{"pageNumber":"635","pageRowStart":"15850","pageSize":"25","recordCount":46883,"records":[{"id":70038644,"text":"sir20115198 - 2012 - Quantifying components of the hydrologic cycle in Virginia using chemical hydrograph separation and multiple regression analysis","interactions":[],"lastModifiedDate":"2018-08-15T14:57:41","indexId":"sir20115198","displayToPublicDate":"2012-06-08T00:00:00","publicationYear":"2012","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":"2011-5198","title":"Quantifying components of the hydrologic cycle in Virginia using chemical hydrograph separation and multiple regression analysis","docAbstract":"This study by the U.S. Geological Survey, prepared in cooperation with the Virginia Department of Environmental Quality, quantifies the components of the hydrologic cycle across the Commonwealth of Virginia. Long-term, mean fluxes were calculated for precipitation, surface runoff, infiltration, total evapotranspiration (ET), riparian ET, recharge, base flow (or groundwater discharge) and net total outflow. Fluxes of these components were first estimated on a number of real-time-gaged watersheds across Virginia. Specific conductance was used to distinguish and separate surface runoff from base flow. Specific-conductance data were collected every 15 minutes at 75 real-time gages for approximately 18 months between March 2007 and August 2008. Precipitation was estimated for 1971–2000 using PRISM climate data. Precipitation and temperature from the PRISM data were used to develop a regression-based relation to estimate total ET. The proportion of watershed precipitation that becomes surface runoff was related to physiographic province and rock type in a runoff regression equation. Component flux estimates from the watersheds were transferred to flux estimates for counties and independent cities using the ET and runoff regression equations. Only 48 of the 75 watersheds yielded sufficient data, and data from these 48 were used in the final runoff regression equation. The base-flow proportion for the 48 watersheds averaged 72 percent using specific conductance, a value that was substantially higher than the 61 percent average calculated using a graphical-separation technique (the USGS program PART). Final results for the study are presented as component flux estimates for all counties and independent cities in Virginia.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20115198","collaboration":"Prepared with support from the U.S. Geological Survey Groundwater Resources Program in cooperation with the Virginia Department of Environmental Quality","usgsCitation":"Sanford, W.E., Nelms, D.L., Pope, J.P., and Selnick, D.L., 2012, Quantifying components of the hydrologic cycle in Virginia using chemical hydrograph separation and multiple regression analysis: U.S. Geological Survey Scientific Investigations Report 2011-5198, xi, 78 p.; PDF Download of Appendix 1; PDF Download of Appendix 2, https://doi.org/10.3133/sir20115198.","productDescription":"xi, 78 p.; PDF Download of Appendix 1; PDF Download of Appendix 2","additionalOnlineFiles":"Y","costCenters":[{"id":434,"text":"National Research Program","active":false,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":257382,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2011_5198.jpg"},{"id":257373,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2011/5198/pdf/2011-5198.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":257372,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2011/5198/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Virginia","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -83.61666666666666,36.516666666666666 ], [ -83.61666666666666,39.61666666666667 ], [ -75.21666666666667,39.61666666666667 ], [ -75.21666666666667,36.516666666666666 ], [ -83.61666666666666,36.516666666666666 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a91c4e4b0c8380cd80447","contributors":{"authors":[{"text":"Sanford, Ward E. 0000-0002-6624-0280 wsanford@usgs.gov","orcid":"https://orcid.org/0000-0002-6624-0280","contributorId":2268,"corporation":false,"usgs":true,"family":"Sanford","given":"Ward","email":"wsanford@usgs.gov","middleInitial":"E.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":464584,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nelms, David L. 0000-0001-5747-642X dlnelms@usgs.gov","orcid":"https://orcid.org/0000-0001-5747-642X","contributorId":1892,"corporation":false,"usgs":true,"family":"Nelms","given":"David","email":"dlnelms@usgs.gov","middleInitial":"L.","affiliations":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true},{"id":37759,"text":"VA/WV Water Science Center","active":true,"usgs":true}],"preferred":true,"id":464582,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pope, Jason P. 0000-0003-3199-993X jpope@usgs.gov","orcid":"https://orcid.org/0000-0003-3199-993X","contributorId":2044,"corporation":false,"usgs":true,"family":"Pope","given":"Jason","email":"jpope@usgs.gov","middleInitial":"P.","affiliations":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true},{"id":37759,"text":"VA/WV Water Science Center","active":true,"usgs":true}],"preferred":true,"id":464583,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Selnick, David L.","contributorId":13480,"corporation":false,"usgs":true,"family":"Selnick","given":"David","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":464585,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70005963,"text":"70005963 - 2012 - Evaluation of NDVI to assess avian abundance and richness along the upper San Pedro River","interactions":[],"lastModifiedDate":"2017-11-25T13:48:25","indexId":"70005963","displayToPublicDate":"2012-06-08T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2183,"text":"Journal of Arid Environments","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of NDVI to assess avian abundance and richness along the upper San Pedro River","docAbstract":"Remote-sensing models have become increasingly popular for identifying, characterizing, monitoring, and predicting avian habitat but have largely focused on single bird species. The Normalized Difference Vegetation Index (NDVI) has been shown to positively correlate with avian abundance and richness and has been successfully applied to southwestern riparian systems which are uniquely composed of narrow bands of vegetation in an otherwise dry landscape. Desert riparian ecosystems are important breeding and stopover sites for many bird species but have been degraded due to altered hydrology and land management practices. Here we investigated the use of NDVI, coupled with vegetation, to model the avian community structure along the San Pedro River, Arizona. We also investigated how vegetation and physical features measured locally compared to those data that can be gathered through remote-sensing. We found that NDVI has statistically significant relationships with both avian abundance and species richness, although is better applied at the individual species level. However, the amount of variation explained by even our best models was quite low, suggesting that NDVI habitat models may not presently be an accurate tool for extensive modeling of avian communities. We suggest additional studies in other watersheds to increase our understanding of these bird/NDVI relationships.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Arid Environments","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.jaridenv.2011.09.010","usgsCitation":"McFarland, T., van Riper, C., and Johnson, G.E., 2012, Evaluation of NDVI to assess avian abundance and richness along the upper San Pedro River: Journal of Arid Environments, v. 77, p. 45-53, https://doi.org/10.1016/j.jaridenv.2011.09.010.","productDescription":"9 p.","startPage":"45","endPage":"53","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":257403,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":257390,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.jaridenv.2011.09.010","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Arizona","otherGeospatial":"San Pedro River","volume":"77","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a0c1ce4b0c8380cd52a37","contributors":{"authors":[{"text":"McFarland, T.M.","contributorId":68580,"corporation":false,"usgs":true,"family":"McFarland","given":"T.M.","email":"","affiliations":[],"preferred":false,"id":353535,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"van Riper, Charles III 0000-0003-1084-5843 charles_van_riper@usgs.gov","orcid":"https://orcid.org/0000-0003-1084-5843","contributorId":169488,"corporation":false,"usgs":true,"family":"van Riper","given":"Charles","suffix":"III","email":"charles_van_riper@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":false,"id":353536,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, G. E.","contributorId":103261,"corporation":false,"usgs":true,"family":"Johnson","given":"G.","email":"","middleInitial":"E.","affiliations":[],"preferred":true,"id":353537,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70003760,"text":"70003760 - 2012 - Lithostratigraphy from downhole logs in Hole AND-1B, Antarctica","interactions":[],"lastModifiedDate":"2012-06-09T01:01:37","indexId":"70003760","displayToPublicDate":"2012-06-08T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"Lithostratigraphy from downhole logs in Hole AND-1B, Antarctica","docAbstract":"The ANDRILL (Antarctic Drilling Project) McMurdo Ice Shelf (MIS) project drilled 1285 m of sediment in Hole AND–1B, representing the past 12 m.y. of glacial history. Downhole geophysical logs were acquired to a depth of 1018 mbsf (meters below seafloor), and are complementary to data acquired from the core. The natural gamma radiation (NGR) and magnetic susceptibility logs are particularly useful for understanding lithological and paleoenvironmental change at ANDRILL McMurdo Ice Shelf Hole AND–1B. NGR logs cover the entire interval from the seafloor to 1018 mbsf, and magnetic susceptibility and other logs covered the open hole intervals between 692 and 1018 and 237–342 mbsf. In the upper part of AND–1B, clear alternations between low and high NGR values distinguish between diatomite (lacking minerals containing naturally radioactive K, U, and Th) and diamictite (containing K-bearing clays, K-feldspar, mica, and heavy minerals). In the lower open hole logged section, NGR and magnetic susceptibility can also distinguish claystones (rich in K-bearing clay minerals, relatively low in magnetite) and diamictites (relatively high in magnetite). Sandstones can be distinguished by their high resistivity values in AND–1B. On the basis of these three downhole logs, diamictite, claystones, and sandstones can be predicted correctly for 74% of the 692–1018 mbsf interval. The logs were then used to predict facies for the 6% of this interval that was unrecovered by coring. Given the understanding of the physical property characteristics of different facies, it is also possible to identify subtle changes in lithology from the physical properties and help refine parts of the lithostratigraphy, for example, the varying terrigenous content of diatomites and the transitions from subice diamictite to open-water diatomite.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Geosphere","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"The Geological Society of America","publisherLocation":"Boulder, CO","doi":"10.1130/GES00655.1","usgsCitation":"Williams, T., Morin, R.H., Jarrard, R.D., Jackolski, C.L., Henrys, S.A., Niessen, F., Magens, D., Kuhn, G., Monien, D., and Powell, R.D., 2012, Lithostratigraphy from downhole logs in Hole AND-1B, Antarctica: Geosphere, v. 8, no. 1, p. 127-140, https://doi.org/10.1130/GES00655.1.","productDescription":"14 p.","startPage":"127","endPage":"140","costCenters":[{"id":145,"text":"Branch of Regional Research-Central Region","active":false,"usgs":true}],"links":[{"id":474472,"rank":10000,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges00655.1","text":"Publisher Index Page"},{"id":257384,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":257371,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1130/GES00655.1","linkFileType":{"id":5,"text":"html"}}],"otherGeospatial":"Antarctica","volume":"8","issue":"1","noUsgsAuthors":false,"publicationDate":"2012-01-23","publicationStatus":"PW","scienceBaseUri":"505a48a5e4b0c8380cd67ff6","contributors":{"authors":[{"text":"Williams, Trevor","contributorId":70662,"corporation":false,"usgs":true,"family":"Williams","given":"Trevor","email":"","affiliations":[],"preferred":false,"id":348738,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Morin, Roger H. rhmorin@usgs.gov","contributorId":2432,"corporation":false,"usgs":true,"family":"Morin","given":"Roger","email":"rhmorin@usgs.gov","middleInitial":"H.","affiliations":[],"preferred":true,"id":348734,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jarrard, Richard D.","contributorId":26201,"corporation":false,"usgs":true,"family":"Jarrard","given":"Richard","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":348736,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jackolski, Chris L.","contributorId":66134,"corporation":false,"usgs":true,"family":"Jackolski","given":"Chris","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":348737,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Henrys, Stuart A.","contributorId":89028,"corporation":false,"usgs":true,"family":"Henrys","given":"Stuart","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":348741,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Niessen, Frank","contributorId":77813,"corporation":false,"usgs":true,"family":"Niessen","given":"Frank","email":"","affiliations":[],"preferred":false,"id":348739,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Magens, Diana","contributorId":82995,"corporation":false,"usgs":true,"family":"Magens","given":"Diana","email":"","affiliations":[],"preferred":false,"id":348740,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kuhn, Gerhard","contributorId":102080,"corporation":false,"usgs":true,"family":"Kuhn","given":"Gerhard","email":"","affiliations":[],"preferred":false,"id":348743,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Monien, Donata","contributorId":18239,"corporation":false,"usgs":true,"family":"Monien","given":"Donata","email":"","affiliations":[],"preferred":false,"id":348735,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Powell, Ross D.","contributorId":89768,"corporation":false,"usgs":true,"family":"Powell","given":"Ross","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":348742,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70003726,"text":"70003726 - 2012 - Pore- and fracture-filling gas hydrate reservoirs in the Gulf of Mexico Gas Hydrate Joint Industry Project Leg II Green Canyon 955 H well","interactions":[],"lastModifiedDate":"2012-06-09T01:01:37","indexId":"70003726","displayToPublicDate":"2012-06-08T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2682,"text":"Marine and Petroleum Geology","active":true,"publicationSubtype":{"id":10}},"title":"Pore- and fracture-filling gas hydrate reservoirs in the Gulf of Mexico Gas Hydrate Joint Industry Project Leg II Green Canyon 955 H well","docAbstract":"High-quality logging-while-drilling (LWD) downhole logs were acquired in seven wells drilled during the Gulf of MexicoGasHydrateJointIndustryProjectLegII in the spring of 2009. Well logs obtained in one of the wells, the GreenCanyon Block 955Hwell (GC955-H), indicate that a 27.4-m thick zone at the depth of 428 m below sea floor (mbsf; 1404 feet below sea floor (fbsf)) contains gashydrate within sand with average gashydrate saturations estimated at 60% from the compressional-wave (P-wave) velocity and 65% (locally more than 80%) from resistivity logs if the gashydrate is assumed to be uniformly distributed in this mostly sand-rich section. Similar analysis, however, of log data from a shallow clay-rich interval between 183 and 366 mbsf (600 and 1200 fbsf) yielded average gashydrate saturations of about 20% from the resistivity log (locally 50-60%) and negligible amounts of gashydrate from the P-wave velocity logs. Differences in saturations estimated between resistivity and P-wave velocities within the upper clay-rich interval are caused by the nature of the gashydrate occurrences. In the case of the shallow clay-rich interval, gashydrate fills vertical (or high angle) fractures in rather than fillingpore space in sands. In this study, isotropic and anisotropic resistivity and velocity models are used to analyze the occurrence of gashydrate within both the clay-rich and sand dominated gas-hydrate-bearing reservoirs in the GC955-Hwell.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Marine and Petroleum Geology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.marpetgeo.2011.08.002","usgsCitation":"Lee, M.W., and Collett, T.S., 2012, Pore- and fracture-filling gas hydrate reservoirs in the Gulf of Mexico Gas Hydrate Joint Industry Project Leg II Green Canyon 955 H well: Marine and Petroleum Geology, v. 34, no. 1, p. 62-71, https://doi.org/10.1016/j.marpetgeo.2011.08.002.","productDescription":"10 p.","startPage":"62","endPage":"71","numberOfPages":"32","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":257393,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.marpetgeo.2011.08.002","linkFileType":{"id":5,"text":"html"}},{"id":257400,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Gulf Of Mexico","volume":"34","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a7dcde4b0c8380cd7a17e","contributors":{"authors":[{"text":"Lee, Myung W.","contributorId":84358,"corporation":false,"usgs":true,"family":"Lee","given":"Myung","middleInitial":"W.","affiliations":[],"preferred":false,"id":348545,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Collett, T. S. 0000-0002-7598-4708","orcid":"https://orcid.org/0000-0002-7598-4708","contributorId":86342,"corporation":false,"usgs":true,"family":"Collett","given":"T.","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":348546,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70038153,"text":"70038153 - 2012 - Semiparametric bivariate zero-inflated Poisson models with application to studies of abundance for multiple species","interactions":[],"lastModifiedDate":"2017-05-22T15:43:30","indexId":"70038153","displayToPublicDate":"2012-06-06T11:47:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1577,"text":"Environmetrics","active":true,"publicationSubtype":{"id":10}},"title":"Semiparametric bivariate zero-inflated Poisson models with application to studies of abundance for multiple species","docAbstract":"Ecological studies involving counts of abundance, presence–absence or occupancy rates often produce data having a substantial proportion of zeros. Furthermore, these types of processes are typically multivariate and only adequately described by complex nonlinear relationships involving externally measured covariates. Ignoring these aspects of the data and implementing standard approaches can lead to models that fail to provide adequate scientific understanding of the underlying ecological processes, possibly resulting in a loss of inferential power. One method of dealing with data having excess zeros is to consider the class of univariate zero-inflated generalized linear models. However, this class of models fails to address the multivariate and nonlinear aspects associated with the data usually encountered in practice. Therefore, we propose a semiparametric bivariate zero-inflated Poisson model that takes into account both of these data attributes. The general modeling framework is hierarchical Bayes and is suitable for a broad range of applications. We demonstrate the effectiveness of our model through a motivating example on modeling catch per unit area for multiple species using data from the Missouri River Benthic Fishes Study, implemented by the United States Geological Survey.","language":"English","publisher":"Wiley","publisherLocation":"Hoboken, NJ","doi":"10.1002/env.1142","usgsCitation":"Arab, A., Holan, S.H., Wikle, C.K., and Wildhaber, M.L., 2012, Semiparametric bivariate zero-inflated Poisson models with application to studies of abundance for multiple species: Environmetrics, v. 23, no. 2, p. 183-196, https://doi.org/10.1002/env.1142.","productDescription":"14 p.","startPage":"183","endPage":"196","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":474473,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://arxiv.org/abs/1105.3169","text":"External Repository"},{"id":257436,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"23","issue":"2","noUsgsAuthors":false,"publicationDate":"2011-12-02","publicationStatus":"PW","scienceBaseUri":"505b8d14e4b08c986b31825a","contributors":{"authors":[{"text":"Arab, Ali","contributorId":75002,"corporation":false,"usgs":true,"family":"Arab","given":"Ali","email":"","affiliations":[],"preferred":false,"id":463523,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Holan, Scott H.","contributorId":15878,"corporation":false,"usgs":true,"family":"Holan","given":"Scott","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":463521,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wikle, Christopher K.","contributorId":55680,"corporation":false,"usgs":true,"family":"Wikle","given":"Christopher","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":463522,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wildhaber, Mark L. 0000-0002-6538-9083 mwildhaber@usgs.gov","orcid":"https://orcid.org/0000-0002-6538-9083","contributorId":1386,"corporation":false,"usgs":true,"family":"Wildhaber","given":"Mark","email":"mwildhaber@usgs.gov","middleInitial":"L.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":463520,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70038319,"text":"70038319 - 2012 - Reconciling estimates of the contemporary North American carbon balance among terrestrial biosphere models, atmospheric inversions, and a new approach for estimating net ecosystem exchange from inventory-based data","interactions":[],"lastModifiedDate":"2015-06-17T13:10:31","indexId":"70038319","displayToPublicDate":"2012-06-06T11:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"Reconciling estimates of the contemporary North American carbon balance among terrestrial biosphere models, atmospheric inversions, and a new approach for estimating net ecosystem exchange from inventory-based data","docAbstract":"<p>We develop an approach for estimating net ecosystem exchange (NEE) using inventory-based information over North America (NA) for a recent 7-year period (ca. 2000&ndash;2006). The approach notably retains information on the spatial distribution of NEE, or the vertical exchange between land and atmosphere of all non-fossil fuel sources and sinks of CO<sub>2</sub>, while accounting for lateral transfers of forest and crop products as well as their eventual emissions. The total NEE estimate of a -327 &plusmn; 252 TgC yr<sup>-1</sup> sink for NA was driven primarily by CO<sub>2</sub> uptake in the Forest Lands sector (-248 TgC yr<sup>-1</sup>), largely in the Northwest and Southeast regions of the US, and in the Crop Lands sector (-297 TgC yr<sup>-1</sup>), predominantly in the Midwest US states. These sinks are counteracted by the carbon source estimated for the Other Lands sector (+218 TgC yr<sup>-1</sup>), where much of the forest and crop products are assumed to be returned to the atmosphere (through livestock and human consumption). The ecosystems of Mexico are estimated to be a small net source (+18 TgC yr<sup>-1</sup>) due to land use change between 1993 and 2002. We compare these inventory-based estimates with results from a suite of terrestrial biosphere and atmospheric inversion models, where the mean continental-scale NEE estimate for each ensemble is -511 TgC yr<sup>-1</sup> and -931 TgC yr<sup>-1</sup>, respectively. In the modeling approaches, all sectors, including Other Lands, were generally estimated to be a carbon sink, driven in part by assumed CO<sub>2</sub> fertilization and/or lack of consideration of carbon sources from disturbances and product emissions. Additional fluxes not measured by the inventories, although highly uncertain, could add an additional -239 TgC yr<sup>-1</sup> to the inventory-based NA sink estimate, thus suggesting some convergence with the modeling approaches.</p>","language":"English","publisher":"Wiley","doi":"10.1111/j.1365-2486.2011.02627.x","usgsCitation":"Hayes, D.J., Turner, D., Stinson, G., McGuire, A., Wei, Y., West, T.O., Heath, L., de Jong, B., McConkey, B.G., Birdsey, R.A., Kurz, W., Jacobson, A.R., Huntzinger, D.N., Pan, Y., Post, W.M., and Cook, R.B., 2012, Reconciling estimates of the contemporary North American carbon balance among terrestrial biosphere models, atmospheric inversions, and a new approach for estimating net ecosystem exchange from inventory-based data: Global Change Biology, v. 18, no. 4, p. 1282-1299, https://doi.org/10.1111/j.1365-2486.2011.02627.x.","productDescription":"18 p.","startPage":"1282","endPage":"1299","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"2000-01-01","temporalEnd":"2006-12-31","costCenters":[{"id":108,"text":"Alaska Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true}],"links":[{"id":257434,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"18","issue":"4","noUsgsAuthors":false,"publicationDate":"2012-01-20","publicationStatus":"PW","scienceBaseUri":"505a969fe4b0c8380cd820d8","contributors":{"authors":[{"text":"Hayes, Daniel J.","contributorId":100237,"corporation":false,"usgs":true,"family":"Hayes","given":"Daniel","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":463873,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Turner, David P.","contributorId":85454,"corporation":false,"usgs":true,"family":"Turner","given":"David P.","affiliations":[],"preferred":false,"id":463870,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stinson, Graham","contributorId":24623,"corporation":false,"usgs":true,"family":"Stinson","given":"Graham","email":"","affiliations":[],"preferred":false,"id":463861,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McGuire, A. David","contributorId":18494,"corporation":false,"usgs":true,"family":"McGuire","given":"A. David","affiliations":[],"preferred":false,"id":463860,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wei, Yaxing","contributorId":79347,"corporation":false,"usgs":true,"family":"Wei","given":"Yaxing","email":"","affiliations":[],"preferred":false,"id":463868,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"West, Tristram O.","contributorId":39230,"corporation":false,"usgs":true,"family":"West","given":"Tristram","email":"","middleInitial":"O.","affiliations":[],"preferred":false,"id":463862,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Heath, Linda S.","contributorId":84207,"corporation":false,"usgs":true,"family":"Heath","given":"Linda S.","affiliations":[],"preferred":false,"id":463869,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"de Jong, Bernardus","contributorId":8715,"corporation":false,"usgs":true,"family":"de Jong","given":"Bernardus","email":"","affiliations":[],"preferred":false,"id":463858,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"McConkey, Brian G.","contributorId":96949,"corporation":false,"usgs":true,"family":"McConkey","given":"Brian","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":463871,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Birdsey, Richard A.","contributorId":17751,"corporation":false,"usgs":true,"family":"Birdsey","given":"Richard","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":463859,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Kurz, Werner A.","contributorId":50644,"corporation":false,"usgs":true,"family":"Kurz","given":"Werner A.","affiliations":[],"preferred":false,"id":463865,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Jacobson, Andrew R.","contributorId":50397,"corporation":false,"usgs":true,"family":"Jacobson","given":"Andrew","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":463864,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Huntzinger, Deborah N.","contributorId":70636,"corporation":false,"usgs":true,"family":"Huntzinger","given":"Deborah","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":463867,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Pan, Yude","contributorId":68872,"corporation":false,"usgs":true,"family":"Pan","given":"Yude","email":"","affiliations":[],"preferred":false,"id":463866,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Post, W. Mac","contributorId":43224,"corporation":false,"usgs":true,"family":"Post","given":"W.","email":"","middleInitial":"Mac","affiliations":[],"preferred":false,"id":463863,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Cook, Robert B.","contributorId":98166,"corporation":false,"usgs":true,"family":"Cook","given":"Robert","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":463872,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}}
,{"id":70038503,"text":"70038503 - 2012 - Role of turbulence fluctuations on uncertainties of acoutic Doppler current profiler discharge measurements","interactions":[],"lastModifiedDate":"2012-06-12T01:01:50","indexId":"70038503","displayToPublicDate":"2012-06-06T10:42:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Role of turbulence fluctuations on uncertainties of acoutic Doppler current profiler discharge measurements","docAbstract":"This work presents a systematic analysis quantifying the role of the presence of turbulence fluctuations on uncertainties (random errors) of acoustic Doppler current profiler (ADCP) discharge measurements from moving platforms. Data sets of three-dimensional flow velocities with high temporal and spatial resolution were generated from direct numerical simulation (DNS) of turbulent open channel flow. Dimensionless functions relating parameters quantifying the uncertainty in discharge measurements due to flow turbulence (relative variance and relative maximum random error) to sampling configuration were developed from the DNS simulations and then validated with field-scale discharge measurements. The validated functions were used to evaluate the role of the presence of flow turbulence fluctuations on uncertainties in ADCP discharge measurements. The results of this work indicate that random errors due to the flow turbulence are significant when: (a) a low number of transects is used for a discharge measurement, and (b) measurements are made in shallow rivers using high boat velocity (short time for the boat to cross a flow turbulence structure).","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Water Resources Research","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Geophysical Union","publisherLocation":"Washington, D.C.","doi":"10.1029/2011WR011185","usgsCitation":"Tarrab, L., Garcia, C.M., Cantero, M.I., and Oberg, K., 2012, Role of turbulence fluctuations on uncertainties of acoutic Doppler current profiler discharge measurements: Water Resources Research, v. 48, https://doi.org/10.1029/2011WR011185.","productDescription":"12 p.","startPage":"W06507","numberOfPages":"31","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":474474,"rank":101,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2011wr011185","text":"Publisher Index Page"},{"id":257439,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":257421,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://dx.doi.org/10.1029/2011WR011185","linkFileType":{"id":5,"text":"html"}}],"volume":"48","noUsgsAuthors":false,"publicationDate":"2012-06-06","publicationStatus":"PW","scienceBaseUri":"505aae74e4b0c8380cd870da","contributors":{"authors":[{"text":"Tarrab, Leticia","contributorId":64116,"corporation":false,"usgs":true,"family":"Tarrab","given":"Leticia","email":"","affiliations":[],"preferred":false,"id":464439,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Garcia, Carlos M.","contributorId":71432,"corporation":false,"usgs":true,"family":"Garcia","given":"Carlos","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":464440,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cantero, Mariano I.","contributorId":37609,"corporation":false,"usgs":true,"family":"Cantero","given":"Mariano","email":"","middleInitial":"I.","affiliations":[],"preferred":false,"id":464438,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Oberg, Kevin","contributorId":89385,"corporation":false,"usgs":true,"family":"Oberg","given":"Kevin","affiliations":[],"preferred":false,"id":464441,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70038494,"text":"70038494 - 2012 - Distribution and geochemistry of selected trace elements in the Sacramento River near Keswick Reservoir","interactions":[],"lastModifiedDate":"2018-09-13T10:22:14","indexId":"70038494","displayToPublicDate":"2012-06-06T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1213,"text":"Chemical Geology","active":true,"publicationSubtype":{"id":10}},"title":"Distribution and geochemistry of selected trace elements in the Sacramento River near Keswick Reservoir","docAbstract":"The effect of heavy metals from the Iron Mountain Mines (IMM) Superfund site on the upper Sacramento River is examined using data from water and bed sediment samples collected during 1996-97. Relative to surrounding waters, aluminum, cadmium, cobalt, copper, iron, lead, manganese, thallium, zinc and the rare-earth elements (REE) were all present in high concentrations in effluent from Spring Creek Reservoir (SCR), which enters into the Sacramento River in the Spring Creek Arm of Keswick Reservoir. SCR was constructed in part to regulate the flow of acidic, metal-rich waters draining the IMM Superfund site. Although virtually all of these metals exist in SCR in the dissolved form, upon entering Keswick Reservoir they at least partially converted via precipitation and/or adsorption to the particulate phase. In spite of this, few of the metals settled out; instead the vast majority was transported colloidally down the Sacramento River at least to Bend Bridge, 67 km from Keswick Dam. The geochemical influence of IMM on the upper Sacramento River was variable, chiefly dependent on the flow of Spring Creek. Although the average flow of the Sacramento River at Keswick Dam is 250 m<sup>3</sup>/s (cubic meters per second), even flows as low as 0.3 m<sup>3</sup>/s from Spring Creek were sufficient to account for more than 15% of the metals loading at Bend Bridge, and these proportions increased with increasing Spring Creek flow. The dissolved proportion of the total bioavailable load was dependent on the element but steadily decreased for all metals, from near 100% in Spring Creek to values (for some elements) of less than 1% at Bend Bridge; failure to account for the suspended sediment load in assessments of the effect of metals transport in the Sacramento River can result in estimates which are low by as much as a factor of 100.","language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.chemgeo.2011.12.025","usgsCitation":"Antweiler, R.C., Taylor, H.E., and Alpers, C.N., 2012, Distribution and geochemistry of selected trace elements in the Sacramento River near Keswick Reservoir: Chemical Geology, v. 298-9, p. 70-78, https://doi.org/10.1016/j.chemgeo.2011.12.025.","productDescription":"9 p.","startPage":"70","endPage":"78","costCenters":[{"id":145,"text":"Branch of Regional Research-Central Region","active":false,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":257291,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":257269,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.chemgeo.2011.12.025","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"California","otherGeospatial":"Sacramento River, Keswick Reservoir","volume":"298-9","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a028ee4b0c8380cd500d1","contributors":{"authors":[{"text":"Antweiler, Ronald C. 0000-0001-5652-6034 antweil@usgs.gov","orcid":"https://orcid.org/0000-0001-5652-6034","contributorId":1481,"corporation":false,"usgs":true,"family":"Antweiler","given":"Ronald","email":"antweil@usgs.gov","middleInitial":"C.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":464407,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Taylor, Howard E. hetaylor@usgs.gov","contributorId":1551,"corporation":false,"usgs":true,"family":"Taylor","given":"Howard","email":"hetaylor@usgs.gov","middleInitial":"E.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":464408,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Alpers, Charles N. 0000-0001-6945-7365 cnalpers@usgs.gov","orcid":"https://orcid.org/0000-0001-6945-7365","contributorId":411,"corporation":false,"usgs":true,"family":"Alpers","given":"Charles","email":"cnalpers@usgs.gov","middleInitial":"N.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":464406,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70038478,"text":"70038478 - 2012 - Use of flow-normalization to evaluate nutrient concentration and flux changes in Lake Champlain tributaries, 1990-2009","interactions":[],"lastModifiedDate":"2012-06-07T01:01:38","indexId":"70038478","displayToPublicDate":"2012-06-06T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Use of flow-normalization to evaluate nutrient concentration and flux changes in Lake Champlain tributaries, 1990-2009","docAbstract":"The U.S. Geological Survey evaluated 20 years of total phosphorus (P) and total nitrogen (N) concentration data for 18 Lake Champlain tributaries using a new statistical method based on weighted regressions to estimate daily concentration and flux histories based on discharge, season, and trend as explanatory variables. The use of all the streamflow discharge values for a given date in the record, in a process called \"flow-normalization,\" removed the year-to-year variation due to streamflow and generated a smooth time series from which trends were calculated. This approach to data analysis can be of great value to evaluations of the success of restoration efforts because it filters out the large random fluctuations in the flux that are due to the temporal variability in streamflow. Results for the full 20 years of record showed a mixture of upward and downward trends for concentrations and yields of P and N. When the record was broken into two 10-year periods, for many tributaries, the more recent period showed a reversal in N from upward to downward trends and a similar reversal or reduction in magnitude of upward trends for P. Some measures of P and N concentrations and yields appear to be related to intensity of agricultural activities, point-source loads of P, or population density. Total flow-normalized P flux aggregated from the monitored tributaries showed a decrease of 30 metric tons per year from 1991 to 2009, which is about 15% of the targeted reduction established by the operational management plan for the Lake Champlain Basin.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Great Lakes Research","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.jglr.2011.10.002","usgsCitation":"Medalie, L., Hirsch, R.M., and Archfield, S.A., 2012, Use of flow-normalization to evaluate nutrient concentration and flux changes in Lake Champlain tributaries, 1990-2009: Journal of Great Lakes Research, v. 38, no. 1, p. 58-67, https://doi.org/10.1016/j.jglr.2011.10.002.","productDescription":"10 p.","startPage":"58","endPage":"67","numberOfPages":"10","costCenters":[{"id":468,"text":"New Hampshire-Vermont Water Science Center","active":false,"usgs":true}],"links":[{"id":257305,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":257287,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.jglr.2011.10.002"}],"country":"United States","state":"Vermont;New York","otherGeospatial":"Lake Champlain","volume":"38","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505bbf03e4b08c986b3298fc","contributors":{"authors":[{"text":"Medalie, Laura 0000-0002-2440-2149 lmedalie@usgs.gov","orcid":"https://orcid.org/0000-0002-2440-2149","contributorId":3657,"corporation":false,"usgs":true,"family":"Medalie","given":"Laura","email":"lmedalie@usgs.gov","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":464339,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hirsch, Robert M. 0000-0002-4534-075X rhirsch@usgs.gov","orcid":"https://orcid.org/0000-0002-4534-075X","contributorId":2005,"corporation":false,"usgs":true,"family":"Hirsch","given":"Robert","email":"rhirsch@usgs.gov","middleInitial":"M.","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":464338,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Archfield, Stacey A. 0000-0002-9011-3871 sarch@usgs.gov","orcid":"https://orcid.org/0000-0002-9011-3871","contributorId":1874,"corporation":false,"usgs":true,"family":"Archfield","given":"Stacey","email":"sarch@usgs.gov","middleInitial":"A.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":true,"id":464337,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70038480,"text":"70038480 - 2012 - Studying biodiversity: is a new paradigm really needed?","interactions":[],"lastModifiedDate":"2012-06-07T01:01:38","indexId":"70038480","displayToPublicDate":"2012-06-06T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":997,"text":"BioScience","active":true,"publicationSubtype":{"id":10}},"title":"Studying biodiversity: is a new paradigm really needed?","docAbstract":"Authors in this journal have recommended a new approach to the conduct of biodiversity science. This data-driven approach requires the organization of large amounts of ecological data, analysis of these data to discover complex patterns, and subsequent development of hypotheses corresponding to detected patterns. This proposed new approach has been contrasted with more-traditional knowledge-based approaches in which investigators deduce consequences of competing hypotheses to be confronted with actual data, providing a basis for discriminating among the hypotheses. We note that one approach is directed at hypothesis generation, whereas the other is also focused on discriminating among competing hypotheses. Here, we argue for the importance of using existing knowledge to the separate issues of (a) hypothesis selection and generation and (b) hypothesis discrimination and testing. In times of limited conservation funding, the relative efficiency of different approaches to learning should be an important consideration in decisions about how to study biodiversity.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"BioScience","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Institute of Biological Sciences","publisherLocation":"Washington, D.C.","doi":"10.1525/bio.2012.62.5.11","usgsCitation":"Nichols, J., Cooch, E.G., Nichols, J., and Sauer, J., 2012, Studying biodiversity: is a new paradigm really needed?: BioScience, v. 62, no. 5, p. 497-502, https://doi.org/10.1525/bio.2012.62.5.11.","productDescription":"6 p.","startPage":"497","endPage":"502","numberOfPages":"6","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":474479,"rank":10000,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1525/bio.2012.62.5.11","text":"Publisher Index Page"},{"id":257307,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":257279,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1525/bio.2012.62.5.11","linkFileType":{"id":5,"text":"html"}}],"volume":"62","issue":"5","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505b9ce3e4b08c986b31d505","contributors":{"authors":[{"text":"Nichols, James D. 0000-0002-7631-2890 jnichols@usgs.gov","orcid":"https://orcid.org/0000-0002-7631-2890","contributorId":405,"corporation":false,"usgs":true,"family":"Nichols","given":"James D.","email":"jnichols@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":464344,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cooch, Evan G.","contributorId":100673,"corporation":false,"usgs":true,"family":"Cooch","given":"Evan","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":464347,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nichols, Jonathan M.","contributorId":45945,"corporation":false,"usgs":true,"family":"Nichols","given":"Jonathan M.","affiliations":[],"preferred":false,"id":464346,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sauer, John R. jrsauer@usgs.gov","contributorId":3737,"corporation":false,"usgs":true,"family":"Sauer","given":"John R.","email":"jrsauer@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":464345,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70038609,"text":"fs20123072 - 2012 - Landsat: A global land-imaging mission","interactions":[{"subject":{"id":70038609,"text":"fs20123072 - 2012 - Landsat: A global land-imaging mission","indexId":"fs20123072","publicationYear":"2012","noYear":false,"title":"Landsat: A global land-imaging mission"},"predicate":"SUPERSEDED_BY","object":{"id":70159774,"text":"fs20153081 - 2015 - Landsat—Earth observation satellites","indexId":"fs20153081","publicationYear":"2015","noYear":false,"title":"Landsat—Earth observation satellites"},"id":1}],"supersededBy":{"id":70159774,"text":"fs20153081 - 2015 - Landsat—Earth observation satellites","indexId":"fs20153081","publicationYear":"2015","noYear":false,"title":"Landsat—Earth observation satellites"},"lastModifiedDate":"2017-03-28T11:08:59","indexId":"fs20123072","displayToPublicDate":"2012-06-06T00:00:00","publicationYear":"2012","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":"2012-3072","title":"Landsat: A global land-imaging mission","docAbstract":"<p>Across four decades since 1972, Landsat satellites have continuously acquired space-based images of the Earth's land surface, coastal shallows, and coral reefs. The Landsat Program, a joint effort of the U.S. Geological Survey (USGS) and the National Aeronautics and Space Administration (NASA), was established to routinely gather land imagery from space. NASA develops remote-sensing instruments and spacecraft, then launches and validates the performance of the instruments and satellites. The USGS then assumes ownership and operation of the satellites, in addition to managing all ground reception, data archiving, product generation, and distribution. The result of this program is a long-term record of natural and human induced changes on the global landscape.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20123072","usgsCitation":"Water Resources Division, U.S. Geological Survey, 2012, Landsat: A global land-imaging mission: U.S. Geological Survey Fact Sheet 2012-3072, 4 p., https://doi.org/10.3133/fs20123072.","productDescription":"4 p.","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":257250,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs_2012_3072.gif"},{"id":299698,"rank":101,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2012/3072/fs2012-3072.pdf","text":"Report","size":"3.95 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":257249,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2012/3072/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a43f3e4b0c8380cd6670d","contributors":{"authors":[{"text":"Water Resources Division, U.S. Geological Survey","contributorId":128075,"corporation":true,"usgs":false,"organization":"Water Resources Division, U.S. Geological Survey","id":535188,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70038483,"text":"70038483 - 2012 - Estimating parameters of hidden Markov models based on marked individuals: use of robust design data","interactions":[],"lastModifiedDate":"2012-06-07T01:01:38","indexId":"70038483","displayToPublicDate":"2012-06-06T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Estimating parameters of hidden Markov models based on marked individuals: use of robust design data","docAbstract":"Development and use of multistate mark-recapture models, which provide estimates of parameters of Markov processes in the face of imperfect detection, have become common over the last twenty years. Recently, estimating parameters of hidden Markov models, where the state of an individual can be uncertain even when it is detected, has received attention. Previous work has shown that ignoring state uncertainty biases estimates of survival and state transition probabilities, thereby reducing the power to detect effects. Efforts to adjust for state uncertainty have included special cases and a general framework for a single sample per period of interest. We provide a flexible framework for adjusting for state uncertainty in multistate models, while utilizing multiple sampling occasions per period of interest to increase precision and remove parameter redundancy. These models also produce direct estimates of state structure for each primary period, even for the case where there is just one sampling occasion. We apply our model to expected value data, and to data from a study of Florida manatees, to provide examples of the improvement in precision due to secondary capture occasions. We also provide user-friendly software to implement these models. This general framework could also be used by practitioners to consider constrained models of particular interest, or model the relationship between within-primary period parameters (e.g., state structure) and between-primary period parameters (e.g., state transition probabilities).","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ecology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Ecological Society of America","publisherLocation":"Ithaca, NY","doi":"10.1890/11-1538.1","usgsCitation":"Kendall, W.L., White, G.C., Hines, J., Langtimm, C.A., and Yoshizaki, J., 2012, Estimating parameters of hidden Markov models based on marked individuals: use of robust design data: Ecology, v. 93, no. 4, p. 913-920, https://doi.org/10.1890/11-1538.1.","productDescription":"8 p.","startPage":"913","endPage":"920","numberOfPages":"8","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":257309,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":257270,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1890/11-1538.1","linkFileType":{"id":5,"text":"html"}}],"volume":"93","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a0b34e4b0c8380cd52607","contributors":{"authors":[{"text":"Kendall, William L. wkendall@usgs.gov","contributorId":406,"corporation":false,"usgs":true,"family":"Kendall","given":"William","email":"wkendall@usgs.gov","middleInitial":"L.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":464352,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"White, Gary C.","contributorId":66831,"corporation":false,"usgs":false,"family":"White","given":"Gary","email":"","middleInitial":"C.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":464355,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hines, James E. jhines@usgs.gov","contributorId":3506,"corporation":false,"usgs":true,"family":"Hines","given":"James E.","email":"jhines@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":464354,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Langtimm, Catherine A. 0000-0001-8499-5743 clangtimm@usgs.gov","orcid":"https://orcid.org/0000-0001-8499-5743","contributorId":3045,"corporation":false,"usgs":true,"family":"Langtimm","given":"Catherine","email":"clangtimm@usgs.gov","middleInitial":"A.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":464353,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Yoshizaki, Jun","contributorId":69403,"corporation":false,"usgs":true,"family":"Yoshizaki","given":"Jun","email":"","affiliations":[],"preferred":false,"id":464356,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70038461,"text":"ofr20101091 - 2012 - High-resolution geophysical data collected within Red Brook Harbor, Buzzards Bay, Massachusetts, in 2009","interactions":[],"lastModifiedDate":"2012-10-01T17:16:13","indexId":"ofr20101091","displayToPublicDate":"2012-06-05T00:00:00","publicationYear":"2012","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":"2010-1091","title":"High-resolution geophysical data collected within Red Brook Harbor, Buzzards Bay, Massachusetts, in 2009","docAbstract":"The U.S. Geological Survey conducted a high-resolution geophysical survey within Red Brook Harbor, Massachusetts, from September 28 through November 17, 2009. Red Brook Harbor is located on the eastern edge of Buzzards Bay, south of the Cape Cod Canal. The survey area was approximately 7 square kilometers, with depths ranging from 0 to approximately 10 meters. Data were collected aboard the U.S. Geological Survey Research Vessel Rafael. The research vessel was equipped with a 234-kilohertz interferometric sonar system to collect bathymetry and backscatter data, a dual frequency (3.5- and 200-kilohertz) compression high-intensity radar pulse seismic reflection profiler to collect subbottom data, a sound velocity profiler to acquire speed of sound within the water column, and a sea floor sampling device to collect sediment samples, video, and photographs. The survey was part of an ongoing cooperative effort between the U.S. Geological Survey and the Massachusetts Office of Coastal Zone Management to map the geology of the Massachusetts inner continental shelf. In addition to inclusion within the cooperative geologic mapping effort, these data will be used to assess the shallow-water mapping capability of the geophysical systems deployed for this project, with an emphasis on identifying resolution benchmarks for the interferometric sonar system.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20101091","collaboration":"Prepared in cooperation with the Massachusetts Office of Coastal Zone Management","usgsCitation":"Turecek, A.M., Danforth, W.W., Baldwin, W.E., and Barnhardt, W., 2012, High-resolution geophysical data collected within Red Brook Harbor, Buzzards Bay, Massachusetts, in 2009: U.S. Geological Survey Open-File Report 2010-1091, HTML Document, https://doi.org/10.3133/ofr20101091.","productDescription":"HTML Document","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":257215,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2010_1091.gif"},{"id":257207,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2010/1091/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Massachusetts","otherGeospatial":"Buzzards Bay;Red Brook Harbor","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a3101e4b0c8380cd5db5c","contributors":{"authors":[{"text":"Turecek, Aaron M.","contributorId":22190,"corporation":false,"usgs":true,"family":"Turecek","given":"Aaron","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":464266,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Danforth, William W. 0000-0002-6382-9487 bdanforth@usgs.gov","orcid":"https://orcid.org/0000-0002-6382-9487","contributorId":3292,"corporation":false,"usgs":true,"family":"Danforth","given":"William","email":"bdanforth@usgs.gov","middleInitial":"W.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":464265,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Baldwin, Wayne E. 0000-0001-5886-0917 wbaldwin@usgs.gov","orcid":"https://orcid.org/0000-0001-5886-0917","contributorId":1321,"corporation":false,"usgs":true,"family":"Baldwin","given":"Wayne","email":"wbaldwin@usgs.gov","middleInitial":"E.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":464264,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barnhardt, Walter A.","contributorId":80656,"corporation":false,"usgs":true,"family":"Barnhardt","given":"Walter A.","affiliations":[],"preferred":false,"id":464267,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70038460,"text":"ofr20121106 - 2012 - Interim results from a study of the behavior of juvenile Chinook salmon at Cougar Reservoir and Dam, Oregon, March--August 2011","interactions":[],"lastModifiedDate":"2012-06-06T01:01:36","indexId":"ofr20121106","displayToPublicDate":"2012-06-05T00:00:00","publicationYear":"2012","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":"2012-1106","title":"Interim results from a study of the behavior of juvenile Chinook salmon at Cougar Reservoir and Dam, Oregon, March--August 2011","docAbstract":"The movements and dam passage of yearling juvenile Chinook salmon implanted with acoustic transmitters and passive integrated transponder tags were studied at Cougar Reservoir and Dam, near Springfield, Oregon. A total of 411 hatchery fish and 26 wild fish were tagged and released between March 7 and May 21, 2011. A series of 16 autonomous hydrophones placed throughout the reservoir were used to determine general fish movements over the life of the acoustic transmitter, which was expected to be 91 days. Movements within the reservoir were directional, and it was common for fish to migrate repeatedly from the head of the reservoir downstream to the dam outlet and back. The dam passage rate was 11.2 percent (95-percent confidence interval 7.8&ndash;14.6 percent) for hatchery fish and 15.4 percent (95-percent confidence interval -1.0&ndash;31.8 percent) for wild fish within 91 days from release. Most fish passage occurred at night. The median time from release to dam passage was 34.5 days for hatchery fish and 34.2 days for wild fish. A system of hydrophones near the dam outlet, a temperature control tower, was used to estimate positions of fish in three dimensions to enable detailed analyses of fish behavior near the tower. Analyses of these data indicate that hourly averaged depths of fish within a distance of 74 m from the upstream face of the tower ranged from 0.6 to 9.6 meters, with a median depth of 3.6 meters for hatchery fish and 3.4 meters for wild fish. Dam discharge rates and the diurnal period affected the rates of dam passage. Rates of dam passage were similar when the dam discharge rate was less than 1,200 cubic feet per second, but increased sharply at higher discharges. The rate of dam passage at night was 4.4&ndash;7.8 times greater than during the day, depending on the distance of fish from the dam. This report is an interim summary of data collected as of August 3, 2011, for planning purposes.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121106","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Beeman, J.W., Hansel, H.C., Hansen, A.C., Haner, P.V., Sprando, J.M., Smith, C., and Evans, S.D., 2012, Interim results from a study of the behavior of juvenile Chinook salmon at Cougar Reservoir and Dam, Oregon, March--August 2011: U.S. Geological Survey Open-File Report 2012-1106, vi, 28 p.; Appendix, https://doi.org/10.3133/ofr20121106.","productDescription":"vi, 28 p.; Appendix","startPage":"i","endPage":"31","numberOfPages":"37","additionalOnlineFiles":"N","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":257214,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1106.jpg"},{"id":257206,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1106/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Oregon","otherGeospatial":"Cougar Reservoir And Dam","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a3d19e4b0c8380cd632cf","contributors":{"authors":[{"text":"Beeman, John W. jbeeman@usgs.gov","contributorId":2646,"corporation":false,"usgs":true,"family":"Beeman","given":"John","email":"jbeeman@usgs.gov","middleInitial":"W.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":464258,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hansel, Hal C. 0000-0002-3537-8244 hhansel@usgs.gov","orcid":"https://orcid.org/0000-0002-3537-8244","contributorId":2887,"corporation":false,"usgs":true,"family":"Hansel","given":"Hal","email":"hhansel@usgs.gov","middleInitial":"C.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":464259,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hansen, Amy C. 0000-0002-0298-9137 achansen@usgs.gov","orcid":"https://orcid.org/0000-0002-0298-9137","contributorId":4350,"corporation":false,"usgs":true,"family":"Hansen","given":"Amy","email":"achansen@usgs.gov","middleInitial":"C.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":464261,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Haner, Philip V. 0000-0001-6940-487X phaner@usgs.gov","orcid":"https://orcid.org/0000-0001-6940-487X","contributorId":2364,"corporation":false,"usgs":true,"family":"Haner","given":"Philip","email":"phaner@usgs.gov","middleInitial":"V.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":464257,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sprando, Jamie M. jsprando@usgs.gov","contributorId":4005,"corporation":false,"usgs":true,"family":"Sprando","given":"Jamie","email":"jsprando@usgs.gov","middleInitial":"M.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":464260,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Smith, Collin D. 0000-0003-4184-5686 cdsmith@usgs.gov","orcid":"https://orcid.org/0000-0003-4184-5686","contributorId":7915,"corporation":false,"usgs":true,"family":"Smith","given":"Collin D.","email":"cdsmith@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":false,"id":464263,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Evans, Scott D. 0000-0003-0452-7726 sdevans@usgs.gov","orcid":"https://orcid.org/0000-0003-0452-7726","contributorId":4408,"corporation":false,"usgs":true,"family":"Evans","given":"Scott","email":"sdevans@usgs.gov","middleInitial":"D.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":464262,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70007364,"text":"70007364 - 2012 - Building the United States National Vegetation Classification","interactions":[],"lastModifiedDate":"2021-04-07T13:47:28.743202","indexId":"70007364","displayToPublicDate":"2012-06-05T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":785,"text":"Annali di Botanica - Coenology and Plant Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Building the United States National Vegetation Classification","docAbstract":"The Federal Geographic Data Committee (FGDC) Vegetation Subcommittee, the Ecological Society of America Panel on Vegetation Classification, and NatureServe have worked together to develop the United States National Vegetation Classification (USNVC). The current standard was accepted in 2008 and fosters consistency across Federal agencies and non-federal partners for the description of each vegetation concept and its hierarchical classification. The USNVC is structured as a dynamic standard, where changes to types at any level may be proposed at any time as new information comes in. But, because much information already exists from previous work, the NVC partners first established methods for screening existing types to determine their acceptability with respect to the 2008 standard. Current efforts include a screening process to assign confidence to Association and Group level descriptions, and a review of the upper three levels of the classification. For the upper levels especially, the expectation is that the review process includes international scientists. Immediate future efforts include the review of remaining levels and the development of a proposal review process.","language":"English","publisher":"Department of Environmental Biology - University La Sapienza of Rome, Italy","publisherLocation":"Rome, Italy","doi":"10.4462/annbotrm-9261","usgsCitation":"Franklin, S.B., Faber-Langendoen, D., Jennings, M., Keeler-Wolf, T., Loucks, O., Peet, R., Roberts, D., and McKerrow, A., 2012, Building the United States National Vegetation Classification: Annali di Botanica - Coenology and Plant Ecology, v. 2012, no. 2, p. 1-9, https://doi.org/10.4462/annbotrm-9261.","productDescription":"9 p.","startPage":"1","endPage":"9","costCenters":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true},{"id":37226,"text":"Core Science Analytics, Synthesis, and Libraries","active":true,"usgs":true},{"id":38315,"text":"GAP Analysis Project","active":true,"usgs":true}],"links":[{"id":257193,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"2012","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059f2abe4b0c8380cd4b2b1","contributors":{"authors":[{"text":"Franklin, S. B.","contributorId":78190,"corporation":false,"usgs":true,"family":"Franklin","given":"S.","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":356327,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Faber-Langendoen, D.","contributorId":14569,"corporation":false,"usgs":true,"family":"Faber-Langendoen","given":"D.","affiliations":[],"preferred":false,"id":356321,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jennings, M.","contributorId":6787,"corporation":false,"usgs":true,"family":"Jennings","given":"M.","affiliations":[],"preferred":false,"id":356320,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Keeler-Wolf, T.","contributorId":62455,"corporation":false,"usgs":true,"family":"Keeler-Wolf","given":"T.","affiliations":[],"preferred":false,"id":356326,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Loucks, O.","contributorId":18617,"corporation":false,"usgs":true,"family":"Loucks","given":"O.","email":"","affiliations":[],"preferred":false,"id":356322,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Peet, R.","contributorId":21403,"corporation":false,"usgs":true,"family":"Peet","given":"R.","affiliations":[],"preferred":false,"id":356323,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Roberts, D.","contributorId":24157,"corporation":false,"usgs":true,"family":"Roberts","given":"D.","affiliations":[],"preferred":false,"id":356324,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"McKerrow, A. 0000-0002-8312-2905","orcid":"https://orcid.org/0000-0002-8312-2905","contributorId":49982,"corporation":false,"usgs":true,"family":"McKerrow","given":"A.","affiliations":[],"preferred":false,"id":356325,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70006184,"text":"70006184 - 2012 - Rapid microsatellite identification from Illumina paired-end genomic sequencing in two birds and a snake","interactions":[],"lastModifiedDate":"2012-06-05T01:01:48","indexId":"70006184","displayToPublicDate":"2012-06-04T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Rapid microsatellite identification from Illumina paired-end genomic sequencing in two birds and a snake","docAbstract":"Identification of microsatellites, or simple sequence repeats (SSRs), can be a time-consuming and costly investment requiring enrichment, cloning, and sequencing of candidate loci. Recently, however, high throughput sequencing (with or without prior enrichment for specific SSR loci) has been utilized to identify SSR loci. The direct \"Seq-to-SSR\" approach has an advantage over enrichment-based strategies in that it does not require a priori selection of particular motifs, or prior knowledge of genomic SSR content. It has been more expensive per SSR locus recovered, however, particularly for genomes with few SSR loci, such as bird genomes. The longer but relatively more expensive 454 reads have been preferred over less expensive Illumina reads. Here, we use Illumina paired-end sequence data to identify potentially amplifiable SSR loci (PALs) from a snake (the Burmese python, <i>Python molurus bivittatus</i>), and directly compare these results to those from 454 data. We also compare the python results to results from Illumina sequencing of two bird genomes (Gunnison Sage-grouse, <i>Centrocercus minimus</i>, and Clark's Nutcracker, <i>Nucifraga columbiana</i>), which have considerably fewer SSRs than the python. We show that direct Illumina Seq-to-SSR can identify and characterize thousands of potentially amplifiable SSR loci for as little as $10 per sample &ndash; a fraction of the cost of 454 sequencing. Given that Illumina Seq-to-SSR is effective, inexpensive, and reliable even for species such as birds that have few SSR loci, it seems that there are now few situations for which prior hybridization is justifiable.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"PLoS ONE","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Public Library of Science","publisherLocation":"San Francisco, CA","doi":"10.1371/journal.pone.0030953","usgsCitation":"Castoe, T.A., Poole, A.W., de Koning, A.P., Jones, K., Tomback, D.F., Oyler-McCance, S.J., Fike, J., Lance, S., Streicher, J.W., Smith, E., and Pollock, D., 2012, Rapid microsatellite identification from Illumina paired-end genomic sequencing in two birds and a snake: PLoS ONE, v. 7, no. 2, 10 p.; e30953, https://doi.org/10.1371/journal.pone.0030953.","productDescription":"10 p.; e30953","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":474486,"rank":10000,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0030953","text":"Publisher Index Page"},{"id":257162,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":257145,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1371/journal.pone.0030953","linkFileType":{"id":5,"text":"html"}}],"volume":"7","issue":"2","noUsgsAuthors":false,"publicationDate":"2012-02-14","publicationStatus":"PW","scienceBaseUri":"505a94f2e4b0c8380cd816fa","contributors":{"authors":[{"text":"Castoe, Todd A.","contributorId":23819,"corporation":false,"usgs":true,"family":"Castoe","given":"Todd","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":354029,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Poole, Alexander W.","contributorId":72267,"corporation":false,"usgs":true,"family":"Poole","given":"Alexander","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":354034,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"de Koning, A. P. Jason","contributorId":104353,"corporation":false,"usgs":true,"family":"de Koning","given":"A.","email":"","middleInitial":"P. Jason","affiliations":[],"preferred":false,"id":354037,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jones, Kenneth L.","contributorId":72112,"corporation":false,"usgs":true,"family":"Jones","given":"Kenneth L.","affiliations":[],"preferred":false,"id":354033,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Tomback, Diana F.","contributorId":69427,"corporation":false,"usgs":true,"family":"Tomback","given":"Diana","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":354032,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Oyler-McCance, Sara J. 0000-0003-1599-8769 sara_oyler-mccance@usgs.gov","orcid":"https://orcid.org/0000-0003-1599-8769","contributorId":1973,"corporation":false,"usgs":true,"family":"Oyler-McCance","given":"Sara","email":"sara_oyler-mccance@usgs.gov","middleInitial":"J.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":354027,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Fike, Jennifer A.","contributorId":54468,"corporation":false,"usgs":true,"family":"Fike","given":"Jennifer A.","affiliations":[],"preferred":false,"id":354030,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lance, Stacey L.","contributorId":65976,"corporation":false,"usgs":true,"family":"Lance","given":"Stacey L.","affiliations":[],"preferred":false,"id":354031,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Streicher, Jeffrey W.","contributorId":18236,"corporation":false,"usgs":true,"family":"Streicher","given":"Jeffrey","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":354028,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Smith, Eric N.","contributorId":90989,"corporation":false,"usgs":true,"family":"Smith","given":"Eric N.","affiliations":[],"preferred":false,"id":354035,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Pollock, David D.","contributorId":93351,"corporation":false,"usgs":true,"family":"Pollock","given":"David D.","affiliations":[],"preferred":false,"id":354036,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70004500,"text":"70004500 - 2012 - Improved mapping of National Atmospheric Deposition Program wet-deposition in complex terrain using PRISM-gridded data sets","interactions":[],"lastModifiedDate":"2012-06-05T01:01:49","indexId":"70004500","displayToPublicDate":"2012-06-04T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1552,"text":"Environmental Monitoring and Assessment","onlineIssn":"1573-2959","printIssn":"0167-6369","active":true,"publicationSubtype":{"id":10}},"title":"Improved mapping of National Atmospheric Deposition Program wet-deposition in complex terrain using PRISM-gridded data sets","docAbstract":"High-elevation regions in the United States lack detailed atmospheric wet-deposition data. The National Atmospheric Deposition Program/National Trends Network (NADP/NTN) measures and reports precipitation amounts and chemical constituent concentration and deposition data for the United States on annual isopleth maps using inverse distance weighted (IDW) interpolation methods. This interpolation for unsampled areas does not account for topographic influences. Therefore, NADP/NTN isopleth maps lack detail and potentially underestimate wet deposition in high-elevation regions. The NADP/NTN wet-deposition maps may be improved using precipitation grids generated by other networks. The Parameter-elevation Regressions on Independent Slopes Model (PRISM) produces digital grids of precipitation estimates from many precipitation-monitoring networks and incorporates influences of topographical and geographical features. Because NADP/NTN ion concentrations do not vary with elevation as much as precipitation depths, PRISM is used with unadjusted NADP/NTN data in this paper to calculate ion wet deposition in complex terrain to yield more accurate and detailed isopleth deposition maps in complex terrain. PRISM precipitation estimates generally exceed NADP/NTN precipitation estimates for coastal and mountainous regions in the western United States. NADP/NTN precipitation estimates generally exceed PRISM precipitation estimates for leeward mountainous regions in Washington, Oregon, and Nevada, where abrupt changes in precipitation depths induced by topography are not depicted by IDW interpolation. PRISM-based deposition estimates for nitrate can exceed NADP/NTN estimates by more than 100% for mountainous regions in the western United States.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Environmental Monitoring and Assessment","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","publisherLocation":"Amsterdam, Netherlands","doi":"10.1007/s10661-011-2009-7","usgsCitation":"Latysh, N.E., and Wetherbee, G.A., 2012, Improved mapping of National Atmospheric Deposition Program wet-deposition in complex terrain using PRISM-gridded data sets: Environmental Monitoring and Assessment, v. 184, no. 2, p. 913-928, https://doi.org/10.1007/s10661-011-2009-7.","productDescription":"16 p.","startPage":"913","endPage":"928","costCenters":[{"id":143,"text":"Branch of Quality Systems","active":true,"usgs":true}],"links":[{"id":257177,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":257170,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s10661-011-2009-7","linkFileType":{"id":5,"text":"html"}}],"country":"United States","volume":"184","issue":"2","noUsgsAuthors":false,"publicationDate":"2011-04-08","publicationStatus":"PW","scienceBaseUri":"505a3959e4b0c8380cd618ba","contributors":{"authors":[{"text":"Latysh, Natalie E.","contributorId":39860,"corporation":false,"usgs":true,"family":"Latysh","given":"Natalie","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":350511,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wetherbee, Gregory Alan","contributorId":36414,"corporation":false,"usgs":true,"family":"Wetherbee","given":"Gregory","email":"","middleInitial":"Alan","affiliations":[],"preferred":false,"id":350510,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70005873,"text":"70005873 - 2012 - Gulf of Mexico Gas Hydrate Joint Industry Project Leg II logging-while-drilling data acquisition and analysis","interactions":[],"lastModifiedDate":"2021-08-24T19:33:54.923296","indexId":"70005873","displayToPublicDate":"2012-06-04T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2682,"text":"Marine and Petroleum Geology","active":true,"publicationSubtype":{"id":10}},"title":"Gulf of Mexico Gas Hydrate Joint Industry Project Leg II logging-while-drilling data acquisition and analysis","docAbstract":"<p><span>One of the objectives of the Gulf of Mexico Gas Hydrate Joint Industry Project Leg II (GOM JIP Leg II) was the collection of a comprehensive suite of logging-while-drilling (LWD) data within gas-hydrate-bearing sand reservoirs in order to make accurate estimates of the concentration of gas hydrates under various geologic conditions and to understand the geologic controls on the occurrence of gas hydrate at each of the sites drilled during this expedition. The LWD sensors just above the drill bit provided important information on the nature of the sediments and the occurrence of gas hydrate. There has been significant advancements in the use of downhole well-logging tools to acquire detailed information on the occurrence of gas hydrate in nature: From using electrical resistivity and acoustic logs to identify gas hydrate occurrences in wells to where wireline and advanced logging-while-drilling tools are routinely used to examine the petrophysical nature of gas hydrate reservoirs and the distribution and concentration of gas hydrates within various complex reservoir systems. Recent integrated sediment coring and well-log studies have confirmed that electrical resistivity and acoustic velocity data can yield accurate gas hydrate saturations in sediment grain supported (isotropic) systems such as sand reservoirs, but more advanced log analysis models are required to characterize gas hydrate in fractured (anisotropic) reservoir systems. In support of the GOM JIP Leg II effort, well-log data montages have been compiled and presented in this report which includes downhole logs obtained from all seven wells drilled during this expedition with a focus on identifying and characterizing the potential gas-hydrate-bearing sedimentary section in each of the wells. Also presented and reviewed in this report are the gas-hydrate saturation and sediment porosity logs for each of the wells as calculated from available downhole well logs.</span></p>","largerWorkTitle":"Marine and Petroleum Geology","language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.marpetgeo.2011.08.003","usgsCitation":"Collett, T.S., Lee, M.W., Zyrianova, M., Mrozewski, S.A., Guerin, G., Cook, A.E., and Goldberg, D.S., 2012, Gulf of Mexico Gas Hydrate Joint Industry Project Leg II logging-while-drilling data acquisition and analysis: Marine and Petroleum Geology, v. 34, no. 1, p. 41-61, https://doi.org/10.1016/j.marpetgeo.2011.08.003.","productDescription":"21 p.","startPage":"41","endPage":"61","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":257165,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Gulf Of Mexico","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -95.592041015625,\n              26.696545111585152\n            ],\n            [\n              -89.53857421875,\n              26.696545111585152\n            ],\n            [\n              -89.53857421875,\n              30.50548389892728\n            ],\n            [\n              -95.592041015625,\n              30.50548389892728\n            ],\n            [\n              -95.592041015625,\n              26.696545111585152\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"34","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a2e5ae4b0c8380cd5c49e","contributors":{"authors":[{"text":"Collett, Timothy S. 0000-0002-7598-4708 tcollett@usgs.gov","orcid":"https://orcid.org/0000-0002-7598-4708","contributorId":1698,"corporation":false,"usgs":true,"family":"Collett","given":"Timothy","email":"tcollett@usgs.gov","middleInitial":"S.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":353428,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lee, Myung W. mlee@usgs.gov","contributorId":779,"corporation":false,"usgs":true,"family":"Lee","given":"Myung","email":"mlee@usgs.gov","middleInitial":"W.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":353427,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zyrianova, Margarita V. 0000-0002-3669-1320","orcid":"https://orcid.org/0000-0002-3669-1320","contributorId":30665,"corporation":false,"usgs":true,"family":"Zyrianova","given":"Margarita V.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":353430,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mrozewski, Stefan A.","contributorId":75000,"corporation":false,"usgs":true,"family":"Mrozewski","given":"Stefan","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":353432,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Guerin, Gilles","contributorId":77783,"corporation":false,"usgs":true,"family":"Guerin","given":"Gilles","email":"","affiliations":[],"preferred":false,"id":353433,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cook, Ann E.","contributorId":18218,"corporation":false,"usgs":true,"family":"Cook","given":"Ann","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":353429,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Goldberg, Dave S.","contributorId":42474,"corporation":false,"usgs":true,"family":"Goldberg","given":"Dave","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":353431,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70004894,"text":"70004894 - 2012 - Modelling rating curves using remotely sensed LiDAR data","interactions":[],"lastModifiedDate":"2018-04-02T15:28:10","indexId":"70004894","displayToPublicDate":"2012-06-04T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Modelling rating curves using remotely sensed LiDAR data","docAbstract":"Accurate stream discharge measurements are important for many hydrological studies. In remote locations, however, it is often difficult to obtain stream flow information because of the difficulty in making the discharge measurements necessary to define stage-discharge relationships (rating curves). This study investigates the feasibility of defining rating curves by using a fluid mechanics-based model constrained with topographic data from an airborne LiDAR scanning. The study was carried out for an 8m-wide channel in the boreal landscape of northern Sweden. LiDAR data were used to define channel geometry above a low flow water surface along the 90-m surveyed reach. The channel topography below the water surface was estimated using the simple assumption of a flat streambed. The roughness for the modelled reach was back calculated from a single measurment of discharge. The topographic and roughness information was then used to model a rating curve. To isolate the potential influence of the flat bed assumption, a 'hybrid model' rating curve was developed on the basis of data combined from the LiDAR scan and a detailed ground survey. Whereas this hybrid model rating curve was in agreement with the direct measurements of discharge, the LiDAR model rating curve was equally in agreement with the medium and high flow measurements based on confidence intervals calculated from the direct measurements. The discrepancy between the LiDAR model rating curve and the low flow measurements was likely due to reduced roughness associated with unresolved submerged bed topography. Scanning during periods of low flow can help minimize this deficiency. These results suggest that combined ground surveys and LiDAR scans or multifrequency LiDAR scans that see 'below' the water surface (bathymetric LiDAR) could be useful in generating data needed to run such a fluid mechanics-based model. This opens a realm of possibility to remotely sense and monitor stream flows in channels in remote locations.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Hydrological Processes","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","publisherLocation":"Hoboken, NJ","doi":"10.1002/hyp.9225","usgsCitation":"Nathanson, M., Kean, J.W., Grabs, T.J., Seibert, J., Laudon, H., and Lyon, S.W., 2012, Modelling rating curves using remotely sensed LiDAR data: Hydrological Processes, v. 26, no. 9, p. 1427-1434, https://doi.org/10.1002/hyp.9225.","productDescription":"8 p.","startPage":"1427","endPage":"1434","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":257151,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":257150,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/hyp.9225","linkFileType":{"id":5,"text":"html"}}],"volume":"26","issue":"9","noUsgsAuthors":false,"publicationDate":"2012-03-27","publicationStatus":"PW","scienceBaseUri":"505a5c72e4b0c8380cd6fcd8","contributors":{"authors":[{"text":"Nathanson, Marcus","contributorId":85452,"corporation":false,"usgs":true,"family":"Nathanson","given":"Marcus","affiliations":[],"preferred":false,"id":351621,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kean, Jason W. 0000-0003-3089-0369 jwkean@usgs.gov","orcid":"https://orcid.org/0000-0003-3089-0369","contributorId":1654,"corporation":false,"usgs":true,"family":"Kean","given":"Jason","email":"jwkean@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":351617,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Grabs, Thomas J.","contributorId":107971,"corporation":false,"usgs":true,"family":"Grabs","given":"Thomas","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":351622,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Seibert, Jan","contributorId":176322,"corporation":false,"usgs":false,"family":"Seibert","given":"Jan","email":"","affiliations":[],"preferred":false,"id":351620,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Laudon, Hjalmar","contributorId":46812,"corporation":false,"usgs":true,"family":"Laudon","given":"Hjalmar","affiliations":[],"preferred":false,"id":351619,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lyon, Steve W.","contributorId":44780,"corporation":false,"usgs":true,"family":"Lyon","given":"Steve","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":351618,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70038456,"text":"ofr20121093 - 2012 - Science strategy for Core Science Systems in the U.S. Geological Survey, 2013-2023","interactions":[],"lastModifiedDate":"2018-08-10T16:54:09","indexId":"ofr20121093","displayToPublicDate":"2012-06-04T00:00:00","publicationYear":"2012","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":"2012-1093","title":"Science strategy for Core Science Systems in the U.S. Geological Survey, 2013-2023","docAbstract":"<p>Core Science Systems is a new mission of the U.S. Geological Survey (USGS) that grew out of the 2007 Science Strategy, “Facing Tomorrow’s Challenges: U.S. Geological Survey Science in the Decade 2007–2017.” This report describes the vision for this USGS mission and outlines a strategy for Core Science Systems to facilitate integrated characterization and understanding of the complex earth system. The vision and suggested actions are bold and far-reaching, describing a conceptual model and framework to enhance the ability of USGS to bring its core strengths to bear on pressing societal problems through data integration and scientific synthesis across the breadth of science.</p><p>The context of this report is inspired by a direction set forth in the 2007 Science Strategy. Specifically, ecosystem-based approaches provide the underpinnings for essentially all science themes that define the USGS. Every point on earth falls within a specific ecosystem where data, other information assets, and the expertise of USGS and its many partners can be employed to quantitatively understand how that ecosystem functions and how it responds to natural and anthropogenic disturbances. Every benefit society obtains from the planet—food, water, raw materials to build infrastructure, homes and automobiles, fuel to heat homes and cities, and many others, are derived from or effect ecosystems.</p><p>The vision for Core Science Systems builds on core strengths of the USGS in characterizing and understanding complex earth and biological systems through research, modeling, mapping, and the production of high quality data on the nation’s natural resource infrastructure. Together, these research activities provide a foundation for ecosystem-based approaches through geologic mapping, topographic mapping, and biodiversity mapping. The vision describes a framework founded on these core mapping strengths that makes it easier for USGS scientists to discover critical information, share and publish results, and identify potential collaborations that transcend all USGS missions. The framework is designed to improve the efficiency of scientific work within USGS by establishing a means to preserve and recall data for future applications, organizing existing scientific knowledge and data to facilitate new use of older information, and establishing a future workflow that naturally integrates new data, applications, and other science products to make it easier and more efficient to conduct interdisciplinary research over time. Given the increasing need for integrated data and interdisciplinary approaches to solve modern problems, leadership by the Core Science Systems mission will facilitate problem solving by all USGS missions in ways not formerly possible.</p><p>The report lays out a strategy to achieve this vision through three goals with accompanying objectives and actions. The first goal builds on and enhances the strengths of the Core Science Systems mission in characterizing and understanding the earth system from the geologic framework to the topographic characteristics of the land surface and biodiversity across the nation. The second goal enhances and develops new strengths in computer and information science to make it easier for USGS scientists to discover data and models, share and publish results, and discover connections between scientific information and knowledge. The third goal brings additional focus to research and development methods to address complex issues affecting society that require integration of knowledge and new methods for synthesizing scientific information. Collectively, the report lays out a strategy to create a seamless connection between all USGS activities to accelerate and make USGS science more efficient by fully integrating disciplinary expertise within a new and evolving science paradigm for a changing world in the 21st century.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121093","usgsCitation":"Bristol, R., Euliss, N.H., Booth, N., Burkardt, N., Diffendorfer, J.E., Gesch, D.B., McCallum, B.E., Miller, D., Morman, S.A., Poore, B.S., Signell, R.P., and Viger, R., 2012, Science strategy for Core Science Systems in the U.S. Geological Survey, 2013-2023: U.S. Geological Survey Open-File Report 2012-1093, vi, 29 p., https://doi.org/10.3133/ofr20121093.","productDescription":"vi, 29 p.","onlineOnly":"Y","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":37226,"text":"Core Science Analytics, Synthesis, and Libraries","active":true,"usgs":true}],"links":[{"id":257158,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1093.gif"},{"id":338619,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1093/of2012-1093.pdf"},{"id":257139,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1093/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505b8774e4b08c986b3164be","contributors":{"authors":[{"text":"Bristol, R. Sky 0000-0003-1682-4031","orcid":"https://orcid.org/0000-0003-1682-4031","contributorId":88196,"corporation":false,"usgs":true,"family":"Bristol","given":"R. Sky","affiliations":[],"preferred":false,"id":464231,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Euliss, Ned H. Jr. ceuliss@usgs.gov","contributorId":2916,"corporation":false,"usgs":true,"family":"Euliss","given":"Ned","suffix":"Jr.","email":"ceuliss@usgs.gov","middleInitial":"H.","affiliations":[],"preferred":false,"id":464228,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Booth, Nathaniel L. nlbooth@usgs.gov","contributorId":651,"corporation":false,"usgs":true,"family":"Booth","given":"Nathaniel L.","email":"nlbooth@usgs.gov","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":false,"id":464221,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Burkardt, Nina 0000-0002-9392-9251 burkardtn@usgs.gov","orcid":"https://orcid.org/0000-0002-9392-9251","contributorId":2781,"corporation":false,"usgs":true,"family":"Burkardt","given":"Nina","email":"burkardtn@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":464227,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Diffendorfer, Jay E. 0000-0003-1093-6948 jediffendorfer@usgs.gov","orcid":"https://orcid.org/0000-0003-1093-6948","contributorId":55137,"corporation":false,"usgs":true,"family":"Diffendorfer","given":"Jay","email":"jediffendorfer@usgs.gov","middleInitial":"E.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":false,"id":464230,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gesch, Dean B. 0000-0002-8992-4933 gesch@usgs.gov","orcid":"https://orcid.org/0000-0002-8992-4933","contributorId":2956,"corporation":false,"usgs":true,"family":"Gesch","given":"Dean","email":"gesch@usgs.gov","middleInitial":"B.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":464229,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McCallum, Brian E. 0000-0002-8935-0343 bemccall@usgs.gov","orcid":"https://orcid.org/0000-0002-8935-0343","contributorId":1591,"corporation":false,"usgs":true,"family":"McCallum","given":"Brian","email":"bemccall@usgs.gov","middleInitial":"E.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":464224,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Miller, David M. 0000-0003-3711-0441 dmiller@usgs.gov","orcid":"https://orcid.org/0000-0003-3711-0441","contributorId":1707,"corporation":false,"usgs":true,"family":"Miller","given":"David M.","email":"dmiller@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":false,"id":464225,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Morman, Suzette A. 0000-0002-2532-1033 smorman@usgs.gov","orcid":"https://orcid.org/0000-0002-2532-1033","contributorId":996,"corporation":false,"usgs":true,"family":"Morman","given":"Suzette","email":"smorman@usgs.gov","middleInitial":"A.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":464222,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Poore, Barbara S. bspoore@usgs.gov","contributorId":2541,"corporation":false,"usgs":true,"family":"Poore","given":"Barbara","email":"bspoore@usgs.gov","middleInitial":"S.","affiliations":[],"preferred":true,"id":464226,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Signell, Richard P. rsignell@usgs.gov","contributorId":1435,"corporation":false,"usgs":true,"family":"Signell","given":"Richard","email":"rsignell@usgs.gov","middleInitial":"P.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":464223,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Viger, Roland J.","contributorId":97528,"corporation":false,"usgs":true,"family":"Viger","given":"Roland J.","affiliations":[],"preferred":false,"id":464232,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
,{"id":70037939,"text":"70037939 - 2012 - Optimizing bankfull discharge and hydraulic geometry relations for streams in New York state","interactions":[],"lastModifiedDate":"2012-06-05T01:01:48","indexId":"70037939","displayToPublicDate":"2012-06-04T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Optimizing bankfull discharge and hydraulic geometry relations for streams in New York state","docAbstract":"This study analyzes how various data stratification schemes can be used to optimize the accuracy and utility of regional hydraulic geometry (HG) models of bankfull discharge, width, depth, and cross-sectional area for streams in New York. Topographic surveys and discharge records from 281 cross sections at 82 gaging stations with drainage areas of 0.52-396 square miles were used to create log-log regressions of region-based relations between bankfull HG metrics and drainage area. The success with which regional models distinguished unique bankfull discharge and HG patterns was assessed by comparing each regional model to those for all other regions and a pooled statewide model. Gages were also stratified (grouped) by mean annual runoff (MAR), Rosgen stream type, and water-surface slope to test if these models were better predictors of HG to drainage area relations. Bankfull discharge models for Regions 4 and 7 were outside the 95% confidence interval bands of the statewide model, and bankfull width, depth, and cross-sectional area models for Region 3 differed significantly (<i>p</i> < 0.05) from those of other regions. This study found that statewide relations between drainage area and HG were strongest when data were stratified by hydrologic region, but that co-variable models could yield more accurate HG estimates in some local regional curve applications.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of the American Water Resources Association","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Water Resources Association","publisherLocation":"Middleburg, VA","doi":"10.1111/j.1752-1688.2011.00623.x","usgsCitation":"Mulvihill, C., and Baldigo, B.P., 2012, Optimizing bankfull discharge and hydraulic geometry relations for streams in New York state: Journal of the American Water Resources Association, v. 48, no. 3, p. 449-463, https://doi.org/10.1111/j.1752-1688.2011.00623.x.","productDescription":"15 p.","startPage":"449","endPage":"463","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":474485,"rank":10000,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/j.1752-1688.2011.00623.x","text":"Publisher Index Page"},{"id":257153,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":257140,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/j.1752-1688.2011.00623.x"}],"country":"United States","state":"New York","volume":"48","issue":"3","noUsgsAuthors":false,"publicationDate":"2012-01-17","publicationStatus":"PW","scienceBaseUri":"505a6effe4b0c8380cd758e3","contributors":{"authors":[{"text":"Mulvihill, Christiane I.","contributorId":31821,"corporation":false,"usgs":true,"family":"Mulvihill","given":"Christiane I.","affiliations":[],"preferred":false,"id":463120,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baldigo, Barry P. 0000-0002-9862-9119 bbaldigo@usgs.gov","orcid":"https://orcid.org/0000-0002-9862-9119","contributorId":1234,"corporation":false,"usgs":true,"family":"Baldigo","given":"Barry","email":"bbaldigo@usgs.gov","middleInitial":"P.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":463119,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70038455,"text":"ofr20121092 - 2012 - The U.S. Geological Survey Ecosystem Science Strategy, 2012-2022 - Advancing discovery and application through collaboration","interactions":[],"lastModifiedDate":"2018-05-24T15:26:19","indexId":"ofr20121092","displayToPublicDate":"2012-06-04T00:00:00","publicationYear":"2012","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":"2012-1092","title":"The U.S. Geological Survey Ecosystem Science Strategy, 2012-2022 - Advancing discovery and application through collaboration","docAbstract":"<p>Ecosystem science is critical to making informed decisions about natural resources that can sustain our Nation’s economic and environmental well-being. Resource managers and policy-makers are faced with countless decisions each year at local, state, tribal, territorial, and national levels on issues as diverse as renewable and non-renewable energy development, agriculture, forestry, water supply, and resource allocations at the urban-rural interface. The urgency for sound decision-making is increasing dramatically as the world is being transformed at an unprecedented pace and in uncertain directions. Environmental changes are associated with natural hazards, greenhouse gas emissions, and increasing demands for water, land, food, energy, mineral, and living resources. At risk is the Nation’s environmental capital, the goods and services provided by resilient ecosystems that are vital to the health and well-being of human societies. Ecosystem science—the study of systems of organisms interacting with their environment and the consequences of natural and human-induced change on these systems—is necessary to inform decision-makers as they develop policies to adapt to these changes.</p><p>This Ecosystems Science Strategy is built on a framework that includes basic and applied science. It highlights the critical roles that USGS scientists and partners can play in building scientific understanding and providing timely information to decision-makers. The strategy underscores the connection between scientific discoveries and the application of new knowledge. The strategy integrates ecosystem science and decision-making, producing new scientific outcomes to assist resource managers and providing public benefits.</p><p>The USGS is uniquely positioned to play an important role in ecosystem science. With its wide range of expertise, the agency can bring holistic, cross-scale, interdisciplinary capabilities to the design and conduct of monitoring, research, and modeling and to new technologies for data collection, management, and visualization. Collectively, these capabilities can be used to reveal ecological patterns and processes, explain how and why ecosystems change, and forecast change over different spatial and temporal scales. USGS science can provide managers with options and decision-support tools to use resources sustainably. The USGS has long-standing, collaborative relationships with the DOI and other partners in the natural sciences, in both conducting science and its application. The USGS engages these partners in cooperative investigations that otherwise would lack the necessary support or be too expensive for a single bureau to conduct.</p><p>The heart of this strategy is a framework and vision for USGS ecosystems science that focuses on five long-term goals, which are seen as interconnected and reinforcing components:<br>•<span>&nbsp;</span><strong>Improve understanding of ecosystem structure, function, and processes.</strong><span>&nbsp;</span>The focus for this goal is an understanding of how ecosystems work, including the dynamics of species, their populations, interactions, and genetics, and how they change across spatial and temporal scales.<span>&nbsp;</span><br>•<span>&nbsp;</span><strong>Advance understanding of how drivers influence ecosystem change.</strong><span>&nbsp;</span>The challenges here are explaining the drivers of ecosystem change, their spatio-temporal patterns, their uncertainties and interactions, and their influence on ecosystem processes and dynamics.<span>&nbsp;</span><br>•<strong><span>&nbsp;</span>Improve understanding of the services that ecosystems provide to society.</strong><span>&nbsp;</span>Here the emphasis is on the measurement of environmental capital and ecosystem services, and the identification of sources and patterns of change in space and time.<span>&nbsp;</span><br>•<span>&nbsp;</span><strong>Develop tools, technologies, and capacities to inform decision-making about ecosystems.</strong><span>&nbsp;</span>This includes developing new technologies and approaches for conducting applications-oriented ecosystem science. A principal challenge will be how to quantify uncertainty and incorporate it in decision analysis.<span>&nbsp;</span><br>•<strong><span>&nbsp;</span>Apply science to enhance strategies for management, conservation, and restoration of ecosystems.</strong><span>&nbsp;</span>These challenges include development of novel approaches to monitoring, assessment, and restoration of ecosystems; new methods to address species of concern and communities at risk; and innovations in decision analysis and support to address imminent ecosystem changes or those that are underway.</p><p>Closely integrated with the five goals are four strategic approaches that provide the path forward for the USGS Ecosystems Mission Area. These approaches cross-cut all of the goals and are seen as essential to the implementation of this strategy:<br><br>•<strong><span>&nbsp;</span>Assess information needs for ecosystem science through enhanced partnerships.</strong><span>&nbsp;</span>Work with the DOI and other agencies and institutions to identify, design, and implement priority decision-driven ecological research.<br>•<span>&nbsp;</span><strong>Promote the use of interdisciplinary ecosystem science.</strong><span>&nbsp;</span>Design and conduct interdisciplinary process-oriented research in ecosystem science.<span>&nbsp;</span><br>•<span>&nbsp;</span><strong>Enhance modeling and forecasting.</strong><span>&nbsp;</span>Build models to forecast ecosystem change, assess future management scenarios, and reduce uncertainties through an adaptive learning process.<span>&nbsp;</span><br>•<span>&nbsp;</span><strong>Support decision-making.</strong><span>&nbsp;</span>Use quantitative approaches to assess the vulnerabilities of ecosystems, habitats, and species, and evaluate strategies for adaptation, restoration, and sustainable management.</p><p>Following the strategic approaches are a set of proposed actions that represent a sampling of specific activities that align with this strategy and that address the Nation’s most pressing environmental needs.</p><p>The strategy emphasizes coordination of activities across the USGS mission areas pursuant to these goals. Ecosystem science is inherently interdisciplinary and requires a broad perspective that incorporates the biological and physical sciences, climate science, information technology, and scientific capacity in mission areas across the Bureau. With its emphasis on coordination, this strategy can provide a critical underpinning for integrated science efforts with scientists from multiple mission areas of the USGS working together. Of course, the USGS will continue to conduct both discipline-specific and interdisciplinary investigations, and both will continue to be vital parts of the ecosystem science portfolio.</p><p>Finally, the strategy stresses the importance of coordination with other Federal agencies and organizations in the natural resources community. The USGS collaborates with resource agencies in the DOI and other organizations throughout the world to meet societal needs for species and ecosystem management. Working with these agencies and organizations, the USGS will play a key role over the next decade in advancing the scientific foundation for sustaining the natural resources that diverse, productive, resilient ecosystems provide.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121092","collaboration":"Public Review Release - Feedback on this report will be accepted through August 1, 2012.  Please see index page for feedback instructions.","usgsCitation":"Williams, B.K., Wingard, G.L., Brewer, G., Cloern, J.E., Gelfenbaum, G.R., Jacobson, R.B., Kershner, J.L., McGuire, A.D., Nichols, J., Shapiro, C.D., van Riper, C., and White, R.P., 2012, The U.S. Geological Survey Ecosystem Science Strategy, 2012-2022 - Advancing discovery and application through collaboration: U.S. Geological Survey Open-File Report 2012-1092, viii, 25 p.; Appendices, https://doi.org/10.3133/ofr20121092.","productDescription":"viii, 25 p.; Appendices","onlineOnly":"Y","costCenters":[],"links":[{"id":257157,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1092.gif"},{"id":257138,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1092/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505ba92ce4b08c986b3220c0","contributors":{"authors":[{"text":"Williams, Byron K. 0000-0001-7644-1396","orcid":"https://orcid.org/0000-0001-7644-1396","contributorId":86616,"corporation":false,"usgs":true,"family":"Williams","given":"Byron","email":"","middleInitial":"K.","affiliations":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"preferred":false,"id":464220,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wingard, G. Lynn 0000-0002-3833-5207 lwingard@usgs.gov","orcid":"https://orcid.org/0000-0002-3833-5207","contributorId":605,"corporation":false,"usgs":true,"family":"Wingard","given":"G.","email":"lwingard@usgs.gov","middleInitial":"Lynn","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":464217,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brewer, Gary","contributorId":37589,"corporation":false,"usgs":true,"family":"Brewer","given":"Gary","email":"","affiliations":[],"preferred":false,"id":464216,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cloern, James E. 0000-0002-5880-6862 jecloern@usgs.gov","orcid":"https://orcid.org/0000-0002-5880-6862","contributorId":1488,"corporation":false,"usgs":true,"family":"Cloern","given":"James","email":"jecloern@usgs.gov","middleInitial":"E.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":464215,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gelfenbaum, Guy R. 0000-0003-1291-6107 ggelfenbaum@usgs.gov","orcid":"https://orcid.org/0000-0003-1291-6107","contributorId":742,"corporation":false,"usgs":true,"family":"Gelfenbaum","given":"Guy","email":"ggelfenbaum@usgs.gov","middleInitial":"R.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":464219,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jacobson, Robert B. 0000-0002-8368-2064 rjacobson@usgs.gov","orcid":"https://orcid.org/0000-0002-8368-2064","contributorId":1289,"corporation":false,"usgs":true,"family":"Jacobson","given":"Robert","email":"rjacobson@usgs.gov","middleInitial":"B.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":464212,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kershner, Jeffrey L. 0000-0002-7093-9860 jkershner@usgs.gov","orcid":"https://orcid.org/0000-0002-7093-9860","contributorId":310,"corporation":false,"usgs":true,"family":"Kershner","given":"Jeffrey","email":"jkershner@usgs.gov","middleInitial":"L.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":464210,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"McGuire, Anthony D. 0000-0003-4646-0750 ffadm@usgs.gov","orcid":"https://orcid.org/0000-0003-4646-0750","contributorId":2493,"corporation":false,"usgs":true,"family":"McGuire","given":"Anthony","email":"ffadm@usgs.gov","middleInitial":"D.","affiliations":[],"preferred":false,"id":464213,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Nichols, James D. 0000-0002-7631-2890 jnichols@usgs.gov","orcid":"https://orcid.org/0000-0002-7631-2890","contributorId":405,"corporation":false,"usgs":true,"family":"Nichols","given":"James D.","email":"jnichols@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":464211,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Shapiro, Carl D. 0000-0002-1598-6808 cshapiro@usgs.gov","orcid":"https://orcid.org/0000-0002-1598-6808","contributorId":3048,"corporation":false,"usgs":true,"family":"Shapiro","given":"Carl","email":"cshapiro@usgs.gov","middleInitial":"D.","affiliations":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"preferred":true,"id":464214,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"van Riper, Charles III 0000-0003-1084-5843 charles_van_riper@usgs.gov","orcid":"https://orcid.org/0000-0003-1084-5843","contributorId":169488,"corporation":false,"usgs":true,"family":"van Riper","given":"Charles","suffix":"III","email":"charles_van_riper@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":false,"id":464218,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"White, Robin P. rpwhite@usgs.gov","contributorId":239,"corporation":false,"usgs":true,"family":"White","given":"Robin","email":"rpwhite@usgs.gov","middleInitial":"P.","affiliations":[{"id":5053,"text":"IPDS Training","active":true,"usgs":true}],"preferred":true,"id":464209,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
,{"id":70038452,"text":"ofr20121066 - 2012 - Strategic directions for U.S. Geological Survey water science, 2012-2022 - Observing, understanding, predicting, and delivering water science to the Nation","interactions":[],"lastModifiedDate":"2017-03-29T13:22:13","indexId":"ofr20121066","displayToPublicDate":"2012-06-04T00:00:00","publicationYear":"2012","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":"2012-1066","title":"Strategic directions for U.S. Geological Survey water science, 2012-2022 - Observing, understanding, predicting, and delivering water science to the Nation","docAbstract":"<h1>Executive Summary</h1>\n<p>This report expands the Water Science Strategy that was begun in the USGS Science Strategy, &ldquo;Facing Tomorrow&rsquo;s Challenges&mdash;U.S. Geological Survey Science in the Decade 2007&ndash;2017&rdquo; (U.S. Geological Survey, 2007). The report looks at the relevant issues facing society and develops a strategy built around observing, understanding, predicting, and delivering water science for the next 5 to 10 years by building new capabilities, tools, and delivery systems to meet the Nation&rsquo;s water-resource needs. This report begins by presenting the vision of water science for the USGS and the societal issues that are influenced by, and in turn influence, the water resources of our Nation. The essence of the Water Strategic Science Plan is built on the concept of &ldquo;water availability,&rdquo; defined&nbsp;<i>as spatial and temporal distribution of water quantity and quality, as related to human and ecosystem needs, as affected by human and natural influences</i>. The report also describes the core capabilities of the USGS in water science&mdash;the strengths, partnerships, and science integrity that the USGS has built over its 130-year history.</p>\n<p>Nine priority actions are presented in the report, which combine and elevate the numerous specific strategic actions listed throughout the report. Priority actions were developed as a means of providing the audience of this report with a list for focused attention, even if resources and time limit the ability of managers to address all of the strategic actions in the report. Priority actions focus on the following:</p>\n<ul>\n<li><span>Improve integrated science planning for water.&nbsp;</span></li>\n<li><span>Expand and enhance water-resource monitoring networks.</span></li>\n<li><span>Characterize the water cycle through development of state-of-the-art 3-D/4-D hydrogeologic framework models at multiple scales.&nbsp;</span></li>\n<li><span>Clarify the linkage between human water use (engineered hydrology) and the water cycle (natural hydrology).</span></li>\n<li><span class=\"indent0\">Advance ecological flow science.</span><span>&nbsp;</span></li>\n<li><span class=\"indent0\">Provide flood-inundation science and information.</span><span>&nbsp;</span></li>\n<li><span class=\"indent0\">Develop rapid deployment teams for water-related emergencies.</span><span>&nbsp;</span></li>\n<li><span class=\"indent0\">Conduct integrated watershed assessment, research, and modeling.</span><span>&nbsp;</span></li>\n<li><span>Deliver water data and analyses to the Nation.</span></li>\n</ul>\n<p>The body of the report is presented as a hierarchal set of 5 goals, 14 objectives, and 27 strategic actions that the USGS should undertake to advance water science through year 2022.&nbsp;<br />The goals deal with:</p>\n<ol>\n<li><span>Providing society the information it needs regarding the amount and quality of water in all components of the water cycle at high temporal and spatial resolution, nationwide;&nbsp;</span></li>\n<li><span>Advancing our understanding of processes that determine water availability;&nbsp;</span></li>\n<li><span>Predicting changes in the quantity and quality of water resources in response to changing climate, population, land use, and management scenarios;</span></li>\n<li><span>Anticipating and responding to water-related emergencies and conflicts; and&nbsp;</span></li>\n<li><span>Delivering timely hydrologic data, analyses, and decision-support tools seamlessly across the Nation to support water-resource decisions.</span></li>\n</ol>\n<p>Scientific information produced on water resources would be without value if it were not communicated to society in a fashion that can inform decisions and actions. Therefore, the chapter following the goals describes how the USGS should inform, involve, and educate society about the science it produces. This includes discussions on local outreach and the use of social media for effective communication.</p>\n<p>This report concludes with a chapter devoted to the crosscutting science issues of the Water Mission Area with the other USGS Mission Areas: Climate and Land Use Change, Core Science Systems, Ecosystems, Energy and Minerals, Environmental Health Science, and Natural Hazards. Not one of these Mission Areas stands alone&mdash;all must work together and integrate their actions to fulfill the USGS science mission for the future. This final chapter identifies the important linkages that must be realized and maintained for this integration to occur.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121066","usgsCitation":"Evenson, E.J., Orndorff, R.C., Blome, C.D., Böhlke, J., Hershberger, P., Langenheim, V., McCabe, G., Morlock, S.E., Reeves, H.W., Verdin, J.P., Weyers, H., and Wood, T.M., 2012, Strategic directions for U.S. Geological Survey water science, 2012-2022 - Observing, understanding, predicting, and delivering water science to the Nation: U.S. Geological Survey Open-File Report 2012-1066, viii, 42 p., https://doi.org/10.3133/ofr20121066.","productDescription":"viii, 42 p.","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":257136,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1066.gif"},{"id":338629,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1066/of2012-1066.pdf"},{"id":257126,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1066/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505b98a3e4b08c986b31c0e3","contributors":{"authors":[{"text":"Evenson, Eric J. eevenson@usgs.gov","contributorId":4072,"corporation":false,"usgs":true,"family":"Evenson","given":"Eric","email":"eevenson@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":true,"id":464183,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Orndorff, Randall C. 0000-0002-8956-5803 rorndorf@usgs.gov","orcid":"https://orcid.org/0000-0002-8956-5803","contributorId":2739,"corporation":false,"usgs":true,"family":"Orndorff","given":"Randall","email":"rorndorf@usgs.gov","middleInitial":"C.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":501,"text":"Office of Science Quality and Integrity","active":true,"usgs":true}],"preferred":true,"id":464181,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Blome, Charles D. 0000-0002-3449-9378 cblome@usgs.gov","orcid":"https://orcid.org/0000-0002-3449-9378","contributorId":1246,"corporation":false,"usgs":true,"family":"Blome","given":"Charles","email":"cblome@usgs.gov","middleInitial":"D.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":464175,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Böhlke, John Karl 0000-0001-5693-6455","orcid":"https://orcid.org/0000-0001-5693-6455","contributorId":22843,"corporation":false,"usgs":true,"family":"Böhlke","given":"John Karl","affiliations":[],"preferred":false,"id":464184,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hershberger, Paul K. phershberger@usgs.gov","contributorId":1945,"corporation":false,"usgs":true,"family":"Hershberger","given":"Paul K.","email":"phershberger@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":false,"id":464179,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Langenheim, Victoria E. 0000-0003-2170-5213 zulanger@usgs.gov","orcid":"https://orcid.org/0000-0003-2170-5213","contributorId":1526,"corporation":false,"usgs":true,"family":"Langenheim","given":"Victoria E.","email":"zulanger@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":false,"id":464178,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McCabe, Gregory J. 0000-0002-9258-2997 gmccabe@usgs.gov","orcid":"https://orcid.org/0000-0002-9258-2997","contributorId":1453,"corporation":false,"usgs":true,"family":"McCabe","given":"Gregory J.","email":"gmccabe@usgs.gov","affiliations":[{"id":218,"text":"Denver Federal Center","active":false,"usgs":true}],"preferred":false,"id":464176,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Morlock, Scott E. smorlock@usgs.gov","contributorId":3212,"corporation":false,"usgs":true,"family":"Morlock","given":"Scott","email":"smorlock@usgs.gov","middleInitial":"E.","affiliations":[],"preferred":true,"id":464182,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Reeves, Howard W. 0000-0001-8057-2081 hwreeves@usgs.gov","orcid":"https://orcid.org/0000-0001-8057-2081","contributorId":2307,"corporation":false,"usgs":true,"family":"Reeves","given":"Howard","email":"hwreeves@usgs.gov","middleInitial":"W.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":464180,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Verdin, James P. 0000-0003-0238-9657 verdin@usgs.gov","orcid":"https://orcid.org/0000-0003-0238-9657","contributorId":720,"corporation":false,"usgs":true,"family":"Verdin","given":"James","email":"verdin@usgs.gov","middleInitial":"P.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":464173,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Weyers, Holly S. hsweyers@usgs.gov","contributorId":1457,"corporation":false,"usgs":true,"family":"Weyers","given":"Holly S.","email":"hsweyers@usgs.gov","affiliations":[],"preferred":true,"id":464177,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Wood, Tamara M. 0000-0001-6057-8080 tmwood@usgs.gov","orcid":"https://orcid.org/0000-0001-6057-8080","contributorId":1164,"corporation":false,"usgs":true,"family":"Wood","given":"Tamara","email":"tmwood@usgs.gov","middleInitial":"M.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":464174,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
,{"id":70038479,"text":"70038479 - 2012 - Modelling effects of chemical exposure on birds wintering in agricultural landscapes: The western burrowing owl (<i>Athene cunicularia hypugaea</i>) as a case study","interactions":[],"lastModifiedDate":"2017-05-23T16:29:09","indexId":"70038479","displayToPublicDate":"2012-06-02T13:30:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"title":"Modelling effects of chemical exposure on birds wintering in agricultural landscapes: The western burrowing owl (<i>Athene cunicularia hypugaea</i>) as a case study","docAbstract":"We describe an ecotoxicological model that simulates the sublethal and lethal effects of chronic, low-level, chemical exposure on birds wintering in agricultural landscapes. Previous models estimating the impact on wildlife of chemicals used in agro-ecosystems typically have not included the variety of pathways, including both dermal and oral, by which individuals are exposed. The present model contains four submodels simulating (1) foraging behavior of individual birds, (2) chemical applications to crops, (3) transfers of chemicals among soil, insects, and small mammals, and (4) transfers of chemicals to birds via ingestion and dermal exposure. We demonstrate use of the model by simulating the impacts of a variety of commonly used herbicides, insecticides, growth regulators, and defoliants on western burrowing owls (<i>Athene cunicularia hypugaea</i>) that winter in agricultural landscapes in southern Texas, United States. The model generated reasonable movement patterns for each chemical through soil, water, insects, and rodents, as well as into the owl via consumption and dermal absorption. Sensitivity analysis suggested model predictions were sensitive to uncertainty associated with estimates of chemical half-lives in birds, soil, and prey, sensitive to parameters associated with estimating dermal exposure, and relatively insensitive to uncertainty associated with details of chemical application procedures (timing of application, amount of drift). Nonetheless, the general trends in chemical accumulations and the relative impacts of the various chemicals were robust to these parameter changes. Simulation results suggested that insecticides posed a greater potential risk to owls of both sublethal and lethal effects than do herbicides, defoliants, and growth regulators under crop scenarios typical of southern Texas, and that use of multiple indicators, or endpoints provided a more accurate assessment of risk due to agricultural chemical exposure. The model should prove useful in helping prioritize the chemicals and transfer pathways targeted in future studies and also, as these new data become available, in assessing the relative danger to other birds of exposure to different types of agricultural chemicals.","language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.ecolmodel.2011.10.017","usgsCitation":"Engelman, C.A., Grant, W.E., Mora, M.A., and Woodin, M., 2012, Modelling effects of chemical exposure on birds wintering in agricultural landscapes: The western burrowing owl (<i>Athene cunicularia hypugaea</i>) as a case study: Ecological Modelling, v. 224, no. 1, p. 90-102, https://doi.org/10.1016/j.ecolmodel.2011.10.017.","productDescription":"13 p.","startPage":"90","endPage":"102","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":257306,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas","volume":"224","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a5c66e4b0c8380cd6fc7e","contributors":{"authors":[{"text":"Engelman, Catherine A.","contributorId":33566,"corporation":false,"usgs":true,"family":"Engelman","given":"Catherine","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":464340,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grant, William E.","contributorId":88590,"corporation":false,"usgs":true,"family":"Grant","given":"William","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":464343,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mora, Miguel A. 0000-0002-8393-0216","orcid":"https://orcid.org/0000-0002-8393-0216","contributorId":46643,"corporation":false,"usgs":true,"family":"Mora","given":"Miguel","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":464341,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Woodin, Marc","contributorId":84201,"corporation":false,"usgs":true,"family":"Woodin","given":"Marc","affiliations":[],"preferred":false,"id":464342,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70038450,"text":"sir20125026 - 2012 - Dam-breach analysis and flood-inundation mapping for Lakes Ellsworth and Lawtonka near Lawton, Oklahoma","interactions":[],"lastModifiedDate":"2020-05-20T12:07:36.292534","indexId":"sir20125026","displayToPublicDate":"2012-06-02T00:00:00","publicationYear":"2012","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":"2012-5026","title":"Dam-breach analysis and flood-inundation mapping for Lakes Ellsworth and Lawtonka near Lawton, Oklahoma","docAbstract":"Dams provide beneficial functions such as flood control, recreation, and reliable water supplies, but they also entail risk: dam breaches and resultant floods can cause substantial property damage and loss of life. The State of Oklahoma requires each owner of a high-hazard dam, which the Federal Emergency Management Agency defines as dams for which failure or misoperation probably will cause loss of human life, to develop an emergency action plan specific to that dam. Components of an emergency action plan are to simulate a flood resulting from a possible dam breach and map the resulting downstream flood-inundation areas. The resulting flood-inundation maps can provide valuable information to city officials, emergency managers, and local residents for planning the emergency response if a dam breach occurs. Accurate topographic data are vital for developing flood-inundation maps. This report presents results of a cooperative study by the city of Lawton, Oklahoma, and the U.S. Geological Survey (USGS) to model dam-breach scenarios at Lakes Ellsworth and Lawtonka near Lawton and to map the potential flood-inundation areas of such dam breaches. To assist the city of Lawton with completion of the emergency action plans for Lakes Ellsworth and Lawtonka Dams, the USGS collected light detection and ranging (lidar) data that were used to develop a high-resolution digital elevation model and a 1-foot contour elevation map for the flood plains downstream from Lakes Ellsworth and Lawtonka. This digital elevation model and field measurements, streamflow-gaging station data (USGS streamflow-gaging station 07311000, East Cache Creek near Walters, Okla.), and hydraulic values were used as inputs for the dynamic (unsteady-flow) model, Hydrologic Engineering Center's River Analysis System (HEC-RAS). The modeled flood elevations were exported to a geographic information system to produce flood-inundation maps. Water-surface profiles were developed for a 75-percent probable maximum flood scenario and a sunny-day dam-breach scenario, as well as for maximum flood-inundation elevations and flood-wave arrival times for selected bridge crossings. Some areas of concern near the city of Lawton, if a dam breach occurs at Lakes Ellsworth or Lawtonka, include water treatment plants, wastewater treatment plants, recreational areas, and community-services offices.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125026","collaboration":"Prepared in cooperation with the city of Lawton","usgsCitation":"Rendon, S.H., Ashworth, C., and Smith, S.J., 2012, Dam-breach analysis and flood-inundation mapping for Lakes Ellsworth and Lawtonka near Lawton, Oklahoma: U.S. Geological Survey Scientific Investigations Report 2012-5026, iii, 9 p., https://doi.org/10.3133/sir20125026.","productDescription":"iii, 9 p.","costCenters":[{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true}],"links":[{"id":257123,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5026.bmp"},{"id":257119,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5026/","linkFileType":{"id":5,"text":"html"}}],"projection":"Oklahoma State Plane South Projection","datum":"North American Datum, 1983","country":"United States","state":"Oklahoma","county":"Comanche County","city":"Lawton","otherGeospatial":"Ellsworth Lake, Lawtonka Lake","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -98.6,34.3 ], [ -98.6,34.93333333333333 ], [ -98.2,34.93333333333333 ], [ -98.2,34.3 ], [ -98.6,34.3 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059fd5de4b0c8380cd4e7d4","contributors":{"authors":[{"text":"Rendon, Samuel H. 0000-0001-5589-0563 srendon@usgs.gov","orcid":"https://orcid.org/0000-0001-5589-0563","contributorId":3940,"corporation":false,"usgs":true,"family":"Rendon","given":"Samuel","email":"srendon@usgs.gov","middleInitial":"H.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":464170,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ashworth, Chad E.","contributorId":62449,"corporation":false,"usgs":true,"family":"Ashworth","given":"Chad E.","affiliations":[],"preferred":false,"id":464171,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, S. Jerrod 0000-0002-9379-8167 sjsmith@usgs.gov","orcid":"https://orcid.org/0000-0002-9379-8167","contributorId":981,"corporation":false,"usgs":true,"family":"Smith","given":"S.","email":"sjsmith@usgs.gov","middleInitial":"Jerrod","affiliations":[{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true}],"preferred":true,"id":464169,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
]}