{"pageNumber":"723","pageRowStart":"18050","pageSize":"25","recordCount":40783,"records":[{"id":70032496,"text":"70032496 - 2012 - Evidence for earthquake triggering of large landslides in coastal Oregon, USA","interactions":[],"lastModifiedDate":"2013-05-14T11:43:08","indexId":"70032496","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1801,"text":"Geomorphology","active":true,"publicationSubtype":{"id":10}},"title":"Evidence for earthquake triggering of large landslides in coastal Oregon, USA","docAbstract":"Landslides are ubiquitous along the Oregon coast. Many are large, deep slides in sedimentary rock and are dormant or active only during the rainy season. Morphology, observed movement rates, and total movement suggest that many are at least several hundreds of years old. The offshore Cascadia subduction zone produces great earthquakes every 300–500 years that generate tsunami that inundate the coast within minutes. Many slides and slide-prone areas underlie tsunami evacuation and emergency response routes. We evaluated the likelihood of existing and future large rockslides being triggered by pore-water pressure increase or earthquake-induced ground motion using field observations and modeling of three typical slides. Monitoring for 2–9 years indicated that the rockslides reactivate when pore pressures exceed readily identifiable levels. Measurements of total movement and observed movement rates suggest that two of the rockslides are 296–336 years old (the third could not be dated). The most recent great Cascadia earthquake was M 9.0 and occurred during January 1700, while regional climatological conditions have been stable for at least the past 600 years. Hence, the estimated ages of the slides support earthquake ground motion as their triggering mechanism. Limit-equilibrium slope-stability modeling suggests that increased pore-water pressures could not trigger formation of the observed slides, even when accompanied by progressive strength loss. Modeling suggests that ground accelerations comparable to those recorded at geologically similar sites during the M 9.0, 11 March 2011 Japan Trench subduction-zone earthquake would trigger formation of the rockslides. Displacement modeling following the Newmark approach suggests that the rockslides would move only centimeters upon coseismic formation; however, coseismic reactivation of existing rockslides would involve meters of displacement. Our findings provide better understanding of the dynamic coastal bluff environment and hazards from future subduction-zone earthquakes.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Geomorphology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.geomorph.2011.12.026","issn":"0169555X","usgsCitation":"Schulz, W., Galloway, S., and Higgins, J., 2012, Evidence for earthquake triggering of large landslides in coastal Oregon, USA: Geomorphology, v. 141-142, p. 88-98, https://doi.org/10.1016/j.geomorph.2011.12.026.","productDescription":"11 p.","startPage":"88","endPage":"98","costCenters":[],"links":[{"id":213971,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.geomorph.2011.12.026"},{"id":241649,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.61,42.0 ], [ -124.61,46.29 ], [ -116.46,46.29 ], [ -116.46,42.0 ], [ -124.61,42.0 ] ] ] } } ] }","volume":"141-142","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a0d3de4b0c8380cd52ec6","contributors":{"authors":[{"text":"Schulz, W.H.","contributorId":61225,"corporation":false,"usgs":true,"family":"Schulz","given":"W.H.","email":"","affiliations":[],"preferred":false,"id":436472,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Galloway, S.L.","contributorId":107945,"corporation":false,"usgs":true,"family":"Galloway","given":"S.L.","email":"","affiliations":[],"preferred":false,"id":436473,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Higgins, J.D.","contributorId":37154,"corporation":false,"usgs":true,"family":"Higgins","given":"J.D.","email":"","affiliations":[],"preferred":false,"id":436471,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70173603,"text":"70173603 - 2012 - Native rainbow smelt and nonnative alewife distribution related to temperature and light gradients in Lake Champlain","interactions":[],"lastModifiedDate":"2016-06-07T16:04:12","indexId":"70173603","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Native rainbow smelt and nonnative alewife distribution related to temperature and light gradients in Lake Champlain","docAbstract":"<p><span>Alewife (</span><i>Alosa pseudoharengus</i><span>) recently became established in Lake Champlain and may compete with native rainbow smelt (</span><i>Osmerus mordax</i><span>) for food or consume larval rainbow smelt. The strength of this effect depends partly on the spatial and temporal overlap of different age groups of the two species; therefore, we need a better understanding of factors affecting alewife and rainbow smelt distributions in Lake Champlain. We used hydroacoustics, trawls, and gill nets to document vertical fish distribution, and recorded environmental data during 16&nbsp;day&ndash;night surveys over two years. Temperature, temperature change, and light were all predictors of adult and age-0 rainbow smelt distribution, and temperature and light were predictors of age-0 alewives' distribution (based on GAMM models evaluated with AIC). Adult alewives were 5&ndash;30&nbsp;m shallower and age-0 alewives were 2&ndash;15&nbsp;m shallower than their rainbow smelt counterparts. Adult rainbow smelt distribution overlapped with age-0 rainbow smelt and age-0 alewives near the thermocline (10&ndash;25&nbsp;m), whereas adult alewives were shallower (0&ndash;6&nbsp;m) and overlapped with age-0 alewives and rainbow smelt in the epilimnion. Adult rainbow smelt were in water &lt;&nbsp;10&ndash;12&nbsp;&deg;C, whereas age-0 rainbow smelt were in 10&ndash;20&nbsp;&deg;C, and adult and age-0 alewives were in 15&ndash;22&nbsp;&deg;C water. Predicting these species distributions is necessary for quantifying the strength of predatory and competitive interactions between alewife and rainbow smelt, as well as between alewife and other fish species in Lake Champlain.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.jglr.2011.06.002","usgsCitation":"Parrish, D.L., Simonin, P.W., Rudstam, L.G., Sullivan, P., and Pientka, B., 2012, Native rainbow smelt and nonnative alewife distribution related to temperature and light gradients in Lake Champlain: Journal of Great Lakes Research, v. 38, no. 1, p. 115-122, https://doi.org/10.1016/j.jglr.2011.06.002.","productDescription":"8 p.","startPage":"115","endPage":"122","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-025329","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":323221,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Vermont","otherGeospatial":"Lake Champlain","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -73.22250366210938,\n              44.457309801319305\n            ],\n            [\n              -73.29391479492188,\n              44.46025037930627\n            ],\n            [\n              -73.33511352539062,\n              44.3670601700202\n            ],\n            [\n              -73.21563720703125,\n              44.37196862007497\n            ],\n            [\n              -73.21975708007812,\n              44.449467536006935\n            ],\n            [\n              -73.22250366210938,\n              44.457309801319305\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"38","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5757f062e4b04f417c24dcf6","contributors":{"authors":[{"text":"Parrish, Donna L. 0000-0001-9693-6329 dparrish@usgs.gov","orcid":"https://orcid.org/0000-0001-9693-6329","contributorId":138661,"corporation":false,"usgs":true,"family":"Parrish","given":"Donna","email":"dparrish@usgs.gov","middleInitial":"L.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":637392,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Simonin, Paul W.","contributorId":171499,"corporation":false,"usgs":false,"family":"Simonin","given":"Paul","email":"","middleInitial":"W.","affiliations":[{"id":18160,"text":"Rubenstein School of Environment and Natural Resources, University of Vermont","active":true,"usgs":false}],"preferred":false,"id":637741,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rudstam, Lars G.","contributorId":56609,"corporation":false,"usgs":false,"family":"Rudstam","given":"Lars","email":"","middleInitial":"G.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":637742,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sullivan, Patrick J.","contributorId":97813,"corporation":false,"usgs":true,"family":"Sullivan","given":"Patrick J.","affiliations":[],"preferred":false,"id":637743,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pientka, Bernard","contributorId":171500,"corporation":false,"usgs":false,"family":"Pientka","given":"Bernard","email":"","affiliations":[],"preferred":false,"id":637744,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70032402,"text":"70032402 - 2012 - Spatial interpolation schemes of daily precipitation for hydrologic modeling","interactions":[],"lastModifiedDate":"2020-12-01T22:44:17.77653","indexId":"70032402","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3478,"text":"Stochastic Environmental Research and Risk Assessment","active":true,"publicationSubtype":{"id":10}},"title":"Spatial interpolation schemes of daily precipitation for hydrologic modeling","docAbstract":"<p><span>Distributed hydrologic models typically require spatial estimates of precipitation interpolated from sparsely located observational points to the specific grid points. We compare and contrast the performance of regression-based statistical methods for the spatial estimation of precipitation in two hydrologically different basins and confirmed that widely used regression-based estimation schemes fail to describe the realistic spatial variability of daily precipitation field. The methods assessed are: (1) inverse distance weighted average; (2) multiple linear regression (MLR); (3) climatological MLR; and (4) locally weighted polynomial regression (LWP). In order to improve the performance of the interpolations, the authors propose a two-step regression technique for effective daily precipitation estimation. In this simple two-step estimation process, precipitation occurrence is first generated via a logistic regression model before estimate the amount of precipitation separately on wet days. This process generated the precipitation occurrence, amount, and spatial correlation effectively. A distributed hydrologic model (PRMS) was used for the impact analysis in daily time step simulation. Multiple simulations suggested noticeable differences between the input alternatives generated by three different interpolation schemes. Differences are shown in overall simulation error against the observations, degree of explained variability, and seasonal volumes. Simulated streamflows also showed different characteristics in mean, maximum, minimum, and peak flows. Given the same parameter optimization technique, LWP input showed least streamflow error in Alapaha basin and CMLR input showed least error (still very close to LWP) in Animas basin. All of the two-step interpolation inputs resulted in lower streamflow error compared to the directly interpolated inputs.</span></p>","language":"English","publisher":"Springer Link","doi":"10.1007/s00477-011-0509-1","issn":"14363240","usgsCitation":"Hwang, Y., Clark, M., Rajagopalan, B., and Leavesley, G.H., 2012, Spatial interpolation schemes of daily precipitation for hydrologic modeling: Stochastic Environmental Research and Risk Assessment, v. 26, no. 2, p. 295-320, https://doi.org/10.1007/s00477-011-0509-1.","productDescription":"26 p.","startPage":"295","endPage":"320","costCenters":[],"links":[{"id":214027,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s00477-011-0509-1"},{"id":241714,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, Georgia","otherGeospatial":"Durango, Statenville","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -108.0010986328125,\n              37.118716304960124\n            ],\n            [\n              -107.78961181640625,\n              37.118716304960124\n            ],\n            [\n              -107.78961181640625,\n              37.32102825630305\n            ],\n            [\n              -108.0010986328125,\n              37.32102825630305\n            ],\n            [\n              -108.0010986328125,\n              37.118716304960124\n            ]\n          ]\n        ]\n      }\n    },\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -84.078369140625,\n              30.637912028341123\n            ],\n            [\n              -82.85888671875,\n              30.637912028341123\n            ],\n            [\n              -82.85888671875,\n              32.519026027827515\n            ],\n            [\n              -84.078369140625,\n              32.519026027827515\n            ],\n            [\n              -84.078369140625,\n              30.637912028341123\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"26","issue":"2","noUsgsAuthors":false,"publicationDate":"2011-07-06","publicationStatus":"PW","scienceBaseUri":"505b9483e4b08c986b31ab31","contributors":{"authors":[{"text":"Hwang, Y.","contributorId":62034,"corporation":false,"usgs":true,"family":"Hwang","given":"Y.","email":"","affiliations":[],"preferred":false,"id":435983,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Clark, M.R.","contributorId":88135,"corporation":false,"usgs":true,"family":"Clark","given":"M.R.","email":"","affiliations":[],"preferred":false,"id":435985,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rajagopalan, B.","contributorId":86947,"corporation":false,"usgs":true,"family":"Rajagopalan","given":"B.","email":"","affiliations":[],"preferred":false,"id":435984,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Leavesley, George H. george@usgs.gov","contributorId":1202,"corporation":false,"usgs":true,"family":"Leavesley","given":"George","email":"george@usgs.gov","middleInitial":"H.","affiliations":[],"preferred":true,"id":435986,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70044132,"text":"70044132 - 2012 - Digital outcrop model of stratigraphy and breccias of the southern Franklin Mountains, El Paso, Texas","interactions":[],"lastModifiedDate":"2020-09-11T18:41:20.076485","indexId":"70044132","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"seriesTitle":{"id":606,"text":"AAPG Memoir","active":true,"publicationSubtype":{"id":10}},"title":"Digital outcrop model of stratigraphy and breccias of the southern Franklin Mountains, El Paso, Texas","docAbstract":"<p>This chapter reviews and synthesizes the lithostratigraphy, biostratigraphy, chronostratigraphy, and breccia types of the southwestern part of the great American carbonate bank in the southern Franklin Mountains (SFM), El Paso, Texas. Primary stratigraphic units of focus are the Lower Ordovician El Paso and Upper Ordovician Montoya Groups. These groups preserve breccias formed by collapse of a paleocave system. Precambrian and Silurian units are discussed in the context of breccia clast composition and relative timing of breccia emplacement. Specific attention is paid to the juxtaposition of the top-Sauk second-order supersequence unconformity between the El Paso and Montoya Groups and its relationship to breccias above and below it. The unconformity represents a 10-m.y. exposure event that separates Upper and Lower Ordovician carbonates. The top-Sauk exposure has been previously documented as a significant karst horizon across much of North America.</p><p>The breccias of the SFM were previously described as the result of collapsed paleocaves that formed during subaerial exposure related to the Sauk-Tippecanoe unconformity. A new approach in this work uses traditional field mapping combined with high-resolution (<img src=\"http://archives.datapages.com/data/specpubs/memoir98/CHAPTER36/IMAGES/LT.JPG\" alt=\"lt\" data-mce-src=\"http://archives.datapages.com/data/specpubs/memoir98/CHAPTER36/IMAGES/LT.JPG\">1-m [<img src=\"http://archives.datapages.com/data/specpubs/memoir98/CHAPTER36/IMAGES/LT.JPG\" alt=\"lt\" data-mce-src=\"http://archives.datapages.com/data/specpubs/memoir98/CHAPTER36/IMAGES/LT.JPG\">3.3-ft] point spacing) airborne light detection and ranging (LIDAR) data over 24 km<sup>2</sup><span>&nbsp;</span>(9 mi<sup>2</sup>) to map breccia and relevant stratal surfaces. Airborne LIDAR data were used to create a digital outcrop model of the SFM from which a detailed (1:2000 scale) geologic map was created. The geologic map includes formation, fault, and breccia contacts. The digital outcrop model was used to interpret three-dimensional spatial relationships of breccia bodies with respect to the current understanding of the tectonic and stratigraphic evolution of the SFM. The data presented here are used to discuss potential stratigraphic, temporal, and tectonic controls on the formation of caves within the study area that eventually collapsed to form the breccias currently exposed in outcrop.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"The great American carbonate bank: The geology and economic resources of the Cambrian-Ordovician Sauk megasequence of Laurentia","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"AAPG","publisherLocation":"Tulsa, OK","doi":"10.1306/13331521M983516","usgsCitation":"Bellian, J.A., Kerans, C., and Repetski, J.E., 2012, Digital outcrop model of stratigraphy and breccias of the southern Franklin Mountains, El Paso, Texas, chap. <i>of</i> The great American carbonate bank: The geology and economic resources of the Cambrian-Ordovician Sauk megasequence of Laurentia: AAPG Memoir, v. 98, p. 909-939, https://doi.org/10.1306/13331521M983516.","productDescription":"31 p.","startPage":"909","endPage":"939","numberOfPages":"31","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-042949","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":270970,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":298191,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://archives.datapages.com/data/specpubs/memoir98/CHAPTER36/CHAPTER36.HTM"}],"country":"United States","state":"Texas","city":"El Paso","otherGeospatial":"Franklin Mountains","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -106.56944274902344,\n              31.766121200173643\n            ],\n            [\n              -106.56944274902344,\n              31.99875937194732\n            ],\n            [\n              -106.43074035644531,\n              31.99875937194732\n            ],\n            [\n              -106.43074035644531,\n              31.766121200173643\n            ],\n            [\n              -106.56944274902344,\n              31.766121200173643\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"98","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"516e64d8e4b00154e4368b5b","contributors":{"editors":[{"text":"Derby, James R.","contributorId":68207,"corporation":false,"usgs":false,"family":"Derby","given":"James","email":"","middleInitial":"R.","affiliations":[{"id":13326,"text":"The University of Tulsa","active":true,"usgs":false}],"preferred":false,"id":509234,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Fritz, R.D.","contributorId":113600,"corporation":false,"usgs":true,"family":"Fritz","given":"R.D.","email":"","affiliations":[],"preferred":false,"id":509237,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Longacre, S.A.","contributorId":112394,"corporation":false,"usgs":true,"family":"Longacre","given":"S.A.","email":"","affiliations":[],"preferred":false,"id":509235,"contributorType":{"id":2,"text":"Editors"},"rank":3},{"text":"Morgan, W.A.","contributorId":21228,"corporation":false,"usgs":true,"family":"Morgan","given":"W.A.","email":"","affiliations":[],"preferred":false,"id":509233,"contributorType":{"id":2,"text":"Editors"},"rank":4},{"text":"Sternbach, C.A.","contributorId":113505,"corporation":false,"usgs":true,"family":"Sternbach","given":"C.A.","email":"","affiliations":[],"preferred":false,"id":509236,"contributorType":{"id":2,"text":"Editors"},"rank":5}],"authors":[{"text":"Bellian, Jerome A.","contributorId":139515,"corporation":false,"usgs":false,"family":"Bellian","given":"Jerome","email":"","middleInitial":"A.","affiliations":[{"id":12430,"text":"University of Texas at Austin","active":true,"usgs":false}],"preferred":false,"id":541613,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kerans, Charles","contributorId":75838,"corporation":false,"usgs":false,"family":"Kerans","given":"Charles","email":"","affiliations":[{"id":12430,"text":"University of Texas at Austin","active":true,"usgs":false}],"preferred":false,"id":474848,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Repetski, John E. 0000-0002-2298-7120 jrepetski@usgs.gov","orcid":"https://orcid.org/0000-0002-2298-7120","contributorId":2596,"corporation":false,"usgs":true,"family":"Repetski","given":"John","email":"jrepetski@usgs.gov","middleInitial":"E.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":474847,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70136359,"text":"70136359 - 2012 - Can arsenic occurrence rate in bedrock aquifers be predicted?","interactions":[],"lastModifiedDate":"2014-12-30T14:15:38","indexId":"70136359","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Can arsenic occurrence rate in bedrock aquifers be predicted?","docAbstract":"<p><span>A high percentage (31%) of groundwater samples from bedrock aquifers in the greater Augusta area, Maine was found to contain greater than 10 &mu;g L</span><span>&ndash;1</span><span>&nbsp;of arsenic. Elevated arsenic concentrations are associated with bedrock geology, and more frequently observed in samples with high pH, low dissolved oxygen, and low nitrate. These associations were quantitatively compared by statistical analysis. Stepwise logistic regression models using bedrock geology and/or water chemistry parameters are developed and tested with external data sets to explore the feasibility of predicting groundwater arsenic occurrence rates (the percentages of arsenic concentrations higher than 10 &mu;g L</span><span>&ndash;1</span><span>) in bedrock aquifers. Despite the under-prediction of high arsenic occurrence rates, models including groundwater geochemistry parameters predict arsenic occurrence rates better than those with bedrock geology only. Such simple models with very few parameters can be applied to obtain a preliminary arsenic risk assessment in bedrock aquifers at local to intermediate scales at other localities with similar geology.</span></p>","language":"English","publisher":"American Chemical Society","doi":"10.1021/es203793x","usgsCitation":"Yang, Q., Jung, H.B., Marvinney, R.G., Culbertson, C.W., and Zheng, Y., 2012, Can arsenic occurrence rate in bedrock aquifers be predicted?: Environmental Science & Technology, v. 46, no. 4, p. 2080-2087, https://doi.org/10.1021/es203793x.","productDescription":"8 p.","startPage":"2080","endPage":"2087","numberOfPages":"8","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-034607","costCenters":[{"id":371,"text":"Maine Water Science Center","active":true,"usgs":true}],"links":[{"id":474645,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.7916/d8rn3jhw","text":"External Repository"},{"id":296941,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"46","issue":"4","noUsgsAuthors":false,"publicationDate":"2012-02-09","publicationStatus":"PW","scienceBaseUri":"54dd2b4ae4b08de9379b32fd","contributors":{"authors":[{"text":"Yang, Qiang","contributorId":131129,"corporation":false,"usgs":false,"family":"Yang","given":"Qiang","email":"","affiliations":[{"id":7255,"text":"City University of New York, Queens College","active":true,"usgs":false}],"preferred":false,"id":537444,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jung, Hun Bok","contributorId":131128,"corporation":false,"usgs":false,"family":"Jung","given":"Hun","email":"","middleInitial":"Bok","affiliations":[{"id":7255,"text":"City University of New York, Queens College","active":true,"usgs":false}],"preferred":false,"id":537445,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Marvinney, Robert G.","contributorId":131130,"corporation":false,"usgs":false,"family":"Marvinney","given":"Robert","email":"","middleInitial":"G.","affiliations":[{"id":7257,"text":"Maine Geological Survey","active":true,"usgs":false}],"preferred":false,"id":537446,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Culbertson, Charles W. cculbert@usgs.gov","contributorId":1607,"corporation":false,"usgs":true,"family":"Culbertson","given":"Charles","email":"cculbert@usgs.gov","middleInitial":"W.","affiliations":[{"id":371,"text":"Maine Water Science Center","active":true,"usgs":true}],"preferred":true,"id":537447,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zheng, Yan","contributorId":99046,"corporation":false,"usgs":false,"family":"Zheng","given":"Yan","email":"","affiliations":[{"id":7255,"text":"City University of New York, Queens College","active":true,"usgs":false}],"preferred":false,"id":537448,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70032390,"text":"70032390 - 2012 - Temporal scaling of groundwater level fluctuations near a stream","interactions":[],"lastModifiedDate":"2020-12-02T13:01:19.21464","indexId":"70032390","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1861,"text":"Ground Water","active":true,"publicationSubtype":{"id":10}},"title":"Temporal scaling of groundwater level fluctuations near a stream","docAbstract":"<p>Temporal scaling in stream discharge and hydraulic heads in riparian wells was evaluated to determine the feasibility of using spectral analysis to identify potential surface and groundwater interaction. In floodplains where groundwater levels respond rapidly to precipitation recharge, potential interaction is established if the hydraulic head (h) spectrum of riparian groundwater has a power spectral density similar to stream discharge (Q), exhibiting a characteristic breakpoint between high and low frequencies. At a field site in Walnut Creek watershed in central Iowa, spectral analysis of h in wells located 1 m from the channel edge showed a breakpoint in scaling very similar to the spectrum of Q (∼20 h), whereas h in wells located 20 and 40 m from the channel showed temporal scaling from 1 to 10,000 h without a well‐defined breakpoint. The spectral exponent (β) in the riparian zone decreased systematically from the channel into the floodplain as groundwater levels were increasingly dominated by white noise groundwater recharge. The scaling pattern of hydraulic head was not affected by land cover type, although the number of analyses was limited and site conditions were variable among sites. Spectral analysis would not replace quantitative tracer or modeling studies, but the method may provide a simple means of confirming potential interaction at some sites.</p>","language":"English","publisher":"National Ground Water Association","doi":"10.1111/j.1745-6584.2011.00804.x","issn":"0017467X","usgsCitation":"Schilling, K.E., and Zhang, Y., 2012, Temporal scaling of groundwater level fluctuations near a stream: Ground Water, v. 50, no. 1, p. 59-67, https://doi.org/10.1111/j.1745-6584.2011.00804.x.","productDescription":"9 p.","startPage":"59","endPage":"67","costCenters":[],"links":[{"id":241506,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":213844,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/j.1745-6584.2011.00804.x"}],"country":"United States","state":"Iowa","county":"Jasper County","otherGeospatial":"Walnut Creek Watershed","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-93.234,41.8622],[-93.1187,41.8624],[-93.0035,41.8624],[-92.8845,41.8619],[-92.7674,41.8618],[-92.7683,41.776],[-92.768,41.6879],[-92.7683,41.6007],[-92.7567,41.6011],[-92.7564,41.509],[-92.8729,41.5082],[-92.9894,41.5083],[-93.1047,41.5078],[-93.2181,41.5076],[-93.3304,41.5074],[-93.3314,41.6004],[-93.3504,41.6004],[-93.3496,41.688],[-93.3494,41.7757],[-93.3492,41.8624],[-93.234,41.8622]]]},\"properties\":{\"name\":\"Jasper\",\"state\":\"IA\"}}]}","volume":"50","issue":"1","noUsgsAuthors":false,"publicationDate":"2011-02-25","publicationStatus":"PW","scienceBaseUri":"505ba518e4b08c986b3207e1","contributors":{"authors":[{"text":"Schilling, K. E.","contributorId":61982,"corporation":false,"usgs":true,"family":"Schilling","given":"K.","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":435922,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zhang, Y.-K.","contributorId":44309,"corporation":false,"usgs":true,"family":"Zhang","given":"Y.-K.","email":"","affiliations":[],"preferred":false,"id":435921,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70154812,"text":"70154812 - 2012 - Exploring similarities among many species distributions","interactions":[],"lastModifiedDate":"2015-08-20T11:25:31","indexId":"70154812","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Exploring similarities among many species distributions","docAbstract":"<p><span>Collecting species presence data and then building models to predict species distribution has been long practiced in the field of ecology for the purpose of improving our understanding of species relationships with each other and with the environment. Due to limitations of computing power as well as limited means of using modeling software on HPC facilities, past species distribution studies have been unable to fully explore diverse data sets. We build a system that can, for the first time to our knowledge, leverage HPC to support effective exploration of species similarities in distribution as well as their dependencies on common environmental conditions. Our system can also compute and reveal uncertainties in the modeling results enabling domain experts to make informed judgments about the data. Our work was motivated by and centered around data collection efforts within the Great Smoky Mountains National Park that date back to the 1940s. Our findings present new research opportunities in ecology and produce actionable field-work items for biodiversity management personnel to include in their planning of daily management activities.</span></p>","largerWorkType":{"id":24,"text":"Conference Paper"},"largerWorkTitle":"Proceedings of the 1st Conference of the Extreme Science and Engineering Discovery Environment: Bridging from the eXtreme to the campus and beyond","largerWorkSubtype":{"id":19,"text":"Conference Paper"},"conferenceTitle":"1st Conference of the Extreme Science and Engineering Discovery Environment: Bridging from the eXtreme to the campus and beyond","conferenceDate":"July 16-20, 2012","conferenceLocation":"Chicago, IL","language":"English","publisher":"ACM","doi":"10.1145/2335755.2335835","usgsCitation":"Simmerman, S., Wang, J., Osborne, J., Shook, K., Huang, J., Godsoe, W., and Simons, T.R., 2012, Exploring similarities among many species distributions, <i>in</i> Proceedings of the 1st Conference of the Extreme Science and Engineering Discovery Environment: Bridging from the eXtreme to the campus and beyond, Chicago, IL, July 16-20, 2012, art38, https://doi.org/10.1145/2335755.2335835.","productDescription":"art38","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-038608","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":307001,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2012-07-16","publicationStatus":"PW","scienceBaseUri":"55d6fa32e4b0518e3546bc3a","contributors":{"authors":[{"text":"Simmerman, Scott","contributorId":146748,"corporation":false,"usgs":false,"family":"Simmerman","given":"Scott","email":"","affiliations":[],"preferred":false,"id":568863,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wang, Jingyuan","contributorId":10771,"corporation":false,"usgs":false,"family":"Wang","given":"Jingyuan","email":"","affiliations":[],"preferred":false,"id":568864,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Osborne, James","contributorId":92188,"corporation":false,"usgs":true,"family":"Osborne","given":"James","email":"","affiliations":[],"preferred":false,"id":568865,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shook, Kimberly","contributorId":146749,"corporation":false,"usgs":false,"family":"Shook","given":"Kimberly","email":"","affiliations":[],"preferred":false,"id":568866,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hu, Jia","contributorId":146750,"corporation":false,"usgs":false,"family":"Hu","given":"Jia","affiliations":[],"preferred":false,"id":568867,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Godsoe, William","contributorId":131175,"corporation":false,"usgs":false,"family":"Godsoe","given":"William","email":"","affiliations":[{"id":6711,"text":"University of Idaho, Moscow ID","active":true,"usgs":false}],"preferred":false,"id":568868,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Simons, Theodore R. 0000-0002-1884-6229 tsimons@usgs.gov","orcid":"https://orcid.org/0000-0002-1884-6229","contributorId":2623,"corporation":false,"usgs":true,"family":"Simons","given":"Theodore","email":"tsimons@usgs.gov","middleInitial":"R.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":564226,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70189578,"text":"70189578 - 2012 - Copper(II) binding by dissolved organic matter: Importance of the copper-to-dissolved organic matter ratio and implications for the Biotic Ligand Model","interactions":[],"lastModifiedDate":"2017-07-17T16:51:31","indexId":"70189578","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Copper(II) binding by dissolved organic matter: Importance of the copper-to-dissolved organic matter ratio and implications for the Biotic Ligand Model","docAbstract":"<p><span>The ratio of copper to dissolved organic matter (DOM) is known to affect the strength of copper binding by DOM, but previous methods to determine the Cu</span><sup>2+</sup><span>–DOM binding strength have generally not measured binding constants over the same Cu:DOM ratios. In this study, we used a competitive ligand exchange–solid-phase extraction (CLE-SPE) method to determine conditional stability constants for Cu</span><sup>2+</sup><span>–DOM binding at pH 6.6 and 0.01 M ionic strength over a range of Cu:DOM ratios that bridge the detection windows of copper-ion-selective electrode and voltammetry measurements. As the Cu:DOM ratio increased from 0.0005 to 0.1 mg of Cu/mg of DOM, the measured conditional binding constant (</span><sup>c</sup><i>K</i><sub>CuDOM</sub><span>) decreased from 10</span><sup>11.5</sup><span><span>&nbsp;</span>to 10</span><sup>5.6</sup><span><span>&nbsp;</span>M</span><sup>–1</sup><span>. A comparison of the binding constants measured by CLE-SPE with those measured by copper-ion-selective electrode and voltammetry demonstrates that the Cu:DOM ratio is an important factor controlling Cu</span><sup>2+</sup><span>–DOM binding strength even for DOM isolates of different types and different sources and for whole water samples. The results were modeled with Visual MINTEQ and compared to results from the biotic ligand model (BLM). The BLM was found to over-estimate Cu</span><sup>2+</sup><span><span>&nbsp;</span>at low total copper concentrations and under-estimate Cu</span><sup>2+</sup><span><span>&nbsp;</span>at high total copper concentrations.</span></p>","language":"English","publisher":"ACS","doi":"10.1021/es301015p","usgsCitation":"Craven, A.M., Aiken, G.R., and Ryan, J.N., 2012, Copper(II) binding by dissolved organic matter: Importance of the copper-to-dissolved organic matter ratio and implications for the Biotic Ligand Model: Environmental Science & Technology, v. 46, no. 18, p. 9948-9955, https://doi.org/10.1021/es301015p.","productDescription":"8 p.","startPage":"9948","endPage":"9955","ipdsId":"IP-036934","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":343959,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"46","issue":"18","noUsgsAuthors":false,"publicationDate":"2012-08-30","publicationStatus":"PW","scienceBaseUri":"596dcca6e4b0d1f9f062757f","contributors":{"authors":[{"text":"Craven, Alison M.","contributorId":194767,"corporation":false,"usgs":false,"family":"Craven","given":"Alison","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":705290,"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":705291,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ryan, Joseph N.","contributorId":54290,"corporation":false,"usgs":false,"family":"Ryan","given":"Joseph","email":"","middleInitial":"N.","affiliations":[{"id":604,"text":"University of Colorado- Boulder","active":false,"usgs":true}],"preferred":false,"id":705292,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70189575,"text":"70189575 - 2012 - Identifying fluorescent pulp mill effluent in the Gulf of Maine and its watershed","interactions":[],"lastModifiedDate":"2018-02-21T17:41:04","indexId":"70189575","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2676,"text":"Marine Pollution Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"Identifying fluorescent pulp mill effluent in the Gulf of Maine and its watershed","docAbstract":"<p><span>Using fluorescence spectroscopy and parallel factor analysis (PARAFAC) we characterized and modeled the fluorescence properties of dissolved organic matter (DOM) in samples from the Penobscot River, Androscoggin River, Penobscot Bay, and the Gulf of Maine (GoM). We analyzed excitation-emission matrices (EEMs) using an existing PARAFAC model (</span>Cory and McKnight, 2005<span>) and created a system-specific model with seven components (GoM PARAFAC). The GoM PARAFAC model contained six components similar to those in other PARAFAC models and one unique component with a spectrum similar to a residual found using the<span>&nbsp;</span></span>Cory and McKnight (2005)<span><span>&nbsp;</span>model. The unique component was abundant in samples from the Androscoggin River immediately downstream of a pulp mill effluent release site. The detection of a PARAFAC component associated with an anthropogenic source of DOM, such as pulp mill effluent, demonstrates the importance for rigorously analyzing PARAFAC residuals and developing system-specific models.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.marpolbul.2012.05.040","usgsCitation":"Cawley, K.M., Butler, K.D., Aiken, G.R., Larsen, L., Huntington, T.G., and McKnight, D.M., 2012, Identifying fluorescent pulp mill effluent in the Gulf of Maine and its watershed: Marine Pollution Bulletin, v. 64, no. 8, p. 1678-1687, https://doi.org/10.1016/j.marpolbul.2012.05.040.","productDescription":"10 p.","startPage":"1678","endPage":"1687","ipdsId":"IP-036937","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":343956,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maine","otherGeospatial":"Gulf of Maine","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -70.99639892578125,\n              43.30919109985686\n            ],\n            [\n              -66.533203125,\n              43.30919109985686\n            ],\n            [\n              -66.533203125,\n              46.37725420510028\n            ],\n            [\n              -70.99639892578125,\n              46.37725420510028\n            ],\n            [\n              -70.99639892578125,\n              43.30919109985686\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"64","issue":"8","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"596dcca7e4b0d1f9f0627583","contributors":{"authors":[{"text":"Cawley, Kaelin M.","contributorId":194765,"corporation":false,"usgs":false,"family":"Cawley","given":"Kaelin","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":705277,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":705278,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":705279,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Larsen, Laurel G. lglarsen@usgs.gov","contributorId":1987,"corporation":false,"usgs":true,"family":"Larsen","given":"Laurel G.","email":"lglarsen@usgs.gov","affiliations":[],"preferred":false,"id":705280,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Huntington, Thomas G. 0000-0002-9427-3530 thunting@usgs.gov","orcid":"https://orcid.org/0000-0002-9427-3530","contributorId":1884,"corporation":false,"usgs":true,"family":"Huntington","given":"Thomas","email":"thunting@usgs.gov","middleInitial":"G.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":371,"text":"Maine Water Science Center","active":true,"usgs":true}],"preferred":true,"id":705281,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McKnight, Diane M.","contributorId":59773,"corporation":false,"usgs":false,"family":"McKnight","given":"Diane","email":"","middleInitial":"M.","affiliations":[{"id":16833,"text":"INSTAAR, University of Colorado","active":true,"usgs":false}],"preferred":false,"id":705282,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70044967,"text":"70044967 - 2012 - Ore genesis constraints on the Idaho Cobalt Belt from fluid inclusion gas, noble gas isotope, and ion ratio analyses","interactions":[],"lastModifiedDate":"2020-01-10T15:05:07","indexId":"70044967","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1472,"text":"Economic Geology","active":true,"publicationSubtype":{"id":10}},"title":"Ore genesis constraints on the Idaho Cobalt Belt from fluid inclusion gas, noble gas isotope, and ion ratio analyses","docAbstract":"<p>The Idaho cobalt belt is a 60-km-long alignment of deposits composed of cobaltite, Co pyrite, chalcopyrite, and gold with anomalous Nb, Y, Be, and rare-earth elements (REEs) in a quartz-biotite-tourmaline gangue hosted in Mesoproterozoic metasedimentary rocks of the Lemhi Group. It is the largest cobalt resource in the United States with historic production from the Blackbird Mine. All of the deposits were deformed and metamorphosed to upper greenschist-lower amphibolite grade in the Cretaceous. They occur near a 1377 Ma anorogenic bimodal plutonic complex. The enhanced solubility of Fe, Co, Cu, and Au as chloride complexes together with gangue biotite rich in Fe and Cl and gangue quartz containing hypersaline inclusions allows that hot saline fluids were involved. The isotopes of B in gangue tourmaline are suggestive of a marine source, whereas those of Pb in ore suggest a U ± Th-enriched source.</p><p>The ore and gangue minerals in this belt may have trapped components in fluid inclusions that are distinct from those in post-ore minerals and metamorphic minerals. Such components can potentially be identified and distinguished by their relative abundances in contrasting samples. Therefore, we obtained samples of Co and Cu sulfides, gangue quartz, biotite, and tourmaline and post-ore quartz veins as well as Cretaceous metamorphic garnet and determined the gas, noble gas isotope, and ion ratios of fluid inclusion extracts by mass spectrometry and ion chromatography.</p><p>The most abundant gases present in extracts from each sample type are biased toward the gas-rich population of inclusions trapped during maximum burial and metamorphism. All have CO<sub>2</sub>/CH<sub>4</sub><span>&nbsp;</span>and N<sub>2</sub>/Ar ratios of evolved crustal fluids, and many yield a range of H<sub>2</sub>-CH<sub>4</sub>-CO<sub>2</sub>-H<sub>2</sub>S equilibration temperatures consistent with the metamorphic grade. Cretaceous garnet and post-ore minerals have high R<sub>H</sub><span>&nbsp;</span>and R<sub>S</sub><span>&nbsp;</span>values suggestive of reduced sulfidic conditions. Most extracts have anomalous<span>&nbsp;</span><sup>4</sup>He produced by decay of U and Th and<span>&nbsp;</span><sup>38</sup>Ar produced by nucleogenic production from<span>&nbsp;</span><sup>41</sup>K. In contrast, some ore and gangue minerals yield significant SO<sub>2</sub><span>&nbsp;</span>and have low R<sub>H</sub><span>&nbsp;</span>and R<sub>S</sub><span>&nbsp;</span>values of a more oxidized fluid. Three extracts from gangue quartz have high helium R/R<sub>A</sub><span>&nbsp;</span>values indicative of a mantle source and neon isotope compositions that require nucleogenic production of<span>&nbsp;</span><sup>22</sup>Ne in fluorite from U ± Th decay. Two extracts from gangue quartz have estimated<span>&nbsp;</span><sup>40</sup>K/<sup>40</sup>Ar that permit a Precambrian age.</p><p>Extracts from gangue quartz in three different ore zones are biased toward the hypersaline population of inclusions and have a tight range of ion ratios (Na, K, NH<sub>4</sub>, Cl, Br, F) suggestive of a single fluid. Their Na, Cl, Br ratios suggest this fluid was a mixture of magmatic and basinal brine. Na-K-Ca temperatures (279°–347°C) are similar to homogenization temperatures of hypersaline inclusions. The high K/Na of the brine may be due to albitization of K silicate minerals in country rocks. Influx of K-rich brines is consistent with the K metasomatism necessary to form gangue biotite with high Cl. An extract from a post-ore quartz vein is distinct and has Na, Cl, Br ratios that resemble metamorphic fluids in Cretaceous silver veins of the Coeur d’Alene district in the Belt Basin.</p><p>The results show that in some samples, for certain components, it is possible to “see through” the Cretaceous metamorphic overprint. Of great import for genetic models, the volatiles trapped in gangue quartz have<span>&nbsp;</span><sup>3</sup>He derived from a mantle source and<span>&nbsp;</span><sup>22</sup>Ne derived from fluorite, both of which may be attributed to nearby ~1377 Ma basalt-rhyolite magmatism. The brine trapped in gangue quartz is a mixture of magmatic fluid and evaporated seawater. The former requires a granitic intrusion that is present in the bimodal intrusive complex, and the latter equatorial paleolatitudes that existed in the Mesoproterozoic. The results permit genetic models involving heat and fluids from the neighboring bimodal plutonic complex and convection of basinal brine in the Lemhi Group. While the inferred fluid sources in the Idaho cobalt belt are similar in many respects to those in iron oxide copper-gold deposits, the fluids were more reduced such that iron was fixed in biotite and tourmaline instead of iron oxides.</p>","language":"English","publisher":"Society of Economic Geologists","publisherLocation":"Littleton, CO","doi":"10.2113/econgeo.107.6.1189","usgsCitation":"Hofstra, A.H., and Landis, G.P., 2012, Ore genesis constraints on the Idaho Cobalt Belt from fluid inclusion gas, noble gas isotope, and ion ratio analyses: Economic Geology, v. 107, no. 6, p. 1189-1205, https://doi.org/10.2113/econgeo.107.6.1189.","productDescription":"17 p.","startPage":"1189","endPage":"1205","numberOfPages":"17","additionalOnlineFiles":"N","ipdsId":"IP-033500","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":270441,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -114.508438,44.9784 ], [ -114.508438,45.124413 ], [ -114.077911,45.124413 ], [ -114.077911,44.9784 ], [ -114.508438,44.9784 ] ] ] } } ] }","volume":"107","issue":"6","noUsgsAuthors":false,"publicationDate":"2012-09-20","publicationStatus":"PW","scienceBaseUri":"515bfdf7e4b075500ee5ca7f","contributors":{"authors":[{"text":"Hofstra, Albert H. 0000-0002-2450-1593 ahofstra@usgs.gov","orcid":"https://orcid.org/0000-0002-2450-1593","contributorId":1302,"corporation":false,"usgs":true,"family":"Hofstra","given":"Albert","email":"ahofstra@usgs.gov","middleInitial":"H.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":476533,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Landis, Gary P.","contributorId":72405,"corporation":false,"usgs":true,"family":"Landis","given":"Gary","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":476534,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70035654,"text":"70035654 - 2012 - Recent paleorecords document rising mercury contamination in Lake Tanganyika","interactions":[],"lastModifiedDate":"2020-11-16T21:20:59.329352","indexId":"70035654","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","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":"Recent paleorecords document rising mercury contamination in Lake Tanganyika","docAbstract":"<p><span>Recent Lake Tanganyika Hg deposition records were derived using&nbsp;</span><sup>14</sup><span>C and excess&nbsp;</span><sup>210</sup><span>Pb geochronometers in sediment cores collected from two contrasting depositional environments: the Kalya Platform, located mid-lake and more removed from watershed impacts, and the Nyasanga/Kahama River delta region, located close to the lake’s shoreline north of Kigoma. At the Kalya Platform area, pre-industrial Hg concentrations are 23</span><span>&nbsp;</span><span>±</span><span>&nbsp;</span><span>0.2</span><span>&nbsp;</span><span>ng/g, increasing to 74</span><span>&nbsp;</span><span>ng/g in modern surface sediment, and the Hg accumulation rate has increased from 1.0 to 7.2</span><span>&nbsp;</span><span>μg/m</span><sup>2</sup><span>/a from pre-industrial to present, which overall represents a 6-fold increase in Hg concentration and accumulation. At the Nyasanga/Kahama delta region, pre-industrial Hg concentrations are 20</span><span>&nbsp;</span><span>±</span><span>&nbsp;</span><span>3</span><span>&nbsp;</span><span>ng/g, increasing to 46</span><span>&nbsp;</span><span>ng/g in surface sediment. Mercury accumulation rate has increased from 30 to 70</span><span>&nbsp;</span><span>μg/m</span><sup>2</sup><span>/a at this site, representing a 2–3-fold increase in Hg concentration and accumulation. There is a lack of correlation between charcoal abundance and Hg accumulation rate in the sediment cores, demonstrating that local biomass burning has little relationship with the observed Hg concentration or Hg accumulation rates. Examined using a sediment focusing-corrected mass accumulation rate approach, the cores have similar anthropogenic atmospheric Hg deposition profiles, suggesting that after accounting for background sediment concentrations the source of accumulating Hg is predominantly atmospheric in origin. In summary, the data document an increase of Hg flux to the Lake Tanganyika ecosystem that is consistent with increasing watershed sediment delivery with background-level Hg contamination, and regional as well as global increases in atmospheric Hg deposition.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.apgeochem.2011.11.005","issn":"08832927","usgsCitation":"Conaway, C.H., Swarzenski, P.W., and Cohen, A., 2012, Recent paleorecords document rising mercury contamination in Lake Tanganyika: Applied Geochemistry, v. 27, no. 1, p. 352-359, https://doi.org/10.1016/j.apgeochem.2011.11.005.","productDescription":"8 p.","startPage":"352","endPage":"359","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":244359,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":216486,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.apgeochem.2011.11.005"}],"country":"United States","county":"Tanzania, the Democratic Republic of the Congo , Burundi, and Zambia","otherGeospatial":"Lake Tanganyika","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              28.872070312500004,\n              -3.2063329870791315\n            ],\n            [\n              28.872070312500004,\n              -5.98760689165826\n            ],\n            [\n              30.344238281249996,\n              -8.646195681181904\n            ],\n            [\n              31.09130859375,\n              -9.123792057073972\n            ],\n            [\n              31.61865234375,\n              -8.885071663468981\n            ],\n            [\n              29.487304687499996,\n              -3.118576216781991\n            ],\n            [\n              28.872070312500004,\n              -3.2063329870791315\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"27","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a9630e4b0c8380cd81e5b","contributors":{"authors":[{"text":"Conaway, Christopher H. 0000-0002-0991-033X cconaway@usgs.gov","orcid":"https://orcid.org/0000-0002-0991-033X","contributorId":5074,"corporation":false,"usgs":true,"family":"Conaway","given":"Christopher","email":"cconaway@usgs.gov","middleInitial":"H.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":451690,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Swarzenski, Peter W. 0000-0003-0116-0578 pswarzen@usgs.gov","orcid":"https://orcid.org/0000-0003-0116-0578","contributorId":1070,"corporation":false,"usgs":true,"family":"Swarzenski","given":"Peter","email":"pswarzen@usgs.gov","middleInitial":"W.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":451689,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cohen, A.S.","contributorId":19313,"corporation":false,"usgs":true,"family":"Cohen","given":"A.S.","email":"","affiliations":[],"preferred":false,"id":451688,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70035652,"text":"70035652 - 2012 - Initiation of long-term coupled microbiological, geochemical, and hydrological experimentation within the seafloor at North Pond, western flank of the Mid-Atlantic Ridge","interactions":[],"lastModifiedDate":"2020-11-24T12:33:25.521792","indexId":"70035652","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2007,"text":"Integrated Ocean Drilling Program: Preliminary Reports","active":true,"publicationSubtype":{"id":10}},"title":"Initiation of long-term coupled microbiological, geochemical, and hydrological experimentation within the seafloor at North Pond, western flank of the Mid-Atlantic Ridge","docAbstract":"<p>Integrated Ocean Drilling Program (IODP) Expedition 336 successfully initiated subseafloor observatory science at a young mid-ocean-ridge flank setting. All of the drilled sites are located in the North Pond region of the Atlantic Ocean (22°45′N, 46°05′W) in 4414–4483 m water depth. This area is known from previous ocean drilling and site survey investigations as a site of particularly vigorous circulation of seawater in permeable 8 Ma basaltic basement underlying a &lt;300 m thick sedimentary pile. Understanding how this seawater circulation affects microbial and geochemical processes in the uppermost basement was the primary science objective of Expedition 336. </p><p>Basement was cored and wireline-logged in Holes U1382A and U1383C. Upper oceanic crust in Hole U1382A, which is only 50 m west of Deep Sea Drilling Project (DSDP) Hole 395A, recovered 32 m of core between 110 and 210 meters below seafloor (mbsf). Core recovery in basement was 32%, yielding a number of volcanic flow units with distinct geochemical and petrographic characteristics. A unit of sedimentary breccia containing clasts of basalt, gabbroic rocks, and mantle peridotite was found intercalated between two volcanic flow units and was interpreted as a rock slide deposit. From Hole U1383C we recovered 50.3 m of core between 69.5 and 331.5 mbsf (19%). The basalts are aphyric to highly plagioclase-olivine-phyric tholeiites that fall on a liquid line of descent controlled by olivine fractionation. They are fresh to moderately altered, with clay minerals (saponite, nontronite, and celadonite), Fe oxyhydroxide, carbonate, and zeolite as secondary phases replacing glass and olivine to variable extents. In addition to traditional downhole logs, we also used a new logging tool for detecting in situ microbial life in ocean floor boreholes—the Deep Exploration Biosphere Investigative tool (DEBI-t). </p><p>Sediment thickness was ~90 m at Sites U1382 and U1384 and varied between 38 and 53 m at Site U1383. The sediments are predominantly nannofossil ooze with layers of coarse foraminiferal sand and occasional pebble-size clasts of basalt, serpentinite, gabbroic rocks, and bivalve debris. The bottommost meters of sections cored with the advanced piston corer feature brown clay. Extended core barrel coring at the sediment/ basement interface recovered &lt;1 m of brecciated basalt with micritic limestone. Sediments were intensely sampled for geochemical pore water analyses and microbiological work. In addition, high-resolution measurements of dissolved oxygen concentration were performed on the whole-round sediment cores</p><p>Major strides in ridge-flank studies have been made with subseafloor borehole observatories (CORKs) because they facilitate combined hydrological, geochemical, and microbiological studies and controlled experimentation in the subseafloor. During Expedition 336, two fully functional observatories were installed in two newly drilled holes (U1382A and U1383C) and an instrument and sampling string were placed in an existing hole (395A). Although the CORK wellhead in Hole 395A broke off and Hole U1383B was abandoned after a bit failure, these holes and installations are intended for future observatory science targets. The CORK observatory in Hole U1382A has a packer seal in the bottom of the casing and monitors/samples a single zone in uppermost oceanic crust extending from 90 to 210 mbsf. Hole U1383C was equipped with a three-level CORK observatory that spans a zone of thin basalt flows with intercalated limestone (~70–146 mbsf), a zone of glassy, thin basaltic flows and hyaloclastites (146–200 mbsf), and a lowermost zone (~200–331.5 mbsf) of more massive pillow flows with occasional hyaloclastites in the upper part.</p>","language":"English","publisher":"IODP","doi":"10.2204/iodp.pr.336.2012","issn":"19329423","usgsCitation":"Edwards, K., Backert, N., Bach, W., Becker, K., Klaus, A., Griffin, D., Anderson, L., Haddad, A., Harigane, Y., Campion, P., Hirayama, H., Mills, H., Hulme, S., Nakamura, K., Jorgensen, S., Orcutt, B., Insua, T., Park, Y., Rennie, V., Salas, E., Rouxel, O., Wang, F., Russel, J., Wheat, C., Sakata, K., Brown, M., Magnusson, J., and Ettlinger, Z., 2012, Initiation of long-term coupled microbiological, geochemical, and hydrological experimentation within the seafloor at North Pond, western flank of the Mid-Atlantic Ridge: Integrated Ocean Drilling Program: Preliminary Reports, p. 1-72, https://doi.org/10.2204/iodp.pr.336.2012.","productDescription":"336, 72 p.","startPage":"1","endPage":"72","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":474682,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2204/iodp.pr.336.2012","text":"Publisher Index Page"},{"id":244327,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2012-01-09","publicationStatus":"PW","scienceBaseUri":"505a3bf1e4b0c8380cd62951","contributors":{"authors":[{"text":"Edwards, K.J.","contributorId":101090,"corporation":false,"usgs":true,"family":"Edwards","given":"K.J.","email":"","affiliations":[],"preferred":false,"id":451666,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Backert, N.","contributorId":51127,"corporation":false,"usgs":true,"family":"Backert","given":"N.","email":"","affiliations":[],"preferred":false,"id":451650,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bach, W.","contributorId":65673,"corporation":false,"usgs":true,"family":"Bach","given":"W.","affiliations":[],"preferred":false,"id":451656,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Becker, K.","contributorId":96437,"corporation":false,"usgs":true,"family":"Becker","given":"K.","affiliations":[],"preferred":false,"id":451664,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Klaus, A.","contributorId":70957,"corporation":false,"usgs":true,"family":"Klaus","given":"A.","email":"","affiliations":[],"preferred":false,"id":451658,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Griffin, Dale W.","contributorId":23668,"corporation":false,"usgs":true,"family":"Griffin","given":"Dale W.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":451646,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Anderson, L.","contributorId":22571,"corporation":false,"usgs":false,"family":"Anderson","given":"L.","affiliations":[],"preferred":false,"id":451645,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Haddad, A.G.","contributorId":52427,"corporation":false,"usgs":true,"family":"Haddad","given":"A.G.","email":"","affiliations":[],"preferred":false,"id":451651,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Harigane, Y.","contributorId":16673,"corporation":false,"usgs":true,"family":"Harigane","given":"Y.","email":"","affiliations":[],"preferred":false,"id":451641,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Campion, 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,{"id":70044875,"text":"70044875 - 2012 - Mineral resource of the month: manganese","interactions":[],"lastModifiedDate":"2013-05-08T16:49:54","indexId":"70044875","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1419,"text":"Earth","active":true,"publicationSubtype":{"id":10}},"title":"Mineral resource of the month: manganese","docAbstract":"Manganese is a silver-colored metal resembling iron and often found in conjunction with iron. The earliest-known human use of manganese compounds was in the Stone Age, when early humans used manganese dioxide as pigments in cave paintings. In ancient Rome and Egypt, people started using it to color or remove the color from glass - a practice that continued to modern times. Today, manganese is predominantly used in metallurgical applications as an alloying addition, particularly in steel and cast iron production. Steel and cast iron together provide the largest market for manganese (historically 85 to 90 percent), but it is also alloyed with nonferrous metals such as aluminum and copper. Its importance to steel cannot be overstated, as almost all types of steel contain manganese and could not exist without it.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Earth","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Geosciences Institute","publisherLocation":"Alexandria, VA","usgsCitation":"Corathers, L.A., 2012, Mineral resource of the month: manganese: Earth, v. 57, no. 5, p. 23-23.","productDescription":"1 p.","startPage":"23","endPage":"23","additionalOnlineFiles":"N","ipdsId":"IP-036063","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":270511,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":270508,"type":{"id":11,"text":"Document"},"url":"https://www.agiweb.org/store/library/imprint.php?id=2012_05"}],"volume":"57","issue":"5","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"515bfdf2e4b075500ee5ca63","contributors":{"authors":[{"text":"Corathers, Lisa A. lcorathers@usgs.gov","contributorId":3213,"corporation":false,"usgs":true,"family":"Corathers","given":"Lisa","email":"lcorathers@usgs.gov","middleInitial":"A.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":false,"id":476426,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70032723,"text":"70032723 - 2012 - On valuing patches: Estimating contributions to metapopulation growth with reverse-time capture-recapture modelling","interactions":[],"lastModifiedDate":"2020-11-24T12:47:05.824503","indexId":"70032723","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","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":"On valuing patches: Estimating contributions to metapopulation growth with reverse-time capture-recapture modelling","docAbstract":"<p><span>Metapopulation ecology has historically been rich in theory, yet analytical approaches for inferring demographic relationships among local populations have been few. We show how reverse-time multi-state capture–recapture models can be used to estimate the importance of local recruitment and interpopulation dispersal to metapopulation growth. We use ‘contribution metrics’ to infer demographic connectedness among eight local populations of banner-tailed kangaroo rats, to assess their demographic closure, and to investigate sources of variation in these contributions. Using a 7 year dataset, we show that: (i) local populations are relatively independent demographically, and contributions to local population growth via dispersal within the system decline with distance; (ii) growth contributions via local survival and recruitment are greater for adults than juveniles, while contributions involving dispersal are greater for juveniles; (iii) central populations rely more on local recruitment and survival than peripheral populations; (iv) contributions involving dispersal are not clearly related to overall metapopulation density; and (v) estimated contributions from outside the system are unexpectedly large. Our analytical framework can classify metapopulations on a continuum between demographic independence and panmixia, detect hidden population growth contributions, and make inference about other population linkage forms, including rescue effects and source–sink structures. Finally, we discuss differences between demographic and genetic population linkage patterns for our system.</span></p>","language":"English","publisher":"Royal Publishing Society","doi":"10.1098/rspb.2011.0885","issn":"09628452","usgsCitation":"Sanderlin, J., Waser, P., Hines, J., and Nichols, J., 2012, On valuing patches: Estimating contributions to metapopulation growth with reverse-time capture-recapture modelling: Proceedings of the Royal Society B: Biological Sciences, v. 279, no. 1728, p. 480-488, https://doi.org/10.1098/rspb.2011.0885.","productDescription":"9 p.","startPage":"480","endPage":"488","costCenters":[],"links":[{"id":474651,"rank":10000,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1098/rspb.2011.0885","text":"Publisher Index Page"},{"id":241459,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":213800,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1098/rspb.2011.0885"}],"country":"United States","state":"Arizona","county":"Cochise County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-109.0478,32.4251],[-109.0478,32.4059],[-109.0478,32.4016],[-109.0479,32.3866],[-109.0479,32.3576],[-109.048,32.3257],[-109.048,32.3111],[-109.0481,32.266],[-109.0481,32.2514],[-109.0486,32.0745],[-109.0486,32.0391],[-109.0486,31.9747],[-109.0487,31.9592],[-109.0487,31.9408],[-109.0488,31.9112],[-109.0495,31.6101],[-109.0496,31.5944],[-109.0498,31.5717],[-109.0494,31.506],[-109.0497,31.4862],[-109.0498,31.4497],[-109.0499,31.436],[-109.0501,31.3809],[-109.0501,31.3699],[-109.05,31.3319],[-109.2268,31.3323],[-109.2788,31.3322],[-109.3678,31.3321],[-109.3844,31.332],[-109.4021,31.332],[-109.4182,31.3324],[-109.4857,31.3321],[-109.7532,31.3324],[-109.7585,31.3324],[-109.7904,31.3323],[-109.9462,31.3324],[-110.0011,31.3323],[-110.1457,31.3321],[-110.3642,31.3319],[-110.4413,31.3318],[-110.4603,31.3318],[-110.4611,31.3328],[-110.4561,31.3328],[-110.4562,31.4684],[-110.4555,31.5871],[-110.4558,31.6017],[-110.4561,31.6154],[-110.448,31.6157],[-110.4483,31.6536],[-110.4482,31.6883],[-110.4485,31.702],[-110.4485,31.7307],[-110.4482,31.7462],[-110.4484,31.7622],[-110.4481,31.7759],[-110.4467,31.9054],[-110.447,31.9209],[-110.4477,31.993],[-110.4482,32.0518],[-110.4484,32.0668],[-110.4482,32.0801],[-110.446,32.0805],[-110.4444,32.1657],[-110.4443,32.1712],[-110.4437,32.2551],[-110.447,32.2551],[-110.4472,32.2701],[-110.448,32.4274],[-110.3448,32.4268],[-110.3453,32.4255],[-110.2981,32.4252],[-110.2888,32.4255],[-110.2785,32.4254],[-110.2731,32.4258],[-110.2638,32.4256],[-110.2584,32.426],[-110.2296,32.426],[-110.2117,32.4257],[-110.1617,32.4258],[-110.1112,32.4259],[-110.0422,32.4266],[-109.9396,32.4252],[-109.8375,32.4256],[-109.7353,32.4258],[-109.6327,32.4242],[-109.5311,32.4243],[-109.5116,32.4244],[-109.4947,32.4244],[-109.461,32.4241],[-109.4442,32.4242],[-109.4274,32.4248],[-109.3258,32.4238],[-109.3084,32.4234],[-109.2916,32.4234],[-109.2579,32.423],[-109.2405,32.4226],[-109.2242,32.4227],[-109.2242,32.4245],[-109.2068,32.425],[-109.1894,32.4246],[-109.1726,32.4246],[-109.1552,32.4251],[-109.1394,32.4251],[-109.122,32.4252],[-109.1131,32.4251],[-109.0786,32.4249],[-109.0478,32.4251]]]},\"properties\":{\"name\":\"Cochise\",\"state\":\"AZ\"}}]}","volume":"279","issue":"1728","noUsgsAuthors":false,"publicationDate":"2011-06-22","publicationStatus":"PW","scienceBaseUri":"505a6e17e4b0c8380cd754ad","contributors":{"authors":[{"text":"Sanderlin, J.S.","contributorId":98122,"corporation":false,"usgs":true,"family":"Sanderlin","given":"J.S.","affiliations":[],"preferred":false,"id":437635,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Waser, P.M.","contributorId":66454,"corporation":false,"usgs":true,"family":"Waser","given":"P.M.","affiliations":[],"preferred":false,"id":437634,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hines, J.E. 0000-0001-5478-7230","orcid":"https://orcid.org/0000-0001-5478-7230","contributorId":36885,"corporation":false,"usgs":true,"family":"Hines","given":"J.E.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":437633,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nichols, J.D. 0000-0002-7631-2890","orcid":"https://orcid.org/0000-0002-7631-2890","contributorId":14332,"corporation":false,"usgs":true,"family":"Nichols","given":"J.D.","affiliations":[],"preferred":false,"id":437632,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70032722,"text":"70032722 - 2012 - Roost networks of northern myotis (Myotis septentrionalis) in a managed landscape","interactions":[],"lastModifiedDate":"2020-11-23T19:36:25.630698","indexId":"70032722","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1687,"text":"Forest Ecology and Management","active":true,"publicationSubtype":{"id":10}},"title":"Roost networks of northern myotis (Myotis septentrionalis) in a managed landscape","docAbstract":"<p><span>Maternity groups of many bat species conform to fission–fusion models and movements among diurnal roost trees and individual bats belonging to these groups use networks of roost trees. Forest disturbances may alter roost networks and characteristics of roost trees. Therefore, at the Fernow Experimental Forest in West Virginia, we examined roost tree networks of northern myotis (</span><i>Myotis septentrionalis</i><span>) in forest stands subjected to prescribed fire and in unmanipulated control treatments in 2008 and 2009. Northern myotis formed social groups whose roost areas and roost tree networks overlapped to some extent. Roost tree networks largely resembled scale-free network models, as 61% had a single central node roost tree. In control treatments, central node roost trees were in early stages of decay and surrounded by greater basal area than other trees within the networks. In prescribed fire treatments, central node roost trees were small in diameter, low in the forest canopy, and surrounded by low basal area compared to other trees in networks. Our results indicate that forest disturbances, including prescribed fire, can affect availability and distribution of roosts within roost tree networks.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.foreco.2011.11.032","issn":"03781127","usgsCitation":"Johnson, J., Ford, W.M., and Edwards, J., 2012, Roost networks of northern myotis (Myotis septentrionalis) in a managed landscape: Forest Ecology and Management, v. 266, p. 223-231, https://doi.org/10.1016/j.foreco.2011.11.032.","productDescription":"9 p.","startPage":"223","endPage":"231","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":241425,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":213768,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.foreco.2011.11.032"}],"country":"United States","otherGeospatial":"West 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Mark wford@usgs.gov","contributorId":3858,"corporation":false,"usgs":true,"family":"Ford","given":"W.","email":"wford@usgs.gov","middleInitial":"Mark","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":437631,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Edwards, J.W.","contributorId":62002,"corporation":false,"usgs":true,"family":"Edwards","given":"J.W.","email":"","affiliations":[],"preferred":false,"id":437630,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70032695,"text":"70032695 - 2012 - Calibration of amino acid racemization (AAR) kinetics in United States mid-Atlantic Coastal Plain Quaternary mollusks using  87Sr/ 86Sr analyses: Evaluation of kinetic models and estimation of regional Late Pleistocene temperature history","interactions":[],"lastModifiedDate":"2020-11-23T19:59:30.299013","indexId":"70032695","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3216,"text":"Quaternary Geochronology","active":true,"publicationSubtype":{"id":10}},"title":"Calibration of amino acid racemization (AAR) kinetics in United States mid-Atlantic Coastal Plain Quaternary mollusks using  87Sr/ 86Sr analyses: Evaluation of kinetic models and estimation of regional Late Pleistocene temperature history","docAbstract":"<p><span>The use of amino acid&nbsp;<a title=\"Learn more about Racemization from ScienceDirect's AI-generated Topic Pages\" href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/racemization\" data-mce-href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/racemization\">racemization</a>&nbsp;(AAR) for estimating ages of Quaternary fossils usually requires a combination of kinetic and effective temperature modeling or independent age calibration of analyzed samples. Because of limited availability of calibration samples, age estimates are often based on model extrapolations from single calibration points over wide ranges of D/L values. Here we present paired AAR and&nbsp;</span><sup>87</sup><span>Sr/</span><sup>86</sup><span>Sr results for Pleistocene mollusks from the North Carolina Coastal Plain, USA.&nbsp;</span><sup>87</sup><span>Sr/</span><sup>86</sup><span>Sr age estimates, derived from the lookup table of McArthur et&nbsp;al. [McArthur, J.M., Howarth, R.J., Bailey, T.R., 2001.&nbsp;<a title=\"Learn more about Strontium from ScienceDirect's AI-generated Topic Pages\" href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/strontium\" data-mce-href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/strontium\">Strontium</a>&nbsp;isotopic stratigraphy: LOWESS version 3: best fit to the marine Sr-isotopic curve for 0–509 Ma and accompanying Look-up table for deriving numerical age. Journal of Geology 109, 155–169], provide independent age calibration over the full range of amino acid D/L values, thereby allowing comparisons of alternative kinetic models for seven amino acids. The often-used parabolic kinetic model is found to be insufficient to explain the pattern of racemization, although the kinetic pathways for valine racemization and isoleucine epimerization can be closely approximated with this function. Logarithmic and power law regressions more accurately represent the racemization pathways for all amino acids. The reliability of a non-linear model for&nbsp;<a title=\"Learn more about Leucine from ScienceDirect's AI-generated Topic Pages\" href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/leucine\" data-mce-href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/leucine\">leucine</a>&nbsp;racemization, developed and refined over the past 20 years, is confirmed by the&nbsp;</span><sup>87</sup><span>Sr/</span><sup>86</sup><span>Sr age results. This age model indicates that the subsurface record (up to 80</span><span>&nbsp;</span><span>m thick) of the North Carolina Coastal Plain spans the entire Quaternary, back to ∼2.5</span><span>&nbsp;</span><span>Ma. The calibrated kinetics derived from this age model yield an estimate of the effective temperature for the study region of 11</span><span>&nbsp;</span><span>±</span><span>&nbsp;</span><span>2</span><span>&nbsp;</span><span>°C., from which we estimate full glacial (Last Glacial Maximum – LGM) temperatures for the region on the order of 7–10</span><span>&nbsp;</span><span>°C cooler than present. These temperatures compare favorably with independent&nbsp;<a title=\"Learn more about Paleoclimate from ScienceDirect's AI-generated Topic Pages\" href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/paleoclimate\" data-mce-href=\"https://www.sciencedirect.com/topics/earth-and-planetary-sciences/paleoclimate\">paleoclimate</a>&nbsp;information for the region.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.quageo.2011.09.005","issn":"18711014","usgsCitation":"Wehmiller, J., Harris, W., Boutin, B., and Farrell, K., 2012, Calibration of amino acid racemization (AAR) kinetics in United States mid-Atlantic Coastal Plain Quaternary mollusks using  87Sr/ 86Sr analyses: Evaluation of kinetic models and estimation of regional Late Pleistocene temperature history: Quaternary Geochronology, v. 7, no. 1, p. 21-36, https://doi.org/10.1016/j.quageo.2011.09.005.","productDescription":"16 p.","startPage":"21","endPage":"36","costCenters":[],"links":[{"id":241528,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":213863,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.quageo.2011.09.005"}],"country":"United States","state":"Delaware, Florida, Georgia, Maryland, New Jersey, North Carolina, South Carolina, Virginia,","otherGeospatial":"United States Atlantic Coastal Plain","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -84.990234375,\n              29.611670115197377\n            ],\n            [\n              -82.44140625,\n              24.766784522874453\n            ],\n            [\n              -80.85937499999999,\n              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K.M.","contributorId":106573,"corporation":false,"usgs":true,"family":"Farrell","given":"K.M.","email":"","affiliations":[],"preferred":false,"id":437493,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70032694,"text":"70032694 - 2012 - Incidence of adult brain cancers is higher in countries where the protozoan parasite <i>Toxoplasma gondii</i> is common","interactions":[],"lastModifiedDate":"2014-09-18T13:28:00","indexId":"70032694","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1028,"text":"Biology Letters","active":true,"publicationSubtype":{"id":10}},"title":"Incidence of adult brain cancers is higher in countries where the protozoan parasite <i>Toxoplasma gondii</i> is common","docAbstract":"We explored associations between the common protozoan parasite <i>Toxoplasma gondii</i> and brain cancers in human populations. We predicted that <i>T. gondii</i> could increase the risk of brain cancer because it is a long-lived parasite that encysts in the brain, where it provokes inflammation and inhibits apoptosis. We used a medical geography approach based on the national incidence of brain cancers and seroprevalence of <i>T. gondii</i>. We corrected reports of incidence for national gross domestic product because wealth probably increases the ability to detect cancer. We also included gender, cell phone use and latitude as variables in our initial models. Prevalence of <i>T. gondii</i> explained 19 per cent of the residual variance in brain cancer incidence after controlling for the positive effects of gross domestic product and latitude among nations. Infection with <i>T. gondii</i> was associated with a 1.8-fold increase in the risk of brain cancers across the range of <i>T. gondii</i> prevalence in our dataset (4–67%). These results, though correlational, suggest that <i>T. gondii</i> should be investigated further as a possible oncogenic pathogen of humans.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Biology Letters","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"The Royal Society","publisherLocation":"London","doi":"10.1098/rsbl.2011.0588","issn":"17449561","usgsCitation":"Thomas, F., Lafferty, K.D., Brodeur, J., Elguero, E., Gauthier-Clerc, M., and Misse, D., 2012, Incidence of adult brain cancers is higher in countries where the protozoan parasite <i>Toxoplasma gondii</i> is common: Biology Letters, v. 8, no. 1, p. 101-103, https://doi.org/10.1098/rsbl.2011.0588.","productDescription":"3 p.","startPage":"101","endPage":"103","numberOfPages":"3","costCenters":[],"links":[{"id":474734,"rank":10000,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1098/rsbl.2011.0588","text":"External Repository"},{"id":241527,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":213862,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1098/rsbl.2011.0588"}],"volume":"8","issue":"1","noUsgsAuthors":false,"publicationDate":"2011-07-27","publicationStatus":"PW","scienceBaseUri":"505a39d5e4b0c8380cd61a64","contributors":{"authors":[{"text":"Thomas, Frederic","contributorId":57275,"corporation":false,"usgs":true,"family":"Thomas","given":"Frederic","email":"","affiliations":[],"preferred":false,"id":437487,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lafferty, Kevin D. 0000-0001-7583-4593 klafferty@usgs.gov","orcid":"https://orcid.org/0000-0001-7583-4593","contributorId":1415,"corporation":false,"usgs":true,"family":"Lafferty","given":"Kevin","email":"klafferty@usgs.gov","middleInitial":"D.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":437484,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brodeur, Jacques","contributorId":47987,"corporation":false,"usgs":true,"family":"Brodeur","given":"Jacques","email":"","affiliations":[],"preferred":false,"id":437486,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Elguero, Eric","contributorId":80909,"corporation":false,"usgs":true,"family":"Elguero","given":"Eric","email":"","affiliations":[],"preferred":false,"id":437489,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gauthier-Clerc, Michel","contributorId":59639,"corporation":false,"usgs":true,"family":"Gauthier-Clerc","given":"Michel","email":"","affiliations":[],"preferred":false,"id":437488,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Misse, Dorothee","contributorId":29227,"corporation":false,"usgs":true,"family":"Misse","given":"Dorothee","email":"","affiliations":[],"preferred":false,"id":437485,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70032691,"text":"70032691 - 2012 - Increased atmospheric deposition of mercury in reference lakes near major urban areas","interactions":[],"lastModifiedDate":"2020-11-24T16:50:10.031699","indexId":"70032691","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1555,"text":"Environmental Pollution","active":true,"publicationSubtype":{"id":10}},"title":"Increased atmospheric deposition of mercury in reference lakes near major urban areas","docAbstract":"<p><span>Atmospheric deposition of Hg is the predominant pathway for Hg to reach sensitive ecosystems, but the importance of emissions on near-field deposition remains unclear. To better understand spatial variability in Hg deposition, mercury concentrations were analyzed in sediment cores from 12 lakes with undeveloped watersheds near to (&lt;50&nbsp;km) and remote from (&gt;150&nbsp;km) several major urban areas in the United States. Background and focusing corrected Hg fluxes and flux ratios (modern to background) in the near-urban lakes (68&nbsp;±&nbsp;6.9&nbsp;μg&nbsp;m</span><sup>−2</sup><span>&nbsp;yr</span><sup>−1</sup><span>&nbsp;and 9.8&nbsp;±&nbsp;4.8, respectively) greatly exceed those in the remote lakes (14&nbsp;±&nbsp;9.3&nbsp;μg&nbsp;m</span><sup>−2</sup><span>&nbsp;yr</span><sup>−1</sup><span>&nbsp;and 3.5&nbsp;±&nbsp;1.0) and the fluxes are strongly related to distance from the nearest major urban area (</span><i>r</i><sup>2</sup><span>&nbsp;=&nbsp;0.87) and to population and Hg emissions within 50–100&nbsp;km of the lakes. Comparison to monitored wet deposition suggests that dry deposition is a major contributor of Hg to lakes near major urban areas.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.envpol.2011.11.003","usgsCitation":"Van Metre, P., 2012, Increased atmospheric deposition of mercury in reference lakes near major urban areas: Environmental Pollution, v. 162, p. 209-215, https://doi.org/10.1016/j.envpol.2011.11.003.","productDescription":"7 p.","startPage":"209","endPage":"215","costCenters":[],"links":[{"id":241458,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":213799,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.envpol.2011.11.003"}],"country":"United 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States\"}}]}","volume":"162","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a39f4e4b0c8380cd61acd","contributors":{"authors":[{"text":"Van Metre, P. C.","contributorId":92999,"corporation":false,"usgs":true,"family":"Van Metre","given":"P. C.","affiliations":[],"preferred":false,"id":437470,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70032574,"text":"70032574 - 2012 - Regional scale impacts of <i>Tamarix</i> leaf beetles (<i>Diorhabda carinulata</i>) on the water availability of western U.S. rivers as determined by multi-scale remote sensing methods","interactions":[],"lastModifiedDate":"2017-11-25T14:17:42","indexId":"70032574","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"Regional scale impacts of <i>Tamarix</i> leaf beetles (<i>Diorhabda carinulata</i>) on the water availability of western U.S. rivers as determined by multi-scale remote sensing methods","docAbstract":"<i>Tamarix</i> leaf beetles (<i>Diorhabda carinulata</i>) have been widely released on western U.S. rivers to control introduced shrubs in the genus <i>Tamarix</i>. Part of the motivation to control <i>Tamarix</i> is to salvage water for human use. Information is needed on the impact of beetles on <i>Tamarix</i> seasonal leaf production and subsequent water use overwide areas andmultiple cycles of annual defoliation.Herewe combine ground data with high resolution phenocam imagery and moderate resolution (Landsat) and coarser resolution (MODIS) satellite imagery to test the effects of beetles on <i>Tamarix</i> evapotranspiration (ET) and leaf phenology at sites on six western rivers. Satellite imagery covered the period 2000 to 2010 which encompassed years before and after beetle release at each study site. Phenocam images showed that beetles reduced green leaf cover of individual canopies by about 30% during a 6-8 week period in summer, but plants produced new leaves after beetles became dormant in August, and over three years no net reduction in peak summer leaf production was noted. ETwas estimated by vegetation index methods, and both Landsat and MODIS analyses showed that beetles reduced ET markedly in the first year of defoliation, but ET recovered in subsequent years. Over all six sites, ET decreased by 14% to 15% by Landsat and MODIS estimates, respectively. However, resultswere variable among sites, ranging fromno apparent effect on ET to substantial reduction in ET. Baseline ET rates before defoliation were low, 394 mmyr<sup>-1</sup> by Landsat and 314 mm yr<sup>-1</sup> by MODIS estimates (20-25% of potential ET), further constraining the amount of water that could be salvaged. Beetle-<i>Tamarix</i> interactions are in their early stage of development on this continent and it is too soon to predict the eventual extent towhich <i>Tamarix</i> populationswill be reduced. The utility of remote sensing methods for monitoring defoliation was constrained by the small area covered by each phenocamimage, the low temporal resolution of Landsat, and the lowspatial resolution ofMODIS imagery. Even combined image sets did not adequately reveal the details of the defoliation process, and remote sensing data should be combined with ground observations to develop operational monitoring protocols.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Remote Sensing of Environment","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.rse.2011.11.011","issn":"00344257","usgsCitation":"Nagler, P.L., Brown, T., Hultine, K.R., van Riper, C., Bean, D., Dennison, P.E., Murray, R.S., and Glenn, E.P., 2012, Regional scale impacts of <i>Tamarix</i> leaf beetles (<i>Diorhabda carinulata</i>) on the water availability of western U.S. rivers as determined by multi-scale remote sensing methods: Remote Sensing of Environment, v. 118, p. 227-240, https://doi.org/10.1016/j.rse.2011.11.011.","productDescription":"14 p.","startPage":"227","endPage":"240","numberOfPages":"14","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":241759,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":214071,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.rse.2011.11.011"}],"country":"United States","state":"Colorado;Nevada;Utah;Wyoming","otherGeospatial":"Big Horn River;Humbolt River;Lower Delores River;Middle-upper Delores River;Upper Colorado River;Walker River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -120.0800,37.0000 ], [ -120.0800,45.0000 ], [ -106.3000,45.0000 ], [ -106.3000,37.0000 ], [ -120.0800,37.0000 ] ] ] } } ] }","volume":"118","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50788eb2e4b0cfc2d59f5b0d","contributors":{"authors":[{"text":"Nagler, Pamela L. 0000-0003-0674-103X pnagler@usgs.gov","orcid":"https://orcid.org/0000-0003-0674-103X","contributorId":1398,"corporation":false,"usgs":true,"family":"Nagler","given":"Pamela","email":"pnagler@usgs.gov","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":436882,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brown, Tim","contributorId":17841,"corporation":false,"usgs":true,"family":"Brown","given":"Tim","affiliations":[],"preferred":false,"id":436884,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hultine, Kevin R. 0000-0001-9747-6037","orcid":"https://orcid.org/0000-0001-9747-6037","contributorId":23772,"corporation":false,"usgs":true,"family":"Hultine","given":"Kevin","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":436886,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"van Riper, Charles III 0000-0003-1084-5843 charles_van_riper@usgs.gov","orcid":"https://orcid.org/0000-0003-1084-5843","contributorId":169488,"corporation":false,"usgs":true,"family":"van Riper","given":"Charles","suffix":"III","email":"charles_van_riper@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":false,"id":436888,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bean, Daniel W.","contributorId":11016,"corporation":false,"usgs":false,"family":"Bean","given":"Daniel W.","affiliations":[{"id":16124,"text":"Colorado Department of Agriculture, Biological Pest Control","active":true,"usgs":false}],"preferred":false,"id":436883,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dennison, Philip E.","contributorId":105132,"corporation":false,"usgs":true,"family":"Dennison","given":"Philip","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":436889,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Murray, R. Scott","contributorId":64468,"corporation":false,"usgs":true,"family":"Murray","given":"R.","email":"","middleInitial":"Scott","affiliations":[],"preferred":false,"id":436887,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Glenn, Edward P.","contributorId":19289,"corporation":false,"usgs":true,"family":"Glenn","given":"Edward","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":436885,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70032571,"text":"70032571 - 2012 - Design and quantification of an extreme winter storm scenario for emergency preparedness and planning exercises in California","interactions":[],"lastModifiedDate":"2020-11-30T21:27:04.790866","indexId":"70032571","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2822,"text":"Natural Hazards","active":true,"publicationSubtype":{"id":10}},"title":"Design and quantification of an extreme winter storm scenario for emergency preparedness and planning exercises in California","docAbstract":"<p><span>The USGS Multihazards Project is working with numerous agencies to evaluate and plan for hazards and damages that could be caused by extreme winter storms impacting California. Atmospheric and hydrological aspects of a hypothetical storm scenario have been quantified as a basis for estimation of human, infrastructure, economic, and environmental impacts for emergency-preparedness and flood-planning exercises. In order to ensure scientific defensibility and necessary levels of detail in the scenario description, selected historical storm episodes were concatentated to describe a rapid arrival of several major storms over the state, yielding precipitation totals and runoff rates beyond those occurring during the individual historical storms. This concatenation allowed the scenario designers to avoid arbitrary scalings and is based on historical occasions from the 19th and 20th Centuries when storms have stalled over the state and when extreme storms have arrived in rapid succession. Dynamically consistent, hourly precipitation, temperatures, barometric pressures (for consideration of storm surges and coastal erosion), and winds over California were developed for the so-called ARkStorm scenario by downscaling the concatenated global records of the historical storm sequences onto 6- and 2-km grids using a regional weather model of January 1969 and February 1986 storm conditions. The weather model outputs were then used to force a hydrologic model to simulate ARkStorm runoff, to better understand resulting flooding risks. Methods used to build this scenario can be applied to other emergency, nonemergency and non-California applications.</span></p>","language":"English","publisher":"Springer Link","doi":"10.1007/s11069-011-9894-5","issn":"0921030X","usgsCitation":"Dettinger, M.D., Martin, R.F., Hughes, M., Das, T., Neiman, P., Cox, D.A., Estes, G., Reynolds, D., Hartman, R., Cayan, D., and Jones, L., 2012, Design and quantification of an extreme winter storm scenario for emergency preparedness and planning exercises in California: Natural Hazards, v. 60, no. 3, p. 1085-1111, https://doi.org/10.1007/s11069-011-9894-5.","productDescription":"27 p.","startPage":"1085","endPage":"1111","costCenters":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":474740,"rank":10000,"type":{"id":40,"text":"Open Access Publisher Index 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D. 0000-0002-7509-7332","orcid":"https://orcid.org/0000-0002-7509-7332","contributorId":93069,"corporation":false,"usgs":false,"family":"Dettinger","given":"M.","middleInitial":"D.","affiliations":[{"id":16196,"text":"Scripps Institution of Oceanography, La Jolla, CA","active":true,"usgs":false}],"preferred":false,"id":436871,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Martin, Ralph F.","contributorId":43578,"corporation":false,"usgs":true,"family":"Martin","given":"Ralph","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":436866,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hughes, M.","contributorId":102699,"corporation":false,"usgs":true,"family":"Hughes","given":"M.","affiliations":[],"preferred":false,"id":436873,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Das, Tapash","contributorId":49227,"corporation":false,"usgs":true,"family":"Das","given":"Tapash","affiliations":[],"preferred":false,"id":436872,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Neiman, P.","contributorId":43183,"corporation":false,"usgs":true,"family":"Neiman","given":"P.","email":"","affiliations":[],"preferred":false,"id":436865,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cox, Dale A. 0000-0001-8302-3643 dacox@usgs.gov","orcid":"https://orcid.org/0000-0001-8302-3643","contributorId":203281,"corporation":false,"usgs":true,"family":"Cox","given":"Dale","email":"dacox@usgs.gov","middleInitial":"A.","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true}],"preferred":true,"id":436868,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Estes, G.","contributorId":107946,"corporation":false,"usgs":true,"family":"Estes","given":"G.","email":"","affiliations":[],"preferred":false,"id":436874,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Reynolds, D.","contributorId":76149,"corporation":false,"usgs":true,"family":"Reynolds","given":"D.","affiliations":[],"preferred":false,"id":436870,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hartman, R.","contributorId":74968,"corporation":false,"usgs":true,"family":"Hartman","given":"R.","email":"","affiliations":[],"preferred":false,"id":436869,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Cayan, Daniel drcayan@usgs.gov","contributorId":149912,"corporation":false,"usgs":true,"family":"Cayan","given":"Daniel","email":"drcayan@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":436867,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Jones, L.","contributorId":26084,"corporation":false,"usgs":true,"family":"Jones","given":"L.","affiliations":[],"preferred":false,"id":436864,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70032565,"text":"70032565 - 2012 - Mapping carbon flux uncertainty and selecting optimal locations for future flux towers in the Great Plains","interactions":[],"lastModifiedDate":"2018-02-23T13:12:35","indexId":"70032565","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2602,"text":"Landscape Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Mapping carbon flux uncertainty and selecting optimal locations for future flux towers in the Great Plains","docAbstract":"Flux tower networks (e. g., AmeriFlux, Agriflux) provide continuous observations of ecosystem exchanges of carbon (e. g., net ecosystem exchange), water vapor (e. g., evapotranspiration), and energy between terrestrial ecosystems and the atmosphere. The long-term time series of flux tower data are essential for studying and understanding terrestrial carbon cycles, ecosystem services, and climate changes. Currently, there are 13 flux towers located within the Great Plains (GP). The towers are sparsely distributed and do not adequately represent the varieties of vegetation cover types, climate conditions, and geophysical and biophysical conditions in the GP. This study assessed how well the available flux towers represent the environmental conditions or \"ecological envelopes\" across the GP and identified optimal locations for future flux towers in the GP. Regression-based remote sensing and weather-driven net ecosystem production (NEP) models derived from different extrapolation ranges (10 and 50%) were used to identify areas where ecological conditions were poorly represented by the flux tower sites and years previously used for mapping grassland fluxes. The optimal lands suitable for future flux towers within the GP were mapped. Results from this study provide information to optimize the usefulness of future flux towers in the GP and serve as a proxy for the uncertainty of the NEP map.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Landscape Ecology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.1007/s10980-011-9699-7","issn":"09212973","usgsCitation":"Gu, Y., Howard, D., Wylie, B.K., and Zhang, L., 2012, Mapping carbon flux uncertainty and selecting optimal locations for future flux towers in the Great Plains: Landscape Ecology, v. 27, no. 3, p. 319-326, https://doi.org/10.1007/s10980-011-9699-7.","startPage":"319","endPage":"326","numberOfPages":"8","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":241589,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":213917,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s10980-011-9699-7"}],"volume":"27","issue":"3","noUsgsAuthors":false,"publicationDate":"2011-12-28","publicationStatus":"PW","scienceBaseUri":"505a5053e4b0c8380cd6b5f1","contributors":{"authors":[{"text":"Gu, Yingxin 0000-0002-3544-1856 ygu@usgs.gov","orcid":"https://orcid.org/0000-0002-3544-1856","contributorId":139586,"corporation":false,"usgs":true,"family":"Gu","given":"Yingxin","email":"ygu@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":436837,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Howard, Daniel M. 0000-0002-7563-7538 dhoward@usgs.gov","orcid":"https://orcid.org/0000-0002-7563-7538","contributorId":139585,"corporation":false,"usgs":true,"family":"Howard","given":"Daniel M.","email":"dhoward@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":436836,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wylie, Bruce K. 0000-0002-7374-1083 wylie@usgs.gov","orcid":"https://orcid.org/0000-0002-7374-1083","contributorId":750,"corporation":false,"usgs":true,"family":"Wylie","given":"Bruce","email":"wylie@usgs.gov","middleInitial":"K.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":436838,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zhang, Li","contributorId":98139,"corporation":false,"usgs":true,"family":"Zhang","given":"Li","affiliations":[],"preferred":false,"id":436839,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70032540,"text":"70032540 - 2012 - A multi-source satellite data approach for modelling Lake Turkana water level: Calibration and validation using satellite altimetry data","interactions":[],"lastModifiedDate":"2020-11-30T21:58:43.196979","indexId":"70032540","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1928,"text":"Hydrology and Earth System Sciences","active":true,"publicationSubtype":{"id":10}},"title":"A multi-source satellite data approach for modelling Lake Turkana water level: Calibration and validation using satellite altimetry data","docAbstract":"<p><span>Lake Turkana is one of the largest desert lakes in the world and is characterized by high degrees of inter- and intra-annual fluctuations. The hydrology and water balance of this lake have not been well understood due to its remote location and unavailability of reliable ground truth datasets. Managing surface water resources is a great challenge in areas where in-situ data are either limited or unavailable. In this study, multi-source satellite-driven data such as satellite-based rainfall estimates, modelled runoff, evapotranspiration, and a digital elevation dataset were used to model Lake Turkana water levels from 1998 to 2009. Due to the unavailability of reliable lake level data, an approach is presented to calibrate and validate the water balance model of Lake Turkana using a composite lake level product of TOPEX/Poseidon, Jason-1, and ENVISAT satellite altimetry data. Model validation results showed that the satellite-driven water balance model can satisfactorily capture the patterns and seasonal variations of the Lake Turkana water level fluctuations with a Pearson's correlation coefficient of 0.90 and a Nash-Sutcliffe Coefficient of Efficiency (NSCE) of 0.80 during the validation period (2004–2009). Model error estimates were within 10% of the natural variability of the lake. Our analysis indicated that fluctuations in Lake Turkana water levels are mainly driven by lake inflows and over-the-lake evaporation. Over-the-lake rainfall contributes only up to 30% of lake evaporative demand. During the modelling time period, Lake Turkana showed seasonal variations of 1–2 m. The lake level fluctuated in the range up to 4 m between the years 1998–2009. This study demonstrated the usefulness of satellite altimetry data to calibrate and validate the satellite-driven hydrological model for Lake Turkana without using any in-situ data. Furthermore, for Lake Turkana, we identified and outlined opportunities and challenges of using a calibrated satellite-driven water balance model for (i) quantitative assessment of the impact of basin developmental activities on lake levels and for (ii) forecasting lake level changes and their impact on fisheries. From this study, we suggest that globally available satellite altimetry data provide a unique opportunity for calibration and validation of hydrologic models in ungauged basins.</span></p>","language":"English","publisher":"European Geosciences Union","publisherLocation":"Munich, Germany","doi":"10.5194/hess-16-1-2012","issn":"10275606","usgsCitation":"Velpuri, N., Senay, G., and Asante, K., 2012, A multi-source satellite data approach for modelling Lake Turkana water level: Calibration and validation using satellite altimetry data: Hydrology and Earth System Sciences, v. 16, no. 1, p. 1-18, https://doi.org/10.5194/hess-16-1-2012.","productDescription":"18 p.","startPage":"1","endPage":"18","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":474744,"rank":10000,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/hess-16-1-2012","text":"Publisher Index Page"},{"id":241758,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":214070,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.5194/hess-16-1-2012"}],"country":"Kenya","otherGeospatial":"Lake Turkana","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              35.79345703125,\n              2.4162756547063857\n            ],\n            [\n              36.8701171875,\n              2.4162756547063857\n            ],\n            [\n              36.8701171875,\n              4.718777551249855\n            ],\n            [\n              35.79345703125,\n              4.718777551249855\n            ],\n            [\n              35.79345703125,\n              2.4162756547063857\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"16","issue":"1","noUsgsAuthors":false,"publicationDate":"2012-01-03","publicationStatus":"PW","scienceBaseUri":"5059e48be4b0c8380cd466ee","contributors":{"authors":[{"text":"Velpuri, N.M. 0000-0002-6370-1926","orcid":"https://orcid.org/0000-0002-6370-1926","contributorId":66495,"corporation":false,"usgs":true,"family":"Velpuri","given":"N.M.","affiliations":[],"preferred":false,"id":436730,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Senay, Gabriel B. 0000-0002-8810-8539 senay@usgs.gov","orcid":"https://orcid.org/0000-0002-8810-8539","contributorId":152206,"corporation":false,"usgs":true,"family":"Senay","given":"Gabriel B.","email":"senay@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":436729,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Asante, K.O. 0000-0001-5408-1852","orcid":"https://orcid.org/0000-0001-5408-1852","contributorId":17051,"corporation":false,"usgs":true,"family":"Asante","given":"K.O.","affiliations":[],"preferred":false,"id":436728,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70032537,"text":"70032537 - 2012 - The Saturnian satellite Rhea as seen by Cassini VIMS","interactions":[],"lastModifiedDate":"2020-12-22T18:08:40.232536","indexId":"70032537","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3083,"text":"Planetary and Space Science","active":true,"publicationSubtype":{"id":10}},"title":"The Saturnian satellite Rhea as seen by Cassini VIMS","docAbstract":"<p id=\"sp0075\">Since the arrival of the Cassini spacecraft at Saturn in June 2004, the Visual and Infrared Mapping Spectrometer has obtained new spectral data of the icy satellites of Saturn in the spectral range from 0.35 to 5.2&nbsp;μm. Numerous flybys were performed at Saturn’s second largest satellite Rhea, providing a nearly complete coverage with pixel-ground resolutions sufficient to analyze variations of spectral properties across Rhea’s surface in detail. We present an overview of the VIMS observations obtained so far, as well as the analysis of the spectral properties identified in the VIMS spectra and their variations across its surface compared with spatially highly resolved Cassini ISS images and digital elevation models.</p><p id=\"sp0080\">Spectral variations measured across Rhea’s surface are similar to the variations observed in the VIMS observations of its neighbor Dione, implying similar processes causing or at least inducing their occurrence. Thus, magnetospheric particles and dust impacting onto the trailing hemisphere appear to be responsible for the concentration of dark rocky/organic material and minor amounts of CO<sub>2</sub><span>&nbsp;</span>in the cratered terrain on the trailing hemisphere. Despite the prominent spectral signatures of Rhea’s fresh impact crater Inktomi, radiation effects were identified that also affect the H<sub>2</sub>O ice-rich cratered terrain of the leading hemisphere. The concentration of H<sub>2</sub>O ice in the vicinity of steep tectonic scarps near 270°W and geologically fresh impact craters implies that Rhea exhibits an icy crust at least in the upper few kilometers. Despite the evidence for past tectonic events, no indications of recent endogenically powered processes could be identified in the Cassini data.</p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.pss.2011.07.019","issn":"00320633","usgsCitation":"Stephan, K., Jaumann, R., Wagner, R., Clark, R.N., Cruikshank, D.P., Giese, B., Hibbitts, C.A., Roatsch, T., Matz, K., Brown, R.H., Filacchione, G., Cappacioni, F., Scholten, F., Buratti, B.J., Hansen, G.B., Nicholson, P.D., Baines, K.H., Nelson, R., and Matson, D.L., 2012, The Saturnian satellite Rhea as seen by Cassini VIMS: Planetary and Space Science, v. 61, no. 1, p. 142-160, https://doi.org/10.1016/j.pss.2011.07.019.","productDescription":"19 p.","startPage":"142","endPage":"160","costCenters":[],"links":[{"id":474644,"rank":10000,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://elib.dlr.de/67936/1/EPSC2010-920.pdf","text":"External Repository"},{"id":241723,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":214036,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.pss.2011.07.019"}],"volume":"61","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505ba8d9e4b08c986b321ebc","contributors":{"authors":[{"text":"Stephan, K.","contributorId":8976,"corporation":false,"usgs":true,"family":"Stephan","given":"K.","email":"","affiliations":[],"preferred":false,"id":436693,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jaumann, R.","contributorId":81232,"corporation":false,"usgs":false,"family":"Jaumann","given":"R.","email":"","affiliations":[],"preferred":false,"id":436707,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wagner, R.","contributorId":88859,"corporation":false,"usgs":true,"family":"Wagner","given":"R.","affiliations":[],"preferred":false,"id":436708,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Clark, Roger N. 0000-0002-7021-1220 rclark@usgs.gov","orcid":"https://orcid.org/0000-0002-7021-1220","contributorId":515,"corporation":false,"usgs":true,"family":"Clark","given":"Roger","email":"rclark@usgs.gov","middleInitial":"N.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":436692,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cruikshank, D. P.","contributorId":51434,"corporation":false,"usgs":false,"family":"Cruikshank","given":"D.","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":436703,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Giese, B.","contributorId":12220,"corporation":false,"usgs":true,"family":"Giese","given":"B.","email":"","affiliations":[],"preferred":false,"id":436695,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hibbitts, C. 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,{"id":70032511,"text":"70032511 - 2012 - Dissipation of Titans north polar cloud at northern spring equinox","interactions":[],"lastModifiedDate":"2020-12-22T18:18:50.453486","indexId":"70032511","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3083,"text":"Planetary and Space Science","active":true,"publicationSubtype":{"id":10}},"title":"Dissipation of Titans north polar cloud at northern spring equinox","docAbstract":"<p><span>Saturn's Moon&nbsp;Titan&nbsp;has a thick atmosphere with a meteorological cycle. We report on the evolution of the giant cloud system covering its north pole using observations acquired by the Visual and Infrared Mapping&nbsp;Spectrometer&nbsp;onboard the Cassini spacecraft. A&nbsp;radiative transfer&nbsp;model in spherical geometry shows that the clouds are found at an&nbsp;altitude&nbsp;between 30 and 65</span><span>&nbsp;</span><span>km. We also show that the polar cloud system vanished progressively as Titan approached&nbsp;equinox&nbsp;in August 2009, revealing at optical wavelengths the underlying sea known as Kraken Mare. This decrease of activity suggests that the north-polar downwelling has begun to shut off. Such a scenario is compared with the Titan global circulation model of&nbsp;</span>Rannou et al. (2006)<span>, which predicts a decrease of cloud coverage in northern latitudes at the same period of time.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.pss.2011.04.006","issn":"00320633","usgsCitation":"Le Mouelic, S., Rannou, P., Rodriguez, S., Sotin, C., Griffith, C., Le Corre, L., Barnes, J.W., Brown, R.H., Baines, K.H., Buratti, B.J., Clark, R.N., Nicholson, P.D., and Tobie, G., 2012, Dissipation of Titans north polar cloud at northern spring equinox: Planetary and Space Science, v. 60, no. 1, p. 86-92, https://doi.org/10.1016/j.pss.2011.04.006.","productDescription":"7 p.","startPage":"86","endPage":"92","costCenters":[],"links":[{"id":474691,"rank":10000,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://u-paris.hal.science/hal-03657797","text":"External Repository"},{"id":241313,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":213664,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.pss.2011.04.006"}],"volume":"60","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a022ae4b0c8380cd4ff07","contributors":{"authors":[{"text":"Le Mouelic, S.","contributorId":92786,"corporation":false,"usgs":false,"family":"Le Mouelic","given":"S.","affiliations":[],"preferred":false,"id":436555,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rannou, P.","contributorId":19761,"corporation":false,"usgs":true,"family":"Rannou","given":"P.","email":"","affiliations":[],"preferred":false,"id":436547,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rodriguez, S.","contributorId":54329,"corporation":false,"usgs":false,"family":"Rodriguez","given":"S.","email":"","affiliations":[],"preferred":false,"id":436551,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sotin, Christophe","contributorId":53924,"corporation":false,"usgs":false,"family":"Sotin","given":"Christophe","email":"","affiliations":[],"preferred":false,"id":436550,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Griffith, C.A.","contributorId":10141,"corporation":false,"usgs":true,"family":"Griffith","given":"C.A.","email":"","affiliations":[],"preferred":false,"id":436545,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Le Corre, L.","contributorId":92874,"corporation":false,"usgs":false,"family":"Le Corre","given":"L.","email":"","affiliations":[],"preferred":false,"id":436556,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Barnes, J. 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,{"id":70032498,"text":"70032498 - 2012 - Advancing representation of hydrologic processes in the Soil and Water Assessment Tool (SWAT) through integration of the TOPographic MODEL (TOPMODEL) features","interactions":[],"lastModifiedDate":"2013-04-07T10:14:19","indexId":"70032498","displayToPublicDate":"2012-01-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Advancing representation of hydrologic processes in the Soil and Water Assessment Tool (SWAT) through integration of the TOPographic MODEL (TOPMODEL) features","docAbstract":"This paper presents a study of the integration of the Soil and Water Assessment Tool (SWAT) model and the TOPographic MODEL (TOPMODEL) features for enhancing the physical representation of hydrologic processes. In SWAT, four hydrologic processes, which are surface runoff, baseflow, groundwater re-evaporation and deep aquifer percolation, are modeled by using a group of empirical equations. The empirical equations usually constrain the simulation capability of relevant processes. To replace these equations and to model the influences of topography and water table variation on streamflow generation, the TOPMODEL features are integrated into SWAT, and a new model, the so-called SWAT-TOP, is developed. In the new model, the process of deep aquifer percolation is removed, the concept of groundwater re-evaporation is refined, and the processes of surface runoff and baseflow are remodeled. Consequently, three parameters in SWAT are discarded, and two new parameters to reflect the TOPMODEL features are introduced. SWAT-TOP and SWAT are applied to the East River basin in South China, and the results reveal that, compared with SWAT, the new model can provide a more reasonable simulation of the hydrologic processes of surface runoff, groundwater re-evaporation, and baseflow. This study evidences that an established hydrologic model can be further improved by integrating the features of another model, which is a possible way to enhance our understanding of the workings of catchments.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Hydrology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.jhydrol.2011.12.022","issn":"00221694","usgsCitation":"Chen, J., and Wu, Y., 2012, Advancing representation of hydrologic processes in the Soil and Water Assessment Tool (SWAT) through integration of the TOPographic MODEL (TOPMODEL) features: Journal of Hydrology, v. 420-421, p. 319-328, https://doi.org/10.1016/j.jhydrol.2011.12.022.","productDescription":"10 p.","startPage":"319","endPage":"328","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":213999,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.jhydrol.2011.12.022"},{"id":241683,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"420-421","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059e708e4b0c8380cd477e5","contributors":{"authors":[{"text":"Chen, J.","contributorId":104634,"corporation":false,"usgs":true,"family":"Chen","given":"J.","email":"","affiliations":[],"preferred":false,"id":436481,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wu, Y.","contributorId":79312,"corporation":false,"usgs":true,"family":"Wu","given":"Y.","email":"","affiliations":[],"preferred":false,"id":436480,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
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