{"pageNumber":"736","pageRowStart":"18375","pageSize":"25","recordCount":40783,"records":[{"id":70005917,"text":"sir20115163 - 2011 - New U.S. Geological Survey method for the assessment of reserve growth","interactions":[],"lastModifiedDate":"2018-07-31T10:21:05","indexId":"sir20115163","displayToPublicDate":"2011-11-08T00:00:00","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":"2011-5163","title":"New U.S. Geological Survey method for the assessment of reserve growth","docAbstract":"Reserve growth is defined as the estimated increases in quantities of crude oil, natural gas, and natural gas liquids that have the potential to be added to remaining reserves in discovered accumulations through extension, revision, improved recovery efficiency, and additions of new pools or reservoirs. A new U.S. Geological Survey method was developed to assess the reserve-growth potential of technically recoverable crude oil and natural gas to be added to reserves under proven technology currently in practice within the trend or play, or which reasonably can be extrapolated from geologically similar trends or plays. This method currently is in use to assess potential additions to reserves in discovered fields of the United States. The new approach involves (1) individual analysis of selected large accumulations that contribute most to reserve growth, and (2) conventional statistical modeling of reserve growth in remaining accumulations. This report will focus on the individual accumulation analysis.\r\nIn the past, the U.S. Geological Survey estimated reserve growth by statistical methods using historical recoverable-quantity data. Those statistical methods were based on growth rates averaged by the number of years since accumulation discovery. Accumulations in mature petroleum provinces with volumetrically significant reserve growth, however, bias statistical models of the data; therefore, accumulations with significant reserve growth are best analyzed separately from those with less significant reserve growth. Large (greater than 500 million barrels) and older (with respect to year of discovery) oil accumulations increase in size at greater rates late in their development history in contrast to more recently discovered accumulations that achieve most growth early in their development history. Such differences greatly affect the statistical methods commonly used to forecast reserve growth.\r\nThe individual accumulation-analysis method involves estimating the in-place petroleum quantity and its uncertainty, as well as the estimated (forecasted) recoverability and its respective uncertainty. These variables are assigned probabilistic distributions and are combined statistically to provide probabilistic estimates of ultimate recoverable quantities. Cumulative production and remaining reserves are then subtracted from the estimated ultimate recoverable quantities to provide potential reserve growth. In practice, results of the two methods are aggregated to various scales, the highest of which includes an entire country or the world total. The aggregated results are reported along with the statistically appropriate uncertainties.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20115163","usgsCitation":"Klett, T., Attanasi, E.D., Charpentier, R., Cook, T.A., Freeman, P., Gautier, D.L., Le, P., Ryder, R., Schenk, C.J., Tennyson, M., and Verma, M., 2011, New U.S. Geological Survey method for the assessment of reserve growth: U.S. Geological Survey Scientific Investigations Report 2011-5163, iv, 8 p., https://doi.org/10.3133/sir20115163.","productDescription":"iv, 8 p.","onlineOnly":"Y","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":116490,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2011_5163.png"},{"id":101699,"rank":100,"type":{"id":15,"text":"Index 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Center","active":true,"usgs":true}],"preferred":false,"id":353459,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Charpentier, Ronald R. charpentier@usgs.gov","contributorId":934,"corporation":false,"usgs":true,"family":"Charpentier","given":"Ronald R.","email":"charpentier@usgs.gov","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":353455,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cook, Troy A.","contributorId":52519,"corporation":false,"usgs":true,"family":"Cook","given":"Troy","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":353462,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Freeman, Philip A. 0000-0002-0863-7431 pfreeman@usgs.gov","orcid":"https://orcid.org/0000-0002-0863-7431","contributorId":193093,"corporation":false,"usgs":true,"family":"Freeman","given":"Philip A.","email":"pfreeman@usgs.gov","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":353461,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gautier, Donald L. gautier@usgs.gov","contributorId":1310,"corporation":false,"usgs":true,"family":"Gautier","given":"Donald","email":"gautier@usgs.gov","middleInitial":"L.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":353457,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Le, Phuong A. 0000-0003-2477-509X ple@usgs.gov","orcid":"https://orcid.org/0000-0003-2477-509X","contributorId":2151,"corporation":false,"usgs":true,"family":"Le","given":"Phuong A.","email":"ple@usgs.gov","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":353460,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ryder, Robert T.","contributorId":77918,"corporation":false,"usgs":true,"family":"Ryder","given":"Robert T.","affiliations":[],"preferred":false,"id":353463,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Schenk, Christopher J. 0000-0002-0248-7305 schenk@usgs.gov","orcid":"https://orcid.org/0000-0002-0248-7305","contributorId":826,"corporation":false,"usgs":true,"family":"Schenk","given":"Christopher","email":"schenk@usgs.gov","middleInitial":"J.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":353454,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Tennyson, Marilyn E. 0000-0002-5166-2421 tennyson@usgs.gov","orcid":"https://orcid.org/0000-0002-5166-2421","contributorId":1433,"corporation":false,"usgs":true,"family":"Tennyson","given":"Marilyn E.","email":"tennyson@usgs.gov","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":353458,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Verma, Mahendra K. mverma@usgs.gov","contributorId":1027,"corporation":false,"usgs":true,"family":"Verma","given":"Mahendra K.","email":"mverma@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":353456,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70005905,"text":"ofr20111283 - 2011 - Deposit model for closed-basin potash-bearing brines","interactions":[],"lastModifiedDate":"2012-02-02T00:16:02","indexId":"ofr20111283","displayToPublicDate":"2011-11-08T00:00:00","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":"2011-1283","title":"Deposit model for closed-basin potash-bearing brines","docAbstract":"Closed-basin potash-bearing brines are one of the types of potash deposits that are a source of potash production within the United States, as well as other countries. Though these deposits are of highly variable size, they are important sources of potash on a regional basis. In addition, these deposits have a high potential of co- and by-product production of one or more commodities such as lithium, boron, magnesium, and others.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20111283","usgsCitation":"Orris, G.J., 2011, Deposit model for closed-basin potash-bearing brines: U.S. Geological Survey Open-File Report 2011-1283, iii, 11 p., https://doi.org/10.3133/ofr20111283.","productDescription":"iii, 11 p.","onlineOnly":"Y","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":94691,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2011/1283/","linkFileType":{"id":5,"text":"html"}},{"id":116488,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2011_1283.png"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4ab1e4b07f02db66eaab","contributors":{"authors":[{"text":"Orris, Greta J. 0000-0002-2340-9955 greta@usgs.gov","orcid":"https://orcid.org/0000-0002-2340-9955","contributorId":3472,"corporation":false,"usgs":true,"family":"Orris","given":"Greta","email":"greta@usgs.gov","middleInitial":"J.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":662,"text":"Western Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":353452,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70003702,"text":"70003702 - 2011 - Prediction and assimilation of surf-zone processes using a Bayesian network: Part I: Forward models","interactions":[],"lastModifiedDate":"2021-01-07T20:07:40.784844","indexId":"70003702","displayToPublicDate":"2011-11-04T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1262,"text":"Coastal Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Prediction and assimilation of surf-zone processes using a Bayesian network: Part I: Forward models","docAbstract":"Prediction of coastal processes, including waves, currents, and sediment transport, can be obtained from a variety of detailed geophysical-process models with many simulations showing significant skill. This capability supports a wide range of research and applied efforts that can benefit from accurate numerical predictions. However, the predictions are only as accurate as the data used to drive the models and, given the large temporal and spatial variability of the surf zone, inaccuracies in data are unavoidable such that useful predictions require corresponding estimates of uncertainty. We demonstrate how a Bayesian-network model can be used to provide accurate predictions of wave-height evolution in the surf zone given very sparse and/or inaccurate boundary-condition data. The approach is based on a formal treatment of a data-assimilation problem that takes advantage of significant reduction of the dimensionality of the model system. We demonstrate that predictions of a detailed geophysical model of the wave evolution are reproduced accurately using a Bayesian approach. In this surf-zone application, forward prediction skill was 83%, and uncertainties in the model inputs were accurately transferred to uncertainty in output variables. We also demonstrate that if modeling uncertainties were not conveyed to the Bayesian network (i.e., perfect data or model were assumed), then overly optimistic prediction uncertainties were computed. More consistent predictions and uncertainties were obtained by including model-parameter errors as a source of input uncertainty. Improved predictions (skill of 90%) were achieved because the Bayesian network simultaneously estimated optimal parameters while predicting wave heights.","language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.coastaleng.2010.09.003","usgsCitation":"Plant, N.G., and Holland, K.T., 2011, Prediction and assimilation of surf-zone processes using a Bayesian network: Part I: Forward models: Coastal Engineering, v. 58, no. 1, p. 119-130, https://doi.org/10.1016/j.coastaleng.2010.09.003.","productDescription":"12 p.","startPage":"119","endPage":"130","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":204217,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"58","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4acce4b07f02db67e7e4","contributors":{"authors":[{"text":"Plant, Nathaniel G. 0000-0002-5703-5672 nplant@usgs.gov","orcid":"https://orcid.org/0000-0002-5703-5672","contributorId":3503,"corporation":false,"usgs":true,"family":"Plant","given":"Nathaniel","email":"nplant@usgs.gov","middleInitial":"G.","affiliations":[{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":348413,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Holland, K. Todd","contributorId":68748,"corporation":false,"usgs":true,"family":"Holland","given":"K.","email":"","middleInitial":"Todd","affiliations":[],"preferred":false,"id":348414,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70003693,"text":"70003693 - 2011 - Preface: Multiscale feedbacks in ecogeomorphology","interactions":[],"lastModifiedDate":"2017-05-23T12:19:32","indexId":"70003693","displayToPublicDate":"2011-11-04T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1801,"text":"Geomorphology","active":true,"publicationSubtype":{"id":10}},"title":"Preface: Multiscale feedbacks in ecogeomorphology","docAbstract":"Geomorphic systems are known to exhibit nonlinear responses to physical–biological feedbacks (Thornes, 1985; Baas, 2002; Reinhardt et al., 2010). These responses make understanding and/or predicting system response to change highly challenging. With growing concerns over ecosystem health, a pressing need exists for research that tries to elucidate these feedbacks (Jerolmack, 2008; Darby, 2010; National Research Council, 2010). A session was convened at the Fall 2008 meeting of the American Geophysical Union (AGU) to provide an outlet for some of this truly interdisciplinary and original research, which is central to understanding geomorphic and ecological dynamics. The session attracted over 39 contributions, which were divided into two well-attended oral sessions and a very busy poster session. This special issue presents new research from the AGU session, which highlights clear physical–biological feedbacks. The aim is to bring together contrasting perspectives on biological and geomorphic feedbacks in a diversity of physiographic settings, ranging from wetlands and estuaries, through rivers, to uplands. These papers highlight biological and physical feedbacks which involve the modulation or amplification of geomorphic processes. These papers will be of interest to a core geomorphology audience, and should also draw attention from the fields of ecohydraulics, hydroecology, ecohydrology, ecomorphology, biogeochemistry and biogeography, and biogeomorphology as well as the more traditional fields of hydrology, ecology and biology.  In this preface to the special issue, we a) review past contributions to the emerging field of ecogeomorphology and related disciplines, b) provide some context for how this topical special issue came to fruition, and c) summarize the contributions to this special issue.","language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.geomorph.2011.01.002","usgsCitation":"Wheaton, J.M., Gibbins, C., Wainwright, J., Larsen, L., and McElroy, B., 2011, Preface: Multiscale feedbacks in ecogeomorphology: Geomorphology, v. 126, no. 3-4, p. 265-268, https://doi.org/10.1016/j.geomorph.2011.01.002.","productDescription":"4 p.","startPage":"265","endPage":"268","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":204537,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"126","issue":"3-4","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4acce4b07f02db67e503","contributors":{"authors":[{"text":"Wheaton, Joseph M.","contributorId":29126,"corporation":false,"usgs":true,"family":"Wheaton","given":"Joseph","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":348371,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gibbins, Chris","contributorId":18501,"corporation":false,"usgs":true,"family":"Gibbins","given":"Chris","affiliations":[],"preferred":false,"id":348370,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wainwright, John","contributorId":6578,"corporation":false,"usgs":true,"family":"Wainwright","given":"John","email":"","affiliations":[],"preferred":false,"id":348369,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Larsen, Laurel G. lglarsen@usgs.gov","contributorId":1987,"corporation":false,"usgs":true,"family":"Larsen","given":"Laurel G.","email":"lglarsen@usgs.gov","affiliations":[],"preferred":false,"id":348368,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McElroy, Brandon 0000-0002-9683-4282","orcid":"https://orcid.org/0000-0002-9683-4282","contributorId":90453,"corporation":false,"usgs":true,"family":"McElroy","given":"Brandon","email":"","affiliations":[],"preferred":false,"id":348372,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70003802,"text":"70003802 - 2011 - Prediction and assimilation of surf-zone processes using a Bayesian network: Part II: Inverse models","interactions":[],"lastModifiedDate":"2021-01-07T20:06:01.681955","indexId":"70003802","displayToPublicDate":"2011-11-04T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1262,"text":"Coastal Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Prediction and assimilation of surf-zone processes using a Bayesian network: Part II: Inverse models","docAbstract":"<p><span>A Bayesian network model has been developed to simulate a relatively simple problem of wave propagation in the surf zone (detailed in Part I). Here, we demonstrate that this Bayesian model can provide both inverse modeling and data-assimilation solutions for predicting offshore wave heights and depth estimates given limited wave-height and depth information from an onshore location. The inverse method is extended to allow data assimilation using observational inputs that are not compatible with deterministic solutions of the problem. These inputs include sand bar positions (instead of bathymetry) and estimates of the intensity of wave breaking (instead of wave-height observations). Our results indicate that wave breaking information is essential to reduce prediction errors. In many practical situations, this information could be provided from a shore-based observer or from remote-sensing systems. We show that various combinations of the assimilated inputs significantly reduce the uncertainty in the estimates of water depths and wave heights in the model domain. Application of the Bayesian network model to new field data demonstrated significant predictive skill (R</span><sup>2</sup><span>&nbsp;</span><span>=</span><span>&nbsp;</span><span>0.7) for the inverse estimate of a month-long time series of offshore wave heights. The Bayesian inverse results include uncertainty estimates that were shown to be most accurate when given uncertainty in the inputs (e.g., depth and tuning parameters). Furthermore, the inverse modeling was extended to directly estimate tuning parameters associated with the underlying wave-process model. The inverse estimates of the model parameters not only showed an offshore wave height dependence consistent with results of previous studies but the uncertainty estimates of the tuning parameters also explain previously reported variations in the model parameters.</span></p>","language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.coastaleng.2010.11.002","usgsCitation":"Plant, N.G., and Holland, K.T., 2011, Prediction and assimilation of surf-zone processes using a Bayesian network: Part II: Inverse models: Coastal Engineering, v. 58, no. 3, p. 256-266, https://doi.org/10.1016/j.coastaleng.2010.11.002.","productDescription":"11 p.","startPage":"256","endPage":"266","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":204256,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"58","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4acce4b07f02db67e7da","contributors":{"authors":[{"text":"Plant, Nathaniel G. 0000-0002-5703-5672 nplant@usgs.gov","orcid":"https://orcid.org/0000-0002-5703-5672","contributorId":3503,"corporation":false,"usgs":true,"family":"Plant","given":"Nathaniel","email":"nplant@usgs.gov","middleInitial":"G.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true}],"preferred":true,"id":348949,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Holland, K. Todd","contributorId":68748,"corporation":false,"usgs":true,"family":"Holland","given":"K.","email":"","middleInitial":"Todd","affiliations":[],"preferred":false,"id":348950,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70005276,"text":"70005276 - 2011 - Probability of detecting perchlorate under natural conditions in deep groundwater in California and the Southwestern United States","interactions":[],"lastModifiedDate":"2021-02-23T15:52:40.639899","indexId":"70005276","displayToPublicDate":"2011-11-04T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Probability of detecting perchlorate under natural conditions in deep groundwater in California and the Southwestern United States","docAbstract":"We use data from 1626 groundwater samples collected in California, primarily from public drinking water supply wells, to investigate the distribution of perchlorate in deep groundwater under natural conditions. The wells were sampled for the California Groundwater Ambient Monitoring and Assessment Priority Basin Project. We develop a logistic regression model for predicting probabilities of detecting perchlorate at concentrations greater than multiple threshold concentrations as a function of climate (represented by an aridity index) and potential anthropogenic contributions of perchlorate (quantified as an anthropogenic score, AS). AS is a composite categorical variable including terms for nitrate, pesticides, and volatile organic compounds. Incorporating water-quality parameters in AS permits identification of perturbation of natural occurrence patterns by flushing of natural perchlorate salts from unsaturated zones by irrigation recharge as well as addition of perchlorate from industrial and agricultural sources. The data and model results indicate low concentrations (0.1-0.5 &mu;g/L) of perchlorate occur under natural conditions in groundwater across a wide range of climates, beyond the arid to semiarid climates in which they mostly have been previously reported. The probability of detecting perchlorate at concentrations greater than 0.1 &mu;g/L under natural conditions ranges from 50-70% in semiarid to arid regions of California and the Southwestern United States to 5-15% in the wettest regions sampled (the Northern California coast). The probability of concentrations above 1 &mu;g/L under natural conditions is low (generally <3%).","language":"English","publisher":"American Chemical Society Publications","publisherLocation":"Washington, D.C.","doi":"10.1021/es103103p","usgsCitation":"Fram, M.S., and Belitz, K., 2011, Probability of detecting perchlorate under natural conditions in deep groundwater in California and the Southwestern United States: Environmental Science & Technology, v. 45, no. 4, p. 1271-1277, https://doi.org/10.1021/es103103p.","productDescription":"7 p.","startPage":"1271","endPage":"1277","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":204538,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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 \"}}]}","volume":"45","issue":"4","noUsgsAuthors":false,"publicationDate":"2011-01-19","publicationStatus":"PW","scienceBaseUri":"4f4e4ae4e4b07f02db689f37","contributors":{"authors":[{"text":"Fram, Miranda S. 0000-0002-6337-059X mfram@usgs.gov","orcid":"https://orcid.org/0000-0002-6337-059X","contributorId":1156,"corporation":false,"usgs":true,"family":"Fram","given":"Miranda","email":"mfram@usgs.gov","middleInitial":"S.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":352198,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Belitz, Kenneth 0000-0003-4481-2345 kbelitz@usgs.gov","orcid":"https://orcid.org/0000-0003-4481-2345","contributorId":442,"corporation":false,"usgs":true,"family":"Belitz","given":"Kenneth","email":"kbelitz@usgs.gov","affiliations":[{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":352197,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70005570,"text":"70005570 - 2011 - Lead exposure and poisoning of songbirds using the Coeur d'Alene River Basin, Idaho, USA","interactions":[],"lastModifiedDate":"2020-01-09T19:39:20","indexId":"70005570","displayToPublicDate":"2011-11-02T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2006,"text":"Integrated Environmental Assessment and Management","active":true,"publicationSubtype":{"id":10}},"title":"Lead exposure and poisoning of songbirds using the Coeur d'Alene River Basin, Idaho, USA","docAbstract":"Previous studies have found widespread Pb poisoning of waterfowl in the Coeur d'Alene River Basin in northern Idaho, USA, which has been contaminated by mining and smelting activities. We studied the exposure of ground-feeding songbirds to Pb, sampling 204 American robins (<i>Turdus migratorius</i>), song sparrows (<i>Melospiza melodia</i>), and Swainson's thrushes (<i>Catharus ustulatus</i>) throughout the basin. These songbirds had mean blood Pb concentrations (mg/kg, dry weight) of less than 0.19 at a reference area (25 mg Pb/kg soil), 1.09 at moderately contaminated sites (170 to 1300 mg Pb/kg soil), and 2.06 at highly contaminated sites (2000 to 5000 mg Pb/kg soil). Based on guidelines for evaluating blood Pb in birds, 6% of robins from the highly contaminated sites had background concentrations, 24% were subclinically poisoned, 52% were clinically poisoned, and 18% were severely clinically poisoned with Pb. Blood Pb concentrations were lower in song sparrows than in robins and lowest in Swainson's thrushes. More than half of the robins and song sparrows from all contaminated sites and more than half of the Swainson's thrushes from highly contaminated sites showed at least 50% inhibition of the activity of the enzyme &delta;-aminolevulinic acid dehydratase (ALAD), commonly used as a measure of exposure to Pb. The highest hepatic Pb concentration of 61 mg/kg (dry weight) was detected in a song sparrow. Using Al as a marker for soil in songbird ingesta, we estimated average soil ingestion rates as 20% in robins, 17% in song sparrows, and 0.7% in Swainson's thrushes. Soil Pb in ingesta accounted for almost all of the songbirds' exposure to Pb. Based on these results, it is recommended that ecological risk assessments of ground-feeding songbirds at contaminated sites include soil ingestion as a pathway of exposure to Pb.","language":"English","publisher":"Society of Environmental Toxicology and Chemistry","doi":"10.1002/ieam.201","usgsCitation":"Hansen, J.A., Audet, D., Spears, B.L., Healy, K.A., Brazzle, R.E., Hoffman, D.J., Dailey, A., and Beyer, W.N., 2011, Lead exposure and poisoning of songbirds using the Coeur d'Alene River Basin, Idaho, USA: Integrated Environmental Assessment and Management, v. 7, no. 4, p. 587-595, https://doi.org/10.1002/ieam.201.","productDescription":"9 p.","startPage":"587","endPage":"595","numberOfPages":"9","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":204261,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"Coeur D'alene River Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -117.01538085937499,\n              47.27922900257082\n            ],\n            [\n              -116.4276123046875,\n              47.27922900257082\n            ],\n            [\n              -116.4276123046875,\n              47.70976154266637\n            ],\n            [\n              -117.01538085937499,\n              47.70976154266637\n            ],\n            [\n              -117.01538085937499,\n              47.27922900257082\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"7","issue":"4","noUsgsAuthors":false,"publicationDate":"2011-10-01","publicationStatus":"PW","scienceBaseUri":"4f4e4b1ae4b07f02db6a885e","contributors":{"authors":[{"text":"Hansen, James A.","contributorId":98454,"corporation":false,"usgs":true,"family":"Hansen","given":"James","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":352840,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Audet, Daniel","contributorId":43486,"corporation":false,"usgs":true,"family":"Audet","given":"Daniel","email":"","affiliations":[],"preferred":false,"id":352835,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Spears, Brian L.","contributorId":56784,"corporation":false,"usgs":true,"family":"Spears","given":"Brian","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":352837,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Healy, Kate A.","contributorId":102195,"corporation":false,"usgs":true,"family":"Healy","given":"Kate","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":352841,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brazzle, Roy E.","contributorId":92414,"corporation":false,"usgs":true,"family":"Brazzle","given":"Roy","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":352839,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hoffman, David J.","contributorId":86075,"corporation":false,"usgs":true,"family":"Hoffman","given":"David","email":"","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":352838,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dailey, Anne","contributorId":53936,"corporation":false,"usgs":true,"family":"Dailey","given":"Anne","email":"","affiliations":[],"preferred":false,"id":352836,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Beyer, W. Nelson 0000-0002-8911-9141 nbeyer@usgs.gov","orcid":"https://orcid.org/0000-0002-8911-9141","contributorId":3301,"corporation":false,"usgs":true,"family":"Beyer","given":"W.","email":"nbeyer@usgs.gov","middleInitial":"Nelson","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":352834,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70148715,"text":"70148715 - 2011 - Refuge habitats for fishes during seasonal drying in an intermittent stream: movement, survival and abundance of three minnow species","interactions":[],"lastModifiedDate":"2015-06-22T09:21:49","indexId":"70148715","displayToPublicDate":"2011-11-01T10:30:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":873,"text":"Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Refuge habitats for fishes during seasonal drying in an intermittent stream: movement, survival and abundance of three minnow species","docAbstract":"<p>Drought and summer drying can be important disturbance events in many small streams leading to intermittent or isolated habitats. We examined what habitats act as refuges for fishes during summer drying, hypothesizing that pools would act as refuge habitats. We predicted that during drying fish would show directional movement into pools from riffle habitats, survival rates would be greater in pools than in riffles, and fish abundance would increase in pool habitats. We examined movement, survival and abundance of three minnow species, bigeye shiner (<i>Notropis boops</i>), highland stoneroller (<i>Campostoma spadiceum</i>) and creek chub (<i>Semotilus atromaculatus</i>), during seasonal stream drying in an Ozark stream using a closed robust multi-strata mark-recapture sampling. Population parameters were estimated using plausible models within program MARK, where a priori models are ranked using Akaike's Information Criterion. Creek chub showed directional movement into pools and increased survival and abundance in pools during drying. Highland stonerollers showed strong directional movement into pools and abundance increased in pools during drying, but survival rates were not significantly greater in pools than riffles. Bigeye shiners showed high movement rates during drying, but the movement was non-directional, and survival rates were greater in riffles than pools. Therefore, creek chub supported our hypothesis and pools appear to act as refuge habitats for this species, whereas highland stonerollers partly supported the hypothesis and bigeye shiners did not support the pool refuge hypothesis. Refuge habitats during drying are species dependent. An urgent need exists to further understand refuge habitats in streams given projected changes in climate and continued alteration of hydrological regimes.</p>","language":"English","publisher":"Birkhauser","publisherLocation":"Boston","doi":"10.1007/s00027-011-0206-7","collaboration":"Univ Arkansas, Dept Biol Sci, US Geol Survey, Arkansas Cooperat Fish & Wildlife Res Unit","usgsCitation":"Hodges, S., and Magoulick, D.D., 2011, Refuge habitats for fishes during seasonal drying in an intermittent stream: movement, survival and abundance of three minnow species: Aquatic Sciences, v. 73, no. 4, p. 513-522, https://doi.org/10.1007/s00027-011-0206-7.","productDescription":"10 p.","startPage":"513","endPage":"522","numberOfPages":"10","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-025585","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":301399,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"73","issue":"4","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2011-05-17","publicationStatus":"PW","scienceBaseUri":"558931d6e4b0b6d21dd61c10","contributors":{"authors":[{"text":"Hodges, S.W.","contributorId":98563,"corporation":false,"usgs":true,"family":"Hodges","given":"S.W.","email":"","affiliations":[],"preferred":false,"id":549101,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Magoulick, Daniel D. 0000-0001-9665-5957 danmag@usgs.gov","orcid":"https://orcid.org/0000-0001-9665-5957","contributorId":2513,"corporation":false,"usgs":true,"family":"Magoulick","given":"Daniel","email":"danmag@usgs.gov","middleInitial":"D.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":549082,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70005872,"text":"fs20113133 - 2011 - A promising tool for subsurface permafrost mapping-An application of airborne geophysics from the Yukon River Basin, Alaska","interactions":[],"lastModifiedDate":"2012-02-10T00:12:00","indexId":"fs20113133","displayToPublicDate":"2011-11-01T00:00:00","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":"2011-3133","title":"A promising tool for subsurface permafrost mapping-An application of airborne geophysics from the Yukon River Basin, Alaska","docAbstract":"Permafrost is a predominant physical feature of the Earth's Arctic and Subarctic clines and a major consideration encompassing ecosystem structure to infrastructure engineering and placement. Perennially frozen ground is estimated to cover about 85 percent of the state of Alaska where northern reaches are underlain with continuous permafrost and parts of interior Alaska are underlain by areas of discontinuous and (or) sporadic permafrost (fig. 1). The region of Interior Alaska, where permafrost is scattered among unfrozen ground, is a complex mosaic of terrains and habitats. Such diversity creates arrays of lakes and surface-water and groundwater patterns that continental populations of migratory waterfowl and internationally significant fisheries have adapted to over time. A road or pipeline might pass over frozen and unfrozen ground, affecting the types of materials and engineering approaches needed to sustain the infrastructure.\nEffective mapping of discontinuous permafrost at scales meaningful ecologically and (or) from an engineering perspective has been a long-standing challenge. Using techniques such as borehole logging for site-specific assessments or botanical techniques that can suggest underlying permafrost distributions can be labor intensive and difficult to accomplish at the scale and remoteness of much of Alaska.\nThe climate is changing in the Arctic and Subarctic regions. The warming observed throughout much of Alaska could create widespread changes in permafrost. How the warming of the permafrost affects near-surface processes, ecosystems, and community infrastructure and ecosystems is not clear. A better understanding of the dynamic distribution and physical properties of permafrost, from continuous to discontinuous, will provide knowledge of how the permafrost environment may change in the future and help inform engineering and natural resource response strategies.\nHere we discuss an application of an airborne remote sensing methodology for mapping and shade imaging permafrost characteristics at various scales. This work provides the first look into three-dimensional distribution of permafrost in the areas around Fort Yukon and is a demonstration of the application of airborne electromagnetic (AEM) to permafrost mapping. Such an approach is attractive, particularly in Arctic and Subarctic studies, where ground access is difficult and ecosystems are fragile.\nIn June 2010, the U.S. Geological Survey (USGS) conducted an AEM survey near Fort Yukon, Alaska. The primary focus of this survey was to map the distribution of permafrost in selected areas in order to supply information for the development of groundwater models of the Yukon River Basin. However, the methodologies have more far-reaching ecological and engineering applications. Approximately 1,800 line kilometers were acquired in a combination of typical block style surveying in the immediate area of Fort Yukon and in long reconnaissance lines over a broader area. The widely spaced lines were flown to cross the modern Yukon River in \"X\" like patterns with intersections at features that have been previously studied (fig. 2).\nAEM is used to gather data on the electrical resistivity of materials in the subsurface below the flight path of the helicopter, which are then analyzed to interpret the subsurface lithology and the location and extent of permafrost. For this survey, the electrical resistivity was imaged to depths on the order of 50-100 meters. Images from the survey can be qualitatively compared with known permafrost features and suggest new permafrost features. Electrical properties of earth materials are affected by lithology as well as temperature and the presence of ice; frozen materials become substantially more resistive. This allows for the identification of permafrost from the resistivity image (Abraham and others, 2011).\nIn the area of Fort Yukon, the AEM survey shows elevated resistivities extending to depth, likely indicative of thick permafrost. This depth corresponds well to observations from a borehole drilled in the area in the late 1990s, which detected permafrost to a depth of about 100 meters (Clark and others, 2009). In contrast to the area of Fort Yukon, the Yukon River and its floodplain are not associated with deep resistive sediments, suggesting a lack of deep permafrost, at least within the depth range of the AEM mapping (fig. 3).","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20113133","usgsCitation":"Abraham, J.E., 2011, A promising tool for subsurface permafrost mapping-An application of airborne geophysics from the Yukon River Basin, Alaska: U.S. Geological Survey Fact Sheet 2011-3133, 4 p., https://doi.org/10.3133/fs20113133.","productDescription":"4 p.","costCenters":[{"id":542,"text":"Regional Executive for Alaska","active":false,"usgs":true}],"links":[{"id":116304,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs_2011_3133.png"},{"id":94600,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2011/3133/","linkFileType":{"id":5,"text":"html"}}],"state":"Alaska","otherGeospatial":"Yukon River Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -149.5,66 ], [ -149.5,67.5 ], [ -143,67.5 ], [ -143,66 ], [ -149.5,66 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b1be4b07f02db6a8d0d","contributors":{"authors":[{"text":"Abraham, Jared E.","contributorId":73739,"corporation":false,"usgs":true,"family":"Abraham","given":"Jared","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":353426,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70040589,"text":"70040589 - 2011 - Lineage diversification and morphological evolution in a large-scale continental radiation: The neotropical ovenbirds and woodcreepers (Aves: Furnariidae)","interactions":[],"lastModifiedDate":"2012-11-02T09:43:30","indexId":"70040589","displayToPublicDate":"2011-10-31T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1598,"text":"Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Lineage diversification and morphological evolution in a large-scale continental radiation: The neotropical ovenbirds and woodcreepers (Aves: Furnariidae)","docAbstract":"Patterns of diversification in species-rich clades provide insight into the processes that generate biological diversity. We tested different models of lineage and phenotypic diversification in an exceptional continental radiation, the ovenbird family Furnariidae, using the most complete species-level phylogenetic hypothesis produced to date for a major avian clade (97% of 293 species). We found that the Furnariidae exhibit nearly constant rates of lineage accumulation but show evidence of constrained morphological evolution. This pattern of sustained high rates of speciation despite limitations on phenotypic evolution contrasts with the results of most previous studies of evolutionary radiations, which have found a pattern of decelerating diversity-dependent lineage accumulation coupled with decelerating or constrained phenotypic evolution. Our results suggest that lineage accumulation in tropical continental radiations may not be as limited by ecological opportunities as in temperate or island radiations. More studies examining patterns of both lineage and phenotypic diversification are needed to understand the often complex tempo and mode of evolutionary radiations on continents.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Evolution","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","publisherLocation":"Hoboken, NJ","doi":"10.1111/j.1558-5646.2011.01374.x","usgsCitation":"Derryberry, E.P., Claramunt, S., Derryberry, G., Chesser, R., Cracraft, J., Aleixo, A., Perez-Eman, J., Remsen, J., and Brumfield, R.T., 2011, Lineage diversification and morphological evolution in a large-scale continental radiation: The neotropical ovenbirds and woodcreepers (Aves: Furnariidae): Evolution, v. 65, no. 10, p. 2973-2986, https://doi.org/10.1111/j.1558-5646.2011.01374.x.","productDescription":"14 p.","startPage":"2973","endPage":"2986","ipdsId":"IP-021177","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":262911,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":262910,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/j.1558-5646.2011.01374.x"}],"volume":"65","issue":"10","noUsgsAuthors":false,"publicationDate":"2011-07-04","publicationStatus":"PW","scienceBaseUri":"5094ebdbe4b0e5cfc2acdce1","contributors":{"authors":[{"text":"Derryberry, Elizabeth P.","contributorId":7974,"corporation":false,"usgs":true,"family":"Derryberry","given":"Elizabeth","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":468622,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Claramunt, Santiago","contributorId":58004,"corporation":false,"usgs":true,"family":"Claramunt","given":"Santiago","affiliations":[],"preferred":false,"id":468626,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Derryberry, Graham","contributorId":13114,"corporation":false,"usgs":true,"family":"Derryberry","given":"Graham","affiliations":[],"preferred":false,"id":468623,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chesser, R. Terry 0000-0003-4389-7092","orcid":"https://orcid.org/0000-0003-4389-7092","contributorId":87669,"corporation":false,"usgs":true,"family":"Chesser","given":"R. Terry","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":468630,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cracraft, Joel","contributorId":83652,"corporation":false,"usgs":true,"family":"Cracraft","given":"Joel","affiliations":[],"preferred":false,"id":468629,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Aleixo, Alexandre","contributorId":39108,"corporation":false,"usgs":true,"family":"Aleixo","given":"Alexandre","affiliations":[],"preferred":false,"id":468625,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Perez-Eman, Jorge","contributorId":20615,"corporation":false,"usgs":true,"family":"Perez-Eman","given":"Jorge","email":"","affiliations":[],"preferred":false,"id":468624,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Remsen, J.V. Jr.","contributorId":82258,"corporation":false,"usgs":true,"family":"Remsen","given":"J.V.","suffix":"Jr.","email":"","affiliations":[],"preferred":false,"id":468628,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Brumfield, Robb T.","contributorId":74492,"corporation":false,"usgs":true,"family":"Brumfield","given":"Robb","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":468627,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70005836,"text":"ofr20111272 - 2011 - Joint Ecosystem Modeling (JEM) ecological model documentation volume 1: Estuarine prey fish biomass availability v1.0.0","interactions":[],"lastModifiedDate":"2012-02-02T00:15:58","indexId":"ofr20111272","displayToPublicDate":"2011-10-28T00:00:00","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":"2011-1272","title":"Joint Ecosystem Modeling (JEM) ecological model documentation volume 1: Estuarine prey fish biomass availability v1.0.0","docAbstract":"Estuarine fish serve as an important prey base in the Greater Everglades ecosystem for key fauna such as wading birds, crocodiles, alligators, and piscivorous fishes. Human-made changes to freshwater flow across the Greater Everglades have resulted in less freshwater flow into the fringing estuaries and coasts. These changes in freshwater input have altered salinity patterns and negatively affected primary production of the estuarine fish prey base. Planned restoration projects should affect salinity and water depth both spatially and temporally and result in an increase in appropriate water conditions in areas occupied by estuarine fish. To assist in restoration planning, an ecological model of estuarine prey fish biomass availability was developed as an evaluation tool to aid in the determination of acceptable ranges of salinity and water depth. Comparisons of model output to field data indicate that the model accurately predicts prey biomass in the estuarine regions of the model domain. This model can be used to compare alternative restoration plans and select those that provide suitable conditions.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20111272","collaboration":"Prepared as part of the U.S. Geological Survey Priority Ecosystems Science Initiative","usgsCitation":"Romañach, S., Conzelmann, C., Daugherty, A., Lorenz, J.L., Hunnicutt, C., and Mazzotti, F., 2011, Joint Ecosystem Modeling (JEM) ecological model documentation volume 1: Estuarine prey fish biomass availability v1.0.0: U.S. Geological Survey Open-File Report 2011-1272, iv, 20 p., https://doi.org/10.3133/ofr20111272.","productDescription":"iv, 20 p.","startPage":"i","endPage":"20","numberOfPages":"24","additionalOnlineFiles":"N","costCenters":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"links":[{"id":94484,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2011/1272/","linkFileType":{"id":5,"text":"html"}},{"id":116479,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2011_1272.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Greater Everglades","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a56e4b07f02db62dd2a","contributors":{"authors":[{"text":"Romañach, Stephanie S. 0000-0003-0271-7825 sromanach@usgs.gov","orcid":"https://orcid.org/0000-0003-0271-7825","contributorId":2331,"corporation":false,"usgs":true,"family":"Romañach","given":"Stephanie S.","email":"sromanach@usgs.gov","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":false,"id":353339,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conzelmann, Craig 0000-0002-4227-8719 conzelmannc@usgs.gov","orcid":"https://orcid.org/0000-0002-4227-8719","contributorId":2361,"corporation":false,"usgs":true,"family":"Conzelmann","given":"Craig","email":"conzelmannc@usgs.gov","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":353340,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Daugherty, Adam","contributorId":92417,"corporation":false,"usgs":true,"family":"Daugherty","given":"Adam","email":"","affiliations":[],"preferred":false,"id":353343,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lorenz, Jerome L.","contributorId":62738,"corporation":false,"usgs":true,"family":"Lorenz","given":"Jerome","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":353342,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hunnicutt, Christina 0000-0001-8624-6420","orcid":"https://orcid.org/0000-0001-8624-6420","contributorId":52312,"corporation":false,"usgs":true,"family":"Hunnicutt","given":"Christina","affiliations":[],"preferred":false,"id":353341,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mazzotti, Frank J.","contributorId":100018,"corporation":false,"usgs":false,"family":"Mazzotti","given":"Frank J.","affiliations":[{"id":12557,"text":"University of Florida, FLREC","active":true,"usgs":false}],"preferred":false,"id":353344,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70005843,"text":"sir20105090c - 2011 - Porphyry copper assessment of British Columbia and Yukon Territory, Canada: Chapter C in <i>Global mineral resource assessment</i>","interactions":[{"subject":{"id":70005843,"text":"sir20105090c - 2011 - Porphyry copper assessment of British Columbia and Yukon Territory, Canada: Chapter C in <i>Global mineral resource assessment</i>","indexId":"sir20105090c","publicationYear":"2011","noYear":false,"chapter":"C","title":"Porphyry copper assessment of British Columbia and Yukon Territory, Canada: Chapter C in <i>Global mineral resource assessment</i>"},"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":"2015-06-19T10:52:47","indexId":"sir20105090c","displayToPublicDate":"2011-10-28T00:00:00","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":"C","title":"Porphyry copper assessment of British Columbia and Yukon Territory, Canada: Chapter C in <i>Global mineral resource assessment</i>","docAbstract":"<p>The U.S. Geological Survey does regional, national, and global assessments of resources (mineral, energy, water, biologic) to provide science in support of land management and decision making. Mineral resource assessments provide a synthesis of available information about where mineral deposits are known and suspected to be in the Earth&rsquo;s crust, which commodities may be present, and estimates of amounts of resources that may be present in undiscovered deposits.</p>\n<p>Canada is an important source of copper, consistently ranking as one of the top 10 world producers during the past decade (2000&ndash;2010). The preponderance of this production has been from porphyry-copper-type deposits in the western Canadian Cordillera. A probabilistic mineral resource assessment of undiscovered resources associated with porphyry copper deposits in western Canada was completed as part of a global mineral resource assessment. The purpose of the assessment was to (1) compile a database of known deposits and significant prospects, (2) delineate permissive areas (tracts) for undiscovered porphyry copper deposits that may be present in the upper kilometer (minimally) of the Earth&rsquo;s crust, and (3) provide probabilistic estimates of amounts of copper (Cu), molybdenum (Mo), gold (Au), and silver (Ag) that could be contained in undiscovered porphyry copper deposits in the tracts. The study was done by the U.S. Geological Survey (USGS) in collaboration with geologists from the British Columbia Geological Survey, Yukon Geological Survey, and industry consultants.</p>\n<p>The database of known deposits and significant prospects includes an inventory of mineral resources in 89 known porphyry copper (and 2 related copper-bearing polymetallic vein) ore zones, representing 50 porphyry copper deposits, and lists key characteristics of 280 additional porphyry copper and related copper-bearing prospects, as indicated by currently available exploration results, which also are summarized. Resource and exploration and development activity are updated with information current through April 2010.</p>\n<p>The delineation of permissive tracts and probabilistic estimation of resources in undiscovered deposits were done using the USGS three-part mineral resource assessment approach. Permissive tracts are defined in accordance with descriptive models for porphyry copper deposits to include igneous rocks and known deposits and prospects within magmatic arcs related to convergent plate-margin boundary zones. Frequency distributions of total tonnages and average grades of thoroughly explored deposits were used as models for undiscovered deposits and include a new grade and tonnage model for calc-alkaline porphyry Cu&plusmn;Mo&plusmn;Au deposits in western Canada.</p>\n<p>Five permissive tracts for the occurrence of porphyry copper deposits were delineated: 2 island-arc tracts, 1 tract of transitional, mixed island-arc and continental arc affinities, and 2 continental arc tracts. In permissive tract 003pCu2001, calc-alkaline igneous rocks of Middle Triassic to Late Jurassic age in accreted island-arc terranes of the Intermontane belt are assessed for calc-alkaline porphyry Cu&plusmn;Mo&plusmn;Au deposits. The area of this tract is 175,250 km<sup>2</sup>. In 12 known deposits, the total reported tonnage of ore is 8,100 million metric tons (Mt) containing 24.6 Mt copper. An estimated 6.9 undiscovered deposits contain a calculated mean of 8.9 Mt copper and a median of 6.9 Mt copper. The spatial density for the 18.9 known plus estimated undiscovered deposits in this tract is approximately 11 deposits per 100,000 km<sup>2</sup>.</p>\n<p>In permissive tract 003pCu2002, alkaline igneous rocks of Middle Triassic to Late Jurassic age within the Intermontane accreted island-arc terranes are assessed for alkaline porphyry Cu-Au deposits. The area of this tract is 109,290 km<sup>2</sup>. In 12 known deposits the total reported tonnage of ore is 6,440 Mt, containing 20.9 Mt copper. An estimated 7 undiscovered deposits contain a calculated mean of 22 Mt copper and a median of 13 Mt copper. The spatial density for the 19 known plus estimated undiscovered deposits in this tract is approximately 17 deposits per 100,000 km<sup>2</sup>.</p>\n<p>In permissive tract 003pCu2003, calc-alkaline igneous rocks of Late Triassic to Early Cretaceous age within the accreted Insular terranes of mixed island-arc and continental arc affinities are assessed for calc-alkaline porphyry Cu&plusmn;Mo&plusmn;Au deposits. The area of this tract is 58,360 km<sup>2</sup>. The total tonnage of ore reported in the 2 known deposits is 1,160 Mt containing 3.17 Mt copper. An estimated 2.3 undiscovered deposits contain a calculated mean of 3 Mt copper and a median of 1.9 Mt copper. The spatial density for the 4.3 known plus estimated undiscovered deposits in this tract is approximately 7 deposits per 100,000 km<sup>2</sup>.</p>\n<p>In permissive tract 003pCu2004, calc-alkaline igneous rocks in continental magmatic arcs of Jurassic to Eocene age are assessed for porphyry Cu&plusmn;Mo&plusmn;Au deposits. The area of this tract is 639,500 km<sup>2</sup>. The total tonnage of ore reported for the 23 known deposits is 6,520 Mt containing 17.9 Mt copper. An estimated 9.6 undiscovered deposits contain a calculated mean of 13 Mt copper and a median of 11 Mt copper. The spatial density for the 32.6 known deposits plus the estimated undiscovered deposits in this tract is approximately 5 deposits per 100,000 km<sup>2</sup>.</p>\n<p>In permissive tract 003pCu2005, calc-alkaline igneous rocks in continental magmatic arcs of Oligocene to Pliocene age are assessed for porphyry Cu&plusmn;Mo&plusmn;Au deposits. The area of this tract is 32,840 km<sup>2</sup>. The total tonnage of ore reported for the 1 known deposit is 44.8 Mt containing 0.224 Mt copper. An estimated 1.4 undiscovered deposits contain a calculated mean of 1.8 Mt copper and a median of 0.72 Mt copper. The spatial density for the 2.4 known plus estimated undiscovered deposits in this permissive tract is approximately 7 deposits per 100,000 km<sup>2</sup>.</p>\n<p>Western Canada has been thoroughly explored for porphyry copper deposits. The total estimated copper contained in known deposits is about 66.8 Mt (based on 2010 data), as compared to a 49 Mt mean of estimated copper in undiscovered deposits and a 34 Mt median of estimated copper in undiscovered deposits. The copper contained in known porphyry copper deposits represents about 58 percent of the total of known and undiscovered porphyry copper deposits (based on mean values). About 86 percent of the increase in estimated copper resources between 1993 and 2009 resulted from the discovery of extensions to known deposits. Nevertheless, exploration for undiscovered deposits continues, especially in and around significant prospects and in parts of permissive tracts that are mostly hidden beneath younger volcanic, sedimentary, or vegetated surficial cover.</p>","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Global mineral resource assessment (Scientific Investigations Report 2010-5090)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20105090c","collaboration":"Prepared in cooperation with the British Columbia Geological Survey, Yukon Geological Survey, and XDM Geological Consultants, Inc.","usgsCitation":"Mihalasky, M.J., Bookstrom, A.A., Frost, T.P., and Ludington, S., 2011, Porphyry copper assessment of British Columbia and Yukon Territory, Canada: Chapter C in <i>Global mineral resource assessment</i> (Version 1.0: Originally posted October 2011; Version 1.1: February 2013): U.S. Geological Survey Scientific Investigations Report 2010-5090, Report: x, 128 p.; Appendix F Table; Appendix H GIS Data, https://doi.org/10.3133/sir20105090c.","productDescription":"Report: x, 128 p.; Appendix F Table; Appendix H GIS Data","numberOfPages":"142","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"links":[{"id":204177,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2010_5090_C.gif"},{"id":301355,"rank":103,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2010/5090/c/sir2010-5090c_appendix_h.zip","text":"Appendix H GIS data","size":"12.8 MB","linkFileType":{"id":6,"text":"zip"},"description":"Appendix H","linkHelpText":"Geographic Information System (GIS) Files Representing the Porphyry Copper Mineral Resource Assessment Permissive Tracts, Deposits and Significant Prospects, and Accompanying Metadata, Porphyry Copper Assessment, British Columbia and Yukon Territory, Canada"},{"id":301353,"rank":101,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2010/5090/c/sir2010-5090c_text.pdf","text":"Report","size":"13.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":94466,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2010/5090/c/","linkFileType":{"id":5,"text":"html"}},{"id":301354,"rank":102,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2010/5090/c/appendix_f","text":"Appendix F table","description":"Appendix F","linkHelpText":"Table of Attributes of Porphyry Copper Deposits and Prospects, British Columbia and Yukon Territory, Canada (given in several file formats)"}],"country":"Canada","state":"British Columbia, Yukon Territory","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": 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,{"id":70005835,"text":"ofr20111273 - 2011 - Joint Ecosystem Modeling (JEM) ecological model documentation volume 2: roseate spoonbill (<i>Platalea ajaja</i>) landscape habitat suitability index v1.0.0","interactions":[],"lastModifiedDate":"2012-02-02T00:15:58","indexId":"ofr20111273","displayToPublicDate":"2011-10-28T00:00:00","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":"2011-1273","title":"Joint Ecosystem Modeling (JEM) ecological model documentation volume 2: roseate spoonbill (<i>Platalea ajaja</i>) landscape habitat suitability index v1.0.0","docAbstract":"Ecological conditions in the Greater Everglades have changed due to human activities, including the construction of canals to divert water away from the core of the landscape. Current and planned restoration projects are designed to produce a natural sheetflow of water across the landscape. This restoration of water flow should provide an increase in freshwater needed to restore natural salinities to the fringing estuarine ecosystem. In this report, we describe a Landscape Habitat Suitability Index model designed to evaluate alternative restoration plans for the benefit of a key species, the roseate spoonbill (Platalea ajaja). Model output has shown to be a good indicator of areas capable of supporting spoonbills. Use of this model will allow examination of the potential response of this key species to water management proposed through the Greater Everglades restoration process.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20111273","collaboration":"Prepared as part of the U.S. Geological Survey Priority Ecosystems Science Initiative","usgsCitation":"Romañach, S., Conzelmann, C., Daugherty, A., Lorenz, J., Hunnicutt, C., and Mazzotti, F., 2011, Joint Ecosystem Modeling (JEM) ecological model documentation volume 2: roseate spoonbill (<i>Platalea ajaja</i>) landscape habitat suitability index v1.0.0: U.S. Geological Survey Open-File Report 2011-1273, iv, 23 p.; XLS Download of Appendix 1, https://doi.org/10.3133/ofr20111273.","productDescription":"iv, 23 p.; XLS Download of Appendix 1","startPage":"i","endPage":"23","numberOfPages":"27","additionalOnlineFiles":"Y","costCenters":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"links":[{"id":116480,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2011_1273.jpg"},{"id":94485,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2011/1273/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Florida","otherGeospatial":"Greater Everglades","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a9fe4b07f02db6614f1","contributors":{"authors":[{"text":"Romañach, Stephanie S. 0000-0003-0271-7825 sromanach@usgs.gov","orcid":"https://orcid.org/0000-0003-0271-7825","contributorId":2331,"corporation":false,"usgs":true,"family":"Romañach","given":"Stephanie S.","email":"sromanach@usgs.gov","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":false,"id":353333,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conzelmann, Craig 0000-0002-4227-8719 conzelmannc@usgs.gov","orcid":"https://orcid.org/0000-0002-4227-8719","contributorId":2361,"corporation":false,"usgs":true,"family":"Conzelmann","given":"Craig","email":"conzelmannc@usgs.gov","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":353334,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Daugherty, Adam","contributorId":92417,"corporation":false,"usgs":true,"family":"Daugherty","given":"Adam","email":"","affiliations":[],"preferred":false,"id":353337,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lorenz, Jerome J.","contributorId":20062,"corporation":false,"usgs":true,"family":"Lorenz","given":"Jerome J.","affiliations":[],"preferred":false,"id":353335,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hunnicutt, Christina 0000-0001-8624-6420","orcid":"https://orcid.org/0000-0001-8624-6420","contributorId":52312,"corporation":false,"usgs":true,"family":"Hunnicutt","given":"Christina","affiliations":[],"preferred":false,"id":353336,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mazzotti, Frank J.","contributorId":100018,"corporation":false,"usgs":false,"family":"Mazzotti","given":"Frank J.","affiliations":[{"id":12557,"text":"University of Florida, FLREC","active":true,"usgs":false}],"preferred":false,"id":353338,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70005847,"text":"sim3179 - 2011 - Geologic map of the Montoso Peak quadrangle, Santa Fe and Sandoval Counties, New Mexico","interactions":[],"lastModifiedDate":"2022-04-15T19:13:46.957292","indexId":"sim3179","displayToPublicDate":"2011-10-28T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3179","title":"Geologic map of the Montoso Peak quadrangle, Santa Fe and Sandoval Counties, New Mexico","docAbstract":"The Montoso Peak quadrangle is underlain by volcanic rocks and associated sediments of the Cerros del Rio volcanic field in the southern part of the Espa&#241;ola Basin that record volcanic, faulting, alluvial, colluvial, and eolian processes over the past three million years. The geology was mapped from 1997 to 1999 and modified in 2004 to 2008. The geologic mapping was carried out in support of the U.S. Geological Survey (USGS) Rio Grande Basin Project, funded by the USGS National Cooperative Geologic mapping Program. The mapped distribution of units is based primarily on interpretation of 1:16,000-scale, color aerial photographs taken in 1992, and 1:40,000-scale, black-and-white, aerial photographs taken in 1996. Most of the contacts on the map were transferred from the aerial photographs using a photogrammetric stereoplotter and subsequently field checked for accuracy and revised based on field determination of allostratigraphic and lithostratigraphic units. Determination of lithostratigraphic units in volcanic deposits was aided by geochemical data, <sup>40</sup>Ar/<sup>39</sup>Ar geochronology, aeromagnetic and paleomagnetic data. Supplemental revision of mapped contacts was based on interpretation of USGS 1-meter orthoimagery. This version of the Montoso Peak quadrangle geologic map uses a traditional USGS topographic base overlain on a shaded relief base generated from 10-m digital elevation model (DEM) data from the USGS National Elevation Dataset (NED). Faults are identified with varying confidence levels in the map area. Recognizing and mapping faults developed near the surface in young, brittle volcanic rocks is difficult because (1) they tend to form fractured zones tens of meters wide rather than discrete fault planes, (2) the youth of the deposits has allowed only modest displacements to accumulate for most faults, and (3) many may have significant strike-slip components that do not result in large vertical offsets that are readily apparent in offset of sub-horizontal contacts. Those faults characterized as \"certain\" either have distinct offset of map units or had slip planes that were directly observed in the field. Faults classed as \"inferred\" were traced based on linear alignments of geologic, topographic and aerial photo features such as vents, lava flow edges, and drainages inferred to preferentially develop on fractured rock. Lineaments defined from magnetic anomalies form an additional constraint on potential fault locations.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3179","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Thompson, R.A., Hudson, M., Shroba, R.R., Minor, S.A., and Sawyer, D.A., 2011, Geologic map of the Montoso Peak quadrangle, Santa Fe and Sandoval Counties, New Mexico: U.S. Geological Survey Scientific Investigations Map 3179, Pamphlet: iv, 20 p.; 1 Sheet: 36.00 x 36.00 inches; Downloads Directory, https://doi.org/10.3133/sim3179.","productDescription":"Pamphlet: iv, 20 p.; 1 Sheet: 36.00 x 36.00 inches; Downloads Directory","numberOfPages":"24","onlineOnly":"N","additionalOnlineFiles":"Y","costCenters":[{"id":308,"text":"Geology and Environmental Change Science Center","active":false,"usgs":true}],"links":[{"id":116478,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim_3179.png"},{"id":94482,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3179/","linkFileType":{"id":5,"text":"html"}},{"id":398857,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_96087.htm"}],"scale":"24000","projection":"Universal Transverse Mercator","datum":"NAD 27","country":"United States","state":"New Mexico","county":"Sandoval County, Santa Fe County","otherGeospatial":"Montoso Peak quadrangle","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -106.25,\n              35.625\n            ],\n            [\n              -106.125,\n              35.625\n            ],\n            [\n              -106.125,\n              35.750\n            ],\n            [\n              -106.25,\n              35.750\n            ],\n            [\n              -106.25,\n              35.625\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4af4e4b07f02db692084","contributors":{"authors":[{"text":"Thompson, Ren A. 0000-0002-3044-3043 rathomps@usgs.gov","orcid":"https://orcid.org/0000-0002-3044-3043","contributorId":1265,"corporation":false,"usgs":true,"family":"Thompson","given":"Ren","email":"rathomps@usgs.gov","middleInitial":"A.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":353378,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hudson, Mark R. 0000-0003-0338-6079 mhudson@usgs.gov","orcid":"https://orcid.org/0000-0003-0338-6079","contributorId":1236,"corporation":false,"usgs":true,"family":"Hudson","given":"Mark R.","email":"mhudson@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":353376,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shroba, Ralph R. 0000-0002-2664-1813 rshroba@usgs.gov","orcid":"https://orcid.org/0000-0002-2664-1813","contributorId":1266,"corporation":false,"usgs":true,"family":"Shroba","given":"Ralph","email":"rshroba@usgs.gov","middleInitial":"R.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":353379,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Minor, Scott A. 0000-0002-6976-9235 sminor@usgs.gov","orcid":"https://orcid.org/0000-0002-6976-9235","contributorId":765,"corporation":false,"usgs":true,"family":"Minor","given":"Scott","email":"sminor@usgs.gov","middleInitial":"A.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":353375,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sawyer, David A. dsawyer@usgs.gov","contributorId":1262,"corporation":false,"usgs":true,"family":"Sawyer","given":"David","email":"dsawyer@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":353377,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70005840,"text":"sir20115175 - 2011 - Assessment of channel changes, model of historical floods, and effects of backwater on flood stage, and flood mitigation alternatives for the Wichita River at Wichita Falls, Texas","interactions":[],"lastModifiedDate":"2016-08-11T15:19:29","indexId":"sir20115175","displayToPublicDate":"2011-10-28T00:00:00","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":"2011-5175","title":"Assessment of channel changes, model of historical floods, and effects of backwater on flood stage, and flood mitigation alternatives for the Wichita River at Wichita Falls, Texas","docAbstract":"<p>In cooperation with the City of Wichita Falls, the U.S. Geological Survey assessed channel changes on the Wichita River at Wichita Falls, Texas, and modeled historical floods to investigate possible causes and potential mitigation alternatives to higher flood stages in recent (2007 and 2008) floods. Extreme flooding occurred on the Wichita River on June 30, 2007, inundating 167 homes in Wichita Falls. Although a record flood stage was reached in June 2007, the peak discharge was much less than some historical floods at Wichita Falls. Streamflow and stage data from two gages on the Wichita River and one on Holliday Creek were used to assess the interaction of the two streams. Changes in the Wichita River channel were evaluated using historical aerial and ground photography, comparison of recent and historical cross sections, and comparison of channel roughness coefficients with those from earlier studies. The floods of 2007 and 2008 were modeled using a one-dimensional step-backwater model. Calibrated channel roughness was larger for the 2007 flood compared to the 2008 flood, and the 2007 flood peaked about 4 feet higher than the 2008 flood. Calibration of the 1941 flood yielded a channel roughness coefficient (Manning's <i>n</i>) of 0.030, which represents a fairly clean natural channel. The step-backwater model was also used to evaluate the following potential mitigation alternatives: (1) increasing the capacity of the bypass channel near River Road in Wichita Falls, Texas; (2) removal of obstructions near the Scott Avenue and Martin Luther King Junior Boulevard bridges in Wichita Falls, Texas; (3) widening of aggraded channel banks in the reach between Martin Luther King Junior Boulevard and River Road; and (4) reducing channel bank and overbank roughness. Reductions in water-surface elevations ranged from 0.1 foot to as much as 3.0 feet for the different mitigation alternatives. The effects of implementing a combination of different flood-mitigation alternatives were not investigated.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20115175","collaboration":"Prepared in cooperation with the City of Wichita Falls, Texas","usgsCitation":"Winters, K.E., and Baldys, S., 2011, Assessment of channel changes, model of historical floods, and effects of backwater on flood stage, and flood mitigation alternatives for the Wichita River at Wichita Falls, Texas: U.S. Geological Survey Scientific Investigations Report 2011-5175, vi, 28 p., https://doi.org/10.3133/sir20115175.","productDescription":"vi, 28 p.","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":94462,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2011/5175/","linkFileType":{"id":5,"text":"html"}},{"id":116359,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2011_5175.gif"}],"country":"United States","state":"Texas","city":"Wichita Falls","otherGeospatial":"Wichita River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -98.56666666666666,33.8675 ], [ -98.56666666666666,33.93472222222222 ], [ -98.43333333333334,33.93472222222222 ], [ -98.43333333333334,33.8675 ], [ -98.56666666666666,33.8675 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4afee4b07f02db6978d3","contributors":{"authors":[{"text":"Winters, Karl E. kwinters@usgs.gov","contributorId":3554,"corporation":false,"usgs":true,"family":"Winters","given":"Karl","email":"kwinters@usgs.gov","middleInitial":"E.","affiliations":[],"preferred":true,"id":353356,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baldys, Stanley sbaldys@usgs.gov","contributorId":3366,"corporation":false,"usgs":true,"family":"Baldys","given":"Stanley","email":"sbaldys@usgs.gov","affiliations":[],"preferred":true,"id":353355,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70005844,"text":"sir20105057 - 2011 - Development of flood-inundation maps for the West Branch Susquehanna River near the Borough of Jersey Shore, Lycoming County, Pennsylvania","interactions":[],"lastModifiedDate":"2012-03-08T17:16:43","indexId":"sir20105057","displayToPublicDate":"2011-10-28T00:00:00","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":"2010-5057","title":"Development of flood-inundation maps for the West Branch Susquehanna River near the Borough of Jersey Shore, Lycoming County, Pennsylvania","docAbstract":"Streamflow data, water-surface-elevation profiles derived from a Hydrologic Engineering Center River Analysis System hydraulic model, and geographical information system digital elevation models were used to develop a set of 18 flood-inundation maps for an approximately 5-mile reach of the West Branch Susquehanna River near the Borough of Jersey Shore, Pa. The inundation maps were created by the U.S. Geological Survey in cooperation with the Susquehanna River Basin Commission and Lycoming County as part of an ongoing effort by the National Oceanic and Atmospheric Administration's National Weather Service to focus on continued improvements to the flood forecasting and warning abilities in the Susquehanna River Basin and to modernize flood-forecasting methodologies. The maps, ranging from 23.0 to 40.0 feet in 1-foot increments, correspond to river stage at the U.S. Geological Survey streamgage 01549760 at Jersey Shore. The electronic files used to develop the maps were provided to the National Weather Service for incorporation into their Advanced Hydrologic Prediction Service website. The maps are displayed on this website, which serves as a web-based floodwarning system, and can be used to identify areas of predicted flood inundation associated with forecasted flood-peak stages. During times of flooding or predicted flooding, these maps can be used by emergency managers and the public to take proactive steps to protect life and reduce property damage caused by floods.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20105057","collaboration":"Prepared in cooperation with the Susquehanna River Basin Commission and Lycoming County","usgsCitation":"Roland, M.A., and Hoffman, S.A., 2011, Development of flood-inundation maps for the West Branch Susquehanna River near the Borough of Jersey Shore, Lycoming County, Pennsylvania: U.S. Geological Survey Scientific Investigations Report 2010-5057, iv, 9 p., https://doi.org/10.3133/sir20105057.","productDescription":"iv, 9 p.","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":116364,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2010_5057.gif"},{"id":94467,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2010/5057/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Pennsylvania","county":"Lycoming","city":"Borough Of Jersey Shore","otherGeospatial":"Wes Branch Susquehanna River Basin;Pine Creek;Larrys Creek","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -77.31666666666666,41.166666666666664 ], [ -77.31666666666666,41.233333333333334 ], [ -77.2,41.233333333333334 ], [ -77.2,41.166666666666664 ], [ -77.31666666666666,41.166666666666664 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a9be4b07f02db65dedf","contributors":{"authors":[{"text":"Roland, Mark A. 0000-0002-0268-6507 mroland@usgs.gov","orcid":"https://orcid.org/0000-0002-0268-6507","contributorId":2116,"corporation":false,"usgs":true,"family":"Roland","given":"Mark","email":"mroland@usgs.gov","middleInitial":"A.","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":353366,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hoffman, Scott A. shoffman@usgs.gov","contributorId":2634,"corporation":false,"usgs":true,"family":"Hoffman","given":"Scott","email":"shoffman@usgs.gov","middleInitial":"A.","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":353367,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70005219,"text":"70005219 - 2011 - Distribution and habitat use of the Missouri River and Lower Yellowstone River benthic fishes from 1996 to 1998: A baseline for fish community recovery","interactions":[],"lastModifiedDate":"2016-11-17T16:01:33","indexId":"70005219","displayToPublicDate":"2011-10-28T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3301,"text":"River Research and Applications","active":true,"publicationSubtype":{"id":10}},"title":"Distribution and habitat use of the Missouri River and Lower Yellowstone River benthic fishes from 1996 to 1998: A baseline for fish community recovery","docAbstract":"<p><span>Past and present Missouri River management practices have resulted in native fishes being identified as in jeopardy. In 1995, the Missouri River Benthic Fishes Study was initiated to provide improved information on Missouri River fish populations and how alterations might affect them. The study produced a baseline against which to evaluate future changes in Missouri River operating criteria. The objective was to evaluate population structure and habitat use of benthic fishes along the entire mainstem Missouri River, exclusive of reservoirs. Here we use the data from this study to provide a recent-past baseline for on-going Missouri River fish population monitoring programmes along with a more powerful method for analysing data containing large percentages of zero values. This is carried out by describing the distribution and habitat use of 21 species of Missouri River benthic fishes based on catch-per-unit area data from multiple gears. We employ a Bayesian zero-inflated Poisson model expanded to include continuous measures of habitat quality (i.e. substrate composition, depth, velocity, temperature, turbidity and conductivity). Along with presenting the method, we provide a relatively complete picture of the Missouri River benthic fish community and the relationship between their relative population numbers and habitat conditions. We demonstrate that our single model provides all the information that is often obtained by a myriad of analytical techniques. An important advantage of the present approach is reliable inference for patterns of relative abundance using multiple gears without using gear efficiencies.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/rra.1559","usgsCitation":"Wildhaber, M., Gladish, D., and Arab, A., 2011, Distribution and habitat use of the Missouri River and Lower Yellowstone River benthic fishes from 1996 to 1998: A baseline for fish community recovery: River Research and Applications, v. 28, no. 10, p. 1780-1803, https://doi.org/10.1002/rra.1559.","productDescription":"24 p.","startPage":"1780","endPage":"1803","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":438823,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9RIFWBM","text":"USGS data release","linkHelpText":"Captures and habitat classification of benthic fishes along the Missouri and Lower Yellowstone Rivers, 1996-1998"},{"id":204159,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"28","issue":"10","noUsgsAuthors":false,"publicationDate":"2011-07-31","publicationStatus":"PW","scienceBaseUri":"4f4e4a81e4b07f02db64a18e","contributors":{"authors":[{"text":"Wildhaber, M. L. 0000-0002-6538-9083","orcid":"https://orcid.org/0000-0002-6538-9083","contributorId":62961,"corporation":false,"usgs":true,"family":"Wildhaber","given":"M. L.","affiliations":[],"preferred":false,"id":352084,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gladish, D. W.","contributorId":68445,"corporation":false,"usgs":false,"family":"Gladish","given":"D. W.","affiliations":[],"preferred":false,"id":352085,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Arab, A.","contributorId":71770,"corporation":false,"usgs":true,"family":"Arab","given":"A.","email":"","affiliations":[],"preferred":false,"id":352086,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70237835,"text":"70237835 - 2011 - Exploring the potential for a fused Landsat-MODIS snow covered area product","interactions":[],"lastModifiedDate":"2022-10-26T12:02:42.161927","indexId":"70237835","displayToPublicDate":"2011-10-26T07:01:58","publicationYear":"2011","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Exploring the potential for a fused Landsat-MODIS snow covered area product","docAbstract":"Results from nine 3 x 3 km study areas in the Rocky Mountains of Colorado, USA demonstrate there is potential for using sporadically acquired Landsat images in combination with daily coarse resolution fractional snow covered area (SCA) images to produce daily high resolution binary SCA images. The results also highlight several challenges to implementing this type of approach. The approach described here consistently yields accurate results in locations with persistent winter and spring snow cover where ten or more partially snow covered images are available to populate the image database, but is less successful in areas with shallower or more ephemeral snow covers or when fewer images are available to populate the image database. This work represents a first step towards developing an algorithm to combine Landsat and MODIS data to produce daily 30 m resolution binary SCA images. Further research should focus on testing the accuracy of this approach across a range of landscape types and snow cover regimes, developing methods to improve prediction accuracy when snow cover is nearly complete or nearly absent, and developing methods to compensate for the effects of canopy cover on SCA retrievals.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the 79th Annual Western Snow Conference","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"Western Snow Conference","usgsCitation":"Selkowitz, D.J., 2011, Exploring the potential for a fused Landsat-MODIS snow covered area product, <i>in</i> Proceedings of the 79th Annual Western Snow Conference, p. 31-36.","productDescription":"6 p.","startPage":"31","endPage":"36","ipdsId":"IP-033390","costCenters":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"links":[{"id":408742,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":408741,"rank":1,"type":{"id":39,"text":"HTML Document"},"url":"https://westernsnowconference.org/sites/westernsnowconference.org/PDFs/2011Selkowitz.pdf"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Selkowitz, David J. 0000-0003-0824-7051 dselkowitz@usgs.gov","orcid":"https://orcid.org/0000-0003-0824-7051","contributorId":3259,"corporation":false,"usgs":true,"family":"Selkowitz","given":"David","email":"dselkowitz@usgs.gov","middleInitial":"J.","affiliations":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":855820,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70005815,"text":"ofr20111217 - 2011 - 2010 bathymetric survey and digital elevation model of Corte Madera Bay, California","interactions":[],"lastModifiedDate":"2017-08-23T09:20:20","indexId":"ofr20111217","displayToPublicDate":"2011-10-26T00:00:00","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":"2011-1217","title":"2010 bathymetric survey and digital elevation model of Corte Madera Bay, California","docAbstract":"A high-resolution bathymetric survey of Corte Madera Bay, California, was collected in early 2010 in support of a collaborative research project initiated by the San Francisco Bay Conservation and Development Commission and funded by the U.S. Environmental Protection Agency. The primary objective of the Innovative Wetland Adaptation in the Lower Corte Madera Creek Watershed Project is to develop shoreline adaptation strategies to future sea-level rise based upon sound science. Fundamental to this research was the development of an of an up-to-date, high-resolution digital elevation model (DEM) extending from the subtidal environment through the surrounding intertidal marsh. We provide bathymetric data collected by the U.S. Geological Survey and have merged the bathymetry with a 1-m resolution aerial lidar data set that was collected by the National Oceanic and Atmospheric Administration during the same time period to create a seamless, high-resolution DEM of Corte Madera Bay and the surrounding topography. The bathymetric and DEM surfaces are provided at both 1 m and 10 m resolutions formatted as both X, Y, Z text files and ESRI Arc ASCII files, which are accompanied by Federal Geographic Data Committee compliant metadata.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20111217","usgsCitation":"Foxgrover, A., Finlayson, D.P., Jaffe, B.E., Takekawa, J.Y., Thorne, K.M., and Spragens, K., 2011, 2010 bathymetric survey and digital elevation model of Corte Madera Bay, California: U.S. Geological Survey Open-File Report 2011-1217, iv, 19 p.; Appendix; Download of Metadata; Download of Data Folder, https://doi.org/10.3133/ofr20111217.","productDescription":"iv, 19 p.; Appendix; Download of Metadata; Download of Data Folder","startPage":"i","endPage":"20","numberOfPages":"24","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":116477,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2011_1217.gif"},{"id":94439,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2011/1217/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"California","otherGeospatial":"Corte Madera Bay","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd4926e4b0b290850eeeb2","contributors":{"authors":[{"text":"Foxgrover, Amy C.","contributorId":45775,"corporation":false,"usgs":true,"family":"Foxgrover","given":"Amy C.","affiliations":[],"preferred":false,"id":353301,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Finlayson, David P. dfinlayson@usgs.gov","contributorId":1381,"corporation":false,"usgs":true,"family":"Finlayson","given":"David","email":"dfinlayson@usgs.gov","middleInitial":"P.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":353298,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jaffe, Bruce E. 0000-0002-8816-5920 bjaffe@usgs.gov","orcid":"https://orcid.org/0000-0002-8816-5920","contributorId":2049,"corporation":false,"usgs":true,"family":"Jaffe","given":"Bruce","email":"bjaffe@usgs.gov","middleInitial":"E.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":353299,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Takekawa, John Y. 0000-0003-0217-5907 john_takekawa@usgs.gov","orcid":"https://orcid.org/0000-0003-0217-5907","contributorId":176168,"corporation":false,"usgs":true,"family":"Takekawa","given":"John","email":"john_takekawa@usgs.gov","middleInitial":"Y.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":353297,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thorne, Karen M. 0000-0002-1381-0657 kthorne@usgs.gov","orcid":"https://orcid.org/0000-0002-1381-0657","contributorId":4191,"corporation":false,"usgs":true,"family":"Thorne","given":"Karen","email":"kthorne@usgs.gov","middleInitial":"M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":353300,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Spragens, Kyle A.","contributorId":98452,"corporation":false,"usgs":true,"family":"Spragens","given":"Kyle A.","affiliations":[],"preferred":false,"id":353302,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70005825,"text":"ds630 - 2011 - Adjustment of pesticide concentrations for temporal changes in analytical recovery, 1992&ndash;2010","interactions":[],"lastModifiedDate":"2012-02-02T00:15:57","indexId":"ds630","displayToPublicDate":"2011-10-26T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"630","title":"Adjustment of pesticide concentrations for temporal changes in analytical recovery, 1992&ndash;2010","docAbstract":"Recovery is the proportion of a target analyte that is quantified by an analytical method and is a primary indicator of the analytical bias of a measurement. Recovery is measured by analysis of quality-control (QC) water samples that have known amounts of target analytes added (\"spiked\" QC samples). For pesticides, recovery is the measured amount of pesticide in the spiked QC sample expressed as a percentage of the amount spiked, ideally 100 percent. Temporal changes in recovery have the potential to adversely affect time-trend analysis of pesticide concentrations by introducing trends in apparent environmental concentrations that are caused by trends in performance of the analytical method rather than by trends in pesticide use or other environmental conditions. This report presents data and models related to the recovery of 44 pesticides and 8 pesticide degradates (hereafter referred to as \"pesticides\") that were selected for a national analysis of time trends in pesticide concentrations in streams. Water samples were analyzed for these pesticides from 1992 through 2010 by gas chromatography/mass spectrometry. Recovery was measured by analysis of pesticide-spiked QC water samples. Models of recovery, based on robust, locally weighted scatterplot smooths (lowess smooths) of matrix spikes, were developed separately for groundwater and stream-water samples. The models of recovery can be used to adjust concentrations of pesticides measured in groundwater or stream-water samples to 100 percent recovery to compensate for temporal changes in the performance (bias) of the analytical method.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds630","collaboration":"National Water-Quality Assessment Program","usgsCitation":"Martin, J.D., and Eberle, M., 2011, Adjustment of pesticide concentrations for temporal changes in analytical recovery, 1992&ndash;2010: U.S. Geological Survey Data Series 630, vi, 11 p.; PDF Download of Appendix 3; PDF Download of Appendix 3 List of Figures; PDF Download of Appendix 1 Metadata; PDF Download of Appendix 2 Metadata; PDF Download of Appendix 4 Metadata; PDF Download of Appendix 5 Metadata; Download of Appendixes 1, 2, 4, and 5, https://doi.org/10.3133/ds630.","productDescription":"vi, 11 p.; PDF Download of Appendix 3; PDF Download of Appendix 3 List of Figures; PDF Download of Appendix 1 Metadata; PDF Download of Appendix 2 Metadata; PDF Download of Appendix 4 Metadata; PDF Download of Appendix 5 Metadata; Download of Appendixes 1, 2, 4, and 5","startPage":"i","endPage":"11","numberOfPages":"17","additionalOnlineFiles":"Y","temporalStart":"1992-01-01","temporalEnd":"2010-12-31","costCenters":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":533,"text":"Pesticide National Synthesis Project","active":false,"usgs":true}],"links":[{"id":116357,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds_630.gif"},{"id":94445,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/630/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4afde4b07f02db696dc3","contributors":{"authors":[{"text":"Martin, Jeffrey D. 0000-0003-1994-5285 jdmartin@usgs.gov","orcid":"https://orcid.org/0000-0003-1994-5285","contributorId":1066,"corporation":false,"usgs":true,"family":"Martin","given":"Jeffrey","email":"jdmartin@usgs.gov","middleInitial":"D.","affiliations":[{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true},{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":353317,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Eberle, Michael","contributorId":39770,"corporation":false,"usgs":true,"family":"Eberle","given":"Michael","email":"","affiliations":[],"preferred":false,"id":353318,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70129410,"text":"70129410 - 2011 - Results and evaluation of a survey to estimate Pacific walrus population size, 2006","interactions":[],"lastModifiedDate":"2018-06-16T17:51:24","indexId":"70129410","displayToPublicDate":"2011-10-22T09:13:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2671,"text":"Marine Mammal Science","active":true,"publicationSubtype":{"id":10}},"title":"Results and evaluation of a survey to estimate Pacific walrus population size, 2006","docAbstract":"In spring 2006, we conducted a collaborative U.S.-Russia survey to estimate abundance of the Pacific walrus (<i>Odobenus rosmarus divergens</i>).  The Bering Sea was partitioned into survey blocks, and a systematic random sample of transects within a subset of the blocks was surveyed with airborne thermal scanners using standard strip-transect methodology.  Counts of walruses in photographed groups were used to model the relation between thermal signatures and the number of walruses in groups, which was used to estimate the number of walruses in groups that were detected by the scanner but not photographed.  We also modeled the probability of thermally detecting various-sized walrus groups to estimate the number of walruses in groups undetected by the scanner.  We used data from radio-tagged walruses to adjust on-ice estimates to account for walruses in the water during the survey.  The estimated area of available habitat averaged 668,000 km<sup>2</sup> and the area of surveyed blocks was 318,204 km<sup>2</sup>.  The number of Pacific walruses within the surveyed area was estimated at 129,000 with 95% confidence limits of 55,000 to 507,000 individuals.  This value can be used by managers as a minimum estimate of the total population size.","language":"English","publisher":"Society for Marine Mammalogy","doi":"10.1111/j.1748-7692.2010.00419.x","usgsCitation":"Speckman, S.G., Chernook, V.I., Burn, D., Udevitz, M.S., Kochnev, A.A., Vasilev, A., Jay, C.V., Lisovsky, A., Fischbach, A.S., and Benter, R., 2011, Results and evaluation of a survey to estimate Pacific walrus population size, 2006: Marine Mammal Science, v. 27, no. 3, p. 514-553, https://doi.org/10.1111/j.1748-7692.2010.00419.x.","productDescription":"40 p.","startPage":"514","endPage":"553","ipdsId":"IP-017489","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":295601,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Russia, United States","otherGeospatial":"Bering Sea","volume":"27","issue":"3","noUsgsAuthors":false,"publicationDate":"2010-09-30","publicationStatus":"PW","scienceBaseUri":"5448c71fe4b0f888a81b87b0","contributors":{"authors":[{"text":"Speckman, Suzann G.","contributorId":83044,"corporation":false,"usgs":true,"family":"Speckman","given":"Suzann","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":503696,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chernook, Vladimir I.","contributorId":56988,"corporation":false,"usgs":true,"family":"Chernook","given":"Vladimir","email":"","middleInitial":"I.","affiliations":[],"preferred":false,"id":503694,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Burn, Douglas M.","contributorId":65022,"corporation":false,"usgs":true,"family":"Burn","given":"Douglas M.","affiliations":[],"preferred":false,"id":503695,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Udevitz, Mark S. 0000-0003-4659-138X mudevitz@usgs.gov","orcid":"https://orcid.org/0000-0003-4659-138X","contributorId":3189,"corporation":false,"usgs":true,"family":"Udevitz","given":"Mark","email":"mudevitz@usgs.gov","middleInitial":"S.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":503688,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kochnev, Anatoly A.","contributorId":50096,"corporation":false,"usgs":true,"family":"Kochnev","given":"Anatoly","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":503693,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Vasilev, Alexander","contributorId":19891,"corporation":false,"usgs":true,"family":"Vasilev","given":"Alexander","email":"","affiliations":[],"preferred":false,"id":503690,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jay, Chadwick V. 0000-0002-9559-2189 cjay@usgs.gov","orcid":"https://orcid.org/0000-0002-9559-2189","contributorId":192736,"corporation":false,"usgs":true,"family":"Jay","given":"Chadwick","email":"cjay@usgs.gov","middleInitial":"V.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":503689,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lisovsky, Alexander","contributorId":47313,"corporation":false,"usgs":true,"family":"Lisovsky","given":"Alexander","email":"","affiliations":[],"preferred":false,"id":503692,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Fischbach, Anthony S. 0000-0002-6555-865X afischbach@usgs.gov","orcid":"https://orcid.org/0000-0002-6555-865X","contributorId":2865,"corporation":false,"usgs":true,"family":"Fischbach","given":"Anthony","email":"afischbach@usgs.gov","middleInitial":"S.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":503687,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Benter, R. Bradley","contributorId":21482,"corporation":false,"usgs":true,"family":"Benter","given":"R. Bradley","affiliations":[],"preferred":false,"id":503691,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70005798,"text":"ofr20111113 - 2011 - Summary of oceanographic and water&ndash;quality measurements in West Falmouth Harbor and Buzzards Bay, Massachusetts, 2009&ndash;2010","interactions":[],"lastModifiedDate":"2012-02-10T00:12:01","indexId":"ofr20111113","displayToPublicDate":"2011-10-21T00:00:00","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":"2011-1113","title":"Summary of oceanographic and water&ndash;quality measurements in West Falmouth Harbor and Buzzards Bay, Massachusetts, 2009&ndash;2010","docAbstract":"This data report presents oceanographic and water-quality observations made at six locations in West Falmouth Harbor and Buzzards Bay, Massachusetts, from August 2009 to September 2010. Both Buzzards Bay and West Falmouth Harbor are estuarine embayments; the input of freshwater on the eastern margin of Buzzards Bay adjacent to Cape Cod and West Falmouth Harbor is largely due to groundwater. In West Falmouth Harbor, the groundwater that seeps into the harbor is characterized by relatively high levels of nitrate. This high nitrate load has modified the ecology of the harbor (Howes and others, 2006) and may be a significant source of nitrate to Buzzards Bay during seasons with low biological nitrate uptake. The U.S. Geological Survey undertook these measurements to improve understanding of circulation, residence time, and water quality in the harbor and bay. We set up and monitored multiple sites in both Buzzards Bay and West Falmouth Harbor, measuring depth, water velocity,salinity, pH, dissolved oxygen, chlorophyll-a, and nitrate concentration. In this report we present the processed time-series data at these locations and provide access to the data and metadata. The results will be used to understand circulation mechanisms and verify numerical models of hydrodynamics and biogeochemistry.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20111113","usgsCitation":"Ganju, N., Dickhudt, P., Thomas, J., Borden, J., Sherwood, C.R., Montgomery, E., Twomey, E.R., and Martini, M.A., 2011, Summary of oceanographic and water&ndash;quality measurements in West Falmouth Harbor and Buzzards Bay, Massachusetts, 2009&ndash;2010: U.S. Geological Survey Open-File Report 2011-1113, HTML Document, https://doi.org/10.3133/ofr20111113.","productDescription":"HTML Document","temporalStart":"2009-01-01","temporalEnd":"2010-12-31","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":116505,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2011_1113.gif"},{"id":94432,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2011/1113/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Massachusetts","otherGeospatial":"West Falmouth Harbor;Buzzards Bay","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -71.01666666666667,14.066666666666666 ], [ -71.01666666666667,41.13333333333333 ], [ -70.06666666666666,41.13333333333333 ], [ -70.06666666666666,14.066666666666666 ], [ -71.01666666666667,14.066666666666666 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b02e4b07f02db698c5b","contributors":{"authors":[{"text":"Ganju, Neil K. 0000-0002-1096-0465","orcid":"https://orcid.org/0000-0002-1096-0465","contributorId":93543,"corporation":false,"usgs":true,"family":"Ganju","given":"Neil K.","affiliations":[],"preferred":false,"id":353260,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dickhudt, Patrick J.","contributorId":48302,"corporation":false,"usgs":true,"family":"Dickhudt","given":"Patrick J.","affiliations":[],"preferred":false,"id":353258,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thomas, Jennifer A.","contributorId":16153,"corporation":false,"usgs":true,"family":"Thomas","given":"Jennifer A.","affiliations":[],"preferred":false,"id":353256,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Borden, Jonathan 0000-0001-6844-3340 jborden@usgs.gov","orcid":"https://orcid.org/0000-0001-6844-3340","contributorId":3098,"corporation":false,"usgs":true,"family":"Borden","given":"Jonathan","email":"jborden@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":353255,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"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":353254,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Montgomery, Ellyn T.","contributorId":78038,"corporation":false,"usgs":true,"family":"Montgomery","given":"Ellyn T.","affiliations":[],"preferred":false,"id":353259,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Twomey, Erin R.","contributorId":44860,"corporation":false,"usgs":true,"family":"Twomey","given":"Erin","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":353257,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Martini, Marinna A. 0000-0002-7757-5158 mmartini@usgs.gov","orcid":"https://orcid.org/0000-0002-7757-5158","contributorId":2456,"corporation":false,"usgs":true,"family":"Martini","given":"Marinna","email":"mmartini@usgs.gov","middleInitial":"A.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":353253,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70005793,"text":"fs20113104 - 2011 - Application of the SPARROW watershed model to describe nutrient sources and transport in the Missouri River Basin","interactions":[],"lastModifiedDate":"2012-03-02T17:16:08","indexId":"fs20113104","displayToPublicDate":"2011-10-21T00:00:00","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":"2011-3104","title":"Application of the SPARROW watershed model to describe nutrient sources and transport in the Missouri River Basin","docAbstract":"Spatially Referenced Regression On Watershed attributes (SPARROW) models were developed to provide spatially explicit information on local and regional total nitrogen and total phosphorus sources and transport in the Missouri River Basin. Model results provide estimates of the relative contributions from various nutrient sources and delivery factors. The models also describe instream decay and reservoir and lake attenuation of nutrients. Results aid in the prioritization of nutrient-reduction strategies by identifying major sources and delivery factors contributing to instream nutrient loads and stream reaches carrying the largest nutrient loads in the Missouri River Basin.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20113104","usgsCitation":"Brown, J., 2011, Application of the SPARROW watershed model to describe nutrient sources and transport in the Missouri River Basin: U.S. Geological Survey Fact Sheet 2011-3104, 4 p., https://doi.org/10.3133/fs20113104.","productDescription":"4 p.","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":116472,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs_2011_3104.gif"},{"id":94429,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2011/3104/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","otherGeospatial":"Missouri River Basin","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4ac6e4b07f02db67a69d","contributors":{"authors":[{"text":"Brown, Juliane B.","contributorId":74040,"corporation":false,"usgs":true,"family":"Brown","given":"Juliane B.","affiliations":[],"preferred":false,"id":353244,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70005745,"text":"sir20115147 - 2011 - Proceedings of the third USGS modeling conference, June 7-11, 2010, Broomfield, Colorado-Understanding and predicting for a changing world","interactions":[],"lastModifiedDate":"2012-02-02T00:15:59","indexId":"sir20115147","displayToPublicDate":"2011-10-20T00:00:00","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":"2011-5147","title":"Proceedings of the third USGS modeling conference, June 7-11, 2010, Broomfield, Colorado-Understanding and predicting for a changing world","docAbstract":"The Third USGS Modeling Conference was held June 7th-11, 2010, in Broomfield, Colorado. The conference focused on the development and application of analytical and theoretical models and data availability that support managing the Nation's resources and help protect lives and property. Participants at the conference included scientists and managers from Department of the Interior (DOI) Bureaus; national and international Federal, State, and local agencies; academic institutions; and nongovernmental organizations. The conference was organized according to DOI priorities and the strategic directions of the USGS Science Strategy; the following themes were emphasized: (1) Understanding Ecosystems and Restoring America's Treasured Landscapes; (2) Climate Change and Impact; (3) New Energy Frontier and Minerals for America; (4) A National Hazards, Risk, and Resilience Assessment Program; (5) Role of Environment and Wildlife in Human Health; (6) A Water Census of the United States; and (7) New Methods of Investigation and Discovery. The conference theme-\"Understanding and Predicting for a Changing World\"-focused on the following goals: advance development and application of models; provide tools that address management issues; present state-of-the-art models ranging from individual phenomena to integrated systems; and foster a working community among scientists and managers.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20115147","usgsCitation":"Brady, S.R., 2011, Proceedings of the third USGS modeling conference, June 7-11, 2010, Broomfield, Colorado-Understanding and predicting for a changing world: U.S. Geological Survey Scientific Investigations Report 2011-5147, x, 80 p.; Appendices, https://doi.org/10.3133/sir20115147.","productDescription":"x, 80 p.; Appendices","temporalStart":"2010-06-07","temporalEnd":"2010-06-11","costCenters":[{"id":261,"text":"Energy and Minerals and Environmental Health","active":false,"usgs":true}],"links":[{"id":116470,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2011_5147.gif"},{"id":94427,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2011/5147/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a9ee4b07f02db660353","contributors":{"authors":[{"text":"Brady, Shailaja R. srbrady@usgs.gov","contributorId":1762,"corporation":false,"usgs":true,"family":"Brady","given":"Shailaja","email":"srbrady@usgs.gov","middleInitial":"R.","affiliations":[],"preferred":true,"id":353150,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70005787,"text":"ofr20111231 - 2011 - Probabilistic seismic hazard assessment including site effects for Evansville, Indiana, and the surrounding region","interactions":[],"lastModifiedDate":"2012-02-10T00:12:00","indexId":"ofr20111231","displayToPublicDate":"2011-10-19T00:00:00","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":"2011-1231","title":"Probabilistic seismic hazard assessment including site effects for Evansville, Indiana, and the surrounding region","docAbstract":"We provide a probabilistic seismic hazard assessment for the Evansville, Indiana region incorporating information from new surficial geologic mapping efforts on the part of the U.S. Geological Survey (USGS) and the Kentucky and Indiana State Geological Surveys, as well as information on the thickness and properties of near surface soils and their associated uncertainties. The subsurface information has been compiled to determine bedrock elevation and reference depth-dependent shear-wave velocity models for the different soil types. The probabilistic seismic hazard calculation applied here follows the method used for the 2008 U.S. Geological Survey National Seismic Hazard Maps, with modifications to incorporate estimates of local site conditions and their uncertainties, in a completely probabilistic manner. The resulting analysis shows strong local variations of acceleration with 2 percent probability of exceedance in 50 years, particularly for 0.2-second (s) period spectral acceleration (SA), that are clearly correlated with variations in the thickness of unconsolidated soils above bedrock. These values are much greater than the USGS national seismic hazard map values, which assume B/C site conditions. When compared to the national maps with an assumed uniform site D class amplification factor applied, the high-resolution seismic hazard maps have higher amplitudes for peak ground acceleration and 0.2-s SA for most of the map region. However, deamplification relative to the D class national seismic hazard maps appears to play an important role within the limits of the ancient bedrock valley underlying Evansville where soils are thickest. For 1.0-s SA, the new high-resolution seismic hazard maps show levels consistent with D class site response within the limits of this ancient bedrock valley, but levels consistent with B/C site conditions outside.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20111231","collaboration":"In collaboration with the Evansville Area Earthquake Hazards Mapping Project (EAEHMP)","usgsCitation":"Haase, J.S., Bowling, T., Nowack, R.L., Choi, Y.S., Cramer, C.H., Boyd, O.S., and Bauer, R., 2011, Probabilistic seismic hazard assessment including site effects for Evansville, Indiana, and the surrounding region: U.S. Geological Survey Open-File Report 2011-1231, iv, 29 p., https://doi.org/10.3133/ofr20111231.","productDescription":"iv, 29 p.","onlineOnly":"Y","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":116469,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2011_1231.gif"},{"id":94426,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2011/1231/","linkFileType":{"id":5,"text":"html"}}],"state":"Indiana","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -87.75,37.75 ], [ -87.75,38.13333333333333 ], [ -87.36749999999999,38.13333333333333 ], [ -87.36749999999999,37.75 ], [ -87.75,37.75 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a9ee4b07f02db660c76","contributors":{"authors":[{"text":"Haase, Jennifer S.","contributorId":81238,"corporation":false,"usgs":true,"family":"Haase","given":"Jennifer","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":353217,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bowling, Tim","contributorId":80002,"corporation":false,"usgs":true,"family":"Bowling","given":"Tim","affiliations":[],"preferred":false,"id":353216,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nowack, Robert L.","contributorId":100516,"corporation":false,"usgs":true,"family":"Nowack","given":"Robert","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":353219,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Choi, Yoon S.","contributorId":41128,"corporation":false,"usgs":true,"family":"Choi","given":"Yoon","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":353215,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cramer, Chris H.","contributorId":32196,"corporation":false,"usgs":true,"family":"Cramer","given":"Chris","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":353214,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Boyd, Oliver S. olboyd@usgs.gov","contributorId":956,"corporation":false,"usgs":true,"family":"Boyd","given":"Oliver","email":"olboyd@usgs.gov","middleInitial":"S.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":353213,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bauer, Robert A.","contributorId":92412,"corporation":false,"usgs":true,"family":"Bauer","given":"Robert A.","affiliations":[],"preferred":false,"id":353218,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
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