Geologic and geophysical investigations in the vicinity of Fort Irwin National Training Center, California, have been completed in support of groundwater investigations, and are presented in eight chapters of this report. A generalized surficial geologic map along with field and borehole investigations conducted during 2010–11 provide a lithostratigraphic and structural framework for the area during the Cenozoic. Electromagnetic properties of resistivity were measured in the laboratory on hand and core samples, and compared to borehole geophysical resistivity data. These data were used in conjunction with ground-based time-domain and airborne data and interpretations to provide a framework for the shallow lithologic units and structure. Gravity and aeromagnetic maps cover areas ~4 to 5 times that of Fort Irwin. Each chapter includes hydrogeologic applications of the data or model results.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131024","collaboration":"Prepared in cooperation with the U.S. Army, Fort Irwin National Training Center","usgsCitation":"Buesch, D.C., ed., Geology and geophysics applied to groundwater hydrology at Fort Irwin, California: U.S. Geological Survey Open-file Report 2013–1024, 2 p., https://doi.org/10.3133/ofr20131024.","productDescription":"9 Chapters","onlineOnly":"Y","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":359949,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1024/ofr2013-1024_cover.pdf","text":"Cover image","size":"1.2 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":359948,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2013/1024/coverthb.jpg"}],"contact":"Contact Information,
Geology, Minerals, Energy, & Geophysics Science Center—Menlo Park
U.S. Geological Survey
345 Middlefield Road
Menlo Park, CA 94025-3591
Between 2010 and 2012, a total of 79 time-domain electromagnetic (TEM) soundings were collected in 12 groundwater basins in the U.S. Army Fort Irwin National Training Center (NTC) study area to help improve the understanding of the hydrogeology of the NTC. The TEM data are discussed in this chapter in the context of geologic observations of the study area, the details of which are provided in the other chapters of this volume. Selection of locations for TEM soundings in unexplored basins was guided by gravity data that estimated depth to pre-Tertiary basement complex of crystalline rock and alluvial thickness. Some TEM data were collected near boreholes with geophysical logs. The TEM response at locations near boreholes was used to evaluate sounding data for areas without boreholes. TEM models also were used to guide site selection of subsequent boreholes drilled as part of this study. Following borehole completion, geophysical logs were used to ground-truth and reinterpret previously collected TEM data. This iterative process was used to site subsequent TEM soundings and borehole locations as the study progressed. Although each groundwater subbasin within the NTC boundaries was explored using the TEM method, collection of TEM data was focused in those basins identified as best suited for development of water resources. At the NTC, TEM estimates of some lithologic thicknesses and electrical properties in the unsaturated zone are in good accordance with borehole data; however, water-table elevations were not easily identifiable from TEM data.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Geology and geophysics applied to groundwater hydrology at Fort Irwin, California","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131024F","collaboration":"Prepared in cooperation with the U.S. Army, Fort Irwin National Training Center","usgsCitation":"Burgess, M.K., and Bedrosian, P.A., 2014, Time-domain electromagnetic surveys at Fort Irwin, San Bernardino County, California, 2010–12, chap. F of Buesch, D.C., ed., Geology and geophysics applied to groundwater hydrology at Fort Irwin, California: U.S. Geological Survey Open-File Report 2013–1024, 64 p., https://doi.org/10.3133/ofr20131024F.","productDescription":"Report: v, 64 p.","numberOfPages":"69","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-044319","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":296420,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2013/1024/f/images/coverthb.jpg"},{"id":296367,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1024/f/downloads/ofr2013-1024_f.pdf","text":"Report","size":"6.8 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"California","county":"San Bernardino County","city":"Fort Irwin","contact":"Contact Information,
Geology, Minerals, Energy, & Geophysics Science Center—Menlo Park
U.S. Geological Survey
345 Middlefield Road
Menlo Park, CA 94025-3591
The U.S. Geological Survey operated six distinct programs to provide external quality-assurance monitoring for the National Atmospheric Deposition Program (NADP) / National Trends Network (NTN) and Mercury Deposition Network (MDN) during 2011–2012. The field-audit program assessed the effects of onsite exposure, sample handling, and shipping on the chemistry of NTN samples; a system-blank program assessed the same effects for MDN. Two interlaboratory-comparison programs assessed the bias and variability of the chemical analysis data from the Central Analytical Laboratory and Mercury Analytical Laboratory (HAL). A blind-audit program was implemented for the MDN during 2011 to evaluate analytical bias in HAL total mercury concentration data. The co-located–sampler program was used to identify and quantify potential shifts in NADP data resulting from the replacement of original network instrumentation with new electronic recording rain gages and precipitation collectors that use optical precipitation sensors.
The results indicate that NADP data continue to be of sufficient quality for the analysis of spatial distributions and time trends of chemical constituents in wet deposition across the United States. Co-located rain gage results indicate -3.7 to +6.5 percent bias in NADP precipitation-depth measurements. Co-located collector results suggest that the retrofit of the NADP networks with the new precipitation collectors could cause +10 to +36 percent shifts in NADP annual deposition values for ammonium, nitrate, and sulfate; -7.5 to +41 percent shifts for hydrogen-ion deposition; and larger shifts (-51 to +52 percent) for calcium, magnesium, sodium, potassium, and chloride. The prototype N-CON Systems bucket collector typically catches more precipitation than the NADP-approved Aerochem Metrics Model 301 collector.
","language":"English","publisher":"University of Illinois, Prairie Research Institute, Illinois State Water Survey","publisherLocation":"Champaign, IL","usgsCitation":"Wetherbee, G.A., and Martin, R., 2014, U.S. Geological Survey external quality-assurance project report for the National Atmospheric Deposition Program / National Trends Network and Mercury Deposition Network, 2011-2012, viii, 52 p.","productDescription":"viii, 52 p.","ipdsId":"IP-050735","costCenters":[{"id":143,"text":"Branch of Quality Systems","active":true,"usgs":true}],"links":[{"id":342452,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5940f9b4e4b0764e6c63eacd","contributors":{"authors":[{"text":"Wetherbee, Gregory A. 0000-0002-6720-2294 wetherbe@usgs.gov","orcid":"https://orcid.org/0000-0002-6720-2294","contributorId":1044,"corporation":false,"usgs":true,"family":"Wetherbee","given":"Gregory","email":"wetherbe@usgs.gov","middleInitial":"A.","affiliations":[{"id":143,"text":"Branch of Quality Systems","active":true,"usgs":true}],"preferred":true,"id":524792,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Martin, RoseAnn ramartin@usgs.gov","contributorId":5367,"corporation":false,"usgs":true,"family":"Martin","given":"RoseAnn","email":"ramartin@usgs.gov","affiliations":[{"id":143,"text":"Branch of Quality Systems","active":true,"usgs":true}],"preferred":true,"id":524793,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70169892,"text":"70169892 - 2014 - USGS/EPA collection protocol for bacterial pathogens in soil","interactions":[],"lastModifiedDate":"2017-04-25T09:53:53","indexId":"70169892","displayToPublicDate":"2017-04-25T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"seriesNumber":"EPA/600/R-14/027","title":"USGS/EPA collection protocol for bacterial pathogens in soil","docAbstract":"This Sample Collection Procedure (SCP) describes the activities and considerations for the collection of bacterial pathogens from representative surface soil samples (0-5 cm). This sampling depth can be reached without the use of a drill rig, direct-push technology, or other mechanized equipment.
This procedure can be used in most soil types but is limited to sampling at or near the ground surface. This protocol has components for two different types of sampling applications: (1) typical sampling, when there is no suspicion of contamination (e.g., surveillance or background studies); and (2) in response to known or suspected accidental contamination (e.g., the presence of animal carcasses). This protocol does not cover sampling in response to a suspected bioterrorist or intentional release event.
Surface material is removed to the required depth (0-5 cm) and clean trowel or 50 ml sample tube is used to collect the sample. Sample containers are sealed, bagged, and shipped to the laboratory for analysis. Associated documentation, including a Field Data Log and Chain-of-Custody are also included in this document.
","language":"English","publisher":"Environmental Protection Agency","usgsCitation":"Griffin, D.W., Shaefer, F., Bowling, C., Mattorano, D., Nichols, T., and Erin Silvestri, 2014, USGS/EPA collection protocol for bacterial pathogens in soil (1.0), Report: vi, 34 p.","productDescription":"Report: vi, 34 p.","ipdsId":"IP-045336","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":340233,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":340232,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://cfpub.epa.gov/si/si_public_record_report.cfm?dirEntryId=285571"}],"country":"United States","edition":"1.0","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59006064e4b0e85db3a5dde9","contributors":{"authors":[{"text":"Griffin, Dale W. 0000-0003-1719-5812 dgriffin@usgs.gov","orcid":"https://orcid.org/0000-0003-1719-5812","contributorId":2178,"corporation":false,"usgs":true,"family":"Griffin","given":"Dale","email":"dgriffin@usgs.gov","middleInitial":"W.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":625490,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shaefer, F.L.","contributorId":91169,"corporation":false,"usgs":true,"family":"Shaefer","given":"F.L.","email":"","affiliations":[],"preferred":false,"id":692719,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bowling, Charlena","contributorId":168331,"corporation":false,"usgs":false,"family":"Bowling","given":"Charlena","email":"","affiliations":[{"id":6784,"text":"US EPA","active":true,"usgs":false}],"preferred":false,"id":625491,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Mattorano, Dino","contributorId":168332,"corporation":false,"usgs":false,"family":"Mattorano","given":"Dino","email":"","affiliations":[{"id":6784,"text":"US EPA","active":true,"usgs":false}],"preferred":false,"id":625492,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Nichols, Tonya","contributorId":168334,"corporation":false,"usgs":false,"family":"Nichols","given":"Tonya","email":"","affiliations":[{"id":6784,"text":"US EPA","active":true,"usgs":false}],"preferred":false,"id":625494,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Erin Silvestri","contributorId":168333,"corporation":false,"usgs":false,"family":"Erin Silvestri","affiliations":[{"id":6784,"text":"US EPA","active":true,"usgs":false}],"preferred":false,"id":625493,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}} ,{"id":70179913,"text":"70179913 - 2014 - Groundwater conditions in Utah, spring of 2014","interactions":[],"lastModifiedDate":"2019-05-22T09:26:33","indexId":"70179913","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"seriesTitle":{"id":110,"text":"Cooperative Investigations Report","active":true,"publicationSubtype":{"id":2}},"seriesNumber":"55","title":"Groundwater conditions in Utah, spring of 2014","docAbstract":"This is the fifty-first in a series of annual reports that describe groundwater conditions in Utah. Reports in this series, published cooperatively by the U.S. Geological Survey and the Utah Department of Natural Resources, Division of Water Rights, and the Utah Department of Environmental Quality, Division of Water Quality, provide data to enable interested parties to maintain awareness of changing groundwater conditions.
This report, like the others in the series, contains information on well construction, groundwater withdrawal from wells, water-level changes, precipitation, streamflow, and chemical quality of water. Information on well construction included in this report refers only to wells constructed for new appropriations of groundwater. Supplementary data are included in reports of this series only for those years or areas that are important to a discussion of changing groundwater conditions and for which applicable data are available.
This report includes individual discussions of selected significant areas of groundwater development in the State for calendar year 2013. Most of the reported data were collected by the U.S. Geological Survey in cooperation with the Utah Department of Natural Resources, Division of Water Rights, and the Utah Department of Environmental Quality, Division of Water Quality. This report is also available online at http://www.waterrights.utah.gov/techinfo/ and http://ut.water. usgs.gov/publications/GW2014.pdf. Groundwater conditions in Utah for calendar year 2012 are reported in Burden and others (2013) and are available online at http://ut.water.usgs. gov/publications/GW2013.pdf
","language":"English","publisher":"Utah Department of Natural Resources","publisherLocation":"Salt Lake City, UT","collaboration":"Prepared in cooperation with the Utah Department of Natural Resources, Division of Water Rights, and Utah Department of Environmental Quality, Division of Water Quality","usgsCitation":"Burden, C.B., Birken, A.S., Gerner, S.J., Carricaburu, J.P., Derrick, V.N., Downhour, P., Smith, L., Eacret, R.J., Gibson, T.L., Slaugh, B.A., Whittier, N.R., Howells, J.H., Christiansen, H.K., and Fisher, M.J., 2014, Groundwater conditions in Utah, spring of 2014: Cooperative Investigations Report 55, x, 118 p.","productDescription":"x, 118 p.","numberOfPages":"132","costCenters":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":333538,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":364062,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://waterrights.utah.gov/techinfo/wwwpub/GW2014.pdf"}],"country":"United States","state":"Utah","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58833023e4b0d00231637796","contributors":{"authors":[{"text":"Burden, Carole B. cburden@usgs.gov","contributorId":852,"corporation":false,"usgs":true,"family":"Burden","given":"Carole","email":"cburden@usgs.gov","middleInitial":"B.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":659189,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Birken, Adam S.","contributorId":178617,"corporation":false,"usgs":false,"family":"Birken","given":"Adam","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":660141,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gerner, Steven J. 0000-0002-5701-1304 sjgerner@usgs.gov","orcid":"https://orcid.org/0000-0002-5701-1304","contributorId":972,"corporation":false,"usgs":true,"family":"Gerner","given":"Steven","email":"sjgerner@usgs.gov","middleInitial":"J.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":660142,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Carricaburu, John P.","contributorId":178619,"corporation":false,"usgs":false,"family":"Carricaburu","given":"John","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":660143,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Derrick, V. Noah","contributorId":178618,"corporation":false,"usgs":false,"family":"Derrick","given":"V.","email":"","middleInitial":"Noah","affiliations":[],"preferred":false,"id":660144,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Downhour, Paul downhour@usgs.gov","contributorId":968,"corporation":false,"usgs":true,"family":"Downhour","given":"Paul","email":"downhour@usgs.gov","affiliations":[],"preferred":true,"id":660145,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Smith, Lincoln","contributorId":178614,"corporation":false,"usgs":false,"family":"Smith","given":"Lincoln","affiliations":[],"preferred":false,"id":660146,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Eacret, Robert J. rjeacret@usgs.gov","contributorId":971,"corporation":false,"usgs":true,"family":"Eacret","given":"Robert","email":"rjeacret@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":true,"id":660147,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Gibson, Travis L.","contributorId":178615,"corporation":false,"usgs":false,"family":"Gibson","given":"Travis","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":660148,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Slaugh, Bradley A. baslaugh@usgs.gov","contributorId":966,"corporation":false,"usgs":true,"family":"Slaugh","given":"Bradley","email":"baslaugh@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":660149,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Whittier, Nickolas R.","contributorId":178616,"corporation":false,"usgs":false,"family":"Whittier","given":"Nickolas","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":660150,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Howells, James H. jhowells@usgs.gov","contributorId":969,"corporation":false,"usgs":true,"family":"Howells","given":"James","email":"jhowells@usgs.gov","middleInitial":"H.","affiliations":[],"preferred":true,"id":660151,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Christiansen, Howard K.","contributorId":47830,"corporation":false,"usgs":true,"family":"Christiansen","given":"Howard","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":660152,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Fisher, Martel J. mjfisher@usgs.gov","contributorId":4410,"corporation":false,"usgs":true,"family":"Fisher","given":"Martel","email":"mjfisher@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":true,"id":660153,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}} ,{"id":70179707,"text":"70179707 - 2014 - Comparison of mineral weathering and biomass nutrient uptake in two small forested watersheds underlain by quartzite bedrock, Catoctin Mountain, Maryland, USA","interactions":[],"lastModifiedDate":"2017-01-13T10:07:12","indexId":"70179707","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":866,"text":"Aquatic Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Comparison of mineral weathering and biomass nutrient uptake in two small forested watersheds underlain by quartzite bedrock, Catoctin Mountain, Maryland, USA","docAbstract":"To quantify chemical weathering and biological uptake, mass-balance calculations were performed on two small forested watersheds located in the Blue Ridge Physiographic Province in north-central Maryland, USA. Both watersheds, Bear Branch (BB) and Fishing Creek Tributary (FCT), are underlain by relatively unreactive quartzite bedrock. Such unreactive bedrock and associated low chemical-weathering rates offer the opportunity to quantify biological processes operating within the watershed. Hydrologic and stream-water chemistry data were collected from the two watersheds for the 9-year period from June 1, 1990 to May 31, 1999. Of the two watersheds, FCT exhibited both higher chemical-weathering rates and biomass nutrient uptake rates, suggesting that forest biomass aggradation was limited by the rate of chemical weathering of the bedrock. Although the chemical-weathering rate in the FCT watershed was low relative to the global average, it masked the influence of biomass base-cation uptake on stream-water chemistry. Any differences in bedrock mineralogy between the two watersheds did not exert a significant influence on the overall weathering stoichiometry. The difference in chemical-weathering rates between the two watersheds is best explained by a larger proportion of reactive phyllitic layers within the bedrock of the FCT watershed. Although the stream gradient of BB is about two-times greater than that of FCT, its influence on chemical weathering appears to be negligible. The findings of this study support the biomass nutrient uptake stoichiometry of K1.0Mg1.1Ca0.97 previously determined for the study site. Investigations of the chemical weathering of relatively unreactive quartzite bedrock may provide insight into critical zone processes.
","language":"English","publisher":"Springer","doi":"10.1007/s10498-013-9205-8","usgsCitation":"Rice, K.C., and Price, J.R., 2014, Comparison of mineral weathering and biomass nutrient uptake in two small forested watersheds underlain by quartzite bedrock, Catoctin Mountain, Maryland, USA: Aquatic Geochemistry, v. 20, no. 2, p. 225-242, https://doi.org/10.1007/s10498-013-9205-8.","productDescription":"18 p.","startPage":"225","endPage":"242","ipdsId":"IP-043877","costCenters":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true}],"links":[{"id":333125,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland","county":"Frederick","otherGeospatial":"Catoctin Mountain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.50957489013672,\n 39.525494363862606\n ],\n [\n -77.50957489013672,\n 39.67019926771586\n ],\n [\n -77.37361907958984,\n 39.67019926771586\n ],\n [\n -77.37361907958984,\n 39.525494363862606\n ],\n [\n -77.50957489013672,\n 39.525494363862606\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"20","issue":"2","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2013-09-07","publicationStatus":"PW","scienceBaseUri":"5878a48de4b04df303d9581c","contributors":{"authors":[{"text":"Rice, Karen C. 0000-0002-9356-5443 kcrice@usgs.gov","orcid":"https://orcid.org/0000-0002-9356-5443","contributorId":178269,"corporation":false,"usgs":true,"family":"Rice","given":"Karen","email":"kcrice@usgs.gov","middleInitial":"C.","affiliations":[{"id":37280,"text":"Virginia and West Virginia Water Science Center ","active":true,"usgs":true}],"preferred":true,"id":658360,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Price, Jason R.","contributorId":178278,"corporation":false,"usgs":false,"family":"Price","given":"Jason","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":658361,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70176232,"text":"70176232 - 2014 - Fate of nutrients in shallow groundwater receiving treated septage, Malibu, CA","interactions":[],"lastModifiedDate":"2016-09-06T20:06:38","indexId":"70176232","displayToPublicDate":"2016-09-05T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3825,"text":"Groundwater","active":true,"publicationSubtype":{"id":10}},"title":"Fate of nutrients in shallow groundwater receiving treated septage, Malibu, CA","docAbstract":"Treated wastewater discharged from more than 400 onsite wastewater treatment systems (OWTS) near the Civic Center area of Malibu, California, 40 km west of downtown Los Angeles, composes 28% of the recharge to a 3.4 km2 alluvial aquifer. On the basis of δ18O and δD data, the fraction of wastewater in some samples was >70%. Ammonium and nitrate concentrations in water from 15 water-table wells sampled in July 2009 and April 2010 ranged from <0.01 to 12 milligrams per liter as nitrogen (mg/L as N), and from <0.01 to 11 mg/L as N, respectively. Chemical and isotopic data (δ15N of ammonium and nitrate, and δ18O of nitrate) show two processes remove nitrogen discharged from OWTS. Where groundwater was reducing, sorption of ammonium resulted in 30 to 50% nitrogen removal. Where groundwater was initially oxic, nitrification with subsequent denitrification as reducing conditions developed, resulted in up to 60% nitrogen removal. Nitrogen removal through sorption dominated during the cooler April sample period, and denitrification dominated during the warmer July sample period. The combination of mixing and nitrogen removal due to denitrification, sorption, and volatilization produces a δ15N apparent fractionation factor (εapp= -5), that can be explained using laboratory-derived fractionation factors (ε) for the individual processes. Phosphate concentrations ranged from <0.04 to 2 mg/L as phosphorous. Sorption to iron oxides on the surfaces of mineral grains at near-neutral pH's removed some phosphate; however, little removal occurred at more alkaline pH's (>7.3).
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","language":"English","publisher":"Frontiers","doi":"10.3389/fmicb.2014.00078","usgsCitation":"VanBlaricom, G.R., 2014, Reduced disease in black abalone following mass mortality: Phage therapy and natural selection: Frontiers in Microbiology, v. 5, no. 78, https://doi.org/10.3389/fmicb.2014.00078.","productDescription":"10 p.","startPage":"10","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-054924","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":472498,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fmicb.2014.00078","text":"Publisher Index Page"},{"id":323874,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"5","issue":"78","edition":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2014-03-18","publicationStatus":"PW","scienceBaseUri":"57651f3ae4b07657d19c7924","contributors":{"authors":[{"text":"VanBlaricom, Glenn R. glennvb@usgs.gov","contributorId":3540,"corporation":false,"usgs":true,"family":"VanBlaricom","given":"Glenn","email":"glennvb@usgs.gov","middleInitial":"R.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":false,"id":637199,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70173949,"text":"70173949 - 2014 - Prevalence of pure versus mixed snow cover pixels across spatial resolutions in alpine environments: implications for binary and fractional remote sensing approaches","interactions":[],"lastModifiedDate":"2016-06-20T10:22:54","indexId":"70173949","displayToPublicDate":"2016-01-19T07:45:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Prevalence of pure versus mixed snow cover pixels across spatial resolutions in alpine environments: implications for binary and fractional remote sensing approaches","docAbstract":"Remote sensing of snow-covered area (SCA) can be binary (indicating the presence/absence of snow cover at each pixel) or fractional (indicating the fraction of each pixel covered by snow). Fractional SCA mapping provides more information than binary SCA, but is more difficult to implement and may not be feasible with all types of remote sensing data. The utility of fractional SCA mapping relative to binary SCA mapping varies with the intended application as well as by spatial resolution, temporal resolution and period of interest, and climate. We quantified the frequency of occurrence of partially snow-covered (mixed) pixels at spatial resolutions between 1 m and 500 m over five dates at two study areas in the western U.S., using 0.5 m binary SCA maps derived from high spatial resolution imagery aggregated to fractional SCA at coarser spatial resolutions. In addition, we used in situ monitoring to estimate the frequency of partially snow-covered conditions for the period September 2013–August 2014 at 10 60-m grid cell footprints at two study areas with continental snow climates. Results from the image analysis indicate that at 40 m, slightly above the nominal spatial resolution of Landsat, mixed pixels accounted for 25%–93% of total pixels, while at 500 m, the nominal spatial resolution of MODIS bands used for snow cover mapping, mixed pixels accounted for 67%–100% of total pixels. Mixed pixels occurred more commonly at the continental snow climate site than at the maritime snow climate site. The in situ data indicate that some snow cover was present between 186 and 303 days, and partial snow cover conditions occurred on 10%–98% of days with snow cover. Four sites remained partially snow-free throughout most of the winter and spring, while six sites were entirely snow covered throughout most or all of the winter and spring. Within 60 m grid cells, the late spring/summer transition from snow-covered to snow-free conditions lasted 17–56 days and averaged 37 days. Our results suggest that mixed snow-covered snow-free pixels are common at the spatial resolutions imaged by both the Landsat and MODIS sensors. This highlights the additional information available from fractional SCA products and suggests fractional SCA can provide a major advantage for hydrological and climatological monitoring and modeling, particularly when accurate representation of the spatial distribution of snow cover is critical.
","language":"English","publisher":"MDPI","doi":"10.3390/rs61212478","usgsCitation":"Selkowitz, D.J., Forster, R., and Caldwell, M.K., 2014, Prevalence of pure versus mixed snow cover pixels across spatial resolutions in alpine environments: implications for binary and fractional remote sensing approaches: Remote Sensing, v. 6, no. 12, p. 12478-12508, https://doi.org/10.3390/rs61212478.","productDescription":"30 p.","startPage":"12478","endPage":"12508","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060122","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":472504,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs61212478","text":"Publisher Index Page"},{"id":323952,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","issue":"12","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2014-12-11","publicationStatus":"PW","scienceBaseUri":"576913e4e4b07657d19ff238","contributors":{"authors":[{"text":"Selkowitz, David J. 0000-0003-0824-7051 dselkowitz@usgs.gov","orcid":"https://orcid.org/0000-0003-0824-7051","contributorId":3259,"corporation":false,"usgs":true,"family":"Selkowitz","given":"David","email":"dselkowitz@usgs.gov","middleInitial":"J.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"preferred":true,"id":639740,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Forster, Richard","contributorId":172149,"corporation":false,"usgs":false,"family":"Forster","given":"Richard","affiliations":[{"id":26993,"text":"University of Utah, Department of Geography","active":true,"usgs":false}],"preferred":false,"id":639741,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Caldwell, Megan K. mcaldwell@usgs.gov","contributorId":4243,"corporation":false,"usgs":true,"family":"Caldwell","given":"Megan","email":"mcaldwell@usgs.gov","middleInitial":"K.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":639742,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70173946,"text":"70173946 - 2014 - Thermal measurements of dark and bright surface features on Vesta as derived from Dawn/VIR","interactions":[],"lastModifiedDate":"2016-06-20T10:25:51","indexId":"70173946","displayToPublicDate":"2016-01-13T13:30:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1963,"text":"Icarus","active":true,"publicationSubtype":{"id":10}},"title":"Thermal measurements of dark and bright surface features on Vesta as derived from Dawn/VIR","docAbstract":"Remote sensing data acquired during Dawn’s orbital mission at Vesta showed several local concentrations of high-albedo (bright) and low-albedo (dark) material units, in addition to spectrally distinct meteorite impact ejecta. The thermal behavior of such areas seen at local scale (1-10 km) is related to physical properties that can provide information about the origin of those materials. We use Dawn’s Visible and InfraRed (VIR) mapping spectrometer hyperspectral data to retrieve surface temperatures and emissivities, with high accuracy as long as temperatures are greater than 220 K. Some of the dark and bright features were observed multiple times by VIR in the various mission phases at variable spatial resolution, illumination and observation angles, local solar time, and heliocentric distance. This work presents the first temperature maps and spectral emissivities of several kilometer-scale dark and bright material units on Vesta. Results retrieved from the infrared data acquired by VIR show that bright regions generally correspond to regions with lower temperature, while dark regions correspond to areas with higher temperature. During maximum daily insolation and in the range of heliocentric distances explored by Dawn, i.e. 2.23-2.54 AU, the warmest dark unit found on Vesta rises to a temperature of 273 K, while bright units observed under comparable conditions do not exceed 266 K. Similarly, dark units appear to have higher emissivity on average compared to bright units. Dark-material units show a weak anticorrelation between temperature and albedo, whereas the relation is stronger for bright material units observed under the same conditions. Individual features may show either evanescent or distinct margins in the thermal images, as a consequence of the cohesion of the surface material. Finally, for the two categories of dark and bright materials, we were able to highlight the influence of heliocentric distance on surface temperatures, and estimate an average temperature rate change of 1% following a variation of 0.04 AU in the solar distance.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.icarus.2014.03.017","usgsCitation":"Tosi, F., Capria, M.T., Sanctis, D., Combe, J., Zambon, F., Nathues, A., Schröder, S., Li, J., Palomba, E., Longobardo, A., Blewett, D., Denevi, B., Palmer, E., Capaccioni, F., Ammannito, E., Titus, T.N., Mittlefehldt, D., Sunshine, J., Russell, C., Raymond, C., and Team, D., 2014, Thermal measurements of dark and bright surface features on Vesta as derived from Dawn/VIR: Icarus, v. 240, p. 36-57, https://doi.org/10.1016/j.icarus.2014.03.017.","productDescription":"21 p.","startPage":"36","endPage":"57","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-049721","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":323955,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"240","publishingServiceCenter":{"id":14,"text":"Menlo Park 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Agency","active":true,"usgs":false}],"preferred":false,"id":639717,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Longobardo, A.","contributorId":172144,"corporation":false,"usgs":false,"family":"Longobardo","given":"A.","email":"","affiliations":[{"id":26990,"text":"INAF-IAPS Istituto di Astrofisica e Planetologia Spaziali, Rome","active":true,"usgs":false}],"preferred":false,"id":639718,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Blewett, D.T.","contributorId":79283,"corporation":false,"usgs":true,"family":"Blewett","given":"D.T.","email":"","affiliations":[],"preferred":false,"id":639719,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Denevi, B.W.","contributorId":20559,"corporation":false,"usgs":true,"family":"Denevi","given":"B.W.","affiliations":[],"preferred":false,"id":639720,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Palmer, E.","contributorId":172145,"corporation":false,"usgs":false,"family":"Palmer","given":"E.","email":"","affiliations":[{"id":24732,"text":"Planetary Science Institute, Tucson","active":true,"usgs":false}],"preferred":false,"id":639721,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Capaccioni, F.","contributorId":90900,"corporation":false,"usgs":true,"family":"Capaccioni","given":"F.","email":"","affiliations":[],"preferred":false,"id":639722,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Ammannito, E.","contributorId":145550,"corporation":false,"usgs":false,"family":"Ammannito","given":"E.","email":"","affiliations":[{"id":16145,"text":"Italian Space Agency","active":true,"usgs":false}],"preferred":false,"id":639723,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Titus, Timothy N. 0000-0003-0700-4875 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C.T.","contributorId":32275,"corporation":false,"usgs":false,"family":"Russell","given":"C.T.","email":"","affiliations":[{"id":33607,"text":"University of California Los Angeles","active":true,"usgs":false}],"preferred":false,"id":639726,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Raymond, C.A.","contributorId":50301,"corporation":false,"usgs":false,"family":"Raymond","given":"C.A.","email":"","affiliations":[{"id":18954,"text":"Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA","active":true,"usgs":false}],"preferred":false,"id":639727,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Team, Dawn/VIR","contributorId":172146,"corporation":false,"usgs":false,"family":"Team","given":"Dawn/VIR","email":"","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":639728,"contributorType":{"id":1,"text":"Authors"},"rank":21}]}} ,{"id":70173668,"text":"70173668 - 2014 - When to be discrete: The importance of time formulation in understanding animal movement","interactions":[],"lastModifiedDate":"2016-06-08T09:57:47","indexId":"70173668","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2792,"text":"Movement Ecology","active":true,"publicationSubtype":{"id":10}},"title":"When to be discrete: The importance of time formulation in understanding animal movement","docAbstract":"Animal movement is essential to our understanding of population dynamics, animal behavior, and the impacts of global change. Coupled with high-resolution biotelemetry data, exciting new inferences about animal movement have been facilitated by various specifications of contemporary models. These approaches differ, but most share common themes. One key distinction is whether the underlying movement process is conceptualized in discrete or continuous time. This is perhaps the greatest source of confusion among practitioners, both in terms of implementation and biological interpretation. In general, animal movement occurs in continuous time but we observe it at fixed discrete-time intervals. Thus, continuous time is conceptually and theoretically appealing, but in practice it is perhaps more intuitive to interpret movement in discrete intervals. With an emphasis on state-space models, we explore the differences and similarities between continuous and discrete versions of mechanistic movement models, establish some common terminology, and indicate under which circumstances one form might be preferred over another. Counter to the overly simplistic view that discrete- and continuous-time conceptualizations are merely different means to the same end, we present novel mathematical results revealing hitherto unappreciated consequences of model formulation on inferences about animal movement. Notably, the speed and direction of movement are intrinsically linked in current continuous-time random walk formulations, and this can have important implications when interpreting animal behavior. We illustrate these concepts in the context of state-space models with multiple movement behavior states using northern fur seal (Callorhinus ursinus) biotelemetry data.
","language":"English","publisher":"BioMed Central","doi":"10.1186/s40462-014-0021-6","usgsCitation":"McClintock, B.T., Johnson, D., Hooten, M., Ver Hoef, J.M., and Morales, J.M., 2014, When to be discrete: The importance of time formulation in understanding animal movement: Movement Ecology, v. 2, no. 21, 14 p., https://doi.org/10.1186/s40462-014-0021-6.","productDescription":"14 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-054164","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":472507,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s40462-014-0021-6","text":"Publisher Index Page"},{"id":323248,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"2","issue":"21","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2014-10-15","publicationStatus":"PW","scienceBaseUri":"5759423ae4b04f417c256a1b","contributors":{"authors":[{"text":"McClintock, Brett T. 0000-0001-6154-4376","orcid":"https://orcid.org/0000-0001-6154-4376","contributorId":83785,"corporation":false,"usgs":true,"family":"McClintock","given":"Brett","email":"","middleInitial":"T.","affiliations":[{"id":12448,"text":"U.S. National Oceanic and Atmospheric Administration","active":true,"usgs":false},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":637821,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Devin S.","contributorId":47524,"corporation":false,"usgs":true,"family":"Johnson","given":"Devin S.","affiliations":[],"preferred":false,"id":637822,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hooten, Mevin 0000-0002-1614-723X mhooten@usgs.gov","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":2958,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","email":"mhooten@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false}],"preferred":true,"id":637476,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ver Hoef, Jay M.","contributorId":42504,"corporation":false,"usgs":true,"family":"Ver Hoef","given":"Jay","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":637823,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Morales, Juan M.","contributorId":171521,"corporation":false,"usgs":false,"family":"Morales","given":"Juan","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":637824,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70173455,"text":"70173455 - 2014 - Regional variability among nonlinear chlorophyll-phosphorus relationships in lakes","interactions":[],"lastModifiedDate":"2016-06-17T14:53:37","indexId":"70173455","displayToPublicDate":"2015-12-22T13:30:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2620,"text":"Limnology and Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"Regional variability among nonlinear chlorophyll-phosphorus relationships in lakes","docAbstract":"The relationship between chlorophyll a (Chl a) and total phosphorus (TP) is a fundamental relationship in lakes that reflects multiple aspects of ecosystem function and is also used in the regulation and management of inland waters. The exact form of this relationship has substantial implications on its meaning and its use. We assembled a spatially extensive data set to examine whether nonlinear models are a better fit for Chl a—TP relationships than traditional log-linear models, whether there were regional differences in the form of the relationships, and, if so, which regional factors were related to these differences. We analyzed a data set from 2105 temperate lakes across 35 ecoregions by fitting and comparing two different nonlinear models and one log-linear model. The two nonlinear models fit the data better than the log-linear model. In addition, the parameters for the best-fitting model varied among regions: the maximum and lower Chl aasymptotes were positively and negatively related to percent regional pasture land use, respectively, and the rate at which chlorophyll increased with TP was negatively related to percent regional wetland cover. Lakes in regions with more pasture fields had higher maximum chlorophyll concentrations at high TP concentrations but lower minimum chlorophyll concentrations at low TP concentrations. Lakes in regions with less wetland cover showed a steeper Chl a—TP relationship than wetland-rich regions. Interpretation of Chl a—TP relationships depends on regional differences, and theory and management based on a monolithic relationship may be inaccurate.
","language":"English","publisher":"ASLO","doi":"10.4319/lo.2014.59.5.1691","usgsCitation":"Filstrup, C.T., Wagner, T., Soranno, P.A., Stanley, E.H., Stow, C., Webster, K.E., and Downing, J., 2014, Regional variability among nonlinear chlorophyll-phosphorus relationships in lakes: Limnology and Oceanography, v. 59, no. 5, p. 1691-1703, https://doi.org/10.4319/lo.2014.59.5.1691.","productDescription":"12 p.","startPage":"1691","endPage":"1703","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-051853","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":323926,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Iowa, Maine, Michigan, New Hampshire, Ohio, 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predicting mean daily river water temperature","docAbstract":"Water temperature is a fundamental property of river habitat and often a key aspect of river resource management, but measurements to characterize thermal regimes are not available for most streams and rivers. As such, we developed an artificial neural network (ANN) ensemble model to predict mean daily water temperature in 197,402 individual stream reaches during the warm season (May–October) throughout the native range of brook trout Salvelinus fontinalis in the eastern U.S. We compared four models with different groups of predictors to determine how well water temperature could be predicted by climatic, landform, and land cover attributes, and used the median prediction from an ensemble of 100 ANNs as our final prediction for each model. The final model included air temperature, landform attributes and forested land cover and predicted mean daily water temperatures with moderate accuracy as determined by root mean squared error (RMSE) at 886 training sites with data from 1980 to 2009 (RMSE = 1.91 °C). Based on validation at 96 sites (RMSE = 1.82) and separately for data from 2010 (RMSE = 1.93), a year with relatively warmer conditions, the model was able to generalize to new stream reaches and years. The most important predictors were mean daily air temperature, prior 7 day mean air temperature, and network catchment area according to sensitivity analyses. Forest land cover at both riparian and catchment extents had relatively weak but clear negative effects. Predicted daily water temperature averaged for the month of July matched expected spatial trends with cooler temperatures in headwaters and at higher elevations and latitudes. Our ANN ensemble is unique in predicting daily temperatures throughout a large region, while other regional efforts have predicted at relatively coarse time steps. The model may prove a useful tool for predicting water temperatures in sampled and unsampled rivers under current conditions and future projections of climate and land use changes, thereby providing information that is valuable to management of river ecosystems and biota such as brook trout.
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We used hierarchical Bayesian models to evaluate the spatial and temporal variability in density and capture probability of age-1 and older Brook Trout Salvelinus fontinalis from three-pass removal data collected at 291 sites over a 37-year time period (1975–2011) in Pennsylvania streams. There was high between-year variability in density, with annual posterior means ranging from 2.1 to 10.2 fish/100 m2; however, there was no significant long-term linear trend. Brook Trout density was positively correlated with elevation and negatively correlated with percent developed land use in the network catchment. Probability of capture did not vary substantially across sites or years but was negatively correlated with mean stream width. Because of the low spatiotemporal variation in capture probability and a strong correlation between first-pass CPUE (catch/min) and three-pass removal density estimates, the use of an abundance index based on first-pass CPUE could represent a cost-effective alternative to conducting multiple-pass removal sampling for some Brook Trout monitoring and assessment objectives. Single-pass indices may be particularly relevant for monitoring objectives that do not require precise site-specific estimates, such as regional monitoring programs that are designed to detect long-term linear trends in density.
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PA","active":true,"usgs":false}],"preferred":false,"id":639614,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Detar, Jason","contributorId":171356,"corporation":false,"usgs":false,"family":"Detar","given":"Jason","email":"","affiliations":[{"id":26873,"text":"Pennsylvania Fish and Boat Commission, Bellefonte, PA","active":true,"usgs":false}],"preferred":false,"id":639615,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kristine, David","contributorId":172107,"corporation":false,"usgs":false,"family":"Kristine","given":"David","email":"","affiliations":[],"preferred":false,"id":639616,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"John A. Sweka","contributorId":171358,"corporation":false,"usgs":false,"family":"John A. Sweka","affiliations":[{"id":26874,"text":"USFWS, Lamar, PA","active":true,"usgs":false}],"preferred":false,"id":639617,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70173450,"text":"70173450 - 2014 - Modeling spatially-varying landscape change points in species occurrence thresholds","interactions":[],"lastModifiedDate":"2016-06-20T12:48:28","indexId":"70173450","displayToPublicDate":"2015-12-15T02:30:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Modeling spatially-varying landscape change points in species occurrence thresholds","docAbstract":"Predicting species distributions at scales of regions to continents is often necessary, as large-scale phenomena influence the distributions of spatially structured populations. Land use and land cover are important large-scale drivers of species distributions, and landscapes are known to create species occurrence thresholds, where small changes in a landscape characteristic results in abrupt changes in occurrence. The value of the landscape characteristic at which this change occurs is referred to as a change point. We present a hierarchical Bayesian threshold model (HBTM) that allows for estimating spatially varying parameters, including change points. Our model also allows for modeling estimated parameters in an effort to understand large-scale drivers of variability in land use and land cover on species occurrence thresholds. We use range-wide detection/nondetection data for the eastern brook trout (Salvelinus fontinalis), a stream-dwelling salmonid, to illustrate our HBTM for estimating and modeling spatially varying threshold parameters in species occurrence. We parameterized the model for investigating thresholds in landscape predictor variables that are measured as proportions, and which are therefore restricted to values between 0 and 1. Our HBTM estimated spatially varying thresholds in brook trout occurrence for both the proportion agricultural and urban land uses. There was relatively little spatial variation in change point estimates, although there was spatial variability in the overall shape of the threshold response and associated uncertainty. In addition, regional mean stream water temperature was correlated to the change point parameters for the proportion of urban land use, with the change point value increasing with increasing mean stream water temperature. We present a framework for quantify macrosystem variability in spatially varying threshold model parameters in relation to important large-scale drivers such as land use and land cover. Although the model presented is a logistic HBTM, it can easily be extended to accommodate other statistical distributions for modeling species richness or abundance.
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critical zone processes","interactions":[],"lastModifiedDate":"2017-10-26T11:12:27","indexId":"70159864","displayToPublicDate":"2015-12-01T15:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1213,"text":"Chemical Geology","active":true,"publicationSubtype":{"id":10}},"title":"Hydrogeochemistry of prairie pothole region wetlands: Role of long-term critical zone processes","docAbstract":"This study addresses the geologic and hydrogeochemical processes operating at a range of scales within the prairie pothole region (PPR). The PPR is a 750,000 km2portion of north central North America that hosts millions of small wetlands known to be critical habitat for waterfowl and other wildlife. At a local scale, we characterized the geochemical evolution of the 92-ha Cottonwood Lake study area (CWLSA), located in North Dakota, USA. Critical zone processes are the long-term determinant of wetland water and groundwater geochemistry via the interaction of oxygenated groundwater with pyrite in the underlying glacial till. Pyrite oxidation produced a brown, iron oxide-bearing surface layer locally over 13 m thick and an estimated minimum of 1.3 × 1010 g sulfate (SO42 −) at CWLSA. We show that the majority of this SO42− now resides in solid-phase gypsum (CaSO4•2H2O) and gypsum-saturated groundwater.
\nResults from the CWLSA were scaled up to a 9700 km2 area surrounding CWLSA using ~ 1800 drill logs and literature data on wetland water chemistry for 178 wetlands within this larger area. The oxidized brown zone depth and wetland water compositional trends are very similar to the CWLSA. Additionally, surface water data from 176 southern Canadian pothole wetlands that conform to the same wetland water geochemical trends as those recorded in the CWLSA further corroborate that SO42 − accumulation driven by pyrite oxidation is a nearly ubiquitous process in the prairie pothole region and distinguishes PPR wetlands from other wetlands worldwide that have a similar overall hydrology.
","language":"English","publisher":"ScienceDirect","doi":"10.1016/j.chemgeo.2014.08.023","usgsCitation":"Goldhaber, M.B., Mills, C., Morrison, J.M., Stricker, C.A., Mushet, D.M., and LaBaugh, J.W., 2014, Hydrogeochemistry of prairie pothole region wetlands: Role of long-term critical zone processes: Chemical Geology, v. 387, p. 170-183, https://doi.org/10.1016/j.chemgeo.2014.08.023.","productDescription":"14 p.","startPage":"170","endPage":"183","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-036658","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":311772,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Manitoba, North Dakota, Saskatchewan","otherGeospatial":"Cottonwood Lake Study Area, Erickson-Elphinstone District, Moose Mountain Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -103.370361328125,\n 46.44542749723387\n ],\n [\n -103.370361328125,\n 50.078294547389426\n ],\n [\n -98.887939453125,\n 50.078294547389426\n ],\n [\n -98.887939453125,\n 46.44542749723387\n ],\n [\n -103.370361328125,\n 46.44542749723387\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"387","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"565ec4afe4b071e7ea54440f","chorus":{"doi":"10.1016/j.chemgeo.2014.08.023","url":"http://dx.doi.org/10.1016/j.chemgeo.2014.08.023","publisher":"Elsevier BV","authors":"Goldhaber Martin B., Mills Christopher T., Morrison Jean M., Stricker Craig A., Mushet David M., LaBaugh James W.","journalName":"Chemical Geology","publicationDate":"11/2014","auditedOn":"11/1/2014"},"contributors":{"authors":[{"text":"Goldhaber, Martin B. 0000-0002-1785-4243 mgold@usgs.gov","orcid":"https://orcid.org/0000-0002-1785-4243","contributorId":1339,"corporation":false,"usgs":true,"family":"Goldhaber","given":"Martin","email":"mgold@usgs.gov","middleInitial":"B.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":580795,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mills, Christopher T. 0000-0001-8414-1414 cmills@usgs.gov","orcid":"https://orcid.org/0000-0001-8414-1414","contributorId":150137,"corporation":false,"usgs":true,"family":"Mills","given":"Christopher T.","email":"cmills@usgs.gov","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":580791,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Morrison, Jean M. 0000-0002-6614-8783 jmorrison@usgs.gov","orcid":"https://orcid.org/0000-0002-6614-8783","contributorId":994,"corporation":false,"usgs":true,"family":"Morrison","given":"Jean","email":"jmorrison@usgs.gov","middleInitial":"M.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":580794,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stricker, Craig A. 0000-0002-5031-9437 cstricker@usgs.gov","orcid":"https://orcid.org/0000-0002-5031-9437","contributorId":1097,"corporation":false,"usgs":true,"family":"Stricker","given":"Craig","email":"cstricker@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":580792,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mushet, David M. 0000-0002-5910-2744 dmushet@usgs.gov","orcid":"https://orcid.org/0000-0002-5910-2744","contributorId":1299,"corporation":false,"usgs":true,"family":"Mushet","given":"David","email":"dmushet@usgs.gov","middleInitial":"M.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":580793,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"LaBaugh, James W. 0000-0002-4112-2536 jlabaugh@usgs.gov","orcid":"https://orcid.org/0000-0002-4112-2536","contributorId":1311,"corporation":false,"usgs":true,"family":"LaBaugh","given":"James","email":"jlabaugh@usgs.gov","middleInitial":"W.","affiliations":[{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true}],"preferred":true,"id":580796,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70157275,"text":"70157275 - 2014 - Dynamics of a large, restless, rhyolitic magma system at Laguna del Maule, southern Andes, Chile","interactions":[],"lastModifiedDate":"2015-09-21T13:49:49","indexId":"70157275","displayToPublicDate":"2015-09-01T13:15:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1728,"text":"GSA Today","active":true,"publicationSubtype":{"id":10}},"title":"Dynamics of a large, restless, rhyolitic magma system at Laguna del Maule, southern Andes, Chile","docAbstract":"Explosive eruptions of large-volume rhyolitic magma systems are common in the geologic record and pose a major potential threat to society. Unlike other natural hazards, such as earthquakes and tsunamis, a large rhyolitic volcano may provide warning signs long before a caldera-forming eruption occurs. Yet, these signs—and what they imply about magma-crust dynamics—are not well known. This is because we have learned how these systems form, grow, and erupt mainly from the study of ash flow tuffs deposited tens to hundreds of thousands of years ago or more, or from the geophysical imaging of the unerupted portions of the reservoirs beneath the associated calderas. The Laguna del Maule Volcanic Field, Chile, includes an unusually large and recent concentration of silicic eruptions. Since 2007, the crust there has been inflating at an astonishing rate of at least 25 cm/yr. This unique opportunity to investigate the dynamics of a large rhyolitic system while magma migration, reservoir growth, and crustal deformation are actively under way is stimulating a new international collaboration. Findings thus far lead to the hypothesis that the silicic vents have tapped an extensive layer of crystal-poor, rhyolitic melt that began to form atop a magmatic mush zone that was established by ca. 20 ka with a renewed phase of rhyolite eruptions during the Holocene. Modeling of surface deformation, magnetotelluric data, and gravity changes suggest that magma is currently intruding at a depth of ~5 km. The next phase of this investigation seeks to enlarge the sets of geophysical and geochemical data and to use these observations in numerical models of system dynamics.
","language":"English","publisher":"Geological Society of America","publisherLocation":"Boulder, Co","doi":"10.1130/GSATG216A.1","collaboration":"Singer, Brad; Andersen, N; Le Mevel, H; Feigl, K; DeMets, C; Tikoff, B; Thurber, C; Jicha, B; Cardona, C; Cordoba, L; Gil, F; Unsworth, M; Williams-Jones, G; Miller, C; Hildreth, W; Vazquez, J","usgsCitation":"Singer, B., Andersen, N.L., Le Mevel, H., Feigl, K.L., DeMets, C., Tikoff, B., Thurber, C.H., Jicha, B.R., Cardonna, C., Cordova, L., Gil, F., Unsworth, M.J., Williams-Jones, G., Miller, C., Fierstein, J., Hildreth, E., and Vazquez, J.A., 2014, Dynamics of a large, restless, rhyolitic magma system at Laguna del Maule, southern Andes, Chile: GSA Today, v. 24, no. 12, p. 4-10, https://doi.org/10.1130/GSATG216A.1.","productDescription":"7 p.","startPage":"4","endPage":"10","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059316","costCenters":[{"id":617,"text":"Volcano Science 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distribution and abundance of the American crocodile (Crocodylus acutus) in the Florida Everglades is dependent on the timing, amount, and location of freshwater flow. One of the goals of the Comprehensive Everglades Restoration Plan (CERP) is to restore historic freshwater flows to American crocodile habitat throughout the Everglades. To predict the impacts on the crocodile population from planned restoration activities, we created a stage-based spatially explicit crocodile population model that incorporated regional hydrology models and American crocodile research and monitoring data. Growth and survival were influenced by salinity, water depth, and density-dependent interactions. A stage-structured spatial model was used with discrete spatial convolution to direct crocodiles toward attractive sources where conditions were favorable. The model predicted that CERP would have both positive and negative impacts on American crocodile growth, survival, and distribution. Overall, crocodile populations across south Florida were predicted to decrease approximately 3 % with the implementation of CERP compared to future conditions without restoration, but local increases up to 30 % occurred in the Joe Bay area near Taylor Slough, and local decreases up to 30 % occurred in the vicinity of Buttonwood Canal due to changes in salinity and freshwater flows.
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It previously was observed that there are more short interevent times between consecutive tsunami sources than expected from a stationary Poisson process. The epidemic‐type aftershock sequence (ETAS) branching process model is fitted to tsunami catalog events, using the earthquake magnitude of the causative event from the Centennial and Global Centroid Moment Tensor (CMT) catalogs and tsunami sizes above a completeness level as a mark to indicate that a tsunami was generated. The ETAS parameters are estimated using the maximum‐likelihood method. The interevent distribution associated with the ETAS model provides a better fit to the data than the Poisson model or other temporal clustering models. When tsunamigenic conditions (magnitude threshold, submarine location, dip‐slip mechanism) are applied to the Global CMT catalog, ETAS parameters are obtained that are consistent with those estimated from the tsunami catalog. In particular, the dip‐slip condition appears to result in a near zero magnitude effect for triggered tsunami sources. The overall consistency between results from the tsunami catalog and that from the earthquake catalog under tsunamigenic conditions indicates that ETAS models based on seismicity can provide the structure for understanding patterns of tsunami source occurrence. The fractional rate of triggered tsunami sources on a global basis is approximately 14%.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120130275","usgsCitation":"Geist, E.L., 2014, Explanation of temporal clustering of tsunami sources using the epidemic-type aftershock sequence model: Bulletin of the Seismological Society of America, v. 104, no. 4, p. 2091-2103, https://doi.org/10.1785/0120130275.","productDescription":"13 p.","startPage":"2091","endPage":"2103","numberOfPages":"13","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-052031","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":300395,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"104","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2014-07-01","publicationStatus":"PW","scienceBaseUri":"5555b931e4b0a92fa7e95122","contributors":{"authors":[{"text":"Geist, Eric L. 0000-0003-0611-1150 egeist@usgs.gov","orcid":"https://orcid.org/0000-0003-0611-1150","contributorId":1956,"corporation":false,"usgs":true,"family":"Geist","given":"Eric","email":"egeist@usgs.gov","middleInitial":"L.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":546907,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70139422,"text":"pp1708I.1 - 2014 - Digital data in support of studies and assessments of coal and petroleum resources in the Appalachian basin","interactions":[{"subject":{"id":70139422,"text":"pp1708I.1 - 2014 - Digital data in support of studies and assessments of coal and petroleum resources in the Appalachian basin","indexId":"pp1708I.1","publicationYear":"2014","noYear":false,"chapter":"I.1","title":"Digital data in support of studies and assessments of coal and petroleum resources in the Appalachian basin"},"predicate":"IS_PART_OF","object":{"id":70143874,"text":"pp1708 - 2014 - Coal and petroleum resources in the Appalachian basin: distribution, geologic framework, and geochemical character","indexId":"pp1708","publicationYear":"2014","noYear":false,"title":"Coal and petroleum resources in the Appalachian basin: distribution, geologic framework, and geochemical character"},"id":1}],"isPartOf":{"id":70143874,"text":"pp1708 - 2014 - Coal and petroleum resources in the Appalachian basin: distribution, geologic framework, and geochemical character","indexId":"pp1708","publicationYear":"2014","noYear":false,"title":"Coal and petroleum resources in the Appalachian basin: distribution, geologic framework, and geochemical character"},"lastModifiedDate":"2020-05-14T18:24:33.884533","indexId":"pp1708I.1","displayToPublicDate":"2015-04-02T11:30:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":331,"text":"Professional Paper","code":"PP","onlineIssn":"2330-7102","printIssn":"1044-9612","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1708","chapter":"I.1","title":"Digital data in support of studies and assessments of coal and petroleum resources in the Appalachian basin","docAbstract":"The Appalachian basin is a mature basin containing abundant oil, gas, and coal resources. Its fossil-fuel-bearing strata range in age from Cambrian to Permian and extend over the States of New York, Pennsylvania, Maryland, Ohio, West Virginia, Virginia, Kentucky, Tennessee, Georgia, and Alabama. The basin has provided abundant fossil fuels to support the Nation’s economic growth for at least 150 years and U.S. Geological Survey (USGS) assessments suggest that substantial untapped resources remain. A merger of new and old geologic data and ideas is required to locate and extract those remaining resources.
\nThis chapter brings together abundant existing datasets in a common and integrated spatial format to advance our understanding of the distribution, geologic framework, burial history, and geochemical character of the basin’s oil, gas, and coal resources. These datasets support the information and findings in chapters B through G of this volume, which include (1) geologic cross sections, seismic profiles, and burial history models that document the depositional and structural framework of the basin; (2) assessments of Carboniferous coal-bed gas and Devonian shale gas; (3) studies about the distribution of oil, gas, and coal fields and the geochemistry of natural gas and oil; and (4) a history of fossil-fuel production in the basin.
\nThe data that supported these studies were refined and made more accessible using geographic information system (GIS) tools. The following types of data are included: (1) the bedrock geology of States included within the boundary of the Appalachian basin, (2) the locations of oil and gas wells and fields, (3) data produced for the National Oil and Gas Assessment, and (4) the stratigraphy, geochemistry, and production of coal. Data layers are available in shapefile and Zipped Keyhole Markup Language (KMZ) formats, which can be viewed using ArcGIS, Google Earth, or any software package that supports these data formats.
\nMetadata for these datasets are available in HTML and XML formats. Metadata files contain information about the sources of data used to create the dataset, the creation process steps, the data quality, the geographic coordinate system and horizontal datum used for the dataset, the values of attributes used in the dataset table, information about the publication and the publishing organization, and other information that may be useful to the reader. All links in the metadata were valid at the time of compilation. Some of these links may no longer be valid. No attempt has been made to determine the new online location (if one exists) for the data.
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Silurian carbonate and sandstone reservoirs in the Appalachian basin probably originated from one or more of the following source rocks: (1) Upper Ordovician Utica Shale, (2) Middle to Upper Devonian black shale, and (3) Lower to Upper Silurian shale and carbonate units. In this reconnaissance study, selected Silurian shale and carbonate rocks in the subsurface of New York, Ohio, Pennsylvania, and West Virginia were analyzed for total organic carbon (TOC) content and Rock-Eval parameters to evaluate whether or not a Silurian total petroleum system exists in the Appalachian basin. A total of 308 samples were collected and analyzed for this investigation. Dark-gray to black shale and argillaceous carbonate intervals in the Salina Group (and equivalent units), Cabot Head Shale, Rochester Shale, Rose Hill Formation, Lockport Dolomite (or Group), and McKenzie Limestone (or Member) were prioritized for sampling and analysis.
\nTwenty nine of the 308 samples analyzed had TOC values of 0.50 or greater that qualify them as a petroleum source rock. Also, 24 of the 29 samples (with TOC values of 0.50 or greater) had TOC values between 0.50 and less than 1.00 weight percent. Only 5 samples in the dataset are classified as good to very good source rocks (TOC values of 1.00 to 3.35 weight percent). The majority (n=18) of the 29 samples of potential source rocks with a TOC value of 0.5 or greater are located in the Upper Silurian Salina Group and equivalent Wills Creek Formation. Moreover, all of the good to very good source rocks are located in the Salina Group and Wills Creek Formation in southwestern Pennsylvania and northern West Virginia. The remainder (n=11) of the 29 potential source rocks (TOC values of 0.50 to less than 1.00 weight percent) are located in the Lower Silurian Cabot Head Shale (n=2), Rochester Shale (n=6), Rose Hill Formation (n=1), and Lower to Upper Silurian Lockport Dolomite (n=2). These source rocks of secondary importance are widely distributed across eastern Ohio, western Pennsylvania, and West Virginia.
\nAlthough the TOC analyses in this study indicate that good to very good source rocks are present in the Salina Group and Wills Creek Formation of southwestern Pennsylvania and northern West Virginia, data are insufficient to propose a new Silurian total petroleum system in the Appalachian basin. However, the analytical results of this investigation are encouraging enough to undertake more systematic studies of the source rock potential of the Salina Group, Wills Creek Formation, and perhaps the Tonoloway Formation (Limestone) and McKenzie Limestone (or Member).
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