The western sand darter, Ammocrypta clara, and the eastern sand darter, A. pellucida, are sand-dwelling fishes that have undergone range-wide population declines, presumably owing to habitat loss. Habitat use studies have been conducted for the eastern sand darter, but literature on the western sand darter remains sparse. To evaluate substrate selection and preference, western and eastern sand darters were collected from the Elk River, West Virginia, one of the few remaining rivers where both species occur sympatrically. In the laboratory, individuals were given the choice to bury into five equally available and randomly positioned substrates ranging from fine sand to granule gravel (0.12–4.0 mm). The western sand darter selected for coarse and medium sand, while the eastern sand darter was more of a generalist selecting for fine, medium, and coarse sand. Substrate selection was significantly different (p = 0.02) between species in the same environment, where the western sand darter preferred coarser substrate more often compared to the eastern sand darter. Habitat degradation is often a limiting factor for many species of rare freshwater fish, and results from this study suggest that western and eastern sand darters may respond differently to variations in benthic substrate composition.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/02705060.2017.1319880","usgsCitation":"Thompson, P., Welsh, S.A., Rizzo, A.A., and Smith, D.M., 2017, Effect of substrate size on sympatric sand darter benthic habitat preferences: Journal of Freshwater Ecology, v. 32, no. 1, p. 455-465, https://doi.org/10.1080/02705060.2017.1319880.","productDescription":"11 p.","startPage":"455","endPage":"465","ipdsId":"IP-079713","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":469880,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/02705060.2017.1319880","text":"Publisher Index Page"},{"id":348211,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"West Virginia","otherGeospatial":"Elk River","volume":"32","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-05-22","publicationStatus":"PW","scienceBaseUri":"5a003150e4b0531197b5a746","contributors":{"authors":[{"text":"Thompson, Patricia A. pathompson@usgs.gov","contributorId":5249,"corporation":false,"usgs":true,"family":"Thompson","given":"Patricia A.","email":"pathompson@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":719298,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Welsh, Stuart A. 0000-0003-0362-054X swelsh@usgs.gov","orcid":"https://orcid.org/0000-0003-0362-054X","contributorId":1483,"corporation":false,"usgs":true,"family":"Welsh","given":"Stuart","email":"swelsh@usgs.gov","middleInitial":"A.","affiliations":[{"id":205,"text":"Cooperative Research Units","active":false,"usgs":true}],"preferred":false,"id":720416,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rizzo, Austin A.","contributorId":191439,"corporation":false,"usgs":false,"family":"Rizzo","given":"Austin","email":"","middleInitial":"A.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":720417,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, Dustin M.","contributorId":171829,"corporation":false,"usgs":false,"family":"Smith","given":"Dustin","email":"","middleInitial":"M.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":720418,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70191541,"text":"70191541 - 2017 - Coal-tar-based pavement sealants—a potent source of PAHs","interactions":[],"lastModifiedDate":"2017-10-17T11:03:27","indexId":"70191541","displayToPublicDate":"2017-05-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2593,"text":"Lakeline","active":true,"publicationSubtype":{"id":10}},"title":"Coal-tar-based pavement sealants—a potent source of PAHs","docAbstract":"P avement sealants are applied to the asphalt pavement of many parking lots, driveways, and even playgrounds in North America (Figure 1), where, when first applied, they render the pavement glossy black and looking like new. Sealant products used commercially in the central, eastern, and northern United States typically are coal-tarbased, whereas those used in the western United States typically are asphalt-based. Although the products look similar, they are chemically different. Coal-tarbased pavement sealants typically are 25-35 percent (by weight) coal tar or coal-tar pitch, materials that are known human carcinogens and that contain high concentrations of polycyclic aromatic hydrocarbons (PAHs) and related chemicals (unless otherwise noted, all Figure 1. Pavement sealant is commonly used to seal parking lots, playgrounds, and driveways throughout the United States. Sealants used in the central, northern, eastern, and southern United States typically contain coal tar or coal-tar pitch, both of which are known human carcinogens. Photos by the U.S. Geological Survey. data in this article are from Mahler et al. 2012 and references therein).
","language":"English","publisher":"North American Lake Management Society","usgsCitation":"Mahler, B., and Van Metre, P., 2017, Coal-tar-based pavement sealants—a potent source of PAHs: Lakeline, v. 37, no. 1, p. 13-18.","productDescription":"6 p.","startPage":"13","endPage":"18","ipdsId":"IP-082495","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":346679,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":346647,"type":{"id":15,"text":"Index Page"},"url":"https://www.nalms.org/lakeline-magazine/"}],"volume":"37","issue":"1","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59e71691e4b05fe04cd331a9","contributors":{"authors":[{"text":"Mahler, Barbara 0000-0002-9150-9552 bjmahler@usgs.gov","orcid":"https://orcid.org/0000-0002-9150-9552","contributorId":1249,"corporation":false,"usgs":true,"family":"Mahler","given":"Barbara","email":"bjmahler@usgs.gov","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":712708,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Van Metre, Peter C. 0000-0001-7564-9814 pcvanmet@usgs.gov","orcid":"https://orcid.org/0000-0001-7564-9814","contributorId":172246,"corporation":false,"usgs":true,"family":"Van Metre","given":"Peter C.","email":"pcvanmet@usgs.gov","affiliations":[{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":712709,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70074784,"text":"sim2932A - 2017 - Geologic map of the northeast flank of Mauna Loa volcano, Island of Hawai'i, Hawaii","interactions":[],"lastModifiedDate":"2024-05-23T22:01:59.158496","indexId":"sim2932A","displayToPublicDate":"2017-05-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2932-A","displayTitle":"Geologic Map of the Northeast Flank of Mauna Loa Volcano, Island of Hawai'i, Hawaii","title":"Geologic map of the northeast flank of Mauna Loa volcano, Island of Hawai'i, Hawaii","docAbstract":"Mauna Loa, the largest volcano on Earth, has erupted 33 times since written descriptions became available in 1832. Some eruptions were preceded by only brief seismic unrest, while others followed several months to a year of increased seismicity.
The majority of the eruptions of Mauna Loa began in the summit area (>12,000-ft elevation; Lockwood and Lipman, 1987); yet the Northeast Rift Zone (NERZ) was the source of eight flank eruptions since 1843 (table 1). This zone extends from the 13,680-ft-high summit towards Hilo (population ~60,000), the second largest city in the State of Hawaii. Although most of the source vents are farther than 30 km away, the 1880 flow from one of the vents extends into Hilo, nearly reaching Hilo Bay. The city is built entirely on flows erupted from the NERZ, most older than that erupted in 1843.
Once underway, Mauna Loa's eruptions can produce lava flows that reach the sea in less than 24 hours, severing roads and utilities in their path. For example, lava flows erupted from the Southwest Rift Zone (SWRZ) in 1950 advanced at an average rate of 9.3 km per hour, and all three lobes reached the ocean within approximately 24 hours (Finch and Macdonald, 1953). The flows near the eruptive vents must have traveled even faster.
In terms of eruption frequency, pre-eruption warning, and rapid flow emplacement, Mauna Loa poses an enormous volcanic-hazard threat to the Island of Hawai‘i. By documenting past activity and by alerting the public and local government officials of our findings, we can anticipate the volcanic hazards and substantially mitigate the risks associated with an eruption of this massive edifice.
From the geologic record, we can deduce several generalized facts about the geologic history of the NERZ. The middle to the uppermost section of the rift zone were more active in the past 4,000 years than the lower part, perhaps due to buttressing of the lower east rift zone by Mauna Kea and Kīlauea volcanoes. The historical flows that erupted on the north flank of the rift zone, which is more vulnerable to inundation, advanced toward Hilo. Lockwood (1990) noted that the vents of historical activity are migrating to the south. The volcano appears to have a self-regulating mechanism that evenly distributes long-term activity across its flanks. The geologic record also supports this notion; the time prior to the historical period (Age Group 1, orange units, pre-A.D. 1843–1,000 yr B.P.; see map sheet 2) is dominated by activity on the south side of the NERZ.
The NERZ trends N. 65° E. and is about 40 km long and 2–4 km wide, narrowing at the summit caldera. It becomes diffuse (6–7 km wide) at its down-rift terminus, at the approximately 3,400-ft elevation. Its constructional crest is marked by low spatter ramparts and by spatter cones as high as 60 m. Subparallel eruptive fissures and ground cracks cut vent deposits and flows in and near the rift crest. Lava typically flows to the north, east, or south, depending on vent location relative to the rift crest.
Encompassing 1,140 km2 of the northeast flank of Mauna Loa from the 10,880-ft elevation to sea level, the map covers the area from Hilo to Volcano on the east and includes the rift zone from Puu Ulaula quadrangle in the southwest to Hilo in the northeast. The distribution of 105 eruptive units (flows)—separated into 15 age groups ranging from more than 30,000 years B.P. to A.D. 1984—are shown, as well as the relations of volcanic and surficial sedimentary deposits. This map incorporates previously reported work published in generalized small-scale maps (Lockwood and Lipman, 1987; Buchanan-Banks, 1993; Lockwood, 1995; and Wolfe and Morris, 1996).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim2932A","usgsCitation":"Trusdell, F.A., and Lockwood, J.P., 2017, Geologic map of the northeast flank of Mauna Loa volcano, Island of Hawai'i, Hawaii: U.S. Geological Survey Scientific Investigations Map 2932–A, pamphlet 25 p., 2 sheets, scale 1:50,000, https://doi.org/10.3133/sim2932A.","productDescription":"Pamphlet: ii, 25 p.; 2 Sheets: 54.66 x 29.17 inches and 46.11 x 28.85 inches; Data Table; Metadata; Read Me; Geospatial Data","ipdsId":"IP-054350","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":429219,"rank":11,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sim2932E","text":"Scientific Investigations Map 2932-E","linkHelpText":"- Geologic Map of the Northwest Flank of Mauna Loa Volcano, Island of Hawai‘i, Hawaii"},{"id":374329,"rank":10,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sim2932C","text":"Scientific Investigations Map 2932-C","linkHelpText":"- Geologic Map of the Southern Flank of Mauna Loa Volcano, Island of Hawai‘i, Hawaii"},{"id":374328,"rank":9,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sim2932B","text":"Scientific Investigations Map 2932-B","linkHelpText":"- Geologic Map of the Central-Southeast Flank of Mauna Loa Volcano, Island of Hawai‘i, Hawaii"},{"id":340642,"rank":7,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sim/2932/a/sim2932a_geospatialdata.zip","text":"Geospatial data","size":"6.6 MB","linkFileType":{"id":6,"text":"zip"},"description":"SIM 2932-A Geospatial data"},{"id":340641,"rank":6,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sim/2932/a/sim2932a_geochemical_data_table_2017.xlsx","text":"Geochemical data table 2017","size":"40 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIM 2932-A Geochemical data table 2017"},{"id":340640,"rank":5,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sim/2932/a/sim2932a_metadata.zip","size":"217 KB","linkFileType":{"id":6,"text":"zip"},"description":"SIM 2932-A Metadata"},{"id":340638,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/2932/a/sim2932a_sheet1.pdf","text":"Sheet 1","size":"20.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 2932-A Sheet 1"},{"id":340637,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/2932/a/sim2932a_pamphlet.pdf","text":"Pamphlet","size":"2.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 2932-A Pamphlet"},{"id":340636,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/2932/a/coverthb.jpg"},{"id":340643,"rank":8,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sim/2932/a/sim2932a_readme.txt","size":"2 KB","linkFileType":{"id":2,"text":"txt"},"description":"SIM 2932-A Readme"},{"id":340639,"rank":4,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/2932/a/sim2932a_sheet2.pdf","text":"Sheet 2","size":"13.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 2932-A Sheet 2"}],"country":"United States","state":"Hawaii","otherGeospatial":"Island of Hawai'i, Mauna Loa Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.5,\n 19.5\n ],\n [\n -154.75,\n 19.5\n ],\n [\n -154.75,\n 19.75\n ],\n [\n -155.5,\n 19.75\n ],\n [\n -155.5,\n 19.5\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contact HVO
Volcano Science Center, Hawaiian Volcano Observatory
U.S. Geological Survey
In 2008, the U.S. Congress authorized the establishment of the National Climate Change and Wildlife Science Center (NCCWSC) within the U.S. Department of Interior (DOI). Housed administratively within the U.S. Geological Survey (USGS), NCCWSC is part of the DOI’s ongoing mission to meet the challenges of climate change and its effects on wildlife and aquatic resources. From 2010 through 2012, NCCWSC established eight regional DOI Climate Science Centers (CSCs). Each of these regional CSCs operated with the mission to “synthesize and integrate climate change impact data and develop tools that the Department’s managers and partners can use when managing the Department’s land, water, fish and wildlife, and cultural heritage resources” (Salazar 2009). The model developed by NCCWSC for the regional CSCs employed a dual approach of a federal USGS-staffed component and a parallel host-university component established competitively through a 5-year cooperative agreement with NCCWSC. At the conclusion of this 5-year agreement, a review of each CSC was undertaken, with the Southeast Climate Science Center (SE CSC) review in February 2016.
The SE CSC is hosted by North Carolina State University (NCSU) in Raleigh, North Carolina, and is physically housed within the NCSU Department of Applied Ecology along with the Center for Applied Aquatic Ecology, the North Carolina Cooperative Fish and Wildlife Research Unit (CFWRU), and the North Carolina Agromedicine Institute. The U.S. Department of Agriculture Southeast Regional Climate Hub is based at NCSU as is the National Oceanic and Atmospheric Administration (NOAA) Southeast Regional Climate Center, the North Carolina Institute for Climate Studies, the North Carolina Wildlife Resources Commission, the NOAA National Weather Service, the State Climate Office of North Carolina, and the U.S. Forest Service Eastern Forest Environmental Threat Assessment Center. This creates a strong core of organizations operating in close proximity focused on climate issues.
The geographic area covered by the SE CSC represents all or part of 16 states and the Caribbean Islands and has overlapping boundaries with seven Landscape Conservation Cooperatives (LCCs): Appalachian LCC, Eastern Tallgrass Prairie and Big Rivers LCC, Gulf Coast Prairie LCC, Gulf Coastal Plains and Ozarks LCC, Peninsular Florida LCC, South Atlantic LCC, and Caribbean LCC. The SE CSC region also encompasses 134 U.S. Fish and Wildlife Service refuges and 89 National Park Service (NPS) units and is home to 11 federally recognized and 54 state recognized tribes.
The U.S. Geological Survey conducted a study, in cooperation with the Georgia Environmental Protection Division, to define the hydrologic properties of the Claiborne aquifer and evaluate its connection with the Upper Floridan aquifer in southwest Georgia. The effort involved collecting and compiling hydrologic data from the aquifer in subarea 4 of southwestern Georgia. Data collected for this study include borehole geophysical logs in 7 wells, and two 72-hour aquifer tests to determine aquifer properties.
The top of the Claiborne aquifer extends from an altitude of about 200 feet above the North American Vertical Datum of 1988 (NAVD 88) in Terrell County to 402 feet below NAVD 88 in Decatur County, Georgia. The base of the aquifer extends from an altitude of about 60 feet above NAVD 88 in eastern Sumter County to about 750 feet below NAVD 88 in Decatur County. Aquifer thickness ranges from about 70 feet in eastern Early County to 400 feet in Decatur County.
The transmissivity of the Claiborne aquifer, determined from two 72-hour aquifer tests, was estimated to be 1,500 and 700 feet squared per day in Mitchell and Early Counties, respectively. The storage coefficient was estimated to be 0.0006 and 0.0004 for the same sites, respectively. Aquifer test data from Mitchell County indicate a small amount of leakage occurred during the test. Groundwater-flow models suggest that the source of the leakage was the underlying Clayton aquifer, which produced about 2.5 feet of drawdown in response to pumping in the Claiborne aquifer. The vertical hydraulic conductivity of the confining unit between the Claiborne and Clayton aquifers was simulated to be about 0.02 foot per day.
Results from the 72-hour aquifer tests run for this study indicated no interconnection between the Claiborne and overlying Upper Floridan aquifers at the two test sites. Additional data are needed to monitor the effects that increased withdrawals from the Claiborne aquifer may have on future water resources.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175017","collaboration":"Prepared in cooperation with the Georgia Environmental Protection Division","usgsCitation":"Gordon, D.W., and Gonthier, Gerald, 2017, Hydrology of the Claiborne aquifer and interconnection with the Upper Floridan aquifer in southwest Georgia: U.S. Geological Survey Scientific Investigations Report 2017–5017, 49 p., https://doi.org/10.3133/sir20175017.","productDescription":"x, 49 p.","numberOfPages":"64","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-076880","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":339811,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5017/sir20175017.pdf","text":"Report","size":"8.60 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5017"},{"id":339810,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5017/coverthb.jpg"},{"id":339835,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7B8569W","text":"USGS data release","description":"USGS data release","linkHelpText":"Data collected for Claiborne aquifer study in southwestern Georgia during 2015 to 2016"}],"country":"United States","state":"Georgia","otherGeospatial":"Claiborne Aquifer","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -85.1495361328125,\n 30.60482195075795\n ],\n [\n -83.748779296875,\n 30.60482195075795\n ],\n [\n -83.748779296875,\n 32.57459172113418\n ],\n [\n -85.1495361328125,\n 32.57459172113418\n ],\n [\n -85.1495361328125,\n 30.60482195075795\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, South Atlantic Water Science Center
U.S. Geological Survey
720 Gracern Road
Stephenson Center, Suite 129
Columbia, SC 29210
http://www.usgs.gov/water/southatlantic/
Bacteria-driven restrictions and (or) advisories on swimming at beaches in Presque Isle State Park (PISP), Erie, Pennsylvania, can occur during the summer months. One of the suspected sources of bacteria is sediment. A terrestrial sediment source to the west of PISP is Walnut Creek, which discharges to Lake Erie about 8.5 kilometers southwest of PISP Beach 1. On June 24, June 25, August 18, and August 19, 2015, synoptic surveys were conducted by the U.S. Geological Survey, in cooperation with the Pennsylvania Sea Grant, in Lake Erie between Walnut Creek and PISP Beach 1 to characterize the water-current velocity and direction to determine whether sediment from Walnut Creek could be affecting the PISP beaches. Water-quality data (temperature, specific conductance, and turbidity) were collected in conjunction with the synoptic surveys in June. Water-quality data (Escherichia coli [E. coli] bacteria, temperature, and turbidity) were collected about a meter from the shore (nearshore) on June 24, August 19, and after a precipitation event on August 11, 2015. Additionally, suspended sediment was collected nearshore on June 24 and August 11, 2015. Samples collected near Walnut Creek during all three bacterial sampling events contained higher counts than other samples. Counts steadily decreased from west to east, then increased about 1–2 kilometers from PISP Beach 1; however, this study was not focused on examining other potential sources of bacteria.
The Velocity Mapping Toolbox (VMT) was used to process the water-current synoptic surveys, and the results were visualized within ArcMap. For the survey accomplished on June 24, 2015, potential paths a particle could take between Walnut Creek and PSIP Beach 1 if conditions remained steady over a number of hours were visualized. However, the water-current velocity and direction were variable from one day to the other, indicating this was likely an unrealistic assumption for the study area. This analysis was not accomplished for the other surveys due to unsteady lake conditions encountered on June 25 and August 18, and reduced quality of the survey on August 19.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161206","collaboration":"Prepared in cooperation with the Pennsylvania Sea Grant","usgsCitation":"Hittle, Elizabeth, 2017, Longshore water-current velocity and the potential for transport of contaminants—A pilot study in Lake Erie from Walnut Creek to Presque Isle State Park beaches, Erie, Pennsylvania, June and August 2015: U.S. Geological Survey Open-File Report 2016–1206, 126 p., https://doi.org/10.3133/ofr20161206.","productDescription":"Report: x, 126 p.; Appendixes 2-1 - 2-3; Data Release","numberOfPages":"140","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-077254","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":438368,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7KP808D","text":"USGS data release","linkHelpText":"Data Collected in Support of the Longshore Water-Current Velocity and the Potential for Transport of Contaminants pilot study in Lake Erie from Walnut Creek to Presque Isle State Park Beaches, Erie, Pennsylvania"},{"id":339295,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7KP808D","text":"USGS data release","description":"USGS data release","linkHelpText":"Longshore Water-Current Velocity and the Potential for Transport of Contaminants: A pilot study in Lake Erie from Walnut Creek to Presque Isle State Park Beaches, Erie, Pennsylvania, June and August 2015"},{"id":339174,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1206/coverthb2.jpg"},{"id":339175,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1206/ofr20161206.pdf","text":"Report","size":"28.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1206"},{"id":339176,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2016/1206/ofr20161206_appendix2-1.csv","text":"Appendix 2-1","size":"1.29 KB","linkFileType":{"id":7,"text":"csv"},"linkHelpText":"- Regression Statistics for Figures 23-25"},{"id":339178,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2016/1206/ofr20161206_appendix2-3.csv","text":"Appendix 2-3","size":"1.25 KB","linkFileType":{"id":7,"text":"csv"},"linkHelpText":"- Regression Statistics for Figures 23-25"},{"id":339177,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2016/1206/ofr20161206_appendix2-2.csv","text":"Appendix 2-2","size":"1.29 KB","linkFileType":{"id":7,"text":"csv"},"linkHelpText":"- Regression Statistics for Figures 23-25"}],"country":"United States","state":"Pennsylvania","city":"Erie","otherGeospatial":"Lake Erie, Presque Isle State Park, Walnut Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.25,\n 42.06667\n ],\n [\n -80.13333,\n 42.06667\n ],\n [\n -80.13333,\n 42.13333\n ],\n [\n -80.25,\n 42.13333\n ],\n [\n -80.25,\n 42.06667\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Pennsylvania Water Science Center
U.S. Geological Survey
215 Limekiln Road
New Cumberland, PA 17070
https://pa.water.usgs.gov/
American woodcock (Scolopax minor) are managed as a Central and an Eastern population in the United States and Canada based on band return data showing little crossover between populations or management regions. The observed proportion of crossover between management regions, however, depends on the criteria used to subset the band return data. We analyzed the amount of crossover between management regions using only band return records that represent complete migrations between the breeding and wintering grounds by using only band return records in which the capture took place during the breeding season and the band recovery took place during the wintering season or vice versa (n = 224). Additionally, we applied spatial statistics and a clustering algorithm to investigate woodcock migratory connectivity using this subset of migratory woodcock band return records. Using raw counts, 17.9% of records showed crossover between management regions, a higher proportion than the <5% crossover reported in studies that did not use only migratory band returns. Our results showed woodcock from the breeding grounds in the Central Region largely migrate to destinations within the Central Region, whereas woodcock from the breeding grounds in the Eastern Region migrate to destinations across the entire wintering range and mix with individuals from the Central Region. Using the division coefficient, we estimated that 54% of woodcock from the breeding grounds of the Eastern Region migrate to the Central Region wintering grounds. Our result that many woodcock from separate regions of the breeding grounds mix on the wintering grounds has implications for the 2-region basis for woodcock management. Elucidating finer scale movement patterns among regions provides a basis for reassessing the need for separate management regions to ensure optimal conservation and management of the species.
","language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.21269","usgsCitation":"Moore, J.D., and Krementz, D.G., 2017, Migratory connectivity of american woodcock using band return data: Journal of Wildlife Management, v. 81, no. 6, p. 1063-1072, https://doi.org/10.1002/jwmg.21269.","productDescription":"12 p.","startPage":"1063","endPage":"1072","ipdsId":"IP-080526","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":348470,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -72.26806640624999,\n 45.1510532655634\n ],\n [\n -74.0478515625,\n 46.31658418182218\n ],\n [\n -77.1240234375,\n 47.54687159892238\n ],\n [\n -82.0458984375,\n 48.48748647988415\n ],\n [\n -86.0009765625,\n 48.86471476180277\n ],\n [\n -89.033203125,\n 48.60385760823255\n ],\n [\n -90.615234375,\n 48.019324184801185\n ],\n [\n -93.603515625,\n 46.98025235521883\n ],\n [\n -95.0537109375,\n 45.82879925192134\n ],\n [\n -95.2294921875,\n 43.77109381775651\n ],\n [\n -96.064453125,\n 39.40224434029275\n ],\n [\n -96.15234375,\n 32.0639555946604\n ],\n [\n -95.0537109375,\n 29.22889003019423\n ],\n [\n -87.802734375,\n 30.751277776257812\n ],\n [\n -85.62744140625,\n 34.77771580360469\n ],\n [\n -80.74951171875,\n 37.59682400108367\n ],\n [\n -74.02587890625,\n 41.32732632036622\n ],\n [\n -71.7626953125,\n 43.229195113965005\n ],\n [\n -72.26806640624999,\n 45.1510532655634\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"81","issue":"6","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-04-19","publicationStatus":"PW","scienceBaseUri":"5a0425b9e4b0dc0b45b4538e","contributors":{"authors":[{"text":"Moore, Joseph D.","contributorId":199996,"corporation":false,"usgs":false,"family":"Moore","given":"Joseph","email":"","middleInitial":"D.","affiliations":[{"id":6623,"text":"University of Arkansas","active":true,"usgs":false}],"preferred":false,"id":720543,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Krementz, David G. 0000-0002-5661-4541 dkrementz@usgs.gov","orcid":"https://orcid.org/0000-0002-5661-4541","contributorId":2827,"corporation":false,"usgs":true,"family":"Krementz","given":"David","email":"dkrementz@usgs.gov","middleInitial":"G.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":720542,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70186888,"text":"70186888 - 2017 - Geogenic organic contaminants in the low-rank coal-bearing Carrizo-Wilcox aquifer of East Texas, USA","interactions":[],"lastModifiedDate":"2017-05-24T10:18:54","indexId":"70186888","displayToPublicDate":"2017-04-13T00:00:00","publicationYear":"2017","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":"Geogenic organic contaminants in the low-rank coal-bearing Carrizo-Wilcox aquifer of East Texas, USA","docAbstract":"The organic composition of groundwater along the Carrizo-Wilcox aquifer in East Texas (USA), sampled from rural wells in May and September 2015, was examined as part of a larger study of the potential health and environmental effects of organic compounds derived from low-rank coals. The quality of water from the low-rank coal-bearing Carrizo-Wilcox aquifer is a potential environmental concern and no detailed studies of the organic compounds in this aquifer have been published. Organic compounds identified in the water samples included: aliphatics and their fatty acid derivatives, phenols, biphenyls, N-, O-, and S-containing heterocyclic compounds, polycyclic aromatic hydrocarbons (PAHs), aromatic amines, and phthalates. Many of the identified organic compounds (aliphatics, phenols, heterocyclic compounds, PAHs) are geogenic and originated from groundwater leaching of young and unmetamorphosed low-rank coals. Estimated concentrations of individual compounds ranged from about 3.9 to 0.01 μg/L. In many rural areas in East Texas, coal strata provide aquifers for drinking water wells. Organic compounds observed in groundwater are likely to be present in drinking water supplied from wells that penetrate the coal. Some of the organic compounds identified in the water samples are potentially toxic to humans, but at the estimated levels in these samples, the compounds are unlikely to cause acute health problems. The human health effects of low-level chronic exposure to coal-derived organic compounds in drinking water in East Texas are currently unknown, and continuing studies will evaluate possible toxicity.
","language":"English","publisher":"Springer","doi":"10.1007/s10040-016-1508-6","usgsCitation":"Chakraborty, J., Varonka, M.S., Orem, W.H., Finkelman, R.B., and Manton, W., 2017, Geogenic organic contaminants in the low-rank coal-bearing Carrizo-Wilcox aquifer of East Texas, USA: Hydrogeology Journal, v. 25, no. 4, p. 1219-1228, https://doi.org/10.1007/s10040-016-1508-6.","productDescription":"10 p.","startPage":"1219","endPage":"1228","ipdsId":"IP-076592","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":339690,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas","otherGeospatial":"Carrizo-Wilcox Aquifer","volume":"25","issue":"4","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-01-07","publicationStatus":"PW","scienceBaseUri":"58f08e5ee4b06911a29fa83e","contributors":{"authors":[{"text":"Chakraborty, Jayeeta","contributorId":190842,"corporation":false,"usgs":false,"family":"Chakraborty","given":"Jayeeta","email":"","affiliations":[],"preferred":false,"id":690860,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Varonka, Matthew S. 0000-0003-3620-5262 mvaronka@usgs.gov","orcid":"https://orcid.org/0000-0003-3620-5262","contributorId":4726,"corporation":false,"usgs":true,"family":"Varonka","given":"Matthew","email":"mvaronka@usgs.gov","middleInitial":"S.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":690859,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Orem, William H. 0000-0003-4990-0539 borem@usgs.gov","orcid":"https://orcid.org/0000-0003-4990-0539","contributorId":577,"corporation":false,"usgs":true,"family":"Orem","given":"William","email":"borem@usgs.gov","middleInitial":"H.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":690861,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Finkelman, Robert B.","contributorId":85951,"corporation":false,"usgs":true,"family":"Finkelman","given":"Robert","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":690862,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Manton, William","contributorId":190844,"corporation":false,"usgs":false,"family":"Manton","given":"William","email":"","affiliations":[],"preferred":false,"id":690863,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70184177,"text":"70184177 - 2017 - Final synthesis report for factors controlling DDE dechlorination rates on the palos verdes shelf: A field and laboratory investigation","interactions":[],"lastModifiedDate":"2017-04-12T14:43:00","indexId":"70184177","displayToPublicDate":"2017-04-12T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"seriesNumber":"022817","title":"Final synthesis report for factors controlling DDE dechlorination rates on the palos verdes shelf: A field and laboratory investigation","docAbstract":"This project was organized into separate field and laboratory studies aimed at answering “18\nquestions” in the original Scope of Work (cf., section 2 of this report, Background, for\nexplanation). Because of some early results, certain questions became irrelevant and were,\ntherefore, not pursued. In other cases, there simply was not enough time to complete the\noriginally planned studies. On the other hand, additional work, not identified in any of the\noriginal “18 questions”, was carried out for purposes of addressing specific issues of concern to\nthe USEPA (United States Environmental Protection Agency). Examples of the latter include: 1)\nthe analysis of an expanded list of sediment cores for DDX (DDX refers to the ten DDT-related\ncompounds of interest in this study; cf., Eganhouse et al., [1]) and selected PCB congeners to\nfacilitate estimation of site-specific reductive dechlorination (RDC) and total loss rates, 2)\nanalysis of gravity and box cores for trace elements to allow stratigraphic alignment, and 3)\ndetermination of the extent of mineralization of p,p’-DDE (1-chloro-2-[2,2-dichloro-1-(4-\nchlorophenyl)ethyl]benzene) in microcosm experiments.\nIn this Executive Summary, we offer a brief recapitulation of what was learned about the\nfactors controlling reductive dechlorination of p,p’-DDE in Palos Verdes Shelf (PVS) sediments\nusing the “18 questions” as a structural guide. The summary is written in narrative form, but\nreferences to specific sections (corresponding to the “18 questions”) are identified\nparenthetically in the text so that the reader can explore the expanded answers that appear later in\nthe report.","language":"English","publisher":"United States Environmental Protection Agency","usgsCitation":"Eganhouse, R., Orem, W.H., and Reinhard, M., 2017, Final synthesis report for factors controlling DDE dechlorination rates on the palos verdes shelf: A field and laboratory investigation, 31 p.","productDescription":"31 p.","ipdsId":"IP-079956","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":339624,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":336717,"type":{"id":15,"text":"Index Page"},"url":"https://yosemite.epa.gov/r9/sfund/r9sfdocw.nsf/3dc283e6c5d6056f88257426007417a2/7f7e980f35ff63c6882580ce006621e0!OpenDocument"}],"country":"United States","otherGeospatial":"Palos Verdes Shelf","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.47244262695312,\n 33.78599582629231\n ],\n [\n -118.51364135742189,\n 33.789419868423714\n ],\n [\n -118.51089477539064,\n 33.688924428426475\n ],\n [\n -118.47518920898438,\n 33.64663552343716\n ],\n [\n -118.42300415039062,\n 33.643205782197015\n ],\n [\n -118.37493896484375,\n 33.6031820405205\n ],\n [\n -118.32000732421875,\n 33.61233196336391\n ],\n [\n -118.28704833984375,\n 33.648921941686545\n ],\n [\n -118.30627441406249,\n 33.687781758439364\n ],\n [\n -118.33236694335938,\n 33.69920777465873\n ],\n [\n -118.37081909179689,\n 33.715201644740844\n ],\n [\n -118.39553833007812,\n 33.72205524868729\n ],\n [\n -118.41613769531249,\n 33.71862851510573\n ],\n [\n -118.43261718749999,\n 33.72776616734187\n ],\n [\n -118.43948364257812,\n 33.73804486328907\n ],\n [\n -118.47244262695312,\n 33.78599582629231\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58ef3daae4b0eed1ab8e3bda","contributors":{"authors":[{"text":"Eganhouse, Robert P. eganhous@usgs.gov","contributorId":2031,"corporation":false,"usgs":true,"family":"Eganhouse","given":"Robert P.","email":"eganhous@usgs.gov","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":680358,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Orem, William H. 0000-0003-4990-0539 borem@usgs.gov","orcid":"https://orcid.org/0000-0003-4990-0539","contributorId":577,"corporation":false,"usgs":true,"family":"Orem","given":"William","email":"borem@usgs.gov","middleInitial":"H.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":680359,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reinhard, Martin","contributorId":187403,"corporation":false,"usgs":false,"family":"Reinhard","given":"Martin","email":"","affiliations":[],"preferred":false,"id":680360,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70184176,"text":"70184176 - 2017 - Final data report for factors controlling DDE dechlorination rates on the Palos Verdes Shelf: A field and laboratory investigation","interactions":[],"lastModifiedDate":"2019-03-06T13:44:23","indexId":"70184176","displayToPublicDate":"2017-04-12T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Final data report for factors controlling DDE dechlorination rates on the Palos Verdes Shelf: A field and laboratory investigation","docAbstract":"This data report provides a compilation of information developed over the last 6+ years by a\nmulti-disciplinary, multi-institutional research team. The overall goal of this work has been to\nidentify the biological, chemical, and physical factors that control rates of reductive\ndechlorination of DDE and DDMU in sediments of the Palos Verdes Shelf (PVS). More specific\nquestions and objectives are delineated in the Scope of Work (section 12.1., Appendix 1).\nThe study was composed of two parts: 1) field characterization studies, and 2) laboratory\nmicrocosm experiments. The goal of the field characterization studies was to define the\nconditions under which reductive dechlorination of DDE (and DDMU) is occurring in PVS\nsediments. This involved two separate cruises (2009, 2010) during which sediment cores,\nbottom water and other real-time field measurements (e.g., conductivity, temperature, depth of\nthe water column) were acquired. The sediment cores were distributed among research team\nmembers for detailed chemical (R. Eganhouse, B. Orem, M. Reinhard), microbiological (A.\nSpormann), and physical (B. Edwards) analysis as well as for laboratory microcosm experiments\n(M. Reinhard). A team of collaborating USGS scientists generously contributed valuable\ninformation pertaining to geochronology (P. Swarzenski), the character of sedimentary\ngeosorbent phases (P. Hackley), mineralogy (D. Webster), and grain-size characteristics (C.\nSherwood) of PVS sediment samples.\nTogether, this information will serve as framework for a conceptual model of natural degradation\nprocesses in the DDT-contaminated sediments on the PVS. These findings will enable the\nUSEPA to gain a better understanding of the controls on reductive dechlorination and how\ndechlorination rates vary spatially and temporally. This, in turn, should facilitate decision\nmaking concerning the progress of natural attenuation and when monitoring at the site can be\nterminated. Toward that end, a brief Synthesis Report, summarizing and interpreting the\nacquired data, is being prepared and will be released in the coming year.","language":"English","publisher":"U.S. Environmental Protection Agency","usgsCitation":"Eganhouse, R., Pontolillo, J., Orem, W.H., Webster, D.M., Hackley, P.C., Edwards, B.D., Rosenberger, K.J., Dickhudt, P., Sherwood, C.R., Reinhard, M., Qin, S., Dougherty, J., Hopkins, G., Marshall, I., and Spormann, A., 2017, Final data report for factors controlling DDE dechlorination rates on the Palos Verdes Shelf: A field and laboratory investigation, Zip File.","productDescription":"Zip File","ipdsId":"IP-063652","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":339628,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":336716,"type":{"id":15,"text":"Index Page"},"url":"https://cumulis.epa.gov/supercpad/cursites/cscdocument.cfm?id=0900993&doc=Y&colid=36797"}],"country":"United States","otherGeospatial":"Palos Verdes Shelf","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.44085693359375,\n 33.773439833797724\n ],\n [\n -118.47381591796875,\n 33.799691173251084\n ],\n [\n -118.5163879394531,\n 33.78827853625996\n ],\n [\n -118.52600097656249,\n 33.76773195605407\n ],\n [\n -118.5150146484375,\n 33.75174787568194\n ],\n [\n -118.50128173828125,\n 33.71291698851023\n ],\n [\n -118.48205566406249,\n 33.678639851675555\n ],\n [\n -118.44223022460938,\n 33.64434904445888\n ],\n [\n -118.4230041503906,\n 33.63062889539564\n ],\n [\n -118.3941650390625,\n 33.618050171974545\n ],\n [\n -118.34747314453125,\n 33.622624465698685\n ],\n [\n -118.31039428710936,\n 33.63634588982396\n ],\n [\n -118.28018188476561,\n 33.67406853374198\n ],\n [\n -118.29666137695311,\n 33.687781758439364\n ],\n [\n -118.32550048828124,\n 33.70377775573253\n ],\n [\n -118.36120605468747,\n 33.72205524868731\n ],\n [\n -118.39691162109375,\n 33.7243396617476\n ],\n [\n -118.41339111328125,\n 33.73119253613475\n ],\n [\n -118.42849731445312,\n 33.75060604160645\n ],\n [\n -118.44085693359375,\n 33.773439833797724\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58ef3dabe4b0eed1ab8e3bdc","contributors":{"authors":[{"text":"Eganhouse, Robert P. eganhous@usgs.gov","contributorId":2031,"corporation":false,"usgs":true,"family":"Eganhouse","given":"Robert P.","email":"eganhous@usgs.gov","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":680343,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pontolillo, James jpontoli@usgs.gov","contributorId":2033,"corporation":false,"usgs":true,"family":"Pontolillo","given":"James","email":"jpontoli@usgs.gov","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":680344,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Orem, William H. 0000-0003-4990-0539 borem@usgs.gov","orcid":"https://orcid.org/0000-0003-4990-0539","contributorId":577,"corporation":false,"usgs":true,"family":"Orem","given":"William","email":"borem@usgs.gov","middleInitial":"H.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":680345,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Webster, Daniel M. webster@usgs.gov","contributorId":3529,"corporation":false,"usgs":true,"family":"Webster","given":"Daniel","email":"webster@usgs.gov","middleInitial":"M.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":680346,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hackley, Paul C. 0000-0002-5957-2551 phackley@usgs.gov","orcid":"https://orcid.org/0000-0002-5957-2551","contributorId":592,"corporation":false,"usgs":true,"family":"Hackley","given":"Paul","email":"phackley@usgs.gov","middleInitial":"C.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":680347,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Edwards, Brian D. bedwards@usgs.gov","contributorId":3161,"corporation":false,"usgs":true,"family":"Edwards","given":"Brian","email":"bedwards@usgs.gov","middleInitial":"D.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":680348,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rosenberger, Kurt J. 0000-0002-5185-5776 krosenberger@usgs.gov","orcid":"https://orcid.org/0000-0002-5185-5776","contributorId":140453,"corporation":false,"usgs":true,"family":"Rosenberger","given":"Kurt","email":"krosenberger@usgs.gov","middleInitial":"J.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":680349,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Dickhudt, Patrick 0000-0001-8003-7089 pdickhudt@usgs.gov","orcid":"https://orcid.org/0000-0001-8003-7089","contributorId":187402,"corporation":false,"usgs":true,"family":"Dickhudt","given":"Patrick","email":"pdickhudt@usgs.gov","affiliations":[],"preferred":true,"id":680350,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Sherwood, Christopher R. 0000-0001-6135-3553 csherwood@usgs.gov","orcid":"https://orcid.org/0000-0001-6135-3553","contributorId":2866,"corporation":false,"usgs":true,"family":"Sherwood","given":"Christopher","email":"csherwood@usgs.gov","middleInitial":"R.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":680351,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Reinhard, Martin","contributorId":187403,"corporation":false,"usgs":false,"family":"Reinhard","given":"Martin","email":"","affiliations":[],"preferred":false,"id":680352,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Qin, Sujie","contributorId":187404,"corporation":false,"usgs":false,"family":"Qin","given":"Sujie","email":"","affiliations":[],"preferred":false,"id":680353,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Dougherty, Jennifer","contributorId":187405,"corporation":false,"usgs":false,"family":"Dougherty","given":"Jennifer","affiliations":[],"preferred":false,"id":680354,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Hopkins, Gary","contributorId":187406,"corporation":false,"usgs":false,"family":"Hopkins","given":"Gary","affiliations":[],"preferred":false,"id":680355,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Marshall, Ian","contributorId":187407,"corporation":false,"usgs":false,"family":"Marshall","given":"Ian","email":"","affiliations":[],"preferred":false,"id":680356,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Spormann, Alfred","contributorId":187408,"corporation":false,"usgs":false,"family":"Spormann","given":"Alfred","email":"","affiliations":[],"preferred":false,"id":680357,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}} ,{"id":70186227,"text":"sir20175030 - 2017 - Status and threats analysis for the Florida manatee (Trichechus manatus latirostris), 2016","interactions":[],"lastModifiedDate":"2024-03-04T20:25:12.948526","indexId":"sir20175030","displayToPublicDate":"2017-04-11T15:15:00","publicationYear":"2017","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":"2017-5030","title":"Status and threats analysis for the Florida manatee (Trichechus manatus latirostris), 2016","docAbstract":"Trichechus manatus (West Indian manatee), especially T. m. latirostris, the Florida subspecies, has been the focus of conservation efforts and extensive research since its listing under the Endangered Species Act of 1973. To determine the status of, and severity of threats to, the Florida manatee, a comprehensive revision and update of the manatee Core Biological Model was completed and used to perform a population viability analysis for the Florida manatee. The probability of the Florida manatee population falling below 500 adults on either the Gulf or East coast within the next 100 years was estimated to be 0.42 percent. This risk of quasi-extinction is low because the estimated adult survival rates are high, the current population size is greater than 2,500 on each coast, and the estimated carrying capacity for manatees is much larger than the current abundance estimates in all four regions of Florida. Three threats contribute in roughly equal measures to the risk of quasi-extinction: watercraft-related mortality, red-tide mortality, and loss of warm-water habitat. Only an increase in watercraft-related mortality has the potential to substantially increase the risk of quasi-extinction at the statewide or coastal level. Expected losses of warm-water habitat are likely to cause a major change in the distribution of the population from the regions where manatees rely heavily on power plant effluents for warmth in winter (Southwest and Atlantic regions) to the regions where manatees primarily use natural springs in winter (Northwest and Upper St. Johns regions). The chances are nearly 50 percent that manatee populations in the Southwest and Atlantic regions will decrease from their 2011 levels by at least 30 percent over the next century.
A large number of scenarios were examined to explore the possible effects of potential emerging threats, and in most of them, the risk of quasi-extinction at the coastal scale within 100 years did not rise above 1 percent. The four exceptions are scenarios in which the rate of watercraft-related mortality increases, carrying capacity is only a fraction of the current estimates, a new chronic source of mortality emerges, or multiple threats emerge in concert. Even in these scenarios, however, the risk of falling below 500 adults on either the East coast or the Gulf coast within 100 years from 2011 is less than 10 percent. High adult survival provides the population with strong resilience to a variety of current and future threats. On the basis of these analyses, we conclude that if these threats continue to be managed effectively, manatees are likely to persist on both coasts of Florida and remain an integral part of the coastal Florida ecosystem through the 21st century. If vigilance in management is reduced, however, the scenarios in which manatees could face risk of decline become more likely.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175030","collaboration":"Prepared in cooperation with the Florida Fish and Wildlife Conservation Commission","usgsCitation":"Runge, M.C., Sanders-Reed, C.A., Langtimm, C.A., Hostetler, J.A., Martin, Julien, Deutsch, C.J., Ward-Geiger, L.I., and Mahon, G.L., 2017, Status and threats analysis for the Florida manatee (Trichechus manatus latirostris), 2016: U.S. Geological Survey Scientific Investigation Report 2017–5030, 40 p., https://doi.org/10.3133/sir20175030.","productDescription":"ix, 40 p.","numberOfPages":"54","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-083198","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":339559,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5030/sir20175030.pdf","text":"Report","size":"2.59 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5030"},{"id":339558,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5030/coverthb2.jpg"}],"country":"United States","state":"Florida","contact":"Director, Eastern Ecological Science Center
U.S. Geological Survey
12100 Beech Forest Rd., Ste 4039
Laurel, MD 20708-4039
Since 1952, wastewater discharged to in ltration ponds (also called percolation ponds) and disposal wells at the Idaho National Laboratory (INL) has affected water quality in the eastern Snake River Plain (ESRP) aquifer and perched groundwater zones underlying the INL. The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Energy, maintains groundwater-monitoring networks at the INL to determine hydrologic trends and to delineate the movement of radiochemical and chemical wastes in the aquifer and in perched groundwater zones. This report presents an analysis of water-level and water-quality data collected from the ESRP aquifer, multilevel monitoring system (MLMS) wells in the ESRP aquifer, and perched groundwater wells in the USGS groundwater monitoring networks during 2012-15.
Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Road
Boise, Idaho 83702
https://id.water.usgs.gov
Investigations of coastal change at Fire Island, New York (N.Y.), sought to characterize sediment budgets and determine geologic framework controls on coastal processes. Nearshore sediment thickness is critical for assessing coastal system sediment availability, but it is largely unquantified due to the difficulty of conducting geological or geophysical surveys across the nearshore. This study used an amphibious vessel to acquire chirp subbottom profiles. These profiles were used to characterize nearshore geology and provide an assessment of nearshore sediment volume. Two resulting sediment-thickness maps are provided: total Holocene sediment thickness and the thickness of the active shoreface. The Holocene sediment section represents deposition above the maximum flooding surface that is related to the most recent marine transgression. The active shoreface section is the uppermost Holocene sediment, which is interpreted to represent the portion of the shoreface thought to contribute to present and future coastal behavior. The sediment distribution patterns correspond to previously defined zones of erosion, accretion, and stability along the island, demonstrating the importance of sediment availability in the coastal response to storms and seasonal variability. The eastern zone has a thin nearshore sediment thickness, except for an ebb-tidal deposit at the wilderness breach caused by Hurricane Sandy. Thicker sediment is found along a central zone that includes shoreface-attached sand ridges, which is consistent with a stable or accretional coastline in this area. The thickest overall Holocene section is found in the western zone of the study, where a thicker lower section of Holocene sediment appears related to the westward migration of Fire Island Inlet over several hundred years.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171024","usgsCitation":"Locker, S.D., Miselis, J.L., Buster, N.A., Hapke, C.J., Wadman, H.M., McNinch, J.E., Forde, A.S., and Stalk, C.A., 2017, Nearshore sediment thickness, Fire Island, New York: U.S. Geological Survey Open-File Report 2017–1024, 21 p., https://doi.org/10.3133/ofr20171024.","productDescription":"vii, 21 p.","numberOfPages":"29","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-079609","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":338703,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1024/ofr20171024.pdf","text":"Report","size":"6.61 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1024"},{"id":338702,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1024/coverthb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Fire Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -72.87986755371094,\n 40.77534183237267\n ],\n [\n -72.87986755371094,\n 40.77534183237267\n ],\n [\n -72.87986755371094,\n 40.77534183237267\n ],\n [\n -72.87986755371094,\n 40.77534183237267\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -72.87574768066406,\n 40.77534183237267\n ],\n [\n -73.27743530273438,\n 40.65563874006118\n ],\n [\n -73.24447631835938,\n 40.59674926086908\n ],\n [\n -72.84210205078125,\n 40.7202010588415\n ],\n [\n -72.87574768066406,\n 40.77534183237267\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, St. Petersburg Coastal and Marine Science Center
U.S. Geological Survey
600 4th Street South
St. Petersburg, FL 33701
https://coastal.er.usgs.gov/
Changes in snowmelt-related streamflow timing have implications for water availability and use as well as ecologically relevant shifts in streamflow. Historical trends in snowmelt-related streamflow timing (winter-spring center volume date, WSCVD) were computed for minimally disturbed river basins in the conterminous United States. WSCVD was computed by summing daily streamflow for a seasonal window then calculating the day that half of the seasonal volume had flowed past the gage. We used basins where at least 30 percent of annual precipitation was received as snow, and streamflow data were restricted to regionally based winter-spring periods to focus the analyses on snowmelt-related streamflow. Trends over time in WSCVD at gages in the eastern U.S. were relatively homogenous in magnitude and direction and statistically significant; median WSCVD was earlier by 8.2 days (1.1 days/decade) and 8.6 days (1.6 days/decade) for 1940–2014 and 1960–2014 periods respectively. Fewer trends in the West were significant though most trends indicated earlier WSCVD over time. Trends at low-to-mid elevation (<1600 m) basins in the West, predominantly located in the Northwest, had median earlier WSCVD by 6.8 days (1940–2014, 0.9 days/decade) and 3.4 days (1960–2014, 0.6 days/decade). Streamflow timing at high-elevation (⩾1600 m) basins in the West had median earlier WSCVD by 4.0 days (1940–2014, 0.5 days/decade) and 5.2 days (1960–2014, 0.9 days/decade). Trends toward earlier WSCVD in the Northwest were not statistically significant, differing from previous studies that observed many large and (or) significant trends in this region. Much of this difference is likely due to the sensitivity of trend tests to the time period being tested, as well as differences in the streamflow timing metrics used among the studies. Mean February–May air temperature was significantly correlated with WSCVD at 100 percent of the study gages (field significant, p < 0.0001), demonstrating the sensitivity of WSCVD to air temperature across snowmelt dominated basins in the U.S. WSCVD in high elevation basins in the West, however, was related to both air temperature and precipitation yielding earlier snowmelt-related streamflow timing under warmer and drier conditions.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2017.01.051","usgsCitation":"Dudley, R.W., Hodgkins, G.A., McHale, M., Kolian, M., and Renard, B., 2017, Trends in snowmelt-related streamflow timing in the conterminous United States: Journal of Hydrology, v. 547, p. 208-221, https://doi.org/10.1016/j.jhydrol.2017.01.051.","productDescription":"14 p.","startPage":"208","endPage":"221","ipdsId":"IP-076605","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":469955,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jhydrol.2017.01.051","text":"Publisher Index Page"},{"id":356297,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"547","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b6fc6f5e4b0f5d57878ebad","contributors":{"authors":[{"text":"Dudley, Robert W. 0000-0002-0934-0568 rwdudley@usgs.gov","orcid":"https://orcid.org/0000-0002-0934-0568","contributorId":2223,"corporation":false,"usgs":true,"family":"Dudley","given":"Robert","email":"rwdudley@usgs.gov","middleInitial":"W.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":371,"text":"Maine Water Science Center","active":true,"usgs":true}],"preferred":true,"id":669220,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hodgkins, Glenn A. 0000-0002-4916-5565 gahodgki@usgs.gov","orcid":"https://orcid.org/0000-0002-4916-5565","contributorId":2020,"corporation":false,"usgs":true,"family":"Hodgkins","given":"Glenn","email":"gahodgki@usgs.gov","middleInitial":"A.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":371,"text":"Maine Water Science Center","active":true,"usgs":true}],"preferred":true,"id":669221,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McHale, Michael 0000-0003-3780-1816 mmchale@usgs.gov","orcid":"https://orcid.org/0000-0003-3780-1816","contributorId":177292,"corporation":false,"usgs":true,"family":"McHale","given":"Michael","email":"mmchale@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":669222,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kolian, Michael J.","contributorId":177290,"corporation":false,"usgs":false,"family":"Kolian","given":"Michael J.","affiliations":[],"preferred":false,"id":669223,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Renard, Benjamin","contributorId":177291,"corporation":false,"usgs":false,"family":"Renard","given":"Benjamin","email":"","affiliations":[],"preferred":false,"id":669224,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70193334,"text":"70193334 - 2017 - The 3.6 ka Aniakchak tephra in the Arctic Ocean: A constraint on the Holocene radiocarbon reservoir age in the Chukchi Sea ","interactions":[],"lastModifiedDate":"2017-10-31T15:52:26","indexId":"70193334","displayToPublicDate":"2017-04-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1250,"text":"Climate of the Past","active":true,"publicationSubtype":{"id":10}},"title":"The 3.6 ka Aniakchak tephra in the Arctic Ocean: A constraint on the Holocene radiocarbon reservoir age in the Chukchi Sea ","docAbstract":"The caldera-forming eruption of the Aniakchak volcano in the Aleutian Range on the Alaskan Peninsula at 3.6 cal kyr BP was one of the largest Holocene eruptions worldwide. The resulting ash is found as a visible sediment layer in several Alaskan sites and as a cryptotephra on Newfoundland and Greenland. This large geographic distribution, combined with the fact that the eruption is relatively well constrained in time using radiocarbon dating of lake sediments and annual layer counts in ice cores, makes it an excellent stratigraphic marker for dating and correlating mid–late Holocene sediment and paleoclimate records. This study presents the outcome of a targeted search for the Aniakchak tephra in a marine sediment core from the Arctic Ocean, namely Core SWERUS-L2-2-PC1 (2PC), raised from 57 m water depth in Herald Canyon, western Chukchi Sea. High concentrations of tephra shards, with a geochemical signature matching that of Aniakchak ash, were observed across a more than 1.5 m long sediment sequence. Since the primary input of volcanic ash is through atmospheric transport, and assuming that bioturbation can account for mixing up to ca. 10 cm of the marine sediment deposited at the coring site, the broad signal is interpreted as sustained reworking at the sediment source input. The isochron is therefore placed at the base of the sudden increase in tephra concentrations rather than at the maximum concentration. This interpretation of major reworking is strengthened by analysis of grain size distribution which points to ice rafting as an important secondary transport mechanism of volcanic ash. Combined with radiocarbon dates on mollusks in the same sediment core, the volcanic marker is used to calculate a marine radiocarbon reservoir age offset ΔR = 477 ± 60 years. This relatively high value may be explained by the major influence of typically \"carbon-old\" Pacific waters, and it agrees well with recent estimates of ΔR along the northwest Alaskan coast, possibly indicating stable oceanographic conditions during the second half of the Holocene. Our use of a volcanic absolute age marker to obtain the marine reservoir age offset is the first of its kind in the Arctic Ocean and provides an important framework for improving chronologies and correlating marine sediment archives in this region. Core 2PC has a high sediment accumulation rate averaging 200 cm kyr throughout the last 4000 years, and the chronology presented here provides a solid base for high-resolution reconstructions of late Holocene climate and ocean variability in the Chukchi Sea.
","language":"English","publisher":"European Geosciences Union","doi":"10.5194/cp-13-303-2017","usgsCitation":"Pearce, C., Varhelyi, A., Wastegard, S., Muschitiello, F., Barrientos Macho, N., O’Regan, M., Cronin, T.M., Gemery, L., Semiletov, I., Backman, J., and Jakobsson, M., 2017, The 3.6 ka Aniakchak tephra in the Arctic Ocean: A constraint on the Holocene radiocarbon reservoir age in the Chukchi Sea : Climate of the Past, v. 13, p. 303-316, https://doi.org/10.5194/cp-13-303-2017.","productDescription":"14 p.","startPage":"303","endPage":"316","ipdsId":"IP-081754","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":469959,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/cp-13-303-2017","text":"Publisher Index Page"},{"id":347928,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Russia, United States","state":"Alaska","otherGeospatial":"Chukchi Sea","volume":"13","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-04-05","publicationStatus":"PW","scienceBaseUri":"59f98bb8e4b0531197af9ff7","contributors":{"authors":[{"text":"Pearce, Christof","contributorId":197126,"corporation":false,"usgs":false,"family":"Pearce","given":"Christof","email":"","affiliations":[{"id":25421,"text":"Department of Geological Sciences, Stockholm University, Sweden","active":true,"usgs":false}],"preferred":false,"id":718726,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Varhelyi, Aron","contributorId":199345,"corporation":false,"usgs":false,"family":"Varhelyi","given":"Aron","email":"","affiliations":[{"id":25421,"text":"Department of Geological Sciences, Stockholm University, Sweden","active":true,"usgs":false}],"preferred":false,"id":718727,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wastegard, Stefan","contributorId":199346,"corporation":false,"usgs":false,"family":"Wastegard","given":"Stefan","email":"","affiliations":[{"id":25546,"text":"Stockholm University, Sweden","active":true,"usgs":false}],"preferred":false,"id":718728,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Muschitiello, Francesco","contributorId":199347,"corporation":false,"usgs":false,"family":"Muschitiello","given":"Francesco","email":"","affiliations":[{"id":25546,"text":"Stockholm University, Sweden","active":true,"usgs":false}],"preferred":false,"id":718729,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Barrientos Macho, Natalia","contributorId":199348,"corporation":false,"usgs":false,"family":"Barrientos Macho","given":"Natalia","email":"","affiliations":[{"id":24562,"text":"Stockholm University","active":true,"usgs":false}],"preferred":false,"id":718730,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"O’Regan, Matt","contributorId":197135,"corporation":false,"usgs":false,"family":"O’Regan","given":"Matt","email":"","affiliations":[{"id":25421,"text":"Department of Geological Sciences, Stockholm University, Sweden","active":true,"usgs":false}],"preferred":false,"id":718731,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cronin, Thomas M. 0000-0002-2643-0979 tcronin@usgs.gov","orcid":"https://orcid.org/0000-0002-2643-0979","contributorId":2579,"corporation":false,"usgs":true,"family":"Cronin","given":"Thomas","email":"tcronin@usgs.gov","middleInitial":"M.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":718725,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Gemery, Laura 0000-0003-1966-8732 lgemery@usgs.gov","orcid":"https://orcid.org/0000-0003-1966-8732","contributorId":5402,"corporation":false,"usgs":true,"family":"Gemery","given":"Laura","email":"lgemery@usgs.gov","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":718732,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Semiletov, Igor","contributorId":197134,"corporation":false,"usgs":false,"family":"Semiletov","given":"Igor","email":"","affiliations":[{"id":35519,"text":"Russian Academy Sciences, Vladivostok, Russia","active":true,"usgs":false},{"id":24563,"text":"Tomsk Polytechnic University","active":true,"usgs":false}],"preferred":false,"id":718782,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Backman, Jan","contributorId":166857,"corporation":false,"usgs":false,"family":"Backman","given":"Jan","email":"","affiliations":[{"id":24562,"text":"Stockholm University","active":true,"usgs":false}],"preferred":false,"id":718783,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Jakobsson, Martin","contributorId":166854,"corporation":false,"usgs":false,"family":"Jakobsson","given":"Martin","email":"","affiliations":[{"id":24562,"text":"Stockholm University","active":true,"usgs":false}],"preferred":false,"id":718784,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70192091,"text":"70192091 - 2017 - The Evergreen basin and the role of the Silver Creek fault in the San Andreas fault system, San Francisco Bay region, California","interactions":[],"lastModifiedDate":"2018-05-01T16:45:24","indexId":"70192091","displayToPublicDate":"2017-04-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"The Evergreen basin and the role of the Silver Creek fault in the San Andreas fault system, San Francisco Bay region, California","docAbstract":"The Evergreen basin is a 40-km-long, 8-km-wide Cenozoic sedimentary basin that lies mostly concealed beneath the northeastern margin of the Santa Clara Valley near the south end of San Francisco Bay (California, USA). The basin is bounded on the northeast by the strike-slip Hayward fault and an approximately parallel subsurface fault that is structurally overlain by a set of west-verging reverse-oblique faults which form the present-day southeastward extension of the Hayward fault. It is bounded on the southwest by the Silver Creek fault, a largely dormant or abandoned fault that splays from the active southern Calaveras fault. We propose that the Evergreen basin formed as a strike-slip pull-apart basin in the right step from the Silver Creek fault to the Hayward fault during a time when the Silver Creek fault served as a segment of the main route by which slip was transferred from the central California San Andreas fault to the Hayward and other East Bay faults. The dimensions and shape of the Evergreen basin, together with palinspastic reconstructions of geologic and geophysical features surrounding it, suggest that during its lifetime, the Silver Creek fault transferred a significant portion of the ∼100 km of total offset accommodated by the Hayward fault, and of the 175 km of total San Andreas system offset thought to have been accommodated by the entire East Bay fault system. As shown previously, at ca. 1.5–2.5 Ma the Hayward-Calaveras connection changed from a right-step, releasing regime to a left-step, restraining regime, with the consequent effective abandonment of the Silver Creek fault. This reorganization was, perhaps, preceded by development of the previously proposed basin-bisecting Mount Misery fault, a fault that directly linked the southern end of the Hayward fault with the southern Calaveras fault during extinction of pull-apart activity. Historic seismicity indicates that slip below a depth of 5 km is mostly transferred from the Calaveras fault to the Hayward fault across the Mission seismic trend northeast of the Evergreen basin, whereas slip above a depth of 5 km is transferred through a complex zone of oblique-reverse faults along and over the northeast basin margin. However, a prominent groundwater flow barrier and related land-subsidence discontinuity coincident with the concealed Silver Creek fault, a discontinuity in the pattern of seismicity on the Calaveras fault at the Silver Creek fault intersection, and a structural sag indicative of a negative flower structure in Quaternary sediments along the southwest basin margin indicate that the Silver Creek fault has had minor ongoing slip over the past few hundred thousand years. Two earthquakes with ∼M6 occurred in A.D. 1903 in the vicinity of the Silver Creek fault, but the available information is not sufficient to reliably identify them as Silver Creek fault events.
","language":"English","publisher":"The Geological Society of America","doi":"10.1130/GES01385.1","usgsCitation":"Jachens, R.C., Wentworth, C.M., Graymer, R.W., Williams, R., Ponce, D.A., Mankinen, E.A., Stephenson, W.J., and Langenheim, V., 2017, The Evergreen basin and the role of the Silver Creek fault in the San Andreas fault system, San Francisco Bay region, California: Geosphere, v. 13, no. 2, p. 269-286, https://doi.org/10.1130/GES01385.1.","productDescription":"18 p.","startPage":"269","endPage":"286","ipdsId":"IP-075589","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":461657,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges01385.1","text":"Publisher Index Page"},{"id":347167,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Andreas Fault","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123,\n 36.48314061639213\n ],\n [\n -121,\n 36.48314061639213\n ],\n [\n -121,\n 38.5\n ],\n [\n -123,\n 38.5\n ],\n [\n -123,\n 36.48314061639213\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"13","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-01-27","publicationStatus":"PW","scienceBaseUri":"59eeffa9e4b0220bbd988faf","contributors":{"authors":[{"text":"Jachens, Robert C. jachens@usgs.gov","contributorId":1180,"corporation":false,"usgs":true,"family":"Jachens","given":"Robert","email":"jachens@usgs.gov","middleInitial":"C.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":714172,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wentworth, Carl M. 0000-0003-2569-569X cwent@usgs.gov","orcid":"https://orcid.org/0000-0003-2569-569X","contributorId":1178,"corporation":false,"usgs":true,"family":"Wentworth","given":"Carl","email":"cwent@usgs.gov","middleInitial":"M.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":714173,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Graymer, Russell W. 0000-0003-4910-5682 rgraymer@usgs.gov","orcid":"https://orcid.org/0000-0003-4910-5682","contributorId":1052,"corporation":false,"usgs":true,"family":"Graymer","given":"Russell","email":"rgraymer@usgs.gov","middleInitial":"W.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":714174,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Williams, Robert 0000-0002-2973-8493 rawilliams@usgs.gov","orcid":"https://orcid.org/0000-0002-2973-8493","contributorId":140741,"corporation":false,"usgs":true,"family":"Williams","given":"Robert","email":"rawilliams@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":714175,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ponce, David A. 0000-0003-4785-7354 ponce@usgs.gov","orcid":"https://orcid.org/0000-0003-4785-7354","contributorId":1049,"corporation":false,"usgs":true,"family":"Ponce","given":"David","email":"ponce@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":714176,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mankinen, Edward A. 0000-0001-7496-2681 emank@usgs.gov","orcid":"https://orcid.org/0000-0001-7496-2681","contributorId":1054,"corporation":false,"usgs":true,"family":"Mankinen","given":"Edward","email":"emank@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":714177,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Stephenson, William J. 0000-0001-8699-0786 wstephens@usgs.gov","orcid":"https://orcid.org/0000-0001-8699-0786","contributorId":695,"corporation":false,"usgs":true,"family":"Stephenson","given":"William","email":"wstephens@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":714178,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Langenheim, Victoria E. 0000-0003-2170-5213 zulanger@usgs.gov","orcid":"https://orcid.org/0000-0003-2170-5213","contributorId":151042,"corporation":false,"usgs":true,"family":"Langenheim","given":"Victoria E.","email":"zulanger@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":714179,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70186553,"text":"70186553 - 2017 - Using diets of Canis breeding pairs to assess resource partitioning between sympatric red wolves and coyotes","interactions":[],"lastModifiedDate":"2017-04-05T16:20:30","indexId":"70186553","displayToPublicDate":"2017-04-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2373,"text":"Journal of Mammalogy","onlineIssn":"1545-1542","printIssn":"0022-2372","active":true,"publicationSubtype":{"id":10}},"title":"Using diets of Canis breeding pairs to assess resource partitioning between sympatric red wolves and coyotes","docAbstract":"Foraging behaviors of red wolves (Canis rufus) and coyotes (Canis latrans) are complex and their ability to form congeneric breeding pairs and hybridize further complicates our understanding of factors influencing their diets. Through scat analysis, we assessed prey selection of red wolf, coyote, and congeneric breeding pairs formed by red wolves and coyotes, and found that all 3 had similar diets. However, red wolf and congeneric pairs consumed more white-tailed deer (Odocoileus virginianus) than coyote pairs. Coyotes forming breeding pairs with red wolves had 12% more white-tailed deer in their diet than conspecifics paired with coyotes. Contrary to many studies on coyotes in the southeastern United States, we found coyotes in eastern North Carolina to be primarily carnivorous with increased consumption of deer during winter. Although prey selection was generally similar among the 3 groups, differences in diet among different breeding pairs were strongly associated with body mass. Larger breeding pairs consumed more white-tailed deer, and fewer rabbits (Sylvilagus spp.) and other small mammals. Partitioning of food resources by sympatric red wolves and coyotes is likely via differences in the proportions of similar prey consumed, rather than differences in types of prey exploited. Consequently, our results suggest coexistence of red wolves and coyotes in the southeastern United States may not be possible because there are limited opportunities for niche partitioning to reduce competitive interactions.
","language":"English","publisher":"American Society of Mammalogists","doi":"10.1093/jmammal/gyw233","usgsCitation":"Hinton, J.W., Ashley, A.K., Dellinger, J.A., Gittleman, J.L., van Manen, F.T., and Chamberlain, M.J., 2017, Using diets of Canis breeding pairs to assess resource partitioning between sympatric red wolves and coyotes: Journal of Mammalogy, v. 98, no. 2, p. 475-488, https://doi.org/10.1093/jmammal/gyw233.","productDescription":"14 p.","startPage":"475","endPage":"488","ipdsId":"IP-079451","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":339274,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"98","issue":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-02-09","publicationStatus":"PW","scienceBaseUri":"58e60271e4b09da6799ac67d","contributors":{"authors":[{"text":"Hinton, Joseph W.","contributorId":179346,"corporation":false,"usgs":false,"family":"Hinton","given":"Joseph","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":688723,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ashley, Annaliese K.","contributorId":190531,"corporation":false,"usgs":false,"family":"Ashley","given":"Annaliese","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":688724,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dellinger, Justin A.","contributorId":190532,"corporation":false,"usgs":false,"family":"Dellinger","given":"Justin","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":688725,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gittleman, John L.","contributorId":190533,"corporation":false,"usgs":false,"family":"Gittleman","given":"John","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":688726,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"van Manen, Frank T. 0000-0001-5340-8489 fvanmanen@usgs.gov","orcid":"https://orcid.org/0000-0001-5340-8489","contributorId":2267,"corporation":false,"usgs":true,"family":"van Manen","given":"Frank","email":"fvanmanen@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":688722,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Chamberlain, Michael J.","contributorId":179350,"corporation":false,"usgs":false,"family":"Chamberlain","given":"Michael","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":688727,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70193045,"text":"70193045 - 2017 - Spatiotemporal ecology of Apalone spinifera in a large, Great Plains river ecosystem","interactions":[],"lastModifiedDate":"2017-11-06T16:31:52","indexId":"70193045","displayToPublicDate":"2017-04-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1894,"text":"Herpetological Conservation and Biology","onlineIssn":"2151-0733","printIssn":"1931-7603","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Spatiotemporal ecology of Apalone spinifera in a large, Great Plains river ecosystem","title":"Spatiotemporal ecology of Apalone spinifera in a large, Great Plains river ecosystem","docAbstract":"Sparse information exists about the ecology of Spiny Softshell Turtles (Apalone spinifera) in large rivers, at the northwestern extent of their natural range, and in Montana, where they are disjunct from downstream populations and a State Species of Concern. We determined spatiotemporal ecology of 47 female and 12 male turtles from 2009 through 2012 and identified fundamental habitats in the Missouri River in east-central Montana. Movement rates of females were greater than those of males and peaked before nesting. Movement rates of males peaked before overwintering, and movement rates of both sexes were minimal in winter. Home range sizes were not different between sexes, varied among individuals and seasons, and were similar to those reported elsewhere in their northern range. Turtles aggregated and showed interannual fidelity to separate and disparate habitats in different seasons. Turtles often chose fine substrates, tributary confluences, and reaches with islands during summer and mainstem outside bends in the winter. They inhabited shallow, slow water velocity areas from May to September. They inhabited deeper, moderate velocity areas from October to April. We did not observe ice jams and associated riverbed scour at hibernacula, but did observe them elsewhere. Ice jams may be spatially predictable and influence the distribution of riverine turtles during autumn and winter. Preservation of dissimilar habitats used during major portions of the life cycle (lateral habitats, islands, and hibernacula) and natural streamflow patterns, which influenced timing of habitat availability and turtle movement, may facilitate continued existence of Spiny Softshell Turtles in the Missouri River in Montana
","language":"English","publisher":"Herpetological Conservation and Biology","usgsCitation":"Tornabene, B., Bramblett, R.G., Zale, A.V., and Leathe, S.A., 2017, Spatiotemporal ecology of Apalone spinifera in a large, Great Plains river ecosystem: Herpetological Conservation and Biology, v. 12, no. 1, p. 252-271.","productDescription":"20 p.","startPage":"252","endPage":"271","ipdsId":"IP-071425","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":348308,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":347693,"type":{"id":15,"text":"Index Page"},"url":"https://www.herpconbio.org/contents_vol12_issue1.html"}],"volume":"12","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a07e90fe4b09af898c8cbeb","contributors":{"authors":[{"text":"Tornabene, Brian J.","contributorId":200041,"corporation":false,"usgs":false,"family":"Tornabene","given":"Brian J.","affiliations":[],"preferred":false,"id":720774,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bramblett, Robert G.","contributorId":169857,"corporation":false,"usgs":false,"family":"Bramblett","given":"Robert","email":"","middleInitial":"G.","affiliations":[{"id":5098,"text":"Department of Ecology, Montana State University","active":true,"usgs":false}],"preferred":false,"id":720775,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zale, Alexander V. 0000-0003-1703-885X zale@usgs.gov","orcid":"https://orcid.org/0000-0003-1703-885X","contributorId":3010,"corporation":false,"usgs":true,"family":"Zale","given":"Alexander","email":"zale@usgs.gov","middleInitial":"V.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":717743,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Leathe, Stephen A.","contributorId":200042,"corporation":false,"usgs":false,"family":"Leathe","given":"Stephen","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":720776,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70188545,"text":"70188545 - 2017 - Evidence for strong lateral seismic velocity variation in the lower crust and upper mantle beneath the California margin","interactions":[],"lastModifiedDate":"2017-06-15T12:15:46","indexId":"70188545","displayToPublicDate":"2017-04-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1427,"text":"Earth and Planetary Science Letters","active":true,"publicationSubtype":{"id":10}},"title":"Evidence for strong lateral seismic velocity variation in the lower crust and upper mantle beneath the California margin","docAbstract":"Regional seismograms from earthquakes in Northern California show a systematic difference in arrival times across Southern California where long period (30–50 seconds) SH waves arrive up to 15 seconds earlier at stations near the coast compared with sites towards the east at similar epicentral distances. We attribute this time difference to heterogeneity of the velocity structure at the crust-mantle interface beneath the California margin. To model these observations, we propose a fast seismic layer, with thickness growing westward from the San Andreas along with a thicker and slower continental crust to the east. Synthetics generated from such a model are able to match the observed timing of SH waveforms better than existing 3D models. The presence of a strong upper mantle buttressed against a weaker crust has a major influence in how the boundary between the Pacific plate and North American plate deforms and may explain the observed asymmetric strain rate across the boundary.","language":"English","publisher":"Elsevier","doi":"10.1016/j.epsl.2017.02.002","usgsCitation":"Lai, V., Graves, R., Wei, S., and Helmberger, D., 2017, Evidence for strong lateral seismic velocity variation in the lower crust and upper mantle beneath the California margin: Earth and Planetary Science Letters, p. 202-211, https://doi.org/10.1016/j.epsl.2017.02.002.","productDescription":"10 p. ","startPage":"202","endPage":"211","ipdsId":"IP-080254","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":461653,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.epsl.2017.02.002","text":"Publisher Index Page"},{"id":342548,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States ","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.33349609375,\n 38.41916639395372\n ],\n [\n -122.091064453125,\n 36.55377524336089\n ],\n [\n -122.04711914062499,\n 36.13787471840729\n ],\n [\n -121.73950195312499,\n 35.67514743608467\n ],\n [\n -121.46484375,\n 35.35321610123823\n ],\n [\n -120.9375,\n 34.97600151317588\n ],\n [\n -120.87158203125,\n 34.786739162702524\n ],\n [\n -120.88256835937499,\n 34.49750272138159\n ],\n [\n -120.728759765625,\n 34.30714385628804\n ],\n [\n -120.5419921875,\n 34.23451236236987\n ],\n [\n -120.201416015625,\n 34.225429015241396\n ],\n [\n -119.44335937499999,\n 34.288991865037524\n ],\n [\n -118.05908203124999,\n 35.16482750605027\n ],\n [\n -117.344970703125,\n 35.71975793933433\n ],\n [\n -116.8505859375,\n 36.11125252076156\n ],\n [\n -119.33349609375,\n 38.41916639395372\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59439c94e4b062508e31a9af","contributors":{"authors":[{"text":"Lai, Voon","contributorId":192952,"corporation":false,"usgs":false,"family":"Lai","given":"Voon","affiliations":[],"preferred":false,"id":698269,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Graves, Robert 0000-0001-9758-453X rwgraves@usgs.gov","orcid":"https://orcid.org/0000-0001-9758-453X","contributorId":140738,"corporation":false,"usgs":true,"family":"Graves","given":"Robert","email":"rwgraves@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":698268,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wei, Shengji","contributorId":192953,"corporation":false,"usgs":false,"family":"Wei","given":"Shengji","email":"","affiliations":[],"preferred":false,"id":698270,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Helmberger, Don","contributorId":192954,"corporation":false,"usgs":false,"family":"Helmberger","given":"Don","email":"","affiliations":[],"preferred":false,"id":698271,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70186216,"text":"70186216 - 2017 - Long-term spatial heterogeneity in mallard distribution in the Prairie pothole region","interactions":[],"lastModifiedDate":"2017-03-31T15:21:45","indexId":"70186216","displayToPublicDate":"2017-03-31T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3779,"text":"Wildlife Society Bulletin","onlineIssn":"1938-5463","printIssn":"0091-7648","active":true,"publicationSubtype":{"id":10}},"title":"Long-term spatial heterogeneity in mallard distribution in the Prairie pothole region","docAbstract":"The Prairie Pothole Region (PPR) of north-central United States and south-central Canada supports greater than half of all breeding mallards (Anas platyrhynchos) annually counted in North America and is the focus of widespread conservation and research efforts. Allocation of conservation resources for this socioeconomically important population would benefit from an understanding of the nature of spatiotemporal variation in distribution of breeding mallards throughout the 850,000 km2 landscape. We used mallard counts from the Waterfowl Breeding Population and Habitat Survey to test for spatial heterogeneity and identify high- and low-abundance regions of breeding mallards over a 50-year time series. We found strong annual spatial heterogeneity in all years: 90% of mallards counted annually were on an average of only 15% of surveyed segments. Using a local indicator of spatial autocorrelation, we found a relatively static distribution of low-count clusters in northern Montana, USA, and southern Alberta, Canada, and a dynamic distribution of high-count clusters throughout the study period. Distribution of high-count clusters shifted southeast from northwestern portions of the PPR in Alberta and western Saskatchewan, Canada, to North and South Dakota, USA, during the latter half of the study period. This spatial redistribution of core mallard breeding populations was likely driven by interactions between environmental variation that created favorable hydrological conditions for wetlands in the eastern PPR and dynamic land-use patterns related to upland cropping practices and government land-retirement programs. Our results highlight an opportunity for prioritizing relatively small regions within the PPR for allocation of wetland and grassland conservation for mallard populations. However, the extensive spatial heterogeneity in core distributions over our study period suggests such spatial prioritization will have to overcome challenges presented by dynamic land-use and climate patterns in the region, and thus merits additional monitoring and empirical research to anticipate future population distribution. Published 2017. This article is a U.S. Government work and is in the public domain in the USA.
","language":"English","publisher":"Wiley","doi":"10.1002/wsb.747","usgsCitation":"Janke, A.K., Anteau, M.J., and Stafford, J.D., 2017, Long-term spatial heterogeneity in mallard distribution in the Prairie pothole region: Wildlife Society Bulletin, v. 41, no. 1, p. 116-124, https://doi.org/10.1002/wsb.747.","productDescription":"9 p.","startPage":"116","endPage":"124","ipdsId":"IP-066605","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":469979,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://lib.dr.iastate.edu/nrem_pubs/208","text":"External Repository"},{"id":338982,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"41","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-03-22","publicationStatus":"PW","scienceBaseUri":"58df6abee4b02ff32c6aea25","contributors":{"authors":[{"text":"Janke, Adam K. 0000-0003-2781-7857","orcid":"https://orcid.org/0000-0003-2781-7857","contributorId":130959,"corporation":false,"usgs":false,"family":"Janke","given":"Adam","email":"","middleInitial":"K.","affiliations":[{"id":7176,"text":"Dept of Natl Res Mgmt, SDSU, Brookings, SD","active":true,"usgs":false}],"preferred":false,"id":687899,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anteau, Michael J. 0000-0002-5173-5870 manteau@usgs.gov","orcid":"https://orcid.org/0000-0002-5173-5870","contributorId":3427,"corporation":false,"usgs":true,"family":"Anteau","given":"Michael","email":"manteau@usgs.gov","middleInitial":"J.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":687903,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stafford, Joshua D. jstafford@usgs.gov","contributorId":4267,"corporation":false,"usgs":true,"family":"Stafford","given":"Joshua","email":"jstafford@usgs.gov","middleInitial":"D.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":687904,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70187422,"text":"70187422 - 2017 - Reconnaissance sedimentology of selected tertiary exposures in the upland region bordering the Yukon Flats basin, east-central Alaska","interactions":[],"lastModifiedDate":"2017-05-08T13:48:52","indexId":"70187422","displayToPublicDate":"2017-03-31T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"seriesTitle":{"id":5388,"text":"Preliminary Interpretive Report","active":true,"publicationSubtype":{"id":2}},"seriesNumber":"2016-6","title":"Reconnaissance sedimentology of selected tertiary exposures in the upland region bordering the Yukon Flats basin, east-central Alaska","docAbstract":"This report summarizes reconnaissance sedimentologic and stratigraphic observations made during six days of helicopter-supported fieldwork in 2002 on Tertiary sedimentary rocks exposed in the upland region around the flanks of the Yukon Flats basin in east-central Alaska (fig. 1). This project was a cooperative effort between the Alaska Division of Geological & Geophysical Surveys (DGGS) and the U.S. Geological Survey (USGS) to investigate the geology of the basin in preparation for an assessment of the undiscovered, technically recoverable hydrocarbon resources (Stanley and others, 2004). Field observations and interpretations summarized in this report are reconnaissance level. At most, no more than a few hours were spent on the ground at any location. Measured sections included in this report are sketch sec- tions and thicknesses shown are approximate. Relatively detailed observations were made by the authors at only three locations, including The Mudbank (Hodzana River), Rampart (east bank of the Yukon River), and Bryant Creek (along the Tintina fault near the Canada border). These three locations are described first in relative detail, then followed by general descriptions of other locations.
","language":"English","publisher":"Alaska Division of Geological & Geophysical Surveys","doi":"10.14509/29700","usgsCitation":"LePain, D.L., and Stanley, R.G., 2017, Reconnaissance sedimentology of selected tertiary exposures in the upland region bordering the Yukon Flats basin, east-central Alaska: Preliminary Interpretive Report 2016-6, vi, 14 p., https://doi.org/10.14509/29700.","productDescription":"vi, 14 p.","ipdsId":"IP-079523","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":469978,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.14509/29700","text":"Publisher Index Page"},{"id":340755,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Yukon Flats","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.06103515624997,\n 66.86108230224609\n ],\n [\n -153.896484375,\n 63.73390885572919\n ],\n [\n -141.08642578125,\n 65.22910188319217\n ],\n [\n -142.93212890625,\n 68.13885164925573\n ],\n [\n -155.06103515624997,\n 66.86108230224609\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"590aec49e4b0fc4e4492aba5","contributors":{"authors":[{"text":"LePain, David L.","contributorId":191714,"corporation":false,"usgs":false,"family":"LePain","given":"David","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":693953,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stanley, Richard G. 0000-0001-6192-8783 rstanley@usgs.gov","orcid":"https://orcid.org/0000-0001-6192-8783","contributorId":1832,"corporation":false,"usgs":true,"family":"Stanley","given":"Richard","email":"rstanley@usgs.gov","middleInitial":"G.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":693952,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70181024,"text":"ofr20171016 - 2017 - Numerical modeling of the effects of Hurricane Sandy and potential future hurricanes on spatial patterns of salt marsh morphology in Jamaica Bay, New York City","interactions":[],"lastModifiedDate":"2017-03-29T15:19:26","indexId":"ofr20171016","displayToPublicDate":"2017-03-29T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-1016","title":"Numerical modeling of the effects of Hurricane Sandy and potential future hurricanes on spatial patterns of salt marsh morphology in Jamaica Bay, New York City","docAbstract":"The salt marshes of Jamaica Bay, managed by the New York City Department of Parks & Recreation and the Gateway National Recreation Area of the National Park Service, serve as a recreational outlet for New York City residents, mitigate flooding, and provide habitat for critical wildlife species. Hurricanes and extra-tropical storms have been recognized as one of the critical drivers of coastal wetland morphology due to their effects on hydrodynamics and sediment transport, deposition, and erosion processes. However, the magnitude and mechanisms of hurricane effects on sediment dynamics and associated coastal wetland morphology in the northeastern United States are poorly understood. In this study, the depth-averaged version of the Delft3D modeling suite, integrated with field measurements, was utilized to examine the effects of Hurricane Sandy and future potential hurricanes on salt marsh morphology in Jamaica Bay, New York City. Hurricane Sandy-induced wind, waves, storm surge, water circulation, sediment transport, deposition, and erosion were simulated by using the modeling system in which vegetation effects on flow resistance, surge reduction, wave attenuation, and sedimentation were also incorporated. Observed marsh elevation change and accretion from a rod surface elevation table and feldspar marker horizons and cesium-137- and lead-210-derived long-term accretion rates were used to calibrate and validate the wind-waves-surge-sediment transport-morphology coupled model.
The model results (storm surge, waves, and marsh deposition and erosion) agreed well with field measurements. The validated modeling system was then used to detect salt marsh morphological change due to Hurricane Sandy across the entire Jamaica Bay over the short-term (for example, 4 days and 1 year) and long-term (for example, 5 and 10 years). Because Hurricanes Sandy (2012) and Irene (2011) were two large and destructive tropical cyclones which hit the northeast coast, the validated coupled model was run to predict the effects of Sandy-like and Irene-like hurricanes with different storm tracks and wind intensities on wetland morphology in Jamaica Bay. Model results indicate that, in Jamaica Bay salt marshes, the morphological changes (greater than 5 millimeters [mm] determined by the long-term marsh accretion rate) caused by Hurricane Sandy were complex and spatially heterogeneous. Most of the erosion (5–40 mm) and deposition (5–30 mm) were mainly characterized by fine sand for channels and bay bottoms and by mud for marsh areas. Hurricane Sandy-generated deposition and erosion were generated locally. The storm-induced net sediment input through Rockaway Inlet was only about 1 percent of the total amount of the sediment reworked by the hurricane. Salt marshes inside the western part of the bay showed erosion overall while marshes inside the eastern part showed deposition from Hurricane Sandy. Model results indicated that most of the marshes could recover from Hurricane Sandy-induced erosion after 1 year and demonstrated continued marsh accretion after the hurricane over the course of long simulation periods although the effect (accretion) was diminished. Local waves and currents generated by Hurricane Sandy appeared to play a critical role in sediment transport and associated wetland morphological change in Jamaica Bay. Hypothetical hurricanes, depending on their track and intensity, cause variable responses in spatial patterns of sediment deposition and erosion compared to simulations without the hurricane. In general, hurricanes passing west of the Jamaica Bay estuary appear to be more destructive to the salt marshes than those passing the east. Consequently, marshes inside the western part of the bay were likely to be more vulnerable to hurricanes than marshes inside the eastern part of the bay.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171016","usgsCitation":"Wang, H., Chen, Q., Hu, K., Snedden, G.A., Hartig, E.K., Couvillion, B.R., Johnson, C.L., and Orton, P.M., 2017, Numerical modeling of the effects of Hurricane Sandy and potential future hurricanes on spatial patterns of salt marsh morphology in Jamaica Bay, New York City: U.S. Geological Survey Open-File Report 2017–1016, 43 p., https://doi.org/10.3133/ofr20171016.","productDescription":"vii, 43 p.","numberOfPages":"56","onlineOnly":"Y","ipdsId":"IP-079827","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":338515,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1016/coverthb.jpg"},{"id":338516,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1016/ofr20171016.pdf","text":"Report","size":"30.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017–1016"}],"country":"United States","state":"New York","city":"New York City","otherGeospatial":"Jamaica Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.95687103271484,\n 40.539112438263516\n ],\n [\n -73.72684478759766,\n 40.539112438263516\n ],\n [\n -73.72684478759766,\n 40.658503716866974\n ],\n [\n -73.95687103271484,\n 40.658503716866974\n ],\n [\n -73.95687103271484,\n 40.539112438263516\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"
Director, Wetland and Aquatic Research Center
U.S. Geological Survey
7920 NW 71st Street
Gainesville, FL 32653
https://www.usgs.gov/centers/wetland-and-aquatic-research-center-warc
","tableOfContents":"Scientists from the U.S. Geological Survey St. Petersburg Coastal and Marine Science Center in St. Petersburg, Florida, conducted a bathymetric survey of Fire Island, New York, from October 5 to 10, 2014. The U.S. Geological Survey is involved in a post-Hurricane Sandy effort to map and monitor the morphologic evolution of the wilderness breach, which formed in October 2012 during Hurricane Sandy, as part of the Hurricane Sandy Supplemental Project GS2-2B. During this study, bathymetry data were collected, using single-beam echo sounders and global positioning systems mounted to personal watercraft, along the Fire Island shoreface and within the wilderness breach, Fire Island Inlet, Narrow Bay, and Great South Bay east of Nicoll Bay. Additional bathymetry and elevation data were collected using backpack and wheel-mounted global positioning systems along the subaerial beach (foreshore and backshore), flood shoals, and shallow channels within the wilderness breach and adjacent shoreface.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1034","usgsCitation":"Nelson, T.R., Miselis, J.L., Hapke, C.J., Brenner, O.T., Henderson, R.E., Reynolds, B.J., and Wilson, K.E., 2017, Bathymetry data collected in October 2014 from Fire Island, New York—The wilderness breach, shoreface, and bay: U.S. Geological Survey Data Series 1034, https://doi.org/10.3133/ds1034.","productDescription":"HTML Document","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-071668","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":337454,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1034/index.html","text":"Report HTML","linkFileType":{"id":5,"text":"html"},"description":"DS 1034"},{"id":337453,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1034/coverthb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Fire Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.3172607421875,\n 40.60821853973967\n ],\n [\n -72.77412414550781,\n 40.60821853973967\n ],\n [\n -72.77412414550781,\n 40.77586181063573\n ],\n [\n -73.3172607421875,\n 40.77586181063573\n ],\n [\n -73.3172607421875,\n 40.60821853973967\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, St. Petersburg Coastal and Marine Science Center
U.S. Geological Survey
600 4th Street South
St. Petersburg, FL 33701
https://coastal.er.usgs.gov/