The Wolf Point quadrangle encompasses approximately 16,084 km2 (6,210 mi2). The northern boundary is the Montana/Saskatchewan (U.S.-Canada) boundary. The quadrangle is in the Northern Plains physiographic province and it includes the Peerless Plateau and Flaxville Plain. The primary river is the Missouri River.
The map units are surficial deposits and materials, not landforms. Deposits that comprise some constructional landforms (for example, ground-moraine deposits, end-moraine deposits, and stagnation-moraine deposits, all composed of till) are distinguished for purposes of reconstruction of glacial history. Surficial deposits and materials are assigned to 23 map units on the basis of genesis, age, lithology or composition, texture or particle size, and other physical, chemical, and engineering characteristics. It is not a map of soils that are recognized in pedology or agronomy. Rather, it is a generalized map of soils recognized in engineering geology, or of substrata or parent materials in which pedologic or agronomic soils are formed. Glaciotectonic (ice-thrust) structures and deposits are mapped separately, represented by a symbol. The surficial deposits are glacial, ice-contact, glaciofluvial, alluvial, lacustrine, eolian, colluvial, and mass-movement deposits.
Till of late Wisconsin age is represented by three map units. Till of Illinoian age also is mapped. Till deposited during pre-Illinoian glaciations is not mapped, but is widespread in the subsurface. Linear ice-molded landforms (primarily drumlins), shown by symbol, indicate directions of ice flow during late Wisconsin and Illinoian glaciations. The Quaternary geologic map of the Wolf Point quadrangle, northeastern Montana and North Dakota, was prepared to provide a database for compilation of a Quaternary geologic map of the Regina 4° × 6° quadrangle, United States and Canada, at scale 1:1,000,000, for the U.S. Geological Survey Quaternary Geologic Atlas of the United States map series. This map was compiled from data from many sources, at several different map scales. That information was generalized and simplified, and then transferred to a base map at 1:250,000 scale to serve as the base for final reduction to 1:1,000,000, the nominal reading scale of maps in the Quaternary Geologic Atlas of the United States map series. This map is the generalized and simplified 1:250,000 scale compilation. Letter symbols for the map units are those used for the same units in the Quaternary Geologic Atlas of the United States map series. The map summarizes new, and selected published and unpublished, geologic information for public use and for use by Federal, State, and local governmental agencies for land use planning, including assessment of natural resources, natural hazards, recreation potential, and land use management. It also is a base from which a variety of maps relating to earth surface processes and Quaternary geologic history can be derived.
Center Director, USGS Geosciences and Environmental Change Science Center
Box 25046, Mail Stop 980
Denver, CO 80225
Sand Hollow Reservoir in Washington County, Utah, was completed in March 2002 and is operated primarily for managed aquifer recharge by the Washington County Water Conservancy District. From 2002 through 2014, diversions of about 216,000 acre-feet from the Virgin River to Sand Hollow Reservoir have allowed the reservoir to remain nearly full since 2006. Groundwater levels in monitoring wells near the reservoir rose through 2006 and have fluctuated more recently because of variations in reservoir stage and nearby pumping from production wells. Between 2004 and 2014, about 29,000 acre-feet of groundwater was withdrawn by these wells for municipal supply. In addition, about 31,000 acre-feet of shallow seepage was captured by French drains adjacent to the North and West Dams and used for municipal supply, irrigation, or returned to the reservoir. From 2002 through 2014, about 127,000 acre-feet of water seeped beneath the reservoir to recharge the underlying Navajo Sandstone aquifer.
Water quality continued to be monitored at various wells in Sand Hollow during 2013–14 to evaluate the timing and location of reservoir recharge as it moved through the aquifer. Changing geochemical conditions at monitoring wells WD 4 and WD 12 indicate rising groundwater levels and mobilization of vadose-zone salts, which could be a precursor to the arrival of reservoir recharge.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161078","collaboration":"Prepared in cooperation with the Washington County Water Conservancy District","usgsCitation":"Marston, T.M., and Heilweil, V.M., 2016, Assessment of managed aquifer recharge at Sand Hollow Reservoir, Washington County, Utah, updated to conditions through 2014: U.S. Geological Survey Open-File Report 2016–1078, 35 p., https://dx.doi.org/10.3133/ofr20161078.","productDescription":"vi, 35 p.","numberOfPages":"46","onlineOnly":"Y","ipdsId":"IP-065917","costCenters":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":328183,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1078/coverthb.jpg"},{"id":328184,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1078/ofr20161078.pdf","text":"Report","size":"2.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1078"}],"country":"United States","state":"Utah","county":"Washington County","otherGeospatial":"Sand Hollow Reservoir","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -113.41289520263672,\n 37.09325224703316\n ],\n [\n -113.41289520263672,\n 37.15087639355426\n ],\n [\n -113.34148406982422,\n 37.15087639355426\n ],\n [\n -113.34148406982422,\n 37.09325224703316\n ],\n [\n -113.41289520263672,\n 37.09325224703316\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Utah Water Science Center
U.S. Geological Survey
2329 Orton Circle
Salt Lake City, Utah 84119
http://ut.water.usgs.gov/
Surface-water supplies are important sources of drinking water for residents in the Triangle area of North Carolina, which is located within the upper Cape Fear and Neuse River Basins. Since 1988, the U.S. Geological Survey and a consortium of local governments have tracked water-quality conditions and trends in several of the area’s water-supply lakes and streams. This report summarizes data collected through this cooperative effort, known as the Triangle Area Water Supply Monitoring Project, during October 2011 through September 2012 (water year 2012) and October 2012 through September 2013 (water year 2013). Major findings for this period include:
Director South Atlantic Water Science Center
U.S. Geological Survey
720 Gracern Road
Columbia, SC 29210
http://www.usgs.gov/water/southatlantic/
Geologic, sediment texture, and physiographic zone maps characterize the sea floor of Vineyard and western Nantucket Sounds, Massachusetts. These maps were derived from interpretations of seismic-reflection profiles, high-resolution bathymetry, acoustic-backscatter intensity, bottom photographs/video, and surficial sediment samples collected within the 494-square-kilometer study area. Interpretations of seismic stratigraphy and mapping of glacial and Holocene marine units provided a foundation on which the surficial maps were created. This mapping is a result of a collaborative effort between the U.S. Geological Survey and the Massachusetts Office of Coastal Zone Management to characterize the surface and subsurface geologic framework offshore of Massachusetts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161119","collaboration":"Prepared in cooperation with the Massachusetts Office of Coastal Zone Management","usgsCitation":"Baldwin, W.E., Foster, D.S., Pendleton, E.A., Barnhardt, W.A., Schwab, W.C., Andrews, B.D., and Ackerman, S.D., 2016, Shallow geology, sea-floor texture, and physiographic zones of Vineyard and western Nantucket Sounds, Massachusetts: U.S. Geological Survey Open-File Report 2016–1119, https://dx.doi.org/10.3133/ofr20161119.","productDescription":"HTML Document","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-072016","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":328161,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1119/coverthb.jpg"},{"id":326826,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2016/1119/index.html","text":"Report HTML"}],"country":"United States","state":"Massachusetts","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -71.1,\n 41.25\n ],\n [\n -71.1,\n 41.6\n ],\n [\n -70.4,\n 41.6\n ],\n [\n -70.4,\n 41.25\n ],\n [\n -71.1,\n 41.25\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Woods Hole Coastal and Marine Science Center
U.S. Geological Survey
384 Woods Hole Road
Quissett Campus
Woods Hole, MA 02543
http://woodshole.er.usgs.gov/
The vertical avoidance behavior of the tadpole madtom (Noturus gyrinus) exposed to environmentally relevant concentrations of the granular formulation of the lampricide Bayluscide® was evaluated. The lampricide formulation (3.2 percent active ingredient coated on a sand granule) is used to control larval sea lamprey populations in the Great Lakes. The tadpole madtom was chosen as a surrogate to the federally endangered northern madtom (Noturus stigmosus) based on similar life history characteristics and habitat requirements. Vertical avoidance of tadpole madtoms in response to the granular formulation was documented in clear Plexiglas columns (107 centimeters in height, 30.5 centimeters in diameter) for 1 hour after chemical application. Each avoidance trial produced data consisting of the number of tadpole madtoms avoiding the chemical at a given time. Based on the overall data, tadpole madtoms in treated columns were 11.7 times more likely to display avoidance compared to those in untreated controls. Results indicate that it is likely that northern madtoms will be able to detect and avoid Bayluscide® from granular applications if their response is similar to that of the tadpole madtom.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161130","usgsCitation":"Boogaard, M.A., Erickson, R.A., and Hubert, T.D, 2016, Evaluation of avoidance behavior of tadpole madtoms (Noturus gyrinus) as a surrogate for the endangered northern madtom (Noturus stigmosus) in response to granular Bayluscide: U.S. Geological Survey Open-File Report 2016‒1130, 6 p., https://dx.doi.org/10.3133/ofr20161130. ","productDescription":"Report: iv, 6 p. ","startPage":"1","endPage":"6","numberOfPages":"12","onlineOnly":"Y","ipdsId":"IP-075622","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":438554,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7K35RS7","text":"USGS data release","linkHelpText":"Evaluation of avoidance behavior of tadpole madtoms (Noturus gyrinus) as a surrogate to the endangered northern madtom (Noturus stigmosus) in response to granular Bayluscide®"},{"id":326363,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1130/coverthb.jpg"},{"id":326364,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1130/ofr20161130.pdf","text":"Report","size":"509 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1130"}],"country":"United States","otherGeospatial":"Great Lakes ","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.935546875,\n 46.49839225859763\n ],\n [\n -82.880859375,\n 46.49839225859763\n ],\n [\n -81.82617187499999,\n 46.31658418182218\n ],\n [\n -80.2001953125,\n 46.07323062540838\n ],\n [\n -79.8046875,\n 45.55252525134013\n ],\n [\n -79.453125,\n 45.089035564831036\n ],\n [\n -79.8046875,\n 44.62175409623324\n ],\n [\n -80.5078125,\n 44.402391829093915\n ],\n [\n -81.03515625,\n 44.59046718130883\n ],\n [\n -81.4306640625,\n 44.18220395771566\n ],\n [\n -81.650390625,\n 43.73935207915473\n ],\n [\n -81.6943359375,\n 43.13306116240612\n ],\n [\n -82.08984375,\n 42.87596410238254\n ],\n [\n -82.2216796875,\n 42.68243539838623\n ],\n [\n -81.2548828125,\n 42.87596410238254\n ],\n [\n -80.5517578125,\n 42.84375132629021\n ],\n [\n -80.068359375,\n 43.197167282501276\n ],\n [\n -79.716796875,\n 43.67581809328344\n ],\n [\n -79.1455078125,\n 43.866218006556394\n ],\n [\n -77.87109375,\n 44.08758502824518\n ],\n [\n -77.2998046875,\n 44.05601169578525\n ],\n [\n -76.9482421875,\n 44.308126684886126\n ],\n [\n -75.9814453125,\n 44.308126684886126\n ],\n [\n -75.7177734375,\n 43.929549935614595\n ],\n [\n -76.5087890625,\n 43.32517767999296\n ],\n [\n -77.51953125,\n 43.068887774169625\n ],\n [\n -78.92578124999999,\n 43.13306116240612\n ],\n [\n -78.75,\n 42.65012181368025\n ],\n [\n -79.40917968749999,\n 42.09822241118974\n ],\n [\n -81.03515625,\n 41.672911819602085\n ],\n [\n -81.8701171875,\n 41.3108238809182\n ],\n [\n -82.8369140625,\n 41.37680856570233\n ],\n [\n -83.4521484375,\n 41.57436130598913\n ],\n [\n -83.4521484375,\n 42.22851735620852\n ],\n [\n -82.6611328125,\n 42.90816007196054\n ],\n [\n -82.7490234375,\n 43.67581809328344\n ],\n [\n -83.0126953125,\n 43.8028187190472\n ],\n [\n -83.671875,\n 43.58039085560786\n ],\n [\n -84.111328125,\n 43.83452678223684\n ],\n [\n -83.75976562499999,\n 44.33956524809713\n ],\n [\n -83.5400390625,\n 44.84029065139799\n ],\n [\n -83.84765625,\n 45.24395342262324\n ],\n [\n -84.462890625,\n 45.521743896993634\n ],\n [\n -84.9462890625,\n 45.36758436884978\n ],\n [\n -85.95703125,\n 44.5278427984555\n ],\n [\n -86.17675781249999,\n 44.02442151965934\n ],\n [\n -86.17675781249999,\n 43.51668853502909\n ],\n [\n -85.9130859375,\n 42.84375132629021\n ],\n [\n -85.9130859375,\n 41.96765920367816\n ],\n [\n -86.4404296875,\n 41.64007838467894\n ],\n [\n -87.3193359375,\n 41.37680856570233\n ],\n [\n -88.06640625,\n 41.64007838467894\n ],\n [\n -88.06640625,\n 42.45588764197166\n ],\n [\n -88.11035156249999,\n 43.42100882994726\n ],\n [\n -88.11035156249999,\n 43.89789239125797\n ],\n [\n -88.41796875,\n 43.67581809328344\n ],\n [\n -88.76953125,\n 44.24519901522129\n ],\n [\n -88.2861328125,\n 45.089035564831036\n ],\n [\n -87.802734375,\n 45.55252525134013\n ],\n [\n -87.275390625,\n 46.042735653846506\n ],\n [\n -86.572265625,\n 46.31658418182218\n ],\n [\n -86.17675781249999,\n 46.31658418182218\n ],\n [\n -85.4296875,\n 46.34692761055676\n ],\n [\n -85.078125,\n 46.46813299215554\n ],\n [\n -83.935546875,\n 46.49839225859763\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Upper Midwest Environmental Sciences Center
U.S. Geological Survey
2630 Fanta Reed Road
La Crosse, WI 54603
http://www.umesc.usgs.gov/
Inland bathymetry survey collections, survey data types, features, sources, availability, and the effort required to integrate inland bathymetric data into the U.S. Geological Survey 3D Elevation Program are assessed to help determine the feasibility of integrating three-dimensional water feature elevation data into The National Map. Available data from wading, acoustic, light detection and ranging, and combined technique surveys are provided by the U.S. Geological Survey, National Oceanic and Atmospheric Administration, U.S. Army Corps of Engineers, and other sources. Inland bathymetric data accessed through Web-hosted resources or contacts provide useful baseline parameters for evaluating survey types and techniques used for collection and processing, and serve as a basis for comparing survey methods and the quality of results. Historically, boat-mounted acoustic surveys have provided most inland bathymetry data. Light detection and ranging techniques that are beneficial in areas hard to reach by boat, that can collect dense data in shallow water to provide comprehensive coverage, and that can be cost effective for surveying large areas with good water clarity are becoming more common; however, optimal conditions and techniques for collecting and processing light detection and ranging inland bathymetry surveys are not yet well defined.
Assessment of site condition parameters important for understanding inland bathymetry survey issues and results, and an evaluation of existing inland bathymetry survey coverage are proposed as steps to develop criteria for implementing a useful and successful inland bathymetry survey plan in the 3D Elevation Program. These survey parameters would also serve as input for an inland bathymetry survey data baseline. Integration and interpolation techniques are important factors to consider in developing a robust plan; however, available survey data are usually in a triangulated irregular network format or other format compatible with the 3D Elevation Program so that data can be integrated with a minimal level of effort. Geomorphic site conditions are known to affect the success and accuracy of light detection and ranging and other bathymetric surveys, and a baseline that includes geomorphic data is recommended to help in evaluation of limitations imposed by geomorphology for surveys completed in the variable physiographic provinces across the United States. The geographic distribution for existing surveys identifies regions where inland bathymetry data have been collected and, conversely, where little or no survey data seem to be available to provide hydrologic and hydraulic information. This distribution, in conjunction with local to regional data needs to characterize and monitor river and lake resources, provides another important set of criteria to propose and guide acquisition of new bathymetry data for the 3D Elevation Program. An initial evaluation of needs can be based on the importance of water resources that provide primary water supplies for communities, agriculture, energy, and ecological systems; the importance of flood plain analyses; and projected population growth across the United States.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161126","usgsCitation":"Miller-Corbett, Cynthia, 2016, Evaluating integration of inland bathymetry in the U.S. Geological Survey 3D Elevation Program, 2014: U.S. Geological Survey Open-File Report 2016–1126, 44 p., https://dx.doi.org/10.3133/ofr20161126.\n","productDescription":"vi, 44 p.","numberOfPages":"54","onlineOnly":"Y","ipdsId":"IP-065698","costCenters":[{"id":5047,"text":"NGTOC Denver","active":true,"usgs":true}],"links":[{"id":328148,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1126/coverthb.jpg"},{"id":328149,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1126/ofr20161126.pdf","text":"Report","size":"10.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016–1126"}],"contact":"Director, National Geospatial Technical Operations Center
U.S. Geological Survey
1400 Independence Road
Rolla, MO 65401
A multiyear radiotelemetry evaluation was conducted to monitor adult steelhead (Oncorhynchus mykiss), Chinook salmon (O. tshawytscha), and coho salmon (O. kisutch) behavior and movement patterns in the upper Cowlitz River Basin. Volitional passage to this area was eliminated by dam construction in the mid-1960s, and a reintroduction program began in the mid-1990s. Fish are transported around the dams using a trap-and-haul program, and adult release sites are located in Lake Scanewa, the uppermost reservoir in the system, and in the Cowlitz and Cispus Rivers. Our goal was to estimate the proportion of tagged fish that fell back downstream of Cowlitz Falls Dam before the spawning period and to determine the proportion that were present in the Cowlitz and Cispus Rivers during the spawning period. Fallback is important because Cowlitz Falls Dam does not have upstream fish passage, so fish that pass the dam are unable to move back upstream and spawn. A total of 2,051 steelhead and salmon were tagged for the study, which was conducted during 2005–09 and 2012, and 173 (8.4 percent) of these regurgitated their transmitter prior to, or shortly after release. Once these fish were removed from the dataset, the final number of fish that was monitored totaled 1,878 fish, including 647 steelhead, 770 Chinook salmon, and 461 coho salmon.
Hatchery-origin (HOR) and natural-origin (NOR) steelhead, Chinook salmon, and coho salmon behaved differently following release into Lake Scanewa. Detection records showed that the percentage of HOR fish that moved upstream and entered the Cowlitz River or Cispus River after release was relatively low (steelhead = 38 percent; Chinook salmon = 67 percent; coho salmon = 41 percent) compared to NOR fish (steelhead = 84 percent; Chinook salmon = 82 percent; coho salmon = 76 percent). The elapsed time from release to river entry was significantly lower for NOR fish than for HOR fish for all three species. Tagged fish entered the Cowlitz River in greater proportions than the Cispus River, regardless of origin. We found that 23–47 percent of the HOR fish entered the Cowlitz River and 12–38 percent entered the Cispus River. Similarly, 67–70 percent of the NOR fish entered the Cowlitz River and 38–66 percent entered the Cispus River. These behavioral differences translated into similar differences in fates during the spawning periods as higher percentages of tagged fish were assigned Cowlitz River fates than Cispus River fates.
Fallback rates were affected by fish origin and release site. Overall, 12 percent of steelhead, 19 percent of Chinook salmon, and 8 percent of coho salmon fell back downstream of Cowlitz Falls Dam prior to spawning. Fallback rates were lower for fish that were released in the Cowlitz River or the Cispus River than for reservoir-released fish, but statistical comparisons were not robust because of small sample sizes at the river release sites. Fallback rates for fish released at the river release sites were 10 percent lower for steelhead, 4 percent lower for Chinook salmon, and 9 percent lower for coho salmon than for reservoir-released fish. However, fallback rates also were different between HOR and NOR fish. Fallback rates were significantly higher for HOR reservoir-released fish than for NOR reservoir-released fish.
This study provided data that were insightful for understanding behavior and movement patterns in the upper Cowlitz River Basin and yielded estimates of fallback rates and fish fates that may be useful for fishery managers in the years to come. Studies from other systems have shown that factors such as prespawn mortality and fallback have resulted in substantial losses to spawning populations where trap-and-haul programs are being used as a restoration tool. Future research in the upper Cowlitz River Basin may use additional telemetry studies, genetic analyses, and spawning ground surveys to provide answers for new questions and to continue to monitor the progress of the reintroduction effort.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161144","collaboration":"Prepared in cooperation with the Public Utility District Number 1 of Lewis County, Washington, and the Washington Department of Fish and Wildlife","usgsCitation":"Kock, T.J., Ekstrom, B.K., Liedtke, T.L., Serl, J.D., and Kohn, Mike, 2016, Behavior patterns and fates of adult steelhead, Chinook salmon, and coho salmon released into the upper Cowlitz River Basin, 2005–09 and 2012, Washington: U.S. Geological Survey Open-File Report 2016-1144, 36 p., https://dx.doi.org/10.3133/ofr20161144.","productDescription":"vi, 36 p.","numberOfPages":"46","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-077163","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":327910,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1144/ofr20161144.pdf"},{"id":327909,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1144/coverthb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Upper Cowlitz River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.12677001953124,\n 46.41655893628349\n ],\n [\n -122.12677001953124,\n 46.59661864884465\n ],\n [\n -121.69418334960939,\n 46.59661864884465\n ],\n [\n -121.69418334960939,\n 46.41655893628349\n ],\n [\n -122.12677001953124,\n 46.41655893628349\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115
http://wfrc.usgs.gov/
Centimeter-scale ground-surface deformation was produced by the August 23, 2011, magnitude (M) 5.8 earthquake that occurred in Mineral, Virginia. Ground-surface deformation also resulted from the earthquake aftershock sequence. This deformation occurred along a linear northeast-trend near Pendleton, Virginia. It is approximately 10 kilometers (km) northeast of the M5.8 epicenter and near the northeastern periphery of the epicentral area as defined by aftershocks. The ground-surface deformation extends over a distance of approximately 1.4 km and consists of parallel, small-scale (a few centimeters (cm) in amplitude) linear ridges and swales. Individual ridge and swale features are discontinuous and vary in length across a zone that ranges from about 20 meters (m) to less than 5 m in width. At one location, three fence posts and adjoining rails were vertically misaligned. Approximately 5 cm of uplift on one post provides a maximum estimate of vertical change from pre-earthquake conditions along the ridge and swale features. There was no change in the alignment of fence posts, indicating that deformation was entirely vertical. A broad monoclinal flexure with approximately 1 m of relief was identified by transit survey across surface deformation at the Carter farm site. There, surface deformation overlies the Carter farm fault, which is a zone of brittle faulting and fracturing along quartz veins, striking N40°E and dipping approximately 75°SE. Brecciation and shearing along this fault is interpreted as Quaternary in age because it disrupts the modern B-soil horizon. However, deformation is confined to saprolitized schist of the Ordovician Quantico Formation and the lowermost portion of overlying residuum, and is absent in the uppermost residuum and colluvial layer at the ground surface. Because there is a lack of surface shearing and very low relief, landslide processes were not a causative mechanism for the surface deformation. Two possible tectonic models and one non-tectonic model are considered: (1) tectonic, monoclinal flexuring along the Carter farm fault, probably aseismic, (2) tectonic, monoclinal flexuring related to a shallow (1–3 km) cluster of aftershocks (M2 to M3) that occurred approximately 1 to 1.5 km to the east of Carter farm, and (3) non-tectonic, differential response to seismic shaking between more-rigid quartz veins and soft residuum-saprolite under vertical motions that were created by Rayleigh surface waves radiating away from the August 23, 2011, hypocenter and propagating along strike of the Carter farm fault. These processes are not considered mutually exclusive, and all three support brittle deformation on the Carter farm fault during the Quaternary. In addition, abandoned stream valleys and active stream piracy are consistent with long-term uplift in vicinity of the Carter farm fault.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161134","usgsCitation":"Harrison, R.W., Schindler, J.S., Pavich, M.J., Horton, J.W., Jr., and Carter, M.W., 2016, Centimeter-scale surface deformation caused by the 2011 Mineral, Virginia, earthquake sequence at the Carter farm site—Subsidiary structures with a Quaternary history: U.S. Geological Survey Open-File Report 2016–1134, 18 p., https://dx.doi.org/10.3133/ofr20161134.","productDescription":"iv, 18 p.","onlineOnly":"Y","ipdsId":"IP-055730","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":327108,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1134/coverthb1.jpg"},{"id":327109,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1134/ofr20161134.pdf","text":"Report","size":"31.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1134"}],"country":"United States","state":"Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.970278,\n 38.008333\n ],\n [\n -77.970278,\n 37.941667\n ],\n [\n -77.814444,\n 37.941667\n ],\n [\n -77.814444,\n 38.008333\n ],\n [\n -77.970278,\n 38.008333\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Eastern Geology and Paleoclimate Science Center
U.S. Geological Survey
926A National Center
12201 Sunrise Valley Drive
Reston, VA 20192
http://geology.er.usgs.gov/egpsc/
The U.S. Geological Survey, in cooperation with the Fargo Diversion Board of Authority, collected water-surface elevations during a range of discharges needed for calibration of hydrologic and hydraulic models for specific reaches of interest in water years 2014–15. These water-surface elevation and discharge measurement data were collected for design planning of diversion structures on the Red River of the North and Wild Rice River and the aqueduct/diversion structures on the Sheyenne and Maple Rivers. The Red River of the North and Sheyenne River reaches were surveyed six times, and discharges ranged from 276 to 6,540 cubic feet per second and from 166 to 2,040 cubic feet per second, respectively. The Wild Rice River reach also was surveyed six times during 2014 and 2015, and discharges ranged from 13 to 1,550 cubic feet per second. The Maple River reach was surveyed four times, and discharges ranged from 16.4 to 633 cubic feet per second. Water-surface elevation differences from upstream to downstream in the reaches ranged from 0.33 feet in the Red River of the North reach to 9.4 feet in the Maple River reach.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161139","collaboration":"Prepared in cooperation with the Fargo Diversion Board of Authority","usgsCitation":"Damschen, W.C., and Galloway, J.M., 2016, Water-surface elevation and discharge measurement data for the Red River of the North and its tributaries near Fargo, North Dakota, water years 2014–15: U.S. Geological Survey Open-File Report 2016–1139, 16 p., https://dx.doi.org/10.3133/ofr20161139.","productDescription":"iv, 16 p.","numberOfPages":"24","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-074364","costCenters":[{"id":478,"text":"North Dakota Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":327822,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1139/coverthb.jpg"},{"id":327823,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1139/ofr20161139.pdf","text":"Report","size":"1.74 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016–1139"}],"country":"United States","state":"North Dakota","city":"Fargo","otherGeospatial":"Maple River, Red River of the North, Sheyenne River, Wild Rice River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97,\n 46.6667\n ],\n [\n -97,\n 47.10378387099161\n ],\n [\n -96.6667,\n 47.10378387099161\n ],\n [\n -96.6667,\n 46.6667\n ],\n [\n -97,\n 46.6667\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, North Dakota Water Science Center
U.S. Geological Survey
821 E Interstate Ave
Bismarck, ND 58503
In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within the 3-nautical-mile limit of California’s State Waters. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath bathymetry data, acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow subsurface geology.
The Offshore of Monterey map area in central California is located on the Pacific Coast, about 120 km south of San Francisco. Incorporated cities in the map area include Seaside, Monterey, Marina, Pacific Grove, Carmel-by-the-Sea, and Sand City. The local economy receives significant resources from tourism, as well as from the Federal Government. Tourist attractions include the Monterey Bay Aquarium, Cannery Row, Fisherman’s Wharf, and the many golf courses near Pebble Beach, and the area serves as a gateway to the spectacular scenery and outdoor activities along the Big Sur coast to the south. Federal facilities include the Army’s Defense Language Institute, the Naval Postgraduate School, and the Fleet Numerical Meteorology and Oceanography Center (operated by the Navy). In 1994, Fort Ord army base, located between Seaside and Marina, was closed; much of former army base land now makes up the Fort Ord National Monument, managed by the U.S. Bureau of Land Management as part of the National Landscape Conservation System. In addition, part of the old Fort Ord is now occupied by California State University, Monterey Bay.
The offshore part of the map area lies entirely within the Monterey Bay National Marine Sanctuary, one of the nation’s largest marine sanctuaries. State beaches and parks within the map area include Fort Ord Dunes State Park and the Marina, Monterey, and Asilomar State Beaches, as well as Carmel River State Beach, which includes the Carmel River Lagoon and Wetland Natural Preserve. The map area also includes all or part of several State Marine Protected Areas, including the Carmel Pinnacles, Asilomar, and Lovers Point–Julia Platt State Marine Reserves, as well as the Carmel Bay, Pacific Grove Marine Gardens, Edward F. Ricketts, and Portuguese Ledge State Marine Conservation Areas.
The coastal zone in the map area is characterized by two distinct physiographies. From Marina to Monterey, sandy beaches are backed by a belt of sand dunes, as much as 30 to 40 m high and as wide as 8 km. The Salinas River supplies the sand for the beaches and dunes. Nearshore sediment transport is primarily to the south, in the southern Monterey littoral cell.
Along the Monterey peninsula, which lies at the north end of the rugged Santa Lucia Range, coastal relief is very different. The peninsula is characterized largely by low marine terraces that formed mostly on hard and relatively stable granitic bedrock. Carmel Beach in Carmel-by-the-Sea is the longest continuous beach in this area; bedrock points and small pocket beaches characterize most of the rest of the peninsula. The Carmel River littoral cell extends along the coast from Point Pinos to Point Lobos (just south of the map area), including Carmel Beach; sediment transport is primarily to the south.
The granitic rocks that crop out so prominently along the Monterey peninsula make up part of the Salinian block, a crustal terrane that in this area lies west of the San Andreas Fault and east of the San Gregorio Fault. The strike-slip San Andreas Fault Zone, which lies just 26 km east of the map area, is the most important structure within the Pacific–North American transform plate boundary. The San Gregorio Fault, a secondary fault within the distributed plate boundary, cuts through (and is roughly aligned with) Carmel Canyon, a submarine canyon in the southwest corner of the map area that is part of the Monterey Canyon system. The San Gregorio Fault Zone is part of a fault system that is present predominantly in the offshore for about 400 km, from Point Conception in the south (where it is known as the Hosgri Fault) to Bolinas and Point Reyes in the north.
The offshore part of the map area primarily consists of relatively flat continental shelf, bounded on the west by the steep flanks of Carmel Canyon. Shelf width varies from 2 to 3 km in the southern part of the map area, near the mouth of Carmel Canyon, to 14 km in Monterey Bay. Bedrock beneath the shelf is overlain in many areas by variable amounts (0 to 16 m) of upper Quaternary shelf and nearshore sediments deposited as sea level fluctuated in the late Pleistocene. “Soft-induration,” unconsolidated sediment is the dominant (about 63 percent) habitat type on the continental shelf, followed by “hard-induration” rock and boulders (about 34 percent) and “mixed-induration” substrate (about 3 percent). At water depths of about 100 to 130 m, the shelf break approximates the shoreline during the sea-level lowstand of the Last Glacial Maximum, about 21,000 years ago.
Carmel Canyon and other parts of the Monterey Canyon system in the map area extend from the shelf break to water depths that reach 1,600 m. Most of the extensive incision of the shelf break and canyon flanks probably occurred during repeated Quaternary sea-level lowstands. The relatively straight floor of Carmel Canyon notably is aligned with the San Gregorio Fault Zone. Mixed hard-soft substrate is the most common (about 51 percent) habitat type in Carmel Canyon; hard bedrock and soft, unconsolidated sediment cover about 40 percent and 9 percent of canyon habitat, respectively.
This part of the central California coast is exposed to large North Pacific swells from the northwest throughout the year. Wave heights range from 2 to 10 m, the larger swells occurring from October to May. During El Niño–Southern Oscillation (ENSO) events, winter storms track farther south than they do in normal (non-ENSO) years, thereby impacting the map area more frequently and with waves of larger heights.
Benthic species observed in the map area are natives of the cold-temperate biogeographic zone that is called either the “Oregonian province” or the “northern California ecoregion.” This biogeographic province is maintained by the long-term stability of the southward-flowing California Current, the eastern limb of the North Pacific subtropical gyre that flows from southern British Columbia to Baja California.
Biological productivity resulting from coastal upwelling supports populations of Sooty Shearwater, Western Gull, Common Murre, Cassin’s Auklet, and many other less populous bird species. An observable recovery of Humpback and Blue Whales has occurred in the area; both species are dependent on coastal upwelling to provide nutrients. The large extent of exposed inner shelf bedrock supports large forests of “bull kelp,” which is well adapted for high-wave-energy environments. The kelp beds are well-known habitat for the population of southern sea otters. Common fish species found in the kelp beds and rocky reefs include lingcod and various species of rockfish and greenling.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161110","usgsCitation":"Johnson, S.Y., Dartnell, P., Hartwell, S.R., Cochrane, G.R., Golden, N.E., Watt, J.T., Davenport, C.W., Kvitek, R.G., Erdey, M.D., Krigsman, L.M., Sliter, R.W., and Maier, K.L. (S.Y. Johnson and S.A. Cochran, eds.), 2016, California State Waters Map Series — Offshore of Monterey, California: U.S. Geological Survey Open-File Report 2016–1110, pamphlet 44 p., 10 sheets, scale 1:24,000, https://dx.doi.org/10.3133/ofr20161110.","productDescription":"Report: iv, 44 p. 10 Sheets: 66.00 x 36.00 or smaller; Dataset; Metadata","numberOfPages":"48","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-072255","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":438573,"rank":23,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F70Z71C8","text":"USGS data release","linkHelpText":"California State Waters Map Series Data Catalog--Offshore of Monterey, California"},{"id":326510,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/ofr20161024","text":"Open-File Report 2016–1024","linkHelpText":"California State Waters Map Series—Offshore of Santa Cruz, California, by Guy R. 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Each GIS data file is listed with a brief description, a small image, and links to the metadata files and the downloadable data files."}],"scale":"24000","country":"United States","state":"California","city":"Monterey","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.0628,\n 36.69\n ],\n [\n -122.0628,\n 36.5319\n ],\n [\n -121.7853,\n 36.5319\n ],\n [\n -121.7853,\n 36.69\n ],\n [\n -122.0628,\n 36.69\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contact Information
Pacific Coastal & Marine Science Center
U.S. Geological Survey
Pacific Science Center
2885 Mission St.
Santa Cruz, CA 95060
http://walrus.wr.usgs.gov/
","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2016-08-18","noUsgsAuthors":false,"publicationDate":"2016-08-18","publicationStatus":"PW","scienceBaseUri":"57b6ce28e4b03fd6b7d919cc","contributors":{"editors":[{"text":"Johnson, Samuel Y. 0000-0001-7972-9977 sjohnson@usgs.gov","orcid":"https://orcid.org/0000-0001-7972-9977","contributorId":2607,"corporation":false,"usgs":true,"family":"Johnson","given":"Samuel","email":"sjohnson@usgs.gov","middleInitial":"Y.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":645522,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Cochran, Susan A. 0000-0002-2442-8787 scochran@usgs.gov","orcid":"https://orcid.org/0000-0002-2442-8787","contributorId":2062,"corporation":false,"usgs":true,"family":"Cochran","given":"Susan A.","email":"scochran@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science 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Center","active":true,"usgs":true}],"preferred":true,"id":640918,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Golden, Nadine E. 0000-0001-6007-6486 ngolden@usgs.gov","orcid":"https://orcid.org/0000-0001-6007-6486","contributorId":138974,"corporation":false,"usgs":true,"family":"Golden","given":"Nadine","email":"ngolden@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":640919,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Watt, Janet 0000-0002-4759-3814 jwatt@usgs.gov","orcid":"https://orcid.org/0000-0002-4759-3814","contributorId":146222,"corporation":false,"usgs":true,"family":"Watt","given":"Janet","email":"jwatt@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":640920,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Davenport, Clifton W.","contributorId":172491,"corporation":false,"usgs":false,"family":"Davenport","given":"Clifton","email":"","middleInitial":"W.","affiliations":[{"id":12640,"text":"California Geological Survey","active":true,"usgs":false}],"preferred":false,"id":640921,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kvitek, Rikk G.","contributorId":44099,"corporation":false,"usgs":true,"family":"Kvitek","given":"Rikk","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":640922,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Erdey, Mercedes D. merdey@usgs.gov","contributorId":5411,"corporation":false,"usgs":true,"family":"Erdey","given":"Mercedes","email":"merdey@usgs.gov","middleInitial":"D.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":640923,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Krigsman, Lisa M.","contributorId":43642,"corporation":false,"usgs":true,"family":"Krigsman","given":"Lisa M.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":640927,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Sliter, Ray W. 0000-0003-0337-3454 rsliter@usgs.gov","orcid":"https://orcid.org/0000-0003-0337-3454","contributorId":1992,"corporation":false,"usgs":true,"family":"Sliter","given":"Ray","email":"rsliter@usgs.gov","middleInitial":"W.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":640928,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Maier, Katherine L.","contributorId":91411,"corporation":false,"usgs":true,"family":"Maier","given":"Katherine L.","affiliations":[],"preferred":false,"id":640924,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70175123,"text":"ofr20161121 - 2016 - U.S. Geological Survey science strategy for highly pathogenic avian influenza in wildlife and the environment (2016–2020)","interactions":[],"lastModifiedDate":"2018-10-11T15:01:32","indexId":"ofr20161121","displayToPublicDate":"2016-08-18T11:00:00","publicationYear":"2016","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":"2016-1121","title":"U.S. Geological Survey science strategy for highly pathogenic avian influenza in wildlife and the environment (2016–2020)","docAbstract":"
Through the Science Strategy for Highly Pathogenic Avian Influenza (HPAI) in Wildlife and the Environment, the USGS will assess avian influenza (AI) dynamics in an ecological context to inform decisions made by resource managers and policymakers from the local to national level. Through collection of unbiased scientific information on the ecology of AI viruses and wildlife hosts in a changing world, the U.S. Geological Survey (USGS) will enhance the development of AI forecasting tools and ensure this information is integrated with a quality decision process for managing HPAI.
The overall goal of this USGS Science Strategy for HPAI in Wildlife and the Environment goes beyond documenting the occurrence and distribution of AI viruses in wild birds. The USGS aims to understand the epidemiological processes and environmental factors that influence HPAI distribution and describe the mechanisms of transmission between wild birds and poultry. USGS scientists developed a conceptual model describing the process linking HPAI dispersal in wild waterfowl to the outbreaks in poultry. This strategy focuses on five long-term science goals, which include:
These goals will help define and describe the processes outlined in the conceptual model with the ultimate goal of facilitating biosecurity and minimizing transfer of diseases across the wildlife-poultry interface. The first four science goals are focused on scientific discovery and the fifth goal is application-based. Decision analyses in the fifth goal will guide prioritization of proposed actions in the first four goals.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161121","usgsCitation":"Harris, M.C., Pearce, J.M., Prosser, D.J., White, C.L., Miles, A.K., Sleeman, J.M., Brand, C.J., Cronin, J.P., De La Cruz, S., Densmore, C.L., Doyle, T.W., Dusek, R.J., Fleskes, J.P., Flint, P.L., Guala, G.F., Hall, J.S., Hubbard, L.E., Hunt, R.J., Ip, H.S., Katz, R.A., Laurent, K.W., Miller, M.P., Munn, M.D., Ramey, A.M., Richards, K.D., Russell, R.E., Stokdyk, J.P., Takekawa, J.Y., and Walsh, D.P., 2016, U.S. Geological Survey science strategy for highly pathogenic avian influenza in wildlife and the environment (2016–2020): U.S. Geological Survey Open-File Report 2016–1121, 38 p., https://dx.doi.org/10.3133/ofr20161121.","productDescription":"v, 38 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-070395","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true},{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true},{"id":37226,"text":"Core Science Analytics, Synthesis, and Libraries","active":true,"usgs":true}],"links":[{"id":326589,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1121/coverthb.jpg"},{"id":326590,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1121/ofr20161121.pdf","text":"Report","size":"4.77 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1121"}],"country":"United States","contact":"Associate Director for Ecosystems
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
https://www2.usgs.gov/ecosystems/
This report provides an overview of the capabilities and design of Hydra, the global seismic monitoring and analysis system used for earthquake response and catalog production at the U.S. Geological Survey National Earthquake Information Center (NEIC). Hydra supports the NEIC’s worldwide earthquake monitoring mission in areas such as seismic event detection, seismic data insertion and storage, seismic data processing and analysis, and seismic data output.
The Hydra system automatically identifies seismic phase arrival times and detects the occurrence of earthquakes in near-real time. The system integrates and inserts parametric and waveform seismic data into discrete events in a database for analysis. Hydra computes seismic event parameters, including locations, multiple magnitudes, moment tensors, and depth estimates. Hydra supports the NEIC’s 24/7 analyst staff with a suite of seismic analysis graphical user interfaces.
In addition to the NEIC’s monitoring needs, the system supports the processing of aftershock and temporary deployment data, and supports the NEIC’s quality assurance procedures. The Hydra system continues to be developed to expand its seismic analysis and monitoring capabilities.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161128","usgsCitation":"Patton, J.M., Guy, M.R., Benz, H.M., Buland, R.P., Erickson, B.K., and Kragness, D.S., 2016, Hydra—The National Earthquake Information Center’s 24/7 seismic monitoring, analysis, catalog production, quality analysis, and special studies tool suite: U.S. Geological Survey Open-File Report 2016–1128, 28 p., https://dx.doi.org/10.3133/ofr20161128. ","productDescription":"vi, 28 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-074998","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":326763,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1128/ofr20161128.pdf","text":"Report","size":"2.76 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1128"},{"id":326762,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1128/coverthb.jpg"}],"contact":"Director, Geologic Hazards Science Center
U.S. Geological Survey
Box 25046, MS 966
Denver, CO 80225-0046
http://geohazards.cr.usgs.gov/
","tableOfContents":"The removal of dams has recently increased over historical levels due to aging infrastructure, changing societal needs, and modern safety standards rendering some dams obsolete. Where possibilities for river restoration, or improved safety, exceed the benefits of retaining a dam, removal is more often being considered as a viable option. Yet, as this is a relatively new development in the history of river management, science is just beginning to guide our understanding of the physical and ecological implications of dam removal. Ultimately, the “lessons learned” from previous scientific studies on the outcomes dam removal could inform future scientific understanding of ecosystem outcomes, as well as aid in decision-making by stakeholders. We created a database visualization tool, the Dam Removal Information Portal (DRIP), to display map-based, interactive information about the scientific studies associated with dam removals. Serving both as a bibliographic source as well as a link to other existing databases like the National Hydrography Dataset, the derived National Dam Removal Science Database serves as the foundation for a Web-based application that synthesizes the existing scientific studies associated with dam removals. Thus, using the DRIP application, users can explore information about completed dam removal projects (for example, their location, height, and date removed), as well as discover sources and details of associated of scientific studies. As such, DRIP is intended to be a dynamic collection of scientific information related to dams that have been removed in the United States and elsewhere. This report describes the architecture and concepts of this “metaknowledge” database and the DRIP visualization tool.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161132","usgsCitation":"Duda, J.J., Wieferich, D.J., Bristol, R.S., Bellmore, J.R., Hutchison, V.B., Vittum, K.M., Craig, Laura, and Warrick, J.A., 2016, Dam Removal Information Portal (DRIP)—A map-based resource linking scientific studies and associated geospatial information about dam removals: U.S. Geological Survey Open-File Report 2016-1132, 14 p., https://dx.doi.org/10.3133/ofr20161132.","productDescription":"iv, 14 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-076705","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true},{"id":37226,"text":"Core Science Analytics, Synthesis, and Libraries","active":true,"usgs":true}],"links":[{"id":326867,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1132/coverthb.jpg"},{"id":326868,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1132/ofr20161132.pdf","text":"Report","size":"441 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1132"}],"contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115
http://wfrc.usgs.gov/
Information about groundwater-flow paths and locations where groundwater discharges at and near Puget Sound Naval Shipyard is necessary for understanding the potential migration of subsurface contaminants by groundwater at the shipyard. The design of some remediation alternatives would be aided by knowledge of whether groundwater flowing at specific locations beneath the shipyard will eventually discharge directly to Sinclair Inlet of Puget Sound, or if it will discharge to the drainage system of one of the six dry docks located in the shipyard. A 1997 numerical (finite difference) groundwater-flow model of the shipyard and surrounding area was constructed to help evaluate the potential for groundwater discharge to Puget Sound. That steady-state, multilayer numerical model with homogeneous hydraulic characteristics indicated that groundwater flowing beneath nearly all of the shipyard discharges to the dry-dock drainage systems, and only shallow groundwater flowing beneath the western end of the shipyard discharges directly to Sinclair Inlet.
Updated information from a 2016 regional groundwater-flow model constructed for the greater Kitsap Peninsula was used to update the 1997 groundwater model of the Puget Sound Naval Shipyard. That information included a new interpretation of the hydrogeologic units underlying the area, as well as improved recharge estimates. Other updates to the 1997 model included finer discretization of the finite-difference model grid into more layers, rows, and columns, all with reduced dimensions. This updated Puget Sound Naval Shipyard model was calibrated to 2001–2005 measured water levels, and hydraulic characteristics of the model layers representing different hydrogeologic units were estimated with the aid of state-of-the-art parameter optimization techniques.
The flow directions and discharge locations predicted by this updated model generally match the 1997 model despite refinements and other changes. In the updated model, most groundwater discharge recharged within the boundaries of the shipyard is to the dry docks; only at the western end of the shipyard does groundwater discharge directly to Puget Sound. Particle tracking for the existing long-term monitoring well network suggests that only a few wells intercept groundwater that originates as recharge within the shipyard boundary.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161135","collaboration":"Prepared in cooperation with the Naval Facilities Engineering Command-Northwest","usgsCitation":"Jones, J.L., Johnson, K.H., and Frans, L.M., 2016, Numerical simulation of groundwater flow at Puget Sound Naval Shipyard, Naval Base Kitsap, Bremerton, Washington: U.S. Geological Survey Open-File Report 2016-1135, 35 p., https://dx.doi.org/10.3133/ofr20161135.","productDescription":"Report:","startPage":"1","endPage":"35","numberOfPages":"44","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-076467","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":438574,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P94FCYGV","text":"USGS data release","linkHelpText":"MODFLOW-NWT model to simulate the groundwater flow system at Puget Sound Naval Shipyard, Naval Base Kitsap, Bremerton, Washington"},{"id":326832,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1135/coverthb.jpg"},{"id":326833,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1135/ofr20161135.pdf","text":"Report","size":"1.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1135"}],"country":"United States","state":"Washington","city":"Bremerton","otherGeospatial":"Puget Sound Naval Shipyard, Naval Base Kitsap,","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.6953125,\n 47.529488341715265\n ],\n [\n -122.67230987548828,\n 47.53899190311993\n ],\n [\n -122.67093658447266,\n 47.54432241518175\n ],\n [\n -122.65960693359374,\n 47.55150616084034\n ],\n [\n -122.6513671875,\n 47.55382328811835\n ],\n [\n -122.63866424560547,\n 47.556603705614094\n ],\n [\n -122.63248443603514,\n 47.5586889219186\n ],\n [\n -122.62390136718749,\n 47.5610057315948\n ],\n [\n -122.62115478515625,\n 47.569808674020344\n ],\n [\n -122.62493133544922,\n 47.575136052077276\n ],\n [\n -122.64038085937499,\n 47.58023129789275\n ],\n [\n -122.64896392822264,\n 47.584168193691696\n ],\n [\n -122.65445709228516,\n 47.58903100916583\n ],\n [\n -122.65926361083984,\n 47.5996813120644\n ],\n [\n -122.66578674316406,\n 47.60384823184624\n ],\n [\n -122.67162322998047,\n 47.604774168947614\n ],\n [\n -122.68054962158202,\n 47.593198777144636\n ],\n [\n -122.68466949462892,\n 47.58301031389572\n ],\n [\n -122.68260955810545,\n 47.5714301073211\n ],\n [\n -122.69359588623047,\n 47.557067094186735\n ],\n [\n -122.70973205566406,\n 47.54663986006874\n ],\n [\n -122.6953125,\n 47.529488341715265\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402
http://wa.water.usgs.gov
Acoustic technologies have the potential to be used as a surrogate for measuring suspended-sediment concentration (SSC). This potential was examined in a fine-grained (97-100 percent fines) riverine system in central Illinois by way of installation of an acoustic instrument. Acoustic data were collected continuously over the span of 5.5 years. Acoustic parameters were regressed against SSC data to determine the accuracy of using acoustic technology as a surrogate for measuring SSC in a fine-grained riverine system. The resulting regressions for SSC and sediment acoustic parameters had coefficients of determination ranging from 0.75 to 0.97 for various events and configurations. The overall Nash-Sutcliffe model-fit efficiency was 0.95 for the 132 observed and predicted SSC values determined using the sediment acoustic parameter regressions. The study of using acoustic technologies as a surrogate for measuring SSC in fine-grained riverine systems is ongoing. The results at this site are promising in the realm of surrogate technology.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161117","collaboration":"Prepared in cooperation with the Illinois Environmental Protection Agency and the Federal Interagency Sedimentation Project","usgsCitation":"Manaster, A.D, Domanski, M.M., Straub, T.D., and Boldt, J.A., 2016, Estimating suspended sediment using acoustics in a fine-grained riverine system on Kickapoo Creek at Bloomington, Illinois: U.S. Geological Survey Open-File Report 2016–1117, 42 p., https://dx.doi.org/10.3133/ofr20161117.","productDescription":"viii, 43 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-074002","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":326412,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1117/coverthb.jpg"},{"id":326413,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1117/ofr20161117.pdf","text":"Report","size":"13.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1117"}],"country":"United States","state":"Illinois","city":"Bloomington","otherGeospatial":"Kickapoo Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.02952575683594,\n 40.57432635193039\n ],\n [\n -90.02952575683594,\n 40.875103022165824\n ],\n [\n -89.6978759765625,\n 40.875103022165824\n ],\n [\n -89.6978759765625,\n 40.57432635193039\n ],\n [\n -90.02952575683594,\n 40.57432635193039\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Illinois Water Science Center
U.S. Geological Survey
405 North Goodwin Avenue
Urbana, IL 61801
http://il.water.usgs.gov
Climate change impacts ecosystems in many ways, from effects on species to phenology to wildfire dynamics. Assessing the potential vulnerability of ecosystems to future changes in climate is an important first step in prioritizing and planning for conservation. Although assessments of climate change vulnerability commonly are done for species, fewer have been done for ecosystems. To aid regional conservation planning efforts, we assessed climate change vulnerability for ecosystems in the Southeastern United States and Caribbean.
First, we solicited input from experts to create a list of candidate ecosystems for assessment. From that list, 12 ecosystems were selected for a vulnerability assessment that was based on a synthesis of available geographic information system (GIS) data and literature related to 3 components of vulnerability—sensitivity, exposure, and adaptive capacity. This literature and data synthesis comprised “Phase I” of the assessment. Sensitivity is the degree to which the species or processes in the ecosystem are affected by climate. Exposure is the likely future change in important climate and sea level variables. Adaptive capacity is the degree to which ecosystems can adjust to changing conditions. Where available, GIS data relevant to each of these components were used. For example, we summarized observed and projected climate, protected areas existing in 2011, projected sea-level rise, and projected urbanization across each ecosystem’s distribution. These summaries were supplemented with information in the literature, and a short narrative assessment was compiled for each ecosystem. We also summarized all information into a qualitative vulnerability rating for each ecosystem.
Next, for 2 of the 12 ecosystems (East Gulf Coastal Plain Near-Coast Pine Flatwoods and Nashville Basin Limestone Glade and Woodland), the NatureServe Habitat Climate Change Vulnerability Index (HCCVI) framework was used as an alternative approach for assessing vulnerability. Use of the HCCVI approach comprised “Phase II” of the assessment. This approach uses summaries of GIS data and models to develop a series of numeric indices for components of vulnerability. We incorporated many of the data sources used in Phase I, but added the results of several other data sources, including climate envelope modeling and vegetation dynamics modeling. The results of Phase II were high and low numeric vulnerability ratings for mid-century and the end of century for each ecosystem. The high and low ratings represented the potential range of vulnerability scores owing to uncertainties in future climate conditions and ecosystem effects.
Of the 12 ecosystems assessed in the first approach, five were rated as having high vulnerability (Caribbean Coastal Mangrove, Caribbean Montane Wet Elfin Forest, East Gulf Coastal Plain Southern Loess Bluff Forest, Edwards Plateau Limestone Shrubland, and Nashville Basin Limestone Glade and Woodland). Six ecosystems had medium vulnerability, and one ecosystem had low vulnerability. For the two ecosystems assessed with both approaches, vulnerability ratings generally agreed. The assessment concluded by comparing the two approaches, identifying critical research needs, and making suggestions for future ecosystem vulnerability assessments in the Southeast and beyond. Research needs include reducing uncertainty in the degree of climate exposure likely in the future, as well as acquiring more information on how climate might affect biotic interactions and hydrologic processes. Ideally, a comprehensive vulnerability assessment would include both the narrative summaries that resulted from the synthesis in Phase I, as well as a numeric index that incorporates uncertainty as in Phase II.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161073","usgsCitation":"Costanza, Jennifer, Beck, Scott, Pyne, Milo, Terando, Adam, Rubino, Matthew, White, Rickie, and Collazo, Jaime, 2016, Assessing climate-sensitive ecosystems in the southeastern United States: U.S. Geological Survey Open-File Report 2016–1073, 278 p., https://dx.doi.org/10.3133/ofr20161073.","productDescription":"v, 278 p.","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-064978","costCenters":[{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true}],"links":[{"id":325860,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/publication/fs20163052","text":"Fact Sheet 2016–3052 -","description":"OFR 2016-1073","linkHelpText":"Ecosystem Vulnerability to Climate Change in the Southeastern United States"},{"id":325861,"rank":4,"type":{"id":7,"text":"Companion 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\"}}]}","contact":"Director, South Atlantic Water Science Center
U.S. Geological Survey
3916 Sunset Ridge Rd
Raleigh, N.C. 27607
http://nc.water.usgs.gov/
Water from the Little Arkansas River is used as source water for artificial recharge of the Equus Beds aquifer, one of the primary water-supply sources for the city of Wichita, Kansas. The U.S. Geological Survey has operated two continuous real-time water-quality monitoring stations since 1995 on the Little Arkansas River in Kansas. Regression models were developed to establish relations between discretely sampled constituent concentrations and continuously measured physical properties to compute concentrations of those constituents of interest. Site-specific regression models were originally published in 2000 for the near Halstead and near Sedgwick U.S. Geological Survey streamgaging stations and the site-specific regression models were then updated in 2003. This report updates those regression models using discrete and continuous data collected during May 1998 through August 2014. In addition to the constituents listed in the 2003 update, new regression models were developed for total organic carbon. The real-time computations of water-quality concentrations and loads are available at http://nrtwq.usgs.gov. The water-quality information in this report is important to the city of Wichita because water-quality information allows for real-time quantification and characterization of chemicals of concern (including chloride), in addition to nutrients, sediment, bacteria, and atrazine transported in the Little Arkansas River. The water-quality information in this report aids in the decision making for water treatment before artificial recharge.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161057","collaboration":"Prepared in cooperation with the city of Wichita, Kansas","usgsCitation":"Rasmussen, P.P., Eslick, P.J., and Ziegler, A.C., 2016, Relations between continuous real-time physical properties and discrete water-quality constituents in the Little Arkansas River, south-central Kansas, 1998-2014: U.S. Geological Survey Open-File Report 2016–1057, 20 p., https://dx.doi.org/10.3133/ofr20161057.","productDescription":"Report: ii, 16 p.; Appendixes 1-2","numberOfPages":"21","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-073013","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":326275,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1057/ofr20161057.pdf","text":"Report","size":"783 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016–1057"},{"id":326274,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1057/coverthb.jpg"},{"id":326280,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2016/1057/ofr20161057_appendix2.pdf","text":"Appendix 2","size":"2.90 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016–1057 Appendix 2"},{"id":326276,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2016/1057/ofr20161057_appendix1.pdf","text":"Appendix 1","size":"2.65 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016–1057 Appendix 1"}],"country":"United States","state":"Kansas","otherGeospatial":"Little Arkansas River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -98.2,\n 37.75\n ],\n [\n -98.2,\n 38.6\n ],\n [\n -97.25,\n 38.6\n ],\n [\n -97.25,\n 37.75\n ],\n [\n -98.2,\n 37.75\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Kansas Water Science Center
U.S. Geological Survey
4821 Quail Crest Place
Lawrence, KS 66049
Dissolved-selenium loading analyses of data collected at 18 water-quality sites in the lower Gunnison River Basin in Colorado were completed through water year (WY) 2014. A WY is defined as October 1–September 30. Selenium is a trace element that bioaccumulates in aquatic food chains and can cause reproductive failure, deformities, and other harmful effects. This report presents information on the dissolved-selenium loads at 18 sites in the lower Gunnison River Basin for WYs 2011–2014. Annual dissolved-selenium loads were calculated at 5 sites with continuous U.S. Geological Survey (USGS) streamflow gages, whereas instantaneous dissolved-selenium loads were calculated for the remaining 13 sites using water-quality samples that had been collected periodically during WYs 2011–2014. Annual dissolved-selenium loads for WY 2014 ranged from 336 pounds (lb) at Uncompahgre River at Colona to 13,300 lb at Gunnison River near Grand Junction (Whitewater). Most sites in the basin had a median instantaneous dissolved-selenium load of less than 20.0 lb per day. In general, dissolved-selenium loads at Gunnison River main-stem sites showed an increase from upstream to downstream.
The State of Colorado water-quality standard for dissolved selenium of 4.6 micrograms per liter (µg/L) was compared to the 85th percentiles for dissolved selenium at selected water-quality sites. Annual 85th percentiles for dissolved selenium were calculated for the five core USGS sites having streamflow gages using estimated dissolved-selenium concentrations from linear regression models. These annual 85th percentiles in WY 2014 ranged from 0.97 µg/L at Uncompahgre River at Colona to 16.7 µg/L at Uncompahgre River at Delta. Uncompahgre River at Delta and Whitewater were the only core sites where water samples exceeded the State of Colorado water-quality standard for dissolved selenium of 4.6 µg/L.
Instantaneous 85th percentiles for dissolved selenium were calculated for sites with sufficient data using water-quality samples collected during WYs 2011–2014. The instantaneous 85th percentiles for samples for WY 2014 ranged from 1.1 µg/L at Uncompahgre River at Colona to 125 µg/L at Loutzenhizer Arroyo at North River Road.
A trend analysis was completed for Whitewater to determine if dissolved-selenium loads are increasing or decreasing. The trend analysis indicates a decrease of 8,000 lb from WY 1986 to WY 2014, a 34.8 percent reduction during the time period, and an additional 6.2 percent reduction from a reported 28.6 percent reduction during WYs 1986–2008. The trend analysis for WY 1992 to WY 2014 indicates a decrease of 5,800 lb per year, or 27.9 percent.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161129","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Henneberg, M.F., 2016, 2014 annual summary of the lower Gunnison River Basin Selenium Management Program water-quality monitoring, Colorado: U.S. Geological Survey Open-File Report 2016–1129, 25 p., https://dx.doi.org/10.3133/ofr20161129. ","productDescription":"iv, 26 p.","numberOfPages":"30","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-076878","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":326308,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1129/ofr20161129.pdf","text":"Report","size":"3.15 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1129"},{"id":326307,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1129/coverthb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Lower Gunnison River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.39935302734375,\n 39.095962936305504\n ],\n [\n -108.270263671875,\n 39.059716474034666\n ],\n [\n -108.160400390625,\n 39.03838632847038\n ],\n [\n -107.99011230468749,\n 39.06824672852526\n ],\n [\n -107.874755859375,\n 39.095962936305504\n ],\n [\n -107.786865234375,\n 39.089567854849314\n ],\n [\n -107.70172119140624,\n 39.0533181067413\n ],\n [\n -107.6055908203125,\n 38.976492485539424\n ],\n [\n -107.6055908203125,\n 38.805470223177466\n ],\n [\n -107.70721435546875,\n 38.62116234642254\n ],\n [\n -107.808837890625,\n 38.43207668538204\n ],\n [\n -107.841796875,\n 38.28131307922969\n ],\n [\n -107.81982421874999,\n 38.048091067457236\n ],\n [\n -107.81982421874999,\n 37.95286091815649\n ],\n [\n -107.92144775390625,\n 37.91820111976663\n ],\n [\n -108.0120849609375,\n 37.91603433975963\n ],\n [\n -108.15216064453125,\n 37.94203148678865\n ],\n [\n -108.26202392578125,\n 38.07404145941957\n ],\n [\n -108.44329833984374,\n 38.47939467327645\n ],\n [\n -108.5723876953125,\n 38.70908932739828\n ],\n [\n -108.6053466796875,\n 38.83542884007303\n ],\n [\n -108.58612060546875,\n 39.04691915968503\n ],\n [\n -108.49822998046875,\n 39.104488809440475\n ],\n [\n -108.39935302734375,\n 39.095962936305504\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,Colorado Water Science Center
U.S. Geological Survey
Box 25046, MS 415
Denver, CO 80225-0046
The Central Platte River Valley provides breeding habitat for a variety of migratory birds, including federally endangered interior least terns (Sternula antillarum; least tern) and threatened piping plovers (Charadrius melodus). Since 2009, researchers have collected demographic data on both species that span their lifecycle (that is, from egg laying through survival of adults). Demographic data were used to estimate vital rates (for example, nest survival, chick survival, and so on) for both species and assess how these vital rates were related to type and age of nesting habitat. Nest survival of both species was unrelated to the age of the site a nest was initiated on. Piping plover chick survival to fledging age was not related to the age of the site it was hatched at, however, the probability of a least tern chick surviving to fledging was higher at older sites. In general there were fewer piping plover nests than least tern nests found at sites created through either the physical construction of a new site or new vegetation management regimes, during 2009–14.
Mean daily least tern nest survival was 0.9742 (95-percent confidence interval [CI]: 0.9692–0.9783) and cumulative nest survival was 0.59 (95-percent CI: 0.53–0.65). Mean daily least tern chick survival was 0.9602 (95-percent CI: 0.9515–0.9673) and cumulative survival to fledging was 0.54 (95-percent CI = 0.48–0.61). Annual apparent survival rates were estimated at 0.42 (95-percent CI = 0.22–0.64) for adult least terns nesting in the Central Platte River Valley and an apparent survival rate of 0.14 (95-pecent CI = 0.04–0.41) for juvenile least terns. The number of least tern nests present at sites created during 2009–14 was associated with the age of the site; more least tern nests were associated with older sites. During 2009–14, there were four (less than 1 percent of all chicks marked) least tern chicks hatched from the Central Platte River Valley that were subsequently captured on nests as adults. Two of these least terns returned to nest at the same site they had hatched from. Ten instances were documented in which an adult least tern could either switch to nest at a new location or remain at the previous location with the onset of a new year. In five (50 percent) of these instances, least terns returned to nest on the site where they had nested in a previous year.
For piping plovers, mean daily apparent nest survival was 0.9880 (95-pecent CI: 0.9836–0.9912) and cumulative nest survival was 0.66 (95-pecent CI: 0.57–0.74). Mean daily piping plover chick survival was 0.9621 (95-pecent CI: 0.9514–0.9706) and cumulative survival to fledging was 0.46 (95-pecent CI = 0.37– 0.56). The annual apparent survival estimate for adult piping plovers nesting in the Central Platte River Valley was 0.76 (95-pecent CI = 0.65–0.85) and was 0.20 (95-pecent CI = 0.14–0.29) for juvenile piping plovers. The number of piping plover nests present at sites created through either the physical construction of a new site or new vegetation management regimes was also associated with site age, with more piping plover nests associated with older sites; however, in general there were fewer piping plover nests found at created sites than least tern nests. Only first-year adult piping plovers were observed on sites in the first year of availability, whereas older sites had a higher proportion of after-first-year adult piping plovers than first-year adult piping plovers. Twelve piping plover chicks (approximately 3 percent of all chicks marked) hatched from the Central Platte River Valley and were subsequently documented on nests as adults. All piping plovers returned to nest on different sites from the one on which they hatched. A total of 45 instances were documented in which an adult plover could either switch to nest at a new location or remain at the previous location with the onset of a new year. In 39 instances (87 percent), the adult nested on the same site as its prior documented nesting attempt and in 6 of these instances the adult switched to a new nesting location between years. There were 13 of 75 uniquely identifiable piping plovers observed to renest (that is, initiate more than one nest in a season) during 2009–14; no renests were observed among uniquely identifiable least terns. In all but one case, piping plover renests were found at the same site as the first nest initiated that season. For birds that renested, the mean initiation date of the first nest was May 6 and the mean initiation date of the second nest was June 8. On average, renests were initiated 7.5 days plus or minus 7.3 (SD [standard deviation]) following the date the initial nesting attempt was ‘fated’ (considered either failed or hatched).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161061","usgsCitation":"Roche, E.A., Sherfy, M.H., Ring, M.M., Shaffer, T.L., Anteau, M.J., and Stucker, J.H., 2016, Demographics and movements of least terns and piping plovers in the Central Platte River Valley, Nebraska: U.S. Geological Survey Open-File Report 2016–1061, 27 p., https://dx.doi.org/10.3133/ofr20161061.","productDescription":"vi, 27 p.","startPage":"1","endPage":"27","numberOfPages":"38","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-066073","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":326293,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1061/ofr20161061.pdf","text":"Report","size":"2.98 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016–1061"},{"id":326292,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1061/coverthb.jpg"}],"country":"United States","state":"Nebraska","otherGeospatial":"Central Platte River Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -99.69680786132812,\n 40.81588791441588\n ],\n [\n -99.78195190429688,\n 40.66813955408042\n ],\n [\n -99.71466064453125,\n 40.63896734381723\n ],\n [\n -99.60617065429688,\n 40.62437645591559\n ],\n [\n -99.49905395507812,\n 40.622291783092706\n ],\n [\n -99.39743041992188,\n 40.629587853312174\n ],\n [\n -99.36309814453125,\n 40.629587853312174\n ],\n [\n -99.283447265625,\n 40.61186744303007\n ],\n [\n -99.217529296875,\n 40.61082491956405\n ],\n [\n -99.07470703125,\n 40.60456943720527\n ],\n [\n -98.95660400390625,\n 40.606654663050485\n ],\n [\n -98.81927490234375,\n 40.614994915836924\n ],\n [\n -98.75198364257811,\n 40.637925243274374\n ],\n [\n -98.6956787109375,\n 40.65355504328842\n ],\n [\n -98.60641479492188,\n 40.67126439151552\n ],\n [\n -98.51852416992186,\n 40.70042247927178\n ],\n [\n -98.44436645507812,\n 40.713955826286046\n ],\n [\n -98.349609375,\n 40.751418432997454\n ],\n [\n -98.3056640625,\n 40.7743018636372\n ],\n [\n -98.2342529296875,\n 40.831475967182925\n ],\n [\n -98.16146850585938,\n 40.898981853950986\n ],\n [\n -98.09005737304688,\n 40.95915977213492\n ],\n [\n -98.00216674804688,\n 40.99959341455489\n ],\n [\n -97.943115234375,\n 41.036894775104436\n ],\n [\n -98.06121826171875,\n 41.12695250600846\n ],\n [\n -98.09692382812499,\n 41.088667173210624\n ],\n [\n -98.16421508789062,\n 41.05243077390835\n ],\n [\n -98.25759887695312,\n 41.01099329360268\n ],\n [\n -98.34686279296874,\n 40.977824533189526\n ],\n [\n -98.37844848632811,\n 40.95189982816191\n ],\n [\n -98.43475341796875,\n 40.90313381465847\n ],\n [\n -98.4814453125,\n 40.861602479810266\n ],\n [\n -98.54461669921875,\n 40.83667117059108\n ],\n [\n -98.63662719726562,\n 40.80861223601287\n ],\n [\n -98.70529174804686,\n 40.78054143186031\n ],\n [\n -98.75885009765625,\n 40.771181859756496\n ],\n [\n -98.84124755859375,\n 40.758700379161034\n ],\n [\n -98.93600463867188,\n 40.74725696280421\n ],\n [\n -99.01702880859374,\n 40.72956780913899\n ],\n [\n -99.11590576171875,\n 40.73268976628568\n ],\n [\n -99.22027587890624,\n 40.73268976628568\n ],\n [\n -99.32327270507812,\n 40.74309523218185\n ],\n [\n -99.40155029296875,\n 40.75245875985305\n ],\n [\n -99.49081420898438,\n 40.75557964275591\n ],\n [\n -99.62677001953125,\n 40.77846164090355\n ],\n [\n -99.69680786132812,\n 40.81588791441588\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Northern Prairie Wildlife Research Center
U.S. Geological Survey
8711 37th Street Southeast
Jamestown, North Dakota 58401
The study described in this report represents the first time that a satellite model has been used to identify potential Southwestern Willow Flycatcher (Empidonax traillii extimus) (hereinafter referred to as “flycatcher”) breeding habitat rangewide for 2013–15. Fifty-seven Landsat scenes were required to map the entire range of the flycatcher, encompassing parts of six States and more than 1 billion 30-meter pixels. Predicted flycatcher habitat was summarized in a hierarchical fashion from largest to smallest: regionwide, State, U.S. Fish and Wildlife Service (FWS) management unit, 7.5-minute quadrangle, and critical-habitat reach. The term “predicted habitat” is used throughout this report to distinguish areas the satellite model predicts as suitable flycatcher habitat from what may actually exist on the ground. A rangewide accuracy assessment was done with 758 territories collected in 2014, and change detection was done with yearly habitat maps to identify how and where habitat changed over time. Additionally, effects of tamarisk leaf beetles (Diorhabda spp.) on flycatcher habitat were summarized for the lower Virgin River from 2010 to 2015, and simulations of how tamarisk leaf beetles may affect flycatcher habitat in the lower Colorado and upper Gila Rivers were done for 2015. Model results indicated that the largest areas of predicted flycatcher habitat at elevations below 1,524 meters were in New Mexico and Arizona, areas followed in descending order by California, Texas, Nevada, Utah, and Colorado. By FWS management unit, the largest area of flycatcher habitat during all 3 years were the Middle Rio Grande (New Mexico), followed by the Upper Gila (Arizona and New Mexico) and Middle Gila/San Pedro (Arizona) management units. The area of predicted flycatcher habitat varied considerably in 7.5-minute quadrangles, ranging from 0 to1,398 hectares (ha). Averaged across 3 years, the top three producing quadrangles were Paraje Well (New Mexico), San Marcial (New Mexico), and San Carlos Reservoir (Arizona). The top three FWS critical-habitat reaches in 2015 were Rio Grande-middle (9,544 ha), San Pedro River (1,779 ha), and Gila River-mid San Carlos (1,356 ha); this ranking did not change in 2013 or 2014. Change detection among years showed a large shift in predicted flycatcher habitat influenced by drought patterns, with California habitat decreasing and New Mexico habitat increasing. An accuracy assessment indicated that 88 percent of territories were correctly classified at a 40 percent probability threshold, with an exponential relationship between territory densities and five probability classes. A spatially explicit analysis indicated that beetles decreased predicted flycatcher habitat 94.2 percent from 2010 to 2015 along the lower Virgin River, with only 5.8 percent persisting. In contrast, beetle simulations indicated that 64.1 percent of habitat will persist along the lower Colorado River and 45 percent will persist along the upper Gila River. This project shows that the satellite model adequately predicts flycatcher habitat rangewide, but it lacks the ability to predict which patches will be occupied in a given year. The next logical step is the development of an occupancy model that ties the habitat predictions of the satellite model to patch occupancy so managers can better allocate their resources for survey and restoration activities. Finally, the methods presented in this report seem well suited for automated mapping applications and cloud-based resources.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161120","usgsCitation":"Hatten, J.R., 2016, A satellite model of Southwestern Willow Flycatcher (Empidonax traillii extimus) breeding habitat and a simulation of potential effects of tamarisk leaf beetles (Diorhabda spp.), Southwestern United States: U.S. Geological Survey Open-File Report 2016–1120, 88 p., https://dx.doi.org/10.3133/ofr20161120.","productDescription":"vi, 88 p.","numberOfPages":"98","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-074418","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":326223,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1120/coverthb.jpg"},{"id":326224,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1120/ofr20161120.pdf","text":"Report","size":"13.6 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U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115
http://wfrc.usgs.gov/
The coastal region of California supports a wealth of ecosystem services including habitat provision for wildlife and fisheries. Tidal marshes, mudflats, and shallow bays within coastal estuaries link marine, freshwater and terrestrial habitats, and provide economic and recreational benefits to local communities. Climate change effects such as sea-level rise (SLR) are altering these habitats, but we know little about how these areas will change over the next 50–100 years. Our study examined the projected effects of three recent SLR scenarios produced for the West Coast of North America on tidal marshes in California. We compiled physical and biological data, including coastal topography, tidal inundation, plant composition, and sediment accretion to project how SLR may alter these ecosystems in the future. The goal of our research was to provide results that support coastal management and conservation efforts across California. Under a low SLR scenario, all study sites remained vegetated tidal wetlands, with most sites showing little elevation and vegetation change relative to sea level. At most sites, mid SLR projections led to increases in low marsh habitat at the expense of middle and high marsh habitat. Marshes at Morro Bay and Tijuana River Estuary were the most vulnerable to mid SLR with many areas becoming intertidal mudflat. Under a high SLR scenario, most sites were projected to lose vegetated habitat, eventually converting to intertidal mudflats. Our results suggest that California marshes are vulnerable to major habitat shifts under mid or high rates of SLR, especially in the latter part of the century. Loss of vegetated tidal marshes in California due to SLR is expected to impact ecosystem services that are dependent on coastal wetlands such as wildlife habitat, carbon sequestration, improved water quality, and coastal protection from storms.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161125","collaboration":"Prepared in cooperation with the Southwest Climate Science Center","usgsCitation":"Thorne, K.M., MacDonald, G.M., Ambrose, R.F., Buffington, K.J., Freeman, C.M., Janousek, C.N., Brown, L.N., Holmquist, J.R., Guntenspergen, G.R., Powelson, K.W., Barnard, P.L., and Takekawa, J.Y., 2016, Effects of climate change on tidal marshes along a latitudinal gradient in California: U.S. Geological Survey Open-File Report 2016-1125, 75 p., https://dx.doi.org/10.3133/ofr20161125.","productDescription":"Report: viii, 75 p.; Appendixes","numberOfPages":"87","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-075871","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":326133,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1125/coverthb.jpg"},{"id":326134,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1125/ofr20161125.pdf","text":"Report","size":"4.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1125 Report PDF"},{"id":326135,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1125/ofr20161125_appendixes.pdf","text":"Appendixes","size":"11 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1125 Appendixes PDF"}],"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 -124.91455078125,\n 40.94671366508002\n ],\n [\n -122.51953124999999,\n 35.99578538642032\n ],\n [\n -120.52001953124999,\n 33.61461929233378\n ],\n [\n -117.92724609375,\n 32.41706632846282\n ],\n [\n -116.05957031249999,\n 32.657875736955305\n ],\n [\n -118.65234374999999,\n 34.63320791137959\n ],\n [\n -120.65185546875,\n 36.58024660149866\n ],\n [\n -122.98095703125,\n 41.0130657870063\n ],\n [\n -124.91455078125,\n 40.94671366508002\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
http://www.werc.usgs.gov/
In 2014 and 2015, the U.S. Geological Survey (USGS) sampled water wells in the Los Angeles Basin and southern San Joaquin Valley, California, and oil wells in the San Joaquin Valley for analysis of multiple chemical, isotopic, and groundwater-age tracers. The purpose of this reconnaissance sampling was to evaluate the utility of tracers for assessing the effects of oil and gas production activities on groundwater quality in California. The study was done in cooperation with the California State Water Resources Control Board. Results of the study are intended to help design a regional groundwater-monitoring program to be implemented as part of California Senate Bill 4 (SB 4 statutes of 2013). The regional monitoring program plans to assess the effects of oil and gas production activities on groundwater quality and to provide a regional context for local monitoring of the groundwater-quality effects from well-stimulation treatments, which are techniques used to improve oil and gas production by increasing their rate of flow to the well. California SB 4 mandates that this local monitoring is to be done by oil-well operators in accordance with monitoring criteria established by the State Water Board.
\nThis report evaluates the utility of the chemical, isotopic, and groundwater-age tracers for assessing sources of salinity, methane, and petroleum hydrocarbons in groundwater overlying or near several California oil fields. Tracers of dissolved organic carbon in
oil-field-formation water are also discussed. Tracer data for samples collected from 51 water wells and 4 oil wells are examined.
Director, California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
http://ca.water.usgs.gov
Characterizing bathymetric change in coastal environments is an important component in understanding shoreline evolution, especially along barrier island platforms. Bathymetric change is a function of the regional sediment budget, long-term wave and current patterns, and episodic impact from high-energy events such as storms. Human modifications may also cause changes in seafloor elevation. This study, conducted by the U.S. Geological Survey in collaboration with the U.S. Fish and Wildlife Service, evaluates bathymetric and volumetric change and sediment characteristics around Breton Island and Gosier Shoals located offshore of the Mississippi River Delta in Louisiana. This area has been affected by significant storm events such as Hurricane Katrina in 2005. Sedimentation patterns at Breton Island and offshore have also been modified by the excavation of a shipping channel north of the island. Four time periods are considered that encompass these episodes and include long-term change and short-term storm recovery: 1869–2014, 1869–1920, 1920–2014, and 2007–2014. Finally, sediment characteristics are reported in the context of seafloor elevation.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161069","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Flocks, J.G., and Terrano, J.F., 2016, Analysis of seafloor change at Breton Island, Gosier Shoals, and surrounding waters, 1869–2014, Breton National Wildlife Refuge, Louisiana: U.S. Geological Survey Open-File Report 2016–1069, 27 p., https://dx.doi.org/10.3133/ofr20161069.","productDescription":"Report: vi, 27 p.; Data Releases","numberOfPages":"34","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-073884","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":324961,"rank":4,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/publication/ds1005","text":"Data Series 1005","description":"OFR 2016-1069","linkHelpText":"Archive of Bathymetry and Backscatter Data Collected in 2014 Nearshore Breton and Gosier Islands, Breton National Wildlife Refuge, Louisiana"},{"id":324963,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7XS5SGM","text":"USGS data release - A GIS Compilation of Vector Shorelines and Associated Shoreline Change Data for Breton Island, Louisiana: 1869–2014","description":"OFR 2016-1069"},{"id":324960,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://dx.doi.org/10.3133/ofr20161039","text":"Open-File Report 2016–1039","description":"OFR 2016-1069","linkHelpText":"Analysis of shoreline and geomorphic change for Breton Island, Louisiana, from 1869 to 2014"},{"id":324962,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F70G3H6G","text":"USGS data release - Topobathymetric Lidar Survey of Breton and Gosier Islands, Louisiana, January 16 and 18, 2014","description":"OFR 2016-1069"},{"id":324958,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1069/coverthb.jpg"},{"id":324959,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1069/ofr20161069.pdf","text":"Report","size":"7.40 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1069"}],"country":"United States","state":"Louisana","otherGeospatial":"Breton Island, Breton National Wildlife Refuge, Gosier Shoals","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.07234191894531,\n 29.471883455244765\n ],\n [\n -88.98994445800781,\n 29.538216607905866\n ],\n [\n -89.07096862792969,\n 29.614057949691468\n ],\n [\n -89.31060791015624,\n 29.44438130948883\n ],\n [\n -89.22477722167967,\n 29.361231724636678\n ],\n [\n -89.19525146484375,\n 29.38576493113888\n ],\n [\n -89.14581298828125,\n 29.387559811639232\n ],\n [\n -89.10804748535155,\n 29.352254684201622\n ],\n [\n -89.0826416015625,\n 29.369011186354562\n ],\n [\n -89.07920837402344,\n 29.39952487234379\n ],\n [\n -89.05654907226562,\n 29.4186660412453\n ],\n [\n -89.05517578125,\n 29.44916482692468\n ],\n [\n -89.07234191894531,\n 29.471883455244765\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, St. Petersburg Coastal and Marine Science Center
U.S. Geological Survey
600 4th Street South
St. Petersburg, FL 33701
(727) 502–8000
http://coastal.er.usgs.gov
Boreal soils play an important role in the global carbon cycle owing to the large amount of carbon stored within this northern region. To understand how carbon and nitrogen storage varied among different ecosystems, a vegetation gradient was established in the Bonanza Creek Long Term Ecological Research (LTER) site, located in interior Alaska. The ecosystems represented are a black spruce (Picea mariana)–feather moss (for example, Hylocomium sp.) forest ecosystem, a shrub-dominated ecosystem, a tussock-grass-dominated ecosystem, a sedge-dominated ecosystem, and a rich fen ecosystem. Here, we report the physical, chemical, and descriptive properties for the soil cores collected at these sites. These data have been used to calculate carbon and nitrogen accumulation rates on a long-term (decadal and century) basis (Manies and others, in press).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161034","usgsCitation":"Manies, K.L., Harden, J.W., Fuller, C.C., Xu, Xiaomei, and McGeehin, J.P., 2016, Soil data for a vegetation gradient located at Bonanza Creek Long Term Ecological Research Site, interior Alaska: U.S. Geological Survey Open-File Report 2016–1034, 10 p., https://dx.doi.org/10.3133/ofr20161034.","productDescription":"Report: iv, 10 p.; Data Files","numberOfPages":"16","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-072809","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":325710,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1034/coverthb.jpg"},{"id":325738,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2016/1034/ofr20161034_appendix.zip","text":"Data Files","size":"120 KB","linkFileType":{"id":6,"text":"zip"},"description":"OFR 2016-1034"},{"id":325737,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1034/ofr20161034.pdf","text":"Report","size":"393 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1034"}],"contact":"Contact Information
Soil Carbon Research - Menlo Park
U.S. Geological Survey
345 Middlefield Road, MS 962
Menlo Park, CA 94025
http://carbon.wr.usgs.gov/
http://carbon.wr.usgs.gov/people.html