Processes controlling the composition of seafloor hydrothermal fluids in silicic back-arc or near-arc crustal settings remain poorly constrained despite growing evidence for extensive magmatic–hydrothermal activity in such environments. We conducted a survey of vent fluid compositions from two contrasting sites in the Manus back-arc basin, Papua New Guinea, to examine the influence of variations in host rock composition and magmatic inputs (both a function of arc proximity) on hydrothermal fluid chemistry. Fluid samples were collected from felsic-hosted hydrothermal vent fields located on Pual Ridge (PACMANUS and Northeast (NE) Pual) near the active New Britain Arc and a basalt-hosted vent field (Vienna Woods) located farther from the arc on the Manus Spreading Center. Vienna Woods fluids were characterized by relatively uniform endmember temperatures (273–285 °C) and major element compositions, low dissolved CO2 concentrations (4.4 mmol/kg) and high measured pH (4.2–4.9 at 25 °C). Temperatures and compositions were highly variable at PACMANUS/NE Pual and a large, newly discovered vent area (Fenway) was observed to be vigorously venting boiling (358 °C) fluid. All PACMANUS fluids are characterized by negative
Many biogeochemical processes in rivers and lakes respond to the solar photocycle and produce persistent patterns of measureable phenomena that exhibit a day–night, or 24-h, cycle. Despite a large body of recent literature, the mechanisms responsible for these diel fluctuations are widely debated, with a growing consensus that combinations of physical, chemical, and biological processes are involved. These processes include streamflow variation, photosynthesis and respiration, plant assimilation, and reactions involving photochemistry, adsorption and desorption, and mineral precipitation and dissolution. Diel changes in streamflow and water properties such as temperature, pH, and dissolved oxygen concentration have been widely recognized, and recently, diel studies have focused more widely by considering other constituents such as dissolved and particulate trace metals, metalloids, rare earth elements, mercury, organic matter, dissolved inorganic carbon (DIC), and nutrients. The details of many diel processes are being studied using stable isotopes, which also can exhibit diel cycles in response to microbial metabolism, photosynthesis and respiration, or changes in phase, speciation, or redox state. In addition, secondary effects that diel cycles might have, for example, on biota or in the hyporheic zone are beginning to be considered.
This special issue is composed primarily of papers presented at the topical session “Diurnal Biogeochemical Processes in Rivers, Lakes, and Shallow Groundwater” held at the annual meeting of the Geological Society of America in October 2009 in Portland, Oregon. This session was organized because many of the growing number of diel studies have addressed just a small part of the full range of diel cycling phenomena found in rivers and lakes. This limited focus is understandable because (1) fundamental aspects of many diel processes are poorly understood and require detailed study, (2) the interests and expertise of individual scientists typically do not encompass the wide diversity and range of processes that produce diel cycles, and (3) the logistics of making field measurements for 24-h periods has limited recognition and understanding of these important cycles. Thus, the topical session brought together hydrologists, biologists, geochemists, and ecologists to discuss field studies, laboratory experiments, theoretical modeling, and measurement techniques related to diel cycling. Hopefully with the cross-disciplinary synergy developed at the session as well as by this special issue, a more comprehensive understanding of the interrelationships between the diel processes will be developed. Needless to say, understanding diel processes is critical for regulatory agencies and the greater scientific community. And perhaps more importantly, expanded knowledge of biogeochemical cycling may lead to better predictions of how aquatic ecosystems might react to changing conditions of contaminant loading, eutrophication, climate change, drought, industrialization, development, and other variables.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.chemgeo.2011.01.023","usgsCitation":"Nimick, D.A., and Gammons, C.H., 2011, Diel biogeochemical processes in terrestrial waters: Chemical Geology, v. 283, no. 1-2, p. 1-2, https://doi.org/10.1016/j.chemgeo.2011.01.023.","productDescription":"2 p.","startPage":"1","endPage":"2","costCenters":[{"id":400,"text":"Montana Water Science Center","active":false,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":203864,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"283","issue":"1-2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a9ae4b07f02db65da0c","contributors":{"authors":[{"text":"Nimick, David A. dnimick@usgs.gov","contributorId":421,"corporation":false,"usgs":true,"family":"Nimick","given":"David","email":"dnimick@usgs.gov","middleInitial":"A.","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true},{"id":573,"text":"Special Applications Science Center","active":true,"usgs":true}],"preferred":true,"id":730084,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gammons, Chris","contributorId":140801,"corporation":false,"usgs":false,"family":"Gammons","given":"Chris","affiliations":[{"id":13574,"text":"Montana Tech of the University of Montana, Butte, MT","active":true,"usgs":false}],"preferred":false,"id":730085,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70118549,"text":"70118549 - 2011 - Three types of gas hydrate reservoirs in the Gulf of Mexico identified in LWD data","interactions":[],"lastModifiedDate":"2014-07-29T11:19:35","indexId":"70118549","displayToPublicDate":"2011-07-17T11:16:55","publicationYear":"2011","noYear":false,"publicationType":{"id":4,"text":"Book"},"publicationSubtype":{"id":12,"text":"Conference publication"},"title":"Three types of gas hydrate reservoirs in the Gulf of Mexico identified in LWD data","docAbstract":"High quality logging-while-drilling (LWD) well logs were acquired in seven wells drilled during the Gulf of Mexico Gas Hydrate Joint Industry Project Leg II in the spring of 2009. These data help to identify three distinct types of gas hydrate reservoirs: isotropic reservoirs in sands, vertical fractured reservoirs in shale, and horizontally layered reservoirs in silty shale. In general, most gas hydratebearing sand reservoirs exhibit isotropic elastic velocities and formation resistivities, and gas hydrate saturations estimated from the P-wave velocity agree well with those from the resistivity. However, in highly gas hydrate-saturated sands, resistivity-derived gas hydrate-saturation estimates appear to be systematically higher by about 5% over those estimated by P-wave velocity, possibly because of the uncertainty associated with the consolidation state of gas hydrate-bearing sands. Small quantities of gas hydrate were observed in vertical fractures in shale. These occurrences are characterized by high formation resistivities with P-wave velocities close to those of water-saturated sediment. Because the formation factor varies significantly with respect to the gas hydrate saturation for vertical fractures at low saturations, an isotropic analysis of formation factor highly overestimates the gas hydrate saturation. Small quantities of gas hydrate in horizontal layers in shale are characterized by moderate increase in P-wave velocities and formation resistivities and either measurement can be used to estimate gas hydrate saturations.","largerWorkTitle":"Proceedings of the 7th International Conference on Gas Hydrates","conferenceTitle":"7th International Conference on Gas Hydrates","conferenceDate":"2011-07-17T00:00:00","conferenceLocation":"Edinburgh, Scotland","language":"English","publisher":"ICGH","publisherLocation":"Edinburgh, Scotland","usgsCitation":"Lee, M.W., and Collett, T.S., 2011, Three types of gas hydrate reservoirs in the Gulf of Mexico identified in LWD data, 12 p.","productDescription":"12 p.","numberOfPages":"12","costCenters":[],"links":[{"id":291282,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57fe7f2ee4b0824b2d1476c5","contributors":{"authors":[{"text":"Lee, Myung Woong","contributorId":15114,"corporation":false,"usgs":true,"family":"Lee","given":"Myung","email":"","middleInitial":"Woong","affiliations":[],"preferred":false,"id":496985,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Collett, Timothy S. 0000-0002-7598-4708 tcollett@usgs.gov","orcid":"https://orcid.org/0000-0002-7598-4708","contributorId":1698,"corporation":false,"usgs":true,"family":"Collett","given":"Timothy","email":"tcollett@usgs.gov","middleInitial":"S.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":496984,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70169875,"text":"70169875 - 2011 - Bedform response to flow variability","interactions":[],"lastModifiedDate":"2024-09-18T17:19:20.258326","indexId":"70169875","displayToPublicDate":"2011-07-15T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1425,"text":"Earth Surface Processes and Landforms","active":true,"publicationSubtype":{"id":10}},"title":"Bedform response to flow variability","docAbstract":"Laboratory observations and computational results for the response of bedform fields to rapid variations in discharge are compared and discussed. The simple case considered here begins with a relatively low discharge over a flat bed on which bedforms are initiated, followed by a short high-flow period with double the original discharge, during which the morphology of the bedforms adjusts, followed in turn by a relatively long period of the original low discharge. For the grain size and hydraulic conditions selected, the Froude number remains subcritical during the experiment, and sediment moves predominantly as bedload. Observations show rapid development of quasi-two-dimensional bedforms during the initial period of low flow with increasing wavelength and height over the initial low-flow period. When the flow increases, the bedforms rapidly increase in wavelength and height, as expected from other empirical results. When the flow decreases back to the original discharge, the height of the bedforms quickly decreases in response, but the wavelength decreases much more slowly. Computational results using an unsteady two-dimensional flow model coupled to a disequilibrium bedload transport model for the same conditions simulate the formation and initial growth of the bedforms fairly accurately and also predict an increase in dimensions during the high-flow period. However, the computational model predicts a much slower rate of wavelength increase, and also performs less accurately during the final low-flow period, where the wavelength remains essentially constant, rather than decreasing. In addition, the numerical results show less variability in bedform wavelength and height than the measured values; the bedform shape is also somewhat different. Based on observations, these discrepancies may result from the simplified model for sediment particle step lengths used in the computational approach. Experiments show that the particle step length varies spatially and temporally over the bedforms during the evolution process. Assuming a constant value for the step length neglects the role of flow alterations in the bedload sediment-transport process, which appears to result in predicted bedform wavelength changes smaller than those observed. However, observations also suggest that three-dimensional effects play at least some role in the decrease of bedform wavelength, so incorporating better models for particle hop lengths alone may not be sufficient to improve model predictions.
","language":"English","publisher":"Wiley","doi":"10.1002/esp.2212","usgsCitation":"Nelson, J.M., Logan, B., Kinzel, P.J., Shimizu, Y., Giri, S., Shreve, R., and McLean, S., 2011, Bedform response to flow variability: Earth Surface Processes and Landforms, v. 36, no. 14, p. 1938-1947, https://doi.org/10.1002/esp.2212.","productDescription":"10 p.","startPage":"1938","endPage":"1947","ipdsId":"IP-009360","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":364389,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"36","issue":"14","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2011-09-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Nelson, Jonathan M. 0000-0002-7632-8526 jmn@usgs.gov","orcid":"https://orcid.org/0000-0002-7632-8526","contributorId":2812,"corporation":false,"usgs":true,"family":"Nelson","given":"Jonathan","email":"jmn@usgs.gov","middleInitial":"M.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":625413,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Logan, Brandy L. blogan@usgs.gov","contributorId":168305,"corporation":false,"usgs":true,"family":"Logan","given":"Brandy L.","email":"blogan@usgs.gov","affiliations":[{"id":25245,"text":"USGS, Golden, CO","active":true,"usgs":false}],"preferred":false,"id":625415,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kinzel, Paul J. 0000-0002-6076-9730 pjkinzel@usgs.gov","orcid":"https://orcid.org/0000-0002-6076-9730","contributorId":743,"corporation":false,"usgs":true,"family":"Kinzel","given":"Paul","email":"pjkinzel@usgs.gov","middleInitial":"J.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":625414,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shimizu, Y.","contributorId":168309,"corporation":false,"usgs":false,"family":"Shimizu","given":"Y.","email":"","affiliations":[{"id":25249,"text":"Univ. of Hokkaido, Sapporo,Japan","active":true,"usgs":false}],"preferred":false,"id":625419,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Giri, S.","contributorId":102621,"corporation":false,"usgs":true,"family":"Giri","given":"S.","email":"","affiliations":[],"preferred":false,"id":913413,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Shreve, R.L.","contributorId":168306,"corporation":false,"usgs":false,"family":"Shreve","given":"R.L.","email":"","affiliations":[{"id":25246,"text":"Univ. of Washington, Seattle, WA","active":true,"usgs":false}],"preferred":false,"id":625416,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McLean, S.R.","contributorId":168308,"corporation":false,"usgs":false,"family":"McLean","given":"S.R.","email":"","affiliations":[{"id":25248,"text":"Univ. of CA, Santa Barbara, CA","active":true,"usgs":false}],"preferred":false,"id":625418,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70003619,"text":"70003619 - 2011 - Developing seismogenic source models based on geologic fault data","interactions":[],"lastModifiedDate":"2021-05-21T17:40:36.908792","indexId":"70003619","displayToPublicDate":"2011-07-15T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Developing seismogenic source models based on geologic fault data","docAbstract":"Calculating seismic hazard usually requires input that includes seismicity associated with known faults, historical earthquake catalogs, geodesy, and models of ground shaking. This paper will address the input generally derived from geologic studies that augment the short historical catalog to predict ground shaking at time scales of tens, hundreds, or thousands of years (e.g., SSHAC 1997). A seismogenic source model, terminology we adopt here for a fault source model, includes explicit three-dimensional faults deemed capable of generating ground motions of engineering significance within a specified time frame of interest. In tectonically active regions of the world, such as near plate boundaries, multiple seismic cycles span a few hundred to a few thousand years. In contrast, in less active regions hundreds of kilometers from the nearest plate boundary, seismic cycles generally are thousands to tens of thousands of years long. Therefore, one should include sources having both longer recurrence intervals and possibly older times of most recent rupture in less active regions of the world rather than restricting the model to include only Holocene faults (i.e., those with evidence of large-magnitude earthquakes in the past 11,500 years) as is the practice in tectonically active regions with high deformation rates. \r\n\r\nDuring the past 15 years, our institutions independently developed databases to characterize seismogenic sources based on geologic data at a national scale. Our goal here is to compare the content of these two publicly available seismogenic source models compiled for the primary purpose of supporting seismic hazard calculations by the Istituto Nazionale di Geofisica e Vulcanologia (INGV) and the U.S. Geological Survey (USGS); hereinafter we refer to the two seismogenic source models as INGV and USGS, respectively. This comparison is timely because new initiatives are emerging to characterize seismogenic sources at the continental scale (e.g., SHARE in the Euro-Mediterranean, http://www.share-eu.org/; EMME in the Middle East, http://www.emme-gem.org/) and global scale (e.g., GEM, http://www.globalquakemodel.org/; Anonymous 2008). To some extent, each of these efforts is still trying to resolve the level of optimal detail required for this type of compilation. The comparison we provide defines a common standard for consideration by the international community for future regional and global seismogenic source models by identifying the necessary parameters that capture the essence of geological fault data in order to characterize seismogenic sources. In addition, we inform potential users of differences in our usage of common geological/seismological terms to avoid inappropriate use of the data in our models and provide guidance to convert the data from one model to the other (for detailed instructions, see the electronic supplement to this article). Applying our recommendations will permit probabilistic seismic hazard assessment codes to run seamlessly using either seismogenic source input. \r\n\r\nThe USGS and INGV database schema compare well at a first-level inspection. Both databases contain a set of fields representing generalized fault three-dimensional geometry and additional fields that capture the essence of past earthquake occurrences. Nevertheless, there are important differences. When we further analyze supposedly comparable fields, many are defined differently. These differences would cause anomalous results in hazard prediction if one assumes the values are similarly defined. The data, however, can be made fully compatible using simple transformations.","language":"English","publisher":"Seismological Society of America","publisherLocation":"El Cerrito, CA","doi":"10.1785/gssrl.82.4.519","usgsCitation":"Haller, K., and Basili, R., 2011, Developing seismogenic source models based on geologic fault data: Seismological Research Letters, v. 82, no. 4, p. 519-525, https://doi.org/10.1785/gssrl.82.4.519.","productDescription":"7 p.","startPage":"519","endPage":"525","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":204124,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"82","issue":"4","noUsgsAuthors":false,"publicationDate":"2011-07-05","publicationStatus":"PW","scienceBaseUri":"4f4e4aa8e4b07f02db6672f8","contributors":{"authors":[{"text":"Haller, Kathleen M. haller@usgs.gov","contributorId":1331,"corporation":false,"usgs":true,"family":"Haller","given":"Kathleen M.","email":"haller@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":347978,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Basili, Roberto","contributorId":9760,"corporation":false,"usgs":true,"family":"Basili","given":"Roberto","affiliations":[],"preferred":false,"id":347979,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70005762,"text":"70005762 - 2011 - Conceptualizing and communicating ecological river restoration","interactions":[],"lastModifiedDate":"2022-12-20T14:37:00.220258","indexId":"70005762","displayToPublicDate":"2011-07-14T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"2","title":"Conceptualizing and communicating ecological river restoration","docAbstract":"We present a general conceptual model for communicating aspects of river restoration and management. The model is generic and adaptable to most riverine settings, independent of size. The model has separate categories of natural and social-economic drivers, and management actions are envisioned as modifiers of naturally dynamic systems. The model includes a decision-making structure in which managers, stakeholders, and scientists interact to define management objectives and performance evaluation. The model depicts a stress to the riverine ecosystem as either (1) deviation in the regimes (flow, sediment, temperature, light, biogeochemical, and genetic) by altering the frequency, magnitude, duration, timing, or rate of change of the fluxes or (2) imposition of a hard structural constraint on channel form. Restoration is depicted as naturalization of those regimes or removal of the constraint. The model recognizes the importance of river history in conditioning future responses. Three hierarchical tiers of essential ecosystem characteristics (EECs) illustrate how management actions typically propagate through physical/chemical processes to habitat to biotic responses. Uncertainty and expense in modeling or measuring responses increase in moving from tiers 1 to 3. Social-economic characteristics are shown in a parallel structure that emphasizes the need to quantify trade-offs between ecological and social-economic systems. Performance measures for EECs are also hierarchical, showing that selection of measures depend on participants’ willingness to accept uncertainty. The general form is of an adaptive management loop in which the performance measures are compared to reference conditions or success criteria and the information is fed back into the decision-making process.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Stream restoration in dynamic fluvial systems","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"American Geophysical Union","publisherLocation":"Washington, D.C.","doi":"10.1029/2010GM000967","usgsCitation":"Jacobson, R.B., and Berkley, J., 2011, Conceptualizing and communicating ecological river restoration, chap. 2 of Stream restoration in dynamic fluvial systems, v. 194, p. 9-27, https://doi.org/10.1029/2010GM000967.","productDescription":"19 p.","startPage":"9","endPage":"27","ipdsId":"IP-009301","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":342440,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"194","noUsgsAuthors":false,"publicationDate":"2013-04-02","publicationStatus":"PW","scienceBaseUri":"5940f9b6e4b0764e6c63eaee","contributors":{"authors":[{"text":"Jacobson, Robert B. 0000-0002-8368-2064 rjacobson@usgs.gov","orcid":"https://orcid.org/0000-0002-8368-2064","contributorId":1289,"corporation":false,"usgs":true,"family":"Jacobson","given":"Robert","email":"rjacobson@usgs.gov","middleInitial":"B.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":697974,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Berkley, Jim","contributorId":115360,"corporation":false,"usgs":true,"family":"Berkley","given":"Jim","email":"","affiliations":[],"preferred":false,"id":697975,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70004887,"text":"sir20105090b - 2011 - Aggregation of estimated numbers of undiscovered deposits: an R-script with an example from the Chu Sarysu Basin, Kazakhtan: Chapter B in Global mineral resource assessment","interactions":[{"subject":{"id":70004887,"text":"sir20105090b - 2011 - Aggregation of estimated numbers of undiscovered deposits: an R-script with an example from the Chu Sarysu Basin, Kazakhtan: Chapter B in Global mineral resource assessment","indexId":"sir20105090b","publicationYear":"2011","noYear":false,"chapter":"B","title":"Aggregation of estimated numbers of undiscovered deposits: an R-script with an example from the Chu Sarysu Basin, Kazakhtan: Chapter B in Global mineral resource assessment"},"predicate":"IS_PART_OF","object":{"id":70040436,"text":"sir20105090 - 2010 - Global mineral resource assessment","indexId":"sir20105090","publicationYear":"2010","noYear":false,"title":"Global mineral resource assessment"},"id":1}],"isPartOf":{"id":70040436,"text":"sir20105090 - 2010 - Global mineral resource assessment","indexId":"sir20105090","publicationYear":"2010","noYear":false,"title":"Global mineral resource assessment"},"lastModifiedDate":"2015-06-19T10:40:35","indexId":"sir20105090b","displayToPublicDate":"2011-07-14T00:00:00","publicationYear":"2011","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":"2010-5090","chapter":"B","title":"Aggregation of estimated numbers of undiscovered deposits: an R-script with an example from the Chu Sarysu Basin, Kazakhtan: Chapter B in Global mineral resource assessment","docAbstract":"Mineral resource assessments completed by the U.S. Geological Survey during the past three decades express geologically based estimates of numbers of undiscovered mineral deposits as probability distributions. Numbers of undiscovered deposits of a given type are estimated in geologically defined regions. Using Monte Carlo simulations, these undiscovered deposit estimates are combined with tonnage and grade models to derive a probability distribution describing amounts of commodities and rock that could be present in undiscovered deposits within a study area. In some situations, it is desirable to aggregate the assessment results from several study areas. This report provides a script developed in open-source statistical software, R, that aggregates undiscovered deposit estimates of a given type, assuming independence, total dependence, or some degree of correlation among aggregated areas, given a user-specified correlation matrix.
","largerWorkTitle":"Global mineral resource assessment (Scientific Investigations Report 2010-5090)","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20105090b","usgsCitation":"Schuenemeyer, J.H., Zientek, M.L., and Box, S.E., 2011, Aggregation of estimated numbers of undiscovered deposits: an R-script with an example from the Chu Sarysu Basin, Kazakhtan: Chapter B in Global mineral resource assessment: U.S. Geological Survey Scientific Investigations Report 2010-5090, Report: vi, 6 p.; Code package, https://doi.org/10.3133/sir20105090b.","productDescription":"Report: vi, 6 p.; Code package","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"links":[{"id":204008,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20105090b.gif"},{"id":24402,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2010/5090/b/","linkFileType":{"id":5,"text":"html"}},{"id":301347,"rank":102,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2010/5090/b/sir2010-5090b_code.zip","text":"Code package","size":"4 kB","linkFileType":{"id":6,"text":"zip"},"description":"Code package"},{"id":301346,"rank":101,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2010/5090/b/sir2010-5090b_text.pdf","text":"Report","size":"2.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"projection":"Asia North Albers Equal Area Conic","country":"Kazakhstan","otherGeospatial":"Chu Sarysu Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 66,43 ], [ 66,49 ], [ 73,49 ], [ 73,43 ], [ 66,43 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4abee4b07f02db674bf6","contributors":{"authors":[{"text":"Schuenemeyer, John H.","contributorId":54227,"corporation":false,"usgs":true,"family":"Schuenemeyer","given":"John","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":351598,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zientek, Michael L. 0000-0002-8522-9626 mzientek@usgs.gov","orcid":"https://orcid.org/0000-0002-8522-9626","contributorId":2420,"corporation":false,"usgs":true,"family":"Zientek","given":"Michael","email":"mzientek@usgs.gov","middleInitial":"L.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":351597,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Box, Stephen E. 0000-0002-5268-8375 sbox@usgs.gov","orcid":"https://orcid.org/0000-0002-5268-8375","contributorId":1843,"corporation":false,"usgs":true,"family":"Box","given":"Stephen","email":"sbox@usgs.gov","middleInitial":"E.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":351596,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70004888,"text":"sir20115105 - 2011 - Modeling hydrodynamics, water temperature, and water quality in the Klamath River upstream of Keno Dam, Oregon, 2006-09","interactions":[],"lastModifiedDate":"2022-12-23T17:04:02.596722","indexId":"sir20115105","displayToPublicDate":"2011-07-14T00:00:00","publicationYear":"2011","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":"2011-5105","title":"Modeling hydrodynamics, water temperature, and water quality in the Klamath River upstream of Keno Dam, Oregon, 2006-09","docAbstract":"A hydrodynamic, water temperature, and water-quality model was constructed for a 20-mile reach of the Klamath River downstream of Upper Klamath Lake, from Link River to Keno Dam, for calendar years 2006-09. The two-dimensional, laterally averaged model CE-QUAL-W2 was used to simulate water velocity, ice cover, water temperature, specific conductance, dissolved and suspended solids, dissolved oxygen, total nitrogen, ammonia, nitrate, total phosphorus, orthophosphate, dissolved and particulate organic matter, and three algal groups. The Link-Keno model successfully simulated the most important spatial and temporal patterns in the measured data for this 4-year time period. The model calibration process provided critical insights into water-quality processes and the nature of those inputs and processes that drive water quality in this reach. The model was used not only to reproduce and better understand water-quality conditions that occurred in 2006-09, but also to test several load-reduction scenarios that have implications for future water-resources management in the river basin. The model construction and calibration process provided results concerning water quality and transport in the Link-Keno reach of the Klamath River, ranging from interesting circulation patterns in the Lake Ewauna area to the nature and importance of organic matter and algae. These insights and results include: * Modeled segment-average water velocities ranged from near 0.0 to 3.0 ft/s in 2006 through 2009. Travel time through the model reach was about 4 days at 2,000 ft3/s and 12 days at 700 ft3/s flow. Flow direction was aligned with the upstream-downstream channel axis for most of the Link-Keno reach, except for Lake Ewauna. Wind effects were pronounced at Lake Ewauna during low-flow conditions, often with circulation in the form of a gyre that rotated in a clockwise direction when winds were towards the southeast and in a counterclockwise direction when winds were towards the northwest. * Water temperatures ranged from near freezing in winter to near 30 degrees C at some locations and periods in summer; seasonal water temperature patterns were similar at the inflow and outflow. Although vertical temperature stratification was not present at most times and locations, weak stratification could persist for periods up to 1-2 weeks, especially in the downstream parts of the reach. Thermal stratification was important in controlling vertical variations in water quality. * The specific conductance, and thus density, of tributaries within the reach usually was higher than that of the river itself, so that inflows tended to sink below the river surface. This was especially notable for inflows from the Klamath Straits Drain, which tended to sink to the bottom of the Klamath River at its confluence and not mix vertically for several miles downstream. * The model was able to capture most of the seasonal changes in the algal population by modeling that population with three algal groups: blue-green algae, diatoms, and other algae. The blooms of blue-green algae, consisting mostly of Aphanizomenon flos aquae that entered from Upper Klamath Lake, were dominant, dwarfing the populations of the other two algae groups in summer. A large part of the blue-green algae population that entered this reach from upstream tended to settle out, die, and decompose, especially in the upper part of the Link-Keno reach. Diatoms reached a maximum in spring and other algae in midsummer. * Organic matter, occurring in both dissolved and particulate forms, was critical to the water quality of this reach of the Klamath River, and was strongly tied to nutrient and dissolved-oxygen dynamics. Dissolved and particulate organic matter were subdivided into labile (quickly decaying) and refractory (slowing decaying) groups for modeling purposes. The particulate matter in summer, consisting largely of dead blue-green algae, decayed quickly. Consequently, this particulate matt","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20115105","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Sullivan, A.B., Rounds, S.A., Deas, M., Asbill, J.R., Wellman, R.E., Stewart, M.A., Johnston, M.W., and Sogutlugil, I.E., 2011, Modeling hydrodynamics, water temperature, and water quality in the Klamath River upstream of Keno Dam, Oregon, 2006-09: U.S. Geological Survey Scientific Investigations Report 2011-5105, viii, 70 p., https://doi.org/10.3133/sir20115105.","productDescription":"viii, 70 p.","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":116150,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2011_5105.jpg"},{"id":24397,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2011/5105/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Oregon","otherGeospatial":"Keno Dam, Klamath River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -121.98333333333333,42.05 ], [ -121.98333333333333,42.28333333333333 ], [ -121.73333333333333,42.28333333333333 ], [ -121.73333333333333,42.05 ], [ -121.98333333333333,42.05 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a2de4b07f02db6146fa","contributors":{"authors":[{"text":"Sullivan, Annett B. 0000-0001-7783-3906 annett@usgs.gov","orcid":"https://orcid.org/0000-0001-7783-3906","contributorId":56317,"corporation":false,"usgs":true,"family":"Sullivan","given":"Annett","email":"annett@usgs.gov","middleInitial":"B.","affiliations":[],"preferred":false,"id":351605,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rounds, Stewart A. 0000-0002-8540-2206 sarounds@usgs.gov","orcid":"https://orcid.org/0000-0002-8540-2206","contributorId":905,"corporation":false,"usgs":true,"family":"Rounds","given":"Stewart","email":"sarounds@usgs.gov","middleInitial":"A.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":351599,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Deas, Michael L.","contributorId":98830,"corporation":false,"usgs":true,"family":"Deas","given":"Michael L.","affiliations":[],"preferred":false,"id":351606,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Asbill, Jessica R.","contributorId":39896,"corporation":false,"usgs":true,"family":"Asbill","given":"Jessica","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":351603,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wellman, Roy E. 0000-0003-4460-8918 rwellman@usgs.gov","orcid":"https://orcid.org/0000-0003-4460-8918","contributorId":1706,"corporation":false,"usgs":true,"family":"Wellman","given":"Roy","email":"rwellman@usgs.gov","middleInitial":"E.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":351600,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stewart, Marc A. 0000-0003-1140-6316 mastewar@usgs.gov","orcid":"https://orcid.org/0000-0003-1140-6316","contributorId":2277,"corporation":false,"usgs":true,"family":"Stewart","given":"Marc","email":"mastewar@usgs.gov","middleInitial":"A.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":351601,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Johnston, Matthew W. mattj@usgs.gov","contributorId":3066,"corporation":false,"usgs":true,"family":"Johnston","given":"Matthew","email":"mattj@usgs.gov","middleInitial":"W.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":351602,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sogutlugil, I. Ertugrul","contributorId":50277,"corporation":false,"usgs":true,"family":"Sogutlugil","given":"I.","email":"","middleInitial":"Ertugrul","affiliations":[],"preferred":false,"id":351604,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70189033,"text":"70189033 - 2011 - Hydrogeophysical investigations at Hidden Dam, Raymond, California","interactions":[],"lastModifiedDate":"2017-06-29T13:48:41","indexId":"70189033","displayToPublicDate":"2011-07-14T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3928,"text":"Journal of Environmental & Engineering Geophysics","printIssn":"1083-1363","active":true,"publicationSubtype":{"id":10}},"title":"Hydrogeophysical investigations at Hidden Dam, Raymond, California","docAbstract":"Self-potential and direct current resistivity surveys are carried out at the Hidden Dam site in Raymond, California to assess present-day seepage patterns and better understand the hydrogeologic mechanisms that likely influence seepage. Numerical modeling is utilized in conjunction with the geophysical measurements to predict variably-saturated flow through typical two-dimensional dam cross-sections as a function of reservoir elevation. Several different flow scenarios are investigated based on the known hydrogeology, as well as information about typical subsurface structures gained from the resistivity survey. The flow models are also used to simulate the bulk electrical resistivity in the subsurface under varying saturation conditions, as well as the self-potential response using petrophysical relationships and electrokinetic coupling equations.
The self-potential survey consists of 512 measurements on the downstream area of the dam, and corroborates known seepage areas on the northwest side of the dam. Two direct-current resistivity profiles, each approximately 2,500 ft (762 m) long, indicate a broad sediment channel under the northwest side of the dam, which may be a significant seepage pathway through the foundation. A focusing of seepage in low-topography areas downstream of the dam is confirmed from the numerical flow simulations, which is also consistent with past observations. Little evidence of seepage is identified from the self-potential data on the southeast side of the dam, also consistent with historical records, though one possible area of focused seepage is identified near the outlet works. Integration of the geophysical surveys, numerical modeling, and observation well data provides a framework for better understanding seepage at the site through a combined hydrogeophysical approach.
","language":"English","publisher":"Environmental and Engineering Geophysical Society","doi":"10.2113/JEEG16.4.145","usgsCitation":"Minsley, B.J., Burton, B.L., Ikard, S., and Powers, M.H., 2011, Hydrogeophysical investigations at Hidden Dam, Raymond, California: Journal of Environmental & Engineering Geophysics, v. 16, no. 4, p. 145-164, https://doi.org/10.2113/JEEG16.4.145.","productDescription":"20 p.","startPage":"145","endPage":"164","ipdsId":"IP-022264","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":343136,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"Raymond","otherGeospatial":"Hidden Dam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.89240407943724,\n 37.11503755152569\n ],\n [\n -119.89349842071533,\n 37.11428466832454\n ],\n [\n -119.89163160324095,\n 37.11158107148775\n ],\n [\n -119.8788857460022,\n 37.103743517498586\n ],\n [\n -119.87809181213377,\n 37.10437671245446\n ],\n [\n -119.87950801849364,\n 37.10625915268512\n ],\n [\n -119.88178253173828,\n 37.10898005178678\n ],\n [\n -119.8827052116394,\n 37.10993833259634\n ],\n [\n -119.88624572753906,\n 37.112385316076114\n ],\n [\n -119.88764047622679,\n 37.113172440806665\n ],\n [\n -119.89240407943724,\n 37.11503755152569\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"16","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"595611c7e4b0d1f9f05067e5","contributors":{"authors":[{"text":"Minsley, Burke J. 0000-0003-1689-1306 bminsley@usgs.gov","orcid":"https://orcid.org/0000-0003-1689-1306","contributorId":697,"corporation":false,"usgs":true,"family":"Minsley","given":"Burke","email":"bminsley@usgs.gov","middleInitial":"J.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":702494,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burton, Bethany L. 0000-0001-5011-7862 blburton@usgs.gov","orcid":"https://orcid.org/0000-0001-5011-7862","contributorId":138925,"corporation":false,"usgs":true,"family":"Burton","given":"Bethany","email":"blburton@usgs.gov","middleInitial":"L.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":702493,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ikard, Scott 0000-0002-8304-4935 sikard@usgs.gov","orcid":"https://orcid.org/0000-0002-8304-4935","contributorId":171751,"corporation":false,"usgs":true,"family":"Ikard","given":"Scott","email":"sikard@usgs.gov","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":702603,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Powers, Michael H. 0000-0002-4480-7856 mhpowers@usgs.gov","orcid":"https://orcid.org/0000-0002-4480-7856","contributorId":851,"corporation":false,"usgs":true,"family":"Powers","given":"Michael","email":"mhpowers@usgs.gov","middleInitial":"H.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":702495,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70190223,"text":"70190223 - 2011 - White-tailed deer age ratios as herd management and predator impact measures in Pennsylvania","interactions":[],"lastModifiedDate":"2017-08-20T10:09:41","indexId":"70190223","displayToPublicDate":"2011-07-14T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3779,"text":"Wildlife Society Bulletin","onlineIssn":"1938-5463","printIssn":"0091-7648","active":true,"publicationSubtype":{"id":10}},"title":"White-tailed deer age ratios as herd management and predator impact measures in Pennsylvania","docAbstract":"A review of the Pennsylvania Game Commission's (PGC) deer management program and public concern about predator impacts on deer (Odocoileus virginianus) populations compelled the PGC to investigate the role of age ratios in developing management recommendations. Age ratios, such as proportion of juveniles in the antlerless harvest, may provide an index to population productivity and predator impacts. We estimated proportion of juveniles in the antlerless harvest from hunter-killed deer, population trends using the Pennsylvania (USA) sex–age–kill model, and reproduction from road-killed females. Using these estimates and a simulation model, we concluded that no single age-ratio value would serve as a reliable measure of population status. Wildlife Management Unit-specific trends in proportion of juveniles in the antlerless harvest and population trends provided the most relevant management information. We also provide an example decision chart to guide management actions in response to declining age ratios in the harvest. Although predator management activities and juvenile survival studies are often desired by the public, our decision-chart example indicated a number of deer management options exist before investing resources in predator management activities and juvenile survival studies.
","language":"English","publisher":"Wildlife Soceity","doi":"10.1002/wsb.81","usgsCitation":"Rosenberry, C.S., Norton, A.S., Diefenbach, D.R., Fleegle, J.T., and Wallingford, B.D., 2011, White-tailed deer age ratios as herd management and predator impact measures in Pennsylvania: Wildlife Society Bulletin, v. 35, no. 4, p. 461-468, https://doi.org/10.1002/wsb.81.","productDescription":"8 p.","startPage":"461","endPage":"468","ipdsId":"IP-026137","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":500014,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doaj.org/article/7a02161416ac43dcb898230c8d79945e","text":"External Repository"},{"id":344975,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Pennsylvannia","volume":"35","issue":"4","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2011-11-21","publicationStatus":"PW","scienceBaseUri":"599a9fb8e4b0b589267d58c1","contributors":{"authors":[{"text":"Rosenberry, Christopher S.","contributorId":171633,"corporation":false,"usgs":false,"family":"Rosenberry","given":"Christopher","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":708090,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Norton, Andrew S.","contributorId":171631,"corporation":false,"usgs":false,"family":"Norton","given":"Andrew","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":708091,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Diefenbach, Duane R. 0000-0001-5111-1147 drd11@usgs.gov","orcid":"https://orcid.org/0000-0001-5111-1147","contributorId":5235,"corporation":false,"usgs":true,"family":"Diefenbach","given":"Duane","email":"drd11@usgs.gov","middleInitial":"R.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":708025,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fleegle, Jeannine T.","contributorId":195768,"corporation":false,"usgs":false,"family":"Fleegle","given":"Jeannine","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":708092,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wallingford, Bret D.","contributorId":171632,"corporation":false,"usgs":false,"family":"Wallingford","given":"Bret","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":708093,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70236061,"text":"70236061 - 2011 - Gravity lineaments of the Cocos Plate: Evidence for a thermal contraction crack origin","interactions":[],"lastModifiedDate":"2022-08-26T16:47:18.375518","indexId":"70236061","displayToPublicDate":"2011-07-13T11:43:42","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9540,"text":"Geochemistry Geophysics Geosystems","active":true,"publicationSubtype":{"id":10}},"title":"Gravity lineaments of the Cocos Plate: Evidence for a thermal contraction crack origin","docAbstract":"Lineaments in the gravity field with wavelengths of 100–200 km affect the south-central Pacific. Because they align with absolute plate motion, it has been proposed that they reflect small-scale convection cells beneath the lithosphere that become elongated by basal shear. Alternatively, it was suggested that they reflect channelized flow of low viscosity material following the base of the lithosphere toward the East Pacific Rise, or that they result from lithospheric-scale thermal contraction cracks. Here, we report about previously undetected gravity lineaments across the Cocos Plate. Similarly to the south-central Pacific lineaments, the Cocos lineaments affect a plate that is anomalously shallow, with seamounts aligning mostly within their troughs. However, the Cocos lineaments strike markedly oblique to absolute plate motion and follow instead trajectories that are perpendicular to seafloor isochrons, a characteristic best explained by the thermal contraction crack model. The presence of steep scarps at the base of seamounts and the seismic imaging of faults striking perpendicular to isochrons further support this interpretation. Assuming that the slow subsidence rates of the south-central Pacific and Cocos plates reflect a warmer upper mantle, we propose that the associated thinner elastic plates favor the formation of thermal contraction cracks. A thinner elastic plate may also explain the pattern of ridge propagation in both areas. At large ridge offsets with a history of steady migration, the propagating segments have been those cutting into the shallower flanks, consistent with the concept that a warmer, thinner plate is more easily cracked.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2011GC003573","usgsCitation":"Cormier, M., Gans, K.D., and Wilson, D.S., 2011, Gravity lineaments of the Cocos Plate: Evidence for a thermal contraction crack origin: Geochemistry Geophysics Geosystems, v. 12, no. 7, Q07007, 19 p., https://doi.org/10.1029/2011GC003573.","productDescription":"Q07007, 19 p.","costCenters":[],"links":[{"id":474963,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2011gc003573","text":"Publisher Index Page"},{"id":405692,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","issue":"7","noUsgsAuthors":false,"publicationDate":"2011-07-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Cormier, Marie-Helene","contributorId":79765,"corporation":false,"usgs":true,"family":"Cormier","given":"Marie-Helene","email":"","affiliations":[],"preferred":false,"id":849890,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gans, Kathleen D. 0000-0002-7545-9655 kgans@usgs.gov","orcid":"https://orcid.org/0000-0002-7545-9655","contributorId":5403,"corporation":false,"usgs":true,"family":"Gans","given":"Kathleen","email":"kgans@usgs.gov","middleInitial":"D.","affiliations":[],"preferred":true,"id":849891,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wilson, Douglas S.","contributorId":68782,"corporation":false,"usgs":true,"family":"Wilson","given":"Douglas","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":849892,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70004660,"text":"70004660 - 2011 - Amplification and dampening of soil respiration by changes in temperature variability","interactions":[],"lastModifiedDate":"2013-01-20T12:53:47","indexId":"70004660","displayToPublicDate":"2011-07-13T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1011,"text":"Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Amplification and dampening of soil respiration by changes in temperature variability","docAbstract":"Accelerated release of carbon from soils is one of the most important feed backs related to anthropogenically induced climate change. Studies addressing the mechanisms for soil carbon release through organic matter decomposition have focused on the effect of changes in the average temperature, with little attention to changes in temperature vari-ability. Anthropogenic activities are likely to modify both the average state and the variability of the climatic system; therefore, the effects of future warming on decomposition should not only focus on trends in the average temperature, but also variability expressed as a change of the probability distribution of temperature.Using analytical and numerical analyses we tested common relationships between temperature and respiration and found that the variability of temperature plays an important role determining respiration rates of soil organic matter. Changes in temperature variability, without changes in the average temperature, can affect the amount of carbon released through respiration over the long term. Furthermore, simultaneous changes in the average and variance of temperature can either amplify or dampen there release of carbon through soil respiration as climate regimes change. The effects depend on the degree of convexity of the relationship between temperature and respiration and the magnitude of the change in temperature variance. A potential consequence of this effect of variability would be higher respiration in regions where both the mean and variance of temperature are expected to increase, such as in some low latitude regions; and lower amounts of respiration where the average temperature is expected to increase and the variance to decrease, such as in northern high latitudes.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Biogeosciences","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Copernicus Gesellschaft MBH","publisherLocation":"Gottingen, Germany","doi":"10.5194/bg-8-951-2011","usgsCitation":"Sierra, C., Harmon, M.E., Thomann, E., Perakis, S., and Loescher, H., 2011, Amplification and dampening of soil respiration by changes in temperature variability: Biogeosciences, v. 8, no. 4, p. 951-961, https://doi.org/10.5194/bg-8-951-2011.","startPage":"951","endPage":"961","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":474964,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/bg-8-951-2011","text":"Publisher Index Page"},{"id":266031,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.5194/bg-8-951-2011"},{"id":204058,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"8","issue":"4","noUsgsAuthors":false,"publicationDate":"2011-04-19","publicationStatus":"PW","scienceBaseUri":"4f4e49e5e4b07f02db5e6b5e","contributors":{"authors":[{"text":"Sierra, C.A.","contributorId":80908,"corporation":false,"usgs":true,"family":"Sierra","given":"C.A.","email":"","affiliations":[],"preferred":false,"id":351037,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harmon, M. E.","contributorId":80452,"corporation":false,"usgs":false,"family":"Harmon","given":"M.","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":351036,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thomann, E.","contributorId":32801,"corporation":false,"usgs":true,"family":"Thomann","given":"E.","email":"","affiliations":[],"preferred":false,"id":351034,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Perakis, S.S.","contributorId":82039,"corporation":false,"usgs":true,"family":"Perakis","given":"S.S.","affiliations":[],"preferred":false,"id":351038,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Loescher, H.W.","contributorId":68966,"corporation":false,"usgs":true,"family":"Loescher","given":"H.W.","affiliations":[],"preferred":false,"id":351035,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70004872,"text":"ofr20111003 - 2011 - Combined multibeam and LIDAR bathymetry data from eastern Long Island Sound and westernmost Block Island Sound-A regional perspective","interactions":[],"lastModifiedDate":"2012-02-02T00:15:56","indexId":"ofr20111003","displayToPublicDate":"2011-07-13T00:00:00","publicationYear":"2011","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":"2011-1003","title":"Combined multibeam and LIDAR bathymetry data from eastern Long Island Sound and westernmost Block Island Sound-A regional perspective","docAbstract":"Detailed bathymetric maps of the sea floor in Long Island Sound are of great interest to the Connecticut and New York research and management communities because of this estuary's ecological, recreational, and commercial importance. The completed, geologically interpreted digital terrain models (DTMs), ranging in area from 12 to 293 square kilometers, provide important benthic environmental information, yet many applications require a geographically broader perspective. For example, individual surveys are of limited use for the planning and construction of cross-sound infrastructure, such as cables and pipelines, or for the testing of regional circulation models. To address this need, we integrated 12 multibeam and 2 LIDAR (Light Detection and Ranging) contiguous bathymetric DTMs, produced by the National Oceanic and Atmospheric Administration during charting operations, into one dataset that covers much of eastern Long Island Sound and extends into westernmost Block Island Sound. The new dataset is adjusted to mean lower low water, is gridded to 4-meter resolution, and is provided in UTM Zone 18 NAD83 and geographic WGS84 projections. This resolution is adequate for sea floor-feature and process interpretation but is small enough to be queried and manipulated with standard Geographic Information System programs and to allow for future growth. Natural features visible in the grid include exposed bedrock outcrops, boulder lag deposits of submerged moraines, sand-wave fields, and scour depressions that reflect the strength of the oscillating and asymmetric tidal currents. Bedform asymmetry allows interpretations of net sediment transport. Anthropogenic artifacts visible in the bathymetric data include a dredged channel, shipwrecks, dredge spoils, mooring anchors, prop-scour depressions, buried cables, and bridge footings. Together the merged data reveal a larger, more continuous perspective of bathymetric topography than previously available, providing a fundamental framework for research and resource management activities in this major east-coast estuary.","language":"English","publisher":"U. S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20111003","usgsCitation":"Poppe, L., Danforth, W.W., McMullen, K., Parker, C.E., and Doran, E.F., 2011, Combined multibeam and LIDAR bathymetry data from eastern Long Island Sound and westernmost Block Island Sound-A regional perspective: U.S. Geological Survey Open-File Report 2011-1003, HTML Page, https://doi.org/10.3133/ofr20111003.","productDescription":"HTML Page","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":116654,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2011_1003.png"},{"id":24384,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2011/1003/","linkFileType":{"id":5,"text":"html"}}],"geographicExtents":"{\"crs\": {\"type\": \"name\", \"properties\": {\"name\": \"urn:ogc:def:crs:OGC:1.3:CRS84\"}}, \"geometry\": {\"type\": \"Polygon\", \"coordinates\": [[[-72.64578435384327, 41.21420149913303], [-72.4009181372618, 41.21869445723546], [-72.34196176021061, 41.23431022624995], [-72.34190696803863, 41.262582986991944], [-72.3244830573488, 41.257596899341706], [-72.30026491733334, 41.27606186129919], [-72.25999267092757, 41.28055481940162], [-72.24503440797686, 41.29847185963929], [-72.22481609651601, 41.29666371796391], [-72.22103543664933, 41.30937550186342], [-72.21955604800584, 41.29337618764508], [-72.20448820071117, 41.28625320528759], [-72.2032827729276, 41.31255344783832], [-72.1848178109701, 41.32762129513297], [-72.17533876521745, 41.32679941255328], [-72.16744869245224, 41.30570442634073], [-72.15035353479428, 41.31551222512526], [-72.14761392619523, 41.32548440042575], [-72.14394285067254, 41.30274564905378], [-72.11249214395565, 41.29891019701514], [-72.09030131430347, 41.31551222512526], [-72.08843695748531, 41.32339903350462], [-72.0998899444001, 41.336935964369715], [-72.09210945597884, 41.34438769975909], [-72.09923243833633, 41.34937378740931], [-72.08597273271701, 41.367729165022844], [-72.07868537384358, 41.32838838554074], [-72.06652151166386, 41.31529305643735], [-72.05550828509575, 41.31748474331659], [-72.0551755981885, 41.3286508270778], [-72.0526042999808, 41.318306625896305], [-72.04367317594794, 41.322909168342676], [-72.03539955797886, 41.33622366613397], [-72.03682415445036, 41.323731050922376], [-72.0466319532349, 41.32016955974362], [-72.0347420519151, 41.31271782435429], [-72.01589354475375, 41.32258041531079], [-72.01161975533925, 41.30712902281224], [-72.00526386338949, 41.30636193240452], [-71.9995654775035, 41.31737515897261], [-71.99940110098754, 41.301649805614176], [-72.01331831267065, 41.30038958565863], [-72.01320872832669, 41.28619841311561], [-71.99929151664361, 41.28817093130693], [-71.99457938985327, 41.26992513803737], [-72.0077295111286, 41.26017213142484], [-72.0126060144349, 41.26384320694752], [-72.00729117375278, 41.27085660496103], [-72.020824840232, 41.276116653471206], [-72.02235902104745, 41.262254233960086], [-72.02871491299722, 41.263459661743646], [-72.03854491854008, 41.24899862455118], [-72.0029077999943, 41.25261081169149], [-71.99123706736245, 41.260994014004524], [-71.99918193229963, 41.24756993186928], [-71.99923672447161, 41.19354485029635], [-72.1901326516522, 41.189764190429685], [-72.21226868913239, 41.17825783431373], [-72.20777573102997, 41.17086089109635], [-72.21298098736813, 41.16346394787899], [-72.2682662888966, 41.15502595339394], [-72.28486831700674, 41.159628495840316], [-72.32311325304923, 41.14012248261521], [-72.35450916759413, 41.14072519650701], [-72.38990491069363, 41.103959649107956], [-72.65044168846163, 41.106206128159165], [-72.65126357104135, 41.11749331558719], [-72.65729070995921, 41.11743852341521], [-72.65093481800946, 41.118369990338884], [-72.65082523366549, 41.153108227374624], [-72.64512684777951, 41.15886140543259], [-72.64578435384327, 41.21420149913303]]]}, \"properties\": {\"extentType\": \"Custom\", \"code\": \"\", \"name\": \"\", \"notes\": \"\", \"promotedForReuse\": false, \"abbreviation\": \"\", \"shortName\": \"\", \"description\": \"\"}, \"bbox\": [-72.65729070995921, 41.10330214304421, -71.99112748301849, 41.367729165022844], \"type\": \"Feature\", \"id\": \"3091921\"}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b24e4b07f02db6ae707","contributors":{"authors":[{"text":"Poppe, L.J.","contributorId":72782,"corporation":false,"usgs":true,"family":"Poppe","given":"L.J.","affiliations":[],"preferred":false,"id":351538,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Danforth, W. W.","contributorId":16386,"corporation":false,"usgs":true,"family":"Danforth","given":"W.","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":351534,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McMullen, K.Y.","contributorId":51857,"corporation":false,"usgs":true,"family":"McMullen","given":"K.Y.","email":"","affiliations":[],"preferred":false,"id":351537,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Parker, Castle E.","contributorId":28684,"corporation":false,"usgs":false,"family":"Parker","given":"Castle","email":"","middleInitial":"E.","affiliations":[{"id":12448,"text":"U.S. National Oceanic and Atmospheric Administration","active":true,"usgs":false}],"preferred":false,"id":351535,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Doran, E. F.","contributorId":31066,"corporation":false,"usgs":true,"family":"Doran","given":"E.","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":351536,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70004542,"text":"70004542 - 2011 - Density estimation in a wolverine population using spatial capture-recapture models","interactions":[],"lastModifiedDate":"2021-05-18T14:29:16.586796","indexId":"70004542","displayToPublicDate":"2011-07-13T00:00:00","publicationYear":"2011","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":"Density estimation in a wolverine population using spatial capture-recapture models","docAbstract":"Classical closed-population capture-recapture models do not accommodate the spatial information inherent in encounter history data obtained from camera-trapping studies. As a result, individual heterogeneity in encounter probability is induced, and it is not possible to estimate density objectively because trap arrays do not have a well-defined sample area. We applied newly-developed, capture-recapture models that accommodate the spatial attribute inherent in capture-recapture data to a population of wolverines (Gulo gulo) in Southeast Alaska in 2008. We used camera-trapping data collected from 37 cameras in a 2,140-km2 area of forested and open habitats largely enclosed by ocean and glacial icefields. We detected 21 unique individuals 115 times. Wolverines exhibited a strong positive trap response, with an increased tendency to revisit previously visited traps. Under the trap-response model, we estimated wolverine density at 9.7 individuals/1,000-km2(95% Bayesian CI: 5.9-15.0). Our model provides a formal statistical framework for estimating density from wolverine camera-trapping studies that accounts for a behavioral response due to baited traps. Further, our model-based estimator does not have strict requirements about the spatial configuration of traps or length of trapping sessions, providing considerable operational flexibility in the development of field studies.","language":"English","publisher":"The Wildlife Society","publisherLocation":"Bethesda, MD","doi":"10.1002/jwmg.79","usgsCitation":"Royle, J., Magoun, A.J., Gardner, B., Valkenbury, P., and Lowell, R.E., 2011, Density estimation in a wolverine population using spatial capture-recapture models: Journal of Wildlife Management, v. 75, no. 3, p. 604-611, https://doi.org/10.1002/jwmg.79.","productDescription":"8 p.","startPage":"604","endPage":"611","numberOfPages":"7","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":204059,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Southeast Alaska","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 173,54.666666666666664 ], [ 173,71.83333333333333 ], [ -130,71.83333333333333 ], [ -130,54.666666666666664 ], [ 173,54.666666666666664 ] ] ] } } ] }","volume":"75","issue":"3","noUsgsAuthors":false,"publicationDate":"2011-05-11","publicationStatus":"PW","scienceBaseUri":"4f4e4ab2e4b07f02db66eb17","contributors":{"editors":[{"text":"McKelvey, Kevin","contributorId":112036,"corporation":false,"usgs":true,"family":"McKelvey","given":"Kevin","affiliations":[],"preferred":false,"id":508242,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"authors":[{"text":"Royle, J. Andrew 0000-0003-3135-2167","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":80808,"corporation":false,"usgs":true,"family":"Royle","given":"J. Andrew","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":350664,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Magoun, Audrey J.","contributorId":34249,"corporation":false,"usgs":true,"family":"Magoun","given":"Audrey","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":350663,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gardner, Beth","contributorId":91612,"corporation":false,"usgs":false,"family":"Gardner","given":"Beth","affiliations":[{"id":13553,"text":"University of Washington-Seattle","active":true,"usgs":false}],"preferred":false,"id":350665,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Valkenbury, Patrick","contributorId":25279,"corporation":false,"usgs":true,"family":"Valkenbury","given":"Patrick","email":"","affiliations":[],"preferred":false,"id":350662,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lowell, Richard E.","contributorId":8214,"corporation":false,"usgs":true,"family":"Lowell","given":"Richard","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":350661,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70042936,"text":"70042936 - 2011 - Simulating oil droplet dispersal from the Deepwater Horizon spill with a Lagrangian approach","interactions":[],"lastModifiedDate":"2021-03-17T14:50:37.435241","indexId":"70042936","displayToPublicDate":"2011-07-13T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Simulating oil droplet dispersal from the Deepwater Horizon spill with a Lagrangian approach","docAbstract":"An analytical multiphase plume model, combined with time-varying flow and hydrographic fields generated by the 3-D South Atlantic Bight and Gulf of Mexico model (SABGOM) hydrodynamic model, were used as input to a Lagrangian transport model (LTRANS), to simulate transport of oil droplets dispersed at depth from the recent Deepwater Horizon MC 252 oil spill. The plume model predicts a stratification-dominated near field, in which small oil droplets detrain from the central plume containing faster rising large oil droplets and gas bubbles and become trapped by density stratification. Simulated intrusion (trap) heights of ∼ 310–370 m agree well with the midrange of conductivity-temperature-depth observations, though the simulated variation in trap height was lower than observed, presumably in part due to unresolved variability in source composition (percentage oil versus gas) and location (multiple leaks during first half of spill). Simulated droplet trajectories by the SABGOM-LTRANS modeling system showed that droplets with diameters between 10 and 50 μm formed a distinct subsurface plume, which was transported horizontally and remained in the subsurface for >1 month. In contrast, droplets with diameters ≥90 μm rose rapidly to the surface. Simulated trajectories of droplets ≤50 μm in diameter were found to be consistent with field observations of a southwest-tending subsurface plume in late June 2010 reported by Camilli et al. [2010]. Model results suggest that the subsurface plume looped around to the east, with potential subsurface oil transport to the northeast and southeast. Ongoing work is focusing on adding degradation processes to the model to constrain droplet dispersal.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Monitoring and modeling the Deepwater Horizon oil spill: A record-breaking enterprise","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"American Geophysical Union","doi":"10.1029/2011GM001102","usgsCitation":"North, E.W., Adams, E.E., Schlag, Z., Sherwood, C.R., He, R., Hyun, H., and Socolofsky, S.A., 2011, Simulating oil droplet dispersal from the Deepwater Horizon spill with a Lagrangian approach, chap. of Monitoring and modeling the Deepwater Horizon oil spill: A record-breaking enterprise, v. 195, p. 217-226, https://doi.org/10.1029/2011GM001102.","productDescription":"10 p.","startPage":"217","endPage":"226","ipdsId":"IP-032315","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":384453,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2011GM001102"},{"id":273850,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Gulf Of Mexico","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -97.86,18.18 ], [ -97.86,30.4 ], [ -81.04,30.4 ], [ -81.04,18.18 ], [ -97.86,18.18 ] ] ] } } ] }","volume":"195","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51c02ff6e4b0ee1529ed3d55","contributors":{"authors":[{"text":"North, Elizabeth W.","contributorId":41727,"corporation":false,"usgs":true,"family":"North","given":"Elizabeth","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":472621,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Adams, E. Eric","contributorId":14561,"corporation":false,"usgs":true,"family":"Adams","given":"E.","email":"","middleInitial":"Eric","affiliations":[],"preferred":false,"id":472620,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schlag, Zachary","contributorId":101548,"corporation":false,"usgs":true,"family":"Schlag","given":"Zachary","email":"","affiliations":[],"preferred":false,"id":472625,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sherwood, Christopher R. 0000-0001-6135-3553 csherwood@usgs.gov","orcid":"https://orcid.org/0000-0001-6135-3553","contributorId":2866,"corporation":false,"usgs":true,"family":"Sherwood","given":"Christopher","email":"csherwood@usgs.gov","middleInitial":"R.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":472619,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"He, Ruoying","contributorId":68029,"corporation":false,"usgs":true,"family":"He","given":"Ruoying","affiliations":[],"preferred":false,"id":472622,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hyun, Hoon","contributorId":68206,"corporation":false,"usgs":true,"family":"Hyun","given":"Hoon","email":"","affiliations":[],"preferred":false,"id":472623,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Socolofsky, Scott A.","contributorId":93181,"corporation":false,"usgs":true,"family":"Socolofsky","given":"Scott","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":472624,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70208567,"text":"70208567 - 2011 - Treatment of anchor pixels in the METRIC model for improved estimation of sensible and latent heat fluxes","interactions":[],"lastModifiedDate":"2020-02-20T10:00:34","indexId":"70208567","displayToPublicDate":"2011-07-12T10:23:50","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1927,"text":"Hydrological Sciences Journal","active":true,"publicationSubtype":{"id":10}},"title":"Treatment of anchor pixels in the METRIC model for improved estimation of sensible and latent heat fluxes","docAbstract":"Reliable estimation of sensible heat flux (H) is important in energy balance models for quantifying evapotranspiration (ET). This study was conducted to evaluate the value of adding the Priestley-Taylor (PT) equation to the METRIC (Mapping Evapotranspiration at high Resolution with Internalized Calibration) model. METRIC was used to estimate energy fluxes for 10 Landsat images from the 2005, 2006 and 2007 crop growing seasons in south-central Nebraska, USA, where each image owing to recent rainfall exhibited high residual moisture content even at the hot pixel. The METRIC model performed satisfactorily for net radiation (Rn ) and soil heat flux (G) estimation with a root mean square error (RMSE) of 52 and 24 W m-2, respectively. A RMSE of 122 W m-2 for H indicated the limitation of the METRIC model in estimating H for high residual moisture content of the hot pixel (Alfalfa reference ET fraction, ET r F > 0.15). The modified METRIC model (wet METRIC or wMETRIC) incorporating the PT equation was applied to calculate H at the anchor pixels (hot and cold) for high residual moisture content of the hot pixel. The α coefficient of the PT equation was locally calibrated using hourly meteorological data from an automatic weather station and Rn and G data from a Bowen ratio flux tower. The mean α coefficient value was 1.14. The wMETRIC model reduced the RMSE of H from 122 to 64 W m-2 and that of latent heat flux, LE, from 163 to 106 W m-2. The RMSE of daily ET decreased from 1.7 to 1.1 mm d-1 with wMETRIC. The results indicate that treatment of anchor pixels for high residual moisture content with the PT approach gives improved estimation of H, LE and daily ET. It is recommended that the wMETRIC model be used for estimating ET if the hot pixel has high residual moisture (i.e. reference ET fraction > 0.15).
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/02626667.2011.587424","usgsCitation":"Singh, R.K., and Irmak, A., 2011, Treatment of anchor pixels in the METRIC model for improved estimation of sensible and latent heat fluxes: Hydrological Sciences Journal, v. 56, no. 5, p. 895-906, https://doi.org/10.1080/02626667.2011.587424.","productDescription":"12 p.","startPage":"895","endPage":"906","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":372386,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nebraska","otherGeospatial":"South Central Agricultural Laboratory","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -98.13434600830078,\n 40.53859061142965\n ],\n [\n -98.06156158447266,\n 40.53859061142965\n ],\n [\n -98.06156158447266,\n 40.57563021524945\n ],\n [\n -98.13434600830078,\n 40.57563021524945\n ],\n [\n -98.13434600830078,\n 40.53859061142965\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"56","issue":"5","noUsgsAuthors":false,"publicationDate":"2011-07-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Singh, Ramesh K. 0000-0002-8164-3483 rsingh@usgs.gov","orcid":"https://orcid.org/0000-0002-8164-3483","contributorId":3895,"corporation":false,"usgs":true,"family":"Singh","given":"Ramesh","email":"rsingh@usgs.gov","middleInitial":"K.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":782549,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Irmak, A.","contributorId":101473,"corporation":false,"usgs":true,"family":"Irmak","given":"A.","email":"","affiliations":[],"preferred":false,"id":782550,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70003468,"text":"70003468 - 2011 - Coastal subsidence in Oregon, USA during the giant Cascadia earthquake of AD 1700","interactions":[],"lastModifiedDate":"2021-05-21T14:10:05.251733","indexId":"70003468","displayToPublicDate":"2011-07-12T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3219,"text":"Quaternary Science Reviews","active":true,"publicationSubtype":{"id":10}},"title":"Coastal subsidence in Oregon, USA during the giant Cascadia earthquake of AD 1700","docAbstract":"Quantitative estimates of land-level change during the giant AD 1700 Cascadia earthquake along the Oregon coast are inferred from relative sea-level changes reconstructed from fossil foraminiferal assemblages preserved within the stratigraphic record. A transfer function, based upon a regional training set of modern sediment samples from Oregon estuaries, is calibrated to fossil assemblages in sequences of samples across buried peat-mud and peat-sand contacts marking the AD 1700 earthquake. Reconstructions of sample elevations with sample-specific errors estimate the amount of coastal subsidence during the earthquake at six sites along 400 km of coast. The elevation estimates are supported by lithological, carbon isotope, and faunal tidal zonation data. Coseismic subsidence at Nehalem River, Nestucca River, Salmon River, Alsea Bay, Siuslaw River and South Slough varies between 0.18 m and 0.85 m with errors between 0.18 m and 0.32 m. These subsidence estimates are more precise, consistent, and generally lower than previous semi-quantitative estimates. Following earlier comparisons of semi-quantitative subsidence estimates with elastic dislocation models of megathrust rupture during great earthquakes, our lower estimates for central and northern Oregon are consistent with modeled rates of strain accumulation and amounts of slip on the subduction megathrust, and thus, with a magnitude of 9 for the AD 1700 earthquake.","language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.quascirev.2010.11.017","usgsCitation":"Hawkes, A., Horton, B.P., Nelson, A., Vane, C., and Sawai, Y., 2011, Coastal subsidence in Oregon, USA during the giant Cascadia earthquake of AD 1700: Quaternary Science Reviews, v. 30, no. 3-4, p. 364-376, https://doi.org/10.1016/j.quascirev.2010.11.017.","productDescription":"13 p.","startPage":"364","endPage":"376","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":474966,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://nora.nerc.ac.uk/id/eprint/13572/1/Hawkes_QSR_2011.pdf","text":"External Repository"},{"id":204028,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -125.079345703125,\n 42.01665183556825\n ],\n [\n -123.01391601562499,\n 42.01665183556825\n ],\n [\n -123.01391601562499,\n 46.27863122156088\n ],\n [\n -125.079345703125,\n 46.27863122156088\n ],\n [\n -125.079345703125,\n 42.01665183556825\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"30","issue":"3-4","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b24e4b07f02db6aeaad","contributors":{"authors":[{"text":"Hawkes, A. D.","contributorId":97618,"corporation":false,"usgs":false,"family":"Hawkes","given":"A. D.","affiliations":[],"preferred":false,"id":347405,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Horton, B. P.","contributorId":96816,"corporation":false,"usgs":false,"family":"Horton","given":"B.","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":347404,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nelson, A.R. 0000-0001-7117-7098","orcid":"https://orcid.org/0000-0001-7117-7098","contributorId":55078,"corporation":false,"usgs":true,"family":"Nelson","given":"A.R.","affiliations":[],"preferred":false,"id":347403,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vane, C. H.","contributorId":12172,"corporation":false,"usgs":false,"family":"Vane","given":"C. H.","affiliations":[],"preferred":false,"id":347401,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sawai, Y.","contributorId":47510,"corporation":false,"usgs":false,"family":"Sawai","given":"Y.","affiliations":[],"preferred":false,"id":347402,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70003819,"text":"70003819 - 2011 - Agricultural herbicide transport in a first-order intermittent stream, Nebraska, USA","interactions":[],"lastModifiedDate":"2017-01-18T13:42:51","indexId":"70003819","displayToPublicDate":"2011-07-12T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":833,"text":"Applied Engineering in Agriculture","active":true,"publicationSubtype":{"id":10}},"title":"Agricultural herbicide transport in a first-order intermittent stream, Nebraska, USA","docAbstract":"The behavior of herbicides in surface waters is a function of many variables, including scale of the watershed, physical and chemical properties of the herbicide, physical and chemical properties of the soil, rainfall intensity, and time of year. In this study, the transport of 6 herbicides and 12 herbicide degradates was examined during the 2004 growing season in an intermediate-scale agricultural watershed (146 ha) that is drained by a first-order intermittent stream, and the mass load for each herbicide in the stream was estimated. The herbicide load during the first week of storm events after application ranged from 17% of annual load for trifluralin to 84% of annual load for acetochlor. The maximum weekly herbicide load in the stream was generally within the first 3 weeks after application for those compounds that were applied within the watershed during 2004, and later for herbicides not applied within the watershed during 2004 but still detected in the stream. The apparent dominant mode of herbicide transport in the stream-determined by analysis amongst herbicide and conservative ion concentrations at different points in the hydrograph and in base flow samples-was either overland runoff or shallow subsurface flow, depending on the elapsed time after application and type of herbicide. The load as a percentage of use (LAPU) for the parent compounds in this study was similar to literature values for those compounds applied by the farmer within the watershed, but smaller for those herbicides that had rainfall as their only source within the watershed.","language":"English","publisher":"American Society Agricultural & Biological Engineers","doi":"10.13031/2013.36227","usgsCitation":"Vogel, J.R., and Linard, J., 2011, Agricultural herbicide transport in a first-order intermittent stream, Nebraska, USA: Applied Engineering in Agriculture, v. 27, no. 1, p. 63-74, https://doi.org/10.13031/2013.36227.","productDescription":"12 p.","startPage":"63","endPage":"74","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"links":[{"id":502534,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://digitalcommons.unl.edu/usgsstaffpub/519","text":"External Repository"},{"id":204045,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nebraska","county":"Colfax","volume":"27","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e49e6e4b07f02db5e71b3","contributors":{"authors":[{"text":"Vogel, J. R.","contributorId":21639,"corporation":false,"usgs":true,"family":"Vogel","given":"J.","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":349014,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Linard, J.I.","contributorId":64376,"corporation":false,"usgs":true,"family":"Linard","given":"J.I.","email":"","affiliations":[],"preferred":false,"id":349015,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70004865,"text":"ofr20111162 - 2011 - Analysis of dam-passage survival of yearling and subyearling Chinook salmon and juvenile steelhead at The Dalles Dam, Oregon, 2010","interactions":[],"lastModifiedDate":"2012-02-02T00:15:56","indexId":"ofr20111162","displayToPublicDate":"2011-07-12T00:00:00","publicationYear":"2011","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":"2011-1162","title":"Analysis of dam-passage survival of yearling and subyearling Chinook salmon and juvenile steelhead at The Dalles Dam, Oregon, 2010","docAbstract":"We performed a series of analyses of mark-recapture data from a study at The Dalles Dam during 2010 to determine if model assumptions for estimation of juvenile salmonid dam-passage survival were met and if results were similar to those using the University of Washington's newly developed ATLAS software. The study was conducted by the Pacific Northwest National Laboratory and used acoustic telemetry of yearling Chinook salmon, juvenile steelhead, and subyearling Chinook salmon released at three sites according to the new virtual/paired-release statistical model. This was the first field application of the new model, and the results were used to measure compliance with minimum survival standards set forth in a recent Biological Opinion. Our analyses indicated that most model assumptions were met. The fish groups mixed in time and space, and no euthanized tagged fish were detected. Estimates of reach-specific survival were similar in fish tagged by each of the six taggers during the spring, but not in the summer. Tagger effort was unevenly allocated temporally during tagging of subyearling Chinook salmon in the summer; the difference in survival estimates among taggers was more likely a result of a temporal trend in actual survival than of tagger effects. The reach-specific survival of fish released at the three sites was not equal in the reaches they had in common for juvenile steelhead or subyearling Chinook salmon, violating one model assumption. This violation did not affect the estimate of dam-passage survival, because data from the common reaches were not used in its calculation. Contrary to expectation, precision of survival estimates was not improved by using the most parsimonious model of recapture probabilities instead of the fully parameterized model. Adjusting survival estimates for differences in fish travel times and tag lives increased the dam-passage survival estimate for yearling Chinook salmon by 0.0001 and for juvenile steelhead by 0.0004. The estimate was unchanged for subyearling Chinook salmon. The tag-life-adjusted dam-passage survival estimates from our analyses were 0.9641 (standard error [SE] 0.0096) for yearling Chinook salmon, 0.9534 (SE 0.0097) for juvenile steelhead, and 0.9404 (SE 0.0091) for subyearling Chinook salmon. These were within 0.0001 of estimates made by the University of Washington using the ATLAS software. Contrary to the intent of the virtual/paired-release model to adjust estimates of the paired-release model downward in order to account for differential handling mortality rates between release groups, random variation in survival estimates may result in an upward adjustment of survival relative to estimates from the paired-release model. Further investigation of this property of the virtual/paired-release model likely would prove beneficial. In addition, we suggest that differential selective pressures near release sites of the two control groups could bias estimates of dam-passage survival from the virtual/paired-release model.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20111162","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Beeman, J.W., Kock, T.J., Perry, R.W., and Smith, S.G., 2011, Analysis of dam-passage survival of yearling and subyearling Chinook salmon and juvenile steelhead at The Dalles Dam, Oregon, 2010: U.S. Geological Survey Open-File Report 2011-1162, vi, 32 p.; Appendices, https://doi.org/10.3133/ofr20111162.","productDescription":"vi, 32 p.; Appendices","additionalOnlineFiles":"N","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":116803,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2011_1162.bmp"},{"id":24380,"rank":200,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2011/1162/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4acfe4b07f02db680659","contributors":{"authors":[{"text":"Beeman, John W. jbeeman@usgs.gov","contributorId":2646,"corporation":false,"usgs":true,"family":"Beeman","given":"John","email":"jbeeman@usgs.gov","middleInitial":"W.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":351519,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kock, Tobias J. 0000-0001-8976-0230 tkock@usgs.gov","orcid":"https://orcid.org/0000-0001-8976-0230","contributorId":3038,"corporation":false,"usgs":true,"family":"Kock","given":"Tobias","email":"tkock@usgs.gov","middleInitial":"J.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":351521,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Perry, Russell W. 0000-0003-4110-8619 rperry@usgs.gov","orcid":"https://orcid.org/0000-0003-4110-8619","contributorId":2820,"corporation":false,"usgs":true,"family":"Perry","given":"Russell","email":"rperry@usgs.gov","middleInitial":"W.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":351520,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, Steven G. sgsmith@usgs.gov","contributorId":1560,"corporation":false,"usgs":true,"family":"Smith","given":"Steven","email":"sgsmith@usgs.gov","middleInitial":"G.","affiliations":[],"preferred":true,"id":351518,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70004861,"text":"ofr20111124 - 2011 - Computer programs for forward and inverse modeling of acoustic and electromagnetic data","interactions":[],"lastModifiedDate":"2012-02-02T00:15:55","indexId":"ofr20111124","displayToPublicDate":"2011-07-12T00:00:00","publicationYear":"2011","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":"2011-1124","title":"Computer programs for forward and inverse modeling of acoustic and electromagnetic data","docAbstract":"A suite of computer programs was developed by U.S. Geological Survey personnel for forward and inverse modeling of acoustic and electromagnetic data. This report describes the computer resources that are needed to execute the programs, the installation of the programs, the program designs, some tests of their accuracy, and some suggested improvements.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20111124","usgsCitation":"Ellefsen, K.J., 2011, Computer programs for forward and inverse modeling of acoustic and electromagnetic data: U.S. Geological Survey Open-File Report 2011-1124, iii, 11 p., https://doi.org/10.3133/ofr20111124.","productDescription":"iii, 11 p.","startPage":"i","endPage":"11","numberOfPages":"14","onlineOnly":"N","additionalOnlineFiles":"Y","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":116223,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2011_1124.png"},{"id":24378,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2011/1124/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b15e4b07f02db6a490d","contributors":{"authors":[{"text":"Ellefsen, Karl J. 0000-0003-3075-4703 ellefsen@usgs.gov","orcid":"https://orcid.org/0000-0003-3075-4703","contributorId":789,"corporation":false,"usgs":true,"family":"Ellefsen","given":"Karl","email":"ellefsen@usgs.gov","middleInitial":"J.","affiliations":[{"id":82803,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":false}],"preferred":true,"id":351497,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70004846,"text":"fs20113074 - 2011 - USGS science for the Nation's changing coasts; shoreline change assessment","interactions":[],"lastModifiedDate":"2012-02-02T00:15:54","indexId":"fs20113074","displayToPublicDate":"2011-07-12T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2011-3074","title":"USGS science for the Nation's changing coasts; shoreline change assessment","docAbstract":"The coastline of the United States features some of the most popular tourist and recreational destinations in the world and is the site of intense residential, commercial, and industrial development. The coastal zone also has extensive and pristine natural areas, with diverse ecosystems providing essential habitat and resources that support wildlife, fish, and human use. Coastal erosion is a widespread process along most open-ocean shores of the United States that affects both developed and natural coastlines. As the coast changes, there are a wide range of ways that change can affect coastal communities, habitats, and the physical characteristics of the coast?including beach erosion, shoreline retreat, land loss, and damage to infrastructure. Global climate change will likely increase the rate of coastal change. A recent study of the U.S. Mid-Atlantic coast, for example, found that it is virtually certain that sandy beaches will erode faster in the future as sea level rises because of climate change.\n\nThe U.S. Geological Survey (USGS) is responsible for conducting research on coastal change hazards, understanding the processes that cause coastal change, and developing models to predict future change. To understand and adapt to shoreline change, accurate information regarding the past and present configurations of the shoreline is essential. A comprehensive, nationally consistent analysis of shoreline movement is needed. To meet this national need, the USGS is conducting an analysis of historical shoreline changes along open-ocean coasts of the conterminous United States and parts of Alaska and Hawaii, as well as the coasts of the Great Lakes.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20113074","usgsCitation":"Thieler, E.R., and Hapke, C.J., 2011, USGS science for the Nation's changing coasts; shoreline change assessment: U.S. Geological Survey Fact Sheet 2011-3074, 2 p., https://doi.org/10.3133/fs20113074.","productDescription":"2 p.","startPage":"1","endPage":"2","numberOfPages":"2","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":680,"text":"Woods Hole Science Center","active":false,"usgs":true}],"links":[{"id":116129,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs_2011_3074.gif"},{"id":24367,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2011/3074/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a26e4b07f02db60f91c","contributors":{"authors":[{"text":"Thieler, E. Robert 0000-0003-4311-9717 rthieler@usgs.gov","orcid":"https://orcid.org/0000-0003-4311-9717","contributorId":2488,"corporation":false,"usgs":true,"family":"Thieler","given":"E.","email":"rthieler@usgs.gov","middleInitial":"Robert","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":351471,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hapke, Cheryl J. 0000-0002-2753-4075 chapke@usgs.gov","orcid":"https://orcid.org/0000-0002-2753-4075","contributorId":2981,"corporation":false,"usgs":true,"family":"Hapke","given":"Cheryl","email":"chapke@usgs.gov","middleInitial":"J.","affiliations":[{"id":6676,"text":"USGS (retired)","active":true,"usgs":false}],"preferred":true,"id":351472,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ]}