The Wind River Basin in Wyoming is one of many structural and sedimentary basins that formed in the Rocky Mountain foreland during the Laramide orogeny. The basin is nearly 200 miles long, 70 miles wide, and encompasses about 7,400 square miles in central Wyoming. The basin is bounded by the Washakie Range, Owl Creek uplift, and southern Bighorn Mountains on the north, the Casper arch on the east, the Granite Mountains on the south, and Wind River Range on the west.
Many important conventional oil and gas fields producing from reservoirs ranging in age from Mississippian through Tertiary have been discovered in this basin. In addition, an extensive unconventional overpressured basin-centered gas accumulation has been identified in Cretaceous and Tertiary strata in the deeper parts of the basin. It has long been suggested that various Upper Cretaceous marine shales, including the Cody Shale, are the principal hydrocarbon source rocks for many of these accumulations. With recent advances and success in horizontal drilling and multistage fracture stimulation, there has been an increase in exploration and completion of wells in these marine shales in other Rocky Mountain Laramide basins that were traditionally thought of only as hydrocarbon source rocks.
The two stratigraphic cross sections presented in this report were constructed as part of a project carried out by the U.S. Geological Survey to characterize and evaluate the undiscovered continuous (unconventional) oil and gas resources of the Niobrara interval of the Upper Cretaceous Cody Shale in the Wind River Basin in central Wyoming. The primary purpose of the cross sections is to show the stratigraphic relationship of the Niobrara equivalent strata and associated rocks in the lower part of the Cody Shale in the Wind River Basin. These two cross sections were constructed using borehole geophysical logs from 37 wells drilled for oil and gas exploration and production, and one surface section along East Sheep Creek near Shotgun Butte in the northwestern part of the basin. Both lines originate at the East Sheep Creek surface section and end near Clarkson Hill in the extreme southeastern part of the basin. The stratigraphic interval extends from the upper part of the Frontier Formation to the middle part of the Cody Shale. The datum is the base of the “chalk kick” marker bed, a distinctive resistivity peak or zone in the lower part of the Cody Shale. A gamma ray and (or) spontaneous potential (SP) log was used in combination with a resistivity log to identify and correlate units. Marine molluscan index fossils collected from nearby outcrop sections were projected into the subsurface to help determine the relative ages of the strata and aid in correlation.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3370","usgsCitation":"Finn, T.M., 2017, Stratigraphic cross sections of the Niobrara interval of the Cody Shale and associated rocks in the Wind River Basin, central Wyoming: U.S. Geological Survey Scientific Investigations Map 3370, 19 p., 1 sheet, https://doi.org/10.3133/sim3370.","productDescription":"Report: iv, 19 p.; Sheet: 56.00 x 29.00 inches","onlineOnly":"Y","ipdsId":"IP-073462","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":334322,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3370/coverthb.jpg"},{"id":334325,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3370/sim3370.pdf","text":"Report","size":"5.98 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3370 Pamphlet"},{"id":334327,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3370/sim3370_sheet.pdf","text":"Map","size":"1.56 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3370 Map"}],"country":"United States","state":"Wyoming","otherGeospatial":"Wind River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110,\n 42.5\n ],\n [\n -110,\n 43.75\n ],\n [\n -106.5,\n 43.75\n ],\n [\n -106.5,\n 42.5\n ],\n [\n -110,\n 42.5\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, USGS Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, Mail Stop 939
Denver Federal Center
Denver, CO 80225
In 1916, Swedish geologist Ernst Jakob Lennart von Post delivered a provocative lecture in Oslo, Norway, advocating the use of pollen grains in bog sediments as indicators of past vegetation and climate. The lecture spawned many applications and represents a landmark in multidisciplinary science.
","largerWorkTitle":"Nature Plants","language":"English","doi":"10.1038/nplants.2017.1","usgsCitation":"Edwards, K.J., Fyfe, R., and Jackson, S., 2017, The first 100 years of pollen analysis: Nature Plants, v. 3, 17001, https://doi.org/10.1038/nplants.2017.1.","productDescription":"17001","ipdsId":"IP-082947","costCenters":[{"id":41166,"text":"Southwest Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":470080,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/2164/9078","text":"External Repository"},{"id":381137,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"3","noUsgsAuthors":false,"publicationDate":"2017-02-07","publicationStatus":"PW","contributors":{"authors":[{"text":"Edwards, Kevin J.","contributorId":245536,"corporation":false,"usgs":false,"family":"Edwards","given":"Kevin","email":"","middleInitial":"J.","affiliations":[{"id":39960,"text":"University of Aberdeen, UK","active":true,"usgs":false}],"preferred":false,"id":806384,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fyfe, Ralph","contributorId":245537,"corporation":false,"usgs":false,"family":"Fyfe","given":"Ralph","email":"","affiliations":[{"id":39461,"text":"University of Plymouth, UK","active":true,"usgs":false}],"preferred":false,"id":806385,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jackson, Stephen T. 0000-0002-1487-4652","orcid":"https://orcid.org/0000-0002-1487-4652","contributorId":245538,"corporation":false,"usgs":true,"family":"Jackson","given":"Stephen T.","affiliations":[{"id":41166,"text":"Southwest Climate Adaptation Science Center","active":true,"usgs":true}],"preferred":true,"id":806386,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70189688,"text":"70189688 - 2017 - Comparing stream-specific to generalized temperature models to guide salmonid management in a changing climate","interactions":[],"lastModifiedDate":"2018-04-24T13:34:59","indexId":"70189688","displayToPublicDate":"2017-02-07T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3278,"text":"Reviews in Fish Biology and Fisheries","active":true,"publicationSubtype":{"id":10}},"title":"Comparing stream-specific to generalized temperature models to guide salmonid management in a changing climate","docAbstract":"Global climate change is predicted to increase air and stream temperatures and alter thermal habitat suitability for growth and survival of coldwater fishes, including brook charr (Salvelinus fontinalis), brown trout (Salmo trutta), and rainbow trout (Oncorhynchus mykiss). In a changing climate, accurate stream temperature modeling is increasingly important for sustainable salmonid management throughout the world. However, finite resource availability (e.g. funding, personnel) drives a tradeoff between thermal model accuracy and efficiency (i.e. cost-effective applicability at management-relevant spatial extents). Using different projected climate change scenarios, we compared the accuracy and efficiency of stream-specific and generalized (i.e. region-specific) temperature models for coldwater salmonids within and outside the State of Michigan, USA, a region with long-term stream temperature data and productive coldwater fisheries. Projected stream temperature warming between 2016 and 2056 ranged from 0.1 to 3.8 °C in groundwater-dominated streams and 0.2–6.8 °C in surface-runoff dominated systems in the State of Michigan. Despite their generally lower accuracy in predicting exact stream temperatures, generalized models accurately projected salmonid thermal habitat suitability in 82% of groundwater-dominated streams, including those with brook charr (80% accuracy), brown trout (89% accuracy), and rainbow trout (75% accuracy). In contrast, generalized models predicted thermal habitat suitability in runoff-dominated streams with much lower accuracy (54%). These results suggest that, amidst climate change and constraints in resource availability, generalized models are appropriate to forecast thermal conditions in groundwater-dominated streams within and outside Michigan and inform regional-level salmonid management strategies that are practical for coldwater fisheries managers, policy makers, and the public. We recommend fisheries professionals reserve resource-intensive stream-specific models for runoff-dominated systems containing high-priority fisheries resources (e.g. trophy individuals, endangered species) that will be directly impacted by projected stream warming.","language":"English","publisher":"SpringerLink","doi":"10.1007/s11160-017-9467-0","usgsCitation":"Andrew K. Carlson, Taylor, W.W., Hartikainen, K.M., Dana M. Infante, Beard, and Lynch, A., 2017, Comparing stream-specific to generalized temperature models to guide salmonid management in a changing climate: Reviews in Fish Biology and Fisheries, v. 2, no. 27, p. 443-462, https://doi.org/10.1007/s11160-017-9467-0.","productDescription":"19 p. 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Box 25046, Mail Stop 980
Denver, CO 80225
The U.S. Geological Survey Branch of Quality Systems operates the Precipitation Chemistry Quality Assurance Project (PCQA) for the National Atmospheric Deposition Program/National Trends Network (NADP/NTN) and National Atmospheric Deposition Program/Mercury Deposition Network (NADP/MDN). Since 1978, various programs have been implemented by the PCQA to estimate data variability and bias contributed by changing protocols, equipment, and sample submission schemes within NADP networks. These programs independently measure the field and laboratory components which contribute to the overall variability of NADP wet-deposition chemistry and precipitation depth measurements. The PCQA evaluates the quality of analyte-specific chemical analyses from the two, currently (2016) contracted NADP laboratories, Central Analytical Laboratory and Mercury Analytical Laboratory, by comparing laboratory performance among participating national and international laboratories. Sample contamination and stability are evaluated for NTN and MDN by using externally field-processed blank samples provided by the Branch of Quality Systems. A colocated sampler program evaluates the overall variability of NTN measurements and bias between dissimilar precipitation gages and sample collectors.
This report documents historical PCQA operations and general procedures for each of the external quality-assurance programs from 2007 to 2016.
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USGS Branch of Quality Systems
Box 25046, Mail Stop 401
Denver, CO 80225
Heavy rainfall occurred across Louisiana and southwestern Mississippi in August 2016 as a result of a slow-moving area of low pressure and a high amount of atmospheric moisture. The storm caused major flooding in the southern portions of Louisiana including areas surrounding Baton Rouge and Lafayette. Flooding occurred along the rivers such as the Amite, Comite, Tangipahoa, Tickfaw, Vermilion, and Mermentau Rivers. Over 31 inches of rain was reported in the city of Watson, 20 miles northeast of Baton Rouge, La., over the duration of the event. Streamflow-gaging stations operated by the U.S. Geological Survey (USGS) recorded peak streamflows of record at 10 locations, and 7 other locations experienced peak streamflows ranking in the top five for the duration of the period of record. In August 2016, USGS hydrographers made 50 discharge measurements at 21 locations on streams in Louisiana. Many of those discharge measurements were made for the purpose of verifying the accuracy of stage-streamflow relations at gaging stations operated by the USGS. Following the storm event, USGS hydrographers recovered and documented 590 high-water marks, noting location and height of the water above land surface. Many of these high-water marks were used to create 12 flood-inundation maps for selected communities of Louisiana that experienced flooding in August 2016. Digital datasets of the inundation area, modeling boundary, water depth rasters, and final map products are available online.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175005","collaboration":"Prepared in cooperation with the Federal Emergency Management Agency","usgsCitation":"Watson, K.M., Storm, J.B., Breaker, B.K., and Rose, C.E., 2017, Characterization of peak streamflows and flood inundation of selected areas in Louisiana from the August 2016 flood: U.S. Geological Survey Scientific Investigations Report 2017–5005, 26 p., https://doi.org/10.3133/sir20175005.","productDescription":"Report: v, 26 p.; Data Release","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-081535","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":334119,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5005/sir20175005.pdf","text":"Report","size":"7.98 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017–5005"},{"id":334118,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5005/coverthb2.jpg"},{"id":334120,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F79K48C1","text":"USGS Data Release","description":"USGS Data Release","linkHelpText":"Flood Inundation Extent and Depth in Selected Areas of Louisiana in August 2016"}],"country":"United States","state":"Louisiana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.3123779296875,\n 28.859107573773\n ],\n [\n -93.3123779296875,\n 31.475524020001806\n ],\n [\n -89.879150390625,\n 31.475524020001806\n ],\n [\n -89.879150390625,\n 28.859107573773\n ],\n [\n -93.3123779296875,\n 28.859107573773\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Lower Mississippi-Gulf Water Science Center
U.S. Geological Survey
401 Hardin Road
Little Rock, AR 72211
Groundwater quality in the 2,390-square-mile Madera/Chowchilla–Kings Shallow Aquifer study unit was investigated by the U.S. Geological Survey from August 2013 to April 2014 as part of the California State Water Resources Control Board Groundwater Ambient Monitoring and Assessment Program’s Priority Basin Project. The study was designed to provide a statistically unbiased, spatially distributed assessment of untreated groundwater quality in the shallow aquifer systems of the Madera, Chowchilla, and Kings subbasins of the San Joaquin Valley groundwater basin. The shallow aquifer system corresponds to the part of the aquifer system generally used by domestic wells and is shallower than the part of the aquifer system generally used by public-supply wells. This report presents the data collected for the study and a brief preliminary description of the results.
Groundwater samples were collected from 77 wells and were analyzed for organic constituents, inorganic constituents, selected isotopic and age-dating tracers, and microbial indicators. Most of the wells sampled for this study were private domestic wells. Unlike groundwater from public-supply wells, the groundwater from private domestic wells is not regulated for quality in California and is rarely analyzed for water-quality constituents. To provide context for the sampling results, however, concentrations of constituents measured in the untreated groundwater were compared with regulatory and non-regulatory benchmarks established for drinking-water quality by the U.S. Environmental Protection Agency, the State of California, and the U.S. Geological Survey.
Of the 319 organic constituents assessed in this study (90 volatile organic compounds and 229 pesticides and pesticide degradates), 17 volatile organic compounds and 23 pesticides and pesticide degradates were detected in groundwater samples; concentrations of all but 2 were less than the respective benchmarks. The fumigants 1,2-dibromo-3-chloropropane (DBCP) and 1,2-dibromoethane (EDB) were detected at concentrations above their respective regulatory benchmarks in samples from a total of four wells.
Most detections of inorganic constituents were at concentrations or activities less than the respective benchmark levels. Five inorganic constituents were detected in groundwater samples from one or more wells at concentrations or activities greater than their respective regulatory, health-based benchmarks: arsenic, uranium, nitrate, adjusted gross alpha particle activity, and gross beta particle activity. Four inorganic constituents were detected in samples from one or more wells at concentrations or activities greater than their respective non-regulatory, health-based benchmarks: manganese, molybdenum, vanadium, and radon-222. Three inorganic constituents were detected in groundwater samples from one or more wells at concentrations greater than their respective non-regulatory, aesthetic-based benchmarks: iron, sulfate, and total dissolved solids.
Microbial indicators (Escherichia coli, total coliform, and enterococci) were analyzed for presence or absence. The presence of Escherichia coli (E. coli) was not detected; the presence of total coliform was detected in samples from 10 of the 72 grid wells for which it was analyzed, and the presence of enterococci was detected in samples from 5 of the 73 grid wells analyzed.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1019","collaboration":"Prepared in cooperation with the California State Water Resources Control Board","usgsCitation":"Shelton, J.L., and Fram, M.S., 2017, Groundwater-quality data for the Madera/Chowchilla–Kings shallow aquifer study unit, 2013–14: Results from the California GAMA Program: U.S. Geological Survey Data Series 1019, 115 p., https://doi.org/10.3133/ds1019.","productDescription":"Report: viii, 115 p.","numberOfPages":"128","onlineOnly":"N","ipdsId":"IP-056132","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":334554,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1019/ds1019.pdf","text":"Report","size":"3.67 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1019"},{"id":334553,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1019/coverthb2.jpg"}],"country":"United States","state":"California","otherGeospatial":"Madera/Chowchilla-Kings Shallow Aquifer study unit","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.666667,\n 37.416667\n ],\n [\n -120.666667,\n 36\n ],\n [\n -119.166667,\n 36\n ],\n [\n -119.166667,\n 37.416667\n ],\n [\n -120.666667,\n 37.416667\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
For this study, a methodology was developed for assessing impacts of wind energy generation on populations of birds and bats at regional to national scales. The approach combines existing methods in applied ecology for prioritizing species in terms of their potential risk from wind energy facilities and estimating impacts of fatalities on population status and trend caused by collisions with wind energy infrastructure. Methods include a qualitative prioritization approach, demographic models, and potential biological removal. The approach can be used to prioritize species in need of more thorough study as well as to identify species with minimal risk. However, the components of this methodology require simplifying assumptions and the data required may be unavailable or of poor quality for some species. These issues should be carefully considered before using the methodology. The approach will increase in value as more data become available and will broaden the understanding of anthropogenic sources of mortality on bird and bat populations.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Wind energy and wildlife interactions","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer International Publishing","doi":"10.1007/978-3-319-51272-3_4","usgsCitation":"Diffendorfer, J., Beston, J.A., Merrill, M., Stanton, J.C., Corum, M., Loss, S., Thogmartin, W.E., Johnson, D.H., Erickson, R.A., and Heist, K.W., 2017, A method to assess the population-level consequences of wind energy facilities on bird and bat species, chap. of Wind energy and wildlife interactions, p. 65-76, https://doi.org/10.1007/978-3-319-51272-3_4.","productDescription":"12 p.","startPage":"65","endPage":"76","ipdsId":"IP-073352","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":339790,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-02-03","publicationStatus":"PW","scienceBaseUri":"58f5d43de4b0f2e20545e405","contributors":{"authors":[{"text":"Diffendorfer, James E. 0000-0003-1093-6948 jediffendorfer@usgs.gov","orcid":"https://orcid.org/0000-0003-1093-6948","contributorId":3208,"corporation":false,"usgs":true,"family":"Diffendorfer","given":"James E.","email":"jediffendorfer@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":649358,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beston, Julie A. jbeston@usgs.gov","contributorId":5673,"corporation":false,"usgs":true,"family":"Beston","given":"Julie","email":"jbeston@usgs.gov","middleInitial":"A.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":649359,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Merrill, Matthew D. 0000-0003-3766-847X mmerrill@usgs.gov","orcid":"https://orcid.org/0000-0003-3766-847X","contributorId":145534,"corporation":false,"usgs":true,"family":"Merrill","given":"Matthew D.","email":"mmerrill@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":649360,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stanton, Jessica C. 0000-0002-6225-3703 jcstanton@usgs.gov","orcid":"https://orcid.org/0000-0002-6225-3703","contributorId":5634,"corporation":false,"usgs":true,"family":"Stanton","given":"Jessica","email":"jcstanton@usgs.gov","middleInitial":"C.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":649361,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Corum, M.D. 0000-0002-9038-3935 mcorum@usgs.gov","orcid":"https://orcid.org/0000-0002-9038-3935","contributorId":2249,"corporation":false,"usgs":true,"family":"Corum","given":"M.D.","email":"mcorum@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":649362,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Loss, Scott R.","contributorId":140471,"corporation":false,"usgs":false,"family":"Loss","given":"Scott R.","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":649363,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Thogmartin, Wayne E. 0000-0002-2384-4279 wthogmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":2545,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","email":"wthogmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":649364,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Johnson, Douglas H. 0000-0002-7778-6641 douglas_h_johnson@usgs.gov","orcid":"https://orcid.org/0000-0002-7778-6641","contributorId":1387,"corporation":false,"usgs":true,"family":"Johnson","given":"Douglas","email":"douglas_h_johnson@usgs.gov","middleInitial":"H.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":649365,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Erickson, Richard A. 0000-0003-4649-482X rerickson@usgs.gov","orcid":"https://orcid.org/0000-0003-4649-482X","contributorId":5455,"corporation":false,"usgs":true,"family":"Erickson","given":"Richard","email":"rerickson@usgs.gov","middleInitial":"A.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":649366,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Heist, Kevin W.","contributorId":83040,"corporation":false,"usgs":false,"family":"Heist","given":"Kevin","email":"","middleInitial":"W.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":649367,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70178186,"text":"ofr20161193 - 2017 - The Wetland and Aquatic Research Center strategic science plan","interactions":[],"lastModifiedDate":"2017-02-06T09:04:14","indexId":"ofr20161193","displayToPublicDate":"2017-02-02T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-1193","title":"The Wetland and Aquatic Research Center strategic science plan","docAbstract":"The U.S. Geological Survey (USGS) Wetland and Aquatic Research Center (WARC) has two primary locations (Gainesville, Florida, and Lafayette, Louisiana) and field stations throughout the southeastern United States and Caribbean. WARC’s roots are in U.S. Fish and Wildlife Service (USFWS) and National Park Service research units that were brought into the USGS as the Biological Research Division in 1996. Founded in 2015, WARC was created from the merger of two long-standing USGS biology science Centers—the Southeast Ecological Science Center and the National Wetlands Research Center—to bring together expertise in biology, ecology, landscape science, geospatial applications, and decision support in order to address issues nationally and internationally. WARC scientists apply their expertise to a variety of wetland and aquatic research and monitoring issues that require coordinated, integrated efforts to better understand natural environments. By increasing basic understanding of the biology of important species and broader ecological and physiological processes, this research provides information to policymakers and aids managers in their stewardship of natural resources and in regulatory functions.
This strategic science plan (SSP) was developed to guide WARC research during the next 5–10 years in support of Department of the Interior (DOI) partnering bureaus such as the USFWS, the National Park Service, and the Bureau of Ocean Energy Management, as well as other Federal, State, and local natural resource management agencies. The SSP demonstrates the alignment of the WARC goals with the USGS mission areas, associated programs, and other DOI initiatives. The SSP is necessary for workforce planning and, as such, will be used as a guide for future needs for personnel. The SSP also will be instrumental in developing internal funding priorities and in promoting WARC’s capabilities to both external cooperators and other groups within the USGS.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161193","usgsCitation":"U.S. Geological Survey, 2017, The Wetland and Aquatic Research Center strategic science plan: U.S. Geological Survey Open-File Report 2016–1193, 17 p., https://doi.org/10.3133/ofr20161193.","productDescription":"iii, 17 p.","numberOfPages":"26","onlineOnly":"Y","ipdsId":"IP-072367","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":334602,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1193/ofr20161193.pdf","text":"Report","size":"2.60 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016–1193"},{"id":331220,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1193/coverthb.jpg"}],"contact":"Director, Wetland and Aquatic Research Center
U.S. Geological Survey
7920 NW 71st Street
Gainesville, FL 32653
https://www.usgs.gov/centers/wetland-and-aquatic-research-center-warc
","tableOfContents":"Renibacterium salmoninarum, the causative agent of salmonid bacterial kidney disease (BKD), is endemic in many wild trout species in northerly regions. The aim of the present study was to determine the optimal R. salmoninarum sampling/testing strategy for wild brown trout (Salmo trutta L.) populations in Iceland. Fish were netted in a lake and multiple organs—kidney, spleen, gills, oesophagus and mid-gut—were sampled and subjected to five detection tests i.e. culture, polyclonal enzyme-linked immunosorbent assay (pELISA) and three different PCR tests. The results showed that each fish had encountered R. salmoninarum but there were marked differences between results obtained depending on organ and test. The bacterium was not cultured from any kidney sample while all kidney samples were positive by pELISA. At least one organ from 92.9% of the fish tested positive by PCR. The results demonstrated that the choice of tissue and diagnostic method can dramatically influence the outcome of R. salmoninarum surveys.
","language":"English","publisher":"European Association of Fish Pathologists","usgsCitation":"Guomundsdottir, S., Applegate, L.M., Arnason, I., Kristmundsson, A., Purcell, M., and Elliott, D.G., 2017, Detecting Renibacterium salmoninarum in wild brown trout by use of multiple organ samples and diagnostic methods: Bulletin of the European Association of Fish Pathologists, v. 37, no. 1, p. 31-40.","productDescription":"12 p.","startPage":"31","endPage":"40","numberOfPages":"12","ipdsId":"IP-080542","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":347174,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":347206,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://eafp.org/bulletin-contents-37-1/"}],"volume":"37","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59eeffa9e4b0220bbd988fb5","contributors":{"authors":[{"text":"Guomundsdottir, S.","contributorId":198069,"corporation":false,"usgs":false,"family":"Guomundsdottir","given":"S.","email":"","affiliations":[],"preferred":false,"id":714997,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Applegate, Lynn M. capplegate@usgs.gov","contributorId":5647,"corporation":false,"usgs":true,"family":"Applegate","given":"Lynn","email":"capplegate@usgs.gov","middleInitial":"M.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":714998,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Arnason, I.O.","contributorId":198070,"corporation":false,"usgs":false,"family":"Arnason","given":"I.O.","email":"","affiliations":[],"preferred":false,"id":714999,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kristmundsson, A.","contributorId":198071,"corporation":false,"usgs":false,"family":"Kristmundsson","given":"A.","email":"","affiliations":[],"preferred":false,"id":715000,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Purcell, Maureen K. mpurcell@usgs.gov","contributorId":3061,"corporation":false,"usgs":true,"family":"Purcell","given":"Maureen K.","email":"mpurcell@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":false,"id":715001,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Elliott, Diane G. 0000-0002-4809-6692 dgelliott@usgs.gov","orcid":"https://orcid.org/0000-0002-4809-6692","contributorId":2947,"corporation":false,"usgs":true,"family":"Elliott","given":"Diane","email":"dgelliott@usgs.gov","middleInitial":"G.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":715002,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70199536,"text":"70199536 - 2017 - Resampling of spatially correlated data with preferential sampling for the estimation of frequency distributions and semivariograms","interactions":[],"lastModifiedDate":"2018-09-20T15:32:04","indexId":"70199536","displayToPublicDate":"2017-02-01T15:31:58","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3478,"text":"Stochastic Environmental Research and Risk Assessment","active":true,"publicationSubtype":{"id":10}},"title":"Resampling of spatially correlated data with preferential sampling for the estimation of frequency distributions and semivariograms","docAbstract":"Spatial data are commonly minimal and may have been collected in the process of confirming the profitability of a mining venture or investigating a contaminated site. In such situations, it is common to have measurements preferentially taken in the most critical areas (sweet spots, allegedly contaminated areas), thus conditionally biasing the sample. While preferential sampling makes good practical sense, its direct use leads to distorted sample moments and percentiles. Spatial clusters are a problem that has been identified in the past and solved with approaches ranging from ad hoc solutions to highly elaborate mathematical formulations, covering mostly the effect of clustering on the cumulative frequency distribution. The method proposed here is a form of resample, free of special assumptions, does not use weights to ponder the measurements, does not find solutions by successive approximation and provides variability in the results. The new method is illustrated with a synthetic dataset with an exponential semivariogram and purposely generated to follow a lognormal distribution. The lognormal distribution is both difficult to work with and typical of many attributes of practical interest. Testing of the new solution shows that sample subsets derived from resampled datasets can closely approximate the true probability distribution and the semivariogram, clearly outperforming the original preferentially sampled data.
","language":"English","publisher":"Springer","doi":"10.1007/s00477-016-1289-4","usgsCitation":"Olea, R., 2017, Resampling of spatially correlated data with preferential sampling for the estimation of frequency distributions and semivariograms: Stochastic Environmental Research and Risk Assessment, v. 31, no. 2, p. 481-491, https://doi.org/10.1007/s00477-016-1289-4.","productDescription":"11 p.","startPage":"481","endPage":"491","ipdsId":"IP-075731","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":357567,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"31","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-07-09","publicationStatus":"PW","scienceBaseUri":"5bc031e1e4b0fc368eb53a4e","contributors":{"authors":[{"text":"Olea, Ricardo A. 0000-0003-4308-0808","orcid":"https://orcid.org/0000-0003-4308-0808","contributorId":26436,"corporation":false,"usgs":true,"family":"Olea","given":"Ricardo A.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":745812,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70200023,"text":"70200023 - 2017 - In situ assessment of lampricide toxicity to age-0 lake sturgeon","interactions":[],"lastModifiedDate":"2018-10-11T11:01:41","indexId":"70200023","displayToPublicDate":"2017-02-01T11:01:35","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"displayTitle":"In situ assessment of lampricide toxicity to age-0 lake sturgeon","title":"In situ assessment of lampricide toxicity to age-0 lake sturgeon","docAbstract":"The lampricides 3-trifluoromethyl-4-nitrophenol (TFM) and 2′, 5-dichloro-4′-nitrosalicylanilide (niclosamide) are used to control sea lamprey (Petromyzon marinus), an invasive species in the Great Lakes. Age-0 lake sturgeon (Acipenser fulvescens), a species of conservationconcern, share similar stream habitats with larval sea lampreys and these streams can be targeted for lampricide applications on a 3- to 5-year cycle. Previous laboratory researchfound that lake sturgeon smaller than 100 mm could be susceptible to lampricide treatments. We conducted stream-side toxicity (bioassay) and in situ studies in conjunction with 10 lampricide applications in nine Great Lakes tributaries to determine whether sea lamprey treatments could result in in situ age-0 lake sturgeon mortality, and developed a logistic model to help predict lake sturgeon survival during future treatments. In the bioassays the observed concentrations where no lake sturgeon mortality occurred (no observable effect concentration, NOEC) were at or greater than the observed sea lamprey minimum lethal concentration (MLC or LC99) in 7 of 10 tests. We found that the mean in situ survival of age-0 lake sturgeon during 10 lampricide applications was 80%, with a range of 45–100% survival within streams. Modeling indicated that in age-0 lake sturgeon survival was negatively correlated with absolute TFM concentration and stream alkalinity, and positively correlated with stream pH and temperature. Overall survival was higher than expected based on previous research, and we expect that these data will help managers with decisions on the trade-offs between sea lamprey control and the effect on stream-specific populations of age-0 lake sturgeon.
When and whence does wood enter large mountain alluvial rivers? How stable through time are characteristics and quantities of wood deposited in a reach? These simple questions related to the complex practice of wood budgeting are explored on the Isère River in France. We hypothesise that (i) the wood originates from the riparian zone all along the alluvial reach and that (ii) the characters and quantity of wood in the reach can vary through time according to flood occurrence and provenance. In order to validate these hypotheses, two complementary approaches were performed: (i) wood pieces were surveyed along 190 km river length and taxonomy, in-channel wood macromorphology, and dendrochemistry were used to infer wood origin (local vs. upstream, respective subbasin contributions) and transport conditions; (ii) wood movement was monitored using both tracking techniques in specific sampling plots and with an experiment orchestrated using wood placement coupled with a significant artificial flood. Surveys were done over a period of 3 years so as to include two distinct sampling events to explore wood deposition and mobilisation within a channel network under different flood conditions. One of the subbasins, the Arly River, underwent a 1-in-30-year flood in 2004, allowing us to assess its effect on in-channel wood quantity and characteristics.
Results confirm that wood is primarily introduced by erosion from river banks but they are not always as close as expected from the sites of deposition. Temporal variability of wood introduced, deposited, and transferred downstream is also significant in terms of abundance and origin as shown by dendrochemical and macromorphological signatures. The types of wood observed along the channel length changes through time. Large flood signature can be detected from wood characteristics and uplands make a slight contribution. But in average, wood characteristics do not change much (no significant difference between years and tributaries in wood characteristics based on discriminant analysis). Data suggest that the interannual variability is fairly low, so that the diversity of wood characteristics is maintained by the complex and multiple sources of wood in the network. Further research is needed to better understand such patterns and to study physical breakage in space and time to better infer distance between sources and depositional zones.
Earthquake ground‐motion recordings are scarce in the central and eastern United States (CEUS) for large‐magnitude events and at close distances. We use two different simulation approaches, a deterministic physics‐based method and a site‐based stochastic method, to simulate ground motions over a wide range of magnitudes. Drawing on previous results for the modeling of recordings from the 2011 Mw 5.8 Mineral, Virginia, earthquake and using the 2001 Mw 7.6 Bhuj, India, earthquake as a tectonic analog for a large magnitude CEUS event, we are able to calibrate the two simulation methods over this magnitude range. Both models show a good fit to the Mineral and Bhuj observations from 0.1 to 10 Hz. Model parameters are then adjusted to obtain simulations for Mw 6.5, 7.0, and 7.6 events in the CEUS. Our simulations are compared with the 2014 U.S. Geological Survey weighted combination of existing ground‐motion prediction equations in the CEUS. The physics‐based simulations show comparable response spectral amplitudes and a fairly similar attenuation with distance. The site‐based stochastic simulations suggest a slightly faster attenuation of the response spectral amplitudes with distance for larger magnitude events and, as a result, slightly lower amplitudes at distances greater than 200 km. Both models are plausible alternatives and, given the few available data points in the CEUS, can be used to represent the epistemic uncertainty in modeling of postulated CEUS large‐magnitude events.
Trout species often segregate along elevational gradients, yet the mechanisms driving this pattern are not fully understood. On the Logan River, Utah, USA, exotic brown trout (Salmo trutta) dominate at low elevations but are near-absent from high elevations with native Bonneville cutthroat trout (Onchorhynchus clarkii utah). We used a spatially-explicit Bayesian modeling approach to evaluate how abiotic conditions (describing mechanisms related to temperature and physical habitat) as well as propagule pressure explained the distribution of brown trout in this system. Many covariates strongly explained redd abundance based on model performance and coefficient strength, including average annual temperature, average summer temperature, gravel availability, distance from a concentrated stocking area, and anchor ice-impeded distance from a concentrated stocking area. In contrast, covariates that exhibited low performance in models and/or a weak relationship to redd abundance included reach-average water depth, stocking intensity to the reach, average winter temperature, and number of days with anchor ice. Even if climate change creates more suitable summer temperature conditions for brown trout at high elevations, our findings suggest their success may be limited by other conditions. The potential role of anchor ice in limiting movement upstream is compelling considering evidence suggesting anchor ice prevalence on the Logan River has decreased significantly over the last several decades, likely in response to climatic changes. Further experimental and field research is needed to explore the role of anchor ice, spawning gravel availability, and locations of historical stocking in structuring brown trout distributions on the Logan River and elsewhere.
","language":"English","publisher":"Springer","doi":"10.1007/s10530-016-1322-z","usgsCitation":"Meredith, C.S., Budy, P., Hooten, M., and Oliveira Prates, M., 2017, Assessing conditions influencing the longitudinal distribution of exotic brown trout (Salmo trutta) in a mountain stream: a spatially-explicit modeling approach: Biological Invasions, v. 19, no. 2, p. 503-519, https://doi.org/10.1007/s10530-016-1322-z.","productDescription":"17 p.","startPage":"503","endPage":"519","ipdsId":"IP-069503","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":346993,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","otherGeospatial":"Logan River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.8023681640625,\n 41.734941789858006\n ],\n [\n -111.53594970703125,\n 41.734941789858006\n ],\n [\n -111.53594970703125,\n 41.95336258301847\n ],\n [\n -111.8023681640625,\n 41.95336258301847\n ],\n [\n -111.8023681640625,\n 41.734941789858006\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"19","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-11-16","publicationStatus":"PW","scienceBaseUri":"59e9b996e4b05fe04cd65cac","contributors":{"authors":[{"text":"Meredith, Christy S.","contributorId":197695,"corporation":false,"usgs":false,"family":"Meredith","given":"Christy","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":714105,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Budy, Phaedra E. 0000-0002-9918-1678 pbudy@usgs.gov","orcid":"https://orcid.org/0000-0002-9918-1678","contributorId":140028,"corporation":false,"usgs":true,"family":"Budy","given":"Phaedra","email":"pbudy@usgs.gov","middleInitial":"E.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":714037,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hooten, Mevin 0000-0002-1614-723X mhooten@usgs.gov","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":2958,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","email":"mhooten@usgs.gov","affiliations":[{"id":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":714038,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Oliveira Prates, Marcos","contributorId":197696,"corporation":false,"usgs":false,"family":"Oliveira Prates","given":"Marcos","email":"","affiliations":[],"preferred":false,"id":714106,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70188352,"text":"70188352 - 2017 - Oxygen isotope geochemistry of mafic phenocrysts in primitive mafic lavas from the southernmost Cascade Range, California","interactions":[],"lastModifiedDate":"2018-03-16T11:29:21","indexId":"70188352","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":738,"text":"American Mineralogist","active":true,"publicationSubtype":{"id":10}},"title":"Oxygen isotope geochemistry of mafic phenocrysts in primitive mafic lavas from the southernmost Cascade Range, California","docAbstract":"Previously reported whole-rock δ18O values (5.6–7.8‰) for primitive quaternary mafic lavas from the southernmost Cascades (SMC) are often elevated (up to 1‰) relative to δ18O values expected for mafic magmas in equilibrium with mantle peridotite. Olivine, clinopyroxene, and plagioclase crystals were separated from 29 geochemically well-characterized mafic lavas for δ18O measurements by laser fluorination to assess modification of the mantle sources by ancient and modern subducted components. Oxygen isotope values of olivine phenocrysts in calc-alkaline lavas and contemporaneous high alumina olivine tholeiitic (HAOT) lavas generally exceed depleted mantle olivine values (~4.9–5.3‰). Modern addition of up to 6 wt% slab-derived fluid from Gorda serpentinized peridotite dehydration (~15‰) or chlorite dehydration (~10‰) within the serpentinized peridotite can provide the 18O enrichment detected in olivine phenocrysts (δ18Oolivine = 5.3–6.3‰) in calc-alkaline mafic lavas, and elevate 18O in overlying mantle lithosphere, as well. Specifically, although HAOT δ18Oolivine values (5.5–5.7‰) may reflect partial melting in heterogeneous 18O enriched mantle source domains that developed during multiple subduction events associated with terrane accretion (e.g., <1 wt% of ~15‰ materials), an additional 18O enrichment of up to 2 wt% of 10–15‰ slab-derived hydrous fluids might be accommodated. The calc-alkaline primitive magmas appear to have experienced a continuous range of open system processes, which operate in the mantle and during rapid magma ascent to eruption, and occasionally post quench. Textural relationships and geochemistry of these lava samples are consistent with blends of mafic phenocrysts and degassed melts in varying states of 18O disequilibrium. In lenses of accumulated melt within peridotite near the base of the crust, coexisting olivine and clinopyroxene δ18O values probably are not at isotopic equilibrium because fluids introduced into the system perturbed the δ18Omelt values. A “sudden” melt extraction event interrupts 18O equilibration in phenocrysts and poorly mixed melt(s). Rapid ascent of volatile oversaturated primitive mafic magma through the crust appears to be accompanied by devolatilization and crystallization of anorthite-rich plagioclase with elevated δ18Oplag values. The (Sr/P)N values for the whole rock geochemistry are consistent with a 87Sr/86Sr ~0.7027 slab-derived fluid addition into the infertile peridotite source of magmas, and melt devolatilization is recorded in the mixture of disequilibrium δ18O values for the constituent phases of lavas. Morbidity of the Gorda Plate as it undergoes intense deformation from the spreading ridge to the trench is likely a key factor to developing the carrying capacity of hydrous fluids and mineral phases in the slab subducting into the SMC mantle.
","language":"English","publisher":"Mineralogical Society of America","doi":"10.2138/am-2017-5588","usgsCitation":"Underwood, S.J., and Clynne, M.A., 2017, Oxygen isotope geochemistry of mafic phenocrysts in primitive mafic lavas from the southernmost Cascade Range, California: American Mineralogist, v. 102, no. 2, p. 251-261, https://doi.org/10.2138/am-2017-5588.","productDescription":"11 p.","startPage":"251","endPage":"261","ipdsId":"IP-075965","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":352601,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Cascade Range","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.4920654296875,\n 39.9434364619742\n ],\n [\n -120.794677734375,\n 39.9434364619742\n ],\n [\n -120.794677734375,\n 40.990264773996884\n ],\n [\n -122.4920654296875,\n 40.990264773996884\n ],\n [\n -122.4920654296875,\n 39.9434364619742\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"102","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-02-01","publicationStatus":"PW","scienceBaseUri":"5afee8d3e4b0da30c1bfc4be","contributors":{"authors":[{"text":"Underwood, Sandra J.","contributorId":192684,"corporation":false,"usgs":false,"family":"Underwood","given":"Sandra","email":"","middleInitial":"J.","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":697361,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Clynne, Michael A. 0000-0002-4220-2968 mclynne@usgs.gov","orcid":"https://orcid.org/0000-0002-4220-2968","contributorId":2032,"corporation":false,"usgs":true,"family":"Clynne","given":"Michael","email":"mclynne@usgs.gov","middleInitial":"A.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":697360,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70189317,"text":"70189317 - 2017 - Human health screening and public health significance of contaminants of emerging concern detected in public water supplies","interactions":[],"lastModifiedDate":"2017-07-11T09:02:13","indexId":"70189317","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5331,"text":"Science of Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Human health screening and public health significance of contaminants of emerging concern detected in public water supplies","docAbstract":"The source water and treated drinking water from twenty five drinking water treatment plants (DWTPs) across the United States were sampled in 2010–2012. Samples were analyzed for 247 contaminants using 15 chemical and microbiological methods. Most of these contaminants are not regulated currently either in drinking water or in discharges to ambient water by the U. S. Environmental Protection Agency (USEPA) or other U.S. regulatory agencies. This analysis shows that there is little public health concern for most of the contaminants detected in treated water from the 25 DWTPs participating in this study. For vanadium, the calculated Margin of Exposure (MOE) was less than the screening MOE in two DWTPs. For silicon, the calculated MOE was less than the screening MOE in one DWTP. Additional study, for example a national survey may be needed to determine the number of people ingesting vanadium and silicon above a level of concern. In addition, the concentrations of lithium found in treated water from several DWTPs are within the range previous research has suggested to have a human health effect. Additional investigation of this issue is necessary. Finally, new toxicological data suggest that exposure to manganese at levels in public water supplies may present a public health concern which will require a robust assessment of this information.
","language":"English","publisher":"ScienceDirect","doi":"10.1016/j.scitotenv.2016.03.146","usgsCitation":"Benson, R., Conerly, O.D., Sander, W., Batt, A.L., Boone, J.S., Furlong, E.T., Glassmeyer, S., Kolpin, D.W., and Mash, H., 2017, Human health screening and public health significance of contaminants of emerging concern detected in public water supplies: Science of Total Environment, v. 579, p. 1643-1648, https://doi.org/10.1016/j.scitotenv.2016.03.146.","productDescription":"6 p.","startPage":"1643","endPage":"1648","ipdsId":"IP-061632","costCenters":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"links":[{"id":470103,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/6277017","text":"External Repository"},{"id":343548,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"579","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5965b227e4b0d1f9f05b37df","contributors":{"authors":[{"text":"Benson, Robert","contributorId":194436,"corporation":false,"usgs":false,"family":"Benson","given":"Robert","email":"","affiliations":[],"preferred":false,"id":704125,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conerly, Octavia D.","contributorId":194437,"corporation":false,"usgs":false,"family":"Conerly","given":"Octavia","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":704126,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sander, William","contributorId":194438,"corporation":false,"usgs":false,"family":"Sander","given":"William","email":"","affiliations":[],"preferred":false,"id":704127,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Batt, Angela L.","contributorId":184134,"corporation":false,"usgs":false,"family":"Batt","given":"Angela","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":704128,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Boone, J. Scott","contributorId":178697,"corporation":false,"usgs":false,"family":"Boone","given":"J.","email":"","middleInitial":"Scott","affiliations":[],"preferred":false,"id":704129,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Furlong, Edward T. 0000-0002-7305-4603 efurlong@usgs.gov","orcid":"https://orcid.org/0000-0002-7305-4603","contributorId":740,"corporation":false,"usgs":true,"family":"Furlong","given":"Edward","email":"efurlong@usgs.gov","middleInitial":"T.","affiliations":[{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":704130,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Glassmeyer, Susan T.","contributorId":72924,"corporation":false,"usgs":true,"family":"Glassmeyer","given":"Susan T.","affiliations":[],"preferred":false,"id":704131,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kolpin, Dana W. 0000-0002-3529-6505 dwkolpin@usgs.gov","orcid":"https://orcid.org/0000-0002-3529-6505","contributorId":1239,"corporation":false,"usgs":true,"family":"Kolpin","given":"Dana","email":"dwkolpin@usgs.gov","middleInitial":"W.","affiliations":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"preferred":true,"id":704119,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Mash, Heath","contributorId":184088,"corporation":false,"usgs":false,"family":"Mash","given":"Heath","affiliations":[],"preferred":false,"id":704132,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70190678,"text":"70190678 - 2017 - Integration of genetic and demographic data to assess population risk in a continuously distributed species","interactions":[],"lastModifiedDate":"2018-03-26T14:33:09","indexId":"70190678","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1324,"text":"Conservation Genetics","active":true,"publicationSubtype":{"id":10}},"title":"Integration of genetic and demographic data to assess population risk in a continuously distributed species","docAbstract":"The identification and demographic assessment of biologically meaningful populations is fundamental to species’ ecology and management. Although genetic tools are used frequently to identify populations, studies often do not incorporate demographic data to understand their respective population trends. We used genetic data to define subpopulations in a continuously distributed species. We assessed demographic independence and variation in population trends across the distribution. Additionally, we identified potential barriers to gene flow among subpopulations. We sampled greater sage-grouse (Centrocercus urophasianus) leks from across their range (≈175,000 Km2) in Wyoming and amplified DNA at 14 microsatellite loci for 1761 samples. Subsequently, we assessed population structure in unrelated individuals (n = 872) by integrating results from multiple Bayesian clustering approaches and used the boundaries to inform our assessment of long-term population trends and lek activity over the period of 1995–2013. We identified four genetic clusters of which two northern ones showed demographic independence from the others. Trends in population size for the northwest subpopulation were statistically different from the other three genetic clusters and the northeast and southwest subpopulations demonstrated a general trend of increasing proportion of inactive leks over time. Population change from 1996 to 2012 suggested population growth in the southern subpopulations and decline, or neutral, change in the northern subpopulations. We suggest that sage-grouse subpopulations in northern Wyoming are at greater risk of extirpation than the southern subpopulations due to smaller census and effective population sizes and higher variability within subpopulations. Our research is an example of incorporating genetic and demographic data and provides guidance on the identification of subpopulations of conservation concern.
","language":"English","publisher":"Springer","doi":"10.1007/s10592-016-0885-7","usgsCitation":"Fedy, B., Row, J.R., and Oyler-McCance, S.J., 2017, Integration of genetic and demographic data to assess population risk in a continuously distributed species: Conservation Genetics, v. 18, no. 1, p. 89-104, https://doi.org/10.1007/s10592-016-0885-7.","productDescription":"16 p.","startPage":"89","endPage":"104","ipdsId":"IP-060878","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":345643,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"18","issue":"1","noUsgsAuthors":false,"publicationDate":"2016-09-22","publicationStatus":"PW","scienceBaseUri":"59b8f220e4b08b1644e0aeeb","contributors":{"authors":[{"text":"Fedy, Bradley C.","contributorId":40536,"corporation":false,"usgs":true,"family":"Fedy","given":"Bradley C.","affiliations":[],"preferred":false,"id":710146,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Row, Jeffery R.","contributorId":178107,"corporation":false,"usgs":false,"family":"Row","given":"Jeffery","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":710147,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Oyler-McCance, Sara J. 0000-0003-1599-8769 sara_oyler-mccance@usgs.gov","orcid":"https://orcid.org/0000-0003-1599-8769","contributorId":1973,"corporation":false,"usgs":true,"family":"Oyler-McCance","given":"Sara","email":"sara_oyler-mccance@usgs.gov","middleInitial":"J.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":710148,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70187625,"text":"70187625 - 2017 - Is “morphodynamic equilibrium” an oxymoron?","interactions":[],"lastModifiedDate":"2017-05-11T12:52:18","indexId":"70187625","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1431,"text":"Earth-Science Reviews","active":true,"publicationSubtype":{"id":10}},"title":"Is “morphodynamic equilibrium” an oxymoron?","docAbstract":"Morphodynamic equilibrium is a widely adopted yet elusive concept in the field of geomorphology of coasts, rivers and estuaries. Based on the Exner equation, an expression of mass conservation of sediment, we distinguish three types of equilibrium defined as static and dynamic, of which two different types exist. Other expressions such as statistical and quasi-equilibrium which do not strictly satisfy the Exner conditions are also acknowledged for their practical use. The choice of a temporal scale is imperative to analyse the type of equilibrium. We discuss the difference between morphodynamic equilibrium in the “real world” (nature) and the “virtual world” (model). Modelling studies rely on simplifications of the real world and lead to understanding of process interactions. A variety of factors affect the use of virtual-world predictions in the real world (e.g., variability in environmental drivers and variability in the setting) so that the concept of morphodynamic equilibrium should be mathematically unequivocal in the virtual world and interpreted over the appropriate spatial and temporal scale in the real world. We draw examples from estuarine settings which are subject to various governing factors which broadly include hydrodynamics, sedimentology and landscape setting. Following the traditional “tide-wave-river” ternary diagram, we summarize studies to date that explore the “virtual world”, discuss the type of equilibrium reached and how it relates to the real world.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.earscirev.2016.12.002","usgsCitation":"Zhou, Z., Coco, G., Townend, I., Olabarrieta, M., van der Wegen, M., Gong, Z., D’Alpaos, A., Gao, S., Jaffe, B.E., Gelfenbaum, G.R., He, Q., Wang, Y., Lanzoni, S., Wang, Z., Winterwerp, H., and Zhang, C., 2017, Is “morphodynamic equilibrium” an oxymoron?: Earth-Science Reviews, v. 165, p. 257-267, https://doi.org/10.1016/j.earscirev.2016.12.002.","productDescription":"11 p.","startPage":"257","endPage":"267","ipdsId":"IP-080889","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":470085,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://doi.org/10.1016/j.earscirev.2016.12.002>).","text":"External Repository"},{"id":341111,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"165","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59154664e4b01a342e6912e1","contributors":{"authors":[{"text":"Zhou, Zeng","contributorId":191934,"corporation":false,"usgs":false,"family":"Zhou","given":"Zeng","email":"","affiliations":[],"preferred":false,"id":694808,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coco, Giovanni","contributorId":84978,"corporation":false,"usgs":true,"family":"Coco","given":"Giovanni","affiliations":[],"preferred":false,"id":694809,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Townend, Ian","contributorId":191936,"corporation":false,"usgs":false,"family":"Townend","given":"Ian","affiliations":[],"preferred":false,"id":694810,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Olabarrieta, Maitane 0000-0002-7619-7992 molabarrieta@usgs.gov","orcid":"https://orcid.org/0000-0002-7619-7992","contributorId":81631,"corporation":false,"usgs":true,"family":"Olabarrieta","given":"Maitane","email":"molabarrieta@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":694811,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"van der Wegen, Mick","contributorId":76455,"corporation":false,"usgs":true,"family":"van der Wegen","given":"Mick","affiliations":[],"preferred":false,"id":694812,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gong, Zheng","contributorId":191939,"corporation":false,"usgs":false,"family":"Gong","given":"Zheng","email":"","affiliations":[],"preferred":false,"id":694813,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"D’Alpaos, 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ggelfenbaum@usgs.gov","orcid":"https://orcid.org/0000-0003-1291-6107","contributorId":742,"corporation":false,"usgs":true,"family":"Gelfenbaum","given":"Guy","email":"ggelfenbaum@usgs.gov","middleInitial":"R.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":694807,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"He, Qing","contributorId":191942,"corporation":false,"usgs":false,"family":"He","given":"Qing","email":"","affiliations":[],"preferred":false,"id":694817,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Wang, Yaping","contributorId":191943,"corporation":false,"usgs":false,"family":"Wang","given":"Yaping","email":"","affiliations":[],"preferred":false,"id":694818,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Lanzoni, Stefano","contributorId":191944,"corporation":false,"usgs":false,"family":"Lanzoni","given":"Stefano","email":"","affiliations":[],"preferred":false,"id":694819,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Wang, Zhengbing","contributorId":191945,"corporation":false,"usgs":false,"family":"Wang","given":"Zhengbing","email":"","affiliations":[],"preferred":false,"id":694820,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Winterwerp, Han","contributorId":191946,"corporation":false,"usgs":false,"family":"Winterwerp","given":"Han","email":"","affiliations":[],"preferred":false,"id":694821,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Zhang, Changkuan","contributorId":191947,"corporation":false,"usgs":false,"family":"Zhang","given":"Changkuan","email":"","affiliations":[],"preferred":false,"id":694822,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}} ,{"id":70188375,"text":"70188375 - 2017 - Multi-year microbial source tracking 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Concentrations, loadings and yields of E. coli and microbial source tracking (MST) markers, were characterized during base flow and storm events in five subbasins within Independence, as well as sources entering and leaving the city through the river. The E. coli water quality threshold was exceeded in 29% of base-flow and 89% of storm-event samples. The total contribution of E. coli and MST markers from tributaries within Independence to the Little Blue River, regardless of streamflow, did not significantly increase the median concentrations leaving the city. Daily loads and yields of E. coli and MST markers were used to rank the subbasins according to their contribution of each constituent to the river. The ranking methodology used in this study may prove useful in prioritizing remediation in the different subbasins.
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Center","active":true,"usgs":true}],"preferred":true,"id":697453,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stelzer, Erin A. 0000-0001-7645-7603 eastelzer@usgs.gov","orcid":"https://orcid.org/0000-0001-7645-7603","contributorId":1933,"corporation":false,"usgs":true,"family":"Stelzer","given":"Erin","email":"eastelzer@usgs.gov","middleInitial":"A.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true},{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"preferred":true,"id":697454,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70189149,"text":"70189149 - 2017 - Paleoseismic potential of sublacustrine landslide records in a high-seismicity setting (south-central Alaska)","interactions":[],"lastModifiedDate":"2023-11-08T15:51:27.424228","indexId":"70189149","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2667,"text":"Marine Geology","active":true,"publicationSubtype":{"id":10}},"title":"Paleoseismic potential of sublacustrine landslide records in a high-seismicity setting (south-central Alaska)","docAbstract":"Sublacustrine landslide stratigraphy is considered useful for quantitative paleoseismology in low-seismicity settings. However, as the recharging of underwater slopes with sediments is one of the factors that governs the recurrence of slope failures, it is not clear if landslide deposits can provide continuous paleoseismic records in settings of frequent strong shaking. To test this, we selected three lakes in south-central Alaska that experienced a strong historical megathrust earthquake (the 1964 Mw9.2 Great Alaska Earthquake) and exhibit high sedimentation rates in their main basins (0.2 cm yr− 1–1.0 cm yr− 1). We present high-resolution reflection seismic data (3.5 kHz) and radionuclide data from sediment cores in order to investigate factors that control the establishment of a reliable landslide record. Seismic stratigraphy analysis reveals the presence of several landslide deposits in the lacustrine sedimentary infill. Most of these landslide deposits can be attributed to specific landslide events, as multiple landslide deposits sourced from different lacustrine slopes occur on a single stratigraphic horizon. We identify numerous events in the lakes: Eklutna Lake proximal basin (14 events), Eklutna Lake distal basin (8 events), Skilak Lake (7 events) and Kenai Lake (7 events). The most recent event in each basin corresponds to the historic 1964 megathrust earthquake. All events are characterized by multiple landslide deposits, which hints at a regional trigger mechanism, such as an earthquake (the synchronicity criterion). This means that the landslide record in each basin represents a record of past seismic events. Based on extrapolation of sedimentation rates derived from radionuclide dating, we roughly estimate a mean recurrence interval in the Eklutna Lake proximal basin, Eklutna Lake distal basin, Skilak Lake and Kenai Lake, at ~ 250 yrs., ~ 450 yrs., ~ 900 yrs. and ~ 450 yrs., respectively. This distinct difference in recording can be explained by variations in preconditioning factors like slope angle, slope recharging (sedimentation rate) and the sediment source area: faster slope recharging and a predominance of delta and alluvial fan failures, increase the sensitivity and lower the intensity threshold for slope instability. Also, the seismotectonic setting of the lakes has to be taken into account. This study demonstrates that sublacustrine landslides in several Alaskan lakes can be used as reliable recorders of strong earthquake shaking, when a multi-lake approach is used, and can enhance the temporal and spatial resolution of the paleoseismic record of south-central Alaska.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.margeo.2016.05.004","usgsCitation":"Praet, N., Moernaut, J., Van Daele, M., Boes, E., Haeussler, P.J., Strupler, M., Schmidt, S., Loso, M.G., and De Batist, M., 2017, Paleoseismic potential of sublacustrine landslide records in a high-seismicity setting (south-central Alaska): Marine Geology, v. 384, p. 103-119, https://doi.org/10.1016/j.margeo.2016.05.004.","productDescription":"17 p.","startPage":"103","endPage":"119","ipdsId":"IP-073802","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":489654,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9GK6YZG","text":"USGS data release","linkHelpText":"Gridded Data from Multibeam Bathymetric Surveys of Eklutna, Kenai, and Skilak Lakes, Alaska"},{"id":470106,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.margeo.2016.05.004","text":"Publisher Index Page"},{"id":343261,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Kenai Peninsula","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -153.5009765625,\n 59.108308258604964\n ],\n [\n -147.48046875,\n 59.108308258604964\n ],\n [\n -147.48046875,\n 61.37567331572747\n ],\n [\n -153.5009765625,\n 61.37567331572747\n ],\n [\n -153.5009765625,\n 59.108308258604964\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"384","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"595b5797e4b0d1f9f0536db1","contributors":{"authors":[{"text":"Praet, Nore","contributorId":194083,"corporation":false,"usgs":false,"family":"Praet","given":"Nore","email":"","affiliations":[],"preferred":false,"id":703165,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moernaut, Jasper","contributorId":194084,"corporation":false,"usgs":false,"family":"Moernaut","given":"Jasper","email":"","affiliations":[],"preferred":false,"id":703166,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Van Daele, Maarten 0000-0002-8530-4438","orcid":"https://orcid.org/0000-0002-8530-4438","contributorId":194085,"corporation":false,"usgs":false,"family":"Van Daele","given":"Maarten","email":"","affiliations":[{"id":27279,"text":"Department of Geology and Soil Science, Ghent University, Ghent, Belgium","active":true,"usgs":false}],"preferred":false,"id":703167,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Boes, Evelien","contributorId":194086,"corporation":false,"usgs":false,"family":"Boes","given":"Evelien","email":"","affiliations":[],"preferred":false,"id":703168,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Haeussler, Peter J. 0000-0002-1503-6247 pheuslr@usgs.gov","orcid":"https://orcid.org/0000-0002-1503-6247","contributorId":503,"corporation":false,"usgs":true,"family":"Haeussler","given":"Peter","email":"pheuslr@usgs.gov","middleInitial":"J.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":703164,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Strupler, Michael","contributorId":194087,"corporation":false,"usgs":false,"family":"Strupler","given":"Michael","email":"","affiliations":[],"preferred":false,"id":703169,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Schmidt, Sabine","contributorId":194088,"corporation":false,"usgs":false,"family":"Schmidt","given":"Sabine","email":"","affiliations":[],"preferred":false,"id":703170,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Loso, Michael G.","contributorId":146361,"corporation":false,"usgs":false,"family":"Loso","given":"Michael","email":"","middleInitial":"G.","affiliations":[{"id":12915,"text":"Alaska Pacific University","active":true,"usgs":false}],"preferred":false,"id":703171,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"De Batist, Marc 0000-0002-1625-2080","orcid":"https://orcid.org/0000-0002-1625-2080","contributorId":194089,"corporation":false,"usgs":false,"family":"De Batist","given":"Marc","email":"","affiliations":[],"preferred":false,"id":703172,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70188345,"text":"70188345 - 2017 - Ground motion in the presence of complex Topography II: Earthquake sources and 3D simulations","interactions":[],"lastModifiedDate":"2017-06-06T16:13:07","indexId":"70188345","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Ground motion in the presence of complex Topography II: Earthquake sources and 3D simulations","docAbstract":"Eight seismic stations were placed in a linear array with a topographic relief of 222 m over Mission Peak in the east San Francisco Bay region for a period of one year to study topographic effects. Seventy‐two well‐recorded local earthquakes are used to calculate spectral amplitude ratios relative to a reference site. A well‐defined fundamental resonance peak is observed with individual station amplitudes following the theoretically predicted progression of larger amplitudes in the upslope direction. Favored directions of vibration are also seen that are related to the trapping of shear waves within the primary ridge dimensions. Spectral peaks above the fundamental one are also related to topographic effects but follow a more complex pattern. Theoretical predictions using a 3D velocity model and accurate topography reproduce many of the general frequency and time‐domain features of the data. Shifts in spectral frequencies and amplitude differences, however, are related to deficiencies of the model and point out the importance of contributing factors, including the shear‐wave velocity under the topographic feature, near‐surface velocity gradients, and source parameters.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120160159","usgsCitation":"Hartzell, S.H., Ramirez-Guzman, L., Meremonte, M., and Leeds, A.L., 2017, Ground motion in the presence of complex Topography II: Earthquake sources and 3D simulations: Bulletin of the Seismological Society of America, v. 107, no. 1, p. 344-358, https://doi.org/10.1785/0120160159.","productDescription":"15 p.","startPage":"344","endPage":"358","ipdsId":"IP-078909","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":342187,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.05,\n 37.85\n ],\n [\n -121.65,\n 37.85\n ],\n [\n -121.65,\n 37.3\n ],\n [\n -122.05,\n 37.3\n ],\n [\n -122.05,\n 37.85\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"107","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-12-20","publicationStatus":"PW","scienceBaseUri":"5937bf2de4b0f6c2d0d9c75e","contributors":{"authors":[{"text":"Hartzell, Stephen H. 0000-0003-0858-9043 shartzell@usgs.gov","orcid":"https://orcid.org/0000-0003-0858-9043","contributorId":2594,"corporation":false,"usgs":true,"family":"Hartzell","given":"Stephen","email":"shartzell@usgs.gov","middleInitial":"H.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":697336,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ramirez-Guzman, Leonardo","contributorId":175444,"corporation":false,"usgs":false,"family":"Ramirez-Guzman","given":"Leonardo","email":"","affiliations":[],"preferred":false,"id":697337,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Meremonte, Mark","contributorId":192672,"corporation":false,"usgs":false,"family":"Meremonte","given":"Mark","email":"","affiliations":[],"preferred":false,"id":697338,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Leeds, Alena L. 0000-0002-8756-3687 aleeds@usgs.gov","orcid":"https://orcid.org/0000-0002-8756-3687","contributorId":4077,"corporation":false,"usgs":true,"family":"Leeds","given":"Alena","email":"aleeds@usgs.gov","middleInitial":"L.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":697339,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70189348,"text":"70189348 - 2017 - Variability of runoff-based drought conditions in the conterminous United States","interactions":[],"lastModifiedDate":"2017-08-29T09:35:36","indexId":"70189348","displayToPublicDate":"2017-02-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2032,"text":"International Journal of Climatology","active":true,"publicationSubtype":{"id":10}},"title":"Variability of runoff-based drought conditions in the conterminous United States","docAbstract":"In this study, a monthly water-balance model is used to simulate monthly runoff for 2109 hydrologic units (HUs) in the conterminous United States (CONUS) for water-years 1901 through 2014. The monthly runoff time series for each HU were smoothed with a 3-month moving average, and then the 3-month moving-average runoff values were converted to percentiles. For each HU, a drought was considered to occur when the HU runoff percentile dropped to the 20th percentile or lower. A drought was considered to end when the HU runoff percentile exceeded the 20th percentile. After identifying drought events for each HU, the frequency and length of drought events were examined. Results indicated that (1) the longest mean drought lengths occur in the eastern CONUS and parts of the Rocky Mountain region and the northwestern CONUS, (2) the frequency of drought is highest in the southwestern and central CONUS, and lowest in the eastern CONUS, the Rocky Mountain region, and the northwestern CONUS, (3) droughts have occurred during all months of the year and there does not appear to be a seasonal pattern to drought occurrence, (4) the variability of precipitation appears to have been the principal climatic factor determining drought, and (5) for most of the CONUS, drought frequency appears to have decreased during the 1901 through 2014 period.
","language":"English","publisher":"Royal Meteorological Society","doi":"10.1002/joc.4756","usgsCitation":"McCabe, G., Wolock, D.M., and Austin, S.H., 2017, Variability of runoff-based drought conditions in the conterminous United States: International Journal of Climatology, v. 37, no. 2, p. 1014-1021, https://doi.org/10.1002/joc.4756.","productDescription":"8 p.","startPage":"1014","endPage":"1021","ipdsId":"IP-073812","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":343608,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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ShakeCast system is an openly available, near real-time post-earthquake information management system. ShakeCast is widely used by public and private emergency planners and responders, lifeline utility operators and transportation engineers to automatically receive and process ShakeMap products for situational awareness, inspection priority, or damage assessment of their own infrastructure or building portfolios. The success of ShakeCast to date and its broad, critical-user base mandates improved software usability and functionality, including improved engineering-based damage and loss functions. In order to make the software more accessible to novice users—while still utilizing advanced users’ technical and engineering background—we have developed a “ShakeCast Workbook”, a well documented, Excel spreadsheet-based user interface that allows users to input notification and inventory data and export XML files requisite for operating the ShakeCast system. Users will be able to select structure based on a minimum set of user-specified facility (building location, size, height, use, construction age, etc.). “Expert” users will be able to import user-modified structural response properties into facility inventory associated with the HAZUS Advanced Engineering Building Modules (AEBM). The goal of the ShakeCast system is to provide simplified real-time potential impact and inspection metrics (i.e., green, yellow, orange and red priority ratings) to allow users to institute customized earthquake response protocols. Previously, fragilities were approximated using individual ShakeMap intensity measures (IMs, specifically PGA and 0.3 and 1s spectral accelerations) for each facility but we are now performing capacity-spectrum damage state calculations using a more robust characterization of spectral deamnd.We are also developing methods for the direct import of ShakeMap’s multi-period spectra in lieu of the assumed three-domain design spectrum (at 0.3s for constant acceleration; 1s or 3s for constant velocity and constant displacement at very long response periods). As part of ongoing ShakeCast research and development, we will also explore the use of ShakeMap IM uncertainty estimates and evaluate the assumption of employing multiple response spectral damping values rather than the single 5%-damped value currently employed. Developing and incorporating advanced fragility assignments into the ShakeCast Workbook requires related software modifications and database improvements; these enhancements are part of an extensive rewrite of the ShakeCast application.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the 16th World Conference on Earthquake Engineering","largerWorkSubtype":{"id":15,"text":"Monograph"},"conferenceTitle":"16th World Conference on Earthquake Engineering","language":"English","publisher":"16th World Conference on Earthquake Engineering","usgsCitation":"Wald, D.J., Lin, K., Kircher, C.A., Jaiswal, K.S., Luco, N., Turner, L., and Slosky, D., 2017, Development and utilization of USGS ShakeCast for rapid post-earthquake assessment of critical facilities and infrastructure, in Proceedings of the 16th World Conference on Earthquake Engineering.","ipdsId":"IP-080219","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":344164,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":344163,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://usgs.github.io/shakecast/2017_16WCEE.html"}],"publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"597312aae4b0ec1a488718d7","contributors":{"authors":[{"text":"Wald, David J. 0000-0002-1454-4514 wald@usgs.gov","orcid":"https://orcid.org/0000-0002-1454-4514","contributorId":795,"corporation":false,"usgs":true,"family":"Wald","given":"David","email":"wald@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":705900,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lin, Kuo-wan 0000-0002-7520-8151 klin@usgs.gov","orcid":"https://orcid.org/0000-0002-7520-8151","contributorId":1539,"corporation":false,"usgs":true,"family":"Lin","given":"Kuo-wan","email":"klin@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":705904,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kircher, C. A.","contributorId":194952,"corporation":false,"usgs":false,"family":"Kircher","given":"C.","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":705901,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jaiswal, Kishor S. 0000-0002-5803-8007 kjaiswal@usgs.gov","orcid":"https://orcid.org/0000-0002-5803-8007","contributorId":149796,"corporation":false,"usgs":true,"family":"Jaiswal","given":"Kishor","email":"kjaiswal@usgs.gov","middleInitial":"S.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":705905,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"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":705906,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Turner, L.","contributorId":194953,"corporation":false,"usgs":false,"family":"Turner","given":"L.","email":"","affiliations":[],"preferred":false,"id":705902,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Slosky, Daniel 0000-0001-7407-3606 dslosky@usgs.gov","orcid":"https://orcid.org/0000-0001-7407-3606","contributorId":194954,"corporation":false,"usgs":true,"family":"Slosky","given":"Daniel","email":"dslosky@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":705903,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ]}