet 2015-3019, 2 p., https://doi.org/10.3133/fs20153019.","productDescription":"2 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-060799","costCenters":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"links":[{"id":298462,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20153019.jpg"},{"id":298460,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2015/3019/"},{"id":298461,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2015/3019/pdf/fs2015-3019.pdf","text":"Report","size":"267 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Jr. carswell@usgs.gov","contributorId":127609,"corporation":false,"usgs":true,"family":"Carswell","given":"William J.","suffix":"Jr.","email":"carswell@usgs.gov","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":false,"id":541907,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70142446,"text":"fs20153018 - 2015 - The 3D Elevation Program: summary for Iowa","interactions":[],"lastModifiedDate":"2016-08-17T15:06:20","indexId":"fs20153018","displayToPublicDate":"2015-03-12T15:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-3018","title":"The 3D Elevation Program: summary for Iowa","docAbstract":"Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, national security, recreation, and many others. For the State of Iowa, elevation data are critical for agriculture and precision farming, infrastructure and construction management, natural resources conservation, flood risk management, water supply and quality, and other business uses. Today, high-density light detection and ranging (lidar) data are the primary sources for deriving elevation models and other datasets. Federal, State, Tribal, and local agencies work in partnership to (1) replace data that are older and of lower quality and (2) provide coverage where publicly accessible data do not exist. A joint goal of State and Federal partners is to acquire consistent, statewide coverage to support existing and emerging applications enabled by lidar data.
\nThe National Enhanced Elevation Assessment evaluated multiple elevation data acquisition options to determine the optimal data quality and data replacement cycle relative to cost to meet the identified requirements of the user community. The evaluation demonstrated that lidar acquisition at quality level 2 for the conterminous United States and quality level 5 interferometric synthetic aperture radar (ifsar) data for Alaska with a 6- to 10-year acquisition cycle provided the highest benefit/cost ratios. The 3D Elevation Program (3DEP) initiative selected an 8-year acquisition cycle for the respective quality levels. 3DEP, managed by the U.S. Geological Survey, the Office of Management and Budget Circular A–16 lead agency for terrestrial elevation data, responds to the growing need for high-quality topographic data and a wide range of other 3D representations of the Nation’s natural and constructed features.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20153018","usgsCitation":"Carswell, W., 2015, The 3D Elevation Program: summary for Iowa (Version 1.0: Originally posted March 12, 2015; Version 1.1: June 25, 2015): U.S. Geological Survey Fact Sheet 2015-3018, 2 p., https://doi.org/10.3133/fs20153018.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-060453","costCenters":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"links":[{"id":298459,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20153018.jpg"},{"id":298458,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2015/3018/pdf/fs2015-3018.pdf","text":"Report","size":"260 kB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":298457,"rank":1,"type":{"id":15,"text":"Index 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\"}}]}","edition":"Version 1.0: Originally posted March 12, 2015; Version 1.1: June 25, 2015","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5502aa9ce4b02e76d7564e98","contributors":{"authors":[{"text":"Carswell, William J. Jr. carswell@usgs.gov","contributorId":1787,"corporation":false,"usgs":true,"family":"Carswell","given":"William J.","suffix":"Jr.","email":"carswell@usgs.gov","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":false,"id":541906,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70137387,"text":"sir20155001 - 2015 - Low-flow characteristics and flow-duration statistics for selected USGS continuous-record streamgaging stations in North Carolina through 2012","interactions":[],"lastModifiedDate":"2017-01-18T13:18:37","indexId":"sir20155001","displayToPublicDate":"2015-03-12T14:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-5001","title":"Low-flow characteristics and flow-duration statistics for selected USGS continuous-record streamgaging stations in North Carolina through 2012","docAbstract":"In 2013, the U.S. Geological Survey, in cooperation with the North Carolina Division of Water Resources, compiled updated low-flow characteristics and flow-duration statistics for selected continuous-record streamgages in North Carolina. The compilation of updated streamflow statistics provides regulators and planners with relevant hydrologic information reflective of the recent droughts, which can be used to better manage the quantity and quality of streams in North Carolina. Streamflow records available through the 2012 water year1 were used to determine the annual (based on climatic year2) and winter 7-day, 10-year (7Q10, W7Q10) low-flow discharges, the 30-day, 2-year (30Q2) low-flow discharge, and the 7-day, 2-year (7Q2) low-flow discharge. Consequently, streamflow records available through March 31, 2012 (or the 2011 climatic year) were used to determine the updated low-flow characteristics. Low-flow characteristics were published for 177 unregulated sites, 56 regulated sites, and 33 sites known or considered to be affected by varying degrees of minor regulation and (or) diversions upstream from the streamgages (266 sites total). The updated 7Q10 discharges were compared for 63 streamgages across North Carolina where (1) long-term streamflow record consisted of 30 or more climatic years of data available as of the 1998 climatic year, and (2) streamflows were not known to be regulated. The 7Q10 discharges did not change for 3 sites, whereas increases and decreases were noted at 5 and 55 sites, respectively. Positive changes (increases) ranged from 4.3 percent (site 362) to 34.1 percent (site 112) with a median of 13.2 percent. Negative percentage changes (decreases) ranged from –3.3 percent (site 514) to –80.0 percent (site 308) with a median of –22.2 percent. The median percentage change for all 63 streamgages was –18.4 percent. Streamflow statistics determined as a part of this compilation included minimum, mean, maximum, and flow-duration statistics of daily mean discharges for categorical periods. Flow-duration statistics based on the daily mean discharge records were compiled in this study for the 5th, 10th, 25th, 50th, 75th, 90th, and 95th percentiles. Flow-duration statistics were determined for each complete water year of record at a streamgage as well as the available period of record (or selected periods if flows were regulated) and selected seasonal, monthly, and calendar day periods. In addition to the streamflow statistics compiled for each of the water years, the number of days the daily mean discharge was at or below the 10th percentile was summed for each water year as well as the number of events during the water year when streamflow was consistently at or below the 10th percentile. All low-flow characteristics for the streamgages were added into the StreamStatsDB, which is a database accessible to users through the recently released USGS StreamStats application for North Carolina. The minimum, mean, maximum, and flow-duration statistics of daily mean discharges based on the available (or selected if regulated flows) period of record were updated in the North Carolina StreamStatsDB. However, for the selected seasonal, monthly, calendar day, and annual water year periods, tab-delimited American Standard Code for Information Interchange (ASCII) tables of the streamflow statistics are available online to users from a link provided in the StreamStats application. 1The annual period from October 1 through September 30, designated by the year in which the period ends. 2The annual period from April 1 through March 31, designated by the year in which the period begins.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155001","collaboration":"Prepared in cooperation with North Carolina Department of Environment and Natural Resources, Division of Water Resources","usgsCitation":"Weaver, J.C., 2016, Low-flow characteristics and flow-duration statistics for selected USGS continuous-record streamgaging stations in North Carolina through 2012 (ver. 1.1, March 2016): U.S. Geological Survey Scientific Investigations Report 2015–5001, 89 p., https://dx.doi.org/10.3133/sir20155001.","productDescription":"vii, 89 p.","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-051713","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":318509,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2015/5001/versionHist.txt","size":"3.96 KB","linkFileType":{"id":2,"text":"txt"},"description":"SIR 2015-5001"},{"id":318636,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2015/5001/downloads/","text":"Downloads Directory","linkFileType":{"id":5,"text":"html"},"linkHelpText":"An alternative method to accessing the streamflow statistcs not provided in the report outside of the StreamStats application http://water.usgs.gov/osw/streamstats/north_carolina.html is through the Downloads Directory link above. Tables 3 and 5 in the report provide the low-flow characteristics and flow-duration statistics, respectively, for the available (or selected if regulated flows) period of records at the streamages. The Downloads directory contains the minimum, mean, maximum, and flow-duration statistics of daily mean discharges based on the available (or selected if regulated flows) period of record, each complete water year of record, each calendar day, each month, and selected seasonal periods."},{"id":318508,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5001/pdf/sir20155001.pdf","text":"Report","size":"4.73 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5001"},{"id":318510,"rank":5,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5001/images/coverthb2.jpg"},{"id":298463,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2015/5001/index.html"}],"country":"United States","state":"North 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U.S. Geological Survey
3916 Sunset Ridge Road
Raleigh, NC 27607
http://nc.water.usgs.gov/
With rapidly changing landscape conditions within Wyoming and the potential effects of landscape changes on sage-grouse habitat, land managers and conservation planners, among others, need procedures to assess the location and juxtaposition of important habitats, land-cover, and land-use patterns to balance wildlife requirements with multiple human land uses. Biologists frequently develop habitat-selection studies to identify prioritization efforts for species of conservation concern to increase understanding and help guide habitat-conservation efforts. Recently, the authors undertook a large-scale collaborative effort that developed habitat-selection models for Greater Sage-grouse (Centrocercus urophasianus) across large landscapes in Wyoming, USA and for multiple life-stages (nesting, late brood-rearing, and winter). We developed these habitat models using resource selection functions, based upon sage-grouse telemetry data collected for localized studies and within each life-stage. The models allowed us to characterize and spatially predict seasonal sage-grouse habitat use in Wyoming. Due to the quantity of models, the diversity of model predictors (in the form of geographic information system data) produced by analyses, and the variety of potential applications for these data, we present here a resource that complements our published modeling effort, which will further support land managers.
\nWe deliver all products described herein as online geographic information system data for visualization and downloading. We outline the data properties for each model and their data inputs, describe the process of selecting appropriate data products for multifarious applications, describe all data products and software, provide newly derived model composites, and discuss how land managers may use the models to inform future sage-grouse studies and potentially refine conservation efforts. The models, software tools, and associated opportunities for novel applications of these products should provide a suite of additional, but not exclusive, tools for assessing Wyoming Greater Sage-grouse habitats, which land managers, conservationists, and scientists can apply to myriad applications.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds891","usgsCitation":"O’Donnell, M.S., Aldridge, C.L., Doherty, K., and Fedy, B., 2015, Wyoming greater sage-grouse habitat prioritization: A collection of multi-scale seasonal models and geographic information systems land management tools: U.S. Geological Survey Data Series 891, Report: iv, 27 p.; Downloads Directory, https://doi.org/10.3133/ds891.","productDescription":"Report: iv, 27 p.; Downloads Directory","numberOfPages":"35","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-052571","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":298435,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds891.jpg"},{"id":298434,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/ds/0891/downloads/","text":"Downloads Directory","description":"Downloads Directory","linkHelpText":"Contains: geospatial database."},{"id":298433,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0891/pdf/ds891.pdf","text":"Report","size":"8.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":298425,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0891/"}],"country":"United States","state":"Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.060791015625,\n 40.9964840143779\n ],\n [\n -111.060791015625,\n 45.00365115687189\n ],\n [\n -104.051513671875,\n 45.00365115687189\n ],\n [\n -104.051513671875,\n 40.9964840143779\n ],\n [\n -111.060791015625,\n 40.9964840143779\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"551a65bee4b0323842783480","contributors":{"authors":[{"text":"O’Donnell, Michael S. 0000-0002-3488-003X odonnellm@usgs.gov","orcid":"https://orcid.org/0000-0002-3488-003X","contributorId":3351,"corporation":false,"usgs":true,"family":"O’Donnell","given":"Michael","email":"odonnellm@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":542119,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aldridge, Cameron L. 0000-0003-3926-6941 aldridgec@usgs.gov","orcid":"https://orcid.org/0000-0003-3926-6941","contributorId":191773,"corporation":false,"usgs":true,"family":"Aldridge","given":"Cameron","email":"aldridgec@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":542120,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Doherty, Kevin E.","contributorId":62452,"corporation":false,"usgs":true,"family":"Doherty","given":"Kevin E.","affiliations":[],"preferred":false,"id":542122,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fedy, Bradley C.","contributorId":40536,"corporation":false,"usgs":true,"family":"Fedy","given":"Bradley C.","affiliations":[],"preferred":false,"id":542121,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70139794,"text":"sir20155008 - 2015 - Water-quality trends for selected sites in the Boulder River and Tenmile Creek watersheds, Montana, based on data collected during water years 1997-2013","interactions":[],"lastModifiedDate":"2015-03-11T10:53:50","indexId":"sir20155008","displayToPublicDate":"2015-03-11T10:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-5008","title":"Water-quality trends for selected sites in the Boulder River and Tenmile Creek watersheds, Montana, based on data collected during water years 1997-2013","docAbstract":"In the Boulder River and Tenmile Creek watersheds in southwestern Montana, there was intensive mining during a 40-year period after the discovery of gold in the early 1860s. Potential effects from the historic mining activities include acid-mine drainage and elevated concentrations of potentially toxic trace elements from mining remnants such as waste rock and tailing piles. In support of remediation efforts, water-quality monitoring by the U.S. Geological Survey began in 1997 in the Boulder River and Tenmile Creek watersheds and has continued to present (2014). The U.S. Geological Survey, in cooperation with the U.S. Forest Service, investigated temporal trends in water quality at 13 sites, including 2 adit (or mine entrance) sites and 11 stream sites. The primary purpose of this report is to present results of trend analysis of specific conductance, selected trace-elements (cadmium, copper, lead, zinc, and arsenic), and suspended sediment for the 13 sites.
\nTrend results for most stream sites in the Boulder River watershed for water years 2000–13 (water year is the 12-month period from October 1 through September 30 and is designated by the year in which it ends) indicate decreasing trends in flow-adjusted specific conductance, in flow-adjusted concentrations (FACs) for most filtered and unfiltered-recoverable trace elements, and in suspended sediment. Overall, magnitudes of the decreasing trends in FACs of metallic contaminants are largest for Bullion Mine tributary at mouth (site 3), Jack Creek at mouth (site 4), and Cataract Creek at Basin (site 8). For sites 3, 4, and 8, magnitudes of decreasing trends generally ranged from about -5 to -10 percent per year. Notably, the watersheds upstream from sites 3, 4, and 8 have been targeted by substantial remediation activities. Consideration of trend patterns among all stream sites in the Boulder River watershed provides strong evidence that remediation activities are the primary cause of decreasing trends in metallic contaminants.
\nTrend results for sites in the Tenmile Creek watershed generally are more variable and difficult to interpret than for sites in the Boulder River watershed. Trend results for Tenmile Creek above City Diversion (site 11) and Minnehaha Creek near Rimini (site 12) for water years 2000–13 indicate decreasing trends in FACs of cadmium, copper, and zinc. The magnitudes of the decreasing trends in FACs of copper generally are moderate and statistically significant for sites 11 and 12. The magnitudes of the decreasing trends in FACs of cadmium and zinc for site 11 are minor to small and not statistically significant; however, the magnitudes for site 12 are moderate and statistically significant. In general, patterns in FACs for Tenmile Creek near Rimini (site 13) are not well represented by fitted trends within the short data collection period, which might indicate that the trend-analysis structure of the study is not appropriate for describing trends in FACs for site 13. The large decreasing trend in FACs of suspended sediment is the strongest indication of change in water quality during the short period of record for site 13; however, this trend is not statistically significant.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155008","collaboration":"Prepared in cooperation with the U.S. Forest Service","usgsCitation":"Sando, S.K., Clark, M.L., Cleasby, T., and Barnhart, E.P., 2015, Water-quality trends for selected sites in the Boulder River and Tenmile Creek watersheds, Montana, based on data collected during water years 1997-2013: U.S. Geological Survey Scientific Investigations Report 2015-5008, Report: x, 46 p.; Appendix 1 tables; Appendix 2 table; Appendix 3 tables; Appendix 3 figures, https://doi.org/10.3133/sir20155008.","productDescription":"Report: x, 46 p.; Appendix 1 tables; Appendix 2 table; Appendix 3 tables; Appendix 3 figures","numberOfPages":"62","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"1996-10-01","temporalEnd":"2013-09-30","ipdsId":"IP-058590","costCenters":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"links":[{"id":298432,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20155008.jpg"},{"id":298429,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5008/downloads/sir20155008_Appendix02_table.pdf","text":"Appendix 2 table","size":"70 kB","linkFileType":{"id":1,"text":"pdf"},"description":"Appendix 2 table"},{"id":298430,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5008/downloads/sir20155008_Appendix03_tables.pdf","text":"Appendix 3 tables","size":"400 kB","linkFileType":{"id":1,"text":"pdf"},"description":"Appendix 3 tables"},{"id":298426,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2015/5008/"},{"id":298427,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5008/pdf/sir2015-5008.pdf","text":"Report","size":"4.92 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":298431,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5008/downloads/sir20155008_Appendix03_figures.pdf","text":"Appendix 3 figures","size":"2.47 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Appendix 3 figures"},{"id":298428,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5008/downloads/sir20155008_Appendix01_tables.pdf","text":"Appendix 1 tables","size":"294 kB","linkFileType":{"id":1,"text":"pdf"},"description":"Appendix 1 tables"}],"projection":"Lambert Conformal Conic projection","datum":"North American Datum 1983","country":"United States","state":"Montana","otherGeospatial":"Boulder River watershed, Tenmile Creek watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.10174560546875,\n 46.22402775339081\n ],\n [\n -112.21435546875,\n 46.63105019776468\n ],\n [\n -112.45811462402342,\n 46.63057868059483\n ],\n [\n -112.46292114257812,\n 46.22284011773094\n ],\n [\n -112.10174560546875,\n 46.22402775339081\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"551a65bde4b032384278347d","contributors":{"authors":[{"text":"Sando, Steven K. 0000-0003-1206-1030 sksando@usgs.gov","orcid":"https://orcid.org/0000-0003-1206-1030","contributorId":1016,"corporation":false,"usgs":true,"family":"Sando","given":"Steven","email":"sksando@usgs.gov","middleInitial":"K.","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":542123,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Clark, Melanie L. mlclark@usgs.gov","contributorId":1827,"corporation":false,"usgs":true,"family":"Clark","given":"Melanie","email":"mlclark@usgs.gov","middleInitial":"L.","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":542124,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cleasby, Tom 0000-0003-0694-1541 tcleasby@usgs.gov","orcid":"https://orcid.org/0000-0003-0694-1541","contributorId":1137,"corporation":false,"usgs":true,"family":"Cleasby","given":"Tom","email":"tcleasby@usgs.gov","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":false,"id":542125,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barnhart, Elliott P. 0000-0002-8788-8393 epbarnhart@usgs.gov","orcid":"https://orcid.org/0000-0002-8788-8393","contributorId":5385,"corporation":false,"usgs":true,"family":"Barnhart","given":"Elliott","email":"epbarnhart@usgs.gov","middleInitial":"P.","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":542126,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70142756,"text":"70142756 - 2015 - Modelling non-Euclidean movement and landscape connectivity in highly structured ecological networks","interactions":[],"lastModifiedDate":"2015-03-11T10:23:50","indexId":"70142756","displayToPublicDate":"2015-03-11T10:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2717,"text":"Methods in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Modelling non-Euclidean movement and landscape connectivity in highly structured ecological networks","docAbstract":"Using older and in part flawed data, Ruff (1989) suggested that thick sediment entering the subduction zone (SZ) smooths and strengthens the trench-parallel distribution of interplate coupling. This circumstance was conjectured to favor rupture continuation and the generation of high-magnitude (≥Mw8.0) interplate thrust (IPT) earthquakes. Using larger and more accurate compilations of sediment thickness and instrumental (1899 to January 2013) and pre-instrumental era (1700–1898) IPTs (n = 176 and 12, respectively), we tested if a compelling relation existed between where IPT earthquakes ≥Mw7.5 occurred and where thick (≥1.0 km) versus thin (≤1.0 km) sedimentary sections entered the SZ.
\nBased on the new compilations, a statistically supported statement (see Summary and Conclusions) can be made that high-magnitude earthquakes are most prone to nucleate at well-sedimented SZs. For example, despite the 7500 km shorter global length of thick-sediment trenches, they account for ∼53% of instrumental era IPTs ≥Mw8.0, ∼75% ≥Mw8.5, and 100% ≥Mw9.1. No megathrusts >Mw9.0 ruptured at thin-sediment trenches, whereas three occurred at thick-sediment trenches (1960 Chile Mw9.5, 1964 Alaska Mw9.2, and 2004 Sumatra Mw9.2).
\nHowever, large Mw8.0–9.0 IPTs commonly (n = 23) nucleated at thin-sediment trenches. These earthquakes are associated with the subduction of low-relief ocean floor and where the debris of subduction erosion thickens the plate-separating subduction channel. The combination of low bathymetric relief and subduction erosion is inferred to also produce a smooth trench-parallel distribution of coupling posited to favor the characteristic lengthy rupturing of high-magnitude IPT earthquakes. In these areas subduction of a weak sedimentary sequence further enables rupture continuation.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES01079.1","usgsCitation":"Scholl, D.W., Kirby, S.H., von Huene, R.E., Ryan, H., Wells, R., and Geist, E.L., 2015, Great (≥Mw8.0) megathrust earthquakes and the subduction of excess sediment and bathymetrically smooth seafloor: Geosphere, v. 11, no. 2, p. 236-265, https://doi.org/10.1130/GES01079.1.","productDescription":"20 p.","startPage":"236","endPage":"265","numberOfPages":"20","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057488","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":472215,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges01079.1","text":"Publisher Index Page"},{"id":300320,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55532430e4b0a92fa7e94c8d","contributors":{"authors":[{"text":"Scholl, David W. 0000-0001-6500-6962 dscholl@usgs.gov","orcid":"https://orcid.org/0000-0001-6500-6962","contributorId":3738,"corporation":false,"usgs":true,"family":"Scholl","given":"David","email":"dscholl@usgs.gov","middleInitial":"W.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":546743,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kirby, Stephe H.","contributorId":140745,"corporation":false,"usgs":false,"family":"Kirby","given":"Stephe","email":"","middleInitial":"H.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":546744,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"von Huene, Roland E. 0000-0003-1301-3866 rvonhuene@usgs.gov","orcid":"https://orcid.org/0000-0003-1301-3866","contributorId":191070,"corporation":false,"usgs":true,"family":"von Huene","given":"Roland","email":"rvonhuene@usgs.gov","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":7065,"text":"USGS emeritus","active":true,"usgs":false}],"preferred":false,"id":546745,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ryan, Holly F. hryan@usgs.gov","contributorId":140746,"corporation":false,"usgs":true,"family":"Ryan","given":"Holly F.","email":"hryan@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":546746,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wells, Ray E. 0000-0002-7796-0160 rwells@usgs.gov","orcid":"https://orcid.org/0000-0002-7796-0160","contributorId":2692,"corporation":false,"usgs":true,"family":"Wells","given":"Ray E.","email":"rwells@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":false,"id":546747,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Geist, Eric L. 0000-0003-0611-1150 egeist@usgs.gov","orcid":"https://orcid.org/0000-0003-0611-1150","contributorId":1956,"corporation":false,"usgs":true,"family":"Geist","given":"Eric","email":"egeist@usgs.gov","middleInitial":"L.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":546763,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70173530,"text":"70173530 - 2015 - Quantifying avian predation on fish populations: integrating predator-specific deposition probabilities in tag-recovery studies","interactions":[],"lastModifiedDate":"2016-06-09T15:28:46","indexId":"70173530","displayToPublicDate":"2015-03-11T00:00:00","publicationYear":"2015","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":"Quantifying avian predation on fish populations: integrating predator-specific deposition probabilities in tag-recovery studies","docAbstract":"Accurate assessment of specific mortality factors is vital to prioritize recovery actions for threatened and endangered species. For decades, tag recovery methods have been used to estimate fish mortality due to avian predation. Predation probabilities derived from fish tag recoveries on piscivorous waterbird colonies typically reflect minimum estimates of predation due to an unknown and unaccounted-for fraction of tags that are consumed but not deposited on-colony (i.e., deposition probability). We applied an integrated tag recovery modeling approach in a Bayesian context to estimate predation probabilities that accounted for predator-specific tag detection and deposition probabilities in a multiple-predator system. Studies of PIT tag deposition were conducted across three bird species nesting at seven different colonies in the Columbia River basin, USA. Tag deposition probabilities differed significantly among predator species (Caspian ternsHydroprogne caspia: deposition probability = 0.71, 95% credible interval [CRI] = 0.51–0.89; double-crested cormorants Phalacrocorax auritus: 0.51, 95% CRI = 0.34–0.70; California gulls Larus californicus: 0.15, 95% CRI = 0.11–0.21) but showed little variation across trials within a species or across years. Data from a 6-year study (2008–2013) of PIT-tagged juvenile Snake River steelhead Oncorhynchus mykiss (listed as threatened under the Endangered Species Act) indicated that colony-specific predation probabilities ranged from less than 0.01 to 0.17 and varied by predator species, colony location, and year. Integrating the predator-specific deposition probabilities increased the predation probabilities by a factor of approximately 1.4 for Caspian terns, 2.0 for double-crested cormorants, and 6.7 for California gulls compared with traditional minimum predation rate methods, which do not account for deposition probabilities. Results supported previous findings on the high predation impacts from strictly piscivorous waterbirds nesting in the Columbia River estuary (i.e., terns and cormorants), but our findings also revealed greater impacts of a generalist predator species (i.e., California gulls) than were previously documented. Approaches used in this study allow for direct comparisons among multiple fish mortality factors and considerably improve the reliability of tag recovery models for estimating predation probabilities in multiple-predator systems.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/00028487.2014.988882","usgsCitation":"Hostetter, N.J., Evans, A.F., Cramer, B.M., Collis, K., Lyons, D., and Roby, D.D., 2015, Quantifying avian predation on fish populations: integrating predator-specific deposition probabilities in tag-recovery studies: Transactions of the American Fisheries Society, v. 144, no. 2, p. 410-422, https://doi.org/10.1080/00028487.2014.988882.","productDescription":"13 p.","startPage":"410","endPage":"422","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-058968","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":472214,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://figshare.com/articles/journal_contribution/Quantifying_Avian_Predation_on_Fish_Populations_Integrating_Predator_Specific_Deposition_Probabilities_in_Tag_Recovery_Studies/1332455","text":"External Repository"},{"id":323421,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"144","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-03-11","publicationStatus":"PW","scienceBaseUri":"575a9335e4b04f417c275178","contributors":{"authors":[{"text":"Hostetter, Nathan J.","contributorId":171690,"corporation":false,"usgs":false,"family":"Hostetter","given":"Nathan","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":638312,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Evans, Allen F.","contributorId":171691,"corporation":false,"usgs":false,"family":"Evans","given":"Allen","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":638313,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cramer, Bradley M.","contributorId":171692,"corporation":false,"usgs":false,"family":"Cramer","given":"Bradley","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":638314,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Collis, Ken","contributorId":149991,"corporation":false,"usgs":false,"family":"Collis","given":"Ken","email":"","affiliations":[{"id":17879,"text":"Real Time Research, Inc., 231 SW Scalehouse Loop, Suite 101, Bend, OR 97702","active":true,"usgs":false}],"preferred":false,"id":638315,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lyons, Donald E.","contributorId":20119,"corporation":false,"usgs":true,"family":"Lyons","given":"Donald E.","affiliations":[],"preferred":false,"id":638316,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Roby, Daniel D. 0000-0001-9844-0992 droby@usgs.gov","orcid":"https://orcid.org/0000-0001-9844-0992","contributorId":3702,"corporation":false,"usgs":true,"family":"Roby","given":"Daniel","email":"droby@usgs.gov","middleInitial":"D.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":637266,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70142371,"text":"ofr20151025 - 2015 - Geochemical maps of stream sediments in central Colorado, from New Mexico to Wyoming","interactions":[],"lastModifiedDate":"2015-05-04T10:18:12","indexId":"ofr20151025","displayToPublicDate":"2015-03-10T15:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-1025","title":"Geochemical maps of stream sediments in central Colorado, from New Mexico to Wyoming","docAbstract":"The U.S. Geological Survey has completed a series of geologic, mineral resource, and environmental assessment studies in the Rocky Mountains of central Colorado, from Leadville eastward to the range front and from New Mexico to the Wyoming border. Regional stream-sediment geochemical maps, useful for assessing mineral resources and environmental effects of historical mining activities, were produced as part of the study. The data portrayed in this 56-parameter portfolio of landscape geochemical maps serve as a geochemical baseline for the region, indicate element abundances characteristic of various lithologic terranes, and identify gross anthropogenic effects of historical mining. However, although reanalyzed in this study by modern, sensitive methods, the majority of the stream-sediment samples were collected in the 1970s. Thus, metal concentrations portrayed in these maps represent stream-sediment geochemistry at the time of collection.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151025","usgsCitation":"Eppinger, R.G., Giles, S.A., and Klein, T.L., 2015, Geochemical maps of stream sediments in central Colorado, from New Mexico to Wyoming: U.S. Geological Survey Open-File Report 2015-1025, Report: viii, 120 p.; Downloads Directory, https://doi.org/10.3133/ofr20151025.","productDescription":"Report: viii, 120 p.; Downloads Directory","numberOfPages":"131","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-054650","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":298413,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20151025.jpg"},{"id":298411,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1025/pdf/ofr2015-1025.pdf","size":"54.1 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":298410,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2015/1025/"},{"id":298412,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2015/1025/downloads/","text":"Downloads Directory"}],"country":"United States","state":"Colorado","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.6168212890625,\n 41.00270266805319\n ],\n [\n -105.14190673828125,\n 41.00270266805319\n ],\n [\n -105.1556396484375,\n 39.76210275375137\n ],\n [\n -104.9853515625,\n 39.757879992021756\n ],\n [\n -104.9908447265625,\n 39.38526381099774\n ],\n [\n -104.83154296875,\n 39.38738660316804\n ],\n [\n -104.853515625,\n 36.99377838872517\n ],\n [\n -105.99884033203125,\n 36.99158465967016\n ],\n [\n -105.985107421875,\n 38.37396220263092\n ],\n [\n -106.64978027343749,\n 38.3868805698475\n ],\n [\n -106.6168212890625,\n 41.00270266805319\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55000799e4b02419550fa5cd","contributors":{"authors":[{"text":"Eppinger, Robert G. eppinger@usgs.gov","contributorId":849,"corporation":false,"usgs":true,"family":"Eppinger","given":"Robert","email":"eppinger@usgs.gov","middleInitial":"G.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":541851,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Giles, Stuart A. 0000-0002-8696-5078 sgiles@usgs.gov","orcid":"https://orcid.org/0000-0002-8696-5078","contributorId":1233,"corporation":false,"usgs":true,"family":"Giles","given":"Stuart","email":"sgiles@usgs.gov","middleInitial":"A.","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":541850,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Klein, Terry L. tklein@usgs.gov","contributorId":1244,"corporation":false,"usgs":true,"family":"Klein","given":"Terry","email":"tklein@usgs.gov","middleInitial":"L.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":541852,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70142660,"text":"tm13A2 - 2015 - A multipurpose camera system for monitoring Kīlauea Volcano, Hawai'i","interactions":[],"lastModifiedDate":"2015-03-10T10:23:46","indexId":"tm13A2","displayToPublicDate":"2015-03-10T11:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"13-A2","title":"A multipurpose camera system for monitoring Kīlauea Volcano, Hawai'i","docAbstract":"We describe a low-cost, compact multipurpose camera system designed for field deployment at active volcanoes that can be used either as a webcam (transmitting images back to an observatory in real-time) or as a time-lapse camera system (storing images onto the camera system for periodic retrieval during field visits). The system also has the capability to acquire high-definition video. The camera system uses a Raspberry Pi single-board computer and a 5-megapixel low-light (near-infrared sensitive) camera, as well as a small Global Positioning System (GPS) module to ensure accurate time-stamping of images. Custom Python scripts control the webcam and GPS unit and handle data management. The inexpensive nature of the system allows it to be installed at hazardous sites where it might be lost. Another major advantage of this camera system is that it provides accurate internal timing (independent of network connection) and, because a full Linux operating system and the Python programming language are available on the camera system itself, it has the versatility to be configured for the specific needs of the user. We describe example deployments of the camera at Kīlauea Volcano, Hawai‘i, to monitor ongoing summit lava lake activity.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Section A: Methods Used in Volcano Monitoring in Book 13 Volcano Monitoring","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm13A2","usgsCitation":"Patrick, M.R., Orr, T.R., Lee, L., and Moniz, C.J., 2015, A multipurpose camera system for monitoring Kīlauea Volcano, Hawai'i: U.S. Geological Survey Techniques and Methods 13-A2, Report: iv, 25 p.; 6 videos, https://doi.org/10.3133/tm13A2.","productDescription":"Report: iv, 25 p.; 6 videos","numberOfPages":"34","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-055070","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":298406,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/tm13a2.gif"},{"id":298393,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/tm/13/a2/"},{"id":298399,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/13/a2/tm13-A2.pdf","size":"7.9 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":298400,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/tm/13/a2/videos/TM_13-A2_video01.mov","text":"Halema'uma'u plume time-lapse MOV","size":"54.7 MB","linkHelpText":"This video shows an image every 10 minutes, from February 3, 2014, at 0001 Hawai‘i Standard Time (HST) to February 9, 2014, at 2359 HST. The movie shows the commonly fluctuating wind directions typical of winter months, when the normally steady trade winds become unstable. The camera was positioned in the Hawaiian Volcano Observatory observation tower. In the lower right corner of the image is the public overlook at Jaggar Museum."},{"id":298403,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/tm/13/a2/videos/TM_13-A2_video02.mp4","text":"Halema'uma'u lake time-lapse MP4","size":"7.4 MB","linkHelpText":"This video shows an image every minute, from February 14, 2014, at 1200 Hawai‘i Standard Time (HST) to February 15, 2014, at 1200 HST. The plot of RSAM (real-time seismic amplitude measurement), which can be taken as a proxy for the amplitude of seismic tremor, is shown below. Spikes in RSAM correspond with the appearance of additional spattering sources on the lake margin, whereas the sustained low level in RSAM after about 0800 on February 15 is an indicator of the absence of spattering at the lake and very quiet activity."},{"id":298404,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/tm/13/a2/videos/TM_13-A2_video03.mov","text":"Halema'uma'u lake video clips MOV","size":"20.2 MB","linkHelpText":"Four clips from February 2014 are shown, taken at the following times: (1) February 14, 1200 Hawai‘i Standard Time (HST); (2) February 14, 1800 HST; (3) February 15, 0000 HST; (4) February 15, 0600 HST. Videos are shown at 3× speed."},{"id":298405,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/tm/13/a2/videos/TM_13-A2_video03.mp4","text":"Halema'uma'u lake video clips MP4","size":"4.7 MB","linkHelpText":"Four clips from February 2014 are shown, taken at the following times: (1) February 14, 1200 Hawai‘i Standard Time (HST); (2) February 14, 1800 HST; (3) February 15, 0000 HST; (4) February 15, 0600 HST. Videos are shown at 3× speed."},{"id":298401,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/tm/13/a2/videos/TM_13-A2_video01.mp4","text":"Halema'uma'u plume time-lapse MP4","size":"14.9 MB","linkHelpText":"This video shows an image every 10 minutes, from February 3, 2014, at 0001 Hawai‘i Standard Time (HST) to February 9, 2014, at 2359 HST. The movie shows the commonly fluctuating wind directions typical of winter months, when the normally steady trade winds become unstable. The camera was positioned in the Hawaiian Volcano Observatory observation tower. In the lower right corner of the image is the public overlook at Jaggar Museum."},{"id":298402,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/tm/13/a2/videos/TM_13-A2_video02.mov","text":"Halema'uma'u lake time-lapse MOV","size":"19.1 MB","linkHelpText":"This video shows an image every minute, from February 14, 2014, at 1200 Hawai‘i Standard Time (HST) to February 15, 2014, at 1200 HST. The plot of RSAM (real-time seismic amplitude measurement), which can be taken as a proxy for the amplitude of seismic tremor, is shown below. 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The new model, referred to as the third Uniform California Earthquake Rupture Forecast, or \"UCERF\" (http://www.WGCEP.org/UCERF3), provides authoritative estimates of the magnitude, location, and likelihood of earthquake fault rupture throughout the state. Overall the results confirm previous findings, but with some significant changes because of model improvements. For example, compared to the previous forecast (Uniform California Earthquake Rupture Forecast 2), the likelihood of moderate-sized earthquakes (magnitude 6.5 to 7.5) is lower, whereas that of larger events is higher. This is because of the inclusion of multifault ruptures, where earthquakes are no longer confined to separate, individual faults, but can occasionally rupture multiple faults simultaneously. The public-safety implications of this and other model improvements depend on several factors, including site location and type of structure (for example, family dwelling compared to a long-span bridge). Building codes, earthquake insurance products, emergency plans, and other risk-mitigation efforts will be updated accordingly. This model also serves as a reminder that damaging earthquakes are inevitable for California. Fortunately, there are many simple steps residents can take to protect lives and property.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20153009","usgsCitation":"Field, E.H., and 2014 Working Group on California Earthquake Probabilities, 2015, UCERF3: A new earthquake forecast for California's complex fault system: U.S. Geological Survey Fact Sheet 2015-3009, 6 p., https://doi.org/10.3133/fs20153009.","productDescription":"6 p.","numberOfPages":"6","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062714","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":298397,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20153009.jpg"},{"id":298396,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2015/3009/pdf/fs2015-3009.pdf","text":"Report","size":"32.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2015-3009 Report"},{"id":298394,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2015/3009/"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.365234375,\n 42.00032514831621\n ],\n [\n -119.970703125,\n 42.01665183556825\n ],\n [\n -119.94873046875,\n 39.07890809706475\n ],\n [\n -114.63134765625001,\n 35.10193405724606\n ],\n [\n -113.9501953125,\n 34.23451236236984\n ],\n [\n -114.3896484375,\n 32.731840896865684\n ],\n [\n -117.18017578125,\n 32.52828936482526\n ],\n [\n -117.53173828125,\n 33.119150226768866\n ],\n [\n -119.64111328125,\n 34.27083595165\n ],\n [\n -120.82763671875,\n 34.379712580462204\n ],\n [\n -123.90380859374999,\n 38.94232097947902\n ],\n [\n -124.49707031249999,\n 40.38002840251183\n ],\n [\n -124.365234375,\n 42.00032514831621\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55000799e4b02419550fa5cf","contributors":{"authors":[{"text":"Field, Edward H. 0000-0001-8172-7882 field@usgs.gov","orcid":"https://orcid.org/0000-0001-8172-7882","contributorId":52242,"corporation":false,"usgs":true,"family":"Field","given":"Edward","email":"field@usgs.gov","middleInitial":"H.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":542095,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"2014 Working Group on California Earthquake Probabilities","contributorId":139622,"corporation":true,"usgs":false,"organization":"2014 Working Group on California Earthquake Probabilities","id":542098,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70146556,"text":"70146556 - 2015 - Multivariate analysis relating oil shale geochemical properties to NMR relaxometry","interactions":[],"lastModifiedDate":"2015-04-17T10:28:26","indexId":"70146556","displayToPublicDate":"2015-03-10T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1506,"text":"Energy & Fuels","active":true,"publicationSubtype":{"id":10}},"title":"Multivariate analysis relating oil shale geochemical properties to NMR relaxometry","docAbstract":"Low-field nuclear magnetic resonance (NMR) relaxometry has been used to provide insight into shale composition by separating relaxation responses from the various hydrogen-bearing phases present in shales in a noninvasive way. Previous low-field NMR work using solid-echo methods provided qualitative information on organic constituents associated with raw and pyrolyzed oil shale samples, but uncertainty in the interpretation of longitudinal-transverse (T1–T2) relaxometry correlation results indicated further study was required. Qualitative confirmation of peaks attributed to kerogen in oil shale was achieved by comparing T1–T2 correlation measurements made on oil shale samples to measurements made on kerogen isolated from those shales. Quantitative relationships between T1–T2 correlation data and organic geochemical properties of raw and pyrolyzed oil shales were determined using partial least-squares regression (PLSR). Relaxometry results were also compared to infrared spectra, and the results not only provided further confidence in the organic matter peak interpretations but also confirmed attribution of T1–T2 peaks to clay hydroxyls. In addition, PLSR analysis was applied to correlate relaxometry data to trace element concentrations with good success. The results of this work show that NMR relaxometry measurements using the solid-echo approach produce T1–T2 peak distributions that correlate well with geochemical properties of raw and pyrolyzed oil shales.
","language":"English","publisher":"American Chemical Society","doi":"10.1021/ef502828k","usgsCitation":"Birdwell, J.E., and Washburn, K.E., 2015, Multivariate analysis relating oil shale geochemical properties to NMR relaxometry: Energy & Fuels, v. 29, no. 4, p. 2234-2243, https://doi.org/10.1021/ef502828k.","productDescription":"10 p.","startPage":"2234","endPage":"2243","numberOfPages":"10","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061762","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":299752,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"29","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-03-23","publicationStatus":"PW","scienceBaseUri":"55322edbe4b0b22a158063f0","contributors":{"authors":[{"text":"Birdwell, Justin E. 0000-0001-8263-1452 jbirdwell@usgs.gov","orcid":"https://orcid.org/0000-0001-8263-1452","contributorId":3302,"corporation":false,"usgs":true,"family":"Birdwell","given":"Justin","email":"jbirdwell@usgs.gov","middleInitial":"E.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":545140,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Washburn, Kathryn E.","contributorId":76644,"corporation":false,"usgs":false,"family":"Washburn","given":"Kathryn","email":"","middleInitial":"E.","affiliations":[{"id":7152,"text":"Weatherford International","active":true,"usgs":false}],"preferred":false,"id":545141,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70124468,"text":"fs20143076 - 2015 - Invasive Species Science Branch: research and management tools for controlling invasive species","interactions":[],"lastModifiedDate":"2015-03-09T12:42:18","indexId":"fs20143076","displayToPublicDate":"2015-03-09T12:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-3076","title":"Invasive Species Science Branch: research and management tools for controlling invasive species","docAbstract":"Invasive, nonnative species of plants, animals, and disease organisms adversely affect the ecosystems they enter. Like “biological wildfires,” they can quickly spread and affect nearly all terrestrial and aquatic ecosystems. Invasive species have become one of the greatest environmental challenges of the 21st century in economic, environmental, and human health costs, with an estimated effect in the United States of more than $120 billion per year. Managers of the Department of the Interior and other public and private lands often rank invasive species as their top resource management problem. The Invasive Species Science Branch of the Fort Collins Science Center provides research and technical assistance relating to management concerns for invasive species, including understanding how these species are introduced, identifying areas vulnerable to invasion, forecasting invasions, and developing control methods. To disseminate this information, branch scientists are developing platforms to share invasive species information with DOI cooperators, other agency partners, and the public. From these and other data, branch scientists are constructing models to understand and predict invasive species distributions for more effective management. The branch also has extensive herpetological and population biology expertise that is applied to harmful reptile invaders such as the Brown Treesnake on Guam and Burmese Python in Florida.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20143076","usgsCitation":"Reed, R., and Walters, K.D., 2015, Invasive Species Science Branch: research and management tools for controlling invasive species: U.S. Geological Survey Fact Sheet 2014-3076, 4 p., https://doi.org/10.3133/fs20143076.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-056936","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":298376,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20143076.jpg"},{"id":298374,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2014/3076/"},{"id":298375,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2014/3076/pdf/fs2014-3076.pdf","text":"Report","size":"5.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54feb61ce4b02419550deb9d","contributors":{"authors":[{"text":"Reed, Robert N. reedr@usgs.gov","contributorId":1686,"corporation":false,"usgs":true,"family":"Reed","given":"Robert N.","email":"reedr@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":519444,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Walters, Katie D. waltersk@usgs.gov","contributorId":741,"corporation":false,"usgs":true,"family":"Walters","given":"Katie","email":"waltersk@usgs.gov","middleInitial":"D.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":519443,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70141768,"text":"fs20153013 - 2015 - National Unmanned Aircraft Systems Project Office","interactions":[],"lastModifiedDate":"2015-03-09T11:17:11","indexId":"fs20153013","displayToPublicDate":"2015-03-09T12:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-3013","title":"National Unmanned Aircraft Systems Project Office","docAbstract":"The U.S. Geological Survey (USGS) National Unmanned Aircraft Systems (UAS) Project Office leads the implementation of UAS technology in the Department of the Interior (DOI). Our mission is to support the transition of UAS into DOI as a new cost-effective tool for collecting remote-sensing data to monitor environmental conditions, respond to natural hazards, recognize the consequences and benefits of land and climate change and conduct wildlife inventories. The USGS is teaming with all DOI agencies and academia as well as local, State, and Tribal governments with guidance from the Federal Aviation Administration and the DOI Office of Aviation Services (OAS) to lead the safe, efficient, costeffective and leading-edge adoption of UAS technology into the scientific research and operational activities of the DOI.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20153013","usgsCitation":"Goplen, S.E., and Sloan, J.L., 2015, National Unmanned Aircraft Systems Project Office: U.S. Geological Survey Fact Sheet 2015-3013, 2 p., https://doi.org/10.3133/fs20153013.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-061097","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":298365,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20153013.jpg"},{"id":298364,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2015/3013/pdf/fs2015-3013.pdf","text":"Report","size":"3.12 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":298363,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2015/3013/"}],"publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54feb61de4b02419550deb9f","contributors":{"authors":[{"text":"Goplen, Susan E. segoplen@usgs.gov","contributorId":1790,"corporation":false,"usgs":true,"family":"Goplen","given":"Susan","email":"segoplen@usgs.gov","middleInitial":"E.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":542017,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sloan, Jeff L. jlsloan@usgs.gov","contributorId":3918,"corporation":false,"usgs":true,"family":"Sloan","given":"Jeff","email":"jlsloan@usgs.gov","middleInitial":"L.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":542018,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70144493,"text":"70144493 - 2015 - Using near-real-time monitoring data from Pu'u 'Ō'ō vent at Kīlauea Volcano for training and educational purposes","interactions":[],"lastModifiedDate":"2015-03-31T11:50:05","indexId":"70144493","displayToPublicDate":"2015-03-08T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3841,"text":"Journal of Applied Volcanology","active":true,"publicationSubtype":{"id":10}},"title":"Using near-real-time monitoring data from Pu'u 'Ō'ō vent at Kīlauea Volcano for training and educational purposes","docAbstract":"Training non-scientists in the use of volcano-monitoring data is critical preparation in advance of a volcanic crisis, but it is currently unclear which methods are most effective for improving the content-knowledge of non-scientists to help bridge communications between volcano experts and non-experts. We measured knowledge gains for beginning-(introductory-level students) and novice-level learners (students with a basic understanding of geologic concepts) engaged in the Volcanoes Exploration Program: Pu‘u ‘Ō‘ō (VEPP) “Monday Morning Meeting at the Hawaiian Volcano Observatory” classroom activity that incorporates authentic Global Positioning System (GPS), tilt, seismic, and webcam data from the Pu‘u ‘Ō‘ō eruptive vent on Kīlauea Volcano, Hawai‘i (NAGT website, 2010), as a means of exploring methods for effectively advancing non-expert understanding of volcano monitoring. Learner groups consisted of students in introductory and upper-division college geology courses at two different institutions. Changes in their content knowledge and confidence in the use of data were assessed before and after the activity using multiple-choice and open-ended questions. Learning assessments demonstrated that students who took part in the exercise increased their understanding of volcano-monitoring practices and implications, with beginners reaching a novice stage, and novices reaching an advanced level (akin to students who have completed an upper-division university volcanology class). Additionally, participants gained stronger confidence in their ability to understand the data. These findings indicate that training modules like the VEPP: Monday Morning Meeting classroom activity that are designed to prepare non-experts for responding to volcanic activity and interacting with volcano scientists should introduce real monitoring data prior to proceeding with role-paying scenarios that are commonly used in such courses. The learning gains from the combined approach will help improve effective communications between volcano experts and non-experts during times of crisis, thereby reducing the potential for confusion and misinterpretation of data.
","language":"English","publisher":"Springer","doi":"10.1186/s13617-015-0026-x","usgsCitation":"Teasdale, R., Kraft, K.V., and Poland, M.P., 2015, Using near-real-time monitoring data from Pu'u 'Ō'ō vent at Kīlauea Volcano for training and educational purposes: Journal of Applied Volcanology, v. 4, no. 11, 16 p., https://doi.org/10.1186/s13617-015-0026-x.","productDescription":"16 p.","numberOfPages":"16","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-055760","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":472219,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s13617-015-0026-x","text":"Publisher Index Page"},{"id":299209,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Kīlauea Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.3075408935547,\n 19.38888634723281\n ],\n [\n -155.3075408935547,\n 19.442636882017393\n ],\n [\n -155.2338981628418,\n 19.442636882017393\n ],\n [\n -155.2338981628418,\n 19.38888634723281\n ],\n [\n -155.3075408935547,\n 19.38888634723281\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"4","issue":"11","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-03-08","publicationStatus":"PW","scienceBaseUri":"551bc52ee4b0323842783a5c","contributors":{"authors":[{"text":"Teasdale, Rachel","contributorId":102388,"corporation":false,"usgs":false,"family":"Teasdale","given":"Rachel","email":"","affiliations":[],"preferred":false,"id":543660,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kraft, Katrien van der Hoeven","contributorId":139983,"corporation":false,"usgs":false,"family":"Kraft","given":"Katrien","email":"","middleInitial":"van der Hoeven","affiliations":[{"id":13342,"text":"Mesa Community College","active":true,"usgs":false}],"preferred":false,"id":543661,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Poland, Michael P. 0000-0001-5240-6123 mpoland@usgs.gov","orcid":"https://orcid.org/0000-0001-5240-6123","contributorId":127857,"corporation":false,"usgs":true,"family":"Poland","given":"Michael","email":"mpoland@usgs.gov","middleInitial":"P.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":false,"id":543659,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70142305,"text":"70142305 - 2015 - Evaluating the status of individuals and populations: Advantages of multiple approaches and time scales","interactions":[],"lastModifiedDate":"2023-01-03T15:27:28.201045","indexId":"70142305","displayToPublicDate":"2015-03-06T11:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"6","title":"Evaluating the status of individuals and populations: Advantages of multiple approaches and time scales","docAbstract":"The assessment of population status is a central goal of applied wildlife research and essential to the field of wildlife conservation. “Population status” has a number of definitions, the most widely used having to do with the current trajectory of the population (i.e., growing, stable, or declining), or the probability of persistence (i.e., extinction risk), perhaps without any specific knowledge as to the factors driving a population’s dynamics. In contrast, a population’s status relative to the carrying capacity of the environment (K) is an ecologically-based definition that explicitly provides information about a major mechanism of population control. That is, it relates to the relative per capita availability of resources to individuals in a population, which can also be used to infer the state of the environment itself.
\nSea otters in the North Pacific provide an excellent system with which to examine various approaches to assessing population status relative to K. This is because sea otters were nearly extirpated by historic commercial overexploitation in the eighteenth and nineteenth centuries, followed by natural and translocation-aided population recovery during the twentieth century, and this decline and recovery has been relatively well documented. This provided a unique opportunity to study populations at the extremes of the population status spectrum. Here we describe and review the approaches that have been utilized in sea otter research to understand the status of populations relative to resource abundance. Specifically, we will illustrate the utility of various indices of population status for understanding population dynamics using the case study of a second precipitous sea otter decline in the Western Aleutians. The indices or “tools” described here fit into several broad categories including (1) energetic, (2) morphological, and (3) demographic as well as a fourth category of emerging tools that have not yet been employed in many other situations including dietary diversity, community structure, spatial distribution, and gene expression.
\nOverall, a variety of indices used to measure population status throughout the sea otter’s range have provided insights for understanding the mechanisms driving the trajectory of various sea otter populations, which a single index could not, and we suggest using multiple methods to measure a population’s status at multiple spatial and temporal scales. The work described here also illustrates the usefulness of long-term data sets and/or approaches that can be used to assess population status retrospectively, providing information otherwise not available. While not all systems will be as amenable to using all the approaches presented here, we expect innovative researchers could adapt analogous multi-scale methods to a broad range of habitats and species including apex predators occupying the top trophic levels, which are often of conservation concern.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Sea Otter Conservation","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Academic Press","publisherLocation":"Amsterdam","doi":"10.1016/B978-0-12-801402-8.00006-8","usgsCitation":"Monson, D., and Bowen, L., 2015, Evaluating the status of individuals and populations: Advantages of multiple approaches and time scales, chap. 6 of Sea Otter Conservation, p. 121-158, https://doi.org/10.1016/B978-0-12-801402-8.00006-8.","productDescription":"38 p.","startPage":"121","endPage":"158","numberOfPages":"38","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-049066","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":298330,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54facfaae4b02419550db6ca","contributors":{"authors":[{"text":"Monson, Daniel H. 0000-0002-4593-5673 dmonson@usgs.gov","orcid":"https://orcid.org/0000-0002-4593-5673","contributorId":140480,"corporation":false,"usgs":true,"family":"Monson","given":"Daniel H.","email":"dmonson@usgs.gov","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":false,"id":541818,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bowen, Lizabeth 0000-0001-9115-4336 lbowen@usgs.gov","orcid":"https://orcid.org/0000-0001-9115-4336","contributorId":4539,"corporation":false,"usgs":true,"family":"Bowen","given":"Lizabeth","email":"lbowen@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":541819,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70156251,"text":"70156251 - 2015 - Heterogeneous movement of insectivorous Amazonian birds through primary and secondary forest: A case study using multistate models with radiotelemetry data","interactions":[],"lastModifiedDate":"2022-11-10T16:36:18.01769","indexId":"70156251","displayToPublicDate":"2015-03-06T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1015,"text":"Biological Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Heterogeneous movement of insectivorous Amazonian birds through primary and secondary forest: A case study using multistate models with radiotelemetry data","docAbstract":"Given rates of deforestation, disturbance, and secondary forest accumulation in tropical rainforests, there is a great need to quantify habitat use and movement among different habitats. This need is particularly pronounced for animals most sensitive to disturbance, such as insectivorous understory birds. Here we use multistate capture–recapture models with radiotelemetry data to determine the successional stage at which within-day movement probabilities of Amazonian birds in secondary forest are similar to those in primary forest. We radio-tracked three common understory insectivore species in primary and secondary forest at the Biological Dynamics of Forest Fragments project near Manaus, Brazil: two woodcreepers, Glyphorynchus spirurus (n = 19) andXiphorhynchus pardalotus (n = 18), and the terrestrial antthrush Formicarius colma(n = 19). Forest age was a strong predictor of fidelity to a given habitat. All three species showed greater fidelity to primary forest than to 8–14-year-old secondary forest, indicating the latter’s relatively poor quality. The two woodcreeper species used 12–18-year-old secondary forest in a manner comparable to continuous forest, but F. colmaavoided moving even to 27–31-year-old secondary forest—the oldest at our site. Our results suggest that managers concerned with less sensitive species can assume that forest reserves connected by 12–18-year-old secondary forest corridors are effectively connected. On the other hand, >30 years are required after land abandonment before secondary forest serves as a primary forest-like conduit for movement by F. colma; more sensitive terrestrial insectivores may take longer still.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.biocon.2015.01.028","usgsCitation":"Hines, J.E., Powell, L.L., Wolfe, J.D., Johnson, E.L., Nichols, J., and Stouffer, P.C., 2015, Heterogeneous movement of insectivorous Amazonian birds through primary and secondary forest: A case study using multistate models with radiotelemetry data: Biological Conservation, v. 188, p. 100-108, https://doi.org/10.1016/j.biocon.2015.01.028.","productDescription":"8 p.","startPage":"100","endPage":"108","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064220","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":306824,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Brazil","city":"Manaus","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -61.384530576017966,\n -1.6981363640401668\n ],\n [\n -61.384530576017966,\n -4.235218153320815\n ],\n [\n -58.61166836481719,\n -4.235218153320815\n ],\n [\n -58.61166836481719,\n -1.6981363640401668\n ],\n [\n -61.384530576017966,\n -1.6981363640401668\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"188","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55d305b5e4b0518e35468cfe","contributors":{"authors":[{"text":"Hines, James E. 0000-0001-5478-7230 jhines@usgs.gov","orcid":"https://orcid.org/0000-0001-5478-7230","contributorId":146530,"corporation":false,"usgs":true,"family":"Hines","given":"James","email":"jhines@usgs.gov","middleInitial":"E.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":568246,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Powell, Luke L.","contributorId":146576,"corporation":false,"usgs":false,"family":"Powell","given":"Luke","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":568338,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wolfe, Jared D.","contributorId":146577,"corporation":false,"usgs":false,"family":"Wolfe","given":"Jared","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":568339,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Johnson, Erik l.","contributorId":146578,"corporation":false,"usgs":false,"family":"Johnson","given":"Erik","email":"","middleInitial":"l.","affiliations":[],"preferred":false,"id":568340,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nichols, James D. 0000-0002-7631-2890 jnichols@usgs.gov","orcid":"https://orcid.org/0000-0002-7631-2890","contributorId":405,"corporation":false,"usgs":true,"family":"Nichols","given":"James D.","email":"jnichols@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":568341,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stouffer, Phillip C.","contributorId":146579,"corporation":false,"usgs":false,"family":"Stouffer","given":"Phillip","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":568342,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70142156,"text":"ofr20131024E - 2015 - Laboratory electrical resistivity analysis of geologic samples from Fort Irwin, California","interactions":[{"subject":{"id":70142156,"text":"ofr20131024E - 2015 - Laboratory electrical resistivity analysis of geologic samples from Fort Irwin, California","indexId":"ofr20131024E","publicationYear":"2015","noYear":false,"chapter":"E","displayTitle":"Laboratory Electrical Resistivity Analysis of Geologic Samples from Fort Irwin, California","title":"Laboratory electrical resistivity analysis of geologic samples from Fort Irwin, California"},"predicate":"IS_PART_OF","object":{"id":70201192,"text":"ofr20131024 - 2014 - Geology and geophysics applied to groundwater hydrology at Fort Irwin, California","indexId":"ofr20131024","publicationYear":"2014","noYear":false,"title":"Geology and geophysics applied to groundwater hydrology at Fort Irwin, California"},"id":1}],"isPartOf":{"id":70201192,"text":"ofr20131024 - 2014 - Geology and geophysics applied to groundwater hydrology at Fort Irwin, California","indexId":"ofr20131024","publicationYear":"2014","noYear":false,"title":"Geology and geophysics applied to groundwater hydrology at Fort Irwin, California"},"lastModifiedDate":"2018-12-14T11:56:25","indexId":"ofr20131024E","displayToPublicDate":"2015-03-05T13:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-1024","chapter":"E","displayTitle":"Laboratory Electrical Resistivity Analysis of Geologic Samples from Fort Irwin, California","title":"Laboratory electrical resistivity analysis of geologic samples from Fort Irwin, California","docAbstract":"Correlating laboratory resistivity measurements with geophysical resistivity models helps constrain these models to the geology and lithology of an area. Throughout the Fort Irwin National Training Center area, 111 samples from both cored boreholes and surface outcrops were collected and processed for laboratory measurements. These samples represent various lithologic types that include plutonic and metamorphic (basement) rocks, lava flows, consolidated sedimentary rocks, and unconsolidated sedimentary deposits that formed in a series of intermountain basins. Basement rocks, lava flows, and some lithified tuffs are generally resistive (≥100 ohm-meters [Ω·m]) when saturated. Saturated unconsolidated samples are moderately conductive to conductive, with resistivities generally less than 100 Ω·m, and many of these samples are less than 50 Ω·m. The unconsolidated samples can further be separated into two broad groups: (1) younger sediments that are moderately conductive, owing to their limited clay content, and (2) older, more conductive sediments with a higher clay content that reflects substantial amounts of originally glassy volcanic ash subsequently altered to clay. The older sediments are believed to be Tertiary. Time-domain electromagnetic (TEM) data were acquired near most of the boreholes, and, on the whole, close agreements between laboratory measurements and resistivity models were found.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Geology and geophysics applied to groundwater hydrology at Fort Irwin, California","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131024E","collaboration":"Prepared in cooperation with the U.S. Army, Fort Irwin National Training Center","usgsCitation":"Bloss, B.R., and Bedrosian, P.A, 2015, Laboratory electrical resistivity analysis of geologic samples from Fort Irwin, California, chap. E of Buesch, D.C., ed., Geology and geophysics applied to groundwater hydrology at Fort Irwin, California: U.S. Geological Survey Open-file Report 2013-1024, 104 p., https://doi.org/10.3133/ofr20131024E.","productDescription":"Report: vii, 104 p.; Supplemental Data ReadMe; Supplemental Data ZIP","numberOfPages":"104","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-060545","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":298311,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2013/1024/e/images/coverthb.jpg"},{"id":298308,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1024/e/downloads/ofr2013-1024_e.pdf","text":"Report","size":"15.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":298309,"rank":2,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/of/2013/1024/e/downloads/ofr2013-1024_e_README.pdf","text":"Supplemental Data README","size":"78 kB","linkFileType":{"id":1,"text":"pdf"},"description":"Supplemental Data README"},{"id":298310,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2013/1024/e/downloads/ofr2013-1024_supplemental_data.zip","text":"Supplemental Data","size":"362 kB","linkFileType":{"id":1,"text":"pdf"},"description":"Supplemental Data"}],"country":"United States","state":"California","county":"San Bernardino County","city":"Fort Irwin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.99890136718749,\n 35.12889434101051\n ],\n [\n -116.99890136718749,\n 35.639441068973916\n ],\n [\n -116.18591308593749,\n 35.639441068973916\n ],\n [\n -116.18591308593749,\n 35.12889434101051\n ],\n [\n -116.99890136718749,\n 35.12889434101051\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contact Information,
Geology, Minerals, Energy, & Geophysics Science Center—Menlo Park
U.S. Geological Survey
345 Middlefield Road
Menlo Park, CA 94025-3591
We mapped oil presence in the marshes of Barataria Bay, Louisiana following the Deepwater Horizon oil spill using Airborne Visible InfraRed Imaging Spectrometer (AVIRIS) data. Oil and non-photosynthetic vegetation (NPV) have very similar spectra, differing only in two narrow hydrocarbon absorption regions around 1700 and 2300 nm. Confusion between NPV and oil is expressed as an increase in oil fraction error with increasing NPV, as shown by Multiple Endmember Spectral Mixture Analysis (MESMA) applied to synthetic spectra generated with known endmember fractions. Significantly, the magnitude of error varied depending upon the type of NPV in the mixture. To reduce error, we used stable zone unmixing to identify a nine band subset that emphasized the hydrocarbon absorption regions, allowing for more accurate detection of oil presence using MESMA. When this band subset was applied to post-spill AVIRIS data acquired over Barataria Bay on several dates following the 2010 oil spill, accuracies ranged from 87.5% to 93.3%. Oil presence extended 10.5 m into the marsh for oiled shorelines, showing a reduced oil fraction with increasing distance from the shoreline.
","language":"English","publisher":"Elsevier Inc.","doi":"10.1016/j.rse.2014.12.009","usgsCitation":"Peterson, S.H., Roberts, D.A., Beland, M., Kokaly, R., and Ustin, S.L., 2015, Oil detection in the coastal marshes of Louisiana using MESMA applied to band subsets of AVIRIS data: Remote Sensing of Environment, v. 159, p. 222-231, https://doi.org/10.1016/j.rse.2014.12.009.","productDescription":"10 p.","startPage":"222","endPage":"231","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057762","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":298303,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Barataria Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.054931640625,\n 29.27202470909843\n ],\n [\n -90.054931640625,\n 29.476665675902137\n ],\n [\n -89.85580444335938,\n 29.476665675902137\n ],\n [\n -89.85580444335938,\n 29.27202470909843\n ],\n [\n -90.054931640625,\n 29.27202470909843\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"159","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54f97e2de4b02419550d9b5c","contributors":{"authors":[{"text":"Peterson, Seth H.","contributorId":139568,"corporation":false,"usgs":false,"family":"Peterson","given":"Seth","email":"","middleInitial":"H.","affiliations":[{"id":12804,"text":"Univ. of California Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":541862,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Roberts, Dar A.","contributorId":100503,"corporation":false,"usgs":false,"family":"Roberts","given":"Dar","email":"","middleInitial":"A.","affiliations":[{"id":12804,"text":"Univ. of California Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":541863,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Beland, Michael","contributorId":139569,"corporation":false,"usgs":false,"family":"Beland","given":"Michael","email":"","affiliations":[{"id":12805,"text":"Univ. of California at San Diego","active":true,"usgs":false}],"preferred":false,"id":541864,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kokaly, Raymond F. 0000-0003-0276-7101 raymond@usgs.gov","orcid":"https://orcid.org/0000-0003-0276-7101","contributorId":1785,"corporation":false,"usgs":true,"family":"Kokaly","given":"Raymond F.","email":"raymond@usgs.gov","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":false,"id":541861,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ustin, Susan L.","contributorId":52878,"corporation":false,"usgs":false,"family":"Ustin","given":"Susan","email":"","middleInitial":"L.","affiliations":[{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":541865,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70180868,"text":"70180868 - 2015 - A new approach for continuous estimation of baseflow using discrete water quality data: Method description and comparison with baseflow estimates from two existing approaches","interactions":[],"lastModifiedDate":"2017-05-03T13:36:22","indexId":"70180868","displayToPublicDate":"2015-03-05T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"A new approach for continuous estimation of baseflow using discrete water quality data: Method description and comparison with baseflow estimates from two existing approaches","docAbstract":"Understanding how watershed characteristics and climate influence the baseflow component of stream discharge is a topic of interest to both the scientific and water management communities. Therefore, the development of baseflow estimation methods is a topic of active research. Previous studies have demonstrated that graphical hydrograph separation (GHS) and conductivity mass balance (CMB) methods can be applied to stream discharge data to estimate daily baseflow. While CMB is generally considered to be a more objective approach than GHS, its application across broad spatial scales is limited by a lack of high frequency specific conductance (SC) data. We propose a new method that uses discrete SC data, which are widely available, to estimate baseflow at a daily time step using the CMB method. The proposed approach involves the development of regression models that relate discrete SC concentrations to stream discharge and time. Regression-derived CMB baseflow estimates were more similar to baseflow estimates obtained using a CMB approach with measured high frequency SC data than were the GHS baseflow estimates at twelve snowmelt dominated streams and rivers. There was a near perfect fit between the regression-derived and measured CMB baseflow estimates at sites where the regression models were able to accurately predict daily SC concentrations. We propose that the regression-derived approach could be applied to estimate baseflow at large numbers of sites, thereby enabling future investigations of watershed and climatic characteristics that influence the baseflow component of stream discharge across large spatial scales.
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Center","active":true,"usgs":true}],"preferred":true,"id":662641,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wolock, David M. 0000-0002-6209-938X dwolock@usgs.gov","orcid":"https://orcid.org/0000-0002-6209-938X","contributorId":540,"corporation":false,"usgs":true,"family":"Wolock","given":"David","email":"dwolock@usgs.gov","middleInitial":"M.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":662642,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70141749,"text":"70141749 - 2015 - Geotechnical aspects in the epicentral region of the 2011, Mw5.8 Mineral, Virginia earthquake","interactions":[],"lastModifiedDate":"2017-04-14T10:22:17","indexId":"70141749","displayToPublicDate":"2015-03-04T15:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1727,"text":"GSA Special Papers","active":true,"publicationSubtype":{"id":10}},"title":"Geotechnical aspects in the epicentral region of the 2011, Mw5.8 Mineral, Virginia earthquake","docAbstract":"A reconnaissance team documented the geotechnical and geological aspects in the epicentral region of the Mw (moment magnitude) 5.8 Mineral, Virginia (USA), earthquake of 23 August 2011. Tectonically and seismically induced ground deformations, evidence of liquefaction, rock slides, river bank slumps, ground subsidence, performance of earthen dams, damage to public infrastructure and lifelines, and other effects of the earthquake were documented. This moderate earthquake provided the rare opportunity to collect data to help assess current geoengineering practices in the region, as well as to assess seismic performance of the aging infrastructure in the region. Ground failures included two marginal liquefaction sites, a river bank slump, four minor rockfalls, and a ~4-m-wide, ~12-m-long, ~0.3-m-deep subsidence on a residential property. Damage to lifelines included subsidence of the approaches for a bridge and a water main break to a heavily corroded, 5-cm-diameter valve in Mineral, Virginia. Observed damage to dams, landfills, and public-use properties included a small, shallow slide in the temporary (“working”) clay cap of the county landfill, damage to two earthen dams (one in the epicentral region and one further away near Bedford, Virginia), and substantial structural damage to two public school buildings.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/2014.2509(09)","usgsCitation":"Green, R.A., Lasley, S., Carter, M.W., Munsey, J.W., Maurer, B.W., and Tuttle, M.P., 2015, Geotechnical aspects in the epicentral region of the 2011, Mw5.8 Mineral, Virginia earthquake: GSA Special Papers, v. 509, p. 151-172, https://doi.org/10.1130/2014.2509(09).","productDescription":"22 p.","startPage":"151","endPage":"172","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-054097","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":298295,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Virginia","city":"Mineral","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.495849609375,\n 36.10237644873644\n ],\n [\n -84.495849609375,\n 39.918162846609455\n ],\n [\n -74.77294921875,\n 39.918162846609455\n ],\n [\n -74.77294921875,\n 36.10237644873644\n ],\n [\n -84.495849609375,\n 36.10237644873644\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"509","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54f82cafe4b02419550d99de","contributors":{"authors":[{"text":"Green, Russell A.","contributorId":94708,"corporation":false,"usgs":false,"family":"Green","given":"Russell","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":540989,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lasley, Samuel","contributorId":139385,"corporation":false,"usgs":false,"family":"Lasley","given":"Samuel","email":"","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":540990,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Carter, Mark W. 0000-0003-0460-7638 mcarter@usgs.gov","orcid":"https://orcid.org/0000-0003-0460-7638","contributorId":4808,"corporation":false,"usgs":true,"family":"Carter","given":"Mark","email":"mcarter@usgs.gov","middleInitial":"W.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"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":540988,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Munsey, Jeffrey W.","contributorId":139386,"corporation":false,"usgs":false,"family":"Munsey","given":"Jeffrey","email":"","middleInitial":"W.","affiliations":[{"id":12759,"text":"TVA","active":true,"usgs":false}],"preferred":false,"id":540991,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Maurer, Brett W.","contributorId":139387,"corporation":false,"usgs":false,"family":"Maurer","given":"Brett","email":"","middleInitial":"W.","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":540992,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Tuttle, Martitia P.","contributorId":139388,"corporation":false,"usgs":false,"family":"Tuttle","given":"Martitia","email":"","middleInitial":"P.","affiliations":[{"id":12760,"text":"Tuttle and Associates","active":true,"usgs":false}],"preferred":false,"id":540993,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70136492,"text":"sir20145235 - 2015 - Simulation of groundwater flow and streamflow depletion in the Branch Brook, Merriland River, and parts of the Mousam River watersheds in southern Maine","interactions":[],"lastModifiedDate":"2015-03-04T10:40:00","indexId":"sir20145235","displayToPublicDate":"2015-03-04T10:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-5235","title":"Simulation of groundwater flow and streamflow depletion in the Branch Brook, Merriland River, and parts of the Mousam River watersheds in southern Maine","docAbstract":"Watersheds of three streams, the Mousam River, Branch Brook, and Merriland River in southeastern Maine were investigated from 2010 through 2013 under a cooperative project between the U.S. Geological Survey and the Maine Geological Survey. The Branch Brook watershed previously had been deemed “at risk” by the Maine Geological Survey because of the proportionally large water withdrawals compared to estimates of the in-stream flow requirements for habitat protection. The primary groundwater withdrawals in the study area include a water-supply well in the headwaters of the system and three water-supply wells in the coastal plain near the downstream end of the system. A steady-state groundwater flow model was used to understand the movement of water within the system, to evaluate the water budget and the effect of groundwater withdrawals on streamflows, and to understand streamflow depletion in relation to the State of Maine’s requirements to maintain in-stream flows for habitat protection.
\nDelineation of the simulated groundwater divides compared to the surface-water divides suggests that the groundwater divides in the headwater areas do not exactly correspond to the surface-water divides. Under both pumping and non-pumping conditions, groundwater flows from the headwaters of the Branch Brook watershed into the Mousam River watershed. Pumping in the Mousam River watershed captures a small amount of groundwater from the Branch Brook basin.
\nThe cumulative effect of groundwater withdrawals on base flows in two rivers in the study area (Branch Brook and the Merriland River) was evaluated using the groundwater flow model. Streamflow depletion in the headwaters of Branch Brook was 0.12 cubic feet per second (ft3/s) for the steady-state simulation, or about 10 percent of the average base flow at that location. Downstream on Branch Brook, the total streamflow depletion from all the wells was 0.59 ft3/s, or 3 percent of the average base flow at that location. In the Merriland River downstream from the Merriland River well, the total amount of streamflow depletion was 0.6 ft3/s, or about 7 percent of the average base flow.
\nThe groundwater model was used to evaluate several different scenarios that could affect streamflow and groundwater discharging to the rivers and streams in the study area. The scenarios were (1) no pumping from the water-supply wells; (2) current pumping from the water-supply wells, but simulated drought conditions (25 percent reduction in recharge); (3) current recharge, but with increased pumping from the large water-supply wells; and (4) drought conditions and increased pumping combined.
\nSimulations of increased pumping in the water-supply wells resulted in streamflow depletion in the headwaters of Branch Brook increasing to 16 percent of the headwater base flow. Simulated increases in the pumping in the coastal plain wells increased the amount of streamflow depletion to 6 percent of the flow in Branch Brook and to 8 percent of the flow in the Merriland River. The additional stress of a drought imposed on the model (25 percent less recharge) had a substantial impact on streamflows, as expected. If the simulated drought occurred simultaneously with an increase in pumping, the base flows would be reduced 48 percent in the headwaters of Branch Brook, compared to the no-pumping scenario. Downstream in Branch Brook, the total reduction in flow would be 29 percent of the simulated base flows in the no-pumping scenario, and in the Merriland River, the reduction would be 33 percent of the base flows in the no-pumping scenario.
\nThe study evaluated two different methods of calculating in-stream flow requirements for Branch Brook and the Merriland River—a set of statewide equations used to calculate monthly median flows and the MOVE.1 record-extension technique used on site-specific streamflow measurements. The August median in-stream flow requirement in the Merriland River was calculated as 7.18 ft3/s using the statewide equations but was 3.07 ft3/s using the MOVE.1 analysis. In Branch Brook, the August median in-stream flow requirements were calculated as 20.3 ft3/s using the statewide equations and 11.8 ft3/s using the MOVE.1 analysis. In each case, using site-specific data yields an estimate of in-stream flow that is much lower than an estimate the statewide equations provide.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145235","collaboration":"Prepared in cooperation with the Maine Geological Survey","usgsCitation":"Nielsen, M.G., and Locke, D.B., 2015, Simulation of groundwater flow and streamflow depletion in the Branch Brook, Merriland River, and parts of the Mousam River watersheds in southern Maine: U.S. Geological Survey Scientific Investigations Report 2014-5235, x, 78 p., https://doi.org/10.3133/sir20145235.","productDescription":"x, 78 p.","numberOfPages":"92","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-057435","costCenters":[{"id":371,"text":"Maine Water Science Center","active":true,"usgs":true}],"links":[{"id":298274,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145235.jpg"},{"id":298272,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5235/"},{"id":298273,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5235/pdf/sir2014-5235.pdf","text":"Report","size":"9.83 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"projection":"Universal Transverse Mercator projection","datum":"North American Datum of 1988","country":"United States","state":"Maine","otherGeospatial":"Branch Brook, Merriland River, Mousam River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -70.7571029663086,\n 43.303944586803205\n ],\n [\n -70.7571029663086,\n 43.4576541092803\n ],\n [\n -70.49789428710938,\n 43.4576541092803\n ],\n [\n -70.49789428710938,\n 43.303944586803205\n ],\n [\n -70.7571029663086,\n 43.303944586803205\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54f82cb0e4b02419550d99e0","contributors":{"authors":[{"text":"Nielsen, Martha G. 0000-0003-3038-9400 mnielsen@usgs.gov","orcid":"https://orcid.org/0000-0003-3038-9400","contributorId":4169,"corporation":false,"usgs":true,"family":"Nielsen","given":"Martha","email":"mnielsen@usgs.gov","middleInitial":"G.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":537485,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Locke, Daniel B.","contributorId":131153,"corporation":false,"usgs":false,"family":"Locke","given":"Daniel","email":"","middleInitial":"B.","affiliations":[{"id":7257,"text":"Maine Geological Survey","active":true,"usgs":false}],"preferred":false,"id":537486,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70175225,"text":"70175225 - 2015 - Empirical evaluation of the conceptual model underpinning a regional aquatic long-term monitoring program using causal modelling","interactions":[],"lastModifiedDate":"2016-08-03T12:49:34","indexId":"70175225","displayToPublicDate":"2015-03-04T06:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Empirical evaluation of the conceptual model underpinning a regional aquatic long-term monitoring program using causal modelling","docAbstract":"Conceptual models are an integral facet of long-term monitoring programs. Proposed linkages between drivers, stressors, and ecological indicators are identified within the conceptual model of most mandated programs. We empirically evaluate a conceptual model developed for a regional aquatic and riparian monitoring program using causal models (i.e., Bayesian path analysis). We assess whether data gathered for regional status and trend estimation can also provide insights on why a stream may deviate from reference conditions. We target the hypothesized causal pathways for how anthropogenic drivers of road density, percent grazing, and percent forest within a catchment affect instream biological condition. We found instream temperature and fine sediments in arid sites and only fine sediments in mesic sites accounted for a significant portion of the maximum possible variation explainable in biological condition among managed sites. However, the biological significance of the direct effects of anthropogenic drivers on instream temperature and fine sediments were minimal or not detected. Consequently, there was weak to no biological support for causal pathways related to anthropogenic drivers’ impact on biological condition. With weak biological and statistical effect sizes, ignoring environmental contextual variables and covariates that explain natural heterogeneity would have resulted in no evidence of human impacts on biological integrity in some instances. For programs targeting the effects of anthropogenic activities, it is imperative to identify both land use practices and mechanisms that have led to degraded conditions (i.e., moving beyond simple status and trend estimation). Our empirical evaluation of the conceptual model underpinning the long-term monitoring program provided an opportunity for learning and, consequently, we discuss survey design elements that require modification to achieve question driven monitoring, a necessary step in the practice of adaptive monitoring. We suspect our situation is not unique and many programs may suffer from the same inferential disconnect. Commonly, the survey design is optimized for robust estimates of regional status and trend detection and not necessarily to provide statistical inferences on the causal mechanisms outlined in the conceptual model, even though these relationships are typically used to justify and promote the long-term monitoring of a chosen ecological indicator. Our application demonstrates a process for empirical evaluation of conceptual models and exemplifies the need for such interim assessments in order for programs to evolve and persist.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2014.10.011","usgsCitation":"Irvine, K.M., Miller, S., Al-Chokhachy, R.K., Archer, E., Roper, B.B., and Kershner, J.L., 2015, Empirical evaluation of the conceptual model underpinning a regional aquatic long-term monitoring program using causal modelling: Ecological Indicators, v. 50, p. 8-23, https://doi.org/10.1016/j.ecolind.2014.10.011.","productDescription":"16 p.","startPage":"8","endPage":"23","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-053097","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":326044,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Colorado, Idaho, Montana, Nevada, Oregon, Utah, Washington, Wyoming","otherGeospatial":"Interior Columbia River Basin, Upper Missouri River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -104.19433593749999,\n 49.03786794532644\n ],\n [\n -106.2158203125,\n 38.34165619279593\n ],\n [\n -124.5849609375,\n 40.74725696280421\n ],\n [\n -124.541015625,\n 41.60722821271717\n ],\n [\n -124.62890625,\n 42.553080288955826\n ],\n [\n -124.76074218749999,\n 43.16512263158296\n ],\n [\n -124.4091796875,\n 43.96119063892024\n ],\n [\n -124.18945312500001,\n 45.42929873257377\n ],\n [\n -124.1455078125,\n 46.07323062540838\n ],\n [\n -124.45312499999999,\n 47.338822694822\n ],\n [\n -124.93652343749999,\n 48.1367666796927\n ],\n [\n -124.71679687499999,\n 48.45835188280866\n ],\n [\n -123.79394531249999,\n 48.3416461723746\n ],\n [\n -123.134765625,\n 48.48748647988415\n ],\n [\n -123.26660156249999,\n 48.777912755501845\n ],\n [\n -123.04687499999999,\n 48.80686346108517\n ],\n [\n -123.22265625000001,\n 49.03786794532644\n ],\n [\n -104.19433593749999,\n 49.03786794532644\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"50","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57a315bee4b006cb45558a79","contributors":{"authors":[{"text":"Irvine, Kathryn M. 0000-0002-6426-940X kirvine@usgs.gov","orcid":"https://orcid.org/0000-0002-6426-940X","contributorId":2218,"corporation":false,"usgs":true,"family":"Irvine","given":"Kathryn","email":"kirvine@usgs.gov","middleInitial":"M.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":644411,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Miller, Scott","contributorId":58387,"corporation":false,"usgs":true,"family":"Miller","given":"Scott","affiliations":[],"preferred":false,"id":644412,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":644413,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Archer, Erik","contributorId":173367,"corporation":false,"usgs":false,"family":"Archer","given":"Erik","email":"","affiliations":[{"id":27214,"text":"U.S.D.A. Forest Service, Forest Sciences Lab, 860 North 1200 East, Logan, UT","active":true,"usgs":false}],"preferred":false,"id":644414,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Roper, Brett B.","contributorId":120701,"corporation":false,"usgs":false,"family":"Roper","given":"Brett","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":644415,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"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":644416,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70173595,"text":"70173595 - 2015 - Occupancy modeling for improved accuracy and understanding of pathogen prevalence and dynamics","interactions":[],"lastModifiedDate":"2016-06-09T15:53:01","indexId":"70173595","displayToPublicDate":"2015-03-04T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Occupancy modeling for improved accuracy and understanding of pathogen prevalence and dynamics","docAbstract":"Most pathogen detection tests are imperfect, with a sensitivity < 100%, thereby resulting in the potential for a false negative, where a pathogen is present but not detected. False negatives in a sample inflate the number of non-detections, negatively biasing estimates of pathogen prevalence. Histological examination of tissues as a diagnostic test can be advantageous as multiple pathogens can be examined and providing important information on associated pathological changes to the host. However, it is usually less sensitive than molecular or microbiological tests for specific pathogens. Our study objectives were to 1) develop a hierarchical occupancy model to examine pathogen prevalence in spring Chinook salmonOncorhynchus tshawytscha and their distribution among host tissues 2) use the model to estimate pathogen-specific test sensitivities and infection rates, and 3) illustrate the effect of using replicate within host sampling on sample sizes required to detect a pathogen. We examined histological sections of replicate tissue samples from spring Chinook salmon O. tshawytscha collected after spawning for common pathogens seen in this population:Apophallus/echinostome metacercariae, Parvicapsula minibicornis, Nanophyetus salmincola/metacercariae, and Renibacterium salmoninarum. A hierarchical occupancy model was developed to estimate pathogen and tissue-specific test sensitivities and unbiased estimation of host- and organ-level infection rates. Model estimated sensitivities and host- and organ-level infections rates varied among pathogens and model estimated infection rate was higher than prevalence unadjusted for test sensitivity, confirming that prevalence unadjusted for test sensitivity was negatively biased. The modeling approach provided an analytical approach for using hierarchically structured pathogen detection data from lower sensitivity diagnostic tests, such as histology, to obtain unbiased pathogen prevalence estimates with associated uncertainties. Accounting for test sensitivity using within host replicate samples also required fewer individual fish to be sampled. This approach is useful for evaluating pathogen or microbe community dynamics when test sensitivity is <100%.
","language":"English","publisher":"PLOS One","doi":"10.1371/journal.pone.0116605","usgsCitation":"Colvin, M., Peterson, J., Kent, M.L., and Schreck, C.B., 2015, Occupancy modeling for improved accuracy and understanding of pathogen prevalence and dynamics: PLoS ONE, v. 10, no. 3, https://doi.org/10.1371/journal.pone.0116605.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-056718","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":472225,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0116605","text":"Publisher Index Page"},{"id":323433,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","issue":"3","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-03-04","publicationStatus":"PW","scienceBaseUri":"575a9334e4b04f417c27516c","contributors":{"authors":[{"text":"Colvin, Michael E.","contributorId":140975,"corporation":false,"usgs":false,"family":"Colvin","given":"Michael E.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":638334,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Peterson, James T. 0000-0002-7709-8590 james_peterson@usgs.gov","orcid":"https://orcid.org/0000-0002-7709-8590","contributorId":2111,"corporation":false,"usgs":true,"family":"Peterson","given":"James","email":"james_peterson@usgs.gov","middleInitial":"T.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":637383,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kent, Michael L.","contributorId":16693,"corporation":false,"usgs":true,"family":"Kent","given":"Michael","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":638335,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schreck, Carl B. 0000-0001-8347-1139 carl.schreck@usgs.gov","orcid":"https://orcid.org/0000-0001-8347-1139","contributorId":878,"corporation":false,"usgs":true,"family":"Schreck","given":"Carl","email":"carl.schreck@usgs.gov","middleInitial":"B.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":638336,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70140639,"text":"ofr20151029 - 2015 - Resilience and risk: a demographic model to inform conservation planning for polar bears","interactions":[],"lastModifiedDate":"2015-03-03T13:45:09","indexId":"ofr20151029","displayToPublicDate":"2015-03-03T14:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-1029","title":"Resilience and risk: a demographic model to inform conservation planning for polar bears","docAbstract":"Climate change is having widespread ecological effects, including loss of Arctic sea ice. This has led to listing of the polar bear (Ursus maritimus) and other ice-dependent marine mammals under the U.S. Endangered Species Act (ESA). Methods are needed to evaluate the effects of climate change on population persistence to inform recovery planning for listed species. For polar bears, this includes understanding interactions between climate and secondary factors, such as subsistence harvest, which provide economic, nutritional, or cultural value to humans.
\nWe developed a matrix-based demographic model for polar bears that can be used for population viability analysis and to evaluate the effects of human-caused removals. This model includes density-dependence (the potential for a declining environmental carrying capacity), density-independent limitation, and sex- and age-specific harvest vulnerabilities. We estimated values of adult female survival (0.93–0.96), recruitment (number of yearling cubs per adult female; 0.1–0.3), and carrying capacity (>250 animals) that must be maintained for a hypothetical population to achieve a 90-percent probability of persistence over 100 years.
\nWe also developed a state-dependent management framework, based on harvest theory and the potential biological removal method, by linking the demographic model to simulated population assessments. This framework can be used to estimate the maximum sustainable rate of human-caused removals, including subsistence harvest, which maintains a population at its maximum net productivity level. The framework also can be used to calculate a recommended sustainable harvest rate, which generally is lower than the maximum sustainable rate and depends on management objectives, the precision and frequency of population data, and risk tolerance. The historical standard 4.5-percent harvest rate for polar bears, at a 2:1 male-to-female ratio, is reasonable under many biological and management conditions, although lower or higher rates may be appropriate in some cases.
\nOur modeling results suggest that harvest of polar bears is unlikely to accelerate population declines that result from declining carrying capacity caused by sea-ice loss, provided that several conditions are met: (1) the sustainable harvest rate reflects the population’s intrinsic growth rate, and the corresponding harvest level is obtained by applying this rate to an estimate of population size; (2) the sustainable harvest rate reflects the quality of population data (e.g., lower harvest when data are poor); and (3) the level of human-caused removals can be adjusted. Finally, our results suggest that stopgap measures (e.g., further reduction or cessation of harvest when the population size is less than a critical threshold) may be necessary to minimize the incremental risk associated with harvest, if environmental conditions are deteriorating rapidly. We suggest that the demographic model and approaches presented here can serve as a template for conservation planning for polar bears and other species facing similar challenges.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151029","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Regehr, E.V., Wilson, R.H., Rode, K.D., and Runge, M.C., 2015, Resilience and risk: a demographic model to inform conservation planning for polar bears: U.S. Geological Survey Open-File Report 2015-1029, vi, 56 p., https://doi.org/10.3133/ofr20151029.","productDescription":"vi, 56 p.","numberOfPages":"66","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-060795","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":298250,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20151029.jpg"},{"id":298248,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2015/1029/"},{"id":298249,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1029/pdf/ofr2015-1029.pdf","size":"2.1 MB","linkFileType":{"id":1,"text":"pdf"}}],"publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54f6db2be4b02419550d3094","contributors":{"authors":[{"text":"Regehr, Eric V. 0000-0003-4487-3105","orcid":"https://orcid.org/0000-0003-4487-3105","contributorId":66364,"corporation":false,"usgs":false,"family":"Regehr","given":"Eric","email":"","middleInitial":"V.","affiliations":[{"id":12428,"text":"U. S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":541774,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wilson, Ryan H. 0000-0001-7740-7771","orcid":"https://orcid.org/0000-0001-7740-7771","contributorId":130989,"corporation":false,"usgs":false,"family":"Wilson","given":"Ryan","email":"","middleInitial":"H.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":541775,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rode, Karyn D. 0000-0002-3328-8202 krode@usgs.gov","orcid":"https://orcid.org/0000-0002-3328-8202","contributorId":5053,"corporation":false,"usgs":true,"family":"Rode","given":"Karyn","email":"krode@usgs.gov","middleInitial":"D.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":541776,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Runge, Michael C. 0000-0002-8081-536X mrunge@usgs.gov","orcid":"https://orcid.org/0000-0002-8081-536X","contributorId":3358,"corporation":false,"usgs":true,"family":"Runge","given":"Michael","email":"mrunge@usgs.gov","middleInitial":"C.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":541777,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ]}