{"pageNumber":"1195","pageRowStart":"29850","pageSize":"25","recordCount":184858,"records":[{"id":70159861,"text":"70159861 - 2015 - Mortality patterns in endangered Hawaiian geese (Nene; Branta sandvicensis)","interactions":[],"lastModifiedDate":"2016-02-08T10:32:37","indexId":"70159861","displayToPublicDate":"2015-12-01T12:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2507,"text":"Journal of Wildlife Diseases","active":true,"publicationSubtype":{"id":10}},"title":"Mortality patterns in endangered Hawaiian geese (Nene; Branta sandvicensis)","docAbstract":"

Understanding causes of death can aid management and recovery of endangered bird populations. Toward those ends, we systematically examined 300 carcasses of endangered Hawaiian Geese (Nene; Branta sandvicensis) from Hawaii, Maui, Molokai, and Kauai between 1992 and 2013. The most common cause of death was emaciation, followed by trauma (vehicular strikes and predation), and infectious/inflammatory diseases of which toxoplasmosis (infection with Toxoplasma gondii) predominated. Toxicoses were less common and were dominated by lead poisoning or botulism. For captive birds, inflammatory conditions predominated, whereas emaciation, trauma, and inflammation were common in free-ranging birds. Mortality patterns were similar for males and females. Trauma predominated for adults, whereas emaciation was more common for goslings. Causes of death varied among islands, with trauma dominating on Molokai, emaciation and inflammation on Kauai, emaciation on Hawaii, and inflammation and trauma on Maui. Understanding habitat or genetic-related factors that predispose Nene (particularly goslings) to emaciation might reduce the impact of this finding. In addition, trauma and infection with T. gondii are human-related problems that may be attenuated if effectively managed (e.g., road signs, enforcement of speed limits, feral cat [Felis catus] control). Such management actions might serve to enhance recovery of this endangered species.

","language":"English","publisher":"BioOne","doi":"10.7589/2014-11-256","usgsCitation":"Work, T.M., Dagenais, J., Rameyer, R., and Breeden, R., 2015, Mortality patterns in endangered Hawaiian geese (Nene; Branta sandvicensis): Journal of Wildlife Diseases, v. 51, no. 3, p. 688-695, https://doi.org/10.7589/2014-11-256.","productDescription":"8 p.","startPage":"688","endPage":"695","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"1992-01-01","temporalEnd":"2013-12-31","ipdsId":"IP-062090","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":311762,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"51","issue":"3","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"565ec4b0e4b071e7ea544413","contributors":{"authors":[{"text":"Work, Thierry M. 0000-0002-4426-9090 thierry_work@usgs.gov","orcid":"https://orcid.org/0000-0002-4426-9090","contributorId":1187,"corporation":false,"usgs":true,"family":"Work","given":"Thierry","email":"thierry_work@usgs.gov","middleInitial":"M.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":580742,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dagenais, Julie 0000-0001-5560-9946 jdagenais@usgs.gov","orcid":"https://orcid.org/0000-0001-5560-9946","contributorId":5955,"corporation":false,"usgs":true,"family":"Dagenais","given":"Julie","email":"jdagenais@usgs.gov","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":580743,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rameyer, Robert 0000-0002-2145-1746 bob_rameyer@usgs.gov","orcid":"https://orcid.org/0000-0002-2145-1746","contributorId":150128,"corporation":false,"usgs":true,"family":"Rameyer","given":"Robert","email":"bob_rameyer@usgs.gov","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":580744,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Breeden, Renee 0000-0001-5910-3627 rbreeden@usgs.gov","orcid":"https://orcid.org/0000-0001-5910-3627","contributorId":149679,"corporation":false,"usgs":true,"family":"Breeden","given":"Renee","email":"rbreeden@usgs.gov","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":580745,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70159860,"text":"70159860 - 2015 - Increased land use by Chukchi Sea polar bears in relation to changing sea ice conditions","interactions":[],"lastModifiedDate":"2018-10-30T14:24:46","indexId":"70159860","displayToPublicDate":"2015-12-01T12:00:00","publicationYear":"2015","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":"Increased land use by Chukchi Sea polar bears in relation to changing sea ice conditions","docAbstract":"

Recent observations suggest that polar bears (Ursus maritimus) are increasingly using land habitats in some parts of their range, where they have minimal access to their preferred prey, likely in response to loss of their sea ice habitat associated with climatic warming. We used location data from female polar bears fit with satellite radio collars to compare land use patterns in the Chukchi Sea between two periods (1986–1995 and 2008–2013) when substantial summer sea-ice loss occurred. In both time periods, polar bears predominantly occupied sea-ice, although land was used during the summer sea-ice retreat and during the winter for maternal denning. However, the proportion of bears on land for > 7 days between August and October increased between the two periods from 20.0% to 38.9%, and the average duration on land increased by 30 days. The majority of bears that used land in the summer and for denning came to Wrangel and Herald Islands (Russia), highlighting the importance of these northernmost land habitats to Chukchi Sea polar bears. Where bears summered and denned, and how long they spent there, was related to the timing and duration of sea ice retreat. Our results are consistent with other studies supporting increased land use as a common response of polar bears to sea-ice loss. Implications of increased land use for Chukchi Sea polar bears are unclear, because a recent study observed no change in body condition or reproductive indices between the two periods considered here. This result suggests that the ecology of this region may provide a degree of resilience to sea ice loss. However, projections of continued sea ice loss suggest that polar bears in the Chukchi Sea and other parts of the Arctic may increasingly use land habitats in the future, which has the potential to increase nutritional stress and human-polar bear interactions.

","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0142213","usgsCitation":"Rode, K.D., Wilson, R.H., Regehr, E.V., St. Martin, M., Douglas, D., and Olson, J., 2015, Increased land use by Chukchi Sea polar bears in relation to changing sea ice conditions: PLoS ONE, v. 10, no. 11, e0142213; 18 p., https://doi.org/10.1371/journal.pone.0142213.","productDescription":"e0142213; 18 p.","numberOfPages":"18","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064932","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":471592,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0142213","text":"Publisher Index Page"},{"id":438661,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7BZ643N","text":"USGS data release","linkHelpText":"Chukchi Sea Polar Bear Locations, 1985-1996"},{"id":311761,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Chukchi Sea","volume":"10","issue":"11","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-11-18","publicationStatus":"PW","scienceBaseUri":"565ec4b0e4b071e7ea544411","contributors":{"authors":[{"text":"Rode, Karyn D. 0000-0002-3328-8202 krode@usgs.gov","orcid":"https://orcid.org/0000-0002-3328-8202","contributorId":5053,"corporation":false,"usgs":true,"family":"Rode","given":"Karyn","email":"krode@usgs.gov","middleInitial":"D.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":580721,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wilson, Ryan H. 0000-0001-7740-7771","orcid":"https://orcid.org/0000-0001-7740-7771","contributorId":130989,"corporation":false,"usgs":false,"family":"Wilson","given":"Ryan","email":"","middleInitial":"H.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":580722,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Regehr, Eric V. 0000-0003-4487-3105","orcid":"https://orcid.org/0000-0003-4487-3105","contributorId":66364,"corporation":false,"usgs":false,"family":"Regehr","given":"Eric","email":"","middleInitial":"V.","affiliations":[{"id":12428,"text":"U. S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":580723,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"St. Martin, Michelle","contributorId":150114,"corporation":false,"usgs":false,"family":"St. Martin","given":"Michelle","email":"","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":580724,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Douglas, David C. 0000-0003-0186-1104 ddouglas@usgs.gov","orcid":"https://orcid.org/0000-0003-0186-1104","contributorId":150115,"corporation":false,"usgs":true,"family":"Douglas","given":"David C.","email":"ddouglas@usgs.gov","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":580725,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Olson, Jay","contributorId":150116,"corporation":false,"usgs":false,"family":"Olson","given":"Jay","affiliations":[{"id":6681,"text":"Brigham Young University","active":true,"usgs":false}],"preferred":false,"id":580726,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70160371,"text":"70160371 - 2015 - Evaluation of the U.S. Geological Survey standard elevation products in a two-dimensional hydraulic modeling application for a low relief coastal floodplain","interactions":[],"lastModifiedDate":"2015-12-23T11:00:01","indexId":"70160371","displayToPublicDate":"2015-12-01T12:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of the U.S. Geological Survey standard elevation products in a two-dimensional hydraulic modeling application for a low relief coastal floodplain","docAbstract":"

Growing use of two-dimensional (2-D) hydraulic models has created a need for high resolution data to support flood volume estimates, floodplain specific engineering data, and accurate flood inundation scenarios. Elevation data are a critical input to these models that guide the flood-wave across the landscape allowing the computation of valuable engineering specific data that provides a better understanding of flooding impacts on structures, debris movement, bed scour, and direction. High resolution elevation data are becoming publicly available that can benefit the 2-D flood modeling community. Comparison of these newly available data with legacy data suggests that better modeling outcomes are achieved by using 3D Elevation Program (3DEP) lidar point data and the derived 1 m Digital Elevation Model (DEM) product relative to the legacy 3 m, 10 m, or 30 m products currently available in the U.S. Geological Survey (USGS) National Elevation Dataset. Within the low topographic relief of a coastal floodplain, the newer 3DEP data better resolved elevations within the forested and swampy areas achieving simulations that compared well with a historic flooding event. Results show that the 1 m DEM derived from 3DEP lidar source provides a more conservative estimate of specific energy, static pressure, and impact pressure for grid elements at maximum flow relative to the legacy DEM data. Better flood simulations are critically important in coastal floodplains where climate change driven storm frequency and sea level rise will contribute to more frequent flooding events.

","language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam","doi":"10.1016/j.jhydrol.2015.10.051","usgsCitation":"Witt, E.C., 2015, Evaluation of the U.S. Geological Survey standard elevation products in a two-dimensional hydraulic modeling application for a low relief coastal floodplain: Journal of Hydrology, v. 531, no. 3, p. 759-767, https://doi.org/10.1016/j.jhydrol.2015.10.051.","productDescription":"9 p.","startPage":"759","endPage":"767","numberOfPages":"9","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066431","costCenters":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"links":[{"id":312794,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina","city":"Greenville","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.3298454284668,\n 35.628488848361336\n ],\n [\n -77.32804298400879,\n 35.60330002507124\n ],\n [\n -77.36005783081055,\n 35.604346810028304\n ],\n [\n -77.37645149230957,\n 35.61174370007563\n ],\n [\n -77.37722396850586,\n 35.62583776685229\n ],\n [\n -77.3298454284668,\n 35.628488848361336\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"531","issue":"3","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"567bd3bbe4b0a04ef491a1f9","contributors":{"authors":[{"text":"Witt, Emitt C. III 0000-0002-1814-7807 ecwitt@usgs.gov","orcid":"https://orcid.org/0000-0002-1814-7807","contributorId":1612,"corporation":false,"usgs":true,"family":"Witt","given":"Emitt","suffix":"III","email":"ecwitt@usgs.gov","middleInitial":"C.","affiliations":[{"id":404,"text":"NGTOC Rolla","active":true,"usgs":true},{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"preferred":true,"id":582830,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70170986,"text":"70170986 - 2015 - Probabilistic 3-D time-lapse inversion of magnetotelluric data: Application to an enhanced geothermal system","interactions":[],"lastModifiedDate":"2016-05-17T10:44:52","indexId":"70170986","displayToPublicDate":"2015-12-01T11:45:00","publicationYear":"2015","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":"Probabilistic 3-D time-lapse inversion of magnetotelluric data: Application to an enhanced geothermal system","docAbstract":"

Surface-based monitoring of mass transfer caused by injections and extractions in deep boreholes is crucial to maximize oil, gas and geothermal production. Inductive electromagnetic methods, such as magnetotellurics, are appealing for these applications due to their large penetration depths and sensitivity to changes in fluid conductivity and fracture connectivity. In this work, we propose a 3-D Markov chain Monte Carlo inversion of time-lapse magnetotelluric data to image mass transfer following a saline fluid injection. The inversion estimates the posterior probability density function of the resulting plume, and thereby quantifies model uncertainty. To decrease computation times, we base the parametrization on a reduced Legendre moment decomposition of the plume. A synthetic test shows that our methodology is effective when the electrical resistivity structure prior to the injection is well known. The centre of mass and spread of the plume are well retrieved.We then apply our inversion strategy to an injection experiment in an enhanced geothermal system at Paralana, South Australia, and compare it to a 3-D deterministic time-lapse inversion. The latter retrieves resistivity changes that are more shallow than the actual injection interval, whereas the probabilistic inversion retrieves plumes that are located at the correct depths and oriented in a preferential north-south direction. To explain the time-lapse data, the inversion requires unrealistically large resistivity changes with respect to the base model. We suggest that this is partly explained by unaccounted subsurface heterogeneities in the base model from which time-lapse changes are inferred.

","language":"English","publisher":"Blackwell Science","publisherLocation":"Oxford","doi":"10.1093/gji/ggv406","usgsCitation":"Rosas-Carbajal, M., Linde, N., Peacock, J.R., Zyserman, F.I., Kalscheuer, T., and Thiel, S., 2015, Probabilistic 3-D time-lapse inversion of magnetotelluric data: Application to an enhanced geothermal system: Geophysical Journal International, v. 203, no. 3, p. 1946-1960, https://doi.org/10.1093/gji/ggv406.","productDescription":"15 p.","startPage":"1946","endPage":"1960","numberOfPages":"15","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068406","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":471594,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/gji/ggv406","text":"Publisher Index Page"},{"id":321296,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"203","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-10-30","publicationStatus":"PW","scienceBaseUri":"574d661fe4b07e28b6684bbd","contributors":{"authors":[{"text":"Rosas-Carbajal, Marina","contributorId":169322,"corporation":false,"usgs":false,"family":"Rosas-Carbajal","given":"Marina","affiliations":[{"id":25473,"text":"Applied and Environmental Group, University of Lausanne, Switzerland","active":true,"usgs":false}],"preferred":false,"id":629336,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Linde, Nicolas","contributorId":169323,"corporation":false,"usgs":false,"family":"Linde","given":"Nicolas","email":"","affiliations":[{"id":25474,"text":"Institut de Physique du Globe, Paris, France","active":true,"usgs":false}],"preferred":false,"id":629337,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Peacock, Jared R. 0000-0002-0439-0224 jpeacock@usgs.gov","orcid":"https://orcid.org/0000-0002-0439-0224","contributorId":4996,"corporation":false,"usgs":true,"family":"Peacock","given":"Jared","email":"jpeacock@usgs.gov","middleInitial":"R.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":629335,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zyserman, F. I.","contributorId":169324,"corporation":false,"usgs":false,"family":"Zyserman","given":"F.","email":"","middleInitial":"I.","affiliations":[{"id":25475,"text":"CONICET-Facultad de Ciencias Astronomicas y Geofisicas, Universidad Nacional de La Plata, Argentina","active":true,"usgs":false}],"preferred":false,"id":629338,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kalscheuer, Thomas","contributorId":169325,"corporation":false,"usgs":false,"family":"Kalscheuer","given":"Thomas","email":"","affiliations":[{"id":25476,"text":"Department of Earth Sciences, Uppsala University, Sweden","active":true,"usgs":false}],"preferred":false,"id":629339,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Thiel, Stephan","contributorId":169326,"corporation":false,"usgs":false,"family":"Thiel","given":"Stephan","email":"","affiliations":[{"id":25477,"text":"Geological Survey of South Australia","active":true,"usgs":false}],"preferred":false,"id":629340,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70160278,"text":"70160278 - 2015 - Validation of mercury tip-switch and accelerometer activity sensors for identifying resting and active behavior in bears","interactions":[],"lastModifiedDate":"2018-03-17T17:35:23","indexId":"70160278","displayToPublicDate":"2015-12-01T11:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3671,"text":"Ursus","active":true,"publicationSubtype":{"id":10}},"title":"Validation of mercury tip-switch and accelerometer activity sensors for identifying resting and active behavior in bears","docAbstract":"

Activity sensors are often included in wildlife transmitters and can provide information on the behavior and activity patterns of animals remotely. However, interpreting activity-sensor data relative to animal behavior can be difficult if animals cannot be continuously observed. In this study, we examined the performance of a mercury tip-switch and a tri-axial accelerometer housed in collars to determine whether sensor data can be accurately classified as resting and active behaviors and whether data are comparable for the 2 sensor types. Five captive bears (3 polar [Ursus maritimus] and 2 brown [U. arctos horribilis]) were fitted with a collar specially designed to internally house the sensors. The bears’ behaviors were recorded, classified, and then compared with sensor readings. A separate tri-axial accelerometer that sampled continuously at a higher frequency and provided raw acceleration values from 3 axes was also mounted on the collar to compare with the lower resolution sensors. Both accelerometers more accurately identified resting and active behaviors at time intervals ranging from 1 minute to 1 hour (≥91.1% accuracy) compared with the mercury tip-switch (range = 75.5–86.3%). However, mercury tip-switch accuracy improved when sampled at longer intervals (e.g., 30–60 min). Data from the lower resolution accelerometer, but not the mercury tip-switch, accurately predicted the percentage of time spent resting during an hour. Although the number of bears available for this study was small, our results suggest that these activity sensors can remotely identify resting versus active behaviors across most time intervals. We recommend that investigators consider both study objectives and the variation in accuracy of classifying resting and active behaviors reported here when determining sampling interval.

","language":"English","publisher":"International Association for Bear Research and Management","publisherLocation":"New York, NY","doi":"10.2192/URSUS-D-14-00031.1","usgsCitation":"Jasmine Ware, Rode, K.D., Pagano, A.M., Bromaghin, J.F., Robbins, C.T., Erlenbach, J., Jensen, S., Amy Cutting, Nicassio-Hiskey, N., Amy Hash, Owen, M.A., and Heiko Jansen, 2015, Validation of mercury tip-switch and accelerometer activity sensors for identifying resting and active behavior in bears: Ursus, v. 26, no. 2, p. 8-18, https://doi.org/10.2192/URSUS-D-14-00031.1.","productDescription":"11 p.","startPage":"8","endPage":"18","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059830","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":312353,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"26","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5672994ae4b01a7f82451dc6","contributors":{"authors":[{"text":"Jasmine Ware","contributorId":150612,"corporation":false,"usgs":false,"family":"Jasmine Ware","affiliations":[{"id":5127,"text":"Washington State University, P.O. Box 644236, Pullman, WA 99164","active":true,"usgs":false}],"preferred":false,"id":582414,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rode, Karyn D. 0000-0002-3328-8202 krode@usgs.gov","orcid":"https://orcid.org/0000-0002-3328-8202","contributorId":5053,"corporation":false,"usgs":true,"family":"Rode","given":"Karyn","email":"krode@usgs.gov","middleInitial":"D.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":582413,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pagano, Anthony M. 0000-0003-2176-0909 apagano@usgs.gov","orcid":"https://orcid.org/0000-0003-2176-0909","contributorId":3884,"corporation":false,"usgs":true,"family":"Pagano","given":"Anthony","email":"apagano@usgs.gov","middleInitial":"M.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":582415,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bromaghin, Jeffrey F. 0000-0002-7209-9500 jbromaghin@usgs.gov","orcid":"https://orcid.org/0000-0002-7209-9500","contributorId":139899,"corporation":false,"usgs":true,"family":"Bromaghin","given":"Jeffrey","email":"jbromaghin@usgs.gov","middleInitial":"F.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":582421,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Robbins, Charles T.","contributorId":32436,"corporation":false,"usgs":false,"family":"Robbins","given":"Charles","email":"","middleInitial":"T.","affiliations":[{"id":5132,"text":"Washington State University, Pullman","active":true,"usgs":false}],"preferred":false,"id":582416,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Erlenbach, Joy","contributorId":150614,"corporation":false,"usgs":false,"family":"Erlenbach","given":"Joy","email":"","affiliations":[{"id":5127,"text":"Washington State University, P.O. Box 644236, Pullman, WA 99164","active":true,"usgs":false}],"preferred":false,"id":582417,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jensen, Shannon","contributorId":150619,"corporation":false,"usgs":false,"family":"Jensen","given":"Shannon","email":"","affiliations":[{"id":18051,"text":"Alaska Zoo","active":true,"usgs":false}],"preferred":false,"id":582423,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Amy Cutting","contributorId":150615,"corporation":false,"usgs":false,"family":"Amy Cutting","affiliations":[{"id":18050,"text":"Oregon Zoo","active":true,"usgs":false}],"preferred":false,"id":582418,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Nicassio-Hiskey, Nicole","contributorId":150616,"corporation":false,"usgs":false,"family":"Nicassio-Hiskey","given":"Nicole","email":"","affiliations":[{"id":18050,"text":"Oregon Zoo","active":true,"usgs":false}],"preferred":false,"id":582419,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Amy Hash","contributorId":150617,"corporation":false,"usgs":false,"family":"Amy Hash","affiliations":[{"id":18050,"text":"Oregon Zoo","active":true,"usgs":false}],"preferred":false,"id":582420,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Owen, Megan A.","contributorId":138918,"corporation":false,"usgs":false,"family":"Owen","given":"Megan","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":582424,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Heiko Jansen","contributorId":150618,"corporation":false,"usgs":false,"family":"Heiko Jansen","affiliations":[{"id":5127,"text":"Washington State University, P.O. Box 644236, Pullman, WA 99164","active":true,"usgs":false}],"preferred":false,"id":582422,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70164443,"text":"70164443 - 2015 - White-tailed Deer (Odocoileus virginianus) fawn risk from Gray Wolf (Canis lupus) predation during summer","interactions":[],"lastModifiedDate":"2020-12-17T21:28:28.992773","indexId":"70164443","displayToPublicDate":"2015-12-01T11:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1163,"text":"Canadian Field-Naturalist","active":true,"publicationSubtype":{"id":10}},"title":"White-tailed Deer (Odocoileus virginianus) fawn risk from Gray Wolf (Canis lupus) predation during summer","docAbstract":"

Little is known about how often various prey animals are at risk of predation by Gray Wolves (Canis lupus). We used a system to monitor the presence during the day of two radio-collared Gray Wolves within 2 km of a radio-collared White-tailed Deer (Odocoileus virginianus) with a fawn or fawns in August 2013 in the Superior National Forest of northeastern Minnesota. We concluded that the fawn or fawns were at risk of predation by at least one wolf at least daily.

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David 0000-0003-3944-7769 david_mech@usgs.gov","orcid":"https://orcid.org/0000-0003-3944-7769","contributorId":2518,"corporation":false,"usgs":true,"family":"Mech","given":"L.","email":"david_mech@usgs.gov","middleInitial":"David","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":597369,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Morris, Aaron","contributorId":156298,"corporation":false,"usgs":false,"family":"Morris","given":"Aaron","email":"","affiliations":[{"id":20305,"text":"Hamline University, St. Paul, MN","active":true,"usgs":false}],"preferred":false,"id":597370,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barber-Meyer, Shannon M. 0000-0002-3048-2616 sbarber-meyer@usgs.gov","orcid":"https://orcid.org/0000-0002-3048-2616","contributorId":4422,"corporation":false,"usgs":true,"family":"Barber-Meyer","given":"Shannon M.","email":"sbarber-meyer@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":597371,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70159871,"text":"70159871 - 2015 - Alpine biodiversity and assisted migration: The case of the American pika (Ochotona princeps)","interactions":[],"lastModifiedDate":"2016-01-25T12:34:42","indexId":"70159871","displayToPublicDate":"2015-12-01T11:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1004,"text":"Biodiversity","active":true,"publicationSubtype":{"id":10}},"title":"Alpine biodiversity and assisted migration: The case of the American pika (Ochotona princeps)","docAbstract":"

Alpine mammals are predicted to be among the species most threatened by climate change, due to the projected loss and further fragmentation of alpine habitats. As temperature or precipitation regimes change, alpine mammals may also be faced with insurmountable barriers to dispersal. The slow rate or inability to adjust to rapidly shifting environmental conditions may cause isolated alpine species to become locally extirpated, resulting in reduced biodiversity. One proposed method for mitigating the impacts of alpine species loss is assisted migration. This method, which involves translocating a species to an area with more favourable climate and habitat characteristics, has become the subject of debate and controversy in the conservation community. The uncertainty associated with climate change projections, coupled with the thermal sensitivity of many alpine mammals, makes it difficult to a priori assess the efficacy of this technique as a conservation management tool. Here we present the American pika (Ochotona princeps) as a case study. American pikas inhabit rocky areas throughout the western US, and populations in some mountainous areas have become locally extirpated in recent years. We review known climatic and habitat requirements for this species, and also propose protocols designed to reliably identify favourable relocation areas. We present data related to the physiological constraints of this species and outline specific requirements which must be addressed for translocation of viable populations, including wildlife disease and genetic considerations. Finally, we discuss potential impacts on other alpine species and alpine communities, and overall implications for conserving alpine biodiversity in a changing climate.

","language":"English","publisher":"Taylor & Francis","publisherLocation":"London","doi":"10.1080/14888386.2015.1112304","usgsCitation":"Wilkening, J.L., Ray, C., Ramsay, N.G., and Klingler, K., 2015, Alpine biodiversity and assisted migration: The case of the American pika (Ochotona princeps): Biodiversity, v. 16, no. 4, p. 1-13, https://doi.org/10.1080/14888386.2015.1112304.","productDescription":"13 p.","startPage":"1","endPage":"13","numberOfPages":"13","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-067134","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":311784,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.04687499999999,\n 49.095452162534826\n ],\n [\n -105.29296874999999,\n 49.095452162534826\n ],\n [\n -104.23828125,\n 44.902577996288876\n ],\n [\n -103.88671875,\n 40.979898069620155\n ],\n [\n -103.798828125,\n 38.548165423046584\n ],\n [\n -103.271484375,\n 36.24427318493909\n ],\n [\n -103.095703125,\n 34.379712580462204\n ],\n [\n -103.0078125,\n 32.10118973232094\n ],\n [\n -104.4140625,\n 31.50362930577303\n ],\n [\n -106.34765625,\n 31.57853542647338\n ],\n [\n -108.19335937499999,\n 31.728167146023935\n ],\n [\n -111.357421875,\n 31.353636941500987\n ],\n [\n -114.78515624999999,\n 32.694865977875075\n ],\n [\n -117.42187500000001,\n 32.694865977875075\n ],\n [\n -118.125,\n 33.211116472416855\n ],\n [\n -119.44335937499999,\n 33.94335994657882\n ],\n [\n -121.025390625,\n 34.161818161230386\n ],\n [\n -121.81640624999999,\n 35.24561909420681\n ],\n [\n -123.22265625000001,\n 37.16031654673677\n ],\n [\n -124.365234375,\n 38.61687046392973\n ],\n [\n -124.45312499999999,\n 39.774769485295465\n ],\n [\n -125.15625000000001,\n 41.244772343082076\n ],\n [\n -124.892578125,\n 41.902277040963696\n ],\n [\n -125.24414062499999,\n 43.51668853502909\n ],\n [\n -124.71679687499999,\n 45.27488643704894\n ],\n [\n -124.71679687499999,\n 47.2195681123155\n ],\n [\n -125.068359375,\n 48.574789910928864\n ],\n [\n -123.31054687499999,\n 48.3416461723746\n ],\n [\n -123.04687499999999,\n 49.095452162534826\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"16","issue":"4","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5660243ae4b071e7ea544ca5","contributors":{"authors":[{"text":"Wilkening, Jennifer L. 0000-0001-8748-4578","orcid":"https://orcid.org/0000-0001-8748-4578","contributorId":127685,"corporation":false,"usgs":false,"family":"Wilkening","given":"Jennifer","email":"","middleInitial":"L.","affiliations":[{"id":7111,"text":"U. Colorado, Boulder, Dept. Ecology & Evol.Biol., PhD Student","active":true,"usgs":false}],"preferred":false,"id":580835,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ray, Chris","contributorId":150148,"corporation":false,"usgs":false,"family":"Ray","given":"Chris","email":"","affiliations":[{"id":17921,"text":"Department of Ecology and Evolutionary Biology, University of Colorado, Boulder, Colorado","active":true,"usgs":false}],"preferred":false,"id":580836,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ramsay, Nathan G. nramsay@usgs.gov","contributorId":3191,"corporation":false,"usgs":true,"family":"Ramsay","given":"Nathan","email":"nramsay@usgs.gov","middleInitial":"G.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":580834,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Klingler, Kelly","contributorId":150149,"corporation":false,"usgs":false,"family":"Klingler","given":"Kelly","affiliations":[{"id":17922,"text":"Program in Ecology, Evolution, and Conservation Biology, University of Nevada, Reno,","active":true,"usgs":false}],"preferred":false,"id":580837,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70160012,"text":"70160012 - 2015 - On the prediction of threshold friction velocity of wind erosion using soil reflectance spectroscopy","interactions":[],"lastModifiedDate":"2015-12-09T09:56:53","indexId":"70160012","displayToPublicDate":"2015-12-01T11:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":666,"text":"Aeolian Research","active":true,"publicationSubtype":{"id":10}},"title":"On the prediction of threshold friction velocity of wind erosion using soil reflectance spectroscopy","docAbstract":"

Current approaches to estimate threshold friction velocity (TFV) of soil particle movement, including both experimental and empirical methods, suffer from various disadvantages, and they are particularly not effective to estimate TFVs at regional to global scales. Reflectance spectroscopy has been widely used to obtain TFV-related soil properties (e.g., moisture, texture, crust, etc.), however, no studies have attempted to directly relate soil TFV to their spectral reflectance. The objective of this study was to investigate the relationship between soil TFV and soil reflectance in the visible and near infrared (VIS–NIR, 350–2500 nm) spectral region, and to identify the best range of wavelengths or combinations of wavelengths to predict TFV. Threshold friction velocity of 31 soils, along with their reflectance spectra and texture were measured in the Mojave Desert, California and Moab, Utah. A correlation analysis between TFV and soil reflectance identified a number of isolated, narrow spectral domains that largely fell into two spectral regions, the VIS area (400–700 nm) and the short-wavelength infrared (SWIR) area (1100–2500 nm). A partial least squares regression analysis (PLSR) confirmed the significant bands that were identified by correlation analysis. The PLSR further identified the strong relationship between the first-difference transformation and TFV at several narrow regions around 1400, 1900, and 2200 nm. The use of PLSR allowed us to identify a total of 17 key wavelengths in the investigated spectrum range, which may be used as the optimal spectral settings for estimating TFV in the laboratory and field, or mapping of TFV using airborne/satellite sensors.

","language":"English","publisher":"International Society of Aeolian Research","publisherLocation":"Amsterdam","doi":"10.1016/j.aeolia.2015.10.001","usgsCitation":"Li, J., Flagg, C.B., Okin, G.S., Painter, T.H., Dintwe, K., and Belnap, J., 2015, On the prediction of threshold friction velocity of wind erosion using soil reflectance spectroscopy: Aeolian Research, v. 19, no. A, p. 129-136, https://doi.org/10.1016/j.aeolia.2015.10.001.","productDescription":"8 p.","startPage":"129","endPage":"136","numberOfPages":"8","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066251","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":471596,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.aeolia.2015.10.001","text":"Publisher Index Page"},{"id":312061,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"19","issue":"A","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56695edae4b08895842a1c91","contributors":{"authors":[{"text":"Li, Junran","contributorId":23418,"corporation":false,"usgs":true,"family":"Li","given":"Junran","affiliations":[],"preferred":false,"id":581560,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Flagg, Cody B. cflagg@usgs.gov","contributorId":4573,"corporation":false,"usgs":true,"family":"Flagg","given":"Cody","email":"cflagg@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":581561,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Okin, Gregory S.","contributorId":50025,"corporation":false,"usgs":true,"family":"Okin","given":"Gregory","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":581562,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Painter, Thomas H.","contributorId":12378,"corporation":false,"usgs":true,"family":"Painter","given":"Thomas","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":581563,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dintwe, Kebonye","contributorId":150409,"corporation":false,"usgs":false,"family":"Dintwe","given":"Kebonye","email":"","affiliations":[{"id":18017,"text":"Department of Geography, University of California, Los Angeles, CA 90095, USA","active":true,"usgs":false}],"preferred":false,"id":581564,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Belnap, Jayne 0000-0001-7471-2279 jayne_belnap@usgs.gov","orcid":"https://orcid.org/0000-0001-7471-2279","contributorId":1332,"corporation":false,"usgs":true,"family":"Belnap","given":"Jayne","email":"jayne_belnap@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":581559,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70263583,"text":"70263583 - 2015 - Foreward","interactions":[],"lastModifiedDate":"2026-02-11T16:49:46.469349","indexId":"70263583","displayToPublicDate":"2015-12-01T10:43:06","publicationYear":"2015","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Foreward","docAbstract":"

No abstract available.

","conferenceTitle":"34th GCSSEPM Foundation Bob F. Perkins Research Conference on Petroleum Systems in “Rift” Basins","conferenceDate":"December 13-16, 2015","conferenceLocation":"Houston, TX","language":"English","publisher":"Society for Sedimentary Geology","doi":"10.5724/gcs.15.34","usgsCitation":"Coleman, J.L., Post, P.J., and Brown, D.E., 2015, Foreward, 34th GCSSEPM Foundation Bob F. Perkins Research Conference on Petroleum Systems in “Rift” Basins, Houston, TX, December 13-16, 2015, p. ii-v, https://doi.org/10.5724/gcs.15.34.","productDescription":"4 p.","startPage":"ii","endPage":"v","ipdsId":"IP-069267","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":499944,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5724/gcs.15.34","text":"Publisher Index Page"},{"id":499758,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2015-12-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Coleman, James L. jlcoleman@usgs.gov","contributorId":141060,"corporation":false,"usgs":true,"family":"Coleman","given":"James","email":"jlcoleman@usgs.gov","middleInitial":"L.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":927435,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Post, Paul J.","contributorId":366204,"corporation":false,"usgs":false,"family":"Post","given":"Paul","middleInitial":"J.","affiliations":[],"preferred":false,"id":955417,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brown, David E.","contributorId":49421,"corporation":false,"usgs":true,"family":"Brown","given":"David","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":955418,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70175000,"text":"70175000 - 2015 - Western water and climate change","interactions":[],"lastModifiedDate":"2016-07-27T11:37:12","indexId":"70175000","displayToPublicDate":"2015-12-01T10:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Western water and climate change","docAbstract":"

The western United States is a region long defined by water challenges. Climate change adds to those historical challenges, but does not, for the most part, introduce entirely new challenges; rather climate change is likely to stress water supplies and resources already in many cases stretched to, or beyond, natural limits. Projections are for continued and, likely, increased warming trends across the region, with a near certainty of continuing changes in seasonality of snowmelt and streamflows, and a strong potential for attendant increases in evaporative demands. Projections of future precipitation are less conclusive, although likely the northernmost West will see precipitation increases while the southernmost West sees declines. However, most of the region lies in a broad area where some climate models project precipitation increases while others project declines, so that only increases in precipitation uncertainties can be projected with any confidence. Changes in annual and seasonal hydrographs are likely to challenge water managers, users, and attempts to protect or restore environmental flows, even where annual volumes change little. Other impacts from climate change (e.g., floods and water-quality changes) are poorly understood and will likely be location dependent.

\n

In this context, four iconic river basins offer glimpses into specific challenges that climate change may bring to the West. The Colorado River is a system in which overuse and growing demands are projected to be even more challenging than climate-change-induced flow reductions. The Rio Grande offers the best example of how climate-change-induced flow declines might sink a major system into permanent drought. The Klamath is currently projected to face the more benign precipitation future, but fisheries and irrigation management may face dire straits due to warming air temperatures, rising irrigation demands, and warming waters in a basin already hobbled by tensions between endangered fisheries and agricultural demands. Finally, California's Bay-Delta system is a remarkably localized and severe weakness at the heart of the region's trillion-dollar economy. It is threatened by the full range of potential climate-change impacts expected across the West, along with major vulnerabilities to increased flooding and rising sea levels.

","language":"English","publisher":"Ecological Society of America","doi":"10.1890/15-0938.1","usgsCitation":"Dettinger, M.D., Udall, B., and Georgakakos, A.P., 2015, Western water and climate change: Ecological Applications, v. 25, no. 8, p. 2069-2093, https://doi.org/10.1890/15-0938.1.","productDescription":"24 p.","startPage":"2069","endPage":"2093","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065996","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":325697,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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Bradley","contributorId":87862,"corporation":false,"usgs":true,"family":"Udall","given":"Bradley","email":"","affiliations":[],"preferred":false,"id":643552,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Georgakakos, Aris P.","contributorId":59828,"corporation":false,"usgs":true,"family":"Georgakakos","given":"Aris","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":643553,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70203506,"text":"70203506 - 2015 - A practical guide to the use of major elements, trace elements, and isotopes in compositional data analysis: Applications for deep formation brine geochemistry","interactions":[],"lastModifiedDate":"2019-05-20T10:16:54","indexId":"70203506","displayToPublicDate":"2015-12-01T10:16:27","publicationYear":"2015","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"A practical guide to the use of major elements, trace elements, and isotopes in compositional data analysis: Applications for deep formation brine geochemistry","docAbstract":"In the geosciences, isotopic ratios and trace element concentrations are often used along with major element concentrations to help determine sources of and processes affecting geochemical variation. Compositional Data Analysis (CoDA) is a set of tools, generally attuned to major element data, concerned with the proper statistical treatment and removal of spurious correlations from compositional data. Though recent insights have been made on the incorporation of trace elements and stable isotope ratios to CoDA, this study provides a general approach to thinking about how radiogenic isotopes, stable isotopes, and trace elements fit with major elements in the CoDA framework. In the present study, we use multiple data sets of deep formation brines and compare traditional mixing models to their CoDA counterparts to examine fluid movement between reservoirs. Concentrations of individual isotopes are calculated using isotopic ratios and global mean isotopic abundances. One key result is that isotope parts (e.g. 18O, 17O, 16O, 2H, 1H, 87Sr, 86Sr) can simply be modelled by the major element concentration (H2O, Sr) in a clr-biplot as they are perfectly dependent. Another important result is that an ilr transformation of radiogenic isotope parts (e.g. 86Sr and 87Sr in 87Sr/86Sr) and trace elements can, like stable isotopes in delta notation, be treated as a linear function of the isotopic ratio or trace element concentration, scaled only by a constant. This implies that there are multiple situations in which an ilr transformation provides little additional insight for the analysis of trends: (1) any two parts with low log ratio variance (e.g. an isotope ratio), no matter their concentrations in the solution, (2) any low concentration parts (trace elements) or a ratio of a trace to a major element, no matter the variance of the elements, and (3) large positive ratios (major/trace) over a restricted range of variance. Similarly, a multivariate ilr transformation of a large data set with many parts will also be a simple perturbation if the balances are evenly split between parts. CoDA transformations, however, even if they do not provide new insight in some specific cases, will provide consistent interpretations for all types of data.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the International Workshop on Compositional Data Analysis","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"International Workshop on Compositional Data Analysis","conferenceDate":"June 1-5, 2015","conferenceLocation":"L'Escala, Spain","language":"English","publisher":"Springer","doi":"10.1007/978-3-319-44811-4_2","usgsCitation":"Blondes, M., Engle, M.A., and Geboy, N., 2015, A practical guide to the use of major elements, trace elements, and isotopes in compositional data analysis: Applications for deep formation brine geochemistry, in Proceedings of the International Workshop on Compositional Data Analysis, L'Escala, Spain, June 1-5, 2015, p. 13-29, https://doi.org/10.1007/978-3-319-44811-4_2.","productDescription":"17 p.","startPage":"13","endPage":"29","ipdsId":"IP-070706","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":364003,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-11-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Blondes, Madalyn S. 0000-0003-0320-0107 mblondes@usgs.gov","orcid":"https://orcid.org/0000-0003-0320-0107","contributorId":3598,"corporation":false,"usgs":true,"family":"Blondes","given":"Madalyn S.","email":"mblondes@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":762918,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Engle, Mark A. 0000-0001-5258-7374 engle@usgs.gov","orcid":"https://orcid.org/0000-0001-5258-7374","contributorId":584,"corporation":false,"usgs":true,"family":"Engle","given":"Mark","email":"engle@usgs.gov","middleInitial":"A.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":762919,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Geboy, Nicholas 0000-0003-3949-3001 ngeboy@usgs.gov","orcid":"https://orcid.org/0000-0003-3949-3001","contributorId":215664,"corporation":false,"usgs":true,"family":"Geboy","given":"Nicholas","email":"ngeboy@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":762920,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70160736,"text":"70160736 - 2015 - Current land bird distribution and trends in population abundance between 1982 and 2012 on Rota, Mariana Islands","interactions":[],"lastModifiedDate":"2018-01-04T13:06:31","indexId":"70160736","displayToPublicDate":"2015-12-01T09:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Current land bird distribution and trends in population abundance between 1982 and 2012 on Rota, Mariana Islands","docAbstract":"

The western Pacific island of Rota is the fourth largest human-inhabited island in the Mariana archipelago and designated an Endemic Bird Area. Between 1982 and 2012, 12 point-transect distance-sampling surveys were conducted to assess bird population status. Surveys did not consistently sample the entire island; thus, we used a ratio estimator to estimate bird abundances in strata not sampled during every survey. Trends in population size were reliably estimated for 11 of 13 bird species, and 7 species declined over the 30-y time series, including the island collared-dove Streptopelia bitorquata, white-throated ground-dove Gallicolumba xanthonura, Mariana fruit-dove Ptilinopus roseicapilla, collared kingfisher Todiramphus chloris orii, Micronesian myzomela Myzomela rubratra, black drongo Dicrurus macrocercus, and Mariana crow Corvus kubaryi. The endangered Mariana crow (x̄  =  81 birds, 95% CI 30–202) declined sharply to fewer than 200 individuals in 2012, down from 1,491 birds in 1982 (95% CI  =  815–3,115). Trends increased for white tern Gygis alba, rufous fantail Rhipidura rufifrons mariae, and Micronesian starling Aplonis opaca. Numbers of the endangered Rota white-eye Zosterops rotensis declined from 1982 to the late 1990s but returned to 1980s levels by 2012, resulting in an overall stable trend. Trends for the yellow bittern Ixobrychus sinensis were inconclusive. Eurasian tree sparrow Passer montanus trends were not assessed; however, their numbers in 1982 and 2012 were similar. Occupancy models of the 2012 survey data revealed general patterns of land cover use and detectability among 12 species that could be reliably modeled. Occupancy was not assessed for the Eurasian tree sparrow because of insufficient detections. Based on the 2012 survey, bird distribution and abundance across Rota revealed three general patterns: 1) range restriction, including Mariana crow, Rota white-eye, and Eurasian tree sparrow; 2) widespread distribution, low abundance, including collared kingfisher, island collared-dove, white-throated ground-dove, Mariana fruit-dove, white tern, yellow bittern, black drongo, and Micronesian myzomela; and 3) widespread distribution, high abundance, including rufous fantail and Micronesian starling. The Mariana crow was dispersed around the periphery of the island in steep forested land-cover types. In contrast, the Rota white-eye was restricted to the high-elevation mesa. Only for the white-throated ground-dove was there a significant difference among cover types, with lower occupancy in open field than in forested areas. Vegetation was included in the best-fit occupancy models for yellow bittern, black drongo, Micronesian myzomela, and Micronesian starling, but vegetation type was not a significant variable nor included in the top models for the remaining five species: white tern, island collared-dove, Mariana fruit-dove, collared kingfisher, and rufous fantail. Given declining population trends, the Rota bird-monitoring program could benefit from establishing threshold and alert limits and identifying alternative research and management actions. Continued monitoring and demographic sampling, in conjunction with ecological studies, are needed to understand why most bird species on Rota are declining, identify the causative agents, and assess effectiveness of conservation actions, especially for the Mariana crow.

","language":"English","publisher":"U.S. Fish and Wildlife Service","publisherLocation":"Washington D.C.","doi":"10.3996/112014-JFWM-085","usgsCitation":"Camp, R., Brinck, K., Gorresen, P.M., Amidon, F.A., Radley, P.M., Berkowitz, S., and Banko, P.C., 2015, Current land bird distribution and trends in population abundance between 1982 and 2012 on Rota, Mariana Islands: Journal of Fish and Wildlife Management, v. 6, no. 2, p. 511-540, https://doi.org/10.3996/112014-JFWM-085.","productDescription":"30 p.","startPage":"511","endPage":"540","numberOfPages":"30","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061310","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":471597,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/112014-jfwm-085","text":"Publisher Index Page"},{"id":313025,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mariana Islands","state":"Rota","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 145.19943237304688,\n 14.176523220962142\n ],\n [\n 145.23822784423828,\n 14.200488387358332\n ],\n [\n 145.26020050048828,\n 14.199822722521063\n ],\n [\n 145.29144287109375,\n 14.191168901588167\n ],\n [\n 145.29144287109375,\n 14.186176162222909\n ],\n [\n 145.2835464477539,\n 14.17519174854198\n ],\n [\n 145.2835464477539,\n 14.163208145157167\n ],\n [\n 145.2783966064453,\n 14.157549001430372\n ],\n [\n 145.26947021484372,\n 14.151889716702629\n ],\n [\n 145.2605438232422,\n 14.154885826178303\n ],\n [\n 145.2509307861328,\n 14.153221325791632\n ],\n [\n 145.24131774902344,\n 14.150558099810224\n ],\n [\n 145.2293014526367,\n 14.141569481729656\n ],\n [\n 145.23033142089844,\n 14.129584104960793\n ],\n [\n 145.22037506103516,\n 14.127919419368935\n ],\n [\n 145.21522521972656,\n 14.115600367711947\n ],\n [\n 145.20458221435547,\n 14.115267411122721\n ],\n [\n 145.19771575927734,\n 14.111937818471539\n ],\n [\n 145.1839828491211,\n 14.116266279430716\n ],\n [\n 145.1753997802734,\n 14.109607074671294\n ],\n [\n 145.16819000244138,\n 14.111271894103563\n ],\n [\n 145.16750335693357,\n 14.124590011664882\n ],\n [\n 145.15995025634766,\n 14.132247576582762\n ],\n [\n 145.14690399169922,\n 14.138573196735809\n ],\n [\n 145.1400375366211,\n 14.136908576905723\n ],\n [\n 145.1300811767578,\n 14.123591179859591\n ],\n [\n 145.12184143066406,\n 14.116932189203125\n ],\n [\n 145.12115478515625,\n 14.124257068216625\n ],\n [\n 145.12664794921875,\n 14.129584104960793\n ],\n [\n 145.14175415039062,\n 14.14423281302652\n ],\n [\n 145.1451873779297,\n 14.149892288437943\n ],\n [\n 145.1572036743164,\n 14.163541031572493\n ],\n [\n 145.15926361083984,\n 14.168201390133587\n ],\n [\n 145.17436981201172,\n 14.166869868879445\n ],\n [\n 145.19050598144528,\n 14.173194525258433\n ],\n [\n 145.19943237304688,\n 14.176523220962142\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"6","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-09-01","publicationStatus":"PW","scienceBaseUri":"5685003de4b0a04ef49336f3","contributors":{"authors":[{"text":"Camp, Richard J.","contributorId":27392,"corporation":false,"usgs":true,"family":"Camp","given":"Richard J.","affiliations":[],"preferred":false,"id":583732,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brinck, Kevin W. 0000-0001-7581-2482 kbrinck@usgs.gov","orcid":"https://orcid.org/0000-0001-7581-2482","contributorId":3847,"corporation":false,"usgs":true,"family":"Brinck","given":"Kevin W.","email":"kbrinck@usgs.gov","affiliations":[],"preferred":false,"id":583733,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gorresen, P. 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Paul","affiliations":[],"preferred":false,"id":583737,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Banko, Paul C. 0000-0002-6035-9803 pbanko@usgs.gov","orcid":"https://orcid.org/0000-0002-6035-9803","contributorId":3179,"corporation":false,"usgs":true,"family":"Banko","given":"Paul","email":"pbanko@usgs.gov","middleInitial":"C.","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true},{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":true,"id":583731,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70175224,"text":"70175224 - 2015 - Meteorological variables to aid forecasting deep slab avalanches on persistent weak layers","interactions":[],"lastModifiedDate":"2016-08-03T08:22:38","indexId":"70175224","displayToPublicDate":"2015-12-01T09:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1264,"text":"Cold Regions Science and Technology","active":true,"publicationSubtype":{"id":10}},"title":"Meteorological variables to aid forecasting deep slab avalanches on persistent weak layers","docAbstract":"

Deep slab avalanches are particularly challenging to forecast. These avalanches are difficult to trigger, yet when they release they tend to propagate far and can result in large and destructive avalanches. We utilized a 44-year record of avalanche control and meteorological data from Bridger Bowl ski area in southwest Montana to test the usefulness of meteorological variables for predicting seasons and days with deep slab avalanches. We defined deep slab avalanches as those that failed on persistent weak layers deeper than 0.9 m, and that occurred after February 1st. Previous studies often used meteorological variables from days prior to avalanches, but we also considered meteorological variables over the early months of the season. We used classification trees and random forests for our analyses. Our results showed seasons with either dry or wet deep slabs on persistent weak layers typically had less precipitation from November through January than seasons without deep slabs on persistent weak layers. Days with deep slab avalanches on persistent weak layers often had warmer minimum 24-hour air temperatures, and more precipitation over the prior seven days, than days without deep slabs on persistent weak layers. Days with deep wet slab avalanches on persistent weak layers were typically preceded by three days of above freezing air temperatures. Seasonal and daily meteorological variables were found useful to aid forecasting dry and wet deep slab avalanches on persistent weak layers, and should be used in combination with continuous observation of the snowpack and avalanche activity.

","language":"English","publisher":"Elsevier Science","publisherLocation":"New York, NY","doi":"10.1016/j.coldregions.2015.08.007","usgsCitation":"Marienthal, A., Hendrikx, J., Birkeland, K.W., and Irvine, K.M., 2015, Meteorological variables to aid forecasting deep slab avalanches on persistent weak layers: Cold Regions Science and Technology, v. 120, p. 227-236, https://doi.org/10.1016/j.coldregions.2015.08.007.","startPage":"227","endPage":"236","numberOfPages":"10","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061005","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":326005,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","otherGeospatial":"Bridger Bowl ski area","volume":"120","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57a315cae4b006cb45558b0a","contributors":{"authors":[{"text":"Marienthal, Alex","contributorId":173365,"corporation":false,"usgs":false,"family":"Marienthal","given":"Alex","email":"","affiliations":[{"id":27212,"text":"Snow and Avalanche Laboratory, Montana State University, Bozeman, MT, USA","active":true,"usgs":false}],"preferred":false,"id":644408,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hendrikx, Jordy 0000-0001-6194-3596","orcid":"https://orcid.org/0000-0001-6194-3596","contributorId":140954,"corporation":false,"usgs":false,"family":"Hendrikx","given":"Jordy","email":"","affiliations":[{"id":13628,"text":"Department of Earth Sciences, P.O. Box 173480, Montana State University, Bozeman, MT, USA. 59717.","active":true,"usgs":false}],"preferred":false,"id":644409,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Birkeland, Karl W.","contributorId":173366,"corporation":false,"usgs":false,"family":"Birkeland","given":"Karl","middleInitial":"W.","affiliations":[{"id":27213,"text":"USDA Forest Service National Avalanche Center, Bozeman, MT, USA","active":true,"usgs":false}],"preferred":false,"id":644410,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Irvine, Kathryn M. 0000-0002-6426-940X kirvine@usgs.gov","orcid":"https://orcid.org/0000-0002-6426-940X","contributorId":2218,"corporation":false,"usgs":true,"family":"Irvine","given":"Kathryn","email":"kirvine@usgs.gov","middleInitial":"M.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":644407,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70168396,"text":"70168396 - 2015 - Assessment of environmental DNA for detecting presence of imperiled aquatic amphibian species in isolated wetlands","interactions":[],"lastModifiedDate":"2016-11-30T15:03:17","indexId":"70168396","displayToPublicDate":"2015-12-01T05:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Assessment of environmental DNA for detecting presence of imperiled aquatic amphibian species in isolated wetlands","docAbstract":"

Environmental DNA (eDNA) is an emerging tool that allows low-impact sampling for aquatic species by isolating DNA from water samples and screening for DNA sequences specific to species of interest. However, researchers have not tested this method in naturally acidic wetlands that provide breeding habitat for a number of imperiled species, including the frosted salamander (Ambystoma cingulatum), reticulated flatwoods salamanders (Ambystoma bishopi), striped newt (Notophthalmus perstriatus), and gopher frog (Lithobates capito). Our objectives for this study were to develop and optimize eDNA survey protocols and assays to complement and enhance capture-based survey methods for these amphibian species. We collected three or more water samples, dipnetted or trapped larval and adult amphibians, and conducted visual encounter surveys for egg masses for target species at 40 sites on 12 different longleaf pine (Pinus palustris) tracts. We used quantitative PCRs to screen eDNA from each site for target species presence. We detected flatwoods salamanders at three sites with eDNA but did not detect them during physical surveys. Based on the sample location we assumed these eDNA detections to indicate the presence of frosted flatwoods salamanders. We did not detect reticulated flatwoods salamanders. We detected striped newts with physical and eDNA surveys at two wetlands. We detected gopher frogs at 12 sites total, three with eDNA alone, two with physical surveys alone, and seven with physical and eDNA surveys. We detected our target species with eDNA at 9 of 11 sites where they were present as indicated from traditional surveys and at six sites where they were not detected with traditional surveys. It was, however, critical to use at least three water samples per site for eDNA. Our results demonstrate eDNA surveys can be a useful complement to traditional survey methods for detecting imperiled pond-breeding amphibians. Environmental DNA may be particularly useful in situations where detection probability using traditional survey methods is low or access by trained personnel is limited.

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Understanding fish habitat use is important in determining conditions that ultimately affect fish energetics, growth and reproduction. Great Lakes lake whitefish (Coregonus clupeaformis) have demonstrated dramatic changes in growth and life history traits since the appearance of dreissenid mussels in the Great Lakes, but the role of habitat occupancy in driving these changes is poorly understood. To better understand temporal changes in lake whitefish depth of capture (Dw), we compiled a database of fishery-independent surveys representing multiple populations across all five Laurentian Great Lakes. By demonstrating the importance of survey design in estimating Dw, we describe a novel method for detecting survey-based bias in Dw and removing potentially biased data. Using unbiased Dw estimates, we show clear differences in the pattern and timing of changes in lake whitefish Dw between our reference sites (Lake Superior) and those that have experienced significant benthic food web changes (lakes Michigan, Huron, Erie and Ontario). Lake whitefish Dw in Lake Superior tended to gradually shift to shallower waters, but changed rapidly in other locations coincident with dreissenid establishment and declines in Diporeia densities. Almost all lake whitefish populations that were exposed to dreissenids demonstrated deeper Dw following benthic food web change, though a subset of these populations subsequently shifted to more shallow depths. In some cases in lakes Huron and Ontario, shifts towards more shallow Dw are occurring well after documented Diporeia collapse, suggesting the role of other drivers such as habitat availability or reliance on alternative prey sources.

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The USGS National Seismic Hazard Maps were updated in 2014 and included several important changes for the central United States (CUS). Background seismicity sources were improved using a new moment-magnitude-based catalog; a new adaptive, nearest-neighbor smoothing kernel was implemented; and maximum magnitudes for background sources were updated. Areal source zones developed by the Central and Eastern United States Seismic Source Characterization for Nuclear Facilities project were simplified and adopted. The weighting scheme for ground motion models was updated, giving more weight to models with a faster attenuation with distance compared to the previous maps. Overall, hazard changes (2% probability of exceedance in 50 years, across a range of ground-motion frequencies) were smaller than 10% in most of the CUS relative to the 2008 USGS maps despite new ground motion models and their assigned logic tree weights that reduced the probabilistic ground motions by 5–20%.

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S1, no. 31, p. 109-130, https://doi.org/10.1193/103114EQS174M.","productDescription":"22 p.","startPage":"109","endPage":"130","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064918","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":471598,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1193/103114eqs174m","text":"Publisher Index Page"},{"id":324614,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"S1","issue":"31","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-01","publicationStatus":"PW","scienceBaseUri":"5774f2c6e4b07dd077c6aa3c","contributors":{"authors":[{"text":"Boyd, Oliver S. 0000-0001-9457-0407 olboyd@usgs.gov","orcid":"https://orcid.org/0000-0001-9457-0407","contributorId":140739,"corporation":false,"usgs":true,"family":"Boyd","given":"Oliver","email":"olboyd@usgs.gov","middleInitial":"S.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":641246,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haller, Kathleen 0000-0001-8847-7302 haller@usgs.gov","orcid":"https://orcid.org/0000-0001-8847-7302","contributorId":172556,"corporation":false,"usgs":true,"family":"Haller","given":"Kathleen","email":"haller@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":641247,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Luco, Nico 0000-0002-5763-9847 nluco@usgs.gov","orcid":"https://orcid.org/0000-0002-5763-9847","contributorId":145730,"corporation":false,"usgs":true,"family":"Luco","given":"Nico","email":"nluco@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":641248,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Moschetti, Morgan P. 0000-0001-7261-0295 mmoschetti@usgs.gov","orcid":"https://orcid.org/0000-0001-7261-0295","contributorId":1662,"corporation":false,"usgs":true,"family":"Moschetti","given":"Morgan","email":"mmoschetti@usgs.gov","middleInitial":"P.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":641249,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mueller, Charles 0000-0002-1868-9710 cmueller@usgs.gov","orcid":"https://orcid.org/0000-0002-1868-9710","contributorId":140380,"corporation":false,"usgs":true,"family":"Mueller","given":"Charles","email":"cmueller@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":641250,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Petersen, Mark D. 0000-0001-8542-3990 mpetersen@usgs.gov","orcid":"https://orcid.org/0000-0001-8542-3990","contributorId":1163,"corporation":false,"usgs":true,"family":"Petersen","given":"Mark","email":"mpetersen@usgs.gov","middleInitial":"D.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":641251,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rezaeian, Sanaz 0000-0001-7589-7893 srezaeian@usgs.gov","orcid":"https://orcid.org/0000-0001-7589-7893","contributorId":4395,"corporation":false,"usgs":true,"family":"Rezaeian","given":"Sanaz","email":"srezaeian@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":641252,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Rubinstein, Justin L. 0000-0003-1274-6785 jrubinstein@usgs.gov","orcid":"https://orcid.org/0000-0003-1274-6785","contributorId":2404,"corporation":false,"usgs":true,"family":"Rubinstein","given":"Justin","email":"jrubinstein@usgs.gov","middleInitial":"L.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":641253,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70184233,"text":"70184233 - 2015 - The 2014 update to the National Seismic Hazard Model in California","interactions":[],"lastModifiedDate":"2017-03-06T10:50:05","indexId":"70184233","displayToPublicDate":"2015-12-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1436,"text":"Earthquake Spectra","active":true,"publicationSubtype":{"id":10}},"title":"The 2014 update to the National Seismic Hazard Model in California","docAbstract":"

The 2014 update to the U. S. Geological Survey National Seismic Hazard Model in California introduces a new earthquake rate model and new ground motion models (GMMs) that give rise to numerous changes to seismic hazard throughout the state. The updated earthquake rate model is the third version of the Uniform California Earthquake Rupture Forecast (UCERF3), wherein the rates of all ruptures are determined via a self-consistent inverse methodology. This approach accommodates multifault ruptures and reduces the overprediction of moderate earthquake rates exhibited by the previous model (UCERF2). UCERF3 introduces new faults, changes to slip or moment rates on existing faults, and adaptively smoothed gridded seismicity source models, all of which contribute to significant changes in hazard. New GMMs increase ground motion near large strike-slip faults and reduce hazard over dip-slip faults. The addition of very large strike-slip ruptures and decreased reverse fault rupture rates in UCERF3 further enhances these effects.

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New seismic hazard maps have been developed for the conterminous United States using the latest data, models, and methods available for assessing earthquake hazard. The hazard models incorporate new information on earthquake rupture behavior observed in recent earthquakes; fault studies that use both geologic and geodetic strain rate data; earthquake catalogs through 2012 that include new assessments of locations and magnitudes; earthquake adaptive smoothing models that more fully account for the spatial clustering of earthquakes; and 22 ground motion models, some of which consider more than double the shaking data applied previously. Alternative input models account for larger earthquakes, more complicated ruptures, and more varied ground shaking estimates than assumed in earlier models. The ground motions, for levels applied in building codes, differ from the previous version by less than ±10% over 60% of the country, but can differ by ±50% in localized areas. The models are incorporated in insurance rates, risk assessments, and as input into the U.S. building code provisions for earthquake ground shaking.

","language":"English","publisher":"EERI","doi":"10.1193/120814EQS210M","usgsCitation":"Petersen, M.D., Moschetti, M.P., Powers, P.M., Mueller, C., Haller, K., Frankel, A.D., Zeng, Y., Rezaeian, S., Harmsen, S., Boyd, O.S., Field, E., Chen, R., Rukstales, K.S., Luco, N., Wheeler, R., Williams, R., and Olsen, A.H., 2015, The 2014 United States National Seismic Hazard Model: Earthquake Spectra, v. 31, no. S!, p. 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In the southern part of the Patterson Hills just to the west of the Guadalupe Mountains escarpment ofWest Texas, a 29m outcrop of alternating calcareous siltstone and silty limestone with a few thin fine sandstone interbeds displays the overlap occurrence of a narrowmorphotype of Jinogondolella nankingensis (herein named J. nankingensis behnkeni) with J. aserrata near its base. The transition of Jinogondolella aserrata to J. postserrata is present near the top of this section and marks theWordian-Capitanian boundary, therefore displaying a significant portion of the upper part of theWordian in one short continuous section. Pseudohindeodus brevis n. sp. and H. capitanensis n. sp. are described. Pseudohindeodus ramovsi, Caenodontus serrulatus, Hindeodus wordensis, Sweetina triticum, Jinogondolella palmata, and J. errata also occur in this succession.

","language":"English","publisher":"Micropaleontology Press","usgsCitation":"Wardlaw, B.R., and Nestell, M.K., 2015, Conodont faunas from a complete basinal succession of the upper part of the Wordian (Middle Permian, Guadalupian, West Texas): Micropaleontology, v. 61, p. 257-292.","productDescription":"36 p.","startPage":"257","endPage":"292","ipdsId":"IP-071644","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":341454,"type":{"id":15,"text":"Index Page"},"url":"https://www.micropress.org/microaccess/micropaleontology/issue-320/article-1950"},{"id":341483,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas","volume":"61","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"591eb2e3e4b0a7fdb4418b8f","contributors":{"authors":[{"text":"Wardlaw, Bruce R. bwardlaw@usgs.gov","contributorId":266,"corporation":false,"usgs":true,"family":"Wardlaw","given":"Bruce","email":"bwardlaw@usgs.gov","middleInitial":"R.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":695573,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nestell, Merlynd K.","contributorId":68603,"corporation":false,"usgs":false,"family":"Nestell","given":"Merlynd","email":"","middleInitial":"K.","affiliations":[{"id":12734,"text":"University of Texas at Arlington","active":true,"usgs":false}],"preferred":false,"id":695574,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70187774,"text":"70187774 - 2015 - Conodont biostratigraphy of the Permian-Triassic boundary sequence at Lung Cam, Vietnam","interactions":[],"lastModifiedDate":"2017-05-18T14:33:41","indexId":"70187774","displayToPublicDate":"2015-12-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2735,"text":"Micropaleontology","active":true,"publicationSubtype":{"id":10}},"title":"Conodont biostratigraphy of the Permian-Triassic boundary sequence at Lung Cam, Vietnam","docAbstract":"

The occurrences of a few specimens of Clarkina and many specimens of Hindeodus at the Permian-Triassic boundary section at Lung Cam, Vietnam allow accurate graphic correlation to the P-T boundary stratotype at Meishan, China. One species of Clarkina, ten species and two subspecies of Hindeodus, and the apparatuses of Hindeodus latidentatus and Merrillina ultima are described and illustrated.

","language":"English","publisher":"Micropaleontology Press","usgsCitation":"Wardlaw, B.R., Nestell, M.K., Nestell, G.P., Ellwood, B.B., and Lan, L., 2015, Conodont biostratigraphy of the Permian-Triassic boundary sequence at Lung Cam, Vietnam: Micropaleontology, v. 61, p. 313-334.","productDescription":"22 p.","startPage":"313","endPage":"334","ipdsId":"IP-062992","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":341485,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":341484,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.micropress.org/microaccess/micropaleontology/issue-320/article-1953"}],"country":"Vietnam","volume":"61","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"591eb2e3e4b0a7fdb4418b94","contributors":{"authors":[{"text":"Wardlaw, Bruce R. bwardlaw@usgs.gov","contributorId":266,"corporation":false,"usgs":true,"family":"Wardlaw","given":"Bruce","email":"bwardlaw@usgs.gov","middleInitial":"R.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":695567,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nestell, Merlynd K.","contributorId":68603,"corporation":false,"usgs":false,"family":"Nestell","given":"Merlynd","email":"","middleInitial":"K.","affiliations":[{"id":12734,"text":"University of Texas at Arlington","active":true,"usgs":false}],"preferred":false,"id":695568,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nestell, Galina P.","contributorId":22651,"corporation":false,"usgs":false,"family":"Nestell","given":"Galina","email":"","middleInitial":"P.","affiliations":[{"id":12734,"text":"University of Texas at Arlington","active":true,"usgs":false}],"preferred":false,"id":695569,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ellwood, Brooks B.","contributorId":44814,"corporation":false,"usgs":false,"family":"Ellwood","given":"Brooks","email":"","middleInitial":"B.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":695570,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lan, Luu Thi Phuong","contributorId":192129,"corporation":false,"usgs":false,"family":"Lan","given":"Luu Thi Phuong","affiliations":[],"preferred":false,"id":695571,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70184227,"text":"70184227 - 2015 - Seismic source characterization for the 2014 update of the U.S. National Seismic Hazard Model","interactions":[],"lastModifiedDate":"2017-03-06T11:05:53","indexId":"70184227","displayToPublicDate":"2015-12-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1436,"text":"Earthquake Spectra","active":true,"publicationSubtype":{"id":10}},"title":"Seismic source characterization for the 2014 update of the U.S. National Seismic Hazard Model","docAbstract":"

We present the updated seismic source characterization (SSC) for the 2014 update of the National Seismic Hazard Model (NSHM) for the conterminous United States. Construction of the seismic source models employs the methodology that was developed for the 1996 NSHM but includes new and updated data, data types, source models, and source parameters that reflect the current state of knowledge of earthquake occurrence and state of practice for seismic hazard analyses. We review the SSC parameterization and describe the methods used to estimate earthquake rates, magnitudes, locations, and geometries for all seismic source models, with an emphasis on new source model components. We highlight the effects that two new model components—incorporation of slip rates from combined geodetic-geologic inversions and the incorporation of adaptively smoothed seismicity models—have on probabilistic ground motions, because these sources span multiple regions of the conterminous United States and provide important additional epistemic uncertainty for the 2014 NSHM.

","language":"English","publisher":"EERI","doi":"10.1193/110514EQS183M","usgsCitation":"Moschetti, M.P., Powers, P.M., Petersen, M.D., Boyd, O.S., Chen, R., Field, E.H., Frankel, A.D., Haller, K., Harmsen, S., Mueller, C.S., Wheeler, R., and Zeng, Y., 2015, Seismic source characterization for the 2014 update of the U.S. National Seismic Hazard Model: Earthquake Spectra, v. 31, no. S1, p. S31-S57, https://doi.org/10.1193/110514EQS183M.","productDescription":"27 p.","startPage":"S31","endPage":"S57","ipdsId":"IP-066842","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":471608,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1193/110514eqs183m","text":"Publisher Index Page"},{"id":336861,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"31","issue":"S1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-01","publicationStatus":"PW","scienceBaseUri":"58be833de4b014cc3a3a99f9","contributors":{"authors":[{"text":"Moschetti, Morgan P. 0000-0001-7261-0295 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afrankel@usgs.gov","orcid":"https://orcid.org/0000-0001-9119-6106","contributorId":146285,"corporation":false,"usgs":true,"family":"Frankel","given":"Arthur","email":"afrankel@usgs.gov","middleInitial":"D.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":680641,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Haller, Kathleen 0000-0001-8847-7302 haller@usgs.gov","orcid":"https://orcid.org/0000-0001-8847-7302","contributorId":172556,"corporation":false,"usgs":true,"family":"Haller","given":"Kathleen","email":"haller@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":680642,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Harmsen, Stephen harmsen@usgs.gov","contributorId":152128,"corporation":false,"usgs":true,"family":"Harmsen","given":"Stephen","email":"harmsen@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards 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zeng@usgs.gov","orcid":"https://orcid.org/0000-0003-1161-1264","contributorId":145693,"corporation":false,"usgs":true,"family":"Zeng","given":"Yuehua","email":"zeng@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":680645,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70184232,"text":"70184232 - 2015 - Hydrologic implications of GRACE satellite data in the Colorado River Basin","interactions":[],"lastModifiedDate":"2018-01-30T18:44:55","indexId":"70184232","displayToPublicDate":"2015-12-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Hydrologic implications of GRACE satellite data in the Colorado River Basin","docAbstract":"

Use of GRACE (Gravity Recovery and Climate Experiment) satellites for assessing global water resources is rapidly expanding. Here we advance application of GRACE satellites by reconstructing long-term total water storage (TWS) changes from ground-based monitoring and modeling data. We applied the approach to the Colorado River Basin which has experienced multiyear intense droughts at decadal intervals. Estimated TWS declined by 94 km3 during 1986–1990 and by 102 km3 during 1998–2004, similar to the TWS depletion recorded by GRACE (47 km3) during 2010–2013. Our analysis indicates that TWS depletion is dominated by reductions in surface reservoir and soil moisture storage in the upper Colorado basin with additional reductions in groundwater storage in the lower basin. Groundwater storage changes are controlled mostly by natural responses to wet and dry cycles and irrigation pumping outside of Colorado River delivery zones based on ground-based water level and gravity data. Water storage changes are controlled primarily by variable water inputs in response to wet and dry cycles rather than increasing water use. Surface reservoir storage buffers supply variability with current reservoir storage representing ∼2.5 years of available water use. This study can be used as a template showing how to extend short-term GRACE TWS records and using all available data on storage components of TWS to interpret GRACE data, especially within the context of droughts.

","language":"English","publisher":"AGU Publications","doi":"10.1002/2015WR018090","usgsCitation":"Scanlon, B., Zhang, Z., Reedy, R.C., Pool, D.R., Save, H., Long, D., Chen, J., Wolock, D.M., Conway, B.D., and Winester, D., 2015, Hydrologic implications of GRACE satellite data in the Colorado River Basin: Water Resources Research, v. 51, no. 12, p. 9891-9903, https://doi.org/10.1002/2015WR018090.","productDescription":"13 p.","startPage":"9891","endPage":"9903","ipdsId":"IP-070650","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":471613,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015wr018090","text":"Publisher Index Page"},{"id":336855,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Colorado River Basin","volume":"51","issue":"12","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-24","publicationStatus":"PW","scienceBaseUri":"58be833ce4b014cc3a3a99f3","contributors":{"authors":[{"text":"Scanlon, Bridget R.","contributorId":74093,"corporation":false,"usgs":true,"family":"Scanlon","given":"Bridget R.","affiliations":[],"preferred":false,"id":680670,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zhang, Zizhan","contributorId":187508,"corporation":false,"usgs":false,"family":"Zhang","given":"Zizhan","email":"","affiliations":[],"preferred":false,"id":680671,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reedy, Robert C.","contributorId":187509,"corporation":false,"usgs":false,"family":"Reedy","given":"Robert","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":680672,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pool, Donald R. drpool@usgs.gov","contributorId":1121,"corporation":false,"usgs":true,"family":"Pool","given":"Donald","email":"drpool@usgs.gov","middleInitial":"R.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":680669,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Save, Himanshu","contributorId":187510,"corporation":false,"usgs":false,"family":"Save","given":"Himanshu","email":"","affiliations":[],"preferred":false,"id":680673,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Long, Di","contributorId":187511,"corporation":false,"usgs":false,"family":"Long","given":"Di","email":"","affiliations":[],"preferred":false,"id":680674,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Chen, Jianli","contributorId":187512,"corporation":false,"usgs":false,"family":"Chen","given":"Jianli","email":"","affiliations":[],"preferred":false,"id":680675,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wolock, David M. 0000-0002-6209-938X dwolock@usgs.gov","orcid":"https://orcid.org/0000-0002-6209-938X","contributorId":540,"corporation":false,"usgs":true,"family":"Wolock","given":"David","email":"dwolock@usgs.gov","middleInitial":"M.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":680676,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Conway, Brian D.","contributorId":187513,"corporation":false,"usgs":false,"family":"Conway","given":"Brian","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":680677,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Winester, Daniel","contributorId":187514,"corporation":false,"usgs":false,"family":"Winester","given":"Daniel","email":"","affiliations":[],"preferred":false,"id":680678,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70184226,"text":"70184226 - 2015 - Ground motion models used in the 2014 U.S. National Seismic Hazard Maps","interactions":[],"lastModifiedDate":"2017-03-06T11:18:18","indexId":"70184226","displayToPublicDate":"2015-12-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1436,"text":"Earthquake Spectra","active":true,"publicationSubtype":{"id":10}},"title":"Ground motion models used in the 2014 U.S. National Seismic Hazard Maps","docAbstract":"

The National Seismic Hazard Maps (NSHMs) are an important component of seismic design regulations in the United States. This paper compares hazard using the new suite of ground motion models (GMMs) relative to hazard using the suite of GMMs applied in the previous version of the maps. The new source characterization models are used for both cases. A previous paper (Rezaeian et al. 2014) discussed the five NGA-West2 GMMs used for shallow crustal earthquakes in the Western United States (WUS), which are also summarized here. Our focus in this paper is on GMMs for earthquakes in stable continental regions in the Central and Eastern United States (CEUS), as well as subduction interface and deep intraslab earthquakes. We consider building code hazard levels for peak ground acceleration (PGA), 0.2-s, and 1.0-s spectral accelerations (SAs) on uniform firm-rock site conditions. The GMM modifications in the updated version of the maps created changes in hazard within 5% to 20% in WUS; decreases within 5% to 20% in CEUS; changes within 5% to 15% for subduction interface earthquakes; and changes involving decreases of up to 50% and increases of up to 30% for deep intraslab earthquakes for most U.S. sites. These modifications were combined with changes resulting from modifications in the source characterization models to obtain the new hazard maps.

","language":"English","publisher":"Earthquake Engineering Research Institute","publisherLocation":"El Cerrito, CA","doi":"10.1193/111714EQS194M","usgsCitation":"Rezaeian, S., Petersen, M.D., and Moschetti, M.P., 2015, Ground motion models used in the 2014 U.S. National Seismic Hazard Maps: Earthquake Spectra, v. 31, no. S1, p. 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Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":680634,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Moschetti, Morgan P. 0000-0001-7261-0295 mmoschetti@usgs.gov","orcid":"https://orcid.org/0000-0001-7261-0295","contributorId":1662,"corporation":false,"usgs":true,"family":"Moschetti","given":"Morgan","email":"mmoschetti@usgs.gov","middleInitial":"P.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":680635,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70184219,"text":"70184219 - 2015 - Updates to building-code maps for the 2015 NEHRP recommended seismic provisions","interactions":[],"lastModifiedDate":"2017-03-06T11:25:59","indexId":"70184219","displayToPublicDate":"2015-12-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1436,"text":"Earthquake Spectra","active":true,"publicationSubtype":{"id":10}},"title":"Updates to building-code maps for the 2015 NEHRP recommended seismic provisions","docAbstract":"

With the 2014 update of the U.S. Geological Survey (USGS) National Seismic Hazard Model (NSHM) as a basis, the Building Seismic Safety Council (BSSC) has updated the earthquake ground motion maps in the National Earthquake Hazards Reduction Program (NEHRP) Recommended Seismic Provisions for New Buildings and Other Structures, with partial funding from the Federal Emergency Management Agency. Anticipated adoption of the updated maps into the American Society of Civil Engineers Minimum Design Loads for Building and Other Structures and the International Building and Residential Codes is underway. Relative to the ground motions in the prior edition of each of these documents, most of the updated values are within a ±20% change. The larger changes are, in most cases, due to the USGS NSHM updates, reasons for which are given in companion publications. In some cases, the larger changes are partly due to a BSSC update of the slope of the fragility curve that is used to calculate the risk-targeted ground motions, and/or the introduction by BSSC of a quantitative definition of “active faults” used to calculate deterministic ground motions.

","language":"English","publisher":"EERI","doi":"10.1193/042015EQS058M","usgsCitation":"Luco, N., Bachman, R., Crouse, C., Harris, J.R., Hooper, J.D., Kircher, C.A., Caldwell, P., and Rukstales, K.S., 2015, Updates to building-code maps for the 2015 NEHRP recommended seismic provisions: Earthquake Spectra, v. 31, no. S1, p. S245-S271, https://doi.org/10.1193/042015EQS058M.","productDescription":"27 p.","startPage":"S245","endPage":"S271","ipdsId":"IP-070778","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":438662,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9NT3NRE","text":"USGS data release","linkHelpText":"Gridded earthquake ground motions for the 2015 NEHRP Recommended Seismic Provisions and 2016 ASCE/SEI 7 Standard"},{"id":336870,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"31","issue":"S1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-01","publicationStatus":"PW","scienceBaseUri":"58be833de4b014cc3a3a99fd","contributors":{"authors":[{"text":"Luco, Nico 0000-0002-5763-9847 nluco@usgs.gov","orcid":"https://orcid.org/0000-0002-5763-9847","contributorId":145730,"corporation":false,"usgs":true,"family":"Luco","given":"Nico","email":"nluco@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":680594,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bachman, Robert","contributorId":187485,"corporation":false,"usgs":false,"family":"Bachman","given":"Robert","affiliations":[],"preferred":false,"id":680595,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Crouse, C.B","contributorId":187486,"corporation":false,"usgs":false,"family":"Crouse","given":"C.B","affiliations":[],"preferred":false,"id":680596,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Harris, James R.","contributorId":187541,"corporation":false,"usgs":false,"family":"Harris","given":"James","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":680597,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hooper, John D.","contributorId":7601,"corporation":false,"usgs":true,"family":"Hooper","given":"John","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":680598,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kircher, Charles A.","contributorId":106596,"corporation":false,"usgs":true,"family":"Kircher","given":"Charles","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":680599,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Caldwell, Phillp","contributorId":187488,"corporation":false,"usgs":false,"family":"Caldwell","given":"Phillp","email":"","affiliations":[],"preferred":false,"id":680600,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Rukstales, Kenneth S. 0000-0003-2818-078X rukstales@usgs.gov","orcid":"https://orcid.org/0000-0003-2818-078X","contributorId":775,"corporation":false,"usgs":true,"family":"Rukstales","given":"Kenneth","email":"rukstales@usgs.gov","middleInitial":"S.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":680601,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70174270,"text":"70174270 - 2015 - Hybridization between Dusky Grouse and Sharp-tailed Grouse","interactions":[],"lastModifiedDate":"2016-07-07T09:20:20","indexId":"70174270","displayToPublicDate":"2015-12-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3743,"text":"Western Birds","active":true,"publicationSubtype":{"id":10}},"title":"Hybridization between Dusky Grouse and Sharp-tailed Grouse","docAbstract":"

Cache County, Utah, 7 April 2013: rare hybrid combination of grouse noted. Hybridization between Dusky Grouse (Dendragapus obscurus) and Sharp-tailed Grouse (Tympanuchus phasianellus) has been rarely documented in the wild. The only published record was of one collected from Osoyoos, British Columbia, in 1906 (Brooks 1907, Lincoln 1950). There is also one record of this hybrid in captivity (McCarthy 2006)...Although hybridization within genera is more common than between genera, it is perhaps not all too remarkable that these species would hybridize, given that Dendragapus and Tympanuchus are each other’s closest relatives (Drovetski 2002). The ranges of these two species overlap over a broad area ranging roughly from parts of northern Utah and Colorado to Yukon and the Northwest Territories. Given the close relatedness and extent of overlap of their ranges, it is perhaps surprising that there have not been more reports of this hybrid combination in the over-100 years since Brooks (1907) first described one. The species may be segregated by habitat use, as Sharp-tailed prefer open grassland sites for lekking and shrub areas for nesting, and Dusky are often found in more densely forested conifer stands—although Dusky often use more open habitats in the spring.

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