In January 2015, the U.S. Geological Survey National Geospatial Technical Operations Center began producing the 1-Meter Digital Elevation Model data product. This new product was developed to provide high resolution bare-earth digital elevation models from light detection and ranging (lidar) elevation data and other elevation data collected over the conterminous United States (lower 48 States), Hawaii, and potentially Alaska and the U.S. territories. The 1-Meter Digital Elevation Model consists of hydroflattened, topographic bare-earth raster digital elevation models, with a 1-meter x 1-meter cell size, and is available in 10,000-meter x 10,000-meter square blocks with a 6-meter overlap. This report details the specifications required for the production of the 1-Meter Digital Elevation Model.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Section B: U.S. Geological Survey Standards in Book 11: Collection and Delineation of Spatial Data","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm11B7","usgsCitation":"Arundel, S.T., Archuleta, C.M., Phillips, L.A., Roche, B.L., and Constance, E.W., 2015, 1-meter digital elevation model specification: U.S. Geological Survey Techniques and Methods, book 11, chap. B7, 25 p. with appendixes, https://dx.doi.org/10.3133/tm11B7.","productDescription":"vi, 25 p.","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-066922","costCenters":[{"id":404,"text":"NGTOC Rolla","active":true,"usgs":true}],"links":[{"id":310105,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/11/b07/coverthb.jpg"},{"id":310106,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/11/b07/tm11-b7.pdf","text":"Report","size":"2.35 MB","linkFileType":{"id":1,"text":"pdf"},"description":"T&M 11–B7"}],"publicComments":"This report is Chapter 7 of Section B: U.S. Geological Survey Standards in Book 11: Collection and Delineation of Spatial Data","contact":"Director, National Geospatial Technical Operations Center
U.S. Geological Survey
1400 Independence Road
Rolla, MO 65401–2602
http://ngtoc.usgs.gov/
","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"publishedDate":"2015-10-21","noUsgsAuthors":false,"publicationDate":"2015-10-21","publicationStatus":"PW","scienceBaseUri":"5628a91ce4b0d158f5926bf3","contributors":{"authors":[{"text":"Arundel, Samantha T. sarundel@usgs.gov","contributorId":4920,"corporation":false,"usgs":true,"family":"Arundel","given":"Samantha","email":"sarundel@usgs.gov","middleInitial":"T.","affiliations":[{"id":404,"text":"NGTOC Rolla","active":true,"usgs":true}],"preferred":false,"id":573588,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Archuleta, Christy-Ann M. 0000-0002-4522-8573 carchule@usgs.gov","orcid":"https://orcid.org/0000-0002-4522-8573","contributorId":2128,"corporation":false,"usgs":true,"family":"Archuleta","given":"Christy-Ann","email":"carchule@usgs.gov","middleInitial":"M.","affiliations":[{"id":404,"text":"NGTOC Rolla","active":true,"usgs":true}],"preferred":false,"id":573593,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Phillips, Lori A. 0000-0002-9299-5134 lphillips@usgs.gov","orcid":"https://orcid.org/0000-0002-9299-5134","contributorId":5185,"corporation":false,"usgs":true,"family":"Phillips","given":"Lori","email":"lphillips@usgs.gov","middleInitial":"A.","affiliations":[{"id":404,"text":"NGTOC Rolla","active":true,"usgs":true}],"preferred":true,"id":573589,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Roche, Brittany L. broche@usgs.gov","contributorId":148003,"corporation":false,"usgs":true,"family":"Roche","given":"Brittany L.","email":"broche@usgs.gov","affiliations":[{"id":404,"text":"NGTOC Rolla","active":true,"usgs":true}],"preferred":false,"id":573590,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Constance, Eric W. 0000-0001-9687-7066 econstance@usgs.gov","orcid":"https://orcid.org/0000-0001-9687-7066","contributorId":2056,"corporation":false,"usgs":true,"family":"Constance","given":"Eric","email":"econstance@usgs.gov","middleInitial":"W.","affiliations":[{"id":404,"text":"NGTOC Rolla","active":true,"usgs":true}],"preferred":true,"id":573592,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70168439,"text":"70168439 - 2015 - Projected future vegetation changes for the northwest United States and southwest Canada at a fine spatial resolution using a dynamic global vegetation model.","interactions":[],"lastModifiedDate":"2016-02-17T08:47:53","indexId":"70168439","displayToPublicDate":"2015-10-21T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Projected future vegetation changes for the northwest United States and southwest Canada at a fine spatial resolution using a dynamic global vegetation model.","docAbstract":"
Future climate change may significantly alter the distributions of many plant taxa. The effects of climate change may be particularly large in mountainous regions where climate can vary significantly with elevation. Understanding potential future vegetation changes in these regions requires methods that can resolve vegetation responses to climate change at fine spatial resolutions. We used LPJ, a dynamic global vegetation model, to assess potential future vegetation changes for a large topographically complex area of the northwest United States and southwest Canada (38.0–58.0°N latitude by 136.6–103.0°W longitude). LPJ is a process-based vegetation model that mechanistically simulates the effect of changing climate and atmospheric CO2 concentrations on vegetation. It was developed and has been mostly applied at spatial resolutions of 10-minutes or coarser. In this study, we used LPJ at a 30-second (~1-km) spatial resolution to simulate potential vegetation changes for 2070–2099. LPJ was run using downscaled future climate simulations from five coupled atmosphere-ocean general circulation models (CCSM3, CGCM3.1(T47), GISS-ER, MIROC3.2(medres), UKMO-HadCM3) produced using the A2 greenhouse gases emissions scenario. Under projected future climate and atmospheric CO2 concentrations, the simulated vegetation changes result in the contraction of alpine, shrub-steppe, and xeric shrub vegetation across the study area and the expansion of woodland and forest vegetation. Large areas of maritime cool forest and cold forest are simulated to persist under projected future conditions. The fine spatial-scale vegetation simulations resolve patterns of vegetation change that are not visible at coarser resolutions and these fine-scale patterns are particularly important for understanding potential future vegetation changes in topographically complex areas.
","language":"English","publisher":"Public Library of Science","publisherLocation":"San Francisco, CA","doi":"10.1371/journal.pone.0138759","usgsCitation":"Shafer, S., Bartlein, P.J., Gray, E.M., and Pelltier, R.T., 2015, Projected future vegetation changes for the northwest United States and southwest Canada at a fine spatial resolution using a dynamic global vegetation model.: PLoS ONE, v. 10, no. 10, e0138759, 21 p., https://doi.org/10.1371/journal.pone.0138759.","productDescription":"e0138759, 21 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-051960","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":471711,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0138759","text":"Publisher Index Page"},{"id":438677,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F73X84PH","text":"USGS data release","linkHelpText":"LPJ biomes (30-year mean) simulated using monthly historical (1901-2000) CRU TS 2.1 climate data and projected future (2001-2099) CMIP3 A2 and A1B simulated climate data on a 30-second grid of the northwest United States and southwest Canada, version 1.0"},{"id":438676,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7CF9N51","text":"USGS data release","linkHelpText":"Bioclimatic variables calculated from statistically-downscaled historical (1901-2000) CRU TS 2.1 climate data and projected future (2001-2099) CMIP3 A2 and A1B simulated climate data on a 30-second grid of the northwest United States and southwest Canada, version 1.0"},{"id":438675,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7H70CWW","text":"USGS data release","linkHelpText":"Statistically-downscaled monthly historical (1901-2000) CRU TS 2.1 and projected future (2001-2099) CMIP3 A2 and A1B simulated temperature, precipitation, and sunshine data on a 30-second grid of the northwest United States and southwest Canada, version 1.0"},{"id":318024,"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 -136.6,\n 38\n ],\n [\n -136.6,\n 58\n ],\n [\n -103,\n 58\n ],\n [\n -103,\n 38\n ],\n [\n -136.6,\n 38\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"10","issue":"10","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-10-21","publicationStatus":"PW","scienceBaseUri":"56c304cce4b0946c652087b4","contributors":{"authors":[{"text":"Shafer, Sarah 0000-0003-3739-2637 sshafer@usgs.gov","orcid":"https://orcid.org/0000-0003-3739-2637","contributorId":149866,"corporation":false,"usgs":true,"family":"Shafer","given":"Sarah","email":"sshafer@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":620140,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bartlein, Patrick J.","contributorId":106879,"corporation":false,"usgs":true,"family":"Bartlein","given":"Patrick","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":620141,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gray, Elizabeth M.","contributorId":166817,"corporation":false,"usgs":false,"family":"Gray","given":"Elizabeth","email":"","middleInitial":"M.","affiliations":[{"id":24533,"text":"The Nature Conservancy of Maryland/DC, Bethesda, Maryland","active":true,"usgs":false}],"preferred":false,"id":620142,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pelltier, Richard T. 0000-0001-8322-7961 rtpelltier@usgs.gov","orcid":"https://orcid.org/0000-0001-8322-7961","contributorId":4683,"corporation":false,"usgs":true,"family":"Pelltier","given":"Richard","email":"rtpelltier@usgs.gov","middleInitial":"T.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":620143,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70159278,"text":"70159278 - 2015 - Monitoring, field experiments, and geochemical modeling of Fe(II) oxidation kinetics in a stream dominated by net-alkaline coal-mine drainage, Pennsylvania, USA","interactions":[],"lastModifiedDate":"2016-08-19T18:38:59","indexId":"70159278","displayToPublicDate":"2015-10-20T15:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":835,"text":"Applied Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Monitoring, field experiments, and geochemical modeling of Fe(II) oxidation kinetics in a stream dominated by net-alkaline coal-mine drainage, Pennsylvania, USA","docAbstract":"Watershed-scale monitoring, field aeration experiments, and geochemical equilibrium and kinetic modeling were conducted to evaluate interdependent changes in pH, dissolved CO2, O2, and Fe(II) concentrations that typically take place downstream of net-alkaline, circumneutral coal-mine drainage (CMD) outfalls and during aerobic treatment of such CMD. The kinetic modeling approach, using PHREEQC, accurately simulates observed variations in pH, Fe(II) oxidation, alkalinity consumption, and associated dissolved gas concentrations during transport downstream of the CMD outfalls (natural attenuation) and during 6-h batch aeration tests on the CMD using bubble diffusers (enhanced attenuation). The batch aeration experiments demonstrated that aeration promoted CO2 outgassing, thereby increasing pH and the rate of Fe(II) oxidation. The rate of Fe(II) oxidation was accurately estimated by the abiotic homogeneous oxidation rate law −d[Fe(II)]/dt = k1·[O2]·[H+]−2·[Fe(II)] that indicates an increase in pH by 1 unit at pH 5–8 and at constant dissolved O2 (DO) concentration results in a 100-fold increase in the rate of Fe(II) oxidation. Adjusting for sample temperature, a narrow range of values for the apparent homogeneous Fe(II) oxidation rate constant (k1′) of 0.5–1.7 times the reference value of k1 = 3 × 10−12 mol/L/min (for pH 5–8 and 20 °C), reported by Stumm and Morgan (1996), was indicated by the calibrated models for the 5-km stream reach below the CMD outfalls and the aerated CMD. The rates of CO2 outgassing and O2ingassing in the model were estimated with first-order asymptotic functions, whereby the driving force is the gradient of the dissolved gas concentration relative to equilibrium with the ambient atmosphere. Although the progressive increase in DO concentration to saturation could be accurately modeled as a kinetic function for the conditions evaluated, the simulation of DO as an instantaneous equilibrium process did not affect the model results for Fe(II) or pH. In contrast, the model results for pH and Fe(II) were sensitive to the CO2 mass transfer rate constant (kL,CO2a). The value of kL,CO2a estimated for the stream (0.010 min−1) was within the range for the batch aeration experiments (0–0.033 min−1). These results indicate that the abiotic homogeneous Fe(II) oxidation rate law, with adjustments for variations in temperature and CO2 outgassing rate, may be applied to predict changes in aqueous iron and pH for net-alkaline, ferruginous waters within a stream (natural conditions) or a CMD treatment system (engineered conditions).
","language":"English","publisher":"Pergamon","doi":"10.1016/j.apgeochem.2015.02.009","usgsCitation":"Cravotta, C.A., 2015, Monitoring, field experiments, and geochemical modeling of Fe(II) oxidation kinetics in a stream dominated by net-alkaline coal-mine drainage, Pennsylvania, USA: Applied Geochemistry, v. 62, p. 96-107, https://doi.org/10.1016/j.apgeochem.2015.02.009.","productDescription":"12 p.","startPage":"96","endPage":"107","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056783","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":310196,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Pennsylvania","otherGeospatial":"Schuylkill River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.05422973632812,\n 40.84446321237158\n ],\n [\n -76.11465454101562,\n 40.84342432639293\n ],\n [\n -76.18125915527344,\n 40.82991732677595\n ],\n [\n -76.27120971679688,\n 40.80809251416925\n ],\n [\n -76.3165283203125,\n 40.78626052122175\n ],\n [\n -76.33987426757812,\n 40.7519385984599\n ],\n [\n -76.35017395019531,\n 40.71343536379427\n ],\n [\n -76.35223388671875,\n 40.66918118282895\n ],\n [\n -76.33026123046874,\n 40.617079816381285\n ],\n [\n -76.30691528320311,\n 40.594663726004995\n ],\n [\n -76.27052307128906,\n 40.57849862511043\n ],\n [\n -76.21147155761719,\n 40.560764667193595\n ],\n [\n -76.14761352539062,\n 40.565981025008355\n ],\n [\n -76.09130859375,\n 40.58162765924269\n ],\n [\n -76.04667663574219,\n 40.613952441166596\n ],\n [\n -75.97457885742188,\n 40.66657708045136\n ],\n [\n -75.95878601074219,\n 40.71499673906409\n ],\n [\n -75.95466613769531,\n 40.75453936473234\n ],\n [\n -75.94917297363281,\n 40.809391811146064\n ],\n [\n -75.96256256103516,\n 40.824201998489876\n ],\n [\n -75.97766876220703,\n 40.83745041598948\n ],\n [\n -76.01303100585938,\n 40.844982649254064\n ],\n [\n -76.05422973632812,\n 40.84446321237158\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"62","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"562757a6e4b0d158f5926501","contributors":{"authors":[{"text":"Cravotta, Charles A. III, 0000-0003-3116-4684 cravotta@usgs.gov","orcid":"https://orcid.org/0000-0003-3116-4684","contributorId":2193,"corporation":false,"usgs":true,"family":"Cravotta","given":"Charles","suffix":"III,","email":"cravotta@usgs.gov","middleInitial":"A.","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":false,"id":577954,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70159199,"text":"70159199 - 2015 - Taking a systems approach to ecological systems","interactions":[],"lastModifiedDate":"2016-07-11T15:39:13","indexId":"70159199","displayToPublicDate":"2015-10-20T15:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2490,"text":"Journal of Vegetation Science","active":true,"publicationSubtype":{"id":10}},"title":"Taking a systems approach to ecological systems","docAbstract":"Increasingly, there is interest in a systems-level understanding of ecological problems, which requires the evaluation of more complex, causal hypotheses. In this issue of the Journal of Vegetation Science, Soliveres et al. use structural equation modeling to test a causal network hypothesis about how tree canopies affect understorey communities. Historical analysis suggests structural equation modeling has been under-utilized in ecology.
","language":"English","publisher":"Wiley","doi":"10.1111/jvs.12340","usgsCitation":"Grace, J.B., 2015, Taking a systems approach to ecological systems: Journal of Vegetation Science, v. 26, no. 6, p. 1025-1027, https://doi.org/10.1111/jvs.12340.","productDescription":"3 p.","startPage":"1025","endPage":"1027","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-067715","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":471714,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/jvs.12340","text":"Publisher Index Page"},{"id":310194,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"26","issue":"6","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2015-10-14","publicationStatus":"PW","scienceBaseUri":"562757a9e4b0d158f5926509","contributors":{"authors":[{"text":"Grace, James B. 0000-0001-6374-4726 gracej@usgs.gov","orcid":"https://orcid.org/0000-0001-6374-4726","contributorId":884,"corporation":false,"usgs":true,"family":"Grace","given":"James","email":"gracej@usgs.gov","middleInitial":"B.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":577836,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70155234,"text":"ofr20101274 - 2015 - Geologic and geophysical maps of the El Casco 7.5′ quadrangle, Riverside County, southern California, with accompanying geologic-map database","interactions":[],"lastModifiedDate":"2022-04-18T21:08:50.251635","indexId":"ofr20101274","displayToPublicDate":"2015-10-20T15:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2010-1274","title":"Geologic and geophysical maps of the El Casco 7.5′ quadrangle, Riverside County, southern California, with accompanying geologic-map database","docAbstract":"Earth materials and structures in the El Casco quadrangle provide considerable information about the late Cenozoic geologic evolution of southern California’s Inland Empire region (fig. 2). Important structural and stratigraphic elements include (1) modern traces of the right-lateral San Jacinto Fault zone, (2) older traces of the San Jacinto Fault zone, and (3) sedimentary materials and geologic structures that formed during the last eight million years or so and that record interactions within the San Andreas Fault system. These materials, and the structures that deform them, provide a geologic context 3 for investigations of groundwater recharge and subsurface flow (Waring, 1919; Burnham and Dutcher, 1960; Bloyd, 1971; Rewis and others, 2006).
\nThis geologic database of the El Casco 7.5′ quadrangle was prepared by the Basins and Landscape Co-Evolution Project (BALANCE), a regional geologic-mapping project sponsored jointly by the U.S. Geological Survey and the California Geological Survey. The database was developed as a contribution to the National Cooperative Geologic Mapping Program’s National Geologic Map Database, and provides a general geologic setting of the El Casco quadrangle. The database and map provide information about earth materials and geologic structures, including faults and folds that have developed in the quadrangle due to complexities in the San Andreas Fault system.
\nGeologic information contained in the El Casco database is general-purpose data applicable to land-related investigations in the earth and biological sciences. The term “general-purpose” means that all geologic-feature classes have minimal information content adequate to characterize their general geologic characteristics and to interpret their general geologic history. However, no single feature class has enough information to definitively characterize its properties and origin. For this reason the database cannot be used for site-specific geologic evaluations, although it can be used to plan and guide investigations at the site-specific level.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20101274","usgsCitation":"Matti, J.C., Morton, D.M., and Langenheim, V., 2015, Geologic and geophysical maps of the El Casco 7.5′ quadrangle, Riverside County, southern California, with accompanying geologic-map database: U.S. Geological Survey Open-File Report 2010-1274, Report: vi, 141; 3 Sheets: 46.77 x 36.00 inches or smaller; Dataset; Metadata; Read Me, https://doi.org/10.3133/ofr20101274.","productDescription":"Report: vi, 141; 3 Sheets: 46.77 x 36.00 inches or smaller; Dataset; Metadata; Read Me","numberOfPages":"147","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-021187","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":308467,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2010/1274/ofr20101274_pamphlet.pdf","text":"Pamphlet","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2010-1274 Pamphlet"},{"id":308466,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2010/1274/coverthb.jpg"},{"id":308468,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2010/1274/ofr20101274_sheet1.pdf","text":"Sheet 1","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2010-1274 Sheet 1","linkHelpText":"Plot file of the geologic map of the El Casco 7.5' quadrangle"},{"id":308472,"rank":7,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/of/2010/1274/ofr20101274_metadata.txt","text":"Metadata","linkFileType":{"id":2,"text":"txt"},"description":"OFR 2010-1274 Metadata"},{"id":308471,"rank":6,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/of/2010/1274/ofr20101274_readme.txt","text":"Read Me","linkFileType":{"id":2,"text":"txt"},"description":"OFR 2010-1274 Read Me"},{"id":399006,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_103546.htm"},{"id":308470,"rank":5,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2010/1274/ofr20101274_sheet3.pdf","text":"Sheet 3","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2010-1274 Sheet 3","linkHelpText":"Plot file of the gravity map"},{"id":308469,"rank":4,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2010/1274/ofr20101274_sheet2.pdf","text":"Sheet 2","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2010-1274 Sheet 2","linkHelpText":"Plot file of observation data for the El Casco 7.5' quadrangle"},{"id":308473,"rank":8,"type":{"id":28,"text":"Dataset"},"url":"https://pubs.usgs.gov/of/2010/1274/ofr20101274_data.zip","text":"Data","linkFileType":{"id":6,"text":"zip"},"description":"OFR 2010-1274 Data"}],"scale":"24000","country":"United States","state":"California","county":"Riverside County","otherGeospatial":"El Casco 7.5' quadrangle","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.125,\n 33.875\n ],\n [\n -117,\n 33.875\n ],\n [\n -117,\n 34\n ],\n [\n -117.125,\n 34\n ],\n [\n -117.125,\n 33.875\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"GMEG staff, Geology, Minerals, Energy, & Geophysics Science Center—Tucson
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http://geomaps.wr.usgs.gov/gmeg/
Trace-metal concentrations in sediment and in the clam Macoma petalum (formerly reported as Macoma balthica), clam reproductive activity, and benthic macroinvertebrate community structure were investigated in a mudflat 1 kilometer (km) south of the discharge of the Palo Alto Regional Water Quality Control Plant (PARWQCP) in South San Francisco Bay, Calif. This report includes the data collected by U.S. Geological Survey (USGS) scientists for the period January 2014 to December 2014. These append to long-term datasets extending back to 1974, and serve as the basis for the City of Palo Alto’s Near-Field Receiving Water Monitoring Program, initiated in 1994.
\nFollowing significant reductions in the late 1980s, silver (Ag) and copper (Cu) concentrations in sediment and M. petalum appear to have stabilized. Data for other metals, including chromium (Cr), mercury (Hg), nickel (Ni), selenium (Se), and zinc (Zn), have been collected since 1994. Over this period, concentrations of these elements have remained relatively constant, aside from seasonal variation that is common to all elements. In 2014, concentrations of Ag and Cu in M. petalum varied seasonally in response to a combination of site-specific metal exposures and annual growth and reproduction, as reported previously. Seasonal patterns for other elements, including Cr, Ni, Zn, Hg, and Se, were generally similar in timing and magnitude as those for Ag and Cu. In M. petalum, all observed elements showed annual maxima in January–February and minima in April, except for Zn, which was lowest in December. In sediments, annual maxima also occurred in January–February, and minima were measured in June and September. In 2014, metal concentrations in both sediments and clam tissue were among the lowest on record. This record suggests that regional-scale factors now largely control sedimentary and bioavailable concentrations of Ag and Cu, as well as other elements of regulatory interest, at the Palo Alto site.
\nAnalyses of the benthic community structure of a mudflat in South San Francisco Bay over a 40-year period show that changes in the community have occurred concurrent with reduced concentrations of metals in the sediment and in the tissues of the biosentinel clam, M. petalum, from the same area. Analysis of M. petalum shows increases in reproductive activity concurrent with the decline in metal concentrations in the tissues of this organism. Reproductive activity is presently stable (2014), with almost all animals initiating reproduction in the fall and spawning the following spring. The entire infaunal community has shifted from being dominated by several opportunistic species to a community where the species are more similar in abundance, a pattern that indicates a more stable community that is subjected to fewer stressors. In addition, two of the opportunistic species (Ampelisca abdita and Streblospio benedicti) that brood their young and live on the surface of the sediment in tubes have shown a continual decline in dominance coincident with the decline in metals; both species had short-lived rebounds in abundance in 2008, 2009, and 2010. Heteromastus filiformis (a subsurface polychaete worm that lives in the sediment, consumes sediment and organic particles residing in the sediment, and reproduces by laying its eggs on or in the sediment) showed a concurrent increase in dominance and, in the last several years before 2008, showed a stable population. H. filiformis abundance increased slightly in 2011–2012 and returned to pre-2011 numbers in 2014. An unidentified disturbance occurred on the mudflat in early 2008 that resulted in the loss of the benthic animals, except for deep-dwelling animals like Macoma petalum. However, within two months of this event animals returned to the mudflat. The resilience of the community suggested that the disturbance was not due to a persistent toxin or to anoxia. The reproductive mode of most species present in 2014 is reflective of species that were available either as pelagic larvae or as mobile adults. Although oviparous species were lower in number in this group, the authors hypothesize that these species will return slowly as more species move back into the area. The use of functional ecology was highlighted in the 2014 benthic community data, which showed that the animals that have now returned to the mudflat are those that can respond successfully to a physical, nontoxic disturbance. Today, community data show a mix of species that consume the sediment, or filter feed, have pelagic larvae that must survive landing on the sediment, and those that brood their young. USGS scientists view the 2008 disturbance event as a response by the infaunal community to an episodic natural stressor (possibly sediment accretion or a pulse of freshwater), in contrast to the long-term recovery from metal contamination. We will compare this recovery to the long-term recovery observed after the 1970’s when the decline in sediment pollutants was the dominating factor.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151199","usgsCitation":"Cain, D.J., Thompson, J.K., Crauder, J., Parcheso, F., Stewart, A.R., Kleckner, A.E., Dyke, J., Hornberger, M.I., and Luoma, S.N., 2015, Near-field receiving water monitoring of trace metals and a benthic community near the Palo Alto Regional Water Quality Control Plant in south San Francisco Bay, California: 2014: U.S. Geological Survey Open-File Report 2015-1199, viii, 79 p., https://doi.org/10.3133/ofr20151199.","productDescription":"viii, 79 p.","numberOfPages":"89","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2014-01-01","temporalEnd":"2014-12-31","ipdsId":"IP-068498","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":310004,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1199/ofr20151199.pdf","text":"Report","size":"9.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1199"},{"id":310003,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1199/coverthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.11578369140626,\n 37.43493087364719\n ],\n [\n -122.11578369140626,\n 37.46123344639866\n ],\n [\n -122.09020614624023,\n 37.46123344639866\n ],\n [\n -122.09020614624023,\n 37.43493087364719\n ],\n [\n -122.11578369140626,\n 37.43493087364719\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"NRP staff
National Research Program
U.S. Geological Survey
345 Middlefield Road, MS-435
Menlo Park, CA 94025
http://water.usgs.gov/nrp/
Water quality data collected in 2012 for 10 above- and 14 below-drainage coal mine discharges (CMDs), classified by mining or excavation method, in the anthracite region of Pennsylvania, USA, are compared with data for 1975, 1991, and 1999 to evaluate long-term (37 year) changes in pH, SO42−, and Fe concentrations related to geochemistry, hydrology, and natural attenuation processes. We hypothesized that CMD quality will improve over time because of diminishing quantities of unweathered pyrite, decreased access of O2 to the subsurface after mine closure, decreased rates of acid production, and relatively constant influx of alkalinity from groundwater. Discharges from shafts, slopes, and boreholes, which are vertical or steeply sloping excavations, are classified as below-drainage; these receive groundwater inputs with low dissolved O2, resulting in limited pyrite oxidation, dilution, and gradual improvement of CMD water quality. In contrast, discharges from drifts and tunnels, which are nearly horizontal excavations into hillsides, are classified as above-drainage; these would exhibit less improvement in water quality over time because the rock surfaces continue to be exposed to air, which facilitates sustained pyrite oxidation, acid production, and alkalinity consumption. Nonparametric Wilcoxon matched-pair signed rank tests between 1975 and 2012 samples indicate decreases in Fe and SO42− concentrations were highly significant (p < 0.05) and increases in pH were marginally significant (p < 0.1) for below-drainage discharges. For above-drainage discharges, changes in Fe and SO42−concentrations were not significant, and increases in pH were highly significant between 1975 and 2012. Although a greater proportion of above-drainage discharges were net acidic in 2012 compared to below-drainage discharges, the increase in pH between 1975 and 2012 was greater for above- (median pH increase from 4.4 to 6.0) compared to below- (median pH increase from 5.6 to 6.1) drainage discharges. For cases where O2 is limited, transformation of aqueous FeII species to FeIII may be kinetically limited. In contrast, where O2 is abundant, aqueous Fe concentrations may be limited by FeIIImineral precipitation; thus, trends in Fe may not follow those for SO42−. In either case, when the supply of alkalinity is sufficient to buffer decreased acidity, the pH could increase by a step trend from strongly acidic (3–3.5) to near neutral (6–6.5) values. Modeled equilibrium with respect to FeIII precipitates varies with pH and Fe and SO42−reconcentrations: increasing pH promotes the formation of ferrihydrite, while decreasing concentrations of Fe limit the formation of ferrihydrite, and decreasing Fe and SO42−concentrations limit the precipitation of schwertmannite and favor formation of FeIIIhydroxyl complexes and uncomplexed Fe2+ and Fe3+. The analysis of the long-term geochemical changes in CMDs in the anthracite field and the effect of the hydrologic setting on water quality presented in this paper can help prioritize CMD remediation and facilitate selection and design of the most appropriate treatment systems.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.apgeochem.2015.02.010","usgsCitation":"Burrows, J.E., Peters, S.C., and Cravotta, C.A., 2015, Temporal geochemical variations in above- and below-drainage coal mine discharge: Applied Geochemistry, v. 62, p. 84-95, https://doi.org/10.1016/j.apgeochem.2015.02.010.","productDescription":"12 p.","startPage":"84","endPage":"95","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"2012-01-01","temporalEnd":"2012-12-31","ipdsId":"IP-056784","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":310197,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Pennsylvania","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.04437255859375,\n 40.36328834091583\n ],\n [\n -77.04437255859375,\n 41.605174521299304\n ],\n [\n -75.4595947265625,\n 41.605174521299304\n ],\n [\n -75.4595947265625,\n 40.36328834091583\n ],\n [\n -77.04437255859375,\n 40.36328834091583\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"62","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"562757aae4b0d158f592650b","contributors":{"authors":[{"text":"Burrows, Jill E.","contributorId":149323,"corporation":false,"usgs":false,"family":"Burrows","given":"Jill","email":"","middleInitial":"E.","affiliations":[{"id":16160,"text":"Lehigh University","active":true,"usgs":false}],"preferred":false,"id":577961,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Peters, Stephen C.","contributorId":149324,"corporation":false,"usgs":false,"family":"Peters","given":"Stephen","email":"","middleInitial":"C.","affiliations":[{"id":16160,"text":"Lehigh University","active":true,"usgs":false}],"preferred":false,"id":577962,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cravotta, Charles A. III, 0000-0003-3116-4684 cravotta@usgs.gov","orcid":"https://orcid.org/0000-0003-3116-4684","contributorId":2193,"corporation":false,"usgs":true,"family":"Cravotta","given":"Charles","suffix":"III,","email":"cravotta@usgs.gov","middleInitial":"A.","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":false,"id":577960,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70159233,"text":"70159233 - 2015 - Using a modified time-reverse imaging technique to locate low-frequency earthquakes on the San Andreas Fault near Cholame, California","interactions":[],"lastModifiedDate":"2015-10-20T10:42:55","indexId":"70159233","displayToPublicDate":"2015-10-20T11:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1803,"text":"Geophysical Journal International","active":true,"publicationSubtype":{"id":10}},"title":"Using a modified time-reverse imaging technique to locate low-frequency earthquakes on the San Andreas Fault near Cholame, California","docAbstract":"We present a new method to locate low-frequency earthquakes (LFEs) within tectonic tremor episodes based on time-reverse imaging techniques. The modified time-reverse imaging technique presented here is the first method that locates individual LFEs within tremor episodes within 5 km uncertainty without relying on high-amplitude P-wave arrivals and that produces similar hypocentral locations to methods that locate events by stacking hundreds of LFEs without having to assume event co-location. In contrast to classic time-reverse imaging algorithms, we implement a modification to the method that searches for phase coherence over a short time period rather than identifying the maximum amplitude of a superpositioned wavefield. The method is independent of amplitude and can help constrain event origin time. The method uses individual LFE origin times, but does not rely on a priori information on LFE templates and families.We apply the method to locate 34 individual LFEs within tremor episodes that occur between 2010 and 2011 on the San Andreas Fault, near Cholame, California. Individual LFE location accuracies range from 2.6 to 5 km horizontally and 4.8 km vertically. Other methods that have been able to locate individual LFEs with accuracy of less than 5 km have mainly used large-amplitude events where a P-phase arrival can be identified. The method described here has the potential to locate a larger number of individual low-amplitude events with only the S-phase arrival. Location accuracy is controlled by the velocity model resolution and the wavelength of the dominant energy of the signal. Location results are also dependent on the number of stations used and are negligibly correlated with other factors such as the maximum gap in azimuthal coverage, source–station distance and signal-to-noise ratio.
","language":"English","publisher":"Oxford University Press","doi":"10.1093/gji/ggv337","usgsCitation":"Horstmann, T., Harrington, R., and Cochran, E.S., 2015, Using a modified time-reverse imaging technique to locate low-frequency earthquakes on the San Andreas Fault near Cholame, California: Geophysical Journal International, v. 203, p. 1207-1226, https://doi.org/10.1093/gji/ggv337.","productDescription":"20 p.","startPage":"1207","endPage":"1226","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060666","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":471716,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/gji/ggv337","text":"Publisher Index Page"},{"id":310110,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"Cholame","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 -120.43350219726562,\n 35.453398952505275\n ],\n [\n -120.43350219726562,\n 35.655622494585785\n ],\n [\n -120.15541076660156,\n 35.655622494585785\n ],\n [\n -120.15541076660156,\n 35.453398952505275\n ],\n [\n -120.43350219726562,\n 35.453398952505275\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"203","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2015-10-07","publicationStatus":"PW","scienceBaseUri":"562757ace4b0d158f5926511","contributors":{"authors":[{"text":"Horstmann, Tobias","contributorId":53683,"corporation":false,"usgs":true,"family":"Horstmann","given":"Tobias","email":"","affiliations":[],"preferred":false,"id":577876,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harrington, Rebecca M.","contributorId":71089,"corporation":false,"usgs":true,"family":"Harrington","given":"Rebecca M.","affiliations":[],"preferred":false,"id":577877,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cochran, Elizabeth S. 0000-0003-2485-4484 ecochran@usgs.gov","orcid":"https://orcid.org/0000-0003-2485-4484","contributorId":2025,"corporation":false,"usgs":true,"family":"Cochran","given":"Elizabeth","email":"ecochran@usgs.gov","middleInitial":"S.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":577875,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70160395,"text":"70160395 - 2015 - Responses of macroinvertebrate community metrics to a wastewater discharge in the Upper Blue River of Kansas and Missouri, USA","interactions":[],"lastModifiedDate":"2017-05-22T16:20:37","indexId":"70160395","displayToPublicDate":"2015-10-20T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5025,"text":"Journal of Water Resource and Protection","active":true,"publicationSubtype":{"id":10}},"title":"Responses of macroinvertebrate community metrics to a wastewater discharge in the Upper Blue River of Kansas and Missouri, USA","docAbstract":"The Blue River Main wastewater treatment facility (WWTF) discharges into the upper Blue River (725 km2), and is recently upgraded to implement biological nutrient removal. We measured biotic condition upstream and downstream of the discharge utilizing the macroinvertebrate protocol developed for Kansas streams. We examined responses of 34 metrics to determine the best indicators for discriminating site differences and for predicting biological condition. Significant differences between sites upstream and downstream of the discharge were identified for 15 metrics in April and 12 metrics in August. Upstream biotic condition scores were significantly greater than scores at both downstream sites in April (p = 0.02), and in August the most downstream site was classified as non-biologically supporting. Thirteen EPT taxa (Ephemeroptera, Plecoptera, Trichoptera) considered intolerant of degraded stream quality were absent at one or both downstream sites. Increases in tolerance metrics and filtering macroinvertebrates, and a decline in ratio of scrapers to filterers all indicated effects of increased nutrient enrichment. Stepwise regressions identified several significant models containing a suite of metrics with low redundancy (R2 = 0.90 - 0.99). Based on the rapid decline in biological condition downstream of the discharge, the level of nutrient removal resulting from the facility upgrade (10% - 20%) was not enough to mitigate negative effects on macroinvertebrate communities.
","language":"English","publisher":"Scientific Research","doi":"10.4236/jwarp.2015.715098","usgsCitation":"Poulton, B.C., Graham, J., Rasmussen, T.J., and Stone, M.L., 2015, Responses of macroinvertebrate community metrics to a wastewater discharge in the Upper Blue River of Kansas and Missouri, USA: Journal of Water Resource and Protection, v. 7, p. 1195-1220, https://doi.org/10.4236/jwarp.2015.715098.","productDescription":"26 p.","startPage":"1195","endPage":"1220","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-058489","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":471717,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.4236/jwarp.2015.715098","text":"Publisher Index Page"},{"id":312751,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Kansas and Missouri","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.5783805847168,\n 38.899316235331575\n ],\n [\n -94.58473205566406,\n 38.89677787400279\n ],\n [\n -94.58610534667969,\n 38.89330417988778\n ],\n [\n -94.58215713500977,\n 38.88689075977245\n ],\n [\n -94.5897102355957,\n 38.8771359067301\n ],\n [\n -94.60533142089844,\n 38.86898356409656\n ],\n [\n -94.61219787597655,\n 38.85976093475425\n ],\n [\n -94.61357116699219,\n 38.84986866947367\n ],\n [\n -94.61580276489256,\n 38.8422480135733\n ],\n [\n -94.6113395690918,\n 38.84131208727261\n ],\n [\n -94.59846496582031,\n 38.85722116008798\n ],\n [\n -94.58232879638672,\n 38.876868631634224\n ],\n [\n -94.57700729370116,\n 38.88648990178886\n ],\n [\n -94.57923889160156,\n 38.894773840440934\n ],\n [\n -94.57769393920897,\n 38.89624347058238\n ],\n [\n -94.5783805847168,\n 38.899316235331575\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"7","edition":"15","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"567a8246e4b0a04ef490fd18","contributors":{"authors":[{"text":"Poulton, Barry C. 0000-0002-7219-4911 bpoulton@usgs.gov","orcid":"https://orcid.org/0000-0002-7219-4911","contributorId":2421,"corporation":false,"usgs":true,"family":"Poulton","given":"Barry","email":"bpoulton@usgs.gov","middleInitial":"C.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":582825,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Graham, Jennifer L. 0000-0002-6420-9335 jlgraham@usgs.gov","orcid":"https://orcid.org/0000-0002-6420-9335","contributorId":150737,"corporation":false,"usgs":true,"family":"Graham","given":"Jennifer L.","email":"jlgraham@usgs.gov","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":false,"id":582826,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rasmussen, Teresa J. 0000-0002-7023-3868 rasmuss@usgs.gov","orcid":"https://orcid.org/0000-0002-7023-3868","contributorId":3336,"corporation":false,"usgs":true,"family":"Rasmussen","given":"Teresa","email":"rasmuss@usgs.gov","middleInitial":"J.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":582827,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stone, Mandy L. 0000-0002-6711-1536 mstone@usgs.gov","orcid":"https://orcid.org/0000-0002-6711-1536","contributorId":4409,"corporation":false,"usgs":true,"family":"Stone","given":"Mandy","email":"mstone@usgs.gov","middleInitial":"L.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":582828,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70159225,"text":"sir20155128 - 2015 - Storage capacity of the Fena Valley Reservoir, Guam, Mariana Islands, 2014","interactions":[],"lastModifiedDate":"2015-10-20T09:22:29","indexId":"sir20155128","displayToPublicDate":"2015-10-19T20:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-5128","title":"Storage capacity of the Fena Valley Reservoir, Guam, Mariana Islands, 2014","docAbstract":"The Fena Valley Reservoir is in southern Guam and is the primary source of water for the U.S. Naval Base Guam and nearby village residents. Since the construction of the Fena Dam in 1951, sediment has accumulated in the reservoir and reduced its storage capacity. The reservoir was surveyed previously in 1973, 1979, and 1990 to estimate the loss in storage capacity. To determine the current storage capacity, the U.S. Geological Survey, in cooperation with the U.S. Department of Defense Strategic Environmental Research and Development Program, surveyed the bathymetry of the reservoir in February 2014.
\nThe bathymetric survey was accomplished by making depth soundings using a boat-mounted, acoustic Doppler current profiler. Location during bathymetric data collection was determined using a single-base Global Navigation Satellite System-Real Time Kinematic survey. Vertical profiles of conductivity, temperature, and depth were collected periodically. The conductivity, temperature, and depth profiles were used to spatially and temporally adjust the sound-speed calculations used to determine depth from the soundings. Approximately 108 kilometers of transects with a total of about 380,000 depth soundings were surveyed. In addition, approximately 2,100 topographic survey points in shallow, wadable areas near the Imong River Delta were defined by using a Global Navigation Satellite System receiver attached to a fixed-length survey rod. Depth soundings and topographic survey points were compiled and interpolated to generate a digital-elevation model of the reservoir. Data extracted from the digital-elevation model were then tabulated to determine total reservoir capacity and create reservoir stage–surface area and stage–storage capacity tables.
\nAnalyses of the bathymetric data indicate that the reservoir currently has 6,915 acre-feet of storage capacity. The engineering drawings of record show that the total reservoir capacity in 1951 was estimated to be 8,365 acre-feet. Thus, between 1951 and 2014, the total storage capacity decreased by 1,450 acre-feet (a loss of 17 percent of the original total storage capacity). The remaining live-storage capacity, or the volume of storage above the lowest-level reservoir outlet elevation, was calculated to be 5,511 acre-feet in 2014, indicating a decrease of 372 acre-feet (or 6 percent) of the original 5,883 acre-feet of live-storage capacity. The remaining dead-storage capacity, or volume of storage below the lowest-level outlet, was 1,404 acre-feet in 2014, indicating a decrease of 1,078 acre-feet (or 43 percent) of the original 2,482 acre-feet of dead-storage capacity.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155128","collaboration":"Prepared in cooperation with the Strategic Environmental Research and Development Program","usgsCitation":"Marineau, M.D., and Wright, S., 2015, Storage capacity of the Fena Valley Reservoir, Guam, Mariana Islands, 2014: U.S. Geological Survey Scientific Investigations Report 2015-5128, vi, 31 p., https://doi.org/10.3133/sir20155128.","productDescription":"vi, 31 p.","numberOfPages":"42","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-056696","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":310069,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5128/coverthb.jpg"},{"id":310070,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5128/sir20155128.pdf","text":"Report","size":"19.7","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5128"}],"otherGeospatial":"Fena Valley Reservoir, Guam, Mariana Islands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 144.6954345703125,\n 13.338847687855717\n ],\n [\n 144.6954345703125,\n 13.365738086822018\n ],\n [\n 144.70796585083008,\n 13.365738086822018\n ],\n [\n 144.70796585083008,\n 13.338847687855717\n ],\n [\n 144.6954345703125,\n 13.338847687855717\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, CA 95829
http://ca.water.usgs.gov
Habitat fragmentation is a fundamental cause of population decline and increased risk of extinction for many wildlife species; animals with large home ranges and small population sizes are particularly sensitive. The Louisiana black bear (Ursus americanus luteolus) exists only in small, isolated subpopulations as a result of land clearing for agriculture, but the relative potential for inter-subpopulation movement by Louisiana black bears has not been quantified, nor have characteristics of effective travel routes between habitat fragments been identified. We placed and monitored global positioning system (GPS) radio collars on 8 female and 23 male bears located in 4 subpopulations in Louisiana, which included a reintroduced subpopulation located between 2 of the remnant subpopulations. We compared characteristics of sequential radiolocations of bears (i.e., steps) with steps that were possible but not chosen by the bears to develop step selection function models based on conditional logistic regression. The probability of a step being selected by a bear increased as the distance to natural land cover and agriculture at the end of the step decreased and as distance from roads at the end of a step increased. To characterize connectivity among subpopulations, we used the step selection models to create 4,000 hypothetical correlated random walks for each subpopulation representing potential dispersal events to estimate the proportion that intersected adjacent subpopulations (hereafter referred to as successful dispersals). Based on the models, movement paths for males intersected all adjacent subpopulations but paths for females intersected only the most proximate subpopulations. Cross-validation and genetic and independent observation data supported our findings. Our models also revealed that successful dispersals were facilitated by a reintroduced population located between 2 distant subpopulations. Successful dispersals for males were dependent on natural land cover in private ownership. The addition of hypothetical 1,000-m- or 3,000-m-wide corridors between the 4 study areas had minimal effects on connectivity among subpopulations. For females, our model suggested that habitat between subpopulations would probably have to be permanently occupied for demographic rescue to occur. Thus, the establishment of stepping-stone populations, such as the reintroduced population that we studied, may be a more effective conservation measure than long corridors without a population presence in between.
","language":"English","publisher":"Wildlife Society","doi":"10.1002/jwmg.955","collaboration":"Louisiana Department of Wildlife and Fisheries; University of Tennessee; University of Maryland; U.S. Fish and Wildlife Service","usgsCitation":"Clark, J.D., Jared S. Laufenberg, Davidson, M., and Jennifer L. Murrow, 2015, Connectivity among subpopulations of Louisiana black bears as estimated by a step selection function: Journal of Wildlife Management, v. 79, no. 8, https://doi.org/10.1002/jwmg.955.","productDescription":"14 p.","startPage":"1360","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063498","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":310052,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Tensas River Basin, Three Rivers Complex, Upper Atchafalaya River Basin, Lower Atchafalaya River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.42135620117188,\n 32.41706632846282\n ],\n [\n -91.3677978515625,\n 32.41706632846282\n ],\n [\n -91.2744140625,\n 32.400834826722196\n ],\n [\n -91.17965698242188,\n 32.265071800242445\n ],\n [\n -91.24420166015624,\n 32.19537080888963\n ],\n [\n -91.3348388671875,\n 32.11631176714\n ],\n [\n -91.40350341796875,\n 32.01855598828661\n ],\n [\n -91.5216064453125,\n 31.989441837922904\n ],\n [\n -91.57791137695312,\n 32.07442922894548\n ],\n [\n -91.55181884765625,\n 32.30338454936734\n ],\n [\n -91.51199340820312,\n 32.37416245209553\n ],\n [\n -91.42135620117188,\n 32.41706632846282\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.09152221679688,\n 30.892797477508154\n ],\n [\n -91.97067260742188,\n 30.89161900878617\n ],\n [\n -91.88552856445312,\n 30.901046352477493\n ],\n [\n -91.76605224609375,\n 30.90811625106069\n ],\n [\n -91.72073364257812,\n 30.878654895778272\n ],\n [\n -91.6644287109375,\n 30.69933500437198\n ],\n [\n -91.66717529296875,\n 30.598911818191965\n ],\n [\n -91.66717529296875,\n 30.518498237455404\n ],\n [\n -91.72760009765624,\n 30.41670336862688\n ],\n [\n -91.87728881835938,\n 30.38709188778112\n ],\n [\n -91.99676513671875,\n 30.4060442699695\n ],\n [\n -92.07092285156249,\n 30.4912844521002\n ],\n [\n -92.1807861328125,\n 30.80555164278596\n ],\n [\n -92.09152221679688,\n 30.892797477508154\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.065673828125,\n 29.826348356278118\n ],\n [\n -91.34582519531249,\n 29.99775972557893\n ],\n [\n -91.42547607421875,\n 30.0286775329042\n ],\n [\n -91.4996337890625,\n 30.07622456354286\n ],\n [\n -91.66168212890625,\n 30.05483122485245\n ],\n [\n -91.74957275390625,\n 29.907329376851553\n ],\n [\n -91.4337158203125,\n 29.62360872200976\n ],\n [\n -91.03271484375,\n 29.492206334848714\n ],\n [\n -90.98876953125,\n 29.69759650228319\n ],\n [\n -91.065673828125,\n 29.826348356278118\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.71936035156249,\n 31.60193125799097\n ],\n [\n -91.76467895507812,\n 31.186958816798732\n ],\n [\n -91.88552856445312,\n 31.083517709507184\n ],\n [\n -92.032470703125,\n 31.08116546459057\n ],\n [\n -92.16430664062499,\n 31.135252364697717\n ],\n [\n -92.18765258789061,\n 31.235114421248575\n ],\n [\n -92.20550537109375,\n 31.357155132373343\n ],\n [\n -92.21511840820312,\n 31.481379984249294\n ],\n [\n -91.99264526367186,\n 31.62532121329918\n ],\n [\n -91.93084716796874,\n 31.644028945047847\n ],\n [\n -91.8017578125,\n 31.6358447754293\n ],\n [\n -91.73583984374999,\n 31.618304843852865\n ],\n [\n -91.71936035156249,\n 31.60193125799097\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"79","issue":"8","edition":"1347","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2015-08-28","publicationStatus":"PW","scienceBaseUri":"56260618e4b0fb9a11dd75d6","chorus":{"doi":"10.1002/jwmg.955","url":"http://dx.doi.org/10.1002/jwmg.955","publisher":"Wiley-Blackwell","authors":"Clark Joseph D., Laufenberg Jared S., Davidson Maria, Murrow Jennifer L.","journalName":"The Journal of Wildlife Management","publicationDate":"8/28/2015","auditedOn":"10/5/2015"},"contributors":{"authors":[{"text":"Clark, Joseph D. 0000-0002-8547-8112 jclark1@usgs.gov","orcid":"https://orcid.org/0000-0002-8547-8112","contributorId":2265,"corporation":false,"usgs":true,"family":"Clark","given":"Joseph","email":"jclark1@usgs.gov","middleInitial":"D.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":540630,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jared S. Laufenberg","contributorId":139272,"corporation":false,"usgs":false,"family":"Jared S. Laufenberg","affiliations":[{"id":12716,"text":"University of Tennessee","active":true,"usgs":false}],"preferred":false,"id":540631,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Davidson, Maria","contributorId":139273,"corporation":false,"usgs":false,"family":"Davidson","given":"Maria","email":"","affiliations":[{"id":12717,"text":"Louisiana Department of Wildlife and Fisheries","active":true,"usgs":false}],"preferred":false,"id":540632,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jennifer L. Murrow","contributorId":139274,"corporation":false,"usgs":false,"family":"Jennifer L. Murrow","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":540633,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70158969,"text":"sir20155132 - 2015 - Discharge, suspended sediment, and salinity in the Gulf Intracoastal Waterway and adjacent surface waters in South-Central Louisiana, 1997–2008","interactions":[],"lastModifiedDate":"2015-10-20T08:36:46","indexId":"sir20155132","displayToPublicDate":"2015-10-19T12:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-5132","title":"Discharge, suspended sediment, and salinity in the Gulf Intracoastal Waterway and adjacent surface waters in South-Central Louisiana, 1997–2008","docAbstract":"Discharge, suspended sediment, and salinity data collected between 1997 and 2008 indicate that the Gulf Intracoastal Waterway (GIWW) is an important distributary of river water and suspended sediments to coastal wetlands in south-central coastal Louisiana. Following natural hydraulic gradients, the GIWW passively distributes freshwater and suspended sediments from the Atchafalaya River to areas at least 30 to 50 miles west and east, respectively, of Morgan City. The magnitude and reach of the discharge in the GIWW increase as stage of the Wax Lake Outlet at Calumet and Lower Atchafalaya River (LAR) at Morgan City increase. The magnitude and duration of discharge vary from year to year depending on the flow regime of the Atchafalaya River. Annual discharge of water in the GIWW was greater during years when stage of the LAR remained anomalously high throughout the year, compared with average and peak flood years. During years when Atchafalaya River flow is low, Bayou Boeuf, a waterway draining the Verret subbasin, becomes a major source of water maintaining the eastward flow in the GIWW. The GIWW is the only means of getting river water to some parts of coastal Louisiana.
\nThe length of time stage of the LAR at Morgan City exceeds a given height has increased from the 1940s to 2008. This shift has increased the length of time the GIWW functions as a predictable distributary of river water each year. Similar shifts in the future could be expected to increase the duration and amounts of river water reaching coastal Louisiana wetlands through the GIWW.
\nMedian suspended-sediment concentrations in the GIWW to the west of Morgan City were around 160 milligrams per liter (mg/L). In the GIWW east of Morgan City, median concentrations were 120–160 mg/L, except in Bayou Boeuf at Railroad Bridge in Amelia and the parts of the GIWW between Bayou Boeuf and the Houma Navigation Canal; median concentrations here were around 100 mg/L.
\nRiver water penetrates much of the Louisiana coast, as demonstrated by the large year-to-year fluctuations in salinity regimes of intradistributary basins in response to differences in flow regimes of the Mississippi and the Atchafalaya Rivers. This occurs directly through inflow along the GIWW and through controlled diversions and indirectly by transport into basin interiors after mixing with the Gulf of Mexico. The GIWW plays an important role in moderating salinity in intradistributary basins; for example, salinity in surface waters just south of the GIWW between Bayou Boeuf and the Houma Navigation Canal remained low even during a year with prolonged low water (2000).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155132","usgsCitation":"Swarzenski, C.M., and Perrien, S.M., 2015, Discharge, suspended sediment, and salinity in the Gulf Intracoastal Waterway and adjacent surface waters in south-central Louisiana, 1997–2008: U.S. Geological Survey Scientific Investigations Report 2015–5132, 21 p., https://dx.doi.org/10.3133/sir20155132.","productDescription":"v, 21 p.","numberOfPages":"30","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"links":[{"id":309802,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5132/sir20155132.pdf","text":"Report","size":"1.09 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5132"},{"id":309801,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5132/coverthb.jpg"}],"country":"United States","state":"Louisiana","city":"Houma City, Morgan City","otherGeospatial":"Atchafalaya River, Cypremort Point, Bayou Lafourche, Verret subbasin, Barataria Basin, Terrebonne Basin, Vermilion-Teche Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.26318359375,\n 28.998531814051795\n ],\n [\n -92.26318359375,\n 30.65681556429287\n ],\n [\n -89.80224609374999,\n 30.65681556429287\n ],\n [\n -89.80224609374999,\n 28.998531814051795\n ],\n [\n -92.26318359375,\n 28.998531814051795\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Lower Mississippi-Gulf Water Science Center
U.S. Geological Survey
3535 S. Sherwood Forest Blvd., Suite 120
Baton Rouge, LA 70816
http://la.water.usgs.gov/
The extent, hydrogeologic framework, and potential well yields of valley-fill aquifers within a 151-square-mile area of eastern Chemung County, New York, were investigated, and the upland distribution of till thickness over bedrock was characterized. The hydrogeologic framework of these valleyfill aquifers was interpreted from multiple sources of surficial and subsurface data and an interpretation of the origin of the glacial deposits, particularly during retreat of glacial ice from the region. Potential yields of screened wells are based on the hydrogeologic framework interpretation and existing well-yield data, most of which are from wells finished with open-ended well casing.
\nWater-resource potential is greatest within saturated sand and gravel in the Chemung River valley (nearly 1 mile wide), especially where induced infiltration of additional water from the Chemung River is possible. The second most favorable area is the Newtown Creek valley at the confluence of Newtown Creek with North Branch Newtown Creek east of Horseheads, N.Y. Extensive sand and gravel deposits within the Breesport, N.Y., area are largely unsaturated but may have greater saturation along the east side of Jackson Creek immediately north of Breesport. Till deposits confine sand and gravel along Newtown Creek at Erin, N.Y., and along much of the upper reach of North Branch Newtown Creek; this confining unit may limit recharge and potential well yield. The north-south oriented valleys of Baldwin and Wynkoop Creeks end at notched divides that imply input of glacial meltwater and limited sediment from outside of the present watersheds. These two valleys are relatively narrow but contain variably sorted sand and gravel, which, in places, may be capable of supplying modest-size community water systems.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155092","collaboration":"Prepared in cooperation with the New York State Department of Environmental Conservation","usgsCitation":"Heisig, P.M., 2015, Hydrogeology of valley-fill aquifers and adjacent areas in eastern Chemung County, New York: U.S. Geological Survey Scientific Investigations Report 2015–5092, 19 p. plus appendix and 1 pl., https://dx.doi.org/10.3133/sir20155092.","productDescription":"Report: vi, 18 p.; Plate: 36 x 48 inches; HTML Document; Appendix","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-056841","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":310038,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5092/images/coverthb.jpg"},{"id":310043,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5092/pdf/sir20155092.pdf","text":"Report","size":"7.56 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5092"},{"id":310039,"rank":4,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2015/5092/plate.html","text":"SIR 2015-5092 - Plate Instructions","linkFileType":{"id":5,"text":"html"},"description":"SIR 2015-5092"},{"id":310048,"rank":3,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2015/5092/pdf/sir20155092_plate1.pdf","text":"SIR 2015-5092 - Plate 1 - 36” x 48”","size":"63 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5092"},{"id":310040,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5092/attachments/sir20155092_appendix1.xlsx","text":"SIR 2015-5092 - Appendix 1","size":"86 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2015-5092"}],"country":"United States","state":"New York","county":"Chemung County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.53051757812499,\n 42.00032514831621\n ],\n [\n -77.53051757812499,\n 42.706659563510385\n ],\n [\n -76.22863769531249,\n 42.706659563510385\n ],\n [\n -76.22863769531249,\n 42.00032514831621\n ],\n [\n -77.53051757812499,\n 42.00032514831621\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New York Water Science Center
U.S. Geological Survey
425 Jordan Road
Troy, NY 12180-8349
(518) 285-5602
Visit our Web site at:
http://ny.water.usgs.gov
Landscape-scale factors may have differential effects on the distribution of native and non-native fishes and may help explain invasion success and species declines.
\nGreat Plains, Wyoming, USA
\nWe used hierarchical Bayesian mixture models and constrained ordination techniques to evaluate associations between landscape-scale factors on native and non-native fish species richness, reproductive guilds and individual species distributions.
\nPredicted responses between landscape-scale factors and native and non-native fish species richness were similar, except non-native fish species richness that was positively associated with density of oil and gas wells. Non-native fish species richness was also positively associated with native fish species richness. Spawning guild composition differed between native and non-native fishes. Canonical correspondence analysis revealed that the most abundant non-native and only a few native species were positively associated with oil and gas wells.
\nThe similar relationships between native and non-native fish species richness are likely evidence that they share similar ecological rules, which supports that non-native species become naturalized and they may be affected by the same environmental factors that determine distribution of native species.
","language":"English","publisher":"Wiley","doi":"10.1111/ddi.12383","usgsCitation":"Stewart, D., Walters, A.W., and Rahel, F.J., 2015, Landscape-scale determinants of native and nonnative Great Plains fish distributions: Diversity and Distributions, v. 22, no. 2, p. 225-238, https://doi.org/10.1111/ddi.12383.","productDescription":"14 p.","startPage":"225","endPage":"238","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063585","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":471722,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ddi.12383","text":"Publisher Index Page"},{"id":323606,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"22","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-10-15","publicationStatus":"PW","scienceBaseUri":"57612ab2e4b04f417c2ce4b7","chorus":{"doi":"10.1111/ddi.12383","url":"http://dx.doi.org/10.1111/ddi.12383","publisher":"Wiley-Blackwell","authors":"Stewart David R., Walters Annika W., Rahel Frank J.","journalName":"Diversity and Distributions","publicationDate":"10/15/2015","auditedOn":"11/17/2015"},"contributors":{"authors":[{"text":"Stewart, David R.","contributorId":141323,"corporation":false,"usgs":false,"family":"Stewart","given":"David R.","affiliations":[],"preferred":false,"id":638795,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Walters, Annika W. 0000-0002-8638-6682 awalters@usgs.gov","orcid":"https://orcid.org/0000-0002-8638-6682","contributorId":4190,"corporation":false,"usgs":true,"family":"Walters","given":"Annika","email":"awalters@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":637130,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rahel, Frank J.","contributorId":171824,"corporation":false,"usgs":false,"family":"Rahel","given":"Frank","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":638796,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70158634,"text":"ofr20151193 - 2015 - Hindcast storm events in the Bering Sea for the St. Lawrence Island and Unalakleet Regions, Alaska","interactions":[],"lastModifiedDate":"2017-06-23T12:38:19","indexId":"ofr20151193","displayToPublicDate":"2015-10-14T18:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-1193","title":"Hindcast storm events in the Bering Sea for the St. Lawrence Island and Unalakleet Regions, Alaska","docAbstract":"This study provides viable estimates of historical storm-induced water levels in the coastal communities of Gambell and Savoonga situated on St. Lawrence Island in the Bering Sea, as well as Unalakleet located at the head of Norton Sound on the western coast of Alaska. Gambell, Savoonga, and Unalakleet are small Native Villages that are regularly impacted by coastal storms but where little quantitative information about these storms exists. The closest continuous water-level gauge is at Nome, located more than 200 kilometers from both St. Lawrence Island and Unalakleet. In this study, storms are identified and quantified using historical atmospheric and sea-ice data and then used as boundary conditions for a suite of numerical models. The work includes storm-surge (temporary rise in water levels due to persistent strong winds and low atmospheric pressures) modeling in the Bering Strait region, as well as modeling of wave runup along specified sections of the coast in Gambell and Unalakleet. Modeled historical water levels are used to develop return periods of storm surge and storm surge plus wave runup at key locations in each community. It is anticipated that the results will fill some of the data void regarding coastal flood data in western Alaska and be used for production of coastal vulnerability maps and community planning efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151193","usgsCitation":"Erikson, L., McCall, R.T., van Rooijen, A., and Norris, B., 2015, Hindcast storm events in the Bering Sea for the St. Lawrence Island and Unalakleet Regions, Alaska: U.S. Geological Survey Open-File Report 2015-1193, vii, 47 p., https://doi.org/10.3133/ofr20151193.","productDescription":"vii, 47 p.","numberOfPages":"57","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-059633","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":309820,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1193/coverthb.jpg"},{"id":309821,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1193/ofr20151193.pdf","text":"Report","size":"3.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1192"}],"country":"United States","state":"Alaska","otherGeospatial":"Bering Sea, St. Lawrence Island, Unalakleet Regions","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -171.87011718749997,\n 63.84066844285508\n ],\n [\n -171.36474609375,\n 63.75334975181205\n ],\n [\n -171.01318359374997,\n 63.6949869286095\n ],\n [\n -170.595703125,\n 63.80189351770543\n ],\n [\n -169.892578125,\n 63.66576033778838\n ],\n [\n -169.56298828124997,\n 63.470144746565445\n ],\n [\n -168.64013671875,\n 63.37183226679281\n ],\n [\n -168.55224609375,\n 63.05495931065107\n ],\n [\n -169.21142578125,\n 63.06491420208559\n ],\n [\n -169.56298828124997,\n 62.865168668923125\n ],\n [\n -170.22216796875,\n 62.94523066452288\n ],\n [\n -170.52978515624997,\n 63.22373025329546\n ],\n [\n -171.2109375,\n 63.28306240110864\n ],\n [\n -171.54052734375,\n 63.22373025329546\n ],\n [\n -172.06787109375,\n 63.361982464431236\n ],\n [\n -171.87011718749997,\n 63.84066844285508\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -161.69677734375,\n 64.74601725111455\n ],\n [\n -161.38916015625,\n 64.830253743883\n ],\n [\n -160.7080078125,\n 64.830253743883\n ],\n [\n -160.55419921875,\n 64.67091929440798\n ],\n [\n -160.59814453125,\n 64.37794095121995\n ],\n [\n -160.75195312499997,\n 64.20637724320852\n ],\n [\n -161.25732421875,\n 64.07219957867284\n ],\n [\n -162.09228515625,\n 64.19681461100495\n ],\n [\n -161.982421875,\n 64.58618480339979\n ],\n [\n -161.806640625,\n 64.74601725111455\n ],\n [\n -161.69677734375,\n 64.74601725111455\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Pacific Coastal and Marine Science Center
U.S. Geological Survey
Pacific Science Center
2885 Mission St.
Santa Cruz, CA 95060
http://walrus.wr.usgs.gov/
The U.S. Geological Survey, in cooperation with the Iowa Department of Natural Resources, constructed Precipitation-Runoff Modeling System models to estimate daily streamflow for nine river basins in eastern Iowa that drain into the Mississippi River. The models are part of a suite of methods for estimating daily streamflow at ungaged sites. The Precipitation-Runoff Modeling System is a deterministic, distributed- parameter, physical-process-based modeling system developed to evaluate the response of streamflow and general drainage basin hydrology to various combinations of climate and land use. Calibration and validation periods used in each basin mostly were October 1, 2002, through September 30, 2012, but differed depending on the period of record available for daily mean streamflow measurements at U.S. Geological Survey streamflow-gaging stations.
\nA geographic information system tool was used to delineate each basin and estimate values for model parameters based on basin physical and geographical features. A U.S. Geological Survey auto-calibration tool that uses a shuffled complex evolution algorithm was used for initial calibration, and then manual modifications were made to parameter values to complete the calibration of each basin model. The main objective of the calibration was to match daily discharge values of simulated streamflow to measured daily discharge values.
\nThe accuracy of Precipitation-Runoff Modeling System model streamflow estimates of nine river basins in eastern Iowa as compared to measured values at U.S. Geological Survey streamflow-gaging stations varied. The Precipitation-Runoff Modeling System models of nine river basins in eastern Iowa were satisfactory at estimating daily streamflow at 57 of the 79 calibration sites and 13 of the 14 validation sites based on statistical results. Unsatisfactory performance can be contributed to several factors: (1) low flow, no flow, and flashy flow conditions in headwater subbasins having a small drainage area; (2) poor representation of the groundwater and storage components of flow within a basin; (3) lack of accounting for basin withdrawals and water use; and (4) the availability and accuracy of meteorological input data. The Precipitation- Runoff Modeling System models of nine river basins in eastern Iowa will provide water-resource managers with a consistent and documented method for estimating streamflow at ungaged sites and aid in environmental studies, hydraulic design, water management, and water-quality projects.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155129","collaboration":"Prepared in cooperation with the Iowa Department of Natural Resources","usgsCitation":"Haj, A.E., Christiansen, D.E., and Hutchinson, K.J., 2015, Simulation of daily streamflow for nine river basins in eastern\nIowa using the Precipitation-Runoff Modeling System: U.S. Geological Survey Scientific Investigations Report\n2015–5129, 29 p., https://dx.doi.org/10.3133/sir20155129.","productDescription":"iv, 29 p.","numberOfPages":"38","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-067401","costCenters":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"links":[{"id":309818,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5129/coverthb.jpg"},{"id":309819,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5129/sir20155129.pdf","text":"Report","size":"20.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5129"}],"country":"United States","state":"Iowa","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.263427734375,\n 43.810747313446996\n ],\n [\n -96.04248046875,\n 43.96909818325174\n ],\n [\n -94.50439453125,\n 41.07935114946899\n ],\n [\n -92.64770507812499,\n 40.59727063442027\n ],\n [\n -91.40625,\n 40.245991504199026\n ],\n [\n -90.94482421875,\n 40.98819156349393\n ],\n [\n -91.12060546875,\n 41.3025710943056\n ],\n [\n -91.01074218749999,\n 41.45919537950706\n ],\n [\n -90.3515625,\n 41.566141964768384\n ],\n [\n -90.120849609375,\n 42.02481360781777\n ],\n [\n -90.439453125,\n 42.35042512243457\n ],\n [\n -90.72509765625,\n 42.62587560259137\n ],\n [\n -91.03271484375,\n 42.71473218539458\n ],\n [\n -91.175537109375,\n 43.14909399920127\n ],\n [\n -91.0546875,\n 43.31718491566708\n ],\n [\n -91.25244140624999,\n 43.46089378008257\n ],\n [\n -91.263427734375,\n 43.810747313446996\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Iowa Water Science Center
U.S. Geological Survey
P.O. Box 1230
Iowa City, IA 52244
http://ia.water.usgs.gov/
The use of acoustic and other parameters as surrogates for suspended-sediment concentrations (SSC) in rivers has been successful in multiple applications across the Nation. Tools to process and evaluate the data are critical to advancing the operational use of surrogates along with the subsequent development of regression models from which real-time sediment concentrations can be made available to the public. Recent developments in both areas are having an immediate impact on surrogate research and on surrogate monitoring sites currently (2015) in operation.
\nThe Surrogate Analysis and Index Developer (SAID) standalone tool, under development by the U.S. Geological Survey (USGS), assists in the creation of linear regression models that relate constituent and surrogate parameters by providing visual and quantitative diagnostics to the user. SAID also processes acoustic parameters to be used as explanatory variables for SSC. The sediment acoustic method utilizes acoustic parameters from fixed-mount stationary equipment. The theory and method used by the SAID tool have been described in recent publications. The tool also serves to support sediment-acoustic-index methods and other surrogate guidelines such as turbidity and SSC (Rasmussen and others, 2009).
\nThe regression models created in SAID can be used in utilities that have been developed to work with the USGS National Water Information System (NWIS) and for the USGS National Real-Time Water Quality (NRTWQ) Web site. The real-time dissemination of predicted SSC and prediction intervals for each time step has substantial potential to improve understanding of sediment-related water quality and associated engineering and ecological management decisions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151177","collaboration":"Federal Interagency Sedimentation Project and Midwest Region River Sediments and Nutrients Investigations Initiative","usgsCitation":"Domanski, M.M., Straub, T.D., and Landers, M.N., 2015, Surrogate Analysis and Index Developer (SAID) tool (version 1.0, September 2015): U.S. Geological Survey Open-File Report 2015–1177, 38 p., https://doi.org/10.3133/ofr20151177.","productDescription":"Report: vi, 36 p.; HTML Document","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-066947","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":309366,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1177/coverthb.jpg"},{"id":309367,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1177/ofr20151177.pdf","text":"Report","size":"1.18 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1177"},{"id":309845,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://water.usgs.gov/osw/SALT/SAID/","text":"The Surrogate Analysis and Index Developer (SAID) Tool","linkFileType":{"id":5,"text":"html"},"description":"OFR 2015-1177"}],"contact":"Director, llinois Water Science Center
405 N Goodwin
Urbana, IL 61801
http://il.water.usgs.gov/
Digital flood-inundation maps for a 5.3-mile reach of South Fork Peachtree Creek that extends from about 500 feet above the Brockett Road bridge to the Willivee Drive bridge were developed by the U.S. Geological Survey (USGS) in cooperation with DeKalb County, Georgia. The flood-inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation, depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage at South Fork Peachtree at Casa Drive, near Clarkston, Georgia (02336152). Real-time stage information from this USGS streamgage may be obtained at http://waterdata.usgs.gov/ and can be used in conjunction with these maps to estimate near real-time areas of inundation. The National Weather Service (NWS) is incorporating results from this study into the Advanced Hydrologic Prediction Service (AHPS) flood-warning system (http://water.weather.gov/ahps/).
\nA one-dimensional step-backwater model was developed using the U.S. Army Corps of Engineers HEC–RAS software for South Fork Peachtree Creek and was used to compute flood profiles for a 5.3-mile reach of South Fork Peachtree Creek. The model was calibrated using the most current (2015) stage-discharge relation at the USGS streamgage South Fork Peachtree at Casa Drive, near Clarkston, Georgia (02336152). The hydraulic model was then used to simulate 13 water-surface profiles at 0.5-foot intervals at the South Fork Peachtree Creek near Clarkston streamgage. The profiles ranged from just above bankfull stage (6.0 feet) to approximately 3.21 feet above the highest recorded water level (12.0 feet). The simulated water-surface profiles were then combined with a geographic information system digital elevation model—derived from light detection and ranging data having a 5.0-foot horizontal resolution—to delineate the area flooded at each 0.5-foot interval of stream stage.
\nThe availability of these flood-inundation maps, when combined with real-time stage information from USGS streamgages, provides emergency management personnel and residents with critical information during flood-response activities, such as evacuations and road closures, in addition to post-flood recovery efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3347","collaboration":"Prepared in cooperation with DeKalb County, Georgia","usgsCitation":"Musser, J.W., 2015, Flood-inundation maps for South Fork Peachtree Creek from the Brockett Road bridge to the Willivee Drive bridge, DeKalb County, Georgia: U.S. Geological Survey Scientific Investigations Map 3347, 13 sheets, 10-p. pamphlet, https://dx.doi.org/10.3133/sim3347.","productDescription":"Report: vi, 10 p.; 13 Sheets: 30.50 x 21.00 inches; Metadata; Raw Data","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-068577","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":309770,"rank":7,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3347/pdf/sim3347_sheet5.pdf","text":"Sheet05 - Gage height of 8.0 feet and an elevation of 940.2 feet at streamgage 02336152","size":"10.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3347"},{"id":309771,"rank":8,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3347/pdf/sim3347_sheet6.pdf","text":"Sheet06 - 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SIM 3347 Pamphlet","size":"1.61 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3347"},{"id":309766,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3347/pdf/sim3347_sheet1.pdf","text":"Sheet01 - Gage height of 6.0 feet and an elevation of 938.2 feet at streamgage 02336152","size":"10.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3347"},{"id":309767,"rank":4,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3347/pdf/sim3347_sheet2.pdf","text":"Sheet02 - Gage height of 6.5 feet and an elevation of 938.7 feet at streamgage 02336152","size":"10.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3347"},{"id":309795,"rank":16,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sim/3347/downloads/sim3347_depth-grid-metadata.html","text":"SIM 3347 - Depth-grid Metadata","size":"61.7 KB","linkFileType":{"id":5,"text":"html"},"description":"SIM 3347"},{"id":309764,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3347/coverthb.jpg"}],"country":"United States","state":"Georgia","county":"DeKalb County","otherGeospatial":"South Fork Peachtree Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.45671081542969,\n 33.777720492564896\n ],\n [\n -84.45671081542969,\n 33.83933825431594\n ],\n [\n -84.24694061279297,\n 33.83933825431594\n ],\n [\n -84.24694061279297,\n 33.777720492564896\n ],\n [\n -84.45671081542969,\n 33.777720492564896\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, South Atlantic Water Science Center
U.S. Geological Survey
720 Gracern Road
Columbia, SC 29210
http://www.usgs.gov/water/southatlantic/
Thiadiamondoids (TDs) are diamond-like compounds with a sulfide bond located within the cage structure. These compounds were suggested as a molecular proxy for the occurrence and extent of thermochemical sulfate reduction (TSR). Compound-specific sulfur-isotope analysis of TDs may create a multi-parameter system, based on molecular and δ34S values that may be sensitive over a wider range of TSR and thermal maturation stages. In this study, we analyzed a suite of 12 Upper Jurassic oil and condensate samples generated from source rocks in the Smackover Formation to perform a systematic study of the sulfur isotope distribution in thiadiamondoids (one and two cages). For comparison we measured the δ34S composition of benzothiophenes (BTs) and dibenzothiophenes (DBTs). We also conducted pyrolysis experiments with petroleum and model compounds to have an insight into the formation mechanisms of TDs. The δ34S of the TDs varied significantly (ca 30‰) between the different oils depending on the degree of TSR alteration. The results showed that within the same oil, the one-cage TDs were relatively uniform, with 34S enriched values similar to those of the coexisting BTs. The two-cage TDs had more variable δ34S values that range from the δ34S values of BTs to those of the DBTs, but with general 34S depletion relative to one cage TDs. Hydrous pyrolysis experiments (360 °C, 40 h) with either CaSO4 or elemental S (equivalent S molar concentrations) and adamantane as a model compound demonstrate the formation of one cage TDs in relatively low yields (<0.2%). Higher concentrations of TDs were observed in the elemental sulfur experiments, most likely because of the higher rates of reaction with adamantane under these experimental conditions. These results show that the formation of TDs is not exclusive to TSR reactions, and that they can also form by reaction with reduced S species apart from sulfate reduction, though at low yields. Oxygenated compounds, most notably 2-thiaadamantanone and phenol, were also formed during these pyrolysis experiments. This may represent the first stage in the formation of sulfurized compounds and the oxidation of organic matter under TSR conditions. Pyrolysis experiments with elemental S and a TD-enriched oil showed that the δ34S values of the TDs did not change, whereas the BTs did change significantly. It is therefore concluded that TDs do not exchange S atoms with coexisting inorganic reduced sulfur species. They can only change their δ34S values via addition of newly generated TDs that form predominantly during TSR. We therefore suggest that TDs will preserve their δ34S values even under high-temperature reservoir conditions and will reflect the original sulfates δ34S value. The combination of TDs, BTs, and DBTs δ34S values and concentrations allowed for a more reliable detection of the occurrence and extent of TSR than either proxy alone. It showed that except for two oils, all of the oils that were measured in this study were affected by TSR or TSR-sourced H2S, to some degree. It is still not known if some of the oils with the lower concentrations of TDs and enriched δ34S values (close to sulfate minerals) were affected by TSR or by a secondary charge of 34S-enriched H2S.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.gca.2015.07.008","usgsCitation":"Gvirtzman, Z., Said-Ahmad, W., Ellis, G.S., Hill, R.J., J. Michael Moldowan, Wei, Z., and Alon Amrani, 2015, Compound-specific sulfur isotope analysis of thiadiamondoids of oils from the Smackover Formation, USA: Geochimica et Cosmochimica Acta, v. 167, p. 144-161, https://doi.org/10.1016/j.gca.2015.07.008.","productDescription":"17 p.","startPage":"144","endPage":"161","numberOfPages":"17","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064336","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":309975,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":309959,"type":{"id":15,"text":"Index Page"},"url":"https://dx.doi.org/10.1016/j.gca.2015.07.008"}],"country":"United States","volume":"167","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56221face4b06217fc479214","contributors":{"authors":[{"text":"Gvirtzman, Zvi","contributorId":149269,"corporation":false,"usgs":false,"family":"Gvirtzman","given":"Zvi","email":"","affiliations":[{"id":17694,"text":"Institute of Earth Sciences, Hebrew University, Jerusalem 91904, Israel","active":true,"usgs":false}],"preferred":false,"id":577691,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Said-Ahmad, Ward","contributorId":149270,"corporation":false,"usgs":false,"family":"Said-Ahmad","given":"Ward","email":"","affiliations":[{"id":17694,"text":"Institute of Earth Sciences, Hebrew University, Jerusalem 91904, Israel","active":true,"usgs":false}],"preferred":false,"id":577692,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ellis, Geoffrey S. 0000-0003-4519-3320 gsellis@usgs.gov","orcid":"https://orcid.org/0000-0003-4519-3320","contributorId":1058,"corporation":false,"usgs":true,"family":"Ellis","given":"Geoffrey","email":"gsellis@usgs.gov","middleInitial":"S.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":577690,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hill, Ronald J.","contributorId":149271,"corporation":false,"usgs":false,"family":"Hill","given":"Ronald","email":"","middleInitial":"J.","affiliations":[{"id":17695,"text":"EOG Resources, Denver, CO 80202 USA","active":true,"usgs":false}],"preferred":false,"id":577693,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"J. Michael Moldowan","contributorId":149272,"corporation":false,"usgs":false,"family":"J. Michael Moldowan","affiliations":[{"id":17696,"text":"Biomarker Technologies, Rohnert Park, CA 94928 USA","active":true,"usgs":false}],"preferred":false,"id":577694,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wei, Zhibin","contributorId":149273,"corporation":false,"usgs":false,"family":"Wei","given":"Zhibin","email":"","affiliations":[{"id":17697,"text":"ExxonMobil, Houston, TX USA","active":true,"usgs":false}],"preferred":false,"id":577695,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Alon Amrani","contributorId":149274,"corporation":false,"usgs":false,"family":"Alon Amrani","affiliations":[{"id":17694,"text":"Institute of Earth Sciences, Hebrew University, Jerusalem 91904, Israel","active":true,"usgs":false}],"preferred":false,"id":577696,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70158972,"text":"ofr20151200 - 2015 - Realized detection and capture probabilities for giant gartersnakes (Thamnophis gigas) using modified floating aquatic funnel traps","interactions":[],"lastModifiedDate":"2015-10-14T09:35:01","indexId":"ofr20151200","displayToPublicDate":"2015-10-13T16:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-1200","title":"Realized detection and capture probabilities for giant gartersnakes (Thamnophis gigas) using modified floating aquatic funnel traps","docAbstract":"Rigorous analysis and management of animal populations requires that observers account for limitations inherent to the detection of those populations and the individuals within them. Researchers are usually unable to see every individual of a population or to even detect some entire populations. Ignoring this imperfect detectability can bias estimates of population characteristics, such as probability of occurrence, abundance, survival, recruitment, and population growth rate. Furthermore, the precision with which these population characteristics are estimated is dependent on detection probabilities (the probability that at least one individual of a species is detected during a survey, given that the species occurs where the survey is conducted) and capture probabilities (the probability that a given individual is observed or captured during a single survey); greater detection and capture probabilities result in less uncertainty about the values of population characteristics and a greater ability to evaluate the effects of variables or experimental treatments on the population characteristic(s) of interest.
\nDetection and capture probabilities for giant gartersnakes (Thamnophis gigas) are very low, and successfully evaluating the effects of variables or experimental treatments on giant gartersnake populations will require greater detection and capture probabilities than those that had been achieved with standard trap designs. Previous research identified important trap modifications that can increase the probability of snakes entering traps and help prevent the escape of captured snakes. The purpose of this study was to quantify detection and capture probabilities obtained using the most successful modification to commercially available traps to date (2015), and examine the ability of realized detection and capture probabilities to achieve benchmark levels of precision in occupancy and capture-mark-recapture studies.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151200","collaboration":"Prepared in cooperation with the California Department of Water Resources","usgsCitation":"Halstead, B., Skalos, S., Casazza, M.L., and Wylie, G.D., 2015, Realized detection and capture probabilities for giant gartersnakes (Thamnophis gigas) using modified floating aquatic funnel traps: U.S. Geological Survey Open-File Report 2015-1200, iv, 36 p., https://doi.org/10.3133/ofr20151200.","productDescription":"iv, 36 p.","numberOfPages":"44","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2013-06-14","temporalEnd":"2013-11-30","ipdsId":"IP-067831","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":309850,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1200/ofr20151200.pdf","text":"Report","size":"2.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1200"},{"id":309849,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1200/coverthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.33551025390625,\n 38.50519140240354\n ],\n [\n -122.33551025390625,\n 39.61626788999701\n ],\n [\n -121.4923095703125,\n 39.61626788999701\n ],\n [\n -121.4923095703125,\n 38.50519140240354\n ],\n [\n -122.33551025390625,\n 38.50519140240354\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
http://www.werc.usgs.gov/
We present new images and descriptions of the lithofacies and organic facies of the pebble shale unit and lower part of the Hue Shale (Lower Cretaceous) of Arctic Alaska at a high magnification that illustrates their textural characteristics. Our aims were to describe and determine the distribution of facies in these petroleum source rocks and to identify the processes that formed them. We sampled at high-resolution and applied new petrographic techniques combined with scanning electron microscopy and geochemical analyses to samples collected from three widely spaced sections—located in exposures along the Canning River and continuous core from the Mikkelsen Bay State 1 and Orion 1 wells.
\nResults from these three locations indicate that this succession consists primarily of clay-rich mudstones that are variously silt- or sand-bearing and clay-dominated mudstones that exhibit mainly relict, 2–5 millimeter thick bedding and common but variable microbioturbation, rare macrobioturbation, and common fabrics of pelleted clay and silt. These mudstones contain rare, poorly sorted, silt-rich basal laminae that are often discontinuous and have wavy, sharp bases and crude upward fining. In addition, mud-supported, outsized clasts (dropstones) of fine sand to pebble size are present throughout the succession as isolated clasts or in clusters. We interpret these textures and much of this succession to result from intermittent deposition by suspension settling from melting seasonal sea ice—sometimes sediment-laden—and associated primary productivity. Overall, this mudstone succession fines and deepens upward from the pebble shale unit into the Hue Shale. In the Hue Shale of the Orion well, however, different processes intermittently deposited thin, discrete intervals of coarser sediment that probably represent deposition from density currents. Also in the Hue Shale of the Orion well, several thicker sandstone and silt-dominated mudstone units with discordant, scoured bases and cut and fill structures represent erosion during higher energy events such as major storms.
\nOther lithofacies within the succession are graded tuffs/bentonites and tuffaceous/bentonitic mudstones from episodic volcanic ash falls; these are abundant in the Hue Shale, and very rare in the pebble shale unit of the two wells. Organic-carbon rich strata associated with volcanic ash intervals of the pebble shale unit and Hue Shale in the Mikkelsen 1 well have some of the best petroleum source rock potential determined for this succession. Authigenic pyrite and carbonate-cement-dominated mudstone are also present in both units of all three sections. The carbonate-cemented units indicate breaks in sedimentation and are common in the Hue Shale and in sections of the pebble shale unit interpreted to be more distal, such as along the Canning River.
\nOur results document the variation in facies and textures of the Hauterivian and Barremian Lower Cretaceous mudstone succession of Arctic Alaska. Comparison of these characteristics to the products of modern processes on the North Slope of Alaska, in the Beaufort Sea, and elsewhere suggest that this succession formed primarily from depositional processes related to seasonal sea ice with intermittent fluvial-sourced sediment deposited by density currents and episodic erosion and reworking by storms and other currents.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Studies by the U.S. Geological Survey in Alaska, vol. 15 (Professional Paper 1814)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1814B","usgsCitation":"Keller, M.A., and Macquaker, J.H., 2015, Arctic Alaska’s Lower Cretaceous (Hauterivian and Barremian) mudstone succession—Linking lithofacies, texture, and geochemistry to marine processes: U.S. Geological Survey Professional Paper 1814, v, 34 p., https://doi.org/10.3133/pp1814B.","productDescription":"v, 34 p.","numberOfPages":"44","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-033831","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":309740,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1814/b/pp1814b.pdf","text":"Report","size":"8.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1814-B"},{"id":309739,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1814/b/coverthb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -159.609375,\n 67.64267630796037\n ],\n [\n -159.609375,\n 71.49703690095419\n ],\n [\n -140.9765625,\n 71.49703690095419\n ],\n [\n -140.9765625,\n 67.64267630796037\n ],\n [\n -159.609375,\n 67.64267630796037\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Alaska Science Center staff
U.S. Geological Survey
4210 University Dr.
Anchorage, AK 99508
Alaska Mineral Resources
Alaska Science Center
The Queen Charlotte fault (QCF) is a dextral transform system located offshore of southeastern Alaska and western Canada, accommodating ∼4.4 cm/yr of relative motion between the Pacific and North American plates. Oblique convergence along the fault increases southward, and how this convergence is accommodated is still debated. Using seismic reflection data, we interpret offshore basement structure, faulting, and stratigraphy to provide a geological context for two recent earthquakes, an Mw 7.5 strike‐slip event near Craig, Alaska, and an Mw 7.8 thrust event near Haida Gwaii, Canada. We map downwarped Pacific oceanic crust near 54° N, between the two rupture zones. Observed downwarping decreases north and south of 54° N, parallel to the strike of the QCF. Bending of the Pacific plate here may have initiated with increased convergence rates due to a plate motion change at ∼6 Ma. Tectonic reconstruction implies convergence‐driven Pacific plate flexure, beginning at 6 Ma south of a 10° bend the QCF (which is currently at 53.2° N) and lasting until the plate translated past the bend by ∼2 Ma. Normal‐faulted approximately late Miocene sediment above the deep flexural depression at 54° N, topped by relatively undeformed Pleistocene and younger sediment, supports this model. Aftershocks of the Haida Gwaii event indicate a normal‐faulting stress regime, suggesting present‐day plate flexure and underthrusting, which is also consistent with reconstruction of past conditions. We thus favor a Pacific plate underthrusting model to initiate flexure and accommodation space for sediment loading. In addition, mapped structures indicate two possible fault segment boundaries along the QCF at 53.2° N and at 56° N.
","language":"English","publisher":"Seismological Society of Amercia","doi":"10.1785/0120140174","usgsCitation":"Walton, M.A., Gulick, S., Haeussler, P.J., Roland, E.C., and Trehu, A.M., 2015, Basement and regional structure along strike of the Queen Charlotte Fault in the context of modern and historical earthquake ruptures: Bulletin of the Seismological Society of America, v. 105, no. 28, p. 1090-1105, https://doi.org/10.1785/0120140174.","productDescription":"16 p.","startPage":"1090","endPage":"1105","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061089","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":471724,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/2152/43271","text":"External Repository"},{"id":309842,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Queen Charlotte Fault","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -182.63671875,\n 51.23440735163459\n ],\n [\n -182.02148437499997,\n 52.53627304145948\n ],\n [\n -173.32031249999997,\n 53.22576843579022\n ],\n [\n -166.640625,\n 55.178867663281984\n ],\n [\n -160.400390625,\n 57.32652122521709\n ],\n [\n -156.708984375,\n 59.88893689676585\n ],\n [\n -153.80859375,\n 60.88770004207789\n ],\n [\n -148.974609375,\n 61.897577621605016\n ],\n [\n -141.943359375,\n 61.438767493682825\n ],\n [\n -134.296875,\n 59.40036514079251\n ],\n [\n -129.814453125,\n 55.57834467218206\n ],\n [\n -130.869140625,\n 54.7246201949245\n ],\n [\n -130.341796875,\n 52.53627304145948\n ],\n [\n -131.748046875,\n 51.67255514839676\n ],\n [\n -134.12109375,\n 54.00776876193478\n ],\n [\n -136.669921875,\n 56.992882804633986\n ],\n [\n -139.482421875,\n 58.90464570302001\n ],\n [\n -143.525390625,\n 59.80063426102869\n ],\n [\n -150.732421875,\n 58.99531118795094\n ],\n [\n -151.875,\n 57.040729838360875\n ],\n [\n -155.390625,\n 55.57834467218206\n ],\n [\n -162.509765625,\n 53.9560855309879\n ],\n [\n -173.671875,\n 51.83577752045248\n ],\n [\n -182.28515624999997,\n 50.84757295365389\n ],\n [\n -182.63671875,\n 51.23440735163459\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"105","issue":"28","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-04-14","publicationStatus":"PW","scienceBaseUri":"561e1d25e4b0cdb063e59ca1","contributors":{"authors":[{"text":"Walton, Maureen A. L.","contributorId":147200,"corporation":false,"usgs":false,"family":"Walton","given":"Maureen","email":"","middleInitial":"A. L.","affiliations":[{"id":13603,"text":"University of Texas, Austin","active":true,"usgs":false}],"preferred":false,"id":542177,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gulick, Sean P. S.","contributorId":147201,"corporation":false,"usgs":false,"family":"Gulick","given":"Sean P. S.","affiliations":[{"id":13603,"text":"University of Texas, Austin","active":true,"usgs":false}],"preferred":false,"id":542178,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haeussler, Peter J. 0000-0002-1503-6247 pheuslr@usgs.gov","orcid":"https://orcid.org/0000-0002-1503-6247","contributorId":503,"corporation":false,"usgs":true,"family":"Haeussler","given":"Peter","email":"pheuslr@usgs.gov","middleInitial":"J.","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":542176,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Roland, Emily C. eroland@usgs.gov","contributorId":5075,"corporation":false,"usgs":true,"family":"Roland","given":"Emily","email":"eroland@usgs.gov","middleInitial":"C.","affiliations":[],"preferred":false,"id":542179,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Trehu, Anne M.","contributorId":49884,"corporation":false,"usgs":false,"family":"Trehu","given":"Anne","email":"","middleInitial":"M.","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":542180,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70168614,"text":"70168614 - 2015 - Sediment transport-based metrics of wetland stability","interactions":[],"lastModifiedDate":"2016-02-22T12:52:22","indexId":"70168614","displayToPublicDate":"2015-10-10T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Sediment transport-based metrics of wetland stability","docAbstract":"Despite the importance of sediment availability on wetland stability, vulnerability assessments seldom consider spatiotemporal variability of sediment transport. Models predict that the maximum rate of sea level rise a marsh can survive is proportional to suspended sediment concentration (SSC) and accretion. In contrast, we find that SSC and accretion are higher in an unstable marsh than in an adjacent stable marsh, suggesting that these metrics cannot describe wetland vulnerability. Therefore, we propose the flood/ebb SSC differential and organic-inorganic suspended sediment ratio as better vulnerability metrics. The unstable marsh favors sediment export (18 mg L−1 higher on ebb tides), while the stable marsh imports sediment (12 mg L−1 higher on flood tides). The organic-inorganic SSC ratio is 84% higher in the unstable marsh, and stable isotopes indicate a source consistent with marsh-derived material. These simple metrics scale with sediment fluxes, integrate spatiotemporal variability, and indicate sediment sources.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2015GL065980","usgsCitation":"Ganju, N., Kirwan, M., Dickhudt, P., Guntenspergen, G.R., Cahoon, D.R., and Kroeger, K.D., 2015, Sediment transport-based metrics of wetland stability: Geophysical Research Letters, v. 42, no. 19, p. 7992-8000, https://doi.org/10.1002/2015GL065980.","productDescription":"9 p.","startPage":"7992","endPage":"8000","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-044455","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":471727,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015gl065980","text":"Publisher Index Page"},{"id":318273,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland","otherGeospatial":"Blackwater River, Chesapeake Bay, Transquaking River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.2,\n 38.3\n ],\n [\n -76.2,\n 38.5\n ],\n [\n -75.9,\n 38.5\n ],\n [\n -75.9,\n 38.3\n ],\n [\n -76.2,\n 38.3\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"42","issue":"19","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2015-10-10","publicationStatus":"PW","scienceBaseUri":"56cc3fffe4b059daa47e4688","contributors":{"authors":[{"text":"Ganju, Neil K. 0000-0002-1096-0465 nganju@usgs.gov","orcid":"https://orcid.org/0000-0002-1096-0465","contributorId":149613,"corporation":false,"usgs":true,"family":"Ganju","given":"Neil K.","email":"nganju@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":621030,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kirwan, Matthew L. 0000-0002-0658-3038","orcid":"https://orcid.org/0000-0002-0658-3038","contributorId":84060,"corporation":false,"usgs":true,"family":"Kirwan","given":"Matthew L.","affiliations":[],"preferred":false,"id":621032,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dickhudt, Patrick J.","contributorId":48302,"corporation":false,"usgs":true,"family":"Dickhudt","given":"Patrick J.","affiliations":[],"preferred":false,"id":621031,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Guntenspergen, Glenn R. 0000-0002-8593-0244 glenn_guntenspergen@usgs.gov","orcid":"https://orcid.org/0000-0002-8593-0244","contributorId":2885,"corporation":false,"usgs":true,"family":"Guntenspergen","given":"Glenn","email":"glenn_guntenspergen@usgs.gov","middleInitial":"R.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":621029,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cahoon, Donald R. 0000-0002-2591-5667 dcahoon@usgs.gov","orcid":"https://orcid.org/0000-0002-2591-5667","contributorId":3791,"corporation":false,"usgs":true,"family":"Cahoon","given":"Donald","email":"dcahoon@usgs.gov","middleInitial":"R.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":621028,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kroeger, Kevin D. 0000-0002-4272-2349 kkroeger@usgs.gov","orcid":"https://orcid.org/0000-0002-4272-2349","contributorId":1603,"corporation":false,"usgs":true,"family":"Kroeger","given":"Kevin","email":"kkroeger@usgs.gov","middleInitial":"D.","affiliations":[{"id":41100,"text":"Coastal and Marine Hazards and Resources Program","active":true,"usgs":true}],"preferred":true,"id":621093,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70157408,"text":"ds957 - 2015 - Archive of bathymetry data collected at Cape Canaveral, Florida, 2014","interactions":[],"lastModifiedDate":"2015-10-08T08:37:26","indexId":"ds957","displayToPublicDate":"2015-10-07T15:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"957","title":"Archive of bathymetry data collected at Cape Canaveral, Florida, 2014","docAbstract":"Remotely sensed, geographically referenced elevation measurements of the sea floor, acquired by boat- and aircraft-based survey systems, were produced by the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center, St. Petersburg, Florida, for the area at Cape Canaveral.
\nThe work was conducted as part of a study to describe an updated bathymetric dataset collected in 2014 and compare it to previous data sets. The updated data focus on the bathymetric features and sediment transport pathways that connect the offshore regions to the shoreline and, therefore, are related to the protection of other portions of the coastal environment, such as dunes, that support infrastructure and ecosystems.
\nCape Canaveral Coastal System (CCCS) is a prominent feature along the Southeast U.S. coastline and is the only large cape south of Cape Fear, North Carolina. Most of the CCCS lies within the Merritt Island National Wildlife Refuge and included within its boundaries are the Cape Canaveral Air Force Station (CCAFS), NASA’s Kennedy Space Center (KSC), and a large portion of Canaveral National Seashore. The actual promontory of the modern cape falls within the jurisdictional boundaries of the CCAFS.
\nHydrographic survey data were collected August 18-20, 2014 (USGS Field Activity Number 2014-324-FA). The study covered a 20 kilometer (km) section of shoreline extending from Port Canaveral, Fla., to the northern end of the KSC property, and from the shoreline to about 2.5 km offshore. Data were acquired using both sound navigation and ranging (sonar) and light detection and ranging (lidar) systems. Two jet skis and a 17-foot (ft) outboard motor boat equipped with the USGS SANDS (System for Accurate Nearshore Depth Surveying) hydrographic system collected precision sonar data. The USGS airborne EAARL-B mapping system flown in a twin engine airplane was used to collect lidar data. The missions were synchronized so that there was temporal and spatial overlap between the sonar and lidar operations. Additional data were collected to evaluate water clarity to verify the ability of lidar to receive bathymetric returns. Both systems used differential Global Positioning System GPS and utilized the National Oceanic and Atmospheric Administration/National Geodetic Survey (NOAA/NGS) Continuously Operating Reference Station (CORS) station located at CCAFS was used as the reference station.
\nThis data series serves as an archive of processed single-beam sonar and lidar bathymetry data. Graphical Information System (GIS) data products include XYZ point bathymetry data files, a color coded bathymetry map, and interpolated bathymetry grid surface.
\nAdditional information includes an error analysis and formal Federal Geographic Data Committee (FGDC) metadata.
\nFor more information about similar projects, please visit the Barrier Island Evolution Web site.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds957","usgsCitation":"Hansen, Mark, Plant, N.G., Thompson, D.M., Troche, R.J., Kranenburg, C.J., and Klipp, E.S., 2015, Archive of bathymetry data collected at Cape Canaveral, Florida, 2014: U.S. Geological Survey Data Series 957, https://dx.doi.org/10.3133/ds957.","productDescription":"HTML Document","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2014-08-18","temporalEnd":"2014-08-20","ipdsId":"IP-064065","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":309529,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0957","text":"Report HTML","description":"DS 956"},{"id":309528,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/0957/images/coverthb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Cape Canaveral","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.57132720947264,\n 28.57909501280518\n ],\n [\n -80.56068420410156,\n 28.529337159530115\n ],\n [\n -80.52635192871094,\n 28.461447671879817\n ],\n [\n -80.52532196044922,\n 28.44877013274692\n ],\n [\n -80.5514144897461,\n 28.441525142203908\n ],\n [\n -80.56514739990234,\n 28.434279655423556\n ],\n [\n -80.57716369628906,\n 28.423410494987063\n ],\n [\n -80.5843734741211,\n 28.411030369596805\n ],\n [\n -80.5569076538086,\n 28.397440761221713\n ],\n [\n -80.50712585449219,\n 28.437600565124914\n ],\n [\n -80.49613952636719,\n 28.4656731804089\n ],\n [\n -80.55038452148438,\n 28.585426143239545\n ],\n [\n -80.57132720947264,\n 28.57909501280518\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"St. Petersburg Coastal and Marine Science Center
600 4th Street South
St. Petersburg, FL 33701
http://coastal.er.usgs.gov/
Cape Canaveral, Florida, is a prominent feature along the Southeast U.S. coastline. The region includes Merritt Island National Wildlife Refuge, Cape Canaveral Air Force Station, NASA’s Kennedy Space Center, and a large portion of Canaveral National Seashore. The actual promontory of the modern Cape falls within the jurisdictional boundaries of Cape Canaveral Air Force Station. Erosion hazards result from winter and tropical storms, changes in sand resources, sediment budgets, and sea-level rise. Previous work by the USGS has focused on the vulnerability of the dunes to storms, where updated bathymetry and topography have been used for modeling efforts. Existing research indicates that submerged shoals, ridges, and sandbars affect patterns of wave refraction and height, coastal currents, and control sediment transport. These seabed anomalies indicate the availability and movement of sand within the nearshore environment, which may be directly related to the stability of the Cape Canaveral shoreline. Understanding the complex dynamics of the offshore bathymetry and associated sediment pathways can help identify current and future erosion vulnerabilities due to short-term (for example, hurricane and other extreme storms) and long-term (for example, sea-level rise) hazards.
\nThe purpose of this work is to describe an updated bathymetric dataset collected in 2014 and compare it to previous datasets. The updated data focus on the bathymetric features and sediment transport pathways that connect the offshore regions to the shoreline and, therefore, are related to the protection of other portions of the coastal environment, such as dunes, that support infrastructure and ecosystems. Previous survey data include National Oceanic and Atmospheric Administration’s (NOAA) National Ocean Service (NOS) hydrographic survey from 1956 and a USGS survey from 2010 that is augmented with NOS surveys from 2006 and 2007. The primary result of this analysis is documentation and quantification of the nature and rates of bathymetric changes that are near (within about 2.5 km) the current Cape Canaveral shoreline and interpretation of the impact of these changes on future erosion vulnerability.
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600 4th Street South
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http://coastal.er.usgs.gov/