{"pageNumber":"223","pageRowStart":"5550","pageSize":"25","recordCount":46677,"records":[{"id":70212786,"text":"ofr20191023C - 2020 - Focus areas for data acquisition for potential domestic resources of 11 critical minerals in Alaska—Aluminum, cobalt, graphite, lithium, niobium, platinum group elements, rare earth elements, tantalum, tin, titanium, and tungsten, chap. C of U.S. Geological Survey, Focus areas for data acquisition for potential domestic sources of critical minerals","interactions":[],"lastModifiedDate":"2026-03-25T16:56:03.904619","indexId":"ofr20191023C","displayToPublicDate":"2022-07-14T10:32:00","publicationYear":"2020","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":"2019-1023","chapter":"C","displayTitle":"Focus Areas for Data Acquisition for Potential Domestic Resources of 11 Critical Minerals in Alaska—Aluminum, Cobalt, Graphite, Lithium, Niobium, Platinum Group Elements, Rare Earth Elements, Tantalum, Tin, Titanium, and Tungsten","title":"Focus areas for data acquisition for potential domestic resources of 11 critical minerals in Alaska—Aluminum, cobalt, graphite, lithium, niobium, platinum group elements, rare earth elements, tantalum, tin, titanium, and tungsten, chap. C of U.S. Geological Survey, Focus areas for data acquisition for potential domestic sources of critical minerals","docAbstract":"

Phase 2 of the Earth Mapping Resources Initiative (Earth MRI) focuses on geologic belts that are favorable for hosting mineral systems that may contain select critical minerals. Phase 1 of the Earth MRI program focused on rare earth elements (REE), and phase 2 adds aluminum, cobalt, graphite, lithium, niobium, platinum-group metals, tantalum, tin, titanium, and tungsten. This report describes the methodology and techniques utilized to define focus areas for future data acquisition in Alaska; the conterminous United States are covered in a separate report.

Definition of focus areas relies on a mineral systems framework that considers geologic features that may influence or control the formation and preservation of a mineral deposit and links the critical commodities to genetically related processes. Mineral systems are therefore larger than any given deposit. Evaluation of these larger systems allows for a broader understanding of how and where critical minerals may move through geologic systems.

Delineation of focus areas in Alaska was informed by statewide geological, geochemical, geophysical, and mineral occurrence datasets that are publicly available. Additionally, previously published prospectivity analyses for six different critical mineral-bearing deposit types help identify focus areas. A total of 74 focus areas prospective for the phase 2 critical minerals that occur in 12 different mineral systems were defined in Alaska. Identified focus areas may be used to guide future geologic, geochemical, and geophysical data in the State of Alaska.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191023C","collaboration":"Prepared in cooperation with the Alaska Division of Geological & Geophysical Surveys","usgsCitation":"Kreiner, D.C., and Jones, J.V., 2020, Focus areas for data acquisition for potential domestic resources of 11 critical minerals in Alaska—Aluminum, cobalt, graphite, lithium, niobium, platinum group elements, rare earth elements, tantalum, tin, titanium, and tungsten (ver. 1.1, July 2022), chap. C of U.S. Geological Survey, Focus areas for data acquisition for potential domestic sources of critical minerals: U.S. Geological Survey Open-File Report 2019–1023, 20 p., https://doi.org/10.3133/ofr20191023C.","productDescription":"viii, 20 p.","onlineOnly":"Y","ipdsId":"IP-118999","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":403734,"rank":7,"type":{"id":6,"text":"Chapter"},"url":"https://doi.org/10.3133/ofr20191023E","text":"Open-File Report 2019-1023-E","linkHelpText":"- Alaska Focus Area Definition for Data Acquisition for Potential Domestic Sources of Critical Minerals in Alaska for Antimony, Barite, Beryllium, Chromium, Fluorspar, Hafnium, Magnesium, Manganese, Uranium, Vanadium, and Zirconium"},{"id":403733,"rank":6,"type":{"id":6,"text":"Chapter"},"url":"https://doi.org/10.3133/ofr20191023D","text":"Open-File Report 2019-1023-D","linkHelpText":"- Focus Areas for Data Acquisition for Potential Domestic Resources of 13 Critical Minerals in the Conterminous United States and Puerto Rico—Antimony, Barite, Beryllium, Chromium, Fluorspar, Hafnium, Helium, Magnesium, Manganese, Potash, Uranium, Vanadium, and Zirconium"},{"id":501523,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_110565.htm","linkFileType":{"id":5,"text":"html"}},{"id":378569,"rank":5,"type":{"id":6,"text":"Chapter"},"url":"https://doi.org/10.3133/ofr20191023B","text":"Open-File Report 2019-1023-B","description":"Open-File Report 2019-1023-B","linkHelpText":"- Focus Areas for Data Acquisition for Potential Domestic Resources of 11 Critical Minerals in the Conterminous United States, Hawaii, and Puerto Rico—Aluminum, Cobalt, Graphite, Lithium, Niobium, Platinum-Group Elements, Rare Earth Elements, Tantalum, Tin, Titanium, and Tungsten"},{"id":378568,"rank":4,"type":{"id":6,"text":"Chapter"},"url":"https://doi.org/10.3133/ofr20191023A","text":"Open-File Report 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Director, Alaska Science Center
U.S. Geological Survey
4210 University Drive
Anchorage, Alaska 99508

","tableOfContents":"","publishedDate":"2020-09-17","revisedDate":"2022-07-14","noUsgsAuthors":false,"publicationDate":"2020-09-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Kreiner, Douglas C. 0000-0002-4405-1403","orcid":"https://orcid.org/0000-0002-4405-1403","contributorId":220474,"corporation":false,"usgs":true,"family":"Kreiner","given":"Douglas","email":"","middleInitial":"C.","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":799118,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jones, James V. III 0000-0002-6602-5935 jvjones@usgs.gov","orcid":"https://orcid.org/0000-0002-6602-5935","contributorId":201245,"corporation":false,"usgs":true,"family":"Jones","given":"James","suffix":"III","email":"jvjones@usgs.gov","middleInitial":"V.","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":799119,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70213160,"text":"ofr20191023B - 2020 - Focus areas for data acquisition for potential domestic resources of 11 critical minerals in the conterminous United States, Hawaii, and Puerto Rico—Aluminum, cobalt, graphite, lithium, niobium, platinum-group elements, rare earth elements, tantalum, tin, titanium, and tungsten","interactions":[],"lastModifiedDate":"2026-03-25T16:54:19.281618","indexId":"ofr20191023B","displayToPublicDate":"2022-07-14T10:31:00","publicationYear":"2020","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":"2019-1023","chapter":"B","displayTitle":"Focus Areas for Data Acquisition for Potential Domestic Resources of 11 Critical Minerals in the Conterminous United States, Hawaii, and Puerto Rico—Aluminum, Cobalt, Graphite, Lithium, Niobium, Platinum-Group Elements, Rare Earth Elements, Tantalum, Tin, Titanium, and Tungsten","title":"Focus areas for data acquisition for potential domestic resources of 11 critical minerals in the conterminous United States, Hawaii, and Puerto Rico—Aluminum, cobalt, graphite, lithium, niobium, platinum-group elements, rare earth elements, tantalum, tin, titanium, and tungsten","docAbstract":"

In response to a need for information on potential domestic sources of critical minerals, the Earth Mapping Resources Initiative (Earth MRI) was established to identify and prioritize areas for acquisition of new geologic mapping, geophysical data, and elevation data to improve our knowledge of the geologic framework of the United States. Phase 1 of Earth MRI concentrated on those geologic terranes favorable for hosting the rare earth elements (REEs). Phase 2 continued to address the REEs and also identified focus areas for potential domestic sources of 10 more of the 35 critical minerals on the U.S. critical minerals list (aluminum, cobalt, graphite, lithium, niobium, platinum-group elements, tantalum, tin, titanium, tungsten). This report describes the methodology, data sources, and summary results for mineral systems that host these 11 critical minerals in the conterminous United States, Hawaii, and Puerto Rico; Alaska is covered in a separate report. The mineral systems framework adopted for this study links critical mineral commodities to families of genetically related mineral deposit types. The mineral systems approach is an efficient approach, providing a simultaneous evaluation of geologic terranes through aggregation of genetically related mineral deposit types that are much larger than individual ore deposits. Geologic, geochemical, topographic, and geophysical mapping provided by Earth MRI will document geologic features that reflect the extent of individual mineral systems and provide information about critical mineral deposits that may not have been recognized previously.

Each critical mineral commodity is discussed in terms of importance to the Nation’s economy, modes of occurrence, mineral systems, and deposit types along with maps and tables listing examples of focus areas for each critical mineral. Important mineral systems for these critical minerals include chemical weathering systems for aluminum (bauxite); placer systems for titanium and REEs; metamorphic systems for graphite; mafic magmatic systems for platinum-group elements and cobalt; lacustrine evaporite and porphyry tin systems for lithium; and copper-molybdenum-gold (Cu-Mo-Au) systems for tungsten. REEs occur in many different mineral systems. Focus areas were developed by scientists from the U.S. Geological Survey in collaboration with scientists from State geological surveys and other institutions. This first national-scale compilation of focus areas represents an initial step in addressing the Nation’s critical mineral needs by screening areas for acquisition of new data to provide the geologic framework necessary for identifying domestic sources of critical minerals.

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B of U.S. Geological Survey, Focus areas for data acquisition for potential domestic sources of critical minerals: U.S. Geological Survey Open-File Report 2019–1023, 67 p., https://doi.org/10.3133/ofr20191023B.","productDescription":"xiii, 67 p.","numberOfPages":"67","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-119187","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":436687,"rank":9,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9U6SODG","text":"USGS data release","linkHelpText":"GIS for focus areas of potential domestic resources of 11 critical minerals-aluminum, 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Coordinator, Mineral Resources Program
U.S. Geological Survey
913 National Center
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","tableOfContents":"","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2020-09-18","revisedDate":"2022-07-14","noUsgsAuthors":false,"publicationDate":"2020-09-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Hammarstrom, Jane M. 0000-0003-2742-3460 jhammars@usgs.gov","orcid":"https://orcid.org/0000-0003-2742-3460","contributorId":1226,"corporation":false,"usgs":true,"family":"Hammarstrom","given":"Jane","email":"jhammars@usgs.gov","middleInitial":"M.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"preferred":true,"id":798447,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dicken, Connie L. 0000-0002-1617-8132 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Center","active":true,"usgs":true}],"preferred":true,"id":798457,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Stillings, Lisa L. 0000-0002-9011-8891 stilling@usgs.gov","orcid":"https://orcid.org/0000-0002-9011-8891","contributorId":193548,"corporation":false,"usgs":true,"family":"Stillings","given":"Lisa","email":"stilling@usgs.gov","middleInitial":"L.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":798458,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70228638,"text":"70228638 - 2020 - Animal movement models with mechanistic selection functions","interactions":[],"lastModifiedDate":"2022-02-16T21:09:54.812755","indexId":"70228638","displayToPublicDate":"2022-06-20T15:05:32","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5548,"text":"Spatial Statistics","active":true,"publicationSubtype":{"id":10}},"title":"Animal movement models with mechanistic selection functions","docAbstract":"A suite of statistical methods are used to study animal movement. Most of\nthese methods treat animal trajectory data in one of three ways: as discrete pro-\ncesses, as continuous processes, or as point processes. We brie\ny review each of\nthese approaches and then focus in on the latter. In the context of point processes,\nso-called resource selection analyses are among the most common way to statis-\ntically treat animal trajectory data. However, most resource selection analyses provide inference based on approximations of point process models. The forms of\nthese models have been limited to a few types of specications that provide infer-\nence about relative resource use and, less commonly, probability of use. For more\ngeneral spatio-temporal point process models, the most common type of analysis\noften proceeds with a data augmentation approach that is used to create a binary\ndata set that can be analyzed with conditional logistic regression. We show that\nthe conditional logistic regression likelihood can be generalized to accommodate a\nvariety of alternative specications related to resource selection. We then provide\nan example of a case where a spatio-temporal point process model coincides with\nthat implied by a mechanistic model for movement expressed as a partial dier-\nential equation derived from rst principles of movement. We demonstrate that\ninference from this form of point process model is intuitive (and could be useful\nfor management and conservation) by analyzing a set of telemetry data from a\nmountain lion in Colorado, USA, to understand the eects of spatially explicit\nenvironmental conditions on movement behavior of this species.","language":"English","publisher":"Elsevier","doi":"10.1016/j.spasta.2019.100406","usgsCitation":"Hooten, M., Lu, X., Garlick, M., and Powell, J., 2020, Animal movement models with mechanistic selection functions: Spatial Statistics, v. 37, 100406, 14 p., https://doi.org/10.1016/j.spasta.2019.100406.","productDescription":"100406, 14 p.","ipdsId":"IP-113283","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":454582,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://arxiv.org/abs/1911.03549","text":"External Repository"},{"id":396041,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"37","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hooten, Mevin 0000-0002-1614-723X mhooten@usgs.gov","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":2958,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","email":"mhooten@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false}],"preferred":true,"id":834902,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lu, Xinyi","contributorId":279368,"corporation":false,"usgs":false,"family":"Lu","given":"Xinyi","affiliations":[{"id":13606,"text":"CSU","active":true,"usgs":false}],"preferred":false,"id":834903,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Garlick, Martha J.","contributorId":279369,"corporation":false,"usgs":false,"family":"Garlick","given":"Martha J.","affiliations":[{"id":57249,"text":"sdsmt","active":true,"usgs":false}],"preferred":false,"id":834904,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Powell, James A.","contributorId":279370,"corporation":false,"usgs":false,"family":"Powell","given":"James A.","affiliations":[{"id":28050,"text":"USU","active":true,"usgs":false}],"preferred":false,"id":834905,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70232230,"text":"70232230 - 2020 - Lesser prairie-chicken (Tympanuchus pallidicinctus) use of man-made water sources","interactions":[],"lastModifiedDate":"2022-06-16T13:48:05.370823","indexId":"70232230","displayToPublicDate":"2022-01-26T08:38:26","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3451,"text":"Southwestern Naturalist","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Lesser prairie-chicken (Tympanuchus pallidicinctus) use of man-made water sources","title":"Lesser prairie-chicken (Tympanuchus pallidicinctus) use of man-made water sources","docAbstract":"

The lesser prairie-chicken (Tympanuchus pallidicinctus) occurs in the semiarid southern Great Plains, a region prone to periods of drought. Researchers generally believe that lesser prairie-chickens are able to satisfy their water requirements through preformed water and metabolic processes, but also know that they experience low survival and reproductive success during periods of drought. We used motion-sensing cameras to assess lesser prairie-chicken visits to man-made free water sources over a 48-month period from March 2009 to February 2013 in west Texas. Our objective was to examine temporal patterns of water use by lesser prairie-chickens, and to explore life history phenology and environmental conditions that may influence the species' use of free water. We documented 1,439 visits to water sources by lesser prairie-chickens. Their use of water sources was high during the winter months (December–February; 92 visits per 100 trap days) but the highest average visit rate to water sources occurred during the lekking-nesting life stage (March–May; 146 visits per 100 trap days). Water use was lower during the brood-rearing stage (June–August; 71 visits per 100 trap days) and lowest during the brood dispersal and independence stage (September–November; 19 visits per 100 trap days). Water use was strongly associated with dew point (P < 0.0001) and temperature (P = 0.0002) but was not associated with precipitation (P = 0.1037). These data indicate life-cycle stage (e.g., lekking-nesting) and reduced availability of preformed water may influence use of free water sources by lesser prairie-chickens. Current climate models predict the region of the study area will experience increases in temperature and decreases in frequency of precipitation. The combined effect of this would be reduced environmental moisture. If the prediction of increasing aridity in the region holds true, man-made water sources may become a tool for conservation of the species.

","language":"English","publisher":"Southwestern Association of Naturalists","doi":"10.1894/0038-4909-65.3-4.197","usgsCitation":"Gicklhorn, T.S., Boal, C.W., and Borsdorf, P.K., 2020, Lesser prairie-chicken (Tympanuchus pallidicinctus) use of man-made water sources: Southwestern Naturalist, v. 65, no. 3-4, p. 197-204, https://doi.org/10.1894/0038-4909-65.3-4.197.","productDescription":"8 p.","startPage":"197","endPage":"204","ipdsId":"IP-083938","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":402264,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas","county":"Cochran County, Hockley County, Terry County, Yoakum County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -103.03802490234375,\n 33.01557297778958\n ],\n [\n -102.36785888671875,\n 33.01557297778958\n ],\n [\n -102.36785888671875,\n 33.73347670599252\n ],\n [\n -103.03802490234375,\n 33.73347670599252\n ],\n [\n -103.03802490234375,\n 33.01557297778958\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"65","issue":"3-4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gicklhorn, Trevor S.","contributorId":166698,"corporation":false,"usgs":false,"family":"Gicklhorn","given":"Trevor","email":"","middleInitial":"S.","affiliations":[{"id":24740,"text":"Department of Natural Resources Management, Texas Tech University, Lubbock, TX, 79409, USA","active":true,"usgs":false}],"preferred":false,"id":844733,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boal, Clint W. 0000-0001-6008-8911 cboal@usgs.gov","orcid":"https://orcid.org/0000-0001-6008-8911","contributorId":1909,"corporation":false,"usgs":true,"family":"Boal","given":"Clint","email":"cboal@usgs.gov","middleInitial":"W.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":844734,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Borsdorf, Philip K.","contributorId":93386,"corporation":false,"usgs":false,"family":"Borsdorf","given":"Philip","email":"","middleInitial":"K.","affiliations":[{"id":24740,"text":"Department of Natural Resources Management, Texas Tech University, Lubbock, TX, 79409, USA","active":true,"usgs":false}],"preferred":false,"id":844735,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70208401,"text":"ofr20201012 - 2020 - Major-element compositional data and thermal data for drill core from Kīlauea Iki lava lake, plus analyses of glasses from scoria of the 1959 summit eruption of Kīlauea Volcano, Hawaii","interactions":[],"lastModifiedDate":"2021-12-16T12:03:49.083736","indexId":"ofr20201012","displayToPublicDate":"2021-12-15T15:40:00","publicationYear":"2020","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":"2020-1012","displayTitle":"Major-Element Compositional Data and Thermal Data for Drill Core from Kīlauea Iki Lava Lake, Plus Analyses of Glasses from Scoria of the 1959 Summit Eruption of Kīlauea Volcano, Hawaii","title":"Major-element compositional data and thermal data for drill core from Kīlauea Iki lava lake, plus analyses of glasses from scoria of the 1959 summit eruption of Kīlauea Volcano, Hawaii","docAbstract":"

This report presents electron microprobe data on glasses and selected crystalline phases from Kīlauea Iki lava lake and glasses from the 1959 summit eruption of Kīlauea Volcano, Hawaii. Some of these data have been published previously, but the complete set has not been published before. In addition, this report includes electron microprobe data for phases in melting experiments reported earlier, which form the basis for using many of the glass compositions reported here to estimate quenching temperatures of the samples. Finally, because of the latter application, this report includes all useful field determinations of temperature taken in Kīlauea Iki boreholes from 1967 to 1988. These field measurements have been merged with geothermometry based on glass and Fe-Ti oxide compositions to produce a comprehensive review of all available thermal information for Kīlauea Iki. Making these datasets available completes documentation of field and chemical information on Kīlauea Iki lava lake, supplementing six previous U.S. Geological Survey Open-File Reports listed in the References Cited.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201012","usgsCitation":"Helz, R.T., 2020, Major-element compositional data and thermal data for drill core from Kīlauea Iki lava lake, plus analyses of glasses from scoria of the 1959 summit eruption of Kīlauea Volcano, Hawaii (ver 1.1, December 2021): U.S. Geological Survey Open-File Report 2020–1012, 48 p., https://doi.org/10.3133/ofr20201012.","productDescription":"Report: v, 48 p.; Appendix 1-2","numberOfPages":"54","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-109981","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":374174,"rank":2,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2020/1012/ofr20201012_appendix1.xlsx","text":"Appendix 1","size":"206 KB","linkFileType":{"id":3,"text":"xlsx"},"linkHelpText":"- Tables 1.1–1.13 as an Excel file"},{"id":374175,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2020/1012/ofr20201012_appendix2.xlsx","text":"Appendix 2","size":"48.5 KB","linkFileType":{"id":3,"text":"xlsx"},"linkHelpText":"- Tables 2.1–2.4 as an Excel file"},{"id":374172,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1012/coverthb2.jpg"},{"id":374177,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2020/1012/ofr20201021_appendix2_csv.zip","text":"Appendix 2","size":"5.50 KB","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- Tables 2.1–2.4 as CSV files in a zipped folder"},{"id":374205,"rank":6,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1012/ofr20201012.pdf","text":"Report","size":"3.00 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1012"},{"id":392665,"rank":7,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2020/1012/versionHist.txt","size":"691 B","linkFileType":{"id":2,"text":"txt"}},{"id":374176,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2020/1012/ofr20201021_appendix1_csv.zip","text":"Appendix 1","size":"41.5 KB","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- Tables 1.1–1.13 as CSV files in a zipped folder"}],"country":"United States","state":"Hawaii","otherGeospatial":"Kīlauea Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.30410766601562,\n 19.38759093442151\n ],\n [\n -155.2306365966797,\n 19.38759093442151\n ],\n [\n -155.2306365966797,\n 19.44846418467642\n ],\n [\n -155.30410766601562,\n 19.44846418467642\n ],\n [\n -155.30410766601562,\n 19.38759093442151\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: April 23, 2020; Version 1.1: December 15, 2021","contact":"

Director, Florence Bascom Geoscience Center
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 21092

","tableOfContents":"","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2020-04-23","revisedDate":"2021-12-15","noUsgsAuthors":false,"publicationDate":"2020-04-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Helz, Rosalind Tuthill 0000-0003-1550-0684","orcid":"https://orcid.org/0000-0003-1550-0684","contributorId":16806,"corporation":false,"usgs":true,"family":"Helz","given":"Rosalind Tuthill","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":781733,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70214145,"text":"70214145 - 2020 - Seismic monitoring & response for the Trans-Alaska Pipeline System","interactions":[],"lastModifiedDate":"2024-02-21T15:50:09.404918","indexId":"70214145","displayToPublicDate":"2021-12-01T11:22:40","publicationYear":"2020","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Seismic monitoring & response for the Trans-Alaska Pipeline System","docAbstract":"The 800-mile Trans Alaska Pipeline System (TAPS) passes through extremely remote regions, where there is a high potential for seismic activity. Alyeska Pipeline Service Company, the TAPS operator, has been on the forefront of seismic engineering and situational awareness, and continues to enhance its capabilities. TAPS has used earthquake monitoring since the pipeline was constructed in 1977 and recently upgraded to a fourth-generation of its monitoring system. This upgrade includes recent technology to improve accuracy and increase system redundancy, and it incorporates lessons learned during the 2018 M6.3 Kaktovik and the 2018 M7.1 Anchorage earthquakes. The modernized earthquake monitoring system includes strong-motion accelerograph stations installed at key locations along the pipeline tied into the control system to provide real-time detection of seismic events. The accelerometers also telemeter data to provide local constraints in ShakeMap so that they not only provide site-specific shaking values, but also contribute openly to constraining ground motions elsewhere so shaking at locations without stations can be better inferred. Alyeska then employs U. S. Geological Survey’s ShakeCast system to automatically ingest the ShakeMap to provide near real-time alerts of shaking as well as inspection priorities across the system, both for pipeline assets and infrastructure. TAPS stakeholders who receive ShakeCast alerts via email and text messages include controllers, engineers, and emergency managers. As part of our standard post-earthquake protocol, damage assessment checklists have been pre-deployed at multiple locations to guide these teams as they determine the integrity of TAPS following an event. This unprecedented level of situational awareness allows for rapid prioritization and deployment of damage assessment teams. The purpose of this manuscript is to expand on the details of these systems.","conferenceTitle":"17th World Conference on Earthquake Engineering","conferenceDate":"September 13-18, 2020","conferenceLocation":"Sendai, Japan","language":"English","publisher":"Japan Association for Earthquake Engineering","usgsCitation":"Strait, S., and Wald, D.J., 2020, Seismic monitoring & response for the Trans-Alaska Pipeline System, 17th World Conference on Earthquake Engineering, Sendai, Japan, September 13-18, 2020, 12 p.","productDescription":"12 p.","ipdsId":"IP-116224","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":378710,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://wcee.nicee.org/wcee/seventeenth_conf_sendai_japan/","linkFileType":{"id":5,"text":"html"}},{"id":425800,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -144.3699605637841,\n 60.231305314797595\n ],\n [\n -144.3699605637841,\n 70.37934050762061\n ],\n [\n -152.86285792275456,\n 70.37934050762061\n ],\n [\n -152.86285792275456,\n 60.231305314797595\n ],\n [\n -144.3699605637841,\n 60.231305314797595\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Strait, S","contributorId":241100,"corporation":false,"usgs":false,"family":"Strait","given":"S","email":"","affiliations":[{"id":48206,"text":"Alyeska Pipeline Service Company","active":true,"usgs":false}],"preferred":false,"id":799561,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wald, David J. 0000-0002-1454-4514 wald@usgs.gov","orcid":"https://orcid.org/0000-0002-1454-4514","contributorId":795,"corporation":false,"usgs":true,"family":"Wald","given":"David","email":"wald@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":799562,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70214144,"text":"70214144 - 2020 - An update of USGS bear-real-time earthquake shaking and impact products","interactions":[],"lastModifiedDate":"2024-02-21T15:49:50.02989","indexId":"70214144","displayToPublicDate":"2021-12-01T11:11:54","publicationYear":"2020","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"An update of USGS bear-real-time earthquake shaking and impact products","docAbstract":"We report on advancements in both hazard and consequence modeling that form the core of the U.S. Geological Survey’s (USGS) strategy to improve rapid earthquake shaking and loss estimates. Whereas our primary goal is to improve our operational capabilities of the USGS National Earthquake Information Center, the science, software, and datasets behind these systems continue to advance uses and studies of earthquake shaking and impact by the seismological, engineering, financial, and risk modeling communities. Several important updates to our integrated shaking and impact products are outlined and we introduce new earthquake information products that have recently been brought online, including rapid ground failure estimates and more spatially refined loss estimates domestically (in the U.S). We continue to compile, develop, and refine key openly available models and datasets that contribute to calibrating these systems and report on the collection and storage of new inventories. We also describe some of the basic operational considerations in the current generation of these shaking and loss-estimation systems. A key aspect of the product integration and development is leveraging earthquake-hazard and loss-modeling science done internally (within the USGS) and by external researchers and collaborators. Lastly, we outline new opportunities for further research and development by emphasizing scientific, data, and application gaps and challenges that must be solved in order to improve our shaking and impact information tools.","conferenceTitle":"17th World Conference on Earthquake Engineering","conferenceDate":"September 13-18, 2020","conferenceLocation":"Sendai, Japan","language":"English","publisher":"Japan Association for Earthquake Engineering","usgsCitation":"Wald, D.J., Jaiswal, K.S., Marano, K., Hearne, M., Lin, K., Slosky, D., Allstadt, K.E., Thompson, E.M., Worden, C., Hayes, G.P., and Quitoriano, V., 2020, An update of USGS bear-real-time earthquake shaking and impact products, 17th World Conference on Earthquake Engineering, Sendai, Japan, September 13-18, 2020, 12 p.","productDescription":"12 p.","ipdsId":"IP-116227","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":378709,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://wcee.nicee.org/wcee/seventeenth_conf_sendai_japan/"},{"id":425799,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Wald, David J. 0000-0002-1454-4514 wald@usgs.gov","orcid":"https://orcid.org/0000-0002-1454-4514","contributorId":795,"corporation":false,"usgs":true,"family":"Wald","given":"David","email":"wald@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":799550,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jaiswal, Kishor S. 0000-0002-5803-8007 kjaiswal@usgs.gov","orcid":"https://orcid.org/0000-0002-5803-8007","contributorId":149796,"corporation":false,"usgs":true,"family":"Jaiswal","given":"Kishor","email":"kjaiswal@usgs.gov","middleInitial":"S.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":799551,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Marano, Kristin 0000-0002-0420-2748 kmarano@usgs.gov","orcid":"https://orcid.org/0000-0002-0420-2748","contributorId":207906,"corporation":false,"usgs":true,"family":"Marano","given":"Kristin","email":"kmarano@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":799552,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hearne, Mike 0000-0002-8225-2396 mhearne@usgs.gov","orcid":"https://orcid.org/0000-0002-8225-2396","contributorId":4659,"corporation":false,"usgs":true,"family":"Hearne","given":"Mike","email":"mhearne@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":799553,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lin, Kuo-wan 0000-0002-7520-8151 klin@usgs.gov","orcid":"https://orcid.org/0000-0002-7520-8151","contributorId":1539,"corporation":false,"usgs":true,"family":"Lin","given":"Kuo-wan","email":"klin@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":799554,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Slosky, Daniel 0000-0001-7407-3606 dslosky@usgs.gov","orcid":"https://orcid.org/0000-0001-7407-3606","contributorId":194954,"corporation":false,"usgs":true,"family":"Slosky","given":"Daniel","email":"dslosky@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":799555,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Allstadt, Kate E. 0000-0003-4977-5248","orcid":"https://orcid.org/0000-0003-4977-5248","contributorId":138704,"corporation":false,"usgs":true,"family":"Allstadt","given":"Kate","email":"","middleInitial":"E.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":799556,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Thompson, Eric M. 0000-0002-6943-4806 emthompson@usgs.gov","orcid":"https://orcid.org/0000-0002-6943-4806","contributorId":150897,"corporation":false,"usgs":true,"family":"Thompson","given":"Eric","email":"emthompson@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":799557,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Worden, Charles 0000-0003-1181-685X cbworden@usgs.gov","orcid":"https://orcid.org/0000-0003-1181-685X","contributorId":152042,"corporation":false,"usgs":true,"family":"Worden","given":"Charles","email":"cbworden@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":799558,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Hayes, Gavin P. 0000-0003-3323-0112 ghayes@usgs.gov","orcid":"https://orcid.org/0000-0003-3323-0112","contributorId":147556,"corporation":false,"usgs":true,"family":"Hayes","given":"Gavin","email":"ghayes@usgs.gov","middleInitial":"P.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":799559,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Quitoriano, Vince 0000-0003-4157-1101 vinceq@usgs.gov","orcid":"https://orcid.org/0000-0003-4157-1101","contributorId":2582,"corporation":false,"usgs":true,"family":"Quitoriano","given":"Vince","email":"vinceq@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":799560,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70228603,"text":"70228603 - 2020 - Decision context as an essential component of population viability analysis","interactions":[],"lastModifiedDate":"2022-02-14T14:59:02.146641","indexId":"70228603","displayToPublicDate":"2021-09-30T08:41:55","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1321,"text":"Conservation Biology","active":true,"publicationSubtype":{"id":10}},"title":"Decision context as an essential component of population viability analysis","docAbstract":"

Population viability analysis (PVA) is a widely used tool that applies demographic data in simulation frameworks to assess extinction risk for species or populations. It is used in diverse conservation applications, including evaluating management effectiveness, relative risk of threats, and potential changes to protective status (Beissinger & McCullough, 2002), and can be a critical tool for making decisions with imperfect knowledge of the system state, often on limited timelines (Meine et al., 2006).

Chaudhary and Oli (2020) recently developed a framework to appraise the quality of PVAs based on the presence of essential background, model, and analysis components. They evaluated 160 published PVAs and reported a decline in the quality of PVAs over time (1990−2017). We agree PVA studies should report unambiguous descriptions of their essential components (Table 1 in Chaudhary and Oli) and explicitly state the model's biological and statistical assumptions. The need for increased transparency in PVAs is evident. Morrison et al. (2016) reported that only 50% of PVAs published in peer-reviewed and gray literature were both reproducible and repeatable. Further, in an examination of 67 studies that used matrix population models (widely used in PVAs), Kendall et al. (2019) reported that models frequently contained misspecification errors. Given the rapid advancement of simulation techniques, updated guidance for PVA construction is warranted.

However, we believe the essential PVA components identified by Chaudhary and Oli contain a critical omission: the decision context in which the PVA was created and its usefulness in that context. Quality and utility are not mutually exclusive; however, some models that do not meet idealized quality standards might still be valuable because they are useful and represent the best available science for a given decision context (hereafter, decision-support models). The definition of quality for decision-support models should be different than models developed for the purpose of learning (hereafter, heuristic models) and should incorporate how useful the model was, despite information gaps. We further argue that assessment questions should be used prospectively to guide modeling projects, rather than for retrospective comparison of model quality.

","language":"English","publisher":"Society for Conservation Biology","doi":"10.1111/cobi.13818","usgsCitation":"Lawson, A.J., Folt, B., Tucker, A.M., Erickson, F.T., and McGowan, C.P., 2020, Decision context as an essential component of population viability analysis: Conservation Biology, no. 5, p. 1683-1685, https://doi.org/10.1111/cobi.13818.","productDescription":"3 p.","startPage":"1683","endPage":"1685","ipdsId":"IP-118153","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":395881,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"issue":"5","noUsgsAuthors":false,"publicationDate":"2021-08-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Lawson, Abigail Jean 0000-0002-2799-8750","orcid":"https://orcid.org/0000-0002-2799-8750","contributorId":276319,"corporation":false,"usgs":true,"family":"Lawson","given":"Abigail","email":"","middleInitial":"Jean","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":834747,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Folt, Brian","contributorId":267702,"corporation":false,"usgs":false,"family":"Folt","given":"Brian","affiliations":[{"id":13360,"text":"Auburn University","active":true,"usgs":false}],"preferred":false,"id":834748,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tucker, Anna Maureen 0000-0002-1473-2048 amtucker@usgs.gov","orcid":"https://orcid.org/0000-0002-1473-2048","contributorId":257906,"corporation":false,"usgs":true,"family":"Tucker","given":"Anna","email":"amtucker@usgs.gov","middleInitial":"Maureen","affiliations":[],"preferred":true,"id":834749,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Erickson, Francesca T.","contributorId":276320,"corporation":false,"usgs":false,"family":"Erickson","given":"Francesca","email":"","middleInitial":"T.","affiliations":[{"id":13360,"text":"Auburn University","active":true,"usgs":false}],"preferred":false,"id":834750,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McGowan, Conor P. 0000-0002-7330-9581 cmcgowan@usgs.gov","orcid":"https://orcid.org/0000-0002-7330-9581","contributorId":167162,"corporation":false,"usgs":true,"family":"McGowan","given":"Conor","email":"cmcgowan@usgs.gov","middleInitial":"P.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":834751,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70221394,"text":"70221394 - 2020 - USGS Illinois River monitoring and evaluation","interactions":[],"lastModifiedDate":"2021-11-01T19:06:35.968534","indexId":"70221394","displayToPublicDate":"2021-06-01T08:08:15","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"displayTitle":"USGS Illinois River Monitoring and Evaluation","title":"USGS Illinois River monitoring and evaluation","docAbstract":"Asian carp monitoring and contract removal will continue throughout the Upper Illinois Waterway system as needed for adaptive management to mitigate, control, and contain Asian carp. Compiling data from monitoring and removal efforts into a centralized database (Illinois River Catch Database application) facilitates data standardization, quality, accessibility, sharing, and analysis to aid in Asian carp removal efforts, evaluations of management actions, and modeling efforts (e.g., SEACarP model). Data summarization, visualization, and modeling supports a better understanding of bigheaded carp life history, behavior, and habitat use. Integrating Asian carp-related data and analyses into decision support tools and products aids in applying control and containment methods in an informed and transparent manner (e.g., improved efficiencies in implementations of the Unified Method, inform targeted removal efforts or deterrent deployments in key locations based on preferential benthic characteristics and environmental conditions).","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"2020 Asian Carp Monitoring and Response Plan","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"Invasive Species Regional Coordinating Committee","usgsCitation":"Harrison, T.J., Hop, K.D., Hlavacek, E., and Knights, B.C., 2020, USGS Illinois River monitoring and evaluation, 4 p.","productDescription":"4 p.","startPage":"87","endPage":"90","ipdsId":"IP-119472","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":386469,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":391210,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://invasivecarp.us/Documents/Monitoring-Response-Plan-2020.pdf","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Illinois","otherGeospatial":"Illinois River Waterway system","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.5830078125,\n 41.73852846935917\n ],\n [\n -87.62695312499999,\n 42.00032514831621\n ],\n [\n -87.8466796875,\n 42.00032514831621\n ],\n [\n -88.26416015625,\n 41.713930073371294\n ],\n [\n -88.857421875,\n 41.60722821271717\n ],\n [\n -89.439697265625,\n 41.44272637767212\n ],\n [\n -89.8681640625,\n 41.253032440653186\n ],\n [\n -90.32958984375,\n 40.64730356252251\n ],\n [\n -90.791015625,\n 39.93501296038254\n ],\n [\n -90.791015625,\n 39.257778150283364\n ],\n [\n -90.52734374999999,\n 38.659777730712534\n ],\n [\n -90.098876953125,\n 38.65119833229951\n ],\n [\n -90.087890625,\n 39.07037913108751\n ],\n [\n -90.4833984375,\n 39.45316112807394\n ],\n [\n -90.06591796875,\n 40.027614437486655\n ],\n [\n -89.088134765625,\n 40.94671366508002\n ],\n [\n -88.2861328125,\n 41.29431726315258\n ],\n [\n -87.5830078125,\n 41.73852846935917\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Harrison, Travis J. 0000-0002-9195-738X","orcid":"https://orcid.org/0000-0002-9195-738X","contributorId":213966,"corporation":false,"usgs":true,"family":"Harrison","given":"Travis","email":"","middleInitial":"J.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":817503,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":817504,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hlavacek, Enrika 0000-0002-9872-2305 ehlavacek@usgs.gov","orcid":"https://orcid.org/0000-0002-9872-2305","contributorId":149114,"corporation":false,"usgs":true,"family":"Hlavacek","given":"Enrika","email":"ehlavacek@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":817505,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Knights, Brent C. 0000-0001-8526-8468 bknights@usgs.gov","orcid":"https://orcid.org/0000-0001-8526-8468","contributorId":2906,"corporation":false,"usgs":true,"family":"Knights","given":"Brent","email":"bknights@usgs.gov","middleInitial":"C.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":817506,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70218269,"text":"70218269 - 2020 - Debris-flow growth in Puerto Rico during Hurricane Maria: Preliminary results from analyses of pre- and post-event lidar data","interactions":[],"lastModifiedDate":"2021-04-20T11:52:56.654517","indexId":"70218269","displayToPublicDate":"2021-02-28T09:19:43","publicationYear":"2020","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Debris-flow growth in Puerto Rico during Hurricane Maria: Preliminary results from analyses of pre- and post-event lidar data","docAbstract":"

On September 20, 2017, Hurricane Maria triggered widespread debris flows in Puerto Rico. We used field observations and pre- and post-Maria lidar to study the volumetric growth of long-travelled (>400 m) debris flows in four basins. We found overall growth rates that ranged from 0.7 to 30.4 m3 per meter of channel length. We partitioned the rates into two growth mechanisms, aggregation of multiple landslides, or erosion and entrainment of channel sediment. In three basins, landslides accounted for more than 80% of the total debris-flow volumes. In one basin, entrainment accounted for 96% of the volume. These results indicate that forecasting volumes for regional debris-flow inundation modeling is more complicated than estimating the number and volume of contributing landslide source areas, although this task is difficult by itself. In this preliminary analysis, we did not find geologic, topographic, or morphometric variables that correlated with the growth observations. We suspect that the observed growth rates were heavily influenced by local variations in environmental conditions, including antecedent soil moisture conditions, duration and intensity of rainfall, and availability of channel material. Given these considerations, regional debris-flow inundation modeling may be best achieved by using a suite of scenarios that capture possible mechanisms of debris-flow growth.

","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the 13th International Symposium on Landslides","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"13th International Symposium on Landslides","conferenceDate":"February 22-26, 2021","language":"English","publisher":"International Society for Soil Mechanics and Geotechnical Engineering","usgsCitation":"Coe, J.A., Bessette-Kirton, E., Brien, D.L., and Reid, M.E., 2020, Debris-flow growth in Puerto Rico during Hurricane Maria: Preliminary results from analyses of pre- and post-event lidar data, in Proceedings of the 13th International Symposium on Landslides, February 22-26, 2021, 9 p.","productDescription":"9 p.","ipdsId":"IP-113885","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":385190,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":383574,"type":{"id":15,"text":"Index Page"},"url":"https://www.issmge.org/uploads/publications/105/106/ISL2020-7.pdf"}],"country":"United States","state":"Puerto Rico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -67.30499267578125,\n 17.85590441431915\n ],\n [\n -65.5828857421875,\n 17.85590441431915\n ],\n [\n -65.5828857421875,\n 18.578568865536027\n ],\n [\n -67.30499267578125,\n 18.578568865536027\n ],\n [\n -67.30499267578125,\n 17.85590441431915\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Coe, Jeffrey A. 0000-0002-0842-9608 jcoe@usgs.gov","orcid":"https://orcid.org/0000-0002-0842-9608","contributorId":1333,"corporation":false,"usgs":true,"family":"Coe","given":"Jeffrey","email":"jcoe@usgs.gov","middleInitial":"A.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":810789,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bessette-Kirton, Erin K. 0000-0002-2797-0694","orcid":"https://orcid.org/0000-0002-2797-0694","contributorId":225097,"corporation":false,"usgs":false,"family":"Bessette-Kirton","given":"Erin K.","affiliations":[{"id":13252,"text":"University of Utah","active":true,"usgs":false}],"preferred":false,"id":810790,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brien, Dianne L. 0000-0003-3227-7963 dbrien@usgs.gov","orcid":"https://orcid.org/0000-0003-3227-7963","contributorId":229851,"corporation":false,"usgs":true,"family":"Brien","given":"Dianne","email":"dbrien@usgs.gov","middleInitial":"L.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":810791,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Reid, Mark E. 0000-0002-5595-1503 mreid@usgs.gov","orcid":"https://orcid.org/0000-0002-5595-1503","contributorId":1167,"corporation":false,"usgs":true,"family":"Reid","given":"Mark","email":"mreid@usgs.gov","middleInitial":"E.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":810792,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70216822,"text":"ofr20201131 - 2020 - Mapping Phragmites australis live fractional cover in the lower Mississippi River Delta, Louisiana","interactions":[],"lastModifiedDate":"2021-01-28T01:20:54.786589","indexId":"ofr20201131","displayToPublicDate":"2021-01-27T15:30:00","publicationYear":"2020","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":"2020-1131","displayTitle":"Mapping Phragmites australis Live Fractional Cover in the Lower Mississippi River Delta, Louisiana","title":"Mapping Phragmites australis live fractional cover in the lower Mississippi River Delta, Louisiana","docAbstract":"

In response to a co-occurring non-native scale infestation and Phragmites australis dieback in southeast Louisiana, normalized difference vegetation index (NDVI) satellite mapping was implemented to track P. australis condition in the lower Mississippi River Delta. While the NDVI mapping successfully documented relative condition changes, identification of cause required a quantitative-biophysical metric directly related to P. australis marsh live vegetation proportion. During this study, a satellite mapping tool that quantified P. australis live fraction cover (LFC) magnitude was designed and implemented. The key to development of the quantitative LFC mapping was the field to satellite calibration design. The calibration of P. australis marsh LFC to optical satellite image data combined field and near-in-time satellite data collections in the fall of 2018 and summer of 2019. Basing the field-NDVI to field-LFC calibrations and the satellite-NDVI to field-NDVI calibrations on combined pre-senescence and peak-growth period data offers nearly year-round LFC mapping. The utility of the developed P. australis marsh LFC mapping tool was demonstrated by the creation of a yearly suite of Mississippi River Delta LFC status and change maps extending from 2009 to 2019. P. australis marsh LFC mapping relies on Sentinel-2 for current to future mapping and relies on Landsat for historical mapping.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201131","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Rangoonwala, A., Howard, R.J., and Ramsey, E.W., III, 2020, Mapping Phragmites australis live fractional cover in the lower Mississippi River Delta, Louisiana (ver. 1.1, January 2021): U.S. Geological Survey Open-File Report 2020–1131, 24 p., https://doi.org/10.3133/ofr20201131.","productDescription":"Report: vii, 24 p.; Data Release","numberOfPages":"36","onlineOnly":"Y","ipdsId":"IP-119555","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":381145,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ASPB4E","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Phragmites australis live fractional cover yearly map from 2009 to 2019 of the lower Mississippi River Delta using Landsat and Sentinel-2 satellite data"},{"id":381143,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1131/coverthb2.jpg"},{"id":381144,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1131/ofr20201131.pdf","text":"Report","size":"6.69 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020–1131"},{"id":382663,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2020/1131/versionHist.txt","text":"Version History","size":"4.0 kB","linkFileType":{"id":2,"text":"txt"},"description":"OFR 2020–1131 version history"}],"country":"United States","state":"Louisiana","otherGeospatial":"Lower Mississippi River Delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.54544067382812,\n 28.930045059458923\n ],\n [\n -89.000244140625,\n 28.930045059458923\n ],\n [\n -89.000244140625,\n 29.40371231103247\n ],\n [\n -89.54544067382812,\n 29.40371231103247\n ],\n [\n -89.54544067382812,\n 28.930045059458923\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: December 14, 2020; Version 1.1: January 27, 2021","contact":"

Director, Wetland and Aquatic Research Center
U.S. Geological Survey
700 Cajundome Blvd.
Lafayette, Louisiana 70506

","tableOfContents":"","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2020-12-14","revisedDate":"2021-01-27","noUsgsAuthors":false,"publicationDate":"2020-12-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Rangoonwala, Amina 0000-0002-0556-0598","orcid":"https://orcid.org/0000-0002-0556-0598","contributorId":212060,"corporation":false,"usgs":true,"family":"Rangoonwala","given":"Amina","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":806428,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Howard, Rebecca J. 0000-0001-7264-4364 howardr@usgs.gov","orcid":"https://orcid.org/0000-0001-7264-4364","contributorId":2429,"corporation":false,"usgs":true,"family":"Howard","given":"Rebecca","email":"howardr@usgs.gov","middleInitial":"J.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":806429,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ramsey III, Elijah W. 0000-0002-4518-5796","orcid":"https://orcid.org/0000-0002-4518-5796","contributorId":214746,"corporation":false,"usgs":true,"family":"Ramsey III","given":"Elijah W.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":806430,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70219523,"text":"70219523 - 2020 - Reptiles under the conservation umbrella of the greater sage‐grouse","interactions":[],"lastModifiedDate":"2021-04-12T13:33:16.444302","indexId":"70219523","displayToPublicDate":"2021-01-24T08:30:55","publicationYear":"2020","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":"Reptiles under the conservation umbrella of the greater sage‐grouse","docAbstract":"

In conservation paradigms, management actions for umbrella species also benefit co‐occurring species because of overlapping ranges and similar habitat associations. The greater sage‐grouse (Centrocercus urophasianus) is an umbrella species because it occurs across vast sagebrush ecosystems of western North America and is the recipient of extensive habitat conservation and restoration efforts that might benefit sympatric species. Biologists' understanding of how non‐target species might benefit from sage‐grouse conservation is, however, limited. Reptiles, in particular, are of interest in this regard because of their relatively high diversity in shrublands and grasslands where sage‐grouse are found. Using spatial overlap of species distributions, land cover similarity statistics, and a literature review, we quantified which reptile species may benefit from the protection of intact sage‐grouse habitat and which may be affected by recent (since about 1990) habitat restoration actions targeting sage‐grouse. Of 190 reptile species in the United States and Canadian provinces where greater sage‐grouse occur, 70 (37%) occur within the range of the bird. Of these 70 species, about a third (11 snake and 11 lizard species) have >10% of their distribution area within the sage‐grouse range. Land cover similarity indices revealed that 14 of the 22 species (8 snake and 6 lizard species) had relatively similar land cover associations to those of sage‐grouse, suggesting greater potential to be protected under the sage‐grouse conservation umbrella and greater potential to be affected, either positively or negatively, by habitat management actions intended for sage‐grouse. Conversely, the remaining 8 species are less likely to be protected because of less overlap with sage‐grouse habitat and thus uncertain effects of sage‐grouse habitat management actions. Our analyses of treatment databases indicated that from 1990 to 2014 there were at least 6,400 treatments implemented on public land that covered approximately 4 million ha within the range of the sage‐grouse and, of that, >1.5 million ha were intended to at least partially benefit sage‐grouse. Whereas our results suggest that conservation of intact sagebrush vegetation communities could benefit ≥14 reptiles, a greater number than previously estimated, additional research on each species' response to habitat restoration actions is needed to assess broader claims of multi‐taxa benefits when it comes to manipulative sage‐grouse habitat management. Published 2020. This article is a U.S. Government work and is in the public domain in the USA.

","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.21821","usgsCitation":"Pilliod, D., Jeffries, M.I., Arkle, R., and Olson, D., 2020, Reptiles under the conservation umbrella of the greater sage‐grouse: Journal of Wildlife Management, v. 84, no. 3, p. 478-491, https://doi.org/10.1002/jwmg.21821.","productDescription":"14 p.","startPage":"478","endPage":"491","ipdsId":"IP-103602","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":385006,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, 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\"}}]}","volume":"84","issue":"3","noUsgsAuthors":false,"publicationDate":"2020-01-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Pilliod, David S. 0000-0003-4207-3518","orcid":"https://orcid.org/0000-0003-4207-3518","contributorId":229349,"corporation":false,"usgs":true,"family":"Pilliod","given":"David S.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":813926,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jeffries, Michelle I. 0000-0003-1146-1331","orcid":"https://orcid.org/0000-0003-1146-1331","contributorId":202734,"corporation":false,"usgs":true,"family":"Jeffries","given":"Michelle","middleInitial":"I.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":813927,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Arkle, Robert 0000-0003-3021-1389","orcid":"https://orcid.org/0000-0003-3021-1389","contributorId":216339,"corporation":false,"usgs":true,"family":"Arkle","given":"Robert","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":813928,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Olson, Deanna H.","contributorId":257261,"corporation":false,"usgs":false,"family":"Olson","given":"Deanna H.","affiliations":[{"id":51996,"text":"USDA Forest Service Pacific Northwest Research Station","active":true,"usgs":false}],"preferred":false,"id":813929,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70217282,"text":"70217282 - 2020 - Management of the brown-headed cowbird: Implications for endangered species and agricultural damage mitigation","interactions":[],"lastModifiedDate":"2021-01-18T14:16:03.109888","indexId":"70217282","displayToPublicDate":"2021-01-11T08:12:31","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1914,"text":"Human-Wildlife Interactions","active":true,"publicationSubtype":{"id":10}},"title":"Management of the brown-headed cowbird: Implications for endangered species and agricultural damage mitigation","docAbstract":"

The brown-headed cowbird (Molothrus ater; cowbird) is unique among North American blackbirds (Icteridae) because it is managed to mitigate the negative effects on endangered songbirds and economic losses in agricultural crops. Cowbird brood parasitism can further affect species that are considered threatened or endangered due to anthropogenic land uses. Historically, cowbirds have often been culled without addressing ultimate causes of songbird population declines. Similar to other North American blackbirds, cowbirds depredate agricultural crops, albeit at a lower rate reported for other blackbird species. Conflicting information exists on the extent of agricultural damage caused by cowbirds and the effectiveness of mitigation measures for application to management. In this paper, we reviewed the progress that has been made in cowbird management from approximately 2005 to 2020 in relation to endangered species. We also reviewed losses to the rice (Oryza sativa) crop attributed to cowbirds and the programs designed to reduce depredation. Of the 4 songbird species in which cowbirds have been managed, both the Kirtland’s warbler (Dendroica kirtlandii) and black-capped vireo (Vireo atricapilla) have been removed from the endangered species list following population increases in response to habitat expansion. Cowbird trapping has ceased for Kirtland’s warbler but continues for the vireo. In contrast, least Bell’s vireo (V. bellii pusillus) and southwestern willow flycatcher (Empidonax traillii extimus) still require cowbird control after modest increases in suitable habitat. Our review of rice depredation by cowbirds revealed models that have been created to determine the number of cowbirds that can be taken to decrease rice loss have been useful but require refinement with new data that incorporate cowbird population changes in the rice growing region, dietary preference studies, and current information on population sex ratios and female cowbird egg laying. Once this information has been gathered, bioenergetic and economic models would increase our understanding of the damage caused by cowbirds.


","language":"English","publisher":"Berryman Institute","usgsCitation":"Peer, B.D., Kus, B., Whitfield, M.J., Hall, L.S., and Rothstein, S., 2020, Management of the brown-headed cowbird: Implications for endangered species and agricultural damage mitigation: Human-Wildlife Interactions, v. 14, no. 3, 16, 15 p.","productDescription":"16, 15 p.","ipdsId":"IP-125196","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":382264,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":382196,"type":{"id":15,"text":"Index Page"},"url":"https://digitalcommons.usu.edu/hwi/vol14/iss3/16"}],"country":"United States","state":"California","county":"Ventura County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.55871582031251,\n 34.17090836352573\n ],\n [\n -118.46145629882811,\n 34.17090836352573\n ],\n [\n -118.46145629882811,\n 34.60269355405186\n ],\n [\n -119.55871582031251,\n 34.60269355405186\n ],\n [\n -119.55871582031251,\n 34.17090836352573\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"14","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Peer, Brian D","contributorId":247749,"corporation":false,"usgs":false,"family":"Peer","given":"Brian","email":"","middleInitial":"D","affiliations":[{"id":49637,"text":"Western Illinois University","active":true,"usgs":false}],"preferred":false,"id":808262,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kus, Barbara E. 0000-0002-3679-3044 barbara_kus@usgs.gov","orcid":"https://orcid.org/0000-0002-3679-3044","contributorId":3026,"corporation":false,"usgs":true,"family":"Kus","given":"Barbara E.","email":"barbara_kus@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":808263,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Whitfield, Mary J.","contributorId":174933,"corporation":false,"usgs":false,"family":"Whitfield","given":"Mary","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":808264,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hall, Linnea S.","contributorId":220610,"corporation":false,"usgs":false,"family":"Hall","given":"Linnea","email":"","middleInitial":"S.","affiliations":[{"id":40192,"text":"Western Foundation of Vertebrate Zoology","active":true,"usgs":false}],"preferred":false,"id":808265,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rothstein, Stephen I","contributorId":247750,"corporation":false,"usgs":false,"family":"Rothstein","given":"Stephen I","affiliations":[{"id":36524,"text":"University of California, Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":808266,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70217177,"text":"tm4F5 - 2020 - DGMETA (version 1)—Dissolved gas modeling and environmental tracer analysis computer program","interactions":[],"lastModifiedDate":"2024-02-01T18:43:12.976311","indexId":"tm4F5","displayToPublicDate":"2021-01-08T11:31:29","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"4-F5","displayTitle":"DGMETA (Version 1): Dissolved Gas Modeling and Environmental Tracer Analysis Computer Program","title":"DGMETA (version 1)—Dissolved gas modeling and environmental tracer analysis computer program","docAbstract":"

DGMETA (Dissolved Gas Modeling and Environmental Tracer Analysis) is a Microsoft Excel-based computer program that is used for modeling air-water equilibrium conditions from measurements of dissolved gases and for computing concentrations of environmental tracers that rely on air-water equilibrium model results. DGMETA can solve for the temperature, salinity, excess air, fractionation of gases, or pressure/elevation of water when it is equilibrated with the atmosphere. Models are calibrated inversely using one or more measurements of dissolved gases such as helium, neon, argon, krypton, xenon, and nitrogen. Excess nitrogen gas, originating from denitrification or other sources, also can be included as a fitted parameter or as a separate calculation from the dissolved gas modeling results. DGMETA uses the air-water equilibrium models to separate measured concentrations of gases and isotopes of gases into components that are used for tracing water in the environment. DGMETA calculates atmospheric dry-air mole fractions (mixing ratios) for transient atmospheric gas tracers such as chlorofluorocarbons, sulfur hexafluoride, and bromotrifluoromethane (Halon-1301); and concentrations of tritiogenic helium-3 and radiogenic helium-4, which accumulate from the decay of tritium in water and the decay of uranium and thorium in rocks, respectively. 

Sample data can be graphed to identify applicable models of excess air, samples that contain excess nitrogen gas, or samples that have partially degassed, for example. Monte Carlo analysis of errors associated with dissolved gas equilibrium model results can be carried through computations of environmental tracer concentrations to provide robust estimates of error. In addition, graphical routines for separating helium sources using helium isotopes are included to refine estimates of tritiogenic helium-3 when terrigenic helium from mantle or crustal sources is present in samples. Environmental tracer concentrations and their errors computed from DGMETA can be used with other programs, such as TracerLPM (Jurgens and others, 2012), to determine groundwater ages and biogeochemical reaction rates. DGMETA also produces output files in a format that meets the U.S. Geological Survey open data requirements for documentation of model inputs and outputs. 

DGMETA is a versatile and adaptable program that allows users to add solubility data for new gases, modify the existing set of gas solubility data, modify the default set of gases used for modeling, choose calculations based on real (non-ideal) gas behavior, and select various concentration units for data entry and results to match laboratory reports and study objectives. DGMETA comes with a set of gases widely used in hydrology and oceanography and many gases include multiple solubilities from previous work. Seventeen dissolved gases are included in the default version of the program: noble gases (helium, neon, argon, krypton, and xenon), reactive gases (nitrogen, oxygen, methane, carbon dioxide, carbon monoxide, hydrogen, and nitrous oxide), and environmental tracers (chlorofluorocarbon-11, chlorofluorocarbon-12, chlorofluorocarbon-113, sulfur hexafluoride, and Halon-1301).

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm4F5","collaboration":"National Water Quality Assessment Project","usgsCitation":"Jurgens, B.C., Böhlke, J., Haase, K., Busenberg, E., Hunt, A.G., and Hansen, J.A., 2020, DGMETA (version 1)—Dissolved gas modeling and environmental tracer analysis computer program: U.S. Geological Survey Techniques and Methods 4-F5, 50 p., https://doi.org/10.3133/tm4F5.","productDescription":"Report: viii, 50 p.; Software Release","onlineOnly":"Y","ipdsId":"IP-100912","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":436689,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9NQ1RFY","text":"USGS data release","linkHelpText":"DGMETA (Version 1): Dissolved Gas Modeling and Environmental Tracer Analysis Computer Program"},{"id":382045,"rank":3,"type":{"id":35,"text":"Software Release"},"url":"https://code.usgs.gov/cawsc/DGMETA","text":"DGMETA","linkHelpText":"- DGMETA (Dissolved Gas Modeling and Environmental Tracer Analysis) is a Microsoft Excel-based computer program that is used for modeling air-water equilibrium conditions from measurements of dissolved gases and for computing concentrations of environmental tracers that rely on air-water equilibrium model results."},{"id":382038,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/04/f05/coverthb.jpg"},{"id":382039,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/04/f05/tm4f5.pdf","text":"Report","size":"8.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"TM 4-F5"}],"contact":"

NAWQA Science Team
U.S. Geological Survey
12201 Sunrise Valley Drive, MS 413
Reston, VA 20192–0002

","tableOfContents":"","publishedDate":"2021-01-08","noUsgsAuthors":false,"publicationDate":"2021-01-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Jurgens, Bryant C. 0000-0002-1572-113X bjurgens@usgs.gov","orcid":"https://orcid.org/0000-0002-1572-113X","contributorId":127842,"corporation":false,"usgs":true,"family":"Jurgens","given":"Bryant","email":"bjurgens@usgs.gov","middleInitial":"C.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":807830,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Böhlke, J. K. 0000-0001-5693-6455","orcid":"https://orcid.org/0000-0001-5693-6455","contributorId":173577,"corporation":false,"usgs":true,"family":"Böhlke","given":"J. K.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":false,"id":807831,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haase, Karl B. 0000-0002-6897-6494 khaase@usgs.gov","orcid":"https://orcid.org/0000-0002-6897-6494","contributorId":205943,"corporation":false,"usgs":true,"family":"Haase","given":"Karl","email":"khaase@usgs.gov","middleInitial":"B.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":807832,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Busenberg, Eurybiades ebusenbe@usgs.gov","contributorId":2271,"corporation":false,"usgs":true,"family":"Busenberg","given":"Eurybiades","email":"ebusenbe@usgs.gov","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":807833,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hunt, Andrew G. 0000-0002-3810-8610 ahunt@usgs.gov","orcid":"https://orcid.org/0000-0002-3810-8610","contributorId":1582,"corporation":false,"usgs":true,"family":"Hunt","given":"Andrew","email":"ahunt@usgs.gov","middleInitial":"G.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":807834,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hansen, Jeffrey A. 0000-0002-2185-1686 jahansen@usgs.gov","orcid":"https://orcid.org/0000-0002-2185-1686","contributorId":247521,"corporation":false,"usgs":false,"family":"Hansen","given":"Jeffrey A.","email":"jahansen@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":807835,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70217006,"text":"ofr20201118 - 2020 - Underwater photographic reconnaissance and habitat data collection in the Florida Keys—A procedure for ground truthing remotely sensed bathymetric data","interactions":[],"lastModifiedDate":"2021-01-06T12:49:44.066583","indexId":"ofr20201118","displayToPublicDate":"2021-01-05T12:20:00","publicationYear":"2020","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":"2020-1118","displayTitle":"Underwater Photographic Reconnaissance and Habitat Data Collection in the Florida Keys—A Procedure for Ground Truthing Remotely Sensed Bathymetric Data","title":"Underwater photographic reconnaissance and habitat data collection in the Florida Keys—A procedure for ground truthing remotely sensed bathymetric data","docAbstract":"

Bathymetric geoprocessing analyses of the Florida Reef Tract have provided insights into trends of seafloor accretion and seafloor erosion over time and following major storm events. However, bathymetric surveys sometimes capture manmade structures and vegetation, which do not represent the desired bare-earth data. Therefore, ground truthing is essential to maintain the most accurate bathymetric data possible. Field procedures were developed in the Florida Reef Tract in order to quickly and accurately collect consistent imagery and habitat data across variable sites. Areas of significant elevation change were determined through elevation change analyses; these areas were targeted for ground truthing in order to check the reliability of the surveys. This report outlines the standard operating procedures for underwater photographic imagery and habitat data collection, as well as procedures for the storage of these photographs and associated metadata. These standard operating procedures ensure the reproducibility of photographic operations and habitat data collection in future field excursions, enable longitudinal visual comparisons alongside seafloor elevation change analyses, and also have the potential to be applied to similar studies in different coastal environments.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201118","usgsCitation":"Fehr, Z.W., and Yates, K.K., 2020, Underwater photographic reconnaissance and habitat data collection in the Florida Keys—A procedure for ground truthing remotely sensed bathymetric data: U.S. Geological Survey Open-File Report 2020–1118, 13 p., https://doi.org/10.3133/ofr20201118.","productDescription":"vii, 13 p.","numberOfPages":"13","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-114891","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":381619,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1118/ofr20201118.pdf","text":"Report","size":"5.71 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1118"},{"id":381618,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1118/coverthb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Florida Keys","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.53665161132812,\n 25.022150920405707\n ],\n [\n -80.1177978515625,\n 25.022150920405707\n ],\n [\n -80.1177978515625,\n 25.336579097268118\n ],\n [\n -80.53665161132812,\n 25.336579097268118\n ],\n [\n -80.53665161132812,\n 25.022150920405707\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, St. Petersburg Coastal and Marine Science Center
U.S. Geological Survey
600 4th Street South
St. Petersburg, FL 33701

Contact Pubs Warehouse

","tableOfContents":"","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2021-01-05","noUsgsAuthors":false,"publicationDate":"2021-01-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Fehr, Zachery W. 0000-0001-7885-2885","orcid":"https://orcid.org/0000-0001-7885-2885","contributorId":215764,"corporation":false,"usgs":true,"family":"Fehr","given":"Zachery","email":"","middleInitial":"W.","affiliations":[{"id":25340,"text":"Cherokee Nation Technologies","active":true,"usgs":false}],"preferred":true,"id":807247,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yates, Kimberly K. 0000-0001-8764-0358 kyates@usgs.gov","orcid":"https://orcid.org/0000-0001-8764-0358","contributorId":420,"corporation":false,"usgs":true,"family":"Yates","given":"Kimberly","email":"kyates@usgs.gov","middleInitial":"K.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":807248,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70216078,"text":"70216078 - 2020 - North Atlantic right whale (Eubalaena glacialis) scenario planning summary report","interactions":[],"lastModifiedDate":"2021-10-01T16:33:48.598484","indexId":"70216078","displayToPublicDate":"2020-12-31T11:15:50","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5145,"text":"Technical Memorandum","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"MNFS-OPR-68","displayTitle":"North Atlantic right whale (Eubalaena glacialis) scenario planning summary report","title":"North Atlantic right whale (Eubalaena glacialis) scenario planning summary report","docAbstract":"Scenario planning provides a structured framework that can be used in strategic planning to help manage risk and prioritize actions (Schwartz 1996; Peterson et al. 2003). By providing a mechanism to communicate about complex situations, scenario planning encourages “out-of-the-box” thinking to help groups assess the impacts of plausible future scenarios on a target or resource. The outcomes from scenario planning can be used to improve management decisions, highlight data gaps, and/or identify future science priorities (Star et al. 2015; Borggaard et al. 2019).\nThe application of scenario planning by resource management organizations (e.g., Borggaard et al. 2019; Runyon et al. 2020; Star et al. 2015) and the urgency surrounding the recovery of the critically endangered North Atlantic right whale (Eubalaena glacialis), led to a 2018 NOAA Fisheries scenario planning initiative for the species. In addition to complementing the many management and conservation efforts already underway, this initiative was designed to address the uncertainties around future anthropogenic and environmental changes and how these uncertainties may impact species recovery.\nWe used a scenario planning framework to explore plausible future conditions for North Atlantic right whales and to develop possible options to address those conditions and improve recovery. Specific objectives were to: 1) better understand the challenges of right whale management in a changing climate; 2) identify potential research activities and recovery needs across the species’ range; 3) increase coordination and collaboration related to recovery efforts; and 4) explore how scenario planning can be used to support decisions.\nUsing projected changes in ocean conditions coupled with anthropogenic stressors, we built four plausible future scenarios for right whales. These scenarios helped identify priority research and management actions that NOAA Fisheries and our partners can undertake to improve right whale recovery. We identified priority actions related to science, management, and partnerships including, but not limited to, 1) research on shifting spatial and temporal distributions of right whales and prey in a changing climate; 2) development of technology to further reduce impacts from human activities; 3) continuation of ongoing management efforts related to vessel traffic and fishing; and 4) continued maintenance of existing and development of new partnerships (e.g., industry engagement in problem solving).\nThis scenario planning exercise helped prioritize North Atlantic right whale management and science needs in light of changing ocean conditions and anthropogenic impacts. It can also serve as a reference for how NOAA Fisheries and its partners can better prepare for multiple plausible futures while complementing other on-going initiatives. Priorities identified here can be considered in conjunction with implementation and monitoring actions such as with the Atlantic Large Whale Take Reduction Team (ALWTRT) and/or regional Right Whale U.S. Implementation Teams. The framework can also be repeated and improved upon as additional information becomes available to support future exercises.","language":"English","publisher":"NOAA","usgsCitation":"Borggaard, D., Dick, D., Star, J., Zoodsma, B., Alexander, M., Asaro, M.J., Barre, L., Bettridge, S., Burns, P., Crocker, J., Dortch, Q., Garrison, L., Gulland, F., Haskell, B., Hayes, S., Henry, A., Hyde, K., Milliken, H., Morin, D., Quinlan, J., Rowles, T., Saba, V., Staudinger, M., and Walsh, H., 2020, North Atlantic right whale (Eubalaena glacialis) scenario planning summary report: Technical Memorandum MNFS-OPR-68, 94 p.","productDescription":"94 p.","ipdsId":"IP-122509","costCenters":[{"id":5080,"text":"Northeast Climate Adaptation Science 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Harvey","contributorId":244401,"corporation":false,"usgs":false,"family":"Walsh","given":"Harvey","affiliations":[{"id":36803,"text":"NOAA","active":true,"usgs":false}],"preferred":false,"id":803948,"contributorType":{"id":1,"text":"Authors"},"rank":24}]}} ,{"id":70220610,"text":"70220610 - 2020 - Council monitoring and assessment program (CMAP): Common monitoring program attributes and methodologies for the Gulf of Mexico Region","interactions":[],"lastModifiedDate":"2021-05-21T15:45:26.898403","indexId":"70220610","displayToPublicDate":"2020-12-31T10:37:21","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5134,"text":"NOAA Technical Memorandum","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"285","title":"Council monitoring and assessment program (CMAP): Common monitoring program attributes and methodologies for the Gulf of Mexico Region","docAbstract":"

Executive Summary Under the Resources and Ecosystem Sustainability, Tourist Opportunities, and Revived Economies of the Gulf Coast States Act of 2012 (RESTORE Act), the Gulf Coast Ecosystem Restoration Council (RESTORE Council or Council) is required to report on the progress of funded projects and programs. Systematic monitoring of restoration at the project-specific and programmatic-levels (i.e., watershed and Gulf of Mexico) enables consistent reporting and gives the public confidence that the restoration investments selected by the RESTORE Council will be evaluated and adaptively managed accordingly. Monitoring information that has been collected at different spatial and temporal scales can be used as the foundation to illustrate progress towards comprehensive ecosystem restoration goals and objectives that promote holistic Gulf of Mexico recovery (see ‘RESTORE Council Background’ at the beginning of this report for additional Council information).

Federal, state and local agencies, universities, private industry, and non-governmental organizations (NGOs) have conducted and are conducting extensive monitoring activities around the Gulf of Mexico. In addition, each RESTORE Council-funded project will, at a minimum, perform project-specific monitoring. This collection of monitoring activities was inventoried and compiled into a framework of tools and resources by the Council-funded RESTORE Council Monitoring and Assessment Program (CMAP). CMAP was designed and funded to inventory and integrate existing water quality and habitat monitoring and mapping efforts to support discovery and accessibility of existing monitoring data and ensure the collected information is made available to support management decisions. Results of CMAP Inventory queries can be used to identify opportunities for efficiencies and support crossprogram review of performance across Gulf of Mexico ecosystem recovery efforts.

The fundamental approach being used to inform the build out of the CMAP Gulf of Mexico water quality monitoring, habitat monitoring, and mapping framework includes: 1. Adopt, or construct as needed, a comprehensive inventory of existing habitat and water quality observation, monitoring, and mapping programs in the Gulf of Mexico (hereafter referred to as the “Inventory”; NOAA and USGS, 2019a); 2. Evaluate the suitability/applicability of each program and its existing and prospective data for use in restoration activities; 3. Develop a process to use the Inventory to conduct gap assessments; 4. Develop a catalog of baseline assessments conducted in the Gulf of Mexico (NOAA and USGS, 2019b); and 5. Develop a searchable monitoring information portal/database to enable access to collected information and products.

","language":"English","publisher":"National Oceanic and Atmospheric Administration (NOAA)","doi":"10.25923/vxay-xz10","usgsCitation":"Bosch, J., Burkart, H.B., Chivoiu, B., Clark, R., Clement, C., Enwright, N., Giordano, S., Jeffrey, C., Johnson, E., Hart, R., Hile, S.D., Howell, J.S., Laurenzano, C., Lee, M., McCloskey, T., McTigue, T., Meyers, M.B., Miller, K.E., Mize, S., Monaco, M.E., Owen, K., Rebich, R., Rendon, S.H., Robertson, A., Sample, T., Sanks, K.M., Steyer, G., Suir, K., Swarzenski, C.M., and Thurman, H.R., 2020, Council monitoring and assessment program (CMAP): Common monitoring program attributes and methodologies for the Gulf of Mexico Region: NOAA Technical Memorandum 285, ii, 87 p., https://doi.org/10.25923/vxay-xz10.","productDescription":"ii, 87 p.","ipdsId":"IP-120968","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research 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S","contributorId":258256,"corporation":false,"usgs":false,"family":"Howell","given":"Jacob","email":"","middleInitial":"S","affiliations":[{"id":52262,"text":"CSS, Inc.; NOAA NOS National Centers for Coastal Ocean Science","active":true,"usgs":false}],"preferred":false,"id":816159,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Laurenzano, Claudia 0000-0003-1406-8658","orcid":"https://orcid.org/0000-0003-1406-8658","contributorId":218930,"corporation":false,"usgs":true,"family":"Laurenzano","given":"Claudia","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":816160,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Lee, Michael 0000-0002-8260-8794","orcid":"https://orcid.org/0000-0002-8260-8794","contributorId":218815,"corporation":false,"usgs":true,"family":"Lee","given":"Michael","affiliations":[{"id":583,"text":"Texas Water Science 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Wetland and Aquatic Research Center (former employee)","active":true,"usgs":false}],"preferred":false,"id":816163,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Miller, Katie E","contributorId":258257,"corporation":false,"usgs":false,"family":"Miller","given":"Katie","email":"","middleInitial":"E","affiliations":[{"id":52262,"text":"CSS, Inc.; NOAA NOS National Centers for Coastal Ocean Science","active":true,"usgs":false}],"preferred":false,"id":816164,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Mize, Scott 0000-0001-6751-5568","orcid":"https://orcid.org/0000-0001-6751-5568","contributorId":218508,"corporation":false,"usgs":true,"family":"Mize","given":"Scott","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":816165,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Monaco, Mark E.","contributorId":200279,"corporation":false,"usgs":false,"family":"Monaco","given":"Mark","email":"","middleInitial":"E.","affiliations":[{"id":12448,"text":"U.S. National Oceanic and Atmospheric Administration","active":true,"usgs":false}],"preferred":false,"id":816166,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Owen, Kevin","contributorId":218509,"corporation":false,"usgs":false,"family":"Owen","given":"Kevin","email":"","affiliations":[{"id":39855,"text":"NOAA contractor","active":true,"usgs":false}],"preferred":false,"id":816167,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Rebich, Richard 0000-0003-4256-7171","orcid":"https://orcid.org/0000-0003-4256-7171","contributorId":202202,"corporation":false,"usgs":true,"family":"Rebich","given":"Richard","affiliations":[{"id":394,"text":"Mississippi Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":816147,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Rendon, Samuel H. 0000-0001-5589-0563 srendon@usgs.gov","orcid":"https://orcid.org/0000-0001-5589-0563","contributorId":3940,"corporation":false,"usgs":true,"family":"Rendon","given":"Samuel","email":"srendon@usgs.gov","middleInitial":"H.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":816168,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Robertson, Ali","contributorId":218623,"corporation":false,"usgs":false,"family":"Robertson","given":"Ali","email":"","affiliations":[],"preferred":false,"id":816169,"contributorType":{"id":1,"text":"Authors"},"rank":24},{"text":"Sample, Thomas 0000-0002-3960-8334","orcid":"https://orcid.org/0000-0002-3960-8334","contributorId":218510,"corporation":false,"usgs":true,"family":"Sample","given":"Thomas","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":816170,"contributorType":{"id":1,"text":"Authors"},"rank":25},{"text":"Sanks, Kelly Marie 0000-0002-5966-2370","orcid":"https://orcid.org/0000-0002-5966-2370","contributorId":228881,"corporation":false,"usgs":true,"family":"Sanks","given":"Kelly","email":"","middleInitial":"Marie","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":816171,"contributorType":{"id":1,"text":"Authors"},"rank":26},{"text":"Steyer, Gregory 0000-0001-7231-0110","orcid":"https://orcid.org/0000-0001-7231-0110","contributorId":218813,"corporation":false,"usgs":true,"family":"Steyer","given":"Gregory","affiliations":[{"id":5064,"text":"Southeast Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":816145,"contributorType":{"id":1,"text":"Authors"},"rank":27},{"text":"Suir, Kevin 0000-0003-1570-9648","orcid":"https://orcid.org/0000-0003-1570-9648","contributorId":218812,"corporation":false,"usgs":true,"family":"Suir","given":"Kevin","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":816172,"contributorType":{"id":1,"text":"Authors"},"rank":28},{"text":"Swarzenski, Christopher M. 0000-0001-9843-1471 cswarzen@usgs.gov","orcid":"https://orcid.org/0000-0001-9843-1471","contributorId":656,"corporation":false,"usgs":true,"family":"Swarzenski","given":"Christopher","email":"cswarzen@usgs.gov","middleInitial":"M.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":816173,"contributorType":{"id":1,"text":"Authors"},"rank":29},{"text":"Thurman, Hana Rose 0000-0001-7097-5362","orcid":"https://orcid.org/0000-0001-7097-5362","contributorId":258258,"corporation":false,"usgs":true,"family":"Thurman","given":"Hana","email":"","middleInitial":"Rose","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":816174,"contributorType":{"id":1,"text":"Authors"},"rank":30}]}} ,{"id":70215354,"text":"70215354 - 2020 - Smallmouth buffalo (Ictiobus bubalus) growth across a 1200km human use and ecological disturbance gradient in the Upper Mississippi River System","interactions":[],"lastModifiedDate":"2021-10-01T15:35:34.106947","indexId":"70215354","displayToPublicDate":"2020-12-31T10:25:19","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":9371,"text":"Mississippi River Restoration Program","active":true,"publicationSubtype":{"id":1}},"displayTitle":"Smallmouth buffalo (Ictiobus bubalus) growth across a 1200km human use and ecological disturbance gradient in the Upper Mississippi River System","title":"Smallmouth buffalo (Ictiobus bubalus) growth across a 1200km human use and ecological disturbance gradient in the Upper Mississippi River System","docAbstract":"Smallmouth buffalo (Ictiobus bubalus) is a common and widely distributed large-bodied species of the family Catostomidae. It inhabits large rivers and reservoirs of the eastern continental United States (east of the continental Divide) and is most abundant and common in the large rivers of the Midwest and Central Plains, though it does occur as far north and east as the Hudson Bay drainage and as far south and west as Arizona (Edwards and Twoney 1982).\n\nHistorically, smallmouth buffalo were an important component of commercial fisheries on both the Mississippi and Illinois Rivers. However, following the introduction of common carp (Cyprinus carpio) in the mid-1800s (Carlander 1954), the construction of a system of navigation dams on Upper Mississippi and Illinois River in the 1930s (USGS 1999), and water quality/pollution issues through the 1980s (Weiner 2010), the role of smallmouth buffalo in the overall UMRS fish community and commercial fishery has generally diminished relative to historical standards. Still, smallmouth buffalo remains an important and valued component of the UMRS commercial fishery.\n\nThe study area is represented by three study reaches on the Illinois River and three study reaches on the Upper Mississippi River (Figure 1). Collectively, these study reaches represent nearly 1200 river km and exist across strong and pronounced ecological and disturbance gradients. For example, habitat composition, water quality, commercial navigation intensity, aquatic plant prominence, and the number and abundance of nonnative fish species vary strongly across the study domain, with northern Mississippi River reaches exhibiting less navigation traffic, better water quality, markedly greater aquatic plant prominence, more diverse habitat composition, and comparably much smaller numbers of nonnative species than the lower Mississippi River study reach and those on the Illinois River (USGS 1999; Johnson and Hagerty [eds] 2008; Irons et al. 2009).\n\nLong term monitoring efforts conducted under the auspices of the Upper Mississippi River Restoration program over the past 27 years have provided tremendous insights into shifts and changes of the overall UMRS fish community (Ickes et al. 2005; Garvey et al. 2010; Schramm and Ickes 2016). However, these monitoring efforts observe only the most basic aspects of the UMRS fish community (i.e., catch, length, weight, distribution, and occurrence). To gain a greater understanding of forces driving community level shifts and changes, more directed study is needed on the functional attributes of fish populations (i.e., growth, mortality, recruitment). Collectively, these functional attributes of populations are termed population dynamics and/or vital rates.\n\nIt is important to note, the population dynamics of fishes in large rivers is generally poorly understood, especially for non-game species (Ickes 2018). The prevailing view is that abiotic factors largely govern inter-annual population dynamics, typically based upon rather short-term observations and correlations with assorted abiotic river attributes that vary on a seasonal or annual basis (for example, Risotto and Turner 1985). However, the role that longer-term abiotic factors play in regulating population abundance, or that biotic factors internal to the population (e.g., spawner-recruit dynamics, growth dynamics) or external to the population (e.g., predator-prey dynamics, sympatric competitors, disease) remain poorly understood. Achieving a greater understanding of these dynamics is important for stock, game, and invasive species management.\n\nIn 2017, as part of a larger study designed to gain vital population rate information for smallmouth buffalo in the Upper Mississippi and Illinois Rivers (“Smallmouth Buffalo population demographics of the Upper Mississippi River System”; UMRR LTRM 2018SOW project items 2018MMBF1-2018MMBF6) annual growth patterns in smallmouth buffalo were determined and evaluated. This was accomplished by measuring growth histories recorded in annual growth increments on hard bony parts (here otoliths), a method known generically as biochronology, and somewhat analogous to dendrochronology practiced by foresters. These methods allow one to generate time-series of annual growth histories that depend upon age, year class (i.e., cohort), and annual environmental conditions experienced by the population over time (Weisberg, 1993).\n\nBiochronology methods were used to develop a 36-year time series of smallmouth buffalo growth in the Upper Mississippi and Illinois Rivers across a 1200 km ecological and human use disturbance gradient. Annual growth intervals were identified and measured from otoliths to determine fish age and growth history. A mixed model that parses the growth increment into age and year effects was fit to these data.\n\nGiven the pronounced ecological and disturbance gradients inherent to the UMRS and the study domain, an a priori expectation of differing patterns in growth is accepted as a null hypothesis to test.\n\nThe goal of this study was to model smallmouth buffalo growth as a function of the age of the fish and the growth year in which the growth was gained. The primary modeling objective was to parse growth observed on each annulus into a portion attributable to the age of the fish and the portion attributable to the year in which the growth was gained. In effect, this modeling approach removes the somewhat trivial age effects on growth so that a non-confounded growth year effect can be gained. Results attributable to growth year provide a time series of growth information that is of the same duration as the oldest fish observed and solely reflects environmental influences on growth. These model responses can then be investigated relative to environmental covariate time-series suspected of influencing growth of smallmouth buffalo in the Upper Mississippi and Illinois Rivers (e.g., temperature, discharge, population density, population mortality, forage availability, sympatric competition, habitat composition, navigation intensity, nonnative fish prominence, etc.). Thus, the primary scientific objective was to investigate if and how smallmouth buffalo growth varies in accordance with innate ecological and disturbance gradients across the study domain.","language":"English","publisher":"US Army Corps of Engineers","usgsCitation":"Ickes, B., 2020, Smallmouth buffalo (Ictiobus bubalus) growth across a 1200km human use and ecological disturbance gradient in the Upper Mississippi River System: Mississippi River Restoration Program, 16 p.","productDescription":"16 p.","ipdsId":"IP-111767","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":390126,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":390125,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://umesc.usgs.gov/reports_publications/ltrmp_rep_list.html"}],"country":"United States","state":"Illinois, Iowa, Minnesota, Missouri, Wisconsin","otherGeospatial":"Illinois river, upper Mississippi River system","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.285400390625,\n 40.329795743702064\n ],\n [\n -90.802001953125,\n 41.1290213474951\n ],\n [\n -90.06591796875,\n 41.88592102814744\n ],\n [\n -90.04394531249999,\n 42.13082130188811\n ],\n [\n -90.889892578125,\n 43.052833917627936\n ],\n [\n -91.14257812499999,\n 43.97700467496408\n ],\n [\n -91.900634765625,\n 44.47299117260252\n ],\n [\n -92.757568359375,\n 44.809121700077355\n ],\n [\n -93.71337890625,\n 45.390735154248894\n ],\n [\n -94.141845703125,\n 45.69083283645816\n ],\n [\n -94.15283203125,\n 46.37725420510028\n ],\n [\n -94.7021484375,\n 46.38483322349276\n ],\n [\n -94.39453125,\n 45.583289756006316\n ],\n [\n -93.44970703125,\n 44.92591837128866\n ],\n [\n -92.186279296875,\n 44.37098696297173\n ],\n [\n -91.64794921875,\n 43.98491011404692\n ],\n [\n -91.38427734374999,\n 43.74728909225908\n ],\n [\n -91.34033203125,\n 43.33316939281732\n ],\n [\n -91.2744140625,\n 42.64204079304426\n ],\n [\n -90.582275390625,\n 42.285437007491545\n ],\n [\n -90.3515625,\n 42.00032514831621\n ],\n [\n -91.219482421875,\n 41.36856413680967\n ],\n [\n -91.669921875,\n 40.622291783092706\n ],\n [\n -91.7138671875,\n 39.93501296038254\n ],\n [\n -90.8349609375,\n 38.75408327579141\n ],\n [\n -90.384521484375,\n 38.762650338334154\n ],\n [\n -90.494384765625,\n 38.298559092254344\n ],\n [\n -89.857177734375,\n 37.60552821745789\n ],\n [\n -89.58251953125,\n 37.02886944696474\n ],\n [\n -89.53857421875,\n 36.82687474287728\n ],\n [\n -89.80224609374999,\n 36.30627216957992\n ],\n [\n -89.384765625,\n 36.32397712011264\n ],\n [\n -89.02221679687499,\n 36.76529191711624\n ],\n [\n -89.110107421875,\n 37.28279464911045\n ],\n [\n -89.49462890625,\n 37.92686760148135\n ],\n [\n -90.263671875,\n 38.35027253825765\n ],\n [\n -89.912109375,\n 39.01064750994083\n ],\n [\n -90.50537109375,\n 39.18969082109678\n ],\n [\n -90.362548828125,\n 39.85915479295669\n ],\n [\n -89.593505859375,\n 40.51379915504413\n ],\n [\n -89.154052734375,\n 41.16211393939692\n ],\n [\n -88.4619140625,\n 41.253032440653186\n ],\n [\n -88.05541992187499,\n 41.3850519497068\n ],\n [\n -88.2861328125,\n 41.590796851056005\n ],\n [\n -89.549560546875,\n 41.42625319507269\n ],\n [\n -90.208740234375,\n 40.613952441166596\n ],\n [\n -90.867919921875,\n 39.90130858574735\n ],\n [\n -91.219482421875,\n 39.8928799002948\n ],\n [\n -91.285400390625,\n 40.329795743702064\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ickes, Brian 0000-0001-5622-3842 bickes@usgs.gov","orcid":"https://orcid.org/0000-0001-5622-3842","contributorId":2925,"corporation":false,"usgs":true,"family":"Ickes","given":"Brian","email":"bickes@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":801849,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70216569,"text":"70216569 - 2020 - An analysis of Twitter responses to the 2019 Ridgecrest Earthquake sequence","interactions":[],"lastModifiedDate":"2021-10-04T11:52:22.142345","indexId":"70216569","displayToPublicDate":"2020-12-31T10:03:26","publicationYear":"2020","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"An analysis of Twitter responses to the 2019 Ridgecrest Earthquake sequence","docAbstract":"

Previous research has shown that online social networks can provide valuable insights regarding collective human responses to extreme natural events, such as earthquakes. Most previous studies focused on one large earthquake, while the 2019 Ridgecrest earthquakes involved two significant earthquakes occurring within a short period of time (a M6.4 foreshock on July 4 and a M7.1 mainshock on July 5 in southern California). These earthquakes were the first time in more than a decade that the southern California region, with an estimated population of 15 million, felt light to moderate shaking over an extended period of time. This valuable opportunity allows us to study how people respond dynamically to such sequences of extreme events. We collected 510,579 tweets about the 2019 Ridgecrest earthquakes to answer the following research questions: (1) Which Twitter accounts were the major players? Did they behave differently and get different responses? (2) How did the publics' response change during these sequential earthquakes? and (3) Which earthquake-related rumors were disseminated on Twitter during the earthquake sequence, by whom, and at what time?

","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"2020 IEEE International Conference on Parallel and Distributed Processing with Applications, Big Data & Cloud Computing","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"2020 IEEE Intl Conf on Parallel & Distributed Processing with Applications, Big Data & Cloud Computing, Sustainable Computing & Communications, Social Computing & Networking (ISPA/BDCloud/SocialCom/SustainCom)","conferenceDate":"December 17-19, 2020","conferenceLocation":"Exeter, United Kingdom","language":"English","publisher":"International Conference on Social Computing and Networking","doi":"10.1109/ISPA-BDCloud-SocialCom-SustainCom51426.2020.00127","usgsCitation":"Ruan, T., Kong, Q., Zhang, Y., McBride, S., and Lv, Q., 2020, An analysis of Twitter responses to the 2019 Ridgecrest Earthquake sequence, in 2020 IEEE International Conference on Parallel and Distributed Processing with Applications, Big Data & Cloud Computing, Exeter, United Kingdom, December 17-19, 2020, p. 810-818, https://doi.org/10.1109/ISPA-BDCloud-SocialCom-SustainCom51426.2020.00127.","productDescription":"9 p.","startPage":"810","endPage":"818","ipdsId":"IP-118686","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":390122,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"Ridgecrest","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.157958984375,\n 35.42486791930558\n ],\n [\n -117.3614501953125,\n 35.42486791930558\n ],\n [\n -117.3614501953125,\n 35.92464453144099\n ],\n [\n -118.157958984375,\n 35.92464453144099\n ],\n [\n -118.157958984375,\n 35.42486791930558\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ruan, Tao 0000-0002-6718-7223","orcid":"https://orcid.org/0000-0002-6718-7223","contributorId":245222,"corporation":false,"usgs":false,"family":"Ruan","given":"Tao","email":"","affiliations":[{"id":12502,"text":"University of Colorado - Boulder","active":true,"usgs":false}],"preferred":false,"id":805648,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kong, Qingkai 0000-0002-7399-0661","orcid":"https://orcid.org/0000-0002-7399-0661","contributorId":245223,"corporation":false,"usgs":false,"family":"Kong","given":"Qingkai","email":"","affiliations":[{"id":6643,"text":"University of California - Berkeley","active":true,"usgs":false}],"preferred":false,"id":805649,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zhang, Yawen 0000-0002-6867-0399","orcid":"https://orcid.org/0000-0002-6867-0399","contributorId":245225,"corporation":false,"usgs":false,"family":"Zhang","given":"Yawen","email":"","affiliations":[{"id":12502,"text":"University of Colorado - Boulder","active":true,"usgs":false}],"preferred":false,"id":805650,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McBride, Sara K. 0000-0002-8062-6542","orcid":"https://orcid.org/0000-0002-8062-6542","contributorId":206933,"corporation":false,"usgs":true,"family":"McBride","given":"Sara K.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":805651,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lv, Qin","contributorId":245227,"corporation":false,"usgs":false,"family":"Lv","given":"Qin","email":"","affiliations":[{"id":12502,"text":"University of Colorado - Boulder","active":true,"usgs":false}],"preferred":false,"id":805652,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70217611,"text":"70217611 - 2020 - Coastal permafrost erosion","interactions":[],"lastModifiedDate":"2021-01-25T15:43:05.846253","indexId":"70217611","displayToPublicDate":"2020-12-31T09:40:26","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":7564,"text":"Arctic Report Card","active":true,"publicationSubtype":{"id":1}},"title":"Coastal permafrost erosion","docAbstract":"

Highlights
• Since the early 2000s, erosion of permafrost coasts in the Arctic has increased at 13 of 14 sites with observational data that extend back to ca. 1960 and ca. 1980, coinciding with warming temperatures, sea ice reduction, and permafrost thaw.
• Permafrost coasts along the US and Canadian Beaufort Sea experienced the largest increase in erosion rates in the Arctic, ranging from +80 to +160%, when comparing average rates from the last two decades of the 20th century with the first two decades of the 21st century.
• The initiation of several national and international research networks in recent years has enabled closer coordination and collaboration of measurements and a better understanding of pan-Arctic permafrost coastal dynamics.

","language":"English","publisher":"NOAA","doi":"10.25923/e47w-dw52","usgsCitation":"Jones, B., Irrgang, A.M., Farquharson, L.M., Lantuit, H., Whalen, D., Ogorodov, S., Grigoriev, M., Tweedie, C.E., Gibbs, A.E., Strzelecki, M.C., Baranskaya, A., Belova, N., Sinitsyn, A., Kroon, A., Maslakov, A., Vieira, G., Grosse, G., Overduin, P., Nitze, I., Maio, C.V., Overbeck, J.R., Bendixen, M., Zagorski, P., and Romanovsky, V., 2020, Coastal permafrost erosion: Arctic Report Card, 10 p., https://doi.org/10.25923/e47w-dw52.","productDescription":"10 p.","ipdsId":"IP-123074","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":436690,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9CRBC5I","text":"USGS data release","linkHelpText":"A GIS compilation of vector shorelines and coastal bluff edge positions, and associated rate-of-change data for Barter Island, Alaska"},{"id":382549,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Jones, Benjamin M. 0000-0002-1517-4711","orcid":"https://orcid.org/0000-0002-1517-4711","contributorId":208625,"corporation":false,"usgs":false,"family":"Jones","given":"Benjamin M.","affiliations":[{"id":37848,"text":"Water and Environmental Research Center, University of Alaska Fairbanks, Fairbanks, Alaska, UNITED STATES","active":true,"usgs":false}],"preferred":true,"id":808868,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Irrgang, Anna M.","contributorId":248316,"corporation":false,"usgs":false,"family":"Irrgang","given":"Anna","email":"","middleInitial":"M.","affiliations":[{"id":49850,"text":"Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research, Potsdam, 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Dustin","contributorId":248318,"corporation":false,"usgs":false,"family":"Whalen","given":"Dustin","email":"","affiliations":[{"id":49851,"text":"Natural Resources Canada, Geological Survey of Canada–Atlantic, Dartmouth, Nova Scotia, Canada","active":true,"usgs":false}],"preferred":false,"id":808872,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ogorodov, Stanislav","contributorId":248319,"corporation":false,"usgs":false,"family":"Ogorodov","given":"Stanislav","affiliations":[{"id":49852,"text":"Faculty of Geography, Lomonosov Moscow State University, Moscow, Russia","active":true,"usgs":false}],"preferred":false,"id":808873,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Grigoriev, Mikhail","contributorId":248320,"corporation":false,"usgs":false,"family":"Grigoriev","given":"Mikhail","affiliations":[{"id":49853,"text":"Mel’nikov Permafrost Institute, Siberian Branch, Russian Academy of Sciences, Yakutsk, 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of Geography and Regional Development, University of Wroclaw, Wroclaw, Poland","active":true,"usgs":false}],"preferred":false,"id":808877,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Baranskaya, Alisa","contributorId":248322,"corporation":false,"usgs":false,"family":"Baranskaya","given":"Alisa","affiliations":[{"id":49852,"text":"Faculty of Geography, Lomonosov Moscow State University, Moscow, Russia","active":true,"usgs":false}],"preferred":false,"id":808878,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Belova, Nataliya","contributorId":248323,"corporation":false,"usgs":false,"family":"Belova","given":"Nataliya","email":"","affiliations":[{"id":49852,"text":"Faculty of Geography, Lomonosov Moscow State University, Moscow, Russia","active":true,"usgs":false}],"preferred":false,"id":808879,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Sinitsyn, Anatoly","contributorId":248324,"corporation":false,"usgs":false,"family":"Sinitsyn","given":"Anatoly","email":"","affiliations":[{"id":49855,"text":"SINTEF AS, SINTEF Community, Trondheim, Norway","active":true,"usgs":false}],"preferred":false,"id":808880,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Kroon, Art","contributorId":248325,"corporation":false,"usgs":false,"family":"Kroon","given":"Art","email":"","affiliations":[{"id":49856,"text":"Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark","active":true,"usgs":false}],"preferred":false,"id":808881,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Maslakov, Alexey","contributorId":248326,"corporation":false,"usgs":false,"family":"Maslakov","given":"Alexey","email":"","affiliations":[{"id":49852,"text":"Faculty of Geography, Lomonosov Moscow State University, Moscow, Russia","active":true,"usgs":false}],"preferred":false,"id":808882,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Vieira, Goncalo","contributorId":248327,"corporation":false,"usgs":false,"family":"Vieira","given":"Goncalo","email":"","affiliations":[{"id":49857,"text":"Centre of Geographical Studies, Institute of Geography and Spatial Planning, University of Lisbon, Portugal","active":true,"usgs":false}],"preferred":false,"id":808883,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Grosse, Guido","contributorId":146182,"corporation":false,"usgs":false,"family":"Grosse","given":"Guido","email":"","affiliations":[{"id":12916,"text":"Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Potsdam, Germany","active":true,"usgs":false}],"preferred":false,"id":808884,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Overduin, Paul","contributorId":248328,"corporation":false,"usgs":false,"family":"Overduin","given":"Paul","email":"","affiliations":[{"id":49850,"text":"Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research, Potsdam, Germany","active":true,"usgs":false}],"preferred":false,"id":808885,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Nitze, Ingmar","contributorId":191057,"corporation":false,"usgs":false,"family":"Nitze","given":"Ingmar","affiliations":[],"preferred":false,"id":808886,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Maio, Christopher V.","contributorId":208635,"corporation":false,"usgs":false,"family":"Maio","given":"Christopher","email":"","middleInitial":"V.","affiliations":[{"id":37850,"text":"University of Alaska Fairbanks, Fairbanks, Alaska, UNITED STATES","active":true,"usgs":false}],"preferred":false,"id":808887,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Overbeck, Jacquelyn R.","contributorId":181813,"corporation":false,"usgs":false,"family":"Overbeck","given":"Jacquelyn","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":808888,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Bendixen, Mette","contributorId":248329,"corporation":false,"usgs":false,"family":"Bendixen","given":"Mette","email":"","affiliations":[{"id":49858,"text":"Institute of Arctic and Alpine Research (INSTAAR), University of Colorado, Boulder, USA","active":true,"usgs":false}],"preferred":false,"id":808889,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Zagorski, Piotr","contributorId":248330,"corporation":false,"usgs":false,"family":"Zagorski","given":"Piotr","email":"","affiliations":[{"id":49859,"text":"Institute of Earth and Environmental Sciences, Marie Curie- Skłodowska University, Lublin, Poland","active":true,"usgs":false}],"preferred":false,"id":808890,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Romanovsky, Vladimir","contributorId":175208,"corporation":false,"usgs":false,"family":"Romanovsky","given":"Vladimir","affiliations":[{"id":6695,"text":"UAF","active":true,"usgs":false}],"preferred":false,"id":808891,"contributorType":{"id":1,"text":"Authors"},"rank":24}]}} ,{"id":70218021,"text":"70218021 - 2020 - Geologic map of the Dog River and northern part of the Badger Lake 7.5′ quadrangles, Hood River County, Oregon","interactions":[],"lastModifiedDate":"2021-04-14T14:37:25.364879","indexId":"70218021","displayToPublicDate":"2020-12-31T09:33:36","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"seriesTitle":{"id":8123,"text":"Geological Map","active":true,"publicationSubtype":{"id":2}},"seriesNumber":"126","title":"Geologic map of the Dog River and northern part of the Badger Lake 7.5′ quadrangles, Hood River County, Oregon","docAbstract":"

The Dog River and northern part of the Badger Lake 7.5' quadrangles encompasses an area of ~201 km2 (77.6 mi2) of the High Cascades of north-central Oregon, lying across the eastern slopes of Mount Hood volcano (Figure 1-1; Plate 1; referred to herein as Dog River–Badger Lake area). Mount Hood, known as Wy’east to Native Americans, is Oregon’s tallest peak (3,427 m [11,241 ft]). The volcano has erupted episodically for the past 500,000 years, experiencing two major eruptive periods during the last 1,500 years (Scott and others, 1997a; Scott and others, 2003; Scott and Gardner, 2017). Cascade Range volcanism and structural development in the area dates back longer, with eruptive activity dating from latest Miocene to recent time; part of that volcano-tectonic record is detailed by new high-resolution geologic mapping presented here.

The geology of the Dog River–Badger Lake area was mapped by the Oregon Department of Geology and Mineral Industries (DOGAMI) between 2017 and 2020, in collaboration with geoscientists from the U. S. Geological Survey Cascade Volcano Observatory (USGS CVO) and Hamilton College, New York. The primary objective of this investigation is to provide an updated and spatially accurate geologic framework for the Dog River–Badger Lake area as part of a multi-year study of the geology of the larger Middle Columbia Basin (Figure 1-1, Figure 1-2). Additional key objectives of this project are to: 1) determine the geologic history of volcanic rocks in this part of the northern Oregon Cascade Range, including lava flows and volcaniclastic deposits erupted from Middle Pleistocene to Holocene Mount Hood volcano; 2) provide significant new details about the structure and fault history along the northern segment of the High Cascades intra-arc graben (Hood River graben); and 3) better understand geologic hazards in the region, related to earthquakes, volcanoes, and landslides. New detailed geologic data presented here also provides a basis for future geologic, geohydrologic, and geohazard studies in the greater Middle Columbia Basin. Detailed geologic mapping in this part of the Middle Columbia Basin is a high priority of the Oregon Geologic Map Advisory Committee (OGMAC), supported in part by grants from the STATEMAP component of the USGS National Cooperative Geologic Mapping Program (G17AC00210, G19AC00160). Additional funds were provided by the State of Oregon.

The core products of this study are this report, an accompanying geologic map and cross sections (Plate 1), an Esri ArcGIS™ geodatabase, and Microsoft Excel® spreadsheets tabulating point data for geochemistry, geochronology, magnetic polarity, orientation points, and well data. The geodatabase presents the new geologic mapping in a digital format consistent with the USGS National Cooperative Geologic Mapping Program Geologic Map Schema (GeMS) (U.S. Geological Survey National Cooperative Geologic Mapping Program, 2020). This geodatabase contains spatial information, including geologic polygons, contacts, structures, geochemistry, geochronology, magnetic observation, orientation points, and well data, as well as data about each geologic unit such as age, lithology, mineralogy, and structure. Digitization at scales of 1:8,000 or better was accomplished using a combination of high-resolution lidar topography and imagery. Surficial and bedrock geologic units contained in the geodatabase are depicted on the Plate 1 at a scale of 1:24,000. Both the geodatabase and geologic map are supported by this report describing the geology in detail.

","language":"English","publisher":"Oregon Department of Geology and Mineral Industries","usgsCitation":"McClaughry, J.D., Scott, W., Duda, C.J., and Conrey, R.M., 2020, Geologic map of the Dog River and northern part of the Badger Lake 7.5′ quadrangles, Hood River County, Oregon: Geological Map 126, Report: 154 p.; 1 Plate 48 x 52 inches; Database; Metadata.","productDescription":"Report: 154 p.; 1 Plate 48 x 52 inches; Database; Metadata","ipdsId":"IP-126371","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":385093,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":383245,"type":{"id":15,"text":"Index Page"},"url":"https://www.oregongeology.org/pubs/gms/p-GMS-126.htm"}],"scale":"24000","country":"United States","state":"Oregon","county":"Hood River County","otherGeospatial":"Dog River and Northern Part of the Badger Lake 7.5' Quadrangles","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.87683105468749,\n 44.97839955494438\n ],\n [\n -120.5914306640625,\n 44.97839955494438\n ],\n [\n -120.5914306640625,\n 45.73494252455993\n ],\n [\n -121.87683105468749,\n 45.73494252455993\n ],\n [\n -121.87683105468749,\n 44.97839955494438\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"McClaughry, Jason D.","contributorId":194544,"corporation":false,"usgs":false,"family":"McClaughry","given":"Jason","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":810242,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Scott, William E. 0000-0001-8156-979X","orcid":"https://orcid.org/0000-0001-8156-979X","contributorId":250706,"corporation":false,"usgs":true,"family":"Scott","given":"William E.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":810243,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Duda, Carlie J. M.","contributorId":250707,"corporation":false,"usgs":false,"family":"Duda","given":"Carlie","email":"","middleInitial":"J. M.","affiliations":[{"id":32397,"text":"Oregon Department of Geology and Mineral Industries","active":true,"usgs":false}],"preferred":false,"id":810244,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Conrey, Richard M.","contributorId":194345,"corporation":false,"usgs":false,"family":"Conrey","given":"Richard","email":"","middleInitial":"M.","affiliations":[{"id":13203,"text":"School of the Environment, Washington State University","active":true,"usgs":false}],"preferred":false,"id":810245,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70210826,"text":"70210826 - 2020 - Recent planform changes in the Upper Mississippi River","interactions":[],"lastModifiedDate":"2021-11-03T14:42:36.620726","indexId":"70210826","displayToPublicDate":"2020-12-31T09:03:48","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5000,"text":"Long Term Resource Monitoring Technical Report","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"LTRM-2019GC8","title":"Recent planform changes in the Upper Mississippi River","docAbstract":"Geomorphic changes in the Upper Mississippi River (UMR) have long been a concern of river agencies charged with maintaining and restoring river habitat (GREAT 1980; Jackson et al. 1981; USFWS 1992). Large meandering alluvial rivers like the UMR are expected to constantly change and adjust their fluvial landforms within their riparian corridors as a result of the natural interaction of hydrologic processes, sediment movement, and vegetation over time. However, present geomorphic changes in the UMR reflect altered hydrologic, hydraulic, and sediment conditions caused by regulated flows, constructed agricultural levees and navigation dams, altered land use in the watershed, and climate change. Levees reduce lateral hydrologic and sediment connectivity between channels and floodplains on many tributaries and on the Mississippi River downstream of Pool 13. Between each of the dams are a repeating series of landforms associated with tailwater, intermediate, and impounded conditions. The dams maintain a minimum water level, thus creating many off-channel areas that act as sediment traps. Whereas high-head dams cut off sedimentological connectivity longitudinally through the river corridor (Skalak et al., 2013), low head dams on the UMR only slightly altered transport longitudinally. Deltaic-like sedimentation can be common in the impounded sections of dammed rivers. Erosion of relict land surfaces that remained above the raised impounded water levels has been the dominant change in UMR impounded sections due to increased wind fetch leading to increased wave action. Even though upland sources of sediment from tributaries have decreased over the middle to late 20th century, increased annual precipitation, the interplay of increased variability in flood magnitudes from year to year, and more fall and winter flooding have likely changed erosion and sedimentation patterns in the UMR (Belby, et al., 2019). Paradoxically, monitoring and research indicates that the concentration of some water column constituents like total suspended solids and phosphorous has decreased during the 1991 to 2014 time period (Kreiling and Houser, 2016). In areas prone to increased sedimentation, bed elevations rise and thereby water depths are reduced at a given discharge, resulting in loss of fish habitat. Sediment deposition or erosion further influences water exchange rates between main channel and off-channel areas in the river by increasing resistance in connecting channels or enlarging existing connecting channels. Water depth and water exchange rates are the most prominent features describing habitat quality in the UMR (De Jager et al. 2018), and in some cases, the trajectory of planform change from heightened deposition promises to threaten deep backwater habitats particularly important for overwintering fish.\n\nAlthough information on the rate of vertical change in bed elevation is needed for a complete assessment of geomorphic change associated with the loss of deep backwater habitats, mapping planform changes over time (i.e., lateral changes between the land-water boundary) provide needed information on the location, potential cause, and progressive direction of deposition, especially in the mid sections between dams where deltaic processes are the most pronounced. Several types of planform changes have been observed and identified as concerns. For example, island loss in the large impounded areas of the upper part of the UMR was one of the concerns identified by river managers in the 1980s and 90s, and subsequently island construction became a common form of restoration implemented by the Upper Mississippi River Restoration (UMRR) Program (USACE 2012). Other subtler planform changes, such as channel bank erosion and delta formation in backwaters, are perceived to be important, but have largely gone unquantified. A systemwide reconnaissance of the UMR and IWW conducted in 1998 concluded that 14-percent of the river banks were eroding (Nakato and Anderson 1998). However, stabilization of existing river banks has never been widely pursued as a restoration measure, due to the high cost and uncertain benefits. Delta formation reduces the amount of backwater habitat; however, the deltas maintain and create a mix of riparian and aquatic habitats, and that is generally considered to be beneficial for wildlife and fish. If recent hydrologic trends of more frequent and longer duration flood events continue, a better understanding of planform changes can help in describing past changes, and then be used to forecast potential future trajectories of change. If UMR resource managers determine that past and forecasted conditions are undesirable, then UMRR projects could be identified and prioritized to address those concerns.\n\nVegetative cover associations with landform changes have been used to detect and quantify planform changes in many rivers (Johnson 1985; Hiatt 2015; Volte et al. 2015). Freyer and Jefferson (2013) completed such a study in Pool 6 of the UMR using the landcover data from 12 dates over a 115-yr period, including the 1989, 2000, and 2010/2011 landcover/use (LCU) data from the UMRR Program. Planform change detected over the last 20 years represented by the UMRR Program data best reflect present-day geomorphic patterns, rates and processes. Changes occurring prior to dam construction and changes occurring soon after dam construction are likely not the same as those happening now, 50-70 years after dam construction and creation of the impoundments (McHenry et al., 1984; Bhowmik and Adams, 1986; WEST Consultants, 2000). \n\nThe LCU data from each of the 1989, 2000, and 2010/2011 imagery was developed using similar methods and is available in a Geographical Information System (GIS) for the entire UMR and therefore provides the opportunity for a more comprehensive planform change analysis. This study used GIS overlays of LCU classes to map and quantify changes in planform features over two periods, looking specifically for depositional areas where terrestrial and wetland vegetation expanded at the expense of open water. The land expansion was grouped into four possible process-based types common in large floodplain rivers, some following that used by Lewin et al. (2017). The four types include: crevasse deltas emanating from a breach from a main channel through a natural levee or narrow floodplain into backwaters (crevasse deltas), tributary deltas expanding into backwaters (tributary deltas), deltaic bars at the upstream end of impoundments (impounded deltas), and linear-like bars extending from the downstream ends of narrow levees and remnant floodplains (bar-tail limbs). The methods deployed for change detection addressed possible errors from a variety of sources.","language":"English","publisher":"US Army Corps of Engineers, Upper Mississippi River Restoration (UMRR) Program","usgsCitation":"Rogala, J.T., Fitzpatrick, F., and Hendrickson, J.S., 2020, Recent planform changes in the Upper Mississippi River: Long Term Resource Monitoring Technical Report LTRM-2019GC8, 33 p.","productDescription":"33 p.","ipdsId":"IP-113610","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":391325,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":391323,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://umesc.usgs.gov/documents/publications/2020/rogala_a_2020.html"}],"country":"United States","state":"Illinois, Iowa, Minnesota, Missouri, Wisconsin","otherGeospatial":"Upper Mississippi River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90,\n 38.58252615935333\n ],\n [\n -91.0546875,\n 40.07807142745009\n ],\n [\n -90,\n 41.86956082699455\n ],\n [\n -90.8349609375,\n 43.29320031385282\n ],\n [\n -91.2744140625,\n 44.465151013519616\n ],\n [\n -93.55957031249999,\n 46.01222384063236\n ],\n [\n -93.4716796875,\n 46.619261036171515\n ],\n [\n -95.1416015625,\n 46.46813299215554\n ],\n [\n -94.52636718749999,\n 45.24395342262324\n ],\n [\n -93.251953125,\n 44.55916341529182\n ],\n [\n -91.93359375,\n 43.866218006556394\n ],\n [\n -91.1865234375,\n 42.4234565179383\n ],\n [\n -90.791015625,\n 42.22851735620852\n ],\n [\n -91.14257812499999,\n 41.705728515237524\n ],\n [\n -91.669921875,\n 41.07935114946899\n ],\n [\n -91.97753906249999,\n 39.842286020743394\n ],\n [\n -91.318359375,\n 38.89103282648846\n ],\n [\n -90,\n 38.58252615935333\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Rogala, James T. 0000-0002-1954-4097 jrogala@usgs.gov","orcid":"https://orcid.org/0000-0002-1954-4097","contributorId":2651,"corporation":false,"usgs":true,"family":"Rogala","given":"James","email":"jrogala@usgs.gov","middleInitial":"T.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":791606,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fitzpatrick, Faith A. 0000-0002-9748-7075","orcid":"https://orcid.org/0000-0002-9748-7075","contributorId":209612,"corporation":false,"usgs":true,"family":"Fitzpatrick","given":"Faith A.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":791607,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hendrickson, Jon S.","contributorId":177520,"corporation":false,"usgs":false,"family":"Hendrickson","given":"Jon","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":791608,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70215071,"text":"70215071 - 2020 - 2020 Four-band aerial imagery testing and acquisition for 2020 land cover/land use mission","interactions":[],"lastModifiedDate":"2021-11-03T13:58:46.733652","indexId":"70215071","displayToPublicDate":"2020-12-31T08:58:02","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5000,"text":"Long Term Resource Monitoring Technical Report","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"LTRM-2018CAM4","title":"2020 Four-band aerial imagery testing and acquisition for 2020 land cover/land use mission","docAbstract":"The aerial camera testing project lays the groundwork for the collection of aerial imagery that will be used in the creation of the next iteration of systemic land cover/land use data for the Upper Mississippi River System. Prior to acquisition in the summer of 2020, the new 4-band aerial camera will be assessed for image quality at various resolutions and be compared to the camera used for the 2010/2011 collection. Systemic aerial imagery has been acquired, and vegetation datasets derived from that imagery, by the Upper Mississippi River Restoration Program’s Long Term Resource Monitoring element on a decadal basis beginning in 1989 and follow-up imagery missions in 2000 and 2010/2011. Remote sensing and geographic information system technology has changed dramatically during this time, transitioning from a workflow based on 9-inch by 9-inch aerial film-based cameras to today’s 80-megapixel four-band digital camera. In addition to the camera testing, this report also provides historical information of previous aerial imagery acquisition efforts and how that process has continued to advance in the 30 years since the Program’s genesis.","language":"English","publisher":"U.S. Army Corps of Engineers' Mississippi River Restoration Program","usgsCitation":"Robinson, L.R., 2020, 2020 Four-band aerial imagery testing and acquisition for 2020 land cover/land use mission: Long Term Resource Monitoring Technical Report LTRM-2018CAM4, 17 p.","productDescription":"17 p.","ipdsId":"IP-118904","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":391322,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":391321,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://umesc.usgs.gov/documents/publications/2020/robinson_a_2020.html"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Robinson, Larry R. 0000-0002-3049-6479 lrobinson@usgs.gov","orcid":"https://orcid.org/0000-0002-3049-6479","contributorId":3136,"corporation":false,"usgs":true,"family":"Robinson","given":"Larry","email":"lrobinson@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":800714,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70229205,"text":"70229205 - 2020 - Reconnaissance map of the Cenozoic geology in the Carlin basin area, Elko and Eureka counties, Nevada","interactions":[],"lastModifiedDate":"2022-03-03T14:38:55.904902","indexId":"70229205","displayToPublicDate":"2020-12-31T08:27:42","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"seriesTitle":{"id":10147,"text":"Nevada Bureau of Mines and Geology Open File Report","active":true,"publicationSubtype":{"id":2}},"seriesNumber":"2020-02","title":"Reconnaissance map of the Cenozoic geology in the Carlin basin area, Elko and Eureka counties, Nevada","docAbstract":"
The middle Miocene Carlin sedimentary basin encompasses a large area between the Adobe Range to the east, the Piñon Range to the south, the southern Independence Mountains and Marys Mountain to the west, and Swales Mountain to the north. The town of Carlin is in the southern part of the basin. The geologic map includes detailed to more reconnaissance mapping of Cenozoic units in the main part of the basin, including different facies of the middle Miocene Humboldt Formation. The mapping was part of a broader study of the Miocene and younger paleogeographic evolution of the region. Earlier work obtained numerous 40Ar/39Ar and tephra correlation dates on sedimentary and volcanic units in the basin. The basin connected to the east into the Elko sedimentary basin and to the northwest and northeast into similar smaller basins between present-day mountain ranges. Early sediments, largely fluvial, began to accumulate in the lowlands between the surrounding ranges at about 16.5 Ma. The sediments were derived from Paleozoic sedimentary and middle Tertiary volcanic units in the nearby highlands, and flow patterns indicate a general southward flow towards present-day Pine Valley. The eruption of the Palisade Canyon–Marys Mountain rhyolite flows at the southwest end of the basin at 15.3 Ma blocked the southward flow, and a lake began to form in the basin. As the lake grew in extent, sedimentary units around the fringes of the lake included a mixture of inflowing fluvial sediments mixed with the pyroclastic-fall, ash-rich sediments deposited in the lake. The lake margin expanded, and stratigraphic sections record the progressive transition from fluvial to mixed fluvial and lacustrine, and finally to entirely lacustrine. The volcanic rock dam was breached at about 14.7 Ma, the lake drained, and fluvial sediments blanketed the entire basin for an unknown period of time after that. Sedimentation progressively buried existing highlands and bridged gaps between adjacent basins. For example, the Carlin and Elko basins connected across the southern Adobe Range.

Normal faulting produced numerous, mostly north- to north-northeast-striking faults that cut the sedimentary units and surrounding highlands largely after sedimentation ceased. The largest fault formed in the eastern third of the basin and tilted all of the sedimentary units in the western two-thirds of the basin, as well as the eastern part of Marys Mountain, to the east. Some offset took place during sedimentation. Many other normal faults of smaller extent and offset cut the sedimentary units.

The integration of streams draining the Elko and Carlin basins began after about 9.8 Ma. The streams, which together comprised the early stages of the Humboldt River, flowed regionally southwestward beyond the Carlin basin. As many as thirteen, downward-stepping strath terraces in the Carlin basin record the progressive downcutting into and removal of the middle Miocene sediments. Gravel deposits form a thin veneer on some of the higher terraces. Clasts in those gravel deposits, as well as the overall terrace pattern, indicate southward drainage towards the Humboldt River. The erosion gradually re-exposed the flanks of the surrounding highlands. A brief pause in downcutting allowed the formation of a small lake in the Hemphillian (late Miocene), represented by lacustrine units northwest of Carlin.

The sedimentary rocks of the Carlin basin conceal a large segment of the world-class, late Eocene Carlin gold trend, which extends from the southern Independence Mountains south into the Piñon Range. Sedimentation largely buried the Gold Quarry and Mike gold deposits in the northwestern part of the basin. Later faulting and erosion re-exposed the Gold Quarry deposit, but the Mike deposit remains buried. The basin’s sedimentary units conceal potential Paleozoic host rocks, and the sedimentary facies and post-sedimentation faults shown on the map may help guide interpretations of geophysical and other exploration data in the Carlin basin.

The current map publication was supported by the USGS National Cooperative Geologic Mapping Program under STATEMAP award number G19AC00383.

","language":"English","publisher":"Nevada Bureau of Mines and Geology","usgsCitation":"Wallace, A., 2020, Reconnaissance map of the Cenozoic geology in the Carlin basin area, Elko and Eureka counties, Nevada: Nevada Bureau of Mines and Geology Open File Report 2020-02, Report: 10 p.; 1 Plate: 35.00 x 30.00 inches.","productDescription":"Report: 10 p.; 1 Plate: 35.00 x 30.00 inches","ipdsId":"IP-125443","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":396696,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":396686,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.nbmg.unr.edu/Cen-geol-Carlin-basin-p/of2020-02.htm"}],"scale":"50000","country":"United States","state":"Nevada","county":"Elko County, Eureka County","otherGeospatial":"Carlin basin area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.2,\n 40.625\n ],\n [\n -115.95,\n 40.625\n ],\n [\n -115.95,\n 40.925964939514294\n ],\n [\n -116.2,\n 40.925964939514294\n ],\n [\n -116.2,\n 40.625\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Wallace, Alan R.","contributorId":287598,"corporation":false,"usgs":false,"family":"Wallace","given":"Alan R.","affiliations":[{"id":61619,"text":"USGS emeritus, not in Active Directory","active":true,"usgs":false}],"preferred":false,"id":836933,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70220323,"text":"70220323 - 2020 - Improving the positional and vertical accuracy of named summits above 13,000 ft in the United States","interactions":[],"lastModifiedDate":"2021-05-06T13:30:25.542612","indexId":"70220323","displayToPublicDate":"2020-12-31T08:22:33","publicationYear":"2020","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Improving the positional and vertical accuracy of named summits above 13,000 ft in the United States","docAbstract":"

The National Map (TNM) portal provides public access to U.S. Geological Survey (USGS) high-resolution topographic datasets, and maps from the Historical Topographic Map Collection (HTMC). Elevation values shown on HTMC maps were obtained from ground spot elevation measurements, as compared to today’s elevation measurements derived from more efficient methods, such as lidar, radar, or sonar. These spot elevations were collected either by levelling in the field or by photogrammetrists in the office, and are called mass points with post-spacings of two-arc seconds (arcsec), approximately 60 meters depending on latitude, in steep terrain and one-half arcsec, approximately 15 meters, in flat terrain (Federal Geographic Data Committee 1997). The vertical accuracy of spot elevations is ± 10 feet. Most spot elevations were used only in contour derivation to create a more spatially continuous representations of terrain, but some were also labelled on the maps to supply accurate elevations of culturally important features such as mountain peaks, gaps, and road junctions.

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