{"pageNumber":"546","pageRowStart":"13625","pageSize":"25","recordCount":46677,"records":[{"id":38313,"text":"twri09A7.1 - 2014 - Chapter A7. Section 7.1. Fecal indicator bacteria","interactions":[],"lastModifiedDate":"2026-04-14T14:31:54.169658","indexId":"twri09A7.1","displayToPublicDate":"1994-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":336,"text":"Techniques of Water-Resources Investigations","code":"TWRI","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"09-A7.1","displayTitle":"Chapter A7. Section 7.1. Fecal Indicator Bacteria","title":"Chapter A7. Section 7.1. Fecal indicator bacteria","docAbstract":"<p>Fecal indicator bacteria are used to assess the microbiological quality of water because, although not typically disease causing, they are correlated with the presence of several waterborne disease-causing organisms. The concentration of indicator bacteria is a measure of water safety for body-contact recreation or for consumption. This report provides information on the equipment, sampling protocols, and identification, enumeration, and calculation procedures that are in standard use by U.S. Geological Survey (USGS) personnel for the collection of data on fecal indicator bacteria. Each chapter of the National Field Manual is published separately and revised periodically. Newly published and revised chapters will be announced on the USGS Home Page on the World Wide Web under 'New Publications of the U.S. Geological Survey.'</p>","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"National Field Manual for the Collection of Water-Quality Data. U.S. Geological Survey Techniques of Water-Resources Investigations, Book 9","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/twri09A7.1","usgsCitation":"Myers, D.N., Stoeckel, D.M., Bushon, R.N., Francy, D.S., and Brady A.M.G., 2014, Fecal indicator bacteria (ver. 2.1, revised May 2014): U.S. Geological Survey Techniques of Water-Resources Investigations 09–A7.1, 73 p., https://doi.org/10.3133/twri09A7.1.","productDescription":"Documents: 73 p., 73 p., 64 p.; Related Work","costCenters":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"links":[{"id":363225,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.er.usgs.gov/publication/tm9A0","text":"Techniques and Methods 9-A0","linkHelpText":"- General Introduction for the “National Field Manual for the Collection of Water-Quality Data”"},{"id":363187,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/twri/twri9a7/twri9a7_7.1_ver2.0_5-12-14.pdf","text":"Report February 2007 (Section 7.1)","linkHelpText":"- Version 2.0"},{"id":363188,"rank":4,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/twri/twri9a7/twri9a7_7.1_ver1.2.pdf","text":"Report November 2004 (Section 7.1)","linkHelpText":"- Version 1.2"},{"id":165252,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.er.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":363183,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/twri/twri9a7/twri9a7_7.1_ver2.1.pdf","text":"Report Chapter 7.1 - Version 2.1, May 2014","size":"622 KB","linkFileType":{"id":1,"text":"pdf"},"description":"TWRI 9A7.1","linkHelpText":"- Fecal Indicator Bacteria"}],"edition":"Version 1.2, Revised Nov 2004","contact":"<p><a href=\"https://www.usgs.gov/mission-areas/water-resources?qt-mission_areas_l2_landing_page_ta=0#qt-mission_areas_l2_landing_page_ta\" data-mce-href=\"https://www.usgs.gov/mission-areas/water-resources?qt-mission_areas_l2_landing_page_ta=0#qt-mission_areas_l2_landing_page_ta\">Water Mission Area</a><br>U.S. Geological Survey<br>12201 Sunrise Valley Drive<br>Reston, VA 20192</p><p>Email: <a href=\"mailto:nfm@usgs.gov\" data-mce-href=\"mailto:nfm@usgs.gov\">nfm@usgs.gov</a></p>","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e49e3e4b07f02db5e58ec","contributors":{"authors":[{"text":"Myers, Donna N. 0000-0001-6359-2865 dnmyers@usgs.gov","orcid":"https://orcid.org/0000-0001-6359-2865","contributorId":512,"corporation":false,"usgs":true,"family":"Myers","given":"Donna","email":"dnmyers@usgs.gov","middleInitial":"N.","affiliations":[{"id":503,"text":"Office of Water Quality","active":true,"usgs":true}],"preferred":true,"id":219590,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sylvester, Marc A.","contributorId":90706,"corporation":false,"usgs":true,"family":"Sylvester","given":"Marc","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":219591,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70174161,"text":"70174161 - 2013 - A manual for remote sensing of Maine lake clarity","interactions":[],"lastModifiedDate":"2021-04-02T16:51:06.997095","indexId":"70174161","displayToPublicDate":"2022-03-26T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"seriesTitle":{"id":8024,"text":"Technical Bulletin of the Maine Agricultural & Forest Experiment Station","active":true,"publicationSubtype":{"id":2}},"seriesNumber":"207","title":"A manual for remote sensing of Maine lake clarity","docAbstract":"<p><span>The purpose of this manual is to support use of satellite-based remote sensing for statewide lake water-quality monitoring in Maine. The authors describe step-by-step methods that combine Landsat and MODIS satellite data with field-collected Secchi disk data for statewide assessment of lake water clarity. Landsat can be simul­taneously used to assess more than Maine 1,000 lakes ≥ 8 ha, whereas MODIS can be used to assess a maximum of 364 lakes ≥ 100 ha (250-m image resolution) or 83 lakes ≥ 400 ha (500-m image resolution). Although the methods were specifically developed for Maine, other states or non-Maine agen­cies may find these methods as useful starting points in developing their own protocols for regional remote lake monitoring.</span></p>","language":"English","publisher":"Maine Agricultural and Forest Experiment Station","usgsCitation":"Ian M. 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McCullough","affiliations":[{"id":25572,"text":"University of Maine, Orono","active":true,"usgs":false}],"preferred":false,"id":641009,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Loftin, Cyndy 0000-0001-9104-3724 cyndy_loftin@usgs.gov","orcid":"https://orcid.org/0000-0001-9104-3724","contributorId":146427,"corporation":false,"usgs":true,"family":"Loftin","given":"Cyndy","email":"cyndy_loftin@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":641008,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sader, Steven A.","contributorId":171436,"corporation":false,"usgs":false,"family":"Sader","given":"Steven","email":"","middleInitial":"A.","affiliations":[{"id":25572,"text":"University of Maine, Orono","active":true,"usgs":false}],"preferred":false,"id":641010,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
,{"id":70045222,"text":"ofr20121205 - 2013 - Coal fields of the conterminous United States—National Coal Resource Assessment updated version","interactions":[],"lastModifiedDate":"2021-12-16T17:29:20.544054","indexId":"ofr20121205","displayToPublicDate":"2021-12-16T12:32:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-1205","displayTitle":"Coal fields of the conterminous United States—National Coal Resource Assessment updated version","title":"Coal fields of the conterminous United States—National Coal Resource Assessment updated version","docAbstract":"This map sheet with accompanying Geographic Information System (GIS) project is an update of the existing U.S. Geological Survey (USGS) Conterminous U.S. Coal Fields map. This update was compiled using data primarily from the USGS National Coal Resource Assessment (NCRA) and information from other published maps. The five regions examined by NCRA (Eastern, Gulf Coast, Interior, Rocky Mountain, and Northern Great Plains) constituted 93 percent of U.S. coal production at the time of the assessments. The map sheet shows aerial extent, rank, province, name (region and field), and age information, which are also attributes of the GIS project. Due to changing technological and economic constraints for coal usage, along with the potential for geologic carbon dioxide sequestration, this map sheet and the GIS component of this report do not differentiate between potentially minable coal and uneconomic coal. Additional figures on the map sheet show coal formations, current production by State, coal rank definitions, and charts showing historical trends of coal production.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121205","usgsCitation":"East, J.A., 2013, Coal fields of the conterminous United States—National Coal Resource Assessment updated version: U.S. Geological Survey Open-File Report 2012-1205, Map: 1 Sheet: 60 x 39 inches; Downloads Directory, https://doi.org/10.3133/ofr20121205.","productDescription":"Map: 1 Sheet: 60 x 39 inches; Downloads Directory","costCenters":[],"links":[{"id":270522,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20121205.png"},{"id":391168,"rank":5,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/of/2012/1205/Coal_Fields_Simplified.pdf","text":"Simplified presentation format map","size":"26.4 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Coal Fields of the Conterminous United States—National Coal Resource Assessment Updated Version in Simplified Presentation Format (2021)"},{"id":270520,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1205/pdf/Coal_Fields_Map.pdf","text":"Report","size":"44.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2012-1205"},{"id":270519,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1205/index.html"},{"id":270521,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2012/1205/Downloads"},{"id":391169,"rank":6,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/of/2012/1205/simplified-presentation-format.docx","text":"Simplified presentation format explanation","size":"12.5 KB"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -130.0,22.0 ], [ -130.0,53.0 ], [ -62.0,53.0 ], [ -62.0,22.0 ], [ -130.0,22.0 ] ] ] } } ] }","publicComments":"Scale: 1:5,000,000","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"515befd8e4b075500ee5c9fa","contributors":{"authors":[{"text":"East, Joseph A. 0000-0003-4226-9174 jeast@usgs.gov","orcid":"https://orcid.org/0000-0003-4226-9174","contributorId":2747,"corporation":false,"usgs":true,"family":"East","given":"Joseph","email":"jeast@usgs.gov","middleInitial":"A.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":477063,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70043821,"text":"sir20125282 - 2013 - Hydrogeology of the Susquehanna River valley-fill aquifer system and adjacent areas in eastern Broome and southeastern Chenango Counties, New York","interactions":[],"lastModifiedDate":"2021-11-17T01:53:35.677134","indexId":"sir20125282","displayToPublicDate":"2021-11-16T08:55:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-5282","displayTitle":"Hydrogeology of the Susquehanna River Valley-Fill Aquifer System and Adjacent Areas in Eastern Broome and Southeastern Chenango Counties, New York","title":"Hydrogeology of the Susquehanna River valley-fill aquifer system and adjacent areas in eastern Broome and southeastern Chenango Counties, New York","docAbstract":"The hydrogeology of the valley-fill aquifer system along a 32-mile reach of the Susquehanna River valley and adjacent areas was evaluated in eastern Broome and southeastern Chenango Counties, New York. The surficial geology, inferred ice-marginal positions, and distribution of stratified-drift aquifers were mapped from existing data. Ice-marginal positions, which represent pauses in the retreat of glacial ice from the region, favored the accumulation of coarse-grained deposits whereas more steady or rapid ice retreat between these positions favored deposition of fine-grained lacustrine deposits with limited coarse-grained deposits at depth. Unconfined aquifers with thick saturated coarse-grained deposits are the most favorable settings for water-resource development, and three several-mile-long sections of valley were identified (mostly in Broome County) as potentially favorable: (1) the southernmost valley section, which extends from the New York–Pennsylvania border to about 1 mile north of South Windsor, (2) the valley section that rounds the west side of the umlaufberg (an isolated bedrock hill within a valley) north of Windsor, and (3) the east–west valley section at the Broome County–Chenango County border from Nineveh to East of Bettsburg (including the lower reach of the Cornell Brook valley). Fine-grained lacustrine deposits form extensive confining units between the unconfined areas, and the water-resource potential of confined aquifers is largely untested. Recharge, or replenishment, of these aquifers is dependent not only on infiltration of precipitation directly on unconfined aquifers, but perhaps more so from precipitation that falls in adjacent upland areas. Surface runoff and shallow groundwater from the valley walls flow downslope and recharge valley aquifers. Tributary streams that drain upland areas lose flow as they enter main valleys on permeable alluvial fans. This infiltrating water also recharges valley aquifers. Current (2012) use of water resources in the area is primarily through domestic wells, most of which are completed in fractured bedrock in upland areas. A few villages in the Susquehanna River valley have supply wells that draw water from beneath alluvial fans and near the Susquehanna River, which is a large potential source of water from induced infiltration.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125282","collaboration":"Prepared in cooperation with New York State Department of Environmental Conservation","usgsCitation":"Heisig, P.M., 2013, Hydrogeology of the Susquehanna River valley-fill aquifer system and adjacent areas in eastern Broome and southeastern Chenango Counties, New York: U.S. Geological Survey Scientific Investigations Report 2012–5282, 21 p., at https://pubs.usgs.gov/sir/2012/5282.","productDescription":"vii, 21 p.; 1 Appendix; Map: 1 Sheet: 30.50 x 38.00 inches","startPage":"i","endPage":"21","numberOfPages":"34","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":267842,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5282.gif"},{"id":267840,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2012/5282/appendix1/Appendix%201.xlsx"},{"id":267839,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5282/"},{"id":267841,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2012/5282/plate.html"}],"scale":"24000","country":"United States","state":"New York","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -79.76,40.48 ], [ -79.76,45.02 ], [ -71.85,45.02 ], [ -71.85,40.48 ], [ -79.76,40.48 ] ] ] } } ] }","contact":"<p><a href=\"mailto:dc_ny@usgs.gov\" data-mce-href=\"mailto:dc_ny@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/centers/ny-water\" data-mce-href=\"https://www.usgs.gov/centers/ny-water\">New York Water Science Center</a><br>U.S. Geological Survey<br>425 Jordan Road<br>Troy, NY 12180–8349</p>","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"publishedDate":"2013-02-20","noUsgsAuthors":false,"publicationDate":"2013-02-20","publicationStatus":"PW","scienceBaseUri":"5125f087e4b09d00759cd058","contributors":{"authors":[{"text":"Heisig, Paul M. 0000-0003-0338-4970 pmheisig@usgs.gov","orcid":"https://orcid.org/0000-0003-0338-4970","contributorId":793,"corporation":false,"usgs":true,"family":"Heisig","given":"Paul","email":"pmheisig@usgs.gov","middleInitial":"M.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":474273,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70048771,"text":"ds69FF - 2013 - Supporting data for the U.S. Geological Survey 2012 world assessment of undiscovered oil and gas resources","interactions":[],"lastModifiedDate":"2020-03-27T09:50:57","indexId":"ds69FF","displayToPublicDate":"2020-03-27T11:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"69","chapter":"FF","displayTitle":"Supporting Data for the U.S. Geological Survey 2012 World Assessment of Undiscovered Oil and Gas Resources","title":"Supporting data for the U.S. Geological Survey 2012 world assessment of undiscovered oil and gas resources","docAbstract":"This report provides information pertaining to the 2012 U.S. Geological Survey assessment of undiscovered, technically recoverable conventional oil and gas resources of the world, exclusive of the United States. Some of the results were previously published, mostly in USGS fact sheet series.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds69FF","usgsCitation":"U.S. Geological Survey World Conventional Resources Assessment Team, 2013, Supporting data for the U.S. Geological Survey 2012 world assessment of undiscovered oil and gas resources: U.S. Geological Survey Digital Data Series DDS–69–FF, various pages, https://doi.org/10.3133/ds69FF.","productDescription":"Readme; Downloads Directory","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":278671,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/dds69FF.jpg"},{"id":371099,"rank":6,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/dds/dds-069/dds-069-ff/tabtables.zip","text":"Tab tables","size":"901 KB","linkFileType":{"id":6,"text":"zip"}},{"id":371098,"rank":5,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/dds/dds-069/dds-069-ff/GIS.zip","text":"GIS","size":"3.08MB","linkFileType":{"id":6,"text":"zip"}},{"id":278668,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/dds/dds-069/dds-069-ff/ReadMe.txt","text":"Read Me","size":"94.7 KB","linkFileType":{"id":2,"text":"txt"}},{"id":371100,"rank":7,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/dds/dds-069/dds-069-ff/montecarlo.zip","text":"Monte Carlo Outputs","linkFileType":{"id":6,"text":"zip"}},{"id":371096,"rank":3,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/dds/dds-069/dds-069-ff/geodatabase.zip","text":"Geo database","size":"102 MB","linkFileType":{"id":6,"text":"zip"}},{"id":371097,"rank":4,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/dds/dds-069/dds-069-ff/exceltables.zip","text":"Excel tables","size":"3.43 MB","linkFileType":{"id":6,"text":"zip"}}],"contact":"<p><a href=\"https://www.usgs.gov/energy-and-minerals/energy-resources-program/\" data-mce-href=\"https://www.usgs.gov/energy-and-minerals/energy-resources-program/\">Central Energy Resources Science Center</a><br>U.S. Geological Survey<br>Box 25046, MS-939<br>Denver Federal Center<br>Denver, CO 80225-0046<br></p>","publishedDate":"2013-11-01","noUsgsAuthors":false,"publicationDate":"2013-11-01","publicationStatus":"PW","scienceBaseUri":"5278c215e4b0c04ac3417aa1","contributors":{"authors":[{"text":"World Conventional Resources Assessment Team, USGS","contributorId":17127,"corporation":false,"usgs":true,"family":"World Conventional Resources Assessment Team","given":"USGS","email":"","affiliations":[],"preferred":false,"id":485602,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70045244,"text":"ofr20121247 - 2013 - The Shoreline Management Tool—An ArcMap tool for analyzing water depth, inundated area, volume, and selected habitats, with an example for the lower Wood River Valley, Oregon","interactions":[],"lastModifiedDate":"2020-01-13T06:18:45","indexId":"ofr20121247","displayToPublicDate":"2020-01-10T14:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-1247","displayTitle":"The Shoreline Management Tool—An ArcMap Tool for Analyzing Water Depth, Inundated Area, Volume, and Selected Habitats, with an Example for the Lower Wood River Valley, Oregon","title":"The Shoreline Management Tool—An ArcMap tool for analyzing water depth, inundated area, volume, and selected habitats, with an example for the lower Wood River Valley, Oregon","docAbstract":"<p>The Shoreline Management Tool is a geographic information system (GIS) based program developed to assist water- and land-resource managers in assessing the benefits and effects of changes in surface-water stage on water depth, inundated area, and water volume. Additionally, the Shoreline Management Tool can be used to identify aquatic or terrestrial habitat areas where conditions may be suitable for specific plants or animals as defined by user-specified criteria including water depth, land-surface slope, and land-surface aspect. The tool can also be used to delineate areas for use in determining a variety of hydrologic budget components such as surface-water storage, precipitation, runoff, or evapotranspiration.</p><p>The Shoreline Management Tool consists of two parts, a graphical user interface for use with Esri™ ArcMap™ GIS software to interact with the user to define scenarios and map results, and a spreadsheet in Microsoft® Excel® developed to display tables and graphs of the results. The graphical user interface allows the user to define a scenario consisting of an inundation level (stage), land areas (parcels), and habitats (areas meeting user-specified conditions) based on water depth, slope, and aspect criteria. The tool uses data consisting of land-surface elevation, tables of stage/volume and stage/area, and delineated parcel boundaries to produce maps (data layers) of inundated areas and areas that meet the habitat criteria. The tool can be run in a Single-Time Scenario mode or in a Time-Series Scenario mode, which uses an input file of dates and associated stages. The spreadsheet part of the tool uses a macro to process the results from the graphical user interface to create tables and graphs of inundated water volume, inundated area, dry area, and mean water depth for each land parcel based on the user-specified stage. The macro also creates tables and graphs of the area, perimeter, and number of polygons comprising the user-specified habitat areas within each parcel.</p><p>The Shoreline Management Tool is highly transferable, using easily generated or readily available data. The capabilities of the tool are demonstrated using data from the lower Wood River Valley adjacent to Upper Klamath and Agency Lakes in southern Oregon.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121247","collaboration":"Prepared in cooperation with the Bureau of Land Management","usgsCitation":"Snyder, D.T., Haluska, T.L., and Respini-Irwin, D., 2013, The Shoreline Management Tool—An ArcMap tool for analyzing water depth, inundated area, volume, and selected habitats, with an example for the lower Wood River Valley, Oregon: U.S. Geological Survey Open-File Report 2012–1247, 86 p. (Also available at https://pubs.usgs.gov/of/2012/1247/.)","productDescription":"Report: viii, 86 p.; 2 Videos: 3 minutes; Companion File","numberOfPages":"98","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":270535,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20121247.jpg","text":"Report"},{"id":371153,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2012/1247/videos.zip","text":"Videos","size":"45.4 MB","linkFileType":{"id":6,"text":"zip"}},{"id":270531,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1247/ofr20121247.pdf","text":"Report","size":"9.09 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2012-1247"},{"id":371154,"rank":4,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2012/1247/faq.pdf","text":"Shoreline Management Tool—Frequently Asked Questions","size":"105 KB","linkFileType":{"id":1,"text":"pdf"}},{"id":371166,"rank":5,"type":{"id":21,"text":"Referenced Work"},"url":"https://water.usgs.gov/GIS/dsdl/ShorelineManagementTool_OFR2012-1247_v20130410.zip","text":"Generic version","size":"39 MB","linkFileType":{"id":6,"text":"zip"},"linkHelpText":" - Intended for use in any area. Required input data must be prepared by the users as described in the report. Example Python scripts are provided to assist with the data preparation. Includes all ancillary files except those specific to the lower Wood River Valley example."},{"id":371167,"rank":6,"type":{"id":21,"text":"Referenced Work"},"url":"https://water.usgs.gov/GIS/dsdl/ShorelineManagementTool_NAVD88_OFR2012-1247_v20130410.zip","text":"Example version for the Lower Wood River Valley, Oregon - NAVD88","size":"1.9 GB","linkFileType":{"id":6,"text":"zip"},"linkHelpText":" - Contains all required data for use in the lower Wood River Valley of southern Oregon. Ready to run. Utilizes the North American Vertical Datum of 1988 (NAVD88) for elevation reference. Useful for training purposes or examination of input datasets and output results. Includes all ancillary files."},{"id":371168,"rank":7,"type":{"id":21,"text":"Referenced Work"},"url":"https://water.usgs.gov/GIS/dsdl/ShorelineManagementTool_NGVD29_OFR2012-1247_v20130410.zip","text":"Example version for the Lower Wood River Valley, Oregon - NGVD29/UKLVD","size":"2.0 GB","linkFileType":{"id":6,"text":"zip"},"linkHelpText":" - Contains all required data for use in the lower Wood River Valley of southern Oregon. Ready to run. Utilizes the National Geodetic Vertical Datum of 1929 (NGVD29) for elevation reference. Also contains data for use with the Upper Klamath Lake Vertical Datum (UKLVD). Useful for training purposes or examination of input datasets and output results. Includes all ancillary files."}],"country":"United States","state":"Oregon","otherGeospatial":"Wood River Valley","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.61,42.0 ], [ -124.61,46.29 ], [ -116.46,46.29 ], [ -116.46,42.0 ], [ -124.61,42.0 ] ] ] } } ] }","contact":"<p><a href=\"https://www.usgs.gov/centers/or-water\" data-mce-href=\"https://www.usgs.gov/centers/or-water\">Oregon Water Science Center</a><br>U.S. Geological Survey<br>2130 SW 5th Avenue<br>Portland, Oregon 97201<br><br><a href=\"http://or.water.usgs.gov/proj/shoreline/maillist.html\" data-mce-href=\"http://or.water.usgs.gov/proj/shoreline/maillist.html\">Mailing List</a><br>Request to be notified of updates or<br>receive useful information about the<br>Shoreline Management Tool</p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>The Shoreline Management Tool</li><li>An Example for the Lower Wood River Valley, Oregon</li><li>Acknowledgments</li><li>References Cited</li><li>Appendix A. Shoreline Management Tool User’s Guide</li><li>Appendix B. Preparation of Input Data for use with the Shoreline Management Tool</li><li>Appendix C. Data Files for the Lower Wood River Valley for Use with the Shoreline Management Tool</li><li>Appendix D. Example Python Programming Language Scripts to Automate Data Preparation for the Shoreline Management Tool</li></ul>","publishedDate":"2013-04-03","revisedDate":"2013-04-26","noUsgsAuthors":false,"publicationDate":"2013-04-03","publicationStatus":"PW","scienceBaseUri":"515d4162e4b0803bd2eec4ff","contributors":{"authors":[{"text":"Snyder, Daniel T. dtsnyder@usgs.gov","contributorId":820,"corporation":false,"usgs":true,"family":"Snyder","given":"Daniel","email":"dtsnyder@usgs.gov","middleInitial":"T.","affiliations":[],"preferred":true,"id":477119,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haluska, Tana 0000-0001-6307-4769 thaluska@usgs.gov","orcid":"https://orcid.org/0000-0001-6307-4769","contributorId":1708,"corporation":false,"usgs":true,"family":"Haluska","given":"Tana","email":"thaluska@usgs.gov","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":477120,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Respini-Irwin, Darius","contributorId":51177,"corporation":false,"usgs":true,"family":"Respini-Irwin","given":"Darius","email":"","affiliations":[],"preferred":false,"id":477121,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70046421,"text":"sir20135076 - 2013 - A one-dimensional diffusion analogy model for estimation of tide heights in selected tidal marshes in Connecticut","interactions":[],"lastModifiedDate":"2019-12-30T08:43:11","indexId":"sir20135076","displayToPublicDate":"2019-12-30T09:20:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-5076","displayTitle":"A One-Dimensional Diffusion Analogy Model for Estimation of Tide Heights in Selected Tidal Marshes in Connecticut","title":"A one-dimensional diffusion analogy model for estimation of tide heights in selected tidal marshes in Connecticut","docAbstract":"<p>A one-dimensional diffusion analogy model for estimating tide heights in coastal marshes was developed and calibrated by using data from previous tidal-marsh studies. The method is simpler to use than other one- and two-dimensional hydrodynamic models because it does not require marsh depth and tidal prism information; however, the one-dimensional diffusion analogy model cannot be used to estimate tide heights, flow velocities, and tide arrival times for tide conditions other than the highest tide for which it is calibrated. Limited validation of the method indicates that it has an accuracy within 0.3 feet. The method can be applied with limited calibration information that is based entirely on remote sensing or geographic information system data layers. The method can be used to estimate high-tide heights in tidal wetlands drained by tide gates where tide levels cannot be observed directly by opening the gates without risk of flooding properties and structures. A geographic information system application of the method is demonstrated for Sybil Creek marsh in Branford, Connecticut. The tidal flux into this marsh is controlled by two tide gates that prevent full tidal inundation of the marsh. The method application shows reasonable tide heights for the gates-closed condition (the normal condition) and the one-gate-open condition on the basis of comparison with observed heights. The condition with all tide gates open (two gates) was simulated with the model; results indicate where several structures would be flooded if the gates were removed as part of restoration efforts or if the tide gates were to fail.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135076","collaboration":"Prepared in cooperation with the Connecticut Department of Energy and Environmental Protection","usgsCitation":"Bjerklie, D.M., O’Brien, Kevin, and Rozsa, Ron, 2013, A one-dimensional diffusion analogy model for estimation of tide heights in selected tidal marshes in Connecticut (ver. 1.1, December 2019): U.S. Geological Survey Scientific Investigations Report 2013–5076, 17 p., https://doi.org/10.3133/sir20135076.","productDescription":"iv, 17 p.","numberOfPages":"26","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":273622,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5076/index.html"},{"id":370389,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2013/5076/versionhist.txt","size":"485 B","linkFileType":{"id":2,"text":"txt"}},{"id":273623,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5076/sir20135076.pdf","text":"Report","size":"3.60 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2013-5076"},{"id":273624,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2013/5076/coverthb2.jpg"}],"country":"United States","state":"Connecticut","otherGeospatial":"Leetes Island, Pine Creek, Sybil Creek, Wilson Cove Marshes","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -73.5,41 ], [ -73.5,41.6 ], [ -72.3,41.6 ], [ -72.3,41 ], [ -73.5,41 ] ] ] } } ] }","edition":"Version 1.1: December 30, 2019; Version 1.0 June 11, 2013","contact":"<p><a href=\"mailto:dc_nweng@usgs.gov\" data-mce-href=\"mailto:dc_nweng@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/centers/new-england-water\" data-mce-href=\"https://www.usgs.gov/centers/new-england-water\">New England Water Science Center</a><br>U.S. Geological Survey<br>10 Bearfoot Road<br>Northborough, MA 01532</p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Modeling Method and Calibration</li><li>Method Validation and Application for Sybil Creek</li><li>Summary and Conclusions</li><li>Acknowledgments</li><li>References Cited</li></ul>","publishedDate":"2013-06-11","revisedDate":"2019-12-30","noUsgsAuthors":false,"publicationDate":"2013-06-11","publicationStatus":"PW","scienceBaseUri":"51b838d7e4b03203c522b17e","contributors":{"authors":[{"text":"Bjerklie, David M. 0000-0002-9890-4125 dmbjerkl@usgs.gov","orcid":"https://orcid.org/0000-0002-9890-4125","contributorId":3589,"corporation":false,"usgs":true,"family":"Bjerklie","given":"David","email":"dmbjerkl@usgs.gov","middleInitial":"M.","affiliations":[{"id":196,"text":"Connecticut Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":479643,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"O’Brien, Kevin","contributorId":22662,"corporation":false,"usgs":true,"family":"O’Brien","given":"Kevin","email":"","affiliations":[],"preferred":false,"id":479645,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rozsa, Ron","contributorId":15918,"corporation":false,"usgs":true,"family":"Rozsa","given":"Ron","email":"","affiliations":[],"preferred":false,"id":479644,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70047202,"text":"ds749 - 2013 - Data entry module and manuals for the Land Treatment Digital Library","interactions":[{"subject":{"id":70047202,"text":"ds749 - 2013 - Data entry module and manuals for the Land Treatment Digital Library","indexId":"ds749","publicationYear":"2013","noYear":false,"displayTitle":"Data Entry Module and Manuals for the Land Treatment Digital Library","title":"Data entry module and manuals for the Land Treatment Digital Library"},"predicate":"SUPERSEDED_BY","object":{"id":70057792,"text":"ds806 - 2013 - Land Treatment Digital Library","indexId":"ds806","publicationYear":"2013","noYear":false,"title":"Land Treatment Digital Library"},"id":1}],"supersededBy":{"id":70057792,"text":"ds806 - 2013 - Land Treatment Digital Library","indexId":"ds806","publicationYear":"2013","noYear":false,"title":"Land Treatment Digital Library"},"lastModifiedDate":"2025-09-26T17:31:32.088853","indexId":"ds749","displayToPublicDate":"2019-10-03T08:55:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"749","displayTitle":"Data Entry Module and Manuals for the Land Treatment Digital Library","title":"Data entry module and manuals for the Land Treatment Digital Library","docAbstract":"<p>Across the country, public land managers make decisions each year that influence landscapes and ecosystems within their jurisdictions. Many of these decisions involve vegetation manipulations, which often are referred to as land treatments. These treatments include removal or alteration of plant biomass, seeding of burned areas, application of herbicides, and other activities. Data documenting these land treatments usually are stored at local management offices in various formats. Therefore, anyone interested in the types and effects of land treatments across multiple jurisdictions must first assemble the information, which can be difficult if data discovery and organization involve multiple local offices. A centralized system for storing and accessing the data helps inform land managers when making policy and management considerations and assists scientists in developing sampling designs and studies.</p><p>The Land Treatment Digital Library (LTDL) was created by the U.S. Geological Survey (USGS) as a comprehensive database incorporating tabular data, documentation, photographs, and spatial data about land treatments in a single system. It was developed over a period of several years and refined based on feedback from partner agencies and stakeholders. Currently, Bureau of Land Management (BLM) land treatment data are being entered by USGS personnel as part of a memorandum of understanding between the USGS and BLM. The LTDL has a website maintained by the USGS Forest and Rangeland Ecosystem Science Center where LTDL data can be viewed <a data-mce-href=\"https://www.usgs.gov/apps/ltdl\" href=\"https://www.usgs.gov/apps/ltdl\">https://www.usgs.gov/apps/ltdl</a>.</p><p>The resources and information provided in this data series allow other agencies, organizations, and individuals to download an empty, stand-alone LTDL database to individual or networked computers. Data entered in these databases may be submitted to the USGS for possible inclusion in the online LTDL.</p><p>Multiple computer programs are used to accomplish the objective of the LTDL. The support of an information-technology specialist or professionals familiar with Microsoft Access™, ESRI’s ArcGIS™, Python, Adobe Acrobat Professional™, and computer settings is essential when installing and operating the LTDL. After the program is operational, a critical element for successful data entry is an understanding of the difference between database tables and forms, and how to edit data in both formats. Complete instructions accompany the program, and they should be followed carefully to ensure the setup and operation of the database goes smoothly.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds749","usgsCitation":"Welty, J.L., and Pilliod, D.S., 2013, Data entry module and manuals for the Land Treatment Digital Library: U.S. Geological Survey Data Series 749, https://pubs.usgs.gov/ds/749.","productDescription":"Pamphlet: 56 p.; 5 Companion Files; Metadata","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":275362,"rank":7,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/749/data/ds749_LTDL%20User%20Guides%20for%20ArcGIS%2010.0.zip","size":"5.55 MB","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- Land Treatment Digital Library User Guides for ArcGIS 10.0"},{"id":275363,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/749/data/ds749_LTDL%20User%27s%20Manual%20and%20Installation%20Instructions%20Arc10.1.pdf","size":"4.29 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Land Treatment Digital Library User Guides for ArcGIS 10.1"},{"id":275364,"rank":6,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/749/data/ds749_LTDL%20User%20Guides%20for%20ArcGIS%2010.1.zip","size":"5.55 MB","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- Land Treatment Digital Library User Guides for ArcGIS 10.1"},{"id":275360,"rank":4,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/749/data/ds749_LTDL%20User%27s%20Manual%20and%20Installation%20Instructions%20Arc10.0.pdf","size":"4.19 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Land Treatment Digital Library User Guides for ArcGIS 10.0"},{"id":275366,"rank":8,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/ds/749/data/ds749_LTDL_metadata.zip","size":"30.1 KB","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- Land Treatment Digital Library Metadata"},{"id":275361,"rank":5,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/749/data/ds749_LTDL_Data_10.0.zip","size":"913 MB","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- Land Treatment Digital Library Data 10.0"},{"id":275365,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/749/data/ds749_LTDL_Data_10.1.zip","size":"942 MB","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- Land Treatment Digital Library Data 10.1"},{"id":275367,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds749.png"}],"contact":"<p><a href=\"https://www.usgs.gov/centers/fresc/\" data-mce-href=\"https://www.usgs.gov/centers/fresc/\">Forest and Rangeland Ecosystem Science Center (FRESC)</a><br>U.S. Geological Survey<br>777 NW 9th Street<br>Corvallis, Oregon 97330</p>","publishedDate":"2013-07-24","noUsgsAuthors":false,"publicationDate":"2013-07-24","publicationStatus":"PW","scienceBaseUri":"51f253e9e4b0279fe2e1bfd1","contributors":{"authors":[{"text":"Welty, Justin L.","contributorId":80558,"corporation":false,"usgs":true,"family":"Welty","given":"Justin L.","affiliations":[],"preferred":false,"id":481344,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pilliod, David S.","contributorId":101760,"corporation":false,"usgs":true,"family":"Pilliod","given":"David S.","affiliations":[],"preferred":false,"id":481345,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70057792,"text":"ds806 - 2013 - Land Treatment Digital Library","interactions":[{"subject":{"id":70047202,"text":"ds749 - 2013 - Data entry module and manuals for the Land Treatment Digital Library","indexId":"ds749","publicationYear":"2013","noYear":false,"displayTitle":"Data Entry Module and Manuals for the Land Treatment Digital Library","title":"Data entry module and manuals for the Land Treatment Digital Library"},"predicate":"SUPERSEDED_BY","object":{"id":70057792,"text":"ds806 - 2013 - Land Treatment Digital Library","indexId":"ds806","publicationYear":"2013","noYear":false,"title":"Land Treatment Digital Library"},"id":1}],"lastModifiedDate":"2025-09-26T17:34:57.397898","indexId":"ds806","displayToPublicDate":"2019-10-02T11:35:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"806","title":"Land Treatment Digital Library","docAbstract":"<p>The Land Treatment Digital Library (LTDL) was created by the U.S. Geological Survey to catalog legacy land treatment information on Bureau of Land Management lands in the western United States. The LTDL can be used by federal managers and scientists for compiling information for data-calls, producing maps, generating reports, and conducting analyses at varying spatial and temporal scales. The LTDL currently houses thousands of treatments from BLM lands across 10 states. Users can browse a map to find information on individual treatments, perform more complex queries to identify a set of treatments, and view graphs of treatment summary statistics.&nbsp;</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds806","usgsCitation":"Pilliod, D., and Welty, J., 2013, Land Treatment Digital Library: U.S. Geological Survey Data Series 806, HTML site, https://doi.org/10.3133/ds806.","productDescription":"HTML site","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-052268","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":438777,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P98OBOLS","text":"USGS data release","linkHelpText":"USGS Land Treatment Digital Library Data Release: A centralized archive for land treatment tabular and spatial data (ver. 7.0, September 2024)"},{"id":279964,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://www.usgs.gov/apps/ltdl"},{"id":279965,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds806.jpg"},{"id":279963,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/806/"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"529dac18e4b0516126f66b57","contributors":{"authors":[{"text":"Pilliod, David S. 0000-0003-4207-3518 dpilliod@usgs.gov","orcid":"https://orcid.org/0000-0003-4207-3518","contributorId":161,"corporation":false,"usgs":true,"family":"Pilliod","given":"David S.","email":"dpilliod@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":false,"id":486876,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Welty, Justin L.","contributorId":80558,"corporation":false,"usgs":true,"family":"Welty","given":"Justin L.","affiliations":[],"preferred":false,"id":486877,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70045402,"text":"cir1383C - 2013 - U.S. Geological Survey ecosystems science strategy—Advancing discovery and application through collaboration","interactions":[],"lastModifiedDate":"2019-10-01T10:41:55","indexId":"cir1383C","displayToPublicDate":"2019-10-01T11:45:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":307,"text":"Circular","code":"CIR","onlineIssn":"2330-5703","printIssn":"1067-084X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1383","chapter":"C","displayTitle":"U.S. Geological Survey Ecosystems Science Strategy— Advancing Discovery and Application through Collaboration","title":"U.S. Geological Survey ecosystems science strategy—Advancing discovery and application through collaboration","docAbstract":"<h1>Executive Summary</h1><p>Ecosystem science is critical to making informed decisions about natural resources that can sustain our Nation’s economic and environmental well-being. Resource managers and policymakers are faced with countless decisions each year at local, regional, and national levels on issues as diverse as renewable and nonrenewable energy development, agriculture, forestry, water supply, and resource allocations at the urban-rural interface. The urgency for sound decisionmaking is increasing dramatically as the world is being transformed at an unprecedented pace and in uncertain directions. Environmental changes are associated with natural hazards, greenhouse gas emissions, and increasing demands for water, land, food, energy, mineral, and living resources. At risk is the Nation’s environmental capital, the goods and services provided by resilient ecosystems that are vital to the health and wellbeing of human societies. Ecosystem science—the study of systems of organisms interacting with their environment and the consequences of natural and human-induced change on these systems—is necessary to inform decisionmakers as they develop policies to adapt to these changes.</p><p>This Ecosystems Science Strategy is built on a framework that includes basic and applied science. It highlights the critical roles that U.S. Geological Survey (USGS) scientists and partners can play in building scientific understanding and providing timely information to decisionmakers. The strategy underscores the connection between scientific discoveries and the application of new knowledge, and it integrates ecosystem science and decisionmaking, producing new scientific outcomes to assist resource managers and providing public benefits. We envision the USGS as a leader in integrating scientific information into decisionmaking processes that affect the Nation’s natural resources and human well-being.</p><p>The USGS is uniquely positioned to play a pivotal role in ecosystem science. With its wide range of expertise, the Bureau can bring holistic, cross-scale, interdisciplinary capabilities to the design and conduct of monitoring, research, and modeling and to new technologies for data collection, management, and visualization. Collectively, these capabilities can be used to reveal ecological patterns and processes, explain how and why ecosystems change, and forecast change over different spatial and temporal scales. USGS science can provide managers with options and decision-support tools to use resources sustainably. The USGS has long-standing, collaborative relationships with the Department of the Interior (DOI) and other partners in the natural sciences, in both conducting science and applying the results. The USGS engages these partners in cooperative investigations that otherwise would lack the necessary support or be too expensive for a single bureau to conduct.</p><p>The heart of this strategy is a framework for USGS ecosystems science that focuses on five long-term goals, which are seen as interconnected components that reinforce our vision of the USGS providing science that is at the forefront of decisionmaking:</p><ul><li>Improve understanding of ecosystem structure, function, and processes. The focus for this goal is an understanding of how ecosystems work, including the dynamics of species, their populations, interactions, and genetics, and how they change across spatial and temporal scales.</li><li>Advance understanding of how drivers influence ecosystem change. The challenges here are explaining the drivers of ecosystem change, their spatio-temporal patterns, their uncertainties and interactions, and their influence on ecosystem processes and dynamics.</li><li>Improve understanding of the services that ecosystems provide to society. Here the emphasis is on the measurement of environmental capital and ecosystem services, and the identification of sources and patterns of change in space and time.</li><li>Develop tools, technologies, and capacities to inform decisionmaking about ecosystems. This includes developing new technologies and approaches for conducting applications-oriented ecosystem science. A principal challenge will be how to quantify uncertainty and incorporate it in decision analysis.</li><li>Apply science to enhance strategies for management, conservation, and restoration of ecosystems. These challenges include development of novel approaches to monitoring, assessment, and restoration of ecosystems; new methods to address species of concern and communities at risk; and innovations in decision analysis and support to address imminent ecosystem changes or those that are underway.</li></ul><p>Closely integrated with the five goals are four strategic approaches that provide the path forward for the USGS Ecosystems Mission Area. These approaches cross-cut all of the goals and are seen as essential to the implementation of this strategy:</p><ul><li>Assess information needs for ecosystem science through enhanced partnerships. Work with the DOI and other agencies and institutions to identify, design, and implement priority decision-driven ecological research.</li><li>Promote the use of interdisciplinary ecosystem science. Design and conduct interdisciplinary process-oriented research in ecosystem science.</li><li>Enhance modeling and forecasting. Build models to forecast ecosystem change, assess future management scenarios, and reduce uncertainties through an adaptive learning process.</li><li>Support decisionmaking. Use quantitative approaches to assess the vulnerabilities of ecosystems, habitats, and species, and evaluate strategies for adaptation, restoration, and sustainable management.</li></ul><p>Following the four strategic approaches are a set of proposed actions that represent a sampling of specific USGS activities that align with this strategy and that address the Nation’s most pressing environmental needs.</p><p>The strategy emphasizes coordination of activities across the USGS mission areas pursuant to these goals. Ecosystem science is inherently interdisciplinary and requires a broad perspective that incorporates the biological and physical sciences, climate science, information technology, and scientific capacity in mission areas across the Bureau. With its emphasis on coordination, this strategy can provide a critical underpinning for integrated science efforts with scientists from multiple mission areas of the USGS working together. Of course, the USGS will continue to conduct discipline-specific and interdisciplinary investigations, and both will continue to be vital parts of the ecosystem science portfolio.</p><p>Finally, the strategy stresses the importance of coordination with other Federal agencies and organizations in the natural resources community. The USGS collaborates with resource agencies in the DOI and other organizations throughout the world to meet societal needs for species and ecosystem management. Working with these agencies and organizations, the USGS will play a key role in guiding sound decisionmaking during the next decade by advancing the scientific foundation for sustaining the natural resources that diverse, productive, resilient ecosystems provide.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1383C","usgsCitation":"Williams, B.K., Wingard, G.L., Brewer, Gary, Cloern, J.E., Gelfenbaum, Guy, Jacobson, R.B., Kershner, J.L., McGuire, A.D., Nichols, J.D., Shapiro, C.D., van Riper III, Charles, and White, R.P., 2013, U.S. Geological Survey ecosystems science strategy—Advancing discovery and application through collaboration: U.S. Geological Survey Circular 1383–C, 43 p.","productDescription":"vii, 43 p.","numberOfPages":"56","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":251,"text":"Ecosystems Mission Area","active":false,"usgs":true}],"links":[{"id":270889,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/cir1383c.gif"},{"id":270886,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1383c/circ1383-C.pdf","text":"Report","size":"16.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"CIR 1383-C"}],"contact":"<p><a href=\"https://www.usgs.gov/mission-areas/ecosystems\" data-mce-href=\"https://www.usgs.gov/mission-areas/ecosystems\">Ecosystems</a><br>U.S. Geological Survey<br>12201 Sunrise Valley Drive<br>Reston, VA 20192</p>","tableOfContents":"<ul><li>Foreword</li><li>About this Report</li><li>Executive Summary</li><li>Introduction</li><li>Ecosystem Science Goals</li><li>Integrating Ecosystem Science across the USGS</li><li>Strategic Approaches and Outcomes: The Path Forward</li><li>Proposed Actions</li><li>Summary and Future of Ecosystem Science for the USGS</li><li>Important Next Steps</li><li>References Cited</li><li>Appendix 1. Author Affiliations and Acknowledgments</li><li>Appendix 2. Key Terms</li></ul>","publishedDate":"2013-04-15","noUsgsAuthors":false,"publicationDate":"2013-04-15","publicationStatus":"PW","scienceBaseUri":"516d135be4b0411d430a89a5","contributors":{"authors":[{"text":"Williams, Byron K. 0000-0001-7644-1396","orcid":"https://orcid.org/0000-0001-7644-1396","contributorId":86616,"corporation":false,"usgs":true,"family":"Williams","given":"Byron","email":"","middleInitial":"K.","affiliations":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"preferred":false,"id":477402,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wingard, G. Lynn","contributorId":44969,"corporation":false,"usgs":true,"family":"Wingard","given":"G. Lynn","affiliations":[],"preferred":false,"id":477399,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brewer, Gary","contributorId":37589,"corporation":false,"usgs":true,"family":"Brewer","given":"Gary","email":"","affiliations":[],"preferred":false,"id":477398,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cloern, James E. 0000-0002-5880-6862 jecloern@usgs.gov","orcid":"https://orcid.org/0000-0002-5880-6862","contributorId":1488,"corporation":false,"usgs":true,"family":"Cloern","given":"James","email":"jecloern@usgs.gov","middleInitial":"E.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":477395,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gelfenbaum, Guy","contributorId":79844,"corporation":false,"usgs":true,"family":"Gelfenbaum","given":"Guy","affiliations":[],"preferred":false,"id":477401,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jacobson, Robert B. 0000-0002-8368-2064 rjacobson@usgs.gov","orcid":"https://orcid.org/0000-0002-8368-2064","contributorId":1289,"corporation":false,"usgs":true,"family":"Jacobson","given":"Robert","email":"rjacobson@usgs.gov","middleInitial":"B.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":477394,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"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":477392,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"McGuire, Anthony D. 0000-0003-4646-0750 ffadm@usgs.gov","orcid":"https://orcid.org/0000-0003-4646-0750","contributorId":2493,"corporation":false,"usgs":true,"family":"McGuire","given":"Anthony","email":"ffadm@usgs.gov","middleInitial":"D.","affiliations":[],"preferred":false,"id":477396,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"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":477393,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Shapiro, Carl D. 0000-0002-1598-6808 cshapiro@usgs.gov","orcid":"https://orcid.org/0000-0002-1598-6808","contributorId":3048,"corporation":false,"usgs":true,"family":"Shapiro","given":"Carl","email":"cshapiro@usgs.gov","middleInitial":"D.","affiliations":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"preferred":true,"id":477397,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"van Riper, Charles III 0000-0003-1084-5843 charles_van_riper@usgs.gov","orcid":"https://orcid.org/0000-0003-1084-5843","contributorId":169488,"corporation":false,"usgs":true,"family":"van Riper","given":"Charles","suffix":"III","email":"charles_van_riper@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":false,"id":477400,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"White, Robin P. rpwhite@usgs.gov","contributorId":239,"corporation":false,"usgs":true,"family":"White","given":"Robin","email":"rpwhite@usgs.gov","middleInitial":"P.","affiliations":[{"id":5053,"text":"IPDS Training","active":true,"usgs":true}],"preferred":true,"id":477391,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
,{"id":70045403,"text":"cir1383B - 2013 - U.S. Geological Survey core science systems strategy: characterizing, synthesizing, and understanding the critical zone through a modular science framework","interactions":[],"lastModifiedDate":"2019-10-01T10:15:34","indexId":"cir1383B","displayToPublicDate":"2019-10-01T11:20:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":307,"text":"Circular","code":"CIR","onlineIssn":"2330-5703","printIssn":"1067-084X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1383","chapter":"B","displayTitle":"U.S. Geological Survey Core Science Systems Strategy— Characterizing, Synthesizing, and Understanding the Critical Zone through a Modular Science Framework","title":"U.S. Geological Survey core science systems strategy: characterizing, synthesizing, and understanding the critical zone through a modular science framework","docAbstract":"<h1>Executive Summary</h1><p>Core Science Systems is a new mission of the U.S. Geological Survey (USGS) that resulted from the 2007 Science Strategy, “Facing Tomorrow’s Challenges: U.S. Geological Survey Science in the Decade 2007–2017.” This report describes the Core Science Systems vision and outlines a strategy to facilitate integrated characterization and understanding of the complex Earth system. The vision and suggested actions are bold and far-reaching, describing a conceptual model and framework to enhance the ability of the USGS to bring its core strengths to bear on pressing societal problems through data integration and scientific synthesis across the breadth of science.</p><p>The context of this report is inspired by a direction set forth in the 2007 Science Strategy. Specifically, ecosystem-based approaches provide the underpinnings for essentially all science themes that define the USGS. Every point on Earth falls within a specific ecosystem where data, other information assets, and the expertise of USGS and its many partners can be employed to quantitatively understand how that ecosystem functions and how it responds to natural and anthropogenic disturbances. Every benefit society obtains from the planet— food, water, raw materials to build infrastructure, homes and automobiles, fuel to heat homes and cities, and many others— are derived from or affect ecosystems.</p><p>The vision for Core Science Systems builds on core strengths of the USGS in characterizing and understanding complex Earth and biological systems through research, modeling, mapping, and the production of high quality data on the Nation’s natural resource infrastructure. Together, these research activities provide a foundation for ecosystem-based approaches through geologic mapping, topographic mapping, and biodiversity mapping. The vision describes a framework founded on these core mapping strengths that makes it easier for USGS scientists to discover critical information, share and publish results, and identify potential collaborations that transcend all USGS missions. The framework is designed to improve the efficiency of scientific work within USGS by establishing a means to preserve and recall data for future applications, organizing existing scientific knowledge and data to facilitate new use of older information, and establishing a future workflow that naturally integrates new data, applications, and other science products to make interdisciplinary research easier and more efficient. Given the increasing need for integrated data and interdisciplinary approaches to solve modern problems, leadership by the Core Science Systems mission will facilitate problem solving by all USGS missions in ways not formerly possible.</p><p>The report lays out a strategy to achieve this vision through three goals with accompanying objectives and actions. The first goal builds on and enhances the strengths of the Core Science Systems mission in characterizing and understanding the Earth system from the geologic framework to the topographic characteristics of the land surface and biodiversity across the Nation. The second goal enhances and develops new strengths in computer and information science to make it easier for USGS scientists to discover data and models, share and publish results, and discover connections between scientific information and knowledge. The third goal brings additional focus to research and development methods to address complex issues affecting society that require integration of knowledge and new methods for synthesizing scientific information. Collectively, the report lays out a strategy to create a seamless connection between all USGS activities to accelerate and make USGS science more efficient by fully integrating disciplinary expertise within a new and evolving science paradigm for a changing world in the 21st century.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1383B","usgsCitation":"Bristol, R.S., Euliss, N.H., Jr., Booth, N.L., Burkardt, Nina, Diffendorfer, J.E., Gesch, D.B., McCallum, B.E., Miller, D.M., Morman, S.A., Poore, B.S., Signell, R.P., and Viger, R.J., 2013, U.S. Geological Survey core science systems strategy—Characterizing, synthesizing, and understanding the critical zone through a modular science framework: U.S. Geological Survey Circular 1383–B, 33 p.","productDescription":"vi, 33 p.","numberOfPages":"44","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":37226,"text":"Core Science Analytics, Synthesis, and Libraries","active":true,"usgs":true}],"links":[{"id":270895,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/cir1383b.gif"},{"id":270890,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1383b/circ1383-B.pdf","text":"Report","size":"16.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"CIR 1383-B"}],"country":"United States","contact":"<p><a href=\"https://www.usgs.gov/mission-areas/core-science-systems\" data-mce-href=\"https://www.usgs.gov/mission-areas/core-science-systems\">Core Science Systems</a><br>U.S. Geological Survey<br>12201 Sunrise Valley Drive<br>Reston, VA 20192<br></p><p><br></p>","tableOfContents":"<ul><li>Foreword</li><li>Executive Summary</li><li>Overview: Science for a Changing World—Evolving a Science Paradigm for the 21st Century</li><li>Introducing the Core Science Systems Mission</li><li>Vision for Core Science Systems</li><li>Guiding Concepts</li><li>Goals, Objectives, and Actions</li><li>Conclusion</li><li>Acknowledgments</li><li>References Cited</li></ul>","publishedDate":"2013-04-15","noUsgsAuthors":false,"publicationDate":"2013-04-15","publicationStatus":"PW","scienceBaseUri":"516d135ee4b0411d430a89b5","contributors":{"authors":[{"text":"Bristol, R. Sky 0000-0003-1682-4031","orcid":"https://orcid.org/0000-0003-1682-4031","contributorId":88196,"corporation":false,"usgs":true,"family":"Bristol","given":"R. Sky","affiliations":[],"preferred":false,"id":477413,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Euliss, Ned H. Jr. ceuliss@usgs.gov","contributorId":2916,"corporation":false,"usgs":true,"family":"Euliss","given":"Ned","suffix":"Jr.","email":"ceuliss@usgs.gov","middleInitial":"H.","affiliations":[],"preferred":false,"id":477410,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Booth, Nathaniel L. nlbooth@usgs.gov","contributorId":651,"corporation":false,"usgs":true,"family":"Booth","given":"Nathaniel L.","email":"nlbooth@usgs.gov","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":false,"id":477403,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Burkardt, Nina 0000-0002-9392-9251 burkardtn@usgs.gov","orcid":"https://orcid.org/0000-0002-9392-9251","contributorId":2781,"corporation":false,"usgs":true,"family":"Burkardt","given":"Nina","email":"burkardtn@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":477409,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Diffendorfer, Jay E. 0000-0003-1093-6948 jediffendorfer@usgs.gov","orcid":"https://orcid.org/0000-0003-1093-6948","contributorId":55137,"corporation":false,"usgs":true,"family":"Diffendorfer","given":"Jay","email":"jediffendorfer@usgs.gov","middleInitial":"E.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":false,"id":477412,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gesch, Dean B. 0000-0002-8992-4933 gesch@usgs.gov","orcid":"https://orcid.org/0000-0002-8992-4933","contributorId":2956,"corporation":false,"usgs":true,"family":"Gesch","given":"Dean","email":"gesch@usgs.gov","middleInitial":"B.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":477411,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McCallum, Brian E. 0000-0002-8935-0343 bemccall@usgs.gov","orcid":"https://orcid.org/0000-0002-8935-0343","contributorId":1591,"corporation":false,"usgs":true,"family":"McCallum","given":"Brian","email":"bemccall@usgs.gov","middleInitial":"E.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":477406,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Miller, David M. 0000-0003-3711-0441 dmiller@usgs.gov","orcid":"https://orcid.org/0000-0003-3711-0441","contributorId":1707,"corporation":false,"usgs":true,"family":"Miller","given":"David M.","email":"dmiller@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":false,"id":477407,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Morman, Suzette A. 0000-0002-2532-1033 smorman@usgs.gov","orcid":"https://orcid.org/0000-0002-2532-1033","contributorId":996,"corporation":false,"usgs":true,"family":"Morman","given":"Suzette","email":"smorman@usgs.gov","middleInitial":"A.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":477404,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Poore, Barbara S. bspoore@usgs.gov","contributorId":2541,"corporation":false,"usgs":true,"family":"Poore","given":"Barbara","email":"bspoore@usgs.gov","middleInitial":"S.","affiliations":[],"preferred":true,"id":477408,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Signell, Richard P. rsignell@usgs.gov","contributorId":1435,"corporation":false,"usgs":true,"family":"Signell","given":"Richard","email":"rsignell@usgs.gov","middleInitial":"P.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":477405,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Viger, Roland J.","contributorId":97528,"corporation":false,"usgs":true,"family":"Viger","given":"Roland J.","affiliations":[],"preferred":false,"id":477414,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
,{"id":70187115,"text":"70187115 - 2013 - Validation of chlorine and oxygen isotope ratio analysis to differentiate perchlorate sources and to document perchlorate biodegradation","interactions":[],"lastModifiedDate":"2017-04-25T09:21:38","indexId":"70187115","displayToPublicDate":"2017-04-25T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"seriesNumber":"ER-200509","title":"Validation of chlorine and oxygen isotope ratio analysis to differentiate perchlorate sources and to document perchlorate biodegradation","docAbstract":"Increased health concerns about perchlorate (ClO4-) during the past decade and subsequent regulatory considerations have generated appreciable interest in source identification. The key objective of the isotopic techniques described in this guidance manual is to provide evidence concerning the origin of ClO4- in soils and groundwater and, more specifically, whether that ClO4- is synthetic or natural. Chlorine and oxygen isotopic analyses of ClO4- provide the primary direct approach whereby different sources of ClO4- can be distinguished from each other. These techniques measure the relative abundances of the stable isotopes of chlorine (37Cl and 35Cl) and oxygen (18O, 17O, and 16O) in ClO4- using isotope-ratio mass spectrometry (IRMS). In addition, the relative abundance of the radioactive chlorine isotope 36Cl is measured using accelerator mass spectrometry (AMS). Taken together, these measurements provide four independent quantities that can be used to distinguish natural and synthetic ClO4- sources, to discriminate different types of natural ClO4-, and to detect ClO4- biodegradation in the environment. Other isotopic, chemical, and geochemical techniques that can be applied in conjunction with isotopic analyses of ClO4- to provide supporting data in forensic studies are also described.","language":"English","publisher":"U.S. Department of Defense","usgsCitation":"Hatzinger, P.B., Bohlke, J., Sturchio, N.C., and Gu, B., 2013, Validation of chlorine and oxygen isotope ratio analysis to differentiate perchlorate sources and to document perchlorate biodegradation, Report: xvii, 176 p.; Appendixes A-C; Supporting Information: S1-26.","productDescription":"Report: xvii, 176 p.; Appendixes A-C; Supporting Information: S1-26","ipdsId":"IP-045772","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":340221,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":340160,"type":{"id":15,"text":"Index 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,{"id":70179914,"text":"70179914 - 2013 - Groundwater conditions in Utah, spring of 2013","interactions":[],"lastModifiedDate":"2019-05-22T09:30:37","indexId":"70179914","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"seriesTitle":{"id":110,"text":"Cooperative Investigations Report","active":true,"publicationSubtype":{"id":2}},"seriesNumber":"54","title":"Groundwater conditions in Utah, spring of 2013","docAbstract":"<p>This is the fiftieth in a series of annual reports that describe groundwater conditions in Utah. Reports in this series, published cooperatively by the U.S. Geological Survey and the Utah Department of Natural Resources, Division of Water Rights, and the Utah Department of Environmental Quality, Division of Water Quality, provide data to enable interested parties to maintain awareness of changing groundwater conditions. </p><p>This report, like the others in the series, contains information on well construction, groundwater withdrawals from wells, water-level changes, precipitation, streamflow, and chemical quality of water. Information on well construction included in this report refers only to wells constructed for new appropriations of groundwater. Supplementary data are included in reports of this series only for those years or areas that are important to a discussion of changing groundwater conditions and for which applicable data are available.</p><p>This report includes individual discussions of selected significant areas of groundwater development in the State for calendar year 2012. Most of the reported data were collected by the U.S. Geological Survey in cooperation with the Utah Department of Natural Resources, Division of Water Rights, and the Utah Department of Environmental Quality, Division of Water Quality. This report is also available online at http://www.waterrights.utah.gov/techinfo/ and http://ut.water. usgs.gov/publications/GW2013.pdf. Groundwater conditions in Utah for calendar year 2011 are reported in Burden and others (2012) and available online at http://ut.water.usgs.gov/ publications/GW2012.pdf</p>","language":"English","publisher":"Utah Department of Natural Resources","publisherLocation":"Salt Lake City, UT","collaboration":"Prepared in cooperation with the Utah Department of Natural Resources, Division of Water Rights, and Utah Department of Environmental Quality, Division of Water Quality","usgsCitation":"Burden, C.B., Birken, A.S., Derrick, V.N., Fisher, M.J., Holt, C.M., Downhour, P., Smith, L., Eacret, R.J., Gibson, T.L., Slaugh, B.A., Whittier, N.R., Howells, J.H., and Christiansen, H.K., 2013, Groundwater conditions in Utah, spring of 2013: Cooperative Investigations Report 54, x, 118 p.","productDescription":"x, 118 p.","numberOfPages":"132","costCenters":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":364060,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://waterrights.utah.gov/techinfo/wwwpub/GW2013.pdf"},{"id":333543,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58833023e4b0d00231637798","contributors":{"authors":[{"text":"Burden, Carole B. cburden@usgs.gov","contributorId":852,"corporation":false,"usgs":true,"family":"Burden","given":"Carole","email":"cburden@usgs.gov","middleInitial":"B.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":659192,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Birken, Adam S.","contributorId":178617,"corporation":false,"usgs":false,"family":"Birken","given":"Adam","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":660129,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Derrick, V. Noah","contributorId":178618,"corporation":false,"usgs":false,"family":"Derrick","given":"V.","email":"","middleInitial":"Noah","affiliations":[],"preferred":false,"id":660130,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fisher, Martel J. mjfisher@usgs.gov","contributorId":4410,"corporation":false,"usgs":true,"family":"Fisher","given":"Martel","email":"mjfisher@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":true,"id":660131,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Holt, Christopher M.","contributorId":178613,"corporation":false,"usgs":false,"family":"Holt","given":"Christopher","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":660132,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Downhour, Paul downhour@usgs.gov","contributorId":968,"corporation":false,"usgs":true,"family":"Downhour","given":"Paul","email":"downhour@usgs.gov","affiliations":[],"preferred":true,"id":660133,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Smith, Lincoln","contributorId":178614,"corporation":false,"usgs":false,"family":"Smith","given":"Lincoln","affiliations":[],"preferred":false,"id":660134,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Eacret, Robert J. rjeacret@usgs.gov","contributorId":971,"corporation":false,"usgs":true,"family":"Eacret","given":"Robert","email":"rjeacret@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":true,"id":660135,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Gibson, Travis L.","contributorId":178615,"corporation":false,"usgs":false,"family":"Gibson","given":"Travis","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":660136,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Slaugh, Bradley A. baslaugh@usgs.gov","contributorId":966,"corporation":false,"usgs":true,"family":"Slaugh","given":"Bradley","email":"baslaugh@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":660137,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Whittier, Nickolas R.","contributorId":178616,"corporation":false,"usgs":false,"family":"Whittier","given":"Nickolas","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":660138,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Howells, James H. jhowells@usgs.gov","contributorId":969,"corporation":false,"usgs":true,"family":"Howells","given":"James","email":"jhowells@usgs.gov","middleInitial":"H.","affiliations":[],"preferred":true,"id":660139,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Christiansen, Howard K.","contributorId":47830,"corporation":false,"usgs":true,"family":"Christiansen","given":"Howard","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":660140,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}}
,{"id":70157318,"text":"70157318 - 2013 - Cumulative biological impacts framework for solar energy projects in the California Desert","interactions":[],"lastModifiedDate":"2017-05-11T11:01:08","indexId":"70157318","displayToPublicDate":"2015-12-31T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"seriesNumber":"CEC-500-2015-062","title":"Cumulative biological impacts framework for solar energy projects in the California Desert","docAbstract":"This project developed analytical approaches, tools and geospatial data to support conservation planning for renewable energy development in the California deserts. Research focused on geographical analysis to avoid, minimize and mitigate the cumulative biological effects of utility-scale solar energy development. A hierarchical logic model was created to map the compatibility of new solar energy projects with current biological conservation values. The research indicated that the extent of compatible areas is much greater than the estimated land area required to achieve 2040 greenhouse gas reduction goals. Species distribution models were produced for 65 animal and plant species that were of potential conservation significance to the Desert Renewable Energy Conservation Plan process. These models mapped historical and projected future habitat suitability using 270 meter resolution climate grids. The results were integrated into analytical frameworks to locate potential sites for offsetting project impacts and evaluating the cumulative effects of multiple solar energy projects. Examples applying these frameworks in the Western Mojave Desert ecoregion show the potential of these publicly-available tools to assist regional planning efforts. Results also highlight the necessity to explicitly consider projected land use change and climate change when prioritizing areas for conservation and mitigation offsets. Project data, software and model results are all available online.","language":"English","publisher":"California Energy Commission","usgsCitation":"Davis, F., Kreitler, J.R., Soong, O., Stoms, D.M., Dashiell, S., Hannah, L., Wilkinson, W., and Dingman, J., 2013, Cumulative biological impacts framework for solar energy projects in the California Desert, viii, 89 p.","productDescription":"viii, 89 p.","ipdsId":"IP-055379","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":341052,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":308282,"type":{"id":15,"text":"Index Page"},"url":"https://www.energy.ca.gov/2015publications/CEC-500-2015-062/"}],"country":"United States","state":"California","otherGeospatial":"California Desert","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      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,{"id":70173460,"text":"70173460 - 2013 - Landscape-scale evaluation of asymmetric interactions between Brown Trout and Brook Trout using two-species occupancy models","interactions":[],"lastModifiedDate":"2016-06-17T14:31:53","indexId":"70173460","displayToPublicDate":"2015-12-22T13:30:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Landscape-scale evaluation of asymmetric interactions between Brown Trout and Brook Trout using two-species occupancy models","docAbstract":"<p><span>Predicting the distribution of native stream fishes is fundamental to the management and conservation of many species. Modeling species distributions often consists of quantifying relationships between species occurrence and abundance data at known locations with environmental data at those locations. However, it is well documented that native stream fish distributions can be altered as a result of asymmetric interactions between dominant exotic and subordinate native species. For example, the naturalized exotic Brown Trout&nbsp;</span><i>Salmo trutta</i><span>&nbsp;has been identified as a threat to native Brook Trout&nbsp;</span><i>Salvelinus fontinalis</i><span>&nbsp;in the eastern United States. To evaluate large-scale patterns of co-occurrence and to quantify the potential effects of Brown Trout presence on Brook Trout occupancy, we used data from 624 stream sites to fit two-species occupancy models. These models assumed that asymmetric interactions occurred between the two species. In addition, we examined natural and anthropogenic landscape characteristics we hypothesized would be important predictors of occurrence of both species. Estimated occupancy for Brook Trout, from a co-occurrence model with no landscape covariates, at sites with Brown Trout present was substantially lower than sites where Brown Trout were absent. We also observed opposing patterns for Brook and Brown Trout occurrence in relation to percentage forest, impervious surface, and agriculture within the network catchment. Our results are consistent with other studies and suggest that alterations to the landscape, and specifically the transition from a forested catchment to one that contains impervious surface or agriculture, reduces the occurrence probability of wild Brook Trout. Our results, however, also suggest that the presence of Brown Trout results in lower occurrence probability of Brook Trout over a range of anthropogenic landscape characteristics, compared with streams where Brown Trout were absent.</span></p>","language":"English","publisher":"Taylor & Francis","doi":"10.1080/00028487.2012.734892","usgsCitation":"Wagner, T., Deweber, J.T., Detar, J., and John A. Sweka, 2013, Landscape-scale evaluation of asymmetric interactions between Brown Trout and Brook Trout using two-species occupancy models: Transactions of the American Fisheries Society, v. 142, no. 2, p. 353-361, https://doi.org/10.1080/00028487.2012.734892.","productDescription":"8 p.","startPage":"353","endPage":"361","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-041194","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":323919,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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PA","active":true,"usgs":false}],"preferred":false,"id":637156,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Detar, Jason","contributorId":171356,"corporation":false,"usgs":false,"family":"Detar","given":"Jason","email":"","affiliations":[{"id":26873,"text":"Pennsylvania Fish and Boat Commission, Bellefonte, PA","active":true,"usgs":false}],"preferred":false,"id":637155,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"John A. Sweka","contributorId":171358,"corporation":false,"usgs":false,"family":"John A. Sweka","affiliations":[{"id":26874,"text":"USFWS, Lamar, PA","active":true,"usgs":false}],"preferred":false,"id":637157,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}}
,{"id":70173472,"text":"70173472 - 2013 - Semi-automted analysis of high-resolution aerial images to quantify docks in Upper  Midwest glacial lakes","interactions":[],"lastModifiedDate":"2016-06-17T13:48:54","indexId":"70173472","displayToPublicDate":"2015-12-15T09:45:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1958,"text":"ISPRS Journal of Photogrammetry and Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Semi-automted analysis of high-resolution aerial images to quantify docks in Upper  Midwest glacial lakes","docAbstract":"<p><span>Lake resources can be negatively affected by environmental stressors originating from multiple sources and different spatial scales. Shoreline development, in particular, can negatively affect lake resources through decline in habitat quality, physical disturbance, and impacts on fisheries. The development of remote sensing techniques that efficiently characterize shoreline development in a regional context could greatly improve management approaches for protecting and restoring lake resources. The goal of this study was to develop an approach using high-resolution aerial photographs to quantify and assess docks as indicators of shoreline development. First, we describe a dock analysis workflow that can be used to quantify the spatial extent of docks using aerial images. Our approach incorporates pixel-based classifiers with object-based techniques to effectively analyze high-resolution digital imagery. Second, we apply the analysis workflow to quantify docks for 4261 lakes managed by the Minnesota Department of Natural Resources. Overall accuracy of the analysis results was 98.4% (87.7% based on&nbsp;</span><span id=\"mmlsi3\" class=\"mathmlsrc\"><a class=\"mathImg\" title=\"View the MathML source\" data-mathurl=\"/science?_ob=MathURL&amp;_method=retrieve&amp;_eid=1-s2.0-S0924271613001068&amp;_mathId=si3.gif&amp;_user=111111111&amp;_pii=S0924271613001068&amp;_rdoc=1&amp;_issn=09242716&amp;md5=c850e2fc082efc143e4f8df6c95062a4\"><img class=\"imgLazyJSB inlineImage\" title=\"View the MathML source\" src=\"http://ars.els-cdn.com/content/image/1-s2.0-S0924271613001068-si3.gif\" alt=\"View the MathML source\" width=\"15\" height=\"15\" data-inlimgeid=\"1-s2.0-S0924271613001068-si3.gif\" data-loaded=\"true\" /></a></span><span>) after manual post-processing. The analysis workflow was also 74% more efficient than the time required for manual digitization of docks. These analyses have immediate relevance for resource planning in Minnesota, whereas the dock analysis workflow could be used to quantify shoreline development in other regions with comparable imagery. These data can also be used to better understand the effects of shoreline development on aquatic resources and to evaluate the effects of shoreline development relative to other stressors.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.isprsjprs.2013.04.006","usgsCitation":"Beck, M.W., Vondracek, B.C., Hatch, L.K., and Vinje, J., 2013, Semi-automted analysis of high-resolution aerial images to quantify docks in Upper  Midwest glacial lakes: ISPRS Journal of Photogrammetry and Remote Sensing, v. 81, p. 60-69, https://doi.org/10.1016/j.isprsjprs.2013.04.006.","productDescription":"9 p.","startPage":"60","endPage":"69","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-041517","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":323902,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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,{"id":70173462,"text":"70173462 - 2013 - Estimating spatial and temporal components of variation in count data using negative binomial mixed models","interactions":[],"lastModifiedDate":"2016-06-17T14:27:35","indexId":"70173462","displayToPublicDate":"2015-08-12T14:30:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Estimating spatial and temporal components of variation in count data using negative binomial mixed models","docAbstract":"<p>P<span>artitioning total variability into its component temporal and spatial sources is a powerful way to better understand time series and elucidate trends. The data available for such analyses of fish and other populations are usually nonnegative integer counts of the number of organisms, often dominated by many low values with few observations of relatively high abundance. These characteristics are not well approximated by the Gaussian distribution. We present a detailed description of a negative binomial mixed-model framework that can be used to model count data and quantify temporal and spatial variability. We applied these models to data from four fishery-independent surveys of Walleyes&nbsp;</span><i>Sander vitreus</i><span>&nbsp;across the Great Lakes basin. Specifically, we fitted models to gill-net catches from Wisconsin waters of Lake Superior; Oneida Lake, New York; Saginaw Bay in Lake Huron, Michigan; and Ohio waters of Lake Erie. These long-term monitoring surveys varied in overall sampling intensity, the total catch of Walleyes, and the proportion of zero catches. Parameter estimation included the negative binomial scaling parameter, and we quantified the random effects as the variations among gill-net sampling sites, the variations among sampled years, and site &times; year interactions. This framework (i.e., the application of a mixed model appropriate for count data in a variance-partitioning context) represents a flexible approach that has implications for monitoring programs (e.g., trend detection) and for examining the potential of individual variance components to serve as response metrics to large-scale anthropogenic perturbations or ecological changes.</span></p>","language":"English","publisher":"Taylor & Francis","doi":"10.1080/00028487.2012.728163","usgsCitation":"Irwin, B.J., Wagner, T., Bence, J., Kepler, M.V., Liu, W., and Hayes, D.B., 2013, Estimating spatial and temporal components of variation in count data using negative binomial mixed models: Transactions of the American Fisheries Society, v. 142, no. 1, p. 171-183, https://doi.org/10.1080/00028487.2012.728163.","productDescription":"12 p.","startPage":"171","endPage":"183","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-031058","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":323918,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Iowa, Maine, Michigan, Ohio, 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,{"id":70048359,"text":"70048359 - 2013 - National Park Service Vegetation Inventory Program, Cuyahoga Valley National Park, Ohio","interactions":[],"lastModifiedDate":"2017-04-25T13:35:53","indexId":"70048359","displayToPublicDate":"2015-05-29T13:51:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":54,"text":"Natural Resource Technical Report","active":false,"publicationSubtype":{"id":1}},"seriesNumber":"NPS/HTLN/NRTR—2013/792","title":"National Park Service Vegetation Inventory Program, Cuyahoga Valley National Park, Ohio","docAbstract":"<p>The National Park Service (NPS) Vegetation Inventory Program (VIP) is an effort to classify, describe, and map existing vegetation of national park units for the NPS Natural Resource Inventory and Monitoring (I&amp;M) Program. The NPS VIP is managed by the NPS Biological Resources Management Division and provides baseline vegetation information to the NPS Natural Resource I&amp;M Program. The U.S. Geological Survey (USGS) Vegetation Characterization Program lends a cooperative role in the NPS VIP. The USGS Upper Midwest Environmental Sciences Center, NatureServe, and NPS Cuyahoga Valley National Park (CUVA) have completed vegetation classification and mapping of CUVA.<br></p><p>Mappers, ecologists, and botanists collaborated to identify and describe vegetation types within the National Vegetation Classification Standard (NVCS) and to determine how best to map them by using aerial imagery. The team collected data from 221 vegetation plots within CUVA to develop detailed descriptions of vegetation types. Data from 50 verification sites were also collected to test both the key to vegetation types and the application of vegetation types to a sample set of map polygons. Furthermore, data from 647 accuracy assessment (AA) sites were collected (of which 643 were used to test accuracy of the vegetation map layer). These data sets led to the identification of 45 vegetation types at the association level in the NVCS at CUVA.</p><p>A total of 44 map classes were developed to map the vegetation and general land cover of CUVA, including the following: 29 map classes represent natural/semi-natural vegetation types in the NVCS, 12 map classes represent cultural vegetation (agricultural and developed) in the NVCS, and 3 map classes represent non-vegetation features (open-water bodies). Features were interpreted from viewing color-infrared digital aerial imagery dated October 2010 (during peak leaf-phenology change of trees) via digital onscreen three-dimensional stereoscopic workflow systems in geographic information systems (GIS). The interpreted data were digitally and spatially referenced, thus making the spatial database layers usable in GIS. Polygon units were mapped to either a 0.5 ha or 0.25 ha minimum mapping unit, depending on vegetation type.<br></p><p>A geodatabase containing various feature-class layers and tables shows the locations of vegetation types and general land cover (vegetation map), vegetation plot samples, verification sites, AA sites, project boundary extent, and aerial photographic centers. The feature-class layer and relate tables for the CUVA vegetation map provides 4,640 polygons of detailed attribute data covering 13,288.4 ha, with an average polygon size of 2.9 ha.</p><p>Summary reports generated from the vegetation map layer show map classes representing natural/semi-natural types in the NVCS apply to 4,151 polygons (89.4% of polygons) and cover 11,225.0 ha (84.5%) of the map extent. Of these polygons, the map layer shows CUVA to be 74.4% forest (9,888.8 ha), 2.5% shrubland (329.7 ha), and 7.6% herbaceous vegetation cover (1,006.5 ha). Map classes representing cultural types in the NVCS apply to 435 polygons (9.4% of polygons) and cover 1,825.7 ha (13.7%) of the map extent. Map classes representing non-NVCS units (open water) apply to 54 polygons (1.2% of polygons) and cover 237.7 ha (1.8%) of the map extent.</p><p>A thematic AA study was conducted of map classes representing natural/semi-natural types in the NVCS. Results present an overall accuracy of 80.7% (kappa index of 79.5%) based on data&nbsp;from 643 of the 647 AA sites. Most individual map-class themes exceed the NPS VIP standard of 80% with a 90% confidence interval.</p><p>The CUVA vegetation mapping project delivers many geospatial and vegetation data products in hardcopy and/or digital formats. These products consist of an in-depth project report discussing methods and results, which include descriptions and a dichotomous key to vegetation types, map classification and map-class descriptions, and a contingency table showing AA results. The suite of products also includes a database of vegetation plots, verification sites, and AA sites; digital pictures of field sites; field data sheets; aerial photographic imagery; hardcopy and digital maps; and a geodatabase of vegetation types and land cover (map layer), fieldwork locations (vegetation plots, verification sites, and AA sites), aerial photographic index, project boundary, and metadata. All geospatial products are projected in Universal Transverse Mercator, Zone 17, by using the North American Datum of 1983. Information on the NPS VIP and completed park mapping projects are located on the Internet at &lt;http://science.nature.nps.gov/im/inventory/veg&gt; and &lt;http://www.usgs.gov/core_science_systems/csas/vip/index.html&gt;.</p>","language":"English","publisher":"National Park Service","publisherLocation":"Fort Collins, CO","usgsCitation":"Hop, K.D., Drake, J., Strassman, A.C., Hoy, E.E., Menard, S., Jakusz, J., and Dieck, J., 2013, National Park Service Vegetation Inventory Program, Cuyahoga Valley National Park, Ohio: Natural Resource Technical Report NPS/HTLN/NRTR—2013/792, xv, 66 p.","productDescription":"xv, 66 p.","numberOfPages":"302","ipdsId":"IP-045709","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":340274,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":340273,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://irma.nps.gov/DataStore/Reference/Profile/2198743"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59006066e4b0e85db3a5ddfb","contributors":{"authors":[{"text":"Hop, Kevin D. 0000-0002-9928-4773 khop@usgs.gov","orcid":"https://orcid.org/0000-0002-9928-4773","contributorId":1438,"corporation":false,"usgs":true,"family":"Hop","given":"Kevin","email":"khop@usgs.gov","middleInitial":"D.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":518202,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Drake, J.","contributorId":101003,"corporation":false,"usgs":true,"family":"Drake","given":"J.","email":"","affiliations":[],"preferred":false,"id":692860,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Strassman, Andrew C. 0000-0002-9792-7181 astrassman@usgs.gov","orcid":"https://orcid.org/0000-0002-9792-7181","contributorId":4575,"corporation":false,"usgs":true,"family":"Strassman","given":"Andrew","email":"astrassman@usgs.gov","middleInitial":"C.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":518205,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hoy, Erin E. 0000-0002-2853-3242 ehoy@usgs.gov","orcid":"https://orcid.org/0000-0002-2853-3242","contributorId":4523,"corporation":false,"usgs":true,"family":"Hoy","given":"Erin","email":"ehoy@usgs.gov","middleInitial":"E.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":518204,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Menard, Shannon","contributorId":167864,"corporation":false,"usgs":false,"family":"Menard","given":"Shannon","email":"","affiliations":[{"id":17658,"text":"NatureServe","active":true,"usgs":false}],"preferred":false,"id":692861,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dieck, J.J. jdieck@usgs.gov","contributorId":1699,"corporation":false,"usgs":true,"family":"Dieck","given":"J.J.","email":"jdieck@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":false,"id":518203,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Jakusz, J.W. jjakusz@usgs.gov","contributorId":4835,"corporation":false,"usgs":true,"family":"Jakusz","given":"J.W.","email":"jjakusz@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":false,"id":518206,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70159836,"text":"70159836 - 2013 - Mapping monkeypox transmission risk through time and space in the Congo Basin","interactions":[],"lastModifiedDate":"2015-12-01T11:49:37","indexId":"70159836","displayToPublicDate":"2015-01-01T00:00:00","publicationYear":"2013","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":"Mapping monkeypox transmission risk through time and space in the Congo Basin","docAbstract":"<p><span>Monkeypox is a major public health concern in the Congo Basin area, with changing patterns of human case occurrences reported in recent years. Whether this trend results from better surveillance and detection methods, reduced proportions of vaccinated vs. non-vaccinated human populations, or changing environmental conditions remains unclear. Our objective is to examine potential correlations between environment and transmission of monkeypox events in the Congo Basin. We created ecological niche models based on human cases reported in the Congo Basin by the World Health Organization at the end of the smallpox eradication campaign, in relation to remotely-sensed Normalized Difference Vegetation Index datasets from the same time period. These models predicted independent spatial subsets of monkeypox occurrences with high confidence; models were then projected onto parallel environmental datasets for the 2000s to create present-day monkeypox suitability maps. Recent trends in human monkeypox infection are associated with broad environmental changes across the Congo Basin. Our results demonstrate that ecological niche models provide useful tools for identification of areas suitable for transmission, even for poorly-known diseases like monkeypox.</span></p>","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0074816","usgsCitation":"Nakazawa, Y.J., Lash, R.R., Carroll, D., Damon, I.K., Karem, K.L., Reynolds, M.G., Osorio, J., Rocke, T.E., Malekani, J., Muyembe, J., Formenty, P., and Peterson, A.T., 2013, Mapping monkeypox transmission risk through time and space in the Congo Basin: PLoS ONE, v. 8, no. 9, e74816; 9 p., https://doi.org/10.1371/journal.pone.0074816.","productDescription":"e74816; 9 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-030117","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":473347,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0074816","text":"Publisher Index Page"},{"id":311765,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Democratic Republic of Congo","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              16.611328125,\n              -5.703447982149503\n            ],\n            [\n              17.4462890625,\n              -8.233237111274553\n            ],\n            [\n              19.2919921875,\n              -8.05922962720018\n            ],\n            [\n              19.6435546875,\n              -7.100892668623642\n            ],\n            [\n              25.224609375,\n              -5.659718554577286\n            ],\n            [\n              25.3125,\n              5.003394345022162\n            ],\n            [\n              18.4130859375,\n              3.5572827265412794\n            ],\n            [\n              17.666015625,\n              -0.7470491450051796\n            ],\n            [\n              16.2158203125,\n              -2.2406396093827206\n            ],\n            [\n              16.611328125,\n              -5.703447982149503\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"8","issue":"9","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2013-09-05","publicationStatus":"PW","scienceBaseUri":"565ed2b9e4b071e7ea54442f","contributors":{"authors":[{"text":"Nakazawa, Yoshinori J.","contributorId":150106,"corporation":false,"usgs":false,"family":"Nakazawa","given":"Yoshinori","email":"","middleInitial":"J.","affiliations":[{"id":17914,"text":"CDC","active":true,"usgs":false}],"preferred":false,"id":580772,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lash, R. Ryan","contributorId":150129,"corporation":false,"usgs":false,"family":"Lash","given":"R.","email":"","middleInitial":"Ryan","affiliations":[],"preferred":false,"id":580773,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Carroll, Darin S.","contributorId":150113,"corporation":false,"usgs":false,"family":"Carroll","given":"Darin S.","affiliations":[{"id":17914,"text":"CDC","active":true,"usgs":false}],"preferred":false,"id":580774,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Damon, Inger K.","contributorId":150112,"corporation":false,"usgs":false,"family":"Damon","given":"Inger","email":"","middleInitial":"K.","affiliations":[{"id":17914,"text":"CDC","active":true,"usgs":false}],"preferred":false,"id":580775,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Karem, Kevin L.","contributorId":150111,"corporation":false,"usgs":false,"family":"Karem","given":"Kevin","email":"","middleInitial":"L.","affiliations":[{"id":17914,"text":"CDC","active":true,"usgs":false}],"preferred":false,"id":580776,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Reynolds, Mary G.","contributorId":150131,"corporation":false,"usgs":false,"family":"Reynolds","given":"Mary","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":580777,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Osorio, Jorge E.","contributorId":50392,"corporation":false,"usgs":false,"family":"Osorio","given":"Jorge E.","affiliations":[{"id":13052,"text":"Department of Pathobiological Sciences, School of Veterinary Medicine, University of Wisconsin","active":true,"usgs":false}],"preferred":false,"id":580778,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Rocke, Tonie E. 0000-0003-3933-1563 trocke@usgs.gov","orcid":"https://orcid.org/0000-0003-3933-1563","contributorId":2665,"corporation":false,"usgs":true,"family":"Rocke","given":"Tonie","email":"trocke@usgs.gov","middleInitial":"E.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":580664,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Malekani, Jean","contributorId":150110,"corporation":false,"usgs":false,"family":"Malekani","given":"Jean","affiliations":[{"id":17915,"text":"Univ. of Kinshasa, DRC","active":true,"usgs":false}],"preferred":false,"id":580779,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Muyembe, Jean-Jacques","contributorId":150132,"corporation":false,"usgs":false,"family":"Muyembe","given":"Jean-Jacques","email":"","affiliations":[],"preferred":false,"id":580780,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Formenty, Pierre","contributorId":150133,"corporation":false,"usgs":false,"family":"Formenty","given":"Pierre","email":"","affiliations":[],"preferred":false,"id":580781,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Peterson, A. Townsend","contributorId":150134,"corporation":false,"usgs":false,"family":"Peterson","given":"A.","email":"","middleInitial":"Townsend","affiliations":[],"preferred":false,"id":580782,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
,{"id":70124274,"text":"70124274 - 2013 - County-level analysis of the impact of temperature and population increases on California wildfire data","interactions":[],"lastModifiedDate":"2014-09-11T12:41:46","indexId":"70124274","displayToPublicDate":"2014-09-11T11:58:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1577,"text":"Environmetrics","active":true,"publicationSubtype":{"id":10}},"title":"County-level analysis of the impact of temperature and population increases on California wildfire data","docAbstract":"The extent to which the apparent increase in wildfire incidence and burn area in California from 1990 to 2006 is affected by population and temperature increases is examined. Using generalized linear models with random effects, we focus on the estimated impacts of increases in mean daily temperatures and populations in different counties on wildfire in those counties, after essentially controlling for the overall differences between counties in their overall mean temperatures and populations. We find that temperature increase appears to have a significant positive impact on both total burn area and number of observed wildfires. Population growth appears to have a much less pronounced impact on total burn area than do annual temperature increases, and population growth appears to be negatively correlated with the total number of observed wildfires. These effects are especially pronounced in the winter season and in Southern California counties.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Environmetrics","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1002/env.2257","usgsCitation":"Baltar, M., Keeley, J.E., and Schoenberg, F., 2013, County-level analysis of the impact of temperature and population increases on California wildfire data: Environmetrics, v. 25, no. 6, p. 397-405, https://doi.org/10.1002/env.2257.","productDescription":"9 p.","startPage":"397","endPage":"405","numberOfPages":"9","ipdsId":"IP-051440","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":473349,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://escholarship.org/uc/item/2753572w","text":"External Repository"},{"id":293712,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":293655,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/env.2257"}],"country":"United States","state":"California","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.41,32.53 ], [ -124.41,42.01 ], [ -114.13,42.01 ], [ -114.13,32.53 ], [ -124.41,32.53 ] ] ] } } ] }","volume":"25","issue":"6","noUsgsAuthors":false,"publicationDate":"2014-01-23","publicationStatus":"PW","scienceBaseUri":"5412ab8be4b0239f1986b9d9","contributors":{"authors":[{"text":"Baltar, M.","contributorId":73939,"corporation":false,"usgs":true,"family":"Baltar","given":"M.","email":"","affiliations":[],"preferred":false,"id":500632,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Keeley, Jon E. 0000-0002-4564-6521 jon_keeley@usgs.gov","orcid":"https://orcid.org/0000-0002-4564-6521","contributorId":1268,"corporation":false,"usgs":true,"family":"Keeley","given":"Jon","email":"jon_keeley@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":500630,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schoenberg, F.P.","contributorId":56438,"corporation":false,"usgs":true,"family":"Schoenberg","given":"F.P.","email":"","affiliations":[],"preferred":false,"id":500631,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70116460,"text":"70116460 - 2013 - Geomorphic characterization of four shelf-sourced submarine canyons along the U.S. Mid-Atlantic continental margin","interactions":[],"lastModifiedDate":"2017-11-18T10:19:35","indexId":"70116460","displayToPublicDate":"2014-06-01T16:03:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1371,"text":"Deep-Sea Research Part II: Topical Studies in Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"Geomorphic characterization of four shelf-sourced submarine canyons along the U.S. Mid-Atlantic continental margin","docAbstract":"Shelf-sourced submarine canyons are common features of continental margins and are fundamental to deep-sea sedimentary systems. Despite their geomorphic and geologic significance, relatively few passive margin shelf-breaching canyons worldwide have been mapped using modern geophysical methods. Between 2007 and 2012 a series of geophysical surveys was conducted across four major canyons of the US Mid-Atlantic margin: Wilmington, Baltimore, Washington, and Norfolk canyons. More than 5700 km<sup>2</sup> of high-resolution multibeam bathymetry and 890 line-km of sub-bottom CHIRP profiles were collected along the outer shelf and uppermost slope (depths of 80-1200 m). The data allowed us to compare and contrast the fine-scale morphology of each canyon system. The canyons have marked differences in the morphology and orientation of canyon heads, steepness and density of sidewall gullies, and the character of the continental shelf surrounding canyon rims. Down-canyon axial profiles for Washington, Baltimore and Wilmington canyons have linear shapes, and each canyon thalweg exhibits morphological evidence for recent, relatively small-scale sediment transport. For example, Washington Canyon displays extremely steep wall gradients and contains ~100 m wide, 5–10 m deep, v-shaped incisions down the canyon axis, suggesting modern or recent sediment transport. In contrast, the convex axial thalweg profile, the absence of thalweg incision, and evidence for sediment infilling at the canyon head, suggest that depositional processes strongly influence Norfolk Canyon during the current sea-level high-stand. The north walls of Wilmington, Washington and Norfolk canyons are steeper than the south walls due to differential erosion, though the underlying cause for this asymmetry is not clear. Furthermore, we speculate that most of the geomorphic features observed within the canyons (e.g., terraces, tributary canyons, gullies, and hanging valleys) were formed during the Pleistocene, and show only subtle modification by Holocene processes active during the present sea-level high-stand.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Deep-Sea Research Part II: Topical Studies in Oceanography","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.dsr2.2013.09.013","usgsCitation":"Obelcz, J., Brothers, D., Chaytor, J., ten Brink, U., Ross, S., and Brooke, S., 2013, Geomorphic characterization of four shelf-sourced submarine canyons along the U.S. Mid-Atlantic continental margin: Deep-Sea Research Part II: Topical Studies in Oceanography, v. 104, p. 106-119, https://doi.org/10.1016/j.dsr2.2013.09.013.","productDescription":"14 p.","startPage":"106","endPage":"119","numberOfPages":"14","ipdsId":"IP-051303","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":289824,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":289822,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.dsr2.2013.09.013"}],"country":"United States","otherGeospatial":"Cape Hatteras;Georges Bank;Hudson Canyon","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -75.0,37.0 ], [ -75.0,38.0 ], [ -72.0,38.0 ], [ -72.0,37.0 ], [ -75.0,37.0 ] ] ] } } ] }","volume":"104","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53c0ebe7e4b065ccca5fe38f","contributors":{"authors":[{"text":"Obelcz, Jeffrey jobelcz@usgs.gov","contributorId":5430,"corporation":false,"usgs":true,"family":"Obelcz","given":"Jeffrey","email":"jobelcz@usgs.gov","affiliations":[],"preferred":true,"id":495806,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brothers, Daniel S. dbrothers@usgs.gov","contributorId":3782,"corporation":false,"usgs":true,"family":"Brothers","given":"Daniel S.","email":"dbrothers@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":495804,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chaytor, Jason D. jchaytor@usgs.gov","contributorId":4961,"corporation":false,"usgs":true,"family":"Chaytor","given":"Jason D.","email":"jchaytor@usgs.gov","affiliations":[{"id":6706,"text":"Woods Hole Oceanographic Institution,","active":true,"usgs":false},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":495805,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"ten Brink, Uri S. 0000-0001-6858-3001 utenbrink@usgs.gov","orcid":"https://orcid.org/0000-0001-6858-3001","contributorId":127560,"corporation":false,"usgs":true,"family":"ten Brink","given":"Uri S.","email":"utenbrink@usgs.gov","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":495808,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ross, Steve W.","contributorId":41134,"corporation":false,"usgs":false,"family":"Ross","given":"Steve W.","affiliations":[{"id":32398,"text":"University of North Carolina Wilmington","active":true,"usgs":false}],"preferred":false,"id":495807,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brooke, Sandra","contributorId":101570,"corporation":false,"usgs":true,"family":"Brooke","given":"Sandra","affiliations":[],"preferred":false,"id":495809,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70128155,"text":"70128155 - 2013 - Comparison of elevation and remote sensing derived products as auxiliary data for climate surface interpolation","interactions":[],"lastModifiedDate":"2014-10-07T08:56:56","indexId":"70128155","displayToPublicDate":"2014-06-01T08:55:53","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2032,"text":"International Journal of Climatology","active":true,"publicationSubtype":{"id":10}},"title":"Comparison of elevation and remote sensing derived products as auxiliary data for climate surface interpolation","docAbstract":"Climate models may be limited in their inferential use if they cannot be locally validated or do not account for spatial uncertainty. Much of the focus has gone into determining which interpolation method is best suited for creating gridded climate surfaces, which often a covariate such as elevation (Digital Elevation Model, DEM) is used to improve the interpolation accuracy. One key area where little research has addressed is in determining which covariate best improves the accuracy in the interpolation. In this study, a comprehensive evaluation was carried out in determining which covariates were most suitable for interpolating climatic variables (e.g. precipitation, mean temperature, minimum temperature, and maximum temperature). We compiled data for each climate variable from 1950 to 1999 from approximately 500 weather stations across the Western United States (32° to 49° latitude and −124.7° to −112.9° longitude). In addition, we examined the uncertainty of the interpolated climate surface. Specifically, Thin Plate Spline (TPS) was used as the interpolation method since it is one of the most popular interpolation techniques to generate climate surfaces. We considered several covariates, including DEM, slope, distance to coast (Euclidean distance), aspect, solar potential, radar, and two Normalized Difference Vegetation Index (NDVI) products derived from Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS). A tenfold cross-validation was applied to determine the uncertainty of the interpolation based on each covariate. In general, the leading covariate for precipitation was radar, while DEM was the leading covariate for maximum, mean, and minimum temperatures. A comparison to other products such as PRISM and WorldClim showed strong agreement across large geographic areas but climate surfaces generated in this study (ClimSurf) had greater variability at high elevation regions, such as in the Sierra Nevada Mountains.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"International Journal of Climatology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Royal Meteorological Society","publisherLocation":"Chichester","doi":"10.1002/joc.3835","usgsCitation":"Alvarez, O., Guo, Q., Klinger, R.C., Li, W., and Doherty, P., 2013, Comparison of elevation and remote sensing derived products as auxiliary data for climate surface interpolation: International Journal of Climatology, v. 34, no. 7, p. 2258-2268, https://doi.org/10.1002/joc.3835.","productDescription":"11 p.","startPage":"2258","endPage":"2268","numberOfPages":"11","ipdsId":"IP-050933","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":294969,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":294953,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/joc.3835"}],"volume":"34","issue":"7","noUsgsAuthors":false,"publicationDate":"2013-10-18","publicationStatus":"PW","scienceBaseUri":"543500a1e4b0a4f4b46a237e","contributors":{"authors":[{"text":"Alvarez, Otto","contributorId":86284,"corporation":false,"usgs":true,"family":"Alvarez","given":"Otto","affiliations":[],"preferred":false,"id":502779,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Guo, Qinghua","contributorId":32855,"corporation":false,"usgs":true,"family":"Guo","given":"Qinghua","affiliations":[],"preferred":false,"id":502777,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Klinger, Robert C. 0000-0003-3193-3199 rcklinger@usgs.gov","orcid":"https://orcid.org/0000-0003-3193-3199","contributorId":5395,"corporation":false,"usgs":true,"family":"Klinger","given":"Robert","email":"rcklinger@usgs.gov","middleInitial":"C.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":502776,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Li, Wenkai","contributorId":108044,"corporation":false,"usgs":true,"family":"Li","given":"Wenkai","affiliations":[],"preferred":false,"id":502780,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Doherty, Paul","contributorId":38494,"corporation":false,"usgs":true,"family":"Doherty","given":"Paul","affiliations":[],"preferred":false,"id":502778,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70058631,"text":"70058631 - 2013 - Monitoring gray wolf populations using multiple survey methods","interactions":[],"lastModifiedDate":"2014-05-06T15:55:20","indexId":"70058631","displayToPublicDate":"2014-05-06T15:28:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Monitoring gray wolf populations using multiple survey methods","docAbstract":"The behavioral patterns and large territories of large carnivores make them challenging to monitor. Occupancy modeling provides a framework for monitoring population dynamics and distribution of territorial carnivores. We combined data from hunter surveys, howling and sign surveys conducted at predicted wolf rendezvous sites, and locations of radiocollared wolves to model occupancy and estimate the number of gray wolf (Canis lupus) packs and individuals in Idaho during 2009 and 2010. We explicitly accounted for potential misidentification of occupied cells (i.e., false positives) using an extension of the multi-state occupancy framework. We found agreement between model predictions and distribution and estimates of number of wolf packs and individual wolves reported by Idaho Department of Fish and Game and Nez Perce Tribe from intensive radiotelemetry-based monitoring. Estimates of individual wolves from occupancy models that excluded data from radiocollared wolves were within an average of 12.0% (SD = 6.0) of existing statewide minimum counts. Models using only hunter survey data generally estimated the lowest abundance, whereas models using all data generally provided the highest estimates of abundance, although only marginally higher. Precision across approaches ranged from 14% to 28% of mean estimates and models that used all data streams generally provided the most precise estimates. We demonstrated that an occupancy model based on different survey methods can yield estimates of the number and distribution of wolf packs and individual wolf abundance with reasonable measures of precision. Assumptions of the approach including that average territory size is known, average pack size is known, and territories do not overlap, must be evaluated periodically using independent field data to ensure occupancy estimates remain reliable. Use of multiple survey methods helps to ensure that occupancy estimates are robust to weaknesses or changes in any 1 survey method. Occupancy modeling may be useful for standardizing estimates across large landscapes, even if survey methods differ across regions, allowing for inferences about broad-scale population dynamics of wolves.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Wildlife Management","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.654","usgsCitation":"Ausband, D., Rich, L.N., Glenn, E., Mitchell, M.S., Zager, P., Miller, D.A., Waits, L.P., Ackerman, B.B., and Mack, C.M., 2013, Monitoring gray wolf populations using multiple survey methods: Journal of Wildlife Management, v. 78, no. 2, p. 335-346, https://doi.org/10.1002/jwmg.654.","productDescription":"12 p.","startPage":"335","endPage":"346","ipdsId":"IP-048939","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":286941,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":286940,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/jwmg.654"}],"country":"United States","state":"Idaho","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -117.24,41.99 ], [ -117.24,49.00 ], [ -111.04,49.00 ], [ -111.04,41.99 ], [ -117.24,41.99 ] ] ] } } ] }","volume":"78","issue":"2","noUsgsAuthors":false,"publicationDate":"2014-02-13","publicationStatus":"PW","scienceBaseUri":"5369f651e4b063fb73c0a9e7","contributors":{"authors":[{"text":"Ausband, David E.","contributorId":51441,"corporation":false,"usgs":true,"family":"Ausband","given":"David E.","affiliations":[],"preferred":false,"id":487207,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rich, Lindsey N.","contributorId":42119,"corporation":false,"usgs":true,"family":"Rich","given":"Lindsey","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":487206,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Glenn, Elizabeth M.","contributorId":96568,"corporation":false,"usgs":true,"family":"Glenn","given":"Elizabeth M.","affiliations":[],"preferred":false,"id":487211,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mitchell, Michael S. 0000-0002-0773-6905 mmitchel@usgs.gov","orcid":"https://orcid.org/0000-0002-0773-6905","contributorId":3716,"corporation":false,"usgs":true,"family":"Mitchell","given":"Michael","email":"mmitchel@usgs.gov","middleInitial":"S.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":487203,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zager, Pete","contributorId":90645,"corporation":false,"usgs":true,"family":"Zager","given":"Pete","affiliations":[],"preferred":false,"id":487210,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Miller, David A.W. davidmiller@usgs.gov","contributorId":4043,"corporation":false,"usgs":true,"family":"Miller","given":"David","email":"davidmiller@usgs.gov","middleInitial":"A.W.","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":487204,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Waits, Lisette P.","contributorId":87673,"corporation":false,"usgs":true,"family":"Waits","given":"Lisette","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":487209,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ackerman, Bruce B.","contributorId":6526,"corporation":false,"usgs":true,"family":"Ackerman","given":"Bruce","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":487205,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Mack, Curt M.","contributorId":58948,"corporation":false,"usgs":true,"family":"Mack","given":"Curt","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":487208,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70103281,"text":"sim3022 - 2013 - Metallogenic belt and mineral deposit maps of northeast Asia","interactions":[],"lastModifiedDate":"2023-05-26T15:56:06.537967","indexId":"sim3022","displayToPublicDate":"2014-04-30T14:11:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3022","title":"Metallogenic belt and mineral deposit maps of northeast Asia","docAbstract":"This report contains explanatory material and summary tables for lode mineral deposits and placer districts (Map A, sheet 1) and metallogenic belts of Northeast Asia (Maps B, C, and D on sheets 2, 3, and 4, respectively). The map region includes eastern Siberia, southeastern Russia, Mongolia, northeast China, and Japan. A large group of geologists—members of the joint international project, Major Mineral Deposits, Metallogenesis, and Tectonics of Northeast Asia—prepared the maps, tables, and introductory text. This is a cooperative project with the Russian Academy of Sciences, Mongolian Academy of Sciences, Mongolian National University, Ulaanbaatar, Mongolian Technical University, Mineral Resources Authority of Mongolia, Geological Research Institute, Jilin University, China Geological Survey, Korea Institute of Geoscience and Mineral Resources, Geological Survey of Japan, and U.S. Geological Survey. This report is one of a series of reports on the mineral resources, geodynamics, and metallogenesis of Northeast Asia. Companion studies include (1) a detailed geodynamics map of Northeast Asia (Parfenov and others, 2003); (2) a compilation of major mineral deposit models (Rodionov and Nokleberg, 2000; Rodionov and others, 2000); (3) a series of metallogenic belt maps (Obolenskiy and others, 2004); (4) location map of lode mineral deposits and placer districts of Northeast Asia (Ariunbileg and others, 2003b); (5) descriptions of metallogenic belts (Rodionov and others, 2004); (6) a database on significant metalliferous and selected nonmetalliferous lode deposits and selected placer districts (Ariunbileg and others, 2003a); and (7) a series of summary project publications (Ariunbileg and 74 others, 2003b).","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3022","collaboration":"Prepared in collaboration with Russian Academy of Sciences, Mongolian Academy of Sciences, Jilin University, Korean Institute of Geoscience and Minerals, Geological Survey of Japan/National Institute of Advanced Industrial Science and Technology","usgsCitation":"Obolenskiy, A.A., Rodionov, S.M., Dejidmaa, G., Gerel, O., Hwang, D., Miller, R.J., Nokleberg, W.J., Ogasawara, M., Smelov, A., Yan, H., and Seminskiy, Z.V., 2013, Metallogenic belt and mineral deposit maps of northeast Asia: U.S. Geological Survey Scientific Investigations Map 3022, 4 Sheets: 46.35 x 39.53 inches and smaller; Pamphlet: i, 14 p.; Readme; Metadata; Database; 3 Tables, https://doi.org/10.3133/sim3022.","productDescription":"4 Sheets: 46.35 x 39.53 inches and smaller; Pamphlet: i, 14 p.; Readme; Metadata; Database; 3 Tables","numberOfPages":"16","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":286814,"rank":13,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim3022.jpg"},{"id":286802,"rank":6,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3022/","linkFileType":{"id":5,"text":"html"}},{"id":286810,"rank":5,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/sim/3022/downloads/sim3022_data.zip"},{"id":286807,"rank":4,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sim/3022/pdf/sim3022_pamphlet.pdf"},{"id":286811,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sim/3022/downloads/sim3022_Table%201.zip"},{"id":286812,"rank":2,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sim/3022/downloads/sim3022_Table%202.zip"},{"id":286813,"rank":1,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sim/3022/downloads/sim3022_Table%203.zip"},{"id":286808,"rank":12,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sim/3022/downloads/sim3022_readme.txt"},{"id":286804,"rank":11,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3022/pdf/sim3022_sheet2.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":286805,"rank":10,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3022/pdf/sim3022_sheet3.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":286806,"rank":9,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3022/pdf/sim3022_sheet4.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":286803,"rank":8,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3022/pdf/sim3022_sheet1.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":286809,"rank":7,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sim/3022/downloads/metadata/"}],"scale":"7500000","projection":"Lambert Azimuthal equal-area projection","country":"China, Japan, Mongolia, Russia","otherGeospatial":"Asia","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 75.0,32.0 ], [ 75.0,82.0 ], [ 144.0,82.0 ], [ 144.0,32.0 ], [ 75.0,32.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53620d52e4b0c409c6289a30","contributors":{"authors":[{"text":"Obolenskiy, Alexander A. (compiler)","contributorId":11121,"corporation":false,"usgs":true,"family":"Obolenskiy","given":"Alexander","suffix":"(compiler)","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":493232,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rodionov, Sergey M.","contributorId":64726,"corporation":false,"usgs":true,"family":"Rodionov","given":"Sergey","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":493238,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dejidmaa, Gunchin","contributorId":47865,"corporation":false,"usgs":true,"family":"Dejidmaa","given":"Gunchin","email":"","affiliations":[],"preferred":false,"id":493237,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gerel, Ochir","contributorId":41520,"corporation":false,"usgs":true,"family":"Gerel","given":"Ochir","email":"","affiliations":[],"preferred":false,"id":493235,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hwang, Duk-Hwan","contributorId":43804,"corporation":false,"usgs":true,"family":"Hwang","given":"Duk-Hwan","email":"","affiliations":[],"preferred":false,"id":493236,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Miller, Robert J. rjmiller@usgs.gov","contributorId":2516,"corporation":false,"usgs":true,"family":"Miller","given":"Robert","email":"rjmiller@usgs.gov","middleInitial":"J.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":493231,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Nokleberg, Warren J. 0000-0002-1574-8869 wnokleberg@usgs.gov","orcid":"https://orcid.org/0000-0002-1574-8869","contributorId":2077,"corporation":false,"usgs":true,"family":"Nokleberg","given":"Warren","email":"wnokleberg@usgs.gov","middleInitial":"J.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":493230,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ogasawara, Masatsugu","contributorId":17638,"corporation":false,"usgs":true,"family":"Ogasawara","given":"Masatsugu","email":"","affiliations":[],"preferred":false,"id":493233,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Smelov, Alexander P.","contributorId":30685,"corporation":false,"usgs":true,"family":"Smelov","given":"Alexander P.","affiliations":[],"preferred":false,"id":493234,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Yan, Hongquan","contributorId":81559,"corporation":false,"usgs":true,"family":"Yan","given":"Hongquan","email":"","affiliations":[],"preferred":false,"id":493239,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Seminskiy, Zhan V.","contributorId":102567,"corporation":false,"usgs":true,"family":"Seminskiy","given":"Zhan","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":493240,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70129334,"text":"70129334 - 2013 - Geospatial considerations for a multiorganizational, landscape-scale program","interactions":[],"lastModifiedDate":"2017-06-30T14:06:43","indexId":"70129334","displayToPublicDate":"2014-04-21T10:33:02","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2374,"text":"Journal of Map & Geography Libraries","active":true,"publicationSubtype":{"id":10}},"title":"Geospatial considerations for a multiorganizational, landscape-scale program","docAbstract":"Geospatial data play an increasingly important role in natural resources management, conservation, and science-based projects. The management and effective use of spatial data becomes significantly more complex when the efforts involve a myriad of landscape-scale projects combined with a multiorganizational collaboration. There is sparse literature to guide users on this daunting subject; therefore, we present a framework of considerations for working with geospatial data that will provide direction to data stewards, scientists, collaborators, and managers for developing geospatial management plans. The concepts we present apply to a variety of geospatial programs or projects, which we describe as a “scalable framework” of processes for integrating geospatial efforts with management, science, and conservation initiatives. Our framework includes five tenets of geospatial data management: (1) the importance of investing in data management and standardization, (2) the scalability of content/efforts addressed in geospatial management plans, (3) the lifecycle of a geospatial effort, (4) a framework for the integration of geographic information systems (GIS) in a landscape-scale conservation or management program, and (5) the major geospatial considerations prior to data acquisition. We conclude with a discussion of future considerations and challenges.","language":"English","publisher":"Haworth Information Press","publisherLocation":"Binghamton, NY","doi":"10.1080/15420353.2014.885925","usgsCitation":"O'Donnell, M., Assal, T.J., Anderson, P.J., and Bowen, Z.H., 2013, Geospatial considerations for a multiorganizational, landscape-scale program: Journal of Map & Geography Libraries, v. 10, no. 1, p. 62-99, https://doi.org/10.1080/15420353.2014.885925.","productDescription":"38 p.","startPage":"62","endPage":"99","numberOfPages":"38","ipdsId":"IP-052052","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":473354,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/15420353.2014.885925","text":"Publisher Index Page"},{"id":295532,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":295497,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1080/15420353.2014.885925"}],"volume":"10","issue":"1","noUsgsAuthors":false,"publicationDate":"2014-04-21","publicationStatus":"PW","scienceBaseUri":"544775afe4b0f888a81b831d","contributors":{"authors":[{"text":"O'Donnell, Michael S.","contributorId":40667,"corporation":false,"usgs":true,"family":"O'Donnell","given":"Michael S.","affiliations":[],"preferred":false,"id":503593,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Assal, Timothy J. 0000-0001-6342-2954 assalt@usgs.gov","orcid":"https://orcid.org/0000-0001-6342-2954","contributorId":2203,"corporation":false,"usgs":true,"family":"Assal","given":"Timothy","email":"assalt@usgs.gov","middleInitial":"J.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":503591,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anderson, Patrick J. 0000-0003-2281-389X andersonpj@usgs.gov","orcid":"https://orcid.org/0000-0003-2281-389X","contributorId":3590,"corporation":false,"usgs":true,"family":"Anderson","given":"Patrick","email":"andersonpj@usgs.gov","middleInitial":"J.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":503592,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bowen, Zachary H. 0000-0002-8656-1831 bowenz@usgs.gov","orcid":"https://orcid.org/0000-0002-8656-1831","contributorId":821,"corporation":false,"usgs":true,"family":"Bowen","given":"Zachary","email":"bowenz@usgs.gov","middleInitial":"H.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":503590,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
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