{"pageNumber":"672","pageRowStart":"16775","pageSize":"25","recordCount":184617,"records":[{"id":70212046,"text":"70212046 - 2020 - Mapping climate change resistant vernal pools in the northeastern U.S.","interactions":[],"lastModifiedDate":"2021-09-22T15:37:46.324155","indexId":"70212046","displayToPublicDate":"2017-12-31T10:37:14","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5883,"text":"Cooperator Report","active":true,"publicationSubtype":{"id":1}},"title":"Mapping climate change resistant vernal pools in the northeastern U.S.","docAbstract":"Vernal pools are seasonal wetlands that provide important breeding habitat for a variety of amphibian species. As future climate projections indicate warmer growing seasons and earlier seasonal increases in evapotranspiration, some managers of vernal pools have expressed concern that pools may dry earlier in the season, potentially interfering with completion of amphibian life cycles. In this context, a subset of pools might function as hydrologic refugia by providing wetland habitat later into the year under relatively dry conditions, thus supporting species persistence even as summer conditions become warmer and droughts more frequent. This study used approximately 3,000 field observations of inundation from 450 pools in the northeastern United States—located from West Virginia to Maine—to train machine-learning models for predicting the likelihood of pool inundation. Inputs to these models included pool size, day of the year, climate conditions, short-term weather patterns, and attributes of the landscapes in which pools were embedded. Predictions of pool wetness were generated on a daily time step from late April through late July using three short-term weather scenarios (dry, wet, and average) under historical climate conditions and four sets of downscaled climate projections (2050s and 2080s under Representative Concentration Pathways 4.5 and 8.5). The modeling and inundation prediction process was replicated using four inundation thresholds on wetted area and depth. Model outputs can enable users to examine the inundation thresholds, time points, weather scenarios, and future climate projections most relevant to their management needs. Together with long-term monitoring of individual pools at the site scale, this regional-scale study can support amphibian conservation by helping to identify subsets of pools that may be most likely to function as hydrologic refugia from changing climate conditions.","language":"English","publisher":"Northeast Climate Adaptation Science Center","usgsCitation":"Cartwright, J.M., and Campbell Grant, E.H., 2020, Mapping climate change resistant vernal pools in the northeastern U.S.: Cooperator Report, HTML Document.","productDescription":"HTML Document","ipdsId":"IP-117745","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":389594,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":389593,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://necasc.umass.edu/projects/mapping-climate-change-resistant-vernal-pools-northeastern-us"}],"country":"United States","state":"Connecticut, Delaware, Maine, Maryland, Massachusetts, New Hampshire, New Jersey, New York, Pennsylvania, Rhode Island, Vermont, Virginia, West Virginia","otherGeospatial":"northeastern United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.025390625,\n 37.020098201368114\n ],\n [\n -66.97265625,\n 44.59046718130883\n ],\n [\n -68.64257812499999,\n 47.45780853075031\n ],\n [\n -80.947265625,\n 42.61779143282346\n ],\n [\n -81.38671875,\n 39.436192999314095\n ],\n [\n -76.025390625,\n 37.020098201368114\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Cartwright, Jennifer M. 0000-0003-0851-8456 jmcart@usgs.gov","orcid":"https://orcid.org/0000-0003-0851-8456","contributorId":5386,"corporation":false,"usgs":true,"family":"Cartwright","given":"Jennifer","email":"jmcart@usgs.gov","middleInitial":"M.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true}],"preferred":true,"id":796184,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Campbell Grant, Evan H. 0000-0003-4401-6496 ehgrant@usgs.gov","orcid":"https://orcid.org/0000-0003-4401-6496","contributorId":150443,"corporation":false,"usgs":true,"family":"Campbell Grant","given":"Evan","email":"ehgrant@usgs.gov","middleInitial":"H.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":796185,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70208360,"text":"70208360 - 2020 - Clawpack: Building an open source ecosystem for solving hyperbolic PDEs","interactions":[],"lastModifiedDate":"2020-02-05T15:48:30","indexId":"70208360","displayToPublicDate":"2016-08-08T15:45:30","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5926,"text":"PeerJ Computer Science","onlineIssn":"2376-5992","active":true,"publicationSubtype":{"id":10}},"title":"Clawpack: Building an open source ecosystem for solving hyperbolic PDEs","docAbstract":"Clawpack is a software package designed to solve nonlinear hyperbolic partial differential equations using high-resolution finite volume methods based on Riemann solvers and limiters. The package includes a number of variants aimed at different applications and user communities. Clawpack has been actively developed as an open source project for over 20 years. The latest major release, Clawpack 5, introduces a number of new features and changes to the code base and a new development model based on GitHub and Git submodules. This article provides a summary of the most significant changes, the rationale behind some of these changes, and a description of our current development model.","language":"English","publisher":"PeerJ, Inc.","doi":"10.7717/peerj-cs.68","usgsCitation":"Mandli, K.T., Ahmadia, A.J., Berger, M.J., Calhoun, D.A., George, D.L., Hadjimichael, Y., Ketcheson, D.I., Lemoine, G., and LeVeque, R.J., 2020, Clawpack: Building an open source ecosystem for solving hyperbolic PDEs: PeerJ Computer Science, v. 2, e68, 27 p., https://doi.org/10.7717/peerj-cs.68.","productDescription":"e68, 27 p.","ipdsId":"IP-076298","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":458806,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.7717/peerj-cs.68","text":"Publisher Index Page"},{"id":372094,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-08-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Mandli, Kyle T.","contributorId":222227,"corporation":false,"usgs":false,"family":"Mandli","given":"Kyle","email":"","middleInitial":"T.","affiliations":[{"id":7171,"text":"Columbia University","active":true,"usgs":false}],"preferred":false,"id":781568,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ahmadia, Aron J.","contributorId":199787,"corporation":false,"usgs":false,"family":"Ahmadia","given":"Aron","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":781569,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Berger, Marsha J","contributorId":222228,"corporation":false,"usgs":false,"family":"Berger","given":"Marsha","email":"","middleInitial":"J","affiliations":[{"id":40508,"text":"New York University","active":true,"usgs":false}],"preferred":false,"id":781570,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Calhoun, Donna A","contributorId":222229,"corporation":false,"usgs":false,"family":"Calhoun","given":"Donna","email":"","middleInitial":"A","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":781571,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"George, David L. 0000-0002-5726-0255 dgeorge@usgs.gov","orcid":"https://orcid.org/0000-0002-5726-0255","contributorId":3120,"corporation":false,"usgs":true,"family":"George","given":"David","email":"dgeorge@usgs.gov","middleInitial":"L.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":781572,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hadjimichael, Yiannis","contributorId":222230,"corporation":false,"usgs":false,"family":"Hadjimichael","given":"Yiannis","email":"","affiliations":[{"id":35609,"text":"KAUST University","active":true,"usgs":false}],"preferred":false,"id":781573,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ketcheson, David I.","contributorId":199791,"corporation":false,"usgs":false,"family":"Ketcheson","given":"David","email":"","middleInitial":"I.","affiliations":[],"preferred":false,"id":781574,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lemoine, Grady I.","contributorId":222231,"corporation":false,"usgs":false,"family":"Lemoine","given":"Grady I.","affiliations":[{"id":35610,"text":"CD-Adapco","active":true,"usgs":false}],"preferred":false,"id":781575,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"LeVeque, Randall J.","contributorId":198359,"corporation":false,"usgs":false,"family":"LeVeque","given":"Randall","email":"","middleInitial":"J.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":781576,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70210698,"text":"fs20203027 - No Year - Assessment of continuous oil and gas resources in the Ordovician Collingwood Formation and Utica Shale of the Michigan Basin Province, 2019","interactions":[],"lastModifiedDate":"2020-09-08T15:28:53.379784","indexId":"fs20203027","displayToPublicDate":"2020-06-22T14:00:00","publicationYear":"2020","noYear":true,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-3027","displayTitle":"Assessment of Continuous Oil and Gas Resources in the Ordovician Collingwood Formation and Utica Shale of the Michigan Basin Province, 2019","title":"Assessment of continuous oil and gas resources in the Ordovician Collingwood Formation and Utica Shale of the Michigan Basin Province, 2019","docAbstract":"

Using a geology-based assessment methodology, the U.S. Geological Survey estimated undiscovered, technically recoverable mean resources of 290 milllion barrels of shale oil and 7.9 trillion cubic feet of shale gas in the Ordovician Collingwood-Utica Shale Total Petroleum System of the Michigan Basin Province.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20203027","usgsCitation":"Schenk, C.J., Mercier, T.J., Woodall, C.A., Leathers-Miller, H.M., Finn, T.M., Le, P.A., Brownfield, M.E., Marra, K.R., and Ellis, G.S., 2020, Assessment of continuous oil and gas resources in the Ordovician Collingwood Formation and Utica Shale of the Michigan Basin Province, 2019: U.S. Geological Survey Fact Sheet 2020–3027, 2 p., https://doi.org/10.3133/fs20203027.","productDescription":"Report: 2 p.; Data Release","onlineOnly":"N","ipdsId":"IP-112453","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":437230,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9VY9XD4","text":"USGS data release","linkHelpText":"USGS National and Global Oil and Gas Assessment Project-Michigan Basin Province, Collingwood-Utica Assessment Unit Boundaries and Assessment Input Data Forms"},{"id":375667,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2020/3027/fs20203027.pdf","text":"Report","size":"708 kB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2020-3027"},{"id":375666,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2020/3027/coverthb.jpg"},{"id":375668,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://www.sciencebase.gov/catalog/item/5e50325ce4b0ff554f72dc69","text":"USGS data release","description":"USGS Data Release","linkHelpText":"USGS National and Global Oil and Gas Assessment Project - Michigan Basin Province, Collingwood Shale and Utica Shale Formations Assessment Unit Boundaries and Assessment Input Data Forms"}],"country":"United States","state":"Michigan","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -86.50634765625,\n 44.071800467511565\n ],\n [\n -86.66015624999999,\n 43.24520272203359\n ],\n [\n -83.29833984375,\n 43.40504748787038\n ],\n [\n -83.12255859375,\n 45.506346901083425\n ],\n [\n -84.08935546875,\n 45.78284835197676\n ],\n [\n -85.01220703125,\n 45.75219336063106\n ],\n [\n -85.93505859374999,\n 45.24395342262324\n ],\n [\n -86.50634765625,\n 44.071800467511565\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"

Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver, CO 80225-0046

","tableOfContents":"","publishedDate":"2020-06-22","noUsgsAuthors":false,"publicationDate":"2020-06-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Schenk, Christopher J. 0000-0002-0248-7305 schenk@usgs.gov","orcid":"https://orcid.org/0000-0002-0248-7305","contributorId":826,"corporation":false,"usgs":true,"family":"Schenk","given":"Christopher","email":"schenk@usgs.gov","middleInitial":"J.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":791009,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mercier, Tracey J. 0000-0002-8232-525X tmercier@usgs.gov","orcid":"https://orcid.org/0000-0002-8232-525X","contributorId":2847,"corporation":false,"usgs":true,"family":"Mercier","given":"Tracey","email":"tmercier@usgs.gov","middleInitial":"J.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":791010,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Woodall, Cheryl A. 0000-0002-4844-5768 cwoodall@usgs.gov","orcid":"https://orcid.org/0000-0002-4844-5768","contributorId":194924,"corporation":false,"usgs":true,"family":"Woodall","given":"Cheryl","email":"cwoodall@usgs.gov","middleInitial":"A.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":791011,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Leathers-Miller, Heidi M. 0000-0001-5208-9906 hleathers@usgs.gov","orcid":"https://orcid.org/0000-0001-5208-9906","contributorId":150419,"corporation":false,"usgs":true,"family":"Leathers-Miller","given":"Heidi","email":"hleathers@usgs.gov","middleInitial":"M.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":791012,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Finn, Thomas M. 0000-0001-6396-9351 finn@usgs.gov","orcid":"https://orcid.org/0000-0001-6396-9351","contributorId":778,"corporation":false,"usgs":true,"family":"Finn","given":"Thomas","email":"finn@usgs.gov","middleInitial":"M.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":791013,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Le, Phuong A. 0000-0003-2477-509X ple@usgs.gov","orcid":"https://orcid.org/0000-0003-2477-509X","contributorId":150418,"corporation":false,"usgs":true,"family":"Le","given":"Phuong","email":"ple@usgs.gov","middleInitial":"A.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":791014,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Brownfield, Michael E. 0000-0003-3633-1138 mbrownfield@usgs.gov","orcid":"https://orcid.org/0000-0003-3633-1138","contributorId":1548,"corporation":false,"usgs":true,"family":"Brownfield","given":"Michael","email":"mbrownfield@usgs.gov","middleInitial":"E.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":791015,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Marra, Kristen R. 0000-0001-8027-5255 kmarra@usgs.gov","orcid":"https://orcid.org/0000-0001-8027-5255","contributorId":4844,"corporation":false,"usgs":true,"family":"Marra","given":"Kristen","email":"kmarra@usgs.gov","middleInitial":"R.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":791016,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Ellis, Geoffrey S. 0000-0003-4519-3320 gsellis@usgs.gov","orcid":"https://orcid.org/0000-0003-4519-3320","contributorId":1058,"corporation":false,"usgs":true,"family":"Ellis","given":"Geoffrey","email":"gsellis@usgs.gov","middleInitial":"S.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":791017,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70202572,"text":"ofr20191023A - 2019 - Focus areas for data acquisition for potential domestic sources of critical minerals—Rare earth elements","interactions":[],"lastModifiedDate":"2026-03-25T16:52:23.790127","indexId":"ofr20191023A","displayToPublicDate":"2022-07-14T10:30:00","publicationYear":"2019","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":"A","displayTitle":"Focus Areas for Data Acquisition for Potential Domestic Sources of Critical Minerals—Rare Earth Elements","title":"Focus areas for data acquisition for potential domestic sources of critical minerals—Rare earth elements","docAbstract":"

Rare earth elements (REEs) are critical mineral commodities for the United States. In response to a need for information on potential domestic sources of REEs in mineral deposits, the U.S. Geological Survey (USGS) identified broad focus areas throughout the conterminous United States and Alaska as a guide for selecting new geoscience research areas. This study was done to support the USGS Earth Mapping Resources Initiative (Earth MRI).

Focus areas are identified in four regions of the United States (Alaska, West, Central, and East) by mineral deposit type. The areas are described in a companion USGS data release that consists of a map in a geographic information system and accompanying tables that document the rationale for each focus area (C.L. Dicken and others, 2019, https://doi.org/10.5066/P95CHIL0). This open-file report describes the methodology that was used to identify focus areas and determine new data acquisition needs. Deposit types that are likely to be of interest for future exploration and development of domestic nonfuel REE resources include deposits associated with carbonatites and peralkaline rocks, iron oxide-apatite deposits, monazite-bearing placers, and REE-enriched phosphorites.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191023A","usgsCitation":"Hammarstrom, J.H., and Dicken, C.L., 2019, Focus areas for data acquisition for potential domestic sources of critical minerals—Rare earth elements (ver. 1.1, July 2022), chap. A 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, 11 p, https://doi.org/10.3133/ofr20191023A.","productDescription":"Report: vi, 11 p.; Data Release","numberOfPages":"21","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-104700","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":501521,"rank":10,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_108444.htm","linkFileType":{"id":5,"text":"html"}},{"id":403730,"rank":9,"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":403727,"rank":6,"type":{"id":6,"text":"Chapter"},"url":"https://doi.org/10.3133/ofr20191023B","text":"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":403468,"rank":5,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2019/1023/a/versionHist.txt","size":"2.97 KB","linkFileType":{"id":2,"text":"txt"}},{"id":361988,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P95CHIL0","text":"USGS data release","description":"USGS data release"},{"id":361987,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/fs20193007","text":"Fact Sheet 2019–3007","linkHelpText":"- The Earth Mapping Resources 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Mineral Resources Program
U.S. Geological Survey
913 National Center
12201 Sunrise Valley Drive
Reston, VA 20192
Email: Minerals@usgs.gov

","tableOfContents":"","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2019-03-14","revisedDate":"2022-07-14","noUsgsAuthors":false,"publicationDate":"2019-03-14","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":759159,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dicken, Connie L. 0000-0002-1617-8132 cdicken@usgs.gov","orcid":"https://orcid.org/0000-0002-1617-8132","contributorId":57098,"corporation":false,"usgs":true,"family":"Dicken","given":"Connie","email":"cdicken@usgs.gov","middleInitial":"L.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":759160,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70227755,"text":"70227755 - 2019 - Reproductive biology of Grey-breasted Wood-Wren (Henicorhina leucophrys): A comparative study of tropical and temperate wrens","interactions":[],"lastModifiedDate":"2022-01-28T14:52:47.32805","indexId":"70227755","displayToPublicDate":"2022-01-28T08:44:36","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3784,"text":"Wilson Journal of Ornithology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Reproductive biology of Grey-breasted Wood-Wren (Henicorhina leucophrys): A comparative study of tropical and temperate wrens","title":"Reproductive biology of Grey-breasted Wood-Wren (Henicorhina leucophrys): A comparative study of tropical and temperate wrens","docAbstract":"

We provide a detailed breeding biology account for the Grey-breasted Wood-Wren (Henicorhina leucophrys) and a comparison of the reproductive life history of tropical and temperate wrens using literature data. We conducted this study at Yacambú National Park in Venezuela from 2002 to 2008. Clutch size was 1.99 (SE 0.01) and fresh egg mass was 2.35 g (0.02). Females incubated the eggs for 19.74 d (0.37), and nestlings left nests at 17.37 d (0.18). Nest attentiveness (percent time spent on the nest) increased across the incubation period while brooding attentiveness decreased as nestlings aged. Brooding effort began with similar attentiveness as at the end of incubation. Food provisioning rate and feeding rate per nestling increased as nestlings aged. Growth rates (K) based on mass, tarsus, and wing chord were relatively slow at 0.375, 0.246, and 0.257, respectively. The nesting season extended from mid-March to late June for 7 years and the average nesting season length was 64.5 d (3.68) with a median of May 4. Nest success was 22%. Nest predation was the cause of 77% of nest failures with a total daily predation rate of 0.030 (0.002). Results obtained from the literature demonstrated that tropical wrens averaged smaller clutch sizes and longer incubation periods than relatives in the temperate region.

","language":"English","publisher":"Allen Press","doi":"10.1676/18-12","usgsCitation":"Arslan, N.S., and Martin, T.E., 2019, Reproductive biology of Grey-breasted Wood-Wren (Henicorhina leucophrys): A comparative study of tropical and temperate wrens: Wilson Journal of Ornithology, v. 131, no. 1, p. 1-11, https://doi.org/10.1676/18-12.","productDescription":"11 p.","startPage":"1","endPage":"11","ipdsId":"IP-091643","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":501024,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hdl.handle.net/11491/1636","text":"External Repository"},{"id":395046,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Venezuela","otherGeospatial":"Yacambú National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -69.88677978515625,\n 9.446352499964977\n ],\n [\n -69.46929931640624,\n 9.446352499964977\n ],\n [\n -69.46929931640624,\n 9.82138870534266\n ],\n [\n -69.88677978515625,\n 9.82138870534266\n ],\n [\n -69.88677978515625,\n 9.446352499964977\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"131","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Arslan, Necmiye Sahin","contributorId":272527,"corporation":false,"usgs":false,"family":"Arslan","given":"Necmiye","email":"","middleInitial":"Sahin","affiliations":[{"id":50219,"text":"um","active":true,"usgs":false}],"preferred":false,"id":832048,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Martin, Thomas E. 0000-0002-4028-4867 tmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-4028-4867","contributorId":1208,"corporation":false,"usgs":true,"family":"Martin","given":"Thomas","email":"tmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":832049,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70240329,"text":"70240329 - 2019 - Bighorn sheep habitat and model extrapolation across remote landscapes","interactions":[],"lastModifiedDate":"2023-02-06T15:05:41.116143","indexId":"70240329","displayToPublicDate":"2021-12-31T09:05:05","publicationYear":"2019","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Bighorn sheep habitat and model extrapolation across remote landscapes","docAbstract":"

Determining a species’ habitat use is an essential first step in any wildlife conservation action. We described habitat use, animal movements and probable lambing areas in a remote, restricted-access region of the Mojave Desert. Differences in habitat use between sexes was apparent, supporting the often-reported concept of risk-aversion by females. Animals exhibited low variability in distances travelled, although males travelled further and with more variability than females. All females demonstrated what we interpret as lambing behavior during the same 2 ½ month periods over the two years, strongly supporting our inference of lambing sites. Water appeared critical to animal long-range movements, with no animal moving beyond 8.5 km from known sources. Modeling habitat use across the landscape of concern is another necessary step for conservation of species, allowing managers to plan for and predict the outcomes of management actions. In ecology, models are often created within relatively small areas, then extrapolated across larger regions of concern. The ability to extrapolate ecological models may be especially useful across remote areas, where consistent access by wildlife managers may be highly restricted. These restrictions on access require that most data be collected remotely, necessitating the need for extrapolating models developed in other areas. We used data from GPS-collared desert bighorn sheep to describe and model habitat use across the Pintwater Range, located on the Nevada Test and Training Range of southern Nevada, a highly restricted military training ground. We tested the efficacy of habitat model extrapolation by comparing the performance of two models derived from adjacent but independent desert bighorn sheep populations. The predictive power of seasonal habitat models derived from adjacent mountain ranges was lower than those derived from the local population. However, the performance of the extrapolated model suggests it could still be a feasible alternative for estimating general habitat use.

","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Desert Bighorn Council Transactions 2019: A compilation of papers presented at the 55th meeting","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"Desert Bighorn Council Transactions 2019","conferenceDate":"April 17-19, 2019","conferenceLocation":"Mesquite, NV","language":"English","publisher":"Desert Bighorn Council","usgsCitation":"Lowrey, C., Schuster, S., Longshore, K., Cummings, P., Sprunger, A., Johnson, A., and Wilson-Henjum, G.E., 2019, Bighorn sheep habitat and model extrapolation across remote landscapes, in Desert Bighorn Council Transactions 2019: A compilation of papers presented at the 55th meeting, Mesquite, NV, April 17-19, 2019, p. 1-20.","productDescription":"20 p.","startPage":"1","endPage":"20","ipdsId":"IP-116209","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":412736,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":412735,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.desertbighorncouncil.com/transactions/download-past-dbc-transactions/"}],"country":"United States","state":"Nevada","county":"Clark County, Lincoln County, Nye County","otherGeospatial":"Nevada Test and Training Range","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -115.96047652820107,\n 37.46829180279936\n ],\n [\n -115.96047652820107,\n 36.56268736637935\n ],\n [\n -115.28108193619912,\n 36.56268736637935\n ],\n [\n -115.28108193619912,\n 37.46829180279936\n ],\n [\n -115.96047652820107,\n 37.46829180279936\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lowrey, Chris 0000-0001-5084-7275","orcid":"https://orcid.org/0000-0001-5084-7275","contributorId":216375,"corporation":false,"usgs":true,"family":"Lowrey","given":"Chris","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":863426,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schuster, Sara","contributorId":302080,"corporation":false,"usgs":false,"family":"Schuster","given":"Sara","email":"","affiliations":[{"id":65407,"text":"Center for Environmental Management of Military Lands","active":true,"usgs":false}],"preferred":false,"id":863427,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Longshore, Kathleen 0000-0001-6621-1271","orcid":"https://orcid.org/0000-0001-6621-1271","contributorId":216374,"corporation":false,"usgs":true,"family":"Longshore","given":"Kathleen","email":"","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":863428,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cummings, Patrick","contributorId":174650,"corporation":false,"usgs":false,"family":"Cummings","given":"Patrick","email":"","affiliations":[{"id":27489,"text":"Nevada Department of Wildlife","active":true,"usgs":false}],"preferred":false,"id":863429,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sprunger, Amy","contributorId":302081,"corporation":false,"usgs":false,"family":"Sprunger","given":"Amy","email":"","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":863430,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Johnson, Anna","contributorId":287611,"corporation":false,"usgs":false,"family":"Johnson","given":"Anna","email":"","affiliations":[{"id":52650,"text":"Pennsylvania Natural Heritage Program","active":true,"usgs":false}],"preferred":false,"id":863431,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wilson-Henjum, Grete Elyse 0000-0002-2284-8745","orcid":"https://orcid.org/0000-0002-2284-8745","contributorId":302082,"corporation":false,"usgs":true,"family":"Wilson-Henjum","given":"Grete","email":"","middleInitial":"Elyse","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":863432,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70201026,"text":"sir20185160 - 2019 - Assessment of undiscovered copper resources of the world, 2015","interactions":[],"lastModifiedDate":"2021-12-06T11:36:24.595906","indexId":"sir20185160","displayToPublicDate":"2021-12-03T12:50:00","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-5160","displayTitle":"Assessment of Undiscovered Copper Resources of the World, 2015","title":"Assessment of undiscovered copper resources of the world, 2015","docAbstract":"

The U.S. Geological Survey completed the first-ever global assessment of undiscovered copper resources for the two most significant sources of global copper supply: porphyry copper deposits and sediment-hosted stratabound copper deposits. The geology-based study identified 236 areas for undiscovered copper in 11 regions of the world. Estimated amounts of undiscovered copper resources are reported at different levels of probability. The results of the assessment indicate that a mean of at least 3,500 million metric tons (Mt) of undiscovered copper associated with these deposit types may exist worldwide, exceeding the 2,100 Mt of identified copper resources tabulated for these deposit types.

Porphyry copper deposits contain 1,800 Mt of identified copper resources and are estimated to contain a mean of at least 3,100 Mt of undiscovered copper resources. South America is the dominant source for both identified and undiscovered porphyry copper resources. However, several regions of Asia, including China, have significant potential for undiscovered porphyry copper resources. The amount of mean undiscovered porphyry copper resources that may be economic to extract varies as a function of likely depth to a deposit and quality of local infrastructure that could support mining.

Sediment-hosted stratabound copper deposits contain 310 Mt of identified copper resources and are estimated to contain a mean of at least 420 Mt of undiscovered copper resources. The sedimentary basins that may contain significant undiscovered copper resources are the Katanga Basin in central Africa, the Southern Permian Basin of Poland and Germany, the Chu-Sarysu Basin of Kazakhstan, and the Kodar-Udokan area of Russia. Sedimentary basins in the Northwest Botswana Rift in Botswana and Namibia, the Benguela and Cuanza Basins of Angola, and the Cambrian rocks of Egypt, Israel, and Jordan are recognized as having significant potential for undiscovered copper resources in sediment-hosted stratabound copper deposits; however, these areas require additional research, analysis, and evaluation before quantitative resource estimates can be made.

The estimate of at least 3,500 Mt of undiscovered copper in two deposit types provides a basis for long-range planning for this important commodity. U.S. copper consumption is 2 Mt per year, world consumption is about 20 Mt per year, and global production from these two deposit types is about 12 Mt per year. Total global copper production from all deposit types from 1879 to 2012 was about 600 Mt. The world’s use of mineral resources, such as copper, will continue to increase in the foreseeable future to support a growing world population and increasing standards of living. The world has sufficient copper to last for decades. However, increases in exploration and growth in mining capacity will be necessary to identify and develop undiscovered resources to supply projected demand.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185160","usgsCitation":"Hammarstrom, J.M., Zientek, M.L., Parks, H.L., Dicken, C.L., and the U.S. Geological Survey Global Copper Mineral Resource Assessment Team, 2019, Assessment of undiscovered copper resources of the world, 2015 (ver. 1.2, December 2021): U.S. Geological Survey Scientific Investigations Report 2018–5160, 619 p. (including 3 chap., 3 app., glossary, and atlas of 236 page-size pls.), https://doi.org/10.3133/sir20185160.","productDescription":"Report: xix, 619 p.; 2 Related Works; Data Release; Version History","numberOfPages":"644","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-057358","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":360066,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F70K26Q4","text":"USGS data release","description":"USGS data release","linkHelpText":"Global Mineral Resource Assessment: Summary simulation results for estimates of amounts of copper in undiscovered porphyry copper deposits"},{"id":363662,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://www.usgs.gov/energy-and-minerals/mineral-resources-program/science/global-mineral-resource-assessments?qt-science_center_objects=3#qt-science_center_objects","text":"Global Mineral Resource Assessments","linkHelpText":"- Publications"},{"id":363661,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://dx.doi.org/10.3133/sir20105090Z","text":"Scientific Investigations Report 2010-5090-Z","linkHelpText":"- Spatial Database for a Global Assessment of Undiscovered Copper Resources"},{"id":360007,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5160/coverthb5.jpg"},{"id":360008,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5160/sir20185160.pdf","text":"Report","size":"318 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5160"},{"id":364155,"rank":6,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2018/5160/versionHist.txt","size":"1.26 KB","linkFileType":{"id":2,"text":"txt"}}],"edition":"Version 1.0: May 10, 2019; Version 1.1: May 24, 2019; Version 1.2: December 3, 2021","contact":"

Mineral Resources Program
U.S. Geological Survey
913 National Center
12201 Sunrise Valley Drive
Reston, VA 20192

Contact Pubs Warehouse

","tableOfContents":"","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2019-05-10","revisedDate":"2021-12-03","noUsgsAuthors":false,"publicationDate":"2019-05-10","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":387,"text":"Mineral Resources Program","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":751894,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zientek, Michael L. 0000-0002-8522-9626","orcid":"https://orcid.org/0000-0002-8522-9626","contributorId":210763,"corporation":false,"usgs":true,"family":"Zientek","given":"Michael L.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":751895,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Parks, Heather L. 0000-0002-5917-6866 hparks@usgs.gov","orcid":"https://orcid.org/0000-0002-5917-6866","contributorId":4989,"corporation":false,"usgs":true,"family":"Parks","given":"Heather","email":"hparks@usgs.gov","middleInitial":"L.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":753297,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dicken, Connie L. 0000-0002-1617-8132 cdicken@usgs.gov","orcid":"https://orcid.org/0000-0002-1617-8132","contributorId":57098,"corporation":false,"usgs":true,"family":"Dicken","given":"Connie","email":"cdicken@usgs.gov","middleInitial":"L.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":753298,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"U.S. Geological Survey Global Copper Mineral Resource Assessment Team","contributorId":211156,"corporation":true,"usgs":false,"organization":"U.S. Geological Survey Global Copper Mineral Resource Assessment Team","id":753300,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70206078,"text":"sir20195123 - 2019 - Lithologic descriptions, geophysical logs, and source-rock geochemistry of the U.S. Geological Survey Alcova Reservoir AR–1–13 Core Hole, Natrona County, Wyoming","interactions":[],"lastModifiedDate":"2022-04-25T19:07:50.365269","indexId":"sir20195123","displayToPublicDate":"2021-11-24T10:50:00","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-5123","displayTitle":"Lithologic Descriptions, Geophysical Logs, and Source-Rock Geochemistry of the U.S. Geological Survey Alcova Reservoir AR–1–13 Core Hole, Natrona County, Wyoming","title":"Lithologic descriptions, geophysical logs, and source-rock geochemistry of the U.S. Geological Survey Alcova Reservoir AR–1–13 Core Hole, Natrona County, Wyoming","docAbstract":"

In 2013, a continuous 624-foot core hole was drilled and logged by the U.S. Geological Survey in Natrona County, Wyoming, with the goal to better understand Cretaceous source rocks in the Wind River Basin. The core hole, named the Alcova Reservoir AR–1–13, penetrated the interval extending from the upper part of the Lower Cretaceous Cloverly Formation to the lower part of the Upper Cretaceous Frontier Formation. The lithologies are predominantly mudrock, with minor amounts of sandstone and altered volcanic ash beds that were deposited in open marine, nearshore marine, and fluvial settings.

Samples were collected from open marine clay-rich, dark-colored mudrocks, and these were analyzed for total organic carbon content and by programmed pyrolysis analysis. The results show that the lower part of the Frontier Formation, Shell Creek Shale equivalent, and the Thermopolis Shale contain Type III gas-prone kerogen, with poor to fair generative source rock potential. The upper part of the Mowry Shale has good to excellent generative potential, with organic matter composed mainly of Type II oil-prone kerogen with some mixed Type II/III kerogen capable of generating oil and gas.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195123","usgsCitation":"Kirschbaum, M.A., Finn, T.M., Schenk, C.J., and Hawkins, S.J., 2019, Lithologic descriptions, geophysical logs, and source-rock geochemistry of the U.S. Geological Survey Alcova Reservoir AR–1–13 core hole, Natrona County, Wyoming (ver. 1.1, November 2021): U.S. Geological Survey Scientific Investigations Report 2019–5123, 33 p.,\nhttps://doi.org/10.3133/sir20195123.","productDescription":"Report: iii, 33 p.; 2 Data Releases","onlineOnly":"Y","ipdsId":"IP-107941","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":399605,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109579.htm"},{"id":392048,"rank":5,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2019/5123/versionHist.txt","size":"8.0 kB","linkFileType":{"id":2,"text":"txt"},"description":"SIR 2019-5123 version history"},{"id":370038,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9VLAKVG","text":"USGS data release","description":"USGS data release","linkHelpText":"Total organic carbon and pyrolysis analysis data for the U.S. Geological Survey Alcova AR–1–13 core hole, Natrona County, Wyoming"},{"id":370037,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9J7FJQU","text":"USGS data release","description":"USGS data release","linkHelpText":"LAS digital data files for the U.S. Geological Survey Alcova AR–1–13 core hole, Natrona County, Wyoming"},{"id":370019,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5123/sir20195123.pdf","text":"Report","size":"4.26 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019-5123"},{"id":370018,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5123/coverthb2.jpg"}],"country":"United States","state":"Wyoming","county":"Natrona 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1.0: December 30, 2019; Version 1.1: November 24, 2021","contact":"

Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver, CO 80225-0046

","tableOfContents":"","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"publishedDate":"2019-12-30","revisedDate":"2021-11-24","noUsgsAuthors":false,"publicationDate":"2019-12-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Kirschbaum, Mark A.","contributorId":219879,"corporation":false,"usgs":false,"family":"Kirschbaum","given":"Mark","email":"","middleInitial":"A.","affiliations":[{"id":27571,"text":"USGS volunteer","active":true,"usgs":false}],"preferred":false,"id":773497,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Finn, Thomas M. 0000-0001-6396-9351 finn@usgs.gov","orcid":"https://orcid.org/0000-0001-6396-9351","contributorId":778,"corporation":false,"usgs":true,"family":"Finn","given":"Thomas","email":"finn@usgs.gov","middleInitial":"M.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":773496,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schenk, Christopher J. 0000-0002-0248-7305 schenk@usgs.gov","orcid":"https://orcid.org/0000-0002-0248-7305","contributorId":826,"corporation":false,"usgs":true,"family":"Schenk","given":"Christopher","email":"schenk@usgs.gov","middleInitial":"J.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":773498,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hawkins, Sarah J.","contributorId":219880,"corporation":false,"usgs":false,"family":"Hawkins","given":"Sarah","email":"","middleInitial":"J.","affiliations":[{"id":24583,"text":"former USGS employee","active":true,"usgs":false}],"preferred":false,"id":773499,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70226901,"text":"70226901 - 2019 - Integration of microfacies analysis, inorganic geochemical data, and hyperspectral imaging to unravel mudstone depositional and diagenetic processes in two cores from the Triassic Shublik Formation, Northern Alaska","interactions":[],"lastModifiedDate":"2022-01-20T17:39:02.379393","indexId":"70226901","displayToPublicDate":"2021-10-16T11:32:17","publicationYear":"2019","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Integration of microfacies analysis, inorganic geochemical data, and hyperspectral imaging to unravel mudstone depositional and diagenetic processes in two cores from the Triassic Shublik Formation, Northern Alaska","docAbstract":"

The Middle – Upper Triassic Shublik Formation is an organic-rich heterogeneous carbonate-siliciclastic-phosphatic unit that generated much of the oil in the Prudhoe Bay field and other hydrocarbon accumulations in northern Alaska. A large dataset, including total organic carbon (TOC), X-ray diffraction (XRD), X-ray fluorescence (XRF) and inductively coupled plasma – mass spectrometry (ICP-MS) measurements, has been built from core and outcrop samples of the Shublik, with a focus on the organic-rich intervals. In addition, two core intervals from the Shublik were analyzed using a hyperspectral imaging system in the visible, near-infrared and shortwave-infrared range. Integration of the hyperspectral results with core descriptions, microfacies interpretations, and analytical data is being used to decipher mudstone depositional and diagenetic processes.

Petrographic analysis of Upper Triassic organic-rich intervals within the Shublik suggests that the main microfacies is a laminated bioclastic wackestone/packstone that was episodically disrupted by energetic events of variable intensity. These energetic events produced transitional and sparry calcite bioclastic packstone to grainstone intervals, depending on the depth of sediment column disturbance. By using hyperspectral imaging data from the Ikpikpuk core, individual distribution maps for minerals of interest have been generated and corroborate the microfacies interpretations. These maps also illustrate small-scale vertical changes in mineralogy. The laminated bioclastic wackestone/packstone intervals contain less calcite than the adjacent sparry bioclastic packstone to grainstone intervals. The calcite in these laminated intervals is more iron rich. This interpretation suggests that lower iron concentrations should be expected in the disrupted intervals than in nearby laminated intervals. Textural features are also enhanced in the hyperspectral images relative to visual description of the cores by combining the extraction of the average reflectance in the visible part of the electromagnetic spectrum and the depth of the main carbonate-related feature belonging to calcite. Examples noted in the enhanced imagery include low-angle features, calcite grain-size, and the size, shape and orientation of phosphatic nodules. This enhancement is being used to differentiate laminated from sparry bioclastic packstone to grainstone-rich intervals and provides a more comprehensive assessment of the microfacies than is practical by thin-section analysis.

","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"SEG global meeting abstracts","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"URTeC","doi":"10.15530/urtec-2019-445","usgsCitation":"Whidden, K.J., Birdwell, J.E., Dumoulin, J.A., Fonteneau, L.C., and Martini, B., 2019, Integration of microfacies analysis, inorganic geochemical data, and hyperspectral imaging to unravel mudstone depositional and diagenetic processes in two cores from the Triassic Shublik Formation, Northern Alaska, in SEG global meeting abstracts, p. 3213-3227, https://doi.org/10.15530/urtec-2019-445.","productDescription":"15 p.","startPage":"3213","endPage":"3227","ipdsId":"IP-107898","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":394596,"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 \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -156.8408203125,\n 68.31814602144938\n ],\n [\n -143.349609375,\n 68.31814602144938\n ],\n [\n -143.349609375,\n 71.93815765811694\n ],\n [\n -156.8408203125,\n 71.93815765811694\n ],\n [\n -156.8408203125,\n 68.31814602144938\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Whidden, Katherine J. 0000-0002-7841-2553 kwhidden@usgs.gov","orcid":"https://orcid.org/0000-0002-7841-2553","contributorId":3960,"corporation":false,"usgs":true,"family":"Whidden","given":"Katherine","email":"kwhidden@usgs.gov","middleInitial":"J.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":828725,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Birdwell, Justin E. 0000-0001-8263-1452 jbirdwell@usgs.gov","orcid":"https://orcid.org/0000-0001-8263-1452","contributorId":3302,"corporation":false,"usgs":true,"family":"Birdwell","given":"Justin","email":"jbirdwell@usgs.gov","middleInitial":"E.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":828726,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dumoulin, Julie A. 0000-0003-1754-1287 dumoulin@usgs.gov","orcid":"https://orcid.org/0000-0003-1754-1287","contributorId":203209,"corporation":false,"usgs":true,"family":"Dumoulin","given":"Julie","email":"dumoulin@usgs.gov","middleInitial":"A.","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":828727,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fonteneau, Lionel C.","contributorId":271764,"corporation":false,"usgs":false,"family":"Fonteneau","given":"Lionel","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":828728,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Martini, Brigette","contributorId":225059,"corporation":false,"usgs":false,"family":"Martini","given":"Brigette","email":"","affiliations":[{"id":41030,"text":"North Shore Consulting","active":true,"usgs":false}],"preferred":false,"id":828729,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70223407,"text":"70223407 - 2019 - Movement dynamics of smallmouth bass (Micropterus dolomieu) in a large river-tributary system","interactions":[],"lastModifiedDate":"2021-08-26T16:41:18.516743","indexId":"70223407","displayToPublicDate":"2021-08-26T09:55:59","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1659,"text":"Fisheries Management and Ecology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Movement dynamics of smallmouth bass (Micropterus dolomieu) in a large river-tributary system","title":"Movement dynamics of smallmouth bass (Micropterus dolomieu) in a large river-tributary system","docAbstract":"

Smallmouth bass, Micropterus dolomieu Lacepède, movement dynamics were investigated in a connected mainstem river-tributary system. Smallmouth bass moved large distances annually (n = 84 fish, average = 24.6 ± 25.9 km, range = 0.03 to 118 km) and had three peak movement periods (pre-spawn, post-spawn and overwintering). Movement into and out of tributaries was common, but the movement between mainstem river and tributary habitats varied among tagging locations and season. In general, a large proportion of fish that were tagged in tributaries moved out of the tributaries after spawning (22/30 fish). Because of the importance of fish movement patterns on population dynamics, the observed individual variability in movement, quantified using a hierarchical model, and the potential for long-distance movements are important considerations for smallmouth bass conservation and management. In addition, mainstem river-tributary connectivity appears to play an important role for smallmouth bass during key life history events.

","language":"English","publisher":"Wiley","doi":"10.1111/fme.12369","usgsCitation":"Wagner, T., Schall, M., Timothy Wertz, Smith, G., and Blazer, V., 2019, Movement dynamics of smallmouth bass (Micropterus dolomieu) in a large river-tributary system: Fisheries Management and Ecology, v. 26, no. 6, p. 590-599, https://doi.org/10.1111/fme.12369.","productDescription":"10 p.","startPage":"590","endPage":"599","ipdsId":"IP-102962","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":388544,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Pennsylvania","otherGeospatial":"West Branch Susquehanna River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -78.5302734375,\n 40.8034148344062\n ],\n [\n -76.190185546875,\n 40.8034148344062\n ],\n [\n -76.190185546875,\n 41.638025739250786\n ],\n [\n -78.5302734375,\n 41.638025739250786\n ],\n [\n -78.5302734375,\n 40.8034148344062\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"26","issue":"6","noUsgsAuthors":false,"publicationDate":"2019-06-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Wagner, Tyler 0000-0003-1726-016X twagner@usgs.gov","orcid":"https://orcid.org/0000-0003-1726-016X","contributorId":1050,"corporation":false,"usgs":true,"family":"Wagner","given":"Tyler","email":"twagner@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":821968,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schall, Megan K.","contributorId":264767,"corporation":false,"usgs":false,"family":"Schall","given":"Megan K.","affiliations":[{"id":36985,"text":"Penn State University","active":true,"usgs":false}],"preferred":false,"id":821969,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Timothy Wertz","contributorId":264768,"corporation":false,"usgs":false,"family":"Timothy Wertz","affiliations":[{"id":54545,"text":"PA Department of Environmental Protection","active":true,"usgs":false}],"preferred":false,"id":821970,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, Geoffrey D.","contributorId":264769,"corporation":false,"usgs":false,"family":"Smith","given":"Geoffrey D.","affiliations":[{"id":54546,"text":"PA Fish and Boat Commission","active":true,"usgs":false}],"preferred":false,"id":821971,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Blazer, Vicki S. 0000-0001-6647-9614 vblazer@usgs.gov","orcid":"https://orcid.org/0000-0001-6647-9614","contributorId":150384,"corporation":false,"usgs":true,"family":"Blazer","given":"Vicki S.","email":"vblazer@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":821972,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70223194,"text":"70223194 - 2019 - Evaluation of an elk detection probability model in the Black Hills, South Dakota","interactions":[],"lastModifiedDate":"2021-08-17T12:36:09.959393","indexId":"70223194","displayToPublicDate":"2021-08-17T07:31:29","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":996,"text":"BioOne","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of an elk detection probability model in the Black Hills, South Dakota","docAbstract":"

Since 1993, elk (Cervus canadensis nelsoni) abundance in the Black Hills of South Dakota has been estimated using a detection probability model previously developed in Idaho, though it is likely biased because of a failure to account for visibility biases under local conditions. To correct for this bias, we evaluated the current detection probability across the Black Hills during January and February 2009–2011 using radio-collared elk. We used logistic regression to evaluate topographic features, habitat characteristics, and group characteristics relative to their influence on detection probability of elk. Elk detection probability increased with less vegetation cover (%), increased group size, and more snow cover (%); overall detection probability was 0.60 (95% CI 0.52–0.68), with 91 of 152 elk groups detected. Predictive capability of the selected model was excellent (ROC = 0.807), and prediction accuracy ranged from 70.2% to 73.7%. Cross-validation of the selected model with other population estimation methods resulted in comparable estimates. Future applications of our model should be applied cautiously if characteristics of the area (e.g., vegetation cover >50%, snow cover >90%, group sizes >16 elk) differ notably from the range of variability in these factors under which the model was developed.

","language":"English","publisher":"BioOne","doi":"10.3398/064.079.0408","usgsCitation":"Phillips, E.C., Lehman, C.P., Klaver, R.W., Jarding, A.R., Rupp, S., Jenks, J., and Jacques, C., 2019, Evaluation of an elk detection probability model in the Black Hills, South Dakota: BioOne, v. 79, no. 4, p. 551-565, https://doi.org/10.3398/064.079.0408.","productDescription":"15 p.","startPage":"551","endPage":"565","ipdsId":"IP-100658","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":467310,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://lib.dr.iastate.edu/cgi/viewcontent.cgi?article=1346&context=nrem_pubs","text":"External Repository"},{"id":387979,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"South Dakota","otherGeospatial":"Black Hills","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -104.073486328125,\n 43.34914966389313\n ],\n [\n -102.843017578125,\n 43.34914966389313\n ],\n [\n -102.843017578125,\n 44.56699093657141\n ],\n [\n -104.073486328125,\n 44.56699093657141\n ],\n [\n -104.073486328125,\n 43.34914966389313\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"79","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Phillips, Evan C.","contributorId":264318,"corporation":false,"usgs":false,"family":"Phillips","given":"Evan","email":"","middleInitial":"C.","affiliations":[{"id":5089,"text":"South Dakota State University","active":true,"usgs":false}],"preferred":false,"id":821358,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lehman, Chadwick P.","contributorId":264321,"corporation":false,"usgs":false,"family":"Lehman","given":"Chadwick","email":"","middleInitial":"P.","affiliations":[{"id":54439,"text":"South Dakota Parks, Fish and Wildlife","active":true,"usgs":false}],"preferred":false,"id":821338,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Klaver, Robert W. 0000-0002-3263-9701 bklaver@usgs.gov","orcid":"https://orcid.org/0000-0002-3263-9701","contributorId":3285,"corporation":false,"usgs":true,"family":"Klaver","given":"Robert","email":"bklaver@usgs.gov","middleInitial":"W.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":821334,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jarding, Angela R.","contributorId":264319,"corporation":false,"usgs":false,"family":"Jarding","given":"Angela","email":"","middleInitial":"R.","affiliations":[{"id":5089,"text":"South Dakota State University","active":true,"usgs":false}],"preferred":false,"id":821336,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rupp, Susan P.","contributorId":264320,"corporation":false,"usgs":false,"family":"Rupp","given":"Susan P.","affiliations":[{"id":5089,"text":"South Dakota State University","active":true,"usgs":false}],"preferred":false,"id":821337,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jenks, Jonathan A.","contributorId":264322,"corporation":false,"usgs":false,"family":"Jenks","given":"Jonathan A.","affiliations":[{"id":5089,"text":"South Dakota State University","active":true,"usgs":false}],"preferred":false,"id":821339,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jacques, Christopher N.","contributorId":264323,"corporation":false,"usgs":false,"family":"Jacques","given":"Christopher N.","affiliations":[{"id":49637,"text":"Western Illinois University","active":true,"usgs":false}],"preferred":false,"id":821340,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70223295,"text":"70223295 - 2019 - Black Scoter habitat use along the southeastern coast of the United States","interactions":[],"lastModifiedDate":"2021-08-20T13:58:08.354245","indexId":"70223295","displayToPublicDate":"2021-07-27T08:54:17","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Black Scoter habitat use along the southeastern coast of the United States","docAbstract":"

While the Atlantic Coast of the United States and Canada is a major wintering area for sea ducks, knowledge about their wintering habitat use is relatively limited. Black Scoters have a broad wintering distribution and are the only open water species of sea duck that is abundant along the southeastern coast of the United States. Our study identified variables that affected Black Scoter (Melanitta americana) distribution and abundance in the Atlantic Ocean along the southeastern coast of the United States. We used aerial survey data from 2009 to 2012 provided by the United States Fish and Wildlife Service to identify variables that influenced Black Scoter distribution. We used indicator variable selection to evaluate relationships between Black Scoter habitat use and a variety of broad- and fine-scale oceanographic and weather variables. Average time between waves, ocean floor slope, and the interaction of bathymetry and distance to shore had the strongest association with southeastern Black Scoter distribution.

","language":"English","publisher":"Wiley","doi":"10.1002/ece3.7746","usgsCitation":"Plumpton, H.M., Silverman, E.D., and Ross, B., 2019, Black Scoter habitat use along the southeastern coast of the United States: Ecology and Evolution, v. 11, no. 16, p. 10813-10820, https://doi.org/10.1002/ece3.7746.","productDescription":"8 p.","startPage":"10813","endPage":"10820","ipdsId":"IP-101478","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":458815,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/ece3.7746","text":"External Repository"},{"id":388231,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida, Georgia, North Carolina, South Carolina, Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.38671875,\n 30.031055426540206\n ],\n [\n -80.68359375,\n 31.55981453201843\n ],\n [\n -78.46435546875,\n 33.32134852669881\n ],\n [\n -76.7724609375,\n 34.542762387234845\n ],\n [\n -75.56396484375,\n 35.11990857099681\n ],\n [\n -75.38818359375,\n 36.421282443649496\n ],\n [\n -76.00341796875,\n 36.96744946416934\n ],\n [\n -76.4208984375,\n 36.54494944148322\n ],\n [\n -76.48681640625,\n 35.62158189955968\n ],\n [\n -77.34374999999999,\n 35.0120020431607\n ],\n [\n -79.27734374999999,\n 33.88865750124075\n ],\n [\n -80.88134765625,\n 32.65787573695528\n ],\n [\n -81.84814453125,\n 31.70947636001935\n ],\n [\n -82.001953125,\n 30.334953881988564\n ],\n [\n -81.76025390625,\n 29.783449456820605\n ],\n [\n -81.38671875,\n 30.031055426540206\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","issue":"16","noUsgsAuthors":false,"publicationDate":"2021-07-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Plumpton, H. M.","contributorId":264502,"corporation":false,"usgs":false,"family":"Plumpton","given":"H.","email":"","middleInitial":"M.","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":821633,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Silverman, E. D.","contributorId":264525,"corporation":false,"usgs":false,"family":"Silverman","given":"E.","email":"","middleInitial":"D.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":821634,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ross, Beth 0000-0001-5634-4951 bross@usgs.gov","orcid":"https://orcid.org/0000-0001-5634-4951","contributorId":199242,"corporation":false,"usgs":true,"family":"Ross","given":"Beth","email":"bross@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":821635,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70223382,"text":"70223382 - 2019 - Spatial ecology of urban striped skunks (Mephitis mephitis) in the Northern Great Plains: A framework for future oral rabies vaccination programs","interactions":[],"lastModifiedDate":"2021-08-25T12:54:43.843845","indexId":"70223382","displayToPublicDate":"2021-03-22T07:51:34","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3669,"text":"Urban Ecosystems","active":true,"publicationSubtype":{"id":10}},"title":"Spatial ecology of urban striped skunks (Mephitis mephitis) in the Northern Great Plains: A framework for future oral rabies vaccination programs","docAbstract":"

Few studies have investigated the ecology of urban striped skunks (Mephitis mephitis) despite their role as a primary rabies vector species paired with an ability to thrive in these landscapes. Information on home range, nightly movements, and habitat selection, is important for rabies management planning regarding the placement of oral rabies vaccine (ORV) baits and for management of skunk populations more generally. Our aim was to obtain baseline ecological information with an emphasis on spatial ecology of urban striped skunks in the Northern Great Plains region that is lacking in the literature. We used radio telemetry to track 22 (4 M, 18 F) skunks during September 2016 to November 2016 and March 2017 to November 2017. Size of home range using kernel density estimation with smoothing by least squares cross validation identified that male skunks (x¯\">

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Wildland fire characteristics, such as area burned, number of large fires, burn intensity, and fire season duration, have increased steadily over the past 30 years, resulting in substantial increases in the costs of suppressing fires and managing damages from wildland fire events (National Academies of Sciences, Engineering, and Medicine, 2017). Wildland fire management could benefit from sound decision making based on reliable scientific information. Fire scientists produce data, tools, and information to support fire and land management decision making. With ever-changing land use scenarios, environmental conditions, and emerging technological capabilities, new assessments and studies are continually needed. Established by Congress in 1879, the U.S. Geological Survey (USGS) is the primary science branch of the Department of the Interior (DOI), which manages more than 400 million acres of public lands in the United States. The USGS has more than 100 scientists across seven Mission Areas that help address the wildland fire science needs of DOI bureaus and their stakeholders. The diverse expertise of these scientists allows them to address complex interdisciplinary challenges. In this report, we identify and characterize scientific literature produced by USGS scientists during 2006–17 that addresses topics associated with wildland fire science. Our goals were to (1) make the most complete list possible of product citations readily available in an organized format, and (2) use bibliometric analysis approaches to highlight the productivity of USGS scientists and the impact of contributions that the Bureau has provided to the scientific, land management, and fire management communities.

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Associate Director
Ecosystems Mission Area
U.S. Geological Survey
Mail Stop 300
12201 Sunrise Valley Drive
Reston, VA 20192

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Wildland Fire Science Program
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12201 Sunrise Valley Drive
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Wildland Fire Science Program
U.S Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192

","tableOfContents":"","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2019-04-23","revisedDate":"2023-02-14","noUsgsAuthors":false,"publicationDate":"2019-04-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Steblein, Paul F. 0000-0001-7856-5106","orcid":"https://orcid.org/0000-0001-7856-5106","contributorId":213237,"corporation":false,"usgs":true,"family":"Steblein","given":"Paul","email":"","middleInitial":"F.","affiliations":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"preferred":true,"id":761219,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Miller, Mark P. 0000-0003-1045-1772 mpmiller@usgs.gov","orcid":"https://orcid.org/0000-0003-1045-1772","contributorId":1967,"corporation":false,"usgs":true,"family":"Miller","given":"Mark","email":"mpmiller@usgs.gov","middleInitial":"P.","affiliations":[{"id":38131,"text":"WMA - Office of Planning and Programming","active":true,"usgs":true}],"preferred":true,"id":761218,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Soileau, Suzanna C. 0000-0002-4331-0098","orcid":"https://orcid.org/0000-0002-4331-0098","contributorId":204690,"corporation":false,"usgs":true,"family":"Soileau","given":"Suzanna C.","affiliations":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"preferred":true,"id":761220,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70204151,"text":"tm4A12 - 2019 - Regionalization of surface-water statistics using multiple linear regression","interactions":[],"lastModifiedDate":"2021-02-19T12:50:53.020266","indexId":"tm4A12","displayToPublicDate":"2021-02-18T15:40:00","publicationYear":"2019","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-A12","displayTitle":"Regionalization of Surface-Water Statistics Using Multiple Linear Regression","title":"Regionalization of surface-water statistics using multiple linear regression","docAbstract":"This report serves as a reference document in support of the regionalization of surface-water statistics using multiple linear regression. Streamflow statistics are quantitative characterizations of hydrology and are often derived from observed streamflow records. In the absence of observed streamflow records, as at unmonitored or ungaged locations, other techniques are required. Multiple linear regression is one tool that is widely used to regionalize or transfer information from gaged to ungaged locations. This report provides the background to support regression-based regionalization of streamflow statistics. This background includes tools for data assembly, exploratory data analysis, model estimation in a least-squares framework, and model evaluation.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm4A12","usgsCitation":"Farmer, W.H., Kiang, J.E., Feaster, T.D., and Eng, K., 2019, Regionalization of surface-water statistics using multiple linear regression (ver. 1.1, February 2021): U.S. Geological Survey Techniques and Methods, book 4, chap. A12, 40 p., https://doi.org/10.3133/tm4A12.","productDescription":"Report: v, 40 p.; Data Release; Version History","onlineOnly":"Y","ipdsId":"IP-081278","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":366986,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/04/a12/coverthb2.jpg"},{"id":366987,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/04/a12/tm4a12.pdf","text":"Report","size":"1.58 MB","linkFileType":{"id":1,"text":"pdf"},"description":"T and M 4-A12"},{"id":366988,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9T5ZEXV","text":"USGS Data Release","linkHelpText":"An example dataset for exploration of multiple linear regression"},{"id":383290,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/tm/04/a12/versionHist.txt","text":"version history","size":"4.0 kB","linkFileType":{"id":2,"text":"txt"},"description":"T and M 4-A12 version history"}],"edition":"Version 1.0: August 29, 2019; Version 1.1: February 18, 2021","contact":"

Director, Integrated Modeling and Prediction Division
Water Mission Area
U.S. Geological Survey
MS 415
12201 Sunrise Valley Drive
Reston, VA 20192

","tableOfContents":"","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"publishedDate":"2019-08-29","revisedDate":"2021-02-18","noUsgsAuthors":false,"publicationDate":"2019-08-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Farmer, William H. 0000-0002-2865-2196 wfarmer@usgs.gov","orcid":"https://orcid.org/0000-0002-2865-2196","contributorId":4374,"corporation":false,"usgs":true,"family":"Farmer","given":"William","email":"wfarmer@usgs.gov","middleInitial":"H.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":765739,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kiang, Julie E. 0000-0003-0653-4225 jkiang@usgs.gov","orcid":"https://orcid.org/0000-0003-0653-4225","contributorId":2179,"corporation":false,"usgs":true,"family":"Kiang","given":"Julie","email":"jkiang@usgs.gov","middleInitial":"E.","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":765740,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Feaster, Toby D. 0000-0002-5626-5011","orcid":"https://orcid.org/0000-0002-5626-5011","contributorId":205647,"corporation":false,"usgs":true,"family":"Feaster","given":"Toby","email":"","middleInitial":"D.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":765741,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Eng, Ken 0000-0001-6838-5849 keng@usgs.gov","orcid":"https://orcid.org/0000-0001-6838-5849","contributorId":3580,"corporation":false,"usgs":true,"family":"Eng","given":"Ken","email":"keng@usgs.gov","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":765742,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70216052,"text":"70216052 - 2019 - DTSGUI: A python program to process and visualize fiber‐optic distributed temperature sensing data","interactions":[],"lastModifiedDate":"2020-11-04T12:34:01.107674","indexId":"70216052","displayToPublicDate":"2020-12-15T06:30:17","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3825,"text":"Groundwater","active":true,"publicationSubtype":{"id":10}},"title":"DTSGUI: A python program to process and visualize fiber‐optic distributed temperature sensing data","docAbstract":"

Fiber‐optic distributed temperature sensing (FO‐DTS) has proven to be a transformative technology for the hydrologic sciences, with application to diverse problems including hyporheic exchange, groundwater/surface‐water interaction, fractured‐rock characterization, and cold regions hydrology. FO‐DTS produces large, complex, and information‐rich datasets. Despite the potential of FO‐DTS, adoption of the technology has been impeded by lack of tools for data processing, analysis, and visualization. New tools are needed to efficiently and fully capitalize on the information content of FO‐DTS datasets. To this end, we present DTSGUI, a public‐domain Python‐based software package for editing, parsing, processing, statistical analysis, georeferencing, and visualization of FO‐DTS data.

","language":"English","publisher":"National Groundwater Association","doi":"10.1111/gwat.12974","usgsCitation":"Domanski, M.M., Quinn, D., Day-Lewis, F.D., Briggs, M.A., Werkema, D.D., and Lane, J., 2019, DTSGUI: A python program to process and visualize fiber‐optic distributed temperature sensing data: Groundwater, v. 58, no. 5, p. 799-804, https://doi.org/10.1111/gwat.12974.","productDescription":"6 p.","startPage":"799","endPage":"804","ipdsId":"IP-112500","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":458818,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/7814658","text":"External Repository"},{"id":380115,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"58","issue":"5","noUsgsAuthors":false,"publicationDate":"2020-01-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Domanski, Marian M. 0000-0002-0468-314X mdomanski@usgs.gov","orcid":"https://orcid.org/0000-0002-0468-314X","contributorId":5035,"corporation":false,"usgs":true,"family":"Domanski","given":"Marian","email":"mdomanski@usgs.gov","middleInitial":"M.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":803881,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Quinn, Daven","contributorId":244360,"corporation":false,"usgs":false,"family":"Quinn","given":"Daven","email":"","affiliations":[{"id":48903,"text":"University of Wisconsin–Madison, Department of Geoscience","active":true,"usgs":false}],"preferred":false,"id":803882,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Day-Lewis, Frederick D. 0000-0003-3526-886X daylewis@usgs.gov","orcid":"https://orcid.org/0000-0003-3526-886X","contributorId":1672,"corporation":false,"usgs":true,"family":"Day-Lewis","given":"Frederick","email":"daylewis@usgs.gov","middleInitial":"D.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true}],"preferred":true,"id":803949,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Briggs, Martin A. 0000-0003-3206-4132 mbriggs@usgs.gov","orcid":"https://orcid.org/0000-0003-3206-4132","contributorId":4114,"corporation":false,"usgs":true,"family":"Briggs","given":"Martin","email":"mbriggs@usgs.gov","middleInitial":"A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true},{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true}],"preferred":true,"id":803883,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Werkema, Dale D.","contributorId":40488,"corporation":false,"usgs":false,"family":"Werkema","given":"Dale","email":"","middleInitial":"D.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":803885,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lane, John W. Jr. 0000-0002-3558-243X","orcid":"https://orcid.org/0000-0002-3558-243X","contributorId":210076,"corporation":false,"usgs":true,"family":"Lane","given":"John W.","suffix":"Jr.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true},{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true}],"preferred":true,"id":803886,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70216769,"text":"70216769 - 2019 - Remobilization of old permafrost carbon to Chukchi Sea sediments during the end of the last deglaciation","interactions":[],"lastModifiedDate":"2020-12-04T21:47:23.446633","indexId":"70216769","displayToPublicDate":"2020-12-13T15:42:37","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1836,"text":"Global Biogeochemical Cycles","active":true,"publicationSubtype":{"id":10}},"title":"Remobilization of old permafrost carbon to Chukchi Sea sediments during the end of the last deglaciation","docAbstract":"

Climate warming is expected to destabilize permafrost carbon (PF‐C) by thaw‐erosion and deepening of the seasonally thawed active layer and thereby promote PF‐C mineralization to CO2 and CH4. A similar PF‐C remobilization might have contributed to the increase in atmospheric CO2 during deglacial warming after the last glacial maximum. Using carbon isotopes and terrestrial biomarkers (Δ14C, δ13C, and lignin phenols), this study quantifies deposition of terrestrial carbon originating from permafrost in sediments from the Chukchi Sea (core SWERUS‐L2‐4‐PC1). The sediment core reconstructs remobilization of permafrost carbon during the late Allerød warm period starting at 13,000 cal years before present (BP), the Younger Dryas, and the early Holocene warming until 11,000 cal years BP and compares this period with the late Holocene, from 3,650 years BP until present. Dual‐carbon‐isotope‐based source apportionment demonstrates that Ice Complex Deposit—ice‐ and carbon‐rich permafrost from the late Pleistocene (also referred to as Yedoma)—was the dominant source of organic carbon (66 ± 8%; mean ± standard deviation) to sediments during the end of the deglaciation, with fluxes more than twice as high (8.0 ± 4.6 g·m−2·year−1) as in the late Holocene (3.1 ± 1.0 g·m−2·year−1). These results are consistent with late deglacial PF‐C remobilization observed in a Laptev Sea record, yet in contrast with PF‐C sources, which at that location were dominated by active layer material from the Lena River watershed. Release of dormant PF‐C from erosion of coastal permafrost during the end of the last deglaciation indicates vulnerability of Ice Complex Deposit in response to future warming and sea level changes.

","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2018GB005969","collaboration":"University of Stockholm","usgsCitation":"Martens, J., Wild, B., Pearce, C., Tesi, T., Andersson, A., Broder, L., O’Regan, M., Jakobsson, M., Skold, M., Gemery, L., and Cronin, T.M., 2019, Remobilization of old permafrost carbon to Chukchi Sea sediments during the end of the last deglaciation: Global Biogeochemical Cycles, v. 33, no. 12, p. 210-14, https://doi.org/10.1029/2018GB005969.","productDescription":"13 p.","startPage":"210","endPage":"14","ipdsId":"IP-098952","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":458820,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2018gb005969","text":"Publisher Index Page"},{"id":381002,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Arctic Shelf","volume":"33","issue":"12","noUsgsAuthors":false,"publicationDate":"2019-01-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Martens, Jannik","contributorId":245407,"corporation":false,"usgs":false,"family":"Martens","given":"Jannik","email":"","affiliations":[{"id":49187,"text":"1Department of Environmental Science and Analytical Chemistry (ACES), Stockholm University, Sweden","active":true,"usgs":false}],"preferred":false,"id":806147,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wild, Birgit","contributorId":245408,"corporation":false,"usgs":false,"family":"Wild","given":"Birgit","email":"","affiliations":[{"id":49187,"text":"1Department of Environmental Science and Analytical Chemistry (ACES), Stockholm University, Sweden","active":true,"usgs":false}],"preferred":false,"id":806148,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pearce, Christof","contributorId":197126,"corporation":false,"usgs":false,"family":"Pearce","given":"Christof","email":"","affiliations":[{"id":25421,"text":"Department of Geological Sciences, Stockholm University, Sweden","active":true,"usgs":false}],"preferred":false,"id":806149,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tesi, Tommaso","contributorId":245409,"corporation":false,"usgs":false,"family":"Tesi","given":"Tommaso","affiliations":[{"id":49187,"text":"1Department of Environmental Science and Analytical Chemistry (ACES), Stockholm University, Sweden","active":true,"usgs":false}],"preferred":false,"id":806150,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Andersson, August","contributorId":245410,"corporation":false,"usgs":false,"family":"Andersson","given":"August","email":"","affiliations":[{"id":49187,"text":"1Department of Environmental Science and Analytical Chemistry (ACES), Stockholm University, Sweden","active":true,"usgs":false}],"preferred":false,"id":806151,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Broder, Lisa","contributorId":245411,"corporation":false,"usgs":false,"family":"Broder","given":"Lisa","email":"","affiliations":[{"id":49187,"text":"1Department of Environmental Science and Analytical Chemistry (ACES), Stockholm University, Sweden","active":true,"usgs":false}],"preferred":false,"id":806152,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"O’Regan, Matt","contributorId":197135,"corporation":false,"usgs":false,"family":"O’Regan","given":"Matt","email":"","affiliations":[{"id":25421,"text":"Department of Geological Sciences, Stockholm University, Sweden","active":true,"usgs":false}],"preferred":false,"id":806153,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Jakobsson, Martin","contributorId":166854,"corporation":false,"usgs":false,"family":"Jakobsson","given":"Martin","email":"","affiliations":[{"id":24562,"text":"Stockholm University","active":true,"usgs":false}],"preferred":false,"id":806154,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Skold, Martin","contributorId":245412,"corporation":false,"usgs":false,"family":"Skold","given":"Martin","email":"","affiliations":[{"id":49188,"text":"7Department of Mathematics, Stockholm University, Sweden","active":true,"usgs":false}],"preferred":false,"id":806155,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Gemery, Laura 0000-0003-1966-8732","orcid":"https://orcid.org/0000-0003-1966-8732","contributorId":245413,"corporation":false,"usgs":true,"family":"Gemery","given":"Laura","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":806156,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Cronin, Thomas M. 0000-0002-2643-0979 tcronin@usgs.gov","orcid":"https://orcid.org/0000-0002-2643-0979","contributorId":2579,"corporation":false,"usgs":true,"family":"Cronin","given":"Thomas","email":"tcronin@usgs.gov","middleInitial":"M.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":806157,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70205087,"text":"sir20195094 - 2019 - Development of regression equations for the estimation of flood flows at ungaged streams in Pennsylvania","interactions":[{"subject":{"id":85811,"text":"sir20085102 - 2008 - Regression Equations for Estimating Flood Flows at Selected Recurrence Intervals for Ungaged Streams in Pennsylvania","indexId":"sir20085102","publicationYear":"2008","noYear":false,"title":"Regression Equations for Estimating Flood Flows at Selected Recurrence Intervals for Ungaged Streams in Pennsylvania"},"predicate":"SUPERSEDED_BY","object":{"id":70205087,"text":"sir20195094 - 2019 - Development of regression equations for the estimation of flood flows at ungaged streams in Pennsylvania","indexId":"sir20195094","publicationYear":"2019","noYear":false,"title":"Development of regression equations for the estimation of flood flows at ungaged streams in Pennsylvania"},"id":1}],"lastModifiedDate":"2020-12-09T12:44:17.28198","indexId":"sir20195094","displayToPublicDate":"2020-12-08T10:55:00","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-5094","displayTitle":"Development of Regression Equations for the Estimation of Flood Flows at Ungaged Streams in Pennsylvania","title":"Development of regression equations for the estimation of flood flows at ungaged streams in Pennsylvania","docAbstract":"

Regression equations, which may be used to estimate flood flows at select annual exceedance probabilities, were developed for ungaged streams in Pennsylvania. The equations were developed using annual peak flow data through water year 2015 and basin characteristics for 285 streamflow gaging stations across Pennsylvania and surrounding states. The streamgages included active and discontinued continuous-record stations, as well as crest-stage partial-record stations, and required a minimum of 10 years of annual peak streamflow data for inclusion in the study. Explanatory variables significant at the 95-percent confidence level for one or more regression equations included the following basin characteristics: drainage area, maximum basin elevation, mean basin slope, percent storage, and the percentage of carbonate bedrock within a basin. The State was divided into five regions, and regional regression equations were developed to estimate flood flows associated with the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities (which correspond to the 2-, 5-, 10-, 25-, 50-, 100-, 200-, and 500-year recurrence intervals, respectively). Although the regression equations can be used to estimate the magnitude of flood flows for most streams in the State, they are not valid for streams with drainage areas generally greater than 1,500 square miles or with substantial regulation, diversion, or mining activity within the basin. The regional regression equations will be incorporated into the U.S. Geological Survey StreamStats application (https://water.usgs.gov/osw/streamstats/).

Additionally, annual peak flow data for 356 streamgages initially considered for inclusion in the analysis for development of updated flood-flow regression equations were analyzed for the existence of trends; estimates of flood-flow magnitude and frequency were also computed for these streamgages. Estimates of flood-flow magnitude and frequency for streamgages substantially affected by upstream regulation are also presented.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195094","collaboration":"Prepared in cooperation with the Federal Emergency Management Agency and the Pennsylvania Department of Transportation","usgsCitation":"Roland, M.A., and Stuckey, M.H., 2020, Development of regression equations for the estimation of flood flows at ungaged streams in Pennsylvania (ver. 1.1, December 2020): U.S. Geological Survey Scientific Investigations Report 2019–5094, 36 p., https://doi.org/10.3133/sir20195094. [Supersedes USGS Scientific Investigations Report 2008–5102]","productDescription":"Report: vi, 36 p.; Appendices 1-3; Data Release","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-104380","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":437232,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9YHIU6G","text":"USGS data release","linkHelpText":"Data in support of Development of Regression Equations for the Estimation of Flood Flows at Ungaged Streams in Pennsylvania"},{"id":381091,"rank":7,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2019/5094/versionHist.txt","size":"1.09 KB","linkFileType":{"id":2,"text":"txt"}},{"id":368468,"rank":6,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5094/sir20195094.pdf","text":"Report","size":"15.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019-5094"},{"id":368467,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2019/5094/sir20195094_appendix3.xlsx","text":"Appendix 3","size":"40.1 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2019-5094","linkHelpText":"- Magnitude, variance, and confidence intervals of annual exceedance probability floods for select streamgages in Pennsylvania substantially affected by upstream regulation"},{"id":368466,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2019/5094/sir20195094_appendix2.xlsx","text":"Appendix 2","size":"389 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2019-5094","linkHelpText":"- Magnitude, variance, and confidence intervals of annual exceedance probability floods for select unregulated streamgages in Pennsylvania and surrounding states"},{"id":368462,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://www.sciencebase.gov/catalog/item/5c1aa7a4e4b0708288c5b35c","text":"USGS data release","linkHelpText":"Data in support of development of regression equations for the estimation of flood flows at ungaged streams in Pennsylvania"},{"id":368465,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2019/5094/sir20195094_appendix1.xlsx","text":"Appendix 1","size":"81.4 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2019-5094","linkHelpText":"- Unregulated streamgages considered for the development of updated flood-flow regression equations for Pennsylvania streams"},{"id":368463,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5094/coverthb2.jpg"}],"country":"United 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\"}}]}","edition":"Version 1.0: October 2019; Version 1.1: December 2020","publicComments":"Scientific Investigations Report 2019-5094 supersedes Scientific Investigations Report 2008–5102.","contact":"

Director, Pennsylvania Water Science Center
U.S. Geological Survey
215 Limekiln Road
New Cumberland, PA 17070

","tableOfContents":"","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"publishedDate":"2019-10-28","revisedDate":"2020-12-08","noUsgsAuthors":false,"publicationDate":"2019-10-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Roland, Mark A. 0000-0002-0268-6507 mroland@usgs.gov","orcid":"https://orcid.org/0000-0002-0268-6507","contributorId":2116,"corporation":false,"usgs":true,"family":"Roland","given":"Mark","email":"mroland@usgs.gov","middleInitial":"A.","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":769945,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stuckey, Marla H. 0000-0002-5211-8444 mstuckey@usgs.gov","orcid":"https://orcid.org/0000-0002-5211-8444","contributorId":1734,"corporation":false,"usgs":true,"family":"Stuckey","given":"Marla","email":"mstuckey@usgs.gov","middleInitial":"H.","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":769946,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70215781,"text":"70215781 - 2019 - Try, try again: Lessons learned from success and failure in participatory modeling","interactions":[],"lastModifiedDate":"2020-10-30T14:52:05.595016","indexId":"70215781","displayToPublicDate":"2020-10-29T09:35:41","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3888,"text":"Elementa: Science of the Anthropocene","active":true,"publicationSubtype":{"id":10}},"title":"Try, try again: Lessons learned from success and failure in participatory modeling","docAbstract":"

Participatory Modeling (PM) is becoming increasingly common in environmental planning and conservation, due in part to advances in cyberinfrastructure as well as to greater recognition of the importance of engaging a diverse array of stakeholders in decision making. We provide lessons learned, based on over 200 years of the authors’ cumulative and diverse experience, about PM processes. These include successful and, perhaps more importantly, not-so-successful trials. Our collective interdisciplinary background has supported the development, testing, and evaluation of a rich range of collaborative modeling approaches. We share here what we have learned as a community of participatory modelers, within three categories of reflection: a) lessons learned about participatory modelers; b) lessons learned about the context of collaboration; and c) lessons learned about the PM process. First, successful PM teams encompass a variety of skills beyond modeling expertise. Skills include: effective relationship-building, openness to learn from local experts, awareness of personal motivations and biases, and ability to translate discussions into models and to assess success. Second, the context for collaboration necessitates a culturally appropriate process for knowledge generation and use, for involvement of community co-leads, and for understanding group power dynamics that might influence how people from different backgrounds interact. Finally, knowing when to use PM and when not to, managing expectations, and effectively and equitably addressing conflicts is essential. Managing the participation process in PM is as important as managing the model building process. We recommend that PM teams consider what skills are present within a team, while ensuring inclusive creative space for collaborative exploration and learning supported by simple yet relevant models. With a realistic view of what it entails, PM can be a powerful approach that builds collective knowledge and social capital, thus helping communities to take charge of their future and address complex social and environmental problems.

","language":"English","publisher":"Elementa","doi":"10.1525/elementa.347","usgsCitation":"Sterling, E.J., Zellner, M., Jenni, K.E., Leong, K., Glynn, P.D., BenDor, T.K., Bommel, P., Hubacek, K., Jetter, A.J., Jordan, R., Olabisi, L.S., Paolisso, M., and Gray, S., 2019, Try, try again: Lessons learned from success and failure in participatory modeling: Elementa: Science of the Anthropocene, v. 7, no. 1, 9, 13 p., https://doi.org/10.1525/elementa.347.","productDescription":"9, 13 p.","ipdsId":"IP-097889","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":458824,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1525/elementa.347","text":"Publisher Index Page"},{"id":379965,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"1","noUsgsAuthors":false,"publicationDate":"2019-02-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Sterling, Eleanor J.","contributorId":145439,"corporation":false,"usgs":false,"family":"Sterling","given":"Eleanor","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":803422,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zellner, Moira","contributorId":201924,"corporation":false,"usgs":false,"family":"Zellner","given":"Moira","affiliations":[{"id":36300,"text":"University of Illinois at Chicago, Department of Urban Planning & Policy and Institute for Environmental Science and Policy. 412 S. Peoria St., MC 348, Chicago, IL 60607","active":true,"usgs":false}],"preferred":false,"id":803423,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jenni, Karen Elizabeth 0000-0003-0725-310X","orcid":"https://orcid.org/0000-0003-0725-310X","contributorId":244150,"corporation":false,"usgs":true,"family":"Jenni","given":"Karen","email":"","middleInitial":"Elizabeth","affiliations":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"preferred":true,"id":803424,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Leong, Kirsten","contributorId":207317,"corporation":false,"usgs":false,"family":"Leong","given":"Kirsten","affiliations":[{"id":37520,"text":"NOAA Fisheries, Pacific Islands Fisheries Science Center","active":true,"usgs":false}],"preferred":false,"id":803425,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Glynn, Pierre D. 0000-0001-8804-7003 pglynn@usgs.gov","orcid":"https://orcid.org/0000-0001-8804-7003","contributorId":2141,"corporation":false,"usgs":true,"family":"Glynn","given":"Pierre","email":"pglynn@usgs.gov","middleInitial":"D.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":803426,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"BenDor, Todd K.","contributorId":207319,"corporation":false,"usgs":false,"family":"BenDor","given":"Todd","email":"","middleInitial":"K.","affiliations":[{"id":37522,"text":"Department of City and Regional Planning, University of North Carolina at Chapel Hill","active":true,"usgs":false}],"preferred":false,"id":803427,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bommel, Pierre","contributorId":201916,"corporation":false,"usgs":false,"family":"Bommel","given":"Pierre","email":"","affiliations":[{"id":36294,"text":"CIRAD, Green Research Unit, Montpellier, France & University of Costa Rica, San José, Costa Rica","active":true,"usgs":false}],"preferred":false,"id":803428,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hubacek, Klaus","contributorId":201918,"corporation":false,"usgs":false,"family":"Hubacek","given":"Klaus","email":"","affiliations":[{"id":36296,"text":"University of Maryland, Department of Geographical Sciences, College Park, MD, 20742 USA","active":true,"usgs":false}],"preferred":false,"id":803429,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Jetter, Antonie J.","contributorId":207320,"corporation":false,"usgs":false,"family":"Jetter","given":"Antonie","email":"","middleInitial":"J.","affiliations":[{"id":37523,"text":"Department of Engineering and Technology Management, Portland State University","active":true,"usgs":false}],"preferred":false,"id":803430,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Jordan, Rebecca","contributorId":201914,"corporation":false,"usgs":false,"family":"Jordan","given":"Rebecca","email":"","affiliations":[{"id":36292,"text":"Rutgers University, Human Ecology & Ecology, Evolution and Natural Resources School of Environmental and Biological Sciences, 59 Lipman Drive, New Brunswick, NJ 08901","active":true,"usgs":false}],"preferred":false,"id":803431,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Olabisi, Laura Schmitt","contributorId":207318,"corporation":false,"usgs":false,"family":"Olabisi","given":"Laura","email":"","middleInitial":"Schmitt","affiliations":[{"id":37521,"text":"Department of Community Sustainability, Michigan State University","active":true,"usgs":false}],"preferred":false,"id":803432,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Paolisso, Michael","contributorId":201913,"corporation":false,"usgs":false,"family":"Paolisso","given":"Michael","email":"","affiliations":[{"id":36291,"text":"University of Maryland, Department of Anthropology, College Park, Maryland 20742 USA","active":true,"usgs":false}],"preferred":false,"id":803433,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Gray, Steven","contributorId":201912,"corporation":false,"usgs":false,"family":"Gray","given":"Steven","email":"","affiliations":[{"id":36290,"text":"Michigan State University, Department of Community Sustainability, Natural Resource Building 480 Wilson Road Room 151, East Lansing, MI 48824","active":true,"usgs":false}],"preferred":false,"id":803434,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70226606,"text":"70226606 - 2019 - Assessment of the potential for in-plume sulphur dioxide gas-ash interactions to influence the respiratory toxicity of volcanic ash","interactions":[],"lastModifiedDate":"2021-12-01T13:09:17.225146","indexId":"70226606","displayToPublicDate":"2020-10-05T07:07:10","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1561,"text":"Environmental Research","active":true,"publicationSubtype":{"id":10}},"title":"Assessment of the potential for in-plume sulphur dioxide gas-ash interactions to influence the respiratory toxicity of volcanic ash","docAbstract":"

Background

Volcanic plumes are complex environments composed of gases and ash particles, where chemical and physical processes occur at different temperature and compositional regimes. Commonly, soluble sulphate- and chloride-bearing salts are formed on ash as gases interact with ash surfaces. Exposure to respirable volcanic ash following an eruption is potentially a significant health concern. The impact of such gas-ash interactions on ash toxicity is wholly un-investigated. Here, we study, for the first time, whether the interaction of volcanic particles with sulphur dioxide (SO2) gas, and the resulting presence of sulphate salt deposits on particle surfaces, influences toxicity to the respiratory system, using an advanced in vitro approach.

Methods

To emplace surface sulphate salts on particles, via replication of the physicochemical reactions that occur between pristine ash surfaces and volcanic gas, analogue substrates (powdered synthetic volcanic glass and natural pumice) were exposed to SO2 at 500 °C, in a novel Advanced Gas-Ash Reactor, resulting in salt-laden particles. The solubility of surface salt deposits was then assessed by leaching in water and geochemical modelling. A human multicellular lung model was exposed to aerosolised salt-laden and pristine (salt-free) particles, and incubated for 24 h. Cell cultures were subsequently assessed for biological endpoints, including cytotoxicity (lactate dehydrogenase release), oxidative stress (oxidative stress-related gene expression; heme oxygenase 1 and NAD(P)H dehydrogenase [quinone] 1) and its (pro-)inflammatory response (tumour necrosis factor α, interleukin 8 and interleukin 1β at gene and protein levels).

Results

In the lung cell model no significant effects were observed between the pristine and SO2-exposed particles, indicating that the surface salt deposits, and the underlying alterations to the substrate, do not cause acute adverse effects in vitro. Based on the leachate data, the majority of the sulphate salts from the ash surfaces are likely to dissolve in the lungs prior to cellular uptake.

Conclusions

The findings of this study indicate that interaction of volcanic ash with SO2 during ash generation and transport does not significantly affect the respiratory toxicity of volcanic ash in vitro. Therefore, sulphate salts are unlikely a dominant factor controlling variability in in vitro toxicity assessments observed during previous eruption response efforts.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.envres.2019.108798","usgsCitation":"Tomasek, I., Damby, D., Horwell, C.J., Ayris, P., Delmelle, P., Ottley, C.J., Cubillas, P., Casas, A.S., Bisig, C., Petri-Fink, A., Dingwell, D.B., Clift, M., Drasler, B., and Rothen-Rutishauser, B., 2019, Assessment of the potential for in-plume sulphur dioxide gas-ash interactions to influence the respiratory toxicity of volcanic ash: Environmental Research, v. 179, no. A, 108798, 13 p., https://doi.org/10.1016/j.envres.2019.108798.","productDescription":"108798, 13 p.","ipdsId":"IP-106099","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":458828,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.envres.2019.108798","text":"Publisher Index Page"},{"id":392296,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"179","issue":"A","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Tomasek, Ines","contributorId":205741,"corporation":false,"usgs":false,"family":"Tomasek","given":"Ines","email":"","affiliations":[{"id":37158,"text":"Institute of Hazard, Risk & Resilience, Department of Earth Sciences, Durham University, UK","active":true,"usgs":false}],"preferred":false,"id":827442,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Damby, David 0000-0002-3238-3961","orcid":"https://orcid.org/0000-0002-3238-3961","contributorId":206614,"corporation":false,"usgs":true,"family":"Damby","given":"David","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":827443,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Horwell, Claire J.","contributorId":177455,"corporation":false,"usgs":false,"family":"Horwell","given":"Claire","email":"","middleInitial":"J.","affiliations":[{"id":16770,"text":"Dept. Earth Sciences, Durham University, UK","active":true,"usgs":false}],"preferred":false,"id":827444,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ayris, Paul M","contributorId":269559,"corporation":false,"usgs":false,"family":"Ayris","given":"Paul M","affiliations":[{"id":36958,"text":"LMU Munich, Germany","active":true,"usgs":false}],"preferred":false,"id":827445,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Delmelle, Pierre","contributorId":236964,"corporation":false,"usgs":false,"family":"Delmelle","given":"Pierre","email":"","affiliations":[{"id":47575,"text":"UCLouvain, Belgium","active":true,"usgs":false}],"preferred":false,"id":827446,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ottley, Christopher J","contributorId":236967,"corporation":false,"usgs":false,"family":"Ottley","given":"Christopher","email":"","middleInitial":"J","affiliations":[{"id":40359,"text":"Durham University, UK","active":true,"usgs":false}],"preferred":false,"id":827447,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cubillas, Pablo","contributorId":269562,"corporation":false,"usgs":false,"family":"Cubillas","given":"Pablo","email":"","affiliations":[{"id":40359,"text":"Durham University, UK","active":true,"usgs":false}],"preferred":false,"id":827448,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Casas, Ana S","contributorId":269563,"corporation":false,"usgs":false,"family":"Casas","given":"Ana","email":"","middleInitial":"S","affiliations":[{"id":36958,"text":"LMU Munich, Germany","active":true,"usgs":false}],"preferred":false,"id":827449,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Bisig, Christoph","contributorId":205742,"corporation":false,"usgs":false,"family":"Bisig","given":"Christoph","email":"","affiliations":[{"id":37159,"text":"Adolphe Merkle Institute, University of Fribourg, Switzerland","active":true,"usgs":false}],"preferred":false,"id":827450,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Petri-Fink, Alke","contributorId":177458,"corporation":false,"usgs":false,"family":"Petri-Fink","given":"Alke","email":"","affiliations":[],"preferred":false,"id":827451,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Dingwell, Donald B.","contributorId":201841,"corporation":false,"usgs":false,"family":"Dingwell","given":"Donald","email":"","middleInitial":"B.","affiliations":[{"id":36273,"text":"Ludwig-Maximilians-Universität (LMU) München","active":true,"usgs":false}],"preferred":false,"id":827452,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Clift, Martin J D","contributorId":205745,"corporation":false,"usgs":false,"family":"Clift","given":"Martin J D","affiliations":[{"id":37161,"text":"Swansea University Medical School, Swansea, United Kingdom","active":true,"usgs":false}],"preferred":false,"id":827453,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Drasler, Barbara","contributorId":205746,"corporation":false,"usgs":false,"family":"Drasler","given":"Barbara","email":"","affiliations":[{"id":37159,"text":"Adolphe Merkle Institute, University of Fribourg, Switzerland","active":true,"usgs":false}],"preferred":false,"id":827454,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Rothen-Rutishauser, Barbara","contributorId":177459,"corporation":false,"usgs":false,"family":"Rothen-Rutishauser","given":"Barbara","email":"","affiliations":[],"preferred":false,"id":827455,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}} ,{"id":70212843,"text":"70212843 - 2019 - Towards a predictive framework for biocrust mediation of plant performance: A meta‐analysis","interactions":[],"lastModifiedDate":"2020-09-18T15:25:48.852754","indexId":"70212843","displayToPublicDate":"2020-08-14T09:11:11","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2242,"text":"Journal of Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Towards a predictive framework for biocrust mediation of plant performance: A meta‐analysis","docAbstract":"
  1. Understanding the importance of biotic interactions in driving the distribution and abundance of species is a central goal of plant ecology. Early vascular plants likely colonized land occupied by biocrusts — photoautotrophic, surface‐dwelling soil communities comprised of cyanobacteria, bryophytes, lichens and fungi — suggesting biotic interactions between biocrusts and plants have been at play for some 2,000 million years. Today, biocrusts coexist with plants in dryland ecosystems worldwide, and have been shown to both facilitate or inhibit plant species performance depending on ecological context. Yet, the factors that drive the direction and magnitude of these effects remain largely unknown.
  2. We conducted a meta‐analysis of plant responses to biocrusts using a global dataset encompassing 1,004 studies from six continents.
  3. Meta‐analysis revealed there is no simple positive or negative effect of biocrusts on plants. Rather, plant responses differ by biocrust composition and plant species traits and vary across plant ontogeny. Moss‐dominated biocrusts facilitated, while lichen‐dominated biocrusts inhibited overall plant performance. Plant responses also varied among plant functional groups: C4 grasses received greater benefits from biocrusts compared to C3 grasses, and plants without N‐fixing symbionts responded more positively to biocrusts than plants with N‐fixing symbionts. Biocrusts decreased germination but facilitated growth of non‐native plant species.
  4. Synthesis. Results suggest that interspecific variation in plant responses to biocrusts, contingent on biocrust type, plant traits, and ontogeny can have strong impacts on plant species performance. These findings have important implications for understanding biocrust contributions to plant productivity and community assembly processes in ecosystems worldwide.
","language":"English","publisher":"Wiley","doi":"10.1111/1365-2745.13269","usgsCitation":"Havrilla, C.A., Chaudhary, B.V., Ferrenberg, S., Antoninka, A.J., Belnap, J., Bowker, M.A., Eldridge, D., Faist, A.M., Huber-Sannwald, E., Leslie, A.D., Rodriguez-Caballero, E., Zhang, Y., and Barger, N.N., 2019, Towards a predictive framework for biocrust mediation of plant performance: A meta‐analysis: Journal of Ecology, v. 107, no. 6, p. 2789-2807, https://doi.org/10.1111/1365-2745.13269.","productDescription":"19 p.","startPage":"2789","endPage":"2807","ipdsId":"IP-102308","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true}],"links":[{"id":458833,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2745.13269","text":"Publisher Index Page"},{"id":378023,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"107","issue":"6","noUsgsAuthors":false,"publicationDate":"2019-09-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Havrilla, Caroline A. 0000-0003-3913-0980","orcid":"https://orcid.org/0000-0003-3913-0980","contributorId":146326,"corporation":false,"usgs":true,"family":"Havrilla","given":"Caroline","email":"","middleInitial":"A.","affiliations":[{"id":16669,"text":"U of CO, Boulder","active":true,"usgs":false},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":false,"id":797649,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chaudhary, Bala V.","contributorId":52718,"corporation":false,"usgs":true,"family":"Chaudhary","given":"Bala","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":797650,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ferrenberg, Scott 0000-0002-3542-0334 sferrenberg@usgs.gov","orcid":"https://orcid.org/0000-0002-3542-0334","contributorId":205371,"corporation":false,"usgs":true,"family":"Ferrenberg","given":"Scott","email":"sferrenberg@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":797651,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Antoninka, Anita J.","contributorId":216042,"corporation":false,"usgs":false,"family":"Antoninka","given":"Anita","email":"","middleInitial":"J.","affiliations":[{"id":39356,"text":"School of Forestry, Northern Arizona University, Flagstaff, AZ, 86011, USA","active":true,"usgs":false}],"preferred":false,"id":797652,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Belnap, Jayne 0000-0001-7471-2279 jayne_belnap@usgs.gov","orcid":"https://orcid.org/0000-0001-7471-2279","contributorId":1332,"corporation":false,"usgs":true,"family":"Belnap","given":"Jayne","email":"jayne_belnap@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":797653,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bowker, Matthew A. mbowker@usgs.gov","contributorId":2875,"corporation":false,"usgs":true,"family":"Bowker","given":"Matthew","email":"mbowker@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":797654,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Eldridge, David J. 0000-0002-2191-486X","orcid":"https://orcid.org/0000-0002-2191-486X","contributorId":66535,"corporation":false,"usgs":false,"family":"Eldridge","given":"David J.","affiliations":[{"id":27407,"text":"Centre for Ecosystem Science, School of Biological, Earth and Environmental Sciences, University of New South Wales, Sydney, NSW 2052, Australia","active":true,"usgs":false}],"preferred":false,"id":797655,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Faist, Akasha M.","contributorId":193038,"corporation":false,"usgs":false,"family":"Faist","given":"Akasha","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":797656,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Huber-Sannwald, Elisabeth","contributorId":88700,"corporation":false,"usgs":false,"family":"Huber-Sannwald","given":"Elisabeth","email":"","affiliations":[],"preferred":false,"id":797657,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Leslie, Alexander D.","contributorId":239696,"corporation":false,"usgs":false,"family":"Leslie","given":"Alexander","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":797658,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Rodriguez-Caballero, Emilio 0000-0002-5934-3214","orcid":"https://orcid.org/0000-0002-5934-3214","contributorId":205639,"corporation":false,"usgs":false,"family":"Rodriguez-Caballero","given":"Emilio","email":"","affiliations":[{"id":37132,"text":"Multiphase Chemistry Department, Max Planck Institute for Chemistry, Hahn-Meitner-Weg 1, 55128 Mainz, Germany","active":true,"usgs":false}],"preferred":false,"id":797659,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Zhang, Yuanming","contributorId":173232,"corporation":false,"usgs":false,"family":"Zhang","given":"Yuanming","email":"","affiliations":[{"id":27200,"text":"Key Laboratory of Biogeography and Bioresource in Arid Land, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China","active":true,"usgs":false}],"preferred":false,"id":797660,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Barger, Nichole N.","contributorId":193039,"corporation":false,"usgs":false,"family":"Barger","given":"Nichole","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":797661,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70215098,"text":"70215098 - 2019 - Evaluating environmental change and behavioral decision-making for sustainability policy using an agent-based model: A case study for the Smoky Hill River Watershed, Kansas","interactions":[],"lastModifiedDate":"2020-10-08T13:27:57.138391","indexId":"70215098","displayToPublicDate":"2020-08-07T08:15:09","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating environmental change and behavioral decision-making for sustainability policy using an agent-based model: A case study for the Smoky Hill River Watershed, Kansas","docAbstract":"

Sustainability has been at the forefront of the environmental research agenda of the integrated anthroposphere, hydrosphere, and biosphere since the last century and will continue to be critically important for future environmental science. However, linking humans and the environment through effective policy remains a major challenge for sustainability research and practice. Here we address this gap using an agent-based model (ABM) for a coupled natural and human systems in the Smoky Hill River Watershed (SHRW), Kansas, USA. For this freshwater-dependent agricultural watershed with a highly variable flow regime influenced by human-induced land-use and climate change, we tested the support for an environmental policy designed to conserve and protect fish biodiversity in the SHRW. We develop a proof of concept interdisciplinary ABM that integrates field data on hydrology, ecology (fish richness), social-psychology (value-belief-norm) and economics, to simulate human agents' decisions to support environmental policy. The mechanism to link human behaviors to environmental changes is the social-psychological sequence identified by the value-belief-norm framework and is informed by hydrological and fish ecology models. Our results indicate that (1) cultural factors influence the decision to support the policy; (2) a mechanism modifying social-psychological factors can influence the decision-making process; (3) there is resistance to environmental policy in the SHRW, even under potentially extreme climate conditions; and (4) the best opportunities for policy acceptance were found immediately after extreme environmental events. The modeling approach presented herein explicitly links biophysical and social science has broad generality for sustainability problems.


","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2019.133769","usgsCitation":"Granco, G., Heier Stamm, J.L., Bergtold, J.S., Daniels, M.D., Sanderson, M.R., Sheshukov, A.Y., Mather, M.E., Caldas, M.M., Ramsey, S., Lehrter, R., Haukos, D.A., Gao, J., Chatterjee, S., Nifong, J.C., and Aistrup, J., 2019, Evaluating environmental change and behavioral decision-making for sustainability policy using an agent-based model: A case study for the Smoky Hill River Watershed, Kansas: Science of the Total Environment, v. 695, 133769, 15 p., https://doi.org/10.1016/j.scitotenv.2019.133769.","productDescription":"133769, 15 p.","ipdsId":"IP-098835","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":458836,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2019.133769","text":"Publisher Index 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}\n }\n ]\n}","volume":"695","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Granco, Gabriel","contributorId":242802,"corporation":false,"usgs":false,"family":"Granco","given":"Gabriel","affiliations":[{"id":48532,"text":"swrc","active":true,"usgs":false}],"preferred":false,"id":800839,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Heier Stamm, Jessica L.","contributorId":200848,"corporation":false,"usgs":false,"family":"Heier Stamm","given":"Jessica","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":800840,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bergtold, Jason S.","contributorId":200846,"corporation":false,"usgs":false,"family":"Bergtold","given":"Jason","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":800841,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Daniels, Melinda 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mather@usgs.gov","orcid":"https://orcid.org/0000-0003-3027-0215","contributorId":2580,"corporation":false,"usgs":true,"family":"Mather","given":"Martha","email":"mather@usgs.gov","middleInitial":"E.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":800845,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Caldas, Marcellus M.","contributorId":200844,"corporation":false,"usgs":false,"family":"Caldas","given":"Marcellus","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":800846,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Ramsey, Steven M.","contributorId":242803,"corporation":false,"usgs":false,"family":"Ramsey","given":"Steven M.","affiliations":[{"id":48533,"text":"ksu","active":true,"usgs":false}],"preferred":false,"id":800847,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Lehrter, Richard","contributorId":242804,"corporation":false,"usgs":false,"family":"Lehrter","given":"Richard","affiliations":[{"id":48533,"text":"ksu","active":true,"usgs":false}],"preferred":false,"id":800848,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Haukos, David A. 0000-0001-5372-9960 dhaukos@usgs.gov","orcid":"https://orcid.org/0000-0001-5372-9960","contributorId":3664,"corporation":false,"usgs":true,"family":"Haukos","given":"David","email":"dhaukos@usgs.gov","middleInitial":"A.","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":800849,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Gao, Jungang","contributorId":201267,"corporation":false,"usgs":false,"family":"Gao","given":"Jungang","email":"","affiliations":[],"preferred":false,"id":800850,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Chatterjee, Sarmistha","contributorId":242805,"corporation":false,"usgs":false,"family":"Chatterjee","given":"Sarmistha","email":"","affiliations":[{"id":48534,"text":"ude","active":true,"usgs":false}],"preferred":false,"id":800851,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Nifong, James C.","contributorId":140624,"corporation":false,"usgs":false,"family":"Nifong","given":"James","email":"","middleInitial":"C.","affiliations":[{"id":13453,"text":"University of Florida, Gainesville, FL","active":true,"usgs":false}],"preferred":false,"id":800852,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Aistrup, Joseph","contributorId":200847,"corporation":false,"usgs":false,"family":"Aistrup","given":"Joseph","email":"","affiliations":[],"preferred":false,"id":800853,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}} ,{"id":70211648,"text":"70211648 - 2019 - Daily estimates reveal fine-scale temporal and spatial variation in fish survival across a stream network","interactions":[],"lastModifiedDate":"2020-08-06T18:39:29.873716","indexId":"70211648","displayToPublicDate":"2020-08-06T09:02:40","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Daily estimates reveal fine-scale temporal and spatial variation in fish survival across a stream network","docAbstract":"

Environmental drivers of population vital rates, such as temperature and precipitation, often vary at short time scales, and these fluctuations can have important impacts on population dynamics. However, relationships between survival and environmental conditions are typically modeled at coarse temporal scales, ignoring the role of daily environmental variation in survival. Our goal was to determine the importance of fine-scale temporal variation in survival to population dynamics of stream salmonids. We extended the Cormack–Jolly–Seber model to estimate daily survival rates from seasonal samples of individually marked brook trout (Salvelinus fontinalis) in a stream network. Daily variation in temperature and flow were strongly associated with survival, but relationships varied between juvenile and adult trout and among streams. In all streams, juveniles had higher mortality in warm, low-flow conditions, but in the two larger streams, cold, high-flow conditions also reduced juvenile survival. Adult survival decreased during low flows, particularly in the fall spawning period. Differing survival responses among stream network components to short-term environmental events created shifts in optimal location for maximum survival across life stages, seasons, and years.

","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2018-0191","usgsCitation":"Childress, E., Nislow, K., Whiteley, A.R., O’Donnell, M., and Letcher, B., 2019, Daily estimates reveal fine-scale temporal and spatial variation in fish survival across a stream network: Canadian Journal of Fisheries and Aquatic Sciences, v. 76, no. 8, p. 1446-1458, https://doi.org/10.1139/cjfas-2018-0191.","productDescription":"13 p.","startPage":"1446","endPage":"1458","ipdsId":"IP-098110","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":377086,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"76","issue":"8","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Childress, Evan S.","contributorId":214287,"corporation":false,"usgs":false,"family":"Childress","given":"Evan S.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":794922,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nislow, Keith","contributorId":201434,"corporation":false,"usgs":false,"family":"Nislow","given":"Keith","affiliations":[{"id":27110,"text":"U.S. Dept of Agriculture, Forest Service","active":true,"usgs":false}],"preferred":false,"id":794925,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Whiteley, Andrew R.","contributorId":150155,"corporation":false,"usgs":false,"family":"Whiteley","given":"Andrew","email":"","middleInitial":"R.","affiliations":[{"id":6932,"text":"University of Massachusetts, Amherst","active":true,"usgs":false}],"preferred":false,"id":794923,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"O’Donnell, Matthew 0000-0002-9089-2377 mjodonnell@usgs.gov","orcid":"https://orcid.org/0000-0002-9089-2377","contributorId":167315,"corporation":false,"usgs":true,"family":"O’Donnell","given":"Matthew","email":"mjodonnell@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":794924,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Letcher, Benjamin 0000-0003-0191-5678 bletcher@usgs.gov","orcid":"https://orcid.org/0000-0003-0191-5678","contributorId":169305,"corporation":false,"usgs":true,"family":"Letcher","given":"Benjamin","email":"bletcher@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":794926,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ]}