Digital flood-inundation maps for an 8.3-mile reach of the Wabash River and a 7.6-mile reach of the Eel River at Logansport, Indiana (Ind.), were created by the U.S. Geological Survey (USGS) in cooperation with the Indiana Office of Community and Rural Affairs. The 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 USGS streamgage Wabash River at Logansport, Ind. (sta. no. 03329000) and USGS streamgage Eel River near Logansport, Ind. (sta. no. 03328500). Current conditions for estimating near-real-time areas of inundation using USGS streamgage information may be obtained on the Internet at http://waterdata.usgs.gov/. In addition, information has been provided to the National Weather Service (NWS) for incorporation into their Advanced Hydrologic Prediction Service (AHPS) flood warning system http:/water.weather.gov/ahps/). The NWS forecasts flood hydrographs at many places that are often colocated with USGS streamgages. NWS-forecasted peak-stage information may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation.
\nFor this study, flood profiles were computed for the stream reaches by means of a one-dimensional step-backwater model developed by the U.S. Army Corps of Engineers. The hydraulic model was calibrated by using the most current stage-discharge relations at USGS streamgages 03329000, Wabash River at Logansport, Ind., and 03328500, Eel River near Logansport, Ind. The calibrated hydraulic model was then used to determine five water-surface profiles for flood stage at 1-foot intervals referenced to the Wabash River streamgage datum, and four water-surface profiles for flood stages at 1-foot intervals referenced to the Eel River streamgage datum. The stages range from bankfull to approximately the highest stages that have occurred since 1967 when three flood control dams were built upstream of Logansport, Ind. The simulated water-surface profiles were then combined with a geographic information system (GIS) digital elevation model (DEM, derived from Light Detection and Ranging [lidar] data having a 0.37-foot vertical accuracy and 3.9-foot horizontal resolution) in order to delineate the area flooded at each stage.
\nThe availability of these maps, along with information available on the Internet regarding current stages from the USGS streamgages at Logansport, Ind., and forecasted stream stages from the NWS, provides emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures, as well as for post flood recovery efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3293","issn":"2329-132X","collaboration":"Prepared in cooperation with the Indiana Office of Community and Rural Affairs","usgsCitation":"Fowler, K.K., 2014, Flood inundation maps for the Wabash and Eel Rivers at Logansport, Indiana: U.S. Geological Survey Scientific Investigations Map 3293, Pamphlet: v, 12 p.; Map Sheet Low Resolution: 9 JPGs; Map Sheet High Resolution: 9 PDFs, 22.00 x 17.00 inches; Downloads Directory, https://doi.org/10.3133/sim3293.","productDescription":"Pamphlet: v, 12 p.; Map Sheet Low Resolution: 9 JPGs; Map Sheet High Resolution: 9 PDFs, 22.00 x 17.00 inches; Downloads Directory","numberOfPages":"22","ipdsId":"IP-041227","costCenters":[{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":288319,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim3293.jpg"},{"id":288303,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3293/"},{"id":288310,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3293/pdf/sim3293_mapsheets/sheet02_eel_631_sim3293.pdf"},{"id":288311,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3293/pdf/sim3293_mapsheets/sheet03_wab_584_sim3293.pdf"},{"id":288307,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sim/3293/images/sim3293_mapsheets/"},{"id":288308,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sim/3293/pdf/sim3293_mapsheets/"},{"id":288309,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3293/pdf/sim3293_mapsheets/sheet01_wab_583_sim3293.pdf"},{"id":288312,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3293/pdf/sim3293_mapsheets/sheet04_eel_632_sim3293.pdf"},{"id":288313,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3293/pdf/sim3293_mapsheets/sheet05_wab_585_sim3293.pdf"},{"id":288314,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3293/pdf/sim3293_mapsheets/sheet06_wab_586_sim3292.pdf"},{"id":288315,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3293/pdf/sim3293_mapsheets/sheet07_eel_633_sim3293.pdf"},{"id":288316,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3293/pdf/sim3293_mapsheets/sheet08_wab_587_sim3292.pdf"},{"id":288317,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3293/pdf/sim3293_mapsheets/sheet09_eel_634_sim3293.pdf"},{"id":288318,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sim/3293/downloads"},{"id":288305,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3293/pdf/sim3293.pdf"}],"projection":"Transverse Mercator projection","datum":"North American Datum of 1983","country":"United States","state":"Indiana","city":"Logansport","otherGeospatial":"Eel River;Wabash River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -86.416667,40.733333 ], [ -86.416667,40.8 ], [ -86.266667,40.8 ], [ -86.266667,40.733333 ], [ -86.416667,40.733333 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53996c4ee4b0a59b26496933","contributors":{"authors":[{"text":"Fowler, Kathleen K. 0000-0002-0107-3848 kkfowler@usgs.gov","orcid":"https://orcid.org/0000-0002-0107-3848","contributorId":2439,"corporation":false,"usgs":true,"family":"Fowler","given":"Kathleen","email":"kkfowler@usgs.gov","middleInitial":"K.","affiliations":[{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true},{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":493082,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70158681,"text":"70158681 - 2014 - Multiseason occupancy models for correlated replicate surveys","interactions":[],"lastModifiedDate":"2015-10-05T13:19:20","indexId":"70158681","displayToPublicDate":"2014-06-11T10:30:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2717,"text":"Methods in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Multiseason occupancy models for correlated replicate surveys","docAbstract":"Occupancy surveys collecting data from adjacent (sometimes correlated) spatial replicates have become relatively popular for logistical reasons. Hines et al. (2010) presented one approach to modelling such data for single-season occupancy surveys. Here, we present a multiseason analogue of this model (with corresponding software) for inferences about occupancy dynamics. We include a new parameter to deal with the uncertainty associated with the first spatial replicate for both single-season and multiseason models. We use a case study, based on the brown-headed nuthatch, to assess the need for these models when analysing data from the North American Breeding Bird Survey (BBS), and we test various hypotheses about occupancy dynamics for this species in the south-eastern United States.
\nThe new model permits inference about local probabilities of extinction, colonization and occupancy for sampling conducted over multiple seasons. The model performs adequately, based on a small simulation study and on results of the case study analysis.
\nThe new model incorporating correlated replicates was strongly favoured by model selection for the BBS data for brown-headed nuthatch (Sitta pusilla). Latitude was found to be an important source of variation in local colonization and occupancy probabilities for brown-headed nuthatch, with both probabilities being higher near the centre of the species range, as opposed to more northern and southern areas.
\nWe recommend this new occupancy model for detection–nondetection studies that use potentially correlated replicates.
\nThis report presents information used to characterize the groundwater-flow system on the Kitsap Peninsula, and includes descriptions of the geology and hydrogeologic framework, groundwater recharge and discharge, groundwater levels and flow directions, seasonal groundwater-level fluctuations, interactions between aquifers and the surface‑water system, and a water budget. The Kitsap Peninsula is in the Puget Sound lowland of west-central Washington, is bounded by Puget Sound on the east and by Hood Canal on the west, and covers an area of about 575 square miles. The peninsula encompasses all of Kitsap County, the part of Mason County north of Hood Canal, and part of Pierce County west of Puget Sound. The peninsula is surrounded by saltwater and the hydrologic setting is similar to that of an island. The study area is underlain by a thick sequence of unconsolidated glacial and interglacial deposits that overlie sedimentary and volcanic bedrock units that crop out in the central part of the study area. Geologic units were grouped into 12 hydrogeologic units consisting of aquifers, confining units, and an underlying bedrock unit. A surficial hydrogeologic unit map was developed and used with well information from 2,116 drillers’ logs to construct 6 hydrogeologic sections and unit extent and thickness maps.
\nUnconsolidated aquifers typically consist of moderately to well-sorted alluvial and glacial outwash deposits of sand, gravel, and cobbles, with minor lenses of silt and clay. These units often are discontinuous or isolated bodies and are of highly variable thickness. Unconfined conditions occur in areas where aquifer units are at land surface; however, much of the study area is mantled by glacial till, and confined aquifer conditions are common. Groundwater in the unconsolidated aquifers generally flows radially off the peninsula in the direction of Puget Sound and Hood Canal. These generalized flow patterns likely are complicated by the presence of low-permeability confining units that separate discontinuous bodies of aquifer material and act as local groundwater-flow barriers.
\nGroundwater-level fluctuations observed during the monitoring period (2011–12) in wells completed in unconsolidated hydrogeologic units indicated seasonal variations ranging from 1 to about 20 feet. The largest fluctuation of 33 feet occurred in a well that was completed in the bedrock unit. Streamgage discharge measurements made during 2012 indicate that groundwater discharge to creeks in the area ranged from about 0.41 to 33.3 cubic feet per second.
\nDuring 2012, which was an above-average year of precipitation, the groundwater system received an average of about 664,610 acre-feet of recharge from precipitation and 22,122 acre-feet of recharge from return flows. Most of this annual recharge (66 percent) discharged to streams, and only about 4 percent was withdrawn from wells. The remaining groundwater recharge (30 percent) left the groundwater system as discharge to Hood Canal and Puget Sound.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145106","collaboration":"Prepared in cooperation with the Kitsap Public Utility District","usgsCitation":"Welch, W.B., Frans, L.M., and Olsen, T.D., 2014, Hydrogeologic framework, groundwater movement, and water budget of the Kitsap Peninsula, west-central Washington: U.S. Geological Survey Scientific Investigations Report 2014-5106, Report: vii, 44 p.; 2 Plates: 34.0 x 44.0 inches and 47.0 x 32.68 inches, https://doi.org/10.3133/sir20145106.","productDescription":"Report: vii, 44 p.; 2 Plates: 34.0 x 44.0 inches and 47.0 x 32.68 inches","numberOfPages":"56","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-055785","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":288260,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145106.jpg"},{"id":288223,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5106/"},{"id":288257,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5106/pdf/sir20145106.pdf"},{"id":288258,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2014/5106/pdf/sir20145106_plate01.pdf"},{"id":288259,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2014/5106/pdf/sir20145106_plate02.pdf"}],"projection":"State Plane Washington North FIPS 4601 Feet","datum":"North American Datum of 1983","country":"United States","state":"Washington","otherGeospatial":"Kitsap Peninsula","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -123.17018,47.233146 ], [ -123.17018,47.99093 ], [ -122.347281,47.99093 ], [ -122.347281,47.233146 ], [ -123.17018,47.233146 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53996c4fe4b0a59b26496937","contributors":{"authors":[{"text":"Welch, Wendy B. wwelch@usgs.gov","contributorId":1645,"corporation":false,"usgs":true,"family":"Welch","given":"Wendy","email":"wwelch@usgs.gov","middleInitial":"B.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":false,"id":494302,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Frans, Lonna M. 0000-0002-3217-1862 lmfrans@usgs.gov","orcid":"https://orcid.org/0000-0002-3217-1862","contributorId":1493,"corporation":false,"usgs":true,"family":"Frans","given":"Lonna","email":"lmfrans@usgs.gov","middleInitial":"M.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":494300,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Olsen, Theresa D. 0000-0003-4099-4057 tdolsen@usgs.gov","orcid":"https://orcid.org/0000-0003-4099-4057","contributorId":1644,"corporation":false,"usgs":true,"family":"Olsen","given":"Theresa","email":"tdolsen@usgs.gov","middleInitial":"D.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":494301,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70133710,"text":"70133710 - 2014 - Karst geomorphology and hydrology of the Shenandoah Valley near Harrisonburg, Virginia","interactions":[],"lastModifiedDate":"2017-06-05T15:11:16","indexId":"70133710","displayToPublicDate":"2014-06-11T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1724,"text":"GSA Field Guides","active":true,"publicationSubtype":{"id":10}},"title":"Karst geomorphology and hydrology of the Shenandoah Valley near Harrisonburg, Virginia","docAbstract":"The karst of the central Shenandoah Valley has characteristics of both shallow and deep phreatic formation. This field guide focuses on the region around Harrisonburg, Virginia, where a number of these karst features and their associated geologic context can be examined. Ancient, widespread alluvial deposits cover much of the carbonate bedrock on the western side of the valley, where shallow karstification has resulted in classical fluviokarst development. However, in upland exposures of carbonate rock, isolated caves exist atop hills not affected by surface processes other than exposure during denudation. The upland caves contain phreatic deposits of calcite and fine-grained sediments. They lack any evidence of having been invaded by surface streams. Recent geologic mapping and LIDAR (light detection and ranging) elevation data have enabled interpretive association between bedrock structure, igneous intrusions, silicification and brecciation of host carbonate bedrock, and the location of several caves and karst springs. Geochemistry, water quality, and water temperature data support the broad categorization of springs into those affected primarily by shallow near-surface recharge, and those sourced deeper in the karst aquifer. The deep-seated karst formation occurred in the distant past where subvertical fracture and fault zones intersect thrust faults and/or cross-strike faults, enabling upwelling of deep-circulating meteoric groundwater. Most caves formed in such settings have been overprinted by later circulation of shallow groundwater, thus removing evidence of the history of earliest inception; however, several caves do preserve evidence of an earlier formation.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/2014.0035(06)","usgsCitation":"Doctor, D.H., Orndorff, W., Maynard, J., Heller, M., and Casile, G.C., 2014, Karst geomorphology and hydrology of the Shenandoah Valley near Harrisonburg, Virginia: GSA Field Guides, v. 35, p. 161-213, https://doi.org/10.1130/2014.0035(06).","productDescription":"53 p.","startPage":"161","endPage":"213","ipdsId":"IP-053426","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":342121,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Virginia","otherGeospatial":"Shenandoah 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Daniel H. 0000-0002-8338-9722 dhdoctor@usgs.gov","orcid":"https://orcid.org/0000-0002-8338-9722","contributorId":2037,"corporation":false,"usgs":true,"family":"Doctor","given":"Daniel","email":"dhdoctor@usgs.gov","middleInitial":"H.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":525413,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Orndorff, Wil","contributorId":127487,"corporation":false,"usgs":false,"family":"Orndorff","given":"Wil","affiliations":[{"id":6970,"text":"Virginia Department of Conservation and Recreation, Natural Heritage Program","active":true,"usgs":false}],"preferred":false,"id":525414,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Maynard, Joel","contributorId":127488,"corporation":false,"usgs":false,"family":"Maynard","given":"Joel","email":"","affiliations":[{"id":6971,"text":"Virginia Department of Environmental Quality, Groundwater Characterization Program","active":true,"usgs":false}],"preferred":false,"id":525415,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Heller, Matthew J.","contributorId":81588,"corporation":false,"usgs":true,"family":"Heller","given":"Matthew J.","affiliations":[],"preferred":false,"id":525416,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Casile, Gerolamo C. jcasile@usgs.gov","contributorId":4007,"corporation":false,"usgs":true,"family":"Casile","given":"Gerolamo","email":"jcasile@usgs.gov","middleInitial":"C.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":525417,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70186902,"text":"70186902 - 2014 - Simulating future residential property losses from wildfire in Flathead County, Montana","interactions":[],"lastModifiedDate":"2022-12-09T17:09:48.008363","indexId":"70186902","displayToPublicDate":"2014-06-11T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"1","title":"Simulating future residential property losses from wildfire in Flathead County, Montana","docAbstract":"Wildfire damages to private residences in the United States and elsewhere have increased as a result of expansion of the wildland-urban interface (WUI) and other factors. Understanding this unwelcome trend requires analytical frameworks that simulate how various interacting social, economic, and biophysical factors influence those damages. A methodological framework is developed for simulating expected residential property losses from wildfire [E(RLW)], which is a probabilistic monetary measure of wildfire risk to residential properties in the WUI. E(RLW) is simulated for Flathead County, Montana for five, 10-year subperiods covering the period 2010-2059, under various assumptions about future climate change, economic growth, land use policy, and forest management. Results show statistically significant increases in the spatial extent of WUI properties, the number of residential structures at risk from wildfire, and E(RLW) over the 50-year evaluation period for both the county and smaller subareas (i.e., neighborhoods and parcels). The E(RLW) simulation framework presented here advances the field of wildfire risk assessment by providing a finer-scale tool that incorporates a set of dynamic, interacting processes. The framework can be applied using other scenarios for climate change, economic growth, land use policy, and forest management, and in other areas.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Advances in environmental research","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Nova Science Publishers","publisherLocation":"New York, NY","usgsCitation":"Prato, T., Paveglio, T.B., Barnett, Y., Silverstein, R., Hardy, M., Keane, R., Loehman, R.A., Clark, A., Fagre, D.B., Venn, T., and Stockmann, K., 2014, Simulating future residential property losses from wildfire in Flathead County, Montana, chap. 1 of Advances in environmental research, v. 33, p. 1-40.","productDescription":"40 p.","startPage":"1","endPage":"40","ipdsId":"IP-055862","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science 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hydrocarbons","interactions":[],"lastModifiedDate":"2014-06-10T16:22:29","indexId":"70112026","displayToPublicDate":"2014-06-10T16:18:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1759,"text":"Geochimica et Cosmochimica Acta","active":true,"publicationSubtype":{"id":10}},"title":"Compositional and stable carbon isotopic fractionation during non-autocatalytic thermochemical sulfate reduction by gaseous hydrocarbons","docAbstract":"The possibility of autocatalysis during thermochemical sulfate reduction (TSR) by gaseous hydrocarbons was investigated by examination of previously reported laboratory and field data. This reaction was found to be a kinetically controlled non-autocatalytic process, and the apparent lack of autocatalysis is thought to be due to the absence of the required intermediate species. Kinetic parameters for chemical and carbon isotopic fractionations of gaseous hydrocarbons affected by TSR were calculated and found to be consistent with experimentally derived values for TSR involving long-chain hydrocarbons. Model predictions based on these kinetic values indicate that TSR by gaseous hydrocarbon requires high-temperature conditions. The oxidation of C2–5 hydrocarbons by sulfate reduction is accompanied by carbon isotopic fractionation with the residual C2–5 hydrocarbons becoming more enriched in 13C. Kinetic parameters were calculated for the stable carbon isotopic fractionation of gaseous hydrocarbons that have experienced TSR. Model predictions based on these kinetics indicate that it may be difficult to distinguish the effects of TSR from those of thermal maturation at lower levels of hydrocarbon oxidation; however, unusually heavy δ13C2+ values (>−10‰) can be diagnostic of high levels of conversion (>50%). Stoichiometric and stable carbon isotopic data show that methane is stable under the investigated reaction conditions and is likely a product of TSR by other gaseous hydrocarbons rather than a significant reactant. These results indicate that the overall TSR reaction mechanism for oxidation of organic substrates containing long-chain hydrocarbons involves three distinct phases as follows: (1) an initial slow and non-autocatalytic stage characterized by the reduction of reactive sulfate by long-chain saturated hydrocarbons; (2) a second autocatalytic reaction phase dominated by reactions involving reduced sulfur species and partially oxidized hydrocarbons; (3) and a final, or late-stage, TSR reaction in which hydrocarbon oxidation continues at a slower rate via the non-autocatalytic reduction of sulfate by gaseous hydrocarbons.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Geochimica et Cosmochimica Acta","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.gca.2014.05.004","usgsCitation":"Xia, X., Ellis, G.S., Ma, Q., and Tang, Y., 2014, Compositional and stable carbon isotopic fractionation during non-autocatalytic thermochemical sulfate reduction by gaseous hydrocarbons: Geochimica et Cosmochimica Acta, v. 139, p. 472-486, https://doi.org/10.1016/j.gca.2014.05.004.","productDescription":"15 p.","startPage":"472","endPage":"486","numberOfPages":"15","ipdsId":"IP-051961","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":288222,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":288221,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.gca.2014.05.004"}],"volume":"139","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53981ad1e4b09e5ae91f9d9a","contributors":{"authors":[{"text":"Xia, Xinyu","contributorId":54494,"corporation":false,"usgs":true,"family":"Xia","given":"Xinyu","email":"","affiliations":[],"preferred":false,"id":494558,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":494556,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ma, Qisheng","contributorId":35219,"corporation":false,"usgs":true,"family":"Ma","given":"Qisheng","email":"","affiliations":[],"preferred":false,"id":494557,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tang, Yongchun","contributorId":103166,"corporation":false,"usgs":true,"family":"Tang","given":"Yongchun","affiliations":[],"preferred":false,"id":494559,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70106988,"text":"sir20145098 - 2014 - Completion summary for boreholes USGS 140 and USGS 141 near the Advanced Test Reactor Complex, Idaho National Laboratory, Idaho","interactions":[],"lastModifiedDate":"2014-06-10T15:30:36","indexId":"sir20145098","displayToPublicDate":"2014-06-10T15:16:00","publicationYear":"2014","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":"2014-5098","title":"Completion summary for boreholes USGS 140 and USGS 141 near the Advanced Test Reactor Complex, Idaho National Laboratory, Idaho","docAbstract":"In 2013, the U.S. Geological Survey, in cooperation with the U.S. Department of Energy, drilled and constructed boreholes USGS 140 and USGS 141 for stratigraphic framework analyses and long-term groundwater monitoring of the eastern Snake River Plain aquifer at the Idaho National Laboratory in southeast Idaho. Borehole USGS 140 initially was cored to collect continuous geologic data, and then re-drilled to complete construction as a monitor well. Borehole USGS 141 was drilled and constructed as a monitor well without coring. Boreholes USGS 140 and USGS 141 are separated by about 375 feet (ft) and have similar geologic layers and hydrologic characteristics based on geophysical and aquifer test data collected. The final construction for boreholes USGS 140 and USGS 141 required 6-inch (in.) diameter carbon-steel well casing and 5-in. diameter stainless-steel well screen; the screened monitoring interval was completed about 50 ft into the eastern Snake River Plain aquifer, between 496 and 546 ft below land surface (BLS) at both sites. Following construction and data collection, dedicated pumps and water-level access lines were placed to allow for aquifer testing, for collecting periodic water samples, and for measuring water levels.
\nBorehole USGS 140 was cored continuously, starting from land surface to a depth of 543 ft BLS. Excluding surface sediment, recovery of basalt and sediment core at borehole USGS 140 was about 98 and 65 percent, respectively. Based on visual inspection of core and geophysical data, about 32 basalt flows and 4 sediment layers were collected from borehole USGS 140 between 34 and 543 ft BLS. Basalt texture for borehole USGS 140 generally was described as aphanitic, phaneritic, and porphyritic; rubble zones and flow mold structure also were described in recovered core material. Sediment layers, starting near 163 ft BLS, generally were composed of fine-grained sand and silt with a lesser amount of clay; however, between 223 and 228 ft BLS, silt with gravel was described. Basalt flows generally ranged in thickness from 3 to 76 ft (average of 14 ft) and varied from highly fractured to dense with high to low vesiculation.
\nGeophysical and borehole video logs were collected during certain stages of the drilling and construction process at boreholes USGS 140 and USGS 141. Geophysical logs were examined synergistically with the core material for borehole USGS 140; additionally, geophysical data were examined to confirm geologic and hydrologic similarities between boreholes USGS 140 and USGS 141 because core was not collected for borehole USGS 141. Geophysical data suggest the occurrence of fractured and (or) vesiculated basalt, dense basalt, and sediment layering in both the saturated and unsaturated zones in borehole USGS 141. Omni-directional density measurements were used to assess the completeness of the grout annular seal behind 6-in. diameter well casing. Furthermore, gyroscopic deviation measurements were used to measure horizontal and vertical displacement at all depths in boreholes USGS 140 and USGS 141.
\nSingle-well aquifer tests were done following construction at wells USGS 140 and USGS 141 and data examined after the tests were used to provide estimates of specific-capacity, transmissivity, and hydraulic conductivity. The specific capacity, transmissivity, and hydraulic conductivity for well USGS 140 were estimated at 2,370 gallons per minute per foot [(gal/min)/ft)], 4.06 × 105 feet squared per day (ft2/d), and 740 feet per day (ft/d), respectively. The specific capacity, transmissivity, and hydraulic conductivity for well USGS 141 were estimated at 470 (gal/min)/ft, 5.95 × 104 ft2/d, and 110 ft/d, respectively. Measured flow rates remained relatively constant in well USGS 140 with averages of 23.9 and 23.7 gal/min during the first and second aquifer tests, respectively, and in well USGS 141 with an average of 23.4 gal/min.
\nWater samples were analyzed for cations, anions, metals, nutrients, volatile organic compounds, stable isotopes, and radionuclides. Water samples from both wells indicated that concentrations of tritium, sulfate, and chromium were affected by wastewater disposal practices at the Advanced Test Reactor Complex. Most constituents in water from wells USGS 140 and USGS 141 had concentrations similar to concentrations in well USGS 136, which is upgradient from wells USGS 140 and USGS 141.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145098","collaboration":"DOE/ID-22229. Prepared in cooperation with the U.S. Department of Energy","usgsCitation":"Twining, B.V., Bartholomay, R.C., and Hodges, M., 2014, Completion summary for boreholes USGS 140 and USGS 141 near the Advanced Test Reactor Complex, Idaho National Laboratory, Idaho: U.S. Geological Survey Scientific Investigations Report 2014-5098, Report: vii, 39 p.; Appendixes A-C, https://doi.org/10.3133/sir20145098.","productDescription":"Report: vii, 39 p.; Appendixes A-C","numberOfPages":"52","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-051163","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":288220,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145098.jpg"},{"id":288216,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5098/pdf/sir20145098.pdf"},{"id":288217,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5098/pdf/sir20145098_AppendixA.pdf"},{"id":288218,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5098/pdf/sir20145098_AppendixB.pdf"},{"id":288219,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5098/pdf/sir20145098_AppendixC.pdf"},{"id":288215,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5098/"}],"projection":"Universal Transverse Mercator projection, Zone 12","datum":"North American Datum of 1927","country":"United States","state":"Idaho","otherGeospatial":"Snake River Plain","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -113.4019,43.2995 ], [ -113.4019,44.0971 ], [ -112.347,44.0971 ], [ -112.347,43.2995 ], [ -113.4019,43.2995 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53981ad0e4b09e5ae91f9d96","contributors":{"authors":[{"text":"Twining, Brian V. 0000-0003-1321-4721 btwining@usgs.gov","orcid":"https://orcid.org/0000-0003-1321-4721","contributorId":2387,"corporation":false,"usgs":true,"family":"Twining","given":"Brian","email":"btwining@usgs.gov","middleInitial":"V.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":493830,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bartholomay, Roy C. 0000-0002-4809-9287 rcbarth@usgs.gov","orcid":"https://orcid.org/0000-0002-4809-9287","contributorId":1131,"corporation":false,"usgs":true,"family":"Bartholomay","given":"Roy","email":"rcbarth@usgs.gov","middleInitial":"C.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":493829,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hodges, Mary K.V.","contributorId":66848,"corporation":false,"usgs":true,"family":"Hodges","given":"Mary K.V.","affiliations":[],"preferred":false,"id":493831,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70110751,"text":"ofr20141107 - 2014 - National Land Imaging Requirements (NLIR) Pilot Project summary report: Summary of moderate resolution imaging user requirements","interactions":[],"lastModifiedDate":"2020-06-05T12:08:01.026438","indexId":"ofr20141107","displayToPublicDate":"2014-06-10T14:58:00","publicationYear":"2014","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":"2014-1107","title":"National Land Imaging Requirements (NLIR) Pilot Project summary report: Summary of moderate resolution imaging user requirements","docAbstract":"Under the National Land Imaging Requirements (NLIR) Project, the U.S. Geological Survey (USGS) is developing a functional capability to obtain, characterize, manage, maintain and prioritize all Earth observing (EO) land remote sensing user requirements. The goal is a better understanding of community needs that can be supported with land remote sensing resources, and a means to match needs with appropriate solutions in an effective and efficient way.
The NLIR Project is composed of two components. The first component is focused on the development of the Earth Observation Requirements Evaluation System (EORES) to capture, store and analyze user requirements, whereas, the second component is the mechanism and processes to elicit and document the user requirements that will populate the EORES.
To develop the second component, the requirements elicitation methodology was exercised and refined through a pilot project conducted from June to September 2013. The pilot project focused specifically on applications and user requirements for moderate resolution imagery (5–120 meter resolution) as the test case for requirements development.
The purpose of this summary report is to provide a high-level overview of the requirements elicitation process that was exercised through the pilot project and an early analysis of the moderate resolution imaging user requirements acquired to date to support ongoing USGS sustainable land imaging study needs.
The pilot project engaged a limited set of Federal Government users from the operational and research communities and therefore the information captured represents only a subset of all land imaging user requirements. However, based on a comparison of results, trends, and analysis, the pilot captured a strong baseline of typical applications areas and user needs for moderate resolution imagery.
Because these results are preliminary and represent only a sample of users and application areas, the information from this report should only be used to indicate general user needs for the applications covered. Users of the information are cautioned that use of specific numeric results may be inappropriate without additional research. Any information used or cited from this report should specifically be cited as preliminary findings.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141107","usgsCitation":"Vadnais, C., and Stensaas, G.L., 2014, National Land Imaging Requirements (NLIR) Pilot Project summary report: Summary of moderate resolution imaging user requirements: U.S. Geological Survey Open-File Report 2014-1107, vi, 46 p., https://doi.org/10.3133/ofr20141107.","productDescription":"vi, 46 p.","numberOfPages":"52","onlineOnly":"Y","ipdsId":"IP-054641","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":288212,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1107/","linkFileType":{"id":5,"text":"html"}},{"id":288213,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1107/pdf/ofr2014-1107.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":375352,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2014/1107/images/coverthb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53981ad5e4b09e5ae91f9dae","contributors":{"authors":[{"text":"Vadnais, Carolyn","contributorId":21069,"corporation":false,"usgs":true,"family":"Vadnais","given":"Carolyn","affiliations":[],"preferred":false,"id":494140,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stensaas, Gregory L. 0000-0001-6679-2416 stensaas@usgs.gov","orcid":"https://orcid.org/0000-0001-6679-2416","contributorId":2551,"corporation":false,"usgs":true,"family":"Stensaas","given":"Gregory","email":"stensaas@usgs.gov","middleInitial":"L.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":494141,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70115106,"text":"70115106 - 2014 - Chesapeake Bay hypoxic volume forecasts and results: June 10, 2014","interactions":[],"lastModifiedDate":"2023-02-13T18:33:59.403058","indexId":"70115106","displayToPublicDate":"2014-06-10T13:14:01","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":3,"text":"Organization Series"},"title":"Chesapeake Bay hypoxic volume forecasts and results: June 10, 2014","docAbstract":"The 2014 Forecast - Given the average Jan-May 2014 total nitrogen load of 200,165 kg/day, this summer’s hypoxia volume forecast is 8.2 km3, slightly larger than average size for the period of record and the observed size last year.
","language":"English","publisher":"University of Michigan","publisherLocation":"Ann Arbor, MI","usgsCitation":"Scavia, D., and Evans, M.A., 2014, Chesapeake Bay hypoxic volume forecasts and results: June 10, 2014, 7 p.","productDescription":"7 p.","numberOfPages":"7","ipdsId":"IP-057486","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":289432,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Chesapeake Bay","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -76.4633,36.9078 ], [ -76.4633,37.9656 ], [ -75.6353,37.9656 ], [ -75.6353,36.9078 ], [ -76.4633,36.9078 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53b67b6ce4b014fc094d545e","contributors":{"authors":[{"text":"Scavia, Donald","contributorId":19068,"corporation":false,"usgs":true,"family":"Scavia","given":"Donald","affiliations":[],"preferred":false,"id":495546,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Evans, Mary Anne 0000-0002-1627-7210 maevans@usgs.gov","orcid":"https://orcid.org/0000-0002-1627-7210","contributorId":4883,"corporation":false,"usgs":true,"family":"Evans","given":"Mary","email":"maevans@usgs.gov","middleInitial":"Anne","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":495545,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70111271,"text":"sir20145075 - 2014 - Land subsidence, groundwater levels, and geology in the Coachella Valley, California, 1993-2010","interactions":[],"lastModifiedDate":"2014-06-10T11:17:22","indexId":"sir20145075","displayToPublicDate":"2014-06-10T11:02:00","publicationYear":"2014","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":"2014-5075","title":"Land subsidence, groundwater levels, and geology in the Coachella Valley, California, 1993-2010","docAbstract":"Land subsidence associated with groundwater-level declines has been investigated by the U.S. Geological Survey in the Coachella Valley, California, since 1996. Groundwater has been a major source of agricultural, municipal, and domestic supply in the valley since the early 1920s. Pumping of groundwater resulted in water-level declines as much as 15 meters (50 feet) through the late 1940s. In 1949, the importation of Colorado River water to the southern Coachella Valley began, resulting in a reduction in groundwater pumping and a recovery of water levels during the 1950s through the 1970s. Since the late 1970s, demand for water in the valley has exceeded deliveries of imported surface water, resulting in increased pumping and associated groundwater-level declines and, consequently, an increase in the potential for land subsidence caused by aquifer-system compaction.
\nGlobal Positioning System (GPS) surveying and Interferometric Synthetic Aperture Radar (InSAR) methods were used to determine the location, extent, and magnitude of the vertical land-surface changes in the southern Coachella Valley during 1993–2010. The GPS measurements taken at 11 geodetic monuments in 1996 and in 2010 in the southern Coachella Valley indicated that the elevation of the land surface changed –136 to –23 millimeters (mm) ±54 mm (–0.45 to –0.08 feet (ft) ±0.18 ft) during the 14-year period. Changes at 6 of the 11 monuments exceeded the maximum expected uncertainty of ±54 mm (±0.18 ft) at the 95-percent confidence level, indicating that subsidence occurred at these monuments between June 1996 and August 2010. GPS measurements taken at 17 geodetic monuments in 2005 and 2010 indicated that the elevation of the land surface changed –256 to +16 mm ±28 mm (–0.84 to +0.05 ft ±0.09 ft) during the 5-year period. Changes at 5 of the 17 monuments exceeded the maximum expected uncertainty of ±28 mm (±0.09 ft) at the 95-percent confidence level, indicating that subsidence occurred at these monuments between August 2005 and August 2010. At each of these five monuments, subsidence rates were about the same between 2005 and 2010 as between 2000 and 2005.
\nInSAR measurements taken between June 27, 1995, and September 19, 2010, indicated that the land surface subsided from about 220 to 600 mm (0.72 to 1.97 ft) in three areas of the Coachella Valley: near Palm Desert, Indian Wells, and La Quinta. In Palm Desert, the average subsidence rates increased from about 39 millimeters per year (mm/yr), or 0.13 foot per year (ft/yr), during 1995–2000 to about 45 mm/yr (0.15 ft/yr) during 2003–10. In Indian Wells, average subsidence rates for two subsidence maxima were fairly steady at about 34 and 26 mm/yr (0.11 and 0.09 ft/yr) during both periods; for the third maxima, average subsidence rates increased from about 14 to 19 mm/yr (0.05 to 0.06 ft/yr) from the first to the second period. In La Quinta, average subsidence rates for five selected locations ranged from about 17 to 37 mm/yr (0.06 to 0.12 ft/yr) during 1995–2000; three of the locations had similar rates during 2003–mid-2009, while the other two locations had increased subsidence rates. Decreased subsidence rates were calculated throughout the La Quinta subsidence area during mid-2009–10, however, and uplift was observed during 2010 near the southern extent of this area.
\nWater-level measurements taken at wells near the subsiding monuments and in the three subsiding areas shown by InSAR generally indicated that the water levels fluctuated seasonally and declined annually from the early 1990s, or earlier, to 2010; some water levels in 2010 were at the lowest levels in their recorded histories. An exception to annually declining water levels in and near subsiding areas was observed beginning in mid-2009 in the La Quinta subsidence area, where recovering water levels coincided with increased recharge operations at the Thomas E. Levy Recharge Facility; decreased pumpage also could cause groundwater levels to recover. Subsidence concomitant with declining water levels and land-surface uplift concomitant with recovering water levels indicate that aquifer-system compaction could be causing subsidence. If the stresses imposed by the historically lowest water levels exceeded the preconsolidation stress, the aquifer-system compaction and associated land subsidence could be permanent.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145075","collaboration":"Prepared in cooperation with the Coachella Valley Water District","usgsCitation":"Sneed, M., Brandt, J.T., and Solt, M., 2014, Land subsidence, groundwater levels, and geology in the Coachella Valley, California, 1993-2010: U.S. Geological Survey Scientific Investigations Report 2014-5075, viii, 62 p., https://doi.org/10.3133/sir20145075.","productDescription":"viii, 62 p.","numberOfPages":"75","onlineOnly":"Y","ipdsId":"IP-043650","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":288211,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145075.jpg"},{"id":288210,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5075/pdf/sir2014-5075.pdf"},{"id":288209,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5075"}],"datum":"North American Datum 1927","country":"United States","state":"California","otherGeospatial":"Coachella Valley","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -117.2406,32.9971 ], [ -117.2406,34.1959 ], [ -115.4443,34.1959 ], [ -115.4443,32.9971 ], [ -117.2406,32.9971 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53981ad2e4b09e5ae91f9d9e","contributors":{"authors":[{"text":"Sneed, Michelle 0000-0002-8180-382X micsneed@usgs.gov","orcid":"https://orcid.org/0000-0002-8180-382X","contributorId":155,"corporation":false,"usgs":true,"family":"Sneed","given":"Michelle","email":"micsneed@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":494317,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brandt, Justin T. 0000-0002-9397-6824","orcid":"https://orcid.org/0000-0002-9397-6824","contributorId":28326,"corporation":false,"usgs":true,"family":"Brandt","given":"Justin","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":494318,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Solt, Mike","contributorId":88258,"corporation":false,"usgs":true,"family":"Solt","given":"Mike","email":"","affiliations":[],"preferred":false,"id":494319,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70111960,"text":"70111960 - 2014 - Reducing fatigue damage for ships in transit through structured decision making","interactions":[],"lastModifiedDate":"2014-06-10T10:43:53","indexId":"70111960","displayToPublicDate":"2014-06-10T10:32:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2677,"text":"Marine Structures","active":true,"publicationSubtype":{"id":10}},"title":"Reducing fatigue damage for ships in transit through structured decision making","docAbstract":"Research in structural monitoring has focused primarily on drawing inference about the health of a structure from the structure’s response to ambient or applied excitation. Knowledge of the current state can then be used to predict structural integrity at a future time and, in principle, allows one to take action to improve safety, minimize ownership costs, and/or increase the operating envelope. While much time and effort has been devoted toward data collection and system identification, research to-date has largely avoided the question of how to choose an optimal maintenance plan. This work describes a structured decision making (SDM) process for taking available information (loading data, model output, etc.) and producing a plan of action for maintaining the structure. SDM allows the practitioner to specify his/her objectives and then solves for the decision that is optimal in the sense that it maximizes those objectives. To demonstrate, we consider the problem of a Naval vessel transiting a fixed distance in varying sea-state conditions. The physics of this problem are such that minimizing transit time increases the probability of fatigue failure in the structural supports. It is shown how SDM produces the optimal trip plan in the sense that it minimizes both transit time and probability of failure in the manner of our choosing (i.e., through a user-defined cost function). The example illustrates the benefit of SDM over heuristic approaches to maintaining the vessel.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Marine Structures","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.marstruc.2014.04.002","usgsCitation":"Nichols, J., Fackler, P., Pacifici, K., Murphy, K., and Nichols, J., 2014, Reducing fatigue damage for ships in transit through structured decision making: Marine Structures, v. 38, p. 18-43, https://doi.org/10.1016/j.marstruc.2014.04.002.","productDescription":"26 p.","startPage":"18","endPage":"43","numberOfPages":"26","ipdsId":"IP-054791","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":288208,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":288207,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.marstruc.2014.04.002"}],"volume":"38","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53981ad5e4b09e5ae91f9db6","contributors":{"authors":[{"text":"Nichols, J.M.","contributorId":18080,"corporation":false,"usgs":true,"family":"Nichols","given":"J.M.","email":"","affiliations":[],"preferred":false,"id":494550,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fackler, P.L.","contributorId":30859,"corporation":false,"usgs":true,"family":"Fackler","given":"P.L.","email":"","affiliations":[],"preferred":false,"id":494551,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pacifici, K.","contributorId":71667,"corporation":false,"usgs":true,"family":"Pacifici","given":"K.","email":"","affiliations":[],"preferred":false,"id":494553,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Murphy, K.D.","contributorId":50004,"corporation":false,"usgs":true,"family":"Murphy","given":"K.D.","email":"","affiliations":[],"preferred":false,"id":494552,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nichols, J.D. 0000-0002-7631-2890","orcid":"https://orcid.org/0000-0002-7631-2890","contributorId":14332,"corporation":false,"usgs":true,"family":"Nichols","given":"J.D.","affiliations":[],"preferred":false,"id":494549,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70111909,"text":"70111909 - 2014 - Pluvial lakes in the Great Basin of the western United States: a view from the outcrop","interactions":[],"lastModifiedDate":"2014-06-10T10:01:04","indexId":"70111909","displayToPublicDate":"2014-06-10T09:53:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3219,"text":"Quaternary Science Reviews","active":true,"publicationSubtype":{"id":10}},"title":"Pluvial lakes in the Great Basin of the western United States: a view from the outcrop","docAbstract":"Paleo-lakes in the western United States provide geomorphic and hydrologic records of climate and drainage-basin change at multiple time scales extending back to the Miocene. Recent reviews and studies of paleo-lake records have focused on interpretations of proxies in lake sediment cores from the northern and central parts of the Great Basin. In this review, emphasis is placed on equally important studies of lake history during the past ∼30 years that were derived from outcrop exposures and geomorphology, in some cases combined with cores. Outcrop and core records have different strengths and weaknesses that must be recognized and exploited in the interpretation of paleohydrology and paleoclimate. Outcrops and landforms can yield direct evidence of lake level, facies changes that record details of lake-level fluctuations, and geologic events such as catastrophic floods, drainage-basin changes, and isostatic rebound. Cores can potentially yield continuous records when sampled in stable parts of lake basins and can provide proxies for changes in lake level, water temperature and chemistry, and ecological conditions in the surrounding landscape. However, proxies such as stable isotopes may be influenced by several competing factors the relative effects of which may be difficult to assess, and interpretations may be confounded by geologic events within the drainage basin that were unrecorded or not recognized in a core. The best evidence for documenting absolute lake-level changes lies within the shore, nearshore, and deltaic sediments that were deposited across piedmonts and at the mouths of streams as lake level rose and fell. We review the different shorezone environments and resulting deposits used in such reconstructions and discuss potential estimation errors.
\nLake-level studies based on deposits and landforms have provided paleohydrologic records ranging from general changes during the past million years to centennial-scale details of fluctuations during the late Pleistocene and Holocene. Outcrop studies have documented the integration histories of several important drainage basins, including the Humboldt, Amargosa, Owens, and Mojave river systems, that have evolved since the Miocene within the active tectonic setting of the Great Basin; these histories have influenced lake levels in terminal basins. Many pre-late Pleistocene lakes in the western Great Basin were significantly larger and record wetter conditions than the youngest lakes. Outcrop-based lake-level data provide important checks on core-based proxy interpretations; we discuss four such comparisons. In some cases, such as for Lakes Owens and Manix, outcrop and core data synthesis yields stronger and more complete records; in other cases, such as for Bonneville and Lahontan, conflicts point toward reconsideration of confounding factors in interpretation of core-based proxies.
","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Quaternary Science Reviews","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.quascirev.2014.04.012","usgsCitation":"Reheis, M., Adams, K., Oviatt, C., and Bacon, S.N., 2014, Pluvial lakes in the Great Basin of the western United States: a view from the outcrop: Quaternary Science Reviews, v. 97, p. 33-57, https://doi.org/10.1016/j.quascirev.2014.04.012.","productDescription":"25 p.","startPage":"33","endPage":"57","numberOfPages":"25","ipdsId":"IP-044438","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":288206,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":288205,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.quascirev.2014.04.012"}],"country":"United States","otherGeospatial":"Great Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -121.38,32.36 ], [ -121.38,44.81 ], [ -110.35,44.81 ], [ -110.35,32.36 ], [ -121.38,32.36 ] ] ] } } ] }","volume":"97","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53981ad5e4b09e5ae91f9db2","contributors":{"authors":[{"text":"Reheis, Marith C. 0000-0002-8359-323X","orcid":"https://orcid.org/0000-0002-8359-323X","contributorId":101244,"corporation":false,"usgs":true,"family":"Reheis","given":"Marith C.","affiliations":[],"preferred":false,"id":494540,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Adams, Kenneth D.","contributorId":75586,"corporation":false,"usgs":true,"family":"Adams","given":"Kenneth D.","affiliations":[],"preferred":false,"id":494538,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Oviatt, Charles G.","contributorId":13503,"corporation":false,"usgs":true,"family":"Oviatt","given":"Charles G.","affiliations":[],"preferred":false,"id":494537,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bacon, Steven N.","contributorId":93391,"corporation":false,"usgs":true,"family":"Bacon","given":"Steven","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":494539,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70111934,"text":"70111934 - 2014 - Modeling Hawaiian ecosystem degradation due to invasive plants under current and future climates","interactions":[],"lastModifiedDate":"2014-06-10T09:37:24","indexId":"70111934","displayToPublicDate":"2014-06-10T09:14:00","publicationYear":"2014","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":"Modeling Hawaiian ecosystem degradation due to invasive plants under current and future climates","docAbstract":"Occupation of native ecosystems by invasive plant species alters their structure and/or function. In Hawaii, a subset of introduced plants is regarded as extremely harmful due to competitive ability, ecosystem modification, and biogeochemical habitat degradation. By controlling this subset of highly invasive ecosystem modifiers, conservation managers could significantly reduce native ecosystem degradation. To assess the invasibility of vulnerable native ecosystems, we selected a proxy subset of these invasive plants and developed robust ensemble species distribution models to define their respective potential distributions. The combinations of all species models using both binary and continuous habitat suitability projections resulted in estimates of species richness and diversity that were subsequently used to define an invasibility metric. The invasibility metric was defined from species distribution models with <0.7 niche overlap (Warrens I) and relatively discriminative distributions (Area Under the Curve >0.8; True Skill Statistic >0.75) as evaluated per species. Invasibility was further projected onto a 2100 Hawaii regional climate change scenario to assess the change in potential habitat degradation. The distribution defined by the invasibility metric delineates areas of known and potential invasibility under current climate conditions and, when projected into the future, estimates potential reductions in native ecosystem extent due to climate-driven invasive incursion. We have provided the code used to develop these metrics to facilitate their wider use (Code S1). This work will help determine the vulnerability of native-dominated ecosystems to the combined threats of climate change and invasive species, and thus help prioritize ecosystem and species management actions.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"PLoS ONE","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Public Library of Science","publisherLocation":"San Francisco, CA","doi":"10.1371/journal.pone.0095427","usgsCitation":"Vorsino, A.E., Fortini, L., Amidon, F.A., Miller, S.E., Jacobi, J.D., Price, J.P., `Ohukani`ohi`a Gon, S., and Koob, G.A., 2014, Modeling Hawaiian ecosystem degradation due to invasive plants under current and future climates: PLoS ONE, v. 9, no. 5, 18 p., https://doi.org/10.1371/journal.pone.0095427.","productDescription":"18 p.","numberOfPages":"18","ipdsId":"IP-054741","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":472944,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0095427","text":"Publisher Index Page"},{"id":288204,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":288198,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1371/journal.pone.0095427"}],"country":"United States","state":"Hawai'i","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -159.9917,18.7288 ], [ -159.9917,22.4876 ], [ -154.4937,22.4876 ], [ -154.4937,18.7288 ], [ -159.9917,18.7288 ] ] ] } } ] }","volume":"9","issue":"5","noUsgsAuthors":false,"publicationDate":"2014-05-07","publicationStatus":"PW","scienceBaseUri":"53981ad4e4b09e5ae91f9daa","contributors":{"authors":[{"text":"Vorsino, Adam E.","contributorId":71102,"corporation":false,"usgs":true,"family":"Vorsino","given":"Adam","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":494547,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fortini, Lucas B.","contributorId":10693,"corporation":false,"usgs":true,"family":"Fortini","given":"Lucas B.","affiliations":[],"preferred":false,"id":494543,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Amidon, Fred A.","contributorId":107200,"corporation":false,"usgs":true,"family":"Amidon","given":"Fred","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":494548,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miller, Stephen E.","contributorId":31683,"corporation":false,"usgs":true,"family":"Miller","given":"Stephen","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":494544,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jacobi, James D. 0000-0003-2313-7862 jjacobi@usgs.gov","orcid":"https://orcid.org/0000-0003-2313-7862","contributorId":3705,"corporation":false,"usgs":true,"family":"Jacobi","given":"James","email":"jjacobi@usgs.gov","middleInitial":"D.","affiliations":[{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true},{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":494541,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Price, Jonathan P.","contributorId":8736,"corporation":false,"usgs":true,"family":"Price","given":"Jonathan","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":494542,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"`Ohukani`ohi`a Gon, Sam III","contributorId":60961,"corporation":false,"usgs":true,"family":"`Ohukani`ohi`a Gon","given":"Sam","suffix":"III","email":"","affiliations":[],"preferred":false,"id":494545,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Koob, Gregory A.","contributorId":61752,"corporation":false,"usgs":true,"family":"Koob","given":"Gregory","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":494546,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70111837,"text":"70111837 - 2014 - Methodological developments in US state-level Genuine Progress Indicators: toward GPI 2.0","interactions":[],"lastModifiedDate":"2014-06-10T08:46:22","indexId":"70111837","displayToPublicDate":"2014-06-10T08:35:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Methodological developments in US state-level Genuine Progress Indicators: toward GPI 2.0","docAbstract":"The Genuine Progress Indicator (GPI) has emerged as an important monetary measure of economic well-being. Unlike mainstream economic indicators, primarily Gross Domestic Product (GDP), the GPI accounts for both the benefits and costs of economic production across diverse economic, social, and environmental domains in a more comprehensive manner. Recently, the GPI has gained traction in subnational policy in the United States, with GPI studies being conducted in a number of states and with their formal adoption by several state governments. As the GPI is applied in different locations, new methods are developed, different data sources are available, and new issues of policy relevance are addressed using its component indicators. This has led to a divergence in methods, reducing comparability between studies and yielding results that are of varying methodological sophistication. In this study, we review the “state of the art” in recent US state-level GPI studies, focusing on those from Hawaii, Maryland, Ohio, Utah, and Vermont. Through adoption of a consistent approach, these and future GPI studies could utilize a framework that supports more uniform, comparable, and accurate measurements of progress. We also identify longer-term issues, particularly related to treatment of nonrenewable resource depletion, government spending, income inequality, and ecosystem services. As these issues are successfully addressed and disseminated, a “GPI 2.0” will emerge that better measures economic well-being and has greater accuracy and policy relevance than past GPI measurements. As the GPI expands further into mainstream policy analysis, a more formal process by which methods could be updated, standardized, and applied is needed.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ecological Indicators","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2014.05.005","usgsCitation":"Bagstad, K.J., Berik, G., and Gaddis, E.J., 2014, Methodological developments in US state-level Genuine Progress Indicators: toward GPI 2.0: Ecological Indicators, v. 45, p. 474-485, https://doi.org/10.1016/j.ecolind.2014.05.005.","productDescription":"12 p.","startPage":"474","endPage":"485","numberOfPages":"12","ipdsId":"IP-053091","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":288203,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":288202,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.ecolind.2014.05.005"}],"country":"United States","state":"Hawai'i;Maryl;Ohio;Utah;Vermont","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 144.616667,13.233333 ], [ 144.616667,71.833333 ], [ -64.566667,71.833333 ], [ -64.566667,13.233333 ], [ 144.616667,13.233333 ] ] ] } } ] }","volume":"45","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53981ad3e4b09e5ae91f9da6","contributors":{"authors":[{"text":"Bagstad, Kenneth J. 0000-0001-8857-5615 kjbagstad@usgs.gov","orcid":"https://orcid.org/0000-0001-8857-5615","contributorId":3680,"corporation":false,"usgs":true,"family":"Bagstad","given":"Kenneth","email":"kjbagstad@usgs.gov","middleInitial":"J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":494476,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Berik, Gunseli","contributorId":32829,"corporation":false,"usgs":true,"family":"Berik","given":"Gunseli","email":"","affiliations":[],"preferred":false,"id":494477,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gaddis, Erica J. Brown","contributorId":41345,"corporation":false,"usgs":true,"family":"Gaddis","given":"Erica","email":"","middleInitial":"J. Brown","affiliations":[],"preferred":false,"id":494478,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70107013,"text":"ofr20141089 - 2014 - Landscape consequences of natural gas extraction in Bedford, Blair, Cambria, Centre, Clearfield, Clinton, Columbia, Huntingdon, and Luzerne counties, Pennsylvania, 2004-2010","interactions":[],"lastModifiedDate":"2016-08-19T18:23:48","indexId":"ofr20141089","displayToPublicDate":"2014-06-10T08:00:00","publicationYear":"2014","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":"2014-1089","title":"Landscape consequences of natural gas extraction in Bedford, Blair, Cambria, Centre, Clearfield, Clinton, Columbia, Huntingdon, and Luzerne counties, Pennsylvania, 2004-2010","docAbstract":"Increased demands for cleaner burning energy, coupled with the relatively recent technological advances in accessing unconventional hydrocarbon-rich geologic formations, have led to an intense effort to find and extract natural gas from various underground sources around the country. One of these sources, the Marcellus Shale, located in the Allegheny Plateau, is currently undergoing extensive drilling and production. The technology used to extract gas in the Marcellus Shale is known as hydraulic fracturing and has garnered much attention because of its use of large amounts of fresh water, its use of proprietary fluids for the hydraulic-fracturing process, its potential to release contaminants into the environment, and its potential effect on water resources. Nonetheless, development of natural gas extraction wells in the Marcellus Shale is only part of the overall natural gas story in this area of Pennsylvania. Conventional natural gas wells, which sometimes use the same technique, are commonly located in the same general area as the Marcellus Shale and are frequently developed in clusters across the landscape. The combined effects of these two natural gas extraction methods create potentially serious patterns of disturbance on the landscape. This document quantifies the landscape changes and consequences of natural gas extraction for Bedford, Blair, Cambria, Centre, Clearfield, Clinton, Columbia, Huntingdon, and Luzerne Counties in Pennsylvania between 2004 and 2010. Patterns of landscape disturbance related to natural gas extraction activities were collected and digitized using National Agriculture Imagery Program (NAIP) imagery for 2004, 2005/2006, 2008, and 2010. The disturbance patterns were then used to measure changes in land cover and land use using the National Land Cover Database (NLCD) of 2001. A series of landscape metrics is also used to quantify these changes and is included in this publication. In this region, natural gas development disturbed approximately 943 hectares of land in which forest sustained three times the amount of disturbance as agricultural land. One-quarter of that total disturbance was from Marcellus natural gas development.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141089","usgsCitation":"Slonecker, E., Milheim, L., Roig-Silva, C., and Winters, S., 2014, Landscape consequences of natural gas extraction in Bedford, Blair, Cambria, Centre, Clearfield, Clinton, Columbia, Huntingdon, and Luzerne counties, Pennsylvania, 2004-2010: U.S. Geological Survey Open-File Report 2014-1089, v, 49 p., https://doi.org/10.3133/ofr20141089.","productDescription":"v, 49 p.","numberOfPages":"55","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2004-01-01","temporalEnd":"2010-12-31","ipdsId":"IP-052469","costCenters":[{"id":242,"text":"Eastern Geographic Science 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S.G.","contributorId":99898,"corporation":false,"usgs":true,"family":"Winters","given":"S.G.","email":"","affiliations":[],"preferred":false,"id":493853,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70192979,"text":"70192979 - 2014 - Population trends of smallmouth bass in the upper Colorado River basin with an evaluation of removal effects","interactions":[],"lastModifiedDate":"2017-12-21T10:28:54","indexId":"70192979","displayToPublicDate":"2014-06-10T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"seriesNumber":"Project 161","title":"Population trends of smallmouth bass in the upper Colorado River basin with an evaluation of removal effects","docAbstract":"Smallmouth bass Micropterus dolomieu were rare in the upper Colorado River basin until the early 1990’s when their abundance dramatically increased in the Yampa River sub-basin. Increased abundance was due primarily to colonization from Elkhead Reservoir, which was rapidly drawn down twice, first to make improvements to the dam (1992) and a second time for reservoir expansion (2005), and allowed escapement of resident bass to the river through an unscreened outlet. Elkhead Reservoir is located on Elkhead Creek, a tributary of the Yampa River. The rapid Elkhead Reservoir drawdown in 1992 was followed by a period of drought years with low, early runoff in the Yampa River sub-basin that benefitted smallmouth bass reproduction. This combination of factors allowed smallmouth bass to establish a self-sustaining population in the Yampa River. Subsequently, successful recruitment allowed smallmouth bass to disperse upstream and downstream in the Yampa River and eventually move into the downstream Green River. Smallmouth bass were also likely introduced, by unknown means, into the upper Colorado River and have since dispersed in this sub-basin. The rapid increase of smallmouth bass in the upper Colorado River basin overlapped with significant reductions in native fish populations in some locations. The threat to these native fishes initiated intensive mechanical removal of smallmouth bass by the Upper Colorado River Endangered Fish Recovery Program.
In general, three factors explain fluctuating patterns in smallmouth bass density in the upper Colorado River basin in the last decade: reductions due to electrofishing removal, bass recovery after exploitation due to recruitment and immigration, and changes due to environmental factors not related to electrofishing and other management actions. Our analyses indicated that smallmouth bass densities were substantially reduced in most years by 7 electrofishing removal efforts. Less often, but dramatically in some cases, environmental effects were also responsible for significant declines in smallmouth bass densities in some reaches. Abundant year classes of young smallmouth bass produced in low flow and warm years such as 2007 have potential to overwhelm removal efforts, and the year class persists for one or more years. Nonetheless, it appears that increased electrofishing removal efforts from 2007 to 2011 resulted in sustained reductions in density of smallmouth bass sub-adults and adults throughout the upper basin despite environmental conditions that favored smallmouth bass reproduction in some years (e.g. 2007 and 2009), subsequent recruitment into sub-adult and adult age classes, and movement of smallmouth bass which previously (prior to increases in electrofishing removal efforts) allowed densities to recover in some reaches.
We recommend that removal efforts continue in most areas of the upper basin but that the Recovery Program consider allocating effort based on population trends and suspected areas of highest smallmouth bass reproduction. For instance, reproduction, recruitment, and movement of smallmouth bass allowed densities to recover in some reaches, particularly Little Yampa Canyon. Smallmouth bass population recovery implies that areas such as Little Yampa Canyon itself or adjacent reaches (especially upstream), may provide important habitat for age-0 production. We recommend continued assessment of smallmouth bass populations in reaches where reproduction or age-1 nurseries are suspected, such as Little Yampa Canyon and the adjacent upstream reach. It may also be necessary to expand monitoring to areas surrounding suspected sources of smallmouth bass reproduction and increase electrofishing removal effort in these reaches.
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In 2010, we documented avian foraging behavior, characterized the arthropod community, sampled bird diets, and undertook an experiment to determine whether tamarisk leaf beetles are palatable to birds. We observed that tamarisk leaf beetles compose 24.0 percent (95-percent-confidence interval, 19.9-27.4 percent) and 35.4 percent (95-percent-confidence interval, 32.4-45.1 percent) of arthropod abundance and biomass in the study area, respectively. Birds ate few tamarisk leaf beetles, despite a superabundance of D. carinulata in the environment. The frequency of occurrence of tamarisk leaf beetles in bird diets was 2.1 percent (95-percent-confidence interval, 1.3- 2.9 percent) by abundance and 3.4 percent (95-percent-confidence interval, 2.6-4.2 percent) by biomass. Thus, tamarisk leaf beetles probably do not contribute significantly to the diets of birds in areas where biologic control of tamarisk is being applied.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141100","issn":"2331-1258","usgsCitation":"Puckett, S., and van Riper, C., 2014, Influences of the Tamarisk Leaf Beetle (Diorhabda carinulata) on the diet of insectivorous birds along the Dolores River in Southwestern Colorado: U.S. Geological Survey Open-File Report 2014-1100, iv, 49 p., https://doi.org/10.3133/ofr20141100.","productDescription":"iv, 49 p.","numberOfPages":"53","onlineOnly":"Y","ipdsId":"IP-044426","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":288180,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1100/"},{"id":288182,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141100.PNG"},{"id":288181,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1100/pdf/ofr2014-1100.pdf"}],"country":"United States","state":"Colorado;Utah","otherGeospatial":"Dolores River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -109.2803,37.4408 ], [ -109.2803,38.8276 ], [ -107.9266,38.8276 ], [ -107.9266,37.4408 ], [ -109.2803,37.4408 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5396c953e4b0f7580bc0a8c3","contributors":{"authors":[{"text":"Puckett, Sarah L.","contributorId":34046,"corporation":false,"usgs":true,"family":"Puckett","given":"Sarah L.","affiliations":[],"preferred":false,"id":493847,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"van Riper, Charles III 0000-0003-1084-5843 charles_van_riper@usgs.gov","orcid":"https://orcid.org/0000-0003-1084-5843","contributorId":169488,"corporation":false,"usgs":true,"family":"van Riper","given":"Charles","suffix":"III","email":"charles_van_riper@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":false,"id":493848,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70102224,"text":"70102224 - 2014 - Use of genetic data to infer population-specific ecological and phenotypic traits from mixed aggregations","interactions":[],"lastModifiedDate":"2018-04-21T13:19:15","indexId":"70102224","displayToPublicDate":"2014-06-09T13:58:00","publicationYear":"2014","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":"Use of genetic data to infer population-specific ecological and phenotypic traits from mixed aggregations","docAbstract":"Many applications in ecological genetics involve sampling individuals from a mixture of multiple biological populations and subsequently associating those individuals with the populations from which they arose. Analytical methods that assign individuals to their putative population of origin have utility in both basic and applied research, providing information about population-specific life history and habitat use, ecotoxins, pathogen and parasite loads, and many other non-genetic ecological, or phenotypic traits. Although the question is initially directed at the origin of individuals, in most cases the ultimate desire is to investigate the distribution of some trait among populations. Current practice is to assign individuals to a population of origin and study properties of the trait among individuals within population strata as if they constituted independent samples. It seemed that approach might bias population-specific trait inference. In this study we made trait inferences directly through modeling, bypassing individual assignment. We extended a Bayesian model for population mixture analysis to incorporate parameters for the phenotypic trait and compared its performance to that of individual assignment with a minimum probability threshold for assignment. The Bayesian mixture model outperformed individual assignment under some trait inference conditions. However, by discarding individuals whose origins are most uncertain, the individual assignment method provided a less complex analytical technique whose performance may be adequate for some common trait inference problems. Our results provide specific guidance for method selection under various genetic relationships among populations with different trait distributions.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"PLoS ONE","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Public Library of Science","publisherLocation":"San Francisco, CA","doi":"10.1371/journal.pone.0098470","usgsCitation":"Moran, P., Bromaghin, J.F., and Masuda, M., 2014, Use of genetic data to infer population-specific ecological and phenotypic traits from mixed aggregations: PLoS ONE, v. 9, no. 6, 13 p., https://doi.org/10.1371/journal.pone.0098470.","productDescription":"13 p.","numberOfPages":"13","onlineOnly":"Y","ipdsId":"IP-050953","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":472945,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0098470","text":"Publisher Index Page"},{"id":288179,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":288178,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1371/journal.pone.0098470"}],"volume":"9","issue":"6","noUsgsAuthors":false,"publicationDate":"2014-06-06","publicationStatus":"PW","scienceBaseUri":"5396c953e4b0f7580bc0a8c7","contributors":{"authors":[{"text":"Moran, Paul","contributorId":42140,"corporation":false,"usgs":true,"family":"Moran","given":"Paul","email":"","affiliations":[],"preferred":false,"id":492862,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bromaghin, Jeffrey F. 0000-0002-7209-9500 jbromaghin@usgs.gov","orcid":"https://orcid.org/0000-0002-7209-9500","contributorId":139899,"corporation":false,"usgs":true,"family":"Bromaghin","given":"Jeffrey","email":"jbromaghin@usgs.gov","middleInitial":"F.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":492860,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Masuda, Michele","contributorId":24280,"corporation":false,"usgs":true,"family":"Masuda","given":"Michele","email":"","affiliations":[],"preferred":false,"id":492861,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70107925,"text":"fs20143043 - 2014 - Water resources of Acadia Parish, Louisiana","interactions":[],"lastModifiedDate":"2014-06-09T11:41:11","indexId":"fs20143043","displayToPublicDate":"2014-06-09T11:32:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-3043","title":"Water resources of Acadia Parish, Louisiana","docAbstract":"Information concerning the availability, use, and quality of water in Acadia Parish, Louisiana, is critical for proper water-supply management. The purpose of this fact sheet is to present information that can be used by water managers, parish residents, and others for stewardship of this vital resource. Information on the availability, past and current use, use trends, and water quality from groundwater and surface-water sources in the parish is presented. Previously published reports and data stored in the U.S. Geological Survey’s National Water Information System (http://waterdata.usgs.gov/nwis) are the primary sources of the information presented here.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20143043","issn":"2327-6932","collaboration":"Prepared in cooperation with the Louisiana Department of Transportation and Development","usgsCitation":"Prakken, L., and White, V.E., 2014, Water resources of Acadia Parish, Louisiana: U.S. Geological Survey Fact Sheet 2014-3043, 6 p., https://doi.org/10.3133/fs20143043.","productDescription":"6 p.","numberOfPages":"6","onlineOnly":"N","ipdsId":"IP-055417","costCenters":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"links":[{"id":288175,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20143043.jpg"},{"id":288173,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2014/3043/"},{"id":288174,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2014/3043/pdf/fs2014-3043.pdf"}],"projection":"Albers Equal-Area Conic projection","datum":"North American Datum of 1983","country":"United States","state":"Louisiana","county":"Acadia Parish","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -92.666667,30.0 ], [ -92.666667,30.5 ], [ -92.166667,30.5 ], [ -92.166667,30.0 ], [ -92.666667,30.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5396c954e4b0f7580bc0a8cb","contributors":{"authors":[{"text":"Prakken, Larry B.","contributorId":86673,"corporation":false,"usgs":true,"family":"Prakken","given":"Larry B.","affiliations":[],"preferred":false,"id":493934,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"White, Vincent E. 0000-0002-1660-0102 vwhite@usgs.gov","orcid":"https://orcid.org/0000-0002-1660-0102","contributorId":5388,"corporation":false,"usgs":true,"family":"White","given":"Vincent","email":"vwhite@usgs.gov","middleInitial":"E.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":493933,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70111747,"text":"70111747 - 2014 - Hawaiian forest bird trends: using log-linear models to assess long-term trends is supported by model diagnostics and assumptions (reply to Freed and Cann 2013)","interactions":[],"lastModifiedDate":"2014-06-09T10:37:25","indexId":"70111747","displayToPublicDate":"2014-06-09T10:27:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1318,"text":"Condor","active":true,"publicationSubtype":{"id":10}},"title":"Hawaiian forest bird trends: using log-linear models to assess long-term trends is supported by model diagnostics and assumptions (reply to Freed and Cann 2013)","docAbstract":"Freed and Cann (2013) criticized our use of linear models to assess trends in the status of Hawaiian forest birds through time (Camp et al. 2009a, 2009b, 2010) by questioning our sampling scheme, whether we met model assumptions, and whether we ignored short-term changes in the population time series. In the present paper, we address these concerns and reiterate that our results do not support the position of Freed and Cann (2013) that the forest birds in the Hakalau Forest National Wildlife Refuge (NWR) are declining, or that the federally listed endangered birds are showing signs of imminent collapse. On the contrary, our data indicate that the 21-year long-term trends for native birds in Hakalau Forest NWR are stable to increasing, especially in areas that have received active management.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Condor","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Cooper Ornithological Society","doi":"10.1650/CONDOR-13-089.1","usgsCitation":"Camp, R., Pratt, T.K., Gorresen, P.M., Woodworth, B., and Jeffrey, J.J., 2014, Hawaiian forest bird trends: using log-linear models to assess long-term trends is supported by model diagnostics and assumptions (reply to Freed and Cann 2013): Condor, v. 116, no. 1, p. 97-101, https://doi.org/10.1650/CONDOR-13-089.1.","productDescription":"5 p.","startPage":"97","endPage":"101","numberOfPages":"5","ipdsId":"IP-052204","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":472946,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1650/condor-13-089.1","text":"Publisher Index Page"},{"id":288171,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":288161,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1650/CONDOR-13-089.1"}],"country":"United States","state":"Hawai'i","otherGeospatial":"Hakalau Forest National Wildlife Refuge","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -155.85876,19.363457 ], [ -155.85876,19.922001 ], [ -155.223499,19.922001 ], [ -155.223499,19.363457 ], [ -155.85876,19.363457 ] ] ] } } ] }","volume":"116","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5396c952e4b0f7580bc0a8bf","contributors":{"authors":[{"text":"Camp, Richard J.","contributorId":27392,"corporation":false,"usgs":true,"family":"Camp","given":"Richard J.","affiliations":[],"preferred":false,"id":494460,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pratt, Thane K. tkpratt@usgs.gov","contributorId":5495,"corporation":false,"usgs":true,"family":"Pratt","given":"Thane","email":"tkpratt@usgs.gov","middleInitial":"K.","affiliations":[{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":true,"id":494459,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gorresen, P. Marcos mgorresen@usgs.gov","contributorId":37020,"corporation":false,"usgs":true,"family":"Gorresen","given":"P.","email":"mgorresen@usgs.gov","middleInitial":"Marcos","affiliations":[],"preferred":false,"id":494461,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Woodworth, Bethany L.","contributorId":66797,"corporation":false,"usgs":true,"family":"Woodworth","given":"Bethany L.","affiliations":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"preferred":false,"id":494463,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jeffrey, John J.","contributorId":55256,"corporation":false,"usgs":true,"family":"Jeffrey","given":"John","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":494462,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70128991,"text":"70128991 - 2014 - Hierarchical spatial genetic structure in a distinct population segment of greater sage-grouse","interactions":[],"lastModifiedDate":"2016-12-14T12:11:21","indexId":"70128991","displayToPublicDate":"2014-06-07T09:51:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1324,"text":"Conservation Genetics","active":true,"publicationSubtype":{"id":10}},"title":"Hierarchical spatial genetic structure in a distinct population segment of greater sage-grouse","docAbstract":"Greater sage-grouse (Centrocercus urophasianus) within the Bi-State Management Zone (area along the border between Nevada and California) are geographically isolated on the southwestern edge of the species’ range. Previous research demonstrated that this population is genetically unique, with a high proportion of unique mitochondrial DNA (mtDNA) haplotypes and with significant differences in microsatellite allele frequencies compared to populations across the species’ range. As a result, this population was considered a distinct population segment (DPS) and was recently proposed for listing as threatened under the U.S. Endangered Species Act. A more comprehensive understanding of the boundaries of this genetically unique population (where the Bi-State population begins) and an examination of genetic structure within the Bi-State is needed to help guide effective management decisions. We collected DNA from eight sampling locales within the Bi-State (N = 181) and compared those samples to previously collected DNA from the two most proximal populations outside of the Bi-State DPS, generating mtDNA sequence data and amplifying 15 nuclear microsatellites. Both mtDNA and microsatellite analyses support the idea that the Bi-State DPS represents a genetically unique population, which has likely been separated for thousands of years. Seven mtDNA haplotypes were found exclusively in the Bi-State population and represented 73 % of individuals, while three haplotypes were shared with neighboring populations. In the microsatellite analyses both STRUCTURE and FCA separate the Bi-State from the neighboring populations. We also found genetic structure within the Bi-State as both types of data revealed differences between the northern and southern part of the Bi-State and there was evidence of isolation-by-distance. STRUCTURE revealed three subpopulations within the Bi-State consisting of the northern Pine Nut Mountains (PNa), mid Bi-State, and White Mountains (WM) following a north–south gradient. This genetic subdivision within the Bi-State is likely the result of habitat loss and fragmentation that has been exacerbated by recent human activities and the encroachment of singleleaf pinyon (Pinus monophylla) and juniper (Juniperus spp.) trees. While genetic concerns may be only one of many priorities for the conservation and management of the Bi-State greater sage-grouse, we believe that they warrant attention along with other issues (e.g., quality of sagebrush habitat, preventing future loss of habitat). Management actions that promote genetic connectivity, especially with respect to WM and PNa, may be critical to the long-term viability of the Bi-State DPS.
","language":"English","publisher":"Springer","doi":"10.1007/s10592-014-0618-8","usgsCitation":"Oyler-McCance, S.J., Casazza, M.L., Fike, J.A., and Coates, P.S., 2014, Hierarchical spatial genetic structure in a distinct population segment of greater sage-grouse: Conservation Genetics, v. 15, no. 6, p. 1299-1311, https://doi.org/10.1007/s10592-014-0618-8.","productDescription":"13 p.","startPage":"1299","endPage":"1311","numberOfPages":"13","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-052505","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":295364,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":295348,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s10592-014-0618-8"}],"country":"United States","state":"California, Nevada","volume":"15","issue":"6","noUsgsAuthors":false,"publicationDate":"2014-06-07","publicationStatus":"PW","scienceBaseUri":"5440de2de4b0b0a643c732db","contributors":{"authors":[{"text":"Oyler-McCance, Sara J. 0000-0003-1599-8769 sara_oyler-mccance@usgs.gov","orcid":"https://orcid.org/0000-0003-1599-8769","contributorId":1973,"corporation":false,"usgs":true,"family":"Oyler-McCance","given":"Sara","email":"sara_oyler-mccance@usgs.gov","middleInitial":"J.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":503266,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Casazza, Michael L. 0000-0002-5636-735X mike_casazza@usgs.gov","orcid":"https://orcid.org/0000-0002-5636-735X","contributorId":2091,"corporation":false,"usgs":true,"family":"Casazza","given":"Michael","email":"mike_casazza@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":503267,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fike, Jennifer A. fikej@usgs.gov","contributorId":4564,"corporation":false,"usgs":true,"family":"Fike","given":"Jennifer","email":"fikej@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":503269,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Coates, Peter S. 0000-0003-2672-9994 pcoates@usgs.gov","orcid":"https://orcid.org/0000-0003-2672-9994","contributorId":3263,"corporation":false,"usgs":true,"family":"Coates","given":"Peter","email":"pcoates@usgs.gov","middleInitial":"S.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":503268,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70102827,"text":"ofr20141083 - 2014 - Using a Bayesian Network to predict shore-line change vulnerability to sea-level rise for the coasts of the United States","interactions":[],"lastModifiedDate":"2014-06-06T15:53:08","indexId":"ofr20141083","displayToPublicDate":"2014-06-06T15:50:00","publicationYear":"2014","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":"2014-1083","title":"Using a Bayesian Network to predict shore-line change vulnerability to sea-level rise for the coasts of the United States","docAbstract":"Sea-level rise is an ongoing phenomenon that is expected to continue and is projected to have a wide range of effects on coastal environments and infrastructure during the 21st century and beyond. Consequently, there is a need to assemble relevant datasets and to develop modeling or other analytical approaches to evaluate the likelihood of particular sea-level rise impacts, such as coastal erosion, and to inform coastal management decisions with this information. This report builds on previous work that compiled oceanographic and geomorphic data as part of the U.S. Geological Survey’s Coastal Vulnerability Index (CVI) for the U.S. Atlantic coast, and developed a Bayesian Network to predict shoreline-change rates based on sea-level rise plus variables that describe the hydrodynamic and geologic setting. This report extends the previous analysis to include the Gulf and Pacific coasts of the continental United States and Alaska and Hawaii, which required using methods applied to the USGS CVI dataset to extract data for these regions. The Bayesian Network converts inputs that include observations of local rates of relative sea-level change, mean wave height, mean tide range, a geomorphic classification, coastal slope, and observed shoreline-change rates to calculate the probability of the shoreline-erosion rate exceeding a threshold level of 1 meter per year for the coasts of the United States. The calculated probabilities were compared to the historical observations of shoreline change to evaluate the hindcast success rate of the most likely probability of shoreline change. Highest accuracy was determined for the coast of Hawaii (98 percent success rate) and lowest accuracy was determined for the Gulf of Mexico (34 percent success rate). The minimum success rate rose to nearly 80 percent (Atlantic and Gulf coasts) when success included shoreline-change outcomes that were adjacent to the most likely outcome. Additionally, the probabilistic approach determines the confidence in calculated outcomes as the probability of the most likely outcome. The confidence was highest along the Pacific coast and it was lowest along the Alaskan coast.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141083","issn":"2331-1258","usgsCitation":"Gutierrez, B.T., Plant, N.G., Pendleton, E., and Thieler, E.R., 2014, Using a Bayesian Network to predict shore-line change vulnerability to sea-level rise for the coasts of the United States: U.S. Geological Survey Open-File Report 2014-1083, v, 26 p., https://doi.org/10.3133/ofr20141083.","productDescription":"v, 26 p.","numberOfPages":"32","onlineOnly":"Y","ipdsId":"IP-053816","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":288160,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141083.jpg"},{"id":288158,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1083/"},{"id":288159,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1083/pdf/ofr2014-1083.pdf"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -130.0,20.0 ], [ -130.0,50.0 ], [ -60.0,50.0 ], [ -60.0,20.0 ], [ -130.0,20.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53ae789ce4b0abf75cf2da90","contributors":{"authors":[{"text":"Gutierrez, Benjamin T.","contributorId":58670,"corporation":false,"usgs":true,"family":"Gutierrez","given":"Benjamin","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":493044,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Plant, Nathaniel G. 0000-0002-5703-5672 nplant@usgs.gov","orcid":"https://orcid.org/0000-0002-5703-5672","contributorId":3503,"corporation":false,"usgs":true,"family":"Plant","given":"Nathaniel","email":"nplant@usgs.gov","middleInitial":"G.","affiliations":[{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":493043,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pendleton, Elizabeth A.","contributorId":101312,"corporation":false,"usgs":true,"family":"Pendleton","given":"Elizabeth A.","affiliations":[],"preferred":false,"id":493045,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thieler, E. Robert 0000-0003-4311-9717 rthieler@usgs.gov","orcid":"https://orcid.org/0000-0003-4311-9717","contributorId":2488,"corporation":false,"usgs":true,"family":"Thieler","given":"E.","email":"rthieler@usgs.gov","middleInitial":"Robert","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":493042,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70098476,"text":"ofr20141060 - 2014 - Quality-assurance and data management plan for groundwater activities by the U.S. Geological Survey in Kansas, 2014","interactions":[],"lastModifiedDate":"2014-06-06T15:10:05","indexId":"ofr20141060","displayToPublicDate":"2014-06-06T15:07:00","publicationYear":"2014","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":"2014-1060","title":"Quality-assurance and data management plan for groundwater activities by the U.S. Geological Survey in Kansas, 2014","docAbstract":"As the Nation’s principle earth-science information agency, the U.S. Geological Survey (USGS) is depended on to collect data of the highest quality. This document is a quality-assurance plan for groundwater activities (GWQAP) of the Kansas Water Science Center. The purpose of this GWQAP is to establish a minimum set of guidelines and practices to be used by the Kansas Water Science Center to ensure quality in groundwater activities. Included within these practices are the assignment of responsibilities for implementing quality-assurance activities in the Kansas Water Science Center and establishment of review procedures needed to ensure the technical quality and reliability of the groundwater products. In addition, this GWQAP is intended to complement quality-assurance plans for surface-water and water-quality activities and similar plans for the Kansas Water Science Center and general project activities throughout the USGS.
\nThis document provides the framework for collecting, analyzing, and reporting groundwater data that are quality assured and quality controlled. This GWQAP presents policies directing the collection, processing, analysis, storage, review, and publication of groundwater data. In addition, policies related to organizational responsibilities, training, project planning, and safety are presented. These policies and practices pertain to all groundwater activities conducted by the Kansas Water Science Center, including data-collection programs, interpretive and research projects. This report also includes the data management plan that describes the progression of data management from data collection to archiving and publication.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141060","issn":"2331-1258","usgsCitation":"Putnam, J.E., and Hansen, C.V., 2014, Quality-assurance and data management plan for groundwater activities by the U.S. Geological Survey in Kansas, 2014: U.S. Geological Survey Open-File Report 2014-1060, v, 37 p., https://doi.org/10.3133/ofr20141060.","productDescription":"v, 37 p.","numberOfPages":"48","onlineOnly":"Y","ipdsId":"IP-051485","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":288156,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141060.jpg"},{"id":288154,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1060/"},{"id":288155,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1060/pdf/ofr2014-1060.pdf"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53ae77f9e4b0abf75cf2c668","contributors":{"authors":[{"text":"Putnam, James E. jputnam@usgs.gov","contributorId":2021,"corporation":false,"usgs":true,"family":"Putnam","given":"James","email":"jputnam@usgs.gov","middleInitial":"E.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":false,"id":491730,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hansen, Cristi V. chansen@usgs.gov","contributorId":435,"corporation":false,"usgs":true,"family":"Hansen","given":"Cristi","email":"chansen@usgs.gov","middleInitial":"V.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":false,"id":491729,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ]}