{"pageNumber":"607","pageRowStart":"15150","pageSize":"25","recordCount":165298,"records":[{"id":70211249,"text":"70211249 - 2020 - Black bear movement and food conditioning in an exurban landscape","interactions":[],"lastModifiedDate":"2020-07-22T14:11:35.232544","indexId":"70211249","displayToPublicDate":"2020-04-09T13:46:40","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Black bear movement and food conditioning in an exurban landscape","docAbstract":"Conflicts between humans and wildlife have become increasingly important challenges for resource managers along the urban‐wildland interface. Food conditioning (i.e., reliance by an animal on anthropogenic foods) of American black bears (Ursus americanus ) is related to conflict behavior (i.e., being bold or aggressive toward humans, consuming human food or garbage, causing property damage) and often occurs in communities adjacent to Great Smoky Mountains National Park (GRSM or Park), USA. The goal of our study was to evaluate black bear space use in GRSM and in exurban areas on surrounding private lands and to identify factors associated with food conditioning and conflict behavior. We radio‐collared 53 bears (29 males, 24 females) from 2015 to 2017 to compare space use characteristics and used carbon isotopic signatures (δ13C) from bear hair to assess food conditioning. We then performed an integrated step selection function (iSSF) analysis to characterize and compare movement and resource use as related to food conditioning. Based on the stable isotope analyses, 24 bears were classified as food conditioned (FC; 16 males and 8 females) and 37 were not food conditioned (NFC; 14 males and 23 females). Annual 95% kernel density estimate (KDE) home ranges and 50% KDE core area estimates of female and male bears did not differ by level of food conditioning (i.e., mean δ13C), but 95% and 50% home ranges of FC females were smaller than NFC females when data from 2015, a year of food scarcity and abnormally large home ranges, were excluded. The mean proportion of exurban development (e.g., roads, buildings, openings) within 95% KDE and 50% KDE home ranges of females increased with mean δ13C (i.e., greater food conditioning). The iSSF models indicated that FC bears were more likely to use forest openings associated with higher levels of development than NFC bears. We used those models to demonstrate how landscape modifications can reduce bear use of exurban areas, particularly for NFC bears. Our stable isotope, movement, and resource use data indicate that conflict behaviors displayed by many bears within GRSM were learned in areas outside Park boundaries. © 2020 The Wildlife Society.","language":"English","publisher":"Wiley","doi":"10.1002/jwmg.21870","usgsCitation":"Braunstein, J., Clark, J.D., Williamson, R.H., and Stiver, W., 2020, Black bear movement and food conditioning in an exurban landscape: Journal of Wildlife Management, v. 84, no. 6, p. 1038-1050, https://doi.org/10.1002/jwmg.21870.","productDescription":"13 p.","startPage":"1038","endPage":"1050","ipdsId":"IP-116428","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":376574,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Tennessee, North Carolina","otherGeospatial":"Great Smoky Mountains National Park","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  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jclark1@usgs.gov","orcid":"https://orcid.org/0000-0002-8547-8112","contributorId":2265,"corporation":false,"usgs":true,"family":"Clark","given":"Joseph","email":"jclark1@usgs.gov","middleInitial":"D.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":793408,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Williamson, Ryan H","contributorId":229511,"corporation":false,"usgs":false,"family":"Williamson","given":"Ryan","email":"","middleInitial":"H","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":793409,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stiver, William H","contributorId":228824,"corporation":false,"usgs":false,"family":"Stiver","given":"William H","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":793410,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70218230,"text":"70218230 - 2020 - Volcanological applications of unoccupied aircraft systems (UAS): Developments, strategies, and future challenges","interactions":[],"lastModifiedDate":"2021-02-19T18:05:39.431635","indexId":"70218230","displayToPublicDate":"2020-04-09T12:01:21","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7593,"text":"Volcanica","active":true,"publicationSubtype":{"id":10}},"title":"Volcanological applications of unoccupied aircraft systems (UAS): Developments, strategies, and future challenges","docAbstract":"Unoccupied aircraft systems (UAS) are developing into fundamental tools for tackling the grand challenges in volcanology; here, we review the systems used and their diverse applications. UAS can typically provide image and topographic data at two orders of magnitude better spatial resolution than space-based remote sensing, and close-range observations at temporal resolutions down to those of video frame rates. Responsive deployments facilitate dense time-series measurements, unique opportunities for geophysical surveys, sample collection from hostile environments such as volcanic plumes and crater lakes, and emergency deployment of ground-based sensors (and robots) into hazardous regions. UAS have already been used to support hazard management and decision-makers during eruptive crises. As technologies advance, increased system capabilities, autonomy and availability, supported by more diverse and lighter-weight sensors, will offer unparalleled potential for hazard monitoring. UAS are expected to provide opportunities for pivotal advances in our understanding of complex physical and chemical volcanic processes.","language":"English","publisher":"Presses universitaires de Strasbourg","doi":"10.30909/vol.03.01.67114","usgsCitation":"James, M.R., Carr, B., D’Arcy, F., Diefenbach, A., Dietterich, H., Fornaciai, A., Lev, E., Liu, E.J., Pieri, D.C., Rodgers, M., Smets, B., Terada, A., von Aulock, F.W., Walter, T.R., Wood, K.T., and Zorn, E.U., 2020, Volcanological applications of unoccupied aircraft systems (UAS): Developments, strategies, and future challenges: Volcanica, v. 3, no. 1, p. 67-114, https://doi.org/10.30909/vol.03.01.67114.","productDescription":"48 p.","startPage":"67","endPage":"114","ipdsId":"IP-112178","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":457115,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.30909/vol.03.01.67114","text":"Publisher Index Page"},{"id":383379,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"3","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-04-09","publicationStatus":"PW","contributors":{"authors":[{"text":"James, Mike R.","contributorId":199802,"corporation":false,"usgs":false,"family":"James","given":"Mike","email":"","middleInitial":"R.","affiliations":[{"id":13133,"text":"Lancaster Environment Centre, Lancaster University, Lancaster, UK","active":true,"usgs":false}],"preferred":false,"id":810520,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carr, Brett B 0000-0002-1033-3082","orcid":"https://orcid.org/0000-0002-1033-3082","contributorId":251755,"corporation":false,"usgs":false,"family":"Carr","given":"Brett B","affiliations":[{"id":17701,"text":"Lamont-Doherty Earth Observatory","active":true,"usgs":false}],"preferred":false,"id":810521,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"D’Arcy, Fiona 0000-0002-0879-0508","orcid":"https://orcid.org/0000-0002-0879-0508","contributorId":251756,"corporation":false,"usgs":false,"family":"D’Arcy","given":"Fiona","email":"","affiliations":[{"id":6646,"text":"McGill University","active":true,"usgs":false}],"preferred":false,"id":810522,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Diefenbach, Angela K. 0000-0003-0214-7818","orcid":"https://orcid.org/0000-0003-0214-7818","contributorId":204743,"corporation":false,"usgs":true,"family":"Diefenbach","given":"Angela K.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":810523,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dietterich, Hannah R. 0000-0001-7898-4343","orcid":"https://orcid.org/0000-0001-7898-4343","contributorId":212771,"corporation":false,"usgs":true,"family":"Dietterich","given":"Hannah R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":810524,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fornaciai, Alessandro 0000-0003-4829-4928","orcid":"https://orcid.org/0000-0003-4829-4928","contributorId":251757,"corporation":false,"usgs":false,"family":"Fornaciai","given":"Alessandro","email":"","affiliations":[{"id":39118,"text":"Istituto Nazionale di Geofisica e Vulcanologia","active":true,"usgs":false}],"preferred":false,"id":810525,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lev, Einat 0000-0002-8174-0558","orcid":"https://orcid.org/0000-0002-8174-0558","contributorId":194355,"corporation":false,"usgs":false,"family":"Lev","given":"Einat","email":"","affiliations":[{"id":27369,"text":"Lamont-Doherty Earth Observatory at Columbia University","active":true,"usgs":false}],"preferred":false,"id":810526,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Liu, Emma J 0000-0003-1749-9285","orcid":"https://orcid.org/0000-0003-1749-9285","contributorId":251758,"corporation":false,"usgs":false,"family":"Liu","given":"Emma","email":"","middleInitial":"J","affiliations":[{"id":27136,"text":"University of Cambridge","active":true,"usgs":false}],"preferred":false,"id":810527,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Pieri, David C.","contributorId":211514,"corporation":false,"usgs":false,"family":"Pieri","given":"David","email":"","middleInitial":"C.","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":810528,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Rodgers, Mel 0000-0002-8809-9935","orcid":"https://orcid.org/0000-0002-8809-9935","contributorId":251759,"corporation":false,"usgs":false,"family":"Rodgers","given":"Mel","email":"","affiliations":[{"id":7163,"text":"University of South Florida","active":true,"usgs":false}],"preferred":false,"id":810529,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Smets, Benoit 0000-0002-1044-8314","orcid":"https://orcid.org/0000-0002-1044-8314","contributorId":251760,"corporation":false,"usgs":false,"family":"Smets","given":"Benoit","email":"","affiliations":[{"id":50395,"text":"Royal Museum for Central Africa","active":true,"usgs":false}],"preferred":false,"id":810530,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Terada, Akihiko 0000-0001-5746-4912","orcid":"https://orcid.org/0000-0001-5746-4912","contributorId":251761,"corporation":false,"usgs":false,"family":"Terada","given":"Akihiko","email":"","affiliations":[{"id":38251,"text":"Tokyo Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":810531,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"von Aulock, Felix W 0000-0003-1194-4317","orcid":"https://orcid.org/0000-0003-1194-4317","contributorId":251762,"corporation":false,"usgs":false,"family":"von Aulock","given":"Felix","email":"","middleInitial":"W","affiliations":[{"id":16977,"text":"University of Liverpool","active":true,"usgs":false}],"preferred":false,"id":810532,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Walter, Thomas R.","contributorId":199803,"corporation":false,"usgs":false,"family":"Walter","given":"Thomas","email":"","middleInitial":"R.","affiliations":[{"id":16947,"text":"German Research Centre for Geosciences","active":true,"usgs":false}],"preferred":false,"id":810533,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Wood, Kieran T 0000-0002-5804-7704","orcid":"https://orcid.org/0000-0002-5804-7704","contributorId":251763,"corporation":false,"usgs":false,"family":"Wood","given":"Kieran","email":"","middleInitial":"T","affiliations":[{"id":37322,"text":"University of Bristol","active":true,"usgs":false}],"preferred":false,"id":810534,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Zorn, Edgar U 0000-0002-1896-2844","orcid":"https://orcid.org/0000-0002-1896-2844","contributorId":251764,"corporation":false,"usgs":false,"family":"Zorn","given":"Edgar","email":"","middleInitial":"U","affiliations":[{"id":39797,"text":"GFZ German Research Centre for Geosciences","active":true,"usgs":false}],"preferred":false,"id":810535,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}}
,{"id":70210589,"text":"70210589 - 2020 - Combined effects of biological control of an invasive shrub and fluvial processes on riparian vegetation dynamics","interactions":[],"lastModifiedDate":"2020-08-06T19:32:51.734887","indexId":"70210589","displayToPublicDate":"2020-04-09T10:52:00","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1018,"text":"Biological Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Combined effects of biological control of an invasive shrub and fluvial processes on riparian vegetation dynamics","docAbstract":"<p><span>Plant community responses to biocontrol of invasive plants are understudied, despite the strong influence of the composition of replacement vegetation on ecosystem functions and services. We studied the vegetation response to a folivore beetle (</span><i>Diorhabda</i><span>&nbsp;genus, Coleoptera) that has been introduced along southwestern US river valleys to control the invasion of non-native shrubs in the genus&nbsp;</span><i>Tamarix</i><span>&nbsp;(Tamaricaceae). We collected detailed plant compositional and environmental data during four different surveys over 7&nbsp;years (2010–2017), including two surveys prior to when substantial beetle-induced dieback occurred in summer 2012, along the lower Virgin River, Nevada. The study river was of special interest because it is one of only a few largely unregulated rivers in the region, and a large flood of 40-year return period occurred between the first and second surveys, allowing us to study the combined effects of fluvial processes, which typically drive riparian plant community assembly, and biocontrol. Vegetation trajectories differed as a function of the dominant geomorphological process.&nbsp;</span><i>Tamarix</i><span>&nbsp;cover declined an average of 75% and was replaced by the native shrub&nbsp;</span><i>Pluchea sericea</i><span>&nbsp;as the new dominant species in the floodplain, especially where sediment deposition predominated. Following deposition, and especially erosion, opportunistic native herbs,&nbsp;</span><i>Tamarix</i><span>&nbsp;seedlings, and noxious weeds colonized the understory layer but did not increase in cover over time. Stands of the native shrub&nbsp;</span><i>Salix exigua</i><span>, a desirable replacement species following&nbsp;</span><i>Tamarix</i><span>&nbsp;control, only increased slightly and remained subordinate in the floodplain. Overall, our results showed that, by successfully controlling the target non-native plant, a biocontrol agent can substantially modify the replacement plant communities in a riparian system, but that fluvial processes also strongly influence the resulting communities.</span></p>","language":"English","publisher":"Springer","doi":"10.1007/s10530-020-02259-9","usgsCitation":"Gonzalez, E., Shafroth, P., Lee, S.R., Ostoja, S., and Brooks, M.L., 2020, Combined effects of biological control of an invasive shrub and fluvial processes on riparian vegetation dynamics: Biological Invasions, v. 22, p. 2339-2356, https://doi.org/10.1007/s10530-020-02259-9.","productDescription":"18 p.","startPage":"2339","endPage":"2356","ipdsId":"IP-117377","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":437028,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P97KZJGP","text":"USGS data release","linkHelpText":"Riparian vegetation, topography, sediment quality and river corridor geomorphology in the Lower Virgin River 2010-2017"},{"id":375517,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona, Nevada, Utah","otherGeospatial":"Virgin River","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -115.55419921875,\n              36.328402729422656\n            ],\n            [\n              -113.02734374999999,\n              36.328402729422656\n            ],\n            [\n              -113.02734374999999,\n              37.496652341233364\n            ],\n            [\n              -115.55419921875,\n              37.496652341233364\n            ],\n            [\n              -115.55419921875,\n              36.328402729422656\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"22","noUsgsAuthors":false,"publicationDate":"2020-04-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Gonzalez, Eduardo","contributorId":225181,"corporation":false,"usgs":false,"family":"Gonzalez","given":"Eduardo","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":790705,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shafroth, Patrick B. 0000-0002-6064-871X","orcid":"https://orcid.org/0000-0002-6064-871X","contributorId":225182,"corporation":false,"usgs":true,"family":"Shafroth","given":"Patrick B.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":790706,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lee, Steven R. 0000-0002-4581-3684 srlee@usgs.gov","orcid":"https://orcid.org/0000-0002-4581-3684","contributorId":5630,"corporation":false,"usgs":true,"family":"Lee","given":"Steven","email":"srlee@usgs.gov","middleInitial":"R.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":790707,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ostoja, Steven M.","contributorId":225183,"corporation":false,"usgs":false,"family":"Ostoja","given":"Steven M.","affiliations":[{"id":32922,"text":"USDA California Climate Hub","active":true,"usgs":false}],"preferred":false,"id":790708,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brooks, Matthew L. 0000-0002-3518-6787 mlbrooks@usgs.gov","orcid":"https://orcid.org/0000-0002-3518-6787","contributorId":393,"corporation":false,"usgs":true,"family":"Brooks","given":"Matthew","email":"mlbrooks@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":790709,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70210107,"text":"70210107 - 2020 - Migration corridors and threats in the Gulf of Mexico and Florida Straits for loggerhead sea turtles","interactions":[],"lastModifiedDate":"2020-05-14T15:14:47.624852","indexId":"70210107","displayToPublicDate":"2020-04-09T10:10:05","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3912,"text":"Frontiers in Marine Science","onlineIssn":"2296-7745","active":true,"publicationSubtype":{"id":10}},"title":"Migration corridors and threats in the Gulf of Mexico and Florida Straits for loggerhead sea turtles","docAbstract":"<p><span>Along migration corridors, animals can face natural and anthropogenic threats that differ from those in breeding and non-breeding residence areas. Satellite telemetry can aid in describing the timing and location of these migrations. We use this tool with switching state-space modeling and line kernel density estimates to identify migration corridors of post-nesting adult female loggerhead sea turtles (</span><i>Caretta caretta</i><span>,&nbsp;</span><i>n</i><span>&nbsp;= 89 tracks) that nested at five beaches in the Gulf of Mexico. Turtles migrated in both neritic and oceanic areas of the Gulf of Mexico with some exiting the Gulf. High-use migration corridors were found in neritic areas to the west of Florida and also in the Florida Straits. Repeat tracking of post-nesting migrations for eight turtles showed variability in track overlap, ranging from ∼13 to 82% of tracks within 10 km of each other. Migration primarily occurred in July and August. We document the longest known post-nesting migration to-date of a wild adult female loggerhead of &gt;4,300 km, along with an apparent stopover of about 1 month. Migration corridors overlaid on three spatially explicit anthropogenic threats (shipping density, commercial line fishing, and shrimp trawling) showed hotspots in the Florida Straits, off the northwest Florida coast and off the coast of Tampa Bay. Identifying where and at what intensity multiple human activities and natural processes most likely occur is a key goal of Cumulative Effects Assessments. Our results provide the scientific information needed for designing management strategies for this threatened species. Information about this loggerhead migration corridor can also be used to inform adaptive management as threats shift over time.</span></p>","language":"English","publisher":"Frontiers","doi":"10.3389/fmars.2020.00208","collaboration":"","usgsCitation":"Iverson, A., Benscoter, A., Fujisaki, I., Lamont, M., and Hart, K., 2020, Migration corridors and threats in the Gulf of Mexico and Florida Straits for loggerhead sea turtles: Frontiers in Marine Science, v. 7, 208, 12 p., https://doi.org/10.3389/fmars.2020.00208.","productDescription":"208, 12 p.","ipdsId":"IP-113942","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":457117,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fmars.2020.00208","text":"Publisher Index Page"},{"id":374824,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alabama, Florida","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -79.0576171875,\n              23.28171917560002\n            ],\n            [\n              -80.5517578125,\n              26.07652055985697\n            ],\n            [\n              -82.2216796875,\n              27.68352808378776\n            ],\n            [\n              -83.84765625,\n              30.14512718337613\n            ],\n            [\n              -86.923828125,\n              30.44867367928756\n            ],\n            [\n              -89.3408203125,\n              30.183121842195515\n            ],\n            [\n              -90.8349609375,\n              29.458731185355344\n            ],\n            [\n              -89.3408203125,\n              22.268764039073968\n            ],\n            [\n              -79.0576171875,\n              23.28171917560002\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"7","noUsgsAuthors":false,"publicationDate":"2020-04-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Iverson, Autumn 0000-0002-8353-6745","orcid":"https://orcid.org/0000-0002-8353-6745","contributorId":218320,"corporation":false,"usgs":true,"family":"Iverson","given":"Autumn","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":789140,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Benscoter, Allison 0000-0003-4205-3808","orcid":"https://orcid.org/0000-0003-4205-3808","contributorId":220759,"corporation":false,"usgs":true,"family":"Benscoter","given":"Allison","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":789141,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fujisaki, Ikuko","contributorId":38359,"corporation":false,"usgs":false,"family":"Fujisaki","given":"Ikuko","affiliations":[],"preferred":false,"id":789142,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lamont, Margaret 0000-0001-7520-6669","orcid":"https://orcid.org/0000-0001-7520-6669","contributorId":206815,"corporation":false,"usgs":true,"family":"Lamont","given":"Margaret","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":789143,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hart, Kristen 0000-0002-5257-7974","orcid":"https://orcid.org/0000-0002-5257-7974","contributorId":207590,"corporation":false,"usgs":true,"family":"Hart","given":"Kristen","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":789144,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70219554,"text":"70219554 - 2020 - Magnitude and direction of stream–forest community interactions change with timescale","interactions":[],"lastModifiedDate":"2021-04-13T12:51:49.847707","indexId":"70219554","displayToPublicDate":"2020-04-09T07:50:19","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Magnitude and direction of stream–forest community interactions change with timescale","docAbstract":"<div class=\"abstract-group\"><div class=\"article-section__content en main\"><p>Networks of direct and indirect biotic interactions underpin the complex dynamics and stability of ecological systems, yet experimental and theoretical studies often yield conflicting evidence regarding the direction (positive or negative) or magnitude of these interactions. We revisited pioneering data sets collected at the deciduous forested Horonai Stream and conducted ecosystem‐level syntheses to demonstrate that the direction of direct and indirect interactions can change depending on the timescale of observation. Prior experimental studies showed that terrestrial prey that enter the stream from the adjacent forest caused positive indirect effects on aquatic invertebrates during summer by diverting fish consumption. Seasonal and annual estimates of secondary production and organic matter flows along food web pathways demonstrate that this seasonal input of terrestrial invertebrate prey increases production of certain fish species, reversing the indirect effect on aquatic invertebrates from positive at the seasonal timescale to negative at the annual timescale. Even though terrestrial invertebrate prey contributed 54% of the annual organic matter flux to fishes, primarily during summer, fish still consumed 98% of the aquatic invertebrate annual production, leading to top‐down control that is not revealed in short‐term experiments and demonstrating that aquatic prey may be a limiting resource for fishes. Changes in the direction or magnitude of interactions may be a key factor creating nonlinear or stabilizing feedbacks in complex systems, and these dynamics can be revealed by merging experimental and comparative approaches at different scales.</p></div></div>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecy.3064","usgsCitation":"Marcarelli, A.M., Baxter, C., Benjamin, J.R., Miyake, Y., Murakami, M., Fausch, K., and Nakano, S., 2020, Magnitude and direction of stream–forest community interactions change with timescale: Ecology, v. 101, no. 8, e03064, 10 p., https://doi.org/10.1002/ecy.3064.","productDescription":"e03064, 10 p.","ipdsId":"IP-109993","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":385052,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"101","issue":"8","noUsgsAuthors":false,"publicationDate":"2020-05-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Marcarelli, Amy M 0000-0002-4175-9211","orcid":"https://orcid.org/0000-0002-4175-9211","contributorId":257363,"corporation":false,"usgs":false,"family":"Marcarelli","given":"Amy","email":"","middleInitial":"M","affiliations":[{"id":16203,"text":"Michigan Technological university","active":true,"usgs":false}],"preferred":false,"id":814126,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baxter, Colden V.","contributorId":47334,"corporation":false,"usgs":false,"family":"Baxter","given":"Colden V.","affiliations":[{"id":13656,"text":"Idaho State Univ.","active":true,"usgs":false}],"preferred":false,"id":814127,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Benjamin, Joseph R. 0000-0003-3733-6838 jbenjamin@usgs.gov","orcid":"https://orcid.org/0000-0003-3733-6838","contributorId":3999,"corporation":false,"usgs":true,"family":"Benjamin","given":"Joseph","email":"jbenjamin@usgs.gov","middleInitial":"R.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":814128,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miyake, Yo 0000-0002-3838-2513","orcid":"https://orcid.org/0000-0002-3838-2513","contributorId":257366,"corporation":false,"usgs":false,"family":"Miyake","given":"Yo","email":"","affiliations":[{"id":52005,"text":"Ehime University","active":true,"usgs":false}],"preferred":false,"id":814129,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Murakami, Masashi 0000-0003-4374-4045","orcid":"https://orcid.org/0000-0003-4374-4045","contributorId":257367,"corporation":false,"usgs":false,"family":"Murakami","given":"Masashi","email":"","affiliations":[{"id":37962,"text":"Chiba University","active":true,"usgs":false}],"preferred":false,"id":814130,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fausch, K.D. 0000-0001-5825-7560","orcid":"https://orcid.org/0000-0001-5825-7560","contributorId":84097,"corporation":false,"usgs":false,"family":"Fausch","given":"K.D.","affiliations":[],"preferred":false,"id":814131,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Nakano, Shigeru","contributorId":257368,"corporation":false,"usgs":false,"family":"Nakano","given":"Shigeru","email":"","affiliations":[{"id":36662,"text":"Kyoto University","active":true,"usgs":false}],"preferred":false,"id":814132,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70210212,"text":"70210212 - 2020 - USGS “Did You Feel It?” — Science and lessons from twenty years of citizen science-based macroseismology","interactions":[],"lastModifiedDate":"2020-06-04T12:34:23.786193","indexId":"70210212","displayToPublicDate":"2020-04-09T07:41:57","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5232,"text":"Frontiers in Earth Science","onlineIssn":"2296-6463","active":true,"publicationSubtype":{"id":10}},"title":"USGS “Did You Feel It?” — Science and lessons from twenty years of citizen science-based macroseismology","docAbstract":"The U.S. Geological Survey (USGS) “Did You Feel It?” (DYFI) system is an automatic method for rapidly collecting macroseismic intensity data from Internet users’ shaking and damage reports and for generating intensity maps immediately following felt earthquakes. DYFI has been in operation for nearly two decades (1999-2019) in the United States, and for nearly 15 years globally. During that period the amount of data collected is astounding: Over 5 million individual DYFI intensity reports—spanning all magnitude and distance ranges—have been amassed and archived. DYFI allows for macroseismic data collection at rates and quantities never before imagined, and thus high-quality macroseismic intensity maps can be made almost immediately, and with more complete coverage at higher resolution than in the past. DYFI also allows for valuable positive interactions of the citizenry with a Federal science agency. In essence, the widespread adoption of DYFI—along with ShakeMap—has facilitated the general acceptance of the very concept of shaking intensity, fundamentally improving our agency’s ability to communicate both hazard and risk to the population. DYFI effectively confirms the importance of reporting and inculcating the public’s understanding of intensity—in addition to magnitude—for a proper perspective of earthquake risk-related decision-making. Furthermore, the vast amount of DYFI data allow for data-rich analyses of otherwise intractable seismological, sociological, and earthquake impact studies that range from quantifying the shaking due to induced earthquakes, to human response and risk\nperception, to relating recorded shaking metrics to macroseismic effects, and the attenuation of intensity with magnitude and distance. Naturally, web-based data collection also poses challenges. After two decades of experience acquiring data with the DYFI system, we address some of these hallenges by documenting refinements to our algorithmic and operational procedures that have evolved over that time. Lastly, we outline new opportune research and development directions for our DYFI approach to citizen seismology.","language":"English","publisher":"Frontiers","doi":"10.3389/feart.2020.00120","usgsCitation":"Quitoriano, V., and Wald, D.J., 2020, USGS “Did You Feel It?” — Science and lessons from twenty years of citizen science-based macroseismology: Frontiers in Earth Science, v. 8, no. 120, 13 p., https://doi.org/10.3389/feart.2020.00120.","productDescription":"13 p.","ipdsId":"IP-117773","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":457120,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/feart.2020.00120","text":"Publisher Index Page"},{"id":374981,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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 \"}}]}","volume":"8","issue":"120","noUsgsAuthors":false,"publicationDate":"2020-05-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Quitoriano, Vince 0000-0003-4157-1101 vinceq@usgs.gov","orcid":"https://orcid.org/0000-0003-4157-1101","contributorId":2582,"corporation":false,"usgs":true,"family":"Quitoriano","given":"Vince","email":"vinceq@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":789549,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wald, David J. 0000-0002-1454-4514 wald@usgs.gov","orcid":"https://orcid.org/0000-0002-1454-4514","contributorId":795,"corporation":false,"usgs":true,"family":"Wald","given":"David","email":"wald@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":789550,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70209475,"text":"70209475 - 2020 - Use of genetic mark-recapture to estimate breeding site fidelity and philopatry in a threatened sea duck population, Alaska-breeding Steller’s eiders","interactions":[],"lastModifiedDate":"2020-04-10T12:53:03.407673","indexId":"70209475","displayToPublicDate":"2020-04-09T07:19:26","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1497,"text":"Endangered Species Research","active":true,"publicationSubtype":{"id":10}},"title":"Use of genetic mark-recapture to estimate breeding site fidelity and philopatry in a threatened sea duck population, Alaska-breeding Steller’s eiders","docAbstract":"The Steller’s eider (Polysticta stelleri) is a sea duck that breeds in Arctic tundra regions of Russia and Alaska.  The Alaska-breeding population is listed as threatened under the U.S. Endangered Species Act because of a perceived contraction of their breeding range in North America.  Understanding demographic rates of the listed population is critical for determining and evaluating measures that can lead to an increase in abundance and thus, long-term viability.  Specifically, estimates of return rates to breeding areas by adult females and natal areas by juvenile females are needed for planning effective recovery actions.  We used a suite of polymorphic loci to genotype individuals and generated genetic profiles of nesting females and female offspring from nest materials collected from 1995 – 2016 in a ~170 km2 study area near Utqiaġvik, Alaska.  We analyzed capture histories of genetically-identified individuals to estimate breeding site fidelity, temporary emigration, and natal site fidelity (philopatry).  From a sample of 365 nests, we found that breeding site fidelity of adult females was high (0.91, SE 0.07) and temporary emigration also was high (0.77, SE 0.06) and variable across years (range 0.34 – 0.97).  From egg shell remains of 124 hatched females, we observed nine recaptures as nesting adults, suggesting that philopatry was also high (range 0.6-1.0).  Given the relatively high rates of adult female breeding site fidelity and female philopatry that we estimated, management actions that reduce mortality of adult females and increase annual productivity are likely to help maintain the population of a few hundred breeding Steller’s eiders on the Arctic Coastal Plain of Alaska.","language":"English","publisher":"Inter-Research","doi":"10.3354/esr01026","collaboration":"","usgsCitation":"Safine, D., Lindberg, M., Martin, K., Talbot, S.L., Swem, T., Pearce, J.M., Stellrecht, N., Sage, K., Riddle, A.E., Fales, K., and Hollmen, T.E., 2020, Use of genetic mark-recapture to estimate breeding site fidelity and philopatry in a threatened sea duck population, Alaska-breeding Steller’s eiders: Endangered Species Research, v. 41, p. 349-360  , https://doi.org/10.3354/esr01026.","productDescription":"12 p.","startPage":"349","endPage":"360  ","ipdsId":"IP-107992","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":457123,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/esr01026","text":"Publisher Index Page"},{"id":437029,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P967DZ5L","text":"USGS data release","linkHelpText":"Genetic Data From Nesting Steller's Eiders (Polysticta stelleri), Near Utqiagvik, Alaska, 1995-2016"},{"id":373887,"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              -156.588134765625,\n              70.66360693648447\n            ],\n            [\n              -154.88525390625,\n              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Fairbanks","active":true,"usgs":false}],"preferred":false,"id":786679,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Martin, Kate","contributorId":223948,"corporation":false,"usgs":false,"family":"Martin","given":"Kate","email":"","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":786680,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Talbot, Sandra L. 0000-0002-3312-7214 stalbot@usgs.gov","orcid":"https://orcid.org/0000-0002-3312-7214","contributorId":140512,"corporation":false,"usgs":true,"family":"Talbot","given":"Sandra","email":"stalbot@usgs.gov","middleInitial":"L.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":786681,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Swem, Ted","contributorId":200583,"corporation":false,"usgs":false,"family":"Swem","given":"Ted","affiliations":[],"preferred":false,"id":786682,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pearce, John M. 0000-0002-8503-5485 jpearce@usgs.gov","orcid":"https://orcid.org/0000-0002-8503-5485","contributorId":181766,"corporation":false,"usgs":true,"family":"Pearce","given":"John","email":"jpearce@usgs.gov","middleInitial":"M.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":786683,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Stellrecht, Neesha","contributorId":223949,"corporation":false,"usgs":false,"family":"Stellrecht","given":"Neesha","email":"","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":786684,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sage, Kevin 0000-0003-1431-2286 ksage@usgs.gov","orcid":"https://orcid.org/0000-0003-1431-2286","contributorId":139795,"corporation":false,"usgs":true,"family":"Sage","given":"Kevin","email":"ksage@usgs.gov","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":786685,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Riddle, Ann E.","contributorId":62042,"corporation":false,"usgs":false,"family":"Riddle","given":"Ann","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":786686,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Fales, Kyrstal","contributorId":223950,"corporation":false,"usgs":false,"family":"Fales","given":"Kyrstal","email":"","affiliations":[{"id":24583,"text":"former USGS employee","active":true,"usgs":false}],"preferred":false,"id":786687,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Hollmen, Tuula E.","contributorId":211728,"corporation":false,"usgs":false,"family":"Hollmen","given":"Tuula","email":"","middleInitial":"E.","affiliations":[{"id":16211,"text":"Alaska SeaLife Center","active":true,"usgs":false}],"preferred":false,"id":786688,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70209600,"text":"70209600 - 2020 - Gap fill of Land surface temperature and reflectance products in Analysis Ready Data","interactions":[],"lastModifiedDate":"2020-04-15T11:45:58.03143","indexId":"70209600","displayToPublicDate":"2020-04-09T06:43:38","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Gap fill of Land surface temperature and reflectance products in Analysis Ready Data","docAbstract":"The recently released Landsat Analysis Ready Data (ARD) over the United States provides the opportunity to investigate landscape dynamics using dense time series observations at 30-m resolution. However, the dataset often contains data gaps (or missing data) because of cloud contamination or data acquisition strategy. We present a new algorithm that focuses on data gap filling using clear observations from orbit overlap regions. Multiple linear regression models were established for each pixel time series to estimate stable predictions and uncertainties. The model's training data came from stratified random samples based on the time series similarity between the pixel and data from the overlap regions. The algorithm was evaluated using four tiles (5,000 × 5,000 30-m pixels for each tile) from 2018 land surface temperature data (LST) in Atlanta, Georgia. The accuracy was assessed using 1,000 randomly masked pixels and daily air temperature from eight ground stations. Both assessments showed the r2 value above 0.75, except two stations with mixed Landsat pixels. We also compared our results with the eMODIS LST product in terms of annual mean temperature. The two maps showed a similar spatial pattern at the region level, but our results showed more spatial detail in the urban area that matched the pattern of impervious surface. We also applied the method on ARD surface reflectance bands at Fairbanks, Alaska, to illustrate its improvements in surface reflectance products and in land change modeling. This approach can also be applied to other datasets, vegetation indexes, or spectral reflectance bands of other sensors.","language":"English","publisher":"MDPI","doi":"10.3390/rs12071192","collaboration":"","usgsCitation":"Zhou, Q., Xian, G.Z., and Shi, H., 2020, Gap fill of Land surface temperature and reflectance products in Analysis Ready Data: Remote Sensing, v. 12, no. 7, 1192, 16 p., https://doi.org/10.3390/rs12071192.","productDescription":"1192, 16 p.","ipdsId":"IP-113228","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":457126,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs12071192","text":"Publisher Index Page"},{"id":374000,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","issue":"7","noUsgsAuthors":false,"publicationDate":"2020-04-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Zhou, Qiang 0000-0002-1282-8177","orcid":"https://orcid.org/0000-0002-1282-8177","contributorId":223103,"corporation":false,"usgs":true,"family":"Zhou","given":"Qiang","email":"","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":787086,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Xian, George Z. 0000-0001-5674-2204 xian@usgs.gov","orcid":"https://orcid.org/0000-0001-5674-2204","contributorId":2263,"corporation":false,"usgs":true,"family":"Xian","given":"George","email":"xian@usgs.gov","middleInitial":"Z.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":787087,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shi, Hua 0000-0001-7013-1565 hshi@usgs.gov","orcid":"https://orcid.org/0000-0001-7013-1565","contributorId":646,"corporation":false,"usgs":true,"family":"Shi","given":"Hua","email":"hshi@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":787088,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70208173,"text":"fs20203003 - 2020 - Assessment of tight-gas resources in the Grand Erg/Ahnet Province of Algeria, 2019","interactions":[],"lastModifiedDate":"2020-04-09T11:22:55.898495","indexId":"fs20203003","displayToPublicDate":"2020-04-08T12:30:00","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-3003","displayTitle":"Assessment of Tight-Gas Resources in the Grand Erg/Ahnet Province of Algeria, 2019","title":"Assessment of tight-gas resources in the Grand Erg/Ahnet Province of Algeria, 2019","docAbstract":"<p>Using a geology-based assessment methodology, the U.S. Geological Survey estimated undiscovered, technically recoverable mean resources of 30.5 trillion cubic feet of tight gas in the Grand Erg/Ahnet Province of Algeria.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20203003","collaboration":"","usgsCitation":"Brownfield, M.E., Schenk, C.J., Mercier, T.J., Tennyson, M.E., Woodall, C.A., Finn, T.M., Le, P.A., Pitman, J.K., Drake, R.M., II, Gaswirth, S.B., and Leathers-Miller, H.M., 2020, Assessment of tight-gas resources in the Grand Erg/Ahnet Province of Algeria, 2019: U.S. Geological Survey Fact Sheet 2020–3003, 2 p., https://doi.org/10.3133/fs20203003.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"N","ipdsId":"IP-109442","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":373756,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2020/3003/coverthb.jpg"},{"id":373757,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2020/3003/fs20203003.pdf","text":"Report","size":"1.55 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80225-0046</p>","tableOfContents":"<ul><li>Introduction</li><li>Total Petroleum Systems and Assessment Units</li><li>Undiscovered Resources Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"publishedDate":"2020-04-08","noUsgsAuthors":false,"publicationDate":"2020-04-08","publicationStatus":"PW","contributors":{"authors":[{"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":780802,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":780801,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":780803,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tennyson, Marilyn E. 0000-0002-5166-2421 tennyson@usgs.gov","orcid":"https://orcid.org/0000-0002-5166-2421","contributorId":176582,"corporation":false,"usgs":true,"family":"Tennyson","given":"Marilyn","email":"tennyson@usgs.gov","middleInitial":"E.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":786381,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"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":780805,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"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":780806,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"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":780807,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Pitman, Janet K. 0000-0002-0441-779X jpitman@usgs.gov","orcid":"https://orcid.org/0000-0002-0441-779X","contributorId":767,"corporation":false,"usgs":true,"family":"Pitman","given":"Janet","email":"jpitman@usgs.gov","middleInitial":"K.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":780808,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Drake, Ronald M. II 0000-0002-1770-4667 rmdrake@usgs.gov","orcid":"https://orcid.org/0000-0002-1770-4667","contributorId":1353,"corporation":false,"usgs":true,"family":"Drake","given":"Ronald","suffix":"II","email":"rmdrake@usgs.gov","middleInitial":"M.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":786382,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Gaswirth, Stephanie B. 0000-0001-5821-6347 sgaswirth@usgs.gov","orcid":"https://orcid.org/0000-0001-5821-6347","contributorId":150417,"corporation":false,"usgs":true,"family":"Gaswirth","given":"Stephanie","email":"sgaswirth@usgs.gov","middleInitial":"B.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":780810,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"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":780811,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70210624,"text":"70210624 - 2020 - Establishment of brown anoles (Anolis sagrei) across a southern California county and potential interactions with a native lizard species","interactions":[],"lastModifiedDate":"2022-10-31T14:03:32.868528","indexId":"70210624","displayToPublicDate":"2020-04-08T11:31:39","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3840,"text":"PeerJ","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Establishment of brown anoles (<i>Anolis sagrei</i>) across a southern California county and potential interactions with a native lizard species","title":"Establishment of brown anoles (Anolis sagrei) across a southern California county and potential interactions with a native lizard species","docAbstract":"<p><span>The brown anole,&nbsp;</span><i>Anolis sagrei</i><span>, is a native species to the Caribbean; however,&nbsp;</span><i>A. sagrei</i><span>&nbsp;has invaded multiple parts of the USA, including Florida, Louisiana, Hawai’i and more recently California. The biological impacts of&nbsp;</span><i>A. sagrei</i><span>&nbsp;invading California are currently unknown. Evidence from the invasion in Taiwan shows that they spread quickly and when immediate action is not taken eradication stops being a viable option. In Orange County, California, five urban sites, each less than 100 ha, were surveyed for an average of 49.2 min. Approximately 200&nbsp;</span><i>A. sagrei</i><span>&nbsp;were seen and verified across all survey sites. The paucity of native lizards encountered during the surveys within these sites suggests little to no overlap between the dominant diurnal western fence lizard,&nbsp;</span><i>Sceloporus occidentalis</i><span>, and&nbsp;</span><i>A. sagrei</i><span>. This notable lack of overlap could indicate a potentially disturbing reality that&nbsp;</span><i>A. sagrei</i><span>&nbsp;are driving local extirpations of&nbsp;</span><i>S. occidentalis</i><span>.</span></p>","language":"English","publisher":"PeerJ","doi":"10.7717/peerj.8937","usgsCitation":"Fisher, S., Del Pinto, L.A., and Fisher, R.N., 2020, Establishment of brown anoles (Anolis sagrei) across a southern California county and potential interactions with a native lizard species: PeerJ, v. 8, e8937, 12 p., https://doi.org/10.7717/peerj.8937.","productDescription":"e8937, 12 p.","ipdsId":"IP-116801","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":457129,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.7717/peerj.8937","text":"Publisher Index Page"},{"id":375556,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","county":"Orange 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,{"id":70213050,"text":"70213050 - 2020 - Landslide disparities, flume discoveries, and Oso despair","interactions":[],"lastModifiedDate":"2020-09-09T13:34:21.549288","indexId":"70213050","displayToPublicDate":"2020-04-08T11:12:43","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":6484,"text":"Perspectives of Earth and Space Scientists","active":true,"publicationSubtype":{"id":10}},"title":"Landslide disparities, flume discoveries, and Oso despair","docAbstract":"<p><span>Landslide dynamics is the branch of science that seeks to understand the motion of landslides by applying Newton's laws. This memoir focusses on a 40‐year effort to understand motion of highly mobile—and highly lethal—landslides such as debris avalanches and debris flows. A major component of this work entailed development and operation of the U.S. Geological Survey debris flow flume, a unique, large‐scale experimental facility in Oregon. Experiments there yielded new insights that informed development of mathematical models that were aimed not only at explaining landslide dynamics but also at evaluating landslide and debris flow hazards. The most sophisticated of these models, called D‐Claw, found its first practical application during investigations of the 2014 Oso, Washington, landslide disaster. That event provided indelible lessons about the utility and sociology of science in the real world.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2019CN000117","usgsCitation":"Iverson, R.M., 2020, Landslide disparities, flume discoveries, and Oso despair: Perspectives of Earth and Space Scientists, v. 1, no. 1, e2019CN000117, 12 p., https://doi.org/10.1029/2019CN000117.","productDescription":"e2019CN000117, 12 p.","ipdsId":"IP-111886","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":457131,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2019cn000117","text":"Publisher Index Page"},{"id":378201,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","city":"Oso","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -121.95304870605469,\n              48.25576986959547\n            ],\n            [\n              -121.89262390136717,\n              48.25576986959547\n            ],\n            [\n              -121.89262390136717,\n              48.28593438872724\n            ],\n            [\n              -121.95304870605469,\n              48.28593438872724\n            ],\n            [\n              -121.95304870605469,\n              48.25576986959547\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"1","issue":"1","noUsgsAuthors":false,"publicationDate":"2020-04-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Iverson, Richard M. 0000-0002-7369-3819 riverson@usgs.gov","orcid":"https://orcid.org/0000-0002-7369-3819","contributorId":536,"corporation":false,"usgs":true,"family":"Iverson","given":"Richard","email":"riverson@usgs.gov","middleInitial":"M.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":798078,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70214526,"text":"70214526 - 2020 - How processing methodologies can distort and bias power spectral density estimates of seismic background noise","interactions":[],"lastModifiedDate":"2020-10-01T14:48:49.869932","indexId":"70214526","displayToPublicDate":"2020-04-08T09:39:20","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"How processing methodologies can distort and bias power spectral density estimates of seismic background noise","docAbstract":"<p><span>Power spectral density (PSD) estimates are widely used in seismological studies to characterize background noise conditions, assess instrument performance, and study quasi‐stationary signals that are difficult to observe in the time domain. However, these studies often utilize different processing techniques, each of which can inherently bias the resulting PSD estimates. The level of smoothing, the size of the data window, and the method used for actually estimating the spectral content can all have strong influences on PSD estimates and background noise statistics. We show that although smoothing reduces the variance of the PSD estimate, the corresponding decrease in frequency resolution can eliminate or distort features of interest. For instance, popular software packages such as Incorporated Research Institutions for Seismology Modular Utility for STAatistical kNowledge Gathering (MUSTANG) and earlier versions of Portable Array Seismic Studies of the Continental Lithosphere Quick Look eXtended (PQLX), which were designed for data quality control and are effective in that regard, are less suitable for scientific studies that require accurate resolution of spectral peaks, even for peaks as broad as the primary (</span><span class=\"inline-formula no-formula-id\">⁠<span id=\"MathJax-Element-1-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mo xmlns=&quot;&quot; form=&quot;prefix&quot;>&amp;#x223C;</mo><mn xmlns=&quot;&quot;>14</mn><mtext xmlns=&quot;&quot;>&amp;#x2009;&amp;#x2009;</mtext><mi xmlns=&quot;&quot; mathvariant=&quot;normal&quot;>s</mi></math>\"><span id=\"MathJax-Span-1\" class=\"math\"><span><span id=\"MathJax-Span-2\" class=\"mrow\"><span id=\"MathJax-Span-3\" class=\"mo\">∼</span><span id=\"MathJax-Span-4\" class=\"mn\">14</span><span id=\"MathJax-Span-5\" class=\"mtext\">  </span><span id=\"MathJax-Span-6\" class=\"mi\">s</span></span></span></span></span></span><span>&nbsp;period) and secondary (</span><span class=\"inline-formula no-formula-id\">⁠<span id=\"MathJax-Element-2-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mo xmlns=&quot;&quot; form=&quot;prefix&quot;>&amp;#x223C;</mo><mn xmlns=&quot;&quot;>7</mn><mtext xmlns=&quot;&quot;>&amp;#x2009;&amp;#x2009;</mtext><mi xmlns=&quot;&quot; mathvariant=&quot;normal&quot;>s</mi></math>\"><span id=\"MathJax-Span-7\" class=\"math\"><span><span id=\"MathJax-Span-8\" class=\"mrow\"><span id=\"MathJax-Span-9\" class=\"mo\">∼</span><span id=\"MathJax-Span-10\" class=\"mn\">7</span><span id=\"MathJax-Span-11\" class=\"mtext\">  </span><span id=\"MathJax-Span-12\" class=\"mi\">s</span></span></span></span></span></span><span>&nbsp;period) microseisms. We also demonstrate how the 1 and 3&nbsp;hr data windows used in MUSTANG and PQLX can be strongly influenced by energy generated from moderate‐size (</span><span class=\"inline-formula no-formula-id\">⁠<span id=\"MathJax-Element-3-Frame\" class=\"MathJax\" data-mathml=\"<math xmlns=&quot;http://www.w3.org/1998/Math/MathML&quot;><mi xmlns=&quot;&quot; mathvariant=&quot;bold&quot;>M</mi><mo xmlns=&quot;&quot;>&amp;gt;</mo><mo xmlns=&quot;&quot;>&amp;#x223C;</mo><mn xmlns=&quot;&quot;>4.8</mn></math>\"><span id=\"MathJax-Span-13\" class=\"math\"><span><span id=\"MathJax-Span-14\" class=\"mrow\"><span id=\"MathJax-Span-15\" class=\"mi\">M</span><span id=\"MathJax-Span-16\" class=\"mo\">&gt;</span><span id=\"MathJax-Span-17\" class=\"mo\">∼</span><span id=\"MathJax-Span-18\" class=\"mn\">4.8</span></span></span></span></span>⁠</span><span>) teleseismic earthquakes. The ubiquity of these events is likely skewing median ambient‐noise estimates by as much as 5&nbsp;dB upward, for periods of 10–50&nbsp;s at high‐quality broadband stations. Finally, we illustrate that many of the discrepancies between global low‐noise models are attributable to processing methodologies rather than fundamental differences in the underlying seismic data.</span></p>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220190212","usgsCitation":"Anthony, R.E., Ringler, A.T., Wilson, D.C., Bahavar, M., and Koper, K.D., 2020, How processing methodologies can distort and bias power spectral density estimates of seismic background noise: Seismological Research Letters, v. 91, no. 3, p. 1694-1706, https://doi.org/10.1785/0220190212.","productDescription":"13 p.","startPage":"1694","endPage":"1706","ipdsId":"IP-112932","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":378908,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"91","issue":"3","noUsgsAuthors":false,"publicationDate":"2020-04-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Anthony, Robert 0000-0001-7089-8846 reanthony@usgs.gov","orcid":"https://orcid.org/0000-0001-7089-8846","contributorId":202829,"corporation":false,"usgs":true,"family":"Anthony","given":"Robert","email":"reanthony@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":799812,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ringler, Adam T. 0000-0002-9839-4188 aringler@usgs.gov","orcid":"https://orcid.org/0000-0002-9839-4188","contributorId":145576,"corporation":false,"usgs":true,"family":"Ringler","given":"Adam","email":"aringler@usgs.gov","middleInitial":"T.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":799813,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wilson, David C. 0000-0003-2582-5159 dwilson@usgs.gov","orcid":"https://orcid.org/0000-0003-2582-5159","contributorId":145580,"corporation":false,"usgs":true,"family":"Wilson","given":"David","email":"dwilson@usgs.gov","middleInitial":"C.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":799814,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bahavar, Manochehr","contributorId":241646,"corporation":false,"usgs":false,"family":"Bahavar","given":"Manochehr","email":"","affiliations":[{"id":48379,"text":"Incorporated Research Institutions for Seismology, Data Management Center","active":true,"usgs":false}],"preferred":false,"id":799815,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Koper, Keith D.","contributorId":175489,"corporation":false,"usgs":false,"family":"Koper","given":"Keith","email":"","middleInitial":"D.","affiliations":[{"id":27579,"text":"Swiss Federal Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":799816,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70213345,"text":"70213345 - 2020 - Earthquake early warning ShakeAlert 2.0: Public rollout","interactions":[],"lastModifiedDate":"2020-09-17T14:36:17.949095","indexId":"70213345","displayToPublicDate":"2020-04-08T09:25:18","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Earthquake early warning ShakeAlert 2.0: Public rollout","docAbstract":"The ShakeAlert Earthquake Early Warning System is designed to automatically identify and characterize the initiation and rupture evolution of large earthquakes, estimate the intensity of ground shaking that will result, and deliver alerts to people and systems that may experience shaking, prior to the occurrence of shaking at their location. It is configured to issue alerts to locations within the West Coast of the U.S. In 2018, ShakeAlert 2.0 went live in a regional public test in the first phase of a general public rollout. The ShakeAlert system is now providing alerts to over sixty institutional partners in the three states of the Western U.S. where most of the nation’s earthquake risk is concentrated: California, Oregon, and Washington. The ShakeAlert 2.0 product for public alerting is a message containing a polygon enclosing a region predicted to experience Modified Mercalli Intensity ≥ IV for an earthquake of M5.0 or larger, corresponding to moderate-to-strong ground shaking. A polygon format alert is the easiest description for selective re-broadcasting mechanisms (e.g. cell towers) and is a requirement for some mass notification systems such as the Federal Emergency Management Agency’s Integrated Public Alert and Warning System. ShakeAlert 2.0 is tested using historic waveform data consisting of 60 M3.5+ and 25 M5.0+ earthquakes, in addition to other anomalous waveforms. For the historic event test, the average M5+ false alert rate/missed event rate for ShakeAlert 2.0 is 8%/16%, and the M3.5+ false alert rate/missed event rate is 10%/36.7%. Real-time performance metrics are also presented to assess how the system behaves in regions that are well-instrumented, sparsely instrumented, and offshore.","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220190245","usgsCitation":"Kohler, M., Smith, D.E., Andrews, J., Chung, A.I., Hartog, R., Henson, I., Given, D.D., deGroot, R.M., and Guiwits, S., 2020, Earthquake early warning ShakeAlert 2.0: Public rollout: Seismological Research Letters, v. 91, no. 3, p. 1763-1775, https://doi.org/10.1785/0220190245.","productDescription":"13 p.","startPage":"1763","endPage":"1775","ipdsId":"IP-114869","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":457135,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://resolver.caltech.edu/CaltechAUTHORS:20200506-122500671","text":"External Repository"},{"id":378501,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"British Columbia, California, Oregon, Washinton","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -117.42187500000001,\n              32.54681317351514\n            ],\n            [\n              -114.2578125,\n              32.69486597787505\n            ],\n            [\n              -114.08203125,\n              34.66935854524543\n            ],\n            [\n              -120.234375,\n              39.16414104768742\n            ],\n            [\n              -120.14648437499999,\n              41.902277040963696\n            ],\n            [\n              -117.0703125,\n              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]\n}","volume":"91","issue":"3","noUsgsAuthors":false,"publicationDate":"2020-04-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Kohler, Monica","contributorId":201881,"corporation":false,"usgs":false,"family":"Kohler","given":"Monica","affiliations":[{"id":13711,"text":"Caltech","active":true,"usgs":false}],"preferred":false,"id":799067,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Deborah E. 0000-0002-8317-7762 deborahsmith@usgs.gov","orcid":"https://orcid.org/0000-0002-8317-7762","contributorId":5670,"corporation":false,"usgs":true,"family":"Smith","given":"Deborah","email":"deborahsmith@usgs.gov","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":799068,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Andrews, Jennifer","contributorId":187764,"corporation":false,"usgs":false,"family":"Andrews","given":"Jennifer","affiliations":[],"preferred":false,"id":799069,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chung, Angela I.","contributorId":240899,"corporation":false,"usgs":false,"family":"Chung","given":"Angela","email":"","middleInitial":"I.","affiliations":[{"id":6609,"text":"UC Berkeley","active":true,"usgs":false}],"preferred":false,"id":799070,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hartog, Renate","contributorId":240901,"corporation":false,"usgs":false,"family":"Hartog","given":"Renate","email":"","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":799071,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Henson, Ivan","contributorId":201884,"corporation":false,"usgs":false,"family":"Henson","given":"Ivan","email":"","affiliations":[{"id":6609,"text":"UC Berkeley","active":true,"usgs":false}],"preferred":false,"id":799072,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Given, Douglas D. 0000-0002-3277-5121 doug@usgs.gov","orcid":"https://orcid.org/0000-0002-3277-5121","contributorId":201870,"corporation":false,"usgs":true,"family":"Given","given":"Douglas","email":"doug@usgs.gov","middleInitial":"D.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":799073,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"deGroot, Robert Michael 0000-0001-9995-4207","orcid":"https://orcid.org/0000-0001-9995-4207","contributorId":239577,"corporation":false,"usgs":true,"family":"deGroot","given":"Robert","email":"","middleInitial":"Michael","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":799074,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Guiwits, Stephen Robert 0000-0002-6481-6231","orcid":"https://orcid.org/0000-0002-6481-6231","contributorId":240905,"corporation":false,"usgs":true,"family":"Guiwits","given":"Stephen Robert","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":799075,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70208386,"text":"ofr20191148 - 2020 - Groundwater chloride concentrations in domestic wells and proximity to roadways in Vermont, 2011–2018","interactions":[],"lastModifiedDate":"2020-04-13T22:25:08.237454","indexId":"ofr20191148","displayToPublicDate":"2020-04-08T09:20:00","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-1148","displayTitle":"Groundwater Chloride Concentrations in Domestic Wells and Proximity to Roadways in Vermont, 2011–2018","title":"Groundwater chloride concentrations in domestic wells and proximity to roadways in Vermont, 2011–2018","docAbstract":"<p>The Vermont Department of Health and the U.S. Geological Survey analyzed the concentrations of chloride in groundwater samples collected from 4,319 domestic wells across Vermont between 2011 and 2018. Ninety of these wells were sampled twice and the remaining 4,229 were sampled once. This sample size represents approximately 4 percent of all wells in the State of Vermont. More than half of the wells sampled statewide had groundwater chloride concentrations less than 5 milligrams per liter, whereas more than 1 percent had groundwater concentrations greater than 250 milligrams per liter. Statistical analysis of this dataset revealed distinct patterns in the distribution of chloride in domestic wells. Wells closer (less than 100 meters) to a paved road had significantly higher concentrations of chloride than wells farther ( more than 100 meters) away. Also, wells in urban and in high population density areas, particularly Chittenden and Grand Isle Counties, had significantly higher concentrations of chloride and exhibited greater change in concentrations of chloride over time than wells in less populated areas. This evaluation addresses the distribution of chloride concentrations across the State, which may have adverse health impacts from water infrastructure corrosion and implications for deicing salt application at the State and local levels.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191148","collaboration":"Prepared in cooperation with the Vermont Department of Health","usgsCitation":"Levitt, J.P., and Larsen, S.L., 2020, Groundwater chloride concentrations in domestic wells and proximity to roadways in Vermont, 2011–2018: U.S. Geological Survey Open-File Report 2019–1148, 12 p., https://doi.org/10.3133/ofr20191148.","productDescription":"Report: 12 p.; Data Release","numberOfPages":"12","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-104230","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":373835,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1148/ofr20191148.pdf","text":"Report","size":"77.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1148"},{"id":373355,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9MK78K2","text":"USGS data release","linkHelpText":"Chloride concentrations and georeferenced land use variables from domestic wells in Vermont, 2011–2018"},{"id":373362,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1148/coverthb2.jpg"}],"country":"United 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 \"}}]}","contact":"<p><a href=\"mailto:dc_nweng@usgs.gov\" data-mce-href=\"mailto:dc_nweng@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/centers/new-england-water\" data-mce-href=\"https://www.usgs.gov/centers/new-england-water\">New England Water Science Center</a><br>U.S. Geological Survey<br>10 Bearfoot Road<br>Northborough, MA 01532</p>","tableOfContents":"<ul><li>Introduction</li><li>Highlights</li><li>Methods</li><li>Results</li><li>Implications</li><li>Acknowledgments</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"publishedDate":"2020-04-08","noUsgsAuthors":false,"publicationDate":"2020-04-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Levitt, Joseph P. 0000-0002-2058-9516 jlevitt@usgs.gov","orcid":"https://orcid.org/0000-0002-2058-9516","contributorId":198353,"corporation":false,"usgs":false,"family":"Levitt","given":"Joseph","email":"jlevitt@usgs.gov","middleInitial":"P.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":781681,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Larsen, Sille L. 0000-0001-9356-4726","orcid":"https://orcid.org/0000-0001-9356-4726","contributorId":218798,"corporation":false,"usgs":false,"family":"Larsen","given":"Sille","email":"","middleInitial":"L.","affiliations":[{"id":39914,"text":"Vermont Department of Health","active":true,"usgs":false}],"preferred":false,"id":781682,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70209419,"text":"70209419 - 2020 - The relation of geogenic contaminants to groundwater age, aquifer hydrologic position, water type, and redox conditions in Atlantic and Gulf Coastal Plain aquifers, eastern and south-central USA","interactions":[],"lastModifiedDate":"2020-04-08T14:08:17.456546","indexId":"70209419","displayToPublicDate":"2020-04-08T09:03:25","publicationYear":"2020","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":"The relation of geogenic contaminants to groundwater age, aquifer hydrologic position, water type, and redox conditions in Atlantic and Gulf Coastal Plain aquifers, eastern and south-central USA","docAbstract":"Groundwater age distributions developed from carbon-14 (14C), tritium (3H), and helium-4 (4He) concentrations, along with aquifer hydrologic position, water type, and redox conditions, were compared to geogenic contaminants of concern (GCOC) from 252 public-supply wells in six Atlantic and Gulf Coastal Plain unconsolidated-sediment aquifers.  Concentrations of one or more GCOCs in 168 (67%) wells exceeded MCLs (maximum contaminant levels), SMCLs (secondary MCLs), or HBSLs (health-based screening levels).  Human-health benchmark thresholds (MCLs or HBSLs) were exceeded in 31 (12%) wells, and included 0.8% for fluoride (F), 2.4% for arsenic (As), 4% for lead-210 (210Pb), and 4.8% for polonium-210 (210Po).  Values of pH increase with age and were outside the SMCL in 31% of wells (23% < 6.5 and 7.5% > 8.5, SMCL).  Among GCOCs with concentrations that increased significantly with groundwater age, the frequency of sentry threshold exceedances (i.e., one-half of MCL, SMCL, or HBSL) included 40% for dissolved solids (DS), 12% for chloride (Cl), 3.6% for F, 4.4% for As, and 9.1% for 210Po.  Iron (Fe) concentrations did not correlate with groundwater age but exceeded sentry thresholds in 29% of wells.  Groundwater age, water types, redox, pH, and GCOCs varied because of unique hydrogeologic features of the aquifers (recharge locations and geometry). As expected, primarily confined aquifers had young, oxic, low to near-neutral pH water near the outcrop (recharge area), and older, reduced, high pH water deeper and farther along flow paths.  However, unique aquifer hydrogeologic conditions, such as multiple-recharge zones produced anomalous patterns of young and old groundwater at varying depths and locations along flow paths.  Evidence for this variability is seen in disequilibrium patterns in the progression of the chemical evolution of groundwater with hydrologic position.  When hydrogeologic differences are considered, groundwater age combined with hydrologic-position data, can provide a strong basis for inferring potential occurrence of GCOCs.","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2020.137835","collaboration":"","usgsCitation":"Degnan, J.R., Lindsey, B.D., Levitt, J.P., and Szabo, Z., 2020, The relation of geogenic contaminants to groundwater age, aquifer hydrologic position, water type, and redox conditions in Atlantic and Gulf Coastal Plain aquifers, eastern and south-central USA: Science of the Total Environment, v. 723, 137835, 15 p., https://doi.org/10.1016/j.scitotenv.2020.137835.","productDescription":"137835, 15 p.","ipdsId":"IP-099819","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":457138,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2020.137835","text":"Publisher Index Page"},{"id":373839,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Gulf Coastal Plain aquifers","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -99.49218749999999,\n              27.566721430409707\n            ],\n            [\n              -99.0966796875,\n              26.509904531413927\n            ],\n            [\n              -97.470703125,\n              25.918526162075153\n            ],\n            [\n              -97.03125,\n              26.03704188651584\n            ],\n            [\n              -96.767578125,\n              27.605670826465445\n            ],\n            [\n              -94.6142578125,\n              29.036960648558267\n            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England Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":786439,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lindsey, Bruce D. 0000-0002-7180-4319 blindsey@usgs.gov","orcid":"https://orcid.org/0000-0002-7180-4319","contributorId":175346,"corporation":false,"usgs":true,"family":"Lindsey","given":"Bruce","email":"blindsey@usgs.gov","middleInitial":"D.","affiliations":[{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":786440,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Levitt, Joseph Patrick 0000-0002-2058-9516","orcid":"https://orcid.org/0000-0002-2058-9516","contributorId":223857,"corporation":false,"usgs":true,"family":"Levitt","given":"Joseph","email":"","middleInitial":"Patrick","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":786441,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Szabo, Zoltan 0000-0002-0760-9607","orcid":"https://orcid.org/0000-0002-0760-9607","contributorId":203408,"corporation":false,"usgs":true,"family":"Szabo","given":"Zoltan","affiliations":[{"id":5067,"text":"Northeast Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":786442,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70213220,"text":"70213220 - 2020 - Vegetation‐groundwater dynamics at a former uranium mill site following invasion of a biocontrol agent: A time series analysis of Landsat normalized difference vegetation index data","interactions":[],"lastModifiedDate":"2020-09-15T13:10:28.365993","indexId":"70213220","displayToPublicDate":"2020-04-08T08:00:50","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Vegetation‐groundwater dynamics at a former uranium mill site following invasion of a biocontrol agent: A time series analysis of Landsat normalized difference vegetation index data","docAbstract":"<p><span>Because groundwater recharge in dry regions is generally low, arid and semiarid environments have been considered well‐suited for long‐term isolation of hazardous materials (e.g., radioactive waste). In these dry regions, water lost (transpired) by plants and evaporated from the soil surface, collectively termed evapotranspiration (ET), is usually the primary discharge component in the water balance. Therefore, vegetation can potentially affect groundwater flow and contaminant transport at waste disposal sites. We studied vegetation health and ET dynamics at a Uranium Mill Tailings Radiation Control Act (UMTRCA) disposal site in Shiprock, New Mexico, where a floodplain alluvial aquifer was contaminated by mill effluent. Vegetation on the floodplain was predominantly deep‐rooted, non‐native tamarisk shrubs (</span><i>Tamarix</i><span>&nbsp;sp.). After the introduction of the tamarisk beetle (</span><i>Diorhabda</i><span>&nbsp;sp.) as a biocontrol agent, the health of the invasive tamarisk on the Shiprock floodplain declined. We used Landsat normalized difference vegetation index (NDVI) data to measure greenness and a remote sensing algorithm to estimate landscape‐scale ET along the floodplain of the UMTRCA site in Shiprock prior to (2000–2009) and after (2010–2018) beetle establishment. Using groundwater level data collected from 2011 to 2014, we also assessed the role of ET in explaining seasonal variations in depth to water of the floodplain. Growing season scaled NDVI decreased 30% (</span><i>p</i><span>&nbsp;&lt; .001), while ET decreased 26% from the pre‐ to post‐beetle period and seasonal ET estimates were significantly correlated with groundwater levels from 2011 to 2014 (</span><i>r</i><sup>2</sup><span>&nbsp;= .71;&nbsp;</span><i>p</i><span>&nbsp;= .009). Tamarisk greenness (a proxy for health) was significantly affected by&nbsp;</span><i>Diorhabda</i><span>&nbsp;but has partially recovered since 2012. Despite this, increased ET demand in the summer/fall period might reduce contaminant transport to the San Juan River during this period.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/hyp.13772","usgsCitation":"Jarchow, C.J., Waugh, W.J., Didan, K., Barreto-Munoz, A., Herrmann, S.M., and Nagler, P.L., 2020, Vegetation‐groundwater dynamics at a former uranium mill site following invasion of a biocontrol agent: A time series analysis of Landsat normalized difference vegetation index data: Hydrological Processes, v. 34, no. 12, p. 2739-2749, https://doi.org/10.1002/hyp.13772.","productDescription":"11 p.","startPage":"2739","endPage":"2749","ipdsId":"IP-112673","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":489705,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/hyp.13772","text":"Publisher Index Page"},{"id":378391,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","city":"Shiprock","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -108.71383666992188,\n              36.766667073939736\n            ],\n            [\n              -108.66302490234375,\n              36.766667073939736\n            ],\n            [\n              -108.66302490234375,\n              36.806261006694555\n            ],\n            [\n              -108.71383666992188,\n              36.806261006694555\n            ],\n            [\n              -108.71383666992188,\n              36.766667073939736\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"34","issue":"12","noUsgsAuthors":false,"publicationDate":"2020-04-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Jarchow, Christopher J. 0000-0002-0424-4104 cjarchow@usgs.gov","orcid":"https://orcid.org/0000-0002-0424-4104","contributorId":5813,"corporation":false,"usgs":true,"family":"Jarchow","given":"Christopher","email":"cjarchow@usgs.gov","middleInitial":"J.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":false,"id":798690,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Waugh, William J.","contributorId":196107,"corporation":false,"usgs":false,"family":"Waugh","given":"William","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":798691,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Didan, Kamel","contributorId":130999,"corporation":false,"usgs":false,"family":"Didan","given":"Kamel","email":"","affiliations":[{"id":7204,"text":"University of Arizona, Electrical and Computer Engineering","active":true,"usgs":false}],"preferred":false,"id":798692,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barreto-Munoz, Armando","contributorId":131000,"corporation":false,"usgs":false,"family":"Barreto-Munoz","given":"Armando","email":"","affiliations":[{"id":7204,"text":"University of Arizona, Electrical and Computer Engineering","active":true,"usgs":false}],"preferred":false,"id":798693,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Herrmann, Stefanie M. 0000-0002-4069-2019","orcid":"https://orcid.org/0000-0002-4069-2019","contributorId":20234,"corporation":false,"usgs":true,"family":"Herrmann","given":"Stefanie","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":798694,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nagler, Pamela L. 0000-0003-0674-103X pnagler@usgs.gov","orcid":"https://orcid.org/0000-0003-0674-103X","contributorId":1398,"corporation":false,"usgs":true,"family":"Nagler","given":"Pamela","email":"pnagler@usgs.gov","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":798634,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70210529,"text":"70210529 - 2020 - Comparison of fecal glucocorticoid metabolite concentrations in hand‐ versus parent‐reared whooping cranes (Grus americana)","interactions":[],"lastModifiedDate":"2020-08-04T14:12:43.139962","indexId":"70210529","displayToPublicDate":"2020-04-08T07:37:41","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3807,"text":"Zoo Biology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Comparison of fecal glucocorticoid metabolite concentrations in hand‐ versus parent‐reared whooping cranes (<i>Grus americana</i>)","title":"Comparison of fecal glucocorticoid metabolite concentrations in hand‐ versus parent‐reared whooping cranes (Grus americana)","docAbstract":"<div class=\"article-section__content en main\"><p>Endangered whooping cranes (<i>Grus americana<span>&nbsp;</span></i>) have been produced in captivity for reintroduction programs since the 1980s, using techniques such as artificial insemination, multiple clutching, and captive‐rearing to speed recovery efforts. Chicks are often hand‐reared (HR) by caretakers in crane costumes, socialized into groups and released together, unlike parent‐reared (PR) cranes that are raised individually by a male/female crane pair and released singly. HR cranes historically exhibit greater morbidity rates during development than PR cranes, involving musculoskeletal and respiratory system disease, among others. We hypothesized that HR crane chicks exhibit a higher baseline fecal glucocorticoid metabolite (FGM) concentrations during the development compared with PR chicks. Fecal samples were collected between 15 and 70 days of age from HR (<i>n<span>&nbsp;</span></i> = 15) and PR (<i>n<span>&nbsp;</span></i> = 8) chicks to test for differences in FGM concentrations using a radioimmunoassay technique following ethanol extraction for steroids. Linear mixed model analysis suggests increasing age of the chick was associated with an increase in FGM (<i>p<span>&nbsp;</span></i> &lt; .001). Analysis also supported the interaction between rearing strategy and sex of the crane chick (<i>p<span>&nbsp;</span></i> &lt; .01). Female PR chicks had greater FGM concentrations than all other groups (PR male,<span>&nbsp;</span><i>p<span>&nbsp;</span></i> &lt; .01; HR female,<span>&nbsp;</span><i>p<span>&nbsp;</span></i> &lt; .001; and HR male,<span>&nbsp;</span><i>p<span>&nbsp;</span></i> &lt; .001). This result suggests that there may be an effect of rearing strategy on stress physiology of whooping crane chicks, especially among females. Further research is needed to investigate whether the FGM concentrations are reflective of true differences in stress physiology of young cranes and whether this may impact health and conservation success.zo</p></div>","language":"English","publisher":"Wiley","doi":"10.1002/zoo.21541","usgsCitation":"Brown, M.E., Torkelson, M.R., Olsen, G.H., Krisp, A., and Hartup, B.K., 2020, Comparison of fecal glucocorticoid metabolite concentrations in hand‐ versus parent‐reared whooping cranes (Grus americana): Zoo Biology, v. 39, no. 4, p. 276-280, https://doi.org/10.1002/zoo.21541.","productDescription":"5 p.","startPage":"276","endPage":"280","ipdsId":"IP-107558","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":375456,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"39","issue":"4","noUsgsAuthors":false,"publicationDate":"2020-04-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Brown, Megan E.","contributorId":146367,"corporation":false,"usgs":false,"family":"Brown","given":"Megan","email":"","middleInitial":"E.","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":790535,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Torkelson, Miranda R.","contributorId":194524,"corporation":false,"usgs":false,"family":"Torkelson","given":"Miranda","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":790536,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Olsen, Glenn H. 0000-0002-7188-6203 golsen@usgs.gov","orcid":"https://orcid.org/0000-0002-7188-6203","contributorId":40918,"corporation":false,"usgs":true,"family":"Olsen","given":"Glenn","email":"golsen@usgs.gov","middleInitial":"H.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":790537,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Krisp, Ashley","contributorId":225147,"corporation":false,"usgs":false,"family":"Krisp","given":"Ashley","email":"","affiliations":[{"id":41049,"text":"School of Veterinary Medicine, University of Wisconsin, Madison, WI 53706, USA","active":true,"usgs":false}],"preferred":false,"id":790538,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hartup, Barry K.","contributorId":209630,"corporation":false,"usgs":false,"family":"Hartup","given":"Barry","email":"","middleInitial":"K.","affiliations":[{"id":16606,"text":"International Crane Foundation","active":true,"usgs":false}],"preferred":false,"id":790539,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70209463,"text":"70209463 - 2020 - Seismic and geodetic progression of the 2018 summit caldera collapse of Kīlauea Volcano","interactions":[],"lastModifiedDate":"2020-04-09T12:39:04.12856","indexId":"70209463","displayToPublicDate":"2020-04-08T07:36:18","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1427,"text":"Earth and Planetary Science Letters","active":true,"publicationSubtype":{"id":10}},"title":"Seismic and geodetic progression of the 2018 summit caldera collapse of Kīlauea Volcano","docAbstract":"The 2018 eruption of Kīlauea volcano, Hawaiʻi, resulted in a major collapse of the summit caldera along with an effusive eruption in the lower East Rift Zone. The caldera collapse comprised 62 highly similar collapse cycles of strong ground deformation and earthquake swarms that ended with a magnitude 5 collapse event and one partial cycle that did not end with a collapse event. We analyzed geodetic and seismic data to better understand how the caldera collapse progressed over 3 months of activity, focusing on the cyclical activity. We identified 3 main phases of collapse: initial ring-fault activation and small explosions (Phase 1), an eastward shift in activity and freeing of the central piston (Phase 2), and a recoupling of the piston to the reservoir followed by relatively steady behavior until the eruption’s end (Phase 3). Additionally, we observed geodetic evidence of tangential motion from the localization of the main ring fault (Phase 2) and the formation of a major peripheral ring fault on the eastern side of the collapse caldera during Phase 3. Both geodetic and seismic parameters suggest that the collapse may have had an eastward-component of motion after the ring fault system had formed. The cyclical seismic and geodetic parameters show no obvious signs that the collapse was coming to an end, with the only notable change being a significant increase in the ratio of cyclical displacement to co-collapse displacement observed during the last complete cycle on GNSS stations outside the caldera region.","language":"English","publisher":"Elsevier","doi":"10.1016/j.epsl.2020.116250","collaboration":"","usgsCitation":"Tepp, G., Hotovec-Ellis, A.J., Shiro, B., Johanson, I.A., Thelen, W., and Haney, M.M., 2020, Seismic and geodetic progression of the 2018 summit caldera collapse of Kīlauea Volcano: Earth and Planetary Science Letters, v. 540, 116250, https://doi.org/10.1016/j.epsl.2020.116250.","productDescription":"116250","ipdsId":"IP-114024","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":457144,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.epsl.2020.116250","text":"Publisher Index Page"},{"id":373856,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Kīlauea Volcano","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -155.31097412109372,\n              19.391477141932153\n            ],\n            [\n              -155.2313232421875,\n              19.391477141932153\n            ],\n            [\n              -155.2313232421875,\n              19.43454305903574\n            ],\n            [\n              -155.31097412109372,\n              19.43454305903574\n            ],\n            [\n              -155.31097412109372,\n              19.391477141932153\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"540","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Tepp, Gabrielle 0000-0001-5388-5138","orcid":"https://orcid.org/0000-0001-5388-5138","contributorId":206305,"corporation":false,"usgs":true,"family":"Tepp","given":"Gabrielle","email":"","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":786571,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hotovec-Ellis, Alicia J. 0000-0003-1917-0205","orcid":"https://orcid.org/0000-0003-1917-0205","contributorId":211785,"corporation":false,"usgs":true,"family":"Hotovec-Ellis","given":"Alicia","email":"","middleInitial":"J.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":786572,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shiro, Brian 0000-0001-8756-288X","orcid":"https://orcid.org/0000-0001-8756-288X","contributorId":204040,"corporation":false,"usgs":true,"family":"Shiro","given":"Brian","email":"","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":786573,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Johanson, Ingrid A. 0000-0002-6049-2225","orcid":"https://orcid.org/0000-0002-6049-2225","contributorId":215613,"corporation":false,"usgs":true,"family":"Johanson","given":"Ingrid","email":"","middleInitial":"A.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":786574,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thelen, Weston 0000-0003-2534-5577","orcid":"https://orcid.org/0000-0003-2534-5577","contributorId":215530,"corporation":false,"usgs":true,"family":"Thelen","given":"Weston","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":786575,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Haney, Matthew M. 0000-0003-3317-7884 mhaney@usgs.gov","orcid":"https://orcid.org/0000-0003-3317-7884","contributorId":172948,"corporation":false,"usgs":true,"family":"Haney","given":"Matthew","email":"mhaney@usgs.gov","middleInitial":"M.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":786576,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70209557,"text":"70209557 - 2020 - Testing ecosystem accounting in the United States: A case study for the Southeast","interactions":[],"lastModifiedDate":"2020-09-01T19:55:33.306925","indexId":"70209557","displayToPublicDate":"2020-04-08T07:05:35","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1477,"text":"Ecosystem Services","active":true,"publicationSubtype":{"id":10}},"title":"Testing ecosystem accounting in the United States: A case study for the Southeast","docAbstract":"Ecosystem accounts, as formalized by the System of Environmental-Economic Accounting Experimental Ecosystem Accounts (SEEA EEA), have been compiled in a number of countries, yet there have been few attempts to develop them for the U.S.  We explore the potential for U.S. ecosystem accounting by compiling ecosystem extent, condition, and ecosystem services supply and use accounts for a ten-state region in the Southeast.  The pilot accounts address air quality, water quality, biodiversity, carbon storage, recreation, and pollination for selected years from 2001 to 2015.  Results illustrate how information from ecosystem accounts can contribute to policy and decision-making.  Using an example from Atlanta, we also show how ecosystem accounts can be considered alongside other SEEA accounts to give a more complete picture of a local area’s environmental-economic trends.  The process by which we determined where to place metrics within the accounting framework, which was strongly informed by the National Ecosystem Services Classification System (NESCS), can provide guidance for future ecosystem accounts in the U.S. and other countries.  Finally, we identify knowledge gaps that limit the inclusion of certain ecosystem services in the accounts and suggest future research that can close these gaps and improve future U.S. ecosystem accounts.","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecoser.2020.101099","usgsCitation":"Warnell, K., Russell, M.J., Rhodes, C., Bagstad, K.J., Olander, L.P., Nowak, D., Poudel, R., Glynn, P.D., Hass, J.L., Hiribayashi, S., Ingram, J.C., Matuszak, J., Oleson, K.L., Posner, S.M., and Villa, F., 2020, Testing ecosystem accounting in the United States: A case study for the Southeast: Ecosystem Services, v. 43, 101099, 18 p., https://doi.org/10.1016/j.ecoser.2020.101099.","productDescription":"101099, 18 p.","ipdsId":"IP-108492","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true}],"links":[{"id":457146,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecoser.2020.101099","text":"Publisher Index Page"},{"id":437031,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9VET1YX","text":"USGS data release","linkHelpText":"Data Release for Testing ecosystem accounting in the United States: A case study for the Southeast - 2022 Updates (version 2.0, February 2023)"},{"id":437030,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9MF0K9X","text":"USGS data release","linkHelpText":"Data Release for Testing ecosystem accounting in the United States: A case study for the Southeast"},{"id":373944,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Missouri, Arkansas, Louisiana, Tennessee, Mississippi, Alabama, North Carolina, South Carolina, Georgia, 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,{"id":70209466,"text":"70209466 - 2020 - Describing historical habitat use of a native fish-Cisco (Coregonus artedi)-In Lake Michigan between 1930 and 1932","interactions":[],"lastModifiedDate":"2020-07-09T14:47:53.051322","indexId":"70209466","displayToPublicDate":"2020-04-08T07:04:27","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Describing historical habitat use of a native fish-Cisco (<i>Coregonus artedi</i>)-In Lake Michigan between 1930 and 1932","title":"Describing historical habitat use of a native fish-Cisco (Coregonus artedi)-In Lake Michigan between 1930 and 1932","docAbstract":"<p>With the global-scale loss of biodiversity, current restoration programs have been often required as part of conservation plans for species richness and ecosystem integrity. The restoration of pelagic-oriented cisco (<i>Coregonus artedi</i>) has been an interest of Lake Michigan managers because it may increase the diversity and resilience of the fish assemblages and conserve the integrity of the ecosystems in a changing environment. To inform restoration, we described historical habitat use of cisco by analyzing a unique fishery-independent dataset collected in 1930–1932 by the U.S. Bureau of Fisheries’ first research vessel Fulmar and a commercial catch dataset reported by the State of Michigan in the same period, both based on gear fished on the bottom. Our results confirmed that the two major embayments, Green Bay and Grand Traverse Bay, were important habitats for cisco and suggest that cisco could complete the entire lifecycle within either of the Bays as there was no lack of summer feeding and fall spawning habitats. Seasonally, our results showed that cisco stayed in nearshore waters in spring, migrated to offshore waters in summer, and then migrated back to nearshore waters in fall for spawning. The results also suggest that in summer, most ciscoes were in waters with bottom depths of 20–70 m, but the highest cisco density occurred in waters with a bottom depth around 40 m. We highlight the importance of embayment habitats to cisco restoration and the seasonal migration pattern of cisco identified in this study, which suggests that a restored cisco population can diversify the food web by occupying different habitats from the exotic fishes that now dominate the pelagic waters of Lake Michigan.</p>","language":"English","publisher":"PLoS ONE","doi":"10.1371/journal.pone.0231420","usgsCitation":"Kao, Y., Bunnell, D., Eshenroder, R.L., and Murray, D.N., 2020, Describing historical habitat use of a native fish-Cisco (Coregonus artedi)-In Lake Michigan between 1930 and 1932: PLoS ONE, v. 15, no. 4, e0231420, 21 p., https://doi.org/10.1371/journal.pone.0231420.","productDescription":"e0231420, 21 p.","ipdsId":"IP-112754","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":457149,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index 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Yu-Chun","contributorId":35626,"corporation":false,"usgs":false,"family":"Kao","given":"Yu-Chun","affiliations":[{"id":6649,"text":"University of Michigan, School of Natural Resources and Environment","active":true,"usgs":false}],"preferred":false,"id":786603,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bunnell, David 0000-0003-3521-7747","orcid":"https://orcid.org/0000-0003-3521-7747","contributorId":217344,"corporation":false,"usgs":true,"family":"Bunnell","given":"David","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":786604,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Eshenroder, Randy L.","contributorId":177867,"corporation":false,"usgs":false,"family":"Eshenroder","given":"Randy","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":786605,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Murray, Devin N. 0000-0003-1429-6669","orcid":"https://orcid.org/0000-0003-1429-6669","contributorId":223909,"corporation":false,"usgs":false,"family":"Murray","given":"Devin","email":"","middleInitial":"N.","affiliations":[{"id":37387,"text":"University of Michigan","active":true,"usgs":false}],"preferred":false,"id":786606,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70208493,"text":"ofr20201015 - 2020 - Defining technology operational readiness for the 3D Elevation Program—A plan for investment, incubation, and adoption","interactions":[],"lastModifiedDate":"2020-04-15T16:15:08.574329","indexId":"ofr20201015","displayToPublicDate":"2020-04-07T17:50:00","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-1015","displayTitle":"Defining Technology Operational Readiness for the 3D Elevation Program—A Plan for Investment, Incubation, and Adoption","title":"Defining technology operational readiness for the 3D Elevation Program—A plan for investment, incubation, and adoption","docAbstract":"<p>The 3D Elevation Program (3DEP) is an acquisition strategy that uses data from commercial remote sensing technologies to create three-dimensional maps of the United States and U.S. territories. Currently, light detection and ranging and interferometric synthetic aperture radar are the two commercial technologies being used to provide three-dimensional information to meet the program’s operational requirements. This is because there is not a well-established process for vendors of new and novel instruments to know when and how 3DEP will accept their technologies into the 3DEP portfolio. The purpose of this plan is to provide a strategy and rules for communication between 3DEP and commercial partners interested in proposing their modalities for use in the program. To accomplish this, 3DEP will also consider how it invests in new technologies and how it disseminates data to and categorizes data for the broader community and the public.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/ofr20201015","collaboration":"","usgsCitation":"Stoker, J.M., 2020, Defining technology operational readiness for the 3D Elevation Program—A plan for investment, incubation, and adoption: U.S. Geological Survey Open-File Report 2020–1015, 7 p.,  \nhttps://doi.org/ 10.3133/ ofr20201015.","productDescription":"iv, 7 p.","onlineOnly":"Y","ipdsId":"IP-110726","costCenters":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"links":[{"id":373798,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1015/ofr20201015.pdf","text":"Report","size":"932 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1015"},{"id":373797,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1015/coverthb2.jpg"}],"contact":"<p>Director, <a href=\"https://www.usgs.gov/core-science-systems/national-geospatial-program\" data-mce-href=\"https://www.usgs.gov/core-science-systems/national-geospatial-program\">National Geospatial Program</a><br>U.S. Geological Survey<br>MS-511<br>12201 Sunrise Valley Drive<br>Reston, VA 20192</p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>The 3D Elevation Program Operational Readiness Levels</li><li>Maturation/Gates</li><li>Implementation Plan—Next Steps</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"publishedDate":"2020-04-07","noUsgsAuthors":false,"publicationDate":"2020-04-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Stoker, Jason M. 0000-0003-2455-0931 jstoker@usgs.gov","orcid":"https://orcid.org/0000-0003-2455-0931","contributorId":3021,"corporation":false,"usgs":true,"family":"Stoker","given":"Jason","email":"jstoker@usgs.gov","middleInitial":"M.","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":782145,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70206191,"text":"sir20195120 - 2020 - Rio Grande transboundary integrated hydrologic model and water-availability analysis, New Mexico and Texas, United States, and northern Chihuahua, Mexico","interactions":[{"subject":{"id":70197406,"text":"ofr20181091 - 2018 - Rio Grande transboundary integrated hydrologic model and water-availability analysis, New Mexico and Texas, United States, and Northern Chihuahua, Mexico","indexId":"ofr20181091","publicationYear":"2018","noYear":false,"title":"Rio Grande transboundary integrated hydrologic model and water-availability analysis, New Mexico and Texas, United States, and Northern Chihuahua, Mexico"},"predicate":"SUPERSEDED_BY","object":{"id":70206191,"text":"sir20195120 - 2020 - Rio Grande transboundary integrated hydrologic model and water-availability analysis, New Mexico and Texas, United States, and northern Chihuahua, Mexico","indexId":"sir20195120","publicationYear":"2020","noYear":false,"title":"Rio Grande transboundary integrated hydrologic model and water-availability analysis, New Mexico and Texas, United States, and northern Chihuahua, Mexico"},"id":1}],"lastModifiedDate":"2022-04-25T19:02:23.235988","indexId":"sir20195120","displayToPublicDate":"2020-04-07T14:58:16","publicationYear":"2020","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":"2019-5120","displayTitle":"Rio Grande Transboundary Integrated Hydrologic Model and Water-Availability Analysis, New Mexico and Texas, United States, and Northern Chihuahua, Mexico","title":"Rio Grande transboundary integrated hydrologic model and water-availability analysis, New Mexico and Texas, United States, and northern Chihuahua, Mexico","docAbstract":"<p>Changes in population, agricultural development and practices (including shifts to more water-intensive crops), and climate variability are increasing demands on available water resources, particularly groundwater, in one of the most productive agricultural regions in the Southwest—the Rincon and Mesilla Valley parts of Rio Grande Valley, Doña Ana and Sierra Counties, New Mexico, and El Paso County, Texas. The goal of this study was to produce an integrated hydrological simulation model to help evaluate water-management strategies, including conjunctive use of surface water and groundwater for historical conditions, and to support long-term planning for the Rio Grande Project. This report describes model construction and applications by the U.S.&nbsp;Geological Survey, working in cooperation and collaboration with the Bureau of Reclamation.</p><p>This model, the Rio Grande Transboundary Integrated Hydrologic Model, simulates the most important natural and human components of the hydrologic system, including selected components related to variations in climate, thereby providing a reliable assessment of surface-water and groundwater conditions and processes that can inform water users and help improve planning for future conditions and sustained operations of the Rio Grande Project (RGP) by the Bureau of Reclamation. Model development included a revision of the conceptual model of the flow system, construction of a Transboundary Rio Grande Watershed Model (TRGWM) water-balance model using the Basin Characterization Model, and construction of an integrated hydrologic flow model with MODFLOW-One-Water Hydrologic Flow Model version 2 (referred to as MF-OWHM2). The hydrologic models were developed for and calibrated to historical conditions of water and land use, and parameters were adjusted so that simulated values closely matched available measurements (calibration). The calibrated model was then used to assess the use and movement of water in the Rincon Valley, Mesilla Basin, and northern part of the Conejos-Médanos Basin, with the entire region referred to as the “Transboundary Rio Grande” or TRG. These tools provide a means to understand hydrologic system response to the evolution of water use in the region, its availability, and potential operational constraints of the RGP.</p><p>The conceptual model identified surface-water and groundwater inflows and outflows that included the movement and use of water both in natural and in anthropogenic systems. The groundwater-flow system is characterized by a layered geologic sedimentary sequence combined with the effects of groundwater pumping, operation of the RGP, natural runoff and recharge, and the application of irrigation water at the land surface that is captured and reused in an extensive network of canals and drains as part of the conjunctive use of water in the&nbsp;region.</p><p>Historical groundwater-level fluctuations followed a cyclic pattern that were aligned with climate cycles, which collectively resulted in alternating periods of wet or dry years. Periods of drought that persisted for one or more years are associated with low surface-water availability that resulted in higher rates of groundwater-level decline. Rates of groundwater-level decline also increased during periods of agricultural intensification, which necessitated increasing use of groundwater as a source of irrigation water. Agriculture in the area was initially dominated by alfalfa and cotton, but since 1970 more water-intensive pecan orchards and vegetable production have become more common. Groundwater levels substantially declined in subregions where drier climate combined with increased demand, resulting in periods of reduced streamflows.</p><p>Most of the groundwater was recharged in the Rio Grande Valley floor, and most of the pumpage and aquifer storage depletion was in Mesilla Basin agricultural subregions. A cyclic imbalance between inflows and outflows resulted in the modeled cyclic depletion (groundwater withdrawals in excess of natural recharge) of the groundwater basin during the 75-year simulation period of 1940–2014. Changes in groundwater storage can vary considerably from year to year, depending on land use, pumpage, and climate conditions. Climatic drivers of wet and dry years can greatly affect all inflows, outflows, and water use. Although streamflow and, to a minor extent, precipitation during inter-decadal wet-year periods replenished the groundwater historically, contemporary water use and storage depletion could have reduced the effects of these major recharge events. The average net groundwater flow-rate deficit for 1953–2014 was estimated to be about 1,090 acre-feet per year.<br></p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195120","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Hanson, R.T., Ritchie, A.B., Boyce, S.E., Galanter, A.E., Ferguson, I.A., Flint, L.E., Flint, A., and Henson, W.R., 2020, Rio Grande transboundary integrated hydrologic model and water-availability analysis, New Mexico and Texas, United States, and northern Chihuahua, Mexico: U.S. Geological Survey Scientific Investigations Report 2019–5120, 186 p., https://doi.org/10.3133/sir20195120.","productDescription":"Report: x, 186 p.; Application Site; Data Release","numberOfPages":"186","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-102507","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":399603,"rank":5,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109906.htm"},{"id":373766,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9J9NYND","linkHelpText":"Digital hydrologic and geospatial data for the Rio Grande transboundary integrated hydrologic model and water-availability analysis, New Mexico and Texas, United States, and Northern Chihuahua, Mexico"},{"id":373765,"rank":3,"type":{"id":4,"text":"Application Site"},"url":"https://ca.water.usgs.gov/sustainable-groundwater-management/gwm/archive1/SIR2019-5120_RGTIHM_Rio_Grande.7z"},{"id":373695,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5120/sir20195120.pdf","text":"Report","size":"25 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":373694,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5120/coverthb.jpg"}],"country":"Mexico, United States","state":"Chihuahua, New Mexico, Texas","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -107.2942,\n              31.5833\n            ],\n            [\n              -106.3333,\n              31.5833\n            ],\n            [\n              -106.3333,\n              33\n            ],\n            [\n              -107.2942,\n              33\n            ],\n            [\n              -107.2942,\n              31.5833\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_ca@usgs.gov\" data-mce-href=\"mailto:dc_ca@usgs.gov\">Director</a>,<br><a href=\"https://ca.water.usgs.gov/\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://ca.water.usgs.gov\">California Water Science Center</a><br><a href=\"https://usgs.gov/\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://usgs.gov\">U.S. Geological Survey</a><br>6000 J Street, Placer Hall<br>Sacramento, California 95819</p>","tableOfContents":"<p></p><ul><li>Abstract</li><li>Introduction</li><li>Description of the Study Area</li><li>Hydrologic System</li><li>Model Development</li><li>Calibration and Sensitivity—Rio Grande Transboundary Integrated Hydrologic Model</li><li>Hydrologic Flow Budgets—Rio Grande Transboundary Integrated Hydrologic Model</li><li>Model Limitations, Uncertainty, and Potential Improvements</li><li>Summary and Conclusions</li><li>Acknowledgments</li><li>References Cited</li></ul><p></p>","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2020-04-07","noUsgsAuthors":false,"publicationDate":"2020-04-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Hanson, Randall T. 0000-0002-9819-7141 rthanson@usgs.gov","orcid":"https://orcid.org/0000-0002-9819-7141","contributorId":801,"corporation":false,"usgs":true,"family":"Hanson","given":"Randall","email":"rthanson@usgs.gov","middleInitial":"T.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":773800,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ritchie, Andre B. 0000-0003-1289-653X","orcid":"https://orcid.org/0000-0003-1289-653X","contributorId":214611,"corporation":false,"usgs":true,"family":"Ritchie","given":"Andre","email":"","middleInitial":"B.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":773801,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Boyce, Scott E. 0000-0003-0626-9492 seboyce@usgs.gov","orcid":"https://orcid.org/0000-0003-0626-9492","contributorId":4766,"corporation":false,"usgs":true,"family":"Boyce","given":"Scott","email":"seboyce@usgs.gov","middleInitial":"E.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":773802,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Galanter, Amy E. 0000-0002-2960-0136","orcid":"https://orcid.org/0000-0002-2960-0136","contributorId":205393,"corporation":false,"usgs":true,"family":"Galanter","given":"Amy","email":"","middleInitial":"E.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":773803,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ferguson, Ian A. iferguson@usbr.gov","contributorId":205350,"corporation":false,"usgs":false,"family":"Ferguson","given":"Ian","email":"iferguson@usbr.gov","middleInitial":"A.","affiliations":[{"id":6736,"text":"Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":773804,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Flint, Lorraine E. 0000-0002-7868-441X lflint@usgs.gov","orcid":"https://orcid.org/0000-0002-7868-441X","contributorId":1184,"corporation":false,"usgs":true,"family":"Flint","given":"Lorraine","email":"lflint@usgs.gov","middleInitial":"E.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":773805,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Flint, Alan L. 0000-0002-5118-751X aflint@usgs.gov","orcid":"https://orcid.org/0000-0002-5118-751X","contributorId":1492,"corporation":false,"usgs":true,"family":"Flint","given":"Alan","email":"aflint@usgs.gov","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":786146,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Henson, Wesley R. 0000-0003-4962-5565 whenson@usgs.gov","orcid":"https://orcid.org/0000-0003-4962-5565","contributorId":384,"corporation":false,"usgs":true,"family":"Henson","given":"Wesley","email":"whenson@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":773806,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70205106,"text":"sir20185158 - 2020 - Hydrogeologic framework and simulation of predevelopment groundwater flow, eastern Abu Dhabi Emirate, United Arab Emirates","interactions":[],"lastModifiedDate":"2020-04-08T11:09:10.81413","indexId":"sir20185158","displayToPublicDate":"2020-04-07T14:15:00","publicationYear":"2020","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":"2018-5158","displayTitle":"Hydrogeologic Framework and Simulation of Predevelopment Groundwater Flow, Eastern Abu Dhabi Emirate, United Arab Emirates","title":"Hydrogeologic framework and simulation of predevelopment groundwater flow, eastern Abu Dhabi Emirate, United Arab Emirates","docAbstract":"<p>Groundwater in eastern Abu Dhabi in the United Arab Emirates is an important resource that is widely used for irrigation and domestic supplies in rural areas. The U.S. Geological Survey and the Environment Agency—Abu Dhabi cooperated on an investigation to integrate existing hydrogeologic information and to answer questions about regional groundwater resources in Abu Dhabi by developing a numerical groundwater flow model based on MODFLOW–2005 software. The groundwater flow model developed in this investigation provides an improved understanding of groundwater conditions in the eastern region of the Emirate of Abu Dhabi. The flow model simulates steady-state predevelopment conditions from before the rapid growth of modern pumping in the 1980s and was calibrated with 1,342 groundwater-level observations by use of automated and manual calibration techniques. The calibrated model provides good accuracy, with a mean error of 0.50 meters and a standard error of 5.92 meters for simulated groundwater levels. The results of the regional water budget simulation show that gap recharge, which is groundwater inflow through mountain-front gap alluvium, is the greatest source of water to the aquifer. In the base simulation scenario, gap recharge represents 80 percent of total inflow (119,470 of 149,403 cubic meters per day) and the greatest outflow from the aquifer is from evapotranspiration (93 percent of total outflow). Model scenario and sensitivity results reveal a need for data that more thoroughly and more accurately describe aquifer hydraulic conductivity, inflow to the aquifer from the Oman Mountains, and recharge from precipitation on the piedmont. Additional long-term aquifer pumping test observations would improve understanding of aquifer hydraulic conductivity, which would also improve model accuracy. Future studies can modify the model to understand the effect of land-use change and water use on groundwater supplies and simulate more complex groundwater flow conditions in a predictive mode.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185158","collaboration":"Prepared in cooperation with the Environment Agency—Abu Dhabi","usgsCitation":"Eggleston, J.R., Mack, T.J., Imes, J.L., Kress, W., Woodward, D.W., and Bright, D.J., 2020, Hydrogeologic framework and simulation of predevelopment groundwater flow, eastern Abu Dhabi Emirate, United Arab Emirates: U.S. Geological Survey Scientific Investigations Report 2018–5158, 48 p., https://doi.org/10.3133/sir20185158.","productDescription":"Report: viii, 48 p.; Data Release","numberOfPages":"60","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-088658","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":373295,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5158/coverthb.jpg"},{"id":373296,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5158/sir20185158.pdf","text":"Report","size":"6.17 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5158"},{"id":373297,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ZWZISB","text":"USGS data release","description":"USGS data release","linkHelpText":"MODFLOW-2005 Groundwater Flow Model to Simulate Predevelopment Groundwater Flow in the Eastern Abu Dhabi Emirate, United Arab Emirates"}],"country":"United Arab Emirates","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[51.57952,24.2455],[51.75744,24.29407],[51.79439,24.01983],[52.57708,24.17744],[53.40401,24.15132],[54.008,24.12176],[54.69302,24.79789],[55.43902,25.43915],[56.07082,26.05546],[56.26104,25.71461],[56.39685,24.92473],[55.88623,24.92083],[55.80412,24.2696],[55.98121,24.13054],[55.52863,23.9336],[55.52584,23.52487],[55.23449,23.11099],[55.20834,22.70833],[55.0068,22.49695],[52.00073,23.00115],[51.61771,24.01422],[51.57952,24.2455]]]},\"properties\":{\"name\":\"United Arab Emirates\"}}]}","contact":"<p><a href=\"mailto:dc_nweng@usgs.gov\" data-mce-href=\"mailto:dc_nweng@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/centers/new-england-water\" data-mce-href=\"https://www.usgs.gov/centers/new-england-water\">New England Water Science Center</a><br>U.S. Geological Survey<br>10 Bearfoot Road<br>Northborough, MA 01532</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Environmental Setting</li><li>Hydrogeologic Framework</li><li>Predevelopment Groundwater Conditions</li><li>Groundwater Model Development</li><li>Simulation of Predevelopment Groundwater Flow</li><li>Summary and Conclusions</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"publishedDate":"2020-04-07","noUsgsAuthors":false,"publicationDate":"2020-04-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Eggleston, Jack R. 0000-0001-6633-3041","orcid":"https://orcid.org/0000-0001-6633-3041","contributorId":204628,"corporation":false,"usgs":true,"family":"Eggleston","given":"Jack R.","affiliations":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true},{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":770047,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mack, Thomas J. 0000-0002-0496-3918","orcid":"https://orcid.org/0000-0002-0496-3918","contributorId":218727,"corporation":false,"usgs":true,"family":"Mack","given":"Thomas J.","affiliations":[{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":770048,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Imes, Jeffrey L. 0000-0001-5220-5866 jimes@usgs.gov","orcid":"https://orcid.org/0000-0001-5220-5866","contributorId":218728,"corporation":false,"usgs":true,"family":"Imes","given":"Jeffrey","email":"jimes@usgs.gov","middleInitial":"L.","affiliations":[{"id":349,"text":"International Water Resources Branch","active":true,"usgs":true}],"preferred":true,"id":770049,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kress, Wade 0000-0002-6833-028X","orcid":"https://orcid.org/0000-0002-6833-028X","contributorId":203539,"corporation":false,"usgs":true,"family":"Kress","given":"Wade","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":770050,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Woodward, Dennis W. 0000-0001-6608-7020 woody@usgs.gov","orcid":"https://orcid.org/0000-0001-6608-7020","contributorId":218729,"corporation":false,"usgs":true,"family":"Woodward","given":"Dennis","email":"woody@usgs.gov","middleInitial":"W.","affiliations":[{"id":349,"text":"International Water Resources Branch","active":true,"usgs":true}],"preferred":true,"id":770051,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bright, Daniel J. 0000-0001-5530-4501 djbright@usgs.gov","orcid":"https://orcid.org/0000-0001-5530-4501","contributorId":218145,"corporation":false,"usgs":false,"family":"Bright","given":"Daniel","email":"djbright@usgs.gov","middleInitial":"J.","affiliations":[{"id":349,"text":"International Water Resources Branch","active":true,"usgs":true},{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":770052,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70216817,"text":"70216817 - 2020 - Comparison of settlement-era vegetation reconstructions for STEPPS and REVEALS pollen–vegetation models in the northeastern United States","interactions":[],"lastModifiedDate":"2020-12-09T12:55:37.432205","indexId":"70216817","displayToPublicDate":"2020-04-07T14:01:25","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3218,"text":"Quaternary Research","active":true,"publicationSubtype":{"id":10}},"title":"Comparison of settlement-era vegetation reconstructions for STEPPS and REVEALS pollen–vegetation models in the northeastern United States","docAbstract":"<p><span>Reconstructions of prehistoric vegetation composition help establish natural baselines, variability, and trajectories of forest dynamics before and during the emergence of intensive anthropogenic land use. Pollen–vegetation models (PVMs) enable such reconstructions from fossil pollen assemblages using process-based representations of taxon-specific pollen production and dispersal. However, several PVMs and variants now exist, and the sensitivity of vegetation inferences to PVM selection, variant, and calibration domain is poorly understood. Here, we compare the reconstructions, parameter estimates, and structure of a Bayesian hierarchical PVM, STEPPS, both to observations and to REVEALS, a widely used PVM, for the pre–Euro-American settlement-era vegetation in the northeastern United States (NEUS). We also compare NEUS-based STEPPS parameter estimates to those for the upper midwestern United States (UMW). Both PVMs predict the observed macroscale patterns of vegetation composition in the NEUS; however, reconstructions of minor taxa are less accurate and predictions for some taxa differ between PVMs. These differences can be attributed to intermodel differences in structure and parameter estimates. Estimates of pollen productivity from STEPPS broadly agree with estimates produced for use in REVEALS, while comparison between pollen dispersal parameter estimates shows no significant relationship. STEPPS parameter estimates are similar between the UMW and NEUS, suggesting that STEPPS parameter estimates are transferable between floristically similar regions and scales.</span></p>","language":"English","publisher":"Cambridge University Press","doi":"10.1017/qua.2019.81","usgsCitation":"Trachsel, M., Dawson, A., Paciorek, C.J., Williams, J.W., McLachlan, J.S., Cogbill, C.V., Foster, D.R., Goring, S.J., Jackson, S., Oswald, W.W., and Shuman, B.N., 2020, Comparison of settlement-era vegetation reconstructions for STEPPS and REVEALS pollen–vegetation models in the northeastern United States: Quaternary Research, v. 95, p. 23-42, https://doi.org/10.1017/qua.2019.81.","productDescription":"20 p.","startPage":"23","endPage":"42","ipdsId":"IP-111664","costCenters":[{"id":41166,"text":"Southwest Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":497090,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"text":"External Repository"},{"id":381131,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Connecticut, Maine, Massachusetts, New Hampshire, New Jersey, New York, Pennsylvania, Rhode Island, Vermont","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -66.884765625,\n              44.77793589631623\n            ],\n            [\n              -67.25830078125,\n              45.19752230305682\n            ],\n            [\n              -67.43408203124999,\n              45.182036837015886\n            ],\n            [\n              -67.43408203124999,\n              45.62940492064501\n            ],\n            [\n              -67.74169921875,\n              45.72152152227954\n            ],\n          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,{"id":70208710,"text":"fs20203016 - 2020 - Assessing geohazards to the Denali National Park road with geologic mapping","interactions":[],"lastModifiedDate":"2022-04-20T18:43:23.96299","indexId":"fs20203016","displayToPublicDate":"2020-04-07T11:00:00","publicationYear":"2020","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2020-3016","displayTitle":"Assessing Geohazards to the Denali National Park Road with Geologic Mapping","title":"Assessing geohazards to the Denali National Park road with geologic mapping","docAbstract":"<p>Denali National Park (DENA) is home to iconic and breathtaking landscapes surrounding the tallest mountain range in North America, the Alaska Range. The park, which covers 6 million acres, is a major draw for tourism and recreation, making it an important economic engine for central Alaska. However, the geologic forces that created the beautiful, steep landscape of DENA also make it prone to geologic hazards (geohazards) like landslides, debris flows, and earthquakes. DENA has only one major road, called the Park Road, that serves nearly all of its infrastructure. The success of DENA as a visitor destination, an economic engine, and a safe environment for visitors, residents, and staff relies on the resilience of this road, making it a major transportation lifeline for the region.</p><p>Since 2017, the National Park Service and the U.S. Geological Survey National Cooperative Geologic Mapping Program have partnered to produce a new high-resolution geologic map of the Park Road corridor to identify and address ongoing geohazards affecting DENA infrastructure. In the area of Polychrome Overlook, this map is being used to guide a new route for the Park Road around an area of landslide-prone slopes, where ongoing slumping is costing National Park Service millions of dollars in annual road maintenance costs. Beyond this area, the map serves as a park resource to assess geohazard risk in future infrastructure and management decisions. Geologic mapping is also fueling new research in understanding the geologic and tectonic history of DENA, while training a new generation of geologic mappers through the USGS EDMAP program.</p><p><br data-mce-bogus=\"1\"></p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20203016","collaboration":"Prepared  in collaboration with the National Park Service","usgsCitation":"Hudson, A.M., Ruleman, C.A., Capps, D.M., 2020, Assessing geohazards to the Denali National Park Road with geologic mapping:  U.S. Geological Survey Fact Sheet 2020–3016, 2 p., https://doi.org/10.3133/fs20203016.","productDescription":"2 p.","onlineOnly":"N","ipdsId":"IP-113547","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":399201,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109903.htm"},{"id":373732,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2020/3016/coverthb.jpg"},{"id":373733,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2020/3016/fs20203016.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2020-3016"}],"country":"United States","state":"Alaksa","otherGeospatial":"Denali National Park","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -149.8431,\n              63.5278\n            ],\n            [\n              -149.3,\n              63.5278\n            ],\n            [\n              -149.3,\n              63.75\n            ],\n            [\n              -149.8431,\n              63.75\n            ],\n            [\n              -149.8431,\n              63.5278\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, <a href=\"http://www.usgs.gov/centers/gecsc/\" data-mce-href=\"http://www.usgs.gov/centers/gecsc/\"> Geosciences and Environmental Change Science Center</a><br>U.S. Geological Survey<br>Box 25046, MS-980<br>Denver, CO 80225-0046</p>","tableOfContents":"<ul><li>Denali National Park Road— An Economic Lifeline in Alaska</li><li>U.S. Geological Survey Surficial Geologic Mapping— Identifying Geohazards in the Park Road Corridor</li><li>Park Road Reroute Planning near Polychrome Overlook</li><li>Collaborative Research—Active Faults and Glaciation</li><li>Acknowledgments</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"publishedDate":"2020-04-07","noUsgsAuthors":false,"publicationDate":"2020-04-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Hudson, Adam M. 0000-0002-3387-9838 ahudson@usgs.gov","orcid":"https://orcid.org/0000-0002-3387-9838","contributorId":195419,"corporation":false,"usgs":true,"family":"Hudson","given":"Adam","email":"ahudson@usgs.gov","middleInitial":"M.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":783114,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ruleman, Chester A. 0000-0002-1503-4591 cruleman@usgs.gov","orcid":"https://orcid.org/0000-0002-1503-4591","contributorId":1264,"corporation":false,"usgs":true,"family":"Ruleman","given":"Chester","email":"cruleman@usgs.gov","middleInitial":"A.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":783115,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Capps, Denny M","contributorId":222771,"corporation":false,"usgs":false,"family":"Capps","given":"Denny","email":"","middleInitial":"M","affiliations":[{"id":40598,"text":"Denali National Park, National Park Service","active":true,"usgs":false}],"preferred":false,"id":783116,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
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