The 21 October 1868 Hayward, California, earthquake is among the best-characterized historical earthquakes in California. In contrast to many other moderate-to-large historical events, the causative fault is clearly established. Published magnitude estimates have been fairly consistent, ranging from 6.8 to 7.2, with 95% confidence limits including values as low as 6.5. The magnitude is of particular importance for assessment of seismic hazard associated with the Hayward fault and, more generally, to develop appropriate magnitude–rupture length scaling relations for partially creeping faults. The recent reevaluation of archival accounts by Boatwright and Bundock (2008), together with the growing volume of well-calibrated intensity data from the U.S. Geological Survey “Did You Feel It?” (DYFI) system, provide an opportunity to revisit and refine the magnitude estimate. In this study, we estimate the magnitude using two different methods that use DYFI data as calibration. Both approaches yield preferred magnitude estimates of 6.3–6.6, assuming an average stress drop. A consideration of data limitations associated with settlement patterns increases the range to 6.3–6.7, with a preferred estimate of 6.5. Although magnitude estimates for historical earthquakes are inevitably uncertain, we conclude that, at a minimum, a lower-magnitude estimate represents a credible alternative interpretation of available data. We further discuss implications of our results for probabilistic seismic-hazard assessment from partially creeping faults.
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\nGenerally, the USGS NWC approaches water-availability assessment in terms of a “water budget.” The water-budget approach seeks to better quantify the inflows and outflows of water, as well as the change in storage volume, both nationally and at a regional scale and, by doing so, provides critical information to managers and stakeholders responsible for making water-availability decisions. The NWC has two primary components: Topical Studies and Geographic Focus Area Studies. Topical Studies do research on methods that can provide nationwide estimates of particular water-budget components at the subwatershed scale. Some examples of NWC Topical Studies include estimation of streamflow at ungaged locations; periodic quantification of evapotranspiration; and water use related to development of unconventional oil and gas. These efforts are planned to include additional topics in the future. Geographic Focus Area Studies (FASs) assess water availability and use within a defined geographic area, typically a surface-water drainage basin, to increase the understanding of factors affecting water availability in the region. In the FASs, local stakeholder input helps the USGS identify what components of the water budget are in most need of additional understanding or quantification. Focus Area Studies are planned as 3-year efforts and, typically, three FASs are ongoing in different parts of the country at any given time.
\nThe Colorado River Basin (CRB) and the Delaware and Apalachicola-Chattahoochee-Flint (ACF) River Basins were selected by the Department of the Interior for the first round of FASs because of the perceived water shortages in the basins and potential conflicts over water supply and allocations. After gathering input from numerous stakeholders in the CRB, the USGS determined that surface-water resources in the basin were already being closely monitored and that the most important scientific contribution could be made by helping to improve estimates of four water-budget components: evapotranspiration losses, snowpack hydrodynamics, water-use information, and the relative importance of groundwater discharge in supporting streamflow across the basin. The purpose of this fact sheet is to provide a brief summary of the CRB FAS results as the study nears completion. Although some project results are still in the later stages of review and publication, this fact sheet provides an overall description of the work completed and cites the publications in which additional information can be found.
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National Water Availability and Use
Science Program
U.S. Geological Survey
12201 Sunrise Valley Drive
988 National Center
Reston, VA 20192
http://water.usgs.gov/watercensus/
Habitat degradation and harvest have upset the natural buffering mechanism (i.e., portfolio effects) of many large-scale multi-stock fisheries by reducing spawning stock diversity that is vital for generating population stability and resilience. The application of portfolio theory offers a means to guide management activities by quantifying the importance of multi-stock dynamics and suggesting conservation and restoration strategies to improve naturally occurring portfolio effects. Our application of portfolio theory to Lake Erie Sander vitreus (walleye), a large population that is supported by riverine and open-lake reef spawning stocks, has shown that portfolio effects generated by annual inter-stock larval fish production are currently suboptimal when compared to potential buffering capacity. Reduced production from riverine stocks has resulted in a single open-lake reef stock dominating larval production, and in turn, high inter-annual recruitment variability during recent years. Our analyses have shown (1) a weak average correlation between annual river and reef larval production (ρ̄ = 0.24), suggesting that a natural buffering capacity exists in the population, and (2) expanded annual production of larvae (potential recruits) from riverine stocks could stabilize the fishery by dampening inter-annual recruitment variation. Ultimately, our results demonstrate how portfolio theory can be used to quantify the importance of spawning stock diversity and guide management on ecologically relevant scales (i.e., spawning stocks) leading to greater stability and resilience of multi-stock populations and fisheries.
","language":"English","publisher":"Ecological Society of America","publisherLocation":"Washington D.C.","doi":"10.1890/ES15-00237.1","usgsCitation":"DuFour, M., May, C.J., Roseman, E., Ludsin, S.A., Vandergoot, C.S., Pritt, J., Fraker, M.E., Davis, J.J., Tyson, J.T., Miner, J.G., Marschall, E.A., and Mayer, C.M., 2015, Portfolio theory as a management tool to guide conservation and restoration of multi-stock fish populations: Ecosphere, v. 6, no. 12, 21 p., https://doi.org/10.1890/ES15-00237.1.","productDescription":"21 p.","numberOfPages":"21","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066936","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":471591,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1890/es15-00237.1","text":"Publisher Index 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State University","active":true,"usgs":false}],"preferred":false,"id":583795,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Marschall, Elizabeth A.","contributorId":41388,"corporation":false,"usgs":true,"family":"Marschall","given":"Elizabeth","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":583793,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Mayer, Christine M.","contributorId":50814,"corporation":false,"usgs":true,"family":"Mayer","given":"Christine","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":583787,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70160761,"text":"70160761 - 2015 - Seasonal variation in habitat use of juvenile Steelhead in a tributary of Lake Ontario","interactions":[],"lastModifiedDate":"2015-12-30T12:00:09","indexId":"70160761","displayToPublicDate":"2015-12-01T13:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2898,"text":"Northeastern Naturalist","active":true,"publicationSubtype":{"id":10}},"title":"Seasonal variation in habitat use of juvenile Steelhead in a tributary of Lake Ontario","docAbstract":"We examined seasonal-habitat use by subyearling and yearling Oncorhynchus mykiss (Rainbow Trout or Steelhead) in Trout Brook, a tributary of the Salmon River, NY. We determined daytime fish-habitat use and available habitat during August and October of the same year and observed differences in habitat selection among year classes. Water depth and cover played the greatest role in Steelhead habitat use. During summer and autumn, we found yearling Steelhead in areas with deeper water and more cover than where we observed subyearling Steelhead. Both year classes sought out areas with abundant cover during both seasons; this habitat was limited within the stream reach. Subyearling Steelhead were associated with more cover during autumn, even though available cover within the stream reach was greater during summer. Principal component analysis showed that variation in seasonal-habitat use was most pronounced for subyearling Steelhead and that yearling Steelhead were more selective in their habitat use than subyearling Steelhead. The results of this study contribute to a greater understanding of how this popular sportfish is adapting to a new environment and the factors that may limit juvenile Steelhead survival. Our findings provide valuable new insights into the seasonal-habitat requirements of subyearling and yearling Steelhead that can be used by fisheries managers to enhance and protect the species throughout the Great Lakes region.
","language":"English","publisher":"Eagle Hill","publisherLocation":"Steuben, ME","doi":"10.1656/045.022.0409","usgsCitation":"Studdert, E.W., and Johnson, J.H., 2015, Seasonal variation in habitat use of juvenile Steelhead in a tributary of Lake Ontario: Northeastern Naturalist, v. 22, no. 4, p. 717-729, https://doi.org/10.1656/045.022.0409.","productDescription":"13 p.","startPage":"717","endPage":"729","numberOfPages":"13","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-067098","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":313046,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Trout Brook","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.05148315429688,\n 43.56820304329252\n ],\n [\n -76.05148315429688,\n 43.64700708585035\n ],\n [\n -75.94196319580078,\n 43.64700708585035\n ],\n [\n -75.94196319580078,\n 43.56820304329252\n ],\n [\n -76.05148315429688,\n 43.56820304329252\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"22","issue":"4","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-09","publicationStatus":"PW","scienceBaseUri":"5685005ce4b0a04ef493373b","contributors":{"authors":[{"text":"Studdert, Emily W.","contributorId":150966,"corporation":false,"usgs":false,"family":"Studdert","given":"Emily","email":"","middleInitial":"W.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":583797,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, James H. 0000-0002-5619-3871 jhjohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-5619-3871","contributorId":389,"corporation":false,"usgs":true,"family":"Johnson","given":"James","email":"jhjohnson@usgs.gov","middleInitial":"H.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":583796,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"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":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","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":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"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":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":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true},{"id":404,"text":"NGTOC Rolla","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":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","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":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","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":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. 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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":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.
\nIn 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.
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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. Marcos mgorresen@usgs.gov","contributorId":37020,"corporation":false,"usgs":true,"family":"Gorresen","given":"P.","email":"mgorresen@usgs.gov","middleInitial":"Marcos","affiliations":[],"preferred":false,"id":583734,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Amidon, Fred A.","contributorId":107200,"corporation":false,"usgs":true,"family":"Amidon","given":"Fred","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":583735,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Radley, Paul M.","contributorId":7626,"corporation":false,"usgs":true,"family":"Radley","given":"Paul","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":583736,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Berkowitz, S. Paul","contributorId":44836,"corporation":false,"usgs":true,"family":"Berkowitz","given":"S. 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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.
","language":"English","publisher":"Scientific Journals","doi":"10.3996/042014-JFWM-034","usgsCitation":"McKee, A.M., Calhoun, D.L., Barichivich, W.J., Spear, S.F., Goldberg, C.S., and Glenn, T.C., 2015, Assessment of environmental DNA for detecting presence of imperiled aquatic amphibian species in isolated wetlands: Journal of Fish and Wildlife Management, v. 6, no. 2, p. 498-510, https://doi.org/10.3996/042014-JFWM-034.","productDescription":"13 p.","startPage":"498","endPage":"510","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063883","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":318025,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alabama, Florida, Georgia, South Carolina","county":"Irwin County","otherGeospatial":"Apalachicola National Forest, Fall Line Sandhills Wildlife Management Area, Fort Benning, Fort Stewart, Joseph W. 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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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]\n}","volume":"41","issue":"4","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"567a823ae4b0a04ef490fcdc","contributors":{"authors":[{"text":"Rennie, Michael D.","contributorId":34007,"corporation":false,"usgs":true,"family":"Rennie","given":"Michael","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":583078,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Weidel, Brian 0000-0001-6095-2773 bweidel@usgs.gov","orcid":"https://orcid.org/0000-0001-6095-2773","contributorId":2485,"corporation":false,"usgs":true,"family":"Weidel","given":"Brian","email":"bweidel@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":583077,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Claramunt, Randall M.","contributorId":19047,"corporation":false,"usgs":true,"family":"Claramunt","given":"Randall 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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%.
","language":"English","publisher":"Earthquake Engineering Research Institute","doi":"10.1193/103114EQS174M","usgsCitation":"Boyd, O.S., Haller, K., Luco, N., Moschetti, M.P., Mueller, C., Petersen, M.D., Rezaeian, S., and Rubinstein, J.L., 2015, Seismic hazard in the Nation's breadbasket: Earthquake Spectra, v. 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":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","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":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards 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":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards 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":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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In an effort to improve our ability to detect precursory activity leading to eruption at Okmok, we monitor a recent, and possibly ongoing, GPS-inferred rapid inflation event at the volcano using ambient noise interferometry (ANI). Applying this method, we identify changes in seismic velocity outside of Okmok’s caldera, which are related to the hydrologic cycle. Within the caldera, we observe decreases in seismic velocity that are associated with the GPS-inferred rapid inflation event. We also determine temporal changes in waveform decorrelation and show a continual increase in decorrelation rate over the time associated with the rapid inflation event. Themagnitude of relative velocity decreases and decorrelation rate increases are comparable to previous studies at Piton de la Fournaise that associate such changes with increased production of volatiles and/ormagmatic intrusion within the magma reservoir and associated opening of fractures and/or fissures. Notably, the largest decrease in relative velocity occurs along the intrastation path passing nearest to the center of the caldera. This observation, along with equal amplitude relative velocity decreases revealed via analysis of intracaldera autocorrelations, suggests that the inflation sourcemay be located approximately within the center of the caldera and represent recharge of shallow magma storage in this location. Importantly, there is a relative absence of seismicity associated with this and previous rapid inflation events at Okmok. Thus, these ANI results are the first seismic evidence of such rapid inflation at the volcano.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2015JB011939","usgsCitation":"Bennington, N., Haney, M.M., De Angelis, S., Thurber, C., and Freymueller, J., 2015, Monitoring changes in seismic velocity related to an ongoing rapid inflation event at Okmok volcano, Alaska: Journal of Geophysical Research, v. 120, no. 8, p. 5664-5676, https://doi.org/10.1002/2015JB011939.","productDescription":"13 p.","startPage":"5664","endPage":"5676","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068858","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":471603,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015jb011939","text":"Publisher Index Page"},{"id":325374,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Okmok Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -168.25928811603328,\n 53.48606857460288\n ],\n [\n -168.25928811603328,\n 53.35666372572206\n ],\n [\n -168.0005045660394,\n 53.35666372572206\n ],\n [\n -168.0005045660394,\n 53.48606857460288\n ],\n [\n -168.25928811603328,\n 53.48606857460288\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"120","issue":"8","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-08-18","publicationStatus":"PW","scienceBaseUri":"578dfdb4e4b0f1bea0e0f8a3","contributors":{"authors":[{"text":"Bennington, Ninfa","contributorId":49699,"corporation":false,"usgs":true,"family":"Bennington","given":"Ninfa","affiliations":[],"preferred":false,"id":642731,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haney, Matthew M. 0000-0003-3317-7884 mhaney@usgs.gov","orcid":"https://orcid.org/0000-0003-3317-7884","contributorId":172948,"corporation":false,"usgs":true,"family":"Haney","given":"Matthew","email":"mhaney@usgs.gov","middleInitial":"M.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":642730,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"De Angelis, Silvio","contributorId":172953,"corporation":false,"usgs":false,"family":"De Angelis","given":"Silvio","affiliations":[{"id":27128,"text":"Univ. of Liverpool","active":true,"usgs":false}],"preferred":false,"id":642732,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thurber, Clifford","contributorId":44067,"corporation":false,"usgs":true,"family":"Thurber","given":"Clifford","affiliations":[],"preferred":false,"id":642733,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Freymueller, Jeff","contributorId":82190,"corporation":false,"usgs":true,"family":"Freymueller","given":"Jeff","affiliations":[],"preferred":false,"id":642734,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70176400,"text":"70176400 - 2015 - Quantifying the residence time and flushing characteristics of a shallow, back-barrier estuary: Application of hydrodynamic and particle tracking models","interactions":[],"lastModifiedDate":"2016-09-13T09:39:55","indexId":"70176400","displayToPublicDate":"2015-12-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1584,"text":"Estuaries and Coasts","active":true,"publicationSubtype":{"id":10}},"title":"Quantifying the residence time and flushing characteristics of a shallow, back-barrier estuary: Application of hydrodynamic and particle tracking models","docAbstract":"Estuarine residence time is a major driver of eutrophication and water quality. Barnegat Bay-Little Egg Harbor (BB-LEH), New Jersey, is a lagoonal back-barrier estuary that is subject to anthropogenic pressures including nutrient loading, eutrophication, and subsequent declines in water quality. A combination of hydrodynamic and particle tracking modeling was used to identify the mechanisms controlling flushing, residence time, and spatial variability of particle retention. The models demonstrated a pronounced northward subtidal flow from Little Egg Inlet in the south to Pt. Pleasant Canal in the north due to frictional effects in the inlets, leading to better flushing of the southern half of the estuary and particle retention in the northern estuary. Mean residence time for BB-LEH was 13 days but spatial variability was between ∼0 and 30 days depending on the initial particle location. Mean residence time with tidal forcing alone was 24 days (spatial variability between ∼0 and 50 days); the tides were relatively inefficient in flushing the northern end of the Bay. Scenarios with successive exclusion of physical processes from the models revealed that meteorological and remote offshore forcing were stronger drivers of exchange than riverine inflow. Investigations of water quality and eutrophication should take into account spatial variability in hydrodynamics and residence time in order to better quantify the roles of nutrient loading, production, and flushing.
","language":"English","publisher":"Springer","doi":"10.1007/s12237-014-9885-3","usgsCitation":"Defne, Z., and Ganju, N., 2015, Quantifying the residence time and flushing characteristics of a shallow, back-barrier estuary: Application of hydrodynamic and particle tracking models: Estuaries and Coasts, v. 38, no. 5, p. 1719-1734, https://doi.org/10.1007/s12237-014-9885-3.","productDescription":"16 p.","startPage":"1719","endPage":"1734","ipdsId":"IP-057196","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":471614,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hdl.handle.net/1912/7506","text":"External Repository"},{"id":328587,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"38","issue":"5","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2014-09-23","publicationStatus":"PW","scienceBaseUri":"57d92340e4b090824ffa1b23","contributors":{"authors":[{"text":"Defne, Zafer 0000-0003-4544-4310 zdefne@usgs.gov","orcid":"https://orcid.org/0000-0003-4544-4310","contributorId":5520,"corporation":false,"usgs":true,"family":"Defne","given":"Zafer","email":"zdefne@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":648603,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ganju, Neil K. 0000-0002-1096-0465 nganju@usgs.gov","orcid":"https://orcid.org/0000-0002-1096-0465","contributorId":149613,"corporation":false,"usgs":true,"family":"Ganju","given":"Neil K.","email":"nganju@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":648604,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70193797,"text":"70193797 - 2015 - Determining climate change management priorities: A case study from Wisconsin ","interactions":[],"lastModifiedDate":"2017-11-10T10:32:00","indexId":"70193797","displayToPublicDate":"2015-12-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2231,"text":"Journal of Conservation Planning","active":true,"publicationSubtype":{"id":10}},"title":"Determining climate change management priorities: A case study from Wisconsin ","docAbstract":"A burgeoning dialogue exists regarding how to allocate resources to maximize the likelihood of long-term biodiversity conservation within the context of climate change. To make effective decisions in natural resource management, an iterative, collaborative, and learning-based decision process may be more successful than a strictly consultative approach. One important, early step in a decision process is to identify priority species or systems. Although this promotes the conservation of select species or systems, it may inadvertently alter the future of non-target species and systems. We describe a process to screen terrestrial wildlife for potential sensitivity to climate change and then use the results to engage natural resource professionals in a process of identifying priorities for monitoring, research, and adaptation strategy implementation. We demonstrate this approach using a case study from Wisconsin. In Wisconsin, experts identified 23 out of 353 species with sufficient empirical research and management understanding to inform targeted action. Habitat management and management of hydrological conditions were the common strategies for targeted action. Although there may be an interest in adaptation strategy implementation for many species and systems, experts considered existing information inadequate to inform targeted action. According to experts, 40% of the vertebrate species in Wisconsin will require near-term intervention for climate adaptation. These results will inform state-wide conservation planning as well as regional efforts.
","language":"English","publisher":"The Conservation Fund","usgsCitation":"LeDee, O., and Ribic, C., 2015, Determining climate change management priorities: A case study from Wisconsin : Journal of Conservation Planning, v. 11, no. 1, p. 1-12.","productDescription":"12 p.","startPage":"1","endPage":"12","ipdsId":"IP-040823","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":348449,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":348216,"type":{"id":15,"text":"Index Page"},"url":"https://www.journalconsplanning.org/"}],"country":"United 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,{"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.
","language":"English","publisher":"EERI","doi":"10.1193/110314EQS176M","usgsCitation":"Powers, P.M., and Field, E.H., 2015, The 2014 update to the National Seismic Hazard Model in California: Earthquake Spectra, v. 31, no. S1, p. 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