{"pageNumber":"514","pageRowStart":"12825","pageSize":"25","recordCount":46670,"records":[{"id":70155212,"text":"70155212 - 2014 - Estimating earthquake magnitudes from reported intensities in the central and eastern United States","interactions":[],"lastModifiedDate":"2016-11-09T12:17:29","indexId":"70155212","displayToPublicDate":"2014-08-01T12:15:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Estimating earthquake magnitudes from reported intensities in the central and eastern United States","docAbstract":"

A new macroseismic intensity prediction equation is derived for the central and eastern United States and is used to estimate the magnitudes of the 1811–1812 New Madrid, Missouri, and 1886 Charleston, South Carolina, earthquakes. This work improves upon previous derivations of intensity prediction equations by including additional intensity data, correcting magnitudes in the intensity datasets to moment magnitude, and accounting for the spatial and temporal population distributions. The new relation leads to moment magnitude estimates for the New Madrid earthquakes that are toward the lower range of previous studies. Depending on the intensity dataset to which the new macroseismic intensity prediction equation is applied, mean estimates for the 16 December 1811, 23 January 1812, and 7 February 1812 mainshocks, and 16 December 1811 dawn aftershock range from 6.9 to 7.1, 6.8 to 7.1, 7.3 to 7.6, and 6.3 to 6.5, respectively. One‐sigma uncertainties on any given estimate could be as high as 0.3–0.4 magnitude units. We also estimate a magnitude of 6.9±0.3 for the 1886 Charleston, South Carolina, earthquake. We find a greater range of magnitude estimates when also accounting for multiple macroseismic intensity prediction equations. The inability to accurately and precisely ascertain magnitude from intensities increases the uncertainty of the central United States earthquake hazard by nearly a factor of two. Relative to the 2008 national seismic hazard maps, our range of possible 1811–1812 New Madrid earthquake magnitudes increases the coefficient of variation of seismic hazard estimates for Memphis, Tennessee, by 35%–42% for ground motions expected to be exceeded with a 2% probability in 50 years and by 27%–35% for ground motions expected to be exceeded with a 10% probability in 50 years.

","language":"English","publisher":"Seismological Society of America","publisherLocation":"Stanford, CA","doi":"10.1785/0120120352","usgsCitation":"Boyd, O.S., and Cramer, C.H., 2014, Estimating earthquake magnitudes from reported intensities in the central and eastern United States: Bulletin of the Seismological Society of America, v. 104, no. 4, p. 1709-1722, https://doi.org/10.1785/0120120352.","productDescription":"14 p.","startPage":"1709","endPage":"1722","numberOfPages":"14","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-055669","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":306314,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"104","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2014-07-15","publicationStatus":"PW","scienceBaseUri":"55c090ade4b033ef52104293","contributors":{"authors":[{"text":"Boyd, Oliver S. 0000-0001-9457-0407 olboyd@usgs.gov","orcid":"https://orcid.org/0000-0001-9457-0407","contributorId":140739,"corporation":false,"usgs":true,"family":"Boyd","given":"Oliver","email":"olboyd@usgs.gov","middleInitial":"S.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":565106,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cramer, Chris H.","contributorId":32196,"corporation":false,"usgs":true,"family":"Cramer","given":"Chris","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":565107,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70123176,"text":"70123176 - 2014 - Synthesis of thirty years of surface water quality and aquatic biota data in Shenandoah National Park: Collaboration between the US Geological Survey and the National Park Service","interactions":[],"lastModifiedDate":"2017-03-27T13:57:08","indexId":"70123176","displayToPublicDate":"2014-08-01T11:27:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3561,"text":"The George Wright Forum","active":true,"publicationSubtype":{"id":10}},"title":"Synthesis of thirty years of surface water quality and aquatic biota data in Shenandoah National Park: Collaboration between the US Geological Survey and the National Park Service","docAbstract":"The eastern United States has been the recipient of acidic atmospheric deposition (hereinafter, “acid rain”) for many decades. Deleterious effects of acid rain on natural resources have been well documented for surface water (e.g., Likens et al. 1996; Stoddard et al. 2001), soils (Bailey et al. 2005), forest health (Long et al. 2009), and habitat suitability for stream biota (Baker et al. 1993). Shenandoah National Park (SNP) is located in northern and central Virginia and consists of a long, narrow strip of land straddling the Blue Ridge Mountains (Figure 1). The park’s elevated topography and location downwind of the Ohio River valley, where many acidic emissions to the atmosphere are generated (NSTC 2005), have made it a target for acid rain. Characterizing the link between air quality and water quality as related to acid rain, contaminants, soil conditions, and forest health is a high priority for research and monitoring in SNP. The US Geological Survey (USGS) and SNP have had a long history of collaboration on documenting acid rain effects on the park’s natural resources, starting in 1985 and continuing to the present (Lynch and Dise 1985; Rice et al. 2001, 2004, 2005, 2007; Deviney et al. 2006, 2012; Jastram et al. 2013).","language":"English","publisher":"George Wright Society","issn":"0732-4715","usgsCitation":"Rice, K.C., Jastram, J.D., Wofford, J.E., and Schaberl, J.P., 2014, Synthesis of thirty years of surface water quality and aquatic biota data in Shenandoah National Park: Collaboration between the US Geological Survey and the National Park Service: The George Wright Forum, v. 31, no. 2, p. 198-204.","productDescription":"7 p.","startPage":"198","endPage":"204","ipdsId":"IP-055092","costCenters":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true}],"links":[{"id":293454,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":295626,"type":{"id":15,"text":"Index Page"},"url":"https://www.georgewright.org/node/9643"}],"country":"United States","state":"Virginia","otherGeospatial":"Shenandoah National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -78.20068359374999,\n 38.6275996886131\n ],\n [\n -78.1512451171875,\n 38.7283759182398\n ],\n [\n -78.12103271484375,\n 38.76693348394693\n ],\n [\n -78.1182861328125,\n 38.86109762182888\n ],\n [\n -78.19244384765625,\n 38.92522904714054\n ],\n [\n -78.25286865234375,\n 38.86965182408357\n ],\n [\n -78.24188232421875,\n 38.83756825896614\n ],\n [\n -78.30230712890624,\n 38.841846903808985\n ],\n [\n -78.3929443359375,\n 38.77121637244273\n ],\n [\n -78.4259033203125,\n 38.713375686254714\n ],\n [\n -78.3984375,\n 38.638327308061875\n ],\n [\n -78.4918212890625,\n 38.55031345037904\n ],\n [\n -78.5577392578125,\n 38.567495358827344\n ],\n [\n -78.59344482421875,\n 38.51378825951165\n ],\n [\n -78.55224609374999,\n 38.436379603\n ],\n [\n -78.607177734375,\n 38.41271038284709\n ],\n [\n -78.71429443359375,\n 38.33088431959971\n ],\n [\n -78.80218505859375,\n 38.272688535980976\n ],\n [\n -78.826904296875,\n 38.21012996629426\n ],\n [\n -78.82965087890625,\n 38.13239618602294\n ],\n [\n -78.82415771484375,\n 38.07404145941957\n ],\n [\n -78.70330810546875,\n 38.1237539824224\n ],\n [\n -78.695068359375,\n 38.201496974020806\n ],\n [\n -78.56597900390625,\n 38.28131307922966\n ],\n [\n -78.45611572265625,\n 38.34381037525605\n ],\n [\n -78.37921142578125,\n 38.371808917147554\n ],\n [\n -78.3544921875,\n 38.44498466889473\n ],\n [\n -78.31054687499999,\n 38.50948995925553\n ],\n [\n -78.23638916015625,\n 38.55031345037904\n ],\n [\n -78.23638916015625,\n 38.59326051987162\n ],\n [\n -78.20068359374999,\n 38.6275996886131\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"31","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"540ace53e4b023c1f29d5913","contributors":{"authors":[{"text":"Rice, Karen C. 0000-0002-9356-5443 kcrice@usgs.gov","orcid":"https://orcid.org/0000-0002-9356-5443","contributorId":1998,"corporation":false,"usgs":true,"family":"Rice","given":"Karen","email":"kcrice@usgs.gov","middleInitial":"C.","affiliations":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true}],"preferred":false,"id":499925,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jastram, John D. 0000-0002-9416-3358 jdjastra@usgs.gov","orcid":"https://orcid.org/0000-0002-9416-3358","contributorId":3531,"corporation":false,"usgs":true,"family":"Jastram","given":"John","email":"jdjastra@usgs.gov","middleInitial":"D.","affiliations":[{"id":37759,"text":"VA/WV Water Science Center","active":true,"usgs":true}],"preferred":true,"id":499926,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wofford, John E. B.","contributorId":38951,"corporation":false,"usgs":false,"family":"Wofford","given":"John","email":"","middleInitial":"E. B.","affiliations":[],"preferred":false,"id":499927,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schaberl, James P.","contributorId":53903,"corporation":false,"usgs":true,"family":"Schaberl","given":"James","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":499928,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70132440,"text":"70132440 - 2014 - Performance and effects of land cover type on synthetic surface reflectance data and NDVI estimates for assessment and monitoring of semi-arid rangeland","interactions":[],"lastModifiedDate":"2020-12-31T16:51:48.214552","indexId":"70132440","displayToPublicDate":"2014-08-01T11:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2027,"text":"International Journal of Applied Earth Observation and Geoinformation","active":true,"publicationSubtype":{"id":10}},"title":"Performance and effects of land cover type on synthetic surface reflectance data and NDVI estimates for assessment and monitoring of semi-arid rangeland","docAbstract":"

Federal land management agencies provide stewardship over much of the rangelands in the arid andsemi-arid western United States, but they often lack data of the proper spatiotemporal resolution andextent needed to assess range conditions and monitor trends. Recent advances in the blending of com-plementary, remotely sensed data could provide public lands managers with the needed information.We applied the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) to five Landsat TMand concurrent Terra MODIS scenes, and used pixel-based regression and difference image analyses toevaluate the quality of synthetic reflectance and NDVI products associated with semi-arid rangeland. Pre-dicted red reflectance data consistently demonstrated higher accuracy, less bias, and stronger correlationwith observed data than did analogous near-infrared (NIR) data. The accuracy of both bands tended todecline as the lag between base and prediction dates increased; however, mean absolute errors (MAE)were typically ≤10%. The quality of area-wide NDVI estimates was less consistent than either spectra lband, although the MAE of estimates predicted using early season base pairs were ≤10% throughout the growing season. Correlation between known and predicted NDVI values and agreement with the 1:1regression line tended to decline as the prediction lag increased. Further analyses of NDVI predictions,based on a 22 June base pair and stratified by land cover/land use (LCLU), revealed accurate estimates through the growing season; however, inter-class performance varied. This work demonstrates the successful application of the STARFM algorithm to semi-arid rangeland; however, we encourage evaluation of STARFM’s performance on a per product basis, stratified by LCLU, with attention given to the influence of base pair selection and the impact of the time lag.

","language":"English","publisher":"Elsevier, Inc.","publisherLocation":"Amsterdam, Holland","doi":"10.1016/j.jag.2014.01.008","usgsCitation":"Olexa, E.M., and Lawrence, R.L., 2014, Performance and effects of land cover type on synthetic surface reflectance data and NDVI estimates for assessment and monitoring of semi-arid rangeland: International Journal of Applied Earth Observation and Geoinformation, v. 30, p. 30-41, https://doi.org/10.1016/j.jag.2014.01.008.","productDescription":"12 p.","startPage":"30","endPage":"41","numberOfPages":"12","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-050870","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":296058,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Utah, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.87353515625,\n 41.4509614012039\n ],\n [\n -110.379638671875,\n 40.455307212131494\n ],\n [\n -109.302978515625,\n 42.439674178149424\n ],\n [\n -111.90673828125,\n 43.5326204268101\n ],\n [\n -112.87353515625,\n 41.4509614012039\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"30","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5465d635e4b04d4b7dbd662b","contributors":{"authors":[{"text":"Olexa, Edward M. 0000-0002-2000-6798 eolexa@usgs.gov","orcid":"https://orcid.org/0000-0002-2000-6798","contributorId":4448,"corporation":false,"usgs":true,"family":"Olexa","given":"Edward","email":"eolexa@usgs.gov","middleInitial":"M.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":522880,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lawrence, Rick L","contributorId":127018,"corporation":false,"usgs":false,"family":"Lawrence","given":"Rick","email":"","middleInitial":"L","affiliations":[{"id":6765,"text":"Montana State University, Department of Land Resources and Environmental Sciences","active":true,"usgs":false}],"preferred":false,"id":522881,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70120476,"text":"70120476 - 2014 - Continuous estimation of baseflow in snowmelt-dominated streams and rivers in the Upper Colorado River Basin: A chemical hydrograph separation approach","interactions":[],"lastModifiedDate":"2017-01-03T14:56:27","indexId":"70120476","displayToPublicDate":"2014-08-01T10:45:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Continuous estimation of baseflow in snowmelt-dominated streams and rivers in the Upper Colorado River Basin: A chemical hydrograph separation approach","docAbstract":"

Effective science-based management of water resources in large basins requires a qualitative understanding of hydrologic conditions and quantitative measures of the various components of the water budget, including difficult to measure components such as baseflow discharge to streams. Using widely available discharge and continuously collected specific conductance (SC) data, we adapted and applied a long established chemical hydrograph separation approach to quantify daily and representative annual baseflow discharge at fourteen streams and rivers at large spatial (> 1,000 km2 watersheds) and temporal (up to 37 years) scales in the Upper Colorado River Basin. On average, annual baseflow was 21-58% of annual stream discharge, 13-45% of discharge during snowmelt, and 40-86% of discharge during low-flow conditions. Results suggest that reservoirs may act to store baseflow discharged to the stream during snowmelt and release that baseflow during low-flow conditions, and that irrigation return flows may contribute to increases in fall baseflow in heavily irrigated watersheds. The chemical hydrograph separation approach, and associated conceptual model defined here provide a basis for the identification of land use, management, and climate effects on baseflow.

","language":"English","publisher":"American Geophysical Union","publisherLocation":"Washington, D.C.","doi":"10.1002/2013WR014939","usgsCitation":"Miller, M.P., Susong, D.D., Shope, C.L., Heilweil, V.M., and Stolp, B.J., 2014, Continuous estimation of baseflow in snowmelt-dominated streams and rivers in the Upper Colorado River Basin: A chemical hydrograph separation approach: Water Resources Research, v. 50, no. 8, p. 6986-6999, https://doi.org/10.1002/2013WR014939.","productDescription":"14 p.","startPage":"6986","endPage":"6999","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-052142","costCenters":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":472837,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2013wr014939","text":"Publisher Index Page"},{"id":292271,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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ddsusong@usgs.gov","contributorId":1040,"corporation":false,"usgs":true,"family":"Susong","given":"David","email":"ddsusong@usgs.gov","middleInitial":"D.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":498273,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shope, Christopher L. cshope@usgs.gov","contributorId":5016,"corporation":false,"usgs":true,"family":"Shope","given":"Christopher","email":"cshope@usgs.gov","middleInitial":"L.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":498275,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Heilweil, Victor M. heilweil@usgs.gov","contributorId":837,"corporation":false,"usgs":true,"family":"Heilweil","given":"Victor","email":"heilweil@usgs.gov","middleInitial":"M.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":498271,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stolp, Bernard J. 0000-0003-3803-1497 bjstolp@usgs.gov","orcid":"https://orcid.org/0000-0003-3803-1497","contributorId":963,"corporation":false,"usgs":true,"family":"Stolp","given":"Bernard","email":"bjstolp@usgs.gov","middleInitial":"J.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":498272,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70135163,"text":"70135163 - 2014 - Site fidelity and condition metrics suggest sequential habitat use by early juvenile snook","interactions":[],"lastModifiedDate":"2014-12-11T10:43:28","indexId":"70135163","displayToPublicDate":"2014-08-01T10:45:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2663,"text":"Marine Ecology Progress Series","active":true,"publicationSubtype":{"id":10}},"title":"Site fidelity and condition metrics suggest sequential habitat use by early juvenile snook","docAbstract":"

The common snook Centropomus undecimalis is an estuarine-dependent fish that relies on landward wetlands as nursery habitat. Despite its economic importance, portions of the snook's early life history are poorly understood. We compared habitat use of young-of-the-year (YOY) snook in 2 geomorphic mesohabitats (tidal pond and tidal creek) along an estuarine gradient (upstream vs. downstream) within a single wetland during fall recruitment. We used abundance, length, condition indices, and stable isotopes to assess ontogenetic mesohabitat use and site fidelity. We found that (1) YOY snook were more abundant within the upstream creek and ponds; (2) the smallest snook were found only in ponds; (3) snook from ponds had lower condition (Fulton's K and hepatosomatic index); (4) snook began moving from ponds to the creek at ~40 mm standard length; and (5) snook from the 2 mesohabitats were isotopically distinct, indicating high site fidelity at rather small spatial scales. Collectively, these data identified sequential use of mesohabitats, wherein seaward-spawned YOY snook moved landward and recruited to pond habitats, where they dedicated energy to growth (as length) before making an ontogenetic habitat shift to the creek. Once in the creek, YOY snook condition improved as they approached maturity and started the downstream return towards seaward locations. The wetland network that was previously viewed as generalized nursery habitat instead consists of mesohabitats that support different life stages in sequence. This represents ontogenetic habitat complementation, in which lower availability of a required mesohabitat type may limit the entire wetland's contribution to the adult population.

","language":"English","publisher":"Inter-Research","publisherLocation":"Oldendorf, Germany","doi":"10.3354/meps10902","collaboration":"Adam B. Brame; Ernst B. Peebles; David J. Hollander","usgsCitation":"Brame, A.B., McIvor, C., Peebles, E.B., and Hollander, D.J., 2014, Site fidelity and condition metrics suggest sequential habitat use by early juvenile snook: Marine Ecology Progress Series, v. 509, p. 255-269, https://doi.org/10.3354/meps10902.","productDescription":"15 p.","startPage":"255","endPage":"269","numberOfPages":"15","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-051601","costCenters":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"links":[{"id":472839,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/meps10902","text":"Publisher Index Page"},{"id":296613,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":296611,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.int-res.com/abstracts/meps/v509/p255-269/"}],"volume":"509","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"548ace40e4b00f366bee37c4","contributors":{"authors":[{"text":"Brame, Adam B.","contributorId":64029,"corporation":false,"usgs":true,"family":"Brame","given":"Adam","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":526907,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McIvor, Carole carole_mcivor@usgs.gov","contributorId":3665,"corporation":false,"usgs":true,"family":"McIvor","given":"Carole","email":"carole_mcivor@usgs.gov","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":526906,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Peebles, Ernst B","contributorId":127813,"corporation":false,"usgs":false,"family":"Peebles","given":"Ernst","email":"","middleInitial":"B","affiliations":[{"id":7163,"text":"University of South Florida","active":true,"usgs":false}],"preferred":false,"id":526908,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hollander, David J.","contributorId":11421,"corporation":false,"usgs":true,"family":"Hollander","given":"David","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":526909,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70129219,"text":"70129219 - 2014 - A mass balance approach to investigating geochemical controls on secondary water quality impacts at a crude oil spill site near Bemidji, MN","interactions":[],"lastModifiedDate":"2018-09-14T16:48:05","indexId":"70129219","displayToPublicDate":"2014-08-01T09:52:17","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2233,"text":"Journal of Contaminant Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"A mass balance approach to investigating geochemical controls on secondary water quality impacts at a crude oil spill site near Bemidji, MN","docAbstract":"

Secondary water quality impacts can result from a broad range of coupled reactions triggered by primary groundwater contaminants. Data from a crude-oil spill research site near Bemidji, MN provide an ideal test case for investigating the complex interactions controlling secondary impacts, including depleted dissolved oxygen and elevated organic carbon, inorganic carbon, CH4, Mn, Fe, and other dissolved ions. To better understand these secondary impacts, this study began with an extensive data compilation of various data types, comprising aqueous, sediment, gas, and oil phases, covering a 260 m cross-sectional domain over 30 years. Mass balance calculations are used to quantify pathways that control secondary components, by using the data to constrain the sources and sinks for the important redox processes. The results show that oil constituents other than BTEX (benzene, toluene, ethylbenzene, o-, m- and p-xylenes), including n-alkanes and other aromatic compounds, play significant roles in plume evolution and secondary water quality impacts. The analysis underscores previous results on the importance of non-aqueous phases. Over 99.9% of the Fe2+ plume is attenuated by immobilization on sediments as Fe(II) and 85–95% of the carbon biodegradation products are outgassed. Gaps identified in carbon and Fe mass balances and in pH buffering mechanisms are used to formulate a new conceptual model. This new model includes direct out-gassing of CH4 and CO2 from organic carbon biodegradation, dissolution of directly produced CO2, and sorption with H+ exchange to improve pH buffering. The identification of these mechanisms extends understanding of natural attenuation of potential secondary impacts at enhanced reductive dechlorination sites, particularly for reduced Fe plumes, produced CH4, and pH perturbations.

","language":"English","publisher":"Elsevier Science","publisherLocation":"Amsterdam","doi":"10.1016/j.jconhyd.2014.04.006","usgsCitation":"Ng, G., Bekins, B.A., Cozzarelli, I.M., Baedecker, M., Bennett, P.C., and Amos, R.T., 2014, A mass balance approach to investigating geochemical controls on secondary water quality impacts at a crude oil spill site near Bemidji, MN: Journal of Contaminant Hydrology, v. 164, p. 1-15, https://doi.org/10.1016/j.jconhyd.2014.04.006.","productDescription":"15 p.","startPage":"1","endPage":"15","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-053326","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":472841,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jconhyd.2014.04.006","text":"Publisher Index Page"},{"id":295516,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":295484,"rank":1,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.jconhyd.2014.04.006"}],"country":"United States","state":"Minnesota","city":"Bemidji","volume":"164","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5447759ae4b0f888a81b82e8","chorus":{"doi":"10.1016/j.jconhyd.2014.04.006","url":"http://dx.doi.org/10.1016/j.jconhyd.2014.04.006","publisher":"Elsevier BV","authors":"Ng G.-H. Crystal, Bekins Barbara A., Cozzarelli Isabelle M., Baedecker Mary Jo, Bennett Philip C., Amos Richard T.","journalName":"Journal of Contaminant Hydrology","publicationDate":"8/2014","auditedOn":"7/24/2015","publiclyAccessibleDate":"5/24/2014"},"contributors":{"authors":[{"text":"Ng, Gene-Hua Crystal","contributorId":7212,"corporation":false,"usgs":true,"family":"Ng","given":"Gene-Hua Crystal","affiliations":[],"preferred":false,"id":503556,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bekins, Barbara A. 0000-0002-1411-6018 babekins@usgs.gov","orcid":"https://orcid.org/0000-0002-1411-6018","contributorId":1348,"corporation":false,"usgs":true,"family":"Bekins","given":"Barbara","email":"babekins@usgs.gov","middleInitial":"A.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":503554,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cozzarelli, Isabelle M. 0000-0002-5123-1007 icozzare@usgs.gov","orcid":"https://orcid.org/0000-0002-5123-1007","contributorId":1693,"corporation":false,"usgs":true,"family":"Cozzarelli","given":"Isabelle","email":"icozzare@usgs.gov","middleInitial":"M.","affiliations":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":503555,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Baedecker, Mary Jo","contributorId":68671,"corporation":false,"usgs":true,"family":"Baedecker","given":"Mary Jo","affiliations":[],"preferred":false,"id":503558,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bennett, Philip C.","contributorId":30567,"corporation":false,"usgs":true,"family":"Bennett","given":"Philip","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":503557,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Amos, Richard T.","contributorId":69081,"corporation":false,"usgs":true,"family":"Amos","given":"Richard","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":503559,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70099391,"text":"ofr20141063 - 2014 - Preliminary geologic map of the eastern Willapa Hills, Cowlitz, Lewis, and Wahkiakum Counties, Washington","interactions":[{"subject":{"id":47216,"text":"ofr81674 - 1981 - Geologic map of the eastern Willapa Hills, Cowlitz, Lewis, Pacific, and Wahkiakum counties, Washington","indexId":"ofr81674","publicationYear":"1981","noYear":false,"title":"Geologic map of the eastern Willapa Hills, Cowlitz, Lewis, Pacific, and Wahkiakum counties, Washington"},"predicate":"SUPERSEDED_BY","object":{"id":70099391,"text":"ofr20141063 - 2014 - Preliminary geologic map of the eastern Willapa Hills, Cowlitz, Lewis, and Wahkiakum Counties, Washington","indexId":"ofr20141063","publicationYear":"2014","noYear":false,"title":"Preliminary geologic map of the eastern Willapa Hills, Cowlitz, Lewis, and Wahkiakum Counties, Washington"},"id":1}],"lastModifiedDate":"2023-05-26T15:23:05.59424","indexId":"ofr20141063","displayToPublicDate":"2014-08-01T08:52:00","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":"2014-1063","title":"Preliminary geologic map of the eastern Willapa Hills, Cowlitz, Lewis, and Wahkiakum Counties, Washington","docAbstract":"This digital map database and the PDF derived from the database were created from the analog geologic map: Wells, R.E. (1981), “Geologic map of the eastern Willapa Hills, Cowlitz, Lewis, and Wahkiakum Counties, Washington.” The geodatabase replicates the geologic mapping of the 1981 report with minor exceptions along water boundaries and also along the north and south map boundaries. Slight adjustments to contacts along water boundaries were made to correct differences between the topographic base map used in the 1981 compilation (analog USGS 15-minute series quadrangle maps at 1:62,500 scale) and the base map used for this digital compilation (scanned USGS 7.5-minute series quadrangle maps at 1:24,000 scale). These minor adjustments, however, did not materially alter the geologic map. No new field mapping was performed to create this digital map database, and no attempt was made to fit geologic contacts to the new 1:24,000 topographic base, except as noted above. We corrected typographical errors, formatting errors, and attribution errors (for example, the name change of Goble Volcanics to Grays River Volcanics following current State of Washington usage; Walsh and others, 1987). We also updated selected references, substituted published papers for abstracts, and cited published radiometric ages for the volcanic and plutonic rocks. The reader is referred to Magill and others (1982), Wells and Coe (1985), Walsh and others (1987), Moothart (1993), Payne (1998), Kleibacker (2001), McCutcheon (2003), Wells and others (2009), Chan and others (2012), and Wells and others (in press) for subsequent interpretations of the Willapa Hills geology.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141063","collaboration":"Prepared in cooperation with the State of Washington Department of Natural Resources, Division of Geology and Earth Resources","usgsCitation":"Wells, R., and Sawlan, M.G., 2014, Preliminary geologic map of the eastern Willapa Hills, Cowlitz, Lewis, and Wahkiakum Counties, Washington: U.S. Geological Survey Open-File Report 2014-1063, 2 Sheets: 33.36 x 51.01 inches and 31.54 and 33.49 inches; Database; Shape Files; Metadata, https://doi.org/10.3133/ofr20141063.","productDescription":"2 Sheets: 33.36 x 51.01 inches and 31.54 and 33.49 inches; Database; Shape Files; Metadata","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-053867","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":291508,"rank":6,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/of/2014/1063/downloads/ofr2014-1063_shp.zip"},{"id":291506,"rank":5,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2014/1063/pdf/ofr2014-1063_sheet2.pdf"},{"id":291510,"rank":7,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141063.jpg"},{"id":398954,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_100480.htm"},{"id":291501,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1063/"},{"id":291505,"rank":4,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2014/1063/pdf/ofr2014-1063_sheet1.pdf"},{"id":291509,"rank":3,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/of/2014/1063/downloads/metadata/"},{"id":291507,"rank":1,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/of/2014/1063/downloads/ofr2014-1063_db.zip"}],"scale":"50000","projection":"Universal Transverse Mercator projection","country":"United States","state":"Washington","county":"Cowlitz County, Lewis County, Wahkiakum County","otherGeospatial":"Willapa Hills","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -123.5,46.1425 ], [ -123.5,46.636944 ], [ -123.0,46.636944 ], [ -123.0,46.1425 ], [ -123.5,46.1425 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53dc9bafe4b076157862d964","contributors":{"authors":[{"text":"Wells, Ray E. 0000-0002-7796-0160 rwells@usgs.gov","orcid":"https://orcid.org/0000-0002-7796-0160","contributorId":2692,"corporation":false,"usgs":true,"family":"Wells","given":"Ray E.","email":"rwells@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":false,"id":491973,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sawlan, Michael G. 0000-0003-0637-2051 msawlan@usgs.gov","orcid":"https://orcid.org/0000-0003-0637-2051","contributorId":2291,"corporation":false,"usgs":true,"family":"Sawlan","given":"Michael","email":"msawlan@usgs.gov","middleInitial":"G.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":491972,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70120181,"text":"70120181 - 2014 - Time-averaged discharge rate of subaerial lava at Kīlauea Volcano, Hawai‘i, measured from TanDEM-X interferometry: Implications for magma supply and storage during 2011-2013","interactions":[],"lastModifiedDate":"2019-03-13T15:06:08","indexId":"70120181","displayToPublicDate":"2014-08-01T08:51:24","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2314,"text":"Journal of Geophysical Research B: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Time-averaged discharge rate of subaerial lava at Kīlauea Volcano, Hawai‘i, measured from TanDEM-X interferometry: Implications for magma supply and storage during 2011-2013","docAbstract":"

Differencing digital elevation models (DEMs) derived from TerraSAR add-on for Digital Elevation Measurements (TanDEM-X) synthetic aperture radar imagery provides a measurement of elevation change over time. On the East Rift Zone (EZR) of Kīlauea Volcano, Hawai‘i, the effusion of lava causes changes in topography. When these elevation changes are summed over the area of an active lava flow, it is possible to quantify the volume of lava emplaced at the surface during the time spanned by the TanDEM-X data—a parameter that can be difficult to measure across the entirety of an ~100 km2 lava flow field using ground-based techniques or optical remote sensing data. Based on the differences between multiple TanDEM-X-derived DEMs collected days to weeks apart, the mean dense-rock equivalent time-averaged discharge rate of lava at Kīlauea between mid-2011 and mid-2013 was approximately 2 m3/s, which is about half the long-term average rate over the course of Kīlauea's 1983–present ERZ eruption. This result implies that there was an increase in the proportion of lava stored versus erupted, a decrease in the rate of magma supply to the volcano, or some combination of both during this time period. In addition to constraining the time-averaged discharge rate of lava and the rates of magma supply and storage, topographic change maps derived from space-based TanDEM-X data provide insights into the four-dimensional evolution of Kīlauea's ERZ lava flow field. TanDEM-X data are a valuable complement to other space-, air-, and ground-based observations of eruptive activity at Kīlauea and offer great promise at locations around the world for aiding with monitoring not just volcanic eruptions but any hazardous activity that results in surface change, including landslides, floods, earthquakes, and other natural and anthropogenic processes.

","language":"English","publisher":"American Geophysical Union","publisherLocation":"Richmond, VA","doi":"10.1002/2014JB011132","usgsCitation":"Poland, M., 2014, Time-averaged discharge rate of subaerial lava at Kīlauea Volcano, Hawai‘i, measured from TanDEM-X interferometry: Implications for magma supply and storage during 2011-2013: Journal of Geophysical Research B: Solid Earth, v. 119, no. 7, p. 5464-5481, https://doi.org/10.1002/2014JB011132.","productDescription":"18 p.","startPage":"5464","endPage":"5481","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-055642","costCenters":[{"id":336,"text":"Hawaiian Volcano Observatory","active":false,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":292052,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawai'i","otherGeospatial":"Kilauea Volcano","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -155.303007,19.410477 ], [ -155.303007,19.431523 ], [ -155.270993,19.431523 ], [ -155.270993,19.410477 ], [ -155.303007,19.410477 ] ] ] } } ] }","volume":"119","issue":"7","noUsgsAuthors":false,"publicationDate":"2014-07-29","publicationStatus":"PW","scienceBaseUri":"53ec7bd4e4b02bf5a76740c0","contributors":{"authors":[{"text":"Poland, Michael P. 0000-0001-5240-6123 mpoland@usgs.gov","orcid":"https://orcid.org/0000-0001-5240-6123","contributorId":635,"corporation":false,"usgs":true,"family":"Poland","given":"Michael P.","email":"mpoland@usgs.gov","affiliations":[{"id":336,"text":"Hawaiian Volcano Observatory","active":false,"usgs":true}],"preferred":false,"id":497965,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70118564,"text":"ofr20141165 - 2014 - A hierarchical integrated population model for greater sage-grouse (Centrocercus urophasianus) in the Bi-State Distinct Population Segment, California and Nevada","interactions":[],"lastModifiedDate":"2014-08-01T09:36:09","indexId":"ofr20141165","displayToPublicDate":"2014-08-01T08:36:00","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":"2014-1165","title":"A hierarchical integrated population model for greater sage-grouse (Centrocercus urophasianus) in the Bi-State Distinct Population Segment, California and Nevada","docAbstract":"

Greater sage-grouse (Centrocercus urophasianus, hereafter referred to as “sage-grouse”) are endemic to sagebrush (Artemisia spp.) ecosystems throughout Western North America. Populations of sage-grouse have declined in distribution and abundance across the range of the species (Schroeder and others, 2004; Knick and Connelly, 2011), largely as a result of human disruption of sagebrush communities (Knick and Connelly, 2011). The Bi-State Distinct Population Segment (DPS) represents sage-grouse populations that are geographically isolated and genetically distinct (Benedict and others, 2003; Oyler-McCance and others, 2005) and that are present at the extreme southwestern distribution of the sage-grouse range (Schroeder and others, 2004), straddling the border of California and Nevada. Subpopulations of sage-grouse in the DPS may be at increased risk of extirpation because of a substantial loss of sagebrush habitat and lack of connectivity (Oyler-McCance and others, 2005). Sage-grouse in the Bi-State DPS represent small, localized breeding populations distributed across 18,325 km2.

\n
\n

The U.S. Fish and Wildlife Service currently (2014) is evaluating the Bi-State DPS as threatened or endangered under the Endangered Species Act of 1973, independent of other sage-grouse populations. This DPS was designated as a higher priority for listing than sage-grouse in other parts of the species’ range (U.S. Department of the Interior, 2010). Range-wide population analyses for sage-grouse have included portions of the Bi-State DPS (Sage and Columbian Sharp-tailed Grouse Technical Committee 2008; Garton and others, 2011). Although these analyses are informative, the underlying data only represent a portion of the DPS and are comprised of lek count observations only. A thorough examination of population dynamics and persistence that includes multiple subpopulations and represents the majority of the DPS is largely lacking. Furthermore, fundamental information on population growth rate (i.e., finite rate of change, λ) and specific demographic parameters that explain sources of variation in λ within different subpopulations would be valuable for making conservation and management decisions for this DPS.

\n
\n

During 2003–12, agencies and universities collaborated to conduct extensive monitoring of sage-grouse populations within the Bi-State DPS. Data regarding lek attendance, movement, and survival of sage-grouse across multiple life stages were documented. Specifically, sage-grouse from nearly all subpopulations were marked and tracked across multiple seasons using radio-telemetry techniques. A hierarchical integrated population modeling (IPM) approach was used to derive demographic parameters for the Bi-State DPS using the large amount of data collected over a 10-year period. This modeling approach allows integration of multiple data sources to inform population growth rates and population vital rates for the Bi-State DPS overall, as well as for individual subpopulations. These models are more informative than other models because they integrate inputs of demographic data (for example, survival and fecundity rates) and survey data (for example, lek observations). The findings here will help characterize population growth rates within the Bi-State DPS.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141165","collaboration":"Prepared in cooperation with the Bureau of Land Management, Nevada Department of Wildlife, and U.S. Fish and Wildlife Service","usgsCitation":"Coates, P.S., Halstead, B., Blomberg, E.J., Brussee, B., Howe, K., Wiechman, L., Tebbenkamp, J., Reese, K.P., Gardner, S., and Casazza, M.L., 2014, A hierarchical integrated population model for greater sage-grouse (Centrocercus urophasianus) in the Bi-State Distinct Population Segment, California and Nevada: U.S. Geological Survey Open-File Report 2014-1165, iv, 34 p., https://doi.org/10.3133/ofr20141165.","productDescription":"iv, 34 p.","numberOfPages":"42","onlineOnly":"Y","ipdsId":"IP-057936","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":291511,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141165.jpg"},{"id":291500,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1165/"},{"id":291504,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1165/pdf/ofr2014-1165.pdf"}],"country":"United States","state":"California;Nevada","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.41,32.39 ], [ -124.41,42.01 ], [ -113.96,42.01 ], [ -113.96,32.39 ], [ -124.41,32.39 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53dc9baee4b076157862d957","contributors":{"authors":[{"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":497039,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Halstead, Brian J. 0000-0002-5535-6528 bhalstead@usgs.gov","orcid":"https://orcid.org/0000-0002-5535-6528","contributorId":3051,"corporation":false,"usgs":true,"family":"Halstead","given":"Brian J.","email":"bhalstead@usgs.gov","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":497038,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Blomberg, Erik J.","contributorId":17543,"corporation":false,"usgs":false,"family":"Blomberg","given":"Erik","email":"","middleInitial":"J.","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":497040,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brussee, Brianne","contributorId":62152,"corporation":false,"usgs":true,"family":"Brussee","given":"Brianne","affiliations":[],"preferred":false,"id":497043,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Howe, Kristy B.","contributorId":59354,"corporation":false,"usgs":true,"family":"Howe","given":"Kristy B.","affiliations":[],"preferred":false,"id":497042,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wiechman, Lief","contributorId":108039,"corporation":false,"usgs":true,"family":"Wiechman","given":"Lief","affiliations":[],"preferred":false,"id":497046,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Tebbenkamp, Joel","contributorId":25089,"corporation":false,"usgs":true,"family":"Tebbenkamp","given":"Joel","email":"","affiliations":[],"preferred":false,"id":497041,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Reese, Kerry P.","contributorId":70254,"corporation":false,"usgs":true,"family":"Reese","given":"Kerry","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":497044,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Gardner, Scott C.","contributorId":80206,"corporation":false,"usgs":true,"family":"Gardner","given":"Scott C.","affiliations":[],"preferred":false,"id":497045,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"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":497037,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70118141,"text":"ofr20141163 - 2014 - Spatially explicit modeling of greater sage-grouse (Centrocercus urophasianus) habitat in Nevada and northeastern California: a decision-support tool for management","interactions":[],"lastModifiedDate":"2014-08-01T08:43:10","indexId":"ofr20141163","displayToPublicDate":"2014-08-01T08:22:00","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":"2014-1163","title":"Spatially explicit modeling of greater sage-grouse (Centrocercus urophasianus) habitat in Nevada and northeastern California: a decision-support tool for management","docAbstract":"Greater sage-grouse (Centrocercus urophasianus, hereafter referred to as “sage-grouse”) populations are declining throughout the sagebrush (Artemisia spp.) ecosystem, including millions of acres of potential habitat across the West. Habitat maps derived from empirical data are needed given impending listing decisions that will affect both sage-grouse population dynamics and human land-use restrictions. This report presents the process for developing spatially explicit maps describing relative habitat suitability for sage-grouse in Nevada and northeastern California. Maps depicting habitat suitability indices (HSI) values were generated based on model-averaged resource selection functions informed by more than 31,000 independent telemetry locations from more than 1,500 radio-marked sage-grouse across 12 project areas in Nevada and northeastern California collected during a 15-year period (1998–2013). Modeled habitat covariates included land cover composition, water resources, habitat configuration, elevation, and topography, each at multiple spatial scales that were relevant to empirically observed sage-grouse movement patterns. We then present an example of how the HSI can be delineated into categories. Specifically, we demonstrate that the deviation from the mean can be used to classify habitat suitability into three categories of habitat quality (high, moderate, and low) and one non-habitat category. The classification resulted in an agreement of 93–97 percent for habitat versus non-habitat across a suite of independent validation datasets. Lastly, we provide an example of how space use models can be integrated with habitat models to help inform conservation planning. In this example, we combined probabilistic breeding density with a non-linear probability of occurrence relative to distance to nearest lek (traditional breeding ground) using count data to calculate a composite space use index (SUI). The SUI was then classified into two categories of use (high and low-to-no) and intersected with the HSI categories to create potential management prioritization scenarios based oninformation about sage-grouse occupancy coupled with habitat suitability. This provided an example of a conservation planning application that uses the intersection of the spatially-explicit HSI and empirically-based SUI to identify potential spatially explicit strategies for sage-grouse management. Importantly, the reported categories for the HSI and SUI can be reclassified relatively easily to employ alternative conservation thresholds that may be identified through decision-making processes with stake-holders, managers, and biologists. Moreover, the HSI/SUI interface map can be updated readily as new data become available.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141163","collaboration":"Prepared in cooperation with the State of Nevada Sagebrush Ecosystem Program, Bureau of Land Management, Nevada Department of Wildlife, and California Department of Fish and Wildlife","usgsCitation":"Coates, P.S., Casazza, M.L., Brussee, B.E., Ricca, M., Gustafson, K., Overton, C.T., Sanchez-Chopitea, E., Kroger, T., Mauch, K., Niell, L., Howe, K., Gardner, S., Espinosa, S., and Delehanty, D.J., 2014, Spatially explicit modeling of greater sage-grouse (Centrocercus urophasianus) habitat in Nevada and northeastern California: a decision-support tool for management: U.S. Geological Survey Open-File Report 2014-1163, vi, 83 p., https://doi.org/10.3133/ofr20141163.","productDescription":"vi, 83 p.","numberOfPages":"93","onlineOnly":"Y","ipdsId":"IP-058087","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":438749,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P99E64Y4","text":"USGS data release","linkHelpText":"Spatially Explicit Modeling of Annual and Seasonal Habitat for Greater Sage-Grouse (Centrocercus urophasianus) in Northeastern California"},{"id":291503,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141163.jpg"},{"id":291499,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1163/"},{"id":291502,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1163/pdf/ofr2014-1163.pdf"}],"country":"United States","state":"California;Nevada","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.0,35.0 ], [ -122.0,42.0 ], [ -114.04,42.0 ], [ -114.04,35.0 ], [ -122.0,35.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53dc9bafe4b076157862d968","contributors":{"authors":[{"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":496455,"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":496453,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brussee, Brianne E. 0000-0002-2452-7101 bbrussee@usgs.gov","orcid":"https://orcid.org/0000-0002-2452-7101","contributorId":4249,"corporation":false,"usgs":true,"family":"Brussee","given":"Brianne","email":"bbrussee@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":496456,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ricca, Mark A.","contributorId":39736,"corporation":false,"usgs":true,"family":"Ricca","given":"Mark A.","affiliations":[],"preferred":false,"id":496461,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gustafson, K. Benjamin","contributorId":53710,"corporation":false,"usgs":true,"family":"Gustafson","given":"K. Benjamin","affiliations":[],"preferred":false,"id":496462,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Overton, Cory T. 0000-0002-5060-7447 coverton@usgs.gov","orcid":"https://orcid.org/0000-0002-5060-7447","contributorId":3262,"corporation":false,"usgs":true,"family":"Overton","given":"Cory","email":"coverton@usgs.gov","middleInitial":"T.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":496454,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sanchez-Chopitea, Erika","contributorId":23462,"corporation":false,"usgs":true,"family":"Sanchez-Chopitea","given":"Erika","affiliations":[],"preferred":false,"id":496458,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kroger, Travis","contributorId":38483,"corporation":false,"usgs":true,"family":"Kroger","given":"Travis","affiliations":[],"preferred":false,"id":496460,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Mauch, Kimberly","contributorId":91796,"corporation":false,"usgs":true,"family":"Mauch","given":"Kimberly","affiliations":[],"preferred":false,"id":496466,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Niell, Lara","contributorId":30557,"corporation":false,"usgs":true,"family":"Niell","given":"Lara","affiliations":[],"preferred":false,"id":496459,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Howe, Kristy","contributorId":79815,"corporation":false,"usgs":true,"family":"Howe","given":"Kristy","affiliations":[],"preferred":false,"id":496463,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Gardner, Scott","contributorId":82627,"corporation":false,"usgs":true,"family":"Gardner","given":"Scott","affiliations":[],"preferred":false,"id":496465,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Espinosa, Shawn","contributorId":20253,"corporation":false,"usgs":true,"family":"Espinosa","given":"Shawn","affiliations":[],"preferred":false,"id":496457,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Delehanty, David J.","contributorId":80811,"corporation":false,"usgs":true,"family":"Delehanty","given":"David","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":496464,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}} ,{"id":70041762,"text":"70041762 - 2014 - Drift issues of tall buildings during the March 11, 2011 M9.0 Tohoku earthquake, Japan - Implications","interactions":[],"lastModifiedDate":"2016-04-25T17:53:19","indexId":"70041762","displayToPublicDate":"2014-08-01T03:45:00","publicationYear":"2014","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"title":"Drift issues of tall buildings during the March 11, 2011 M9.0 Tohoku earthquake, Japan - Implications","docAbstract":"
\n

One of the most significant effects of the M9.0 Tohoku, Japan earthquake of March 11, 2011 is the now well-known long duration (>10 minutes) shaking of buildings in Japan – particularly those in Tokyo (~350-375 km from the epicenter) and in places as far as Osaka (~770 km from the epicenter). Although none collapsed, the strong shaking caused many tall buildings not to be functional for days and weeks.

\n

The purpose of this paper is to discuss the behavior and performance of four tall buildings, considered to be representative of most tall buildings in Tokyo and other locations, and from which shaking data were retrieved. Of particular interest is a building in Osaka that almost reached an average of 0.5% drift ratio – this, with a ground level input motion of ~3% g is significant. What might have happened during an event with input level motions with similar low frequency content and in 10-20% g range is a legitimate question that must be pondered. The particular building had serious site effects and was in resonance.

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The other three examples are from Tokyo. For example, based on records obtained from a 54-story building retrofitted with 288 oil dampers on 24 floors, computations show that average drift ratio may have reached ~0.3% and maximum drift ratio likely was > .3%. The maximum allowed by Japanese practice for buildings taller than 60 m and for collapse protection (level 2) motions is 1% (The Building Center of Japan, 2001).

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Performances of tall buildings in many seismically active regions of the world (e.g. Chile, Turkey) or those tall buildings affected by long distance long period effects by sources at a distance (e.g. Abu Dhabi, Dubai) are of interest to the earthquake engineering community. Chile imposes 0.2 % drift limit that result in elastic design. USA and Turkey impose 2% drift limit. Such wide variations of drift limits in design practices deserve discussion in light of functionality and performance of tall buildings during the 2011 Tohoku event.

\n

 

\n
","conferenceTitle":"Tenth U.S. national conference on earthquake engineering: Frontiers of earthquake engineering","conferenceDate":"July 21-25, 2014","conferenceLocation":"Anchorage, Alaska","language":"English","doi":"10.4231/D3930NV9C","usgsCitation":"Çelebi, M., and Okawa, I., 2014, Drift issues of tall buildings during the March 11, 2011 M9.0 Tohoku earthquake, Japan - Implications, Tenth U.S. national conference on earthquake engineering: Frontiers of earthquake engineering, Anchorage, Alaska, July 21-25, 2014, 11 p., https://doi.org/10.4231/D3930NV9C.","productDescription":"11 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-042447","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":320540,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"571f3fb6e4b071321fe56a1e","contributors":{"authors":[{"text":"Çelebi, Mehmet 0000-0002-4769-7357 celebi@usgs.gov","orcid":"https://orcid.org/0000-0002-4769-7357","contributorId":3205,"corporation":false,"usgs":true,"family":"Çelebi","given":"Mehmet","email":"celebi@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":false,"id":627642,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Okawa, Izuru","contributorId":168900,"corporation":false,"usgs":true,"family":"Okawa","given":"Izuru","email":"","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":false,"id":627643,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70135874,"text":"70135874 - 2014 - Causal networks clarify productivity-richness interrelations, bivariate plots do not","interactions":[],"lastModifiedDate":"2014-12-18T11:33:46","indexId":"70135874","displayToPublicDate":"2014-08-01T01:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1711,"text":"Functional Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Causal networks clarify productivity-richness interrelations, bivariate plots do not","docAbstract":"
    \n
  1. Perhaps no other pair of variables in ecology has generated as much discussion as species richness and ecosystem productivity, as illustrated by the reactions by Pierce (2013) and others to Adler et al.'s (2011) report that empirical patterns are weak and inconsistent. Adler et al. (2011) argued we need to move beyond a focus on simplistic bivariate relationships and test mechanistic, multivariate causal hypotheses. We feel the continuing debate over productivity–richness relationships (PRRs) provides a focused context for illustrating the fundamental difficulties of using bivariate relationships to gain scientific understanding.
    2. \n
  2. Pierce (2013) disputes Adler et al.'s (2011) conclusion that bivariate productivity–richness relationships (PRRs) are ‘weak and variable’. He argues, instead, that relationships in the Adler et al. data are actually strong and, further, that failure to adhere to the humped-back model (HBM; sensu Grime 1979) threatens scientists' ability to advise conservationists. Here, we show that Pierce's reanalyses are invalid, that statistically significant boundary relations in the Adler et al. data are difficult to detect when proper methods are used and that his advice neither advances scientific understanding nor provides the quantitative forecasts actually needed by decision makers.
    3. \n
  3. We begin by examining Grimes' HBM through the lens of causal networks. We first translate the ideas contained in the HBM into a causal diagram, which shows explicitly how multiple processes are hypothesized to control biomass production and richness and their interrelationship. We then evaluate the causal diagram using structural equation modelling and example data from a published study of meadows in Finland. Formal analysis rejects the literal translation of the HBM and reveals additional processes at work. This exercise shows how the practice of abstracting systems as causal networks (i) clarifies possible hypotheses, (ii) permits explicit testing and (iii) provides more powerful and useful predictions.
    4. \n
  4. Building on the Finnish meadow example, we contrast the utility of bivariate plots compared with structural equation models for investigating underlying processes. Simulations illustrate the fallibility of bivariate analysis as a means of supporting one theory over another, while models based on causal networks can quantify the sensitivity of diversity patterns to both management and natural constraints.
    5. \n
  5. A key piece of Pierce's critique of Adler et al.'s conclusions relies on upper boundary regression which he claims to reveal strong relationships between production and richness in Adler et al.'s original data. We demonstrate that this technique shows strong associations in purely random data and is invalid for Adler et al.'s data because it depends on a uniform data distribution. We instead perform quantile regression on both the site-level summaries of the data and the plot-level data (using mixed-model quantile regression). Using a variety of nonlinear curve-fitting approaches, we were unable to detect a significant humped-shape boundary in the Adler et al. data. We reiterate that the bivariate productivity–richness relationships in Adler et al.'s data are weak and variable.
    6. \n
  6. We urge ecologists to consider productivity–richness relationships through the lens of causal networks to advance our understanding beyond bivariate analysis. Further, we emphasize that models based on a causal network conceptualization can also provide more meaningful guidance for conservation management than can a bivariate perspective. Measuring only two variables does not permit the evaluation of complex ideas nor resolve debates about underlying mechanisms.
    7. \n
","language":"English","publisher":"Wiley-Blackwell Publishing Ltd.","doi":"10.1111/1365-2435.12269","usgsCitation":"Grace, J.B., Adler, P.B., Harpole, W.S., Borer, E.T., and Seabloom, E.W., 2014, Causal networks clarify productivity-richness interrelations, bivariate plots do not: Functional Ecology, v. 28, no. 4, p. 787-798, https://doi.org/10.1111/1365-2435.12269.","productDescription":"12 p.","startPage":"787","endPage":"798","numberOfPages":"12","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-052277","costCenters":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"links":[{"id":472842,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2435.12269","text":"Publisher Index Page"},{"id":296792,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"28","issue":"4","noUsgsAuthors":false,"publicationDate":"2014-03-24","publicationStatus":"PW","scienceBaseUri":"54dd2b4ee4b08de9379b3309","contributors":{"authors":[{"text":"Grace, James B. 0000-0001-6374-4726 gracej@usgs.gov","orcid":"https://orcid.org/0000-0001-6374-4726","contributorId":884,"corporation":false,"usgs":true,"family":"Grace","given":"James","email":"gracej@usgs.gov","middleInitial":"B.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":536955,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Adler, Peter B.","contributorId":64789,"corporation":false,"usgs":false,"family":"Adler","given":"Peter","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":536956,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Harpole, W. Stanley","contributorId":131024,"corporation":false,"usgs":false,"family":"Harpole","given":"W.","email":"","middleInitial":"Stanley","affiliations":[{"id":6911,"text":"Iowa State University","active":true,"usgs":false}],"preferred":false,"id":536957,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Borer, Elizabeth T.","contributorId":45049,"corporation":false,"usgs":false,"family":"Borer","given":"Elizabeth","email":"","middleInitial":"T.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":536958,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Seabloom, Eric W.","contributorId":60762,"corporation":false,"usgs":false,"family":"Seabloom","given":"Eric","email":"","middleInitial":"W.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":536959,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70189781,"text":"70189781 - 2014 - Comparison of NGA-West2 directivity models","interactions":[],"lastModifiedDate":"2017-07-26T11:05:01","indexId":"70189781","displayToPublicDate":"2014-08-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1436,"text":"Earthquake Spectra","active":true,"publicationSubtype":{"id":10}},"title":"Comparison of NGA-West2 directivity models","docAbstract":"

Five directivity models have been developed based on data from the NGA-West2 database and based on numerical simulations of large strike-slip and reverse-slip earthquakes. All models avoid the use of normalized rupture dimension, enabling them to scale up to the largest earthquakes in a physically reasonable way. Four of the five models are explicitly “narrow-band” (in which the effect of directivity is maximum at a specific period that is a function of earthquake magnitude). Several strategies for determining the zero-level for directivity have been developed. We show comparisons of maps of the directivity amplification. This comparison suggests that the predicted geographic distributions of directivity amplification are dominated by effects of the models' assumptions, and more than one model should be used for ruptures dipping less than about 65 degrees.

","language":"English","publisher":"Earthquake Engineering Research Institute","doi":"10.1193/080313EQS222M","usgsCitation":"Spudich, P.A., Rowshandel, B., Shahi, S., Baker, J.W., and Chiou, B.S., 2014, Comparison of NGA-West2 directivity models: Earthquake Spectra, v. 30, no. 3, p. 1199-1221, https://doi.org/10.1193/080313EQS222M.","productDescription":"23 p.","startPage":"1199","endPage":"1221","ipdsId":"IP-054577","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":344322,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"30","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2014-08-01","publicationStatus":"PW","scienceBaseUri":"5979aa57e4b0ec1a488b8c29","contributors":{"authors":[{"text":"Spudich, Paul A. 0000-0002-9484-4997 spudich@usgs.gov","orcid":"https://orcid.org/0000-0002-9484-4997","contributorId":2372,"corporation":false,"usgs":true,"family":"Spudich","given":"Paul","email":"spudich@usgs.gov","middleInitial":"A.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":706325,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rowshandel, Badie","contributorId":140541,"corporation":false,"usgs":false,"family":"Rowshandel","given":"Badie","email":"","affiliations":[],"preferred":false,"id":706326,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shahi, Shrey","contributorId":140542,"corporation":false,"usgs":false,"family":"Shahi","given":"Shrey","email":"","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":706327,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Baker, Jack W.","contributorId":115861,"corporation":false,"usgs":false,"family":"Baker","given":"Jack","email":"","middleInitial":"W.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":706328,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chiou, Brian S-J","contributorId":195134,"corporation":false,"usgs":false,"family":"Chiou","given":"Brian","email":"","middleInitial":"S-J","affiliations":[],"preferred":false,"id":706329,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70147644,"text":"70147644 - 2014 - Pharmacokinetics of buprenorphine hydrochloride following intramuscular and intravenous administration to American kestrels (Falco sparverius)","interactions":[],"lastModifiedDate":"2018-02-06T12:42:45","indexId":"70147644","displayToPublicDate":"2014-08-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":734,"text":"American Journal of Veterinary Research","active":true,"publicationSubtype":{"id":10}},"title":"Pharmacokinetics of buprenorphine hydrochloride following intramuscular and intravenous administration to American kestrels (Falco sparverius)","docAbstract":"

Objective—To determine the pharmacokinetics of buprenorphine hydrochloride after IM and IV administration to American kestrels (Falco sparverius).

\n

Animals—13 healthy 3-year-old captive-bred American kestrels.

\n

Procedures—Buprenorphine hydrochloride (0.6 mg/kg) was administered IM to all birds. Blood samples were collected at 9 times, ranging from 5 minutes to 9 hours after drug administration. Plasma buprenorphine concentrations were measured by use of tandem liquid chromatography–mass spectrometry. Pharmacokinetic parameters were determined by use of least squares linear regression and noncompartmental analysis of naïve pooled data. After a washout period of 2 weeks, the same dose of buprenorphine was administered IV to all birds and blood samples were collected at the same times after drug administration.

\n

Results—Maximum plasma buprenorphine concentration was achieved within 5 minutes after IM administration. For IM administration, bioavailability was 94.8% and elimination half-life was 92.1 minutes. For IV administration, steady-state volume of distribution was 4,023.8 mL/kg, plasma clearance was 49.2 mL/min/kg, and elimination half-life was 105.5 minutes.

\n

Conclusions and Clinical Relevance—Buprenorphine was rapidly absorbed, and bioavailability was good after IM administration to American kestrels. Plasma buprenorphine concentrations were > 1 ng/mL for 9 hours after both IM and IV administration. These results, in combination with those of a pharmacodynamic study, suggested that the analgesic effects of buprenorphine could last at least 6 to 9 hours in this species. Further investigations of the duration of analgesic effects, multiple-dose protocols, and potential adverse effects of buprenorphine are warranted in American kestrels and other raptors.

","language":"English","publisher":"American Veterinary Medical Association","doi":"10.2460/ajvr.75.8.711","usgsCitation":"Gustavsen, K.A., Guzman, D., Knych, H.K., Petritz, O.A., Olsen, G.H., and Paul-Murphy, J.R., 2014, Pharmacokinetics of buprenorphine hydrochloride following intramuscular and intravenous administration to American kestrels (Falco sparverius): American Journal of Veterinary Research, v. 75, no. 8, p. 711-715, https://doi.org/10.2460/ajvr.75.8.711.","productDescription":"5 p.","startPage":"711","endPage":"715","numberOfPages":"5","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060182","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":472847,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2460/ajvr.75.8.711","text":"Publisher Index Page"},{"id":300126,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"75","issue":"8","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"554b3b38e4b082ec5412718e","contributors":{"authors":[{"text":"Gustavsen, Kate A.","contributorId":140581,"corporation":false,"usgs":false,"family":"Gustavsen","given":"Kate","email":"","middleInitial":"A.","affiliations":[{"id":13536,"text":"University of California, School of Veterinary Medicine, Davis, California","active":true,"usgs":false}],"preferred":false,"id":546222,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Guzman, David Sanchez-Migallon","contributorId":138651,"corporation":false,"usgs":false,"family":"Guzman","given":"David Sanchez-Migallon","affiliations":[{"id":12476,"text":"Veterinary Teaching Hopsital, School of Veterinary Medicine, University of California, Davis CA","active":true,"usgs":false}],"preferred":false,"id":546223,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Knych, Heather K.","contributorId":140582,"corporation":false,"usgs":false,"family":"Knych","given":"Heather","email":"","middleInitial":"K.","affiliations":[{"id":13537,"text":"KL Maddy Equine Analytical Chemistry Laboratory, School of Veterinary Medicine, University of California, Davis, California","active":true,"usgs":false}],"preferred":false,"id":546224,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Petritz, Olivia A.","contributorId":140583,"corporation":false,"usgs":false,"family":"Petritz","given":"Olivia","email":"","middleInitial":"A.","affiliations":[{"id":13536,"text":"University of California, School of Veterinary Medicine, Davis, California","active":true,"usgs":false}],"preferred":false,"id":546225,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Olsen, Glenn H. 0000-0002-7188-6203 golsen@usgs.gov","orcid":"https://orcid.org/0000-0002-7188-6203","contributorId":40918,"corporation":false,"usgs":true,"family":"Olsen","given":"Glenn","email":"golsen@usgs.gov","middleInitial":"H.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":546221,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Paul-Murphy, Joanne R.","contributorId":138654,"corporation":false,"usgs":false,"family":"Paul-Murphy","given":"Joanne","email":"","middleInitial":"R.","affiliations":[{"id":12479,"text":"Department of Medicine and Epidemiology, School of Veterinary Medicine, University of California, Davis, DA","active":true,"usgs":false}],"preferred":false,"id":546226,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70133239,"text":"70133239 - 2014 - Hierarchical model analysis of the Atlantic Flyway Breeding Waterfowl Survey","interactions":[],"lastModifiedDate":"2014-11-14T13:19:24","indexId":"70133239","displayToPublicDate":"2014-08-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Hierarchical model analysis of the Atlantic Flyway Breeding Waterfowl Survey","docAbstract":"

We used log-linear hierarchical models to analyze data from the Atlantic Flyway Breeding Waterfowl Survey. The survey has been conducted by state biologists each year since 1989 in the northeastern United States from Virginia north to New Hampshire and Vermont. Although yearly population estimates from the survey are used by the United States Fish and Wildlife Service for estimating regional waterfowl population status for mallards (Anas platyrhynchos), black ducks (Anas rubripes), wood ducks (Aix sponsa), and Canada geese (Branta canadensis), they are not routinely adjusted to control for time of day effects and other survey design issues. The hierarchical model analysis permits estimation of year effects and population change while accommodating the repeated sampling of plots and controlling for time of day effects in counting. We compared population estimates from the current stratified random sample analysis to population estimates from hierarchical models with alternative model structures that describe year to year changes as random year effects, a trend with random year effects, or year effects modeled as 1-year differences. Patterns of population change from the hierarchical model results generally were similar to the patterns described by stratified random sample estimates, but significant visibility differences occurred between twilight to midday counts in all species. Controlling for the effects of time of day resulted in larger population estimates for all species in the hierarchical model analysis relative to the stratified random sample analysis. The hierarchical models also provided a convenient means of estimating population trend as derived statistics from the analysis. We detected significant declines in mallard and American black ducks and significant increases in wood ducks and Canada geese, a trend that had not been significant for 3 of these 4 species in the prior analysis. We recommend using hierarchical models for analysis of the Atlantic Flyway Breeding Waterfowl Survey.

","language":"English","publisher":"Wiley","doi":"10.1002/jwmg.748","usgsCitation":"Sauer, J., Zimmerman, G.S., Klimstra, J.D., and Link, W., 2014, Hierarchical model analysis of the Atlantic Flyway Breeding Waterfowl Survey: Journal of Wildlife Management, v. 78, no. 6, p. 1050-1059, https://doi.org/10.1002/jwmg.748.","productDescription":"10 p.","startPage":"1050","endPage":"1059","numberOfPages":"10","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056345","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":296095,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"78","issue":"6","noUsgsAuthors":false,"publicationDate":"2014-07-16","publicationStatus":"PW","scienceBaseUri":"546727b7e4b04d4b7dbde84d","contributors":{"authors":[{"text":"Sauer, John R. jrsauer@usgs.gov","contributorId":3737,"corporation":false,"usgs":true,"family":"Sauer","given":"John R.","email":"jrsauer@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":524947,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zimmerman, Guthrie S.","contributorId":42473,"corporation":false,"usgs":false,"family":"Zimmerman","given":"Guthrie","email":"","middleInitial":"S.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":524949,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Klimstra, Jon D.","contributorId":6985,"corporation":false,"usgs":false,"family":"Klimstra","given":"Jon","email":"","middleInitial":"D.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":524950,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Link, William A. wlink@usgs.gov","contributorId":3465,"corporation":false,"usgs":true,"family":"Link","given":"William A.","email":"wlink@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":524948,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70168380,"text":"70168380 - 2014 - Habitat structure and body size distributions: Cross-ecosystem comparison for taxa with determinate and indeterminate growth","interactions":[],"lastModifiedDate":"2017-02-13T15:02:06","indexId":"70168380","displayToPublicDate":"2014-08-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2939,"text":"Oikos","active":true,"publicationSubtype":{"id":10}},"title":"Habitat structure and body size distributions: Cross-ecosystem comparison for taxa with determinate and indeterminate growth","docAbstract":"

Habitat structure across multiple spatial and temporal scales has been proposed as a key driver of body size distributions for associated communities. Thus, understanding the relationship between habitat and body size is fundamental to developing predictions regarding the influence of habitat change on animal communities. Much of the work assessing the relationship between habitat structure and body size distributions has focused on terrestrial taxa with determinate growth, and has primarily analysed discontinuities (gaps) in the distribution of species mean sizes (species size relationships or SSRs). The suitability of this approach for taxa with indeterminate growth has yet to be determined. We provide a cross-ecosystem comparison of bird (determinate growth) and fish (indeterminate growth) body mass distributions using four independent data sets. We evaluate three size distribution indices: SSRs, species size–density relationships (SSDRs) and individual size–density relationships (ISDRs), and two types of analysis: looking for either discontinuities or abundance patterns and multi-modality in the distributions. To assess the respective suitability of these three indices and two analytical approaches for understanding habitat–size relationships in different ecosystems, we compare their ability to differentiate bird or fish communities found within contrasting habitat conditions. All three indices of body size distribution are useful for examining the relationship between cross-scale patterns of habitat structure and size for species with determinate growth, such as birds. In contrast, for species with indeterminate growth such as fish, the relationship between habitat structure and body size may be masked when using mean summary metrics, and thus individual-level data (ISDRs) are more useful. Furthermore, ISDRs, which have traditionally been used to study aquatic systems, present a potentially useful common currency for comparing body size distributions across terrestrial and aquatic ecosystems.

","language":"English","publisher":"Wiley","doi":"10.1111/oik.01314","usgsCitation":"Nash, K.L., Allen, C.R., Barichievy, C., Nystrom, M., Sundstrom, S.M., and Graham, N.A., 2014, Habitat structure and body size distributions: Cross-ecosystem comparison for taxa with determinate and indeterminate growth: Oikos, v. 123, no. 8, p. 971-983, https://doi.org/10.1111/oik.01314.","productDescription":"13 p.","startPage":"971","endPage":"983","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-054487","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true}],"links":[{"id":488029,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://figshare.com/articles/journal_contribution/Habitat_structure_and_body_size_distributions_cross-ecosystem_comparison_for_taxa_with_determinate_and_indeterminate_growth/22938329","text":"External Repository"},{"id":317957,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"123","issue":"8","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2014-04-10","publicationStatus":"PW","scienceBaseUri":"56bdbec4e4b06458514aeecb","contributors":{"authors":[{"text":"Nash, Kirsty L.","contributorId":40897,"corporation":false,"usgs":true,"family":"Nash","given":"Kirsty","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":619953,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Allen, Craig R. 0000-0001-8655-8272 allencr@usgs.gov","orcid":"https://orcid.org/0000-0001-8655-8272","contributorId":1979,"corporation":false,"usgs":true,"family":"Allen","given":"Craig","email":"allencr@usgs.gov","middleInitial":"R.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":619839,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barichievy, Chris","contributorId":17119,"corporation":false,"usgs":true,"family":"Barichievy","given":"Chris","email":"","affiliations":[],"preferred":false,"id":619954,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nystrom, Magnus","contributorId":36460,"corporation":false,"usgs":true,"family":"Nystrom","given":"Magnus","email":"","affiliations":[],"preferred":false,"id":619955,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sundstrom, Shana M.","contributorId":7159,"corporation":false,"usgs":true,"family":"Sundstrom","given":"Shana","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":619956,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Graham, Nicholas A.J.","contributorId":101990,"corporation":false,"usgs":true,"family":"Graham","given":"Nicholas","email":"","middleInitial":"A.J.","affiliations":[],"preferred":false,"id":619957,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70142549,"text":"70142549 - 2014 - A depth-averaged debris-flow model that includes the effects of evolving dilatancy. I. Physical basis","interactions":[],"lastModifiedDate":"2019-03-11T14:01:21","indexId":"70142549","displayToPublicDate":"2014-08-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3878,"text":"Proceedings of the Royal Society A","active":true,"publicationSubtype":{"id":10}},"title":"A depth-averaged debris-flow model that includes the effects of evolving dilatancy. I. Physical basis","docAbstract":"

To simulate debris-flow behaviour from initiation to deposition, we derive a depth-averaged, two-phase model that combines concepts of critical-state soil mechanics, grain-flow mechanics and fluid mechanics. The model's balance equations describe coupled evolution of the solid volume fraction, m, basal pore-fluid pressure, flow thickness and two components of flow velocity. Basal friction is evaluated using a generalized Coulomb rule, and fluid motion is evaluated in a frame of reference that translates with the velocity of the granular phase, vs. Source terms in each of the depth-averaged balance equations account for the influence of the granular dilation rate, defined as the depth integral of ∇⋅vs. Calculation of the dilation rate involves the effects of an elastic compressibility and an inelastic dilatancy angle proportional to m−meq, where meq is the value of m in equilibrium with the ambient stress state and flow rate. Normalization of the model equations shows that predicted debris-flow behaviour depends principally on the initial value of m−meq and on the ratio of two fundamental timescales. One of these timescales governs downslope debris-flow motion, and the other governs pore-pressure relaxation that modifies Coulomb friction and regulates evolution of m. A companion paper presents a suite of model predictions and tests.

","language":"English","publisher":"The Royal Society","doi":"10.1098/rspa.2013.0819","usgsCitation":"Iverson, R.M., and George, D.L., 2014, A depth-averaged debris-flow model that includes the effects of evolving dilatancy. I. Physical basis: Proceedings of the Royal Society A, v. 471, no. 2170, 31 p., https://doi.org/10.1098/rspa.2013.0819.","productDescription":"31 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-053062","costCenters":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":472849,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1098/rspa.2013.0819","text":"Publisher Index Page"},{"id":298720,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"471","issue":"2170","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2014-10-08","publicationStatus":"PW","scienceBaseUri":"550aa1abe4b02e76d7590bc7","contributors":{"authors":[{"text":"Iverson, Richard M. 0000-0002-7369-3819 riverson@usgs.gov","orcid":"https://orcid.org/0000-0002-7369-3819","contributorId":536,"corporation":false,"usgs":true,"family":"Iverson","given":"Richard","email":"riverson@usgs.gov","middleInitial":"M.","affiliations":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":541954,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"George, David L. 0000-0002-5726-0255 dgeorge@usgs.gov","orcid":"https://orcid.org/0000-0002-5726-0255","contributorId":3120,"corporation":false,"usgs":true,"family":"George","given":"David","email":"dgeorge@usgs.gov","middleInitial":"L.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":541955,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70188034,"text":"70188034 - 2014 - Bringing an ecological view of change to Landsat-based remote sensing","interactions":[],"lastModifiedDate":"2017-05-31T15:11:30","indexId":"70188034","displayToPublicDate":"2014-08-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1701,"text":"Frontiers in Ecology and the Environment","active":true,"publicationSubtype":{"id":10}},"title":"Bringing an ecological view of change to Landsat-based remote sensing","docAbstract":"

When characterizing the processes that shape ecosystems, ecologists increasingly use the unique perspective offered by repeat observations of remotely sensed imagery. However, the concept of change embodied in much of the traditional remote-sensing literature was primarily limited to capturing large or extreme changes occurring in natural systems, omitting many more subtle processes of interest to ecologists. Recent technical advances have led to a fundamental shift toward an ecological view of change. Although this conceptual shift began with coarser-scale global imagery, it has now reached users of Landsat imagery, since these datasets have temporal and spatial characteristics appropriate to many ecological questions. We argue that this ecologically relevant perspective of change allows the novel characterization of important dynamic processes, including disturbances, long-term trends, cyclical functions, and feedbacks, and that these improvements are already facilitating our understanding of critical driving forces, such as climate change, ecological interactions, and economic pressures.

","language":"English","publisher":"Ecological Society of America","doi":"10.1890/130066","usgsCitation":"Kennedy, R., Andrefouet, S., Cohen, W., Gomez, C., Griffiths, P., Hais, M., Healey, S., Helmer, E.H., Hostert, P., Lyons, M., Meigs, G., Pflugmacher, D., Phinn, S., Powell, S., Scarth, P., Susmita, S., Schroeder, T.A., Schneider, A., Sonnenschein, R., Vogelmann, J., Wulder, M.A., and Zhu, Z., 2014, Bringing an ecological view of change to Landsat-based remote sensing: Frontiers in Ecology and the Environment, v. 12, no. 6, p. 339-346, https://doi.org/10.1890/130066.","productDescription":"8 p.","startPage":"339","endPage":"346","ipdsId":"IP-053956","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":341956,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","issue":"6","publishingServiceCenter":{"id":4,"text":"Rolla 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The oceanographic data and numerical circulation modeling results from this study demonstrate that circulation in Agat Bay was strongly driven by winds and waves at longer (>1 day) timescales and by the tides at shorter (<1 day) timescales; near-surface currents in deep water were primarily controlled by the winds, whereas currents on the shallow reef flats were dominated by wave-driven motions. Water-column properties exhibited strong seasonality coupled to the shift from the trade wind to the non-trade wind season. During the dry trade-wind season, waters were cooler and more saline. When the winds shifted to a more variable pattern, waters warmed and became less saline because of a combination of increased thermal insolation from lack of wind forcing and higher rainfall. Turbidity was relatively low in Agat Bay and was similar to levels measured elsewhere along west-central Guam. The numerical circulation modeling results provide insight into the potential paths of buoyant material released from a series of locations along west-central Guam under summer non-trade wind forcing conditions that characterize coral spawning events. This information may be useful in evaluating the potential zones of influence/impact resulting from transport by surface currents of material released from these select locations.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141130","usgsCitation":"Storlazzi, C., Cheriton, O., Lescinski, J.M., and Logan, J., 2014, Coastal circulation and water-column properties in the War in the Pacific National Historical Park, Guam: measurements and modeling of waves, currents, temperature, salinity, and turbidity, April-August 2012: U.S. Geological Survey Open-File Report 2014-1130, vi, 104 p., https://doi.org/10.3133/ofr20141130.","productDescription":"vi, 104 p.","numberOfPages":"112","onlineOnly":"Y","temporalStart":"2012-04-01","temporalEnd":"2012-08-31","ipdsId":"IP-052524","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":291498,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141130.jpg"},{"id":291496,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1130/"},{"id":291497,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1130/pdf/ofr2014-1130.pdf"}],"country":"Guam","otherGeospatial":"Agat Bay;War In The Pacific National Historical Park","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 144.618381,13.229648 ], [ 144.618381,13.654225 ], [ 144.956536,13.654225 ], [ 144.956536,13.229648 ], [ 144.618381,13.229648 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53db4a39e4b0fba533f99624","contributors":{"authors":[{"text":"Storlazzi, Curt D. 0000-0001-8057-4490","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":77889,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt D.","affiliations":[],"preferred":false,"id":495291,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cheriton, Olivia M. 0000-0003-3011-9136","orcid":"https://orcid.org/0000-0003-3011-9136","contributorId":7630,"corporation":false,"usgs":true,"family":"Cheriton","given":"Olivia M.","affiliations":[],"preferred":false,"id":495289,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lescinski, Jamie M.R.","contributorId":93579,"corporation":false,"usgs":true,"family":"Lescinski","given":"Jamie","email":"","middleInitial":"M.R.","affiliations":[],"preferred":false,"id":495292,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Logan, Joshua B.","contributorId":34470,"corporation":false,"usgs":true,"family":"Logan","given":"Joshua B.","affiliations":[],"preferred":false,"id":495290,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70101466,"text":"sir20145041 - 2014 - Synthesis of studies in the fall low-salinity zone of the San Francisco Estuary, September-December 2011","interactions":[],"lastModifiedDate":"2017-10-30T11:26:53","indexId":"sir20145041","displayToPublicDate":"2014-07-31T08:29:00","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":"2014-5041","title":"Synthesis of studies in the fall low-salinity zone of the San Francisco Estuary, September-December 2011","docAbstract":"

In fall 2011, a large-scale investigation (fall low-salinity habitat investigation) was implemented by the Bureau of Reclamation in cooperation with the Interagency Ecological Program to explore hypotheses about the ecological role of low-salinity habitat in the San Francisco Estuary—specifically, hypotheses about the importance of fall low-salinity habitat to the biology of delta smelt Hypomesus transpacificus, a species endemic to the San Francisco Estuary and listed as threatened or endangered under federal and state endangered species legislation. The Interagency Ecological Program is a consortium of 10 agencies that work together to develop a better understanding of the ecology of the Estuary and the effects of the State Water Project and Federal Central Valley Project operations on the physical, chemical, and biological conditions of the San Francisco Estuary. The fall low-salinity habitat investigation constitutes one of the actions stipulated in the Reasonable and Prudent Alternative issued with the 2008 Biological Opinion of the U.S. Fish and Wildlife Service, which called for adaptive management of fall Sacramento-San Joaquin Delta outflow following “wet” and “above normal” water years to alleviate jeopardy to delta smelt and adverse modification of delta smelt critical habitat. The basic hypothesis of the adaptive management of fall low-salinity habitat is that greater outflows move the low-salinity zone (salinity 1–6), an important component of delta smelt habitat, westward and that moving the low-salinity zone westward of its position in the fall of recent years will benefit delta smelt, although the specific mechanisms providing such benefit are uncertain. An adaptive management plan was prepared to guide implementation of the adaptive management of fall low-salinity habitat and to reduce uncertainty.

\n
\n

This report has three major objectives:
\n• To provide a summary of the results from the first year of coordinated fall low-salinity habitat studies and monitoring.
\n• To provide a synthesis of the results of the fall low-salinity habitat studies and other ongoing research and monitoring, to determine if the available information supports the hypotheses behind the adaptive management of fall low-salinity habitat as set forth in the adaptive management plan.
\n• To begin to put the results from the fall low-salinity habitat studies into context within the larger body of knowledge regarding the San Francisco Estuary and, in particular, the upper San Francisco Estuary, including the Sacramento-San Joaquin Delta, Suisun Bay, and associated embayments.

\n
\n

The basic approach of this report is to evaluate predictions derived from the hypotheses included in the conceptual model developed within the adaptive management plan. All available data from studies and monitoring conducted in fall 2011 and similar data from fall 2006, which was the most recent wet year preceding 2011, were considered. Data from 2005 and 2010 were also considered, to include the conditions antecedent to those years.

\n
\n

Many of the predictions either could not be evaluated with the data available, or the needed data were not collected. Most of the predictions that could be addressed involved either the abiotic habitat components (that is, the physical environment) or delta smelt responses. In general, the fall low-salinity habitat investigation has been largely inconclusive as of the writing of this report. This is not to be unexpected in the first year of what is intended to be a multi-year adaptive-management effort. This report can be viewed as the first chapter of a “living document” that is to be continually updated as part of the adaptive management cycle. The results of this report, especially predictions with insufficient data for evaluation, indicate a number of science-based approaches to improve the fall low-salinity habitat investigations:
\n• Develop a method of measuring “hydrodynamic complexity.” This concept is central to a number of the predictions that could not be evaluated.
\n• Determine if wind speed warrants a stand-alone prediction. The wind-speed prediction is directly related to the turbidity predictions, and wind is only one of several factors important for determining turbidity.
\n• Determine the correct spatial and temporal scale or scales necessary for monitoring and for studies to address the predicted abiotic and biotic responses. Many of the assessments in this report were based on monthly sampling of dynamic habitat components, such as phytoplankton and zooplankton populations, that can change on daily scales.
\n• Address the nutrient predictions as part of developing a phytoplankton production model that includes nutrient cycling and other important processes, if feasible. At a minimum develop a mechanistic conceptual model to support more processed-based interpretations of data or design of new studies, rather than making simple predictions of increase or decrease.
\n• Determine if studies of predation rates are feasible in areas where there are delta smelt.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145041","collaboration":"Prepared in cooperation with the Bureau of Reclamation and Interagency Ecological Program","usgsCitation":"Brown, L.R., Baxter, R., Castillo, G., Conrad, L., Culberson, S., Erickson, G., Feyrer, F., Fong, S., Gehrts, K., Grimaldo, L., Herbold, B., Kirsch, J., Mueller-Solger, A., Slater, S., Sommer, T., Souza, K., and Van Nieuwenhuyse, E., 2014, Synthesis of studies in the fall low-salinity zone of the San Francisco Estuary, September-December 2011: U.S. Geological Survey Scientific Investigations Report 2014-5041, Report: xii, 136 p.; Appendix Table 6-3, https://doi.org/10.3133/sir20145041.","productDescription":"Report: xii, 136 p.; Appendix Table 6-3","numberOfPages":"152","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2011-09-01","temporalEnd":"2011-12-31","ipdsId":"IP-035573","costCenters":[{"id":154,"text":"California Water 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study","interactions":[],"lastModifiedDate":"2016-11-22T18:54:51","indexId":"70178523","displayToPublicDate":"2014-07-30T00:00:00","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":"Sulfur isotope fractionation between fluid and andesitic melt: An experimental study","docAbstract":"

Glasses produced from decompression experiments conducted by Fiege et al. (2014a) were used to investigate the fractionation of sulfur isotopes between fluid and andesitic melt upon magma degassing. Starting materials were synthetic glasses with a composition close to a Krakatau dacitic andesite. The glasses contained 4.55–7.95 wt% H2O, ∼140 to 2700 ppm sulfur (S), and 0–1000 ppm chlorine (Cl). The experiments were carried out in internally heated pressure vessels (IHPV) at 1030 °C and oxygen fugacities (fO2) ranging from QFM+0.8 log units up to QFM+4.2 log units (QFM: quartz–fayalite–magnetite buffer). The decompression experiments were conducted by releasing pressure (P) continuously from ∼400 MPa to final P of 150, 100, 70 and 30 MPa. The decompression rate (r) ranged from 0.01 to 0.17 MPa/s. The samples were annealed for 0–72 h (annealing time, tA) at the final P and quenched rapidly from 1030 °C to room temperature (T).

The decompression led to the formation of a S-bearing aqueous fluid phase due to the relatively large fluid–melt partitioning coefficients of S. Secondary ion mass spectrometry (SIMS) was used to determine the isotopic composition of the glasses before and after decompression. Mass balance calculations were applied to estimate the gas–melt S isotope fractionation factor αg-m.

No detectable effect of r and tA on αg-m was observed. However, SIMS data revealed a remarkable increase of αg-m from ∼0.9985 ± 0.0007 at >QFM+3 to ∼1.0042 ± 0.0042 at ∼QFM+1. Noteworthy, the isotopic fractionation at reducing conditions was about an order of magnitude larger than predicted by previous works. Based on our experimental results and on previous findings for S speciation in fluid and silicate melt a new model predicting the effect of fO2 on αg-m (or Δ34Sg–m) in andesitic systems at 1030 °C is proposed. Our experimental results as well as our modeling are of high importance for the interpretation of S isotope signatures in natural samples (e.g., melt inclusions or volcanic gases).

","language":"English","publisher":"Elsevier","doi":"10.1016/j.gca.2014.07.015","usgsCitation":"Fiege, A., Holtz, F., Shimizu, N., Mandeville, C., Behrens, H., and Knipping, J.L., 2014, Sulfur isotope fractionation between fluid and andesitic melt: An experimental study: Geochimica et Cosmochimica Acta, v. 142, p. 501-521, https://doi.org/10.1016/j.gca.2014.07.015.","productDescription":"21 p.","startPage":"501","endPage":"521","ipdsId":"IP-057270","costCenters":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"links":[{"id":472852,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hdl.handle.net/1912/6951","text":"External Repository"},{"id":331201,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"142","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5835672de4b0070c0abfb6de","contributors":{"authors":[{"text":"Fiege, Adrian","contributorId":177008,"corporation":false,"usgs":false,"family":"Fiege","given":"Adrian","email":"","affiliations":[{"id":12879,"text":"Department of Earth and Environmental Sciences, University of Michigan, Ann Arbor","active":true,"usgs":false}],"preferred":false,"id":654239,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Holtz, Francois","contributorId":177009,"corporation":false,"usgs":false,"family":"Holtz","given":"Francois","email":"","affiliations":[],"preferred":false,"id":654240,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shimizu, Nobumichi","contributorId":177010,"corporation":false,"usgs":false,"family":"Shimizu","given":"Nobumichi","email":"","affiliations":[{"id":6706,"text":"Woods Hole Oceanographic Institution,","active":true,"usgs":false}],"preferred":false,"id":654241,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mandeville, Charlie 0000-0002-8485-3689 cmandeville@usgs.gov","orcid":"https://orcid.org/0000-0002-8485-3689","contributorId":753,"corporation":false,"usgs":true,"family":"Mandeville","given":"Charlie","email":"cmandeville@usgs.gov","affiliations":[{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true}],"preferred":true,"id":654226,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Behrens, Harald","contributorId":177011,"corporation":false,"usgs":false,"family":"Behrens","given":"Harald","email":"","affiliations":[],"preferred":false,"id":654242,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Knipping, Jaayke L.","contributorId":177012,"corporation":false,"usgs":false,"family":"Knipping","given":"Jaayke","email":"","middleInitial":"L.","affiliations":[{"id":12879,"text":"Department of Earth and Environmental Sciences, University of Michigan, Ann Arbor","active":true,"usgs":false}],"preferred":false,"id":654243,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70111464,"text":"sir20145077 - 2014 - Effects of hydrologic modifications on salinity and formation of hypoxia in the Mississippi River-Gulf Outlet and adjacent waterways, southeastern Louisiana, 2008 to 2012","interactions":[],"lastModifiedDate":"2014-07-29T16:20:37","indexId":"sir20145077","displayToPublicDate":"2014-07-29T16:15:00","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":"2014-5077","title":"Effects of hydrologic modifications on salinity and formation of hypoxia in the Mississippi River-Gulf Outlet and adjacent waterways, southeastern Louisiana, 2008 to 2012","docAbstract":"

The Mississippi River-Gulf Outlet (MRGO) was constructed between 1958 and 1968 to provide a safer and shorter route between the Gulf of Mexico and the Port of New Orleans for ocean-going vessels. In 2006, the U.S. Congress directed the U.S. Army Corps of Engineers (USACE) to develop and implement a plan to deauthorize a portion of the MRGO ship channel from its confluence with the Gulf Intracoastal Waterway to the Gulf of Mexico. In 2009, in accordance with plans submitted to Congress, the USACE built a rock barrier across the MRGO near Hopedale, Louisiana. Following Hurricane Katrina, Congress also authorized the USACE to implement the Hurricane Storm Damage Risk Reduction System (HSDRRS) by building structures in the MRGO and adjacent surface waters, to reduce vulnerability of this area to storm surge. The HSDRRS includes the Gulf Intracoastal Waterway-Lake Borgne Surge Barrier and Gate Complex near mile 58 of the deauthorized portion of the MRGO and the Seabrook Gate Complex on the Inner Harbor Navigation Canal (IHNC). By blocking or limiting tidal exchange in the MRGO, these barriers could affect water quality in the MRGO and nearby waters including Lake Pontchartrain, the IHNC, and Lake Borgne. In 2008, the U.S. Geological Survey, in cooperation with the USACE, began a study to document the effects of the construction activities on salinity and dissolved oxygen in these surface waters. Data were collected from August 2008 through October 2012.

\n
\n

Completion of the rock barrier in the vicinity of mile 35 in July 2009 reduced hydrologic circulation and separated the MRGO into two distinct salinity regimes, with substantially fresher conditions prevailing upstream from the rock barrier. The rock barrier also contributed to a zone of hypoxia (dissolved oxygen less than 2 milligrams per liter) that formed along the channel bottom during the warmer summer months in each year of this monitoring; the zone was much more developed downstream from the rock barrier. The most extensive hypoxic zone was measured in October 2009 when it extended at least 34 miles in the MRGO, from mile 20 to mile 54. Construction of the surge barrier and flood gates did not affect salinity or dissolved oxygen in any comparable manner.

\n
\n

The factors that contributed the most to hypoxia in the MRGO were the reductions in tidal water movement there after completion of the rock barrier combined with the channel depth in the MRGO, in places 10 to 30 feet deeper than surrounding surface water bodies. These factors helped to stratify salinity by reducing vertical mixing in the water column.

","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145077","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Swarzenski, C.M., and Mize, S.V., 2014, Effects of hydrologic modifications on salinity and formation of hypoxia in the Mississippi River-Gulf Outlet and adjacent waterways, southeastern Louisiana, 2008 to 2012: U.S. Geological Survey Scientific Investigations Report 2014-5077, vi, 21 p., https://doi.org/10.3133/sir20145077.","productDescription":"vi, 21 p.","numberOfPages":"30","onlineOnly":"Y","temporalStart":"2008-01-01","temporalEnd":"2012-12-31","ipdsId":"IP-052992","costCenters":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"links":[{"id":291366,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145077.jpg"},{"id":291362,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5077/"},{"id":291365,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5077/pdf/sir2014-5077.pdf"}],"country":"United States","state":"Louisiana","otherGeospatial":"Mississippi River-gulf Outlet","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -90.0,29.5 ], [ -90.0,30.0 ], [ -89.166667,30.0 ], [ -89.166667,29.5 ], [ -90.0,29.5 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57f7f097e4b0bc0bec09f857","contributors":{"authors":[{"text":"Swarzenski, Christopher M. 0000-0001-9843-1471 cswarzen@usgs.gov","orcid":"https://orcid.org/0000-0001-9843-1471","contributorId":656,"corporation":false,"usgs":true,"family":"Swarzenski","given":"Christopher","email":"cswarzen@usgs.gov","middleInitial":"M.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":494365,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mize, Scott V. 0000-0001-6751-5568 svmize@usgs.gov","orcid":"https://orcid.org/0000-0001-6751-5568","contributorId":2997,"corporation":false,"usgs":true,"family":"Mize","given":"Scott","email":"svmize@usgs.gov","middleInitial":"V.","affiliations":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":494366,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70118523,"text":"70118523 - 2014 - Whiting events in SW Florida coastal waters: a case study using MODIS medium-resolution data","interactions":[],"lastModifiedDate":"2014-07-29T15:37:12","indexId":"70118523","displayToPublicDate":"2014-07-29T15:26:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3251,"text":"Remote Sensing Letters","active":true,"publicationSubtype":{"id":10}},"title":"Whiting events in SW Florida coastal waters: a case study using MODIS medium-resolution data","docAbstract":"Whitings, floating patches of calcium carbonate mud, have been found in both shallow carbonate banks and freshwater environments around the world. Although these events have been studied for many decades, much of their characteristics remain unknown. Recent sightings of whitings near Ten Thousand Islands, Florida suggest a phenomenon that has not previously been documented in this area. Using medium-resolution (250-m) data collected by the Moderate Resolution Imaging Spectroradiometer (MODIS) from December 2010 to November 2013, we documented whiting events and their spatial and temporal patterns in this region. Classification rules were first established, and then applied to all 474 cloud-free and sun glint-free MODIS images. Whiting occurrences were found between 25°46′N and 25°20′N and less than 40 km from the southwest Florida coastline. Over the 3-year period, whiting occurrence peaked in spring and autumn and reached a minimum during the winter and summer months. Further field and laboratory research are needed to explain driving force(s) behind these events.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Remote Sensing Letters","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Taylor & Francis","publisherLocation":"Abingdon, United Kingdom","doi":"10.1080/2150704X.2014.933275","usgsCitation":"Long, J., Hu, C., and Robbins, L., 2014, Whiting events in SW Florida coastal waters: a case study using MODIS medium-resolution data: Remote Sensing Letters, v. 5, no. 6, p. 539-547, https://doi.org/10.1080/2150704X.2014.933275.","productDescription":"9 p.","startPage":"539","endPage":"547","numberOfPages":"9","ipdsId":"IP-054316","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":291355,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":291236,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1080/2150704X.2014.933275"}],"country":"United States","state":"Florida","otherGeospatial":"Ten Thousand Islands","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -81.9965,24.9935 ], [ -81.9965,25.9975 ], [ -80.8621,25.9975 ], [ -80.8621,24.9935 ], [ -81.9965,24.9935 ] ] ] } } ] }","volume":"5","issue":"6","noUsgsAuthors":false,"publicationDate":"2014-06-30","publicationStatus":"PW","scienceBaseUri":"57f7f097e4b0bc0bec09f859","contributors":{"authors":[{"text":"Long, Jacqueline","contributorId":45646,"corporation":false,"usgs":true,"family":"Long","given":"Jacqueline","email":"","affiliations":[],"preferred":false,"id":496898,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hu, Chuanmin","contributorId":24696,"corporation":false,"usgs":true,"family":"Hu","given":"Chuanmin","affiliations":[],"preferred":false,"id":496897,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Robbins, Lisa","contributorId":87643,"corporation":false,"usgs":true,"family":"Robbins","given":"Lisa","affiliations":[],"preferred":false,"id":496899,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70118356,"text":"70118356 - 2014 - Precipitation isotopes link regional climate patterns to water supply in a tropical mountain forest, eastern Puerto Rico","interactions":[],"lastModifiedDate":"2014-07-29T14:37:10","indexId":"70118356","displayToPublicDate":"2014-07-29T14:19:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Precipitation isotopes link regional climate patterns to water supply in a tropical mountain forest, eastern Puerto Rico","docAbstract":"Like many mountainous areas in the tropics, watersheds in the Luquillo Mountains of eastern Puerto Rico have abundant rainfall and stream discharge and provide much of the water supply for the densely populated metropolitan areas nearby. Projected changes in regional temperature and atmospheric dynamics as a result of global warming suggest that water availability will be affected by changes in rainfall patterns. It is essential to understand the relative importance of different weather systems to water supply to determine how changes in rainfall patterns, interacting with geology and vegetation, will affect the water balance. To help determine the links between climate and water availability, stable isotope signatures of precipitation from different weather systems were established to identify those that are most important in maintaining streamflow and groundwater recharge. Precipitation stable isotope values in the Luquillo Mountains had a large range, from fog/cloud water with δ2H, δ18O values as high as +12 ‰, −0.73 ‰ to tropical storm rain with values as low as −127 ‰, −16.8 ‰. Temporal isotope values exhibit a reverse seasonality from those observed in higher latitude continental watersheds, with higher isotopic values in the winter and lower values in the summer. Despite the higher volume of convective and low-pressure system rainfall, stable isotope analyses indicated that under the current rainfall regime, frequent trade -wind orographic showers contribute much of the groundwater recharge and stream base flow. Analysis of rain events using 20 years of 15 -minute resolution data at a mountain station (643 m) showed an increasing trend in rainfall amount, in agreement with increased precipitable water in the atmosphere, but differing from climate model projections of drying in the region. The mean intensity of rain events also showed an increasing trend. The determination of recharge sources from stable isotope tracers indicates that water supply will be affected if regional atmospheric dynamics change trade- wind orographic rainfall patterns in the Caribbean.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Water Resources Research","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Geophysical Union","doi":"10.1002/2013WR014413","usgsCitation":"Scholl, M.A., and Murphy, S.F., 2014, Precipitation isotopes link regional climate patterns to water supply in a tropical mountain forest, eastern Puerto Rico: Water Resources Research, v. 50, no. 5, p. 4305-4322, https://doi.org/10.1002/2013WR014413.","productDescription":"18 p.","startPage":"4305","endPage":"4322","numberOfPages":"18","ipdsId":"IP-049266","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":291342,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":291193,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/2013WR014413"}],"country":"Puerto Rico","otherGeospatial":"Luquillo Mountains","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -65.95,18.17 ], [ -65.95,18.39 ], [ -65.583333,18.39 ], [ -65.583333,18.17 ], [ -65.95,18.17 ] ] ] } } ] }","volume":"50","issue":"5","noUsgsAuthors":false,"publicationDate":"2014-05-22","publicationStatus":"PW","scienceBaseUri":"57f7f097e4b0bc0bec09f85d","contributors":{"authors":[{"text":"Scholl, Martha A. 0000-0001-6994-4614 mascholl@usgs.gov","orcid":"https://orcid.org/0000-0001-6994-4614","contributorId":1920,"corporation":false,"usgs":true,"family":"Scholl","given":"Martha","email":"mascholl@usgs.gov","middleInitial":"A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":496809,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Murphy, Sheila F. 0000-0002-5481-3635 sfmurphy@usgs.gov","orcid":"https://orcid.org/0000-0002-5481-3635","contributorId":1854,"corporation":false,"usgs":true,"family":"Murphy","given":"Sheila","email":"sfmurphy@usgs.gov","middleInitial":"F.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":496808,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70188534,"text":"70188534 - 2014 - Imaging P and S attenuation in the Sacramento-San Joaquin Delta region, northern California","interactions":[],"lastModifiedDate":"2017-06-14T15:08:54","indexId":"70188534","displayToPublicDate":"2014-07-29T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Imaging P and S attenuation in the Sacramento-San Joaquin Delta region, northern California","docAbstract":"We obtain 3-D Qp and Qs models for the Delta region of the Sacramento and San Joaquin Rivers, a large fluvial-agricultural portion of the Great Valley located between the Sierra Nevada batholith and the San Francisco Bay - Coast Ranges region of active faulting. Path attenuation t* values have been obtained for P and S data from 124 distributed earthquakes, with a longer variable window for S based on the energy integral. We use frequency dependence of 0.5 consistent with other studies, and weakly favored by the t* S data. A regional initial model was obtained by solving for Q as a function of velocity. In the final model, the Great Valley basin has low Q with very low Q (<50) for the shallowest portion of the Delta. There is an underlying strong Q contrast to the ophiolite basement which is thickest with highest Q under the Sacramento basin, and a change in structure is apparent across the Suisun Bay as a transition to thinner ophiolite. Moderately low Q is found in the upper crust west of the Delta region along the faults in the eastern North Bay Area, while, moderately high Q is found south of the Delta, implying potentially stronger ground motion for earthquake sources to the south. Very low Q values in the shallow crust along parts of the major fault zones may relate to sediment and abundant microfractures. In the lower crust below the San Andreas and Calaveras-Hayward-Rodgers Creek fault zones, the observed low Q is consistent with grain-size reduction in ductile shear zones and is lowest under the San Andreas which has large cumulative strain. Similarly moderately low Q in the ductile lower crust of the Bay Area block between the major fault zones implies a broad distributed shear zone.","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120130336","usgsCitation":"Eberhart-Phillips, D., Thurber, C., and Fletcher, J.P., 2014, Imaging P and S attenuation in the Sacramento-San Joaquin Delta region, northern California: Bulletin of the Seismological Society of America, v. 104, no. 5, p. 2322-2336, https://doi.org/10.1785/0120130336.","productDescription":"15 p. ","startPage":"2322","endPage":"2336","ipdsId":"IP-061952","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":342508,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento-San Joaquin Delta Region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.7117919921875,\n 39.89709437260048\n ],\n [\n -122.01416015625,\n 38.225235239076824\n ],\n [\n -121.4813232421875,\n 37.63163475580643\n ],\n [\n -121.00341796874999,\n 37.08585785263673\n ],\n [\n -120.67932128906249,\n 36.730079507078415\n ],\n [\n -118.55895996093749,\n 37.53150992479082\n ],\n [\n -118.7017822265625,\n 38.043765107439675\n ],\n [\n -119.08630371093749,\n 38.543869175876154\n ],\n [\n -119.80590820312499,\n 39.317300373271024\n ],\n [\n -120.2838134765625,\n 39.774769485295465\n ],\n [\n -120.948486328125,\n 40.29628651711716\n ],\n [\n -121.31103515625,\n 40.53050177574321\n ],\n [\n -121.97021484374999,\n 40.53050177574321\n ],\n [\n -122.398681640625,\n 40.40094763151963\n ],\n [\n -122.72277832031251,\n 40.225024210604964\n ],\n [\n -122.7117919921875,\n 39.89709437260048\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"104","issue":"5","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2014-07-29","publicationStatus":"PW","scienceBaseUri":"59424b3be4b0764e6c65dc5b","contributors":{"authors":[{"text":"Eberhart-Phillips, Donna 0000-0003-0392-8659","orcid":"https://orcid.org/0000-0003-0392-8659","contributorId":190650,"corporation":false,"usgs":false,"family":"Eberhart-Phillips","given":"Donna","email":"","affiliations":[],"preferred":false,"id":698167,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thurber, Clifford","contributorId":44067,"corporation":false,"usgs":true,"family":"Thurber","given":"Clifford","affiliations":[],"preferred":false,"id":698168,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fletcher, Jon Peter B. 0000-0001-8885-6177 jfletcher@usgs.gov","orcid":"https://orcid.org/0000-0001-8885-6177","contributorId":1216,"corporation":false,"usgs":true,"family":"Fletcher","given":"Jon","email":"jfletcher@usgs.gov","middleInitial":"Peter B.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":698166,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ]}