{"pageNumber":"661","pageRowStart":"16500","pageSize":"25","recordCount":46677,"records":[{"id":70005647,"text":"70005647 - 2011 - Comparison of statistical and theoretical habitat models for conservation planning: The benefit of ensemble prediction","interactions":[],"lastModifiedDate":"2021-01-11T17:55:31.154275","indexId":"70005647","displayToPublicDate":"2011-10-07T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Comparison of statistical and theoretical habitat models for conservation planning: The benefit of ensemble prediction","docAbstract":"Selection of a modeling approach is an important step in the conservation planning process, but little guidance is available. We compared two statistical and three theoretical habitat modeling approaches representing those currently being used for avian conservation planning at landscape and regional scales: hierarchical spatial count (HSC), classification and regression tree (CRT), habitat suitability index (HSI), forest structure database (FS), and habitat association database (HA). We focused our comparison on models for five priority forest-breeding species in the Central Hardwoods Bird Conservation Region: Acadian Flycatcher, Cerulean Warbler, Prairie Warbler, Red-headed Woodpecker, and Worm-eating Warbler. Lacking complete knowledge on the distribution and abundance of each species with which we could illuminate differences between approaches and provide strong grounds for recommending one approach over another, we used two approaches to compare models: rank correlations among model outputs and comparison of spatial correspondence. In general, rank correlations were significantly positive among models for each species, indicating general agreement among the models. Worm-eating Warblers had the highest pairwise correlations, all of which were significant (<i>P</i> , 0.05). Red-headed Woodpeckers had the lowest agreement among models, suggesting greater uncertainty in the relative conservation value of areas within the region. We assessed model uncertainty by mapping the spatial congruence in priorities (i.e., top ranks) resulting from each model for each species and calculating the coefficient of variation across model ranks for each location. This allowed identification of areas more likely to be good targets of conservation effort for a species, those areas that were least likely, and those in between where uncertainty is higher and thus conservation action incorporates more risk. Based on our results, models developed independently for the same purpose (conservation planning for a particular species in a particular geography) yield different answers and thus different conservation strategies. We assert that using only one habitat model (even if validated) as the foundation of a conservation plan is risky. Using multiple models (i.e., ensemble prediction) can reduce uncertainty and increase efficacy of conservation action when models corroborate one another and increase understanding of the system when they do not.","language":"English","publisher":"Ecological Society of America","publisherLocation":"Ithaca, NY","doi":"10.1890/10-1047.1","usgsCitation":"Jones-Farrand, D., Fearer, T.M., Thogmartin, W.E., Thompson, F.R., Nelson, M.D., and Tirpak, J.M., 2011, Comparison of statistical and theoretical habitat models for conservation planning: The benefit of ensemble prediction: Ecological Applications, v. 21, no. 6, p. 2269-2282, https://doi.org/10.1890/10-1047.1.","productDescription":"14 p.","startPage":"2269","endPage":"2282","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":204436,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"21","issue":"6","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b23e4b07f02db6adff6","contributors":{"authors":[{"text":"Jones-Farrand, D. Todd","contributorId":54713,"corporation":false,"usgs":true,"family":"Jones-Farrand","given":"D. Todd","affiliations":[],"preferred":false,"id":352992,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fearer, Todd M.","contributorId":42346,"corporation":false,"usgs":true,"family":"Fearer","given":"Todd","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":352991,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thogmartin, Wayne E. 0000-0002-2384-4279 wthogmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":2545,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","email":"wthogmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":352989,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thompson, Frank R. III","contributorId":12608,"corporation":false,"usgs":true,"family":"Thompson","given":"Frank","suffix":"III","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":352990,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nelson, Mark D.","contributorId":107846,"corporation":false,"usgs":true,"family":"Nelson","given":"Mark","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":352994,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Tirpak, John M.","contributorId":85704,"corporation":false,"usgs":true,"family":"Tirpak","given":"John","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":352993,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70005573,"text":"70005573 - 2011 - Augmenting superpopulation capture-recapture models with population assignment data","interactions":[],"lastModifiedDate":"2012-02-02T00:16:01","indexId":"70005573","displayToPublicDate":"2011-10-07T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1039,"text":"Biometrics","active":true,"publicationSubtype":{"id":10}},"title":"Augmenting superpopulation capture-recapture models with population assignment data","docAbstract":"Ecologists applying capture-recapture models to animal populations sometimes have access to additional information about individuals' populations of origin (e.g., information about genetics, stable isotopes, etc.). Tests that assign an individual's genotype to its most likely source population are increasingly used. Here we show how to augment a superpopulation capture-recapture model with such information. We consider a single superpopulation model without age structure, and split each entry probability into separate components due to births in situ and immigration. We show that it is possible to estimate these two probabilities separately. We first consider the case of perfect information about population of origin, where we can distinguish individuals born in situ from immigrants with certainty. Then we consider the more realistic case of imperfect information, where we use genetic or other information to assign probabilities to each individual's origin as in situ or outside the population. We use a resampling approach to impute the true population of origin from imperfect assignment information. The integration of data on population of origin with capture-recapture data allows us to determine the contributions of immigration and in situ reproduction to the growth of the population, an issue of importance to ecologists. We illustrate our new models with capture-recapture and genetic assignment data from a population of banner-tailed kangaroo rats Dipodomys spectabilis in Arizona.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Biometrics","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","publisherLocation":"Hoboken, NJ","usgsCitation":"Wen, Z., Pollock, K., Nichols, J., and Waser, P., 2011, Augmenting superpopulation capture-recapture models with population assignment data: Biometrics, v. 67, no. 3, p. 691-700.","productDescription":"10 p.","startPage":"691","endPage":"700","numberOfPages":"10","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":204446,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":94370,"rank":700,"type":{"id":15,"text":"Index Page"},"url":"https://onlinelibrary.wiley.com/doi/10.1111/j.1541-0420.2010.01522.x/abstract","linkFileType":{"id":1,"text":"pdf"}}],"volume":"67","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a8fe4b07f02db655602","contributors":{"authors":[{"text":"Wen, Zhi","contributorId":30348,"corporation":false,"usgs":true,"family":"Wen","given":"Zhi","email":"","affiliations":[],"preferred":false,"id":352847,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pollock, Kenneth","contributorId":38273,"corporation":false,"usgs":true,"family":"Pollock","given":"Kenneth","affiliations":[],"preferred":false,"id":352849,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nichols, James","contributorId":26059,"corporation":false,"usgs":true,"family":"Nichols","given":"James","affiliations":[],"preferred":false,"id":352846,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Waser, Peter","contributorId":30745,"corporation":false,"usgs":true,"family":"Waser","given":"Peter","email":"","affiliations":[],"preferred":false,"id":352848,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70005596,"text":"70005596 - 2011 - Effects of wetland vs. landscape variables on parasite communities of Rana pipiens: Links to anthropogenic factors","interactions":[],"lastModifiedDate":"2023-10-17T10:59:53.485688","indexId":"70005596","displayToPublicDate":"2011-10-07T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Effects of wetland vs. landscape variables on parasite communities of <i>Rana pipiens</i>: Links to anthropogenic factors","title":"Effects of wetland vs. landscape variables on parasite communities of Rana pipiens: Links to anthropogenic factors","docAbstract":"<p>The emergence of several diseases affecting amphibian populations worldwide has prompted investigations into determinants of the occurrence and abundance of parasites in frogs. To understand the spatial scales and identify specific environmental factors that determine risks of parasitism in frogs, helminth communities in metamorphic frogs of the northern leopard frog (<i>Rana pipiens</i>) were examined in relation to wetland and landscape factors at local (1 km) and regional (10 km) spatial extents in an agricultural region of Minnesota (USA) using regression analyses, ordination, and variance partitioning techniques. Greater amounts of forested and woody wetland habitats, shorter distances between woody wetlands, and smaller-sized open water patches in surrounding landscapes were the most consistently positive correlates with the abundances, richness, and diversity of helminths found in the frogs. Wetland and local landscape variables were suggested as most important for larval trematode abundances, whereas local and regional landscape variables appeared most important for adult helminths. As previously reported, the sum concentration of atrazine and its metabolite desethylatrazine, was the strongest predictor of larval trematode communities. In this report, we highlight the additional influences of landscape factors. In particular, our data suggest that anthropogenic activities that have resulted in the loss of the availability and connectivity of suitable habitats in the surrounding landscapes of wetlands are associated with declines in helminth richness and abundance, but that alteration of wetland water quality through eutrophication or pesticide contamination may facilitate the transmission of certain parasite taxa when they are present at wetlands. Although additional research is needed to quantify the negative effects of parasitism on frog populations, efforts to reduce inputs of agrochemicals into wetlands to limit larval trematode infections may be warranted, given the current high rates of amphibian declines and extinction events.</p>","language":"English","publisher":"Ecological Society of America","doi":"10.1890/10-0374.1","usgsCitation":"Schotthoefer, A.M., Rohr, J.R., Cole, R.A., Koehler, A., Johnson, C.M., Johnson, L.B., and Beasley, V.R., 2011, Effects of wetland vs. landscape variables on parasite communities of Rana pipiens: Links to anthropogenic factors: Ecological Applications, v. 21, no. 4, p. 1257-1271, https://doi.org/10.1890/10-0374.1.","productDescription":"15 p.","startPage":"1257","endPage":"1271","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-019157","costCenters":[{"id":456,"text":"National Wildlife Health 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Center","active":true,"usgs":true}],"preferred":true,"id":352936,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Koehler, Anson V.","contributorId":73740,"corporation":false,"usgs":true,"family":"Koehler","given":"Anson V.","affiliations":[],"preferred":false,"id":352942,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Johnson, Catherine M.","contributorId":53939,"corporation":false,"usgs":true,"family":"Johnson","given":"Catherine","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":352941,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Johnson, Lucinda B.","contributorId":32291,"corporation":false,"usgs":true,"family":"Johnson","given":"Lucinda","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":352939,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Beasley, Val R.","contributorId":47077,"corporation":false,"usgs":true,"family":"Beasley","given":"Val","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":352940,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70005699,"text":"sir20115110 - 2011 - Thermal mapping of Hawaiian volcanoes with ASTER satellite data","interactions":[],"lastModifiedDate":"2020-09-27T19:19:07.928554","indexId":"sir20115110","displayToPublicDate":"2011-10-07T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2011-5110","title":"Thermal mapping of Hawaiian volcanoes with ASTER satellite data","docAbstract":"Thermal mapping of volcanoes is important to determine baseline thermal behavior in order to judge future thermal activity that may precede an eruption. We used cloud-free kinetic temperature images from the ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) sensor obtained between 2000 and 2010 to produce thermal maps for all five subaerial volcanoes in Hawai&#145;i that have had eruptions in the Holocene (K&#299;lauea, Mauna Loa, Hual&#257;lai, Mauna Kea, and Haleakal&#257;). We stacked the images to provide time-averaged thermal maps, as well as to analyze temperature trends through time. Thermal areas are conspicuous at the summits and rift zones of K&#299;lauea and Mauna Loa, and the summit calderas of these volcanoes contain obvious arcuate, concentric linear thermal areas that probably result from channeling of rising gas along buried, historical intracaldera scarps. The only significant change in thermal activity noted in the study period is the opening of the Halema&#145;uma&#145;u vent at K&#299;lauea's summit in 2008. Several small thermal anomalies are coincident with pit craters on Hual&#257;lai. We suspect that these simply result from the sheltered nature of the depression, but closer inspection is warranted to determine if genuine thermal activity exists in the craters. Thermal areas were not detected on Haleakal&#257; or Mauna Kea. The main limitation of the study is the large pixel size (90 m) of the ASTER images, which reduces our ability to detect subtle changes or to identify small, low-temperature thermal activity. This study, therefore, is meant to characterize the broad, large-scale thermal features on these volcanoes. Future work should study these thermal areas with thermal cameras and thermocouples, which have a greater ability to detect small, low-temperature thermal features.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20115110","usgsCitation":"Patrick, M.R., and Witzke, C., 2011, Thermal mapping of Hawaiian volcanoes with ASTER satellite data: U.S. Geological Survey Scientific Investigations Report 2011-5110, iv, 22 p., https://doi.org/10.3133/sir20115110.","productDescription":"iv, 22 p.","onlineOnly":"Y","temporalStart":"2000-01-01","temporalEnd":"2010-12-31","costCenters":[{"id":336,"text":"Hawaiian Volcano Observatory","active":false,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":116561,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2011_5110.gif"},{"id":94364,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2011/5110/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Hawai'i","otherGeospatial":"Kilauea, Mauna Loa, Haulalai, Mauna Kea, Haleakala","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -157,19 ], [ -157,21 ], [ -155,21 ], [ -155,19 ], [ -157,19 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a55e4b07f02db62cf48","contributors":{"authors":[{"text":"Patrick, Matthew R. 0000-0002-8042-6639 mpatrick@usgs.gov","orcid":"https://orcid.org/0000-0002-8042-6639","contributorId":2070,"corporation":false,"usgs":true,"family":"Patrick","given":"Matthew","email":"mpatrick@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":353084,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Witzke, Coral-Nadine","contributorId":30746,"corporation":false,"usgs":true,"family":"Witzke","given":"Coral-Nadine","email":"","affiliations":[],"preferred":false,"id":353085,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70005698,"text":"sim3158 - 2011 - Geologic map of the Metis Mons quadrangle (V&ndash;6), Venus","interactions":[],"lastModifiedDate":"2023-03-15T21:48:52.45365","indexId":"sim3158","displayToPublicDate":"2011-10-07T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3158","title":"Geologic map of the Metis Mons quadrangle (V&ndash;6), Venus","docAbstract":"The Metis Mons quadrangle (V&ndash;6) in the northern hemisphere of Venus (lat 50&deg; to 75&deg; N., long 240&deg; to 300&deg; E.) includes a variety of coronae, large volcanoes, ridge and fracture (structure) belts, tesserae, impact craters, and other volcanic and structural features distributed within a plains setting, affording study of their detailed age relations and evolutionary development. Coronae in particular have magmatic, tectonic, and topographic signatures that indicate complex evolutionary histories.  Previously, the geology of the map region has been described either in general or narrowly focused investigations. Based on Venera radar mapping, a 1:15,000,000-scale geologic map of part of the northern hemisphere of Venus included the V&ndash;6 map region and identified larger features such as tesserae, smooth and hummocky plains materials, ridge belts, coronae, volcanoes, and impact craters but proposed little relative-age information. Global-scale mapping from Magellan data identified similar features and also determined their mean global ages with crater counts. However, the density of craters on Venus is too low for meaningful relative-age determinations at local to regional scales. Several of the coronae in the map area have been described using Venera data (Stofan and Head, 1990), while Crumpler and others (1992) compiled detailed identification and description of volcanic and tectonic features from Magellan data.  The main purpose of this map is to reconstruct the geologic history of the Metis Mons quadrangle at a level of detail commensurate with a scale of 1:5,000,000 using Magellan data. We interpret four partly overlapping stages of geologic activity, which collectively resulted in the formation of tesserae, coronae (oriented along structure belts), plains materials of varying ages, and four large volcanic constructs. Scattered impact craters, small shields and pancake-shaped domes, and isolated flows superpose the tectonically deformed materials and appear to be the most youthful materials in the map region.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3158","collaboration":"Prepared for the National Aeronautics and Space Administration","usgsCitation":"Dohm, J.M., Tanaka, K.L., and Skinner, J., 2011, Geologic map of the Metis Mons quadrangle (V&ndash;6), Venus: U.S. Geological Survey Scientific Investigations Map 3158, Pamphlet: ii, 12 p., Tables; Map: 47.24 x 36.42 inches; GIS Database Downloads: Readme, Metadata, Data, https://doi.org/10.3133/sim3158.","productDescription":"Pamphlet: ii, 12 p., Tables; Map: 47.24 x 36.42 inches; GIS Database Downloads: Readme, Metadata, Data","additionalOnlineFiles":"Y","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":116562,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim_3158.gif"},{"id":414269,"rank":3,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://doi.org/10.5066/P928WA0S","text":"Interactive map","linkHelpText":"- Geologic Map of the Metis Mons Quadrangle (V–6), Venus, 1:5M. Dohm, Tanaka, and Skinner (2011)"},{"id":94363,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3158/","linkFileType":{"id":5,"text":"html"}}],"scale":"5000000","projection":"Lambert","otherGeospatial":"Venus","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4aefe4b07f02db691604","contributors":{"authors":[{"text":"Dohm, James M.","contributorId":83610,"corporation":false,"usgs":true,"family":"Dohm","given":"James","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":353083,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tanaka, Kenneth L. ktanaka@usgs.gov","contributorId":610,"corporation":false,"usgs":true,"family":"Tanaka","given":"Kenneth","email":"ktanaka@usgs.gov","middleInitial":"L.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":353081,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Skinner, James A. 0000-0002-3644-7010 jskinner@usgs.gov","orcid":"https://orcid.org/0000-0002-3644-7010","contributorId":3187,"corporation":false,"usgs":true,"family":"Skinner","given":"James A.","email":"jskinner@usgs.gov","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":353082,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70003860,"text":"70003860 - 2011 - Electrical conductivity of electrolytes applicable to natural waters from 0 to 100 degrees C","interactions":[],"lastModifiedDate":"2020-01-28T09:14:51","indexId":"70003860","displayToPublicDate":"2011-10-07T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2209,"text":"Journal of Chemical and Engineering Data","active":true,"publicationSubtype":{"id":10}},"title":"Electrical conductivity of electrolytes applicable to natural waters from 0 to 100 degrees C","docAbstract":"The electrical conductivities of 34 electrolyte solutions found in natural waters ranging from (10<sup>-4</sup> to 1) mol&#x95;kg<sup>-1</sup> in concentration and from (5 to 90) &deg;C have been determined. High-quality electrical conductivity data for numerous electrolytes exist in the scientific literature, but the data do not span the concentration or temperature ranges of many electrolytes in natural waters. Methods for calculating the electrical conductivities of natural waters have incorporated these data from the literature, and as a result these methods cannot be used to reliably calculate the electrical conductivity over a large enough range of temperature and concentration. For the single-electrolyte solutions, empirical equations were developed that relate electrical conductivity to temperature and molality. For the 942 molar conductivity determinations for single electrolytes from this study, the mean relative difference between the calculated and measured values was 0.1 %. The calculated molar conductivity was compared to literature data, and the mean relative difference for 1978 measurements was 0.2 %. These data provide an improved basis for calculating electrical conductivity for most natural waters.","language":"English","publisher":"American Chemical Society","doi":"10.1021/je101012n","usgsCitation":"McCleskey, R.B., 2011, Electrical conductivity of electrolytes applicable to natural waters from 0 to 100 degrees C: Journal of Chemical and Engineering Data, v. 56, no. 2, p. 317-327, https://doi.org/10.1021/je101012n.","productDescription":"11 p.","startPage":"317","endPage":"327","costCenters":[{"id":145,"text":"Branch of Regional Research-Central Region","active":false,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":204496,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"56","issue":"2","noUsgsAuthors":false,"publicationDate":"2011-01-05","publicationStatus":"PW","scienceBaseUri":"4f4e4a1be4b07f02db6070ff","contributors":{"authors":[{"text":"McCleskey, R. Blaine 0000-0002-2521-8052 rbmccles@usgs.gov","orcid":"https://orcid.org/0000-0002-2521-8052","contributorId":147399,"corporation":false,"usgs":true,"family":"McCleskey","given":"R.","email":"rbmccles@usgs.gov","middleInitial":"Blaine","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true}],"preferred":true,"id":349183,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70005685,"text":"ofr20111270 - 2011 - Digitized data from ground geophysical surveys in Afghanistan: A website for distribution of data","interactions":[],"lastModifiedDate":"2021-08-23T16:25:39.124407","indexId":"ofr20111270","displayToPublicDate":"2011-10-06T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2011-1270","title":"Digitized data from ground geophysical surveys in Afghanistan: A website for distribution of data","docAbstract":"This document describes the process of digitization of a 1974 report on geophysical work undertaken by Soviet geophysicists in southern and eastern Afghanistan. These data, uncovered in Afghanistan, represent magnetic and electrical ground surveys for which locations are not well defined. Due to lack of location information, these surveys were georeferenced using the cities, rivers, and surrounding geology found on the maps used to plot survey locations. A geologic map found in the Soviet report contains profile lines that correspond to the geophysical maps, allowing these data to be georeferenced. The profiles correspond to sets of resistivity, chargeabiliy, and magnetic data. Some datasets were presented as graphs and needed to be gridded into a useable image. Only the vertical component of the magnetic field was collected, so conversion to total field anomaly was necessary. The magnetic data were collected in either gammas or milliorstead, both of which required conversion to standard SI units. To be useful to modern studies, the datasets and images contained in this report have been digitized, georeferenced, and in some cases converted into computer-ready formats.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20111270","usgsCitation":"Polster, S.W., and Drenth, B.J., 2011, Digitized data from ground geophysical surveys in Afghanistan: A website for distribution of data: U.S. Geological Survey Open-File Report 2011-1270, iii, 18 p.; Appendix 1; Digital Data, https://doi.org/10.3133/ofr20111270.","productDescription":"iii, 18 p.; Appendix 1; Digital Data","additionalOnlineFiles":"Y","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":116560,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2011_1270.png"},{"id":94362,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2011/1270/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 60,29 ], [ 60,39 ], [ 75,39 ], [ 75,29 ], [ 60,29 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a82e4b07f02db64ac87","contributors":{"authors":[{"text":"Polster, Sarah W.","contributorId":26427,"corporation":false,"usgs":true,"family":"Polster","given":"Sarah","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":353075,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Drenth, Benjamin J. 0000-0002-3954-8124 bdrenth@usgs.gov","orcid":"https://orcid.org/0000-0002-3954-8124","contributorId":1315,"corporation":false,"usgs":true,"family":"Drenth","given":"Benjamin","email":"bdrenth@usgs.gov","middleInitial":"J.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":353074,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70003660,"text":"70003660 - 2011 - Physical properties of sediment from the Mount Elbert Gas Hydrate Stratigraphic Test Well, Alaska North Slope","interactions":[],"lastModifiedDate":"2018-11-29T10:05:24","indexId":"70003660","displayToPublicDate":"2011-10-05T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2382,"text":"Journal of Marine and Petroleum Geology","active":true,"publicationSubtype":{"id":10}},"title":"Physical properties of sediment from the Mount Elbert Gas Hydrate Stratigraphic Test Well, Alaska North Slope","docAbstract":"This study characterizes cored and logged sedimentary strata from the February 2007 BP Exploration Alaska, Department of Energy, U.S. Geological Survey (BPXA-DOE-USGS) Mount Elbert Gas Hydrate Stratigraphic Test Well on the Alaska North Slope (ANS). The physical-properties program analyzed core samples recovered from the well, and in conjunction with downhole geophysical logs, produced an extensive dataset including grain size, water content, porosity, grain density, bulk density, permeability, X-ray diffraction (XRD) mineralogy, nuclear magnetic resonance (NMR), and petrography. This study documents the physical property interrelationships in the well and demonstrates their correlation with the occurrence of gas hydrate. Gas hydrate (GH) occurs in three unconsolidated, coarse silt to fine sand intervals within the Paleocene and Eocene beds of the Sagavanirktok Formation: Unit D-GH (614.4 m-627.9 m); unit C-GH1 (649.8 m-660.8 m); and unit C-GH2 (663.2 m-666.3 m). These intervals are overlain by fine to coarse silt intervals with greater clay content. A deeper interval (unit B) is similar lithologically to the gas-hydrate-bearing strata; however, it is water-saturated and contains no hydrate. In this system it appears that high sediment permeability (k) is critical to the formation of concentrated hydrate deposits. Intervals D-GH and C-GH1 have average \"plug\" intrinsic permeability to nitrogen values of 1700 mD and 675 mD, respectively. These values are in strong contrast with those of the overlying, gas-hydrate-free sediments, which have k values of 5.7 mD and 49 mD, respectively, and thus would have provided effective seals to trap free gas. The relation between permeability and porosity critically influences the occurrence of GH. For example, an average increase of 4% in porosity increases permeability by an order of magnitude, but the presence of a second fluid (e.g., methane from dissociating gas hydrate) in the reservoir reduces permeability by more than an order of magnitude.","language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.marpetgeo.2010.01.008","usgsCitation":"Winters, W.J., Walker, M., Hunter, R., Collett, T.S., Boswell, R.M., Rose, K.K., Waite, W., Torres, M., Patil, S., and Dandekar, A., 2011, Physical properties of sediment from the Mount Elbert Gas Hydrate Stratigraphic Test Well, Alaska North Slope: Journal of Marine and Petroleum Geology, v. 28, no. 2, p. 361-380, https://doi.org/10.1016/j.marpetgeo.2010.01.008.","productDescription":"20 p.","startPage":"361","endPage":"380","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":474912,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hdl.handle.net/1912/4400","text":"External Repository"},{"id":204542,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","volume":"28","issue":"2","edition":"2011","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4adbe4b07f02db685b1a","contributors":{"authors":[{"text":"Winters, William J. bwinters@usgs.gov","contributorId":522,"corporation":false,"usgs":true,"family":"Winters","given":"William","email":"bwinters@usgs.gov","middleInitial":"J.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":348209,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Walker, Michael","contributorId":7755,"corporation":false,"usgs":true,"family":"Walker","given":"Michael","affiliations":[],"preferred":false,"id":348212,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hunter, Robert","contributorId":50285,"corporation":false,"usgs":true,"family":"Hunter","given":"Robert","affiliations":[],"preferred":false,"id":348214,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":348211,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Boswell, Ray M.","contributorId":72926,"corporation":false,"usgs":true,"family":"Boswell","given":"Ray","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":348215,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rose, Kelly K.","contributorId":82452,"corporation":false,"usgs":true,"family":"Rose","given":"Kelly","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":348216,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Waite, William F. 0000-0002-9436-4109 wwaite@usgs.gov","orcid":"https://orcid.org/0000-0002-9436-4109","contributorId":625,"corporation":false,"usgs":true,"family":"Waite","given":"William F.","email":"wwaite@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":348210,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Torres, Marta","contributorId":86477,"corporation":false,"usgs":true,"family":"Torres","given":"Marta","affiliations":[],"preferred":false,"id":348217,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Patil, Shirish","contributorId":86478,"corporation":false,"usgs":true,"family":"Patil","given":"Shirish","email":"","affiliations":[],"preferred":false,"id":348218,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Dandekar, Abhijit","contributorId":22896,"corporation":false,"usgs":true,"family":"Dandekar","given":"Abhijit","email":"","affiliations":[],"preferred":false,"id":348213,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70005677,"text":"ofr20101094 - 2011 - Continuous resistivity profiling data from the Corsica River Estuary, Maryland","interactions":[],"lastModifiedDate":"2018-05-02T21:29:11","indexId":"ofr20101094","displayToPublicDate":"2011-10-04T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2010-1094","title":"Continuous resistivity profiling data from the Corsica River Estuary, Maryland","docAbstract":"Submarine groundwater discharge (SGD) into Maryland's Corsica River Estuary was investigated as part of a larger study to determine its importance in nutrient delivery to the Chesapeake Bay. The Corsica River Estuary represents a coastal lowland setting typical of much of the eastern bay. An interdisciplinary U.S. Geological Survey (USGS) science team conducted field operations in the lower estuary in April and May 2007. Resource managers are concerned about nutrients that are entering the estuary via SGD that may be contributing to eutrophication, harmful algal blooms, and fish kills. Techniques employed in the study included continuous resistivity profiling (CRP), piezometer sampling of submarine groundwater, and collection of a time series of radon tracer activity in surface water. A CRP system measures electrical resistivity of saturated subestuarine sediments to distinguish those bearing fresh water (high resistivity) from those with saline or brackish pore water (low resistivity). This report describes the collection and processing of CRP data and summarizes the results. Based on a grid of 67.6 kilometers of CRP data, low-salinity (high-resistivity) groundwater extended approximately 50-400 meters offshore from estuary shorelines at depths of 5 to >12 meters below the sediment surface, likely beneath a confining unit. A band of low-resistivity sediment detected along the axis of the estuary indicated the presence of a filled paleochannel containing brackish groundwater. The meandering paleochannel likely incised through the confining unit during periods of lower sea level, allowing the low-salinity groundwater plumes originating from land to mix with brackish subestuarine groundwater along the channel margins and to discharge. A better understanding of the spatial variability and geological controls of submarine groundwater flow beneath the Corsica River Estuary could lead to improved models and mitigation strategies for nutrient over-enrichment in the estuary and in other similar settings.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20101094","usgsCitation":"Cross, V., Bratton, J., Worley, C., Crusius, J., and Kroeger, K., 2011, Continuous resistivity profiling data from the Corsica River Estuary, Maryland: U.S. Geological Survey Open-File Report 2010-1094, HTML Document; DVD-ROM, https://doi.org/10.3133/ofr20101094.","productDescription":"HTML Document; DVD-ROM","temporalStart":"2007-04-01","temporalEnd":"2007-05-31","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":116026,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2010_1094.gif"},{"id":94293,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2010/1094/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Maryl","otherGeospatial":"Corsica River Estuary","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -76.15083333333334,39.05 ], [ -76.15083333333334,39.1 ], [ -76.1,39.1 ], [ -76.1,39.05 ], [ -76.15083333333334,39.05 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4afde4b07f02db696aac","contributors":{"authors":[{"text":"Cross, V.A.","contributorId":88687,"corporation":false,"usgs":true,"family":"Cross","given":"V.A.","email":"","affiliations":[],"preferred":false,"id":353055,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bratton, J.F.","contributorId":94354,"corporation":false,"usgs":true,"family":"Bratton","given":"J.F.","email":"","affiliations":[],"preferred":false,"id":353056,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Worley, C.R.","contributorId":43479,"corporation":false,"usgs":true,"family":"Worley","given":"C.R.","email":"","affiliations":[],"preferred":false,"id":353054,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Crusius, John 0000-0003-2554-0831 jcrusius@usgs.gov","orcid":"https://orcid.org/0000-0003-2554-0831","contributorId":2155,"corporation":false,"usgs":true,"family":"Crusius","given":"John","email":"jcrusius@usgs.gov","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":353053,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kroeger, K.D.","contributorId":26060,"corporation":false,"usgs":true,"family":"Kroeger","given":"K.D.","email":"","affiliations":[],"preferred":false,"id":353052,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70005673,"text":"ofr20111205 - 2011 - Distribution of transmissivity and yield of the surficial, Castle Hayne, and Peedee aquifers in Northern New Hanover County, North Carolina","interactions":[],"lastModifiedDate":"2012-03-08T17:16:41","indexId":"ofr20111205","displayToPublicDate":"2011-10-04T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2011-1205","title":"Distribution of transmissivity and yield of the surficial, Castle Hayne, and Peedee aquifers in Northern New Hanover County, North Carolina","docAbstract":"Data were collected from more than 230 wells in northern New Hanover County, North Carolina, to evaluate the distribution of transmissivity and yield of the surficial, Castle Hayne, and Peedee aquifers of the Coastal Plain Physiographic Province. Constant-rate,single-well aquifer test data were obtained and analyzed to calculate additional transmissivity values for 25 production wells that were completed in the Castle Hayne or Peedee aquifer. In the surficial aquife, transmissivity values ranged from 400 to 12,700 feet squared per day, and reported yields ranged from 6 to 100 gallons per minute. In the Castle Hayne aquifer, transmissivity values ranged from 1,400 to 18,700 feet squared per day, and reported yields ranged from 9 to 640 gallons per minute. In the Peedee aquifer, transmissivity values ranged from 530 to 18,600 feet squared per day, and reported yields ranged from 8 to 1,000 gallons per minute.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20111205","collaboration":"Prepared in cooperation with the Cape Fear Public Utility Authority","usgsCitation":"McSwain, K., and Nagy, L.A., 2011, Distribution of transmissivity and yield of the surficial, Castle Hayne, and Peedee aquifers in Northern New Hanover County, North Carolina: U.S. Geological Survey Open-File Report 2011-1205, 1 Sheet: 34 x 36 inches, https://doi.org/10.3133/ofr20111205.","productDescription":"1 Sheet: 34 x 36 inches","temporalStart":"2004-12-01","temporalEnd":"2008-09-30","costCenters":[{"id":476,"text":"North Carolina Water Science Center","active":true,"usgs":true}],"links":[{"id":116547,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2011_1205.jpg"},{"id":94295,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2011/1205/","linkFileType":{"id":5,"text":"html"}}],"scale":"500000","country":"United States","state":"North Carolina","county":"New Hanover","otherGeospatial":"Castle Hayne Aquifer;Peedee Aquifer;Coastal Plain Physiographic Province","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -78.00083333333333,34.23416666666667 ], [ -78.00083333333333,34.416666666666664 ], [ -77.73416666666667,34.416666666666664 ], [ -77.73416666666667,34.23416666666667 ], [ -78.00083333333333,34.23416666666667 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a6de4b07f02db63f2f9","contributors":{"authors":[{"text":"McSwain, Kristen Bukowski","contributorId":104458,"corporation":false,"usgs":true,"family":"McSwain","given":"Kristen Bukowski","affiliations":[],"preferred":false,"id":353046,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nagy, Laura A. lnagy@usgs.gov","contributorId":5427,"corporation":false,"usgs":true,"family":"Nagy","given":"Laura","email":"lnagy@usgs.gov","middleInitial":"A.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":353045,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70005684,"text":"sir20115106 - 2011 - Characterization of salinity and selenium loading and land-use change in Montrose Arroyo, western Colorado, from 1992 to 2010","interactions":[],"lastModifiedDate":"2012-02-10T00:12:00","indexId":"sir20115106","displayToPublicDate":"2011-10-04T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2011-5106","title":"Characterization of salinity and selenium loading and land-use change in Montrose Arroyo, western Colorado, from 1992 to 2010","docAbstract":"Salinity and selenium are naturally occurring and perva-sive in the lower Gunnison River Basin of Colorado, includ-ing the watershed of Montrose Arroyo. Although some of the salinity and selenium loading in the Montrose Arroyo study area is from natural sources, additional loading has resulted from the introduction of intensive irrigation in the water-shed. With increasing land-use change and the conversion from irrigated agricultural to urban land, land managers and stakeholders need information about the long-term effects of land-use change on salinity and selenium loading. In response to the need to advance salinity and selenium science, the U.S. Geological Survey, in cooperation with the Bureau of Reclamation, Colorado River Basin Salinity Control Forum, and Colorado River Water Conservation District, developed a study to characterize salinity and selenium loading and how salinity and selenium sources may relate to land-use change in Montrose Arroyo. This report characterizes changes in salinity and selenium loading to Montrose Arroyo from March 1992 to February 2010 and the magnitude of land-use change between unirrigated desert, irrigated agricultural, and urban land-use/land-cover types, and discusses how the respective loads may relate to land-use change. Montrose Arroyo is an approximately 8-square-mile watershed in Montrose County in western Colorado. Salinity and selenium were studied in Montrose Arroyo in a 2001 study as part of a salinity- and selenium-control lateral project. The robust nature of the historical dataset indicated that Montrose Arroyo was a prime watershed for a follow-up study. Two sites from the 2001 study were used to monitor salinity and selenium loads in Montrose Arroyo in the follow-up study. Over the period of 2 water years and respective irrigation seasons (2008-2010), 27 water-quality samples were collected and streamflow measurements were made at the historical sites MA2 and MA4. Salinity and selenium concen-trations, loads, and streamflow were compared between the pre-lateral-project and post-growth periods and between the post-lateral-project and post-growth periods.  No significant differences in streamflow, salinity (concen-tration and load), or selenium (concentration and load) were found at MA4 between the pre-lateral project and post-growth periods or between the post-lateral-project and post-growth periods. The statistical analysis indicated no significant dif-ferences in streamflow or salinity (both concentration and load) between the pre-lateral-project and post-growth periods or between the post-lateral-project and post-growth periods at MA2; however, selenium concentrations and loads were significantly greater between the pre-lateral-project and post-growth periods and between the post-lateral-project and post-growth periods at MA2. Land-use change between MA4 and MA2 may have contributed to the determined differences in selenium values, but the specific mechanisms causing the increases between periods are unknown.  The size of the urbanized area in Montrose Arroyo was quantified for 1993, 2002, and 2009 by using a geographic information system (GIS) with imagery from the specified years. The greatest change in land use from 1993 to 2009 was the increase of urban land due to conversion from irrigated agricultural land. The conversion of previously unirrigated desert to urban land or irrigated agriculture could become more common if urbanization and development expands into the eastern part of the watershed because a majority of the un-urbanized land in eastern Montrose Arroyo is unirrigated desert.  By applying GIS to the City of Montrose 2008 com-prehensive growth plan, it was estimated that approximately 786 acres of previously irrigated agricultural land will be converted to urban land and 689 acres of unirrigated desert will be converted to urban land under the plan scenario. New development on previously unirrigated land in shale areas would likely increase the potential for mobilization of sele-nium and salinity from new sources to Montrose Arroyo and the Lower Gunnison River Basin.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20115106","collaboration":"Prepared in cooperation with the Bureau of Reclamation, the Colorado River Basin Salinity Control Forum, and the Colorado River Water Conservation District","usgsCitation":"Moore, J.L., 2011, Characterization of salinity and selenium loading and land-use change in Montrose Arroyo, western Colorado, from 1992 to 2010: U.S. Geological Survey Scientific Investigations Report 2011-5106, v, 23 p., https://doi.org/10.3133/sir20115106.","productDescription":"v, 23 p.","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":116548,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2011_5106.png"},{"id":94299,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2011/5106/","linkFileType":{"id":5,"text":"html"}}],"scale":"1000000","state":"Colorado","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -108.83333333333333,37.833333333333336 ], [ -108.83333333333333,39.416666666666664 ], [ -107,39.416666666666664 ], [ -107,37.833333333333336 ], [ -108.83333333333333,37.833333333333336 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e49a2e4b07f02db5beb92","contributors":{"authors":[{"text":"Moore, Jennifer L.","contributorId":68447,"corporation":false,"usgs":true,"family":"Moore","given":"Jennifer","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":353073,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70005670,"text":"70005670 - 2011 - Wyoming Landscape Conservation Initiative data management and integration","interactions":[],"lastModifiedDate":"2018-09-21T11:22:07","indexId":"70005670","displayToPublicDate":"2011-10-03T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":3,"text":"Organization Series"},"seriesTitle":{"id":234,"text":"WLCI Fact Sheet","active":false,"publicationSubtype":{"id":3}},"seriesNumber":"1","title":"Wyoming Landscape Conservation Initiative data management and integration","docAbstract":"Six Federal agencies, two State agencies, and two local entities formally support the Wyoming Landscape Conservation Initiative (WLCI) and work together on a landscape scale to manage fragile habitats and wildlife resources amidst growing energy development in southwest Wyoming. The U.S. Geological Survey (USGS) was tasked with implementing targeted research and providing scientific information about southwest Wyoming to inform the development of WLCI habitat enhancement and restoration projects conducted by land management agencies. Many WLCI researchers and decisionmakers representing the Bureau of Land Management, U.S. Fish and Wildlife Service, the State of Wyoming, and others have overwhelmingly expressed the need for a stable, robust infrastructure to promote sharing of data resources produced by multiple entities, including metadata adequately describing the datasets. Descriptive metadata facilitates use of the datasets by users unfamiliar with the data. Agency representatives advocate development of common data handling and distribution practices among WLCI partners to enhance availability of comprehensive and diverse data resources for use in scientific analyses and resource management. The USGS Core Science Informatics (CSI) team is developing and promoting data integration tools and techniques across USGS and partner entity endeavors, including a data management infrastructure to aid WLCI researchers and decisionmakers.","language":"English","publisher":"Wyoming Landscape Conservation Initiative","publisherLocation":"Rock Springs, WY","usgsCitation":"Latysh, N., and Bristol, R.S., 2011, Wyoming Landscape Conservation Initiative data management and integration: WLCI Fact Sheet 1, 2 p.","productDescription":"2 p.","onlineOnly":"Y","costCenters":[{"id":37226,"text":"Core Science Analytics, Synthesis, and Libraries","active":true,"usgs":true}],"links":[{"id":204543,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/70005670.gif"},{"id":94291,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/wlci/fs/1","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Wyoming","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e48cee4b07f02db5453b5","contributors":{"authors":[{"text":"Latysh, Natalie 0000-0003-0149-3962 nlatysh@usgs.gov","orcid":"https://orcid.org/0000-0003-0149-3962","contributorId":1356,"corporation":false,"usgs":true,"family":"Latysh","given":"Natalie","email":"nlatysh@usgs.gov","affiliations":[{"id":5060,"text":"Data Preservation Program","active":true,"usgs":true},{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":true,"id":353043,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bristol, R. Sky 0000-0003-1682-4031 sbristol@usgs.gov","orcid":"https://orcid.org/0000-0003-1682-4031","contributorId":3585,"corporation":false,"usgs":true,"family":"Bristol","given":"R.","email":"sbristol@usgs.gov","middleInitial":"Sky","affiliations":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":false,"id":353044,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70147998,"text":"70147998 - 2011 - A multi-agency nutrient dataset used to estimate loads, improve monitoring design, and calibrate regional nutrient SPARROW models","interactions":[],"lastModifiedDate":"2018-04-02T13:16:16","indexId":"70147998","displayToPublicDate":"2011-10-01T10:30:00","publicationYear":"2011","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":"A multi-agency nutrient dataset used to estimate loads, improve monitoring design, and calibrate regional nutrient SPARROW models","docAbstract":"<p>Stream-loading information was compiled from federal, state, and local agencies, and selected universities as part of an effort to develop regional SPAtially Referenced Regressions On Watershed attributes (SPARROW) models to help describe the distribution, sources, and transport of nutrients in streams throughout much of the United States. After screening, 2,739 sites, sampled by 73 agencies, were identified as having suitable data for calculating long-term mean annual nutrient loads required for SPARROW model calibration. These sites had a wide range in nutrient concentrations, loads, and yields, and environmental characteristics in their basins. An analysis of the accuracy in load estimates relative to site attributes indicated that accuracy in loads improve with increases in the number of observations, the proportion of uncensored data, and the variability in flow on observation days, whereas accuracy declines with increases in the root mean square error of the water-quality model, the flow-bias ratio, the number of days between samples, the variability in daily streamflow for the prediction period, and if the load estimate has been detrended. Based on compiled data, all areas of the country had recent declines in the number of sites with sufficient water-quality data to compute accurate annual loads and support regional modeling analyses. These declines were caused by decreases in the number of sites being sampled and data not being entered in readily accessible databases.</p>","language":"English","publisher":"American Water Resources Association","publisherLocation":"Herndon, VA","doi":"10.1111/j.1752-1688.2011.00575.x","usgsCitation":"Saad, D.A., Schwarz, G., Robertson, D.M., and Booth, N., 2011, A multi-agency nutrient dataset used to estimate loads, improve monitoring design, and calibrate regional nutrient SPARROW models: Journal of the American Water Resources Association, v. 47, no. 5, p. 933-949, https://doi.org/10.1111/j.1752-1688.2011.00575.x.","productDescription":"17 p.","startPage":"933","endPage":"949","numberOfPages":"17","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-024914","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":474915,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1111/j.1752-1688.2011.00575.x","text":"External Repository"},{"id":300263,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"47","issue":"5","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2011-08-08","publicationStatus":"PW","scienceBaseUri":"5551d2ace4b0a92fa7e93bcc","contributors":{"authors":[{"text":"Saad, David A. dasaad@usgs.gov","contributorId":121,"corporation":false,"usgs":true,"family":"Saad","given":"David","email":"dasaad@usgs.gov","middleInitial":"A.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":546526,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schwarz, Gregory E. 0000-0002-9239-4566 gschwarz@usgs.gov","orcid":"https://orcid.org/0000-0002-9239-4566","contributorId":543,"corporation":false,"usgs":true,"family":"Schwarz","given":"Gregory E.","email":"gschwarz@usgs.gov","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":5067,"text":"Northeast Regional Director's Office","active":true,"usgs":true}],"preferred":false,"id":546528,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Robertson, Dale M. 0000-0001-6799-0596 dzrobert@usgs.gov","orcid":"https://orcid.org/0000-0001-6799-0596","contributorId":150760,"corporation":false,"usgs":true,"family":"Robertson","given":"Dale","email":"dzrobert@usgs.gov","middleInitial":"M.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":546527,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Booth, Nathaniel 0000-0001-6040-1031 nlbooth@usgs.gov","orcid":"https://orcid.org/0000-0001-6040-1031","contributorId":140641,"corporation":false,"usgs":true,"family":"Booth","given":"Nathaniel","email":"nlbooth@usgs.gov","affiliations":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"preferred":true,"id":546529,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70005669,"text":"ofr20111269 - 2011 - DS-Software for analyzing data collected using double sampling","interactions":[],"lastModifiedDate":"2019-09-24T08:58:05","indexId":"ofr20111269","displayToPublicDate":"2011-10-01T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2011-1269","title":"DS-Software for analyzing data collected using double sampling","docAbstract":"<p>DS analyzes count data to estimate density or relative density and population size when appropriate. The software is no longer available. The software was designed to analyze data collected using double sampling, but it also can be used to analyze index data. DS is not currently configured to apply distance methods or methods based on capture-recapture theory. Double sampling for the purpose of this report means surveying a sample of locations with a rapid method of unknown accuracy and surveying a subset of these locations using a more intensive method assumed to yield unbiased estimates. \"Detection ratios\" are calculated as the ratio of results from rapid surveys on intensive plots to the number actually present as determined from the intensive surveys. The detection ratios are used to adjust results from the rapid surveys. The formula for density is (results from rapid survey)/(estimated detection ratio from intensive surveys). Population sizes are estimated as (density)(area). Double sampling is well-established in the survey sampling literature—see Cochran (1977) for the basic theory, Smith (1995) for applications of double sampling in waterfowl surveys, Bart and Earnst (2002, 2005) for discussions of its use in wildlife studies, and Bart and others (in press) for a detailed account of how the method was used to survey shorebirds across the arctic region of North America. Indices are surveys that do not involve complete counts of well-defined plots or recording information to estimate detection rates (Thompson and others, 1998). In most cases, such data should not be used to estimate density or population size but, under some circumstances, may be used to compare two densities or estimate how density changes through time or across space (Williams and others, 2005). The Breeding Bird Survey (Sauer and others, 2008) provides a good example of an index survey. Surveyors record all birds detected but do not record any information, such as distance or whether each bird is recorded in subperiods, that could be used to estimate detection rates. Nonetheless, the data are widely used to estimate temporal trends and spatial patterns in abundance (Sauer and others, 2008). DS produces estimates of density (or relative density for indices) by species and stratum. Strata are usually defined using region and habitat but other variables may be used, and the entire study area may be classified as a single stratum. Population size in each stratum and for the entire study area also is estimated for each species. For indices, the estimated totals generally are only useful if (a) plots are surveyed so that densities can be calculated and extrapolated to the entire study area and (b) if the detection rates are close to 1.0. All estimates are accompanied by standard errors (SE) and coefficients of variation (CV, that is, SE/estimate).</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20111269","usgsCitation":"Bart, J., and Hartley, D., 2011, DS-Software for analyzing data collected using double sampling: U.S. Geological Survey Open-File Report 2011-1269, iv, 22 p., https://doi.org/10.3133/ofr20111269.","productDescription":"iv, 22 p.","additionalOnlineFiles":"N","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":116546,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2011_1269.png"},{"id":94265,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2011/1269/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4ac8e4b07f02db67bc69","contributors":{"authors":[{"text":"Bart, Jonathan jon_bart@usgs.gov","contributorId":57025,"corporation":false,"usgs":true,"family":"Bart","given":"Jonathan","email":"jon_bart@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":false,"id":353041,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hartley, Dana","contributorId":100520,"corporation":false,"usgs":true,"family":"Hartley","given":"Dana","email":"","affiliations":[],"preferred":false,"id":353042,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70005668,"text":"ofr20111228 - 2011 - Columbia River Estuary ecosystem classification—Concept and application","interactions":[],"lastModifiedDate":"2019-04-24T15:46:29","indexId":"ofr20111228","displayToPublicDate":"2011-10-01T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2011-1228","title":"Columbia River Estuary ecosystem classification—Concept and application","docAbstract":"This document describes the concept, organization, and application of a hierarchical ecosystem classification that integrates saline and tidal freshwater reaches of estuaries in order to characterize the ecosystems of large flood plain rivers that are strongly influenced by riverine and estuarine hydrology. We illustrate the classification by applying it to the Columbia River estuary (Oregon-Washington, USA), a system that extends about 233 river kilometers (rkm) inland from the Pacific Ocean. More than three-quarters of this length is tidal freshwater. The Columbia River Estuary Ecosystem Classification (\"Classification\") is based on six hierarchical levels, progressing from the coarsest, regional scale to the finest, localized scale: (1) Ecosystem Province; (2) Ecoregion; (3) Hydrogeomorphic Reach; (4) Ecosystem Complex; (5) Geomorphic Catena; and (6) Primary Cover Class. We define and map Levels 1-3 for the entire Columbia River estuary with existing geospatial datasets, and provide examples of Levels 4-6 for one hydrogeomorphic reach. In particular, three levels of the Classification capture the scales and categories of ecosystem structure and processes that are most tractable to estuarine research, monitoring, and management. These three levels are the (1) eight hydrogeomorphic reaches that embody the formative geologic and tectonic processes that created the existing estuarine landscape and encompass the influence of the resulting physiography on interactions between fluvial and tidal hydrology and geomorphology across 230 kilometers (km) of estuary, (2) more than 15 ecosystem complexes composed of broad landforms created predominantly by geologic processes during the Holocene, and (3) more than 25 geomorphic catenae embedded within ecosystem complexes that represent distinct geomorphic landforms, structures, ecosystems, and habitats, and components of the estuarine landscape most likely to change over short time periods.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20111228","collaboration":"Prepared in cooperation with the University of Washington and the Lower Columbia River Estuary Partnership","usgsCitation":"Simenstad, C.A., Burke, J.L., O'Connor, J., Cannon, C., Heatwole, D.W., Ramirez, M.F., Waite, I.R., Counihan, T.D., and Jones, K.L., 2011, Columbia River Estuary ecosystem classification—Concept and application: U.S. Geological Survey Open-File Report 2011-1228, vi, 38 p.; Appendix; Figures; Tables; XLSX Download of Appendix A, https://doi.org/10.3133/ofr20111228.","productDescription":"vi, 38 p.; Appendix; Figures; Tables; XLSX Download of Appendix A","startPage":"i","endPage":"54","numberOfPages":"60","additionalOnlineFiles":"Y","costCenters":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":116545,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2011_1228.jpg"},{"id":94266,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2011/1228/","linkFileType":{"id":5,"text":"html"}}],"country":"United States;Canada","otherGeospatial":"Columbia River Estuary","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.25,45 ], [ -124.25,47 ], [ -123.75,47 ], [ -123.75,45 ], [ -124.25,45 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b24e4b07f02db6ae770","contributors":{"authors":[{"text":"Simenstad, Charles A.","contributorId":88477,"corporation":false,"usgs":false,"family":"Simenstad","given":"Charles","email":"","middleInitial":"A.","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":353039,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burke, Jennifer L.","contributorId":61147,"corporation":false,"usgs":true,"family":"Burke","given":"Jennifer","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":353037,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"O'Connor, Jim E. 0000-0002-7928-5883 oconnor@usgs.gov","orcid":"https://orcid.org/0000-0002-7928-5883","contributorId":140771,"corporation":false,"usgs":true,"family":"O'Connor","given":"Jim E.","email":"oconnor@usgs.gov","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":false,"id":353036,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cannon, Charles ccannon@usgs.gov","contributorId":4471,"corporation":false,"usgs":true,"family":"Cannon","given":"Charles","email":"ccannon@usgs.gov","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":353034,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Heatwole, Danelle W.","contributorId":70104,"corporation":false,"usgs":true,"family":"Heatwole","given":"Danelle","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":353038,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ramirez, Mary F.","contributorId":107844,"corporation":false,"usgs":true,"family":"Ramirez","given":"Mary","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":353040,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Waite, Ian R. 0000-0003-1681-6955 iwaite@usgs.gov","orcid":"https://orcid.org/0000-0003-1681-6955","contributorId":616,"corporation":false,"usgs":true,"family":"Waite","given":"Ian","email":"iwaite@usgs.gov","middleInitial":"R.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":353032,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Counihan, Timothy D. 0000-0003-4967-6514 tcounihan@usgs.gov","orcid":"https://orcid.org/0000-0003-4967-6514","contributorId":4211,"corporation":false,"usgs":true,"family":"Counihan","given":"Timothy","email":"tcounihan@usgs.gov","middleInitial":"D.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":353033,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Jones, Krista L. 0000-0002-0301-4497 kljones@usgs.gov","orcid":"https://orcid.org/0000-0002-0301-4497","contributorId":4550,"corporation":false,"usgs":true,"family":"Jones","given":"Krista","email":"kljones@usgs.gov","middleInitial":"L.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":353035,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70192584,"text":"70192584 - 2011 - Moment tensor inversions using strong motion waveforms of Taiwan TSMIP data, 1993–2009","interactions":[],"lastModifiedDate":"2020-03-23T09:41:10","indexId":"70192584","displayToPublicDate":"2011-10-01T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3525,"text":"Tectonophysics","active":true,"publicationSubtype":{"id":10}},"title":"Moment tensor inversions using strong motion waveforms of Taiwan TSMIP data, 1993–2009","docAbstract":"<p><span>Earthquake source parameters are important for earthquake studies and seismic hazard assessment. Moment tensors are among the most important earthquake source parameters, and are now routinely derived using modern broadband seismic networks around the world. Similar waveform inversion techniques can also apply to other available data, including strong-motion seismograms. Strong-motion waveforms are also broadband, and recorded in many regions since the 1980s. Thus, strong-motion data can be used to augment moment tensor catalogs with a much larger dataset than that available from the high-gain, broadband seismic networks. However, a systematic comparison between the moment tensors derived from strong motion waveforms and high-gain broadband waveforms has not been available. In this study, we inverted the source mechanisms of Taiwan earthquakes between 1993 and 2009 by using the regional moment tensor inversion method using digital data from several hundred stations in the Taiwan Strong Motion Instrumentation Program (TSMIP). By testing different velocity models and filter passbands, we were able to successfully derive moment tensor solutions for 107 earthquakes of M</span><sub>w</sub><span>&nbsp;</span><span>&gt;=</span><span>&nbsp;</span><span>4.8. The solutions for large events agree well with other available moment tensor catalogs derived from local and global broadband networks. However, for M</span><sub>w</sub><span>&nbsp;</span><span>=</span><span>&nbsp;</span><span>5.0 or smaller events, we consistently over estimated the moment magnitudes by 0.5 to 1.0. We have tested accelerograms, and velocity waveforms integrated from accelerograms for the inversions, and found the results are similar. In addition, we used part of the catalogs to study important seismogenic structures in the area near Meishan Taiwan which was the site of a very damaging earthquake a century ago, and found that the structures were dominated by events with complex right-lateral strike-slip faulting during the recent decade. The procedures developed from this study may be applied to other strong-motion datasets to compliment or fill gaps in catalogs from regional broadband networks and teleseismic networks.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.tecto.2011.08.020","usgsCitation":"Chang, K., Chi, W., Gung, Y., Dreger, D., Lee, W.H., and Chiu, H., 2011, Moment tensor inversions using strong motion waveforms of Taiwan TSMIP data, 1993–2009: Tectonophysics, v. 511, no. 1-2, p. 53-66, https://doi.org/10.1016/j.tecto.2011.08.020.","productDescription":"14 p.","startPage":"53","endPage":"66","ipdsId":"IP-029382","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":347497,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Taiwan","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              119,\n              21\n            ],\n            [\n              123,\n              21\n            ],\n            [\n              123,\n              26\n            ],\n            [\n              119,\n              26\n            ],\n            [\n              119,\n              21\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"511","issue":"1-2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a07f34ee4b09af898c8cdc9","contributors":{"authors":[{"text":"Chang, Kaiwen","contributorId":198558,"corporation":false,"usgs":false,"family":"Chang","given":"Kaiwen","email":"","affiliations":[],"preferred":false,"id":716448,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chi, Wu-Cheng","contributorId":26148,"corporation":false,"usgs":true,"family":"Chi","given":"Wu-Cheng","email":"","affiliations":[],"preferred":false,"id":716449,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gung, Yuancheng","contributorId":198560,"corporation":false,"usgs":false,"family":"Gung","given":"Yuancheng","email":"","affiliations":[],"preferred":false,"id":716450,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dreger, Douglas","contributorId":20221,"corporation":false,"usgs":true,"family":"Dreger","given":"Douglas","affiliations":[],"preferred":false,"id":716451,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lee, William H. K. whklee@usgs.gov","contributorId":623,"corporation":false,"usgs":true,"family":"Lee","given":"William","email":"whklee@usgs.gov","middleInitial":"H. K.","affiliations":[],"preferred":true,"id":716452,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Chiu, Hung-Chie","contributorId":198557,"corporation":false,"usgs":false,"family":"Chiu","given":"Hung-Chie","email":"","affiliations":[],"preferred":false,"id":716453,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70190219,"text":"70190219 - 2011 - How landscape dynamics link individual- to population-level movement patterns: A multispecies comparison of ungulate relocation data","interactions":[],"lastModifiedDate":"2017-08-21T09:39:14","indexId":"70190219","displayToPublicDate":"2011-09-30T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1839,"text":"Global Ecology and Biogeography","active":true,"publicationSubtype":{"id":10}},"title":"How landscape dynamics link individual- to population-level movement patterns: A multispecies comparison of ungulate relocation data","docAbstract":"<p><strong>Aim </strong><span>&nbsp;</span>To demonstrate how the interrelations of individual movements form large-scale population-level movement patterns and how these patterns are associated with the underlying landscape dynamics by comparing ungulate movements across species.</p><p><strong>Locations </strong><span>&nbsp;</span>Arctic tundra in Alaska and Canada, temperate forests in Massachusetts, Patagonian Steppes in Argentina, Eastern Steppes in Mongolia.</p><p><strong>Methods </strong><span>&nbsp;</span>We used relocation data from four ungulate species (barren-ground caribou, Mongolian gazelle, guanaco and moose) to examine individual movements and the interrelation of movements among individuals. We applied and developed a suite of spatial metrics that measure variation in movement among individuals as population dispersion, movement coordination and realized mobility. Taken together, these metrics allowed us to quantify and distinguish among different large-scale population-level movement patterns such as migration, range residency and nomadism. We then related the population-level movement patterns to the underlying landscape vegetation dynamics via long-term remote sensing measurements of the temporal variability, spatial variability and unpredictability of vegetation productivity.</p><p><strong>Results </strong><span>&nbsp;</span>Moose, which remained in sedentary home ranges, and guanacos, which were partially migratory, exhibited relatively short annual movements associated with landscapes having very little broad-scale variability in vegetation. Caribou and gazelle performed extreme long-distance movements that were associated with broad-scale variability in vegetation productivity during the peak of the growing season. Caribou exhibited regular seasonal migration in which individuals were clustered for most of the year and exhibited coordinated movements. In contrast, gazelle were nomadic, as individuals were independently distributed and moved in an uncoordinated manner that relates to the comparatively unpredictable (yet broad-scale) vegetation dynamics of their landscape.</p><p><strong>Main conclusions </strong><span>&nbsp;</span>We show how broad-scale landscape unpredictability may lead to nomadism, an understudied type of long-distance movement. In contrast to classical migration where landscapes may vary at broad scales but in a predictable manner, long-distance movements of nomadic individuals are uncoordinated and independent from other such individuals. Landscapes with little broad-scale variability in vegetation productivity feature smaller-scale movements and allow for range residency. Nomadism requires distinct integrative conservation strategies that facilitate long-distance movements across the entire landscape and are not limited to certain migration corridors.</p>","language":"English","publisher":"Wiley","doi":"10.1111/j.1466-8238.2010.00638.x","usgsCitation":"Mueller, T., Olson, K., Dressler, G., Leimgruber, P., Fuller, T.K., Nicholson, C., Novaro, A., Bolgeri, M., Wattles, D.W., DeStefano, S., Calabrese, J., and Fagan, W., 2011, How landscape dynamics link individual- to population-level movement patterns: A multispecies comparison of ungulate relocation data: Global Ecology and Biogeography, v. 20, no. 5, p. 683-694, https://doi.org/10.1111/j.1466-8238.2010.00638.x.","productDescription":"12 p.","startPage":"683","endPage":"694","ipdsId":"IP-020939","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":344983,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Argentina, Canada, Mongolia, United States","state":"Alaska, 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 \"}}]}","volume":"20","issue":"5","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2011-02-23","publicationStatus":"PW","scienceBaseUri":"599bf124e4b0b589267ed345","contributors":{"authors":[{"text":"Mueller, Thomas","contributorId":91393,"corporation":false,"usgs":true,"family":"Mueller","given":"Thomas","affiliations":[],"preferred":false,"id":708112,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Olson, K.A.","contributorId":26543,"corporation":false,"usgs":true,"family":"Olson","given":"K.A.","email":"","affiliations":[],"preferred":false,"id":708113,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dressler, G.","contributorId":78965,"corporation":false,"usgs":true,"family":"Dressler","given":"G.","email":"","affiliations":[],"preferred":false,"id":708114,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Leimgruber, Peter","contributorId":192406,"corporation":false,"usgs":false,"family":"Leimgruber","given":"Peter","email":"","affiliations":[],"preferred":false,"id":708115,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fuller, Todd K.","contributorId":35700,"corporation":false,"usgs":true,"family":"Fuller","given":"Todd","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":708116,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nicholson, Craig","contributorId":80695,"corporation":false,"usgs":true,"family":"Nicholson","given":"Craig","email":"","affiliations":[],"preferred":false,"id":708117,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Novaro, A.J.","contributorId":31230,"corporation":false,"usgs":true,"family":"Novaro","given":"A.J.","email":"","affiliations":[],"preferred":false,"id":708118,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Bolgeri, M.J.","contributorId":34357,"corporation":false,"usgs":true,"family":"Bolgeri","given":"M.J.","email":"","affiliations":[],"preferred":false,"id":708119,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Wattles, David W.","contributorId":25012,"corporation":false,"usgs":true,"family":"Wattles","given":"David","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":708120,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"DeStefano, Stephen 0000-0003-2472-8373 destef@usgs.gov","orcid":"https://orcid.org/0000-0003-2472-8373","contributorId":166706,"corporation":false,"usgs":true,"family":"DeStefano","given":"Stephen","email":"destef@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":708021,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Calabrese, J.M.","contributorId":84594,"corporation":false,"usgs":true,"family":"Calabrese","given":"J.M.","email":"","affiliations":[],"preferred":false,"id":708121,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Fagan, William F.","contributorId":108239,"corporation":false,"usgs":true,"family":"Fagan","given":"William F.","affiliations":[],"preferred":false,"id":708122,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}}
,{"id":70005654,"text":"ds595 - 2011 - Geophysical, geochemical, mineralogical, and enivronmental data for rock samples collected in a mineralized volcanic environment, upper Animas River watershed, Colorado","interactions":[],"lastModifiedDate":"2012-02-10T00:12:00","indexId":"ds595","displayToPublicDate":"2011-09-30T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"595","title":"Geophysical, geochemical, mineralogical, and enivronmental data for rock samples collected in a mineralized volcanic environment, upper Animas River watershed, Colorado","docAbstract":"This report provides analyses of 90 rock samples collected in the upper Animas River watershed near Silverton, Colo., from 2001 to 2007. The samples are analyzed for geophysical, geochemical, mineralogical, and environmental rock properties of acid neutralizing capacity and net acid production. The database is derived from both published (n=68) and unpublished (n=32) data. New for all samples are geophysical measurements of electrical resistivity, density, and porosity. Rock samples were acquired from 12 geologic units that include key Tertiary volcanic and plutonic lithologies, all with varying degrees of alteration.\nThe purpose of this study is to\n* provide a comprehensive and complete record of U.S. Geological Survey rock samples collected and similarly analyzed in the upper Animas River watershed for various physical, chemical, and geoenvironmental properties;\n* provide measurements of geophysical rock properties of lithologic units to establish ground truth with respect to watershed-scale airborne magnetic and electrical survey data;\n* use the data to interpret the airborne geophysical anomalies to characterize rocks in terms of acid neutralizing capacity or net acid production; and\n* provide measurements to study the geochemical, mineralogical, and geophysical characteristics of rocks having weak to extreme degrees of alteration and to develop an understanding of how these characteristics change with alteration type.  Data are provided in two digital formats: an Arc/Info geodatabase and a Microsoft Excel spreadsheet.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds595","usgsCitation":"McCafferty, A.E., Horton, R.J., Stanton, M., McDougal, R., and Fey, D., 2011, Geophysical, geochemical, mineralogical, and enivronmental data for rock samples collected in a mineralized volcanic environment, upper Animas River watershed, Colorado: U.S. Geological Survey Data Series 595, iv, 13 p.; Relational Geodatabase; Data Tables; Metadata, https://doi.org/10.3133/ds595.","productDescription":"iv, 13 p.; Relational Geodatabase; Data Tables; Metadata","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":116584,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds_595.png"},{"id":94263,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/595/","linkFileType":{"id":5,"text":"html"}}],"state":"Colorado","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -107.83333333333333,37.75 ], [ -107.83333333333333,38 ], [ -107.5,38 ], [ -107.5,37.75 ], [ -107.83333333333333,37.75 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b32e4b07f02db6b4709","contributors":{"authors":[{"text":"McCafferty, A. E.","contributorId":93499,"corporation":false,"usgs":true,"family":"McCafferty","given":"A.","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":353027,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Horton, R. J.","contributorId":19926,"corporation":false,"usgs":true,"family":"Horton","given":"R.","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":353024,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stanton, M.R.","contributorId":103684,"corporation":false,"usgs":true,"family":"Stanton","given":"M.R.","email":"","affiliations":[],"preferred":false,"id":353028,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McDougal, R.R.","contributorId":32268,"corporation":false,"usgs":true,"family":"McDougal","given":"R.R.","email":"","affiliations":[],"preferred":false,"id":353025,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fey, D.L.","contributorId":44537,"corporation":false,"usgs":true,"family":"Fey","given":"D.L.","email":"","affiliations":[],"preferred":false,"id":353026,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70005257,"text":"70005257 - 2011 - Pb-concentrations and Pb-isotope ratios in soils collected along an east-west transect across the United States","interactions":[],"lastModifiedDate":"2025-05-14T19:24:09.459617","indexId":"70005257","displayToPublicDate":"2011-09-30T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":835,"text":"Applied Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Pb-concentrations and Pb-isotope ratios in soils collected along an east-west transect across the United States","docAbstract":"Analytical results for Pb-concentrations and isotopic ratios from ca. 150 samples of soil A horizon and ca. 145 samples of soil C horizon collected along a 4000-km east&ndash;west transect across the USA are presented. Lead concentrations along the transect show: (1) generally higher values in the soil A-horizon than the C-horizon (median 21 vs. 16.5 mg/kg), (2) an increase in the median value of the soil A-horizon for central to eastern USA (Missouri to Maryland) when compared to the western USA (California to Kansas) (median 26 vs. 20 mg/kg) and (3) a higher A/C ratio for the central to eastern USA (1.35 vs. 1.14). Lead isotopes show a distinct trend across the USA, with the highest <sup>206</sup>Pb/<sup>207</sup>Pb ratios occurring in the centre (Missouri, median A-horizon: 1.245; C-horizon: 1.251) and the lowest at both coasts (e.g., California, median A-horizon: 1.195; C-horizon: 1.216). The soil C-horizon samples show generally higher <sup>206</sup>Pb/<sup>207</sup>Pb ratios than the A-horizon (median C-horizon: 1.224; A-horizon: 1.219). The <sup>206</sup>Pb/<sup>207</sup>Pb-isotope ratios in the soil A horizon show a correlation with the total feldspar content for the same 2500-km portion of the transect from east-central Colorado to the Atlantic coast that shows steadily increasing precipitation. No such correlation exists in the soil C horizon. The data demonstrate the importance of climate and weathering on both Pb-concentration and <sup>206</sup>Pb/<sup>207</sup>Pb-isotope ratios in soil samples and natural shifts thereof in the soil profile during soil-forming processes.","language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.apgeochem.2011.04.018","usgsCitation":"Reimann, C., Smith, D., Woodruff, L.G., and Flem, B., 2011, Pb-concentrations and Pb-isotope ratios in soils collected along an east-west transect across the United States: Applied Geochemistry, v. 26, no. 9-10, p. 1623-1631, https://doi.org/10.1016/j.apgeochem.2011.04.018.","productDescription":"9 p.","startPage":"1623","endPage":"1631","numberOfPages":"9","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":204502,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"26","issue":"9-10","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4ac7e4b07f02db67b01f","contributors":{"authors":[{"text":"Reimann, Clemens","contributorId":40342,"corporation":false,"usgs":true,"family":"Reimann","given":"Clemens","affiliations":[],"preferred":false,"id":352171,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, David B. 0000-0001-8396-9105 dsmith@usgs.gov","orcid":"https://orcid.org/0000-0001-8396-9105","contributorId":1274,"corporation":false,"usgs":true,"family":"Smith","given":"David B.","email":"dsmith@usgs.gov","affiliations":[{"id":218,"text":"Denver Federal Center","active":false,"usgs":true}],"preferred":false,"id":352168,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Woodruff, Laurel G. 0000-0002-2514-9923 woodruff@usgs.gov","orcid":"https://orcid.org/0000-0002-2514-9923","contributorId":2224,"corporation":false,"usgs":true,"family":"Woodruff","given":"Laurel","email":"woodruff@usgs.gov","middleInitial":"G.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":352169,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Flem, Belinda","contributorId":31517,"corporation":false,"usgs":true,"family":"Flem","given":"Belinda","email":"","affiliations":[],"preferred":false,"id":352170,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70005655,"text":"ofr20111266 - 2011 - Digital archive of drilling mud weight pressures and wellbore temperatures from 49 regional cross sections of 967 well logs in Louisiana and Texas, onshore Gulf of Mexico basin","interactions":[],"lastModifiedDate":"2012-02-02T00:15:58","indexId":"ofr20111266","displayToPublicDate":"2011-09-30T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2011-1266","title":"Digital archive of drilling mud weight pressures and wellbore temperatures from 49 regional cross sections of 967 well logs in Louisiana and Texas, onshore Gulf of Mexico basin","docAbstract":"This document provides the digital archive of in-situ temperature and drilling mud weight pressure data that were compiled from several historical sources. The data coverage includes the states of Texas and Louisiana in the Gulf of Mexico basin. Data are also provided graphically, for both Texas and Louisiana, as plots of temperature as a function of depth and pressure as a function of depth. The minimum, arithmetic average, and maximum values are tabulated for each 1,000-foot depth increment for temperature as well as pressure in the Texas and Louisiana data.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20111266","usgsCitation":"Burke, L.A., Kinney, S.A., and Kola-Kehinde, T.B., 2011, Digital archive of drilling mud weight pressures and wellbore temperatures from 49 regional cross sections of 967 well logs in Louisiana and Texas, onshore Gulf of Mexico basin: U.S. Geological Survey Open-File Report 2011-1266, iv, 14 p.; Louisiana XLS; Texas XLS, https://doi.org/10.3133/ofr20111266.","productDescription":"iv, 14 p.; Louisiana XLS; Texas XLS","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":116590,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2011_1266.png"},{"id":94264,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2011/1266/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a9ae4b07f02db65d5b8","contributors":{"authors":[{"text":"Burke, Lauri A. 0000-0002-2035-8048 lburke@usgs.gov","orcid":"https://orcid.org/0000-0002-2035-8048","contributorId":3859,"corporation":false,"usgs":true,"family":"Burke","given":"Lauri","email":"lburke@usgs.gov","middleInitial":"A.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":353030,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kinney, Scott A. 0000-0001-5008-5813 skinney@usgs.gov","orcid":"https://orcid.org/0000-0001-5008-5813","contributorId":1395,"corporation":false,"usgs":true,"family":"Kinney","given":"Scott","email":"skinney@usgs.gov","middleInitial":"A.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":353029,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kola-Kehinde, Temidayo B.","contributorId":54336,"corporation":false,"usgs":true,"family":"Kola-Kehinde","given":"Temidayo","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":353031,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70005601,"text":"ofr20111182 - 2011 - Preliminary analysis of Greater Sage-grouse reproduction in the Virginia Mountains of northwestern Nevada","interactions":[],"lastModifiedDate":"2012-02-02T00:15:57","indexId":"ofr20111182","displayToPublicDate":"2011-09-30T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2011-1182","title":"Preliminary analysis of Greater Sage-grouse reproduction in the Virginia Mountains of northwestern Nevada","docAbstract":"Relationships between habitat selection and population vital rates of greater sage-grouse (Centrocercus urophasianus; hereafter sage-grouse), recently designated as a candidate species under the Endangered Species Act, within the Great Basin are not well-understood. The growing development of renewable energy infrastructure within areas inhabited by sage-grouse is thought to influence predator and vegetation communities. For example, common ravens (Corvus corax), a synanthropic sage-grouse nest predator, are increasing range-wide and select transmission lines and other tall structures for nesting and perching. In the Virginia Mountains of northwestern Nevada, we collected preliminary information of space-use, habitat selection, and population vital rates during the nesting and brood-rearing period over two years on 56 sage-grouse. Additionally, videography at nest sites (n = 22) was used to identify sage-grouse nest predators. The study area is a potential site for renewable energy developments (i.e., wind and solar), and we plan to continue monitoring this population using a before-after-control-impact study design. The results reported here are preliminary and further data are required before conclusions can be drawn from this population of sage-grouse.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20111182","collaboration":"Prepared in cooperation with the Nevada Department of Wildlife, Idaho State University, and the U.S. Fish and Wildlife Service","usgsCitation":"Coates, P.S., Lockyer, Z.B., Farinha, M.A., Sweeney, J.M., Johnson, V.M., Meshriy, M.G., Espinosa, S.P., Delehanty, D.J., and Casazza, M.L., 2011, Preliminary analysis of Greater Sage-grouse reproduction in the Virginia Mountains of northwestern Nevada: U.S. Geological Survey Open-File Report 2011-1182, vi, 32 p., https://doi.org/10.3133/ofr20111182.","productDescription":"vi, 32 p.","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":116580,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2011_1182.jpg"},{"id":94258,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2011/1182/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Nevada","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4ac9e4b07f02db67cbad","contributors":{"authors":[{"text":"Coates, Peter S. 0000-0003-2672-9994 pcoates@usgs.gov","orcid":"https://orcid.org/0000-0003-2672-9994","contributorId":3263,"corporation":false,"usgs":true,"family":"Coates","given":"Peter","email":"pcoates@usgs.gov","middleInitial":"S.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":352945,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lockyer, Zachary B.","contributorId":91614,"corporation":false,"usgs":true,"family":"Lockyer","given":"Zachary","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":352952,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Farinha, Melissa A.","contributorId":7791,"corporation":false,"usgs":true,"family":"Farinha","given":"Melissa","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":352946,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sweeney, Joelle M.","contributorId":91232,"corporation":false,"usgs":true,"family":"Sweeney","given":"Joelle","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":352951,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Johnson, Valerie M.","contributorId":30743,"corporation":false,"usgs":true,"family":"Johnson","given":"Valerie","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":352948,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Meshriy, Matthew G.","contributorId":16151,"corporation":false,"usgs":true,"family":"Meshriy","given":"Matthew","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":352947,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Espinosa, Shawn P.","contributorId":48298,"corporation":false,"usgs":true,"family":"Espinosa","given":"Shawn","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":352949,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Delehanty, David J.","contributorId":80811,"corporation":false,"usgs":true,"family":"Delehanty","given":"David","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":352950,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Casazza, Michael L. 0000-0002-5636-735X mike_casazza@usgs.gov","orcid":"https://orcid.org/0000-0002-5636-735X","contributorId":2091,"corporation":false,"usgs":true,"family":"Casazza","given":"Michael","email":"mike_casazza@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":352944,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70005611,"text":"sir20115117 - 2011 - Evaluation and trends of land cover, streamflow, and water quality in the North Canadian River Basin near Oklahoma City, Oklahoma, 1968-2009","interactions":[],"lastModifiedDate":"2020-02-27T06:09:05","indexId":"sir20115117","displayToPublicDate":"2011-09-30T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2011-5117","title":"Evaluation and trends of land cover, streamflow, and water quality in the North Canadian River Basin near Oklahoma City, Oklahoma, 1968-2009","docAbstract":"<p>The U.S. Geological Survey, in cooperation with the city of Oklahoma City, collected water-quality samples from the North Canadian River at the streamflow-gaging station near Harrah, Oklahoma (Harrah station), since 1968, and at an upstream streamflow-gaging station at Britton Road at Oklahoma City, Oklahoma (Britton Road station), since 1988. Statistical summaries and frequencies of detection of water-quality constituent data from water samples, and summaries of water-quality constituent data from continuous water-quality monitors are described from the start of monitoring at those stations through 2009. Differences in concentrations between stations and time trends for selected constituents were evaluated to determine the effects of: (1) wastewater effluent discharges, (2) changes in land-cover, (3) changes in streamflow, (4) increases in urban development, and (5) other anthropogenic sources of contamination on water quality in the North Canadian River downstream from Oklahoma City. Land-cover changes between 1992 and 2001 in the basin between the Harrah station and Lake Overholser upstream included an increase in developed/barren land-cover and a decrease in pasture/hay land cover. There were no significant trends in median and greater streamflows at either streamflow-gaging station, but there were significant downward trends in lesser streamflows, especially after 1999, which may have been associated with decreases in precipitation between 1999 and 2009 or construction of low-water dams on the river upstream from Oklahoma City in 1999. Concentrations of dissolved chloride, lead, cadmium, and chlordane most frequently exceeded the Criterion Continuous Concentration (a water-quality standard for protection of aquatic life) in water-quality samples collected at both streamflow-gaging stations. Visual trends in annual frequencies of detection were investigated for selected pesticides with frequencies of detection greater than 10 percent in all water samples collected at both streamflow-gaging stations. Annual frequencies of detection of 2,4-dichlorophenoxyacetic acid and bromacil increased with time. Annual frequencies of detection of atrazine, chlorpyrifos, diazinon, dichlorprop, and lindane decreased with time. Dissolved nitrogen and phosphorus concentrations were significantly greater in water samples collected at the Harrah station than at the Britton Road station, whereas specific conductance was greater at the Britton Road station. Concentrations of dissolved oxygen, biochemical oxygen demand, and fecal coliform bacteria were not significantly different between stations. Daily minimum, mean, and maximum specific conductance collected from continuous water-quality monitors were significantly greater at the Britton Road station than in water samples collected at the Harrah station. Daily minimum, maximum, and diurnal fluctuations of water temperature collected from continuous water-quality monitors were significantly greater at the Harrah station than at the Britton Road station. The daily maximums and diurnal range of dissolved oxygen concentrations were significantly greater in water samples collected at the Britton Road station than at the Harrah station, but daily mean dissolved oxygen concentrations in water at those streamflow-gaging stations were not significantly different. Daily mean and diurnal water temperature ranges increased with time at the Britton Road and Harrah streamflow-gaging stations, whereas daily mean and diurnal specific conductance ranges decreased with time at both streamflow-gaging stations from 1988–2009. Daily minimum dissolved oxygen concentrations collected from continuous water-quality monitors more frequently indicated hypoxic conditions at the Harrah station than at the Britton Road station after 1999. Fecal coliform bacteria counts in water decreased slightly from 1988–2009 at the Britton Road station.&nbsp;</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20115117","collaboration":"Prepared in cooperation with the City of Oklahoma City","usgsCitation":"Esralew, R.A., Andrews, W.J., and Smith, S.J., 2011, Evaluation and trends of land cover, streamflow, and water quality in the North Canadian River Basin near Oklahoma City, Oklahoma, 1968-2009: U.S. Geological Survey Scientific Investigations Report 2011-5117, ix, 97 p., https://doi.org/10.3133/sir20115117.","productDescription":"ix, 97 p.","numberOfPages":"107","temporalStart":"1968-01-01","temporalEnd":"2009-12-31","costCenters":[{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true}],"links":[{"id":116577,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2011_5117.gif"},{"id":94249,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2011/5117/sir2011-5117.pdf"}],"country":"United States","state":"Oklahoma","otherGeospatial":"North Canadian River Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -97.91666666666667,35.3 ], [ -97.91666666666667,35.63333333333333 ], [ -97.16666666666667,35.63333333333333 ], [ -97.16666666666667,35.3 ], [ -97.91666666666667,35.3 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a50e4b07f02db62967c","contributors":{"authors":[{"text":"Esralew, Rachel A.","contributorId":104862,"corporation":false,"usgs":true,"family":"Esralew","given":"Rachel","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":352959,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Andrews, William J. 0000-0003-4780-8835 wandrews@usgs.gov","orcid":"https://orcid.org/0000-0003-4780-8835","contributorId":328,"corporation":false,"usgs":true,"family":"Andrews","given":"William","email":"wandrews@usgs.gov","middleInitial":"J.","affiliations":[{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true}],"preferred":true,"id":352957,"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":352958,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70005612,"text":"ofr20111257 - 2011 - Postwildfire debris flows hazard assessment for the area burned by the 2011 Track Fire, northeastern New Mexico and southeastern Colorado","interactions":[],"lastModifiedDate":"2012-03-08T17:16:41","indexId":"ofr20111257","displayToPublicDate":"2011-09-30T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2011-1257","title":"Postwildfire debris flows hazard assessment for the area burned by the 2011 Track Fire, northeastern New Mexico and southeastern Colorado","docAbstract":"In June 2011, the Track Fire burned 113 square kilometers in Colfax County, northeastern New Mexico, and Las Animas County, southeastern Colorado, including the upper watersheds of Chicorica and Raton Creeks. The burned landscape is now at risk of damage from postwildfire erosion, such as that caused by debris flows and flash floods. This report presents a preliminary hazard assessment of the debris-flow potential from basins burned by the Track Fire. A pair of empirical hazard-assessment models developed using data from recently burned basins throughout the intermountain western United States were used to estimate the probability of debris-flow occurrence and volume of debris flows at the outlets of selected drainage basins within the burned area. The models incorporate measures of burn severity, topography, soils, and storm rainfall to estimate the probability and volume of post-fire debris flows following the fire. In response to a design storm of 38 millimeters of rain in 30 minutes (10-year recurrence-interval), the probability of debris flow estimated for basins burned by the Track fire ranged between 2 and 97 percent, with probabilities greater than 80 percent identified for the majority of the tributary basins to Raton Creek in Railroad Canyon; six basins that flow into Lake Maloya, including the Segerstrom Creek and Swachheim Creek basins; two tributary basins to Sugarite Canyon, and an unnamed basin on the eastern flank of the burned area. Estimated debris-flow volumes ranged from 30 cubic meters to greater than 100,000 cubic meters. The largest volumes (greater than 100,000 cubic meters) were estimated for Segerstrom Creek and Swachheim Creek basins, which drain into Lake Maloya. The Combined Relative Debris-Flow Hazard Ranking identifies the Segerstrom Creek and Swachheim Creek basins as having the highest probability of producing the largest debris flows. This finding indicates the greatest post-fire debris-flow impacts may be expected to Lake Maloya. In addition, Interstate Highway 25, Raton Creek and the rail line in Railroad Canyon, County road A-27, and State Highway 526 in Sugarite Canyon may also be affected where they cross drainages downstream from recently burned basins. Although this assessment indicates that a rather large debris flow (approximately 42,000 cubic meters) may be generated from the basin above the City of Raton (basin 9) in response to the design storm, the probability of such an event is relatively low (approximately 10 percent). Additional assessment is necessary to determine if the estimated volume of material is sufficient to travel into the City of Raton. In addition, even small debris flows may affect structures at or downstream from basin outlets and increase the threat of flooding downstream by damaging or blocking flood mitigation structures. The maps presented here may be used to prioritize areas where erosion mitigation or other protective measures may be necessary within a 2- to 3-year window of vulnerability following the Track Fire.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20111257","usgsCitation":"Tillery, A.C., Darr, M.J., Cannon, S.H., and Michael, J.A., 2011, Postwildfire debris flows hazard assessment for the area burned by the 2011 Track Fire, northeastern New Mexico and southeastern Colorado: U.S. Geological Survey Open-File Report 2011-1257, iv, 9 p.; Plate 1: 32.34 inches x 21.13 inches; Plate 2: 31.65 inches x 20.68 inches; Plate 3: 32.34 inches x 21.13 inches, https://doi.org/10.3133/ofr20111257.","productDescription":"iv, 9 p.; Plate 1: 32.34 inches x 21.13 inches; Plate 2: 31.65 inches x 20.68 inches; Plate 3: 32.34 inches x 21.13 inches","numberOfPages":"13","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":116578,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2011_1257.gif"},{"id":94253,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2011/1257/","linkFileType":{"id":5,"text":"html"}}],"projection":"NAD 1983","datum":"UTM Zone 13","country":"United States","state":"Colorado;New Mexico","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -104.53333333333333,36.9 ], [ -104.53333333333333,37.034166666666664 ], [ -104.26666666666667,37.034166666666664 ], [ -104.26666666666667,36.9 ], [ -104.53333333333333,36.9 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4ad5e4b07f02db6839f5","contributors":{"authors":[{"text":"Tillery, Anne C. 0000-0002-9508-7908 atillery@usgs.gov","orcid":"https://orcid.org/0000-0002-9508-7908","contributorId":2549,"corporation":false,"usgs":true,"family":"Tillery","given":"Anne","email":"atillery@usgs.gov","middleInitial":"C.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":352962,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Darr, Michael J. mjdarr@usgs.gov","contributorId":4239,"corporation":false,"usgs":true,"family":"Darr","given":"Michael","email":"mjdarr@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":true,"id":352963,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cannon, Susan H. cannon@usgs.gov","contributorId":1019,"corporation":false,"usgs":true,"family":"Cannon","given":"Susan","email":"cannon@usgs.gov","middleInitial":"H.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":352960,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Michael, John A. jmichael@usgs.gov","contributorId":1877,"corporation":false,"usgs":true,"family":"Michael","given":"John","email":"jmichael@usgs.gov","middleInitial":"A.","affiliations":[{"id":218,"text":"Denver Federal Center","active":false,"usgs":true}],"preferred":false,"id":352961,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70005614,"text":"ofr20111202 - 2011 - Compilation of watershed models for tributaries to the Great Lakes, United States, as of 2010, and identification of watersheds for future modeling for the Great Lakes Restoration Initiative","interactions":[],"lastModifiedDate":"2012-03-08T17:16:41","indexId":"ofr20111202","displayToPublicDate":"2011-09-30T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2011-1202","title":"Compilation of watershed models for tributaries to the Great Lakes, United States, as of 2010, and identification of watersheds for future modeling for the Great Lakes Restoration Initiative","docAbstract":"As part of the Great Lakes Restoration Initiative (GLRI) during 2009&ndash;10, the U.S. Geological Survey (USGS) compiled a list of existing watershed models that had been created for tributaries within the United States that drain to the Great Lakes. Established Federal programs that are overseen by the National Oceanic and Atmospheric Administration (NOAA) and the U.S. Army Corps of Engineers (USACE) are responsible for most of the existing watershed models for specific tributaries. The NOAA Great Lakes Environmental Research Laboratory (GLERL) uses the Large Basin Runoff Model to provide data for the management of water levels in the Great Lakes by estimating United States and Canadian inflows to the Great Lakes from 121 large watersheds. GLERL also simulates streamflows in 34 U.S. watersheds by a grid-based model, the Distributed Large Basin Runoff Model. The NOAA National Weather Service uses the Sacramento Soil Moisture Accounting model to predict flows at river forecast sites. The USACE created or funded the creation of models for at least 30 tributaries to the Great Lakes to better understand sediment erosion, transport, and aggradation processes that affect Federal navigation channels and harbors. Many of the USACE hydrologic models have been coupled with hydrodynamic and sediment-transport models that simulate the processes in the stream and harbor near the mouth of the modeled tributary. Some models either have been applied or have the capability of being applied across the entire Great Lakes Basin; they are (1) the SPAtially Referenced Regressions On Watershed attributes (SPARROW) model, which was developed by the USGS; (2) the High Impact Targeting (HIT) and Digital Watershed models, which were developed by the Institute of Water Research at Michigan State University; (3) the Long-Term Hydrologic Impact Assessment (L&ndash;THIA) model, which was developed by researchers at Purdue University; and (4) the Water Erosion Prediction Project (WEPP) model, which was developed by the National Soil Erosion Research Laboratory of the U.S. Department of Agriculture. During 2010, the USGS used the Precipitation-Runoff Modeling System (PRMS) to create a hydrologic model for the Lake Michigan Basin to assess the probable effects of climate change on future groundwater and surface-water resources. The Water Availability Tool for Environmental Resources (WATER) model and the Analysis of Flows In Networks of CHannels (AFINCH) program also were used to support USGS GLRI projects that required estimates of streamflows throughout the Great Lakes Basin. This information on existing watershed models, along with an assessment of geologic, soils, and land-use data across the Great Lakes Basin and the identification of problems that exist in selected tributary watersheds that could be addressed by a watershed model, was used to identify three watersheds in the Great Lakes Basin for future modeling by the USGS. These watersheds are the Kalamazoo River Basin in Michigan, the Tonawanda Creek Basin in New York, and the Bad River Basin in Wisconsin. These candidate watersheds have hydrogeologic, land-type, and soil characteristics that make them distinct from each other, but that are representative of other tributary watersheds within the Great Lakes Basin. These similarities in the characteristics among nearby watersheds will enhance the usefulness of a model by improving the likelihood that parameter values from a previously modeled watershed could reliably be used in the creation of a model of another watershed in the same region. The software program Hydrological Simulation Program&ndash;Fortran (HSPF) was selected to simulate the hydrologic, sedimentary, and water-quality processes in these selected watersheds. HSPF is a versatile, process-based, continuous-simulation model that has been used extensively by the scientific community, has the ongoing technical support of the U.S. Environmental Protection Agency and USGS, and provides a means to evaluate the effects that land-use changes or management practices might have on the simulated processes.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20111202","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency","usgsCitation":"Coon, W.F., Murphy, E., Soong, D., and Sharpe, J.B., 2011, Compilation of watershed models for tributaries to the Great Lakes, United States, as of 2010, and identification of watersheds for future modeling for the Great Lakes Restoration Initiative: U.S. Geological Survey Open-File Report 2011-1202, vi, 23 p., https://doi.org/10.3133/ofr20111202.","productDescription":"vi, 23 p.","numberOfPages":"29","temporalStart":"2009-01-01","temporalEnd":"2010-12-31","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":116579,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2011_1202.gif"},{"id":94254,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2011/1202/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","otherGeospatial":"Great Lakes Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -94,40 ], [ -94,49 ], [ -73,49 ], [ -73,40 ], [ -94,40 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b1de4b07f02db6a9955","contributors":{"authors":[{"text":"Coon, William F. 0000-0002-7007-7797 wcoon@usgs.gov","orcid":"https://orcid.org/0000-0002-7007-7797","contributorId":1765,"corporation":false,"usgs":true,"family":"Coon","given":"William","email":"wcoon@usgs.gov","middleInitial":"F.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":352969,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Murphy, Elizabeth A.","contributorId":69660,"corporation":false,"usgs":true,"family":"Murphy","given":"Elizabeth A.","affiliations":[],"preferred":false,"id":352971,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Soong, David T.","contributorId":87487,"corporation":false,"usgs":true,"family":"Soong","given":"David T.","affiliations":[],"preferred":false,"id":352972,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sharpe, Jennifer B. 0000-0002-5192-7848 jbsharpe@usgs.gov","orcid":"https://orcid.org/0000-0002-5192-7848","contributorId":2825,"corporation":false,"usgs":true,"family":"Sharpe","given":"Jennifer","email":"jbsharpe@usgs.gov","middleInitial":"B.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":352970,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70005646,"text":"ds600 - 2011 - Occurrence of pesticides in surface water and sediments from three central California coastal watersheds, 2008-2009","interactions":[],"lastModifiedDate":"2012-03-08T17:16:42","indexId":"ds600","displayToPublicDate":"2011-09-30T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"600","title":"Occurrence of pesticides in surface water and sediments from three central California coastal watersheds, 2008-2009","docAbstract":"Water and sediment (bed and suspended) were collected from January 2008 through October 2009 from 12 sites in 3 of the largest watersheds along California's Central Coast (Pajaro, Salinas, and Santa Maria Rivers) and analyzed for a suite of pesticides by the U.S. Geological Survey. Water samples were collected in each watershed from the estuaries and major tributaries during 4 storm events and 11 dry season sampling events in 2008 and 2009. Bed sediments were collected from depositional zones at the tributary sampling sites three times over the course of the study. Suspended sediment samples were collected from the major tributaries during the four storm events and in the tributaries and estuaries during three dry season sampling events in 2009.  Water samples were analyzed for 68 pesticides using gas chromatography/mass spectrometry. A total of 38 pesticides were detected in 144 water samples, and 13 pesticides were detected in more than half the samples collected over the course of the study. Dissolved pesticide concentrations ranged from below their method detection limits to 36,000 nanograms per liter (boscalid). The most frequently detected pesticides in water from all the watersheds were azoxystrobin, boscalid, chlorpyrifos, DCPA, diazinon, oxyfluorfen, prometryn, and propyzamide, which were found in more than 80 percent of the samples. On average, detection frequencies and concentrations were higher in samples collected during winter storm events compared to the summer dry season. With the exception of the fungicide, myclobutanil, the Santa Maria estuary watershed exhibited higher pesticide detection frequencies than the Pajaro and Salinas watersheds.  Bed and suspended sediment samples were analyzed for 55 pesticides using accelerated solvent extraction, gel permeation chromatography for sulfur removal, and carbon/alumina stacked solid-phase extraction cartridges to remove interfering sediment matrices. In bed sediment samples, 17 pesticides were detected including pyrethroid and organophosphate (OP) insecticides, p,p'-DDT and its degradates, as well as several herbicides. The only pesticides detected more than half the time were p,p'-DDD, p,p'-DDE, and p,p'-DDT. Maximum pesticide concentrations ranged from less than their respective method detection limits to 234 micrograms per kilogram (p,p'-DDE). Four pyrethroids (bifenthrin, &# 955;-cyhalothrin, permethrin, and &# 964;-fluvalinate) were detected in bed sediment samples, though concentrations were relatively low (less than 10 microgram per kilogram). The greatest number of pesticides were detected in samples collected from Lower Orcutt Creek, the major tributary to the Santa Maria estuary. In suspended sediment samples, 19 pesticides were detected, and maximum concentrations ranged from less than the method detection limits to 549 micrograms per kilogram (chlorpyrifos). The most frequently detected pesticides were p,p'-DDE (49 percent), p,p'-DDT (38 percent), and chlorpyrifos (32 percent). During storm events, 19 pesticides were detected in suspended sediment samples compared to 10 detected during the dry season. Pesticide concentrations commonly were higher in suspended sediments during storm events than during the dry season, as well.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds600","collaboration":"In cooperation with the California State Water Resources Control Board","usgsCitation":"Smalling, K., and Orlando, J., 2011, Occurrence of pesticides in surface water and sediments from three central California coastal watersheds, 2008-2009: U.S. Geological Survey Data Series 600, x, 70 p., https://doi.org/10.3133/ds600.","productDescription":"x, 70 p.","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":116583,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds_600.jpg"},{"id":94262,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/600/","linkFileType":{"id":5,"text":"html"}}],"state":"California","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.5,34 ], [ -122.5,37.5 ], [ -121,37.5 ], [ -121,34 ], [ -122.5,34 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a51e4b07f02db629b32","contributors":{"authors":[{"text":"Smalling, Kelly L.","contributorId":16105,"corporation":false,"usgs":true,"family":"Smalling","given":"Kelly L.","affiliations":[],"preferred":false,"id":352987,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Orlando, James L. 0000-0002-0099-7221","orcid":"https://orcid.org/0000-0002-0099-7221","contributorId":95954,"corporation":false,"usgs":true,"family":"Orlando","given":"James L.","affiliations":[],"preferred":false,"id":352988,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
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