{"pageNumber":"407","pageRowStart":"10150","pageSize":"25","recordCount":46620,"records":[{"id":70185034,"text":"70185034 - 2016 - Controls on selenium distribution and mobilization in an irrigated shallow groundwater system underlain by Mancos Shale, Uncompahgre River Basin, Colorado, USA","interactions":[],"lastModifiedDate":"2017-03-15T11:16:36","indexId":"70185034","displayToPublicDate":"2016-10-01T00:00:00","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":"Controls on selenium distribution and mobilization in an irrigated shallow groundwater system underlain by Mancos Shale, Uncompahgre River Basin, Colorado, USA","docAbstract":"<p><span>Elevated selenium (Se) concentrations in surface water and groundwater have become a concern in areas of the Western United States due to the deleterious effects of Se on aquatic ecosystems. Elevated Se concentrations are most prevalent in irrigated alluvial valleys underlain by Se-bearing marine shales where Se can be leached from geologic materials into the shallow groundwater and surface water systems. This study presents groundwater chemistry and solid-phase geochemical data from the Uncompahgre River Basin in Western Colorado, an irrigated alluvial landscape underlain by Se-rich Cretaceous marine shale. We analyzed Se species, major and trace elements, and stable nitrogen and oxygen isotopes of nitrate in groundwater and aquifer sediments to examine processes governing selenium release and transport in the shallow groundwater system. Groundwater Se concentrations ranged from below detection limit (&lt;&nbsp;0.5&nbsp;μg&nbsp;L</span><sup>−&nbsp;1</sup><span>) to 4070&nbsp;μg&nbsp;L</span><sup>−&nbsp;1</sup><span>, and primarily are controlled by high groundwater nitrate concentrations that maintain oxidizing conditions in the aquifer despite low dissolved oxygen concentrations. High nitrate concentrations in non-irrigated soils and nitrate isotopes indicate nitrate is largely derived from natural sources in the Mancos Shale and alluvial material. Thus, in contrast to areas that receive substantial NO</span><sub>3</sub><span> inputs through inorganic fertilizer application, Se mitigation efforts that involve limiting NO</span><sub>3</sub><span> application might have little impact on groundwater Se concentrations in the study area. Soluble salts are the primary source of Se to the groundwater system in the study area at-present, but they constitute a small percentage of the total Se content of core material. Sequential extraction results indicate insoluble Se is likely composed of reduced Se in recalcitrant organic matter or discrete selenide phases. Oxidation of reduced Se species that constitute the majority of the Se pool in the study area could be a potential source of Se in the future as soluble salts are progressively depleted.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2016.06.063","usgsCitation":"Mills, T.J., Mast, M.A., Thomas, J.C., and Keith, G.L., 2016, Controls on selenium distribution and mobilization in an irrigated shallow groundwater system underlain by Mancos Shale, Uncompahgre River Basin, Colorado, USA: Science of the Total Environment, v. 566-567, p. 1621-1631, https://doi.org/10.1016/j.scitotenv.2016.06.063.","productDescription":"11 p.","startPage":"1621","endPage":"1631","ipdsId":"IP-072320","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":337598,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Uncompahgre River Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -108.17550659179688,\n              38.41378642476067\n            ],\n            [\n              -107.78961181640625,\n              38.41378642476067\n            ],\n            [\n              -107.78961181640625,\n              38.79476766282312\n            ],\n            [\n              -108.17550659179688,\n              38.79476766282312\n            ],\n            [\n              -108.17550659179688,\n              38.41378642476067\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"566-567","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58ca52cee4b0849ce97c86aa","contributors":{"authors":[{"text":"Mills, Taylor J. 0000-0001-7252-0521 tmills@usgs.gov","orcid":"https://orcid.org/0000-0001-7252-0521","contributorId":4658,"corporation":false,"usgs":true,"family":"Mills","given":"Taylor","email":"tmills@usgs.gov","middleInitial":"J.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":684023,"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":684024,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thomas, Judith C. 0000-0001-7883-1419 juthomas@usgs.gov","orcid":"https://orcid.org/0000-0001-7883-1419","contributorId":1468,"corporation":false,"usgs":true,"family":"Thomas","given":"Judith","email":"juthomas@usgs.gov","middleInitial":"C.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":684025,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Keith, Gabrielle L. gkeith@usgs.gov","contributorId":5247,"corporation":false,"usgs":true,"family":"Keith","given":"Gabrielle","email":"gkeith@usgs.gov","middleInitial":"L.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":684026,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70178440,"text":"70178440 - 2016 - Testing fault growth models with low-temperature thermochronology in the northwest Basin and Range, USA","interactions":[],"lastModifiedDate":"2016-11-21T14:36:13","indexId":"70178440","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3524,"text":"Tectonics","active":true,"publicationSubtype":{"id":10}},"title":"Testing fault growth models with low-temperature thermochronology in the northwest Basin and Range, USA","docAbstract":"<p><span>Common fault growth models diverge in predicting how faults accumulate displacement and lengthen through time. A paucity of field-based data documenting the lateral component of fault growth hinders our ability to test these models and fully understand how natural fault systems evolve. Here we outline a framework for using apatite (U-Th)/He thermochronology (AHe) to quantify the along-strike growth of faults. To test our framework, we first use a transect in the normal fault-bounded Jackson Mountains in the Nevada Basin and Range Province, then apply the new framework to the adjacent Pine Forest Range. We combine new and existing cross sections with 18 new and 16 existing AHe cooling ages to determine the spatiotemporal variability in footwall exhumation and evaluate models for fault growth. Three age-elevation transects in the Pine Forest Range show that rapid exhumation began along the range-front fault between approximately 15 and 11 Ma at rates of 0.2–0.4 km/Myr, ultimately exhuming approximately 1.5–5 km. The ages of rapid exhumation identified at each transect lie within data uncertainty, indicating concomitant onset of faulting along strike. We show that even in the case of growth by fault-segment linkage, the fault would achieve its modern length within 3–4 Myr of onset. Comparison with the Jackson Mountains highlights the inadequacies of spatially limited sampling. A constant fault-length growth model is the best explanation for our thermochronology results. We advocate that low-temperature thermochronology can be further utilized to better understand and quantify fault growth with broader implications for seismic hazard assessments and the coevolution of faulting and topography.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2016TC004211","usgsCitation":"Curry, M.A., Barnes, J., and Colgan, J.P., 2016, Testing fault growth models with low-temperature thermochronology in the northwest Basin and Range, USA: Tectonics, v. 35, no. 10, p. 2467-2492, https://doi.org/10.1002/2016TC004211.","productDescription":"26 p.","startPage":"2467","endPage":"2492","ipdsId":"IP-064596","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":331170,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"35","issue":"10","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-10-29","publicationStatus":"PW","scienceBaseUri":"583415b3e4b0070c0abed824","contributors":{"authors":[{"text":"Curry, Magdalena A. E.","contributorId":176959,"corporation":false,"usgs":false,"family":"Curry","given":"Magdalena","email":"","middleInitial":"A. E.","affiliations":[],"preferred":false,"id":654183,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barnes, Jason B.","contributorId":8877,"corporation":false,"usgs":true,"family":"Barnes","given":"Jason B.","affiliations":[],"preferred":false,"id":654184,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Colgan, Joseph P. 0000-0001-6671-1436 jcolgan@usgs.gov","orcid":"https://orcid.org/0000-0001-6671-1436","contributorId":1649,"corporation":false,"usgs":true,"family":"Colgan","given":"Joseph","email":"jcolgan@usgs.gov","middleInitial":"P.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":654185,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70184238,"text":"70184238 - 2016 - Potential interactions among disease, pesticides, water quality and adjacent land cover in amphibian habitats in the United States","interactions":[],"lastModifiedDate":"2018-08-09T12:24:22","indexId":"70184238","displayToPublicDate":"2016-10-01T00:00:00","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":"Potential interactions among disease, pesticides, water quality and adjacent land cover in amphibian habitats in the United States","docAbstract":"<p id=\"sp0070\">To investigate interactions among disease, pesticides, water quality, and adjacent land cover, we collected samples of water, sediment, and frog tissue from 21 sites in 7 States in the United States (US) representing a variety of amphibian habitats. All samples were analyzed for &gt;&nbsp;90 pesticides and pesticide degradates, and water and frogs were screened for the amphibian chytrid fungus <i>Batrachochytrium dendrobatidis</i> (Bd) using molecular methods. Pesticides and pesticide degradates were detected frequently in frog breeding habitats (water and sediment) as well as in frog tissue. Fungicides occurred more frequently in water, sediment, and tissue than was expected based upon their limited use relative to herbicides or insecticides. Pesticide occurrence in water or sediment was not a strong predictor of occurrence in tissue, but pesticide concentrations in tissue were correlated positively to agricultural and urban land, and negatively to forested land in 2-km buffers around the sites. Bd was detected in water at 45% of sites, and on 34% of swabbed frogs. Bd detections in water were not associated with differences in land use around sites, but sites with detections had colder water. Frogs that tested positive for Bd were associated with sites that had higher total fungicide concentrations in water and sediment, but lower insecticide concentrations in sediments relative to frogs that were Bd negative. Bd concentrations on frog swabs were positively correlated to dissolved organic carbon, and total nitrogen and phosphorus, and negatively correlated to pH and water temperature.</p><p id=\"sp0075\">Data were collected from a range of locations and amphibian habitats and represent some of the first field-collected information aimed at understanding the interactions between pesticides, land use, and amphibian disease. These interactions are of particular interest to conservation efforts as many amphibians live in altered habitats and may depend on wetlands embedded in these landscapes to survive.</p>","language":"English","publisher":"Elsevier","publisherLocation":"New York, NY","doi":"10.1016/j.scitotenv.2016.05.062","usgsCitation":"Battaglin, W.A., Smalling, K., Anderson, C.W., Calhoun, D.L., Chestnut, T.E., and Muths, E.L., 2016, Potential interactions among disease, pesticides, water quality and adjacent land cover in amphibian habitats in the United States: Science of the Total Environment, v. 566-567, p. 320-332, https://doi.org/10.1016/j.scitotenv.2016.05.062.","productDescription":"13 p.","startPage":"320","endPage":"332","ipdsId":"IP-073673","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":336833,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Colorado, Georgia, Idaho, Louisiana, Maine, Oregon","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[-119.789798,34.05726],[-119.5667,34.053452],[-119.795938,33.962929],[-119.916216,34.058351],[-119.789798,34.05726]]],[[[-118.524531,32.895488],[-118.573522,32.969183],[-118.369984,32.839273],[-118.524531,32.895488]]],[[[-118.500212,33.449592],[-118.32446,33.348782],[-118.593969,33.467198],[-118.500212,33.449592]]],[[[-119.999168,41.99454],[-120.001014,38.999574],[-114.633013,35.002085],[-114.139534,34.295844],[-114.401352,34.111652],[-114.5403,33.580615],[-114.701732,33.408388],[-114.707896,33.097432],[-114.502871,33.011153],[-114.468971,32.845155],[-114.612697,32.734516],[-117.118868,32.534706],[-117.50565,33.334063],[-118.088896,33.729817],[-118.428407,33.774715],[-118.519514,34.027509],[-119.159554,34.119653],[-119.616862,34.420995],[-120.441975,34.451512],[-120.608355,34.556656],[-120.644311,35.139616],[-120.873046,35.225688],[-120.884757,35.430196],[-121.851967,36.277831],[-121.932508,36.559935],[-121.788278,36.803994],[-121.880167,36.950151],[-122.140578,36.97495],[-122.419113,37.24147],[-122.511983,37.77113],[-122.425942,37.810979],[-122.168449,37.504143],[-122.144396,37.581866],[-122.385908,37.908136],[-122.301804,38.105142],[-122.484411,38.11496],[-122.492474,37.82484],[-122.972378,38.020247],[-123.103706,38.415541],[-123.725367,38.917438],[-123.851714,39.832041],[-124.373599,40.392923],[-124.063076,41.439579],[-124.536073,42.814175],[-124.150267,43.91085],[-123.962887,45.280218],[-123.996766,46.20399],[-123.468743,46.264531],[-123.332335,46.146132],[-123.051064,46.153599],[-122.884478,46.06028],[-122.713309,45.637438],[-122.266701,45.543841],[-121.533106,45.726541],[-121.196556,45.616689],[-120.210754,45.725951],[-118.987129,45.999855],[-116.985882,45.996974],[-117.032351,48.999188],[-116.049193,49.000912],[-116.049153,47.999923],[-115.763424,47.717313],[-115.657681,47.400651],[-115.294785,47.220914],[-114.76689,46.696901],[-114.332887,46.660756],[-114.527096,46.146218],[-114.387166,45.889164],[-114.544692,45.791447],[-114.549508,45.56059],[-114.279217,45.480616],[-114.019315,45.692937],[-113.806729,45.602146],[-113.474573,44.910846],[-113.102138,44.729027],[-112.881769,44.380315],[-112.749011,44.491233],[-112.387389,44.448058],[-112.286187,44.568472],[-111.524006,44.548385],[-111.355768,44.727602],[-111.062729,44.476073],[-111.046689,42.001567],[-119.999168,41.99454]]],[[[-106.190554,40.997607],[-102.124972,41.002338],[-102.04192,37.035083],[-109.045223,36.999084],[-109.050076,41.000659],[-106.190554,40.997607]]],[[[-84.810477,34.987607],[-83.108714,35.000768],[-83.339029,34.683807],[-82.908365,34.485402],[-82.589245,34.000118],[-81.50203,33.015113],[-81.120034,32.153303],[-80.84313,32.024226],[-81.254218,31.55594],[-81.17831,31.52241],[-81.276862,31.254734],[-81.490586,30.984952],[-81.408484,30.977718],[-81.461065,30.753684],[-82.004973,30.791744],[-82.116385,30.367335],[-82.227254,30.561041],[-84.903122,30.751791],[-85.102052,31.184734],[-85.141831,31.839261],[-84.925427,32.221551],[-85.188741,32.889727],[-85.598781,34.944915],[-84.810477,34.987607]]],[[[-88.865067,29.752714],[-88.940346,29.657234],[-88.86972,30.043798],[-88.865067,29.752714]]],[[[-89.486709,29.621003],[-89.681092,29.534487],[-89.02185,29.218162],[-89.162,29.01586],[-89.225865,29.07866],[-89.383814,28.947434],[-89.447472,29.178576],[-89.782149,29.311132],[-89.832898,29.463536],[-90.01251,29.462775],[-90.097678,29.26199],[-90.019772,29.231903],[-90.174273,29.105301],[-90.343293,29.057062],[-90.311523,29.256374],[-90.495299,29.287277],[-90.811473,29.03658],[-91.278792,29.247776],[-91.258226,29.446954],[-91.854677,29.807436],[-92.134347,29.669516],[-91.719102,29.565568],[-91.848665,29.484144],[-93.17693,29.770487],[-93.888821,29.742234],[-93.516407,31.02955],[-94.018664,31.990843],[-94.043088,32.955592],[-91.09693,32.986412],[-91.164397,32.785821],[-91.011275,32.516596],[-91.108808,32.47204],[-90.92117,32.342073],[-91.158026,32.201956],[-91.079108,32.050255],[-91.51581,31.530894],[-91.625118,31.005374],[-89.752642,31.001853],[-89.845926,30.704157],[-89.588854,30.200296],[-89.854533,30.007821],[-89.711158,29.879287],[-89.418465,30.049747],[-89.231178,29.925484],[-89.42421,29.697638],[-89.598068,29.74757],[-89.486709,29.621003]]],[[[-70.353392,43.535405],[-70.733497,43.073288],[-70.981859,43.373862],[-71.076914,45.246912],[-70.82979,45.286941],[-70.684614,45.395071],[-70.688214,45.563981],[-70.390379,45.728539],[-70.259117,45.890755],[-70.290896,46.185838],[-70.057061,46.415036],[-69.997086,46.69523],[-69.22442,47.459686],[-69.066715,47.43024],[-69.0402,47.2451],[-68.893204,47.182974],[-68.292679,47.359476],[-68.061842,47.256451],[-67.790515,47.067921],[-67.803148,45.696127],[-67.476704,45.604157],[-67.489464,45.282653],[-67.390579,45.154114],[-67.145652,45.146667],[-66.986318,44.820657],[-68.049334,44.33073],[-68.22939,44.463496],[-68.191924,44.306675],[-68.339498,44.222893],[-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 \"}}]}","volume":"566-567","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58ba8ebde4b0bcef64f0b93f","contributors":{"authors":[{"text":"Battaglin, William A. 0000-0001-7287-7096 wbattagl@usgs.gov","orcid":"https://orcid.org/0000-0001-7287-7096","contributorId":1527,"corporation":false,"usgs":true,"family":"Battaglin","given":"William","email":"wbattagl@usgs.gov","middleInitial":"A.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":680688,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smalling, Kelly L.  0000-0002-1214-4920 ksmall@usgs.gov","orcid":"https://orcid.org/0000-0002-1214-4920","contributorId":149769,"corporation":false,"usgs":true,"family":"Smalling","given":"Kelly L. ","email":"ksmall@usgs.gov","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":false,"id":680689,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anderson, Chauncey W. 0000-0002-1016-3781 chauncey@usgs.gov","orcid":"https://orcid.org/0000-0002-1016-3781","contributorId":140160,"corporation":false,"usgs":true,"family":"Anderson","given":"Chauncey","email":"chauncey@usgs.gov","middleInitial":"W.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":680690,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Calhoun, Daniel L. 0000-0003-2371-6936 dcalhoun@usgs.gov","orcid":"https://orcid.org/0000-0003-2371-6936","contributorId":1455,"corporation":false,"usgs":true,"family":"Calhoun","given":"Daniel","email":"dcalhoun@usgs.gov","middleInitial":"L.","affiliations":[{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":680691,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chestnut, Tara E. chestnut@usgs.gov","contributorId":3921,"corporation":false,"usgs":true,"family":"Chestnut","given":"Tara","email":"chestnut@usgs.gov","middleInitial":"E.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":680692,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Muths, Erin L. 0000-0002-5498-3132 muthse@usgs.gov","orcid":"https://orcid.org/0000-0002-5498-3132","contributorId":1260,"corporation":false,"usgs":true,"family":"Muths","given":"Erin","email":"muthse@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":680693,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70179646,"text":"70179646 - 2016 - DOM composition and transformation in boreal forest soils: The effects of temperature and organic-horizon decomposition state","interactions":[],"lastModifiedDate":"2017-01-10T11:13:30","indexId":"70179646","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2320,"text":"Journal of Geophysical Research: Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"DOM composition and transformation in boreal forest soils: The effects of temperature and organic-horizon decomposition state","docAbstract":"<p><span>The boreal region stores large amounts of organic carbon (C) in organic-soil horizons, which are vulnerable to destabilization via warming and disturbance. Decomposition of soil organic matter (SOM) contributes to the production and turnover of dissolved organic matter (DOM). While temperature is a primary control on rates of SOM and DOM cycling, little is known about temperature effects on DOM composition in soil leachate. Here we conducted a 30 day incubation to examine the effects of temperature (20 versus 5°C) and SOM decomposition state (moss versus fibric versus amorphous horizons) on DOM composition in organic soils of interior Alaska. We characterized DOM using bulk dissolved organic C (DOC) concentration, chemical fractionation, optical properties, and ultrahigh-resolution mass spectrometry. We observed an increase in DOC concentration and DOM aromaticity in the 20°C treatment compared to the 5°C treatment. Leachate from fibric horizons had higher DOC concentration than shallow moss or deep amorphous horizons. We also observed chemical shifts in DOM leachate over time, including increases in hydrophobic organic acids, polyphenols, and condensed aromatics and decreases in low-molecular weight hydrophilic compounds and aliphatics. We compared ultrahigh-resolution mass spectrometry and optical data and observed strong correlations between polyphenols, condensed aromatics, SUVA</span><sub>254</sub><span>, and humic-like fluorescence intensities. These findings suggest that biolabile DOM was preferentially mineralized, and the magnitude of this transformation was determined by kinetics (i.e., temperature) and substrate quality (i.e., soil horizon). With future warming, our findings indicate that organic soils may release higher concentrations of aromatic DOM to aquatic ecosystems.</span></p>","language":"English","publisher":"AGU Publications","doi":"10.1002/2016JG003431","usgsCitation":"O’Donnell, J.A., Aiken, G.R., Butler, K.D., Guillemette, F., Podgorski, D.C., and Spencer, R., 2016, DOM composition and transformation in boreal forest soils: The effects of temperature and organic-horizon decomposition state: Journal of Geophysical Research: Biogeosciences, v. 121, no. 10, p. 2727-2744, https://doi.org/10.1002/2016JG003431.","productDescription":"18 p.","startPage":"2727","endPage":"2744","ipdsId":"IP-077855","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":470533,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2016jg003431","text":"Publisher Index Page"},{"id":333013,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"121","issue":"10","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-10-29","publicationStatus":"PW","scienceBaseUri":"58760116e4b04eac8e0746e1","contributors":{"authors":[{"text":"O’Donnell, Jonathan A.","contributorId":178151,"corporation":false,"usgs":false,"family":"O’Donnell","given":"Jonathan","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":658042,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aiken, George R. 0000-0001-8454-0984 graiken@usgs.gov","orcid":"https://orcid.org/0000-0001-8454-0984","contributorId":1322,"corporation":false,"usgs":true,"family":"Aiken","given":"George","email":"graiken@usgs.gov","middleInitial":"R.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":658041,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Butler, Kenna D. kebutler@usgs.gov","contributorId":3283,"corporation":false,"usgs":true,"family":"Butler","given":"Kenna","email":"kebutler@usgs.gov","middleInitial":"D.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":false,"id":658043,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Guillemette, Francois","contributorId":178152,"corporation":false,"usgs":false,"family":"Guillemette","given":"Francois","affiliations":[],"preferred":false,"id":658044,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Podgorski, David C.","contributorId":178153,"corporation":false,"usgs":false,"family":"Podgorski","given":"David","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":658045,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Spencer, Robert G. M.","contributorId":139731,"corporation":false,"usgs":false,"family":"Spencer","given":"Robert G. M.","affiliations":[{"id":12894,"text":"Department of Land, Air, and Water Resources, University of California, One Shields Avenue, Davis, CA, 95616, USA","active":true,"usgs":false}],"preferred":false,"id":658046,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70178430,"text":"70178430 - 2016 - Geology, selected geophysics, and hydrogeology of the White River and parts of the Great Salt Lake Desert regional groundwater flow systems, Utah and Nevada","interactions":[],"lastModifiedDate":"2017-04-19T11:49:02","indexId":"70178430","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Geology, selected geophysics, and hydrogeology of the White River and parts of the Great Salt Lake Desert regional groundwater flow systems, Utah and Nevada","docAbstract":"The east-central Great Basin near the Utah-Nevada border contains two great \ngroundwater flow systems.  The first, the White River regional groundwater \nflow system, consists of a string of hydraulically connected hydrographic basins \nin Nevada spanning about 270 miles from north to south.  The northernmost \nbasin is Long Valley and the southernmost basin is the Black Mountain area, a \nvalley bordering the Colorado River.  The general regional groundwater flow \ndirection is north to south. The second flow system, the Great Salt Lake Desert \nregional groundwater flow system, consists of hydrographic basins that straddle\nthe Utah-Nevada border, with a length of about 150 miles from north to south.  \nThe general regional groundwater flow direction is from south to north towards \nthe Great Salt Lake Desert.\n\nFor 15 years with support from the Southern Nevada Water Authority (SNWA), \nhydrologists, geologists, and geophysicists studied the basin connections and \nthe groundwater resources in these and adjacent flow systems over an area of \nabout 25,000 square miles. A major first part of the SNWA study was \nconstructing a 3-dimensional digital hydrogeologic framework based on \ngeologic maps and cross sections at 1:250,000 scale. This framework \ndocuments the presence of three major aquifers: (1) Paleozoic carbonate \nrocks, (2) Eocene to Miocene volcanic rocks, and (3) Miocene to Holocene \nbasin-fill sediments, as well as confining units that constrain flow. We \ninterpret that movement of most groundwater through and across basins is by \nfracture-dominated flow along faults/fractures, yet in most places flow is \nprevented or retarded across faults, so mapping structures gives a first \napproximation to conduits and barriers to flow.\n\nThe most important structures by far are high-angle normal faults of the \nbasin-range episode of east-west extensional deformation. This event \nbegan at about 20 Ma, although most deformation and the formation of the \npresent topography took place between 10 Ma and present.  This topography \nconsists of north-trending basins (mostly grabens) that alternate with north-\ntrending ranges (mostly horsts); erosion of the ranges filled the basins with \nclastic alluvial basin-fill deposits.\n\nGeophysics provides data on the third dimension (cross sections) of the \nhydrogeologic framework.  Audiomagnetotelluric profiles and gravity \ninversion located faults and enabled us to estimate thicknesses of basin-fill \ndeposits. To this framework, hydrologic studies addressed precipitation, \nsurface water, and springs, as well as groundwater levels, volumes, \ngeochemistry, water budgets, and monitoring. At nearly the same time as \nour study, the Utah Geological Survey (UGS) and U.S. Geological Survey \n(USGS) addressed the same issues in many of the same areas, and publication \nof the efforts by all three agencies reveals a surprising similarity of conclusions, \nwith some critical exceptions, which therefore demonstrates the great value of \nmany scientists independently studying the same complex scientific problem. \nThe differences in conclusions include directions and volumes of some ground-\nwater flow paths, such as one proposed by the USGS of unlikely groundwater \nflow from Steptoe Valley to southern Snake Valley, and another proposed by the \nUGS of unlikely significant groundwater recharge flow from the Snake Range to \nthe Fish Springs complex.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Resources and Geo- logy of Utah's West Desert","language":"English","publisher":"Utah Geologic Association","usgsCitation":"Rowley, P.D., Dixon, G.L., Watrus, J.M., Burns, A.G., Mankinen, E.A., McKee, E.H., Pari, K.T., Ekren, E.B., and Patrick, W.G., 2016, Geology, selected geophysics, and hydrogeology of the White River and parts of the Great Salt Lake Desert regional groundwater flow systems, Utah and Nevada, chap. <i>of</i> Resources and Geo- logy of Utah's West Desert, v. 45, p. 167-200.","productDescription":"34 p. ","startPage":"167","endPage":"200","ipdsId":"IP-073283","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":339955,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":339954,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.mapstore.utah.gov/uga45.html"}],"country":"United 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 \"}}]}","volume":"45","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58f877b8e4b0b7ea54521c18","contributors":{"editors":[{"text":"Comer, John B.","contributorId":147613,"corporation":false,"usgs":false,"family":"Comer","given":"John","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":692018,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Inkenbrandt, Paul C.","contributorId":191156,"corporation":false,"usgs":false,"family":"Inkenbrandt","given":"Paul","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":692019,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Krahulec, K.A.","contributorId":42429,"corporation":false,"usgs":true,"family":"Krahulec","given":"K.A.","affiliations":[],"preferred":false,"id":692020,"contributorType":{"id":2,"text":"Editors"},"rank":3},{"text":"Pinnell, Michael L.","contributorId":191157,"corporation":false,"usgs":false,"family":"Pinnell","given":"Michael","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":692021,"contributorType":{"id":2,"text":"Editors"},"rank":4}],"authors":[{"text":"Rowley, Peter D.","contributorId":27435,"corporation":false,"usgs":true,"family":"Rowley","given":"Peter","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":673660,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dixon, Gary L.","contributorId":23571,"corporation":false,"usgs":true,"family":"Dixon","given":"Gary","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":673661,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Watrus, James M.","contributorId":184152,"corporation":false,"usgs":false,"family":"Watrus","given":"James","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":673662,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Burns, Andrews G.","contributorId":184154,"corporation":false,"usgs":false,"family":"Burns","given":"Andrews","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":673663,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mankinen, Edward A. 0000-0001-7496-2681 emank@usgs.gov","orcid":"https://orcid.org/0000-0001-7496-2681","contributorId":1054,"corporation":false,"usgs":true,"family":"Mankinen","given":"Edward","email":"emank@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":673664,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McKee, Edwin H. mckee@usgs.gov","contributorId":3728,"corporation":false,"usgs":true,"family":"McKee","given":"Edwin","email":"mckee@usgs.gov","middleInitial":"H.","affiliations":[],"preferred":true,"id":673665,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pari, Keith T.","contributorId":184155,"corporation":false,"usgs":false,"family":"Pari","given":"Keith","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":673666,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ekren, E. Bartlett","contributorId":47644,"corporation":false,"usgs":true,"family":"Ekren","given":"E.","email":"","middleInitial":"Bartlett","affiliations":[],"preferred":false,"id":673667,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Patrick, William G.","contributorId":184151,"corporation":false,"usgs":false,"family":"Patrick","given":"William","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":673668,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70182777,"text":"70182777 - 2016 - Inferring invasive species abundance using removal data from management actions","interactions":[],"lastModifiedDate":"2017-03-01T12:32:34","indexId":"70182777","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Inferring invasive species abundance using removal data from management actions","docAbstract":"<p><span>Evaluation of the progress of management programs for invasive species is crucial for demonstrating impacts to stakeholders and strategic planning of resource allocation. Estimates of abundance before and after management activities can serve as a useful metric of population management programs. However, many methods of estimating population size are too labor intensive and costly to implement, posing restrictive levels of burden on operational programs. Removal models are a reliable method for estimating abundance before and after management using data from the removal activities exclusively, thus requiring no work in addition to management. We developed a Bayesian hierarchical model to estimate abundance from removal data accounting for varying levels of effort, and used simulations to assess the conditions under which reliable population estimates are obtained. We applied this model to estimate site-specific abundance of an invasive species, feral swine (</span><i>Sus scrofa</i><span>), using removal data from aerial gunning in 59 site/time-frame combinations (480–19,600 acres) throughout Oklahoma and Texas, USA. Simulations showed that abundance estimates were generally accurate when effective removal rates (removal rate accounting for total effort) were above 0.40. However, when abundances were small (&lt;50) the effective removal rate needed to accurately estimates abundances was considerably higher (0.70). Based on our post-validation method, 78% of our site/time frame estimates were accurate. To use this modeling framework it is important to have multiple removals (more than three) within a time frame during which demographic changes are minimized (i.e., a closed population; ≤3&nbsp;months for feral swine). Our results show that the probability of accurately estimating abundance from this model improves with increased sampling effort (8+ flight hours across the 3-month window is best) and increased removal rate. Based on the inverse relationship between inaccurate abundances and inaccurate removal rates, we suggest auxiliary information that could be collected and included in the model as covariates (e.g., habitat effects, differences between pilots) to improve accuracy of removal rates and hence abundance estimates.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/eap.1383","usgsCitation":"Davis, A.J., Hooten, M., Miller, R.S., Farnsworth, M.L., Lewis, J., Moxcey, M., and Pepin, K., 2016, Inferring invasive species abundance using removal data from management actions: Ecological Applications, v. 26, no. 7, p. 2339-2346, https://doi.org/10.1002/eap.1383.","productDescription":"8 p.","startPage":"2339","endPage":"2346","ipdsId":"IP-067270","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":336748,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"26","issue":"7","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-09-19","publicationStatus":"PW","scienceBaseUri":"58b7eba6e4b01ccd5500bb01","contributors":{"authors":[{"text":"Davis, Amy J.","contributorId":149854,"corporation":false,"usgs":false,"family":"Davis","given":"Amy","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":680416,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hooten, Mevin 0000-0002-1614-723X mhooten@usgs.gov","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":2958,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","email":"mhooten@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false}],"preferred":true,"id":673716,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miller, Ryan S.","contributorId":49005,"corporation":false,"usgs":false,"family":"Miller","given":"Ryan","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":680417,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Farnsworth, Matthew L.","contributorId":56473,"corporation":false,"usgs":false,"family":"Farnsworth","given":"Matthew","email":"","middleInitial":"L.","affiliations":[{"id":12434,"text":"USDA, Wildlife Services, National Wildlife Research Center","active":true,"usgs":false}],"preferred":false,"id":680418,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lewis, Jesse S.","contributorId":147540,"corporation":false,"usgs":false,"family":"Lewis","given":"Jesse S.","affiliations":[{"id":12556,"text":"Florida Fish and Wildlife Conservation Commission","active":true,"usgs":false}],"preferred":false,"id":680419,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Moxcey, Michael","contributorId":187442,"corporation":false,"usgs":false,"family":"Moxcey","given":"Michael","email":"","affiliations":[],"preferred":false,"id":680420,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pepin, Kim M. 0000-0002-9931-8312","orcid":"https://orcid.org/0000-0002-9931-8312","contributorId":187441,"corporation":false,"usgs":false,"family":"Pepin","given":"Kim M.","affiliations":[],"preferred":false,"id":680421,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70182245,"text":"70182245 - 2016 - Species traits and catchment-scale habitat factors influence the occurrence of freshwater mussel populations and assemblages","interactions":[],"lastModifiedDate":"2017-02-22T15:58:24","indexId":"70182245","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1696,"text":"Freshwater Biology","active":true,"publicationSubtype":{"id":10}},"title":"Species traits and catchment-scale habitat factors influence the occurrence of freshwater mussel populations and assemblages","docAbstract":"<ol id=\"fwb12807-list-0001\" class=\"o-list--numbered o-list--paragraph\"><li>Conservation of freshwater unionid mussels presents unique challenges due to their distinctive life cycle, cryptic occurrence and imperilled status. Relevant ecological information is urgently needed to guide their management and conservation.</li><li>We adopted a modelling approach, which is a novel application to freshwater mussels to enhance inference on rare species, by borrowing data among species in a hierarchical framework to conduct the most comprehensive occurrence analysis for freshwater mussels to date. We incorporated imperfect detection to more accurately examine effects of biotic and abiotic factors at multiple scales on the occurrence of 14 mussel species and the entire assemblage of the Tar River Basin of North Carolina, U.S.A.</li><li>The single assemblage estimate of detection probability for all species was 0.42 (95% CI, 0.36–0.47) with no species- or site-specific detection effects identified. We empirically observed 15 mussel species in the basin but estimated total species richness at 21 (95% CI, 16–24) when accounting for imperfect detection.</li><li>Mean occurrence probability among species ranged from 0.04 (95% CI, 0.01–0.16) for <i>Alasmidonta undulata,</i> an undescribed <i>Lampsilis</i> sp.<i>,</i> and <i>Strophitus undulatus</i> to 0.67 (95% CI, 0.42–0.86) for <i>Elliptio icterina</i>. Median occurrence probability among sites was &lt;0.30 for all species with the exception of <i>E.&nbsp;icterina</i>. Site occurrence probability generally related to mussel conservation status, with reduced occurrence for endangered and threatened species.</li><li>Catchment-scale abiotic variables (stream power, agricultural land use) and species traits (brood time, host specificity, tribe) influenced the occurrence of mussel assemblages more than reach- or microhabitat-scale features.</li><li>Our findings reflect the complexity of mussel ecology and indicate that habitat restoration alone may not be adequate for mussel conservation. Catchment-scale management can benefit an entire assemblage, but species-specific strategies may be necessary for successful conservation. The hierarchical multispecies modelling approach revealed findings that could not be elucidated by other means, and the approach may be applied more broadly to other river basins and regions. Accurate measures of assemblage dynamics, such as occurrence and species richness, are required to create management plans for effective conservation.</li></ol>","language":"English","publisher":"Wiley","doi":"10.1111/fwb.12807","usgsCitation":"Pandolfo, T.J., Kwak, T.J., Cope, W., Heise, R.J., Nichols, R.B., and Pacifici, K., 2016, Species traits and catchment-scale habitat factors influence the occurrence of freshwater mussel populations and assemblages: Freshwater Biology, v. 61, no. 10, p. 1671-1684, https://doi.org/10.1111/fwb.12807.","productDescription":"14 p.","startPage":"1671","endPage":"1684","ipdsId":"IP-070554","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":335999,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"61","issue":"10","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2016-08-05","publicationStatus":"PW","scienceBaseUri":"58aeb13ce4b01ccd54f9ee1c","chorus":{"doi":"10.1111/fwb.12807","url":"http://dx.doi.org/10.1111/fwb.12807","publisher":"Wiley-Blackwell","authors":"Pandolfo Tamara J., Kwak Thomas J., Cope W. Gregory, Heise Ryan J., Nichols Robert B., Pacifici Krishna","journalName":"Freshwater Biology","publicationDate":"8/5/2016"},"contributors":{"authors":[{"text":"Pandolfo, Tamara J.","contributorId":146388,"corporation":false,"usgs":false,"family":"Pandolfo","given":"Tamara","email":"","middleInitial":"J.","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":670589,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kwak, Thomas J. 0000-0002-0616-137X tkwak@usgs.gov","orcid":"https://orcid.org/0000-0002-0616-137X","contributorId":834,"corporation":false,"usgs":true,"family":"Kwak","given":"Thomas","email":"tkwak@usgs.gov","middleInitial":"J.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":670206,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cope, W. Gregory","contributorId":70353,"corporation":false,"usgs":true,"family":"Cope","given":"W. Gregory","affiliations":[],"preferred":false,"id":670590,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Heise, Ryan J.","contributorId":145789,"corporation":false,"usgs":false,"family":"Heise","given":"Ryan","email":"","middleInitial":"J.","affiliations":[{"id":16149,"text":"North Carolina Wildlife Resources Commission, 1003 Consolidated Rd., Elizabeth City, NC 27909","active":true,"usgs":false}],"preferred":false,"id":670591,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nichols, Robert B.","contributorId":182112,"corporation":false,"usgs":false,"family":"Nichols","given":"Robert","email":"","middleInitial":"B.","affiliations":[{"id":35598,"text":"North Carolina Wildlife Resources Commission ","active":true,"usgs":false}],"preferred":false,"id":670592,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pacifici, Krishna","contributorId":26564,"corporation":false,"usgs":false,"family":"Pacifici","given":"Krishna","email":"","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":670593,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70178623,"text":"70178623 - 2016 - First direct evidence of long-distance seasonal movements and hibernation in a migratory bat","interactions":[],"lastModifiedDate":"2017-04-27T10:16:44","indexId":"70178623","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"First direct evidence of long-distance seasonal movements and hibernation in a migratory bat","docAbstract":"<p><span>Understanding of migration in small bats has been constrained by limitations of techniques that were labor-intensive, provided coarse levels of resolution, or were limited to population-level inferences. Knowledge of movements and behaviors of individual bats have been unknowable because of limitations in size of tracking devices and methods to attach them for long periods. We used sutures to attach miniature global positioning system (GPS) tags and data loggers that recorded light levels, activity, and temperature to male hoary bats (</span><i>Lasiurus cinereus</i><span>). Results from recovered GPS tags illustrated profound differences among movement patterns by individuals, including one that completed a &gt;1000 km round-trip journey during October 2014. Data loggers allowed us to record sub-hourly patterns of activity and torpor use, in one case over a period of 224 days that spanned an entire winter. In this latter bat, we documented 5 torpor bouts that lasted ≥16 days and a flightless period that lasted 40 nights. These first uses of miniature tags on small bats allowed us to discover that male hoary bats can make multi-directional movements during the migratory season and sometimes hibernate for an entire winter.</span></p>","language":"English","publisher":"Nature","doi":"10.1038/srep34585","usgsCitation":"Weller, T.J., Castle, K.T., Liechti, F., Hein, C.D., Schirmacher, M.R., and Cryan, P.M., 2016, First direct evidence of long-distance seasonal movements and hibernation in a migratory bat: Scientific Reports, v. 6, Article number 34585; 7 p., https://doi.org/10.1038/srep34585.","productDescription":"Article number 34585; 7 p.","ipdsId":"IP-077969","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":470528,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/srep34585","text":"Publisher Index Page"},{"id":331386,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","noUsgsAuthors":false,"publicationDate":"2016-10-04","publicationStatus":"PW","scienceBaseUri":"584144dfe4b04fc80e5073a5","contributors":{"authors":[{"text":"Weller, Theodore J.","contributorId":105961,"corporation":false,"usgs":false,"family":"Weller","given":"Theodore","email":"","middleInitial":"J.","affiliations":[{"id":13261,"text":"USDA Forest Service, Pacific Southwest Research Station, Davis, California","active":true,"usgs":false}],"preferred":false,"id":654600,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Castle, Kevin T.","contributorId":90616,"corporation":false,"usgs":true,"family":"Castle","given":"Kevin","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":654601,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Liechti, Felix","contributorId":177094,"corporation":false,"usgs":false,"family":"Liechti","given":"Felix","email":"","affiliations":[],"preferred":false,"id":654602,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hein, Cris D.","contributorId":73910,"corporation":false,"usgs":false,"family":"Hein","given":"Cris","email":"","middleInitial":"D.","affiliations":[{"id":12591,"text":"Bat Conservation International","active":true,"usgs":false}],"preferred":false,"id":654603,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schirmacher, Michael R.","contributorId":76635,"corporation":false,"usgs":false,"family":"Schirmacher","given":"Michael","email":"","middleInitial":"R.","affiliations":[{"id":12591,"text":"Bat Conservation International","active":true,"usgs":false}],"preferred":false,"id":654604,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cryan, Paul M. 0000-0002-2915-8894 cryanp@usgs.gov","orcid":"https://orcid.org/0000-0002-2915-8894","contributorId":2356,"corporation":false,"usgs":true,"family":"Cryan","given":"Paul","email":"cryanp@usgs.gov","middleInitial":"M.","affiliations":[{"id":547,"text":"Rocky Mountain Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":654605,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70181012,"text":"70181012 - 2016 - Use of mineral/solution equilibrium calculations to assess the potential for carnotite precipitation from groundwater in the Texas Panhandle, USA","interactions":[],"lastModifiedDate":"2018-08-06T13:08:08","indexId":"70181012","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":835,"text":"Applied Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Use of mineral/solution equilibrium calculations to assess the potential for carnotite precipitation from groundwater in the Texas Panhandle, USA","docAbstract":"<p><span>This study investigated the potential for the uranium mineral carnotite (K</span><sub>2</sub><span>(UO</span><sub>2</sub><span>)</span><sub>2</sub><span>(VO</span><sub>4</sub><span>)</span><sub>2</sub><span>·3H</span><sub>2</sub><span>O) to precipitate from evaporating groundwater in the Texas Panhandle region of the United States. The evolution of groundwater chemistry during evaporation was modeled with the USGS geochemical code PHREEQC using water-quality data from 100 groundwater wells downloaded from the USGS National Water Information System (NWIS) database. While most modeled groundwater compositions precipitated calcite upon evaporation, not all groundwater became saturated with respect to carnotite with the system open to CO</span><sub>2</sub><span>. Thus, the formation of calcite is not a necessary condition for carnotite to form. Rather, the determining factor in achieving carnotite saturation was the evolution of groundwater chemistry during evaporation following calcite precipitation. Modeling in this study showed that if the initial major-ion groundwater composition was dominated by calcium-magnesium-sulfate (&gt;70 precent Ca&nbsp;+&nbsp;Mg and &gt;50 percent SO</span><sub>4</sub><span>&nbsp;+&nbsp;Cl) or calcium-magnesium-bicarbonate (&gt;70 percent Ca&nbsp;+&nbsp;Mg and &lt;70 percent HCO</span><sub>3</sub><span>&nbsp;+&nbsp;CO</span><sub>3</sub><span>) and following the precipitation of calcite, the concentration of calcium was greater than the carbonate alkalinity (2</span><i>m</i><span>Ca</span><sup>+2</sup><span>&nbsp;&gt;&nbsp;</span><i>m</i><span>HCO</span><sub>3</sub><sup>−</sup><span>&nbsp;+&nbsp;2</span><i>m</i><span>CO</span><sub>3</sub><sup>−2</sup><span>) carnotite saturation was achieved. If, however, the initial major-ion groundwater composition is sodium-bicarbonate (varying amounts of Na, 40–100 percent Na), calcium-sodium-sulfate, or calcium-magnesium-bicarbonate composition (&gt;70 percent HCO</span><sub>3</sub><span>&nbsp;+&nbsp;CO</span><sub>3</sub><span>) and following the precipitation of calcite, the concentration of calcium was less than the carbonate alkalinity (2</span><i>m</i><span>Ca</span><sup>+2</sup><span>&nbsp;&lt;&nbsp;</span><i>m</i><span>HCO</span><sub>3</sub><sup>-</sup><span>&nbsp;+&nbsp;2</span><i>m</i><span>CO</span><sub>3</sub><sup>−2</sup><span>) carnotite saturation was not achieved. In systems open to CO</span><sub>2,</sub><span> carnotite saturation occurred in most samples in evaporation amounts ranging from 95 percent to 99 percent with the partial pressure of CO</span><sub>2</sub><span> ranging from 10</span><sup>−3.5</sup><span> to 10</span><sup>−2.5</sup><span>&nbsp;atm. Carnotite saturation occurred in a few samples in evaporation amounts ranging from 98 percent to 99 percent with the partial pressure of CO</span><sub>2</sub><span> equal to 10</span><sup>−2.0</sup><span>&nbsp;atm. Carnotite saturation did not occur in any groundwater with the system closed to CO</span><sub>2</sub><span>.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.apgeochem.2016.08.004","usgsCitation":"Ranalli, A.J., and Yager, D.B., 2016, Use of mineral/solution equilibrium calculations to assess the potential for carnotite precipitation from groundwater in the Texas Panhandle, USA: Applied Geochemistry, v. 73, p. 118-131, https://doi.org/10.1016/j.apgeochem.2016.08.004.","productDescription":"14 p.","startPage":"118","endPage":"131","ipdsId":"IP-069663","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":335173,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -103.07373046875,\n              33.925129700072\n            ],\n            [\n              -103.07373046875,\n              36.50963615733049\n            ],\n            [\n              -99.97558593749999,\n              36.50963615733049\n            ],\n            [\n              -99.97558593749999,\n              33.925129700072\n            ],\n            [\n              -103.07373046875,\n              33.925129700072\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"73","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"589fff23e4b099f50d3e0450","contributors":{"authors":[{"text":"Ranalli, Anthony J. tranalli@usgs.gov","contributorId":1195,"corporation":false,"usgs":true,"family":"Ranalli","given":"Anthony","email":"tranalli@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":true,"id":663275,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yager, Douglas B. 0000-0001-5074-4022 dyager@usgs.gov","orcid":"https://orcid.org/0000-0001-5074-4022","contributorId":798,"corporation":false,"usgs":true,"family":"Yager","given":"Douglas","email":"dyager@usgs.gov","middleInitial":"B.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":663274,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70182773,"text":"70182773 - 2016 - The timing of compositionally-zoned magma reservoirs and mafic 'priming' weeks before the 1912 Novarupta-Katmai rhyolite eruption","interactions":[],"lastModifiedDate":"2017-03-01T14:43:11","indexId":"70182773","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1427,"text":"Earth and Planetary Science Letters","active":true,"publicationSubtype":{"id":10}},"title":"The timing of compositionally-zoned magma reservoirs and mafic 'priming' weeks before the 1912 Novarupta-Katmai rhyolite eruption","docAbstract":"The June 6, 1912 eruption of more than 13 km3 of dense rock equivalent (DRE) magma at Novarupta vent, Alaska was the largest of the 20th century. It ejected >7 km3 of rhyolite, ~1.3 km3 of andesite and ~4.6 km3 of dacite. Early ideas about the origin of pyroclastic flows and magmatic differentiation (e.g., compositional zonation of reservoirs) were shaped by this eruption. Despite being well studied, the timing of events that led to the chemically and mineralogically zoned magma reservoir remain poorly known. Here we provide new insights using the textures and chemical compositions of plagioclase and orthopyroxene crystals and by reevaluating previous U-Th isotope data. Compositional zoning of the magma reservoir likely developed a few thousand years before the eruption by several additions of mafic magma below an extant silicic reservoir. Melt compositions calculated from Sr contents in plagioclase fill the compositional gap between 68 and 76% SiO2 in whole pumice clasts, consistent with uninterrupted crystal growth from a continuum of liquids. Thus, our findings support a general model in which large volumes of crystal-poor rhyolite are related to intermediate magmas through gradual separation of melt from crystal-rich mush. The rhyolite is incubated by, but not mixed with, episodic recharge pulses of mafic magma that interact thermochemically with the mush and intermediate magmas. Hot, Mg-, Ca-, and Al-rich mafic magma intruded into, and mixed with, deeper parts of the reservoir (andesite and dacite) multiple times. Modeling the relaxation of the Fe-Mg concentrations in orthopyroxene and Mg in plagioclase rims indicates that the final recharge event occurred just weeks prior to the eruption. Rapid addition of mass, volatiles, and heat from the recharge magma, perhaps aided by partial melting of cumulate mush below the andesite and dacite, pressurized the reservoir and likely propelled a ~10 km lateral dike that allowed the overlying rhyolite to reach the surface.","language":"English","publisher":"Elsevier","doi":"10.1016/j.epsl.2016.07.015","usgsCitation":"Singer, B.S., Costa, F., Herrin, J.S., Hildreth, W., and Fierstein, J., 2016, The timing of compositionally-zoned magma reservoirs and mafic 'priming' weeks before the 1912 Novarupta-Katmai rhyolite eruption: Earth and Planetary Science Letters, v. 451, p. 125-137, https://doi.org/10.1016/j.epsl.2016.07.015.","productDescription":"13 p. ","startPage":"125","endPage":"137","ipdsId":"IP-078234","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":470525,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.epsl.2016.07.015","text":"Publisher Index Page"},{"id":336778,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"451","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58b7eba6e4b01ccd5500bb03","contributors":{"authors":[{"text":"Singer, Brad S.","contributorId":184168,"corporation":false,"usgs":false,"family":"Singer","given":"Brad","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":673703,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Costa, Fidel","contributorId":184169,"corporation":false,"usgs":false,"family":"Costa","given":"Fidel","email":"","affiliations":[],"preferred":false,"id":673704,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Herrin, Jason S.","contributorId":184170,"corporation":false,"usgs":false,"family":"Herrin","given":"Jason","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":673705,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hildreth, Wes 0000-0002-7925-4251 hildreth@usgs.gov","orcid":"https://orcid.org/0000-0002-7925-4251","contributorId":2221,"corporation":false,"usgs":true,"family":"Hildreth","given":"Wes","email":"hildreth@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":680460,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fierstein, Judith 0000-0001-8024-1426 jfierstn@usgs.gov","orcid":"https://orcid.org/0000-0001-8024-1426","contributorId":147000,"corporation":false,"usgs":true,"family":"Fierstein","given":"Judith","email":"jfierstn@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":673707,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70179072,"text":"70179072 - 2016 - A case study on evaluating impacts of potential climate change on groundwater resources: Groundwater recharge in the Upper Colorado River Basin","interactions":[],"lastModifiedDate":"2016-12-20T11:43:51","indexId":"70179072","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"A case study on evaluating impacts of potential climate change on groundwater resources: Groundwater recharge in the Upper Colorado River Basin","docAbstract":"An investigation of the change in groundwater recharge in response to potential climate change\nwas performed for the UCRB using the SWB groundwater recharge model and downscaled\nclimate data from the CMIP5 multi-model dataset. Climate projections from 97 downscaled\nCMIP5 datasets were assumed to be equally likely and recharge simulation results were\ncombined. Results for the UCRB suggest that projected increases in actual ET from higher\ntemperatures may be offset by increases in precipitation, resulting in increased groundwater\nrecharge for many areas in the basin in future time periods.","language":"English","publisher":"Bureau of Reclamation","collaboration":"Bureau of Reclamation","usgsCitation":"Tillman, F.D., Gangopadhyay, S., and Pruitt, T., 2016, A case study on evaluating impacts of potential climate change on groundwater resources: Groundwater recharge in the Upper Colorado River Basin, ii., 20 p.","productDescription":"ii., 20 p.","ipdsId":"IP-066612","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":332339,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":332146,"type":{"id":15,"text":"Index Page"},"url":"https://www.usbr.gov/watersmart/wcra/docs/techmemoclimatechangeongroundwaterresources.pdf"}],"country":"United States","state":"Arizona, Colorado, New Mexico, Utah","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -112.2802734375,\n              37.142803443716836\n            ],\n            [\n              -110.3466796875,\n              39.50404070558415\n            ],\n            [\n              -107.81982421874999,\n              40.111688665595956\n            ],\n            [\n              -105.556640625,\n              39.8928799002948\n            ],\n            [\n              -106.01806640624999,\n              37.03763967977139\n            ],\n            [\n              -108.25927734375,\n              36.50963615733049\n            ],\n            [\n              -112.30224609374999,\n              36.70365959719456\n            ],\n            [\n              -112.2802734375,\n              37.142803443716836\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"585a51bee4b01224f329b5e7","contributors":{"authors":[{"text":"Tillman, Fred D. 0000-0002-2922-402X ftillman@usgs.gov","orcid":"https://orcid.org/0000-0002-2922-402X","contributorId":147809,"corporation":false,"usgs":true,"family":"Tillman","given":"Fred","email":"ftillman@usgs.gov","middleInitial":"D.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":655926,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":655927,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":655928,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70188067,"text":"70188067 - 2016 - Forecasting climate change impacts on plant populations over large spatial extents","interactions":[],"lastModifiedDate":"2018-03-08T12:59:33","indexId":"70188067","displayToPublicDate":"2016-10-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Forecasting climate change impacts on plant populations over large spatial extents","docAbstract":"<p><span>Plant population models are powerful tools for predicting climate change impacts in one location, but are difficult to apply at landscape scales. We overcome this limitation by taking advantage of two recent advances: remotely sensed, species-specific estimates of plant cover and statistical models developed for spatiotemporal dynamics of animal populations. Using computationally efficient model reparameterizations, we fit a spatiotemporal population model to a 28-year time series of sagebrush (</span><i>Artemisia</i><span> spp.) percent cover over a 2.5&nbsp;×&nbsp;5&nbsp;km landscape in southwestern Wyoming while formally accounting for spatial autocorrelation. We include interannual variation in precipitation and temperature as covariates in the model to investigate how climate affects the cover of sagebrush. We then use the model to forecast the future abundance of sagebrush at the landscape scale under projected climate change, generating spatially explicit estimates of sagebrush population trajectories that have, until now, been impossible to produce at this scale. Our broadscale and long-term predictions are rooted in small-scale and short-term population dynamics and provide an alternative to predictions offered by species distribution models that do not include population dynamics. Our approach, which combines several existing techniques in a novel way, demonstrates the use of remote sensing data to model population responses to environmental change that play out at spatial scales far greater than the traditional field study plot.</span></p>","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.1525","usgsCitation":"Tredennick, A.T., Hooten, M., Aldridge, C.L., Homer, C.G., Kleinhesselink, A.R., and Adler, P.B., 2016, Forecasting climate change impacts on plant populations over large spatial extents: Ecosphere, v. 7, no. 10, e01525; 16 p., https://doi.org/10.1002/ecs2.1525.","productDescription":"e01525; 16 p.","ipdsId":"IP-071731","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":470538,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.1525","text":"Publisher Index Page"},{"id":341852,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","volume":"7","issue":"10","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-10-24","publicationStatus":"PW","scienceBaseUri":"592e84b9e4b092b266f10d30","contributors":{"authors":[{"text":"Tredennick, Andrew T.","contributorId":152688,"corporation":false,"usgs":false,"family":"Tredennick","given":"Andrew","email":"","middleInitial":"T.","affiliations":[{"id":18962,"text":"Dept. of Wildland Resources and the Ecology Center, Utah State University, Logan, UT","active":true,"usgs":false}],"preferred":false,"id":696411,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hooten, Mevin 0000-0002-1614-723X mhooten@usgs.gov","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":2958,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","email":"mhooten@usgs.gov","affiliations":[{"id":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":696382,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Aldridge, Cameron L. 0000-0003-3926-6941 aldridgec@usgs.gov","orcid":"https://orcid.org/0000-0003-3926-6941","contributorId":191773,"corporation":false,"usgs":true,"family":"Aldridge","given":"Cameron","email":"aldridgec@usgs.gov","middleInitial":"L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":696412,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Homer, Collin G. 0000-0003-4755-8135 homer@usgs.gov","orcid":"https://orcid.org/0000-0003-4755-8135","contributorId":2262,"corporation":false,"usgs":true,"family":"Homer","given":"Collin","email":"homer@usgs.gov","middleInitial":"G.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":696413,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kleinhesselink, Andrew R.","contributorId":192387,"corporation":false,"usgs":false,"family":"Kleinhesselink","given":"Andrew","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":696414,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Adler, Peter B.","contributorId":64789,"corporation":false,"usgs":false,"family":"Adler","given":"Peter","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":696415,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70176610,"text":"ofr20161170 - 2016 - Preliminary geologic mapping of Cretaceous and Tertiary formations in the eastern part of the Little Snake River coal field, Carbon County, Wyoming","interactions":[],"lastModifiedDate":"2016-09-30T14:14:25","indexId":"ofr20161170","displayToPublicDate":"2016-09-30T13:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-1170","title":"Preliminary geologic mapping of Cretaceous and Tertiary formations in the eastern part of the Little Snake River coal field, Carbon County, Wyoming","docAbstract":"<p>In the 1970s and 1980s, C.S. Venable Barclay conducted geologic mapping of areas primarily underlain by Cretaceous coals in the eastern part of the Little Snake River coal field (LSR) in Carbon County, southwest Wyoming. With some exceptions, most of the mapping data were never published. Subsequently, after his retirement from the U.S. Geological Survey (USGS), his field maps and field notebooks were archived in the USGS Field Records. Due to a pending USGS coal assessment of the Little Snake River coal field area and planned geological mapping to be conducted by the Wyoming State Geological Survey, Barclay’s mapping data needed to be published to support these efforts. Subsequently, geologic maps were scanned and georeferenced into a geographic information system, and project and field notes were scanned into Portable Document Format (PDF) files. Data for seventeen 7½-minute quadrangles are presented in this report. This publication is solely intended to compile the mapping data as it was last worked on by Barclay and provides no interpretation or modification of his work.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161170","usgsCitation":"Haacke, J.E., Barclay, C.S.V., and Hettinger, R.D., 2016, Preliminary geologic mapping of Cretaceous and Tertiary formations in the eastern part of the Little Snake River coal field, Carbon County, Wyoming: U.S. Geological Survey Open-File Report 2016–1170, 9 p., https://dx.doi.org/10.3133/ofr20161170.","productDescription":"Report: iii, 9 p.; Field Notes; Metadata; Read Me; Spatial Data","numberOfPages":"12","onlineOnly":"Y","ipdsId":"IP-070800","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":329139,"rank":3,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/of/2016/1170/ofr20161170_Field 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Director, USGS Central Energy Resources Science Center<br>Box 25046, Mail Stop 939<br>Denver, CO 80225</p><p><a href=\"http://energy.usgs.gov/\" data-mce-href=\"http://energy.usgs.gov/\">http://energy.usgs.gov/</a></p>","tableOfContents":"<ul><li>Abstract</li><li>Overview of Barclay Studies</li><li>The Little Snake River Coal Field Map Data</li><li>Summary</li><li>Acknowledgments</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"publishedDate":"2016-09-30","noUsgsAuthors":false,"publicationDate":"2016-09-30","publicationStatus":"PW","scienceBaseUri":"57f7c63be4b0bc0bec09c838","contributors":{"authors":[{"text":"Haacke, Jon E.","contributorId":86054,"corporation":false,"usgs":true,"family":"Haacke","given":"Jon E.","affiliations":[],"preferred":false,"id":649803,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barclay, C. 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,{"id":70176082,"text":"fs20163065 - 2016 - Assessing potential scour using the South Carolina bridge-scour envelope curves","interactions":[],"lastModifiedDate":"2016-10-11T09:48:07","indexId":"fs20163065","displayToPublicDate":"2016-09-30T10:30:00","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":"2016-3065","title":"Assessing potential scour using the South Carolina bridge-scour envelope curves","docAbstract":"<h1>Summary</h1><p>Bridge-scour equations presented in the Federal Highway Administration Hydraulic Engineering Circular No. 18 reflect the current state-of-the practice for predicting scour at bridges. Although these laboratory-derived equations provide an important resource for assessing scour potential, there is a measure of uncertainty when applying these equations to field conditions. The uncertainty and limitations have been acknowledged by laboratory researchers and confirmed in field investigations.</p><p>Because of the uncertainty associated with bridge-scour equations, HEC-18 recommends that engineers evaluate the computed scour depths obtained from the equations and modify the resulting data if they appear unreasonable. Perhaps the best way to evaluate the reasonableness of predicted scour is to compare it to field measurements of historic scour. Historic field data show scour depths resulting from high flows and provide a reference for evaluating predicted scour. It is rare, however, that such data are available at or near a site of interest, making the evaluation of predicted scour as compared to field data difficult if not impossible. Realizing the value of historic scour measurements, the U.S. Geological Survey (USGS), in cooperation with the South Carolina Department of Transportation (SCDOT), conducted a series of three field investigations to collect historic scour data with the goal of understanding regional trends of scour at riverine bridges in South Carolina.</p><p>Historic scour measurements, including measurements of clear-water abutment, contraction, and pier scour, as well as live-bed contraction and pier scour, were made at more than 200 bridges. These field investigations provided valuable insights into regional scour trends and yielded regional bridge-scour envelope curves that can be used as supplementary tools for assessing all components of scour at riverine bridges in South Carolina.</p><p>The application and limitations of these envelope curves were documented in four reports. Because each report addresses different components of bridge scour, it was recognized that there was a need to develop an integrated procedure for applying the envelope curves to help assess scour potential at riverine bridges in South Carolina. The result of that effort is detailed in Benedict and others (2016) and summarized in this fact sheet.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20163065","collaboration":"Prepared in cooperation with the South Carolina Department of Transportation","usgsCitation":"Benedict, S.T., Feaster, T.D., and Caldwell, A.W., 2016, Assessing potential scour using the South Carolina bridge-scour envelope curves: U.S. Geological Survey Fact Sheet 2016-3065, 2 p., https://dx.doi.org/10.3133/fs20163065.","productDescription":"2 p. ","numberOfPages":"2","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-076488","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":329018,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2016/3065/coverthb.jpg"},{"id":329019,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2016/3065/fs20163065.pdf","text":"Report","size":"1.07 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2016-3065"},{"id":329022,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/sir20165121","text":"Scientific Investigations Report 2016–5121","linkHelpText":"- The South Carolina Bridge-Scour Envelope Curves"}],"country":"United States","state":"South Carolina 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Carolina\",\"nation\":\"USA  \"}}]}","contact":"<p><a href=\"mailto:dc_sc@usgs.gov\" data-mce-href=\"mailto:dc_sc@usgs.gov\">Director</a>, South Atlantic Water Science Center<br> U.S. Geological Survey<br> 720 Gracern Road, Suite 129<br> Columbia, SC 29210<br> <a href=\"http://sc.water.usgs.gov/\" data-mce-href=\"http://sc.water.usgs.gov/\">http://sc.water.usgs.gov/</a></p>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2016-09-30","noUsgsAuthors":false,"publicationDate":"2016-09-30","publicationStatus":"PW","scienceBaseUri":"57f7c63be4b0bc0bec09c83c","contributors":{"authors":[{"text":"Benedict, Stephen T. benedict@usgs.gov","contributorId":3198,"corporation":false,"usgs":true,"family":"Benedict","given":"Stephen T.","email":"benedict@usgs.gov","affiliations":[{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true}],"preferred":false,"id":649728,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Feaster, Toby D. 0000-0002-5626-5011 tfeaster@usgs.gov","orcid":"https://orcid.org/0000-0002-5626-5011","contributorId":174044,"corporation":false,"usgs":true,"family":"Feaster","given":"Toby D.","email":"tfeaster@usgs.gov","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":false,"id":647036,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Caldwell, Andral W. 0000-0003-1269-5463 acaldwel@usgs.gov","orcid":"https://orcid.org/0000-0003-1269-5463","contributorId":138690,"corporation":false,"usgs":true,"family":"Caldwell","given":"Andral W.","email":"acaldwel@usgs.gov","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true}],"preferred":false,"id":647037,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70175349,"text":"ofr20161127 - 2016 - Geologic structure of the Yucaipa area inferred from gravity data, San Bernardino and Riverside Counties, California","interactions":[],"lastModifiedDate":"2016-10-03T11:36:18","indexId":"ofr20161127","displayToPublicDate":"2016-09-30T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-1127","title":"Geologic structure of the Yucaipa area inferred from gravity data, San Bernardino and Riverside Counties, California","docAbstract":"<p class=\"p1\">In the spring of 2009, the U.S. Geological Survey, in cooperation with the San Bernardino Valley Municipal Water District, began working on a gravity survey in the Yucaipa area to explore the three-dimensional shape of the sedimentary fill (alluvial deposits) and the surface of the underlying crystalline basement rocks. As water use has increased in pace with rapid urbanization, water managers have need for better information about the subsurface geometry and the boundaries of groundwater subbasins in the Yucaipa area. The large density contrast between alluvial deposits and the crystalline basement complex permits using modeling of gravity data to estimate the thickness of alluvial deposits. The bottom of the alluvial deposits is considered to be the top of crystalline basement rocks. The gravity data, integrated with geologic information from surface outcrops and 51 subsurface borings (15 of which penetrated basement rock), indicated a complex basin configuration where steep slopes coincide with mapped faults―such as the Crafton Hills Fault and the eastern section of the Banning Fault―and concealed ridges separate hydrologically defined subbasins.</p><p class=\"p2\">Gravity measurements and well logs were the primary data sets used to define the thickness and structure of the groundwater basin. Gravity measurements were collected at 256 new locations along profiles that totaled approximately 104.6 km (65 mi) in length; these data supplemented previously collected gravity measurements. Gravity data were reduced to isostatic anomalies and separated into an anomaly field representing the valley fill. The ‘valley-fill-deposits gravity anomaly’ was converted to thickness by using an assumed, depth-varying density contrast between the alluvial deposits and the underlying bedrock.</p><p class=\"p3\">To help visualize the basin geometry, an animation of the elevation of the top of the basement-rocks was prepared. The animation “flies over” the Yucaipa groundwater basin, viewing the land surface, geology, faults, and ridges and valleys of the shaded-relief elevation of the top of the basement complex.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161127","collaboration":"Prepared in cooperation with the San Bernardino Valley Municipal Water District","usgsCitation":"Mendez, G.O., Langenheim, V.E., Morita, Andrew, and Danskin, W.R., 2016, Geologic structure of the Yucaipa area inferred from gravity data, San Bernardino and Riverside Counties, California: U.S. Geological Survey Open-File Report 2016–1127, 22 p., https://dx.doi.org/10.3133/ofr20161127.","productDescription":"Report: vii, 23 p.; Video Animation","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-077241","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":329070,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1127/ofr20161127.pdf","text":"Report","size":"34 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1127"},{"id":329071,"rank":3,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/of/2016/1127/ofr20161127_gravity.mp4","text":"Video animation","size":"47.3 MB mp4","description":"OFR 2016-1127 Video Animation","linkHelpText":"Land surface, geology, faults, wells, and elevation of the basement rocks in the Yucaipa area, California."},{"id":329069,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1127/coverthb.jpg"}],"country":"United States","state":"California","county":"San Bernardino County, Riverside County","otherGeospatial":"Yucaipa Area","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -117.15888977050781,\n              33.96842016198477\n            ],\n            [\n              -117.15888977050781,\n              34.08962997133382\n            ],\n            [\n              -116.97212219238281,\n              34.08962997133382\n            ],\n            [\n              -116.97212219238281,\n              33.96842016198477\n            ],\n            [\n              -117.15888977050781,\n              33.96842016198477\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p><a href=\"mailto:dc_ca@usgs.gov\" data-mce-href=\"mailto:dc_ca@usgs.gov\">Director</a>, California Water Science Center<br> U.S. Geological Survey<br> 6000 J Street, Placer Hall<br> Sacramento, CA 95819<br> <a href=\"http://ca.water.usgs.gov\" target=\"blank\" data-mce-href=\"http://ca.water.usgs.gov\">http://ca.water.usgs.gov</a></p>","tableOfContents":"<ul><li>Abstract<br></li><li>Introduction<br></li><li>Purpose and Scope<br></li><li>Geology<br></li><li>Geologic Units<br></li><li>Data Sets<br></li><li>Depth-to-Basement Profiles<br></li><li>Limitations<br></li><li>Results<br></li><li>Animation of Alluvial Thickness Model<br></li><li>References Cited<br></li></ul>","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2016-09-30","noUsgsAuthors":false,"publicationDate":"2016-09-30","publicationStatus":"PW","scienceBaseUri":"57f7c63be4b0bc0bec09c842","contributors":{"authors":[{"text":"Mendez, Gregory O. 0000-0002-9955-3726 gomendez@usgs.gov","orcid":"https://orcid.org/0000-0002-9955-3726","contributorId":1489,"corporation":false,"usgs":true,"family":"Mendez","given":"Gregory","email":"gomendez@usgs.gov","middleInitial":"O.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":644830,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Langenheim, Victoria E. 0000-0003-2170-5213 zulanger@usgs.gov","orcid":"https://orcid.org/0000-0003-2170-5213","contributorId":1526,"corporation":false,"usgs":true,"family":"Langenheim","given":"Victoria E.","email":"zulanger@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":false,"id":644831,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Morita, Andrew 0000-0002-8120-996X","orcid":"https://orcid.org/0000-0002-8120-996X","contributorId":52292,"corporation":false,"usgs":true,"family":"Morita","given":"Andrew","affiliations":[],"preferred":false,"id":644832,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Danskin, Wesley R. 0000-0001-8672-5501 wdanskin@usgs.gov","orcid":"https://orcid.org/0000-0001-8672-5501","contributorId":1034,"corporation":false,"usgs":true,"family":"Danskin","given":"Wesley","email":"wdanskin@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":644833,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70176696,"text":"ofr20161175 - 2016 - Benthic processes affecting contaminant transport in Upper Klamath Lake, Oregon","interactions":[],"lastModifiedDate":"2016-10-12T09:45:28","indexId":"ofr20161175","displayToPublicDate":"2016-09-30T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-1175","title":"Benthic processes affecting contaminant transport in Upper Klamath Lake, Oregon","docAbstract":"<h1>Executive Summary</h1><p>Multiple sampling trips during calendar years 2013 through 2015 were coordinated to provide measurements of interdependent benthic processes that potentially affect contaminant transport in Upper Klamath Lake (UKL), Oregon. The measurements were motivated by recognition that such internal processes (for example, solute benthic flux, bioturbation and solute efflux by benthic invertebrates, and physical groundwater-surface water interactions) were not integrated into existing management models for UKL. Up until 2013, all of the benthic-flux studies generally had been limited spatially to a number of sites in the northern part of UKL and limited temporally to 2–3 samplings per year. All of the benthic invertebrate studies also had been limited to the northern part of the lake; however, intensive temporal (weekly) studies had previously been completed independent of benthic-flux studies. Therefore, knowledge of both the spatial and temporal variability in benthic flux and benthic invertebrate distributions for the entire lake was lacking. To address these limitations, we completed a lakewide spatial study during 2013 and a coordinated temporal study with weekly sampling of benthic flux and benthic invertebrates during 2014. Field design of the spatially focused study in 2013 involved 21 sites sampled three times as the summer cyanobacterial bloom developed (that is, <span class=\"aBn\" data-term=\"goog_1023710937\"><span class=\"aQJ\">May 23</span></span>, <span class=\"aBn\" data-term=\"goog_1023710938\"><span class=\"aQJ\">June 13</span></span>, and July 3, 2013). Results of the 27-week, temporally focused study of one site in 2014 were summarized and partitioned into three periods (referred to herein as pre-bloom, bloom and post-bloom periods), each period involving 9 weeks of profiler deployments, water column and benthic sampling. Partitioning of the pre-bloom, bloom, and post-bloom periods were based on water-column chlorophyll concentrations and involved the following date intervals, respectively: <span class=\"aBn\" data-term=\"goog_1023710939\"><span class=\"aQJ\">April 15 through June 10</span></span>, <span class=\"aBn\" data-term=\"goog_1023710940\"><span class=\"aQJ\">June 17 through August 13</span></span>, and August 20 through October 16, 2014.&nbsp;</p><p>To examine dissolved-solute (0.2-micrometer [μm] filtered) benthic flux, sets of nonmetallic pore-water profilers (U.S. Patent 8,051,727 B1) were deployed. In 2013, the deployment of profilers at 21 UKL sites occurred at the beginning of the annual cyanobacterial bloom of <i>Aphanizomenon flos–aquae </i>(AFA), in the middle of the bloom period, and at the peak of the bloom. Coordinated benthic invertebrate collections also were made. Based on results from 2013, weekly deployments of profilers and collection of benthic invertebrate samples from late spring to early autumn were used to estimate temporal trends in solute flux and benthic invertebrate densities. Estimates of nutrient efflux by benthic invertebrates were determined in the spring and autumn from 2011 through 2013 and three times (spring, summer, and autumn) in 2015. This work extends UKL studies that began in 2006 to quantify the importance of benthic solute sources in the lake. In 2015, piezometers and thermistor sets were deployed to quantify potential groundwater exchange with the lake water column.&nbsp;</p><p>Analysis of the 2013 soluble reactive phosphorus (SRP) benthic flux indicated no effect of location (lake region), habitat, or sampling period, and the average lakewide flux values were consistent with earlier studies that had been confined to the northern region of UKL and adjacent wetlands. The 2014 study therefore focused on estimating temporal trends at a site within Ball Bay. During both 2013 and 2014 field studies, fluxes of macronutrients (soluble reactive phosphorus (SRP) and ammonia) and micronutrients (iron [Fe] and manganese [Mn]) were consistently positive and increased prior to the initial AFA bloom, varied or lagged with water-column chlorophyll during the summer bloom period, then decreased after the cyanobacterial blooms, only to rebound toward pre-bloom conditions in the final weeks of sampling. These four solutes exhibited benthic loads greater than maximum riverine loads estimated during the spring and early summers of 2013 and 2014. However, consistently detectable concentrations for all four solutes provide no evidence that they consistently serve as the limiting nutrient for primary production in the lake. In contrast to the four solutes (SRP, ammonia, Fe, and Mn), benthic fluxes of dissolved arsenic (As) were both negative and positive (that is, the lakebed currently serves as both a source and a sink for dissolved As, depending on season). In a further contrast with SRP, ammonia, dissolved Fe, and Mn, dissolved-As riverine loads to UKL were of similar magnitude to benthic loads. A negative relationship between dissolved-As flux and water-column As over the 2014 temporal study provides a potential advantage for the management of water-quality in contrast to solutes, like SRP or ammonia, with consistently positive flux.&nbsp;</p><p>The mean total benthic invertebrate density during 2013 was 12,610 individuals per square meter (n=63). Although benthic invertebrate density did not change over the study period, it was higher in littoral habitats than open-lake or trench habitats and higher in the northern region compared to the central or southern regions of UKL. Mean total benthic invertebrate density during 2014 was 19,726 individuals m<span>−2 </span>(n=27). Density during the pre-bloom and bloom periods of April 15 to August 13, 2014 (the first two thirds of the 2014 sampling period), were similar to 2013. However, benthic invertebrate density more than doubled during the latter one-third of the study, that is, the post-bloom period between August 20 to October 16, 2014. Oligochaeta, Chironomidae and Hirudinea represented well over 90 percent of the benthic fauna; Oligochaeta were twice as abundant as Chironomidae or Hirudinea, the latter two of which were similar in density.&nbsp;</p><p>Benthic invertebrates may enhance dissolved-nutrient (or toxicant) transport across the sediment-water interface by (1) modifying diffusion-layer thicknesses and permeability through bioturbation, (2) enhancing advective flow across the interface through bioirrigation, and (3) excreting or expelling dissolved or particulate solutes directly into the overlying water column (Boudreau and Jorgensen, 2001). We evaluated SRP efflux via excretion for approximately 15 different major taxa in UKL. Once these measures were scaled, it was evident that benthic invertebrates potentially contribute approximately 1.5 times the amount of SRP to the water column of Upper Klamath Lake as diffusive SRP flux alone, measured in profiler deployments.&nbsp;</p><p>Sets of piezometers and temperature loggers were deployed in UKL to obtain estimates of vertical advective solute flux. The pressure transducer installations, within the piezometers, did not perform as designed, rendering the head gradient data unreliable. However, in terms of future research, this field work did demonstrate the feasibility of collecting vertical gradient data with piezometer deployments. Advective flux estimates herein are based solely on heat-flow modeling based on temperature data from four lake sites, without use of transducer data. Given the magnitudes (both positive or negative) of the heat-transfer fluxes for SRP, relative to diffusive-flux and macroinvertebrate efflux measurements (all positive but spanning the same orders of magnitude), further examination of solute advective flux is recommended as a potential transport process to integrate into existing water-quality (for example, Total Maximum Daily Load [TMDL]) models.&nbsp;</p><p>As a complement to the biogeochemical focus of this study, initial analyses of suspended-particle (floc) characteristics and settling velocities from the water column were derived near the surface and lakebed at two UKL sites. To better understand changing particle characteristics during the AFA-bloom period, suspended particles were examined in 2015 using a LabSFLOC (LF), which is a Laboratory Spectral Flocculation Characteristics version of an In-Situ Settling Velocity instrument (INSSEV-LF). Particle characteristics and settling velocities were analyzed from the water column near the surface (sample <i>dp_10</i>) and lakebed (sample <i>dp_90</i>) at two lake sites (open-lake site ML and littoral site LS01). The term “floc” refers herein to suspended particles that may aggregate or disaggregate to change in size, composition, and settling velocity.&nbsp;</p><p>During pre-bloom (May) conditions, where maximum suspended particulate matter concentration (SPMC) was 140 milligrams per liter (mg&nbsp;<span class=\"nowrap\">L<sup>−1</sup></span>) was now observed at site LS01 in close proximity to the bed, where D<span><sub>mean</sub> </span>peaked at 305 μm, and the corresponding Ws<span><sub>mean</sub> </span>was 3.9 millimeters per second (mm s<sup>−1</sup>). The high near-bed SPMC (828 mg L<sup>−1</sup>) experienced during post-bloom October 2015 at LS01 formed a benthic nepheloid layer (BNL) above the lake’s bed. Numerous low density, fast settling macrofloc-sized organic aggregates (D &gt;160 μm) were observed (some up to 1 mm in size) near bed at LS01 both during the bloom and post-bloom conditions; many of these flocs displayed fibrous organic structures. In terms of mass settling fluxes, the post-bloom BNL produced a total MSF of 4,139 milligrams per square meter per second (mg m<span><sup>−2</sup> </span>s<sup>−1</sup>) (92.1 percent of MSF credited to the macrofloc-sized organic aggregates/cyanobacterial colonies); that was nearly three times the corresponding near-bed settling flux observed during the July 2015 bloom and 360 times greater than the pre-bloom conditions from May 2015 (98.8 percent and 14 percent of MSF credited to the macrofloc-sized fractions for those respective months). Such changes in the near-bed settling flux demonstrate the highly significant seasonal effects that the AFA bloom has on the floc depositional fluxes in UKL and highlights the importance of seasonal monitoring of these conditions in order to correctly parameterize the wide range in depositional characteristics and floc properties measured throughout UKL.&nbsp;</p><p>Collectively, floc populations observed within UKL demonstrated a wide range in settling velocity (Ws) for a given particle size, D. Similarly, a given settling velocity was not associated with a specific particle size. This variability in particle characteristics and properties indicates the influence of varying floc effective density and its effect on mass and mass settling fluxes (MSF). The use of instruments, such as the INSSEV-LF, enables measuring the variability of settling velocity and its relation to particle density and size.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161175","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Kuwabara, J.S., Topping, B.R., Carter, J.L., Carlson, R.A., Parchaso, F., Fend, S.V., Stauffer-Olsen, N., Manning, A.J., Land, J.M., 2016, Benthic processes affecting contaminant transport in Upper Klamath Lake, Oregon (ver. 1.1, October 2016): U.S. Geological Survey Open-File Report 2016–1175, 103 p., https://dx.doi.org/10.3133/ofr20161175. ","productDescription":"Report: viii, 103 p.; 2 Tables","numberOfPages":"115","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":329222,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1175/coverthb.jpg"},{"id":329223,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1175/ofr20161175.pdf","text":"Report","size":"4.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1175"},{"id":329224,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2016/1175/ofr20161175_table4.xlsx","text":"Table 4","size":"96 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2016-1175 Table 4"},{"id":329425,"rank":5,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2016/1175/versionHist.txt","size":"1 KB","linkFileType":{"id":2,"text":"txt"},"description":"OFR 2016-1175 Version History"},{"id":329424,"rank":4,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2016/1175/ofr20161175_table19.xlsx","text":"Table 19","size":"18 MB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2016-1175 Table 19"}],"country":"United States","state":"Oregon","otherGeospatial":"Upper Klamath Lake","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -122.09793090820311,\n              42.231567925608616\n            ],\n            [\n              -122.09793090820311,\n              42.70464124398721\n            ],\n            [\n              -121.79992675781249,\n              42.70464124398721\n            ],\n            [\n              -121.79992675781249,\n              42.231567925608616\n            ],\n            [\n              -122.09793090820311,\n              42.231567925608616\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","edition":"Version 1.0: Originally posted September 30, 2016; Version 1.1: October 11, 2016","contact":"<p><a href=\"http://water.usgs.gov/nrp/index-scientists.html\" target=\"_blank\" data-mce-href=\"http://water.usgs.gov/nrp/index-scientists.html\">NRP staff</a>&nbsp;<br>Water Resources National Research Program&nbsp;<br>U.S. Geological Survey&nbsp;<br>345 Middlefield Road, MS-435&nbsp;<br>Menlo Park, CA 94025&nbsp;<br><a href=\"http://water.usgs.gov/nrp/\" target=\"_blank\" data-mce-href=\"http://water.usgs.gov/nrp/\">National Research Program</a></p>","tableOfContents":"<ul><li>Executive Summary</li><li>Introduction</li><li>Results and Discussion</li><li>Methods</li><li>References Cited</li><li>Tables</li></ul>","publishedDate":"2016-09-30","revisedDate":"2016-10-11","noUsgsAuthors":false,"publicationDate":"2016-09-30","publicationStatus":"PW","scienceBaseUri":"57f7c63be4b0bc0bec09c83e","contributors":{"authors":[{"text":"Kuwabara, James S. 0000-0003-2502-1601 kuwabara@usgs.gov","orcid":"https://orcid.org/0000-0003-2502-1601","contributorId":3374,"corporation":false,"usgs":true,"family":"Kuwabara","given":"James","email":"kuwabara@usgs.gov","middleInitial":"S.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":649913,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Topping, Brent R. 0000-0002-7887-4221 btopping@usgs.gov","orcid":"https://orcid.org/0000-0002-7887-4221","contributorId":1484,"corporation":false,"usgs":true,"family":"Topping","given":"Brent","email":"btopping@usgs.gov","middleInitial":"R.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":649914,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Carter, James L. 0000-0002-0104-9776 jlcarter@usgs.gov","orcid":"https://orcid.org/0000-0002-0104-9776","contributorId":3278,"corporation":false,"usgs":true,"family":"Carter","given":"James","email":"jlcarter@usgs.gov","middleInitial":"L.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":649915,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Carlson, Rick A","contributorId":120306,"corporation":false,"usgs":true,"family":"Carlson","given":"Rick A","affiliations":[],"preferred":false,"id":649916,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Parchaso, Francis 0000-0002-9471-7787 parchaso@usgs.gov","orcid":"https://orcid.org/0000-0002-9471-7787","contributorId":150620,"corporation":false,"usgs":true,"family":"Parchaso","given":"Francis","email":"parchaso@usgs.gov","affiliations":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":649917,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fend, Steven V. 0000-0002-4638-6602 svfend@usgs.gov","orcid":"https://orcid.org/0000-0002-4638-6602","contributorId":3591,"corporation":false,"usgs":true,"family":"Fend","given":"Steven","email":"svfend@usgs.gov","middleInitial":"V.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":649918,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Stauffer-Olsen, Natalie","contributorId":175078,"corporation":false,"usgs":true,"family":"Stauffer-Olsen","given":"Natalie","affiliations":[],"preferred":false,"id":649919,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Manning, Andrew J.","contributorId":175079,"corporation":false,"usgs":false,"family":"Manning","given":"Andrew","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":649920,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Land, Jennie M.","contributorId":175080,"corporation":false,"usgs":true,"family":"Land","given":"Jennie","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":649921,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70176920,"text":"70176920 - 2016 - Characterizing changes in streamflow and sediment supply in the Sacramento River Basin, California, using hydrological simulation program—FORTRAN (HSPF)","interactions":[],"lastModifiedDate":"2017-10-30T09:43:05","indexId":"70176920","displayToPublicDate":"2016-09-30T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Characterizing changes in streamflow and sediment supply in the Sacramento River Basin, California, using hydrological simulation program—FORTRAN (HSPF)","docAbstract":"<p><span>A daily watershed model of the Sacramento River Basin of northern California was developed to simulate streamflow and suspended sediment transport to the San Francisco Bay-Delta. To compensate for sparse data, a unique combination of model inputs was developed, including meteorological variables, potential evapotranspiration, and parameters defining hydraulic geometry. A slight decreasing trend of sediment loads and concentrations was statistically significant in the lowest 50% of flows, supporting the observed historical sediment decline. Historical changes in climate, including seasonality and decline of snowpack, contribute to changes in streamflow, and are a significant component describing the mechanisms responsible for the decline in sediment. Several wet and dry hypothetical climate change scenarios with temperature changes of 1.5 °C and 4.5 °C were applied to the base historical conditions to assess the model sensitivity of streamflow and sediment to changes in climate. Of the scenarios evaluated, sediment discharge for the Sacramento River Basin increased the most with increased storm magnitude and frequency and decreased the most with increases in air temperature, regardless of changes in precipitation. The model will be used to develop projections of potential hydrologic and sediment trends to the Bay-Delta in response to potential future climate scenarios, which will help assess the hydrological and ecological health of the Bay-Delta into the next century.</span></p>","language":"English","publisher":"Molecular Diversity Preservation International","publisherLocation":"Basel, Switzerland","doi":"10.3390/w8100432","usgsCitation":"Stern, M.A., Flint, L.E., Minear, J.T., Flint, A.L., and Wright, S., 2016, Characterizing changes in streamflow and sediment supply in the Sacramento River Basin, California, using hydrological simulation program—FORTRAN (HSPF): Water, v. 8, no. 10, https://doi.org/10.3390/w8100432.","startPage":"432","numberOfPages":"21","ipdsId":"IP-073991","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":552,"text":"San Francisco Bay-Delta","active":false,"usgs":true}],"links":[{"id":462073,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w8100432","text":"Publisher Index Page"},{"id":329512,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento River Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -123.5,\n              38.25\n            ],\n            [\n              -123.5,\n              41\n            ],\n            [\n              -121,\n              41\n            ],\n            [\n              -121,\n              38.25\n            ],\n            [\n              -123.5,\n              38.25\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"8","issue":"10","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2016-09-30","publicationStatus":"PW","scienceBaseUri":"57ffdefee4b0824b2d179cf4","contributors":{"authors":[{"text":"Stern, Michelle A. 0000-0003-3030-7065 mstern@usgs.gov","orcid":"https://orcid.org/0000-0003-3030-7065","contributorId":4244,"corporation":false,"usgs":true,"family":"Stern","given":"Michelle","email":"mstern@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":650712,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Flint, Lorraine E. 0000-0002-7868-441X lflint@usgs.gov","orcid":"https://orcid.org/0000-0002-7868-441X","contributorId":1184,"corporation":false,"usgs":true,"family":"Flint","given":"Lorraine","email":"lflint@usgs.gov","middleInitial":"E.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":650713,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Minear, Justin Toby jminear@usgs.gov","contributorId":3736,"corporation":false,"usgs":true,"family":"Minear","given":"Justin","email":"jminear@usgs.gov","middleInitial":"Toby","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":650714,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Flint, Alan L. 0000-0002-5118-751X aflint@usgs.gov","orcid":"https://orcid.org/0000-0002-5118-751X","contributorId":1492,"corporation":false,"usgs":true,"family":"Flint","given":"Alan","email":"aflint@usgs.gov","middleInitial":"L.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":650715,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wright, Scott 0000-0002-0387-5713 sawright@usgs.gov","orcid":"https://orcid.org/0000-0002-0387-5713","contributorId":1536,"corporation":false,"usgs":true,"family":"Wright","given":"Scott","email":"sawright@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":650716,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70174219,"text":"sir20165094 - 2016 - Using inferential sensors for quality control of Everglades Depth Estimation Network water-level data","interactions":[],"lastModifiedDate":"2016-09-29T10:11:07","indexId":"sir20165094","displayToPublicDate":"2016-09-29T10:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-5094","title":"Using inferential sensors for quality control of Everglades Depth Estimation Network water-level data","docAbstract":"<p>The Everglades Depth Estimation Network (EDEN), with over 240 real-time gaging stations, provides hydrologic data for freshwater and tidal areas of the Everglades. These data are used to generate daily water-level and water-depth maps of the Everglades that are used to assess biotic responses to hydrologic change resulting from the U.S. Army Corps of Engineers Comprehensive Everglades Restoration Plan. The generation of EDEN daily water-level and water-depth maps is dependent on high quality real-time data from water-level stations. Real-time data are automatically checked for outliers by assigning minimum and maximum thresholds for each station. Small errors in the real-time data, such as gradual drift of malfunctioning pressure transducers, are more difficult to immediately identify with visual inspection of time-series plots and may only be identified during on-site inspections of the stations. Correcting these small errors in the data often is time consuming and water-level data may not be finalized for several months. To provide daily water-level and water-depth maps on a near real-time basis, EDEN needed an automated process to identify errors in water-level data and to provide estimates for missing or erroneous water-level data.</p><p>The Automated Data Assurance and Management (ADAM) software uses inferential sensor technology often used in industrial applications. Rather than installing a redundant sensor to measure a process, such as an additional water-level station, inferential sensors, or virtual sensors, were developed for each station that make accurate estimates of the process measured by the hard sensor (water-level gaging station). The inferential sensors in the ADAM software are empirical models that use inputs from one or more proximal stations. The advantage of ADAM is that it provides a redundant signal to the sensor in the field without the environmental threats associated with field conditions at stations (flood or hurricane, for example). In the event that a station does malfunction, ADAM provides an accurate estimate for the period of missing data. The ADAM software also is used in the quality assurance and quality control of the data. The virtual signals are compared to the real-time data, and if the difference between the two signals exceeds a certain tolerance, corrective action to the data and (or) the gaging station can be taken. The ADAM software is automated so that, each morning, the real-time EDEN data are compared to the inferential sensor signals and digital reports highlighting potential erroneous real-time data are generated for appropriate support personnel. The development and application of inferential sensors is easily transferable to other real-time hydrologic monitoring networks.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165094","collaboration":"Greater Everglades Priority Ecosystems Science","usgsCitation":"Petkewich, M.D., Daamen, R.C., Roehl, E.A., and Conrads, P.A., 2016, Using inferential sensors for quality control of Everglades Depth Estimation Network water-level data: U.S. Geological Survey Scientific Investigations Report 2016–5094, 25 p., https://dx.doi.org/10.3133/sir20165094.","productDescription":"v, 25 p.","onlineOnly":"Y","ipdsId":"IP-066447","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":329015,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/ofr20161116","text":"Open-File Report 2016–1116","description":"Open-File Report 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Assurance and Management (ADAM) Software</li><li>ADAM Software Architecture&nbsp;</li><li>Using ADAM Software to Process Everglades Depth Estimation Network Data&nbsp;</li><li>Summary&nbsp;</li><li>References Cited</li></ul>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2016-09-29","noUsgsAuthors":false,"publicationDate":"2016-09-29","publicationStatus":"PW","scienceBaseUri":"57ed3e3ee4b090825011d493","contributors":{"authors":[{"text":"Petkewich, Matthew D. 0000-0002-5749-6356 mdpetkew@usgs.gov","orcid":"https://orcid.org/0000-0002-5749-6356","contributorId":982,"corporation":false,"usgs":true,"family":"Petkewich","given":"Matthew","email":"mdpetkew@usgs.gov","middleInitial":"D.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true}],"preferred":true,"id":641330,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Daamen, Ruby C.","contributorId":105391,"corporation":false,"usgs":true,"family":"Daamen","given":"Ruby","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":641333,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Roehl, Edwin A.","contributorId":89242,"corporation":false,"usgs":true,"family":"Roehl","given":"Edwin","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":641332,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Conrads, Paul 0000-0003-0408-4208 pconrads@usgs.gov","orcid":"https://orcid.org/0000-0003-0408-4208","contributorId":764,"corporation":false,"usgs":true,"family":"Conrads","given":"Paul","email":"pconrads@usgs.gov","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true}],"preferred":false,"id":641331,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70174889,"text":"ofr20161116 - 2016 - User’s manual for the Automated Data Assurance and Management application developed for quality control of Everglades Depth Estimation Network water-level data","interactions":[],"lastModifiedDate":"2016-09-29T10:05:26","indexId":"ofr20161116","displayToPublicDate":"2016-09-29T10:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-1116","title":"User’s manual for the Automated Data Assurance and Management application developed for quality control of Everglades Depth Estimation Network water-level data","docAbstract":"<p>The generation of Everglades Depth Estimation Network (EDEN) daily water-level and water-depth maps is dependent on high quality real-time data from over 240 water-level stations. To increase the accuracy of the daily water-surface maps, the Automated Data Assurance and Management (ADAM) tool was created by the U.S. Geological Survey as part of Greater Everglades Priority Ecosystems Science. The ADAM tool is used to provide accurate quality-assurance review of the real-time data from the EDEN network and allows estimation or replacement of missing or erroneous data. This user’s manual describes how to install and operate the ADAM software. File structure and operation of the ADAM software is explained using examples.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161116","collaboration":"Greater Everglades Priority Ecosystems Science","usgsCitation":"Petkewich, M.D., Daamen, R.C., Roehl, E.A., and Conrads, P.A., 2016, User’s manual for the Automated Data Assurance and Management application developed for quality control of Everglades Depth Estimation Network water-level data: U.S. Geological Survey Open-File Report 2016–1116, 28 p., https://dx.doi.org/10.3133/ofr20161116.","productDescription":"Report: vi, 28 p.; Companion File","numberOfPages":"38","onlineOnly":"Y","ipdsId":"IP-076311","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":329016,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/sir20165094","text":"Scientific Investigations Report 2016–5094","description":"Scientific Investigations Report 2016–5094","linkHelpText":"- Using Inferential Sensors for Quality Control of Everglades Depth Estimation Network Water-Level Data"},{"id":328990,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1116/ofr20161116.pdf","text":"Report","size":"13.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1116"},{"id":328989,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1116/coverthb.jpg"},{"id":329002,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2016/1116/downloads","text":"Executable files for Automated Data Assurance and Management application","description":"OFR 2016-1116"}],"contact":"<p><a href=\"mailto:dc_sc@usgs.gov\" data-mce-href=\"mailto:dc_sc@usgs.gov\">Director</a>, South Atlantic Water Science Center<br> U.S. Geological Survey<br> Stephenson Center, Suite 129<br> Gracern Road<br> Columbia, SC 29210<br> <a href=\"https://www2.usgs.gov/water/southatlantic/\" data-mce-href=\"https://www2.usgs.gov/water/southatlantic/\">https://www2.usgs.gov/water/southatlantic</a></p>","tableOfContents":"<ul><li>Abstract&nbsp;</li><li>Introduction</li><li>Application Files&nbsp;</li><li>Installation, System Requirements, and Removal</li><li>Application Overview</li><li>Operation&nbsp;</li><li>Application Input File Format</li><li>Application User Worksheets</li><li>ADAMDB Table Structure</li><li>Summary</li><li>Reference Cited</li></ul>","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"publishedDate":"2016-09-29","noUsgsAuthors":false,"publicationDate":"2016-09-29","publicationStatus":"PW","scienceBaseUri":"57ed2bdae4b090825011d41a","contributors":{"authors":[{"text":"Petkewich, Matthew D. 0000-0002-5749-6356 mdpetkew@usgs.gov","orcid":"https://orcid.org/0000-0002-5749-6356","contributorId":982,"corporation":false,"usgs":true,"family":"Petkewich","given":"Matthew","email":"mdpetkew@usgs.gov","middleInitial":"D.","affiliations":[{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":643008,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Daamen, Ruby C.","contributorId":105391,"corporation":false,"usgs":true,"family":"Daamen","given":"Ruby","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":643009,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Roehl, Edwin A.","contributorId":89242,"corporation":false,"usgs":true,"family":"Roehl","given":"Edwin","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":643010,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Conrads, Paul 0000-0003-0408-4208 pconrads@usgs.gov","orcid":"https://orcid.org/0000-0003-0408-4208","contributorId":764,"corporation":false,"usgs":true,"family":"Conrads","given":"Paul","email":"pconrads@usgs.gov","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true}],"preferred":false,"id":643011,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70159675,"text":"ofr20151222 - 2016 - Monitoring and research on the Bi-State Distinct Population Segment of greater sage-grouse (<i>Centrocercus urophasianus</i>) in the Pine Nut Mountains, California and Nevada—Study progress report, 2011–15","interactions":[],"lastModifiedDate":"2016-09-30T09:23:36","indexId":"ofr20151222","displayToPublicDate":"2016-09-29T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-1222","title":"Monitoring and research on the Bi-State Distinct Population Segment of greater sage-grouse (<i>Centrocercus urophasianus</i>) in the Pine Nut Mountains, California and Nevada—Study progress report, 2011–15","docAbstract":"<p class=\"p1\">The Bi-State distinct population segment (DPS) of greater sage-grouse (<i>Centrocercus urophasianus</i>) that occurs along the Nevada–California border was proposed for listing as threatened under the Endangered Species Act (ESA) by the U.S. Fish and Wildlife Service (FWS) in October 2013. However, in April 2015, the FWS determined that the Bi-State DPS no longer required protection under the ESA and withdrew the proposed rule to list the Bi-State DPS (U.S. Fish and Wildlife Service, 2015). The Bi-State DPS occupies portions of Alpine, Mono, and Inyo Counties in California, and Douglas, Esmeralda, Lyon, Carson City, and Mineral Counties in Nevada. Unique threats facing this population include geographic isolation, expansion of single-leaf pinyon (<i>Pinus monophylla</i>) and Utah juniper (<i>Juniperus osteosperma</i>), anthropogenic activities, and recent changes in predator communities. Estimating population vital rates, identifying seasonal habitat, quantifying threats, and identifying movement patterns are important first steps in developing effective sage-grouse management and conservation plans. During 2011–15, we radio- and Global Positioning System (GPS)-marked (2012–14 only) 44, 47, 17, 9, and 3 sage-grouse, respectively, for a total of 120, in the Pine Nut Mountains Population Management Unit (PMU). No change in lek attendance was detected at Mill Canyon (maximum=18 males) between 2011 and 2012; however, 1 male was observed in 2014 and no males were observed in 2013 and 2015. Males were observed near Bald Mountain in 2013, making it the first year this lek was observed to be active during the study period. Males were observed at a new site in the Buckskin Range in 2014 during trapping efforts and again observed during surveys in 2015. Findings indicate that pinyon-juniper is avoided by sage-grouse during every life stage. Nesting females selected increased sagebrush cover, sagebrush height, and understory horizontal cover, and brood-rearing females selected similar areas, but also preferred increased perennial forb abundance. Using maximum likelihood estimation, nest survival for the Pine Nut Mountains PMU during 2011–14 was 23.8 percent (95-percent confidence interval [CI]=0.3–40.6 percent) and appeared lower in comparison to the average 42 percent nest success for sage-grouse range-wide.&nbsp;</p><p class=\"p1\">Brood survival for 50-day brood-rearing phase in the Pine Nut Mountains PMU during 2011–14 was 53.8 percent (95-percent CI=30.0–73.4 percent). Adult survival during 2011–15 was 67.4 percent (95-percent CI=56.1–76.5 percent). During 2011–14, 696 raptor/raven surveys were completed and results indicate a greater number of raven detections (<i>n</i>=464) in the Pine Nut Mountains PMU than at other study areas in Nevada. These data will be used to develop a predator index. We conducted a more minimal monitoring effort of sage-grouse populations during the 2015 field season, which included trapping efforts, general telemetry, brood monitoring, and GPS monitoring. Nest monitoring, microhabitat sampling, and raptor/raven surveys were not conducted in the 2015 season. Deployment of GPS transmitters has expanded our knowledge of movement corridors and fine-scale movement patterns by sage-grouse in the Pine Nut Mountains PMU. Movement corridors between seasonal habitats were identified with one sage-grouse traveling greater than 100 kilometers south to the Bodie Mountains in California for the winter season. The use of GPS technology to monitor movements in conjunction with intensive field efforts will be important in developing habitat models and maps for the Pine Nut Mountains PMU.</p><p class=\"p1\"><br data-mce-bogus=\"1\"></p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151222","collaboration":"Prepared in cooperation with the Bureau of Land Management, Nevada Department of Wildlife, and U.S. Fish and Wildlife Service","usgsCitation":"Coates, P.S., Andrle, K.M., Ziegler, P.T., and Casazza, M.L., 2016, Monitoring and research on the Bi-State Distinct Population Segment of greater sage-grouse (<em>Centrocercus urophasianus</em>) in the Pine Nut Mountains, California and Nevada—Study progress report, 2011–15: U. S. Geological Survey Open-File Report 2015-1222, 40 p., https://dx.doi.org/10.3133/ofr20151222.","productDescription":"Report: vi, 40 p. 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Western Ecological Research Center<br> U.S. Geological Survey<br> 3020 State University Drive East<br> Sacramento, California 95819<br> <a href=\"http://www.werc.usgs.gov/\" target=\"blank\" data-mce-href=\"http://www.werc.usgs.gov/\">http://www.werc.usgs.gov/</a></p>","tableOfContents":"<ul><li>Abstract<br></li><li>Background<br></li><li>Study Area<br></li><li>Methods<br></li><li>Results<br></li><li>Acknowledgments<br></li><li>Figures<br></li><li>Tables<br></li><li>Appendix A. Evaluation of Bi-State Sage-Grouse Nest Survival Models That Consist of Habitat Characteristic Covariates for the Pine Nut Mountains, Nevada, 2011–13<br></li></ul>","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"publishedDate":"2016-09-29","noUsgsAuthors":false,"publicationDate":"2016-09-29","publicationStatus":"PW","scienceBaseUri":"57f7c63be4b0bc0bec09c84a","contributors":{"authors":[{"text":"Coates, Peter S. 0000-0003-2672-9994 pcoates@usgs.gov","orcid":"https://orcid.org/0000-0003-2672-9994","contributorId":3263,"corporation":false,"usgs":true,"family":"Coates","given":"Peter","email":"pcoates@usgs.gov","middleInitial":"S.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":580017,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Andrle, Katie M.","contributorId":175032,"corporation":false,"usgs":true,"family":"Andrle","given":"Katie M.","affiliations":[],"preferred":false,"id":580019,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ziegler, Pilar T.","contributorId":175033,"corporation":false,"usgs":false,"family":"Ziegler","given":"Pilar","email":"","middleInitial":"T.","affiliations":[{"id":7217,"text":"Bureau of Land Management","active":true,"usgs":false}],"preferred":false,"id":649909,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Casazza, Michael L. 0000-0002-5636-735X mike_casazza@usgs.gov","orcid":"https://orcid.org/0000-0002-5636-735X","contributorId":2091,"corporation":false,"usgs":true,"family":"Casazza","given":"Michael","email":"mike_casazza@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":580016,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70176419,"text":"sir20165130 - 2016 - Altitudes and thicknesses of hydrogeologic units of the Ozark Plateaus aquifer system in Arkansas, Kansas, Missouri, and Oklahoma","interactions":[],"lastModifiedDate":"2017-03-10T13:41:29","indexId":"sir20165130","displayToPublicDate":"2016-09-29T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-5130","title":"Altitudes and thicknesses of hydrogeologic units of the Ozark Plateaus aquifer system in Arkansas, Kansas, Missouri, and Oklahoma","docAbstract":"<p>A hydrogeologic framework was constructed to represent the altitudes and thicknesses of hydrogeologic units within the Ozark Plateaus aquifer system as part of a regional groundwater-flow model supported by the U.S. Geological Survey Water Availability and Use Science Program. The Ozark Plateaus aquifer system study area is nearly 70,000 square miles and includes parts of Arkansas, Kansas, Missouri, and Oklahoma. Nine hydrogeologic units were selected for delineation within the aquifer system and include the Western Interior Plains confining system, the Springfield Plateau aquifer, the Ozark confining unit, the Ozark aquifer, which was divided into the upper, middle, and lower Ozark aquifers to better capture the spatial variation in the hydrologic properties, the St. Francois confining unit, the St. Francois aquifer, and the basement confining unit. Geophysical and well-cutting logs, along with lithologic descriptions by well drillers, were compiled and interpreted to create hydrologic altitudes for each unit. The final compiled dataset included more than 23,000 individual altitude points (excluding synthetic points) representing the nine hydrogeologic units within the Ozark Plateaus aquifer system.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165130","collaboration":"Water Availability and Use Science Program","usgsCitation":"Westerman, D.A., Gillip, J.A., Richards, J.M., Hays, P.D., Clark, B.R., 2016, Altitudes and thicknesses of hydrogeologic units of the Ozark Plateaus aquifer system in Arkansas, Kansas, Missouri, and Oklahoma: U.S. Geological Survey Scientific Investigations Report 2016–5130, 32 p., https://dx.doi.org/10.3133/sir20165130. ","productDescription":"v, 32 p.","startPage":"1","endPage":"32","numberOfPages":"42","onlineOnly":"Y","ipdsId":"IP-063654","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":438543,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7HQ3X0T","text":"USGS data release","linkHelpText":"Altitudes and Thicknesses of Hydrogeologic Units of the Ozark Plateaus Aquifer System in Arkansas, Kansas, Missouri, and Oklahoma"},{"id":337377,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7HQ3X0T","text":"Altitudes and thicknesses of hydrogeologic units of the Ozark Plateaus aquifer system in Arkansas, Kansas, Missouri, and Oklahoma"},{"id":329094,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5130/sir20165130.pdf","text":"Report","size":"21.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR  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,{"id":70176040,"text":"ofr20161141 - 2016 - U.S. Geological Survey science for the Wyoming Landscape Conservation Initiative—2015 annual report","interactions":[],"lastModifiedDate":"2018-09-21T11:27:15","indexId":"ofr20161141","displayToPublicDate":"2016-09-28T12:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-1141","title":"U.S. Geological Survey science for the Wyoming Landscape Conservation Initiative—2015 annual report","docAbstract":"<p>This is the eighth annual report highlighting U.S. Geological Survey (USGS) science and decision-support activities conducted for the Wyoming Landscape Conservation Initiative (WLCI). The activities address specific management needs identified by WLCI partner agencies. In 2015, USGS scientists continued 24 WLCI projects in 5&nbsp;categories: (1) acquiring and analyzing resource-condition data to form a foundation for understanding and monitoring landscape conditions and projecting changes; (2) using new technologies to improve the scope and accuracy of landscape-scale monitoring and assessments, and applying them to monitor indicators of ecosystem conditions and the effectiveness of on-the-ground habitat projects; (3) conducting research to elucidate the mechanisms that drive wildlife and habitat responses to changing land uses; (4) managing and making accessible the large number of databases, maps, and other products being developed; and (5) coordinating efforts among WLCI partners, helping them to use USGS-developed decision-support tools, and integrating WLCI outcomes with future habitat enhancement and research projects. Of the 24 projects, 21 were ongoing, including those that entered new phases or more in-depth lines of inquiry, 2 were new, and 1 was completed.</p><p>A highlight of 2015 was the WLCI science conference sponsored by the USGS, Bureau of Land Management, and National Park Service in coordination with the Wyoming chapter of The Wildlife Society. Of 260 participants, 41 were USGS professionals representing 13 USGS science centers, field offices, and Cooperative Wildlife Research Units. Major themes of USGS presentations included using new technologies for developing more efficient research protocols for modeling and monitoring natural resources, researching effects of energy development and other land uses on wildlife species and habitats of concern, and modeling species distributions, population trends, habitat use, and effects of land-use changes. There was also a special session on the effectiveness of Wyoming’s Sage-Grouse Executive Order. Combined, USGS presentations provided WLCI partners with a wealth of information and conservation tools.</p><p>The project completed in 2015 yielded an index of important agricultural lands in the WLCI region. The index improves upon existing measures of agricultural productivity and provides planners and managers with additional values to consider when making decisions about land use and conservation actions. The two new projects include an analysis of satellite imagery to quantify sagebrush productivity and mortality, and an evaluation of how groundwater and small streams interact in the upper Green River Basin. Initiated in response to concern among WLCI partners that large areas of sagebrush appear to have died recently, the sagebrush study objectives are to assess effects of these mortality events on overall sagebrush ecosystem productivity, evaluate the feasibility of using satellite imagery to detect patterns in sagebrush mortality over time, and identify factors driving these mortality events. The groundwater-streamflow interaction study is being conducted by hydrologists and fish ecologists to better understand how groundwater-streamflow interactions are affected by energy-resource development and how native fish communities are affected by these factors. Expected outcomes of both new projects will provide WLCI partners with additional information and decision-support tools.</p><p>Highlights of ongoing science foundation activities included simulations of nine alternative build-out scenarios for oil and gas development and an associated online fact sheet that explains how the simulations were conducted, with an applied example for the Atlantic Rim. Also completed in 2015 was an update of the USGS online inventory of mineral resources data, and publication of a USGS uranium resource survey for the WLCI region. Combined, the outcomes of this work provide decisionmakers and managers with important baseline information for existing and (or) future planning and monitoring efforts.</p><p>Terrestrial monitoring activities in 2015 emphasized the use of satellite data in combination with other technologies and field data to monitor, assess, and (or) forecast distribution patterns and (or) trends in sagebrush ecosystems, seasonal and migration stopover habitats used by mule deer and elk, and semi-arid aspen woodlands. Several professional papers detailing new monitoring models and results have been published. Combined, this and related work will help managers understand distribution patterns and trends among priority habitats, identify areas in need of restoration or conservation, and monitor the effectiveness of habitat-management actions.</p><p>Aquatic monitoring activities entailed not only the new groundwater-streamflow interaction study already mentioned, but also continued monitoring with streamgages paired with nearby wells in the Green River Basin to assess groundwater effects on streamflow and surface water temperatures. <span>A map that portrays groundwater levels and general direction of flow in the Green River Basin was published as well</span>. Overall, outcomes of USGS hydrological research and monitoring will inform WLCI partners about water resources in the WLCI region and help to explain fish-community responses to energy-resource development.</p><p>In 2015, USGS terrestrial wildlife ecologists continued to make crucial strides towards better understanding wildlife species responses to energy-resource development and other land-use changes. This body of research includes six taxa that require or heavily depend on sagebrush habitats: sage-grouse, pygmy rabbits, 3 songbird species, and mule deer. Native fish communities are also being evaluated. Approaches include modeling and mapping wildlife species distributions, abundances, and trends; using satellite and other technologies to track wildlife seasonal movements; conducting successive phases of research that build on the knowledge gained through prior phases to reveal the specific factors or thresholds that drive population- or individual-level responses to changes; and conducting population viability analyses. Additionally, wildlife habitat association models for pygmy rabbit and sage-grouse were combined with the oil and gas build-out scenarios to project species responses to alternative energy development scenarios. Outcomes of the wildlife response research are helping decisionmakers and managers identify specific factors that contribute to species population trends, the potential for spatial overlap between important wildlife habitats and proposed energy-resource development, locations of priority habitats for restoration and conservation, and more.</p><p>Data and WLCI Web site management highlights of 2015 included not only ongoing software upgrades, but also an update of the datasets displayed in two of the online products developed for the WLCI effort: (1) a map of 15,532 oil and natural gas well pad scars and other features associated with oil and gas extraction, and (2) a map of oil and gas, oil shale, uranium, and solar energy production, both for southwestern Wyoming. In addition, a map viewer was developed for a previously published map of coal and wind production in relation to sage-grouse distribution and core management areas in southwestern Wyoming. Combined, these maps place valuable decision-support tools in the hands of WLCI partners.</p><p>The USGS coordination efforts on behalf of the WLCI in 2015 included significant work on planning and executing the WLCI science conference. They also included ongoing efforts to support Local Project Development Teams and the WLCI Coordination Team (CT) with developing conservation priorities and strategies, identifying priority areas for future conservation actions, supporting the evaluation and ranking of conservation projects, and evaluating the ways in which proposed habitat projects relate to WLCI priorities. In 2015, the USGS also assisted the WLCI CT with updating the WLCI Conservation Action Plan.</p><p>&nbsp;</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161141","usgsCitation":"Bowen, Z.H., Aldridge, C.L., Anderson, P.J., Assal, T.J., Bartos, T.T., Chalfoun, A.D., Chong, G.W., Dematatis, M.K., Eddy-Miller, C.A., Garman, S.L., Germaine, S.S., Homer, C.G., Huber, C.C., Kauffman, M.J., Manier, D.J., Melcher, C.P., Miller, K.A., Norkin, Tamar, Sanders, L.E., Walters, A.W., Wilson, A.B., and Wyckoff, T.B., 2016, U.S. Geological Survey science for the Wyoming Landscape Conservation Initiative—2015 annual report: U.S. Geological Survey Open-File Report 2016–1141, 59 p., https://dx.doi.org/10.3133/ofr20161141.","productDescription":"viii, 59 p.","onlineOnly":"Y","ipdsId":"IP-075182","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":37226,"text":"Core Science Analytics, Synthesis, and Libraries","active":true,"usgs":true}],"links":[{"id":329020,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1141/coverthb.jpg"},{"id":329021,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1141/ofr20161141.pdf","text":"Report","size":"36.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1141"}],"country":"United States","state":"Wyoming","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -111.07177734375,\n              43.40504748787035\n            ],\n            [\n              -111.0498046875,\n              41\n            ],\n            [\n              -105.99609375,\n              41\n            ],\n            [\n              -105.99609375,\n              41.80407814427234\n            ],\n            [\n              -105.35888671875,\n              41.82045509614034\n            ],\n            [\n              -105.380859375,\n              42.47209690919285\n            ],\n            [\n              -106.5673828125,\n              42.52069952914966\n            ],\n            [\n              -107.20458984375,\n              42.48830197960227\n            ],\n            [\n              -107.70996093749999,\n              42.53689200787315\n            ],\n            [\n              -108.5009765625,\n              42.779275360241904\n            ],\n            [\n              -108.80859375,\n              42.98857645832184\n            ],\n            [\n              -109.22607421875,\n              43.229195113965005\n            ],\n            [\n              -109.3798828125,\n              43.42100882994726\n            ],\n            [\n              -109.79736328125,\n              43.5326204268101\n            ],\n            [\n              -110.41259765625,\n              43.56447158721811\n            ],\n            [\n              -111.07177734375,\n              43.40504748787035\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","contact":"<p>Director, Fort Collins Science Center<br>U.S. Geological Survey<br>2150 Centre Ave., Bldg. C<br>Fort Collins, CO 80526-8118</p><p><a href=\"http://www.fort.usgs.gov/\" target=\"_blank\" data-mce-href=\"http://www.fort.usgs.gov/\">http://www.fort.usgs.gov/</a></p>","tableOfContents":"<ul><li>Contributing Authors</li><li>Conversion Factors</li><li>Common and Scientific Names of Species in this Report</li><li>Abbreviations Used in this Report</li><li>Acknowledgments</li><li>Introduction</li><li>Highlights of FY2015 USGS WLCI Science Accomplishments</li><li>Project Reports: Baseline Synthesis</li><li>Project Reports: Long-Term Monitoring</li><li>Project Reports: Effectiveness Monitoring</li><li>Project Reports: Mechanistic Studies of Wildlife</li><li>Project Reports: Data and Information Management</li><li>References Cited and FY2015 WLCI Publications</li></ul>","publishingServiceCenter":{"id":2,"text":"Denver 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,{"id":70215765,"text":"70215765 - 2016 - Development and assessment of a new method for combining catch per unit effort data from different fish sampling gears: Multigear mean standardization (MGMS)","interactions":[],"lastModifiedDate":"2020-10-29T12:44:59.314739","indexId":"70215765","displayToPublicDate":"2016-09-28T07:42:15","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Development and assessment of a new method for combining catch per unit effort data from different fish sampling gears: Multigear mean standardization (MGMS)","docAbstract":"<div>Fish community assessments are often based on sampling with multiple gear types. However, multivariate methods used to assess fish community structure and composition are sensitive to differences in the relative scale of indices or measures of abundance produced by different sampling methods. This makes combining data from different sampling gears and methods a serious challenge. We developed a method of combining catch per unit effort data that standardizes catch per unit effort data across gear types, which we call multigear mean standardization (MGMS). We evaluated how well MGMS and other types of standardization reflect underlying community structure through a computer simulation that generated model riverine-fish communities and simulated sampling data for two gears. In these simulations, combining sampling observations from two gears with MGMS produced community structure estimates that were highly correlated with true community structure under a variety of conditions that are common in large rivers. Our simulation results indicate that the use of MGMS to combine data from different sampling gears is an effective data manipulation method for the analysis of fish community structure.</div>","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2016-0003","usgsCitation":"Gibson-Reinemer, D., Ickes, B., and Chick, J.H., 2016, Development and assessment of a new method for combining catch per unit effort data from different fish sampling gears: Multigear mean standardization (MGMS): Canadian Journal of Fisheries and Aquatic Sciences, v. 74, no. 1, p. 8-14, https://doi.org/10.1139/cjfas-2016-0003.","productDescription":"7 p.","startPage":"8","endPage":"14","ipdsId":"IP-071544","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":470549,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1139/cjfas-2016-0003","text":"Publisher Index Page"},{"id":379904,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"74","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Gibson-Reinemer, D.K. 0000-0002-8992-014X","orcid":"https://orcid.org/0000-0002-8992-014X","contributorId":244119,"corporation":false,"usgs":false,"family":"Gibson-Reinemer","given":"D.K.","affiliations":[{"id":48847,"text":"Illinois River Biological Station, Illinois Natural History Survey","active":true,"usgs":false}],"preferred":false,"id":803341,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ickes, Brian 0000-0001-5622-3842 bickes@usgs.gov","orcid":"https://orcid.org/0000-0001-5622-3842","contributorId":2925,"corporation":false,"usgs":true,"family":"Ickes","given":"Brian","email":"bickes@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":803342,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chick, John H.","contributorId":229508,"corporation":false,"usgs":false,"family":"Chick","given":"John","email":"","middleInitial":"H.","affiliations":[{"id":36894,"text":"Illinois Natural History Survey","active":true,"usgs":false}],"preferred":false,"id":803343,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70182813,"text":"70182813 - 2016 - Geoelectric hazard maps for the continental United States","interactions":[],"lastModifiedDate":"2020-07-13T14:44:19.319025","indexId":"70182813","displayToPublicDate":"2016-09-28T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Geoelectric hazard maps for the continental United States","docAbstract":"<p><span>In support of a multiagency project for assessing induction hazards, we present maps of extreme-value geoelectric amplitudes over about half of the continental United States. These maps are constructed using a parameterization of induction: estimates of Earth surface impedance, obtained at discrete geographic sites from magnetotelluric survey data, are convolved with latitude-dependent statistical maps of extreme-value geomagnetic activity, obtained from decades of magnetic observatory data. Geoelectric amplitudes are estimated for geomagnetic waveforms having 240&nbsp;s sinusoidal period and amplitudes over 10&nbsp;min that exceed a once-per-century threshold. As a result of the combination of geographic differences in geomagnetic activity and Earth surface impedance, once-per-century geoelectric amplitudes span more than 2 orders of magnitude and are an intricate function of location. For north-south induction, once-per-century geoelectric amplitudes across large parts of the United States have a median value of 0.26&nbsp;V/km; for east-west geomagnetic variation the median value is 0.23&nbsp;V/km. At some locations, once-per-century geoelectric amplitudes exceed 3&nbsp;V/km.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/2016GL070469","usgsCitation":"Love, J.J., Pulkkinen, A., Bedrosian, P.A., Jonas, S., Kelbert, A., Rigler, E., Finn, C., Balch, C., Rutledge, R., Waggel, R., Sabata, A., Kozyra, J., and Black, C., 2016, Geoelectric hazard maps for the continental United States: Geophysical Research Letters, v. 43, no. 18, p. 9415-9424, https://doi.org/10.1002/2016GL070469.","productDescription":"10 p.","startPage":"9415","endPage":"9424","ipdsId":"IP-079237","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":470551,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2016gl070469","text":"Publisher Index Page"},{"id":336739,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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,{"id":70180804,"text":"70180804 - 2016 - Demographic mechanisms underpinning genetic assimilation of remnant groups of a large carnivore","interactions":[],"lastModifiedDate":"2017-09-27T17:03:21","indexId":"70180804","displayToPublicDate":"2016-09-28T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3174,"text":"Proceedings of the Royal Society B: Biological Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Demographic mechanisms underpinning genetic assimilation of remnant groups of a large carnivore","docAbstract":"<p><span>Current range expansions of large terrestrial carnivores are occurring following human-induced range contraction. Contractions are often incomplete, leaving small remnant groups in refugia throughout the former range. Little is known about the underlying ecological and evolutionary processes that influence how remnant groups are affected during range expansion. We used data from a spatially explicit, long-term genetic sampling effort of grizzly bears (</span><i>Ursus arctos</i><span>) in the Northern Continental Divide Ecosystem (NCDE), USA, to identify the demographic processes underlying spatial and temporal patterns of genetic diversity. We conducted parentage analysis to evaluate how reproductive success and dispersal contribute to spatio-temporal patterns of genetic diversity in remnant groups of grizzly bears existing in the southwestern (SW), southeastern (SE) and east-central (EC) regions of the NCDE. A few reproductively dominant individuals and local inbreeding caused low genetic diversity in peripheral regions that may have persisted for multiple generations before eroding rapidly (approx. one generation) during population expansion. Our results highlight that individual-level genetic and reproductive dynamics play critical roles during genetic assimilation, and show that spatial patterns of genetic diversity on the leading edge of an expansion may result from historical demographic patterns that are highly ephemeral.</span></p>","language":"English","publisher":"The Royal Society Publishing","doi":"10.1098/rspb.2016.1467","usgsCitation":"Mikle, N., Graves, T.A., Kovach, R.P., Kendall, K.C., and Macleod, A., 2016, Demographic mechanisms underpinning genetic assimilation of remnant groups of a large carnivore: Proceedings of the Royal Society B: Biological Sciences, v. 283, no. 1839, https://doi.org/10.1098/rspb.2016.1467.","ipdsId":"IP-072646","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":470553,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1098/rspb.2016.1467","text":"Publisher Index Page"},{"id":334686,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":335575,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7Q81B63","text":"Northern Continental Divide Ecosystem grizzly bear (Ursus arctos) genetic profiles (1998-2012)"}],"country":"United States","otherGeospatial":"Northern Continental Divide Ecosystem","volume":"283","issue":"1839","noUsgsAuthors":false,"publicationDate":"2016-09-28","publicationStatus":"PW","scienceBaseUri":"5895a4c0e4b0fa1e59bc1e02","contributors":{"authors":[{"text":"Mikle, Nathaniel 0000-0002-6529-8210 nmikle@usgs.gov","orcid":"https://orcid.org/0000-0002-6529-8210","contributorId":177026,"corporation":false,"usgs":true,"family":"Mikle","given":"Nathaniel","email":"nmikle@usgs.gov","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":662475,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Graves, Tabitha A. 0000-0001-5145-2400 tgraves@usgs.gov","orcid":"https://orcid.org/0000-0001-5145-2400","contributorId":5898,"corporation":false,"usgs":true,"family":"Graves","given":"Tabitha","email":"tgraves@usgs.gov","middleInitial":"A.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":662476,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kovach, Ryan P. rkovach@usgs.gov","contributorId":5772,"corporation":false,"usgs":true,"family":"Kovach","given":"Ryan","email":"rkovach@usgs.gov","middleInitial":"P.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":false,"id":662477,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kendall, Katherine C. 0000-0002-4831-2287 kkendall@usgs.gov","orcid":"https://orcid.org/0000-0002-4831-2287","contributorId":3081,"corporation":false,"usgs":true,"family":"Kendall","given":"Katherine","email":"kkendall@usgs.gov","middleInitial":"C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":662478,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Macleod, Amy C.","contributorId":65739,"corporation":false,"usgs":true,"family":"Macleod","given":"Amy C.","affiliations":[],"preferred":false,"id":662479,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
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