{"pageNumber":"604","pageRowStart":"15075","pageSize":"25","recordCount":40828,"records":[{"id":70129247,"text":"70129247 - 2014 - Assessment of parametric uncertainty for groundwater reactive transport modeling,","interactions":[],"lastModifiedDate":"2014-10-21T10:02:56","indexId":"70129247","displayToPublicDate":"2014-05-01T10:01:36","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Assessment of parametric uncertainty for groundwater reactive transport modeling,","docAbstract":"The validity of using Gaussian assumptions for model residuals in uncertainty quantification of a groundwater reactive transport model was evaluated in this study. Least squares regression methods explicitly assume Gaussian residuals, and the assumption leads to Gaussian likelihood functions, model parameters, and model predictions. While the Bayesian methods do not explicitly require the Gaussian assumption, Gaussian residuals are widely used. This paper shows that the residuals of the reactive transport model are non-Gaussian, heteroscedastic, and correlated in time; characterizing them requires using a generalized likelihood function such as the formal generalized likelihood function developed by Schoups and Vrugt (2010). For the surface complexation model considered in this study for simulating uranium reactive transport in groundwater, parametric uncertainty is quantified using the least squares regression methods and Bayesian methods with both Gaussian and formal generalized likelihood functions. While the least squares methods and Bayesian methods with Gaussian likelihood function produce similar Gaussian parameter distributions, the parameter distributions of Bayesian uncertainty quantification using the formal generalized likelihood function are non-Gaussian. In addition, predictive performance of formal generalized likelihood function is superior to that of least squares regression and Bayesian methods with Gaussian likelihood function. The Bayesian uncertainty quantification is conducted using the differential evolution adaptive metropolis (DREAM<sub>(zs)</sub>) algorithm; as a Markov chain Monte Carlo (MCMC) method, it is a robust tool for quantifying uncertainty in groundwater reactive transport models. For the surface complexation model, the regression-based local sensitivity analysis and Morris- and DREAM<sub>(ZS)</sub>-based global sensitivity analysis yield almost identical ranking of parameter importance. The uncertainty analysis may help select appropriate likelihood functions, improve model calibration, and reduce predictive uncertainty in other groundwater reactive transport and environmental modeling.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Water Resources Research","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Geophysical Union","publisherLocation":"Washington, D.C.","doi":"10.1002/2013WR013755","usgsCitation":"Shi, X., Ye, M., Curtis, G.P., Miller, G.L., Meyer, P.D., Kohler, M., Yabusaki, S., and Wu, J., 2014, Assessment of parametric uncertainty for groundwater reactive transport modeling,: Water Resources Research, v. 50, no. 5, p. 4416-4439, https://doi.org/10.1002/2013WR013755.","productDescription":"24 p.","startPage":"4416","endPage":"4439","numberOfPages":"24","ipdsId":"IP-055224","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":473018,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2013wr013755","text":"Publisher Index Page"},{"id":295521,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":295489,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/2013WR013755"},{"id":295490,"type":{"id":15,"text":"Index Page"},"url":"https://onlinelibrary.wiley.com/doi/10.1002/2013WR013755/full"}],"volume":"50","issue":"5","noUsgsAuthors":false,"publicationDate":"2014-05-28","publicationStatus":"PW","scienceBaseUri":"544775a5e4b0f888a81b82f8","contributors":{"authors":[{"text":"Shi, Xiaoqing","contributorId":30931,"corporation":false,"usgs":true,"family":"Shi","given":"Xiaoqing","email":"","affiliations":[],"preferred":false,"id":503569,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ye, Ming","contributorId":78670,"corporation":false,"usgs":true,"family":"Ye","given":"Ming","affiliations":[],"preferred":false,"id":503573,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Curtis, Gary P. 0000-0003-3975-8882 gpcurtis@usgs.gov","orcid":"https://orcid.org/0000-0003-3975-8882","contributorId":2346,"corporation":false,"usgs":true,"family":"Curtis","given":"Gary","email":"gpcurtis@usgs.gov","middleInitial":"P.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":503567,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miller, Geoffery L.","contributorId":80601,"corporation":false,"usgs":true,"family":"Miller","given":"Geoffery","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":503574,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Meyer, Philip D.","contributorId":38493,"corporation":false,"usgs":true,"family":"Meyer","given":"Philip","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":503571,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kohler, Matthias mkohler@usgs.gov","contributorId":2624,"corporation":false,"usgs":true,"family":"Kohler","given":"Matthias","email":"mkohler@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":503568,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Yabusaki, Steve","contributorId":65403,"corporation":false,"usgs":true,"family":"Yabusaki","given":"Steve","affiliations":[],"preferred":false,"id":503572,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wu, Jichun","contributorId":36878,"corporation":false,"usgs":true,"family":"Wu","given":"Jichun","email":"","affiliations":[],"preferred":false,"id":503570,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70170483,"text":"70170483 - 2014 - Cycles of explosive and effusive eruptions at Kīlauea Volcano, Hawai‘i","interactions":[],"lastModifiedDate":"2019-03-14T07:55:48","indexId":"70170483","displayToPublicDate":"2014-05-01T10:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1796,"text":"Geology","active":true,"publicationSubtype":{"id":10}},"title":"Cycles of explosive and effusive eruptions at Kīlauea Volcano, Hawai‘i","docAbstract":"<p><span>The subaerial eruptive activity at Kīlauea Volcano (Hawai&lsquo;i) for the past 2500 yr can be divided into 3 dominantly effusive and 2 dominantly explosive periods, each lasting several centuries. The prevailing style of eruption for 60% of this time was explosive, manifested by repeated phreatic and phreatomagmatic activity in a deep summit caldera. During dominantly explosive periods, the magma supply rate to the shallow storage volume beneath the summit dropped to only a few percent of that during mainly effusive periods. The frequency and duration of explosive activity are contrary to the popular impression that Kīlauea is almost unceasingly effusive. Explosive activity apparently correlates with the presence of a caldera intersecting the water table. The decrease in magma supply rate may result in caldera collapse, because erupted or intruded magma is not replaced. Glasses with unusually high MgO, TiO</span><sub>2</sub><span>, and K</span><sub>2</sub><span>O compositions occur only in explosive tephra (and one related lava flow) and are consistent with disruption of the shallow reservoir complex during caldera formation. Kīlauea is a complex, modulated system in which melting rate, supply rate, conduit stability (in both mantle and crust), reservoir geometry, water table, and many other factors interact with one another. The hazards associated with explosive activity at Kīlauea&rsquo;s summit would have major impact on local society if a future dominantly explosive period were to last several centuries. The association of lowered magma supply, caldera formation, and explosive activity might characterize other basaltic volcanoes, but has not been recognized.</span></p>","language":"English","publisher":"Geological Society of America","publisherLocation":"Boulder, CO","doi":"10.1130/G35701.1","usgsCitation":"Swanson, D., Rose, T.R., Mucek, A., Garcia, M.O., Fiske, R.S., and Mastin, L.G., 2014, Cycles of explosive and effusive eruptions at Kīlauea Volcano, Hawai‘i: Geology, v. 42, no. 7, p. 631-634, https://doi.org/10.1130/G35701.1.","productDescription":"4 p.","startPage":"631","endPage":"634","numberOfPages":"4","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-055751","costCenters":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":320395,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawai'i","otherGeospatial":"Kīlauea Volcano","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -155.2836799621582,\n              19.43065788069488\n            ],\n            [\n              -155.29329299926758,\n              19.425801277078957\n            ],\n            [\n              -155.29672622680664,\n              19.42078263415394\n            ],\n            [\n              -155.29998779296875,\n              19.415116238124682\n            ],\n            [\n              -155.30101776123047,\n              19.408478208711944\n            ],\n            [\n              -155.29998779296875,\n              19.39892544698541\n            ],\n            [\n              -155.2965545654297,\n              19.392448679313798\n            ],\n            [\n              -155.29020309448242,\n              19.388724421195075\n            ],\n            [\n              -155.27990341186523,\n              19.387429007095374\n            ],\n            [\n              -155.26857376098633,\n              19.387914788590646\n            ],\n            [\n              -155.25432586669922,\n              19.393258289368795\n            ],\n            [\n              -155.24351119995117,\n              19.3997350248192\n            ],\n            [\n              -155.23321151733398,\n              19.41106869145732\n            ],\n            [\n              -155.2371597290039,\n              19.41851609944751\n            ],\n            [\n              -155.24471282958984,\n              19.425477498342186\n            ],\n            [\n              -155.25157928466797,\n              19.431467300513766\n            ],\n            [\n              -155.26067733764648,\n              19.434057416826118\n            ],\n            [\n              -155.269775390625,\n              19.43519057972264\n            ],\n            [\n              -155.28196334838867,\n              19.433733654546185\n            ],\n            [\n              -155.2836799621582,\n              19.43065788069488\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"42","issue":"7","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"571b4b2ce4b071321fe31c56","contributors":{"authors":[{"text":"Swanson, Don 0000-0002-1680-3591 donswan@usgs.gov","orcid":"https://orcid.org/0000-0002-1680-3591","contributorId":168817,"corporation":false,"usgs":true,"family":"Swanson","given":"Don","email":"donswan@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":627394,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rose, Timothy R.","contributorId":31275,"corporation":false,"usgs":true,"family":"Rose","given":"Timothy","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":627395,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mucek, Adonara E","contributorId":168821,"corporation":false,"usgs":false,"family":"Mucek","given":"Adonara E","affiliations":[{"id":25364,"text":"Univ. Hawai`i","active":true,"usgs":false}],"preferred":false,"id":627396,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Garcia, Michael O.","contributorId":51636,"corporation":false,"usgs":true,"family":"Garcia","given":"Michael","email":"","middleInitial":"O.","affiliations":[],"preferred":false,"id":627397,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fiske, Richard S.","contributorId":17984,"corporation":false,"usgs":true,"family":"Fiske","given":"Richard","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":627398,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mastin, Larry G. 0000-0002-4795-1992 lgmastin@usgs.gov","orcid":"https://orcid.org/0000-0002-4795-1992","contributorId":555,"corporation":false,"usgs":true,"family":"Mastin","given":"Larry","email":"lgmastin@usgs.gov","middleInitial":"G.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":627399,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70126743,"text":"70126743 - 2014 - Preliminary analysis of the role of lake basin morphology on the modern diatom flora in the Ruby Mountains and East Humboldt Range, Nevada, USA","interactions":[],"lastModifiedDate":"2017-06-30T13:54:25","indexId":"70126743","displayToPublicDate":"2014-05-01T09:51:15","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5057,"text":"Mountain Views","active":true,"publicationSubtype":{"id":10}},"title":"Preliminary analysis of the role of lake basin morphology on the modern diatom flora in the Ruby Mountains and East Humboldt Range, Nevada, USA","docAbstract":"As paleolimnologists, we often look at the world through a 5-cm-diameter hole in the bottom of a lake, and although a number of studies have shown that a single core in the deepest part of a lake does not necessarily reflect the entire diatom flora, time and money often limit our ability to collect more than one core from a given site. This preliminary study is part of a multidisciplinary research project to understand Holocene climate variability in alpine regions of the Great Basin, and ultimately, to compare these high elevation records to the better studied pluvial records from adjacent valleys, in this case, the Ruby Valley.","language":"English","publisher":"Consortium for Integrated Climate Research in Western Mountains (CIRMOUNT)","usgsCitation":"Starratt, S.W., 2014, Preliminary analysis of the role of lake basin morphology on the modern diatom flora in the Ruby Mountains and East Humboldt Range, Nevada, USA: Mountain Views, v. 8, no. 1, p. 8-13.","productDescription":"6 p.","startPage":"8","endPage":"13","numberOfPages":"6","ipdsId":"IP-058546","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":294471,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":294470,"type":{"id":15,"text":"Index Page"},"url":"https://www.fs.fed.us/psw/cirmount/publications/mtnviews.shtml"}],"country":"United States","state":"Nevada","otherGeospatial":"East Humboldt Range;Ruby Mountains","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -115.4112,40.5599 ], [ -115.4112,41.0329 ], [ -115.0725,41.0329 ], [ -115.0725,40.5599 ], [ -115.4112,40.5599 ] ] ] } } ] }","volume":"8","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54252ec7e4b0e641df8a70e3","contributors":{"authors":[{"text":"Starratt, Scott W. 0000-0001-9405-1746 sstarrat@usgs.gov","orcid":"https://orcid.org/0000-0001-9405-1746","contributorId":2891,"corporation":false,"usgs":true,"family":"Starratt","given":"Scott","email":"sstarrat@usgs.gov","middleInitial":"W.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":502156,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70114857,"text":"70114857 - 2014 - Estimating migratory connectivity of birds when re-encounter probabilities are heterogeneous","interactions":[],"lastModifiedDate":"2014-06-27T09:53:59","indexId":"70114857","displayToPublicDate":"2014-05-01T09:50:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Estimating migratory connectivity of birds when re-encounter probabilities are heterogeneous","docAbstract":"Understanding the biology and conducting effective conservation of migratory species requires an understanding of migratory connectivity – the geographic linkages of populations between stages of the annual cycle. Unfortunately, for most species, we are lacking such information. The North American Bird Banding Laboratory (BBL) houses an extensive database of marking, recaptures and recoveries, and such data could provide migratory connectivity information for many species. To date, however, few species have been analyzed for migratory connectivity largely because heterogeneous re-encounter probabilities make interpretation problematic. We accounted for regional variation in re-encounter probabilities by borrowing information across species and by using effort covariates on recapture and recovery probabilities in a multistate capture–recapture and recovery model. The effort covariates were derived from recaptures and recoveries of species within the same regions. We estimated the migratory connectivity for three tern species breeding in North America and over-wintering in the tropics, common (Sterna hirundo), roseate (Sterna dougallii), and Caspian terns (Hydroprogne caspia). For western breeding terns, model-derived estimates of migratory connectivity differed considerably from those derived directly from the proportions of re-encounters. Conversely, for eastern breeding terns, estimates were merely refined by the inclusion of re-encounter probabilities. In general, eastern breeding terns were strongly connected to eastern South America, and western breeding terns were strongly linked to the more western parts of the nonbreeding range under both models. Through simulation, we found this approach is likely useful for many species in the BBL database, although precision improved with higher re-encounter probabilities and stronger migratory connectivity. We describe an approach to deal with the inherent biases in BBL banding and re-encounter data to demonstrate that this large dataset is a valuable source of information about the migratory connectivity of the birds of North America.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ecology and Evolution","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1002/ece3.1059","usgsCitation":"Cohen, E.B., Hostelter, J.A., Royle, J., and Marra, P., 2014, Estimating migratory connectivity of birds when re-encounter probabilities are heterogeneous: Ecology and Evolution, v. 4, no. 9, p. 1659-1670, https://doi.org/10.1002/ece3.1059.","productDescription":"12 p.","startPage":"1659","endPage":"1670","numberOfPages":"12","ipdsId":"IP-055630","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":473019,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.1059","text":"Publisher Index Page"},{"id":289123,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":289116,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/ece3.1059"}],"otherGeospatial":"North America","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 177.1,5.6 ], [ 177.1,85.4 ], [ -4.0,85.4 ], [ -4.0,5.6 ], [ 177.1,5.6 ] ] ] } } ] }","volume":"4","issue":"9","noUsgsAuthors":false,"publicationDate":"2014-04-08","publicationStatus":"PW","scienceBaseUri":"53ae76a9e4b0abf75cf2bfd4","contributors":{"authors":[{"text":"Cohen, Emily B.","contributorId":57774,"corporation":false,"usgs":false,"family":"Cohen","given":"Emily","email":"","middleInitial":"B.","affiliations":[{"id":7035,"text":"Smithsonian Conservation Biology Institute, National Zoological Park","active":true,"usgs":false}],"preferred":false,"id":495408,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hostelter, Jeffrey A.","contributorId":66177,"corporation":false,"usgs":true,"family":"Hostelter","given":"Jeffrey","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":495409,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Royle, J. Andrew 0000-0003-3135-2167","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":80808,"corporation":false,"usgs":true,"family":"Royle","given":"J. Andrew","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":495410,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Marra, Peter P.","contributorId":108030,"corporation":false,"usgs":true,"family":"Marra","given":"Peter P.","affiliations":[],"preferred":false,"id":495411,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70104156,"text":"70104156 - 2014 - Brittle deformation and slope failure at the North Menan Butte tuff cone, Eastern Snake River Plain, Idaho","interactions":[],"lastModifiedDate":"2014-05-12T09:52:50","indexId":"70104156","displayToPublicDate":"2014-05-01T09:47:20","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Brittle deformation and slope failure at the North Menan Butte tuff cone, Eastern Snake River Plain, Idaho","docAbstract":"The manifestation of brittle deformation within inactive slumps along the North Menan Butte, a basaltic tuff cone in the Eastern Snake River Plain, is investigated through field and laboratory studies. Microstructural observations indicate that brittle strain is localized along deformation bands, a class of structural discontinuity that is predominant within moderate to high-porosity, clastic sedimentary rocks. Various subtypes of deformation bands are recognized in the study area based on the sense of strain they accommodate. These include dilation bands (no shear displacement), dilational shear bands, compactional shear bands and simple shear bands (no volume change). Measurements of the host rock permeability between the deformation bands indicate that the amount of brittle strain distributed throughout this part of the rock is negligible, and thus deformation bands are the primary means by which brittle strain is manifest within this tuff. Structural discontinuities that are similar in appearance to deformation bands are observed in other basaltic tuffs. Therefore deformation bands may represent a common structural feature of basaltic tuffs that have been widely misclassified as fractures. Slumping and collapse along the flanks of active volcanoes strongly influence their eruptive behavior and structural evolution. Therefore characterizing the process of deformation band and fault growth within basaltic tuff is key to achieving a more complete understanding of the evolution of basaltic volcanoes and their associated hazards.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Volcanology and Geothermal Research","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2014.04.013","usgsCitation":"Okubo, C., 2014, Brittle deformation and slope failure at the North Menan Butte tuff cone, Eastern Snake River Plain, Idaho: Journal of Volcanology and Geothermal Research, v. 278–279, p. 86-95, https://doi.org/10.1016/j.jvolgeores.2014.04.013.","productDescription":"10 p.","startPage":"86","endPage":"95","ipdsId":"IP-053658","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":287047,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":287033,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.jvolgeores.2014.04.013"}],"country":"United States","state":"Idaho","otherGeospatial":"Snake River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -117.24,41.00 ], [ -117.24,49.0 ], [ -111.04,49.0 ], [ -111.04,41.00 ], [ -117.24,41.00 ] ] ] } } ] }","volume":"278–279","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5371ed68e4b08449547883ff","contributors":{"authors":[{"text":"Okubo, Chris H. cokubo@usgs.gov","contributorId":828,"corporation":false,"usgs":true,"family":"Okubo","given":"Chris H.","email":"cokubo@usgs.gov","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":false,"id":493581,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70099287,"text":"sir20105090Q - 2014 - Platinum-group elements in southern Africa: mineral inventory and an assessment of undiscovered mineral resources","interactions":[{"subject":{"id":70099287,"text":"sir20105090Q - 2014 - Platinum-group elements in southern Africa: mineral inventory and an assessment of undiscovered mineral resources","indexId":"sir20105090Q","publicationYear":"2014","noYear":false,"chapter":"Q","title":"Platinum-group elements in southern Africa: mineral inventory and an assessment of undiscovered mineral resources"},"predicate":"IS_PART_OF","object":{"id":70040436,"text":"sir20105090 - 2010 - Global mineral resource assessment","indexId":"sir20105090","publicationYear":"2010","noYear":false,"title":"Global mineral resource assessment"},"id":1}],"isPartOf":{"id":70040436,"text":"sir20105090 - 2010 - Global mineral resource assessment","indexId":"sir20105090","publicationYear":"2010","noYear":false,"title":"Global mineral resource assessment"},"lastModifiedDate":"2022-12-09T20:58:55.027405","indexId":"sir20105090Q","displayToPublicDate":"2014-05-01T08:48:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2010-5090","chapter":"Q","title":"Platinum-group elements in southern Africa: mineral inventory and an assessment of undiscovered mineral resources","docAbstract":"<p>The platinum-group elements, platinum, palladium, rhodium, ruthenium, iridium, and osmium, possess unique physical and chemical characteristics that make them indispensable to modern technology and industry. However, mineral deposits that are the main sources of these elements occur only in three countries in the world, raising concerns about potential disruption in mineral supply. Using information in the public domain, mineral resource and reserve information has been compiled for mafic and ultramafic rocks in South Africa and Zimbabwe that host most of the world&rsquo;s platinum-group element resources.</p>\n<p>As of 2012, exploration and mining companies have delineated more than 20 billion metric tons of mineralized rock containing 42,000 metric tons of platinum, 29,000 metric tons of palladium, and 5,200 metric tons of rhodium, primarily in mafic and ultramafic intrusions of the Bushveld Complex and the Great Dyke, in southern Africa. Additional mineralized rock is likely to occur in extensions to the well-explored and characterized volumes of mineralized rock. Underexplored extensions of stratabound platinum-group element (PGE) deposits in the Bushveld Complex in South Africa may contain 65,000 metric tons of platinum, palladium, and rhodium to a depth of 3 km. Rocks enriched in PGE, which occur near the contact of the Bushveld Complex with older Transvaal Supergroup sedimentary rocks, may contain 1,100 metric tons of platinum and 1,370 metric tons of palladium (mean estimate to a depth of 1 km). A stratabound platinum-group element deposit in the Great Dyke in Zimbabwe may contain 6,900 metric tons of undiscovered platinum, palladium, and rhodium. By comparison, the global net demand for PGE in 2012 was approximately 460 metric tons. Since the 1920s, mining has recovered 7,200 and 107 metric tons of platinum-group elements from the Bushveld Complex and the Great Dyke, respectively.</p>\n<p>The large layered intrusions in southern Africa&mdash;the Bushveld Complex and the Great Dyke&mdash;are now and will continue to be a major source of the world&rsquo;s supply of PGE. Mining will not deplete the identified mineral resources and reserves or potential undiscovered mineral resources for many decades; however, in the near-term, PGE supply could be affected by social, environmental, political, and economic factors.</p>","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Global mineral resource assessment (Scientific Investigations Report 2010-5090)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20105090Q","usgsCitation":"Zientek, M.L., Causey, J.D., Parks, H.L., and Miller, R.J., 2014, Platinum-group elements in southern Africa: mineral inventory and an assessment of undiscovered mineral resources: U.S. Geological Survey Scientific Investigations Report 2010-5090, Report: xi, 126 p.; GIS Data; Appendix, https://doi.org/10.3133/sir20105090Q.","productDescription":"Report: xi, 126 p.; GIS Data; Appendix","numberOfPages":"142","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-051972","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"links":[{"id":286843,"rank":4,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20105090q.jpg"},{"id":286841,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2010/5090/q/downloads/sir2010-5090Q_appendixC.zip","text":"Appendix C","linkFileType":{"id":6,"text":"zip"},"description":"Appendix C"},{"id":286840,"rank":3,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sir/2010/5090/q/downloads/sir2010-5090Q_GISdata.zip","text":"GIS Data","linkFileType":{"id":6,"text":"zip"},"description":"GIS Data"},{"id":286837,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2010/5090/q/","linkFileType":{"id":5,"text":"html"}},{"id":286839,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2010/5090/q/pdf/sir2010-5090Q.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"projection":"Africa Lambert Conformal Conic Projection","country":"South Africa, Zimbabwe","otherGeospatial":"Southern Africa","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[31.521,-29.25739],[31.32556,-29.40198],[30.90176,-29.90996],[30.62281,-30.42378],[30.05572,-31.14027],[28.92555,-32.17204],[28.21976,-32.77195],[27.46461,-33.22696],[26.41945,-33.61495],[25.90966,-33.66704],[25.78063,-33.94465],[25.17286,-33.79685],[24.67785,-33.98718],[23.59404,-33.79447],[22.98819,-33.91643],[22.57416,-33.86408],[21.5428,-34.25884],[20.68905,-34.41718],[20.07126,-34.79514],[19.61641,-34.81917],[19.19328,-34.4626],[18.85531,-34.44431],[18.42464,-33.99787],[18.37741,-34.13652],[18.2445,-33.86775],[18.25008,-33.28143],[17.92519,-32.61129],[18.24791,-32.42913],[18.22176,-31.66163],[17.56692,-30.72572],[17.06442,-29.87864],[17.06292,-29.87595],[16.34498,-28.57671],[16.82402,-28.08216],[17.21893,-28.35594],[17.3875,-28.78351],[17.83615,-28.85638],[18.4649,-29.04546],[19.00213,-28.97244],[19.89473,-28.4611],[19.89577,-24.76779],[20.16573,-24.91796],[20.75861,-25.86814],[20.66647,-26.47745],[20.88961,-26.82854],[21.6059,-26.72653],[22.10597,-26.28026],[22.57953,-25.97945],[22.82427,-25.50046],[23.3121,-25.26869],[23.73357,-25.39013],[24.21127,-25.67022],[25.02517,-25.71967],[25.66467,-25.48682],[25.76585,-25.17485],[25.94165,-24.69637],[26.48575,-24.61633],[26.78641,-24.24069],[27.11941,-23.57432],[28.01724,-22.82775],[29.43219,-22.09131],[28.79466,-21.63945],[28.02137,-21.48598],[27.72723,-20.8518],[27.72475,-20.49906],[27.2965,-20.39152],[26.16479,-19.29309],[25.85039,-18.71441],[25.64916,-18.53603],[25.26423,-17.73654],[26.38194,-17.84604],[26.70677,-17.96123],[27.04443,-17.93803],[27.59824,-17.29083],[28.46791,-16.4684],[28.82587,-16.38975],[28.94746,-16.04305],[29.51683,-15.64468],[30.27426,-15.50779],[30.33895,-15.88084],[31.17306,-15.86094],[31.6365,-16.07199],[31.85204,-16.31942],[32.32824,-16.39207],[32.84764,-16.7134],[32.84986,-17.97906],[32.65489,-18.67209],[32.61199,-19.41938],[32.77271,-19.71559],[32.65974,-20.30429],[32.50869,-20.39529],[32.24499,-21.11649],[31.19141,-22.25151],[31.6704,-23.65897],[31.93059,-24.36942],[31.75241,-25.48428],[31.83778,-25.84333],[31.33316,-25.66019],[31.04408,-25.73145],[30.94967,-26.02265],[30.67661,-26.39808],[30.68596,-26.74385],[31.28277,-27.28588],[31.86806,-27.17793],[32.07167,-26.73382],[32.83012,-26.74219],[32.58026,-27.47016],[32.46213,-28.30101],[32.20339,-28.7524],[31.521,-29.25739]]],[[[28.5417,-28.6475],[28.97826,-28.9556],[29.32517,-29.25739],[29.01842,-29.74377],[28.8484,-30.07005],[28.29107,-30.22622],[28.1072,-30.54573],[27.7494,-30.64511],[26.99926,-29.87595],[27.53251,-29.24271],[28.07434,-28.85147],[28.5417,-28.6475]]]]},\"properties\":{\"name\":\"South Africa\"}}]}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53659189e4b05b5c4c6db10e","contributors":{"authors":[{"text":"Zientek, Michael L. 0000-0002-8522-9626 mzientek@usgs.gov","orcid":"https://orcid.org/0000-0002-8522-9626","contributorId":2420,"corporation":false,"usgs":true,"family":"Zientek","given":"Michael","email":"mzientek@usgs.gov","middleInitial":"L.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":491954,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Causey, J. Douglas","contributorId":41398,"corporation":false,"usgs":true,"family":"Causey","given":"J.","email":"","middleInitial":"Douglas","affiliations":[],"preferred":false,"id":491957,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Parks, Heather L. 0000-0002-5917-6866 hparks@usgs.gov","orcid":"https://orcid.org/0000-0002-5917-6866","contributorId":4989,"corporation":false,"usgs":true,"family":"Parks","given":"Heather","email":"hparks@usgs.gov","middleInitial":"L.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":491956,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miller, Robert J. rjmiller@usgs.gov","contributorId":2516,"corporation":false,"usgs":true,"family":"Miller","given":"Robert","email":"rjmiller@usgs.gov","middleInitial":"J.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":491955,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70188045,"text":"70188045 - 2014 - Merging remote sensing data and national agricultural statistics to model change in irrigated agriculture","interactions":[],"lastModifiedDate":"2018-12-07T14:42:44","indexId":"70188045","displayToPublicDate":"2014-05-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":679,"text":"Agricultural Systems","active":true,"publicationSubtype":{"id":10}},"title":"Merging remote sensing data and national agricultural statistics to model change in irrigated agriculture","docAbstract":"<p><span>Over 22 million hectares (ha) of U.S. croplands are irrigated. Irrigation is an intensified agricultural land use that increases crop yields and the practice affects water and energy cycles at, above, and below the land surface. Until recently, there has been a scarcity of geospatially detailed information about irrigation that is comprehensive, consistent, and timely to support studies tying agricultural land use change to aquifer water use and other factors. This study shows evidence for a recent overall net expansion of 522 thousand ha across the U.S. (2.33%) and 519 thousand ha (8.7%) in irrigated cropped area across the High Plains Aquifer (HPA) from 2002 to 2007. In fact, over 97% of the net national expansion in irrigated agriculture overlays the HPA. We employed a modeling approach implemented at two time intervals (2002 and 2007) for mapping irrigated agriculture across the conterminous U.S. (CONUS). We utilized U.S. Department of Agriculture (USDA) county statistics, satellite imagery, and a national land cover map in the model. The model output, called the Moderate Resolution Imaging Spectroradiometer (MODIS) Irrigated Agriculture Dataset for the U.S. (MIrAD-US), was then used to reveal relatively detailed spatial patterns of irrigation change across the nation and the HPA. Causes for the irrigation increase in the HPA are complex, but factors include crop commodity price increases, the corn ethanol industry, and government policies related to water use. Impacts of more irrigation may include shifts in local and regional climate, further groundwater depletion, and increasing crop yields and farm income.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.agsy.2014.01.004","usgsCitation":"Brown, J.F., and Pervez, M., 2014, Merging remote sensing data and national agricultural statistics to model change in irrigated agriculture: Agricultural Systems, v. 127, p. 28-40, https://doi.org/10.1016/j.agsy.2014.01.004.","productDescription":"13 p.","startPage":"28","endPage":"40","ipdsId":"IP-039516","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":341877,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"127","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"592e84c4e4b092b266f10d8b","contributors":{"authors":[{"text":"Brown, Jesslyn F. 0000-0002-9976-1998 jfbrown@usgs.gov","orcid":"https://orcid.org/0000-0002-9976-1998","contributorId":176609,"corporation":false,"usgs":true,"family":"Brown","given":"Jesslyn","email":"jfbrown@usgs.gov","middleInitial":"F.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":696309,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pervez, Md Shahriar 0000-0003-3417-1871 spervez@usgs.gov","orcid":"https://orcid.org/0000-0003-3417-1871","contributorId":3099,"corporation":false,"usgs":true,"family":"Pervez","given":"Md Shahriar","email":"spervez@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":696310,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70193445,"text":"70193445 - 2014 - Reflections on a vision for integrated research and monitoring after 15 years","interactions":[],"lastModifiedDate":"2017-11-10T12:18:02","indexId":"70193445","displayToPublicDate":"2014-05-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":866,"text":"Aquatic Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Reflections on a vision for integrated research and monitoring after 15 years","docAbstract":"In May of 1998, Owen Bricker and his co-author Michael Ruggiero introduced a conceptual design for integrating the Nation’s environmental research and monitoring programs. The Framework for Integrated Monitoring and Related Research was an organizing strategy for relating data collected by various programs, at multiple spatial and temporal scales, and by multiple science disciplines to solve complex ecological issues that individual research or monitoring programs were not designed to address. The concept nested existing intensive monitoring and research stations within national and regional surveys, remotely sensed data, and inventories to produce a collaborative program for multi-scale, multi-network integrated environmental monitoring and research. Analyses of gaps in data needed for specific issues would drive decisions on network improvements or enhancements. Data contributions to the Framework from existing networks would help indicate critical research and monitoring programs to protect during budget reductions. Significant progress has been made since 1998 on refining the Framework strategy. Methods and models for projecting scientific information across spatial and temporal scales have been improved, and a few regional pilots of multi-scale data-integration concepts have been attempted. The links between science and decision-making are also slowly improving and being incorporated into science practice. Experiments with the Framework strategy since 1998 have revealed the foundational elements essential to its successful implementation, such as defining core measurements, establishing standards of data collection and management, integrating research and long-term monitoring, and describing baseline ecological conditions. They have also shown us the remaining challenges to establishing the Framework concept: protecting and enhancing critical long-term monitoring, filling gaps in measurement methods, improving science for decision support, and integrating the disparate integrated science efforts now underway. In the 15 years since the Bricker and Ruggiero (Ecol Appl 8(2):326–329, 1998) paper challenged us with a new paradigm for bringing sound and comprehensive science to environmental decisions, the scientific community can take pride in the progress that has been made, while also taking stock of the challenges ahead for completing the Framework vision.","language":"English","publisher":"Springer","doi":"10.1007/s10498-013-9222-7","usgsCitation":"Murdoch, P.S., McHale, M., and Baron, J., 2014, Reflections on a vision for integrated research and monitoring after 15 years: Aquatic Geochemistry, v. 20, no. 2-3, p. 363-380, https://doi.org/10.1007/s10498-013-9222-7.","productDescription":"18 p.","startPage":"363","endPage":"380","ipdsId":"IP-045494","costCenters":[{"id":5067,"text":"Northeast Regional Director's Office","active":true,"usgs":true}],"links":[{"id":348584,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"20","issue":"2-3","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2014-04-01","publicationStatus":"PW","scienceBaseUri":"5a06c8d5e4b09af898c86176","contributors":{"authors":[{"text":"Murdoch, Peter S. 0000-0001-9243-505X pmurdoch@usgs.gov","orcid":"https://orcid.org/0000-0001-9243-505X","contributorId":2453,"corporation":false,"usgs":true,"family":"Murdoch","given":"Peter","email":"pmurdoch@usgs.gov","middleInitial":"S.","affiliations":[{"id":5067,"text":"Northeast Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":719078,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McHale, Michael 0000-0003-3780-1816 mmchale@usgs.gov","orcid":"https://orcid.org/0000-0003-3780-1816","contributorId":177292,"corporation":false,"usgs":true,"family":"McHale","given":"Michael","email":"mmchale@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":719077,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Baron, Jill 0000-0002-5902-6251 jill_baron@usgs.gov","orcid":"https://orcid.org/0000-0002-5902-6251","contributorId":194124,"corporation":false,"usgs":true,"family":"Baron","given":"Jill","email":"jill_baron@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":719076,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70189752,"text":"70189752 - 2014 - Modeling the effects of source and path heterogeneity on ground motions of great earthquakes on the Cascadia Subduction Zone Using 3D simulations","interactions":[],"lastModifiedDate":"2017-07-24T14:47:50","indexId":"70189752","displayToPublicDate":"2014-05-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Modeling the effects of source and path heterogeneity on ground motions of great earthquakes on the Cascadia Subduction Zone Using 3D simulations","docAbstract":"<p id=\"p-2\">We ran finite‐difference earthquake simulations for great subduction zone earthquakes in Cascadia to model the effects of source and path heterogeneity for the purpose of improving strong‐motion predictions. We developed a rupture model for large subduction zone earthquakes based on a<span>&nbsp;</span><i>k</i><sup>−2</sup><span>&nbsp;</span>slip spectrum and scale‐dependent rise times by representing the slip distribution as the sum of normal modes of a vibrating membrane.</p><p id=\"p-3\">Finite source and path effects were important in determining the distribution of strong motions through the locations of the hypocenter, subevents, and crustal structures like sedimentary basins. Some regions in Cascadia appear to be at greater risk than others during an event due to the geometry of the Cascadia fault zone relative to the coast and populated regions. The southern Oregon coast appears to have increased risk because it is closer to the locked zone of the Cascadia fault than other coastal areas and is also in the path of directivity amplification from any rupture propagating north to south in that part of the subduction zone, and the basins in the Puget Sound area are efficiently amplified by both north and south propagating ruptures off the coast of western Washington. We find that the median spectral accelerations at 5&nbsp;s period from the simulations are similar to that of the<span>&nbsp;</span><span id=\"xref-ref-49-1\" class=\"xref-bibr\">Zhao<span>&nbsp;</span><i>et&nbsp;al.</i><span>&nbsp;</span>(2006)</span><span>&nbsp;</span>ground‐motion prediction equation, although our simulations predict higher amplitudes near the region of greatest slip and in the sedimentary basins, such as the Seattle basin.</p>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120130181","usgsCitation":"Delorey, A., Frankel, A.D., Liu, P., and Stephenson, W.J., 2014, Modeling the effects of source and path heterogeneity on ground motions of great earthquakes on the Cascadia Subduction Zone Using 3D simulations: Bulletin of the Seismological Society of America, v. 104, no. 3, p. 1430-1446, https://doi.org/10.1785/0120130181.","productDescription":"17 p.","startPage":"1430","endPage":"1446","ipdsId":"IP-048872","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":344264,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"104","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2014-05-27","publicationStatus":"PW","scienceBaseUri":"59770754e4b0ec1a48889fb8","contributors":{"authors":[{"text":"Delorey, Andrew","contributorId":189149,"corporation":false,"usgs":false,"family":"Delorey","given":"Andrew","email":"","affiliations":[],"preferred":false,"id":706195,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Frankel, Arthur D. 0000-0001-9119-6106 afrankel@usgs.gov","orcid":"https://orcid.org/0000-0001-9119-6106","contributorId":146285,"corporation":false,"usgs":true,"family":"Frankel","given":"Arthur","email":"afrankel@usgs.gov","middleInitial":"D.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":706194,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Liu, Pengcheng","contributorId":63522,"corporation":false,"usgs":true,"family":"Liu","given":"Pengcheng","email":"","affiliations":[],"preferred":false,"id":706197,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stephenson, William J. 0000-0001-8699-0786 wstephens@usgs.gov","orcid":"https://orcid.org/0000-0001-8699-0786","contributorId":695,"corporation":false,"usgs":true,"family":"Stephenson","given":"William","email":"wstephens@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":706196,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70145459,"text":"70145459 - 2014 - Model behavior and sensitivity in an application of the cohesive bed component of the community sediment transport modeling system for the York River estuary, VA, USA","interactions":[],"lastModifiedDate":"2015-04-07T09:11:24","indexId":"70145459","displayToPublicDate":"2014-05-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2380,"text":"Journal of Marine Science and Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Model behavior and sensitivity in an application of the cohesive bed component of the community sediment transport modeling system for the York River estuary, VA, USA","docAbstract":"<p><span>The Community Sediment Transport Modeling System (CSTMS) cohesive bed sub-model that accounts for erosion, deposition, consolidation, and swelling was implemented in a three-dimensional domain to represent the York River estuary, Virginia. The objectives of this paper are to (1) describe the application of the three-dimensional hydrodynamic York Cohesive Bed Model, (2) compare calculations to observations, and (3) investigate sensitivities of the cohesive bed sub-model to user-defined parameters.</span><strong>&nbsp;</strong><span>Model results for summer 2007 showed good agreement with tidal-phase averaged estimates of sediment concentration, bed stress, and current velocity derived from Acoustic Doppler Velocimeter (ADV) field measurements. An important step in implementing the cohesive bed model was specification of both the initial and equilibrium critical shear stress profiles, in addition to choosing other parameters like the consolidation and swelling timescales. This model promises to be a useful tool for investigating the fundamental controls on bed erodibility and settling velocity in the York River, a classical muddy estuary, provided that appropriate data exists to inform the choice of model parameters.</span></p>","language":"English","publisher":"MDPI","doi":"10.3390/jmse2020413","usgsCitation":"Fall, K.A., Harris, C.K., Friedrichs, C.T., Rinehimer, J.P., and Sherwood, C.R., 2014, Model behavior and sensitivity in an application of the cohesive bed component of the community sediment transport modeling system for the York River estuary, VA, USA: Journal of Marine Science and Engineering, v. 2, no. 2, p. 413-436, https://doi.org/10.3390/jmse2020413.","productDescription":"24 p.","startPage":"413","endPage":"436","numberOfPages":"24","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-055223","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":473025,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/jmse2020413","text":"Publisher Index Page"},{"id":299434,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Virginia","otherGeospatial":"York River estuary","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -77.20367431640625,\n              36.758690821098426\n            ],\n            [\n              -77.20367431640625,\n              37.572882155556194\n            ],\n            [\n              -75.87432861328125,\n              37.572882155556194\n            ],\n            [\n              -75.87432861328125,\n              36.758690821098426\n            ],\n            [\n              -77.20367431640625,\n              36.758690821098426\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"2","issue":"2","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2014-05-14","publicationStatus":"PW","scienceBaseUri":"5524ffaee4b027f0aee3d477","contributors":{"authors":[{"text":"Fall, Kelsey A.","contributorId":140080,"corporation":false,"usgs":false,"family":"Fall","given":"Kelsey","email":"","middleInitial":"A.","affiliations":[{"id":13380,"text":"Virginia Institute of Marine Science, College of William and Mary, Gloucester Point, VA 23062","active":true,"usgs":false}],"preferred":false,"id":544181,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harris, Courtney K.","contributorId":19620,"corporation":false,"usgs":false,"family":"Harris","given":"Courtney","email":"","middleInitial":"K.","affiliations":[{"id":6708,"text":"Virginia Institute of Marine Science","active":true,"usgs":false}],"preferred":false,"id":544182,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Friedrichs, Carl T.","contributorId":43989,"corporation":false,"usgs":false,"family":"Friedrichs","given":"Carl","email":"","middleInitial":"T.","affiliations":[{"id":6708,"text":"Virginia Institute of Marine Science","active":true,"usgs":false}],"preferred":false,"id":544183,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rinehimer, J. Paul","contributorId":140081,"corporation":false,"usgs":false,"family":"Rinehimer","given":"J.","email":"","middleInitial":"Paul","affiliations":[{"id":13381,"text":"Center for Coastal Margin Observation & Prediction, Oregon Health and Sciences University, Portland, OR, 97239","active":true,"usgs":false}],"preferred":false,"id":544184,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sherwood, Christopher R. 0000-0001-6135-3553 csherwood@usgs.gov","orcid":"https://orcid.org/0000-0001-6135-3553","contributorId":2866,"corporation":false,"usgs":true,"family":"Sherwood","given":"Christopher","email":"csherwood@usgs.gov","middleInitial":"R.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":544180,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70191614,"text":"70191614 - 2014 - Applications of spatial statistical network models to stream data","interactions":[],"lastModifiedDate":"2017-11-22T10:45:26","indexId":"70191614","displayToPublicDate":"2014-05-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5067,"text":"WIREs Water","active":true,"publicationSubtype":{"id":10}},"title":"Applications of spatial statistical network models to stream data","docAbstract":"<p><span>Streams and rivers host a significant portion of Earth's biodiversity and provide important ecosystem services for human populations. Accurate information regarding the status and trends of stream resources is vital for their effective conservation and management. Most statistical techniques applied to data measured on stream networks were developed for terrestrial applications and are not optimized for streams. A new class of spatial statistical model, based on valid covariance structures for stream networks, can be used with many common types of stream data (e.g., water quality attributes, habitat conditions, biological surveys) through application of appropriate distributions (e.g., Gaussian, binomial, Poisson). The spatial statistical network models account for spatial autocorrelation (i.e., nonindependence) among measurements, which allows their application to databases with clustered measurement locations. Large amounts of stream data exist in many areas where spatial statistical analyses could be used to develop novel insights, improve predictions at unsampled sites, and aid in the design of efficient monitoring strategies at relatively low cost. We review the topic of spatial autocorrelation and its effects on statistical inference, demonstrate the use of spatial statistics with stream datasets relevant to common research and management questions, and discuss additional applications and development potential for spatial statistics on stream networks. Free software for implementing the spatial statistical network models has been developed that enables custom applications with many stream databases.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/wat2.1023","usgsCitation":"Isaak, D.J., Peterson, E.E., Ver Hoef, J.M., Wenger, S.J., Falke, J.A., Torgersen, C.E., Sowder, C., Steel, E.A., Fortin, M., Jordan, C.E., Ruesch, A.S., Som, N., and Monestiez, P., 2014, Applications of spatial statistical network models to stream data: WIREs Water, v. 1, no. 3, p. 277-294, https://doi.org/10.1002/wat2.1023.","productDescription":"18 p.","startPage":"277","endPage":"294","ipdsId":"IP-052526","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":346716,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"1","issue":"3","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2014-03-03","publicationStatus":"PW","scienceBaseUri":"59e71694e4b05fe04cd331d7","contributors":{"authors":[{"text":"Isaak, Daniel J.","contributorId":177835,"corporation":false,"usgs":false,"family":"Isaak","given":"Daniel","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":712898,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Peterson, Erin E.","contributorId":16264,"corporation":false,"usgs":true,"family":"Peterson","given":"Erin","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":712899,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ver Hoef, Jay M.","contributorId":42504,"corporation":false,"usgs":true,"family":"Ver Hoef","given":"Jay","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":712900,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wenger, Seth J.","contributorId":64786,"corporation":false,"usgs":true,"family":"Wenger","given":"Seth","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":712901,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Falke, Jeffrey A. 0000-0002-6670-8250 jfalke@usgs.gov","orcid":"https://orcid.org/0000-0002-6670-8250","contributorId":5195,"corporation":false,"usgs":true,"family":"Falke","given":"Jeffrey","email":"jfalke@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":712902,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Torgersen, Christian E. 0000-0001-8325-2737 ctorgersen@usgs.gov","orcid":"https://orcid.org/0000-0001-8325-2737","contributorId":3578,"corporation":false,"usgs":true,"family":"Torgersen","given":"Christian","email":"ctorgersen@usgs.gov","middleInitial":"E.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":false,"id":712903,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sowder, Colin","contributorId":197201,"corporation":false,"usgs":false,"family":"Sowder","given":"Colin","email":"","affiliations":[],"preferred":false,"id":712904,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Steel, E. Ashley","contributorId":192227,"corporation":false,"usgs":false,"family":"Steel","given":"E.","email":"","middleInitial":"Ashley","affiliations":[],"preferred":false,"id":712905,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Fortin, Marie-Josée","contributorId":40462,"corporation":false,"usgs":true,"family":"Fortin","given":"Marie-Josée","affiliations":[],"preferred":false,"id":712906,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Jordan, Chris E.","contributorId":88233,"corporation":false,"usgs":true,"family":"Jordan","given":"Chris","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":712907,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Ruesch, Aaron S.","contributorId":26559,"corporation":false,"usgs":true,"family":"Ruesch","given":"Aaron","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":712908,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Som, Nicholas","contributorId":100264,"corporation":false,"usgs":true,"family":"Som","given":"Nicholas","affiliations":[],"preferred":false,"id":712909,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Monestiez, Pascal","contributorId":11910,"corporation":false,"usgs":true,"family":"Monestiez","given":"Pascal","email":"","affiliations":[],"preferred":false,"id":712910,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}}
,{"id":70154974,"text":"70154974 - 2014 - Influence of whitebark pine decline on fall habitat use and movements of grizzly bears in the Greater Yellowstone Ecosystem","interactions":[],"lastModifiedDate":"2016-04-08T12:24:16","indexId":"70154974","displayToPublicDate":"2014-05-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Influence of whitebark pine decline on fall habitat use and movements of grizzly bears in the Greater Yellowstone Ecosystem","docAbstract":"<p><span>When abundant, seeds of the high-elevation whitebark pine (WBP;</span><i>&nbsp;Pinus albicaulis</i><span>) are an important fall food for grizzly bears (</span><i>Ursus arctos</i><span>) in the Greater Yellowstone Ecosystem. Rates of bear mortality and bear/human conflicts have been inversely associated with WBP productivity. Recently, mountain pine beetles (</span><i>Dendroctonus ponderosae</i><span>) have killed many cone-producing WBP trees. We used fall (15 August&ndash;30 September) Global Positioning System locations from 89 bear years to investigate temporal changes in habitat use and movements during 2000&ndash;2011. We calculated Manly&ndash;Chesson (MC) indices for selectivity of WBP habitat and secure habitat (&ge;500&nbsp;m from roads and human developments), determined dates of WBP use, and documented net daily movement distances and activity radii. To evaluate temporal trends, we used regression, model selection, and candidate model sets consisting of annual WBP production, sex, and year. One-third of sampled grizzly bears had fall ranges with little or no mapped WBP habitat. Most other bears (72%) had a MC index above 0.5, indicating selection for WBP habitats. From 2000 to 2011, mean MC index decreased and median date of WBP use shifted about 1&nbsp;week later. We detected no trends in movement indices over time. Outside of national parks, there was no correlation between the MC indices for WBP habitat and secure habitat, and most bears (78%) selected for secure habitat. Nonetheless, mean MC index for secure habitat decreased over the study period during years of good WBP productivity. The wide diet breadth and foraging plasticity of grizzly bears likely allowed them to adjust to declining WBP. Bears reduced use of WBP stands without increasing movement rates, suggesting they obtained alternative fall foods within their local surroundings. However, the reduction in mortality risk historically associated with use of secure, high-elevation WBP habitat may be diminishing for bears residing in multiple-use areas.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/ece3.1082","usgsCitation":"Costello, C., van Manen, F.T., Haroldson, M.A., Ebinger, M.R., Cain, S.L., Gunther, K.A., and Bjornlie, D., 2014, Influence of whitebark pine decline on fall habitat use and movements of grizzly bears in the Greater Yellowstone Ecosystem: Ecology and Evolution, v. 4, no. 10, p. 2004-2018, https://doi.org/10.1002/ece3.1082.","productDescription":"15 p.","startPage":"2004","endPage":"2018","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-052303","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":473023,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.1082","text":"Publisher Index Page"},{"id":305905,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Montana, Wyoming","otherGeospatial":"Greater Yellowstone Ecosystem","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -111.6,\n              43.26\n            ],\n            [\n              -111.6,\n              45.69\n            ],\n            [\n              -109.35,\n              45.69\n            ],\n            [\n              -109.35,\n              43.26\n            ],\n            [\n              -111.6,\n              43.26\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"4","issue":"10","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2014-04-22","publicationStatus":"PW","scienceBaseUri":"55b0beade4b09a3b01b53097","contributors":{"authors":[{"text":"Costello, Cecily M.","contributorId":145510,"corporation":false,"usgs":false,"family":"Costello","given":"Cecily M.","affiliations":[{"id":5117,"text":"University of Montana, College of Forestry and Conservation, University Hall, Room 309, Missoula, MT 59812, USA","active":true,"usgs":false}],"preferred":false,"id":564448,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"van Manen, Frank T. 0000-0001-5340-8489 fvanmanen@usgs.gov","orcid":"https://orcid.org/0000-0001-5340-8489","contributorId":2267,"corporation":false,"usgs":true,"family":"van Manen","given":"Frank","email":"fvanmanen@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":564447,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haroldson, Mark A. 0000-0002-7457-7676 mharoldson@usgs.gov","orcid":"https://orcid.org/0000-0002-7457-7676","contributorId":1773,"corporation":false,"usgs":true,"family":"Haroldson","given":"Mark","email":"mharoldson@usgs.gov","middleInitial":"A.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":564449,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ebinger, Michael R. mebinger@usgs.gov","contributorId":5771,"corporation":false,"usgs":true,"family":"Ebinger","given":"Michael","email":"mebinger@usgs.gov","middleInitial":"R.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":564450,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cain, Steven L.","contributorId":145511,"corporation":false,"usgs":false,"family":"Cain","given":"Steven","email":"","middleInitial":"L.","affiliations":[{"id":16139,"text":"National Park Service, Grand Teton National Park, Moose, Wyoming 83012, USA","active":true,"usgs":false}],"preferred":false,"id":564451,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gunther, Kerry A.","contributorId":84621,"corporation":false,"usgs":false,"family":"Gunther","given":"Kerry","email":"","middleInitial":"A.","affiliations":[{"id":5118,"text":"Yellowstone National Park, Yellowstone Center for Resources, Bear Management Office, P.O. Box 168, Yellowstone National Park, WY 82190","active":true,"usgs":false}],"preferred":false,"id":564452,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bjornlie, Daniel D.","contributorId":145512,"corporation":false,"usgs":false,"family":"Bjornlie","given":"Daniel D.","affiliations":[{"id":16140,"text":"Wyoming Game & Fish Department, Large Carnivore Section, Lander, Wyoming 82520, USA","active":true,"usgs":false}],"preferred":false,"id":564453,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70133273,"text":"70133273 - 2014 - Climate, not atmospheric deposition, drives the biogeochemical mass-balance of a mountain watershed","interactions":[],"lastModifiedDate":"2020-12-21T17:29:18.638532","indexId":"70133273","displayToPublicDate":"2014-05-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":866,"text":"Aquatic Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Climate, not atmospheric deposition, drives the biogeochemical mass-balance of a mountain watershed","docAbstract":"<p>Watershed mass-balance methods are valuable tools for demonstrating impacts to water quality from atmospheric deposition and chemical weathering. Owen Bricker, a pioneer of the mass-balance method, began applying mass-balance modeling to small watersheds in the late 1960s and dedicated his career to expanding the literature and knowledge of complex watershed processes. We evaluated long-term trends in surface-water chemistry in the Loch Vale watershed, a 660-ha. alpine/subalpine catchment located in Rocky Mountain National Park, CO, USA. Many changes in surface-water chemistry correlated with multiple drivers, including summer or monthly temperature, snow water equivalent, and the runoff-to-precipitation ratio. Atmospheric deposition was not a significant causal agent for surface-water chemistry trends. We observed statistically significant increases in both concentrations and fluxes of weathering products including cations, SiO<sub>2</sub>, SO<sub>4</sub> <sup>2&minus;</sup>, and ANC, and in inorganic N, with inorganic N being primarily of atmospheric origin. These changes are evident in the individual months June, July, and August, and also in the combined June, July, and August summer season. Increasingly warm summer temperatures are melting what was once permanent ice and this may release elements entrained in the ice, stimulate chemical weathering with enhanced moisture availability, and stimulate microbial nitrification. Weathering rates may also be enhanced by sustained water availability in high snowpack years. Rapid change in the flux of weathering products and inorganic N is the direct and indirect result of a changing climate from warming temperatures and thawing cryosphere.</p>","language":"English","publisher":"Springer","doi":"10.1007/s10498-013-9199-2","usgsCitation":"Baron, J., and Heath, J., 2014, Climate, not atmospheric deposition, drives the biogeochemical mass-balance of a mountain watershed: Aquatic Geochemistry, v. 20, no. 2-3, p. 167-181, https://doi.org/10.1007/s10498-013-9199-2.","productDescription":"15 p.","startPage":"167","endPage":"181","numberOfPages":"15","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-046111","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":473026,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10498-013-9199-2","text":"Publisher Index Page"},{"id":296065,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Loch Vale Watershed, Rock Mountain National Park","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -106.1444091796875,\n              39.977120098439634\n            ],\n            [\n              -106.1444091796875,\n              40.701463603604594\n            ],\n            [\n              -105.3424072265625,\n              40.701463603604594\n            ],\n            [\n              -105.3424072265625,\n              39.977120098439634\n            ],\n            [\n              -106.1444091796875,\n              39.977120098439634\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"20","issue":"2-3","noUsgsAuthors":false,"publicationDate":"2013-08-01","publicationStatus":"PW","scienceBaseUri":"5465d62fe4b04d4b7dbd6584","contributors":{"authors":[{"text":"Baron, Jill S. 0000-0002-5902-6251 jill_baron@usgs.gov","orcid":"https://orcid.org/0000-0002-5902-6251","contributorId":822,"corporation":false,"usgs":true,"family":"Baron","given":"Jill S.","email":"jill_baron@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":524986,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Heath, Jared","contributorId":127392,"corporation":false,"usgs":false,"family":"Heath","given":"Jared","email":"","affiliations":[{"id":6935,"text":"Natural Resources Ecology Laboratory, Colorado State University","active":true,"usgs":false}],"preferred":false,"id":524987,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70144616,"text":"70144616 - 2014 - El Niño-Southern Oscillation is linked to decreased energetic condition in long-distance migrants","interactions":[],"lastModifiedDate":"2018-01-04T12:50:48","indexId":"70144616","displayToPublicDate":"2014-05-01T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"El Niño-Southern Oscillation is linked to decreased energetic condition in long-distance migrants","docAbstract":"<p><span>Predicting how migratory animals respond to changing climatic conditions requires knowledge of how climatic events affect each phase of the annual cycle and how those effects carry-over to subsequent phases. We utilized a 17-year migration dataset to examine how El Ni&ntilde;o-Southern Oscillation climatic events in geographically different regions of the Western hemisphere carry-over to impact the stopover biology of several intercontinental migratory bird species. We found that migratory birds that over-wintered in South America experienced significantly drier environments during El Ni&ntilde;o years, as reflected by reduced Normalized Difference Vegetation Index (NDVI) values, and arrived at stopover sites in reduced energetic condition during spring migration. During El Ni&ntilde;o years migrants were also more likely to stopover immediately along the northern Gulf coast of the southeastern U.S. after crossing the Gulf of Mexico in small suboptimal forest patches where food resources are lower and migrant density often greater than larger more contiguous forests further inland. In contrast, NDVI values did not differ between El Ni&ntilde;o and La Ni&ntilde;a years in Caribbean-Central America, and we found no difference in energetic condition or use of coastal habitats for migrants en route from Caribbean-Central America wintering areas. Birds over-wintering in both regions had consistent median arrival dates along the northern Gulf coast, suggesting that there is a strong drive for birds to maintain their time program regardless of their overall condition. We provide strong evidence that not only is the stopover biology of migratory landbirds influenced by events during the previous phase of their life-cycle, but where migratory birds over-winter determines how vulnerable they are to global climatic cycles. Increased frequency and intensity of ENSO events over the coming decades, as predicted by climatic models, may disproportionately influence long-distance migrants over-wintering in South America.</span></p>","language":"English","publisher":"PLoS One","doi":"10.1371/journal.pone.0095383","usgsCitation":"Paxton, K.L., Cohen, E.B., Paxton, E., Nemeth, Z., and Moore, F.R., 2014, El Niño-Southern Oscillation is linked to decreased energetic condition in long-distance migrants: PLoS ONE, v. 9, no. 5, e95383; 11 p., https://doi.org/10.1371/journal.pone.0095383.","productDescription":"e95383; 11 p.","numberOfPages":"11","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056768","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":473029,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0095383","text":"Publisher Index Page"},{"id":299192,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","issue":"5","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2014-05-02","publicationStatus":"PW","scienceBaseUri":"551bc52ae4b0323842783a43","contributors":{"authors":[{"text":"Paxton, Kristina L. 0000-0003-2321-5090","orcid":"https://orcid.org/0000-0003-2321-5090","contributorId":41917,"corporation":false,"usgs":false,"family":"Paxton","given":"Kristina","email":"","middleInitial":"L.","affiliations":[{"id":12981,"text":"Department of Biological Sciences, University of Southern Mississippi","active":true,"usgs":false},{"id":6977,"text":"University of Hawai`i at Hilo","active":true,"usgs":false}],"preferred":false,"id":543753,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cohen, Emily B.","contributorId":57774,"corporation":false,"usgs":false,"family":"Cohen","given":"Emily","email":"","middleInitial":"B.","affiliations":[{"id":7035,"text":"Smithsonian Conservation Biology Institute, National Zoological Park","active":true,"usgs":false}],"preferred":false,"id":543754,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Paxton, Eben H. 0000-0001-5578-7689 epaxton@usgs.gov","orcid":"https://orcid.org/0000-0001-5578-7689","contributorId":438,"corporation":false,"usgs":true,"family":"Paxton","given":"Eben H.","email":"epaxton@usgs.gov","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true},{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":false,"id":543752,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nemeth, Zoltan","contributorId":140015,"corporation":false,"usgs":false,"family":"Nemeth","given":"Zoltan","email":"","affiliations":[{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":543756,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Moore, Frank R.","contributorId":54582,"corporation":false,"usgs":false,"family":"Moore","given":"Frank","email":"","middleInitial":"R.","affiliations":[{"id":12981,"text":"Department of Biological Sciences, University of Southern Mississippi","active":true,"usgs":false}],"preferred":false,"id":543755,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70103280,"text":"70103280 - 2014 - Assessing reproductive and endocrine parameters in male largescale suckers (<i>Catostomus macrocheilus</i>) along a contaminant gradient in the lower Columbia River, USA","interactions":[],"lastModifiedDate":"2014-05-08T09:10:41","indexId":"70103280","displayToPublicDate":"2014-04-30T14:51:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Assessing reproductive and endocrine parameters in male largescale suckers (<i>Catostomus macrocheilus</i>) along a contaminant gradient in the lower Columbia River, USA","docAbstract":"Persistent organochlorine pollutants such as polychlorinated biphenyls (PCBs), dichlorodiphenyldichloroethylene (p,p′-DDE), and polybrominated diphenyl ethers (PBDEs) are stable, bioaccumulative, and widely found in the environment, wildlife, and the human population. To explore the hypothesis that reproduction in male fish is associated with environmental exposures in the lower Columbia River (LCR), reproductive and endocrine parameters were studied in male resident, non-anadromous largescale sucker (Catostomus macrocheilus) (LSS) in the same habitats as anadromous salmonids having conservation status. Testes, thyroid tissue and plasma collected in 2010 from Longview (LV), Columbia City (CC), and Skamania (SK; reference) were studied. Sperm morphologies and thyrocyte heights were measured by light microscopy, sperm motilities by computer-assisted sperm motion analysis, sperm adenosine triphosphate (ATP) with luciferase, and plasma vitellogenin (VTG), thyroxine (T4), and triiodothyronine (T3) by immunoassay. Sperm apoptosis, viability, mitochondrial membrane potential, nuclear DNA fragmentation, and reproductive stage were measured by flow cytometry. Sperm quality parameters (except counts) and VTG were significantly different among sites, with correlations between VTG and 7 sperm parameters. Thyrocyte heights, T4, T3, gonadosomatic index and Fulton's condition factor differed among sites, but not significantly. Sperm quality was significantly lower and VTG higher where liver contaminants and water estrogen equivalents were highest (LV site). Total PCBs (specifically PCB-138, -146, -151, -170, -174, -177, -180, -183, -187, -194, and -206) and total PBDEs (specifically BDE-47, -100, -153, and -154) were negatively correlated with sperm motility. PCB-206 and BDE-154 were positively correlated with DNA fragmentation, and pentachloroanisole and VTG were positively correlated with sperm apoptosis and negatively correlated with ATP. BDE-99 was positively correlated with sperm counts and motility; T4 was negatively correlated with counts and positively correlated with motility, thus indicating possible androgenic mechanisms and thyroid endocrine disruption. Male LSS proved to be an informative model for studying reproductive and endocrine biomarkers in the LCR.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Science of the Total Environment","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2013.09.097","usgsCitation":"Jenkins, J.A., Olivier, H., Draugelis-Dale, R., Eilts, B., Torres, L., Patiño, R., Nilsen, E.B., and Goodbred, S.L., 2014, Assessing reproductive and endocrine parameters in male largescale suckers (<i>Catostomus macrocheilus</i>) along a contaminant gradient in the lower Columbia River, USA: Science of the Total Environment, v. 484, p. 365-378, https://doi.org/10.1016/j.scitotenv.2013.09.097.","productDescription":"14 p.","startPage":"365","endPage":"378","numberOfPages":"14","ipdsId":"IP-046167","costCenters":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"links":[{"id":473034,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://escholarship.org/uc/item/05h140jb","text":"External Repository"},{"id":286822,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":286801,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.scitotenv.2013.09.097"}],"country":"United States","state":"Oregon;Washington","otherGeospatial":"Columbia River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.09,45.54 ], [ -124.09,49.35 ], [ -117.6,49.35 ], [ -117.6,45.54 ], [ -124.09,45.54 ] ] ] } } ] }","volume":"484","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53620d4fe4b0c409c6289a24","chorus":{"doi":"10.1016/j.scitotenv.2013.09.097","url":"http://dx.doi.org/10.1016/j.scitotenv.2013.09.097","publisher":"Elsevier BV","authors":"Jenkins J.A., Olivier H.M., Draugelis-Dale R.O., Eilts B.E., Torres L., Patiño R., Nilsen E., Goodbred S.L.","journalName":"Science of The Total Environment","publicationDate":"6/2014"},"contributors":{"authors":[{"text":"Jenkins, Jill A. 0000-0002-5087-0894 jenkinsj@usgs.gov","orcid":"https://orcid.org/0000-0002-5087-0894","contributorId":2710,"corporation":false,"usgs":true,"family":"Jenkins","given":"Jill","email":"jenkinsj@usgs.gov","middleInitial":"A.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":493224,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Olivier, H.M.","contributorId":70690,"corporation":false,"usgs":true,"family":"Olivier","given":"H.M.","email":"","affiliations":[],"preferred":false,"id":493228,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Draugelis-Dale, R. O. 0000-0001-8532-3287","orcid":"https://orcid.org/0000-0001-8532-3287","contributorId":103076,"corporation":false,"usgs":true,"family":"Draugelis-Dale","given":"R. 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,{"id":70173452,"text":"70173452 - 2014 - Long-term citizen-collected data reveal geographical patterns and temporal trends in lake water clarity","interactions":[],"lastModifiedDate":"2019-06-03T13:26:54","indexId":"70173452","displayToPublicDate":"2014-04-30T14:30:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Long-term citizen-collected data reveal geographical patterns and temporal trends in lake water clarity","docAbstract":"<p>We compiled a lake-water clarity database using publicly available, citizen volunteer observations made between 1938 and 2012 across eight states in the Upper Midwest, USA. Our objectives were to determine (1) whether temporal trends in lake-water clarity existed across this large geographic area and (2) whether trends were related to the lake-specific characteristics of latitude, lake size, or time period the lake was monitored. Our database consisted of &gt;140,000 individual Secchi observations from 3,251 lakes that we summarized per lake-year, resulting in 21,020 summer averages. Using Bayesian hierarchical modeling, we found approximately a 1% per year increase in water clarity (quantified as Secchi depth) for the <strong>entire population</strong> of lakes. On an <strong>individual lake</strong> basis, 7% of lakes showed increased water clarity and 4% showed decreased clarity. Trend direction and strength were related to latitude and median sample date. Lakes in the southern part of our study-region had lower average annual summer water clarity, more negative long-term trends, and greater inter-annual variability in water clarity compared to northern lakes. Increasing trends were strongest for lakes with median sample dates earlier in the period of record (1938–2012). Our ability to identify specific mechanisms for these trends is currently hampered by the lack of a large, multi-thematic database of variables that drive water clarity (e.g., climate, land use/cover). Our results demonstrate, however, that citizen science can provide the critical monitoring data needed to address environmental questions at large spatial and long temporal scales. Collaborations among citizens, research scientists, and government agencies may be important for developing the data sources and analytical tools necessary to move toward an understanding of the factors influencing macro-scale patterns such as those shown here for lake water clarity.</p>","language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pone.0095769","usgsCitation":"Lottig, N.R., Wagner, T., Henry, E.N., Cheruvelil, K.S., Webster, K.E., Downing, J.A., and Stow, C., 2014, Long-term citizen-collected data reveal geographical patterns and temporal trends in lake water clarity: PLoS ONE, v. 9, no. 4, e95769; 8 p., https://doi.org/10.1371/journal.pone.0095769.","productDescription":"e95769; 8 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-053624","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":473035,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0095769","text":"Publisher Index Page"},{"id":324211,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois, Indiana, Iowa, Michigan, Minnesota, Missouri, Ohio, 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N.","contributorId":172189,"corporation":false,"usgs":false,"family":"Henry","given":"Emily","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":640314,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cheruvelil, Kendra Spence","contributorId":150607,"corporation":false,"usgs":false,"family":"Cheruvelil","given":"Kendra","email":"","middleInitial":"Spence","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":640315,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Webster, Katherine E.","contributorId":147903,"corporation":false,"usgs":false,"family":"Webster","given":"Katherine","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":640316,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Downing, John A.","contributorId":169033,"corporation":false,"usgs":false,"family":"Downing","given":"John","email":"","middleInitial":"A.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":640317,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Stow, Craig A.","contributorId":49733,"corporation":false,"usgs":true,"family":"Stow","given":"Craig A.","affiliations":[],"preferred":false,"id":640318,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70127905,"text":"70127905 - 2014 - Evaluating a slope-stability model for shallow rain-induced landslides using gage and satellite data","interactions":[],"lastModifiedDate":"2016-09-09T15:35:22","indexId":"70127905","displayToPublicDate":"2014-04-29T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Evaluating a slope-stability model for shallow rain-induced landslides using gage and satellite data","docAbstract":"<p class=\"Para\">Improving prediction of landslide early warning systems requires accurate estimation of the conditions that trigger slope failures. This study tested a slope-stability model for shallow rainfall-induced landslides by utilizing rainfall information from gauge and satellite records. We used the TRIGRS model (Transient Rainfall Infiltration and Grid-based Regional Slope-stability analysis) for simulating the evolution of the factor of safety due to rainfall infiltration. Using a spatial subset of a well-characterized digital landscape from an earlier study, we considered shallow failure on a slope adjoining an urban transportation roadway near the Seattle area in Washington, USA.</p><p class=\"Para\">We ran the TRIGRS model using high-quality rain gage and satellite-based rainfall data from the Tropical Rainfall Measuring Mission (TRMM). Preliminary results with parameterized soil depth values suggest that the steeper slope values in this spatial domain have factor of safety values that are extremely close to the failure limit within an extremely narrow range of values, providing multiple false alarms. When the soil depths were constrained using a back analysis procedure to ensure that slopes were stable under initial condtions, the model accurately predicted the timing and location of the landslide observation without false alarms over time for gage rain data. The TRMM satellite rainfall data did not show adequately retreived rainfall peak magnitudes and accumulation over the study period, and as a result failed to predict the landslide event. These preliminary results indicate that more accurate and higher-resolution rain data (e.g., the upcoming Global Precipitation Measurement (GPM) mission) are required to provide accurate and reliable landslide predictions in ungaged basins.</p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Landslide science for a safer geoenvironment","language":"English","publisher":"Springer","doi":"10.1007/978-3-319-05050-8_67","usgsCitation":"Yatheendradas, S., Kirschbaum, D., Baum, R.L., and Godt, J.W., 2014, Evaluating a slope-stability model for shallow rain-induced landslides using gage and satellite data, chap. <i>of</i> Landslide science for a safer geoenvironment, p. 431-436, https://doi.org/10.1007/978-3-319-05050-8_67.","productDescription":"6 p. ","startPage":"431","endPage":"436","ipdsId":"IP-053433","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":328468,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2014-04-29","publicationStatus":"PW","scienceBaseUri":"57d3dd37e4b0571647d19a63","contributors":{"authors":[{"text":"Yatheendradas, S.","contributorId":13035,"corporation":false,"usgs":false,"family":"Yatheendradas","given":"S.","affiliations":[],"preferred":false,"id":519661,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kirschbaum, D.","contributorId":41686,"corporation":false,"usgs":true,"family":"Kirschbaum","given":"D.","affiliations":[],"preferred":false,"id":519662,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Baum, Rex L. 0000-0001-5337-1970 baum@usgs.gov","orcid":"https://orcid.org/0000-0001-5337-1970","contributorId":1288,"corporation":false,"usgs":true,"family":"Baum","given":"Rex","email":"baum@usgs.gov","middleInitial":"L.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":519660,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Godt, Jonathan W. 0000-0002-8737-2493 jgodt@usgs.gov","orcid":"https://orcid.org/0000-0002-8737-2493","contributorId":1166,"corporation":false,"usgs":true,"family":"Godt","given":"Jonathan","email":"jgodt@usgs.gov","middleInitial":"W.","affiliations":[{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":519659,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70102832,"text":"70102832 - 2014 - Geologic models for assessing Pennsylvanian to Jurassic clastic reservoirs of the Paradox Basin","interactions":[],"lastModifiedDate":"2014-04-29T09:11:22","indexId":"70102832","displayToPublicDate":"2014-04-28T12:48:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2789,"text":"Mountain Geologist","active":true,"publicationSubtype":{"id":10}},"title":"Geologic models for assessing Pennsylvanian to Jurassic clastic reservoirs of the Paradox Basin","docAbstract":"No abstract available","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Mountain Geologist","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Rocky Mountain Association of Geologists","publisherLocation":"Denver, CO","usgsCitation":"Pearson, K.M., Whidden, K.J., Anna, L.O., and Dubiel, R.F., 2014, Geologic models for assessing Pennsylvanian to Jurassic clastic reservoirs of the Paradox Basin: Mountain Geologist, v. 51, no. 2.","startPage":"175","ipdsId":"IP-041328","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":286724,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":286723,"type":{"id":15,"text":"Index Page"},"url":"https://www.rmag.org/i4a/pages/index.cfm?pageID=3345"}],"country":"United States","state":"Arizona;Colorado;New Mexico;Utah","otherGeospatial":"Paradox Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -111.01,35.96 ], [ -111.01,39.44 ], [ -107.01,39.44 ], [ -107.01,35.96 ], [ -111.01,35.96 ] ] ] } } ] }","volume":"51","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"535f6a53e4b078dca33ae32c","contributors":{"authors":[{"text":"Pearson, Krystal M. kpearson@usgs.gov","contributorId":3861,"corporation":false,"usgs":true,"family":"Pearson","given":"Krystal","email":"kpearson@usgs.gov","middleInitial":"M.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":493059,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Whidden, Katherine J. 0000-0002-7841-2553 kwhidden@usgs.gov","orcid":"https://orcid.org/0000-0002-7841-2553","contributorId":3960,"corporation":false,"usgs":true,"family":"Whidden","given":"Katherine","email":"kwhidden@usgs.gov","middleInitial":"J.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":493060,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anna, Lawrence O.","contributorId":107318,"corporation":false,"usgs":true,"family":"Anna","given":"Lawrence","email":"","middleInitial":"O.","affiliations":[],"preferred":false,"id":493061,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dubiel, Russell F. 0000-0002-1280-0350 rdubiel@usgs.gov","orcid":"https://orcid.org/0000-0002-1280-0350","contributorId":1294,"corporation":false,"usgs":true,"family":"Dubiel","given":"Russell","email":"rdubiel@usgs.gov","middleInitial":"F.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":493058,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70102829,"text":"70102829 - 2014 - Geology and total petroleum systems of the Paradox Basin, Utah, Colorado, New Mexico, and Arizona","interactions":[],"lastModifiedDate":"2015-04-03T11:19:24","indexId":"70102829","displayToPublicDate":"2014-04-28T11:55:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2789,"text":"Mountain Geologist","active":true,"publicationSubtype":{"id":10}},"title":"Geology and total petroleum systems of the Paradox Basin, Utah, Colorado, New Mexico, and Arizona","docAbstract":"<p class=\"indent\">The geological model for the development of the Total Petroleum Systems (TPSs) within the Paradox Basin formed the foundation of the recent U.S. Geological Survey assessment of undiscovered, technically recoverable resources in the basin. Five TPSs were defined, of which three have known production and two are hypothetical. These TPSs are based on geologic elements of the basin and the potential development of Precambrian, Devonian, Pennsylvanian, Permian-Mississippian, and Cretaceous source rock intervals.</p>\n<p class=\"indent\">The most studied source intervals are the Pennsylvanian black shales that were deposited during relative high stands in an otherwise evaporitic basin. These black shales are the source for most of the discovered hydrocarbons in the Paradox Basin. A second oil type can be traced to either a Mississippian or Permian source rock to the west, and therefore requires long-distance migration to explain its presence in the basin. Upper Cretaceous continental to nearshore-marine sandstones are interbedded with coal beds that have recognized coalbed methane potential. Precambrian and Devonian TPSs are considered hypothetical, as both are known to have organic-rich intervals, but no discovered hydrocarbons have been definitively typed back to either of these units.</p>","language":"English","publisher":"Rocky Mountain Association of Geologists","publisherLocation":"Denver, CO","usgsCitation":"Whidden, K.J., Lillis, P.G., Anna, L.O., Pearson, K.M., and Dubiel, R.F., 2014, Geology and total petroleum systems of the Paradox Basin, Utah, Colorado, New Mexico, and Arizona: Mountain Geologist, v. 51, no. 2, p. 119-139.","productDescription":"21 p.","startPage":"119","endPage":"139","numberOfPages":"21","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-041198","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":286722,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":286718,"type":{"id":15,"text":"Index Page"},"url":"https://archives.datapages.com/data/mountain-geologist-rmag/data/051/051002/119_rmag-mg510119.htm"}],"country":"United States","state":"Arizona, Colorado, New Mexico, Utah","otherGeospatial":"Paradox Basin","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -113.8623046875,\n              36.16448788632064\n            ],\n            [\n              -113.8623046875,\n              40.0360265298117\n            ],\n            [\n              -106.55639648437499,\n              40.0360265298117\n            ],\n            [\n              -106.55639648437499,\n              36.16448788632064\n            ],\n            [\n              -113.8623046875,\n              36.16448788632064\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"51","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"535f6a54e4b078dca33ae330","contributors":{"authors":[{"text":"Whidden, Katherine J. 0000-0002-7841-2553 kwhidden@usgs.gov","orcid":"https://orcid.org/0000-0002-7841-2553","contributorId":3960,"corporation":false,"usgs":true,"family":"Whidden","given":"Katherine","email":"kwhidden@usgs.gov","middleInitial":"J.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":493049,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lillis, Paul G. 0000-0002-7508-1699 plillis@usgs.gov","orcid":"https://orcid.org/0000-0002-7508-1699","contributorId":1817,"corporation":false,"usgs":true,"family":"Lillis","given":"Paul","email":"plillis@usgs.gov","middleInitial":"G.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":493047,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anna, Lawrence O.","contributorId":107318,"corporation":false,"usgs":true,"family":"Anna","given":"Lawrence","email":"","middleInitial":"O.","affiliations":[],"preferred":false,"id":493050,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pearson, Krystal M. kpearson@usgs.gov","contributorId":3861,"corporation":false,"usgs":true,"family":"Pearson","given":"Krystal","email":"kpearson@usgs.gov","middleInitial":"M.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":493048,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dubiel, Russell F. 0000-0002-1280-0350 rdubiel@usgs.gov","orcid":"https://orcid.org/0000-0002-1280-0350","contributorId":1294,"corporation":false,"usgs":true,"family":"Dubiel","given":"Russell","email":"rdubiel@usgs.gov","middleInitial":"F.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":493046,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70103030,"text":"70103030 - 2014 - Thresholds in the response of free-floating plant abundance to variation in hydraulic connectivity, nutrients, and macrophyte abundance in a large floodplain river","interactions":[],"lastModifiedDate":"2014-05-29T15:02:10","indexId":"70103030","displayToPublicDate":"2014-04-28T11:35:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3750,"text":"Wetlands","onlineIssn":"1943-6246","printIssn":"0277-5212","active":true,"publicationSubtype":{"id":10}},"title":"Thresholds in the response of free-floating plant abundance to variation in hydraulic connectivity, nutrients, and macrophyte abundance in a large floodplain river","docAbstract":"Duckweed and other free-floating plants (FFP) can form dense surface mats that affect ecosystem condition and processes, and can impair public use of aquatic resources. FFP obtain their nutrients from the water column, and the formation of dense FFP mats can be a consequence and indicator of river eutrophication. We conducted two complementary surveys of diverse aquatic areas of the Upper Mississippi River as an in situ approach for estimating thresholds in the response of FFP abundance to nutrient concentration and physical conditions in a large, floodplain river. Local regression analysis was used to estimate thresholds in the relations between FFP abundance and phosphorus (P) concentration (0.167 mg l<sup>−1</sup>L), nitrogen (N) concentration (0.808 mg l<sup>−1</sup>), water velocity (0.095 m s<sup>−1</sup>), and aquatic macrophyte abundance (65 % cover). FFP tissue concentrations suggested P limitation was more likely in spring, N limitation was more likely in late summer, and N limitation was most likely in backwaters with minimal hydraulic connection to the channel. The thresholds estimated here, along with observed patterns in nutrient limitation, provide river scientists and managers with criteria to consider when attempting to modify FFP abundance in off-channel areas of large river systems.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Wetlands","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","doi":"10.1007/s13157-013-0508-8","usgsCitation":"Giblin, S.M., Houser, J., Sullivan, J.F., Langrehr, H., Rogala, J.T., and Campbell, B.D., 2014, Thresholds in the response of free-floating plant abundance to variation in hydraulic connectivity, nutrients, and macrophyte abundance in a large floodplain river: Wetlands, v. 34, no. 3, p. 413-425, https://doi.org/10.1007/s13157-013-0508-8.","productDescription":"13 p.","startPage":"413","endPage":"425","numberOfPages":"13","ipdsId":"IP-051347","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":286717,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":286716,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s13157-013-0508-8"}],"country":"United States","otherGeospatial":"Upper Mississippi River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -92.49,42.96 ], [ -92.49,44.58 ], [ -90.31,44.58 ], [ -90.31,42.96 ], [ -92.49,42.96 ] ] ] } } ] }","volume":"34","issue":"3","noUsgsAuthors":false,"publicationDate":"2013-12-28","publicationStatus":"PW","scienceBaseUri":"535f6a57e4b078dca33ae338","contributors":{"authors":[{"text":"Giblin, Shawn M.","contributorId":99889,"corporation":false,"usgs":true,"family":"Giblin","given":"Shawn","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":493099,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Houser, Jeffrey N.","contributorId":26625,"corporation":false,"usgs":true,"family":"Houser","given":"Jeffrey N.","affiliations":[],"preferred":false,"id":493097,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sullivan, John F.","contributorId":21067,"corporation":false,"usgs":false,"family":"Sullivan","given":"John","email":"","middleInitial":"F.","affiliations":[{"id":6913,"text":"Wisconsin Department of Natural Resources","active":true,"usgs":false}],"preferred":false,"id":493096,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Langrehr, H.A.","contributorId":32082,"corporation":false,"usgs":true,"family":"Langrehr","given":"H.A.","email":"","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":false,"id":493098,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rogala, James T. 0000-0002-1954-4097 jrogala@usgs.gov","orcid":"https://orcid.org/0000-0002-1954-4097","contributorId":2651,"corporation":false,"usgs":true,"family":"Rogala","given":"James","email":"jrogala@usgs.gov","middleInitial":"T.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":493094,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Campbell, Benjamin D.","contributorId":18680,"corporation":false,"usgs":true,"family":"Campbell","given":"Benjamin","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":493095,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70171006,"text":"70171006 - 2014 - A synthesis of methane emissions from 71 northern, temperate, and subtropical wetlands","interactions":[],"lastModifiedDate":"2016-05-17T10:11:45","indexId":"70171006","displayToPublicDate":"2014-04-28T05:15:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"A synthesis of methane emissions from 71 northern, temperate, and subtropical wetlands","docAbstract":"<p><span>Wetlands are the largest natural source of atmospheric methane. Here, we assess controls on methane flux using a database of approximately 19&nbsp;000 instantaneous measurements from 71 wetland sites located across subtropical, temperate, and northern high latitude regions. Our analyses confirm general controls on wetland methane emissions from soil temperature, water table, and vegetation, but also show that these relationships are modified depending on wetland type (bog, fen, or swamp), region (subarctic to temperate), and disturbance. Fen methane flux was more sensitive to vegetation and less sensitive to temperature than bog or swamp fluxes. The optimal water table for methane flux was consistently below the peat surface in bogs, close to the peat surface in poor fens, and above the peat surface in rich fens. However, the largest flux in bogs occurred when dry 30-day averaged antecedent conditions were followed by wet conditions, while in fens and swamps, the largest flux occurred when both 30-day averaged antecedent and current conditions were wet. Drained wetlands exhibited distinct characteristics, e.g. the absence of large flux following wet and warm conditions, suggesting that the same functional relationships between methane flux and environmental conditions cannot be used across pristine and disturbed wetlands. Together, our results suggest that water table and temperature are dominant controls on methane flux in pristine bogs and swamps, while other processes, such as vascular transport in pristine fens, have the potential to partially override the effect of these controls in other wetland types. Because wetland types vary in methane emissions and have distinct controls, these ecosystems need to be considered separately to yield reliable estimates of global wetland methane release.</span></p>","language":"English","publisher":"Blackwell Science","doi":"10.1111/gcb.12580","usgsCitation":"Turetsky, M.R., Kotowska, A., Bubier, J., Dise, N.B., Crill, P., Hornibrook, E.R., Minkkinen, K., Moore, T.R., Myers-Smith, I.H., Nykanen, H., Olefeldt, D., Rinne, J., Saarnio, S., Shurpali, N., Tuittila, E., Waddington, J.M., White, J.R., Wickland, K.P., and Wilmking, M., 2014, A synthesis of methane emissions from 71 northern, temperate, and subtropical wetlands: Global Change Biology, v. 20, no. 7, p. 2183-2197, https://doi.org/10.1111/gcb.12580.","productDescription":"15 p.","startPage":"2183","endPage":"2197","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056048","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":321282,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"20","issue":"7","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2014-04-28","publicationStatus":"PW","scienceBaseUri":"574d6434e4b07e28b668343d","contributors":{"authors":[{"text":"Turetsky, Merritt R.","contributorId":169398,"corporation":false,"usgs":false,"family":"Turetsky","given":"Merritt","email":"","middleInitial":"R.","affiliations":[{"id":12660,"text":"University of Guelph","active":true,"usgs":false}],"preferred":false,"id":629496,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kotowska, Agnieszka","contributorId":169399,"corporation":false,"usgs":false,"family":"Kotowska","given":"Agnieszka","email":"","affiliations":[{"id":12660,"text":"University of Guelph","active":true,"usgs":false}],"preferred":false,"id":629497,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bubier, Jill","contributorId":169400,"corporation":false,"usgs":false,"family":"Bubier","given":"Jill","email":"","affiliations":[{"id":25495,"text":"Mount Holyoke College","active":true,"usgs":false}],"preferred":false,"id":629498,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dise, Nancy B.","contributorId":169401,"corporation":false,"usgs":false,"family":"Dise","given":"Nancy","email":"","middleInitial":"B.","affiliations":[{"id":25496,"text":"Manchester Metropolitan University","active":true,"usgs":false}],"preferred":false,"id":629499,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Crill, Patrick","contributorId":169402,"corporation":false,"usgs":false,"family":"Crill","given":"Patrick","affiliations":[{"id":24562,"text":"Stockholm 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,{"id":70099641,"text":"sir20145054 - 2014 - Evaluation of alternative groundwater-management strategies for the Bureau of Reclamation Klamath Project, Oregon and California","interactions":[],"lastModifiedDate":"2014-04-28T09:02:45","indexId":"sir20145054","displayToPublicDate":"2014-04-25T16:11:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-5054","title":"Evaluation of alternative groundwater-management strategies for the Bureau of Reclamation Klamath Project, Oregon and California","docAbstract":"<p>The water resources of the upper Klamath Basin, in southern Oregon and northern California, are managed to achieve various complex and interconnected purposes. Since 2001, irrigators in the Bureau of Reclamation Klamath Irrigation Project (Project) have been required to limit surface-water diversions to protect habitat for endangered freshwater and anadromous fishes. The reductions in irrigation diversions have led to an increased demand for groundwater by Project irrigators, particularly in drought years. The potential effects of sustained pumping on groundwater and surface-water resources have caused concern among Federal and state agencies, Indian tribes, wildlife groups, and groundwater users. To aid in the development of a viable groundwater-management strategy for the Project, the U.S. Geological Survey, in collaboration with the Klamath Water and Power Agency and the Oregon Water Resources Department, developed a groundwater-management model that links groundwater simulation with techniques of constrained optimization.</p>\n<br/>\n<p>The overall goal of the groundwater-management model is to determine the patterns of groundwater pumping that, to the extent possible, meet the supplemental groundwater demands of the Project. To ensure that groundwater development does not adversely affect groundwater and surface-water resources, the groundwater-management model includes constraints to (1) limit the effects of groundwater withdrawal on groundwater discharge to streams and lakes that support critical habitat for fish listed under the Endangered Species Act, (2) ensure that drawdowns do not exceed limits allowed by Oregon water law, and (3) ensure that groundwater withdrawal does not adversely affect agricultural drain flows that supply a substantial portion of water for irrigators and wildlife refuges in downslope areas of the Project. Groundwater-management alternatives were tested and designed within the framework of the Klamath Basin Restoration Agreement (currently [2013] awaiting authorizing Federal legislation), which would establish a permanent limit on the amount of surface water that can be diverted annually to the Project. Groundwater-management scenarios were evaluated for the period 1970•2004; supplemental groundwater demand by the Project was estimated as the part of irrigation demand that would not have been satisfied by the surface-water diversion allowed under the Klamath Basin Restoration Agreement. Over the 35-year management period, 22 years have supplemental groundwater demand, which ranges from a few thousand acre-feet (acre-ft) to about 100,000 acre-ft in the driest years.</p>\n<br/>\n<p>The results of the groundwater-management model indicate that supplemental groundwater pumping by the Project can be managed to avoid adverse effects to groundwater discharge that supports critical aquatic habitat. The existing configuration of wells in the Project would be able to meet groundwater-pumping goals in 14 of the 22 years with supplemental groundwater demand; however, substantial irrigation shortages can be expected during drought periods when the demand for supplemental groundwater is highest. The maximum irrigation-season withdrawal calculated by the groundwater-management model is about 60,000 acre-ft, the average withdrawal in drought years is about 54,000 acre-ft, and the amount of unmet groundwater demand reaches a maximum of about 45,000 acre-ft. A comparison of optimized groundwater withdrawals by geographic region shows that the highest annual withdrawals are associated with wells in the Tule Lake and Klamath Valley regions of the Project. The patterns of groundwater withdrawal also show that a substantial amount of the available pumping capacity is unused due to the restrictions imposed by drawdown constraints.</p>\n<br/>\n<p>Subsequent model applications were used to evaluate the sensitivity of optimization results to various factors. A sensitivity analysis quantified the changes in optimized groundwater withdrawals that result from changes in drawdown-constraint limits. The analysis showed the potential for substantial increases in withdrawals of groundwater with less restrictive drawdown limits at drawdown-control sites in the California part of the model. Systematic variation of the drains-constraint limit yielded a trade-off curve between optimized groundwater withdrawals and the allowable reduction in groundwater discharge to the Project drain system. Additional model applications were used to assess the value of increasing the pumping capacity of the network of wells serving the Project, and the relation between reduced off-Project groundwater pumping and increased pumping by Project irrigators.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145054","collaboration":"Prepared in cooperation with the Klamath Water and Power Agency and the Oregon Water Resources Department","usgsCitation":"Wagner, B.J., and Gannett, M.W., 2014, Evaluation of alternative groundwater-management strategies for the Bureau of Reclamation Klamath Project, Oregon and California: U.S. Geological Survey Scientific Investigations Report 2014-5054, vi, 48 p., https://doi.org/10.3133/sir20145054.","productDescription":"vi, 48 p.","numberOfPages":"58","onlineOnly":"Y","ipdsId":"IP-049260","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":286547,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145054.jpg"},{"id":286524,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5054/"},{"id":286546,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5054/pdf/sir2014-5054.pdf"}],"projection":"Universal Transverse Mercator, Zone 10N","datum":"North American Datum of 1927","country":"United States","state":"California;Oregon","otherGeospatial":"Klamath Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.7722,41.1952 ], [ -122.7722,43.4928 ], [ -120.3992,43.4928 ], [ -120.3992,41.1952 ], [ -122.7722,41.1952 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"535b67dee4b0519b31c21a60","contributors":{"authors":[{"text":"Wagner, Brian J. bjwagner@usgs.gov","contributorId":427,"corporation":false,"usgs":true,"family":"Wagner","given":"Brian","email":"bjwagner@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":true,"id":491996,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gannett, Marshall W. 0000-0003-2498-2427 mgannett@usgs.gov","orcid":"https://orcid.org/0000-0003-2498-2427","contributorId":2942,"corporation":false,"usgs":true,"family":"Gannett","given":"Marshall","email":"mgannett@usgs.gov","middleInitial":"W.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":491997,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70102455,"text":"fs20143041 - 2014 - The 3D Elevation Program: summary for New Mexico","interactions":[],"lastModifiedDate":"2016-08-17T15:40:50","indexId":"fs20143041","displayToPublicDate":"2014-04-25T14:23:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-3041","title":"The 3D Elevation Program: summary for New Mexico","docAbstract":"<p>Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, national security, recreation, and many others. For the State of New Mexico, elevation data are critical for infrastructure and construction management, natural resources conservation, flood risk management, agriculture and precision farming, geologic resource assessment and hazard mitigation, forest resources management, and other business uses. Today, high-density light detection and ranging (lidar) data are the primary sources for deriving elevation models and other datasets. Federal, State, Tribal, and local agencies work in partnership to (1) replace data that are older and of lower quality and (2) provide coverage where publicly accessible data do not exist. A joint goal of State and Federal partners is to acquire consistent, statewide coverage to support existing and emerging applications enabled by lidar data.</p>\n<p>The National Enhanced Elevation Assessment evaluated multiple elevation data acquisition options to determine the optimal data quality and data replacement cycle relative to cost to meet the identified requirements of the user community. The evaluation demonstrated that lidar acquisition at quality level 2 (table 1) for the conterminous United States and quality level 5 ifsar data (table 1) for Alaska with a 6- to 10-year acquisition cycle provided the highest benefit/cost ratios.The 3D Elevation Program (3DEP) initiative selected an 8-year acquisition cycle for the respective quality levels. 3DEP, managed by the U.S. Geological Survey (USGS), the Office of Management and Budget Circular A&ndash;16 lead agency for terrestrial elevation data, responds to the growing need for high-quality topographic data and a wide range of other 3D representations of the Nation&rsquo;s natural and constructed features.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20143041","usgsCitation":"Carswell, W., 2014, The 3D Elevation Program: summary for New Mexico: U.S. Geological Survey Fact Sheet 2014-3041, 2 p., https://doi.org/10.3133/fs20143041.","productDescription":"2 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,{"id":70100344,"text":"ofr20141067 - 2014 - Multi-elemental analysis of aqueous geological samples by inductively coupled plasma-optical emission spectrometry","interactions":[],"lastModifiedDate":"2014-04-25T14:21:10","indexId":"ofr20141067","displayToPublicDate":"2014-04-25T14:12:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-1067","title":"Multi-elemental analysis of aqueous geological samples by inductively coupled plasma-optical emission spectrometry","docAbstract":"Typically, 27 major, minor, and trace elements are determined in natural waters, acid mine drainage, extraction fluids, and leachates of geological and environmental samples by inductively coupled plasma-optical emission spectrometry (ICP-OES). At the discretion of the analyst, additional elements may be determined after suitable method modifications and performance data are established. Samples are preserved in 1–2 percent nitric acid (HNO3) at sample collection or as soon as possible after collection. The aqueous samples are aspirated into the ICP-OES discharge, where the elemental emission signals are measured simultaneously for 27 elements. Calibration is performed with a series of matrix-matched, multi-element solution standards.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141067","usgsCitation":"Todorov, T., Wolf, R.E., and Adams, M., 2014, Multi-elemental analysis of aqueous geological samples by inductively coupled plasma-optical emission spectrometry: U.S. Geological Survey Open-File Report 2014-1067, iii, 21 p., https://doi.org/10.3133/ofr20141067.","productDescription":"iii, 21 p.","onlineOnly":"Y","ipdsId":"IP-038299","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":286660,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141067.jpg"},{"id":286658,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1067/"},{"id":286661,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1067/pdf/ofr2014-1067.pdf"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 172.5,18.9 ], [ 172.5,71.4 ], [ -66.9,71.4 ], [ -66.9,18.9 ], [ 172.5,18.9 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"535b6863e4b0519b31c21cb1","contributors":{"authors":[{"text":"Todorov, Todor I.","contributorId":39621,"corporation":false,"usgs":true,"family":"Todorov","given":"Todor I.","affiliations":[],"preferred":false,"id":492186,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wolf, Ruth E. rwolf@usgs.gov","contributorId":903,"corporation":false,"usgs":true,"family":"Wolf","given":"Ruth","email":"rwolf@usgs.gov","middleInitial":"E.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":492184,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Adams, Monique madams@usgs.gov","contributorId":1231,"corporation":false,"usgs":true,"family":"Adams","given":"Monique","email":"madams@usgs.gov","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":492185,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70102888,"text":"70102888 - 2014 - Utilizing dimensional analysis with observed data to determine the significance of hydrodynamic solutions in coastal hydrology","interactions":[],"lastModifiedDate":"2014-04-25T09:34:03","indexId":"70102888","displayToPublicDate":"2014-04-25T09:12:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1310,"text":"Computational Water, Energy, and Environmental Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Utilizing dimensional analysis with observed data to determine the significance of hydrodynamic solutions in coastal hydrology","docAbstract":"In this paper, the authors present an analysis of the magnitude of the temporal and spatial acceleration (inertial) terms in the surface-water flow equations and determine the conditions under which these inertial terms have sufficient magnitude to be required in the computations. Data from two South Florida field sites are examined and the relative magnitudes of temporal acceleration, spatial acceleration, and the gravity and friction terms are compared. Parameters are derived by using dimensionless numbers and applied to quantify the significance of the hydrodynamic effects. The time series of the ratio of the inertial and gravity terms from field sites are presented and compared with both a simplified indicator parameter and a more complex parameter called the Hydrodynamic Significance Number (HSN). Two test-case models were developed by using the SWIFT2D hydrodynamic simulator to examine flow behavior with and without the inertial terms and compute the HSN. The first model represented one of the previously-mentioned field sites during gate operations of a structure-managed coastal canal. The second model was a synthetic test case illustrating the drainage of water down a sloped surface from an initial stage while under constant flow. The analyses indicate that the times of substantial hydrodynamic effects are sporadic but significant. The simplified indicator parameter correlates much better with the hydrodynamic effect magnitude for a constant width channel such as Miami Canal than at the non-uniform North River. Higher HSN values indicate flow situations where the inertial terms are large and need to be taken into account.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Computational Water, Energy, and Environmental Engineering","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Scientific Research Publishing Inc.","doi":"10.4236/cweee.2014.32008","usgsCitation":"Swain, E.D., Decker, J.D., and Hughes, J.D., 2014, Utilizing dimensional analysis with observed data to determine the significance of hydrodynamic solutions in coastal hydrology: Computational Water, Energy, and Environmental Engineering, v. 3, no. 2, p. 57-77, https://doi.org/10.4236/cweee.2014.32008.","productDescription":"21 p.","startPage":"57","endPage":"77","numberOfPages":"21","ipdsId":"IP-052944","costCenters":[{"id":285,"text":"Florida Water Science Center","active":false,"usgs":true}],"links":[{"id":473040,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.4236/cweee.2014.32008","text":"Publisher Index Page"},{"id":286594,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":286570,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.4236/cweee.2014.32008"},{"id":286591,"type":{"id":15,"text":"Index Page"},"url":"https://www.scirp.org/journal/PaperInformation.aspx?PaperID=45365"}],"country":"United States","state":"Florida","otherGeospatial":"Miami Canal;North River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -81.4993,24.9985 ], [ -81.4993,26.0667 ], [ -79.9915,26.0667 ], [ -79.9915,24.9985 ], [ -81.4993,24.9985 ] ] ] } } ] }","volume":"3","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"535b6927e4b0519b31c22071","contributors":{"authors":[{"text":"Swain, Eric D. 0000-0001-7168-708X edswain@usgs.gov","orcid":"https://orcid.org/0000-0001-7168-708X","contributorId":1538,"corporation":false,"usgs":true,"family":"Swain","given":"Eric","email":"edswain@usgs.gov","middleInitial":"D.","affiliations":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"preferred":true,"id":493066,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Decker, Jeremy D. 0000-0002-0700-515X jdecker@usgs.gov","orcid":"https://orcid.org/0000-0002-0700-515X","contributorId":514,"corporation":false,"usgs":true,"family":"Decker","given":"Jeremy","email":"jdecker@usgs.gov","middleInitial":"D.","affiliations":[{"id":269,"text":"FLWSC-Ft. 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