{"pageNumber":"283","pageRowStart":"7050","pageSize":"25","recordCount":46681,"records":[{"id":70207453,"text":"70207453 - 2019 - The effect of stress changes on time-dependent earthquake probabilities for the central Wasatch Fault Zone, Utah, USA","interactions":[],"lastModifiedDate":"2019-12-19T14:43:31","indexId":"70207453","displayToPublicDate":"2019-07-25T14:41:09","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1803,"text":"Geophysical Journal International","active":true,"publicationSubtype":{"id":10}},"title":"The effect of stress changes on time-dependent earthquake probabilities for the central Wasatch Fault Zone, Utah, USA","docAbstract":"Static and quasi-static Coulomb stress changes produced by large earthquakes can modify the probability of occurrence of subsequent events on neighboring faults. This approach is based on physical (Coulomb stress changes) and statistical (probability calculations) models, which are influenced by the quality and quantity of data available in the study region. Here, we focus on the Wasatch Fault Zone (WFZ), a well-studied active normal fault system having abundant geologic and paleoseismological data. Paleoseismological trench investigations of the WFZ indicate that at least 24 large, surface-faulting earthquakes have ruptured the fault’s five central, 35–59-km long segments since ~7 ka. Our goal is to determine if the stress changes due to the youngest paleoevents have significantly modified the present-day probability of occurrence of large earthquakes on each of the segments. For each segment, we modeled the cumulative (coseismic + postseismic) Coulomb stress changes (∆CFScum) due to earthquakes younger than the most recent event on the segment in question and applied the resulting values to the time-dependent probability calculations. Results from the Coulomb stress modeling suggest that the Brigham City, Salt Lake City, and Provo segments have accumulated ∆CFScum larger than 10 bars, whereas the Weber segment has experienced a stress decrease of 5 bars, in the scenario of recent rupture of the Great Salt Lake fault to the west. Probability calculations predict high probability of occurrence for the Brigham City and Salt Lake City segments, due to their long elapsed times (>1-2 ka) when compared to the Weber, Provo, and Nephi segments (< 1 ka). The range of calculated coefficients of variation (CV) has a large influence on the final probabilities, mostly in the case of the Brigham City segment. Finally, when the Coulomb stress and the probability models are combined, our results indicate that the ∆CFScum resulting from earthquakes postdating the youngest events on each of the five segments significantly affects the probability calculations for three of the segments: Brigham City, Salt Lake City, and Provo. The probability of occurrence of a large earthquake in the next 50 years on these three segments may therefore be underestimated if a time-independent approach, or a time-dependent approach that does not consider ∆CFS, is adopted.","language":"English","publisher":"Oxford Academic","doi":"10.1093/gji/ggz336","usgsCitation":"Verdecchia, A., Carena, S., Pace, B., and DuRoss, C., 2019, The effect of stress changes on time-dependent earthquake probabilities for the central Wasatch Fault Zone, Utah, USA: Geophysical Journal International, v. 219, no. 2, p. 1065-1081, https://doi.org/10.1093/gji/ggz336.","productDescription":"17 p.","startPage":"1065","endPage":"1081","ipdsId":"IP-105869","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":467422,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://eartharxiv.org/bw6ur/","text":"External Repository"},{"id":370511,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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 \"}}]}","volume":"219","issue":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-07-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Verdecchia, A.","contributorId":221418,"corporation":false,"usgs":false,"family":"Verdecchia","given":"A.","affiliations":[{"id":40369,"text":"Institute of Geology, Mineralogy and Geophysics, Ruhr-University Bochum, Bochum, Germany; Department of Earth and Environmental Sciences, Ludwig-Maximilians University, Munich, Germany","active":true,"usgs":false}],"preferred":false,"id":778107,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carena, S.","contributorId":221419,"corporation":false,"usgs":false,"family":"Carena","given":"S.","email":"","affiliations":[{"id":40370,"text":"Department of Earth and Environmental Sciences, Ludwig-Maximilians University, Munich, Germany","active":true,"usgs":false}],"preferred":false,"id":778108,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pace, B.","contributorId":221420,"corporation":false,"usgs":false,"family":"Pace","given":"B.","email":"","affiliations":[{"id":40371,"text":"DiSPUTer, Universita' G. d'Annunzio di Chieti-Pescara, Chieti, Italy","active":true,"usgs":false}],"preferred":false,"id":778109,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"DuRoss, Christopher 0000-0002-6963-7451 cduross@usgs.gov","orcid":"https://orcid.org/0000-0002-6963-7451","contributorId":152321,"corporation":false,"usgs":true,"family":"DuRoss","given":"Christopher","email":"cduross@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":778110,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70204345,"text":"ds1116 - 2019 - Water-level data for the Albuquerque Basin and adjacent areas, central New Mexico, period of record through September 30, 2018","interactions":[],"lastModifiedDate":"2021-08-26T14:16:26.144304","indexId":"ds1116","displayToPublicDate":"2019-07-25T12:57:30","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"1116","displayTitle":"Water-Level Data for the Albuquerque Basin and Adjacent Areas, Central New Mexico, Period of Record Through September 30, 2018","title":"Water-level data for the Albuquerque Basin and adjacent areas, central New Mexico, period of record through September 30, 2018","docAbstract":"<p>The Albuquerque Basin, located in central New Mexico, is about 100 miles long and 25–40 miles wide. The basin is hydrologically defined as the extent of consolidated and unconsolidated deposits of Tertiary and Quaternary age that encompasses the structural Rio Grande Rift between San Acacia to the south and Cochiti Lake to the north. A 20-percent population increase in the basin from 1990 to 2000 and a 22-percent population increase from 2000 to 2010 resulted in an increased demand for water in areas within the basin. Drinking-water supplies throughout the basin were obtained solely from groundwater resources until December 2008, when the Albuquerque Bernalillo County Water Utility Authority (ABCWUA) began treatment and distribution of surface water from the Rio Grande through the San Juan-Chama Drinking Water Project.</p><p>An initial network of wells was established by the U.S. Geological Survey (USGS) in cooperation with the City of Albuquerque from April 1982 through September 1983 to monitor changes in groundwater levels throughout the Albuquerque Basin. In 1983, this network consisted of 6 wells with analog-to-digital recorders and 27 wells where water levels were measured monthly. As of 2018, the network consisted of 120 wells and piezometers. (A piezometer is a specialized well open to a specific depth in the aquifer, often of small diameter and nested with other piezometers open to different depths.) The USGS, in cooperation with the ABCWUA, the New Mexico Office of the State Engineer, and Bernalillo County, measures water levels from the 120 wells and piezometers in the network; this report, prepared in cooperation with the ABCWUA, presents water-level data collected by USGS personnel at those 120 sites through water year 2018 (October 1, 2017, through September 30, 2018). Water levels that were collected from wells in previous water years were published in previous USGS reports.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1116","collaboration":"Prepared in cooperation with the Albuquerque Bernalillo County Water Utility Authority","usgsCitation":"Ritchie, A.B., and Galanter, A.E., 2019, Water-level data for the Albuquerque Basin and adjacent areas, central New Mexico, period of record through September 30, 2018 (ver. 1.1, August 2021): U.S. Geological Survey Data Series 1116, 40 p., https://doi.org/10.3133/ds1116.","productDescription":"iii, 40 p.","numberOfPages":"49","onlineOnly":"Y","ipdsId":"IP-108049","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":365903,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1116/coverthb2.jpg"},{"id":388360,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1116/ds1116.pdf","text":"Report","size":"5.57 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1116"},{"id":388361,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/ds/1116/versionHist.txt","text":"Version History","size":"554 B","linkFileType":{"id":2,"text":"txt"},"description":"DS 1116 Verson History"}],"country":"United States","state":"New Mexico","otherGeospatial":"Albuquerque Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -107,\n              34.85\n            ],\n            [\n              -106.375,\n              34.85\n            ],\n            [\n              -106.375,\n              35.4\n            ],\n            [\n              -107,\n              35.4\n            ],\n            [\n              -107,\n              34.85\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","edition":"Version 1.1: August 2021","contact":"<p><a href=\"mailto:%20dc_nm@usgs.gov\" data-mce-href=\"mailto:%20dc_nm@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/centers/nm-water\" data-mce-href=\"https://www.usgs.gov/centers/nm-water\">New Mexico Water Science Center</a><br>U.S. Geological Survey<br>6700 Edith Blvd. NE<br>Albuquerque, NM 87113</p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Water-Level Data</li><li>Acknowledgments</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2019-07-25","revisedDate":"2021-08-25","noUsgsAuthors":false,"publicationDate":"2019-07-25","publicationStatus":"PW","contributors":{"authors":[{"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":766445,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Galanter, Amy E. 0000-0002-2960-0136","orcid":"https://orcid.org/0000-0002-2960-0136","contributorId":214612,"corporation":false,"usgs":true,"family":"Galanter","given":"Amy E.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":766446,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70204456,"text":"70204456 - 2019 - Alongshore momentum balance over shoreface-connected ridges, Fire Island, NY","interactions":[],"lastModifiedDate":"2019-07-26T09:51:59","indexId":"70204456","displayToPublicDate":"2019-07-25T12:47:59","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1333,"text":"Continental Shelf Research","active":true,"publicationSubtype":{"id":10}},"title":"Alongshore momentum balance over shoreface-connected ridges, Fire Island, NY","docAbstract":"Hydrodynamic and hydrographic data collected on the inner shelf of Fire Island, NY, over a region of shoreface-connected ridges (SFCRs) are used to describe wind-driven circulation over uneven topographies along relatively straight coastlines. The data revealed a predominantly alongshore flow, under westward wind forcing, with localized offshore current veering over the SFCR crests associated with an onshore veering over the adjacent troughs. Momentum balance analysis of the observations revealed that local acceleration, advective acceleration, and bottom stress are balanced by wind stress and regional (>100 km) pressure gradient force. Numerical model results based on simulations of an idealized SFCR bathymetry, as in Warner et al. (2014) but forced with the observed winds, are used to verify the experimentally derived results and constraint inaccuracies in the momentum balance term relationships revealed using the field data. As with previous SFCR studies, our experimental results indicate a current veering over ridge crests. Veering is driven primarily by two processes: cross-shore variation of alongshore advective acceleration which creates cross-shore pressure gradient and drives flow (described as a Bernoulli-like process), and, bottom frictional-torque.\nA synthesis of the numerical and experimental data revealed that the total pressure gradient force can be considered as the sum of a local and a regional pressure gradient force. The former is correlated with the alongshore advective acceleration that develops over the crest of the ridges resembling a Bernoulli-like pressure-flow relationship. The regional pressure gradient force is related to wind stress with which maintains a strong, negative relationship. The realistic driving force analysis revealed the different contributions of the local and regional scale pressure gradients. Under realistic and variable wind conditions the regional pressure gradients are more important and the influence of the local scale pressure gradient increases as the flow reaches quasi steady-state conditions. A time scale of 6 hours was defined as the temporal scale required for the local pressure gradients to have an effect","language":"English","publisher":"Elsevier","doi":"10.1016/j.csr.2019.07.005","usgsCitation":"Ofsthun, C., Wu, X., Voulgaris, G., and Warner, J., 2019, Alongshore momentum balance over shoreface-connected ridges, Fire Island, NY: Continental Shelf Research, v. 186, p. 21-33, https://doi.org/10.1016/j.csr.2019.07.005.","productDescription":"13 p.","startPage":"21","endPage":"33","ipdsId":"IP-093237","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":467423,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.csr.2019.07.005","text":"Publisher Index Page"},{"id":365951,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Fire Island","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -73.31863403320312,\n              40.66709790906187\n            ],\n            [\n              -72.46444702148438,\n              40.66709790906187\n            ],\n            [\n              -72.46444702148438,\n              40.85537053192494\n            ],\n            [\n              -73.31863403320312,\n              40.85537053192494\n            ],\n            [\n              -73.31863403320312,\n              40.66709790906187\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"186","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ofsthun, Conor","contributorId":217600,"corporation":false,"usgs":false,"family":"Ofsthun","given":"Conor","email":"","affiliations":[],"preferred":false,"id":767148,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wu, Xiaodong","contributorId":217601,"corporation":false,"usgs":false,"family":"Wu","given":"Xiaodong","email":"","affiliations":[],"preferred":false,"id":767149,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Voulgaris, George","contributorId":26377,"corporation":false,"usgs":false,"family":"Voulgaris","given":"George","email":"","affiliations":[{"id":27143,"text":"University of South Carolina, Columbia, SC","active":true,"usgs":false}],"preferred":false,"id":767150,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Warner, John C. 0000-0002-3734-8903 jcwarner@usgs.gov","orcid":"https://orcid.org/0000-0002-3734-8903","contributorId":2681,"corporation":false,"usgs":true,"family":"Warner","given":"John C.","email":"jcwarner@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":767151,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70204755,"text":"70204755 - 2019 - Using a Bayesian network to understand the importance of coastal storms and undeveloped landscapes for the creation and maintenance of early successional habitat","interactions":[],"lastModifiedDate":"2019-08-15T11:11:11","indexId":"70204755","displayToPublicDate":"2019-07-25T10:50:49","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Using a Bayesian network to understand the importance of coastal storms and undeveloped landscapes for the creation and maintenance of early successional habitat","docAbstract":"<p><span>Coastal storms have consequences for human lives and infrastructure but also create important early successional habitats for myriad species. For example, storm-induced overwash creates nesting habitat for shorebirds like piping plovers (</span><i>Charadrius melodus</i><span>). We examined how piping plover habitat extent and location changed on barrier islands in New York, New Jersey, and Virginia after Hurricane Sandy made landfall following the 2012 breeding season. We modeled nesting habitat using a nest presence/absence dataset that included characterizations of coastal morphology and vegetation. Using a Bayesian network, we predicted nesting habitat for each study site for the years 2010/2011, 2012, and 2014/2015 based on remotely sensed spatial datasets (e.g., lidar, orthophotos). We found that Hurricane Sandy increased piping plover habitat by 9 to 300% at 4 of 5 study sites but that one site saw a decrease in habitat by 27%. The amount, location, and longevity of new habitat appeared to be influenced by the level of human development at each site. At three of the five sites, the amount of habitat created and the time new habitat persisted were inversely related to the amount of development. Furthermore, the proportion of new habitat created in high-quality overwash was inversely related to the level of development on study areas, from 17% of all new habitat in overwash at one of the most densely developed sites to 80% of all new habitat at an undeveloped site. We also show that piping plovers exploited new habitat after the storm, with 14–57% of all nests located in newly created habitat in the 2013 breeding season. Our results quantify the importance of storms in creating and maintaining coastal habitats for beach-nesting species like piping plovers, and these results suggest a negative correlation between human development and beneficial ecological impacts of these natural disturbances.</span></p>","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0209986","usgsCitation":"Zeigler, S.L., Gutierrez, B.T., Sturdivant, E.J., Catlin, D.H., Fraser, J., Hecht, A., Karpanty, S.M., Plant, N.G., and Thieler, E.R., 2019, Using a Bayesian network to understand the importance of coastal storms and undeveloped landscapes for the creation and maintenance of early successional habitat: PLoS ONE, v. 14, no. 7, e0209986, 30 p., https://doi.org/10.1371/journal.pone.0209986.","productDescription":"e0209986, 30 p.","ipdsId":"IP-092113","costCenters":[{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science 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]\n}","volume":"14","issue":"7","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2019-07-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Zeigler, Sara L. 0000-0002-5472-769X szeigler@usgs.gov","orcid":"https://orcid.org/0000-0002-5472-769X","contributorId":169601,"corporation":false,"usgs":true,"family":"Zeigler","given":"Sara","email":"szeigler@usgs.gov","middleInitial":"L.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":768437,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gutierrez, Benjamin T. 0000-0002-1879-7893 bgutierrez@usgs.gov","orcid":"https://orcid.org/0000-0002-1879-7893","contributorId":2924,"corporation":false,"usgs":true,"family":"Gutierrez","given":"Benjamin","email":"bgutierrez@usgs.gov","middleInitial":"T.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":768438,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sturdivant, Emily J. 0000-0002-2420-3115 esturdivant@usgs.gov","orcid":"https://orcid.org/0000-0002-2420-3115","contributorId":175325,"corporation":false,"usgs":true,"family":"Sturdivant","given":"Emily","email":"esturdivant@usgs.gov","middleInitial":"J.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":768439,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Catlin, Daniel H.","contributorId":87859,"corporation":false,"usgs":false,"family":"Catlin","given":"Daniel","email":"","middleInitial":"H.","affiliations":[{"id":33131,"text":"Dept of Fish and Wildlife Conservation, Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":768440,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fraser, James D.","contributorId":86686,"corporation":false,"usgs":false,"family":"Fraser","given":"James D.","affiliations":[{"id":33131,"text":"Dept of Fish and Wildlife Conservation, Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":768441,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hecht, A.","contributorId":99525,"corporation":false,"usgs":false,"family":"Hecht","given":"A.","email":"","affiliations":[],"preferred":false,"id":768442,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Karpanty, Sarah M.","contributorId":63307,"corporation":false,"usgs":false,"family":"Karpanty","given":"Sarah","email":"","middleInitial":"M.","affiliations":[{"id":33131,"text":"Dept of Fish and Wildlife Conservation, Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":768443,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Plant, Nathaniel G. 0000-0002-5703-5672 nplant@usgs.gov","orcid":"https://orcid.org/0000-0002-5703-5672","contributorId":3503,"corporation":false,"usgs":true,"family":"Plant","given":"Nathaniel","email":"nplant@usgs.gov","middleInitial":"G.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true}],"preferred":true,"id":768444,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Thieler, E. Robert 0000-0003-4311-9717 rthieler@usgs.gov","orcid":"https://orcid.org/0000-0003-4311-9717","contributorId":2488,"corporation":false,"usgs":true,"family":"Thieler","given":"E.","email":"rthieler@usgs.gov","middleInitial":"Robert","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":768445,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70204891,"text":"70204891 - 2019 - Endless forams: >34,000 modern planktonic foraminiferal images for taxonomic training and automated species recognition using convolutional neural networks","interactions":[],"lastModifiedDate":"2019-08-21T14:58:57","indexId":"70204891","displayToPublicDate":"2019-07-23T14:58:11","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5790,"text":"Paleoceanography and Paleoclimatology","active":true,"publicationSubtype":{"id":10}},"title":"Endless forams: >34,000 modern planktonic foraminiferal images for taxonomic training and automated species recognition using convolutional neural networks","docAbstract":"Accurate planktonic foraminiferal species identification is central to many paleoceanographic studies, from selecting specific species for geochemical research to elucidating the biotic dynamics of microfossil communities relevant to physical oceanographic processes and interconnected phenomena such as climate change. However, species identification varies among taxonomic schools, few resources exist to train students in the difficult task of discerning amongst closely related species, and the number of taxonomic experts is limited. Here, we take the first steps towards removing these rate-limiting steps by generating the first extensive image library of modern planktonic foraminifera, providing taxonomic training tools and resources, and automating species-level taxonomic identification of planktonic foraminifera via machine learning using convolution neural networks. Taxonomic experts identified 34,640 images of modern planktonic foraminifera to the species level. These images are served as species exemplars through the online portal Endless Forams (endlessforams.org) and a taxonomic training portal hosted on the citizen science platform Zooniverse (zooniverse.org/projects/ahsiang/endless-forams/). A supervised machine learning classifier was then trained with more than 24,000 images of planktonic foraminifera and tested using the remaining ~10,000 images (i.e., the validation set). The best classifier provided the correct species name for an image in the validation set 87.4% of the time. Together, these resources provide a rigorous set of training tools in modern planktonic foraminiferal taxonomy and a means of rapidly generating assemblage data via machine learning in future studies.","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2019PA003612","usgsCitation":"Hsiang, A.Y., Brombacher, A., Costa Rillo, M., Mleneck-Vautravers, M.J., Connett, S., Lordsmith, S., Jentzen, A., Henehan, M.J., Metcalfe, B., Fenton, I., Wade, B., Fox, L., Meilland, J., Davis, C., Baranowski, U., Groeneveld, J., Edgar, K.M., Movellan, A., Aze, T., Dowsett, H.J., Miller, G., Rios, N., and Hull, P.M., 2019, Endless forams: >34,000 modern planktonic foraminiferal images for taxonomic training and automated species recognition using convolutional neural networks: Paleoceanography and Paleoclimatology, v. 34, p. 1157-1177, https://doi.org/10.1029/2019PA003612.","productDescription":"21 p.","startPage":"1157","endPage":"1177","ipdsId":"IP-106285","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":467427,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2019pa003612","text":"Publisher Index Page"},{"id":366806,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":366798,"type":{"id":15,"text":"Index Page"},"url":"https://doi.org/10.1029/2019PA003612"}],"volume":"34","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2019-07-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Hsiang, Allison Y.","contributorId":218284,"corporation":false,"usgs":false,"family":"Hsiang","given":"Allison","email":"","middleInitial":"Y.","affiliations":[{"id":39794,"text":"Swedish Museum of Natural History","active":true,"usgs":false}],"preferred":false,"id":768906,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brombacher, Anieke","contributorId":218285,"corporation":false,"usgs":false,"family":"Brombacher","given":"Anieke","email":"","affiliations":[{"id":39795,"text":"National Oceanographic Centre Southampton","active":true,"usgs":false}],"preferred":false,"id":768907,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Costa Rillo, Marina","contributorId":218286,"corporation":false,"usgs":false,"family":"Costa Rillo","given":"Marina","email":"","affiliations":[{"id":37250,"text":"Natural History Museum, London","active":true,"usgs":false}],"preferred":false,"id":768908,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mleneck-Vautravers, Maryline J.","contributorId":218287,"corporation":false,"usgs":false,"family":"Mleneck-Vautravers","given":"Maryline","email":"","middleInitial":"J.","affiliations":[{"id":27136,"text":"University of Cambridge","active":true,"usgs":false}],"preferred":false,"id":768909,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Connett, Stephen","contributorId":174313,"corporation":false,"usgs":false,"family":"Connett","given":"Stephen","email":"","affiliations":[],"preferred":false,"id":768910,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lordsmith, Sian","contributorId":218288,"corporation":false,"usgs":false,"family":"Lordsmith","given":"Sian","email":"","affiliations":[{"id":17940,"text":"Cardiff University","active":true,"usgs":false}],"preferred":false,"id":768911,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jentzen, Anna","contributorId":218289,"corporation":false,"usgs":false,"family":"Jentzen","given":"Anna","email":"","affiliations":[{"id":39796,"text":"Max Planck Institute for Chemistry","active":true,"usgs":false}],"preferred":false,"id":768912,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Henehan, Michael 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Bridget","contributorId":218293,"corporation":false,"usgs":false,"family":"Wade","given":"Bridget","affiliations":[{"id":6957,"text":"University College London","active":true,"usgs":false}],"preferred":false,"id":768916,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Fox, Lyndsey","contributorId":218294,"corporation":false,"usgs":false,"family":"Fox","given":"Lyndsey","email":"","affiliations":[{"id":37250,"text":"Natural History Museum, London","active":true,"usgs":false}],"preferred":false,"id":768917,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Meilland, Julie","contributorId":218295,"corporation":false,"usgs":false,"family":"Meilland","given":"Julie","email":"","affiliations":[{"id":39799,"text":"MARUM Center for Marine and Environmental Sciences","active":true,"usgs":false}],"preferred":false,"id":768918,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Davis, Catherine V.","contributorId":218296,"corporation":false,"usgs":false,"family":"Davis","given":"Catherine V.","affiliations":[{"id":37804,"text":"University of South Carolina","active":true,"usgs":false}],"preferred":false,"id":768919,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Baranowski, Ulrike","contributorId":218297,"corporation":false,"usgs":false,"family":"Baranowski","given":"Ulrike","email":"","affiliations":[{"id":7157,"text":"University of Birmingham","active":true,"usgs":false}],"preferred":false,"id":768920,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Groeneveld, Jeroen","contributorId":218298,"corporation":false,"usgs":false,"family":"Groeneveld","given":"Jeroen","email":"","affiliations":[{"id":39799,"text":"MARUM Center for Marine and Environmental Sciences","active":true,"usgs":false}],"preferred":false,"id":768921,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Edgar, Kirsty M.","contributorId":218299,"corporation":false,"usgs":false,"family":"Edgar","given":"Kirsty","email":"","middleInitial":"M.","affiliations":[{"id":7157,"text":"University of Birmingham","active":true,"usgs":false}],"preferred":false,"id":768922,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Movellan, Aurore","contributorId":218300,"corporation":false,"usgs":false,"family":"Movellan","given":"Aurore","email":"","affiliations":[{"id":39800,"text":"Ocean Zoom","active":true,"usgs":false}],"preferred":false,"id":768923,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Aze, Tracy","contributorId":218301,"corporation":false,"usgs":false,"family":"Aze","given":"Tracy","email":"","affiliations":[{"id":13344,"text":"University of Leeds","active":true,"usgs":false}],"preferred":false,"id":768924,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Dowsett, Harry J. 0000-0003-1983-7524 hdowsett@usgs.gov","orcid":"https://orcid.org/0000-0003-1983-7524","contributorId":949,"corporation":false,"usgs":true,"family":"Dowsett","given":"Harry","email":"hdowsett@usgs.gov","middleInitial":"J.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":768905,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Miller, Giles","contributorId":218302,"corporation":false,"usgs":false,"family":"Miller","given":"Giles","email":"","affiliations":[{"id":37250,"text":"Natural History Museum, London","active":true,"usgs":false}],"preferred":false,"id":768925,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Rios, Nelson","contributorId":218303,"corporation":false,"usgs":false,"family":"Rios","given":"Nelson","email":"","affiliations":[{"id":39801,"text":"Yale Peabody Museum of Natural History","active":true,"usgs":false}],"preferred":false,"id":768926,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Hull, Pincelli M.","contributorId":218304,"corporation":false,"usgs":false,"family":"Hull","given":"Pincelli","email":"","middleInitial":"M.","affiliations":[{"id":37550,"text":"Yale University","active":true,"usgs":false}],"preferred":false,"id":768927,"contributorType":{"id":1,"text":"Authors"},"rank":23}]}}
,{"id":70204896,"text":"70204896 - 2019 - The importance of simulation assumptions when evaluating detectability in population models","interactions":[],"lastModifiedDate":"2019-08-26T09:43:48","indexId":"70204896","displayToPublicDate":"2019-07-23T14:36:51","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"The importance of simulation assumptions when evaluating detectability in population models","docAbstract":"Population monitoring is important for investigating a variety of ecological questions, and N-mixture models are increasingly used to model population size (N) and trends (lambda) while estimating detectability (p) from repeated counts within primary periods (when populations are closed to changes). Extending these models to dynamic processes with serial dependence across primary periods may relax the closure assumption, but simulations to evaluate models and inform effort (e.g., number of repeated counts) typically assume p is constant or random across sites and years. Thus, it is unknown how these models perform under scenarios where trends in p confound inferences on N and lambda, and conclusions regarding effort may be overoptimistic. Here, we used global positioning system (GPS) data from greater sage-grouse (Centrocercus urophasianus) to inform simulations of the detection process for lek counts of this species, and we created scenarios with and without linear annual trends in p. We then compared estimates of N and lambda from hierarchical population models either fit with single maximum counts or with detectability estimated from repeated counts (dynamic N-mixture models). We also explored using auxiliary data to correct counts for variation in detectability. Uncorrected count models consistently underestimated N by >50% whereas N-mixture models without auxiliary data underestimated N to a lesser degree due to unmodeled heterogeneity in p such as age. Nevertheless, estimates of lambda from both types of models were unbiased and similar for scenarios without trends in p. When p declined systematically across years, uncorrected count models underestimated lambda whereas N-mixture models estimated lambda with little bias when all sites were counted repeatedly. Auxiliary data also reduced bias in parameter estimates. Evaluating population models using scenarios with systematic variation in p may better reveal potential biases and inform effort than simulations that assume p is constant or random. Dynamic N-mixture models can distinguish between trends in p and N, but also require repeated counts within primary periods for accurate estimates. Auxiliary data may be useful when researchers lack repeated counts, wish to monitor more sites less intensively, or require unbiased estimates of N.","language":"English","publisher":"Wiley","doi":"10.1002/ecs2.2791","usgsCitation":"Monroe, A., Wann, G.T., Aldridge, C.L., and Coates, P.S., 2019, The importance of simulation assumptions when evaluating detectability in population models: Ecosphere, v. 10, no. 7, e02791, 16 p., https://doi.org/10.1002/ecs2.2791.","productDescription":"e02791, 16 p.","ipdsId":"IP-097255","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":467428,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.2791","text":"Publisher Index Page"},{"id":437382,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P91L28PG","text":"USGS data release","linkHelpText":"Simulation to evaluate response of population models to annual trends in detectability"},{"id":366805,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","issue":"7","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-07-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Monroe, Adrian P. 0000-0003-0934-8225 amonroe@usgs.gov","orcid":"https://orcid.org/0000-0003-0934-8225","contributorId":152209,"corporation":false,"usgs":true,"family":"Monroe","given":"Adrian P.","email":"amonroe@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":768938,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wann, Gregory T. 0000-0001-9076-7819 wanng@usgs.gov","orcid":"https://orcid.org/0000-0001-9076-7819","contributorId":3855,"corporation":false,"usgs":true,"family":"Wann","given":"Gregory","email":"wanng@usgs.gov","middleInitial":"T.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":768939,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Aldridge, Cameron L. 0000-0003-3926-6941 aldridgec@usgs.gov","orcid":"https://orcid.org/0000-0003-3926-6941","contributorId":191773,"corporation":false,"usgs":true,"family":"Aldridge","given":"Cameron","email":"aldridgec@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":768940,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Coates, Peter S. 0000-0003-2672-9994 pcoates@usgs.gov","orcid":"https://orcid.org/0000-0003-2672-9994","contributorId":3263,"corporation":false,"usgs":true,"family":"Coates","given":"Peter","email":"pcoates@usgs.gov","middleInitial":"S.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":768941,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70205299,"text":"70205299 - 2019 - Giving ecological meaning to satellite-derived fire severity metrics across North American forests","interactions":[],"lastModifiedDate":"2026-01-21T16:28:34.513942","indexId":"70205299","displayToPublicDate":"2019-07-23T14:29:19","publicationYear":"2019","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":"Giving ecological meaning to satellite-derived fire severity metrics across North American forests","docAbstract":"<p><span>Satellite-derived spectral indices such as the relativized burn ratio (RBR) allow fire severity maps to be produced in a relatively straightforward manner across multiple fires and broad spatial extents. These indices often have strong relationships with field-based measurements of fire severity, thereby justifying their widespread use in management and science. However, satellite-derived spectral indices have been criticized because their non-standardized units render them difficult to interpret relative to on-the-ground fire effects. In this study, we built a Random Forest model describing a field-based measure of fire severity, the composite burn index (CBI), as a function of multiple spectral indices, a variable representing spatial variability in climate, and latitude. CBI data primarily representing forested vegetation from 263 fires (8075 plots) across the United States and Canada were used to build the model. Overall, the model performed well, with a cross-validated R</span><sup>2</sup><span>&nbsp;of 0.72, though there was spatial variability in model performance. The model we produced allows for the direct mapping of CBI, which is more interpretable compared to spectral indices. Moreover, because the model and all spectral explanatory variables were produced in Google Earth Engine, predicting and mapping of CBI can realistically be undertaken on hundreds to thousands of fires. We provide all necessary code to execute the model and produce maps of CBI in Earth Engine. This study and its products will be extremely useful to managers and scientists in North America who wish to map fire effects over large landscapes or regions.</span></p>","language":"English","publisher":"MDPI","doi":"10.3390/rs11141735","usgsCitation":"Parks, S., Holsinger, L.M., Koontz, M.J., Collins, L.S., Whitman, E., Parisien, M., Loehman, R.A., Barnes, J.L., Bourdon, J., Boucher, J., Boucher, Y., Caprio, A.C., Collingwood, A., Hall, R., Park, J., Saperstein, L., Smetanka, C., Smith, R.J., and Soverel, N., 2019, Giving ecological meaning to satellite-derived fire severity metrics across North American forests: Remote Sensing, v. 11, 1735, 19 p., https://doi.org/10.3390/rs11141735.","productDescription":"1735, 19 p.","ipdsId":"IP-109412","costCenters":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"links":[{"id":460326,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs11141735","text":"Publisher 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National Park, PO Box 168, 22 Stable Street, Yellowstone National Park, WY, 82190, USA","active":true,"usgs":false}],"preferred":false,"id":770808,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Soverel, Nick","contributorId":218977,"corporation":false,"usgs":false,"family":"Soverel","given":"Nick","email":"","affiliations":[{"id":39948,"text":"Self-employed","active":true,"usgs":false}],"preferred":false,"id":770809,"contributorType":{"id":1,"text":"Authors"},"rank":19}]}}
,{"id":70203800,"text":"ofr20191062 - 2019 - Monitoring breeding and survival of ring-necked pheasant (Phasianus colchicus) in the Sacramento Valley, Sacramento-San Joaquin River Delta, and Klamath Basin, northern California—Five-year summary, 2013–17","interactions":[],"lastModifiedDate":"2019-07-25T10:24:32","indexId":"ofr20191062","displayToPublicDate":"2019-07-23T14:26:27","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-1062","displayTitle":"Monitoring Breeding and Survival of Ring-Necked Pheasant (<em>Phasianus colchicus</em>) in the Sacramento Valley, Sacramento-San Joaquin River Delta, and Klamath Basin, Northern California—Five-Year Summary, 2013–17","title":"Monitoring breeding and survival of ring-necked pheasant (Phasianus colchicus) in the Sacramento Valley, Sacramento-San Joaquin River Delta, and Klamath Basin, northern California—Five-year summary, 2013–17","docAbstract":"<p class=\"p1\">The U.S. Geological Survey Western Ecological Research Center, Pheasants Forever, Mandeville Island Duck Club, and the California Department of Fish and Wildlife collaborated in a reconnaissance study to monitor populations of ring-necked pheasant (<i>Phasianus colchicus</i>) using radio-telemetry in the Sacramento Valley, Sacramento-San Joaquin River Delta, and Klamath Basin of northern California. The purpose of this study was to provide agencies and private landowners with a framework of decision-support tools to help manage pheasant populations in California. During winter, spring, and autumn of 2013–17, we radio- or Global Positioning System-marked 227 female pheasant across six study sites. Data collection was focused on investigating nest-site and brood-rearing habitat selection, examining avian predator composition, and estimating population vital rates to improve our understanding of pheasant population dynamics and to identify factors that may contribute to decreases in pheasant populations in California. The cumulative annual adult survival probability across all sites during 2013–17 was 27.6 percent (95-percent confidence interval [CI], 21.9–33.6), and the cumulative nest and brood survival probabilities were 34.5 percent (95-percent CI, 27.0–42.2) and 54.2 percent (95-percent CI, 43.7–63.5), respectively. Evidence from microhabitat surveys completed at nest-sites, brood locations, and random locations suggested that marked female pheasant tended to select increasing vertical cover and residual vegetation cover and tended to avoid areas of increasing bare ground cover regardless of life-history stage. However, females at nest-sites selected increasing grass cover and height, whereas brood-rearing females tended to select increasing forb cover and height. Only perennial grass cover and perennial grass height were shown to have a positive influence on nest survival, which suggests that increasing perennial grass cover in areas occupied by pheasant may increase nest survival. Analysis of environmental factors linked to vital rate information are ongoing and will continue with investigations at increased spatial scales (that is, macro-habitat) to develop integrated population models that can&nbsp;incorporate abundance estimates from crow count data with vital rates from telemetry data. This report includes results from 5 years of data collection and should be interpreted with caution, as these findings are preliminary.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191062","collaboration":"Prepared in cooperation with the California Department of Fish and Wildlife and Pheasants Forever","usgsCitation":"=Dwight, I.A., Coates, P.S., Vogt, J.H., Atkinson, J.L., Fleskes, J.P., Connelly, D.P., Meshriy, M.C., Gardner, S.C., Stoute, S.T., and Pitesky M.E., 2019, Monitoring breeding and survival of ring-necked pheasant (Phasianus colchicus) in the Sacramento Valley, Sacramento-San Joaquin River Delta, and Klamath Basin, northern California—Five-year summary, 2013–17: U.S. Geological Survey Open-File Report 2019–1062, 90 p., https://doi.org/10.3133/ofr20191062.","productDescription":"90 p.","onlineOnly":"Y","ipdsId":"IP-099248","costCenters":[{"id":651,"text":"Western Ecological Research 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P.","affiliations":[],"preferred":false,"id":764177,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Connelly, Daniel P.","contributorId":192079,"corporation":false,"usgs":false,"family":"Connelly","given":"Daniel","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":764178,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Meshriy, Matt G.","contributorId":192080,"corporation":false,"usgs":false,"family":"Meshriy","given":"Matt G.","affiliations":[],"preferred":false,"id":764179,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Gardner, Scott C.","contributorId":192081,"corporation":false,"usgs":false,"family":"Gardner","given":"Scott","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":764180,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Stoute, Simone T.","contributorId":202770,"corporation":false,"usgs":false,"family":"Stoute","given":"Simone","email":"","middleInitial":"T.","affiliations":[{"id":36526,"text":"California Animal Health and Food Safety Laboratory","active":true,"usgs":false}],"preferred":false,"id":764181,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Pitesky, Maurice E.","contributorId":176920,"corporation":false,"usgs":false,"family":"Pitesky","given":"Maurice","email":"","middleInitial":"E.","affiliations":[{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":764182,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70200937,"text":"sir20185157 - 2019 - A Methodology to Assess the National and Regional Impacts of U.S. Wind Energy Development on Birds and Bats","interactions":[{"subject":{"id":70147329,"text":"sir20155066 - 2015 - Preliminary methodology to assess the national and regional impact of U.S. wind energy development on birds and bats","indexId":"sir20155066","publicationYear":"2015","noYear":false,"title":"Preliminary methodology to assess the national and regional impact of U.S. wind energy development on birds and bats"},"predicate":"SUPERSEDED_BY","object":{"id":70200937,"text":"sir20185157 - 2019 - A Methodology to Assess the National and Regional Impacts of U.S. Wind Energy Development on Birds and Bats","indexId":"sir20185157","publicationYear":"2019","noYear":false,"title":"A Methodology to Assess the National and Regional Impacts of U.S. Wind Energy Development on Birds and Bats"},"id":1}],"lastModifiedDate":"2019-07-23T13:03:08","indexId":"sir20185157","displayToPublicDate":"2019-07-23T14:04:00","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-5157","displayTitle":"A Methodology to Assess the National and Regional Impacts of U.S. Wind Energy Development on Birds and Bats","title":"A Methodology to Assess the National and Regional Impacts of U.S. Wind Energy Development on Birds and Bats","docAbstract":"<p>This scientific investigations report describes an effort by the U.S. Geological Survey (USGS) that used research, monitoring data, and modeling to develop a methodology to assess both the current and future population-level consequences of wind energy development on species of birds and bats that are present in the United States during any part of their life cycle. The methodology is currently applicable to birds and bats, focuses primarily on the effects of collisions with turbines, and can be applied to any species that breeds in, migrates through, or otherwise uses any part of the United States. The methodology assesses species at the national and regional scales and identifies those species potentially in need of more detailed study, as well as those species that are likely at low risk from wind energy development. This approach is fundamentally different from existing methods focusing on impacts at individual facilities.</p><p>This report supersedes USGS Scientific Investigations Report 2015–5066 by the same authors, which described a preliminary version of the methodology. Following reviews of the preliminary methodology by a panel of external experts, public comments, and additional internal review, the methodology was revised and finalized.</p><p>The three components of the refined methodology described in this new report rely on publicly available fatality information, population estimates, species range maps, turbine location data, biological characteristics of species, and population models. First, three metrics are combined to determine direct and indirect relative effects from wind energy facilities to generate a list of species scores. Second, a generic population model estimates the expected change in population trend caused by the additive mortality from collisions with wind turbines. Third, the methodology combines an estimate of observed fatalities and an estimate of potential biological removal to assess the possibility of a decrease in population size. The latter two components are quantitative. In a test case, the methodology was used to analyze data for six bird species and three bat species.</p><p>Components of the methodology are based on simplifying assumptions and require information that, for many species, may be sparse or unreliable or may require further study. These assumptions should be carefully considered when using outputs from the methodology. Increases in the quality of data for fatalities from collisions with wind turbines, species distributions, abundance, and demography will likely improve results for uses of the methodology.</p><p>The methodology’s design identifies and prioritizes a subset of the bird and bat species that may experience population-level impacts from collisions with wind turbines, both currently and from future wind energy development in the United States. Results of an assessment using this methodology could focus future research to improve our understanding of those impacts and to guide avoidance and minimization strategies. In addition, this methodology can be used to identify species for more intensive demographic modeling or to highlight those species that may not require any additional research because effects of wind energy development on their populations are projected to be small. The effects of wind energy facilities on nine unidentified species used in the test case described in this report have not been assessed. Their data were simply used to show the application of the methodology to real-world data and the types of outputs it would produce.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185157","usgsCitation":"Diffendorfer, J.E., Beston, J.A., Merrill, M.D., Stanton, J.C., Corum, M.D., Loss, S.R., Thogmartin, W.E., Johnson, D.H., Erickson, R.A., and Heist, K.W., 2019, A methodology to assess the national and regional impacts of U.S. wind energy development on birds and bats: U.S. Geological Survey Scientific Investigations Report 2018–5157, 45 p., https://doi.org/10.3133/sir20185157. [Supersedes USGS Scientific Investigations Report 2015–5066.]","productDescription":"ix, 45 p.","onlineOnly":"Y","ipdsId":"IP-079749","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":365690,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5157/coverthb.jpg"},{"id":365691,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5157/sir20185157.pdf","text":"Report","size":"1.94 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5157"}],"publicComments":"Scientific Investigations Report 2018-5157 supersedes Scientific Investigations Report 2015-5066.","contact":"<p><a href=\"mailto:gd-energyprogram@usgs.gov\" data-mce-href=\"mailto:gd-energyprogram@usgs.gov\">Director</a>, <a href=\"https://www.usgs.gov/centers/eersc\" data-mce-href=\"https://www.usgs.gov/centers/eersc\">Eastern Energy Resources Science Center</a><br>U.S. Geological Survey<br>Mail Stop 956<br>12201 Sunrise Valley Drive<br>Reston, VA 20192<br><a href=\"https://www.usgs.gov/energy-and-minerals/energy-resources-program/\" data-mce-href=\"https://www.usgs.gov/energy-and-minerals/energy-resources-program/\">Energy Resources Program</a><br><a href=\"https://www.usgs.gov/energy-and-minerals/energy-resources-program/science/wind-energy?qt-science_center_objects=0#qt-science_center_objects\" data-mce-href=\"https://www.usgs.gov/energy-and-minerals/energy-resources-program/science/wind-energy?qt-science_center_objects=0#qt-science_center_objects\">Wind Energy</a></p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>1.0 Introduction</li><li>2.0 Methodology</li><li>3.0 Overall Methodology Development and Validation</li><li>4.0 Test Case</li><li>5.0 Conclusions</li><li>References Cited</li><li>Glossary</li><li>Appendix 1. Alternative Modeling Approaches Considered</li><li>Appendix 2. Future Projections</li></ul>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2019-07-23","noUsgsAuthors":false,"publicationDate":"2019-07-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Diffendorfer, James E. 0000-0003-1093-6948 jediffendorfer@usgs.gov","orcid":"https://orcid.org/0000-0003-1093-6948","contributorId":3208,"corporation":false,"usgs":true,"family":"Diffendorfer","given":"James E.","email":"jediffendorfer@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":751395,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beston, J.A.","contributorId":210657,"corporation":false,"usgs":false,"family":"Beston","given":"J.A.","affiliations":[{"id":38127,"text":"University of Wisconsin - Stout","active":true,"usgs":false}],"preferred":false,"id":751396,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Merrill, Matthew D. 0000-0003-3766-847X","orcid":"https://orcid.org/0000-0003-3766-847X","contributorId":205698,"corporation":false,"usgs":true,"family":"Merrill","given":"Matthew D.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":751394,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stanton, Jessica C. 0000-0002-6225-3703 jcstanton@usgs.gov","orcid":"https://orcid.org/0000-0002-6225-3703","contributorId":5634,"corporation":false,"usgs":true,"family":"Stanton","given":"Jessica","email":"jcstanton@usgs.gov","middleInitial":"C.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":751397,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Corum, M.D. 0000-0002-9038-3935 mcorum@usgs.gov","orcid":"https://orcid.org/0000-0002-9038-3935","contributorId":2249,"corporation":false,"usgs":true,"family":"Corum","given":"M.D.","email":"mcorum@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":751398,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Loss, S.R.","contributorId":210658,"corporation":false,"usgs":false,"family":"Loss","given":"S.R.","email":"","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":751399,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Thogmartin, W.E. 0000-0002-2384-4279","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":210659,"corporation":false,"usgs":false,"family":"Thogmartin","given":"W.E.","affiliations":[],"preferred":false,"id":751400,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Johnson, D.H. 0000-0002-7778-6641","orcid":"https://orcid.org/0000-0002-7778-6641","contributorId":210660,"corporation":false,"usgs":false,"family":"Johnson","given":"D.H.","affiliations":[{"id":12545,"text":"USGS retired","active":true,"usgs":false}],"preferred":false,"id":751401,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Erickson, R.A. 0000-0003-4649-482X","orcid":"https://orcid.org/0000-0003-4649-482X","contributorId":210661,"corporation":false,"usgs":false,"family":"Erickson","given":"R.A.","affiliations":[],"preferred":false,"id":751402,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Heist, K.W. 0000-0002-0140-861X","orcid":"https://orcid.org/0000-0002-0140-861X","contributorId":210662,"corporation":false,"usgs":false,"family":"Heist","given":"K.W.","email":"","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":751403,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70203969,"text":"sir20195054 - 2019 - The use of continuous water-quality time-series data to compute nutrient loadings for selected Iowa streams, 2008–17","interactions":[],"lastModifiedDate":"2019-07-23T14:31:04","indexId":"sir20195054","displayToPublicDate":"2019-07-23T13:34:03","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-5054","displayTitle":"The Use of Continuous Water-Quality Time-Series Data to Compute Nutrient Loadings for Selected Iowa Streams, 2008–17","title":"The use of continuous water-quality time-series data to compute nutrient loadings for selected Iowa streams, 2008–17","docAbstract":"<p>In support of nutrient reduction efforts, nitrate (as nitrate plus nitrite) and phosphorus loads and yields were computed for selected streams in Iowa based on continuously monitored sensor data for 2008–17 and 2014–17, respectively. Sample data were used to assess nitrate sensor bias and to create phosphorus-turbidity surrogate models. Where needed, nitrate loads were corrected for site-specific sensor bias, which was determined to be as high as 9.25 percent. Nitrate loads presented in this report using continuous (generally 15-minute interval) data were on average 4 percent less, but as much as 38 percent less, than annual loads computed from daily mean nitrate concentrations not corrected for sensor bias. Streamflow-based phosphorus models had poorer fit (adjusted coefficient of determination values less than 0.75) than turbidity-based models (adjusted coefficient of determination approximately 0.9). However, alternate models based on streamflow were used to obtain a more complete annual phosphorus load despite seasonal and fragmentary sensor data.</p><p>Mean annual nitrate yields for 18 selected sites (96 site-years) ranged from 1.68 to 164 pounds per square mile per day (lb/mi<sup>2</sup>/d), compared to 19.4 lb/mi<sup>2</sup>/d average statewide yield needed to achieve the nitrate-reduction goal. Mean annual phosphorus yields for selected sites on the Maquoketa River, South Raccoon River, and West Nishnabotna River range from 1.57 to 7.19 lb/mi<sup>2</sup>/d, compared to 1.06 lb/mi<sup>2</sup>/d average statewide yield needed to achieve the phosphorus-reduction goal.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195054","collaboration":"Prepared in cooperation with the Iowa Department of Natural Resources","usgsCitation":"Garrett, J.D., 2019, The use of continuous water-quality time-series data to compute nutrient loadings for selected Iowa streams, 2008–17: U.S. Geological Survey Scientific Investigations Report 2019–5054, 31 p., https://doi.org/10.3133/sir20195054.","productDescription":"Report: viii, 31 p.; Appendixes: 2","numberOfPages":"44","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-098143","costCenters":[{"id":351,"text":"Iowa Water Science 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 \"}}]}","contact":"<p>Director, <a data-mce-href=\"ttps://www.usgs.gov/centers/cm-water\" href=\"ttps://www.usgs.gov/centers/cm-water\">Central Midwest Water Science Center</a><br> U.S. Geological Survey<br>400 South Clinton Street, Suite 269 <br>Iowa City, IA 52240 </p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Methods for Data Collection and Computation</li><li>Methods for Continuous Concentration Models</li><li>Methods for Generation of Time-Series Concentrations and Loads</li><li>Sample Water-Quality and Sensor Data</li><li>Continuous Water-Quality Time-Series Data to Compute Nutrient Loadings</li><li>Summary</li><li>References Cited</li><li>Appendix 1. Model Calibration Samples</li><li>Appendix 2. Nitrate Check Samples</li></ul>","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2019-07-23","noUsgsAuthors":false,"publicationDate":"2019-07-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Garrett, Jessica D. 0000-0002-4466-3709 jgarrett@usgs.gov","orcid":"https://orcid.org/0000-0002-4466-3709","contributorId":4229,"corporation":false,"usgs":true,"family":"Garrett","given":"Jessica","email":"jgarrett@usgs.gov","middleInitial":"D.","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"preferred":true,"id":765028,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70204463,"text":"70204463 - 2019 - Bayesian statistics for beginners: A step-by-step approach","interactions":[],"lastModifiedDate":"2019-09-20T12:13:53","indexId":"70204463","displayToPublicDate":"2019-07-23T12:11:02","publicationYear":"2019","noYear":false,"publicationType":{"id":4,"text":"Book"},"publicationSubtype":{"id":15,"text":"Monograph"},"title":"Bayesian statistics for beginners: A step-by-step approach","docAbstract":"<p><span>Bayesian statistics is currently undergoing something of a renaissance. At its heart is a method of statistical inference in which Bayes' theorem is used to update the probability for a hypothesis as more evidence or information becomes available. It is an approach that is ideally suited to making initial assessments based on incomplete or imperfect information; as that information is gathered and disseminated, the Bayesian approach corrects or replaces the assumptions and alters its decision-making accordingly to generate a new set of probabilities. As new data/evidence becomes available the probability for a particular hypothesis can therefore be steadily refined and revised. It is very well-suited to the scientific method in general and is widely used across the social, biological, medical, and physical sciences. Key to this book's novel and informal perspective is its unique pedagogy, a question and answer approach that utilizes accessible language, humor, plentiful illustrations, and frequent reference to on-line resources.</span><br><br><i>Bayesian Statistics for Beginners</i><span>&nbsp;is an introductory textbook suitable for senior undergraduate and graduate students, professional researchers, and practitioners seeking to improve their understanding of the Bayesian statistical techniques they routinely use for data analysis in the life and medical sciences, psychology, public health, business, and other fields.</span></p>","language":"English","publisher":"Oxford University Press","isbn":"9780198841296","usgsCitation":"Donovan, T.M., and Mickey, R.M., 2019, Bayesian statistics for beginners: A step-by-step approach, 432 p.","productDescription":"432 p.","ipdsId":"IP-084575","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":367604,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":367603,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://global.oup.com/academic/product/bayesian-statistics-for-beginners-9780198841296?cc=us&lang=en&#"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Donovan, Therese M. 0000-0001-8124-9251 tdonovan@usgs.gov","orcid":"https://orcid.org/0000-0001-8124-9251","contributorId":204296,"corporation":false,"usgs":true,"family":"Donovan","given":"Therese","email":"tdonovan@usgs.gov","middleInitial":"M.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":767022,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mickey, Ruth M.","contributorId":171666,"corporation":false,"usgs":false,"family":"Mickey","given":"Ruth","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":771487,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70203975,"text":"ofr20191070 - 2019 - Geochronologic, isotopic, and geochemical data from igneous rocks in the Lane Mountain area, San Bernardino County, California","interactions":[],"lastModifiedDate":"2023-03-29T17:43:48.197889","indexId":"ofr20191070","displayToPublicDate":"2019-07-23T10:35:52","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-1070","displayTitle":"Geochronologic, Isotopic, and Geochemical Data from Igneous Rocks in the Lane Mountain Area, San Bernardino County, California","title":"Geochronologic, isotopic, and geochemical data from igneous rocks in the Lane Mountain area, San Bernardino County, California","docAbstract":"<p><span>We present new geochronologic, isotopic, and geochemical data for selected igneous rocks in the Lane Mountain area, California. We determined SHRIMP-RG U-Pb zircon ages for the following units: (1) Larrea complex (~253 Ma and ~149–146 Ma); (2) Daisy granodiorite (~151 Ma); (3) Jack Spring quartz monzonite (~85–82 Ma); (4) unnamed porphyritic dikes and stocks (~80–73 Ma); and (5) Lane Mountain volcanics (~22 Ma). These results confirm and refine previous age determinations for the Larrea complex, Jack Spring quartz monzonite, and Lane Mountain volcanics, and provide the first reliable ages for the Daisy granodiorite and the unnamed porphyritic rocks. Sri of the plutonic rocks increases from ~0.704 to ~0.705–0.706 to ~0.708–0.709 for samples dated as ~250, ~150, and ~85–70 Ma, respectively, which indicates progressively greater involvement of Precambrian continental lithosphere in magma generation through time. The Sri and geochemical data suggest that the most significant change in magmatic source occurred between ~150 and 85 Ma.</span></p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191070","usgsCitation":"Stone, P., Brown, H.J., Cecil, M.R., Fleck, R.J., Vazquez, J.A., Fitzpatrick, J.A., and Rosario, J., 2019, Geochronologic, isotopic, and geochemical data from igneous rocks in the Lane Mountain area, San Bernardino County, California: U.S. Geological Survey Open-File Report 2019–1070, 34 p., https://doi.org/10.3133/ofr20191070.","productDescription":"34 p.","onlineOnly":"Y","ipdsId":"IP-102033","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":414905,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20221115","text":"Open-File Report 2022-1115","description":"Stone, P., Cecil, M.R., Brown, H.J., and Vazquez, J.A., 2023, Geochronologic and geochemical data from metasedimentary and associated rocks in the Lane Mountain area, San Bernardino County, California: U.S. Geological Survey Open-File Report 2022–1115, 34 p., https://doi.org/10.3133/ofr20221115.","linkHelpText":"- Geochronologic and Geochemical Data from Metasedimentary and Associated Rocks in the Lane Mountain Area, San Bernardino County, California"},{"id":392865,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20211094","text":"Open-File Report 2021-1094","linkHelpText":"- Geochronologic, Isotopic, and Geochemical Data from Pre- Cretaceous Plutonic Rocks in the Lane Mountain Area, San Bernardino County, California"},{"id":365747,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1070/ofr20191070.pdf","text":"Report","size":"9.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1070"},{"id":365746,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1070/coverthb.jpg"}],"country":"United States","state":"California","county":"San Bernardino 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Bernardino\",\"state\":\"CA\"}}]}","contact":"<p><a href=\"https://www.usgs.gov/centers/gmeg/connect\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/gmeg/connect\">Contact Information</a>,<br><a href=\"https://www.usgs.gov/centers/gmeg\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/gmeg\">Geology, Minerals, Energy, &amp; Geophysics Science Center</a><br><a href=\"https://www.usgs.gov/centers/gmeg\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://www.usgs.gov/centers/gmeg\">Menlo Park, California</a><br><a href=\"https://usgs.gov/\" target=\"_blank\" rel=\"noopener\" data-mce-href=\"https://usgs.gov/\">U.S. Geological Survey</a><br>Building 19, 350 N. Akron Rd.<br>P.O. Box 158<br>Moffett Field, CA 94035</p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Geographic Setting</li><li>Previous Investigations and General Geologic Framework</li><li>Purpose and Scope</li><li>Methods</li><li>Results</li><li>Discussion</li><li>Summary</li><li>Acknowledgments</li><li>References Cited</li><li>Figures and Tables</li></ul>","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2019-07-23","noUsgsAuthors":false,"publicationDate":"2019-07-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Stone, Paul 0000-0002-1439-0156 pastone@usgs.gov","orcid":"https://orcid.org/0000-0002-1439-0156","contributorId":273,"corporation":false,"usgs":true,"family":"Stone","given":"Paul","email":"pastone@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":765053,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brown, Howard J.","contributorId":216565,"corporation":false,"usgs":false,"family":"Brown","given":"Howard","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":765054,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cecil, M. Robinson 0000-0003-1948-1919","orcid":"https://orcid.org/0000-0003-1948-1919","contributorId":216566,"corporation":false,"usgs":false,"family":"Cecil","given":"M.","email":"","middleInitial":"Robinson","affiliations":[{"id":39477,"text":"California State University Northridge","active":true,"usgs":false}],"preferred":true,"id":765055,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fleck, Robert J. 0000-0002-3149-8249 fleck@usgs.gov","orcid":"https://orcid.org/0000-0002-3149-8249","contributorId":1048,"corporation":false,"usgs":true,"family":"Fleck","given":"Robert","email":"fleck@usgs.gov","middleInitial":"J.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":765056,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vazquez, Jorge A. 0000-0003-2754-0456 jvazquez@usgs.gov","orcid":"https://orcid.org/0000-0003-2754-0456","contributorId":4458,"corporation":false,"usgs":true,"family":"Vazquez","given":"Jorge","email":"jvazquez@usgs.gov","middleInitial":"A.","affiliations":[{"id":5056,"text":"Office of the AD Energy and Minerals, and Environmental Health","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":501,"text":"Office of Science Quality and Integrity","active":true,"usgs":true}],"preferred":true,"id":765058,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fitzpatrick, John A. 0000-0001-6738-7180 jfitzpat@usgs.gov","orcid":"https://orcid.org/0000-0001-6738-7180","contributorId":3719,"corporation":false,"usgs":true,"family":"Fitzpatrick","given":"John","email":"jfitzpat@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":false,"id":765057,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rosario, Jose J.","contributorId":216567,"corporation":false,"usgs":false,"family":"Rosario","given":"Jose J.","affiliations":[{"id":39478,"text":"California State Unversity East Bay","active":true,"usgs":false}],"preferred":false,"id":765059,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70204401,"text":"70204401 - 2019 - Preliminary report on engineering and geological effects of the July 2019 Ridgecrest earthquake sequence","interactions":[],"lastModifiedDate":"2019-07-23T09:45:32","indexId":"70204401","displayToPublicDate":"2019-07-23T09:45:00","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Preliminary report on engineering and geological effects of the July 2019 Ridgecrest earthquake sequence","docAbstract":"The Ridgecrest Earthquake sequence included a foreshock event on July 4 2019 (M6.4) and a M7.1 mainshock event on July 5 2019. These events occurred in the Eastern California Shear Zone, near Indian Wells Valley, south of China Lake and west of Searles Valley. GEER has partnered with several organizations to collect perishable data and document the important impacts of these events, including the US Geological Survey, the California Geological Survey, the US Navy, the Southern California Earthquake Center, and local utilities. Critical geotechnical features of this event are extensive left-lateral (M6.4 event) and right-lateral (M7.1 event) surface ruptures over fault segments of variable complexity and width as well as across extensional and compressive step-over zones. We also document lifeline performance at fault crossings (gas, water, electrical), mainshock slip and afterslip, liquefaction and lateral spreading features, and liquefaction effects on structures. These effects are documented using field (ground) mapping and aerial imagery that will support subsequent development of high-resolution digital elevation models. Over 750 ground motions were recorded from the foreshock and mainshock alone, with many additional aftershock records. The data demonstrate significant impacts of site response and rupture directivity on ground motion attributes.","language":"English","publisher":"Geotechnical Extreme Event Reconnaissance Association","doi":"10.18118/G6H66K","collaboration":"Naval Air Weapons Station, China Lake; City of Ridgecrest Police; GEER, EERI, SCEC, UCLA, USC, UNR and many others","usgsCitation":"Brandenberg, S.J., Wang, P., Nweke, C.C., Hudson, K., Mazzoni, S., Bozorgnia, Y., Hudnut, K.W., Davis, C.A., Ahdi, S.K., Zareian, F., Fayaz, J., Koehler, R.D., Chupik, C., Pierce, I., Williams, A., Akciz, S., Hudson, M.B., Kishida, T., Brooks, B.A., Gold, R.D., Ponti, D.J., Scharer, K., McPhillips, D., DuRoss, C., Ericksen, T., Hernandez, J., Patton, J., Olson, B., Dawson, T.E., Treiman, J., Blake, K., Buchhuber, J., Madugo, C.L., Sun, J., Donnellan, A., Lyzenga, G., and Conway, E., 2019, Preliminary report on engineering and geological effects of the July 2019 Ridgecrest earthquake sequence, 69 p., https://doi.org/10.18118/G6H66K.","productDescription":"69 p.","startPage":"1","endPage":"69","ipdsId":"IP-110040","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":365839,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":365756,"type":{"id":15,"text":"Index Page"},"url":"https://www.geerassociation.org/component/geer_reports/?view=geerreports&id=91&layout=build"}],"publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"editors":[{"text":"Stewart, Jonathan P.","contributorId":100110,"corporation":false,"usgs":false,"family":"Stewart","given":"Jonathan","email":"","middleInitial":"P.","affiliations":[{"id":7081,"text":"University of California - Los Angeles","active":true,"usgs":false}],"preferred":false,"id":766652,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"authors":[{"text":"Brandenberg, Scott 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,{"id":70203668,"text":"ofr20191065 - 2019 - Monitoring storm tide, flooding, and precipitation from Hurricane Maria in Puerto Rico and the U.S. Virgin Islands, September 2017","interactions":[],"lastModifiedDate":"2019-07-23T14:27:01","indexId":"ofr20191065","displayToPublicDate":"2019-07-23T08:40:30","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-1065","displayTitle":"Monitoring Storm Tide, Flooding, and Precipitation From Hurricane Maria in Puerto Rico and the U.S. Virgin Islands, September 2017","title":"Monitoring storm tide, flooding, and precipitation from Hurricane Maria in Puerto Rico and the U.S. Virgin Islands, September 2017","docAbstract":"<p>Hurricane Maria made landfall south of Yabucoa Harbor, Puerto Rico, as a category 4 hurricane with maximum sustained winds of 155 miles per hour on September 20, 2017. The hurricane devastated much of the U.S. Virgin Islands and Puerto Rico. The U.S. Geological Survey (USGS), in cooperation with Federal Emergency Management Agency, installed a temporary monitoring network of 13 water-level and barometric pressure sensors along the coast of Puerto Rico prior to the storm. In addition to the temporary sensors, the USGS maintains 99 permanent real-time streamgages and 36 real-time precipitation stations in Puerto Rico. The real-time data, updated hourly, during and after the hurricane are displayed in the USGS Flood Event Viewer (<a data-mce-href=\"https://stn.wim.usgs.gov/FEV/#MariaSeptember2017\" href=\"https://stn.wim.usgs.gov/FEV/#MariaSeptember2017\">https://stn.wim.usgs.gov/FEV/#MariaSeptember2017</a>) and in the USGS National Water Information System.</p><p>The USGS measured 181 coastal and riverine high-water marks throughout Puerto Rico after the storm. Water elevations are referenced to the Puerto Rico Vertical Datum of 2002 (PRVD02) and local datums in Puerto Rico and to the U.S. Virgin Islands Vertical Datum of 2009 (VIVD09) in the U.S. Virgin Islands. Data from the Hurricane Maria storm-tide network are available in tab-delimited, American Standard Code for Information Interchange (ASCII) format and Network Common Data Form (NetCDF) format by site for each sensor through the USGS Flood Event Viewer.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191065","collaboration":"Prepared in cooperation with the Federal Emergency Management Agency","usgsCitation":"Byrne, M.J., Sr., 2019, Monitoring storm tide, flooding, and precipitation from Hurricane Maria in Puerto Rico and the U.S. Virgin Islands, September 2017: U.S. Geological Survey Open-File Report 2019–1065,16 p., https://doi.org/10.3133/ofr20191065.","productDescription":"vi, 16 p.","numberOfPages":"26","onlineOnly":"N","ipdsId":"IP-097015","costCenters":[{"id":27821,"text":"Caribbean-Florida Water Science 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Rico\",\"nation\":\"USA  \"}}]}","contact":"<p>Director, <a href=\"https://www2.usgs.gov/water/caribbeanflorida/index.html\" data-mce-href=\"https://www2.usgs.gov/water/caribbeanflorida/index.html\">Caribbean-Florida Water Science Center</a> <br>U.S. Geological Survey <br>4446 Pet Lane, Suite 108 <br>Lutz, FL 33559</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Hurricane Maria Storm Tide, Flood Monitoring, and Precipitation</li><li>Elevation Surveys</li><li>Data Presentation</li><li>Conclusion</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2019-07-23","noUsgsAuthors":false,"publicationDate":"2019-07-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Byrne, Michael J. Sr. 0000-0001-9190-2728 mbyrne@usgs.gov","orcid":"https://orcid.org/0000-0001-9190-2728","contributorId":959,"corporation":false,"usgs":true,"family":"Byrne","given":"Michael","suffix":"Sr.","email":"mbyrne@usgs.gov","middleInitial":"J.","affiliations":[{"id":156,"text":"Caribbean Water Science Center","active":true,"usgs":true},{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true},{"id":5051,"text":"FLWSC-Orlando","active":true,"usgs":true}],"preferred":false,"id":763505,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70204252,"text":"sir20195049 - 2019 - Water-budget analysis of the Upper Big Sandy Designated Ground-water Basin alluvial aquifer, Elbert, El Paso, and Lincoln Counties, Colorado, 2016","interactions":[],"lastModifiedDate":"2019-12-30T11:37:00","indexId":"sir20195049","displayToPublicDate":"2019-07-22T11:20:00","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-5049","displayTitle":"Water-Budget Analysis of the Upper Big Sandy Designated Groundwater Basin Alluvial Aquifer, Elbert, El Paso, and Lincoln Counties, Colorado, 2016","title":"Water-budget analysis of the Upper Big Sandy Designated Ground-water Basin alluvial aquifer, Elbert, El Paso, and Lincoln Counties, Colorado, 2016","docAbstract":"<p>The U.S. Geological Survey in cooperation with the Colorado Water Conservation Board and the Upper Big Sandy Groundwater Management District carried out a study in 2016 to evaluate potential groundwater storage changes within the Upper Big Sandy Designated Groundwater Basin (UBSDGB) alluvial aquifer, including groundwater flow between the UBSDGB alluvial aquifer and the Denver Basin bedrock aquifers. The UBSDGB alluvial aquifer is located along the ephemeral Big Sandy Creek on the east-central edge of the Denver Basin aquifer system and covers an area of about 66,560 acres within the UBSDGB. The UBSDGB alluvial aquifer consists of unconsolidated Quaternary sand and gravel deposits that contain an unconfined (water table) groundwater system. The western three-fourths of the UBSDGB alluvial aquifer overlies the Tertiary and Cretaceous bedrock formations that compose the Denver Basin aquifer system. The updated water budget for the UBSDGB alluvial aquifer, including annual change in groundwater storage in 2016, was determined by combining water-budget information from an existing Denver Basin model for about three-fourths of the study area with best estimates for the major water-budget components for the area outside the Denver Basin aquifer system. The western part of the UBSDGB was included in the Denver Basin model (modeled area), whereas the eastern part of the UBSDGB was not included in the Denver Basin model (unmodeled area). The water-budget components were first estimated for the modeled area using outputs from the Denver Basin model, which uses the modular finite-difference groundwater flow computer model MODFLOW-2000 with 1-mile grid cells. For this study, the Denver Basin model was updated with additional data from 2004 through 2016 to generate current (2016) estimates of water consumption in the UBSDGB alluvial aquifer. A basin-specific water budget for the UBSDGB alluvial aquifer from the Denver Basin model was computed using a modeling tool called ZONEBUDGET. The modeled area groundwater budget, along with previous studies, was used to estimate a groundwater budget for the unmodeled area, and results for the modeled and unmodeled areas were combined for an overall water-budget estimate for the entire UBSDGB alluvial aquifer.</p><p>The net groundwater flow into the basin from adjacent alluvial aquifers was positive with flow entering the UBSDGB alluvial aquifer. Combining the total inflow from adjacent alluvial and the total outflow to adjacent alluvial aquifers resulted in a net flow from adjacent alluvial aquifers to UBSDGB alluvial aquifer of 5,125 acre-feet (ac-ft) in 2016. The net flow between the underlying bedrock aquifers and the UBSDGB alluvial aquifer was positive with flow entering the UBSDGB alluvial aquifer from the bedrock aquifers. The net flow from the bedrock aquifers to the UBSDGB alluvial aquifer was 347 ac-ft in 2016. Net recharge (precipitation and irrigation return flows minus evaporation) into the UBSDGB alluvial aquifer was negative with groundwater being removed from the UBSDGB alluvial aquifer over the total area of the basin. Combining the total inflow from recharge to the UBSDGB alluvial aquifer of 11,153 ac-ft in 2016 and the total evapo-transpiration of −11,656 ac-ft from the UBSDGB alluvial aquifer in 2016 resulted in a net recharge from UBSDGB alluvial aquifer of −503 ac-ft in 2016. Combining the modeled and unmodeled well pumping resulted in a total well pumping volume of −3,735 ac-ft in 2016 from the UBSDGB alluvial aquifer. The net groundwater flow to the stream network in the basin was negative with flow discharging from the UBSDGB alluvial aquifer into streams. Combining the total inflow from streams and the total outflow to streams for the UBSDGB alluvial aquifer resulted in −1,032 ac-ft in 2016 that was lost to the stream network in the UBSDGB. The net groundwater flow out of the UBSDGB was negative with flow leaving the UBSDGB alluvial aquifer. Combining the total area inflow to the basin from upgradient areas and the total area outflow from the basin for the UBSDGB alluvial aquifer resulted in a net flow out of the basin of −2,300 ac-ft. In the annual groundwater budget for 2016, groundwater storage in the UBSDGB alluvial aquifer system was removed because annual groundwater outflows from storage exceeded groundwater inflows to storage; in other words, water was removed from storage to balance the annual water budget. Combining the net flow from storage for the modeled area of 73 ac-ft and the inflow from storage for the unmodeled area of 2,025 ac-ft resulted in a net positive flow from storage of the UBSDGB alluvial aquifer of 2,098 ac-ft.</p><p>Increased pumping since 1958 in the Denver and upper Arapahoe aquifers, not necessarily in the UBSDGB, has caused a change in flow from bedrock units, which were minor or non-contributors of inflow to the UBSDGB alluvial aquifer, to receiving outflow from the UBSDGB alluvial aquifer. Since 2000, aquifer storage has been an inflow component of the water budget, which means that outflow from the modeled area exceeded inflow for the UBSDGB alluvial aquifer. Increased recharge from wetter than average years could replenish the UBSDGB alluvial aquifer. From 2003 through 2016, 13 of the 25 observation wells completed in the UBSDGB alluvial aquifer had a decline in the groundwater-level elevation with an average decline of −2.21 feet, and 12 of the 25 observation wells had an increase in the groundwater-level elevation with an average increase of 1.54 feet. In general, wells at the eastern and western edges of the UBSDGB showed an increase in groundwater-level elevation that appears related to areas of groundwater discharge from the lower Dawson and Laramie-Fox Hills bedrock aquifers to the UBSDGB alluvial aquifer. The remaining wells exhibited water-level declines. Future work could include the development of a basin-specific model to serve as a basin management tool for modeling changes in groundwater levels and storage under various future groundwater recharge and withdrawal scenarios.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/sir20195049","collaboration":"Prepared in cooperation with the Colorado Water Conservation Board and the Upper Big Sandy Groundwater Management District","usgsCitation":"Kohn, M.S., Oden, J.H., and Arnold, L.R., 2019, Water-budget analysis of the Upper Big Sandy Designated Ground-water Basin alluvial aquifer, Elbert, El Paso, and Lincoln Counties, Colorado, 2016: U.S. Geological Survey Scientific Investigations Report 2019-5049, 25 p., https://dx.doi.org/10.3133/sir20195049.","productDescription":"Report: vi, 25 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-091541","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":365584,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5049/sir20195049.pdf","text":"Report","size":"7.12 M","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019-5049"},{"id":365581,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5049/coverthb.jpg"},{"id":365748,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9DEOYGZ","text":"USGS data release","linkHelpText":"MODFLOW2000 model and ZONEBUDGET computer program used to simulate the Upper Big Sandy Designated Groundwater Basin alluvial aquifer, Elbert, El Paso, and Lincoln Counties, Colorado, 2016"}],"country":"United States","state":"Colorado","county":"Elbert County, El Paso County, Lincoln County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-104.054,38.523],[-104.1629,38.5215],[-104.2759,38.5204],[-104.2794,38.5205],[-104.2836,38.5201],[-104.3759,38.52],[-104.4971,38.5192],[-104.6071,38.5187],[-104.7171,38.5186],[-104.736,38.5183],[-104.8295,38.5183],[-104.943,38.5175],[-104.9432,38.5479],[-104.943,38.5624],[-104.9429,38.6041],[-104.9427,38.6186],[-104.9429,38.6467],[-104.9429,38.6503],[-104.9427,38.6621],[-104.9427,38.6648],[-104.9428,38.6938],[-104.9399,38.6938],[-104.9386,38.7808],[-104.939,38.7949],[-105.0671,38.7946],[-105.0674,38.8666],[-105.0502,38.8665],[-105.0296,38.8668],[-105.026,39.0413],[-105.032,39.1311],[-104.9371,39.1312],[-104.9175,39.131],[-104.8303,39.1311],[-104.6642,39.1308],[-104.6638,39.2165],[-104.664,39.3026],[-104.663,39.3892],[-104.6626,39.4762],[-104.6627,39.5665],[-104.6054,39.5663],[-104.5374,39.5655],[-104.4927,39.5636],[-104.4891,39.5636],[-104.4742,39.5629],[-104.3841,39.5627],[-104.3763,39.5631],[-104.2695,39.5639],[-104.2647,39.5638],[-104.1602,39.5646],[-104.1543,39.565],[-104.0468,39.5652],[-104.0427,39.5651],[-103.9305,39.5646],[-103.9293,39.5646],[-103.8189,39.5646],[-103.8129,39.5649],[-103.7126,39.5649],[-103.7066,39.5648],[-103.6004,39.5646],[-103.595,39.5645],[-103.4882,39.5647],[-103.4804,39.5645],[-103.3748,39.5651],[-103.3658,39.5654],[-103.2631,39.5659],[-103.253,39.5657],[-103.1533,39.5657],[-103.1539,39.475],[-103.1537,39.3879],[-103.1542,39.3009],[-103.154,39.2147],[-103.1527,39.1258],[-103.161,39.1255],[-103.1615,39.0376],[-103.1626,38.9492],[-103.163,38.863],[-103.1634,38.7765],[-103.1638,38.6912],[-103.1709,38.6909],[-103.1705,38.6837],[-103.1731,38.6796],[-103.1716,38.6111],[-103.1714,38.5236],[-103.2809,38.5224],[-103.3897,38.5239],[-103.5086,38.5236],[-103.5089,38.5159],[-103.6118,38.5171],[-103.6116,38.5225],[-103.7228,38.5223],[-103.8328,38.523],[-103.9411,38.523],[-104.054,38.523]]]},\"properties\":{\"name\":\"Elbert\",\"state\":\"CO\"}}]}","contact":"<p>Director, <a href=\"http://co.water.usgs.gov/\" data-mce-href=\"http://co.water.usgs.gov/\">Colorado Water Science Center</a><br>U.S. Geological Survey<br>Box 25046, MS-415<br>Denver, CO 80225</p>","tableOfContents":"<ul><li>Acknowledgments</li><li>Abstract</li><li>Introduction</li><li>Methods</li><li>Water-Budget Analysis</li><li>Possible Future Work</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"publishedDate":"2019-07-22","noUsgsAuthors":false,"publicationDate":"2019-07-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Kohn, Michael S. 0000-0002-5989-7700 mkohn@usgs.gov","orcid":"https://orcid.org/0000-0002-5989-7700","contributorId":4549,"corporation":false,"usgs":true,"family":"Kohn","given":"Michael","email":"mkohn@usgs.gov","middleInitial":"S.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":766176,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Oden, Jeannette H. 0000-0002-6473-1553 jhoden@usgs.gov","orcid":"https://orcid.org/0000-0002-6473-1553","contributorId":1152,"corporation":false,"usgs":true,"family":"Oden","given":"Jeannette","email":"jhoden@usgs.gov","middleInitial":"H.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":766193,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Arnold, L. R. 0000-0002-5110-9642 lrarnold@usgs.gov","orcid":"https://orcid.org/0000-0002-5110-9642","contributorId":1307,"corporation":false,"usgs":true,"family":"Arnold","given":"L.","email":"lrarnold@usgs.gov","middleInitial":"R.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":766196,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70207023,"text":"70207023 - 2019 - Subhourly mesoscale analysis of the 2011-2017 North American monsoon near its northwest boundary","interactions":[],"lastModifiedDate":"2019-12-03T12:12:16","indexId":"70207023","displayToPublicDate":"2019-07-21T12:10:12","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2032,"text":"International Journal of Climatology","active":true,"publicationSubtype":{"id":10}},"title":"Subhourly mesoscale analysis of the 2011-2017 North American monsoon near its northwest boundary","docAbstract":"The North American Monsoon (NAM) delivers precipitation to the southwestern USA during the warm-dry summer season. The seasonal extent of NAM precipitation is highly variable and is likely to change under future climate change. Our objective was to determine how large scale monsoonal patterns as well as local variables influence precipitation events near the NAM northwest boundary. Intra- and inter-annual changes in the northwest sector of the NAM were represented by subhourly weather data collected on the Sheep Range (2300 m asl), in the Mojave Desert of southern Nevada, during 2011-2017. Our study site is part of the Nevada Climate-ecohydrological Assessment Network (NevCAN), an automated observing system established in early 2011. Three seasons were classified using the subhourly weather data including: 1) cool season, 2) early warm season, 3) and late warm season, where the transition between early and late warm season was marked by the day when in situ dewpoint temperature first exceeded 9.4 ºC. Based on analysis of covariance (ANCOVA), dewpoint temperature had the greatest relationship with total hourly precipitation, followed by vapor pressure deficit, solar radiation, and air temperature. The only significant interaction term was between hour of the day and dewpoint temperature, highlighting the importance of dewpoint temperature for afternoon thunderstorms, which are typical of monsoonal precipitation. Besides in situ meteorological variables, we also analyzed NCEP/NCAR vertically integrated water vapor transport (IVT) and long-term 800-m PRISM precipitation time series. Regional composites were developed for IVT for the three seasons. Water vapor in the cool and early warm season originated mostly from the Pacific Ocean, while a transition in IVT to a NAM pattern occurred in the late warm season. Overall, this highly instrumented yet remote site was representative of NAM precipitation, despite noticeable variability in its timing and amount.","language":"English","publisher":"Royal Meteorological Society","doi":"10.3390/atmos10070420","usgsCitation":"Truettner, C., Dettinger, M.D., Ziaco, E., Czank, A., and Biondi, F., 2019, Subhourly mesoscale analysis of the 2011-2017 North American monsoon near its northwest boundary: International Journal of Climatology, v. 10, no. 7, 420, https://doi.org/10.3390/atmos10070420.","productDescription":"420","ipdsId":"IP-101640","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":467434,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/atmos10070420","text":"Publisher Index Page"},{"id":369875,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -117.158203125,\n              34.92197103616377\n            ],\n            [\n              -113.48876953125,\n              34.92197103616377\n            ],\n            [\n              -113.48876953125,\n              37.09023980307208\n            ],\n            [\n              -117.158203125,\n              37.09023980307208\n            ],\n            [\n              -117.158203125,\n              34.92197103616377\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"10","issue":"7","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-07-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Truettner, Charles","contributorId":169536,"corporation":false,"usgs":false,"family":"Truettner","given":"Charles","email":"","affiliations":[{"id":25558,"text":"Norther Arizona University, Flagstaff, AZ","active":true,"usgs":false}],"preferred":false,"id":776545,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dettinger, Michael D. 0000-0002-7509-7332 mddettin@usgs.gov","orcid":"https://orcid.org/0000-0002-7509-7332","contributorId":149896,"corporation":false,"usgs":true,"family":"Dettinger","given":"Michael","email":"mddettin@usgs.gov","middleInitial":"D.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":776544,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ziaco, Emanuele","contributorId":220998,"corporation":false,"usgs":false,"family":"Ziaco","given":"Emanuele","email":"","affiliations":[{"id":12742,"text":"University of Nevada Reno","active":true,"usgs":false}],"preferred":false,"id":776546,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Czank, Adam","contributorId":220999,"corporation":false,"usgs":false,"family":"Czank","given":"Adam","email":"","affiliations":[{"id":12742,"text":"University of Nevada Reno","active":true,"usgs":false}],"preferred":false,"id":776547,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Biondi, Franco","contributorId":221000,"corporation":false,"usgs":false,"family":"Biondi","given":"Franco","email":"","affiliations":[{"id":12742,"text":"University of Nevada Reno","active":true,"usgs":false}],"preferred":false,"id":776548,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70205850,"text":"70205850 - 2019 - Long-term (37 years) impacts of low-head dams on freshwater shrimp habitat connectivity in northeastern Puerto Rico","interactions":[],"lastModifiedDate":"2019-10-08T12:45:28","indexId":"70205850","displayToPublicDate":"2019-07-19T12:43:53","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3301,"text":"River Research and Applications","active":true,"publicationSubtype":{"id":10}},"title":"Long-term (37 years) impacts of low-head dams on freshwater shrimp habitat connectivity in northeastern Puerto Rico","docAbstract":"Freshwater migratory shrimp in Puerto Rico depend on watershed connectivity, from stream headwaters to the ocean, to complete their life cycle. Moreover, shrimp populations in different watersheds are known to be connected in an island-wide metapopulation. However, low-head dams paired with water intakes on streams draining the El Yunque National Forest (EYNF) reduce streamflow. Here, we examine the cumulative effects of low-head dams on shrimp habitat connectivity over 37-years across seven EYNF watersheds. We calculate total and refugia habitat connectivity (where refugia habitat is defined as predator-free upstream reaches above waterfalls > 5 m in height) at a monthly time step using a habitat-weighted index of longitudinal riverine connectivity, which incorporates location and operation of water intakes and streamflow variability. Findings indicate total and refugia habitat connectivity declined over 37 years (by 27% and 16%, respectively) as additional water intakes have been placed in lower reaches of watersheds. On a monthly time-step, the proportion of streamflow withdrawn has the largest effect on habitat connectivity, with the result that connectivity is ~17% lower during drought years than in non-drought years and ~7% lower in dry compared to wet seasons. Our analysis of this long-term dataset highlights how cumulative effects of low-head dams paired with water intakes have reduced shrimp habitat connectivity. These results underscore the importance of reducing existing withdrawal rates in EYNF, and locating intakes where effects on connectivity are minimal, if conserving shrimp habitat is a management objective.","language":"English","publisher":"Wiley","doi":"10.1002/rra.3499","usgsCitation":"Chappell, J., McKay, S.K., Freeman, M., and Pringle, C.M., 2019, Long-term (37 years) impacts of low-head dams on freshwater shrimp habitat connectivity in northeastern Puerto Rico: River Research and Applications, v. 35, no. 7, p. 1034-1043, https://doi.org/10.1002/rra.3499.","productDescription":"10 p.","startPage":"1034","endPage":"1043","ipdsId":"IP-105657","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":467437,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/rra.3499","text":"Publisher Index 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,{"id":70205017,"text":"70205017 - 2019 - Virus-like particle production in atmospheric eubacteria isolates","interactions":[],"lastModifiedDate":"2019-08-28T12:45:30","indexId":"70205017","displayToPublicDate":"2019-07-19T12:41:52","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5634,"text":"Atmosphere","active":true,"publicationSubtype":{"id":10}},"title":"Virus-like particle production in atmospheric eubacteria isolates","docAbstract":"Culturable eubacterial isolates were collected at various altitudes in Earth’s atmosphere to include ~1.5 m above ground in Tallahassee, Florida, USA, ~10.0 m above sea level over the mid-Atlantic ridge (~15oN), ~ 20 km above ground over the continental United States, ~20 km above sea level over the Pacific Ocean near southern California and from the atmosphere of Carlsbad Cavern, Carlsbad Cavern National Park, New Mexico, USA. Isolates were screened for the presence of inducible virus-like particles (VLP) through use of mitomycin C and epifluorescent direct counts. We determined that 92.7% of the isolates carried inducible (VLP) counts in exposed versus non-exposed culture controls and that the relationship was statistically significant. Further statistical analyses revealed that the numbers of isolates that demonstrated VLP production did not vary among collection sites. These data demonstrate a high prevalence of VLP generation in isolates collected in the lower atmosphere and at extreme altitudes. Also shows that species of eubacteria that are resistant to the rigors of atmospheric transport play a significant role in long-range atmospheric inter- and intra-continental dispersion of VLP and that long-range atmospheric transport of VLP may enhance rates of evolution at the microbial scale in receiving environments.","language":"English","publisher":"MDPI","doi":"10.3390/atmos10070417","usgsCitation":"Nuria Teigell-Perez, Cristina Gonzalez-Martin, Basilio Valladares, David J. Smith, and Griffin, D.W., 2019, Virus-like particle production in atmospheric eubacteria isolates: Atmosphere, v. 10, no. 7, 417, 12 p., https://doi.org/10.3390/atmos10070417.","productDescription":"417, 12 p.","ipdsId":"IP-045019","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":467438,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/atmos10070417","text":"Publisher Index Page"},{"id":367016,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","issue":"7","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2019-07-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Nuria Teigell-Perez","contributorId":218568,"corporation":false,"usgs":false,"family":"Nuria Teigell-Perez","affiliations":[{"id":39874,"text":"Univ Inst of Tropical Diseases and Public Health, Canary Islands","active":true,"usgs":false}],"preferred":false,"id":769582,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cristina Gonzalez-Martin","contributorId":218566,"corporation":false,"usgs":false,"family":"Cristina Gonzalez-Martin","affiliations":[{"id":39874,"text":"Univ Inst of Tropical Diseases and Public Health, Canary Islands","active":true,"usgs":false}],"preferred":false,"id":769580,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Basilio Valladares","contributorId":218565,"corporation":false,"usgs":false,"family":"Basilio Valladares","affiliations":[{"id":39874,"text":"Univ Inst of Tropical Diseases and Public Health, Canary Islands","active":true,"usgs":false}],"preferred":false,"id":769579,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"David J. Smith","contributorId":218567,"corporation":false,"usgs":false,"family":"David J. Smith","affiliations":[{"id":38788,"text":"NASA","active":true,"usgs":false}],"preferred":false,"id":769581,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Griffin, Dale W. 0000-0003-1719-5812 dgriffin@usgs.gov","orcid":"https://orcid.org/0000-0003-1719-5812","contributorId":2178,"corporation":false,"usgs":true,"family":"Griffin","given":"Dale","email":"dgriffin@usgs.gov","middleInitial":"W.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":769578,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70215389,"text":"70215389 - 2019 - Mapping irrigated cropland extent across the conterminous United States at 30 m resolution using a semi-automatic training approach on Google Earth Engine","interactions":[],"lastModifiedDate":"2024-05-16T13:57:09.889555","indexId":"70215389","displayToPublicDate":"2019-07-19T08:44:25","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1958,"text":"ISPRS Journal of Photogrammetry and Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Mapping irrigated cropland extent across the conterminous United States at 30 m resolution using a semi-automatic training approach on Google Earth Engine","docAbstract":"<div id=\"abstracts\" class=\"Abstracts u-font-serif\"><div id=\"ab005\" class=\"abstract author\" lang=\"en\"><div id=\"as005\"><p id=\"sp0005\">Accurate and timely information on the distribution of irrigated croplands is crucial to research on agriculture, water availability, land use, and climate change. While agricultural land use has been well characterized, less attention has been paid specifically to croplands that are irrigated, in part due to the difficulty in mapping and distinguishing irrigation in satellite imagery. In this study, we developed a semi-automatic training approach to rapidly map irrigated croplands across the conterminous United States (CONUS) at 30 m resolution using Google Earth Engine. To resolve the issue of lacking nationwide training data, we generated two intermediate irrigation maps by segmenting Landsat-derived annual maximum greenness and enhanced vegetation index using county-level thresholds calibrated from an existing coarse resolution irrigation map. The resulting intermediate maps were then spatially filtered to provide a training data pool for most areas except for the upper midwestern states where we visually collected samples. We then used random samples extracted from the training pool along with remote sensing-derived features and climate variables to train ecoregion-stratified random forest classifiers for pixel-level classification. For ecoregions with a large training pool, the procedure of sample extraction, classifier training, and classification was conducted 10 times to obtain stable classification results. The resulting 2012 Landsat-based irrigation dataset (LANID) identified 23.3 million hectares of irrigated croplands in CONUS. A quantitative assessment of LANID showed superior accuracy to currently available maps, with a mean Kappa value of 0.88 (0.75–0.99), overall accuracy of 94% (87.5–99%), and producer’s and user’s accuracy of the irrigation class of 97.3% and 90.5%, respectively, at the aquifer level. Evaluation of feature importance indicated that Landsat-derived features played the primary role in classification in relatively arid regions while climate variables were important in the more humid eastern states. This methodology has the potential to produce annual irrigation maps for CONUS and provide insights into the field-level spatial and temporal aspects of irrigation.</p></div></div></div>","language":"English","publisher":"Elsevier","doi":"10.1016/j.isprsjprs.2019.07.005","usgsCitation":"Xie, Y., Lark, T.J., Brown, J.F., and Gibbs, H., 2019, Mapping irrigated cropland extent across the conterminous United States at 30 m resolution using a semi-automatic training approach on Google Earth Engine: ISPRS Journal of Photogrammetry and Remote Sensing, v. 155, p. 136-149, https://doi.org/10.1016/j.isprsjprs.2019.07.005.","productDescription":"14 p.","startPage":"136","endPage":"149","ipdsId":"IP-109078","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":467440,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.isprsjprs.2019.07.005","text":"Publisher Index Page"},{"id":379490,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"conterminous United States","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"geometry\": {\n        \"type\": \"MultiPolygon\",\n        \"coordinates\": [\n          [\n            [\n              [\n                -94.81758,\n                49.38905\n              ],\n              [\n                -94.64,\n                48.84\n              ],\n              [\n                -94.32914,\n                48.67074\n              ],\n              [\n                -93.63087,\n                48.60926\n              ],\n              [\n                -92.61,\n                48.45\n              ],\n              [\n                -91.64,\n                48.14\n              ],\n              [\n                -90.83,\n            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         [\n                -124.07963,\n                46.86475\n              ],\n              [\n                -124.39567,\n                47.72017\n              ],\n              [\n                -124.68721,\n                48.18443\n              ],\n              [\n                -124.5661,\n                48.37971\n              ],\n              [\n                -123.12,\n                48.04\n              ],\n              [\n                -122.58736,\n                47.096\n              ],\n              [\n                -122.34,\n                47.36\n              ],\n              [\n                -122.5,\n                48.18\n              ],\n              [\n                -122.84,\n                49\n              ],\n              [\n                -120,\n                49\n              ],\n              [\n                -117.03121,\n                49\n              ],\n              [\n                -116.04818,\n                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]\n}","volume":"155","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Xie, Yanhua 0000-0001-9814-5395","orcid":"https://orcid.org/0000-0001-9814-5395","contributorId":243290,"corporation":false,"usgs":false,"family":"Xie","given":"Yanhua","email":"","affiliations":[{"id":16925,"text":"University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":801959,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lark, Tyler J.","contributorId":211637,"corporation":false,"usgs":false,"family":"Lark","given":"Tyler","email":"","middleInitial":"J.","affiliations":[{"id":38289,"text":"Center for Sustainability and the Global Environment, University of Wisconsin-Madison, Madison, WI 53726, USA","active":true,"usgs":false}],"preferred":false,"id":801960,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brown, Jesslyn F. 0000-0002-9976-1998 jfbrown@usgs.gov","orcid":"https://orcid.org/0000-0002-9976-1998","contributorId":176609,"corporation":false,"usgs":true,"family":"Brown","given":"Jesslyn","email":"jfbrown@usgs.gov","middleInitial":"F.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":801961,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gibbs, Holly","contributorId":243291,"corporation":false,"usgs":false,"family":"Gibbs","given":"Holly","email":"","affiliations":[{"id":16925,"text":"University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":801962,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70226679,"text":"70226679 - 2019 - Distribution of contaminants in the environment and wildlife habitat use: A case study with lead and waterfowl on the Upper Texas Coast","interactions":[],"lastModifiedDate":"2021-12-03T12:59:16.19523","indexId":"70226679","displayToPublicDate":"2019-07-19T06:51:27","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1479,"text":"Ecotoxicology","active":true,"publicationSubtype":{"id":10}},"title":"Distribution of contaminants in the environment and wildlife habitat use: A case study with lead and waterfowl on the Upper Texas Coast","docAbstract":"<div id=\"Abs1-section\" class=\"c-article-section\"><div id=\"Abs1-content\" class=\"c-article-section__content\"><p>The magnitude and distribution of lead contamination remain unknown in wetland systems. Anthropogenic deposition of lead may be contributing to negative population-level effects in waterfowl and other organisms that depend on dynamic wetland habitats, particularly if they are unable to detect and differentiate levels of environmental contamination by lead. Detection of lead and behavioral response to elevated lead levels by waterfowl is poorly understood, but necessary to characterize the risk of lead-contaminated habitats. We measured the relationship between lead contamination of wetland soils and habitat use by mottled ducks (<i>Anas fulvigula</i>) on the Upper Texas Coast, USA. Mottled ducks have historically experienced disproportionate negative effects from lead exposure, and exhibit a unique nonmigratory life history that increases risk of exposure when inhabiting contaminated areas. We used spatial interpolation to estimate lead in wetland soils of the Texas Chenier Plain National Wildlife Refuge Complex. Soil lead levels varied across the refuge complex (0.01–1085.51 ppm), but greater lead concentrations frequently corresponded to areas with high densities of transmittered mottled ducks. We used soil lead concentration data and MaxENT species distribution models to quantify relationships among various habitat factors and locations of mottled ducks. Use of habitats with greater lead concentration increased during years of a major disturbance. Because mottled ducks use habitats with high concentrations of lead during periods of stress, have greater risk of exposure following major disturbance to the coastal marsh system, and no innate mechanism for avoiding the threat of lead exposure, we suggest the potential presence of an ecological trap of quality habitat that warrants further quantification at a population scale for mottled ducks.</p></div></div>","language":"English","publisher":"Springer","doi":"10.1007/s10646-019-02079-1","usgsCitation":"Kearns, B., McDowell, S.K., Moon, J.A., Rigby, E.A., Conway, W.C., and Haukos, D.A., 2019, Distribution of contaminants in the environment and wildlife habitat use: A case study with lead and waterfowl on the Upper Texas Coast: Ecotoxicology, v. 28, p. 809-824, https://doi.org/10.1007/s10646-019-02079-1.","productDescription":"16 p.","startPage":"809","endPage":"824","ipdsId":"IP-106225","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":392430,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Unied States","state":"Texas","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -96.536865234375,\n              28.536274512989916\n            ],\n            [\n              -96.0260009765625,\n              28.507315578441784\n            ],\n            [\n              -95.284423828125,\n              28.62310355452992\n            ],\n            [\n              -94.207763671875,\n              29.52567042617583\n            ],\n            [\n              -94.317626953125,\n              30.90222470517144\n            ],\n            [\n              -96.536865234375,\n              30.90222470517144\n            ],\n            [\n              -96.536865234375,\n              28.536274512989916\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"28","noUsgsAuthors":false,"publicationDate":"2019-07-19","publicationStatus":"PW","contributors":{"authors":[{"text":"Kearns, Brian","contributorId":198470,"corporation":false,"usgs":false,"family":"Kearns","given":"Brian","email":"","affiliations":[],"preferred":false,"id":827633,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McDowell, Stephen K.","contributorId":171603,"corporation":false,"usgs":false,"family":"McDowell","given":"Stephen","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":827634,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Moon, Jena A.","contributorId":171483,"corporation":false,"usgs":false,"family":"Moon","given":"Jena","email":"","middleInitial":"A.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":827635,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rigby, Elizabeth A.","contributorId":171479,"corporation":false,"usgs":false,"family":"Rigby","given":"Elizabeth","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":827636,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Conway, Warren C.","contributorId":51550,"corporation":false,"usgs":true,"family":"Conway","given":"Warren","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":827637,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Haukos, David A. 0000-0001-5372-9960 dhaukos@usgs.gov","orcid":"https://orcid.org/0000-0001-5372-9960","contributorId":3664,"corporation":false,"usgs":true,"family":"Haukos","given":"David","email":"dhaukos@usgs.gov","middleInitial":"A.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":827638,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70204409,"text":"70204409 - 2019 - FLUXNET-CH4 synthesis activity: Objectives, observations, and future directions","interactions":[],"lastModifiedDate":"2020-04-06T20:55:10.925221","indexId":"70204409","displayToPublicDate":"2019-07-17T08:57:49","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1112,"text":"Bulletin of the American Meteorological Society","onlineIssn":"1520-0477","printIssn":"0003-0007","active":true,"publicationSubtype":{"id":10}},"title":"FLUXNET-CH4 synthesis activity: Objectives, observations, and future directions","docAbstract":"<p><span>This paper describes the formation of, and initial results for, a new FLUXNET coordination network for ecosystem-scale methane (CH</span><sub>4</sub><span>) measurements at 60 sites globally, organized by the Global Carbon Project in partnership with other initiatives and regional flux tower networks. The objectives of the effort are presented along with an overview of the coverage of eddy covariance (EC) CH</span><sub>4</sub><span>&nbsp;flux measurements globally, initial results comparing CH</span><sub>4</sub><span>&nbsp;fluxes across the sites, and future research directions and needs. Annual estimates of net CH</span><sub>4</sub><span>&nbsp;fluxes across sites ranged from −0.2 ± 0.02 g C m</span><sup>–2</sup><span>&nbsp;yr</span><sup>–1</sup><span>&nbsp;for an upland forest site to 114.9 ± 13.4 g C m</span><sup>–2</sup><span>&nbsp;yr</span><sup>–1</sup><span>&nbsp;for an estuarine freshwater marsh, with fluxes exceeding 40 g C m</span><sup>–2</sup><span>&nbsp;yr</span><sup>–1</sup><span>&nbsp;at multiple sites. Average annual soil and air temperatures were found to be the strongest predictor of annual CH</span><sub>4</sub><span>&nbsp;flux across wetland sites globally. Water table position was positively correlated with annual CH</span><sub>4</sub><span>&nbsp;emissions, although only for wetland sites that were not consistently inundated throughout the year. The ratio of annual CH</span><sub>4</sub><span>&nbsp;fluxes to ecosystem respiration increased significantly with mean site temperature. Uncertainties in annual CH</span><sub>4</sub><span>&nbsp;estimates due to gap-filling and random errors were on average ±1.6 g C m</span><sup>–2</sup><span>&nbsp;yr</span><sup>–1</sup><span>&nbsp;at 95% confidence, with the relative error decreasing exponentially with increasing flux magnitude across sites. Through the analysis and synthesis of a growing EC CH</span><sub>4</sub><span>&nbsp;flux database, the controls on ecosystem CH</span><sub>4</sub><span>&nbsp;fluxes can be better understood, used to inform and validate Earth system models, and reconcile differences between land surface model- and atmospheric-based estimates of CH</span><sub>4</sub><span>&nbsp;emissions.</span></p>","language":"English","publisher":"American Meteorological Society","doi":"10.1175/BAMS-D-18-0268.1","usgsCitation":"Knox, S.H., Jackson, R.B., Poulter, B., McNicol, G., Fluet-Chouinard, E., Zhang, Z., Hugelius, G., Bousquet, P., Canadell, J.G., Saunois, M., Papale, D., Chu, H., Keenan, T.F., Baldocchi, D., Torn, M.S., Mammarella, I., Trotta, C., Aurela, M., Bohrer, G., Campbell, D.I., Cescatti, A., Chamberlain, S.D., Chen, J., Chen, W., Dengel, S., Desai, A.R., Euskirchen, E.S., Friborg, T., Gasbarra, D., Goded, I., Goeckede, M., Heimann, M., Helbig, M., Hirano, T., Hollinger, D.Y., Iwata, H., Kang, M., Klatt, J., Krauss, K., Kutzbach, L., Lohila, A., Mitra, B., Morin, T., Nilsson, M.B., Niu, S., Noormets, A., Oechel, W.C., Peichl, M., Peltola, O., Reba, M.L., Richardson, A.D., Runkle, B.R., Ryu, Y., Sachs, T., Schafer, K.V., Schmid, H.P., Shurpali, N., Sonnentag, O., Tang, A., Ueyama, M., Vargas, R., Vesala, T., Ward, E., Windham-Myers, L., Wohlfahrt, G., and Zona, D., 2019, FLUXNET-CH4 synthesis activity: Objectives, observations, and future directions: Bulletin of the American Meteorological Society, v. 100, no. 12, p. 2607-2632, https://doi.org/10.1175/BAMS-D-18-0268.1.","productDescription":"26 p.","startPage":"2607","endPage":"2632","ipdsId":"IP-102319","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true}],"links":[{"id":467447,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index 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Since 1988, the U.S. Geological Survey and a consortium of local governments have tracked water-quality conditions and trends in several of the area’s water-supply lakes and streams. This report summarizes data collected through this cooperative effort, known as the Triangle Area Water Supply Monitoring Project, during October 2015 through September 2016 (water year 2016) and October 2016 through September 2017 (water year 2017). Major findings for this period include the following:</p><ul><li>More than 5,000 individual measurements of water quality were made at a total of 20 sites—7 in the Neuse River Basin and 13 in the Cape Fear River Basin. Only the measurements from the photic zone and 1 meter below the water surface are documented in this report.</li><li>Twenty-nine water-quality properties or constituents are presented in this report; State water-quality thresholds exist for 11 of these.</li><li>All observations met State water-quality thresholds for hardness, chloride, fluoride, sulfate, and nitrate plus nitrite.</li><li>North Carolina water-quality thresholds were exceeded one or more times for dissolved oxygen, dissolved-oxygen percent saturation, pH, water temperature, turbidity, and chlorophyll <i>a</i>.</li></ul>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191077","collaboration":"Prepared in cooperation with the Triangle Area Water Supply Monitoring Project Steering Committee","usgsCitation":"Pfeifle, C.A., Cain, J.L., and Rasmussen, R.B., 2019, Triangle Area Water Supply Monitoring Project, North Carolina—Summary of monitoring activities, quality assurance, and data, October 2015–September 2017: U.S. Geological Survey Open-File Report 2019–1077, 16 p., https://doi.org/10.3133/ofr20191077.","productDescription":"Report: iv, 16 p.; Table; Data Relase","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-092956","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":365534,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1077/ofr20191077.pdf","text":"Report","size":"2.36 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1077"},{"id":365532,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F71Z43MD","text":"USGS data release","description":"USGS data release","linkHelpText":"Associated data for the Triangle Area Water Supply Monitoring Project, North Carolina, October 2015–September 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Carolina\",\"nation\":\"USA  \"}}]}","contact":"<p>Director, <a href=\"https://www.usgs.gov/centers/sa-water\" data-mce-href=\"https://www.usgs.gov/centers/sa-water\">South Atlantic Water Science Center</a><br>U.S. Geological Survey<br>720 Gracern Road<br>Stephenson Center, Suite 129<br>Columbia, SC 29210</p>","tableOfContents":"<ul><li>Abstract</li><li>Introduction</li><li>Monitoring Network</li><li>Quality Assurance</li><li>Streamflow</li><li>Water Quality</li><li>Summary</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2019-07-16","noUsgsAuthors":false,"publicationDate":"2019-07-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Pfeifle, Cassandra A. 0000-0001-5002-1625 cmendoza@usgs.gov","orcid":"https://orcid.org/0000-0001-5002-1625","contributorId":198960,"corporation":false,"usgs":true,"family":"Pfeifle","given":"Cassandra","email":"cmendoza@usgs.gov","middleInitial":"A.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":765063,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cain, Jessica L. 0000-0002-0563-8586 jcain@usgs.gov","orcid":"https://orcid.org/0000-0002-0563-8586","contributorId":198959,"corporation":false,"usgs":true,"family":"Cain","given":"Jessica","email":"jcain@usgs.gov","middleInitial":"L.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":765064,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rasmussen, Ryan B. 0000-0003-3059-5511 rbrasmus@usgs.gov","orcid":"https://orcid.org/0000-0003-3059-5511","contributorId":198961,"corporation":false,"usgs":true,"family":"Rasmussen","given":"Ryan","email":"rbrasmus@usgs.gov","middleInitial":"B.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":765065,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70204535,"text":"70204535 - 2019 - Application of multiple-population viability analysis to evaluate species recovery alternatives","interactions":[],"lastModifiedDate":"2020-04-06T20:57:23.05112","indexId":"70204535","displayToPublicDate":"2019-07-16T07:30:37","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1321,"text":"Conservation Biology","active":true,"publicationSubtype":{"id":10}},"title":"Application of multiple-population viability analysis to evaluate species recovery alternatives","docAbstract":"Population viability analysis (PVA) is a powerful conservation tool, but one that remains unapproachable for many species.  This is particularly true for species with multiple, broadly-distributed populations for which collecting suitable data can be challenging.  A recently-developed method of multiple population viability analysis (MPVA), however, addresses many limitations of traditional PVA.  We build on previous development of MPVA for Lahontan cutthroat trout (LCT), a species listed under the US Endangered Species Act which is distributed broadly across habitat fragments in the Great Basin, USA.  We simulated potential management scenarios and assessed their effects on population sizes and extinction risks in 211 streams where LCT exist or may be reintroduced.","language":"English","publisher":"Wiley","doi":"10.1111/cobi.13385","usgsCitation":"Neville, H.M., Leasure, D.R., Dauwalter, D.C., Dunham, J.B., Bjork, R., Fesenmyer, K.A., Chelgren, N., Peacock, M.M., Luce, C.H., Isaak, D.J., Carranza, L.A., Sjoberg, J., and Wenger, S., 2019, Application of multiple-population viability analysis to evaluate species recovery alternatives: Conservation Biology, v. 34, no. 2, p. 482-493, https://doi.org/10.1111/cobi.13385.","productDescription":"12 p.","startPage":"482","endPage":"493","ipdsId":"IP-102725","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":366097,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"34","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2019-09-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Neville, Helen M.","contributorId":214338,"corporation":false,"usgs":false,"family":"Neville","given":"Helen","email":"","middleInitial":"M.","affiliations":[{"id":37131,"text":"Trout Unlimited","active":true,"usgs":false}],"preferred":false,"id":767435,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Leasure, Douglas R.","contributorId":145643,"corporation":false,"usgs":false,"family":"Leasure","given":"Douglas","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":767436,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dauwalter, Daniel C.","contributorId":214339,"corporation":false,"usgs":false,"family":"Dauwalter","given":"Daniel","email":"","middleInitial":"C.","affiliations":[{"id":37131,"text":"Trout Unlimited","active":true,"usgs":false}],"preferred":false,"id":767437,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dunham, Jason B. 0000-0002-6268-0633 jdunham@usgs.gov","orcid":"https://orcid.org/0000-0002-6268-0633","contributorId":147808,"corporation":false,"usgs":true,"family":"Dunham","given":"Jason","email":"jdunham@usgs.gov","middleInitial":"B.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":767438,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bjork, Robin","contributorId":214340,"corporation":false,"usgs":false,"family":"Bjork","given":"Robin","email":"","affiliations":[{"id":37131,"text":"Trout Unlimited","active":true,"usgs":false}],"preferred":false,"id":767439,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fesenmyer, Kurt A.","contributorId":214341,"corporation":false,"usgs":false,"family":"Fesenmyer","given":"Kurt","email":"","middleInitial":"A.","affiliations":[{"id":37131,"text":"Trout Unlimited","active":true,"usgs":false}],"preferred":false,"id":767440,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Chelgren, Nathan 0000-0003-0944-9165 nchelgren@usgs.gov","orcid":"https://orcid.org/0000-0003-0944-9165","contributorId":3134,"corporation":false,"usgs":true,"family":"Chelgren","given":"Nathan","email":"nchelgren@usgs.gov","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":767441,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Peacock, Mary M.","contributorId":167605,"corporation":false,"usgs":false,"family":"Peacock","given":"Mary","email":"","middleInitial":"M.","affiliations":[{"id":24774,"text":"Department of Natural Resources, College of Agriculture and Life","active":true,"usgs":false}],"preferred":false,"id":767442,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Luce, Charles H.","contributorId":177837,"corporation":false,"usgs":false,"family":"Luce","given":"Charles","email":"","middleInitial":"H.","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":767443,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Isaak, Daniel J.","contributorId":177835,"corporation":false,"usgs":false,"family":"Isaak","given":"Daniel","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":767444,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Carranza, Lee Ann","contributorId":217753,"corporation":false,"usgs":false,"family":"Carranza","given":"Lee","email":"","middleInitial":"Ann","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":767445,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Sjoberg, Jon","contributorId":217754,"corporation":false,"usgs":false,"family":"Sjoberg","given":"Jon","email":"","affiliations":[{"id":27489,"text":"Nevada Department of Wildlife","active":true,"usgs":false}],"preferred":false,"id":767446,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Wenger, Seth J.","contributorId":177838,"corporation":false,"usgs":false,"family":"Wenger","given":"Seth 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,{"id":70204498,"text":"70204498 - 2019 - Spatial capture-recapture reveals age- and sex-specific survival and movement in stream amphibians","interactions":[],"lastModifiedDate":"2019-08-29T11:58:54","indexId":"70204498","displayToPublicDate":"2019-07-15T15:17:27","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2932,"text":"Oecologia","active":true,"publicationSubtype":{"id":10}},"title":"Spatial capture-recapture reveals age- and sex-specific survival and movement in stream amphibians","docAbstract":"Life history information sets the foundation for our understanding of ecology and conservation requirements. For many species, this information is lacking even for basic demographic rates such as survival and movement. When survival and movement estimates are available, they are often derived from mixed demographic groups and do not consider differences among life stages or sexes, which is critical because life stages and sexes often contribute differentially to population dynamics. We used hierarchical models informed with spatial capture-mark-recapture data of Ascaphus montanus (Rocky Mountain tailed frog) in 5 streams and A. truei (coastal tailed frog) in 1 stream to estimate variation in survival and movement by sex and age, represented by size. By incorporating survival and movement into a single model, we were able to estimate both parameters with limited bias. Annual survival was similar between sexes of A. montanus (females = 0.885 [95% CI: 0.614–1], males = 0.901 [0.657–1]), but was slightly higher for female A. truei (0.836 [0.560–0.993]) than for males (0.664 [0.354–0.962]). Survival of A. montanus peaked at mid-age, suggesting that lower survival of young and actuarial senescence may influence population demographics. Our models suggest that younger A. montanus moved farther than older individuals, and that females moved farther than males in both species. Our results provide uncommon insight into age- and sex-specific rates of survival and movement that are crucial elements of life-history strategies and are important for modeling population growth and prescribing conservation actions.","language":"English","publisher":"Springer","doi":"10.1007/s00442-019-04464-3","usgsCitation":"Honeycutt, R.K., Garwood, J.M., Lowe, W.H., and Hossack, B.R., 2019, Spatial capture-recapture reveals age- and sex-specific survival and movement in stream amphibians: Oecologia, v. 190, no. 4, p. 821-833, https://doi.org/10.1007/s00442-019-04464-3.","productDescription":"13 p.","startPage":"821","endPage":"833","ipdsId":"IP-086212","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":366004,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":366002,"type":{"id":15,"text":"Index Page"},"url":"https://link.springer.com/content/pdf/10.1007%2Fs00442-019-04464-3.pdf"}],"volume":"190","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-07-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Honeycutt, R. Ken 0000-0002-7157-7195 rhoneycutt@usgs.gov","orcid":"https://orcid.org/0000-0002-7157-7195","contributorId":156282,"corporation":false,"usgs":true,"family":"Honeycutt","given":"R.","email":"rhoneycutt@usgs.gov","middleInitial":"Ken","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":767262,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Garwood, Justin M","contributorId":217674,"corporation":false,"usgs":false,"family":"Garwood","given":"Justin","email":"","middleInitial":"M","affiliations":[{"id":39681,"text":"California Dept fish wildlife","active":true,"usgs":false}],"preferred":false,"id":767263,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lowe, Winsor H.","contributorId":126722,"corporation":false,"usgs":false,"family":"Lowe","given":"Winsor","email":"","middleInitial":"H.","affiliations":[{"id":6577,"text":"University of Montana, Division of Biological Sciences, Missoula, MT, 59812, USA.","active":true,"usgs":false}],"preferred":false,"id":767264,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hossack, Blake R. 0000-0001-7456-9564 blake_hossack@usgs.gov","orcid":"https://orcid.org/0000-0001-7456-9564","contributorId":1177,"corporation":false,"usgs":true,"family":"Hossack","given":"Blake","email":"blake_hossack@usgs.gov","middleInitial":"R.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":767265,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70204134,"text":"fs20193002 - 2019 - Assessment of continuous oil resources in the Eastern Great Basin Province of Nevada, Utah, and Idaho, 2018","interactions":[],"lastModifiedDate":"2019-07-16T09:12:25","indexId":"fs20193002","displayToPublicDate":"2019-07-15T13:15:00","publicationYear":"2019","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":"2019-3002","displayTitle":"Assessment of Continuous Oil Resources in the Eastern Great Basin Province of Nevada, Utah, and Idaho, 2018","title":"Assessment of continuous oil resources in the Eastern Great Basin Province of Nevada, Utah, and Idaho, 2018","docAbstract":"<p>The U.S. Geological Survey (USGS) quantitatively assessed the&nbsp;potential for undiscovered, technically recoverable continuous oil and gas&nbsp;resources in the Eastern Great Basin Province (Anna and others, 2007) of&nbsp;Nevada, Utah, and Idaho (fig. 1). The assessment focused on the area of&nbsp;the province between the Roberts Mountains and Sevier thrust systems&nbsp;(Peterson, 1994). The major petroleum source rocks within this area are the&nbsp;Upper Devonian–Lower Mississippian Pilot Shale and the Mississippian&nbsp;Chainman Formation (Gutschick and Rodriquez, 1979; Poole and Claypool,&nbsp;1984; Giles, 1994; Trexler and others, 1995). The geologic model applied&nbsp;to the Pilot Shale and shales in the Chainman Formation is for these shales&nbsp;to have achieved generative maturity for oil by burial to at least 8,700 feet&nbsp;(2,652 meters) within some of the Neogene extensional basins (Grabb, 1994;&nbsp;Anna and others, 2007). Areas that satisfy this depth requirement were&nbsp;defined using modeled gravity data that were calibrated to the petroleum&nbsp;system in Railroad Valley and Pine Valley in Nevada (Barker and Peterson,&nbsp;1991; Ïnan and Davis, 1994; Meissner, 1995; Anna and others, 2007).&nbsp;</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20193002","usgsCitation":"Schenk, C.J., Mercier, T.J., Woodall, C.A., Finn, T.M., Gaswirth, S.B., Marra, K.R., Le, P.A., Brownfield, M.E., Leathers-Miller, H.M., Drake, R.M., II, and Kinney, S.A., 2019, Assessment of continuous oil resources in the Eastern Great Basin Province of Nevada, Utah, and Idaho, 2018: U.S. Geological Survey Fact Sheet 2019–3002, 2 p., https://doi.org/10.3133/fs20193002.","productDescription":"2 p.","onlineOnly":"N","ipdsId":"IP-101431","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":365379,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2019/3002/coverthb.jpg"},{"id":365364,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2019/3002/fs20193002.pdf","text":"Report","size":"660 kB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2019-3002"}],"country":"United States","state":"Idaho, Nevada, Utah","otherGeospatial":"Eastern Great Basin Province","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -117.02636718749999,\n              42.00032514831621\n            ],\n            [\n              -117.0703125,\n              36.77409249464195\n            ],\n            [\n              -114.60937499999999,\n              34.994003757575776\n    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PSC"},"publishedDate":"2019-07-15","noUsgsAuthors":false,"publicationDate":"2019-07-15","publicationStatus":"PW","contributors":{"authors":[{"text":"Schenk, Christopher J. 0000-0002-0248-7305 schenk@usgs.gov","orcid":"https://orcid.org/0000-0002-0248-7305","contributorId":826,"corporation":false,"usgs":true,"family":"Schenk","given":"Christopher","email":"schenk@usgs.gov","middleInitial":"J.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":765657,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mercier, Tracey J. 0000-0002-8232-525X tmercier@usgs.gov","orcid":"https://orcid.org/0000-0002-8232-525X","contributorId":2847,"corporation":false,"usgs":true,"family":"Mercier","given":"Tracey","email":"tmercier@usgs.gov","middleInitial":"J.","affiliations":[{"id":164,"text":"Central Energy Resources Science 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II 0000-0002-1770-4667","orcid":"https://orcid.org/0000-0002-1770-4667","contributorId":206291,"corporation":false,"usgs":true,"family":"Drake","given":"Ronald M.","suffix":"II","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":765666,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Kinney, Scott A. 0000-0001-5008-5813 skinney@usgs.gov","orcid":"https://orcid.org/0000-0001-5008-5813","contributorId":1395,"corporation":false,"usgs":true,"family":"Kinney","given":"Scott","email":"skinney@usgs.gov","middleInitial":"A.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":765689,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
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