National parks in the United States face the difficult task of managing natural resources within park boundaries that are influenced to a large degree by historical land uses or by forces outside of the park’s protection and mandate. Among the many challenges faced by parks is management of wildlife populations that occupy larger landscapes than individual park units but that concentrate within park lands both seasonally and opportunistically. Great Sand Dunes National Park and Preserve in south-central Colorado is currently developing an Ungulate Management Plan to address management of elk and bison populations within the park. Execution of the Ungulate Management Plan will require monitoring and assessment of habitat conditions in areas that appear sensitive to ungulate use or heavily used by elk and bison. Several sources of information on the various habitats within the park and their use and response to foraging elk and bison exist from recent and on-going research in Great Sand Dunes National Park and Preserve as well as from studies in other regions of the Intermountain West. All of this data can be used to inform the planning process. This report provides background on vegetation types that make up the primary bison and elk ranges in Great Sand Dunes National Park and Preserve and on the potential effects of ungulate grazing and browsing in these specific vegetation communities (both locally and regionally). The report also provides a review of the elements necessary to develop a long-term monitoring program for Great Sand Dunes National Park and Preserve that addresses both the responses to ungulate herbivory seen in important habitats in the park and the amount and patterns of ungulate habitat use.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151136","usgsCitation":"Zeigenfuss, L.C., and Schoenecker, K.A., 2015, Development of a grazing monitoring program for Great Sand Dunes National Park: U.S. Geological Survey, Open-File Report 2015–1136, 44 p., https://dx.doi.org/10.3133/ofr20151136.","productDescription":"v, 44 p.","numberOfPages":"49","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-060650","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":306480,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1136/ofr20151136.pdf","text":"Report","size":"4.32 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1136"},{"id":306479,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1136/coverthb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Great Sand Dunes National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.6005859375,\n 37.84395256743896\n ],\n [\n -105.59715270996092,\n 37.72945260537779\n ],\n [\n -105.545654296875,\n 37.72782336496339\n ],\n [\n -105.51612854003906,\n 37.73488314788311\n ],\n [\n -105.50239562988281,\n 37.79296501804014\n ],\n [\n -105.5181884765625,\n 37.81466615224322\n ],\n [\n -105.55801391601561,\n 37.82659905787503\n ],\n [\n -105.56968688964844,\n 37.83148014503288\n ],\n [\n -105.58135986328124,\n 37.84774810348539\n ],\n [\n -105.6005859375,\n 37.84395256743896\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Fort Collins Science Center
U.S. Geological Survey
2150 Centre Ave., Bldg. C
Fort Collins, CO 80526–8118
http://www.fort.usgs.gov/
In 2010, Utah Department of Environmental Quality (DEQ) Division of Water Quality (UDWQ, 2010) determined that water quality in Pariette Draw was in violation of Federal and State water quality criteria for total dissolved solids (TDS), selenium (Se), and boron (B). The measure of total dissolved solids is the sum of all the major ion concentrations in solution and in this case, the dominant ions are sodium (Na) and sulfate (SO4), which can form salts like thenardite (Na2SO4) and mirabilite (Na2SO4⋅H2O). The Utah Department of Environmental Quality (2010) classified the contamination as natural background and from nonpoint sources related to regional lithology and irrigation practices. Although the daily loads of the constituents of concern and water chemistry have been characterized for parts of the watershed, little is known about the controls that bedrock and soil mineralogy have on salt, Se, and B storage and the water-rock interactions that influence the mobility of these components in ground and surface waters. Studies in the Uncompahgre River watershed in Colorado by Tuttle and others (2014a, 2014b) show that salt derived from weathering of shale in a semiarid climate is stored in a variety of minerals that contribute solutes to runoff and surface waters based on a complex set of conditions such as water availability, geomorphic position (for example, topography controls the depth of salt accumulation in soils), water-table fluctuations, redox conditions, mineral dissolution kinetics, ion-exchange reactions, and secondary mineral formation. Elements like Se and B commonly reside in soluble salt phases, so knowledge of the behavior of salt minerals also sheds light on the behavior of associated contaminants.
\nThe goal of this study was to establish a process-based understanding of salt, Se, and B behavior to address whether these contaminants can be better managed, or if uncontrollable natural processes will overwhelm any attempts to bring Pariette Draw into compliance with respect to recently established total maximum daily limits (TMDLs). We collected data to refine our knowledge about the role of rock weathering and soil formation in the transport and storage of salt in the watershed and to show how salt is cycled under irrigated and natural conditions. Our approach was to sample rock, soils, and sediment on irrigated and natural terrain for mineralogical analysis to determine the residence of salt and associated Se and B, classify minerals as primary (related to rock formation) or secondary weathering products, and characterize mineral dissolution kinetics. Mineral and chemical analyses and selective extractions of rocks and soils provide useful information in understanding solute movement and mineral dissolution/ formation. The resulting data are critical in determining residence of salt, Se, and B in weathered rock and soil and understanding the mobility during water-rock-soil interactions. This report summarizes our methods for sample and data collection and tabulates the mineral, chemical, and isotopic data collected.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151132","collaboration":"U.S. Geological Survey Mineral Resources Program, prepared in cooperation with Bureau of Reclamation, Bureau of Land Management, and Utah Department of Environmental Quality Division of Water Quality","usgsCitation":"Morrison, J.M., Tuttle, M.L.W., and Fahy, J.W., 2015, Results of mineral, chemical, and sulfate isotopic analyses\nof water, soil, rocks, and soil extracts from the Pariette Draw Watershed, Uinta Basin, Utah: U.S. Geological Survey\nOpen-File Report 2015–1132, 10 p., https://dx.doi.org/10.3133/ofr20151132.","productDescription":"Report: vii, 9 p.; 1 Appendix","numberOfPages":"21","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-060327","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":306414,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2015/1132/downloads","text":"Appendix Tables","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2015-1132 Appendix Tables"},{"id":306413,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1132/ofr20151132.pdf","text":"Report","size":"10.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1132"},{"id":306412,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1132/coverthb.jpg"}],"country":"United States","state":"Utah","otherGeospatial":"Uinta Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.18188476562499,\n 39.825413103424786\n ],\n [\n -110.18188476562499,\n 40.12429084831405\n ],\n [\n -109.434814453125,\n 40.12429084831405\n ],\n [\n -109.434814453125,\n 39.825413103424786\n ],\n [\n -110.18188476562499,\n 39.825413103424786\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Crustal Geophysics and Geochemistry Science Center
U.S. Geological Survey
Box 25046, MS 964
Denver, CO 80225
http://crustal.usgs.gov/
Isolated patches of native vegetation in human-modified landscapes are important reservoirs of biological diversity because they may be the only places in which rare or native species can persist. Manassas National Battlefield Park, Virginia, is an island embedded in a matrix of intensively modified lands; it is becoming increasingly isolated due to growth of the greater Washington, D.C. area. A series of cliffs along Bull Run support an eastern white pine community disjunct from its more typical range in the Appalachian Mountains. Cliffs frequently support vegetation communities that differ from surrounding habitat. In this ecological context, the cliffs along Bull Run are islands of specialized habitat within an island of natural and semi-natural communities (the park), surrounded by a human-dominated landscape. A floral survey of these cliffs was a top priority identified by the National Park Service National Capital Region via the National Resource Preservation Program; in 2014, we completed a floral survey of 11 cliffs in the park. We recorded 282 species in 194 genera and 83 families, including 23 newly documented species for the park.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds940","usgsCitation":"Stroh, E.D., Struckhoff, M.A., and Grabner, K.W., 2015, A floral survey of cliff habitats along Bull Run at Manassas National Battlefield Park, Virginia, 2014: U.S. Geological Survey Data Series 940, 20 p., https://dx.doi.org/10.3133/ds940.","productDescription":"Report: iv, 20 p.; Database; ReadMe","numberOfPages":"28","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2014-01-01","ipdsId":"IP-063929","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":306469,"rank":4,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/ds/0940/ReadMe.txt","text":"ReadMe File","size":"5.47 kB","linkFileType":{"id":2,"text":"txt"}},{"id":306409,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/0940/coverthb.jpg"},{"id":306410,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0940/ds940.pdf","text":"Report","size":"1.53 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 940"},{"id":306411,"rank":3,"type":{"id":9,"text":"Database"},"url":"https://dx.doi.org/10.5066/F7NS0RXN","text":"Manassas Bluff Flora Database"}],"country":"United States","state":"Virginia","otherGeospatial":"Bull Run, Manassas National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.62424468994139,\n 38.79369731838258\n ],\n [\n -77.61566162109375,\n 38.80654039080489\n ],\n [\n -77.60948181152344,\n 38.819916129801314\n ],\n [\n -77.60261535644531,\n 38.830614912420565\n ],\n [\n -77.59471893310547,\n 38.849066533608884\n ],\n [\n -77.58956909179688,\n 38.85414657465764\n ],\n [\n -77.58922576904297,\n 38.86083028642411\n ],\n [\n -77.57377624511719,\n 38.85708748522446\n ],\n [\n -77.57068634033203,\n 38.85468129471517\n ],\n [\n -77.552490234375,\n 38.850938169890064\n ],\n [\n -77.54528045654297,\n 38.84505571861154\n ],\n [\n -77.53429412841797,\n 38.841579496043266\n ],\n [\n -77.52399444580078,\n 38.83837052447013\n ],\n [\n -77.50991821289062,\n 38.84345132929943\n ],\n [\n -77.50373840332031,\n 38.83837052447013\n ],\n [\n -77.50099182128906,\n 38.833556795784745\n ],\n [\n -77.50614166259766,\n 38.83034746244922\n ],\n [\n -77.50030517578125,\n 38.82473078093276\n ],\n [\n -77.50133514404297,\n 38.81777618035695\n ],\n [\n -77.4972152709961,\n 38.81536866036827\n ],\n [\n -77.48451232910156,\n 38.81028585091164\n ],\n [\n -77.486572265625,\n 38.80225962384825\n ],\n [\n -77.48485565185547,\n 38.79931644737651\n ],\n [\n -77.47318267822266,\n 38.80225962384825\n ],\n [\n -77.48846054077148,\n 38.79543661993626\n ],\n [\n -77.51644134521484,\n 38.79008478723166\n ],\n [\n -77.5224494934082,\n 38.79704209139086\n ],\n [\n -77.53961563110352,\n 38.793831112316646\n ],\n [\n -77.54631042480467,\n 38.791556581282244\n ],\n [\n -77.54287719726562,\n 38.783795870358176\n ],\n [\n -77.57240295410156,\n 38.77710492428489\n ],\n [\n -77.62046813964844,\n 38.77041335043523\n ],\n [\n -77.62424468994139,\n 38.79369731838258\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Columbia Environmental Research Center
U.S. Geological Survey
4200 New Haven Road
Columbia, MO 65201
http://www.cerc.usgs.gov/
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 sonar 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.
\nThe Offshore of Bodega Head map area is located in northern California, about 70 km north of San Francisco and about 80 km south of Point Arena. The onshore part of the map area is largely undeveloped, used primarily for recreation, farms and ranches, and a few wineries. The small town of Bodega Bay, located on the east side of Bodega Harbor, is the largest cultural center. Bodega Harbor is an important commercial fishing base and, in season, an active sport fishing and recreation harbor. Much of the coastline from Bodega Head north to about 6 km north of the Russian River is part of Sonoma Coast State Park. The Offshore of Bodega Head map area includes two California Marine Protected Areas, the Bodega Head State Marine Reserve and the northern part of the Bodega Head State Marine Conservation Area. Additionally, the inland parts of two large estuaries in the map area, Estero Americano and Estero de San Antonio, have been designated as State Marine Recreational Management Areas.
\nThe map area is cut by the northwest-striking San Andreas Fault, the right-lateral transform boundary between the North American and Pacific plates. This fault juxtaposes rocks of the Jurassic and Cretaceous Franciscan Complex on the northeast with Cretaceous granitic rocks on the southwest, and it has an estimated slip rate of about 17 to 25 mm/yr in this area. The devastating great 1906 California earthquake (M7.8) is thought to have nucleated on the San Andreas Fault offshore of San Francisco, about 80 km south of Bodega Head, with the rupture extending northward through the Offshore of Bodega Head map area and an additional 220 km to the south flank of Cape Mendocino.
\nNorth of the mouth of Salmon Creek, the coast and shoreline are rugged and scenic, characterized by flights of uplifted marine terraces, rocky promontories, nearshore sea stacks, kelp-rich coves, and both pocket beaches and longer beach strands, the latter of which include Wrights Beach and Portuguese Beach. The coast has lower relief between the mouth of Salmon Creek and Mussel Point, where South Salmon Creek Beach is backed by a large (about 4 km2) complex of coastal sand dunes. The enormous volume of sand on the beach and in the dune field is derived by southward littoral drift from the Russian River, Salmon Creek, and smaller coastal watersheds. The sediment is trapped by protruding bedrock at Mussel Point, which represents the south end of the Russian River littoral cell.
\nBodega Head is underlain by Cretaceous granitic rocks, and its shoreline is variously characterized by relatively low-lying terraces, steep and high bluffs, and a few pocket beaches. East of Bodega Head, Doran Beach (part of Doran Regional Park) is a 1.7-km-long sand spit that forms the north boundary of Bodega Bay and the south boundary of Bodega Harbor. The coast south of Doran Beach on the east flank of Bodega Bay is composed of rocky bluffs, hummocky marine terraces, and a few small pocket beaches. The bluffs are underlain by sheared rocks of the Franciscan Complex and are highly susceptible to landslides. This section of coast includes two prominent watersheds, Estero Americano and Estero de San Antonio, which drain westward into Bodega Bay.
\nThe offshore part of the Offshore of Bodega Head map area is characterized by an extensive, rugged and rocky shelf underlain by Cretaceous granitic rocks. This rocky terrain, centered offshore of Bodega Head, extends northwestward for about 15 km, from the south edge of the map area (where it forms the west boundary of Bodega Bay) to the northern-central part of the map area offshore of the mouth of Salmon Creek. This rocky seafloor reaches water depths of 40 to 80 m and is overlain by young sediment.
\nCirculation over the shelf and seafloor in the map area (and in the broader central California region) is dominated by the southward-flowing California Current, the eastern boundary current of the North Pacific Gyre. Associated upwelling brings cool, nutrient-rich waters to the surface, resulting in high biological productivity. Persistent northwest winds are sometimes weak or absent during the fall and winter, causing the California Current to move farther offshore so that the shelf is affected by the Davidson Current, a weaker northward-flowing countercurrent. As a result, net flow over the continental shelf is commonly southeastward during the spring and summer and northwestward during the fall and winter.
\nThroughout the year, this part of the northern California coast is exposed to four wave climate regimes: the north Pacific swell, the southern swell, northwest wind waves, and local wind waves. The north Pacific swell dominates in winter months (typically November through March). During summer months, the largest waves come from the southern swell, generated by storms in the south Pacific and offshore of Central America. Northwest wind waves affect the coast throughout the year, whereas local wind waves are most common from October to April.
\nPotential marine benthic habitats in the Offshore of Bodega Head map area include unconsolidated continental-shelf sediments, mixed continental-shelf substrate, and hard continental-shelf substrate. Rocky-shelf outcrops and rubble are considered to be promising potential habitats for rockfish and lingcod, both of which are recreationally and commercially important species.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151140","usgsCitation":"Johnson, S.Y., Dartnell, P., Golden, N.E., Hartwell, S.R., Erdey, M.D., Greene, H.G., Cochrane, G.R., Kvitek, R.G., Manson, M.W., Endris, C.A., Dieter, B.E., Watt, J.T., Krigsman, L.M., Sliter, R.W., Lowe, E.N., and Chin, J.L. (S.Y. Johnson and S.A. Cochran, eds.), 2015, California State Waters Map Series—Offshore of Bodega Head, California: U.S. Geological Survey Open-File Report 2015–1140, pamphlet 39 p., 10 sheets, scale 1:24,000, https://dx.doi.org/10.3133/ofr20151140.","productDescription":"Report: iv, 39 p.; 10 Plates: 46.0 x 36.0 inches or smaller; Metadata; Data Catalog","numberOfPages":"43","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-055943","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":399007,"rank":20,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_102290.htm"},{"id":306403,"rank":19,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1140/coverthb.jpg"},{"id":306402,"rank":18,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/of/2015/1114/","text":"Open-File Report 2015–1114","description":"Open-File Report 2015–1114","linkHelpText":"California State Waters Map Series—Offshore of Point Reyes and Vicinity, California, by Janet T. Watt and others."},{"id":306401,"rank":17,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/of/2015/1098/","text":"Open-File Report 2015–1098","description":"Open-File Report 2015–1098","linkHelpText":"California State Waters Map Series—Offshore of Salt Point, California, by Samuel Y. Johnson and others."},{"id":306400,"rank":16,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/of/2015/1088/","text":"Open-File Report 2015–1088","description":"Open-File Report 2015–1088","linkHelpText":"California State Waters Map Series—Offshore of Tomales Point, California, by Samuel Y. Johnson and others."},{"id":306399,"rank":15,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/of/2015/1041/","text":"Open-File Report 2015–1041","description":"Open-File Report 2015–1041","linkHelpText":"California State Waters Map Series—Drakes Bay and Vicinity, California, by Janet T. Watt and others."},{"id":306416,"rank":14,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/ds/781/","text":"Data Series 781","description":"Data Series 781","linkHelpText":"California State Waters Map Series Data Catalog"},{"id":306398,"rank":13,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/of/2015/1140/ofr20151140_metadata.html","text":"Metadata","linkFileType":{"id":5,"text":"html"}},{"id":306397,"rank":12,"type":{"id":28,"text":"Dataset"},"url":"https://pubs.usgs.gov/ds/781/OffshoreBodegaHead/data_catalog_OffshoreBodegaHead.html","text":"Data Catalog","linkFileType":{"id":5,"text":"html"},"linkHelpText":"The GIS data layers for this map are accessible from “Data Catalog—Offshore of Bodega Head, California,” which is part of California State Waters Map Series Data Catalog (Data Series 781). Each GIS data file is listed with a brief description, a small image, and links to the metadata files and the downloadable data files."},{"id":306396,"rank":11,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2015/1140/ofr20151140_sheet10.pdf","text":"Sheet 10","linkFileType":{"id":1,"text":"pdf"},"description":"Sheet 10","linkHelpText":"Offshore and Onshore Geology and Geomorphology, Offshore of Bodega Head Map Area, California By Samuel Y. Johnson, Stephen R. Hartwell, and Michael W. Manson"},{"id":306395,"rank":10,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2015/1140/ofr20151140_sheet9.pdf","text":"Sheet 9","linkFileType":{"id":1,"text":"pdf"},"description":"Sheet 9","linkHelpText":"Local (Offshore of Bodega Head Map Area) and Regional (Offshore from Salt Point to Drakes Bay) Shallow-Subsurface Geology and Structure, California By Samuel Y. Johnson, Stephen R. Hartwell, Janet T. Watt, and Ray W. Sliter"},{"id":306394,"rank":9,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2015/1140/ofr20151140_sheet8.pdf","text":"Sheet 8","linkFileType":{"id":1,"text":"pdf"},"description":"Sheet 8","linkHelpText":"Seismic-Reflection Profiles, Offshore of Bodega Head Map Area, California by Samuel Y. Johnson, Ray W. Sliter, Stephen R. Hartwell, and John L. Chin"},{"id":306389,"rank":4,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2015/1140/ofr20151140_sheet3.pdf","text":"Sheet 3","linkFileType":{"id":1,"text":"pdf"},"description":"Sheet 3","linkHelpText":"Acoustic Backscatter, Offshore of Bodega Head Map Area, California By Peter Dartnell, Mercedes D. Erdey, and Rikk G. Kvitek"},{"id":306388,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2015/1140/ofr20151140_sheet2.pdf","text":"Sheet 2","linkFileType":{"id":1,"text":"pdf"},"description":"Sheet 2","linkHelpText":"Shaded-Relief Bathymetry, Offshore of Bodega Head Map Area, California By Peter Dartnell and Rikk G. Kvitek"},{"id":306387,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2015/1140/ofr20151140_sheet1.pdf","text":"Sheet 1","linkFileType":{"id":1,"text":"pdf"},"description":"Sheet 1","linkHelpText":"Colored Shaded-Relief Bathymetry, Offshore of Bodega Head Map Area, California By Peter Dartnell and Rikk G. Kvitek"},{"id":306386,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1140/ofr20151140_pamphlet.pdf","text":"Pamphlet","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1140 Pamphlet"},{"id":306393,"rank":8,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2015/1140/ofr20151140_sheet7.pdf","text":"Sheet 7","linkFileType":{"id":1,"text":"pdf"},"description":"Sheet 7","linkHelpText":"Potential Marine Benthic Habitats, Offshore of Bodega Head Map Area, California By Bryan E. Dieter, H. Gary Greene, Charles A. Endris, and Erik N . Lowe"},{"id":306392,"rank":7,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2015/1140/ofr20151140_sheet6.pdf","text":"Sheet 6","linkFileType":{"id":1,"text":"pdf"},"description":"Sheet 6","linkHelpText":"Ground-Truth Studies, Offshore of Bodega Head Map Area, California By Nadine E. Golden, Guy R. Cochrane, and Lisa M. Krigsman"},{"id":306391,"rank":6,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2015/1140/ofr20151140_sheet5.pdf","text":"Sheet 5","linkFileType":{"id":1,"text":"pdf"},"description":"Sheet 5","linkHelpText":"Seafloor Character, Offshore of Bodega Head Map Area, California By Mercedes D. Erdey and Guy R. Cochrane"},{"id":306390,"rank":5,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2015/1140/ofr20151140_sheet4.pdf","text":"Sheet 4","linkFileType":{"id":1,"text":"pdf"},"description":"Sheet 4","linkHelpText":"Data Integration and Visualization, Offshore of Bodega Head Map Area, California By Peter Dartnell"}],"country":"United States","state":"California","otherGeospatial":"Bodega Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.1719,\n 38.2611\n ],\n [\n -123.1719,\n 38.4122\n ],\n [\n -122.9703,\n 38.4122\n ],\n [\n -122.9703,\n 38.2611\n ],\n [\n -123.1719,\n 38.2611\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/
The U.S. Geological Survey (USGS) and partners in other Federal and State agencies are working collaboratively toward Statewide coverage of interferometric synthetic aperture radar (ifsar) elevation data in Alaska. These data will provide many benefits to a wide range of stakeholders and users. Some applications include development of more accurate and highly detailed topographic maps; improvement of surface water information included in the National Hydrography (NHD) and Watershed Boundary Datasets (WBDs); and use in scientific modeling applications such as calculating glacier surface elevation differences over time and estimating tsunami inundation areas.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20153051","usgsCitation":"Craun, K.J., 2015, Mapping benefits from updated ifsar data in Alaska—Improved source data enables better maps: U.S. Geological Survey Fact Sheet 2015–3051, 2 p., https://dx.doi.org/10.3133/fs20153051.","productDescription":"2 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-067048","costCenters":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"links":[{"id":306439,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2015/3051/fs20153051.pdf","text":"Report","size":"4.39 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2015-3051"},{"id":306438,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2015/3051/coverthb.jpg"}],"country":"United 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\":{\"name\":\"Alaska\",\"nation\":\"USA \"}}]}","contact":"Director, National Geospatial Technical Operations Center
U.S. Geological Survey
1400 Independence Road
Rolla, MO 65401-2602
http://ngtoc.usgs.gov/
Large research studies are often challenged to effectively expose and document the types of information being collected and the reasons for data collection across what are often a diverse cadre of investigators of differing disciplines. We applied concepts from the field of information or data modeling to the U.S. Geological Survey (USGS) Changing Arctic Ecosystems (CAE) initiative to prototype an application of information modeling. The USGS CAE initiative is collecting information from marine and terrestrial environments in Alaska to identify and understand the links between rapid physical changes in the Arctic and response of wildlife populations to these ecosystem changes. An associated need is to understand how data collection strategies are informing the overall science initiative and facilitating communication of those strategies to a wide audience. We explored the use of conceptual data modeling to provide a method by which to document, describe, and visually communicate both enterprise and study level data; provide a simple means to analyze commonalities and differences in data acquisition strategies between studies; and provide a tool for discussing those strategies among researchers and managers.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151148","collaboration":"Science to Support the USGS Changing Arctic Ecosystems Initiative","usgsCitation":"Walworth, Dennis, and Pearce, J.M., 2015, Conceptual data modeling of wildlife response indicators to\necosystem change in the Arctic: U.S. Geological Survey Open-File Report 2015-1148, 28 p.,\nhttps://dx.doi.org/10.3133/ofr20151148.","productDescription":"iv, 28 p.","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-053898","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":306449,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1148/coverthb.jpg"},{"id":306450,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1148/ofr20151148.pdf","text":"Report","size":"1.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1148 Report"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -168.48632812499997,\n 62.3903694381427\n ],\n [\n -168.48632812499997,\n 71.46912418989677\n ],\n [\n -144.84375,\n 71.46912418989677\n ],\n [\n -144.84375,\n 62.3903694381427\n ],\n [\n -168.48632812499997,\n 62.3903694381427\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Alaska Science Center
U.S. Geological Survey
4210 University Dr
Anchorage, Alaska 99508-4560
http://alaska.usgs.gov
Annual peak-flow frequency data from 231 U.S. Geological Survey streamflow-gaging stations in North Dakota and parts of Montana, South Dakota, and Minnesota, with 10 or more years of unregulated peak-flow record, were used to develop regional regression equations for exceedance probabilities of 0.5, 0.20, 0.10, 0.04, 0.02, 0.01, and 0.002 using generalized least-squares techniques. Updated peak-flow frequency estimates for 262 streamflow-gaging stations were developed using data through 2009 and log-Pearson Type III procedures outlined by the Hydrology Subcommittee of the Interagency Advisory Committee on Water Data. An average generalized skew coefficient was determined for three hydrologic zones in North Dakota. A StreamStats web application was developed to estimate basin characteristics for the regional regression equation analysis. Methods for estimating a weighted peak-flow frequency for gaged sites and ungaged sites are presented.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155096","collaboration":"Prepared in cooperation with the North Dakota State Water Commision, the North Dakota Department of Transportation, the North Dakota Department of Health, the Red River Joint Water Resources Board, and the Devils Lake Basin Joint Water Resource Board","usgsCitation":"Williams-Sether, Tara, 2015, Regional regression equations to estimate peak-flow frequency at sites in North Dakota using data through 2009: U.S. Geological Survey Scientific Investigations Report 2015–5096, 12 p.,\nhttps://dx.doi.org/10.3133/sir20155096.","productDescription":"Report: iv, 12 p.; 4 Tables","numberOfPages":"20","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-057778","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":306455,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5096/sir20155096.pdf","text":"Report","size":"4.63 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5096"},{"id":306456,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2015/5096/downloads","text":"Tables 1 and 4","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2015-5096 Tables 1 and 4"},{"id":306454,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5096/coverthb.jpg"}],"country":"United States","state":"North Dakota","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96.56982421875,\n 45.920587344733654\n ],\n [\n -96.591796875,\n 46.37725420510028\n ],\n [\n -96.78955078125,\n 46.6795944656402\n ],\n [\n -96.8115234375,\n 46.965259400349275\n ],\n [\n -96.85546875,\n 47.69497434186282\n ],\n [\n -97.0751953125,\n 48.06339653776211\n ],\n [\n -97.1630859375,\n 48.516604348867475\n ],\n [\n -97.09716796875,\n 48.748945343432936\n ],\n [\n -97.2509765625,\n 49.023461463214126\n ],\n [\n -104.08447265624999,\n 49.009050809382046\n ],\n [\n -104.04052734375,\n 45.9511496866914\n ],\n [\n -96.56982421875,\n 45.920587344733654\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, North Dakota Water Science Center
U.S. Geological Survey
821 East Interstate Avenue
Bismarck, North Dakota 58503
http://nd.water.usgs.gov/
Stream-channel cross-section survey data are a fundamental component to studies of fluvial geomorphology. Such data provide important parameters required by many open-channel flow models, sediment-transport equations, sediment-budget computations, and flood-hazard assessments. At Mount St. Helens, Washington, the long-term response of channels to the May 18, 1980, eruption, which dramatically altered the hydrogeomorphic regime of several drainages, is documented by an exceptional time series of repeat stream-channel cross-section surveys. More than 300 cross sections, most established shortly following the eruption, represent more than 100 kilometers of surveyed topography. Although selected cross sections have been published previously in print form, we present a comprehensive digital database that includes geospatial and tabular data. Furthermore, survey data are referenced to a common geographic projection and to common datums. Database design, maintenance, and data dissemination are accomplished through a geographic information system (GIS) platform, which integrates survey data acquired with theodolite, total station, and global navigation satellite system (GNSS) instrumentation. Users can interactively perform advanced queries and geospatial time-series analysis. An accuracy assessment provides users the ability to quantify uncertainty within these data. At the time of publication, this project is ongoing. Regular database updates are expected; users are advised to confirm they are using the latest version.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds951","usgsCitation":"Mosbrucker, A.R., Spicer, K.R., Major, J.J., Saunders, D.R., Christianson, T.S., and Kingsbury, C.G., 2015, Digital database of channel cross-section surveys, Mount St. Helens, Washington (ver. 1.1, April 2018): U.S. Geological Survey Data Series 951, 9 p. and supplemental data, https://doi.org/10.3133/ds951.","productDescription":"Report: v, 9 p.; Metadata; ReadMe; Spatial Data; Version History","numberOfPages":"20","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-058438","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":306477,"rank":5,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/ds/0951/ds951.zip","text":"Digital cross-section data","size":"9.4 MB","linkFileType":{"id":6,"text":"zip"},"description":"Data include geospatial and tabular files (_.shp, _.lyr, _.xls, _.jpg) as well as an ArcGIS Published Map file (_.pmf)"},{"id":306475,"rank":3,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/ds/0951/1_readme.txt","text":"README","size":"4 kB","linkFileType":{"id":2,"text":"txt"},"description":"README file"},{"id":306474,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0951/ds951v1.1.pdf","text":"Report","size":"4.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 951 Version 1.1"},{"id":353588,"rank":6,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/ds/0951/versionHist.txt","description":"Version History"},{"id":306476,"rank":4,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/ds/0951/fgdc_metadata.txt","text":"FGDC Metadata","size":"14 kB","linkFileType":{"id":2,"text":"txt"},"description":"FGDC compliant metadata file for the ESRI shapefiles"},{"id":306473,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/0951/coverthb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Mount St. Helens","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.95373535156249,\n 46.069419674968536\n ],\n [\n -121.91390991210938,\n 46.144637225509136\n ],\n [\n -121.92352294921874,\n 46.1893382140708\n ],\n [\n -121.90841674804686,\n 46.2397021362749\n ],\n [\n -121.95785522460936,\n 46.28432584258847\n ],\n [\n -122.05123901367186,\n 46.32891323009468\n ],\n [\n -122.08831787109375,\n 46.391464001559086\n ],\n [\n -122.14187622070311,\n 46.39904104733026\n ],\n [\n -122.16110229492186,\n 46.45394316729876\n ],\n [\n -122.26821899414061,\n 46.45772748219606\n ],\n [\n -122.35610961914062,\n 46.46813299215554\n ],\n [\n -122.40142822265625,\n 46.49650154751426\n ],\n [\n -122.44537353515625,\n 46.524855311033434\n ],\n [\n -122.50991821289062,\n 46.53619267489863\n ],\n [\n -122.53463745117186,\n 46.52013071095869\n ],\n [\n -122.56484985351561,\n 46.497446911273606\n ],\n [\n -122.59780883789061,\n 46.494610770689384\n ],\n [\n -122.64312744140624,\n 46.48704700597017\n ],\n [\n -122.71865844726561,\n 46.47191632087041\n ],\n [\n -122.80517578125,\n 46.428392162921234\n ],\n [\n -122.89581298828125,\n 46.41892578708076\n ],\n [\n -123.0084228515625,\n 46.42271253466719\n ],\n [\n -123.05511474609375,\n 46.3810438458062\n ],\n [\n -123.0743408203125,\n 46.322274857040235\n ],\n [\n -123.04962158203124,\n 46.27673288302042\n ],\n [\n -122.96722412109374,\n 46.22735299655779\n ],\n [\n -122.81616210937499,\n 46.231153027822046\n ],\n [\n -122.76397705078124,\n 46.18743678432541\n ],\n [\n -122.684326171875,\n 46.14178273759234\n ],\n [\n -122.55249023437501,\n 46.115133713265415\n ],\n [\n -122.36022949218749,\n 46.117037642576875\n ],\n [\n -122.22290039062499,\n 46.08847179577592\n ],\n [\n -122.13226318359375,\n 46.08085173686787\n ],\n [\n -121.9976806640625,\n 46.057985244793024\n ],\n [\n -121.95373535156249,\n 46.069419674968536\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: Originally released August 6, 2015; Version 1.1: April 18, 2018","contact":"Contact CVO
Volcano Science Center, Cascades Volcano Observatory
U.S. Geological Survey
1300 SE Cardinal Court, Building 10, Ste 100
Vancouver, WA 98683-9589
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 sonar 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.
\nThe Offshore of Bolinas map area is located in northern California, on the Pacific Coast of Marin County about 10 kilometers north of the Golden Gate. The town of Bolinas, named after a local indigenous tribe, is the largest population center along this section of coast, with a population of approximately 1,600 people. Bolinas is situated at the end of a southeast-trending terrain on the west side of the San Andreas Fault that also protects a natural harbor. The harbor lies in Bolinas Lagoon, which is separated from Bolinas Bay by a spit. The coastal lands within the Offshore of Bolinas map area lie entirely within the Point Reyes National Seashore, which limits development and allows existing ranching and farming to continue.
\nThe Offshore of Bolinas map area lies offshore of the northwest-trending Coast Ranges, which lie east of, and are roughly parallel to, the San Andreas Fault Zone. The western margin of North America is the only continental margin in the world delineated largely by transform faults such as the San Andreas Fault. The coastal geomorphology is controlled by late Pleistocene to Holocene slip along the fault. Bolinas Bay and Lagoon have formed where a regional depression along the fault zone intersects the coast. A northward bend in the San Andreas Fault to the north, combined with right-lateral movement, has caused regional extension and the formation of a sediment basin on the continental shelf in, and southeast of, Bolinas Bay.
\nWith the exception of the area adjacent to Bolinas Bay, the coast in the map area consists of high coastal bluffs and vertical sea cliffs. The uplifted headland upon which the town of Bolinas is situated is part of a larger uplifted area that includes exposed bedrock offshore. Uplift in this map area has resulted in relatively shallow depths within California’s State Waters (0 to 40 m) and, thus, little accommodation space for sediment accumulation. Sediment is found in the extensional basin southeast of Bolinas, as well as on the shelf offshore of uplifted coastal areas, where, within California’s State Waters, depths can exceed 40 m. Wave energy keeps the uplifted bedrock areas clear of sediment, and rippled sediment in the outer shelf indicates some mobility.
\nCoastal sediment transport in the Offshore of Bolinas map area is characterized by north-to-south littoral transport of sediment that is derived mainly from ephemeral streams and local coastal erosion. Beyond California’s State Waters, canyons that incise the slope have been disconnected from coastal streams by rising sea level, which has risen about 125 m since the lowstand associated with the Last Glacial Maximum about 18,000 to 20,000 years ago. In the map area, no major submarine canyons extend up past the shelf break and into the nearshore to receive littoral drift. The coastline in the map area is characterized as high risk because of its steep cliffs and large-scale landsliding. The sand spit that separates Bolinas Lagoon from Bolinas Bay is highly developed, and its homes are at risk during storms, especially those from the south.
\nThe benthic species observed in the Offshore of Bolinas map area are natives of the cold-temperate biogeographic zone named 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, an eastern limb of the North Pacific subtropical gyre that flows from Oregon to Baja California. At its midpoint off central California, the California Current transports subarctic surface (0–500 m deep) waters southward, about 150 to 1,300 km from shore. Seasonal northwesterly winds that are, in part, responsible for the California Current, generate coastal upwelling. The south end of the Oregonian province is at Point Conception (about 425 km south of the map area), although its associated phylogeographic group of marine fauna may extend beyond to the area offshore of Los Angeles in southern California. The ocean off central California has seen a warming over the last 50 years that is driving an ecosystem shift from the productive subarctic regime towards a depopulated subtropical environment.
\nSeafloor habitats in the Offshore of Bolinas map area, which lies within the Shelf (continental shelf) megahabitat, range from, in the nearshore, sandy seafloor in the southeast and significant rocky outcrops that support kelp-forest communities in the northwest to, in deeper water, rocky-reef communities. 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. In addition, 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 in the northeast supports large forests of “bull kelp,” which is well adapted for high wave-energy environments. Common fish species found in the kelp beds and rocky reefs include lingcod and various species of greenling and rockfish.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151135","usgsCitation":"Cochrane, G.R., Dartnell, P., Johnson, S.Y., Greene, H.G., Erdey, M.D., Golden, N.E., Hartwell, S.R., Manson, M.W., Sliter, R.W., Endris, C.A., Watt, J.T., Ross, S.L., Kvitek, R.G., Phillips, E.L., Bruns, T.R., and Chin, J.L. (G.R. Cochrane and S.A. Cochran, eds.), 2015, California State Waters Map Series — Offshore of Bolinas, California: U.S. Geological Survey Open-File Report 2015–1135, pamphlet 36 p., 10 sheets, https://dx.doi.org/10.3133/ofr20151135.","productDescription":"Report: iv, 36 p.; 10 Sheets: 46 inches x 36 inches or smaller; Data Catalog; Metadata","numberOfPages":"40","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-052392","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":399008,"rank":21,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_102261.htm"},{"id":306377,"rank":19,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/of/2015/1041/","text":"Open-File Report 2015–1041","description":"Open-File Report 2015–1041","linkHelpText":"California State Waters Map Series—Drakes Bay and Vicinity, California, by Janet T. Watt and others."},{"id":306376,"rank":18,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/of/2015/1068/","text":"Open-File Report 2015–1068","description":"Open-File Report 2015–1068","linkHelpText":"California State Waters Map Series—Offshore of San Francisco, California, by Guy R. Cochrane and others."},{"id":306375,"rank":17,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/of/2014/1260/","text":"Open-File Report 2014–1260","description":"Open-File Report 2014–1260","linkHelpText":"California State Waters Map Series—Offshore of Pacifica, California, by Brian D. Edwards and others."},{"id":306371,"rank":12,"type":{"id":28,"text":"Dataset"},"url":"https://pubs.usgs.gov/ds/781/OffshoreBolinas/data_catalog_OffshoreBolinas.html","text":"Data Catalog","linkFileType":{"id":5,"text":"html"},"description":"Data Catalog","linkHelpText":"The GIS data layers for this map are accessible from “Data Catalog—Offshore of Bolinas, California,” which is part of California State Waters Map Series Data Catalog. Each GIS data file is listed with a brief description, a small image, and links to the metadata files and the downloadable data files."},{"id":306366,"rank":7,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2015/1135/ofr20151135_sheet6.pdf","text":"Sheet 6","linkFileType":{"id":1,"text":"pdf"},"description":"Sheet 6","linkHelpText":"Ground-Truth Studies, Offshore of Bolinas Map Area, California By Nadine E. Golden, Guy R. Cochrane, and Mercedes D. Erdey"},{"id":306364,"rank":5,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2015/1135/ofr20151135_sheet4.pdf","text":"Sheet 4","linkFileType":{"id":1,"text":"pdf"},"description":"Sheet 4","linkHelpText":"Data Integration and Visualization, Offshore of Bolinas Map Area, California By Peter Dartnell"},{"id":306363,"rank":4,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2015/1135/ofr20151135_sheet3.pdf","text":"Sheet 3","linkFileType":{"id":1,"text":"pdf"},"description":"Sheet 3","linkHelpText":"Acoustic Backscatter, Offshore of Bolinas Map Area, California By Peter Dartnell, Rikk G. Kvitek, Mercedes D. Erdey, and Carrie K. Bretz"},{"id":306362,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2015/1135/ofr20151135_sheet2.pdf","text":"Sheet 2","linkFileType":{"id":1,"text":"pdf"},"description":"Sheet 2","linkHelpText":"Shaded-Relief Bathymetry, Offshore of Bolinas Map Area, California By Peter Dartnell, Rikk G. Kvitek, and Carrie K. Bretz"},{"id":306361,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2015/1135/ofr20151135_sheet1.pdf","text":"Sheet 1","linkFileType":{"id":1,"text":"pdf"},"description":"Sheet 1","linkHelpText":"Colored Shaded-Relief Bathymetry, Offshore of Bolinas Map Area, California By Peter Dartnell, Rikk G. Kvitek, and Carrie K. Bretz"},{"id":306369,"rank":10,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2015/1135/ofr20151135_sheet9.pdf","text":"Sheet 9","linkFileType":{"id":1,"text":"pdf"},"description":"Sheet 9","linkHelpText":"Local (Offshore of Bolinas Map Area) and Regional (Offshore from Bolinas to Pescadero) Shallow-Subsurface Geology and Structure, California By Samuel Y. Johnson, Stephen R. Hartwell, Ray W. Sliter, Janet T. Watt, Eleyne L. Phillips, Stephanie L. Ross, and John L. Chin"},{"id":306367,"rank":8,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2015/1135/ofr20151135_sheet7.pdf","text":"Sheet 7","linkFileType":{"id":1,"text":"pdf"},"description":"Sheet 7","linkHelpText":"Potential Marine Benthic Habitats, Offshore of Bolinas Map Area, California By Bryan E. Dieter, H. Gary Greene, Charles A. Endris, and Mercedes D. Erdey"},{"id":306368,"rank":9,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2015/1135/ofr20151135_sheet8.pdf","text":"Sheet 8","linkFileType":{"id":1,"text":"pdf"},"description":"Sheet 8","linkHelpText":"Seismic-Reflection Profiles, Offshore of Bolinas Map Area, California by Samuel Y. Johnson, Ray W. Sliter, Terry R. Bruns, and John L. Chin"},{"id":306365,"rank":6,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2015/1135/ofr20151135_sheet5.pdf","text":"Sheet 5","linkFileType":{"id":1,"text":"pdf"},"description":"Sheet 5","linkHelpText":"Seafloor Character, Offshore of Bolinas Map Area, California By Mercedes D. Erdey and Guy R. Cochrane"},{"id":306378,"rank":20,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1135/coverthb.jpg"},{"id":306372,"rank":13,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/of/2015/1135/ofr20151135_metadata.html","text":"Metadata","linkFileType":{"id":5,"text":"html"},"description":"Metadata"},{"id":306370,"rank":11,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2015/1135/ofr20151135_sheet10.pdf","text":"Sheet 10","linkFileType":{"id":1,"text":"pdf"},"description":"Sheet 10","linkHelpText":"Offshore and Onshore Geology and Geomorphology, Offshore of Bolinas Map Area, California By Samuel Y. Johnson, H. Gary Greene, Michael W. Manson, Stephen R. Hartwell, Charles A. Endris, and Janet T. Watt"},{"id":306374,"rank":16,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/of/2014/1214/","text":"Open-File Report 2014–1214","description":"Open-File Report 2014–1214","linkHelpText":"California State Waters Map Series—Offshore of Half Moon Bay, California, by Guy R. Cochrane and others."},{"id":306373,"rank":15,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/sim/3306/","text":"Scientific Investigations Map 3306","description":"Scientific Investigations Map 3306","linkHelpText":"California State Waters Map Series—Offshore of San Gregorio, California, by Guy R. Cochrane and others."},{"id":306360,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1135/ofr20151135_pamphlet.pdf","text":"Pamphlet","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1135 Pamphlet"},{"id":306415,"rank":14,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/ds/781/","text":"Data Series 781","description":"Data Series 781","linkHelpText":"California State Waters Map Series Data Catalog"}],"scale":"24000","country":"United States","state":"California","city":"Bolinas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.7842,\n 37.8111\n ],\n [\n -122.7842,\n 37.9692\n ],\n [\n -122.6,\n 37.9692\n ],\n [\n -122.6,\n 37.8111\n ],\n [\n -122.7842,\n 37.8111\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/
Migratory behavior in ungulates has declined globally and understanding the causative factors (environmental change vs. human mediated) is needed to formulate effective management strategies. In the Jackson elk herd of northwest Wyoming, demographic differences between summer elk (Cervus elaphus) population segments have led to changes in migratory patterns over a 35-year time period. The proportion of short-distance migrants (SDM) has increased and the proportion of long-distance migrants (LDM) has concurrently declined. The probability of winter-captured elk on the National Elk Refuge being LDM decreased from 0.99 (95% CI = 0.97–1.00) to 0.59 (95% CI = 0.47–0.70) from 1978 to 2012. We tested 4 hypotheses that could contribute toward the decline in the LDM segment: behavioral switching from LDM to SDM, differential survival, harvest availability, and calf recruitment. Switching rates from LDM to SDM were very low (0.2% each elk-year). Survival rates were similar between LDM and SDM, although harvest availability was relatively low for SDM that tended to use areas close to human development during the hunting season. Average summer calf/cow ratios of LDM declined from 42 to 23 calves per 100 cows from 1978–1984 to 2006–2012. Further, during 2006–2012, LDM summer calf/cow ratios were less than half of SDM (23 vs. 47 calves per 100 cows). Our data suggest recruitment is the driving factor behind the declining proportion of LDM in this region. Effectiveness of altering harvest management strategies to conserve the LDM portion of the Jackson elk herd may be limited.
","language":"English","publisher":"Wildlife Society","doi":"10.1002/jwmg.917","usgsCitation":"Cole, E., Foley, A.M., Warren, J.M., Smith, B.L., Dewey, S., Brimeyer, D.G., Fairbanks, W.S., Sawyer, H., and Cross, P.C., 2015, Changing migratory patterns in the Jackson elk herd: Journal of Wildlife Management, v. 79, no. 6, p. 877-886, https://doi.org/10.1002/jwmg.917.","productDescription":"10 p.","startPage":"877","endPage":"886","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059812","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":306429,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.0498046875,\n 42.65820178455667\n ],\n [\n -111.0498046875,\n 44.36313311380771\n ],\n [\n -110.050048828125,\n 44.36313311380771\n ],\n [\n -110.050048828125,\n 42.65820178455667\n ],\n [\n -111.0498046875,\n 42.65820178455667\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"79","issue":"6","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-06-18","publicationStatus":"PW","scienceBaseUri":"55c325a0e4b033ef52106a60","contributors":{"authors":[{"text":"Cole, Eric K. 0000-0002-2229-5853","orcid":"https://orcid.org/0000-0002-2229-5853","contributorId":145755,"corporation":false,"usgs":false,"family":"Cole","given":"Eric K.","affiliations":[{"id":16228,"text":"U.S. Fish and Wildlife Service, National Elk Refuge, PO Box 510, Jackson, WY 83001 USA","active":true,"usgs":false}],"preferred":false,"id":565181,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Foley, Aaron M. afoley@usgs.gov","contributorId":5523,"corporation":false,"usgs":true,"family":"Foley","given":"Aaron","email":"afoley@usgs.gov","middleInitial":"M.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":565180,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Warren, Jeffrey M.","contributorId":16297,"corporation":false,"usgs":true,"family":"Warren","given":"Jeffrey","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":565182,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, Bruce L.","contributorId":145756,"corporation":false,"usgs":false,"family":"Smith","given":"Bruce","email":"","middleInitial":"L.","affiliations":[{"id":16228,"text":"U.S. Fish and Wildlife Service, National Elk Refuge, PO Box 510, Jackson, WY 83001 USA","active":true,"usgs":false}],"preferred":false,"id":565183,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dewey, Sarah","contributorId":145757,"corporation":false,"usgs":false,"family":"Dewey","given":"Sarah","affiliations":[{"id":16229,"text":"National Park Service, Grand Teton National Park, PO Drawer 170, Moose, WY 83012 USA","active":true,"usgs":false}],"preferred":false,"id":565184,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brimeyer, Douglas G.","contributorId":20637,"corporation":false,"usgs":true,"family":"Brimeyer","given":"Douglas","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":565185,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Fairbanks, W. Sue","contributorId":145758,"corporation":false,"usgs":false,"family":"Fairbanks","given":"W.","email":"","middleInitial":"Sue","affiliations":[{"id":16230,"text":"Department of Natural Resource Ecology and Management, Iowa State University, 339 Science Hall II, Ames, Iowa 50011","active":true,"usgs":false}],"preferred":false,"id":565186,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sawyer, Hall","contributorId":39930,"corporation":false,"usgs":false,"family":"Sawyer","given":"Hall","affiliations":[],"preferred":false,"id":565187,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Cross, Paul C. 0000-0001-8045-5213 pcross@usgs.gov","orcid":"https://orcid.org/0000-0001-8045-5213","contributorId":2709,"corporation":false,"usgs":true,"family":"Cross","given":"Paul","email":"pcross@usgs.gov","middleInitial":"C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":565188,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70155172,"text":"70155172 - 2015 - Distribution of near-surface permafrost in Alaska: estimates of present and future conditions","interactions":[],"lastModifiedDate":"2017-01-18T09:59:27","indexId":"70155172","displayToPublicDate":"2015-08-05T12:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"Distribution of near-surface permafrost in Alaska: estimates of present and future conditions","docAbstract":"High-latitude regions are experiencing rapid and extensive changes in ecosystem composition and function as the result of increases in average air temperature. Increasing air temperatures have led to widespread thawing and degradation of permafrost, which in turn has affected ecosystems, socioeconomics, and the carbon cycle of high latitudes. Here we overcome complex interactions among surface and subsurface conditions to map nearsurface permafrost through decision and regression tree approaches that statistically and spatially extend field observations using remotely sensed imagery, climatic data, and thematic maps of a wide range of surface and subsurface biophysical characteristics. The data fusion approach generated medium-resolution (30-m pixels) maps of near-surface (within 1 m) permafrost, active-layer thickness, and associated uncertainty estimates throughout mainland Alaska. Our calibrated models (overall test accuracy of ~85%) were used to quantify changes in permafrost distribution under varying future climate scenarios assuming no other changes in biophysical factors. Models indicate that near-surface permafrost underlies 38% of mainland Alaska and that near-surface permafrost will disappear on 16 to 24% of the landscape by the end of the 21st Century. Simulations suggest that near-surface permafrost degradation is more probable in central regions of Alaska than more northerly regions. Taken together, these results have obvious implications for potential remobilization of frozen soil carbon pools under warmer temperatures. Additionally, warmer and drier conditions may increase fire activity and severity, which may exacerbate rates of permafrost thaw and carbon remobilization relative to climate alone. The mapping of permafrost distribution across Alaska is important for land-use planning, environmental assessments, and a wide-array of geophysical studies.
","language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam","doi":"10.1016/j.rse.2015.07.019","usgsCitation":"Pastick, N.J., Jorgenson, M., Wylie, B.K., Nield, S.J., Johnson, K.D., and Finley, A., 2015, Distribution of near-surface permafrost in Alaska: estimates of present and future conditions: Remote Sensing of Environment, v. 168, p. 301-315, https://doi.org/10.1016/j.rse.2015.07.019.","productDescription":"15 p.","startPage":"301","endPage":"315","numberOfPages":"15","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066157","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":471892,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rse.2015.07.019","text":"Publisher Index Page"},{"id":306428,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -140.9326171875,\n 69.7485511291223\n ],\n [\n -142.9541015625,\n 70.1403642720717\n ],\n [\n -156.6650390625,\n 71.46912418989677\n ],\n [\n -162.2900390625,\n 70.42207856801004\n ],\n [\n -166.81640625,\n 69.06856318696033\n ],\n [\n -167.5634765625,\n 68.25311055665718\n ],\n [\n -168.662109375,\n 65.58572002329473\n ],\n [\n -166.3330078125,\n 60.65164736580915\n ],\n [\n -162.24609375,\n 58.309488840677645\n ],\n [\n -158.642578125,\n 57.89149735271031\n ],\n [\n -166.025390625,\n 54.80068486732233\n ],\n [\n -164.70703125,\n 53.80065082633023\n ],\n [\n -155.7421875,\n 57.040729838360875\n ],\n [\n -154.0283203125,\n 56.145549500679074\n ],\n [\n -151.1279296875,\n 57.7041472343419\n ],\n [\n -150.46875,\n 59.28833169203345\n ],\n [\n -145.5908203125,\n 60.08676274626006\n ],\n [\n -141.7236328125,\n 59.55659188568175\n ],\n [\n -137.5927734375,\n 58.0546319113729\n ],\n [\n -132.2314453125,\n 53.72271667491848\n ],\n [\n -129.0234375,\n 55.60317816902704\n ],\n [\n -135,\n 59.977005492196\n ],\n [\n -137.3291015625,\n 59.24341475839977\n ],\n [\n -138.8671875,\n 60.392147922518845\n ],\n [\n -140.888671875,\n 60.43554230669233\n ],\n [\n -140.9326171875,\n 69.7485511291223\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"168","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55c325a5e4b033ef52106a63","chorus":{"doi":"10.1016/j.rse.2015.07.019","url":"http://dx.doi.org/10.1016/j.rse.2015.07.019","publisher":"Elsevier BV","authors":"Pastick Neal J., Jorgenson M. Torre, Wylie Bruce K., Nield Shawn J., Johnson Kristofer D., Finley Andrew O.","journalName":"Remote Sensing of Environment","publicationDate":"10/2015"},"contributors":{"authors":[{"text":"Pastick, Neal J. 0000-0002-8169-3018 njpastick@usgs.gov","orcid":"https://orcid.org/0000-0002-8169-3018","contributorId":4785,"corporation":false,"usgs":true,"family":"Pastick","given":"Neal","email":"njpastick@usgs.gov","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":564959,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jorgenson, M. Torre","contributorId":34848,"corporation":false,"usgs":true,"family":"Jorgenson","given":"M. Torre","affiliations":[],"preferred":false,"id":564960,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wylie, Bruce K. 0000-0002-7374-1083 wylie@usgs.gov","orcid":"https://orcid.org/0000-0002-7374-1083","contributorId":750,"corporation":false,"usgs":true,"family":"Wylie","given":"Bruce","email":"wylie@usgs.gov","middleInitial":"K.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":564961,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nield, Shawn J.","contributorId":145680,"corporation":false,"usgs":false,"family":"Nield","given":"Shawn","email":"","middleInitial":"J.","affiliations":[{"id":16195,"text":"Natural Resource Conservation Service, U.S. Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":564962,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Johnson, Kristofer D.","contributorId":81027,"corporation":false,"usgs":true,"family":"Johnson","given":"Kristofer","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":564963,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Finley, Andrew O.","contributorId":70666,"corporation":false,"usgs":true,"family":"Finley","given":"Andrew O.","affiliations":[],"preferred":false,"id":564964,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70147550,"text":"sir20155060 - 2015 - A water-budget approach to estimating potential groundwater recharge from two domestic sewage disposal fields in eastern Bernalillo County, New Mexico, 2011-12","interactions":[],"lastModifiedDate":"2015-08-05T09:01:40","indexId":"sir20155060","displayToPublicDate":"2015-08-04T14:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-5060","title":"A water-budget approach to estimating potential groundwater recharge from two domestic sewage disposal fields in eastern Bernalillo County, New Mexico, 2011-12","docAbstract":"Eastern Bernalillo County, New Mexico, is a historically rural area that in recent years has experienced an increase in population and in the construction of new housing units, most of which are not connected to a centralized wastewater treatment system. Increasing water use has raised concerns about the effect of development on the available groundwater resources in the area. During 2011–12, the U.S. Geological Survey, in cooperation with Bernalillo County Public Works Natural Resource Services, used a water-budget approach to quantify the amount of potential groundwater recharge occurring from the domestic sewage (effluent) dosed to the sewage disposal field at two locations—sites A and B—in eastern Bernalillo County, N. Mex. The amount of effluent that is potentially available for groundwater recharge was determined as the mean daily volume of effluent dosed to the disposal field in excess of the mean daily volume of effluent loss from evapotranspiration from the disposal field.
\nDuring this study, the disposal fields at sites A and B received a measured volume of effluent from two-person domestic residences equipped with an onsite low-pressure dosing system. A combined evapotranspiration measurement and modeling technique was used to estimate the amount of evapotranspirative loss from the disposal field and from the surrounding terrain. A portable hemispherical flux chamber was used to measure evapotranspiration at fixed locations on the disposal fields and on the surrounding terrain at sites A and B. Data from hemispherical flux chamber measurements were used to calibrate a Penman-Monteith modeled evapotranspiration rate on the disposal field and on the surrounding terrain at site A from January 1, 2011, to December 31, 2011, and from January 1, 2012, to December 31, 2012, and at site B from January 1, 2011, to December 31, 2011. Micrometeorological and soil data from instrumentation on the disposal fields and on the surrounding terrain at sites A and B were used as input data into the Penman-Monteith equation. The mean potential recharge from disposal field effluent during 2011–12 at sites A and B was 63 percent of the volume of effluent dosed to the disposal field.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155060","collaboration":"Prepared in cooperation with Bernalillo County Public Works Natural Resource Services","usgsCitation":"Crilley, D.M., and Collison, J.W., 2015, A water-budget approach to estimating potential groundwater recharge from two domestic sewage disposal fields in eastern Bernalillo County, New Mexico, 2011–12: U.S. Geological Survey Scientific Investigations Report 2015–5060, 32 p., https://dx.doi.org/10.3133/sir20155060.","productDescription":"Report: ix, 32 p.; Appendices","numberOfPages":"45","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2011-01-01","temporalEnd":"2012-12-31","ipdsId":"IP-035366","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":306379,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5060/coverthb.jpg"},{"id":306381,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5060/sir20155060_appendixes.xlsx","text":"Appendixes","size":"18.9 MB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2015-5060 Appendixes"},{"id":306380,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5060/sir20155060.pdf","text":"Report","size":"5.61 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5060"}],"country":"United States","state":"New Mexico","county":"Bernalillo County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -107.1661376953125,\n 34.854382885097905\n ],\n [\n -107.1661376953125,\n 35.22094130403182\n ],\n [\n -106.13616943359375,\n 35.22094130403182\n ],\n [\n -106.13616943359375,\n 34.854382885097905\n ],\n [\n -107.1661376953125,\n 34.854382885097905\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New Mexico Water Science Center
U.S. Geological Survey
5338 Montgomery Blvd NE, Suite 400
Albuquerque, NM 87109
http://nm.water.usgs.gov/
Depths to selected Cretaceous and lower Tertiary stratigraphic units in the Piceance Basin, northwestern Colorado are presented here for 1,563 wells. This file is updated from the Piceance Basin Oil Shale Database with data for additional new drill holes. Also included in this report are elevations for the base of the Long Point Bed of the Eocene Green River Formation for 347 surface locations obtained by determining locations and elevations from published 7 ½-minute quadrangle maps for the Piceance Basin listed in the “Geologic Maps Used to Generate Long Point Control Points” section.
\nEach entry for the base of the Long Point Bed was obtained at a location where the mapped Long Point Bed intersects a contour line on the published maps. Precision of each elevation is therefore dependent on the precision of the maps and the placement of the mapped contact by the authors.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151036","usgsCitation":"Johnson, R.C., Dietrich, J.D., and Mercier, T.J., 2015: Updated tops file for Cretaceous and lower Tertiary units, Piceance Basin, northwest Colorado: U.S. Geological Survey Open-File Report 2015–1036, 16 p., https://dx.doi.org/10.3133/ofr20151036.","productDescription":"Report: iii, 16 p.; Excel Files","numberOfPages":"19","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-051648","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":306405,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1036/coverthb.jpg"},{"id":306406,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1036/ofr20151036.pdf","text":"Report","size":"3.96 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1036"},{"id":306407,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2015/1036/ofr20151036_supplemental1.xls","text":"Colorado Boreholes and Tops Fieldname Descriptions","size":"40.5 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"Colorado Boreholes and Tops Fieldname Descriptions"},{"id":306408,"rank":4,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2015/1036/ofr20151036_supplemental2.xlsx","text":"Latests Tops Piceance","size":"4.40 MB","linkFileType":{"id":3,"text":"xlsx"},"description":"Latests Tops Piceance"}],"country":"United States","state":"Colorado","otherGeospatial":"Piceance Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.929443359375,\n 38.436379603\n ],\n [\n -108.929443359375,\n 40.455307212131494\n ],\n [\n -106.89697265625,\n 40.455307212131494\n ],\n [\n -106.89697265625,\n 38.436379603\n ],\n [\n -108.929443359375,\n 38.436379603\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Energy Science Center
U.S. Geological Survey
P.O. Box 25046
Denver, CO 80225
http://energy.usgs.gov/
The processes of landscape change are complex, exhibiting spatial variability as well as linear, cyclical, and reversible characteristics. To better understand the various processes that cause transformation, a data aggregation, validation, and attribution approach was developed and applied to an analysis of the Southeastern Coastal Plains (SECP). The approach integrates information from available national land-use, natural disturbance, and land-cover data to efficiently assess spatially-specific changes and causes. Between 2001 and 2006, the processes of change affected 7.8 % of the SECP but varied across small-scale ecoregions. Processes were placed into a simple conceptual framework to explicitly identify the type and direction of change based on three general characteristics: replacement, recurrence, and recovery. Replacement processes, whereby a land use or cover is supplanted by a new land use, including urbanization and agricultural expansion, accounted for approximately 15 % of the extent of change. Recurrent processes that contribute to cyclical changes in land cover, including forest harvest/replanting and fire, accounted for 83 %. Most forest cover changes were recurrent, while the extents of recurrent silviculture and forest replacement processes such as urbanization far exceeded forest recovery processes. The total extent of landscape recovery, from prior land use to natural or semi-natural vegetation cover, accounted for less than 3 % of change. In a region of complex change, increases in transitory grassland and shrubland covers were caused by large-scale intensive plantation silviculture and small-scale activities including mining reclamation. Explicit identification of the process types and dynamics presented here may improve the understanding of land-cover change and landscape trajectory.
","language":"English","publisher":"Elsevier","doi":"10.1007/s00267-015-0574-1","usgsCitation":"Drummond, M.A., Stier, M.P., Auch, R.F., Taylor, J.L., Griffith, G.E., Hester, D.J., Riegle, J.L., Soulard, C.E., and McBeth, J.L., 2015, Assessing landscape change and processes of recurrence, replacement, and recovery in the Southeastern Coastal Plains, USA: Environmental Management, v. 55, no. 5, p. 1252-1271, https://doi.org/10.1007/s00267-015-0574-1.","productDescription":"20 p.","startPage":"1252","endPage":"1271","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060145","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":471896,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s00267-015-0574-1","text":"Publisher Index 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\nThe images provided in this report are Joint Photographic Experts Group (JPEG) images. ExifTool was used to add the following to the header of each photo: time of collection, Global Positioning System (GPS) latitude, GPS longitude, keywords, credit, artist (photographer), caption, copyright, and contact information. The photograph locations are an estimate of the position of the aircraft and do not indicate the location of any feature in the images. These photographs document the state of the coastal features at the time of the survey. Pages containing thumbnail images of the photographs, referred to as contact sheets, were created in 5-minute segments of flight time. These segments can be found on the Photos and Maps page. The photographs can be opened directly with any JPEG-compatible image viewer by clicking on a thumbnail on the contact sheet.
\nTable 1 provides detailed information about the GPS location, name, date, and time for each of the 12,726 photographs taken along with links to each photograph. In addition to the photographs, a Google Earth Keyhole Markup Language (KML) file is provided and can be used can be used to view the images by clicking on the marker and then clicking on either the thumbnail or the link above the thumbnail. The KML files were created using the photographic navigation files
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2015 - ShakeNet: a portable wireless sensor network for instrumenting large civil structures","interactions":[],"lastModifiedDate":"2015-08-24T14:16:02","indexId":"ofr20151134","displayToPublicDate":"2015-08-03T09:30:00","publicationYear":"2015","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":"2015-1134","title":"ShakeNet: a portable wireless sensor network for instrumenting large civil structures","docAbstract":"We report our findings from a U.S. Geological Survey (USGS) National Earthquake Hazards Reduction Program-funded project to develop and test a wireless, portable, strong-motion network of up to 40 triaxial accelerometers for structural health monitoring. The overall goal of the project was to record ambient vibrations for several days from USGS-instrumented structures. Structural health monitoring has important applications in fields like civil engineering and the study of earthquakes. The emergence of wireless sensor networks provides a promising means to such applications. However, while most wireless sensor networks are still in the experimentation stage, very few take into consideration the realistic earthquake engineering application requirements. To collect comprehensive data for structural health monitoring for civil engineers, high-resolution vibration sensors and sufficient sampling rates should be adopted, which makes it challenging for current wireless sensor network technology in the following ways: processing capabilities, storage limit, and communication bandwidth. The wireless sensor network has to meet expectations set by wired sensor devices prevalent in the structural health monitoring community. For this project, we built and tested an application-realistic, commercially based, portable, wireless sensor network called ShakeNet for instrumentation of large civil structures, especially for buildings, bridges, or dams after earthquakes. Two to three people can deploy ShakeNet sensors within hours after an earthquake to measure the structural response of the building or bridge during aftershocks. ShakeNet involved the development of a new sensing platform (ShakeBox) running a software suite for networking, data collection, and monitoring. Deployments reported here on a tall building and a large dam were real-world tests of ShakeNet operation, and helped to refine both hardware and software.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151134","usgsCitation":"Kohler, M.D., Hao, S., Mishra, N., Govindan, R., and Nigbor, R., 2015, ShakeNet—A portable wireless sensor network for instrumenting large civil structures: U.S. Geological Survey Open-File Report 2015–1134, 31 p., https://dx.doi.org/10.3133/ofr20151134.","productDescription":"vi, 31 p.","numberOfPages":"37","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-064108","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":306417,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1134/coverthb.gif"},{"id":305795,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1134/ofr20151134.pdf","text":"Report","size":"3.3 MB"}],"contact":"Earthquake Science Center—Menlo Park, Calif. Office
U.S. Geological Survey
345 Middlefield Road, MS 977
Menlo Park, CA 94025
http://earthquake.usgs.gov/
Gas transport in the unsaturated zone affects contaminant flux and remediation, interpretation of groundwater travel times from atmospheric tracers, and mass budgets of environmentally important gases. Although unsaturated zone transport of gases is commonly treated as dominated by diffusion, the characteristics of transport in deep layered sediments remain uncertain. In this study, we use a multimodel approach to analyze results of a gas-tracer (SF6) test to clarify characteristics of gas transport in deep unsaturated alluvium. Thirty-five separate models with distinct diffusivity structures were calibrated to the tracer-test data and were compared on the basis of Akaike Information Criteria estimates of posterior model probability. Models included analytical and numerical solutions. Analytical models provided estimates of bulk-scale apparent diffusivities at the scale of tens of meters. Numerical models provided information on local-scale diffusivities and feasible lithological features producing the observed tracer breakthrough curves. The combined approaches indicate significant anisotropy of bulk-scale diffusivity, likely associated with high-diffusivity layers. Both approaches indicated that diffusivities in some intervals were greater than expected from standard models relating porosity to diffusivity. High apparent diffusivities and anisotropic diffusivity structures were consistent with previous observations at the study site of rapid lateral transport and limited vertical spreading of gas-phase contaminants. Additional processes such as advective oscillations may be involved. These results indicate that gases in deep, layered unsaturated zone sediments can spread laterally more quickly, and produce higher peak concentrations, than predicted by homogeneous, isotropic diffusion models.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2014WR016055","usgsCitation":"Green, C., Walvoord, M.A., Andraski, B.J., Striegl, R.G., and Stonestrom, D.A., 2015, Multimodel analysis of anisotropic diffusive tracer-gas transport in a deep arid unsaturated zone: Water Resources Research, v. 51, no. 8, p. 6052-6073, https://doi.org/10.1002/2014WR016055.","productDescription":"22 p.","startPage":"6052","endPage":"6073","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057829","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":471899,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2014wr016055","text":"Publisher Index Page"},{"id":306760,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Nevada","otherGeospatial":"Armagosa Desert","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.79977416992188,\n 37.17344871200958\n ],\n [\n -117.20489501953125,\n 36.84336173438382\n ],\n [\n -116.96319580078125,\n 36.62875385775956\n ],\n [\n -116.9110107421875,\n 36.47651531482943\n ],\n [\n -116.66244506835938,\n 36.25756282630298\n ],\n [\n -116.58554077148438,\n 36.25424062786422\n ],\n [\n -116.4111328125,\n 36.274171699242515\n ],\n [\n -116.3067626953125,\n 36.322870678512544\n ],\n [\n -116.25595092773438,\n 36.36269267819595\n ],\n [\n -116.21063232421875,\n 36.61662990355667\n ],\n [\n -116.32049560546875,\n 36.634264115641535\n ],\n [\n -116.46194458007812,\n 36.6320600597707\n ],\n [\n -116.48391723632811,\n 36.6739263393281\n ],\n [\n -116.50039672851561,\n 36.75098882435506\n ],\n [\n -116.5869140625,\n 36.94111143010772\n ],\n [\n -116.66107177734375,\n 37.020098201368114\n ],\n [\n -116.79977416992188,\n 37.17344871200958\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"51","issue":"8","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-08-03","publicationStatus":"PW","scienceBaseUri":"55cf112be4b01487cbfc77bf","chorus":{"doi":"10.1002/2014wr016055","url":"http://dx.doi.org/10.1002/2014wr016055","publisher":"Wiley-Blackwell","authors":"Green Christopher T., Walvoord Michelle A., Andraski Brian J., Striegl Robert G., Stonestrom David A.","journalName":"Water Resources Research","publicationDate":"8/2015"},"contributors":{"authors":[{"text":"Green, Christopher T. ctgreen@usgs.gov","contributorId":146339,"corporation":false,"usgs":true,"family":"Green","given":"Christopher T.","email":"ctgreen@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - 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This is especially true for economically important species such as blackbirds (Icteridae), which cause more than $100 million in crop damages annually in the United States. Using data from the North American Breeding Bird Survey, the National Land Cover Dataset, and the National Climatic Data Center, we modeled effects of regional environmental variables on relative abundance of 3 blackbird species (red-winged blackbird,Agelaius phoeniceus; yellow-headed blackbird, Xanthocephalus xanthocephalus; common grackle, Quiscalus quiscula) in the Prairie Pothole Region of the central United States. We evaluated landscape covariates at 3 logarithmically related spatial scales (1,000 ha, 10,000 ha, and 100,000 ha) and modeled weather variables at the 100,000-ha scale. We constructed models a priori using information from published habitat associations. We fit models with WinBUGS using Markov chain Monte Carlo techniques. Both landscape and weather variables contributed strongly to predicting blackbird relative abundance (95% credibility interval did not overlap 0). Variables with the strongest associations with blackbird relative abundance were the percentage of wetland area and precipitation amount from the year before bird surveys were conducted. The influence of spatial scale appeared small—models with the same variables expressed at different scales were often in the best model subset. This large-scale study elucidated regional effects of weather and landscape variables, suggesting that management strategies aimed at reducing damages caused by these species should consider the broader landscape, including weather effects, because such factors may outweigh the influence of localized conditions or site-specific management actions. The regional species distributional models we developed for blackbirds provide a tool for understanding these broader landscape effects and guiding wildlife management practices to areas that are optimally beneficial. Published 2015. This article is a U.S. Government work and is in the public domain in the USA.
","language":"English","publisher":"Wildlife Society","publisherLocation":"Bethesda, MD","doi":"10.1002/jwmg.912","usgsCitation":"Forcey, G.M., Thogmartin, W.E., Linz, G.M., McKann, P., and Crimmins, S.M., 2015, Spatially explicit modeling of blackbird abundance in the Prairie Pothole Region: Journal of Wildlife Management, v. 79, no. 6, p. 1022-1033, https://doi.org/10.1002/jwmg.912.","productDescription":"12 p.","startPage":"1022","endPage":"1033","numberOfPages":"12","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060021","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":306544,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Iowa, Minnesotta, Montana, Nebraska, North Dakota","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -113.31298828125,\n 48.879167148960214\n ],\n [\n -112.87353515625,\n 48.151428143221224\n ],\n [\n -112.12646484375,\n 48.019324184801185\n ],\n [\n -111.90673828125,\n 47.5913464767971\n ],\n [\n -110.4345703125,\n 47.32393057095941\n ],\n [\n -105.93017578125,\n 47.29413372501023\n ],\n [\n -103.55712890625,\n 47.44294999517949\n ],\n [\n -102.1728515625,\n 47.11499982620772\n ],\n [\n -101.7333984375,\n 46.70973594407157\n ],\n [\n -101.6015625,\n 46.027481852486645\n ],\n [\n -101.3818359375,\n 45.67548217560647\n ],\n [\n -100.96435546875,\n 43.91372326852401\n ],\n [\n -99.140625,\n 41.52502957323801\n ],\n [\n -92.548828125,\n 41.64007838467894\n ],\n [\n -92.3291015625,\n 42.261049162113856\n ],\n [\n -91.95556640625,\n 43.61221676817573\n ],\n [\n -93.2958984375,\n 45.55252525134013\n ],\n [\n -97.75634765625,\n 48.48748647988415\n ],\n [\n -97.998046875,\n 49.023461463214126\n ],\n [\n -113.31298828125,\n 48.879167148960214\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"79","issue":"6","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2015-06-17","publicationStatus":"PW","scienceBaseUri":"55c9cb38e4b08400b1fdb72b","contributors":{"authors":[{"text":"Forcey, Greg M.","contributorId":82835,"corporation":false,"usgs":true,"family":"Forcey","given":"Greg","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":566449,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thogmartin, Wayne E. 0000-0002-2384-4279 wthogmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":2545,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","email":"wthogmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":566448,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Linz, George M.","contributorId":32859,"corporation":false,"usgs":true,"family":"Linz","given":"George","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":566450,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McKann, Patrick C.","contributorId":14940,"corporation":false,"usgs":true,"family":"McKann","given":"Patrick C.","affiliations":[],"preferred":false,"id":566451,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Crimmins, Shawn M. 0000-0001-6229-5543 scrimmins@usgs.gov","orcid":"https://orcid.org/0000-0001-6229-5543","contributorId":5498,"corporation":false,"usgs":true,"family":"Crimmins","given":"Shawn","email":"scrimmins@usgs.gov","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":566452,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70155524,"text":"70155524 - 2015 - Increasing elevation of fire in the Sierra Nevada and implications for forest change","interactions":[],"lastModifiedDate":"2015-08-10T13:11:08","indexId":"70155524","displayToPublicDate":"2015-08-01T14:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Increasing elevation of fire in the Sierra Nevada and implications for forest change","docAbstract":"Fire in high-elevation forest ecosystems can have severe impacts on forest structure, function and biodiversity. Using a 105-year data set, we found increasing elevation extent of fires in the Sierra Nevada, and pose five hypotheses to explain this pattern. Beyond the recognized pattern of increasing fire frequency in the Sierra Nevada since the late 20th century, we find that the upper elevation extent of those fires has also been increasing. Factors such as fire season climate and fuel build up are recognized potential drivers of changes in fire regimes. Patterns of warming climate and increasing stand density are consistent with both the direction and magnitude of increasing elevation of wildfire. Reduction in high elevation wildfire suppression and increasing ignition frequencies may also contribute to the observed pattern. Historical biases in fire reporting are recognized, but not likely to explain the observed patterns. The four plausible mechanistic hypotheses (changes in fire management, climate, fuels, ignitions) are not mutually exclusive, and likely have synergistic interactions that may explain the observed changes. Irrespective of mechanism, the observed pattern of increasing occurrence of fire in these subalpine forests may have significant impacts on their resilience to changing climatic conditions.
Multiple-aperture SAR interferometry (MAI) has demonstrated outstanding measurement accuracy of along-track displacement when compared to pixel-offset-tracking methods; however, measuring slow-moving (cm/year) surface displacement remains a challenge. Stacking of multi-temporal observations is a potential approach to reducing noise and increasing measurement accuracy, but it is difficult to achieve a significant improvement by applying traditional stacking methods to multi-temporal MAI interferograms. This paper proposes an efficient MAI stacking method, where multi-temporal forward- and backward-looking residual interferograms are individually stacked before the MAI interferogram is generated. We tested the performance of this method using ENVISAT data from Kīlauea Volcano, Hawai‘i, where displacement on the order of several centimeters per year is common. By comparing results from the proposed stacking methods with displacements from GPS data, we documented measurement accuracies of about 1.03 and 1.07 cm/year for the descending and ascending tracks, respectively—an improvement of about a factor of two when compared with that from the conventional stacking approach. Three-dimensional surface-displacement maps can be constructed by combining stacked InSAR and MAI observations, which will contribute to a better understanding of a variety of geological phenomena.
","language":"English","publisher":"Springer","publisherLocation":"Berlin, Germany","doi":"10.1007/s00190-014-0786-9","usgsCitation":"Jo, M., Jung, H., Won, J., Poland, M.P., Miklius, A., and Lu, Z., 2015, Measurement of slow-moving along-track displacement from an efficient multiple-aperture SAR interferometry (MAI) stacking: Journal of Geodesy, v. 89, no. 5, p. 411-425, https://doi.org/10.1007/s00190-014-0786-9.","productDescription":"15 p.","startPage":"411","endPage":"425","numberOfPages":"15","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-053829","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":306541,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Kīlauea Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -156.412353515625,\n 18.89329397442673\n ],\n [\n -156.412353515625,\n 20.29053732272331\n ],\n [\n -154.632568359375,\n 20.29053732272331\n ],\n [\n -154.632568359375,\n 18.89329397442673\n ],\n [\n -156.412353515625,\n 18.89329397442673\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"89","issue":"5","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-01-09","publicationStatus":"PW","scienceBaseUri":"55c9cb37e4b08400b1fdb71a","contributors":{"authors":[{"text":"Jo, Min-Jeong","contributorId":146119,"corporation":false,"usgs":false,"family":"Jo","given":"Min-Jeong","email":"","affiliations":[{"id":16586,"text":"Department of Earth System Sciences, Yonsei University, South Korea","active":true,"usgs":false}],"preferred":false,"id":566414,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jung, Hyung-Sup","contributorId":58382,"corporation":false,"usgs":true,"family":"Jung","given":"Hyung-Sup","email":"","affiliations":[],"preferred":false,"id":566415,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Won, Joong-Sun","contributorId":16966,"corporation":false,"usgs":true,"family":"Won","given":"Joong-Sun","email":"","affiliations":[],"preferred":false,"id":566416,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Poland, Michael P. 0000-0001-5240-6123 mpoland@usgs.gov","orcid":"https://orcid.org/0000-0001-5240-6123","contributorId":146118,"corporation":false,"usgs":true,"family":"Poland","given":"Michael","email":"mpoland@usgs.gov","middleInitial":"P.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":566413,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Miklius, Asta 0000-0002-2286-1886 asta@usgs.gov","orcid":"https://orcid.org/0000-0002-2286-1886","contributorId":2060,"corporation":false,"usgs":true,"family":"Miklius","given":"Asta","email":"asta@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":566417,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lu, Zhong 0000-0001-9181-1818 lu@usgs.gov","orcid":"https://orcid.org/0000-0001-9181-1818","contributorId":901,"corporation":false,"usgs":true,"family":"Lu","given":"Zhong","email":"lu@usgs.gov","affiliations":[],"preferred":true,"id":566418,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70155807,"text":"70155807 - 2015 - Optimizing fish sampling for fish - mercury bioaccumulation factors","interactions":[],"lastModifiedDate":"2018-08-09T12:36:18","indexId":"70155807","displayToPublicDate":"2015-08-01T13:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1226,"text":"Chemosphere","active":true,"publicationSubtype":{"id":10}},"title":"Optimizing fish sampling for fish - mercury bioaccumulation factors","docAbstract":"Fish Bioaccumulation Factors (BAFs; ratios of mercury (Hg) in fish (Hgfish) and water (Hgwater)) are used to develop Total Maximum Daily Load and water quality criteria for Hg-impaired waters. Both applications require representative Hgfish estimates and, thus, are sensitive to sampling and data-treatment methods. Data collected by fixed protocol from 11 streams in 5 states distributed across the US were used to assess the effects of Hgfish normalization/standardization methods and fish sample numbers on BAF estimates. Fish length, followed by weight, was most correlated to adult top-predator Hgfish. Site-specific BAFs based on length-normalized and standardized Hgfish estimates demonstrated up to 50% less variability than those based on non-normalized Hgfish. Permutation analysis indicated that length-normalized and standardized Hgfish estimates based on at least 8 trout or 5 bass resulted in mean Hgfish coefficients of variation less than 20%. These results are intended to support regulatory mercury monitoring and load-reduction program improvements.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.chemosphere.2014.12.068","usgsCitation":"Scudder Eikenberry, B.C., Riva-Murray, K., Knightes, C.D., Journey, C.A., Chasar, L., Brigham, M.E., and Bradley, P.M., 2015, Optimizing fish sampling for fish - mercury bioaccumulation factors: Chemosphere, v. 135, p. 467-473, https://doi.org/10.1016/j.chemosphere.2014.12.068.","productDescription":"7 p.","startPage":"467","endPage":"473","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-044433","costCenters":[{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":471902,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.chemosphere.2014.12.068","text":"Publisher Index Page"},{"id":306540,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"135","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55c9cb37e4b08400b1fdb71e","contributors":{"authors":[{"text":"Scudder Eikenberry, Barbara C.","contributorId":63771,"corporation":false,"usgs":true,"family":"Scudder Eikenberry","given":"Barbara","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":572326,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Riva-Murray, Karen 0000-0001-6683-2238 krmurray@usgs.gov","orcid":"https://orcid.org/0000-0001-6683-2238","contributorId":2984,"corporation":false,"usgs":true,"family":"Riva-Murray","given":"Karen","email":"krmurray@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":566400,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Knightes, Christopher D.","contributorId":32666,"corporation":false,"usgs":true,"family":"Knightes","given":"Christopher","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":566403,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Journey, Celeste A. 0000-0002-2284-5851 cjourney@usgs.gov","orcid":"https://orcid.org/0000-0002-2284-5851","contributorId":2617,"corporation":false,"usgs":true,"family":"Journey","given":"Celeste","email":"cjourney@usgs.gov","middleInitial":"A.","affiliations":[{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":false,"id":566404,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chasar, Lia C.","contributorId":52905,"corporation":false,"usgs":true,"family":"Chasar","given":"Lia C.","affiliations":[],"preferred":false,"id":566399,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brigham, Mark E. 0000-0001-7412-6800 mbrigham@usgs.gov","orcid":"https://orcid.org/0000-0001-7412-6800","contributorId":1840,"corporation":false,"usgs":true,"family":"Brigham","given":"Mark","email":"mbrigham@usgs.gov","middleInitial":"E.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":566401,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bradley, Paul M. 0000-0001-7522-8606 pbradley@usgs.gov","orcid":"https://orcid.org/0000-0001-7522-8606","contributorId":361,"corporation":false,"usgs":true,"family":"Bradley","given":"Paul","email":"pbradley@usgs.gov","middleInitial":"M.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":566402,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70155900,"text":"70155900 - 2015 - A comparison of auditory brainstem responses across diving bird species","interactions":[],"lastModifiedDate":"2018-02-07T10:35:53","indexId":"70155900","displayToPublicDate":"2015-08-01T11:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2225,"text":"Journal of Comparative Physiology A","active":true,"publicationSubtype":{"id":10}},"title":"A comparison of auditory brainstem responses across diving bird species","docAbstract":"There is little biological data available for diving birds because many live in hard-to-study, remote habitats. Only one species of diving bird, the black-footed penguin (Spheniscus demersus), has been studied in respect to auditory capabilities (Wever et al., Proc Natl Acad Sci USA 63:676–680, 1969). We, therefore, measured in-air auditory threshold in ten species of diving birds, using the auditory brainstem response (ABR). The average audiogram obtained for each species followed the U-shape typical of birds and many other animals. All species tested shared a common region of the greatest sensitivity, from 1000 to 3000 Hz, although audiograms differed significantly across species. Thresholds of all duck species tested were more similar to each other than to the two non-duck species tested. The red-throated loon (Gavia stellata) and northern gannet (Morus bassanus) exhibited the highest thresholds while the lowest thresholds belonged to the duck species, specifically the lesser scaup (Aythya affinis) and ruddy duck (Oxyura jamaicensis). Vocalization parameters were also measured for each species, and showed that with the exception of the common eider (Somateria mollisima), the peak frequency, i.e., frequency at the greatest intensity, of all species' vocalizations measured here fell between 1000 and 3000 Hz, matching the bandwidth of the most sensitive hearing range.
","language":"English","publisher":"Springer","publisherLocation":"New York, NY","doi":"10.1007/s00359-015-1024-5","usgsCitation":"Crowell, S.E., Berlin, A., Carr, C.E., Olsen, G.H., Therrien, R.E., Yannuzzi, S.E., and Ketten, D.R., 2015, A comparison of auditory brainstem responses across diving bird species: Journal of Comparative Physiology A, v. 201, no. 8, p. 803-815, https://doi.org/10.1007/s00359-015-1024-5.","productDescription":"13 p.","startPage":"803","endPage":"815","numberOfPages":"13","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066076","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":471904,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://doi.org/10.1007/s00359-015-1024-5","text":"External Repository"},{"id":306780,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"201","issue":"8","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2015-07-09","publicationStatus":"PW","scienceBaseUri":"55d305aae4b0518e35468ccf","contributors":{"authors":[{"text":"Crowell, Sara E.","contributorId":146550,"corporation":false,"usgs":false,"family":"Crowell","given":"Sara","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":568216,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Berlin, Alicia aberlin@usgs.gov","contributorId":4139,"corporation":false,"usgs":true,"family":"Berlin","given":"Alicia","email":"aberlin@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":566700,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Carr, Catherine E.","contributorId":146232,"corporation":false,"usgs":false,"family":"Carr","given":"Catherine","email":"","middleInitial":"E.","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":566701,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Olsen, Glenn H. 0000-0002-7188-6203 golsen@usgs.gov","orcid":"https://orcid.org/0000-0002-7188-6203","contributorId":40918,"corporation":false,"usgs":true,"family":"Olsen","given":"Glenn","email":"golsen@usgs.gov","middleInitial":"H.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":566702,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Therrien, Ronald E.","contributorId":146233,"corporation":false,"usgs":false,"family":"Therrien","given":"Ronald","email":"","middleInitial":"E.","affiliations":[{"id":16639,"text":"EcoSmart Research","active":true,"usgs":false}],"preferred":false,"id":566703,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Yannuzzi, Sally E.","contributorId":146234,"corporation":false,"usgs":false,"family":"Yannuzzi","given":"Sally","email":"","middleInitial":"E.","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":566704,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ketten, Darlene R.","contributorId":146235,"corporation":false,"usgs":false,"family":"Ketten","given":"Darlene","email":"","middleInitial":"R.","affiliations":[{"id":6706,"text":"Woods Hole Oceanographic Institution,","active":true,"usgs":false}],"preferred":false,"id":566705,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70155190,"text":"70155190 - 2015 - Sources of high-chloride water and managed aquifer recharge in an alluvial aquifer in California, USA","interactions":[],"lastModifiedDate":"2016-09-04T17:51:09","indexId":"70155190","displayToPublicDate":"2015-08-01T11:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1923,"text":"Hydrogeology Journal","active":true,"publicationSubtype":{"id":10}},"title":"Sources of high-chloride water and managed aquifer recharge in an alluvial aquifer in California, USA","docAbstract":"As a result of pumping in excess of recharge, water levels in alluvial aquifers within the Eastern San Joaquin Groundwater Subbasin, 130 km east of San Francisco (California, USA), declined below sea level in the early 1950s and have remained so to the present. Chloride concentrations in some wells increased during that time and exceeded the US Environmental Protection Agency’s secondary maximum contaminant level of 250 mg/L, resulting in removal of some wells from service. Sources of high-chloride water include irrigation return in 16 % of sampled wells and water from delta sediments and deeper groundwater in 50 % of sampled wells. Chloride concentrations resulting from irrigation return commonly did not exceed 100 mg/L, although nitrate concentrations were as high as 25 mg/L as nitrogen. Chloride concentrations ranged from less than 100–2,050 mg/L in wells affected by water from delta sediments and deeper groundwater. Sequential electromagnetic logs show movement of high-chloride water from delta sediments to pumping wells through permeable interconnected aquifer layers. δD and δ18O data show most groundwater originated as recharge along the front of the Sierra Nevada, but tritium and carbon-14 data suggest recharge rates in this area are low and have decreased over recent geologic time. Managed aquifer recharge at two sites show differences in water-level responses to recharge and in the physical movement of recharged water with depth related to subsurface geology. Well-bore flow logs also show rapid movement of water from recharge sites through permeable interconnected aquifer layers to pumping wells.
","language":"English","publisher":"International Association of Hydrogeologists","publisherLocation":"Berlin","doi":"10.1007/s10040-015-1277-7","usgsCitation":"O’Leary, D., Izbicki, J., and Metzger, L.F., 2015, Sources of high-chloride water and managed aquifer recharge in an alluvial aquifer in California, USA: Hydrogeology Journal, v. 23, no. 7, p. 1515-1533, https://doi.org/10.1007/s10040-015-1277-7.","productDescription":"19 p.","startPage":"1515","endPage":"1533","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-041824","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":471908,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10040-015-1277-7","text":"Publisher Index Page"},{"id":306308,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Eastern San Joaquin Groundwater Subbasin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.25885009765625,\n 38.20797181420939\n ],\n [\n -121.3604736328125,\n 38.257593120395356\n ],\n [\n -121.42913818359376,\n 38.272688535980976\n ],\n [\n -121.50054931640625,\n 38.27053224010455\n ],\n [\n -121.58294677734374,\n 38.225235239076824\n ],\n [\n -121.607666015625,\n 38.16047628099622\n ],\n [\n -121.59393310546875,\n 38.04592811939912\n ],\n [\n -121.55273437499999,\n 37.974514992024616\n ],\n [\n -121.46759033203125,\n 37.920367835943516\n ],\n [\n -121.42913818359376,\n 37.8553385894982\n ],\n [\n -121.40991210937499,\n 37.77722770873696\n ],\n [\n -121.39343261718749,\n 37.694687703235914\n ],\n [\n -121.30828857421875,\n 37.63380988687154\n ],\n [\n -121.19842529296875,\n 37.63380988687154\n ],\n [\n -121.04736328125,\n 37.67729913640427\n ],\n [\n -120.860595703125,\n 37.70120736474139\n ],\n [\n -120.5474853515625,\n 37.8271414168374\n ],\n [\n -120.487060546875,\n 37.90736658145496\n ],\n [\n -120.42938232421874,\n 37.97234987199528\n ],\n [\n -120.47332763671874,\n 38.0545795282119\n ],\n [\n -120.55297851562499,\n 38.16047628099622\n ],\n [\n -120.64910888671876,\n 38.272688535980976\n ],\n [\n -120.7342529296875,\n 38.3287297527893\n ],\n [\n -120.89355468749999,\n 38.33519326105276\n ],\n [\n -121.00616455078124,\n 38.33088431959968\n ],\n [\n -121.17919921875001,\n 38.257593120395356\n ],\n [\n -121.25885009765625,\n 38.20797181420939\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"23","issue":"7","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2015-07-03","publicationStatus":"PW","scienceBaseUri":"55c090b5e4b033ef521042b9","contributors":{"authors":[{"text":"O’Leary, David 0000-0001-9888-1739 doleary@usgs.gov","orcid":"https://orcid.org/0000-0001-9888-1739","contributorId":139900,"corporation":false,"usgs":true,"family":"O’Leary","given":"David","email":"doleary@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":565030,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Izbicki, John A. 0000-0003-0816-4408 jaizbick@usgs.gov","orcid":"https://orcid.org/0000-0003-0816-4408","contributorId":1375,"corporation":false,"usgs":true,"family":"Izbicki","given":"John A.","email":"jaizbick@usgs.gov","affiliations":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"preferred":false,"id":565031,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Metzger, Loren F. 0000-0003-2454-2966 lmetzger@usgs.gov","orcid":"https://orcid.org/0000-0003-2454-2966","contributorId":1378,"corporation":false,"usgs":true,"family":"Metzger","given":"Loren","email":"lmetzger@usgs.gov","middleInitial":"F.","affiliations":[],"preferred":true,"id":565032,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70156538,"text":"70156538 - 2015 - Combining waterfowl and breeding bird survey data to estimate wood duck breeding population size in the Atlantic Flyway","interactions":[],"lastModifiedDate":"2018-08-21T16:32:36","indexId":"70156538","displayToPublicDate":"2015-08-01T11:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Combining waterfowl and breeding bird survey data to estimate wood duck breeding population size in the Atlantic Flyway","docAbstract":"We combined data from the Atlantic Flyway Breeding Waterfowl Survey (AFBWS) and the North American Breeding Bird Survey (BBS) to estimate the number of wood ducks (Aix sponsa) in the United States portion of the Atlantic Flyway from 1993 to 2013. The AFBWS is a plot-based survey that covers most of the northern and central portions of the Flyway; when analyzed with adjustments for survey time of day effects, these data can be used to estimate population size. The BBS provides an index of wood duck abundance along roadside routes. Although factors influencing change in BBS counts over time can be controlled in BBS analysis, BBS indices alone cannot be used to derive population size estimates. We used AFBWS data to scale BBS indices for Bird Conservation Regions (BCR), basing the scaling factors on the ratio of estimated AFBWS population sizes to regional BBS indices for portions of BCRs that were common to both surveys. We summed scaled BBS results for portions of the Flyway not covered by the AFBWS with AFBWS population estimates to estimate a mean yearly total of 1,295,875 (mean 95% CI: 1,013,940–1,727,922) wood ducks. Scaling factors varied among BCRs from 16.7 to 148.0; the mean scaling factor was 68.9 (mean 95% CI: 53.5–90.9). Flyway-wide, population estimates from the combined analysis were consistent with alternative estimates derived from harvest data, and also provide population estimates within states and BCRs. We recommend their use in harvest and habitat management within the Atlantic Flyway.
","language":"English","publisher":"Wildlife Society","doi":"10.1002/jwmg.938","usgsCitation":"Zimmerman, G.S., Sauer, J.R., Fleming, K., Link, W.A., and Garrettson, P.R., 2015, Combining waterfowl and breeding bird survey data to estimate wood duck breeding population size in the Atlantic Flyway: Journal of Wildlife Management, v. 79, no. 7, p. 1051-1061, https://doi.org/10.1002/jwmg.938.","productDescription":"11 p.","startPage":"1051","endPage":"1061","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065594","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":307520,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Connecticut, Delaware, Maryland, Massachusetts, New Hampshire, New Jersey, New York, Pennsylvania, Rhode Island, Vermont, Virginia","otherGeospatial":"Atlantic Flyway","geographicExtents":"{\n \"type\": 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Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":569434,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Garrettson, Pamela R.","contributorId":146921,"corporation":false,"usgs":false,"family":"Garrettson","given":"Pamela","email":"","middleInitial":"R.","affiliations":[{"id":16183,"text":"FWS Papahānaumokuākea Marine National Monument","active":true,"usgs":false}],"preferred":false,"id":569435,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70155504,"text":"70155504 - 2015 - Screening tool to evaluate the vulnerability of down-gradient receptors to groundwater contaminants from uncapped landfills","interactions":[],"lastModifiedDate":"2015-08-10T10:00:42","indexId":"70155504","displayToPublicDate":"2015-08-01T11:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3707,"text":"Waste Management","active":true,"publicationSubtype":{"id":10}},"title":"Screening tool to evaluate the vulnerability of down-gradient receptors to groundwater contaminants from uncapped landfills","docAbstract":"A screening tool for quantifying levels of concern for contaminants detected in monitoring wells on or near landfills to down-gradient receptors (streams, wetlands and residential lots) was developed and evaluated. The tool uses Quick Domenico Multi-scenario (QDM), a spreadsheet implementation of Domenico-based solute transport, to estimate concentrations of contaminants reaching receptors under steady-state conditions from a constant-strength source. Unlike most other available Domenico-based model applications, QDM calculates the time for down-gradient contaminant concentrations to approach steady state and appropriate dispersivity values, and allows for up to fifty simulations on a single spreadsheet. Sensitivity of QDM solutions to critical model parameters was quantified. The screening tool uses QDM results to categorize landfills as having high, moderate and low levels of concern, based on contaminant concentrations reaching receptors relative to regulatory concentrations. The application of this tool was demonstrated by assessing levels of concern (as defined by the New Jersey Pinelands Commission) for thirty closed, uncapped landfills in the New Jersey Pinelands National Reserve, using historic water-quality data from monitoring wells on and near landfills and hydraulic parameters from regional flow models. Twelve of these landfills are categorized as having high levels of concern, indicating a need for further assessment. This tool is not a replacement for conventional numerically-based transport model or other available Domenico-based applications, but is suitable for quickly assessing the level of concern posed by a landfill or other contaminant point source before expensive and lengthy monitoring or remediation measures are taken. In addition to quantifying the level of concern using historic groundwater-monitoring data, the tool allows for archiving model scenarios and adding refinements as new data become available.
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