{"pageNumber":"403","pageRowStart":"10050","pageSize":"25","recordCount":46619,"records":[{"id":70193716,"text":"70193716 - 2016 - Holocene volcanism of the upper McKenzie River catchment, central Oregon Cascades, USA","interactions":[],"lastModifiedDate":"2017-11-05T17:41:42","indexId":"70193716","displayToPublicDate":"2016-11-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1786,"text":"Geological Society of America Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"Holocene volcanism of the upper McKenzie River catchment, central Oregon Cascades, USA","docAbstract":"<p>To assess the complexity of eruptive activity within mafic volcanic fields, we present a detailed geologic investigation of Holocene volcanism in the upper McKenzie River catchment in the central Oregon Cascades, United States. We focus on the Sand Mountain volcanic field, which covers 76 km<sup>2</sup> and consists of 23 vents, associated tephra deposits, and lava fields. We find that the Sand Mountain volcanic field was active for a few decades around 3 ka and involved at least 13 eruptive units. Despite the small total volume erupted (∼1 km<sup>3</sup> dense rock equivalent [DRE]), Sand Mountain volcanic field lava geochemistry indicates that erupted magmas were derived from at least two, and likely three, different magma sources. Single units erupted from one or more vents, and field data provide evidence of both vent migration and reoccupation. Overall, our study shows that mafic volcanism was clustered in space and time, involved both explosive and effusive behavior, and tapped several magma sources. These observations provide important insights on possible future hazards from mafic volcanism in the central Oregon Cascades.</p>","language":"English","publisher":"Geological Society of America","doi":"10.1130/B31405.1","usgsCitation":"Deligne, N.I., Conrey, R.M., Cashman, K.V., Champion, D.E., and Amidon, W.H., 2016, Holocene volcanism of the upper McKenzie River catchment, central Oregon Cascades, USA: Geological Society of America Bulletin, v. 128, no. 11-12, p. 1618-1635, https://doi.org/10.1130/B31405.1.","productDescription":"17 p.","startPage":"1618","endPage":"1635","ipdsId":"IP-069303","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":348199,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"128","issue":"11-12","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-11","publicationStatus":"PW","scienceBaseUri":"5a003151e4b0531197b5a752","contributors":{"authors":[{"text":"Deligne, Natalia I.","contributorId":194343,"corporation":false,"usgs":false,"family":"Deligne","given":"Natalia","email":"","middleInitial":"I.","affiliations":[{"id":13025,"text":"Department of Geological Sciences, University of Oregon","active":true,"usgs":false}],"preferred":false,"id":720031,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conrey, Richard M.","contributorId":194345,"corporation":false,"usgs":false,"family":"Conrey","given":"Richard","email":"","middleInitial":"M.","affiliations":[{"id":13203,"text":"School of the Environment, Washington State University","active":true,"usgs":false}],"preferred":false,"id":720032,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cashman, Katharine V.","contributorId":199542,"corporation":false,"usgs":false,"family":"Cashman","given":"Katharine","email":"","middleInitial":"V.","affiliations":[{"id":13025,"text":"Department of Geological Sciences, University of Oregon","active":true,"usgs":false}],"preferred":false,"id":720033,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Champion, Duane E. 0000-0001-7854-9034 dchamp@usgs.gov","orcid":"https://orcid.org/0000-0001-7854-9034","contributorId":2912,"corporation":false,"usgs":true,"family":"Champion","given":"Duane","email":"dchamp@usgs.gov","middleInitial":"E.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":720030,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Amidon, William H.","contributorId":199781,"corporation":false,"usgs":false,"family":"Amidon","given":"William","email":"","middleInitial":"H.","affiliations":[{"id":27844,"text":"Middlebury College","active":true,"usgs":false}],"preferred":false,"id":720034,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70179629,"text":"70179629 - 2016 - Effect of land cover change on snow free surface albedo across the continental United States","interactions":[],"lastModifiedDate":"2017-04-07T14:28:00","indexId":"70179629","displayToPublicDate":"2016-11-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1844,"text":"Global and Planetary Change","active":true,"publicationSubtype":{"id":10}},"title":"Effect of land cover change on snow free surface albedo across the continental United States","docAbstract":"<p><span>Land cover changes (e.g., forest to grassland) affect albedo, and changes in albedo can influence radiative forcing (warming, cooling). We empirically tested albedo response to land cover change for 130 locations across the continental United States using high resolution (30&nbsp;m-×-30&nbsp;m) land cover change data and moderate resolution (~&nbsp;500&nbsp;m-×-500&nbsp;m) albedo data. The land cover change data spanned 10&nbsp;years (2001&nbsp;−&nbsp;2011) and the albedo data included observations every eight days for 13&nbsp;years (2001&nbsp;−&nbsp;2013). Empirical testing was based on autoregressive time series analysis of snow free albedo for verified locations of land cover change. Approximately one-third of the autoregressive analyses for woody to herbaceous or forest to shrub change classes were not significant, indicating that albedo did not change significantly as a result of land cover change at these locations. In addition, ~&nbsp;80% of mean differences in albedo arising from land cover change were less than ±&nbsp;0.02, a nominal benchmark for precision of albedo measurements that is related to significant changes in radiative forcing. Under snow free conditions, we found that land cover change does not guarantee a significant albedo response, and that the differences in mean albedo response for the majority of land cover change locations were small.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.gloplacha.2016.09.005","usgsCitation":"Wickham, J., Nash, M., and Barnes, C., 2016, Effect of land cover change on snow free surface albedo across the continental United States: Global and Planetary Change, v. 146, p. 1-9, https://doi.org/10.1016/j.gloplacha.2016.09.005.","productDescription":"9 p.","startPage":"1","endPage":"9","ipdsId":"IP-072381","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":333016,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"146","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58760116e4b04eac8e0746df","contributors":{"authors":[{"text":"Wickham, J.","contributorId":102230,"corporation":false,"usgs":true,"family":"Wickham","given":"J.","email":"","affiliations":[],"preferred":false,"id":657954,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nash, M.S.","contributorId":43946,"corporation":false,"usgs":true,"family":"Nash","given":"M.S.","email":"","affiliations":[],"preferred":false,"id":657955,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barnes, Christopher A. 0000-0002-4608-4364 christopher.barnes.ctr@usgs.gov","orcid":"https://orcid.org/0000-0002-4608-4364","contributorId":178108,"corporation":false,"usgs":true,"family":"Barnes","given":"Christopher A.","email":"christopher.barnes.ctr@usgs.gov","affiliations":[],"preferred":false,"id":657953,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70178336,"text":"70178336 - 2016 - Phenology of the adult angel lichen moth (<i>Cisthene angelus</i>) in Grand Canyon, USA","interactions":[],"lastModifiedDate":"2016-11-14T12:41:26","indexId":"70178336","displayToPublicDate":"2016-11-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3451,"text":"Southwestern Naturalist","active":true,"publicationSubtype":{"id":10}},"title":"Phenology of the adult angel lichen moth (<i>Cisthene angelus</i>) in Grand Canyon, USA","docAbstract":"<p><span>We investigated the phenology of adult angel lichen moths (</span><i>Cisthene angelus</i><span>) along a 364-km long segment of the Colorado River in Grand Canyon, Arizona, USA, using a unique data set of 2,437 light-trap samples collected by citizen scientists. We found that adults of </span><i>C. angelus</i><span> were bivoltine from 2012 to 2014. We quantified plasticity in wing lengths and sex ratios among the two generations and across a 545-m elevation gradient. We found that abundance, but not wing length, increased at lower elevations and that the two generations differed in size and sex distributions. Our results shed light on the life history and morphology of a common, but poorly known, species of moth endemic to the southwestern United States and Mexico.</span></p>","language":"English","publisher":"Southwestern Association of Naturalists","doi":"10.1894/0038-4909-61.3.233","usgsCitation":"Metcalfe, A.N., Kennedy, T., and Muehlbauer, J.D., 2016, Phenology of the adult angel lichen moth (<i>Cisthene angelus</i>) in Grand Canyon, USA: Southwestern Naturalist, v. 61, no. 3, p. 233-240, https://doi.org/10.1894/0038-4909-61.3.233.","productDescription":"8 p.","startPage":"233","endPage":"240","ipdsId":"IP-075941","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":438516,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7154F5S","text":"USGS data release","linkHelpText":"Angel Lichen Moth Abundance and Morphology Data, Grand Canyon, AZ, 2012"},{"id":330975,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Grand Canyon","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -114.14245605468749,\n              35.60818490437746\n            ],\n            [\n              -114.14245605468749,\n              37.23470197166817\n            ],\n            [\n              -110.972900390625,\n              37.23470197166817\n            ],\n            [\n              -110.972900390625,\n              35.60818490437746\n            ],\n            [\n              -114.14245605468749,\n              35.60818490437746\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"61","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"582adb45e4b0c253bdfff0b3","contributors":{"authors":[{"text":"Metcalfe, Anya N. 0000-0002-6286-4889 ametcalfe@usgs.gov","orcid":"https://orcid.org/0000-0002-6286-4889","contributorId":5271,"corporation":false,"usgs":true,"family":"Metcalfe","given":"Anya","email":"ametcalfe@usgs.gov","middleInitial":"N.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":653631,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kennedy, Theodore A. tkennedy@usgs.gov","contributorId":3320,"corporation":false,"usgs":true,"family":"Kennedy","given":"Theodore A.","email":"tkennedy@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":false,"id":653632,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Muehlbauer, Jeffrey D. 0000-0003-1808-580X jmuehlbauer@usgs.gov","orcid":"https://orcid.org/0000-0003-1808-580X","contributorId":5045,"corporation":false,"usgs":true,"family":"Muehlbauer","given":"Jeffrey","email":"jmuehlbauer@usgs.gov","middleInitial":"D.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":653633,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70178027,"text":"70178027 - 2016 - Analyses of infrequent (quasi-decadal) large groundwater recharge events in the northern Great Basin: Their importance for groundwater availability, use, and management","interactions":[],"lastModifiedDate":"2017-01-11T16:32:00","indexId":"70178027","displayToPublicDate":"2016-11-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Analyses of infrequent (quasi-decadal) large groundwater recharge events in the northern Great Basin: Their importance for groundwater availability, use, and management","docAbstract":"<p><span>There has been a considerable amount of research linking climatic variability to hydrologic responses in the western United States. Although much effort has been spent to assess and predict changes in surface water resources, little has been done to understand how climatic events and changes affect groundwater resources. This study focuses on characterizing and quantifying the effects of large, multiyear, quasi-decadal groundwater recharge events in the northern Utah portion of the Great Basin for the period 1960–2013. Annual groundwater level data were analyzed with climatic data to characterize climatic conditions and frequency of these large recharge events. Using observed water-level changes and multivariate analysis, five large groundwater recharge events were identified with a frequency of about 11–13 years. These events were generally characterized as having above-average annual precipitation and snow water equivalent and below-average seasonal temperatures, especially during the spring (April through June). Existing groundwater flow models for several basins within the study area were used to quantify changes in groundwater storage from these events. Simulated groundwater storage increases per basin from a single recharge event ranged from about 115 to 205 Mm</span><sup>3</sup><span>. Extrapolating these amounts over the entire northern Great Basin indicates that a single large quasi-decadal recharge event could result in billions of cubic meters of groundwater storage. Understanding the role of these large quasi-decadal recharge events in replenishing aquifers and sustaining water supplies is crucial for long-term groundwater management.</span></p>","language":"English","publisher":"AGU Publications","doi":"10.1002/2016WR019060","usgsCitation":"Masbruch, M.D., Rumsey, C., Gangopadhyay, S., Susong, D.D., and Pruitt, T., 2016, Analyses of infrequent (quasi-decadal) large groundwater recharge events in the northern Great Basin: Their importance for groundwater availability, use, and management: Water Resources Research, v. 52, no. 10, p. 7819-7836, https://doi.org/10.1002/2016WR019060.","productDescription":"18 p.","startPage":"7819","endPage":"7836","ipdsId":"IP-069809","costCenters":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":470453,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2016wr019060","text":"Publisher Index Page"},{"id":330630,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -114.08203125,\n              38.47939467327645\n            ],\n            [\n              -114.08203125,\n              42.00032514831621\n            ],\n            [\n              -109.0283203125,\n              42.00032514831621\n            ],\n            [\n              -109.0283203125,\n              38.47939467327645\n            ],\n            [\n              -114.08203125,\n              38.47939467327645\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"52","issue":"10","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2016-10-11","publicationStatus":"PW","scienceBaseUri":"5819a9c2e4b0bb36a4c9100d","contributors":{"authors":[{"text":"Masbruch, Melissa D. 0000-0001-6568-160X mmasbruch@usgs.gov","orcid":"https://orcid.org/0000-0001-6568-160X","contributorId":1902,"corporation":false,"usgs":true,"family":"Masbruch","given":"Melissa","email":"mmasbruch@usgs.gov","middleInitial":"D.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":652542,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rumsey, Christine 0000-0001-7536-750X crumsey@usgs.gov","orcid":"https://orcid.org/0000-0001-7536-750X","contributorId":146240,"corporation":false,"usgs":true,"family":"Rumsey","given":"Christine","email":"crumsey@usgs.gov","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":652543,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gangopadhyay, Subhrendu 0000-0003-3864-8251","orcid":"https://orcid.org/0000-0003-3864-8251","contributorId":173439,"corporation":false,"usgs":false,"family":"Gangopadhyay","given":"Subhrendu","affiliations":[{"id":7183,"text":"U.S. Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":652544,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Susong, David D. ddsusong@usgs.gov","contributorId":1040,"corporation":false,"usgs":true,"family":"Susong","given":"David","email":"ddsusong@usgs.gov","middleInitial":"D.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":652545,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pruitt, Tom 0000-0002-3543-1324","orcid":"https://orcid.org/0000-0002-3543-1324","contributorId":173440,"corporation":false,"usgs":false,"family":"Pruitt","given":"Tom","email":"","affiliations":[{"id":27228,"text":"Reclamation","active":true,"usgs":false}],"preferred":false,"id":652546,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70177939,"text":"70177939 - 2016 - Migratory bird habitat in relation to tile drainage and poorly drained hydrologic soil groups","interactions":[],"lastModifiedDate":"2017-01-20T11:10:39","indexId":"70177939","displayToPublicDate":"2016-11-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Migratory bird habitat in relation to tile drainage and poorly drained hydrologic soil groups","docAbstract":"<p><span>The Prairie Pothole Region (PPR) is home to more than 50% of the migratory waterfowl in North America. Although the PPR provides an abundance of temporary and permanent wetlands for nesting and feeding, increases in commodity prices and agricultural drainage practices have led to a trend of wetland drainage. The Northern Shoveler is a migratory dabbling duck species that uses wetland habitats and cultivated croplands in the PPR. Richland County in North Dakota and Roberts County in South Dakota have an abundance of wetlands and croplands and were chosen as the study areas for this research to assess the wetland size and cultivated cropland in relation to hydrologic soil groups for the Northern Shoveler habitat. This study used geographic information system data to analyze Northern Shoveler habitats in association with Natural Resource Conservation Service soil data. Habitats, which are spatially associated with certain hydrologic soil groups, may be at risk of artificial drainage installations because of their proximity to cultivated croplands and soil lacking in natural drainage that may become wet or inundated. Findings indicate that most wetlands that are part of Northern Shoveler habitats were within or adjacent to cultivated croplands. The results also revealed soil hydrologic groups with high runoff potential and low water transmission rates account for most of the soil within the Northern Shoveler‘s wetland and cropland habitats. Habitats near agriculture with high runoff potential are likely to be drained and this has the potential of reducing Northern Shoveler habitat.</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"10th International Drainage Symposium Conference","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"10th International Drainage Symposium Conference","conferenceDate":"September 6-9, 2016","conferenceLocation":"Minneapolis, Minnesota","language":"English","publisher":"American Society of Agricultural and Biological Engineers","doi":"10.13031/IDS.20162493338","usgsCitation":"Kastner, B., Christensen, V.G., Williamson, T., and Sanocki, C.A., 2016, Migratory bird habitat in relation to tile drainage and poorly drained hydrologic soil groups, <i>in</i> 10th International Drainage Symposium Conference, Minneapolis, Minnesota, September 6-9, 2016, https://doi.org/10.13031/IDS.20162493338.","ipdsId":"IP-076360","costCenters":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"links":[{"id":333559,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2016-09-07","publicationStatus":"PW","scienceBaseUri":"58833022e4b0d0023163778e","contributors":{"authors":[{"text":"Kastner, Brandi bkastner@usgs.gov","contributorId":176471,"corporation":false,"usgs":true,"family":"Kastner","given":"Brandi","email":"bkastner@usgs.gov","affiliations":[],"preferred":true,"id":659209,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Christensen, Victoria G. 0000-0003-4166-7461 vglenn@usgs.gov","orcid":"https://orcid.org/0000-0003-4166-7461","contributorId":2354,"corporation":false,"usgs":true,"family":"Christensen","given":"Victoria","email":"vglenn@usgs.gov","middleInitial":"G.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":659210,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Williamson, Tanja N. tnwillia@usgs.gov","contributorId":452,"corporation":false,"usgs":true,"family":"Williamson","given":"Tanja N.","email":"tnwillia@usgs.gov","affiliations":[{"id":354,"text":"Kentucky Water Science Center","active":true,"usgs":true}],"preferred":false,"id":659211,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sanocki, Christopher A. 0000-0001-6714-5421 sanocki@usgs.gov","orcid":"https://orcid.org/0000-0001-6714-5421","contributorId":3142,"corporation":false,"usgs":true,"family":"Sanocki","given":"Christopher","email":"sanocki@usgs.gov","middleInitial":"A.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":659212,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70179744,"text":"70179744 - 2016 - Evaluation of gas production potential from gas hydrate deposits in National Petroleum Reserve Alaska using numerical simulations","interactions":[],"lastModifiedDate":"2017-01-17T10:26:02","indexId":"70179744","displayToPublicDate":"2016-11-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5264,"text":"Journal of Natural Gas Science and Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of gas production potential from gas hydrate deposits in National Petroleum Reserve Alaska using numerical simulations","docAbstract":"<p><span>An evaluation of the gas production potential of Sunlight Peak gas hydrate accumulation in the eastern portion of the National Petroleum Reserve Alaska (NPRA) of Alaska North Slope (ANS) is conducted using numerical simulations, as part of the U.S. Geological Survey (USGS) gas hydrate Life Cycle Assessment program. A field scale reservoir model for Sunlight Peak is developed using Advanced Processes &amp; Thermal Reservoir Simulator (STARS) that approximates the production design and response of this gas hydrate field. The reservoir characterization is based on available structural maps and the seismic-derived hydrate saturation map of the study region. A 3D reservoir model, with heterogeneous distribution of the reservoir properties (such as porosity, permeability and vertical hydrate saturation), is developed by correlating the data from the Mount Elbert well logs. Production simulations showed that the Sunlight Peak prospect has the potential of producing 1.53&nbsp;×&nbsp;10</span><sup>9</sup><span>&nbsp;ST&nbsp;m</span><sup>3</sup><span> of gas in 30 years by depressurization with a peak production rate of around 19.4&nbsp;×&nbsp;10</span><sup>4</sup><span>&nbsp;ST&nbsp;m</span><sup>3</sup><span>/day through a single horizontal well. To determine the effect of uncertainty in reservoir properties on the gas production, an uncertainty analysis is carried out. It is observed that for the range of data considered, the overall cumulative production from the Sunlight Peak will always be within the range of ±4.6% error from the overall mean value of 1.43&nbsp;×&nbsp;10</span><sup>9</sup><span>&nbsp;ST&nbsp;m</span><sup>3</sup><span>. A sensitivity analysis study showed that the proximity of the reservoir from the base of permafrost and the base of hydrate stability zone (BHSZ) has significant effect on gas production rates. The gas production rates decrease with the increase in the depth of the permafrost and the depth of BHSZ. From the overall analysis of the results it is concluded that Sunlight Peak gas hydrate accumulation behaves differently than other Class III reservoirs (Class III reservoirs are composed of a single layer of hydrate with no underlying zone of mobile fluids) due to its smaller thickness and high angle of dip.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jngse.2016.11.021","usgsCitation":"Nandanwar, M.S., Anderson, B.J., Ajayi, T., Collett, T.S., and Zyrianova, M.V., 2016, Evaluation of gas production potential from gas hydrate deposits in National Petroleum Reserve Alaska using numerical simulations: Journal of Natural Gas Science and Engineering, v. 36, no. A, p. 760-772, https://doi.org/10.1016/j.jngse.2016.11.021.","productDescription":"13 p.","startPage":"760","endPage":"772","ipdsId":"IP-079065","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":333231,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -154.86328125,\n              69.38804929116819\n            ],\n            [\n              -154.86328125,\n              70.90226826757711\n            ],\n            [\n              -151.402587890625,\n              70.90226826757711\n            ],\n            [\n              -151.402587890625,\n              69.38804929116819\n            ],\n            [\n              -154.86328125,\n              69.38804929116819\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"36","issue":"A","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"587f3c31e4b0d96de2564547","contributors":{"authors":[{"text":"Nandanwar, Manish S.","contributorId":178323,"corporation":false,"usgs":false,"family":"Nandanwar","given":"Manish","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":658498,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, Brian J.","contributorId":147120,"corporation":false,"usgs":false,"family":"Anderson","given":"Brian","email":"","middleInitial":"J.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":658499,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ajayi, Taiwo","contributorId":178324,"corporation":false,"usgs":false,"family":"Ajayi","given":"Taiwo","email":"","affiliations":[],"preferred":false,"id":658500,"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":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":658501,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zyrianova, Margarita V. 0000-0002-3669-1320 rita@usgs.gov","orcid":"https://orcid.org/0000-0002-3669-1320","contributorId":1203,"corporation":false,"usgs":true,"family":"Zyrianova","given":"Margarita","email":"rita@usgs.gov","middleInitial":"V.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":658497,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70192862,"text":"70192862 - 2016 - Influence of anglers' specializations on catch, harvest, and bycatch of targeted taxa","interactions":[],"lastModifiedDate":"2017-11-08T12:18:59","indexId":"70192862","displayToPublicDate":"2016-11-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1661,"text":"Fisheries Research","active":true,"publicationSubtype":{"id":10}},"title":"Influence of anglers' specializations on catch, harvest, and bycatch of targeted taxa","docAbstract":"<p><span>Fishery managers often use catch per unit effort (CPUE) of a given taxon derived from a group of anglers, those that sought said taxon, to evaluate fishery objectives because managers assume CPUE for this group of anglers is most sensitive to changes in fish taxon density. Further, likelihood of harvest may differ for sought and non-sought taxa if taxon sought is a defining characteristic of anglers’ attitude toward harvest. We predicted that taxon-specific catch across parties and reservoirs would be influenced by targeted taxon after controlling for number of anglers in a party and time spent fishing (combine to quantify fishing effort of party); we also predicted similar trends for taxon-specific harvest. We used creel-survey data collected from anglers that varied in taxon targeted, from generalists (targeting “anything” [no primary target taxa, but rather targeting all fishes]) to target specialists (e.g., anglers targeting largemouth bass&nbsp;</span><i>Micropterus salmoides</i><span>) in 19 Nebraska reservoirs during 2009–2011 to test our predictions. Taxon-specific catch and harvest were, in general, positively related to fishing effort. More importantly, we observed differences of catch and harvest among anglers grouped by taxon targeted for each of the eight taxa assessed. Anglers targeting a specific taxon had the greatest catch for that taxon and anglers targeting anything typically had the second highest catch for that taxon. In addition, anglers tended to catch more of closely related taxa and of taxa commonly targeted with similar fishing techniques. We encourage managers to consider taxon-specific objectives of target and non-target catch and harvest.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.fishres.2016.05.025","usgsCitation":"Pope, K.L., Chizinski, C.J., Wiley, C.L., and Martin, D., 2016, Influence of anglers' specializations on catch, harvest, and bycatch of targeted taxa: Fisheries Research, v. 183, p. 128-137, https://doi.org/10.1016/j.fishres.2016.05.025.","productDescription":"10 p.","startPage":"128","endPage":"137","ipdsId":"IP-054691","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":348437,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"183","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a0425bee4b0dc0b45b453df","contributors":{"authors":[{"text":"Pope, Kevin L. 0000-0003-1876-1687 kpope@usgs.gov","orcid":"https://orcid.org/0000-0003-1876-1687","contributorId":1574,"corporation":false,"usgs":true,"family":"Pope","given":"Kevin","email":"kpope@usgs.gov","middleInitial":"L.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":717240,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chizinski, Christopher J.","contributorId":7178,"corporation":false,"usgs":false,"family":"Chizinski","given":"Christopher","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":721117,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wiley, Christopher L.","contributorId":200145,"corporation":false,"usgs":false,"family":"Wiley","given":"Christopher","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":721118,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Martin, Dustin R.","contributorId":43482,"corporation":false,"usgs":true,"family":"Martin","given":"Dustin R.","affiliations":[],"preferred":false,"id":721119,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70187330,"text":"70187330 - 2016 - Active faulting on the Wallula fault zone within the Olympic-Wallowa lineament, Washington State, USA","interactions":[],"lastModifiedDate":"2017-04-28T15:50:03","indexId":"70187330","displayToPublicDate":"2016-11-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1723,"text":"GSA Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"Active faulting on the Wallula fault zone within the Olympic-Wallowa lineament, Washington State, USA","docAbstract":"<p><span>The Wallula fault zone is an integral feature of the Olympic-Wallowa lineament, an ∼500-km-long topographic lineament oblique to the Cascadia plate boundary, extending from Vancouver Island, British Columbia, to Walla Walla, Washington. The structure and past earthquake activity of the Wallula fault zone are important because of nearby infrastructure, and also because the fault zone defines part of the Olympic-Wallowa lineament in south-central Washington and suggests that the Olympic-Wallowa lineament may have a structural origin. We used aeromagnetic and ground magnetic data to locate the trace of the Wallula fault zone in the subsurface and map a quarry exposure of the Wallula fault zone near Finley, Washington, to investigate past earthquakes along the fault. We mapped three main packages of rocks and unconsolidated sediments in an ∼10-m-high quarry exposure. Our mapping suggests at least three late Pleistocene earthquakes with surface rupture, and an episode of liquefaction in the Holocene along the Wallula fault zone. Faint striae on the master fault surface are subhorizontal and suggest reverse dextral oblique motion for these earthquakes, consistent with dextral offset on the Wallula fault zone inferred from offset aeromagnetic anomalies associated with ca. 8.5 Ma basalt dikes. Magnetic surveys show that the Wallula fault actually lies 350 m to the southwest of the trace shown on published maps, passes directly through deformed late Pleistocene or younger deposits exposed at Finley quarry, and extends uninterrupted over 120 km.</span></p>","language":"English","publisher":"Geological Society of America","doi":"10.1130/B31359.1","usgsCitation":"Sherrod, B.L., Blakely, R.J., Lasher, J.P., Lamb, A.P., Mahan, S.A., Foit, F.F., and Barnett, E., 2016, Active faulting on the Wallula fault zone within the Olympic-Wallowa lineament, Washington State, USA: GSA Bulletin, v. 128, no. 11-12, p. 1636-1659, https://doi.org/10.1130/B31359.1.","productDescription":"24 p.","startPage":"1636","endPage":"1659","ipdsId":"IP-066033","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":492812,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1Q68HZT","text":"USGS data release","linkHelpText":"Luminescence data for: Trench Exposures across the Dead Coyote fault scarp in Kittitas Valley, Washington"},{"id":340633,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","volume":"128","issue":"11-12","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-25","publicationStatus":"PW","scienceBaseUri":"590454a3e4b022cee40dc22c","contributors":{"authors":[{"text":"Sherrod, Brian L. 0000-0002-4492-8631 bsherrod@usgs.gov","orcid":"https://orcid.org/0000-0002-4492-8631","contributorId":2834,"corporation":false,"usgs":true,"family":"Sherrod","given":"Brian","email":"bsherrod@usgs.gov","middleInitial":"L.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":693473,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Blakely, Richard J. 0000-0003-1701-5236 blakely@usgs.gov","orcid":"https://orcid.org/0000-0003-1701-5236","contributorId":1540,"corporation":false,"usgs":true,"family":"Blakely","given":"Richard","email":"blakely@usgs.gov","middleInitial":"J.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":662,"text":"Western Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":693474,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lasher, John P.","contributorId":191562,"corporation":false,"usgs":false,"family":"Lasher","given":"John","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":693475,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lamb, Andrew P. alamb@usgs.gov","contributorId":5720,"corporation":false,"usgs":true,"family":"Lamb","given":"Andrew","email":"alamb@usgs.gov","middleInitial":"P.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":693476,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mahan, Shannon A. 0000-0001-5214-7774 smahan@usgs.gov","orcid":"https://orcid.org/0000-0001-5214-7774","contributorId":147159,"corporation":false,"usgs":true,"family":"Mahan","given":"Shannon","email":"smahan@usgs.gov","middleInitial":"A.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":693477,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Foit, Franklin F.","contributorId":191563,"corporation":false,"usgs":false,"family":"Foit","given":"Franklin","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":693478,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Barnett, Elizabeth eli@usgs.gov","contributorId":2156,"corporation":false,"usgs":true,"family":"Barnett","given":"Elizabeth","email":"eli@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":693479,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70194545,"text":"70194545 - 2016 - A glacier runoff extension to the Precipitation Runoff Modeling System","interactions":[],"lastModifiedDate":"2017-12-05T11:00:44","indexId":"70194545","displayToPublicDate":"2016-11-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2318,"text":"Journal of Geophysical Research F: Earth Surface","active":true,"publicationSubtype":{"id":10}},"title":"A glacier runoff extension to the Precipitation Runoff Modeling System","docAbstract":"<p><span>A module to simulate glacier runoff, PRMSglacier, was added to PRMS (Precipitation Runoff Modeling System), a distributed-parameter, physical-process hydrological simulation code. The extension does not require extensive on-glacier measurements or computational expense but still relies on physical principles over empirical relations as much as is feasible while maintaining model usability. PRMSglacier is validated on two basins in Alaska, Wolverine, and Gulkana Glacier basin, which have been studied since 1966 and have a substantial amount of data with which to test model performance over a long period of time covering a wide range of climatic and hydrologic conditions. When error in field measurements is considered, the Nash-Sutcliffe efficiencies of streamflow are 0.87 and 0.86, the absolute bias fractions of the winter mass balance simulations are 0.10 and 0.08, and the absolute bias fractions of the summer mass balances are 0.01 and 0.03, all computed over 42 years for the Wolverine and Gulkana Glacier basins, respectively. Without taking into account measurement error, the values are still within the range achieved by the more computationally expensive codes tested over shorter time periods.</span></p>","language":"English","publisher":"AGU Publications","doi":"10.1002/2015JF003789","usgsCitation":"Van Beusekom, A.E., and Viger, R.J., 2016, A glacier runoff extension to the Precipitation Runoff Modeling System: Journal of Geophysical Research F: Earth Surface, v. 121, no. 11, p. 2001-2021, https://doi.org/10.1002/2015JF003789.","productDescription":"21 p.","startPage":"2001","endPage":"2021","ipdsId":"IP-081396","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":438520,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F75T3HMV","text":"USGS data release","linkHelpText":"Supporting data for  A Glacier Runoff Extension to the Precipitation Runoff Modeling System"},{"id":349679,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"121","issue":"11","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-11-04","publicationStatus":"PW","scienceBaseUri":"5a60fc9be4b06e28e9c24045","contributors":{"authors":[{"text":"Van Beusekom, Ashley E. 0000-0002-6996-978X beusekom@usgs.gov","orcid":"https://orcid.org/0000-0002-6996-978X","contributorId":3992,"corporation":false,"usgs":true,"family":"Van Beusekom","given":"Ashley","email":"beusekom@usgs.gov","middleInitial":"E.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":724413,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Viger, Roland J. 0000-0003-2520-714X rviger@usgs.gov","orcid":"https://orcid.org/0000-0003-2520-714X","contributorId":168799,"corporation":false,"usgs":true,"family":"Viger","given":"Roland","email":"rviger@usgs.gov","middleInitial":"J.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":724414,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70184987,"text":"70184987 - 2016 - Pb-Sr isotopic and geochemical constraints on sources and processes of lead contamination in well waters and soil from former fruit orchards, Pennsylvania, USA: A legacy of anthropogenic activities","interactions":[],"lastModifiedDate":"2017-03-13T13:29:57","indexId":"70184987","displayToPublicDate":"2016-11-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2302,"text":"Journal of Geochemical Exploration","active":true,"publicationSubtype":{"id":10}},"title":"Pb-Sr isotopic and geochemical constraints on sources and processes of lead contamination in well waters and soil from former fruit orchards, Pennsylvania, USA: A legacy of anthropogenic activities","docAbstract":"<p><span>Isotopic discrimination can be an effective tool in establishing a direct link between sources of Pb contamination and the presence of anomalously high concentrations of Pb in waters, soils, and organisms. Residential wells supplying water containing up to 1600&nbsp;ppb Pb to houses built on the former Mohr orchards commercial site, near Allentown, PA, were evaluated to discern anthropogenic from geogenic sources. Pb (n&nbsp;=&nbsp;144) and Sr (n&nbsp;=&nbsp;40) isotopic data and REE (n&nbsp;=&nbsp;29) data were determined for waters from residential wells, test wells (drilled for this study), and surface waters from pond and creeks. Local soils, sediments, bedrock, Zn-Pb mineralization and coal were also analyzed (n&nbsp;=&nbsp;94), together with locally used Pb-As pesticide (n&nbsp;=&nbsp;5). Waters from residential and test wells show overlapping values of </span><sup>206</sup><span>Pb/</span><sup>207</sup><span>Pb, </span><sup>208</sup><span>Pb/</span><sup>207</sup><span>Pb and </span><sup>87</sup><span>Sr/</span><sup>86</sup><span>Sr. Larger negative Ce anomalies (Ce/Ce*) distinguish residential wells from test wells. Results show that residential and test well waters, sediments from residential water filters in water tanks, and surface waters display broad linear trends in Pb isotope plots. Pb isotope data for soils, bedrock, and pesticides have contrasting ranges and overlapping trends. Contributions of Pb from soils to residential well waters are limited and implicated primarily in wells having shallow water-bearing zones and carrying high sediment contents. Pb isotope data for residential wells, test wells, and surface waters show substantial overlap with Pb data reflecting anthropogenic actions (e.g., burning fossil fuels, industrial and urban processing activities). Limited contributions of Pb from bedrock, soils, and pesticides are evident. High Pb concentrations in the residential waters are likely related to sediment build up in residential water tanks. Redox reactions, triggered by influx of groundwater via wells into the residential water systems and leading to subtle changes in pH, are implicated in precipitation of Fe oxyhydroxides, oxidative scavenging of Ce(IV), and desorption and release of Pb into the residential water systems. The Pb isotope features in the residences and the region are best interpreted as reflecting a legacy of industrial Pb present in underlying aquifers that currently supply the drinking water wells.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.gexplo.2016.08.008","usgsCitation":"Ayuso, R.A., and Foley, N.K., 2016, Pb-Sr isotopic and geochemical constraints on sources and processes of lead contamination in well waters and soil from former fruit orchards, Pennsylvania, USA: A legacy of anthropogenic activities: Journal of Geochemical Exploration, v. 170, p. 125-147, https://doi.org/10.1016/j.gexplo.2016.08.008.","productDescription":"23 p.","startPage":"125","endPage":"147","ipdsId":"IP-070677","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":337434,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Pennsylvania","volume":"170","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58c7af9fe4b0849ce9795e96","contributors":{"authors":[{"text":"Ayuso, Robert A. 0000-0002-8496-9534 rayuso@usgs.gov","orcid":"https://orcid.org/0000-0002-8496-9534","contributorId":2654,"corporation":false,"usgs":true,"family":"Ayuso","given":"Robert","email":"rayuso@usgs.gov","middleInitial":"A.","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":683834,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Foley, Nora K. 0000-0003-0124-3509 nfoley@usgs.gov","orcid":"https://orcid.org/0000-0003-0124-3509","contributorId":4010,"corporation":false,"usgs":true,"family":"Foley","given":"Nora","email":"nfoley@usgs.gov","middleInitial":"K.","affiliations":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":683835,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70186297,"text":"70186297 - 2016 - Bacterial genomics reveal the complex epidemiology of an emerging pathogen in arctic and boreal ungulates","interactions":[],"lastModifiedDate":"2017-04-04T11:45:04","indexId":"70186297","displayToPublicDate":"2016-11-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1702,"text":"Frontiers in Microbiology","onlineIssn":"1664-302X","active":true,"publicationSubtype":{"id":10}},"title":"Bacterial genomics reveal the complex epidemiology of an emerging pathogen in arctic and boreal ungulates","docAbstract":"<p><span>Northern ecosystems are currently experiencing unprecedented ecological change, largely driven by a rapidly changing climate. Pathogen range expansion, and emergence and altered patterns of infectious disease, are increasingly reported in wildlife at high latitudes. Understanding the causes and consequences of shifting pathogen diversity and host-pathogen interactions in these ecosystems is important for wildlife conservation, and for indigenous populations that depend on wildlife. Among the key questions are whether disease events are associated with endemic or recently introduced pathogens, and whether emerging strains are spreading throughout the region. In this study, we used a phylogenomic approach to address these questions of pathogen endemicity and spread for </span><i>Erysipelothrix rhusiopathiae</i><span>, an opportunistic multi-host bacterial pathogen associated with recent mortalities in arctic and boreal ungulate populations in North America. We isolated </span><i>E. rhusiopathiae</i><span> from carcasses associated with large-scale die-offs of muskoxen in the Canadian Arctic Archipelago, and from contemporaneous mortality events and/or population declines among muskoxen in northwestern Alaska and caribou and moose in western Canada. Bacterial genomic diversity differed markedly among these locations; minimal divergence was present among isolates from muskoxen in the Canadian Arctic, while in caribou and moose populations, strains from highly divergent clades were isolated from the same location, or even from within a single carcass. These results indicate that mortalities among northern ungulates are not associated with a single emerging strain of </span><i>E. rhusiopathiae</i><span>, and that alternate hypotheses need to be explored. Our study illustrates the value and limitations of bacterial genomic data for discriminating between ecological hypotheses of disease emergence, and highlights the importance of studying emerging pathogens within the broader context of environmental and host factors.</span></p>","language":"English","publisher":"Frontiers","doi":"10.3389/fmicb.2016.01759","usgsCitation":"Forde, T.L., Orsel, K., Zadoks, R.N., Biek, R., Adams, L., Checkley, S.L., Davison, T., De Buck, J., Dumond, M., Elkin, B.T., Finnegan, L., Macbeth, B.J., Nelson, C., Niptanatiak, A., Sather, S., Schwantje, H.M., van der Meer, F., and Kutz, S.J., 2016, Bacterial genomics reveal the complex epidemiology of an emerging pathogen in arctic and boreal ungulates: Frontiers in Microbiology, v. 7, p. 1-14, https://doi.org/10.3389/fmicb.2016.01759.","productDescription":"Article 1759; 14 p.","startPage":"1","endPage":"14","ipdsId":"IP-073288","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":470457,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fmicb.2016.01759","text":"Publisher Index Page"},{"id":339125,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-11-07","publicationStatus":"PW","scienceBaseUri":"58e4b0b2e4b09da67999778f","contributors":{"authors":[{"text":"Forde, Taya L.","contributorId":190364,"corporation":false,"usgs":false,"family":"Forde","given":"Taya","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":688236,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Orsel, Karin","contributorId":190365,"corporation":false,"usgs":false,"family":"Orsel","given":"Karin","email":"","affiliations":[],"preferred":false,"id":688237,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zadoks, Ruth N.","contributorId":190366,"corporation":false,"usgs":false,"family":"Zadoks","given":"Ruth","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":688238,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Biek, Roman","contributorId":190367,"corporation":false,"usgs":false,"family":"Biek","given":"Roman","email":"","affiliations":[],"preferred":false,"id":688239,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Adams, Layne G. 0000-0001-6212-2896 ladams@usgs.gov","orcid":"https://orcid.org/0000-0001-6212-2896","contributorId":2776,"corporation":false,"usgs":true,"family":"Adams","given":"Layne G.","email":"ladams@usgs.gov","affiliations":[{"id":117,"text":"Alaska Science Center Biology 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Mathieu","contributorId":190371,"corporation":false,"usgs":false,"family":"Dumond","given":"Mathieu","email":"","affiliations":[],"preferred":false,"id":688243,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Elkin, Brett T.","contributorId":190372,"corporation":false,"usgs":false,"family":"Elkin","given":"Brett","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":688244,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Finnegan, Laura","contributorId":190373,"corporation":false,"usgs":false,"family":"Finnegan","given":"Laura","email":"","affiliations":[],"preferred":false,"id":688245,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Macbeth, Bryan J.","contributorId":190374,"corporation":false,"usgs":false,"family":"Macbeth","given":"Bryan","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":688246,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Nelson, Cait","contributorId":190375,"corporation":false,"usgs":false,"family":"Nelson","given":"Cait","email":"","affiliations":[],"preferred":false,"id":688247,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Niptanatiak, Amanda","contributorId":190376,"corporation":false,"usgs":false,"family":"Niptanatiak","given":"Amanda","email":"","affiliations":[],"preferred":false,"id":688248,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Sather, Shane","contributorId":190377,"corporation":false,"usgs":false,"family":"Sather","given":"Shane","email":"","affiliations":[],"preferred":false,"id":688249,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Schwantje, Helen M.","contributorId":190378,"corporation":false,"usgs":false,"family":"Schwantje","given":"Helen","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":688250,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"van der Meer, Frank","contributorId":190379,"corporation":false,"usgs":false,"family":"van der Meer","given":"Frank","email":"","affiliations":[],"preferred":false,"id":688251,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Kutz, Susan J.","contributorId":190345,"corporation":false,"usgs":false,"family":"Kutz","given":"Susan","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":688252,"contributorType":{"id":1,"text":"Authors"},"rank":18}]}}
,{"id":70170679,"text":"70170679 - 2016 - Landsat 8: The plans, the reality, and the legacy","interactions":[],"lastModifiedDate":"2017-04-07T13:53:20","indexId":"70170679","displayToPublicDate":"2016-11-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"Landsat 8: The plans, the reality, and the legacy","docAbstract":"<p><span>Landsat 8, originally known as the Landsat Data Continuity Mission (LDCM), is a National Aeronautics and Space Administration (NASA)-U.S. Geological Survey (USGS) partnership that continues the legacy of continuous moderate resolution observations started in 1972. The conception of LDCM to the reality of Landsat 8 followed an arduous path extending over nearly 13&nbsp;years, but the successful launch on February 11, 2013 ensures the continuity of the unparalleled Landsat record. The USGS took over mission operations on May 30, 2013 and renamed LCDM to Landsat 8. Access to Landsat 8 data was opened to users worldwide. Three years following launch we evaluate the science and applications impact of Landsat 8. With a mission objective to enable the detection and characterization of global land changes at a scale where differentiation between natural and human-induced causes of change is possible, LDCM promised incremental technical improvements in capabilities needed for Landsat scientific and applications investigations. Results show that with Landsat 8, we are acquiring more data than ever before, the radiometric and geometric quality of data are generally technically superior to data acquired by past Landsat missions, and the new measurements, e.g., the coastal aerosol and cirrus bands, are opening new opportunities. Collectively, these improvements are sparking the growth of science and applications opportunities. Equally important, with Landsat 7 still operational, we have returned to global imaging on an 8-day&nbsp;cycle, a capability that ended when Landsat 5 ceased operational Earth imaging in November 2011. As a result, the Landsat program is on secure footings and planning is underway to extend the record for another 20 or more years.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2016.07.033","usgsCitation":"Loveland, T.R., and Irons, J.R., 2016, Landsat 8: The plans, the reality, and the legacy: Remote Sensing of Environment, v. 185, p. 1-6, https://doi.org/10.1016/j.rse.2016.07.033.","productDescription":"6 p.","startPage":"1","endPage":"6","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-074490","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":470463,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rse.2016.07.033","text":"Publisher Index Page"},{"id":331816,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"185","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"584bd0dce4b077fc20250e04","contributors":{"authors":[{"text":"Loveland, Thomas R. 0000-0003-3114-6646 loveland@usgs.gov","orcid":"https://orcid.org/0000-0003-3114-6646","contributorId":140256,"corporation":false,"usgs":true,"family":"Loveland","given":"Thomas","email":"loveland@usgs.gov","middleInitial":"R.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":628069,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Irons, James R.","contributorId":59284,"corporation":false,"usgs":false,"family":"Irons","given":"James","email":"","middleInitial":"R.","affiliations":[{"id":7049,"text":"NASA Goddard Space Flight Center","active":true,"usgs":false}],"preferred":false,"id":628070,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70178341,"text":"70178341 - 2016 - Prediction of pesticide toxicity in Midwest streams","interactions":[],"lastModifiedDate":"2018-09-26T12:40:43","indexId":"70178341","displayToPublicDate":"2016-11-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2262,"text":"Journal of Environmental Quality","active":true,"publicationSubtype":{"id":10}},"title":"Prediction of pesticide toxicity in Midwest streams","docAbstract":"<p><span>The occurrence of pesticide mixtures is common in stream waters of the United States, and the impact of multiple compounds on aquatic organisms is not well understood. Watershed Regressions for Pesticides (WARP) models were developed to predict Pesticide Toxicity Index (PTI) values in unmonitored streams in the Midwest and are referred to as WARP-PTI models. The PTI is a tool for assessing the relative toxicity of pesticide mixtures to fish, benthic invertebrates, and cladocera in stream water. One hundred stream sites in the Midwest were sampled weekly in May through August 2013, and the highest calculated PTI for each site was used as the WARP-PTI model response variable. Watershed characteristics that represent pesticide sources and transport were used as the WARP-PTI model explanatory variables. Three WARP-PTI models—fish, benthic invertebrates, and cladocera—were developed that include watershed characteristics describing toxicity-weighted agricultural use intensity, land use, agricultural management practices, soil properties, precipitation, and hydrologic properties. The models explained between 41 and 48% of the variability in the measured PTI values. WARP-PTI model evaluation with independent data showed reasonable performance with no clear bias. The models were applied to streams in the Midwest to demonstrate extrapolation for a regional assessment to indicate vulnerable streams and to guide more intensive monitoring.</span></p>","language":"English","publisher":"ACSESS","doi":"10.2134/jeq2015.12.0624","usgsCitation":"Shoda, M.E., Stone, W.W., and Nowell, L.H., 2016, Prediction of pesticide toxicity in Midwest streams: Journal of Environmental Quality, v. 45, no. 6, p. 1856-1864, https://doi.org/10.2134/jeq2015.12.0624.","productDescription":"9 p.","startPage":"1856","endPage":"1864","ipdsId":"IP-064521","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":470462,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2134/jeq2015.12.0624","text":"Publisher Index Page"},{"id":330980,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Midwest","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -98.41552734375,\n              36.65079252503471\n            ],\n            [\n              -98.41552734375,\n              45.336701909968134\n            ],\n            [\n              -81.71630859375,\n              45.336701909968134\n            ],\n            [\n              -81.71630859375,\n              36.65079252503471\n            ],\n            [\n              -98.41552734375,\n              36.65079252503471\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"45","issue":"6","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"582adb45e4b0c253bdfff0af","contributors":{"authors":[{"text":"Shoda, Megan E. 0000-0002-5343-9717 meshoda@usgs.gov","orcid":"https://orcid.org/0000-0002-5343-9717","contributorId":4352,"corporation":false,"usgs":true,"family":"Shoda","given":"Megan","email":"meshoda@usgs.gov","middleInitial":"E.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true},{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":653653,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stone, Wesley W. 0000-0003-0239-2063 wwstone@usgs.gov","orcid":"https://orcid.org/0000-0003-0239-2063","contributorId":1496,"corporation":false,"usgs":true,"family":"Stone","given":"Wesley","email":"wwstone@usgs.gov","middleInitial":"W.","affiliations":[{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true},{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":653652,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nowell, Lisa H. 0000-0001-5417-7264 lhnowell@usgs.gov","orcid":"https://orcid.org/0000-0001-5417-7264","contributorId":490,"corporation":false,"usgs":true,"family":"Nowell","given":"Lisa","email":"lhnowell@usgs.gov","middleInitial":"H.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":653654,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70179077,"text":"70179077 - 2016 - Do water level fluctuations influence production of walleye and yellow perch young-of-the-year in large northern lakes?","interactions":[],"lastModifiedDate":"2016-12-15T15:27:17","indexId":"70179077","displayToPublicDate":"2016-11-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Do water level fluctuations influence production of walleye and yellow perch young-of-the-year in large northern lakes?","docAbstract":"<p><span>Many ecological processes depend on the regular rise and fall of water levels (WLs), and artificial manipulations to WL regimes can impair important ecosystem services. Previous research has suggested that differences in WL between late summer and early spring may alter the suitability of shoals used by Walleyes </span><i>Sander vitreus</i><span> for spawning. Other species, such as the Yellow Perch </span><i>Perca flavescens</i><span>, are unlikely to be affected in the same way by WL fluctuations because their spawning requirements are quite different. We used 11–23 years of data from six northern Minnesota lakes to assess the effects of WL fluctuations on the abundances of young-of-the-year (age-0) Walleyes and Yellow Perch. In two lakes (Rainy Lake and Lake Kabetogama), a change in WL management occurred in 2000, after which these lakes saw increased age-0 Walleye abundance, while the other study lakes experienced decreases or no change. Rainy Lake and Lake Kabetogama also had increases in age-0 Yellow Perch, but another study lake did also. We used partial least-squares regression to assess whether WL metrics were associated with variation in age-0 Walleye and Yellow Perch abundances, but WL metrics were seldom associated with age-0 abundance for either species. Our analysis suggested a potential influence of WL regulation on age-0 Walleye abundance, but we found no evidence that early spring access to spawning shoals was the mechanism by which this occurred.</span></p>","language":"English","publisher":"American Fisheries Society","doi":"10.1080/02755947.2016.1214645","usgsCitation":"Larson, J.H., Staples, D.F., Maki, R., Vallazza, J., Knights, B.C., and Peterson, K.E., 2016, Do water level fluctuations influence production of walleye and yellow perch young-of-the-year in large northern lakes?: North American Journal of Fisheries Management, v. 36, no. 6, p. 1425-1436, https://doi.org/10.1080/02755947.2016.1214645.","productDescription":"12 p.","startPage":"1425","endPage":"1436","ipdsId":"IP-061712","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":488545,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://figshare.com/articles/dataset/Do_Water_Level_Fluctuations_Influence_Production_of_Walleye_and_Yellow_Perch_Young-of-the-Year_in_Large_Northern_Lakes_/4223739","text":"External Repository"},{"id":332190,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"36","issue":"6","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2016-11-10","publicationStatus":"PW","scienceBaseUri":"5853ba40e4b0e2663625f2b8","contributors":{"authors":[{"text":"Larson, James H. 0000-0002-6414-9758 jhlarson@usgs.gov","orcid":"https://orcid.org/0000-0002-6414-9758","contributorId":4250,"corporation":false,"usgs":true,"family":"Larson","given":"James","email":"jhlarson@usgs.gov","middleInitial":"H.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":655943,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Staples, David F.","contributorId":150561,"corporation":false,"usgs":false,"family":"Staples","given":"David","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":655944,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Maki, Ryan P.","contributorId":100111,"corporation":false,"usgs":true,"family":"Maki","given":"Ryan P.","affiliations":[],"preferred":false,"id":655945,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vallazza, Jon M. jvallazza@usgs.gov","contributorId":139282,"corporation":false,"usgs":true,"family":"Vallazza","given":"Jon M.","email":"jvallazza@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":false,"id":655946,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Knights, Brent C. 0000-0001-8526-8468 bknights@usgs.gov","orcid":"https://orcid.org/0000-0001-8526-8468","contributorId":2906,"corporation":false,"usgs":true,"family":"Knights","given":"Brent","email":"bknights@usgs.gov","middleInitial":"C.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":655947,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Peterson, Kevin E.","contributorId":177489,"corporation":false,"usgs":false,"family":"Peterson","given":"Kevin","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":655948,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70178631,"text":"70178631 - 2016 - Direct photolysis rates and transformation pathways of the lampricides TFM and niclosamide in simulated sunlight","interactions":[],"lastModifiedDate":"2017-07-12T16:12:02","indexId":"70178631","displayToPublicDate":"2016-11-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Direct photolysis rates and transformation pathways of the lampricides TFM and niclosamide in simulated sunlight","docAbstract":"<p><span>The lampricides 3-trifluoromethyl-4-nitrophenol (TFM) and 2′,5-dichloro-4′-nitrosalicylanilide (niclosamide) are directly added to many tributaries of the Great Lakes that harbor the invasive parasitic sea lamprey. Despite their long history of use, the fate of lampricides is not well understood. This study evaluates the rate and pathway of direct photodegradation of both lampricides under simulated sunlight. The estimated half-lives of TFM range from 16.6 ± 0.2 h (pH 9) to 32.9 ± 1.0 h (pH 6), while the half-lives of niclosamide range from 8.88 ± 0.52 days (pH 6) to 382 ± 83 days (pH 9) assuming continuous irradiation over a water depth of 55 cm. Both compounds degrade to form a series of aromatic intermediates, simple organic acids, ring cleavage products, and inorganic ions. Experimental data were used to construct a kinetic model which demonstrates that the aromatic products of TFM undergo rapid photolysis and emphasizes that niclosamide degradation is the rate-limiting step to dehalogenation and mineralization of the lampricide. This study demonstrates that TFM photodegradation is likely to occur on the time scale of lampricide applications (2–5 days), while niclosamide, the less selective lampricide, will undergo minimal direct photodegradation during its passage to the Great Lakes.</span></p>","language":"English","publisher":"ACS Publications","doi":"10.1021/acs.est.6b02607","usgsCitation":"McConville, M.B., Hubert, T.D., and Remucal, C.K., 2016, Direct photolysis rates and transformation pathways of the lampricides TFM and niclosamide in simulated sunlight: Environmental Science & Technology, v. 50, no. 18, p. 9998-10006, https://doi.org/10.1021/acs.est.6b02607.","productDescription":"9 p.","startPage":"9998","endPage":"10006","ipdsId":"IP-076266","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":331398,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"50","issue":"18","noUsgsAuthors":false,"publicationDate":"2016-08-26","publicationStatus":"PW","scienceBaseUri":"584144dee4b04fc80e507398","contributors":{"authors":[{"text":"McConville, Megan B.","contributorId":177099,"corporation":false,"usgs":false,"family":"McConville","given":"Megan","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":654640,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hubert, Terrance D. 0000-0001-9712-1738 thubert@usgs.gov","orcid":"https://orcid.org/0000-0001-9712-1738","contributorId":3036,"corporation":false,"usgs":true,"family":"Hubert","given":"Terrance","email":"thubert@usgs.gov","middleInitial":"D.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":654641,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Remucal, Christina K.","contributorId":177100,"corporation":false,"usgs":false,"family":"Remucal","given":"Christina","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":654642,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70178189,"text":"70178189 - 2016 - Karst","interactions":[],"lastModifiedDate":"2020-08-25T16:59:32.756086","indexId":"70178189","displayToPublicDate":"2016-11-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"89","title":"Karst","docAbstract":"Karst areas present unique hydrologic and hydrogeological characteristics that\nare often challenging to investigate. These characteristics are largely dependent\non the extent of development of solution conduits within the underlying bedrock,\nand the resulting integration of surface and subsurface drainage components\ninto a karst aquifer system. The investigation and characterization of\nkarst aquifers typically require a multidisciplinary approach and the use of\nrelatively specialized methods such as tracer testing, spring discharge monitoring,\nand various hydrograph separation or modeling techniques. Conventional\nmethods of hydrologic or hydrogeologic investigation may be applied successfully\nfor specific purposes; however, proper conceptualization of a given karst\naquifer system is a requirement for effective analysis, modeling, and interpretation\nof karst hydrologic and hydrogeologic data.","language":"English","publisher":"McGraw-Hill","isbn":"9780071835091","usgsCitation":"Taylor, C., and Doctor, D., 2016, Karst, p. 89-1-89-14.","productDescription":"14 p.","startPage":"89-1","endPage":"89-14","ipdsId":"IP-068743","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":330873,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":330782,"type":{"id":15,"text":"Index Page"},"url":"https://www.mhprofessional.com/9780071835091-usa-handbook-of-applied-hydrology-second-edition"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5822f23ae4b0ef3123a9701c","contributors":{"editors":[{"text":"Singh, Vijay P.","contributorId":176741,"corporation":false,"usgs":false,"family":"Singh","given":"Vijay","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":653370,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"authors":[{"text":"Taylor, C.J.","contributorId":22337,"corporation":false,"usgs":true,"family":"Taylor","given":"C.J.","email":"","affiliations":[],"preferred":false,"id":653368,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Doctor, D.H.","contributorId":94773,"corporation":false,"usgs":true,"family":"Doctor","given":"D.H.","affiliations":[],"preferred":false,"id":653369,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70178037,"text":"70178037 - 2016 - Effects of model complexity and priors on estimation using sequential importance sampling/resampling for species conservation","interactions":[],"lastModifiedDate":"2016-11-01T13:25:42","indexId":"70178037","displayToPublicDate":"2016-11-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"title":"Effects of model complexity and priors on estimation using sequential importance sampling/resampling for species conservation","docAbstract":"<p><span>We examined the effects of complexity and priors on the accuracy of models used to estimate ecological and observational processes, and to make predictions regarding population size and structure. State-space models are useful for estimating complex, unobservable population processes and making predictions about future populations based on limited data. To better understand the utility of state space models in evaluating population dynamics, we used them in a Bayesian framework and compared the accuracy of models with differing complexity, with and without informative priors using sequential importance sampling/resampling (SISR). Count data were simulated for 25 years using known parameters and observation process for each model. We used kernel smoothing to reduce the effect of particle depletion, which is common when estimating both states and parameters with SISR. Models using informative priors estimated parameter values and population size with greater accuracy than their non-informative counterparts. While the estimates of population size and trend did not suffer greatly in models using non-informative priors, the algorithm was unable to accurately estimate demographic parameters. This model framework provides reasonable estimates of population size when little to no information is available; however, when information on some vital rates is available, SISR can be used to obtain more precise estimates of population size and process. Incorporating model complexity such as that required by structured populations with stage-specific vital rates affects precision and accuracy when estimating latent population variables and predicting population dynamics. These results are important to consider when designing monitoring programs and conservation efforts requiring management of specific population segments.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolmodel.2016.08.010","usgsCitation":"Dunham, K., and Grand, J.B., 2016, Effects of model complexity and priors on estimation using sequential importance sampling/resampling for species conservation: Ecological Modelling, v. 340, p. 28-36, https://doi.org/10.1016/j.ecolmodel.2016.08.010.","productDescription":"9 p.","startPage":"28","endPage":"36","ipdsId":"IP-069168","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":330621,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"340","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5819a9c1e4b0bb36a4c91007","contributors":{"authors":[{"text":"Dunham, Kylee","contributorId":173081,"corporation":false,"usgs":false,"family":"Dunham","given":"Kylee","affiliations":[{"id":13360,"text":"Auburn University","active":true,"usgs":false}],"preferred":false,"id":652582,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grand, J. Barry 0000-0002-3576-4567 barry_grand@usgs.gov","orcid":"https://orcid.org/0000-0002-3576-4567","contributorId":579,"corporation":false,"usgs":true,"family":"Grand","given":"J.","email":"barry_grand@usgs.gov","middleInitial":"Barry","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":652581,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70182736,"text":"70182736 - 2016 - Climate-change signals in national atmospheric deposition program precipitation data","interactions":[],"lastModifiedDate":"2017-02-27T15:22:19","indexId":"70182736","displayToPublicDate":"2016-11-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1248,"text":"Climate Dynamics","active":true,"publicationSubtype":{"id":10}},"title":"Climate-change signals in national atmospheric deposition program precipitation data","docAbstract":"<p><span>National Atmospheric Deposition Program (NADP)/National Trends Network precipitation type, snow-season duration, and annual timing of selected chemical wet-deposition maxima vary with latitude and longitude within a 35-year (1979–2013) data record for the contiguous United States and Alaska. From the NADP data collected within the region bounded by 35.6645°–48.782° north latitude and 124°–68° west longitude, similarities in latitudinal and longitudinal patterns of changing snow-season duration, fraction of annual precipitation recorded as snow, and the timing of chemical wet-deposition maxima, suggest that the chemical climate of the atmosphere is linked to physical changes in climate. Total annual precipitation depth has increased 4–6&nbsp;% while snow season duration has decreased from approximately 7 to 21&nbsp;days across most of the USA, except in higher elevation regions where it has increased by as much as 21&nbsp;days. Snow-season precipitation is increasingly comprised of snow, but annually total precipitation is increasingly comprised of liquid precipitation. Meanwhile, maximum ammonium deposition occurs as much as 27&nbsp;days earlier, and the maximum nitrate: sulfate concentration ratio in wet-deposition occurs approximately 10–21&nbsp;days earlier in the year. The maximum crustal (calcium&nbsp;+&nbsp;magnesium&nbsp;+&nbsp;potassium) cation deposition occurs 2–35&nbsp;days earlier in the year. The data suggest that these shifts in the timing of atmospheric wet deposition are linked to a warming climate, but the ecological consequences are uncertain.</span></p>","language":"English","publisher":"Springer-Verlag ","doi":"10.1007/s00382-016-3017-7","usgsCitation":"Wetherbee, G.A., and Mast, M.A., 2016, Climate-change signals in national atmospheric deposition program precipitation data: Climate Dynamics, v. 47, no. 9, p. 3141-3155, https://doi.org/10.1007/s00382-016-3017-7.","productDescription":"15 p. ","startPage":"3141","endPage":"3155","ipdsId":"IP-061492","costCenters":[{"id":143,"text":"Branch of Quality Systems","active":true,"usgs":true}],"links":[{"id":336302,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"47","issue":"9","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-02-29","publicationStatus":"PW","scienceBaseUri":"58b548bde4b01ccd54fddfa8","chorus":{"doi":"10.1007/s00382-016-3017-7","url":"http://dx.doi.org/10.1007/s00382-016-3017-7","publisher":"Springer Nature","authors":"Wetherbee Gregory A., Mast M. Alisa","journalName":"Climate Dynamics","publicationDate":"2/29/2016","auditedOn":"8/1/2016","publiclyAccessibleDate":"2/29/2016"},"contributors":{"authors":[{"text":"Wetherbee, Gregory A. 0000-0002-6720-2294 wetherbe@usgs.gov","orcid":"https://orcid.org/0000-0002-6720-2294","contributorId":1044,"corporation":false,"usgs":true,"family":"Wetherbee","given":"Gregory","email":"wetherbe@usgs.gov","middleInitial":"A.","affiliations":[{"id":143,"text":"Branch of Quality Systems","active":true,"usgs":true}],"preferred":true,"id":673508,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mast, M. Alisa 0000-0001-6253-8162 mamast@usgs.gov","orcid":"https://orcid.org/0000-0001-6253-8162","contributorId":827,"corporation":false,"usgs":true,"family":"Mast","given":"M.","email":"mamast@usgs.gov","middleInitial":"Alisa","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":673509,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70193096,"text":"70193096 - 2016 - Evaluation of fisher (Pekania pennanti) restoration in Olympic National Park and the Olympic Recovery Area: 2015 final annual progress report","interactions":[],"lastModifiedDate":"2017-11-27T14:59:21","indexId":"70193096","displayToPublicDate":"2016-11-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":53,"text":"Natural Resource Report","active":false,"publicationSubtype":{"id":1}},"seriesNumber":"NPS/OLYM/NRR—2016/1274","displayTitle":"Evaluation of fisher (<i>Pekania pennanti</i>) restoration in Olympic National Park and the Olympic Recovery Area: 2015 final annual progress report","title":"Evaluation of fisher (Pekania pennanti) restoration in Olympic National Park and the Olympic Recovery Area: 2015 final annual progress report","docAbstract":"<p>With the translocation and release of 90 fishers (Pekania pennanti) from British Columbia to Olympic National Park during 2008–2010, the National Park Service (NPS) and Washington Department of Fish and Wildlife (WDFW) accomplished the first phase of fisher restoration in Washington State. Beginning in 2013, we initiated a new research project to determine the current status of fishers on Washington’s Olympic Peninsula 3–8 years after the releases and evaluate the short-term success of the restoration program. Objectives of the study are to determine the current distribution of fishers and proportion of the recovery area that is currently occupied by fishers, determine several genetic characteristics of the reintroduced population, and determine reproductive success of the founding animals through genetic studies. </p><p>During 2015, we continued working with a broad coalition of cooperating agencies, tribes, and nongovernmental organizations (NGO) to collect data on fisher distribution and genetics using noninvasive sampling methods. The primary sampling frame consisted of 157 24-km2 hexagons (hexes) distributed across all major land ownerships within the Olympic Peninsula target survey area. In 2014 we expanded the study by adding 58 more hexes to an expanded study area in response to incidental fisher observations outside of the target area obtained in 2013; 49 hexes were added south and 9 to the east of the target area. During 2015, Federal, State, Tribal and NGO biologists and volunteers established three Distributioned motion-sensing camera stations, paired with hair snaring devices, in 87 hexes; 75 in the targeted area and 12 in the expansion areas. Each paired camera/hair station was left in place for approximately 6 weeks, with three checks on 2-week intervals. We documented fisher presence in 7 of the 87 hexagons. Four fishers were identified through microsatellite DNA analyses. The 4 identified fishers included 1 of the original founding population of 90 and 3 new recruits to the population. Three additional fishers were detected with cameras but not DNA, consequently their identities were unknown. All fisher detections were in the target area. Additionally, we identified 46 other species of wildlife at the baited camera stations. We also obtained 4 additional confirmed records of fishers in the study area through photographs provided by the public and incidental live capture. </p><p>During 2016, we plan to resample 69 hexagons sampled in the target area in 2014 and 12 new hexes in the expansion area. In addition, we plan to sample non-selected hexes in-between hexes where we had a cluster of fishers in 2014, to provide better understanding of occupancy patterns and minimum number of individuals in an area where fishers appear to be concentrating. </p>","language":"English","publisher":"National Park Service","publisherLocation":"Fort Collins, CO","usgsCitation":"Happe, P.J., Jenkins, K.J., Kay, T.J., Pilgrim, K., Schwartz, M.K., Lewis, J.C., and Aubry, K.B., 2016, Evaluation of fisher (Pekania pennanti) restoration in Olympic National Park and the Olympic Recovery Area: 2015 final annual progress report: Natural Resource Report NPS/OLYM/NRR—2016/1274, ix, 34 p.","productDescription":"ix, 34 p.","numberOfPages":"48","ipdsId":"IP-088873","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science 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kurt_jenkins@usgs.gov","orcid":"https://orcid.org/0000-0003-1415-6607","contributorId":3415,"corporation":false,"usgs":true,"family":"Jenkins","given":"Kurt","email":"kurt_jenkins@usgs.gov","middleInitial":"J.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":717967,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kay, Thomas J.","contributorId":141089,"corporation":false,"usgs":false,"family":"Kay","given":"Thomas","email":"","middleInitial":"J.","affiliations":[{"id":7237,"text":"NPS, Olympic National Park","active":true,"usgs":false}],"preferred":false,"id":717969,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pilgrim, Kristie","contributorId":199034,"corporation":false,"usgs":false,"family":"Pilgrim","given":"Kristie","email":"","affiliations":[],"preferred":false,"id":717970,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schwartz, Michael K.","contributorId":199035,"corporation":false,"usgs":false,"family":"Schwartz","given":"Michael","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":717971,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lewis, Jeffrey C.","contributorId":141090,"corporation":false,"usgs":false,"family":"Lewis","given":"Jeffrey","email":"","middleInitial":"C.","affiliations":[{"id":13674,"text":"WDFW","active":true,"usgs":false}],"preferred":false,"id":717972,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Aubry, Keith B.","contributorId":141091,"corporation":false,"usgs":false,"family":"Aubry","given":"Keith","email":"","middleInitial":"B.","affiliations":[{"id":7134,"text":"USFS","active":true,"usgs":false}],"preferred":false,"id":717973,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70185054,"text":"70185054 - 2016 - Western Lake Erie Basin: Soft-data-constrained, NHDPlus resolution watershed modeling and exploration of applicable conservation scenarios","interactions":[],"lastModifiedDate":"2017-03-13T15:11:54","indexId":"70185054","displayToPublicDate":"2016-11-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Western Lake Erie Basin: Soft-data-constrained, NHDPlus resolution watershed modeling and exploration of applicable conservation scenarios","docAbstract":"<p><span>Complex watershed simulation models are powerful tools that can help scientists and policy-makers address challenging topics, such as land use management and water security. In the Western Lake Erie Basin (WLEB), complex hydrological models have been applied at various scales to help describe relationships between land use and water, nutrient, and sediment dynamics. This manuscript evaluated the capacity of the current Soil and Water Assessment Tool (SWAT2012) to predict hydrological and water quality processes within WLEB at the finest resolution watershed boundary unit (NHDPlus) along with the current conditions and conservation scenarios. The process based SWAT model was capable of the fine-scale computation and complex routing used in this project, as indicated by measured data at five gaging stations. The level of detail required for fine-scale spatial simulation made the use of both hard and soft data necessary in model calibration, alongside other model adaptations. Limitations to the model's predictive capacity were due to a paucity of data in the region at the NHDPlus scale rather than due to SWAT functionality. Results of treatment scenarios demonstrate variable effects of structural practices and nutrient management on sediment and nutrient loss dynamics. Targeting treatment to acres with critical outstanding conservation needs provides the largest return on investment in terms of nutrient loss reduction per dollar spent, relative to treating acres with lower inherent nutrient loss vulnerabilities. Importantly, this research raises considerations about use of models to guide land management decisions at very fine spatial scales. Decision makers using these results should be aware of data limitations that hinder fine-scale model interpretation.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2016.06.202","usgsCitation":"Yen, H., White, M.J., Arnold, J.G., Keitzer, S.C., Johnson, M.V., Atwood, J.D., Daggupati, P., Herbert, M.E., Sowa, S.P., Ludsin, S.A., Robertson, D.M., Srinivasan, R., and Rewa, C.A., 2016, Western Lake Erie Basin: Soft-data-constrained, NHDPlus resolution watershed modeling and exploration of applicable conservation scenarios: Science of the Total Environment, v. 569-570, p. 1265-1281, https://doi.org/10.1016/j.scitotenv.2016.06.202.","productDescription":"17 p.","startPage":"1265","endPage":"1281","ipdsId":"IP-075988","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":470472,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2016.06.202","text":"Publisher Index Page"},{"id":337455,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Lake Erie Basin","volume":"569-570","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58c7af9ee4b0849ce9795e8c","contributors":{"authors":[{"text":"Yen, Haw 0000-0002-5509-8792","orcid":"https://orcid.org/0000-0002-5509-8792","contributorId":169564,"corporation":false,"usgs":false,"family":"Yen","given":"Haw","email":"","affiliations":[{"id":6747,"text":"Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":684085,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"White, Michael J.","contributorId":172348,"corporation":false,"usgs":false,"family":"White","given":"Michael","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":684087,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Arnold, Jeffrey G.","contributorId":172345,"corporation":false,"usgs":false,"family":"Arnold","given":"Jeffrey","email":"","middleInitial":"G.","affiliations":[{"id":6758,"text":"USDA-ARS","active":true,"usgs":false}],"preferred":false,"id":684097,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Keitzer, S. Conor 0000-0002-8164-4099","orcid":"https://orcid.org/0000-0002-8164-4099","contributorId":189196,"corporation":false,"usgs":false,"family":"Keitzer","given":"S.","email":"","middleInitial":"Conor","affiliations":[],"preferred":false,"id":684096,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Johnson, Mari-Vaughn V. 0000-0002-2944-2529","orcid":"https://orcid.org/0000-0002-2944-2529","contributorId":189195,"corporation":false,"usgs":false,"family":"Johnson","given":"Mari-Vaughn","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":684095,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Atwood, Jay D.","contributorId":189194,"corporation":false,"usgs":false,"family":"Atwood","given":"Jay","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":684094,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Daggupati, Prasad 0000-0002-7044-3435","orcid":"https://orcid.org/0000-0002-7044-3435","contributorId":189193,"corporation":false,"usgs":false,"family":"Daggupati","given":"Prasad","email":"","affiliations":[],"preferred":false,"id":684093,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Herbert, Matthew E.","contributorId":189192,"corporation":false,"usgs":false,"family":"Herbert","given":"Matthew","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":684092,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Sowa, Scott P. 0000-0002-5425-2591 sowasp@missouri.edu","orcid":"https://orcid.org/0000-0002-5425-2591","contributorId":146672,"corporation":false,"usgs":false,"family":"Sowa","given":"Scott","email":"sowasp@missouri.edu","middleInitial":"P.","affiliations":[{"id":7041,"text":"The Nature Conservancy","active":true,"usgs":false}],"preferred":false,"id":684091,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Ludsin, Stuart A. 0000-0002-3866-2216","orcid":"https://orcid.org/0000-0002-3866-2216","contributorId":175425,"corporation":false,"usgs":false,"family":"Ludsin","given":"Stuart","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":684090,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"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":684086,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Srinivasan, Raghavan","contributorId":189191,"corporation":false,"usgs":false,"family":"Srinivasan","given":"Raghavan","affiliations":[],"preferred":false,"id":684089,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Rewa, Charles A.","contributorId":189190,"corporation":false,"usgs":false,"family":"Rewa","given":"Charles","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":684088,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}}
,{"id":70187242,"text":"70187242 - 2016 - Chronic wasting disease in white-tailed deer: Infection, mortality, and implications for heterogeneous transmission","interactions":[],"lastModifiedDate":"2017-04-27T17:00:14","indexId":"70187242","displayToPublicDate":"2016-11-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Chronic wasting disease in white-tailed deer: Infection, mortality, and implications for heterogeneous transmission","docAbstract":"<p><span>Chronic wasting disease (CWD) is a fatal neurodegenerative disease affecting free-ranging and captive cervids that now occurs in 24 U.S. states and two Canadian provinces. Despite the potential threat of CWD to deer populations, little is known about the rates of infection and mortality caused by this disease. We used epidemiological models to estimate the force of infection and disease-associated mortality for white-tailed deer in the Wisconsin and Illinois CWD outbreaks. Models were based on age-prevalence data corrected for bias in aging deer using the tooth wear and replacement method. Both male and female deer in the Illinois outbreak had higher corrected age-specific prevalence with slightly higher female infection than deer in the Wisconsin outbreak. Corrected ages produced more complex models with different infection and mortality parameters than those based on apparent prevalence. We found that adult male deer have a more than threefold higher risk of CWD infection than female deer. Males also had higher disease mortality than female deer. As a result, CWD prevalence was twofold higher in adult males than females. We also evaluated the potential impacts of alternative contact structures on transmission dynamics in Wisconsin deer. Results suggested that transmission of CWD among male deer during the nonbreeding season may be a potential mechanism for producing higher rates of infection and prevalence characteristically found in males. However, alternatives based on high environmental transmission and transmission from females to males during the breeding season may also play a role.</span></p>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecy.1538","usgsCitation":"Samuel, M.D., and Storm, D.J., 2016, Chronic wasting disease in white-tailed deer: Infection, mortality, and implications for heterogeneous transmission: Ecology, v. 97, no. 11, p. 3195-3205, https://doi.org/10.1002/ecy.1538.","productDescription":"11 p.","startPage":"3195","endPage":"3205","ipdsId":"IP-066740","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":340548,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"97","issue":"11","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-10-04","publicationStatus":"PW","scienceBaseUri":"59030325e4b0e862d230f71f","contributors":{"authors":[{"text":"Samuel, Michael D. msamuel@usgs.gov","contributorId":1419,"corporation":false,"usgs":true,"family":"Samuel","given":"Michael","email":"msamuel@usgs.gov","middleInitial":"D.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":693094,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Storm, Daniel J.","contributorId":171373,"corporation":false,"usgs":false,"family":"Storm","given":"Daniel","email":"","middleInitial":"J.","affiliations":[{"id":24576,"text":"University of Wisconsin, Madison, WI","active":true,"usgs":false}],"preferred":false,"id":693095,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70185056,"text":"70185056 - 2016 - The use of amino acid indices for assessing organic matter quality and microbial abundance in deep-sea Antarctic sediments of IODP Expedition 318","interactions":[],"lastModifiedDate":"2017-03-13T16:20:03","indexId":"70185056","displayToPublicDate":"2016-11-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2662,"text":"Marine Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"The use of amino acid indices for assessing organic matter quality and microbial abundance in deep-sea Antarctic sediments of IODP Expedition 318","docAbstract":"<p><span>The Adélie Basin, located offshore of the Wilkes Land margin, experiences unusually high sedimentation rates (~&nbsp;2&nbsp;cm&nbsp;yr</span><sup>−&nbsp;1</sup><span>) for the Antarctic coast. This study sought to compare depthwise changes in organic matter (OM) quantity and quality with changes in microbial biomass with depth at this high-deposition site and an offshore continental margin site. Sediments from both sites were collected during the International Ocean Drilling (IODP) Program Expedition 318. Viable microbial biomass was estimated from concentrations of bacterial-derived phospholipid fatty acids, while OM quality was assessed using four different amino acid degradation proxies. Concentrations of total hydrolysable amino acids (THAA) measured from the continental margin suggest an oligotrophic environment, with THAA concentrations representing only 2% of total organic carbon with relative proportions of non-protein amino acids β-alanine and γ-aminobutyric acid as high as 40%. In contrast, THAA concentrations from the near-shore Adélie Basin represent 40%–60% of total organic carbon. Concentrations of β-alanine and γ-aminobutyric acid were often below the detection limit and suggest that the OM of the basin as labile. DI values in surface sediments at the Adélie and margin sites were measured to be +&nbsp;0.78 and −&nbsp;0.76, reflecting labile and more recalcitrant OM, respectively. Greater DI values in deeper and more anoxic portions of both cores correlated positively with increased relative concentrations of phenylalanine plus tyrosine and may represent a change of redox conditions, rather than OM quality. This suggests that DI values calculated along chemical profiles should be interpreted with caution. THAA concentrations, the percentage of organic carbon (C</span><sub>AA</sub><span>%) and total nitrogen (N</span><sub>AA</sub><span>%) represented by amino acids at both sites demonstrated a significant positive correlation with bacterial abundance estimates. These data suggest that the selective degradation of amino acids, as indicated by THAA concentrations, C</span><sub>AA</sub><span>% or N</span><sub>AA</sub><span>% values may be a better proxy for describing the general changes in sedimentary bacterial abundances than total organic matter or bulk sedimentation rates.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.marchem.2016.08.002","usgsCitation":"Carr, S., Mills, C., and Mandernack, K.W., 2016, The use of amino acid indices for assessing organic matter quality and microbial abundance in deep-sea Antarctic sediments of IODP Expedition 318: Marine Chemistry, v. 186, p. 72-82, https://doi.org/10.1016/j.marchem.2016.08.002.","productDescription":"11 p.","startPage":"72","endPage":"82","ipdsId":"IP-076259","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":337469,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"186","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58c7af9ee4b0849ce9795e8a","contributors":{"authors":[{"text":"Carr, Stephanie A","contributorId":189201,"corporation":false,"usgs":false,"family":"Carr","given":"Stephanie A","affiliations":[],"preferred":false,"id":684105,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mills, Christopher T. 0000-0001-8414-1414 cmills@usgs.gov","orcid":"https://orcid.org/0000-0001-8414-1414","contributorId":150137,"corporation":false,"usgs":true,"family":"Mills","given":"Christopher T.","email":"cmills@usgs.gov","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":684104,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mandernack, Kevin W","contributorId":189202,"corporation":false,"usgs":false,"family":"Mandernack","given":"Kevin","email":"","middleInitial":"W","affiliations":[],"preferred":false,"id":684106,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70174906,"text":"fs20163053 - 2016 - Water clarity of the Colorado River—Implications for food webs and fish communities","interactions":[],"lastModifiedDate":"2016-11-01T15:36:18","indexId":"fs20163053","displayToPublicDate":"2016-11-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-3053","title":"Water clarity of the Colorado River—Implications for food webs and fish communities","docAbstract":"<p><span>The closure of Glen Canyon Dam in 1963 resulted in drastic changes to water clarity, temperature, and flow of the Colorado River in Glen, Marble, and Grand Canyons. The Colorado River is now much clearer, water temperature is less variable throughout the year, and the river is much colder in the summer months. The flow—regulated by the dam—is now less variable annually, but has larger daily fluctuations than during pre-dam times. All of these changes have resulted in a different fish community and different food resources for fish than existed before the dam was built. Recent monitoring of water clarity, by measuring turbidity, has helped scientists and river managers understand modern water-clarity patterns in the dam-regulated Colorado River. These data were then used to estimate pre-dam turbidity in the Colorado River in order to make comparisons of pre-dam and dam-regulated conditions, which are useful for assessing biological changes in the river over time. Prior to dam construction, the large sediment load resulted in low water clarity almost all of the time, a condition which was more favorable for the native fish community.</span></p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20163053","usgsCitation":"Voichick, N., Kennedy, T.A., Topping, D.J., Griffiths, R.E., and Fry, K.L., 2016, Water clarity of the Colorado River—Implications for food webs and fish communities: U.S. Geological Survey Fact Sheet 2016–5053, 4 p., https://dx.doi.org/10.3133/fs20163053.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"Y","ipdsId":"IP-067865","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":330598,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2016/3053/fs20163053.pdf","text":"Report","size":"1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2016-3053"},{"id":330597,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2016/3053/coverthb.jpg"}],"country":"United States","state":"Arizona, California, Colorado, Nevada Utah, New Mexico","otherGeospatial":"Colorado River basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -104.52392578125,\n              39.87601941962116\n            ],\n            [\n              -104.62280273437499,\n              39.06184913429154\n            ],\n            [\n              -106.226806640625,\n              38.487994609214795\n            ],\n            [\n              -107.962646484375,\n              38.039438891821746\n            ],\n            [\n              -108.06152343749999,\n              37.31775185163688\n            ],\n            [\n              -108.6328125,\n              36.359374956015856\n            ],\n            [\n              -109.16015624999999,\n              35.24561909420681\n            ],\n            [\n              -109.127197265625,\n              32.90726224488304\n            ],\n            [\n              -109.13818359375,\n              31.484893386890164\n            ],\n            [\n              -111.126708984375,\n              31.316101383495624\n            ],\n            [\n              -114.80712890625,\n              32.47269502206151\n            ],\n            [\n              -114.697265625,\n              32.731840896865684\n            ],\n            [\n              -114.93896484374999,\n              34.415973384481866\n            ],\n            [\n              -114.97192382812499,\n              35.594785665487244\n            ],\n            [\n              -114.78515624999999,\n              36.85325222344018\n            ],\n            [\n              -114.32373046875,\n              37.49229399862877\n            ],\n            [\n              -113.477783203125,\n              37.49229399862877\n            ],\n            [\n              -112.19238281249999,\n              37.60552821745789\n            ],\n            [\n              -111.236572265625,\n              38.09998264736481\n            ],\n            [\n              -110.0830078125,\n              38.7283759182398\n            ],\n            [\n              -109.281005859375,\n              39.554883059924016\n            ],\n            [\n              -108.182373046875,\n              39.9434364619742\n            ],\n            [\n              -106.3916015625,\n              39.93501296038254\n            ],\n            [\n              -104.52392578125,\n              39.87601941962116\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><span class=\"m_6234669218502970143gmail-s1\"><a href=\"http://www.gcmrc.gov/about/staff.aspx%22%20%5Ct%20%22_blank\" target=\"_blank\" data-mce-href=\"http://www.gcmrc.gov/about/staff.aspx%22%20%5Ct%20%22_blank\">GCMRC Staff</a></span>, Southwest Biological Science Center<br>U.S. Geological Survey<span class=\"im\"><br>Grand Canyon Monitoring and Research Center<br></span>2255 N. Gemini Drive<br>Flagstaff, AZ 86001<br><a href=\"http://www.gcmrc.gov/%22%20%5Ct%20%22_blank\" target=\"_blank\" data-mce-href=\"http://www.gcmrc.gov/%22%20%5Ct%20%22_blank\"><span class=\"m_6234669218502970143gmail-s1\">http://www.gcmrc.gov/</span></a><span class=\"m_6234669218502970143gmail-s2\">&nbsp;</span><br></p>","tableOfContents":"<ul><li>Water Clarity in Grand Canyon<br></li><li>Comparing Pre-Dam and Dam-Regulated Water Clarity<br></li><li>Measuring Water Clarity<br></li><li>Water Clarity, Temperature, and Biology<br></li><li>References Cited<br></li></ul>","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"publishedDate":"2016-11-01","noUsgsAuthors":false,"publicationDate":"2016-11-01","publicationStatus":"PW","scienceBaseUri":"5819a9c2e4b0bb36a4c91013","contributors":{"authors":[{"text":"Voichick, Nicholas nvoichick@usgs.gov","contributorId":5015,"corporation":false,"usgs":true,"family":"Voichick","given":"Nicholas","email":"nvoichick@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":643086,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kennedy, Theodore A. 0000-0003-3477-3629 tkennedy@usgs.gov","orcid":"https://orcid.org/0000-0003-3477-3629","contributorId":167537,"corporation":false,"usgs":true,"family":"Kennedy","given":"Theodore","email":"tkennedy@usgs.gov","middleInitial":"A.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":643087,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Topping, David J. 0000-0002-2104-4577 dtopping@usgs.gov","orcid":"https://orcid.org/0000-0002-2104-4577","contributorId":140985,"corporation":false,"usgs":true,"family":"Topping","given":"David","email":"dtopping@usgs.gov","middleInitial":"J.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":643088,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Griffiths, Ronald E. 0000-0003-3620-2926 rgriffiths@usgs.gov","orcid":"https://orcid.org/0000-0003-3620-2926","contributorId":162,"corporation":false,"usgs":true,"family":"Griffiths","given":"Ronald","email":"rgriffiths@usgs.gov","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":643089,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fry, Kyrie","contributorId":176502,"corporation":false,"usgs":true,"family":"Fry","given":"Kyrie","email":"","affiliations":[],"preferred":false,"id":643090,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70185036,"text":"70185036 - 2016 - Review of footnotes and annotations to the 1949–2013 tables of standard atomic weights and tables of isotopic compositions of the elements (IUPAC Technical Report)","interactions":[],"lastModifiedDate":"2017-03-13T16:56:17","indexId":"70185036","displayToPublicDate":"2016-11-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3207,"text":"Pure and Applied Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Review of footnotes and annotations to the 1949–2013 tables of standard atomic weights and tables of isotopic compositions of the elements (IUPAC Technical Report)","docAbstract":"<p><span>The Commission on Isotopic Abundances and Atomic Weights uses annotations given in footnotes that are an integral part of the Tables of Standard Atomic Weights to alert users to the possibilities of quite extraordinary occurrences, as well as sources with abnormal atomic-weight values outside an otherwise acceptable range. The basic need for footnotes to the Standard Atomic Weights Table and equivalent annotations to the Table of Isotopic Compositions of the Elements arises from the necessity to provide users with information that is relevant to one or more elements, but that cannot be provided using numerical data in columns. Any desire to increase additional information conveyed by annotations to these Tables is tempered by the need to preserve a compact format and a style that can alert users, who would not be inclined to consult either the last full element-by-element review or the full text of a current Standard Atomic Weights of the Elements report. Since 1989, the footnotes of the Tables of Standard Atomic Weights and the annotations in column 5 of the Table of Isotopic Compositions of the Elements have been harmonized by use of three lowercase footnotes, “g”, “m”, and “r”, that signify geologically exceptionally specimens (“g”), modified isotopic compositions in material subjected to undisclosed or inadvertent isotopic fractionation (“m”), and the range in isotopic composition of normal terrestrial material prevents more precise atomic-weight value being given (“r”). As some elements are assigned intervals for their standard atomic-weight values (applies to 12 elements since 2009), footnotes “g” and “r” are no longer needed for these elements.</span></p>","language":"English","publisher":"IUPAC","doi":"10.1515/pac-2016-0203","usgsCitation":"Coplen, T.B., and Holden, N.E., 2016, Review of footnotes and annotations to the 1949–2013 tables of standard atomic weights and tables of isotopic compositions of the elements (IUPAC Technical Report): Pure and Applied Chemistry, v. 88, no. 7, p. 689-699, https://doi.org/10.1515/pac-2016-0203.","productDescription":"11 p.","startPage":"689","endPage":"699","ipdsId":"IP-072769","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":470470,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1515/pac-2016-0203","text":"Publisher Index Page"},{"id":337476,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"88","issue":"7","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-09-28","publicationStatus":"PW","scienceBaseUri":"58c7af9fe4b0849ce9795e94","contributors":{"authors":[{"text":"Coplen, Tyler B. 0000-0003-4884-6008 tbcoplen@usgs.gov","orcid":"https://orcid.org/0000-0003-4884-6008","contributorId":508,"corporation":false,"usgs":true,"family":"Coplen","given":"Tyler","email":"tbcoplen@usgs.gov","middleInitial":"B.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":684029,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Holden, Norman E.","contributorId":189167,"corporation":false,"usgs":false,"family":"Holden","given":"Norman","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":684030,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70185051,"text":"70185051 - 2016 - Estimation of time-variable fast flow path chemical concentrations for application in tracer-based hydrograph separation analyses","interactions":[],"lastModifiedDate":"2017-03-13T16:21:41","indexId":"70185051","displayToPublicDate":"2016-11-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Estimation of time-variable fast flow path chemical concentrations for application in tracer-based hydrograph separation analyses","docAbstract":"<p><span>Mixing models are a commonly used method for hydrograph separation, but can be hindered by the subjective choice of the end-member tracer concentrations. This work tests a new variant of mixing model that uses high-frequency measures of two tracers and streamflow to separate total streamflow into water from slowflow and fastflow sources. The ratio between the concentrations of the two tracers is used to create a time-variable estimate of the concentration of each tracer in the fastflow end-member. Multiple synthetic data sets, and data from two hydrologically diverse streams, are used to test the performance and limitations of the new model (two-tracer ratio-based mixing model: TRaMM). When applied to the synthetic streams under many different scenarios, the TRaMM produces results that were reasonable approximations of the actual values of fastflow discharge (±0.1% of maximum fastflow) and fastflow tracer concentrations (±9.5% and ±16% of maximum fastflow nitrate concentration and specific conductance, respectively). With real stream data, the TRaMM produces high-frequency estimates of slowflow and fastflow discharge that align with expectations for each stream based on their respective hydrologic settings. The use of two tracers with the TRaMM provides an innovative and objective approach for estimating high-frequency fastflow concentrations and contributions of fastflow water to the stream. This provides useful information for tracking chemical movement to streams and allows for better selection and implementation of water quality management strategies.</span></p>","language":"English","publisher":"AGU Publications","doi":"10.1002/2016WR018797","usgsCitation":"Kronholm, S.C., and Capel, P.D., 2016, Estimation of time-variable fast flow path chemical concentrations for application in tracer-based hydrograph separation analyses: Water Resources Research, v. 52, no. 9, p. 6881-6896, https://doi.org/10.1002/2016WR018797.","productDescription":"16 p.","startPage":"6881","endPage":"6896","ipdsId":"IP-075597","costCenters":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"links":[{"id":470473,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2016wr018797","text":"Publisher Index Page"},{"id":438519,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F71R6NMQ","text":"USGS data release","linkHelpText":"Real and synthetic data used to test the Two-tracer Ratio-based Mixing Model (TRaMM)"},{"id":337470,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"52","issue":"9","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-09-10","publicationStatus":"PW","scienceBaseUri":"58c7af9ee4b0849ce9795e8e","contributors":{"authors":[{"text":"Kronholm, Scott C.","contributorId":184190,"corporation":false,"usgs":false,"family":"Kronholm","given":"Scott","email":"","middleInitial":"C.","affiliations":[{"id":12644,"text":"University of Minnesota, St. Paul","active":true,"usgs":false}],"preferred":false,"id":684079,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Capel, Paul D. 0000-0003-1620-5185 capel@usgs.gov","orcid":"https://orcid.org/0000-0003-1620-5185","contributorId":1002,"corporation":false,"usgs":true,"family":"Capel","given":"Paul","email":"capel@usgs.gov","middleInitial":"D.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":684078,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
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