{"pageNumber":"614","pageRowStart":"15325","pageSize":"25","recordCount":46883,"records":[{"id":70041629,"text":"70041629 - 2012 - Female Agassiz’s desert tortoise activity at a wind energy facility in southern California: The influence of an El Niño event","interactions":[],"lastModifiedDate":"2012-12-08T22:23:31","indexId":"70041629","displayToPublicDate":"2012-12-08T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2835,"text":"Natural Science","active":true,"publicationSubtype":{"id":10}},"title":"Female Agassiz’s desert tortoise activity at a wind energy facility in southern California: The influence of an El Niño event","docAbstract":"We compared spring-summer activity of adult female Agassiz’s Desert Tortoises (<i>Gopherus agassizii</i>) among three consecutive years (1997, 1998, and 1999) that differed dramatically in winter rainfall and annual plant production at a wind energy facility in the Sonoran Desert of southern California. Winter rainfall was approximately 71%, 190%, and 17% of the long-term average (October-March = 114 mm) for this area in water years (WY) 1997, 1998, and 1999, respectively. The substantial precipitation caused by an El Niño Southern Oscillation (ENSO) event in WY 1998 produced a generous annual food plant supply (138.2 g dry biomass/ m<sup>2</sup>) in the spring. Primary production of winter annuals during below average rainfall years (WY 1997 and WY 1999) was reduced to 98.3 and 0.2 g/m<sup>2</sup>, respectively. Mean rates of movement and mean body condition indices (mass/length) did not differ significantly among the years. The drought year following ENSO (WY 1999) was statistically similar to ENSO in every other measured value, while WY 1997 (end of a two year drought) was statistically different from ENSO using activity area, minimum number of burrows used, and percentage of non-movements. Our data suggest that female G. agassizii activity can be influenced by environmental conditions in previous years.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Natural Science","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"SCIRP","publisherLocation":"Irvine, CA","doi":"10.4236/ns.2012.41006","usgsCitation":"Ennen, J., Meyer-Wilkins, K., and Lovich, J., 2012, Female Agassiz’s desert tortoise activity at a wind energy facility in southern California: The influence of an El Niño event: Natural Science, v. 4, no. 1, p. 30-37, https://doi.org/10.4236/ns.2012.41006.","productDescription":"8 p.","startPage":"30","endPage":"37","ipdsId":"IP-029293","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":474212,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.4236/ns.2012.41006","text":"Publisher Index Page"},{"id":263882,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":263881,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.4236/ns.2012.41006"}],"country":"United States","state":"California","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.41,32.53 ], [ -124.41,42.01 ], [ -114.13,42.01 ], [ -114.13,32.53 ], [ -124.41,32.53 ] ] ] } } ] }","volume":"4","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50c46183e4b0e44331d07164","contributors":{"authors":[{"text":"Ennen, Josh R.","contributorId":9930,"corporation":false,"usgs":true,"family":"Ennen","given":"Josh R.","affiliations":[],"preferred":false,"id":470019,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Meyer-Wilkins, Kathie","contributorId":8742,"corporation":false,"usgs":false,"family":"Meyer-Wilkins","given":"Kathie","affiliations":[],"preferred":false,"id":470018,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lovich, Jeffrey","contributorId":102761,"corporation":false,"usgs":true,"family":"Lovich","given":"Jeffrey","affiliations":[],"preferred":false,"id":470020,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70041622,"text":"ofr20121242 - 2012 - Geomorphic analysis of the river response to sedimentation downstream of Mount Rainier, Washington","interactions":[],"lastModifiedDate":"2012-12-08T15:28:14","indexId":"ofr20121242","displayToPublicDate":"2012-12-08T00:00:00","publicationYear":"2012","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":"2012-1242","title":"Geomorphic analysis of the river response to sedimentation downstream of Mount Rainier, Washington","docAbstract":"A study of the geomorphology of rivers draining Mount Rainier, Washington, was completed to identify sources of sediment to the river network; to identify important processes in the sediment delivery system; to assess current sediment loads in rivers draining Mount Rainier; to evaluate if there were trends in streamflow or sediment load since the early 20th century; and to assess how rates of sedimentation might continue into the future using published climate-change scenarios.\n\nRivers draining Mount Rainier carry heavy sediment loads sourced primarily from the volcano that cause acute aggradation in deposition reaches as far away as the Puget Lowland. Calculated yields ranged from 2,000 tonnes per square kilometer per year [(tonnes/km<sup>2</sup>)/yr] on the upper Nisqually River to 350 (tonnes/km<sup>2</sup>)/yr on the lower Puyallup River, notably larger than sediment yields of 50–200 (tonnes/km2)/yr typical for other Cascade Range rivers. These rivers can be assumed to be in a general state of sediment surplus. As a result, future aggradation rates will be largely influenced by the underlying hydrology carrying sediment downstream. The active-channel width of rivers directly draining Mount Rainier in 2009, used as a proxy for sediment released from Mount Rainier, changed little between 1965 and 1994 reflecting a climatic period that was relatively quiet hydrogeomorphically. From 1994 to 2009, a marked increase in geomorphic disturbance caused the active channels in many river reaches to widen. Comparing active-channel widths of glacier-draining rivers in 2009 to the distance of glacier retreat between 1913 and 1994 showed no correlation, suggesting that geomorphic disturbance in river reaches directly downstream of glaciers is not strongly governed by the degree of glacial retreat. In contrast, there was a correlation between active-channel width and the percentage of superglacier debris mantling the glacier, as measured in 1971. A conceptual model of sediment delivery processes from the mountain indicates that rockfalls, glaciers, debris flows, and main-stem flooding act sequentially to deliver sediment from Mount Rainier to river reaches in the Puget Lowland over decadal time scales. Greater-than-normal runoff was associated with cool phases of the Pacific Decadal Oscillation. Streamflow-gaging station data from four unregulated rivers directly draining Mount Rainier indicated no statistically significant trends of increasing peak flows over the course of the 20th century.\n\nThe total sediment load of the upper Nisqually River from 1945 to 2011 was determined to be 1,200,000±180,000 tonnes/yr. The suspended-sediment load in the lower Puyallup River at Puyallup, Washington, was 860,000±300,000 tonnes/yr between 1978 and 1994, but the long-term load for the Puyallup River likely is about 1,000,000±400,000 tonnes/yr. Using a coarse-resolution bedload transport relation, the long-term average bedload was estimated to be about 30,000 tonnes/yr in the lower White River near Auburn, Washington, which was four times greater than bedload in the Puyallup River and an order of magnitude greater than bedload in the Carbon River. Analyses indicate a general increase in the sediment loads in Mount Rainier rivers in the 1990s and 2000s relative to the time period from the 1960s to 1980s. Data are insufficient, however, to determine definitively if post-1990 increases in sediment production and transport from Mount Rainier represent a statistically significant increase relative to sediment-load values typical from Mount Rainier during the entire 20th century.\n\nOne-dimensional river-hydraulic and sediment-transport models simulated the entrainment, transport, attrition, and deposition of bed material. Simulations showed that bed-material loads were largest for the Nisqually River and smallest for the Carbon River. The models were used to simulate how increases in sediment supply to rivers transport through the river systems and affect lowland reaches. For each simulation, the input sediment pulse evolved through a combination of translation, dispersion, and attrition as it moved downstream. The characteristic transport times for the median sediment-size pulse to arrive downstream for the Nisqually, Carbon, Puyallup, and White Rivers were approximately 70, 300, 80, and 60 years, respectively.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121242","collaboration":"Prepared in cooperation with Pierce County Public Works and Utilities, Surface Water Management; and King County Department of Natural Resources and Parks, Water and Land Resources Division","usgsCitation":"Czuba, J., Magirl, C.S., Czuba, C.R., Curran, C.A., Johnson, K.H., Olsen, T.D., Kimball, H.K., and Gish, C.C., 2012, Geomorphic analysis of the river response to sedimentation downstream of Mount Rainier, Washington: U.S. Geological Survey Open-File Report 2012-1242, xii, 134 p.; col. ill.; maps (col.), https://doi.org/10.3133/ofr20121242.","productDescription":"xii, 134 p.; col. ill.; maps (col.)","startPage":"i","endPage":"134","numberOfPages":"150","additionalOnlineFiles":"N","ipdsId":"IP-040356","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":263870,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1242.jpg"},{"id":263868,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1242/"},{"id":263869,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1242/pdf/ofr20121242.pdf"}],"country":"United States","state":"Washington","otherGeospatial":"Mount Rainier","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.79,45.54 ], [ -124.79,49.0 ], [ -116.92,49.0 ], [ -116.92,45.54 ], [ -124.79,45.54 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50c46187e4b0e44331d07168","contributors":{"authors":[{"text":"Czuba, Jonathan A.","contributorId":19917,"corporation":false,"usgs":true,"family":"Czuba","given":"Jonathan A.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":false,"id":469995,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Magirl, Christopher S. 0000-0002-9922-6549 magirl@usgs.gov","orcid":"https://orcid.org/0000-0002-9922-6549","contributorId":1822,"corporation":false,"usgs":true,"family":"Magirl","given":"Christopher","email":"magirl@usgs.gov","middleInitial":"S.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true},{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":469992,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Czuba, Christiana R. cczuba@usgs.gov","contributorId":4555,"corporation":false,"usgs":true,"family":"Czuba","given":"Christiana","email":"cczuba@usgs.gov","middleInitial":"R.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":false,"id":469994,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Curran, Christopher A. 0000-0001-8933-416X ccurran@usgs.gov","orcid":"https://orcid.org/0000-0001-8933-416X","contributorId":1650,"corporation":false,"usgs":true,"family":"Curran","given":"Christopher","email":"ccurran@usgs.gov","middleInitial":"A.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":469991,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Johnson, Kenneth H. johnson@usgs.gov","contributorId":3103,"corporation":false,"usgs":true,"family":"Johnson","given":"Kenneth","email":"johnson@usgs.gov","middleInitial":"H.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":469993,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Olsen, Theresa D. 0000-0003-4099-4057 tdolsen@usgs.gov","orcid":"https://orcid.org/0000-0003-4099-4057","contributorId":1644,"corporation":false,"usgs":true,"family":"Olsen","given":"Theresa","email":"tdolsen@usgs.gov","middleInitial":"D.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":469990,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kimball, Halley K.","contributorId":36431,"corporation":false,"usgs":true,"family":"Kimball","given":"Halley","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":469996,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Gish, Casey C.","contributorId":55245,"corporation":false,"usgs":true,"family":"Gish","given":"Casey","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":469997,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70041536,"text":"70041536 - 2012 - Do bioclimate variables improve performance of climate envelope models?","interactions":[],"lastModifiedDate":"2012-12-07T15:41:55","indexId":"70041536","displayToPublicDate":"2012-12-07T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"title":"Do bioclimate variables improve performance of climate envelope models?","docAbstract":"Climate envelope models are widely used to forecast potential effects of climate change on species distributions. A key issue in climate envelope modeling is the selection of predictor variables that most directly influence species. To determine whether model performance and spatial predictions were related to the selection of predictor variables, we compared models using bioclimate variables with models constructed from monthly climate data for twelve terrestrial vertebrate species in the southeastern USA using two different algorithms (random forests or generalized linear models), and two model selection techniques (using uncorrelated predictors or a subset of user-defined biologically relevant predictor variables). There were no differences in performance between models created with bioclimate or monthly variables, but one metric of model performance was significantly greater using the random forest algorithm compared with generalized linear models. Spatial predictions between maps using bioclimate and monthly variables were very consistent using the random forest algorithm with uncorrelated predictors, whereas we observed greater variability in predictions using generalized linear models.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ecological Modelling","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.ecolmodel.2012.07.018","usgsCitation":"Watling, J., Romañach, S., Bucklin, D.N., Speroterra, C., Brandt, L., Pearlstine, L.G., and Mazzotti, F., 2012, Do bioclimate variables improve performance of climate envelope models?: Ecological Modelling, v. 246, p. 79-85, https://doi.org/10.1016/j.ecolmodel.2012.07.018.","productDescription":"7 p.","startPage":"79","endPage":"85","ipdsId":"IP-030138","costCenters":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"links":[{"id":263854,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":263853,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.ecolmodel.2012.07.018"}],"volume":"246","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50c31016e4b0b57f2415d186","contributors":{"authors":[{"text":"Watling, James I.","contributorId":101963,"corporation":false,"usgs":true,"family":"Watling","given":"James I.","affiliations":[],"preferred":false,"id":469914,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Romañach, Stephanie S.","contributorId":76064,"corporation":false,"usgs":true,"family":"Romañach","given":"Stephanie S.","affiliations":[],"preferred":false,"id":469912,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bucklin, David N.","contributorId":44812,"corporation":false,"usgs":true,"family":"Bucklin","given":"David","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":469910,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Speroterra, Carolina","contributorId":54089,"corporation":false,"usgs":true,"family":"Speroterra","given":"Carolina","affiliations":[],"preferred":false,"id":469911,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brandt, Laura A.","contributorId":18608,"corporation":false,"usgs":false,"family":"Brandt","given":"Laura A.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":469908,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pearlstine, Leonard G.","contributorId":34751,"corporation":false,"usgs":false,"family":"Pearlstine","given":"Leonard","email":"","middleInitial":"G.","affiliations":[{"id":12462,"text":"U.S. Department of the Interior, National Park Service","active":true,"usgs":false}],"preferred":false,"id":469909,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Mazzotti, Frank J.","contributorId":100018,"corporation":false,"usgs":false,"family":"Mazzotti","given":"Frank J.","affiliations":[{"id":12557,"text":"University of Florida, FLREC","active":true,"usgs":false}],"preferred":false,"id":469913,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70041424,"text":"70041424 - 2012 - Extension of the spatial autocorrelation (SPAC) method to mixed-component correlations of surface waves","interactions":[],"lastModifiedDate":"2019-05-30T12:24:34","indexId":"70041424","displayToPublicDate":"2012-12-07T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1803,"text":"Geophysical Journal International","active":true,"publicationSubtype":{"id":10}},"title":"Extension of the spatial autocorrelation (SPAC) method to mixed-component correlations of surface waves","docAbstract":"Using ambient seismic noise for imaging subsurface structure dates back to the development of the spatial autocorrelation (SPAC) method in the 1950s. We present a theoretical analysis of the SPAC method for multicomponent recordings of surface waves to determine the complete 3 × 3 matrix of correlations between all pairs of three-component motions, called the correlation matrix. In the case of isotropic incidence, when either Rayleigh or Love waves arrive from all directions with equal power, the only non-zero off-diagonal terms in the matrix are the vertical–radial (ZR) and radial–vertical (RZ) correlations in the presence of Rayleigh waves. Such combinations were not considered in the development of the SPAC method. The method originally addressed the vertical–vertical (ZZ), RR and TT correlations, hence the name spatial autocorrelation. The theoretical expressions we derive for the ZR and RZ correlations offer additional ways to measure Rayleigh wave dispersion within the SPAC framework. Expanding on the results for isotropic incidence, we derive the complete correlation matrix in the case of generally anisotropic incidence. We show that the ZR and RZ correlations have advantageous properties in the presence of an out-of-plane directional wavefield compared to ZZ and RR correlations. We apply the results for mixed-component correlations to a data set from Akutan Volcano, Alaska and find consistent estimates of Rayleigh wave phase velocity from ZR compared to ZZ correlations. This work together with the recently discovered connections between the SPAC method and time-domain correlations of ambient noise provide further insights into the retrieval of surface wave Green’s functions from seismic noise.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Geophysical Journal International","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","publisherLocation":"Hoboken, NJ","doi":"10.1111/j.1365-246X.2012.05597.x","usgsCitation":"Haney, M., Mikesell, T.D., van Wijk, K., and Nakahara, H., 2012, Extension of the spatial autocorrelation (SPAC) method to mixed-component correlations of surface waves: Geophysical Journal International, v. 191, no. 1, p. 189-206, https://doi.org/10.1111/j.1365-246X.2012.05597.x.","productDescription":"18 p.","startPage":"189","endPage":"206","ipdsId":"IP-039172","costCenters":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":474214,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/j.1365-246x.2012.05597.x","text":"Publisher Index Page"},{"id":263822,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":263821,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/j.1365-246X.2012.05597.x"}],"volume":"191","issue":"1","noUsgsAuthors":false,"publicationDate":"2012-08-24","publicationStatus":"PW","scienceBaseUri":"50c3101fe4b0b57f2415d18e","contributors":{"authors":[{"text":"Haney, Matthew M.","contributorId":107584,"corporation":false,"usgs":true,"family":"Haney","given":"Matthew M.","affiliations":[],"preferred":false,"id":469710,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mikesell, T. Dylan","contributorId":52856,"corporation":false,"usgs":true,"family":"Mikesell","given":"T.","email":"","middleInitial":"Dylan","affiliations":[],"preferred":false,"id":469709,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"van Wijk, Kasper","contributorId":41306,"corporation":false,"usgs":true,"family":"van Wijk","given":"Kasper","email":"","affiliations":[],"preferred":false,"id":469708,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nakahara, Hisashi","contributorId":27332,"corporation":false,"usgs":true,"family":"Nakahara","given":"Hisashi","email":"","affiliations":[],"preferred":false,"id":469707,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70041465,"text":"70041465 - 2012 - Ash3d: A finite-volume, conservative numerical model for ash transport and tephra deposition","interactions":[],"lastModifiedDate":"2019-05-30T13:41:17","indexId":"70041465","displayToPublicDate":"2012-12-07T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2312,"text":"Journal of Geophysical Research","active":true,"publicationSubtype":{"id":10}},"title":"Ash3d: A finite-volume, conservative numerical model for ash transport and tephra deposition","docAbstract":"We develop a transient, 3-D Eulerian model (Ash3d) to predict airborne volcanic ash concentration and tephra deposition during volcanic eruptions. This model simulates downwind advection, turbulent diffusion, and settling of ash injected into the atmosphere by a volcanic eruption column. Ash advection is calculated using time-varying pre-existing wind data and a robust, high-order, finite-volume method. Our routine is mass-conservative and uses the coordinate system of the wind data, either a Cartesian system local to the volcano or a global spherical system for the Earth. Volcanic ash is specified with an arbitrary number of grain sizes, which affects the fall velocity, distribution and duration of transport. Above the source volcano, the vertical mass distribution with elevation is calculated using a Suzuki distribution for a given plume height, eruptive volume, and eruption duration. Multiple eruptions separated in time may be included in a single simulation. We test the model using analytical solutions for transport. Comparisons of the predicted and observed ash distributions for the 18 August 1992 eruption of Mt. Spurr in Alaska demonstrate to the efficacy and efficiency of the routine.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Geophysical Research","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Geophysical Union","publisherLocation":"Washington, D.C.","doi":"10.1029/2011JB008968","usgsCitation":"Schwaiger, H.F., Denlinger, R.P., and Mastin, L.G., 2012, Ash3d: A finite-volume, conservative numerical model for ash transport and tephra deposition: Journal of Geophysical Research, v. 117, 20 p.; B04204, https://doi.org/10.1029/2011JB008968.","productDescription":"20 p.; B04204","ipdsId":"IP-035746","costCenters":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":499568,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P144K2NA","text":"USGS data release","linkHelpText":"Ash3d (Version 1.1.0)"},{"id":474215,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2011jb008968","text":"Publisher Index Page"},{"id":263788,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":263787,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1029/2011JB008968"}],"volume":"117","noUsgsAuthors":false,"publicationDate":"2012-04-17","publicationStatus":"PW","scienceBaseUri":"50c30ff8e4b0b57f2415d172","contributors":{"authors":[{"text":"Schwaiger, Hans F. 0000-0001-7397-8833 hschwaiger@usgs.gov","orcid":"https://orcid.org/0000-0001-7397-8833","contributorId":4108,"corporation":false,"usgs":true,"family":"Schwaiger","given":"Hans","email":"hschwaiger@usgs.gov","middleInitial":"F.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":469780,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Denlinger, Roger P. 0000-0003-0930-0635 roger@usgs.gov","orcid":"https://orcid.org/0000-0003-0930-0635","contributorId":2679,"corporation":false,"usgs":true,"family":"Denlinger","given":"Roger","email":"roger@usgs.gov","middleInitial":"P.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":469779,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":469778,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70041519,"text":"sir20125227 - 2012 - Flood-inundation maps for a nine-mile reach of the Des Plaines River from Riverwoods to Mettawa, Illinois","interactions":[],"lastModifiedDate":"2012-12-07T11:39:03","indexId":"sir20125227","displayToPublicDate":"2012-12-07T00:00:00","publicationYear":"2012","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":"2012-5227","title":"Flood-inundation maps for a nine-mile reach of the Des Plaines River from Riverwoods to Mettawa, Illinois","docAbstract":"Digital flood-inundation maps for a 9-mile reach of the Des Plaines River from Riverwoods to Mettawa, Illinois, were created by the U.S. Geological Survey (USGS) in cooperation with the Lake County Stormwater Management Commission and the Villages of Lincolnshire and Riverwoods. The inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at <a href=\"http://water.usgs.gov/osw/flood_inundation/\" target=\"_blank\">http://water.usgs.gov/osw/flood_inundation/</a>, depict estimates of the areal extent of flooding corresponding to selected water levels (gage heights) at the USGS streamgage at Des Plaines River at Lincolnshire, Illinois (station no. 05528100). Current conditions at the USGS streamgage may be obtained on the Internet at <a href=\"http://waterdata.usgs.gov/usa/nwis/uv?05528100\" target=\"_blank\">http://waterdata.usgs.gov/usa/nwis/uv?05528100</a>. In addition, this streamgage is incorporated into the Advanced Hydrologic Prediction Service (AHPS) flood warning system (<a href=\"http://water.weather.gov/ahps/\" target=\"_blank\">http://water.weather.gov/ahps/</a>) by the National Weather Service (NWS). The NWS forecasts flood hydrographs at many places that are often co-located at USGS streamgages. The NWS forecasted peak-stage information, also shown on the Des Plaines River at Lincolnshire inundation Web site, may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation. In this study, flood profiles were computed for the stream reach by means of a one-dimensional step-backwater model. The hydraulic model was then used to determine seven water-surface profiles for flood stages at roughly 1-ft intervals referenced to the streamgage datum and ranging from the 50- to 0.2-percent annual exceedance probability flows. The simulated water-surface profiles were then combined with a Geographic Information System (GIS) Digital Elevation Model (DEM) (derived from Light Detection And Ranging (LiDAR) data) in order to delineate the area flooded at each water level. These maps, along with information on the Internet regarding current gage height from USGS streamgages and forecasted stream stages from the NWS, provide emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures, as well as for post-flood recovery efforts.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125227","collaboration":"Prepared in cooperation with the Lake County Stormwater Management Commission and the Villages of Lincolnshire and Riverwoods","usgsCitation":"Murphy, E., Soong, D., and Sharpe, J.B., 2012, Flood-inundation maps for a nine-mile reach of the Des Plaines River from Riverwoods to Mettawa, Illinois: U.S. Geological Survey Scientific Investigations Report 2012-5227, Report: iv, 17 p.; Downloads Directory; 7 Sheets: 11.1 x 17 inches or smaller, https://doi.org/10.3133/sir20125227.","productDescription":"Report: iv, 17 p.; Downloads Directory; 7 Sheets: 11.1 x 17 inches or smaller","numberOfPages":"25","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":263812,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5227.gif"},{"id":263804,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2012/5227/Downloads"},{"id":263802,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5227/"},{"id":263803,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5227/pdf/SIR20125227_DesPlainesRiver_floodinundation.pdf"},{"id":263805,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2012/5227/MapSheets/SIR20125227%20Map_Sheet_1.pdf"},{"id":263806,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2012/5227/MapSheets/SIR20125227%20Map_Sheet_2.pdf"},{"id":263807,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2012/5227/MapSheets/SIR20125227%20Map_Sheet_3.pdf"},{"id":263808,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2012/5227/MapSheets/SIR20125227%20Map_Sheet_4.pdf"},{"id":263809,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2012/5227/MapSheets/SIR20125227%20Map_Sheet_5.pdf"},{"id":263810,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2012/5227/MapSheets/SIR20125227%20Map_Sheet_6.pdf"},{"id":263811,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2012/5227/MapSheets/SIR20125227%20Map_Sheet_7.pdf"}],"country":"United States","state":"Illinois","city":"Lincolnshire;Mettawa;Riverwoods","otherGeospatial":"Des Plaines River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -87.95,42.15 ], [ -87.95,42.25 ], [ -87.9,42.25 ], [ -87.9,42.15 ], [ -87.95,42.15 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50c31024e4b0b57f2415d192","contributors":{"authors":[{"text":"Murphy, Elizabeth A.","contributorId":69660,"corporation":false,"usgs":true,"family":"Murphy","given":"Elizabeth A.","affiliations":[],"preferred":false,"id":469896,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Soong, David T.","contributorId":87487,"corporation":false,"usgs":true,"family":"Soong","given":"David T.","affiliations":[],"preferred":false,"id":469897,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sharpe, Jennifer B. 0000-0002-5192-7848 jbsharpe@usgs.gov","orcid":"https://orcid.org/0000-0002-5192-7848","contributorId":2825,"corporation":false,"usgs":true,"family":"Sharpe","given":"Jennifer","email":"jbsharpe@usgs.gov","middleInitial":"B.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":469895,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70041456,"text":"70041456 - 2012 - Determination and uncertainty of moment tensors for microearthquakes at Okmok Volcano, Alaska","interactions":[],"lastModifiedDate":"2019-05-30T13:16:29","indexId":"70041456","displayToPublicDate":"2012-12-07T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1803,"text":"Geophysical Journal International","active":true,"publicationSubtype":{"id":10}},"title":"Determination and uncertainty of moment tensors for microearthquakes at Okmok Volcano, Alaska","docAbstract":"Efforts to determine general moment tensors (MTs) for microearthquakes in volcanic areas are often hampered by small seismic networks, which can lead to poorly constrained hypocentres and inadequate modelling of seismic velocity heterogeneity. In addition, noisy seismic signals can make it difficult to identify phase arrivals correctly for small magnitude events. However, small volcanic earthquakes can have source mechanisms that deviate from brittle double-couple shear failure due to magmatic and/or hydrothermal processes. Thus, determining reliable MTs in such conditions is a challenging but potentially rewarding pursuit. We pursued such a goal at Okmok Volcano, Alaska, which erupted recently in 1997 and in 2008. The Alaska Volcano Observatory operates a seismic network of 12 stations at Okmok and routinely catalogues recorded seismicity. Using these data, we have determined general MTs for seven microearthquakes recorded between 2004 and 2007 by inverting peak amplitude measurements of P and S phases. We computed Green's functions using precisely relocated hypocentres and a 3-D velocity model. We thoroughly assessed the quality of the solutions by computing formal uncertainty estimates, conducting a variety of synthetic and sensitivity tests, and by comparing the MTs to solutions obtained using alternative methods. The results show that MTs are sensitive to station distribution and errors in the data, velocity model and hypocentral parameters. Although each of the seven MTs contains a significant non-shear component, we judge several of the solutions to be unreliable. However, several reliable MTs are obtained for a group of previously identified repeating events, and are interpreted as compensated linear-vector dipole events.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Geophysical Journal International","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","publisherLocation":"Hoboken, NJ","doi":"10.1111/j.1365-246X.2012.05574.x","usgsCitation":"Pesicek, J., Sileny, J., Prejean, S., and Thurber, C., 2012, Determination and uncertainty of moment tensors for microearthquakes at Okmok Volcano, Alaska: Geophysical Journal International, v. 190, no. 3, p. 1689-1709, https://doi.org/10.1111/j.1365-246X.2012.05574.x.","productDescription":"21 p.","startPage":"1689","endPage":"1709","ipdsId":"IP-038948","costCenters":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":474218,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/j.1365-246x.2012.05574.x","text":"Publisher Index Page"},{"id":263801,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":263800,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/j.1365-246X.2012.05574.x"}],"country":"United States","state":"Alaska","otherGeospatial":"Mt. Okmok","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -168.185415,53.457548 ], [ -168.185415,53.477552 ], [ -168.1654,53.477552 ], [ -168.1654,53.457548 ], [ -168.185415,53.457548 ] ] ] } } ] }","volume":"190","issue":"3","noUsgsAuthors":false,"publicationDate":"2012-08-08","publicationStatus":"PW","scienceBaseUri":"50c3100ee4b0b57f2415d182","contributors":{"authors":[{"text":"Pesicek, J. D. 0000-0001-7964-5845","orcid":"https://orcid.org/0000-0001-7964-5845","contributorId":72604,"corporation":false,"usgs":true,"family":"Pesicek","given":"J. D.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":469762,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sileny, J.","contributorId":14208,"corporation":false,"usgs":true,"family":"Sileny","given":"J.","email":"","affiliations":[],"preferred":false,"id":469759,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Prejean, S. G. 0000-0003-0510-1989","orcid":"https://orcid.org/0000-0003-0510-1989","contributorId":18935,"corporation":false,"usgs":true,"family":"Prejean","given":"S. G.","affiliations":[],"preferred":false,"id":469760,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thurber, C.H.","contributorId":28617,"corporation":false,"usgs":true,"family":"Thurber","given":"C.H.","email":"","affiliations":[],"preferred":false,"id":469761,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70041518,"text":"sir20125071 - 2012 - Phase II modification of the <u>W</u>ater <u>A</u>vailability <u>T</u>ool for <u>E</u>nvironmental <u>R</u>esources (WATER) for Kentucky: The sinkhole-drainage process, point-and-click basin delineation, and results of karst test-basin simulations","interactions":[],"lastModifiedDate":"2020-10-03T16:09:12.003689","indexId":"sir20125071","displayToPublicDate":"2012-12-06T00:00:00","publicationYear":"2012","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":"2012-5071","title":"Phase II modification of the <u>W</u>ater <u>A</u>vailability <u>T</u>ool for <u>E</u>nvironmental <u>R</u>esources (WATER) for Kentucky: The sinkhole-drainage process, point-and-click basin delineation, and results of karst test-basin simulations","docAbstract":"This report describes Phase II modifications made to the Water Availability Tool for Environmental Resources (WATER), which applies the process-based TOPMODEL approach to simulate or predict stream discharge in surface basins in the Commonwealth of Kentucky. The previous (Phase I) version of WATER did not provide a means of identifying sinkhole catchments or accounting for the effects of karst (internal) drainage in a TOPMODEL-simulated basin. In the Phase II version of WATER, sinkhole catchments are automatically identified and delineated as internally drained subbasins, and a modified TOPMODEL approach (called the sinkhole drainage process, or SDP-TOPMODEL) is applied that calculates mean daily discharges for the basin based on summed area-weighted contributions from sinkhole drain-age (SD) areas and non-karstic topographically drained (TD) areas. Results obtained using the SDP-TOPMODEL approach were evaluated for 12 karst test basins located in each of the major karst terrains in Kentucky. Visual comparison of simulated hydrographs and flow-duration curves, along with statistical measures applied to the simulated discharge data (bias, correlation, root mean square error, and Nash-Sutcliffe efficiency coefficients), indicate that the SDPOPMODEL approach provides acceptably accurate estimates of discharge for most flow conditions and typically provides more accurate simulation of stream discharge in karstic basins compared to the standard TOPMODEL approach. Additional programming modifications made to the Phase II version of WATER included implementation of a point-and-click graphical user interface (GUI), which fully automates the delineation of simulation-basin boundaries and improves the speed of input-data processing. The Phase II version of WATER enables the user to select a pour point anywhere on a stream reach of interest, and the program will automatically delineate all upstream areas that contribute drainage to that point. This capability enables automatic delineation of a simulation basin of any size (area) and having any level of stream-network complexity. WATER then automatically identifies the presence of sinkholes catchments within the simulation basin boundaries; extracts and compiles the necessary climatic, topographic, and basin characteristics datasets; and runs the SDP-TOPMODEL approach to estimate daily mean discharges (streamflow).","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125071","collaboration":"Prepared in cooperation with the Kentucky Division of Water","usgsCitation":"Taylor, C.J., Williamson, T., Newson, J.K., Ulery, R.L., Nelson, H.L., and Cinotto, P.J., 2012, Phase II modification of the <u>W</u>ater <u>A</u>vailability <u>T</u>ool for <u>E</u>nvironmental <u>R</u>esources (WATER) for Kentucky: The sinkhole-drainage process, point-and-click basin delineation, and results of karst test-basin simulations: U.S. Geological Survey Scientific Investigations Report 2012-5071, vi, 45 p., https://doi.org/10.3133/sir20125071.","productDescription":"vi, 45 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,{"id":70041481,"text":"70041481 - 2012 - Revolutionary land use change in the 21st century: Is (rangeland) science relevant?","interactions":[],"lastModifiedDate":"2012-12-06T22:39:45","indexId":"70041481","displayToPublicDate":"2012-12-06T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3228,"text":"Rangeland Ecology and Management","onlineIssn":"1551-5028","printIssn":"1550-7424","active":true,"publicationSubtype":{"id":10}},"title":"Revolutionary land use change in the 21st century: Is (rangeland) science relevant?","docAbstract":"Rapidly increasing demand for food, fiber, and fuel together with new technologies and the mobility of global capital are driving revolutionary changes in land use throughout the world. Efforts to increase land productivity include conversion of millions of hectares of rangelands to crop production, including many marginal lands with low resistance and resilience to degradation. Sustaining the productivity of these lands requires careful land use planning and innovative management systems. Historically, this responsibility has been left to agronomists and others with expertise in crop production. In this article, we argue that the revolutionary land use changes necessary to support national and global food security potentially make rangeland science more relevant now than ever. Maintaining and increasing relevance will require a revolutionary change in range science from a discipline that focuses on a particular land use or land cover to one that addresses the challenge of managing all lands that, at one time, were considered to be marginal for crop production. We propose four strategies to increase the relevance of rangeland science to global land management: 1) expand our awareness and understanding of local to global economic, social, and technological trends in order to anticipate and identify drivers and patterns of conversion; 2) emphasize empirical studies and modeling that anticipate the biophysical (ecosystem services) and societal consequences of large-scale changes in land cover and use; 3) significantly increase communication and collaboration with the disciplines and sectors of society currently responsible for managing the new land uses; and 4) develop and adopt a dynamic and flexible resilience-based land classification system and data-supported conceptual models (e.g., state-and-transition models) that represent all lands, regardless of use and the consequences of land conversion to various uses instead of changes in state or condition that are focused on a single land use.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Rangeland Ecology and Management","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Society for Range Management","publisherLocation":"Wheat Ridge, CO","doi":"10.2111/REM-D-11-00186.1","usgsCitation":"Herrick, J.E., Brown, J., Bestelmeyer, B., Andrews, S., Baldi, G., Davies, J., Duniway, M., Havstad, K., Karl, J., Karlen, D., Peters, D., Quinton, J., Riginos, C., Shaver, P., Steinaker, D., and Twomlow, S., 2012, Revolutionary land use change in the 21st century: Is (rangeland) science relevant?: Rangeland Ecology and Management, v. 65, no. 6, p. 590-598, https://doi.org/10.2111/REM-D-11-00186.1.","productDescription":"9 p.","startPage":"590","endPage":"598","numberOfPages":"9","ipdsId":"IP-032539","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":474220,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.2111/rem-d-11-00186.1","text":"External Repository"},{"id":263774,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":263732,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.2111/REM-D-11-00186.1"}],"volume":"65","issue":"6","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50c1be93e4b09fd40bb0eb2f","contributors":{"authors":[{"text":"Herrick, J. E.","contributorId":84709,"corporation":false,"usgs":true,"family":"Herrick","given":"J.","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":469814,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brown, J.R.","contributorId":56872,"corporation":false,"usgs":true,"family":"Brown","given":"J.R.","email":"","affiliations":[],"preferred":false,"id":469807,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bestelmeyer, B.T.","contributorId":44504,"corporation":false,"usgs":true,"family":"Bestelmeyer","given":"B.T.","email":"","affiliations":[],"preferred":false,"id":469805,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Andrews, S.S.","contributorId":44060,"corporation":false,"usgs":true,"family":"Andrews","given":"S.S.","email":"","affiliations":[],"preferred":false,"id":469804,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Baldi, G.","contributorId":70668,"corporation":false,"usgs":true,"family":"Baldi","given":"G.","email":"","affiliations":[],"preferred":false,"id":469811,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Davies, J.","contributorId":37619,"corporation":false,"usgs":true,"family":"Davies","given":"J.","email":"","affiliations":[],"preferred":false,"id":469803,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Duniway, M.","contributorId":84240,"corporation":false,"usgs":true,"family":"Duniway","given":"M.","affiliations":[],"preferred":false,"id":469813,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Havstad, K. M.","contributorId":60587,"corporation":false,"usgs":true,"family":"Havstad","given":"K. M.","affiliations":[],"preferred":false,"id":469809,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Karl, J.W.","contributorId":63978,"corporation":false,"usgs":true,"family":"Karl","given":"J.W.","email":"","affiliations":[],"preferred":false,"id":469810,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Karlen, D.L.","contributorId":12297,"corporation":false,"usgs":true,"family":"Karlen","given":"D.L.","affiliations":[],"preferred":false,"id":469800,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Peters, Debra P. C.","contributorId":36903,"corporation":false,"usgs":false,"family":"Peters","given":"Debra P. C.","affiliations":[{"id":25579,"text":"USDA-ARS Jornada Experimental Range, Las Cruces, NM 88003","active":true,"usgs":false}],"preferred":false,"id":469802,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Quinton, J.N.","contributorId":82595,"corporation":false,"usgs":true,"family":"Quinton","given":"J.N.","email":"","affiliations":[],"preferred":false,"id":469812,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Riginos, C.","contributorId":54437,"corporation":false,"usgs":true,"family":"Riginos","given":"C.","email":"","affiliations":[],"preferred":false,"id":469806,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Shaver, P.L.","contributorId":8705,"corporation":false,"usgs":true,"family":"Shaver","given":"P.L.","email":"","affiliations":[],"preferred":false,"id":469799,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Steinaker, D.","contributorId":57339,"corporation":false,"usgs":true,"family":"Steinaker","given":"D.","email":"","affiliations":[],"preferred":false,"id":469808,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Twomlow, S.","contributorId":22650,"corporation":false,"usgs":true,"family":"Twomlow","given":"S.","email":"","affiliations":[],"preferred":false,"id":469801,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}}
,{"id":70041507,"text":"sir20125205 - 2012 - Relations among water levels, specific conductance, and depths of bedrock fractures in four road-salt-contaminated wells in Maine, 2007–9","interactions":[],"lastModifiedDate":"2017-06-10T11:19:08","indexId":"sir20125205","displayToPublicDate":"2012-12-06T00:00:00","publicationYear":"2012","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":"2012-5205","title":"Relations among water levels, specific conductance, and depths of bedrock fractures in four road-salt-contaminated wells in Maine, 2007–9","docAbstract":"Data on groundwater-level, specific conductance (a surrogate for chloride), and temperature were collected continuously from 2007 through 2009 at four bedrock wells known to be affected by road salts in an effort to determine the effects of road salting and fractures in bedrock that intersect the well at a depth below the casing on the presence of chloride in groundwater. Dissolved-oxygen data collected periodically also were used to make inferences about the interaction of fractures and groundwater flow. Borehole geophysical tools were used to determine the depths of fractures in each well that were actively contributing flow to the well, under both static and pumped conditions; sample- and measurement-depths were selected to correspond to the depths of these active fractures. Samples of water from the wells, collected at depths corresponding to active bedrock fractures, were analyzed for chloride concentration and specific conductance; from these analyses, a linear relation between chloride concentration and specific conductance was established, and continuous and periodic measurements of specific conductance were assumed to represent chloride concentration of the well water at the depth of measurement. To varying degrees, specific conductance increased in at least two of the wells during winter and spring thaws; the shallowest well, which also was closest to the road receiving salt treatment during the winter, exhibited the largest changes in specific conductance during thaws. Recharge events during summer months, long after application of road salt had ceased for the year, also produced increases in specific conductance in some of the wells, indicating that chloride which had accumulated or sequestered in the overburden was transported to the wells throughout the year. Geophysical data and periodic profiles of water quality along the length of each well’s borehole indicated that the greatest changes in water quality were associated with active fractures; in one case, high concentration of dissolved oxygen at the bottom of the well indicated the presence of a highly transmissive fracture that was in good connection with a surficial feature (stream or atmosphere). Data indicated that fractures have a substantial influence on the transport of chlorides to the subsurface; that elevated specific conductance occurred throughout the year, not just when road salts were applied; and that chloride contamination, as indicated by elevated specific conductance, may persist for years.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125205","collaboration":"Prepared in cooperation with Maine Department of Transportation","usgsCitation":"Schalk, C.W., and Stasulis, N.W., 2012, Relations among water levels, specific conductance, and depths of bedrock fractures in four road-salt-contaminated wells in Maine, 2007–9: U.S. Geological Survey Scientific Investigations Report 2012-5205, viii, 47 p., https://doi.org/10.3133/sir20125205.","productDescription":"viii, 47 p.","numberOfPages":"60","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":263738,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5205.gif"},{"id":263736,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5205/"},{"id":263737,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5205/pdf/sir2012-5205_508.pdf"}],"scale":"24000","projection":"Universal Transverse Mercator projection, Zone 19 North","country":"United States","state":"Maine","county":"Cumberland;Hancock;Kennebec","city":"Gray;Sullivan;West Gardiner","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -70.75,43.5 ], [ -70.75,44.75 ], [ -68.0,44.75 ], [ -68.0,43.5 ], [ -70.75,43.5 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50c1be8ae4b09fd40bb0eb27","contributors":{"authors":[{"text":"Schalk, Charles W. cwschalk@usgs.gov","contributorId":1726,"corporation":false,"usgs":true,"family":"Schalk","given":"Charles","email":"cwschalk@usgs.gov","middleInitial":"W.","affiliations":[{"id":371,"text":"Maine Water Science Center","active":true,"usgs":true}],"preferred":true,"id":469872,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stasulis, Nicholas W. 0000-0001-7645-4867 nstasuli@usgs.gov","orcid":"https://orcid.org/0000-0001-7645-4867","contributorId":4520,"corporation":false,"usgs":true,"family":"Stasulis","given":"Nicholas","email":"nstasuli@usgs.gov","middleInitial":"W.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":469873,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70041511,"text":"fs20123133 - 2012 - Wetland fire remote sensing research--The Greater Everglades example","interactions":[],"lastModifiedDate":"2012-12-06T21:52:54","indexId":"fs20123133","displayToPublicDate":"2012-12-06T00:00:00","publicationYear":"2012","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":"2012-3133","title":"Wetland fire remote sensing research--The Greater Everglades example","docAbstract":"Fire is a major factor in the Everglades ecosystem. For thousands of years, lightning-strike fires from summer thunderstorms have helped create and maintain a dynamic landscape suited both to withstand fire and recover quickly in the wake of frequent fires. Today, managers in the Everglades National Park are implementing controlled burns to promote healthy, sustainable vegetation patterns and ecosystem functions. The U.S. Geological Survey (USGS) is using remote sensing to improve fire-management databases in the Everglades, gain insights into post-fire land-cover dynamics, and develop spatially and temporally explicit fire-scar data for habitat and hydrologic modeling.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20123133","usgsCitation":"Jones, J., 2012, Wetland fire remote sensing research--The Greater Everglades example: U.S. Geological Survey Fact Sheet 2012-3133, 2 p.; maps (col.), https://doi.org/10.3133/fs20123133.","productDescription":"2 p.; maps (col.)","numberOfPages":"2","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"links":[{"id":263769,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs_2012_3133.gif"},{"id":263767,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2012/3133/"},{"id":263768,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2012/3133/pdf/fs2012-3133.pdf"}],"country":"United States","state":"Florida","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -81.5183,24.85 ], [ -81.5183,25.8899 ], [ -80.3887,25.8899 ], [ -80.3887,24.85 ], [ -81.5183,24.85 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50c1bea4e4b09fd40bb0eb3e","contributors":{"authors":[{"text":"Jones, John W. 0000-0001-6117-3691 jwjones@usgs.gov","orcid":"https://orcid.org/0000-0001-6117-3691","contributorId":2220,"corporation":false,"usgs":true,"family":"Jones","given":"John","email":"jwjones@usgs.gov","middleInitial":"W.","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"preferred":true,"id":469886,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70041501,"text":"fs20123134 - 2012 - Net Ecosystem Production (NEP) of the Great Plains, United States","interactions":[],"lastModifiedDate":"2012-12-06T21:28:27","indexId":"fs20123134","displayToPublicDate":"2012-12-06T00:00:00","publicationYear":"2012","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":"2012-3134","title":"Net Ecosystem Production (NEP) of the Great Plains, United States","docAbstract":"Gross primary production (GPP) and ecosystem respiration (Re) are the fundamental environmental characteristics that promote carbon exchanges with the atmosphere (Chapin and others, 2009), although other exchanges of carbon, such as direct oxidation (Lovett and others, 2006), can modify net ecosystem production (NEP). The accumulation of carbon in terrestrial ecosystems results in systems in which soil organic matter (SOM) carbon often exceeds biomass carbon (Post and Kwon, 2000). This SOM pool exists at a steady state between GPP and Re in ecosystems unless drivers change or the ecosystem endures environmental perturbations (for example, climatic). As indicated by Wilhelm and others (2011), conversion of grasslands to agriculture and cultivation can result in reduced soil carbon, with the release of carbon dioxide (CO<sub>2</sub>) to the atmosphere by stimulated oxidation and higher Re; therefore, land-use and land management practices have clear effects on NEP, with potential repercussions on ecosystems. The recent demand for biofuels has changed land-use and cropping patterns, especially in Midwestern United States (Wilhelm and others, 2011). It is important to ensure the sustainability of these and other land uses and to assess the effects on NEP.\nFlux tower networks, such as AmeriFlux and FLUXNET, consist of a growing number of eddy covariance flux tower sites that provide a synoptic record of the exchange of carbon, water, and energy between the ecosystem and atmosphere at various temporal frequencies. These towers also detect and measure certain site characteristics, such as wind, temperature, precipitation, humidity, atmospheric pressure, soil features, and phenological progressions. Efforts are continuous to combine flux tower network data with remote sensing data to upscale the conditions observed at specific sites to a regional and, ultimately, worldwide scale. Data-driven regression tree models have the ability to incorporate flux tower records and remote sensing data to quantify exchanges of carbon with the atmosphere (Wylie and others, 2007; Xiao and others, 2010; Zhang and others, 2010; Zhang and others, 2011). Previous study results demonstrated the dramatic effect weather has on NEP and revealed specific ecoregions and times acting as carbon sinks or sources. As of 2012, more than 100 site-years of flux tower measurements, represented by more than 50 individual cropland or grassland sites throughout the Great Plains and surrounding area, have been acquired, quality controlled, and partitioned into gross photosynthesis (Pg) and ecosystem Re using detailed light-response, soil temperature, and vapor pressure deficit (VPD) based analysis.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20123134","usgsCitation":"Howard, D., Gilmanov, T., Gu, Y., Wylie, B., and Zhang, L., 2012, Net Ecosystem Production (NEP) of the Great Plains, United States: U.S. Geological Survey Fact Sheet 2012-3134, 6 p.; maps (col.), https://doi.org/10.3133/fs20123134.","productDescription":"6 p.; maps (col.)","numberOfPages":"6","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-040006","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":263765,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2012/3134/fs12-3134.pdf"},{"id":263764,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2012/3134/"},{"id":263766,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs_2012_3134.gif"}],"country":"United States;Canada","otherGeospatial":"Great Plains","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -114.2,28.2 ], [ -114.2,54.1 ], [ -95.6,54.1 ], [ -95.6,28.2 ], [ -114.2,28.2 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50c1be81e4b09fd40bb0eb1f","contributors":{"authors":[{"text":"Howard, Daniel 0000-0002-7563-7538","orcid":"https://orcid.org/0000-0002-7563-7538","contributorId":56946,"corporation":false,"usgs":true,"family":"Howard","given":"Daniel","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":false,"id":469862,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gilmanov, Tagir","contributorId":6351,"corporation":false,"usgs":true,"family":"Gilmanov","given":"Tagir","affiliations":[],"preferred":false,"id":469861,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gu, Yingxin 0000-0002-3544-1856 ygu@usgs.gov","orcid":"https://orcid.org/0000-0002-3544-1856","contributorId":409,"corporation":false,"usgs":true,"family":"Gu","given":"Yingxin","email":"ygu@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":469860,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wylie, Bruce 0000-0002-7374-1083","orcid":"https://orcid.org/0000-0002-7374-1083","contributorId":107996,"corporation":false,"usgs":true,"family":"Wylie","given":"Bruce","affiliations":[],"preferred":false,"id":469864,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zhang, Li","contributorId":98139,"corporation":false,"usgs":true,"family":"Zhang","given":"Li","affiliations":[],"preferred":false,"id":469863,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70041488,"text":"70041488 - 2012 - Variability in expression of anadromy by female <i>Oncorhynchus mykiss</i> within a river network","interactions":[],"lastModifiedDate":"2012-12-07T10:46:40","indexId":"70041488","displayToPublicDate":"2012-12-06T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1528,"text":"Environmental Biology of Fishes","active":true,"publicationSubtype":{"id":10}},"title":"Variability in expression of anadromy by female <i>Oncorhynchus mykiss</i> within a river network","docAbstract":"We described and predicted spatial variation in marine migration (anadromy) of female <i>Oncorhynchus mykiss</i> in the John Day River watershed, Oregon. We collected 149 juvenile <i>O. mykiss</i> across 72 sites and identified locations used by anadromous females by assigning maternal origin (anadromous versus non-anadromous) to each juvenile. These assignments used comparisons of strontium to calcium ratios in otolith primordia and freshwater growth regions to indicate maternal origin. We used logistic regression to predict probability of anadromy in relation to mean annual stream runoff using data from a subset of individuals. This model correctly predicted anadromy in a second sample of individuals with a moderate level of accuracy (e.g., 68% correctly predicted with a 0.5 classification threshold). Residuals from the models were not spatially autocorrelated, suggesting that remaining variability in the expression of anadromy was due to localized influences, as opposed to broad-scale gradients unrelated to mean annual stream runoff. These results are important for the management of <i>O. mykiss</i> because anadromous individuals (steelhead) within the John Day River watershed are listed as a threatened species, and it is difficult to discern juvenile steelhead from non-anadromous individuals (rainbow trout) in the field. Our results provide a broad-scale description and prediction of locations supporting anadromy, and new insight for habitat restoration, monitoring, and research to better manage and understand the expression of anadromy in <i>O. mykiss</i>.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Environmental Biology of Fishes","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","publisherLocation":"Reston, VA","doi":"10.1007/s10641-011-9946-4","usgsCitation":"Mills, J.S., Dunham, J., Reeves, G.H., McMillan, J.R., Zimmerman, C.E., and Jordan, C.E., 2012, Variability in expression of anadromy by female <i>Oncorhynchus mykiss</i> within a river network: Environmental Biology of Fishes, v. 93, no. 4, p. 505-517, https://doi.org/10.1007/s10641-011-9946-4.","productDescription":"13 p.","startPage":"505","endPage":"517","ipdsId":"IP-034081","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":263783,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":263782,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s10641-011-9946-4"}],"country":"United States","state":"Oregon","otherGeospatial":"John Day River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -118.74582,44.249292 ], [ -118.74582,44.459598 ], [ -118.525734,44.459598 ], [ -118.525734,44.249292 ], [ -118.74582,44.249292 ] ] ] } } ] }","volume":"93","issue":"4","noUsgsAuthors":false,"publicationDate":"2011-11-24","publicationStatus":"PW","scienceBaseUri":"50c31e9ee4b0b57f2415d22b","contributors":{"authors":[{"text":"Mills, Justin S.","contributorId":56944,"corporation":false,"usgs":true,"family":"Mills","given":"Justin","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":469830,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dunham, Jason B.","contributorId":64791,"corporation":false,"usgs":true,"family":"Dunham","given":"Jason B.","affiliations":[],"preferred":false,"id":469831,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reeves, Gordon H.","contributorId":101521,"corporation":false,"usgs":false,"family":"Reeves","given":"Gordon","email":"","middleInitial":"H.","affiliations":[{"id":527,"text":"Pacific Northwest Research Station","active":false,"usgs":true}],"preferred":false,"id":469833,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McMillan, John R.","contributorId":27905,"corporation":false,"usgs":true,"family":"McMillan","given":"John","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":469829,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zimmerman, Christian E. 0000-0002-3646-0688 czimmerman@usgs.gov","orcid":"https://orcid.org/0000-0002-3646-0688","contributorId":410,"corporation":false,"usgs":true,"family":"Zimmerman","given":"Christian","email":"czimmerman@usgs.gov","middleInitial":"E.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":469828,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jordan, Chris E.","contributorId":88233,"corporation":false,"usgs":true,"family":"Jordan","given":"Chris","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":469832,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70041468,"text":"ofr20121147 - 2012 - Streamflow statistics for selected streams in North Dakota, Minnesota, Manitoba, and Saskatchewan","interactions":[],"lastModifiedDate":"2017-10-14T11:24:33","indexId":"ofr20121147","displayToPublicDate":"2012-12-06T00:00:00","publicationYear":"2012","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":"2012-1147","title":"Streamflow statistics for selected streams in North Dakota, Minnesota, Manitoba, and Saskatchewan","docAbstract":"Statistical summaries of streamflow data for the periods of record through water year 2009 for selected active and discontinued U.S. Geological Survey streamflow-gaging stations in North Dakota, Minnesota, Manitoba, and Saskatchewan were compiled. The summaries for each streamflow-gaging station include a brief station description, a graph of the annual peak and annual mean discharge for the period of record, statistics of monthly and annual mean discharges, monthly and annual flow durations, probability of occurrence of annual high discharges, annual peak discharge and corresponding gage height for the period of record, and monthly and annual mean discharges for the period of record.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121147","collaboration":"In cooperation with the North Dakota State Water Commission, North Dakota Department of Health, North Dakota Department of Transportation, and Red River Joint Water Resource Board","usgsCitation":"Williams-Sether, T., 2012, Streamflow statistics for selected streams in North Dakota, Minnesota, Manitoba, and Saskatchewan: U.S. Geological Survey Open-File Report 2012-1147, iv, 11 p., https://doi.org/10.3133/ofr20121147.","productDescription":"iv, 11 p.","numberOfPages":"20","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-029695","costCenters":[{"id":478,"text":"North Dakota Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":263731,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1147.gif"},{"id":263729,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1147/"},{"id":263730,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1147/ofr2012-1147.pdf"}],"country":"Canada;United States","state":"Manitoba;Minnesota;North Dakota;Saskatchewan","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -104.0,45.916667 ], [ -104.0,49.0 ], [ -97.0,49.0 ], [ -97.0,45.916667 ], [ -104.0,45.916667 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50c11ac0e4b005831885e282","contributors":{"authors":[{"text":"Williams-Sether, Tara","contributorId":57846,"corporation":false,"usgs":true,"family":"Williams-Sether","given":"Tara","affiliations":[],"preferred":false,"id":469790,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70041370,"text":"pp1797 - 2012 - Baseline and projected future carbon storage and greenhouse-gas fluxes in ecosystems of the Western United States","interactions":[],"lastModifiedDate":"2012-12-05T15:40:32","indexId":"pp1797","displayToPublicDate":"2012-12-05T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":331,"text":"Professional Paper","code":"PP","onlineIssn":"2330-7102","printIssn":"1044-9612","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1797","title":"Baseline and projected future carbon storage and greenhouse-gas fluxes in ecosystems of the Western United States","docAbstract":"This assessment was conducted to fulfill the requirements of section 712 of the Energy Independence and Security Act (EISA) of 2007 and to improve understanding of carbon and greenhouse gas (GHG) fluxes in ecosystems of the Western United States. The assessment examined carbon storage, carbon fluxes, and other GHG fluxes (methane and nitrous oxide) in all major terrestrial ecosystems (forests, grasslands/shrublands, agricultural lands, and wetlands) and aquatic ecosystems (rivers, streams, lakes, reservoirs, and coastal waters) in two time periods: baseline (generally in the first half of the 2010s) and future (projections from baseline to 2050). The assessment was based on measured and observed data collected by the U.S. Geological Survey (USGS) and many other agencies and organizations and used remote sensing, statistical methods, and simulation models.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1797","isbn":"978-1-4113-3519-6","usgsCitation":"Zhu, Z., and Reed, B.C., 2012, Baseline and projected future carbon storage and greenhouse-gas fluxes in ecosystems of the Western United States: U.S. Geological Survey Professional Paper 1797, x, 192 p., https://doi.org/10.3133/pp1797.","productDescription":"x, 192 p.","numberOfPages":"206","additionalOnlineFiles":"N","costCenters":[{"id":293,"text":"Geographic Analysis and Monitoring Program","active":false,"usgs":true}],"links":[{"id":263716,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/pp_1797.gif"},{"id":263673,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/pp/1797/"},{"id":263674,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1797/pdf/PP1797_WholeDocument.pdf"}],"country":"United States","state":"Arizona;California;Colorado;Idaho;Montana;Nevada;New Mexico;Oregon;South Dakota;Texas;Utah;Wyoming","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.5,28.0 ], [ -124.5,49.0 ], [ -100.0,49.0 ], [ -100.0,28.0 ], [ -124.5,28.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50c11a9ae4b005831885e269","contributors":{"authors":[{"text":"Zhu, Zhi-Liang zzhu@usgs.gov","contributorId":3636,"corporation":false,"usgs":true,"family":"Zhu","given":"Zhi-Liang","email":"zzhu@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":469649,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reed, Bradley C. 0000-0002-1132-7178 reed@usgs.gov","orcid":"https://orcid.org/0000-0002-1132-7178","contributorId":2901,"corporation":false,"usgs":true,"family":"Reed","given":"Bradley","email":"reed@usgs.gov","middleInitial":"C.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":469648,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70041434,"text":"sir20125251 - 2012 - Ecosystem services valuation to support decisionmaking on public lands—A case study of the San Pedro River watershed, Arizona","interactions":[],"lastModifiedDate":"2012-12-05T08:34:24","indexId":"sir20125251","displayToPublicDate":"2012-12-05T00:00:00","publicationYear":"2012","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":"2012-5251","title":"Ecosystem services valuation to support decisionmaking on public lands—A case study of the San Pedro River watershed, Arizona","docAbstract":"This report details the findings of the Bureau of Land Management–U.S. Geological Survey Ecosystem Services Valuation Pilot Study. This project evaluated alternative methods and tools that quantify and value ecosystem services, and it assessed the tools’ readiness for use in the Bureau of Land Management decisionmaking process. We tested these tools on the San Pedro River watershed in northern Sonora, Mexico, and southeast Arizona. The study area includes the San Pedro Riparian National Conservation Area (managed by the Bureau of Land Management), which has been a focal point for conservation activities and scientific research in recent decades. We applied past site-specific primary valuation studies, value transfer, the Wildlife Habitat Benefits Estimation Toolkit, and the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) and Artificial Intelligence for Ecosystem Services (ARIES) models to value locally important ecosystem services for the San Pedro River watershed—water, carbon, biodiversity, and cultural values. We tested these approaches on a series of scenarios to evaluate ecosystem service changes and the ability of the tools to accommodate scenarios. A suite of additional tools were either at too early a stage of development to run, were proprietary, or were place-specific tools inappropriate for application to the San Pedro River watershed. We described the strengths and weaknesses of these additional ecosystem service tools against a series of evaluative criteria related to their usefulness for Bureau of Land Management decisionmaking. Using these tools, we quantified gains or losses of ecosystem services under three categories of scenarios: urban growth, mesquite management, and water augmentation. These results quantify tradeoffs and could be useful for decisionmaking within Bureau of Land Management district or field offices. Results are accompanied by a relatively high level of uncertainty associated with model outputs, valuation methods, and discount rates applied. Further guidance on representing uncertainty and applying uncertain results in decisionmaking would benefit both tool developers and those offices in using ecosystem services to compare management tradeoffs. Decisionmakers and Bureau of Land Management managers at the State-, district-, and field-office level would also benefit from continuing model improvements, training, and guidance on tool use that can be provided by the U.S. Geological Survey, the Bureau of Land Management, and the Department of the Interior. Tradeoffs were identified in the level of effort needed to parameterize and run tools and the amount and quality of information they provide to the decision process. We found the Wildlife Habitat Benefits Estimation Toolkit, Ecosystem Services Review, and United Nations Environment Programme–World Conservation Monitoring Centre Ecosystem Services Toolkit to be immediately feasible for application by the Bureau of Land Management, given proper guidance on their use. It is also feasible for the Bureau of Land Management to use the InVEST model, but in early 2012 the process of parameterizing the model required resources and expertise that are unlikely to be available in most Bureau of Land Management district or field offices. Application of past primary valuation is feasible, but developing new primary-valuation studies is too time consuming for regular application. Value transfer approaches (aside from the Wildlife Habitat Benefits Estimation Toolkit) are best applied carefully on the basis of guidelines described in this report, to reduce transfer error. The ARIES model can provide useful information in regions modeled in the past (Arizona, California, Colorado, and Washington), but it lacks some features that will improve its usability, such as a generalized model that could be applied anywhere in the United States. Eleven other tools described in this report could become useful as the tools more fully develop, in high-profile cases for which additional resources are available for tool application or in case-study regions where place-specific models have already been developed. To improve the value of these tools in decisionmaking, we suggest scientific needs that agencies such as U.S. Geological Survey can help meet—for instance, development and support of data archives. Such archives could greatly reduce resource needs and improve the reliability and consistency of results. Given the rapid state of evolution in the field, periodic follow-up studies on ecosystem services tools would help to ensure that the Bureau of Land Management and other public land management agencies are kept up to date on new tools and features that bring ecosystem services closer to readiness for use in regular decisionmaking.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125251","collaboration":"Prepared in cooperation with the Bureau of Land Management","usgsCitation":"Bagstad, K.J., Semmens, D., Winthrop, R., Jaworksi, D., and Larson, J., 2012, Ecosystem services valuation to support decisionmaking on public lands—A case study of the San Pedro River watershed, Arizona: U.S. Geological Survey Scientific Investigations Report 2012-5251, viii, 93 p., https://doi.org/10.3133/sir20125251.","productDescription":"viii, 93 p.","numberOfPages":"105","additionalOnlineFiles":"N","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":263687,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5251.gif"},{"id":263685,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5251/"},{"id":263686,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5251/sir2012-5251.pdf"}],"scale":"100000","projection":"Universal Transverse Mercator projection, Zone 12 North","datum":"North American Datum 1983","country":"Mexico;United States","state":"Arizona;Sonora","county":"Cochise;Gila;Graham;Pima;Pinal;Santa Cruz","otherGeospatial":"San Pedro River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -111.75,31.0 ], [ -111.75,33.25 ], [ -109.75,33.25 ], [ -109.75,31.0 ], [ -111.75,31.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50bfb8b6e4b01744973f7796","contributors":{"authors":[{"text":"Bagstad, Kenneth J. 0000-0001-8857-5615 kjbagstad@usgs.gov","orcid":"https://orcid.org/0000-0001-8857-5615","contributorId":3680,"corporation":false,"usgs":true,"family":"Bagstad","given":"Kenneth","email":"kjbagstad@usgs.gov","middleInitial":"J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":469711,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Semmens, Darius J. 0000-0001-7924-6529","orcid":"https://orcid.org/0000-0001-7924-6529","contributorId":64201,"corporation":false,"usgs":true,"family":"Semmens","given":"Darius J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":469713,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Winthrop, Rob","contributorId":60099,"corporation":false,"usgs":true,"family":"Winthrop","given":"Rob","affiliations":[],"preferred":false,"id":469712,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jaworksi, Delilah","contributorId":75828,"corporation":false,"usgs":true,"family":"Jaworksi","given":"Delilah","email":"","affiliations":[],"preferred":false,"id":469715,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Larson, Joel","contributorId":69859,"corporation":false,"usgs":true,"family":"Larson","given":"Joel","email":"","affiliations":[],"preferred":false,"id":469714,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70041413,"text":"70041413 - 2012 - Use of ASTER and MODIS thermal infrared data to quantify heat flow and hydrothermal change at Yellowstone National Park","interactions":[],"lastModifiedDate":"2019-05-31T08:23:29","indexId":"70041413","displayToPublicDate":"2012-12-05T00:00:00","publicationYear":"2012","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":"Use of ASTER and MODIS thermal infrared data to quantify heat flow and hydrothermal change at Yellowstone National Park","docAbstract":"<p id=\"sp0005\">The overarching aim of this study was to use satellite thermal infrared (TIR) remote sensing to monitor geothermal activity within the Yellowstone geothermal area to meet the missions of both the U.S. Geological Survey and the Yellowstone National Park Geology Program. Specific goals were to: 1) address the challenges of monitoring the surface thermal characteristics of the &gt;&nbsp;10,000 spatially and temporally dynamic thermal features in the Park (including hot springs, pools, geysers, fumaroles, and mud pots) that are spread out over ~&nbsp;5000&nbsp;km<sup>2</sup>, by using satellite TIR remote sensing tools (e.g., ASTER and MODIS), 2) to estimate the radiant geothermal heat flux (GHF) for Yellowstone's thermal areas, and 3) to identify normal, background thermal changes so that significant, abnormal changes can be recognized, should they ever occur (e.g., changes related to tectonic, hydrothermal, impending volcanic processes, or human activities, such as nearby geothermal development). ASTER TIR data (90-m pixels) were used to estimate the radiant GHF from all of Yellowstone's thermal features and update maps of thermal areas. MODIS TIR data (1-km pixels) were used to record background thermal radiance variations from March 2000 through December 2010 and establish thermal change detection limits.</p><p id=\"sp0010\">A lower limit for the radiant GHF estimated from ASTER TIR temperature data was established at ~&nbsp;2.0&nbsp;GW, which is ~&nbsp;30–45% of the heat flux estimated through geochemical thermometry. Also, about 5&nbsp;km<sup>2</sup><span>&nbsp;</span>of thermal areas was added to the geodatabase of mapped thermal areas. A decade-long time-series of MODIS TIR radiance data was dominated by seasonal cycles. A background subtraction technique was used in an attempt to isolate variations due to geothermal changes. Several statistically significant perturbations were noted in the time-series from Norris Geyser Basin, however many of these did not correspond to documented thermal disturbances. This study provides concrete examples of the strengths and limitations of current satellite TIR monitoring of geothermal areas, highlighting some specific areas that can be improved. This work provides a framework for future satellite-based thermal monitoring at Yellowstone and other volcanic and geothermal systems.</p>","language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.jvolgeores.2012.04.022","usgsCitation":"Vaughan, R.G., Keszthelyi, L., Lowenstern, J.B., Jaworowski, C., and Heasler, H., 2012, Use of ASTER and MODIS thermal infrared data to quantify heat flow and hydrothermal change at Yellowstone National Park: Journal of Volcanology and Geothermal Research, v. 233-234, p. 72-89, https://doi.org/10.1016/j.jvolgeores.2012.04.022.","productDescription":"18 p.","startPage":"72","endPage":"89","ipdsId":"IP-037921","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"links":[{"id":263699,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Montana, Oregon, Wyoming","otherGeospatial":"Yellowstone National Park","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -111.156,44.1324 ], [ -111.156,45.109 ], [ -109.8242,45.109 ], [ -109.8242,44.1324 ], [ -111.156,44.1324 ] ] ] } } ] }","volume":"233-234","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50bfbad2e4b01744973f77c2","contributors":{"authors":[{"text":"Vaughan, R. Greg 0000-0002-0850-6669","orcid":"https://orcid.org/0000-0002-0850-6669","contributorId":69030,"corporation":false,"usgs":true,"family":"Vaughan","given":"R.","email":"","middleInitial":"Greg","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":469674,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Keszthelyi, Laszlo P. 0000-0003-1879-4331 laz@usgs.gov","orcid":"https://orcid.org/0000-0003-1879-4331","contributorId":52802,"corporation":false,"usgs":true,"family":"Keszthelyi","given":"Laszlo P.","email":"laz@usgs.gov","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":469672,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lowenstern, Jacob B. 0000-0003-0464-7779 jlwnstrn@usgs.gov","orcid":"https://orcid.org/0000-0003-0464-7779","contributorId":2755,"corporation":false,"usgs":true,"family":"Lowenstern","given":"Jacob","email":"jlwnstrn@usgs.gov","middleInitial":"B.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":469670,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jaworowski, Cheryl","contributorId":25989,"corporation":false,"usgs":true,"family":"Jaworowski","given":"Cheryl","affiliations":[],"preferred":false,"id":469671,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Heasler, Henry","contributorId":62683,"corporation":false,"usgs":true,"family":"Heasler","given":"Henry","affiliations":[],"preferred":false,"id":469673,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70041454,"text":"fs20123124 - 2012 - The Midwest Stream Quality Assessment","interactions":[],"lastModifiedDate":"2023-03-22T14:05:41.793654","indexId":"fs20123124","displayToPublicDate":"2012-12-05T00:00:00","publicationYear":"2012","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":"2012-3124","title":"The Midwest Stream Quality Assessment","docAbstract":"In 2013, the U.S. Geological Survey (USGS) National Water-Quality Assessment Program (NAWQA) and USGS Columbia Environmental Research Center (CERC) will be collaborating with the U.S. Environmental Protection Agency (EPA) National Rivers and Streams Assessment (NRSA) to assess stream quality across the Midwestern United States. The sites selected for this study are a subset of the larger NRSA, implemented by the EPA, States and Tribes to sample flowing waters across the United States (<a href=\"http://water.epa.gov/type/rsl/monitoring/riverssurvey/index.cfm\"><em>http://water.epa.gov/type/rsl/monitoring/riverssurvey/index.cfm</em></a>). The goals are to characterize water-quality stressors—contaminants, nutrients, and sediment—and ecological conditions in streams throughout the Midwest and to determine the relative effects of these stressors on aquatic organisms in the streams. Findings will contribute useful information for communities and policymakers by identifying which human and environmental factors are the most critical in controlling stream quality. This collaborative study enhances information provided to the public and policymakers and minimizes costs by leveraging and sharing data gathered under existing programs. In the spring and early summer, NAWQA will sample streams weekly for contaminants, nutrients, and sediment. During the same time period, CERC will test sediment and water samples for toxicity, deploy time-integrating samplers, and measure reproductive effects and biomarkers of contaminant exposure in fish or amphibians. NRSA will sample sites once during the summer to assess ecological and habitat conditions in the streams by collecting data on algal, macroinvertebrate, and fish communities and collecting detailed physical-habitat measurements. Study-team members from all three programs will work in collaboration with USGS Water Science Centers and State agencies on study design, execution of sampling and analysis, and reporting.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20123124","collaboration":"A Collaboration Between the U.S. Geological Survey and the U.S. Environmental Protection Agency","usgsCitation":"Van Metre, P.C., Frey, J.W., and Tarquinio, E., 2012, The Midwest Stream Quality Assessment: U.S. Geological Survey Fact Sheet 2012-3124, 2 p., https://doi.org/10.3133/fs20123124.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":263722,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2012/3124/"},{"id":263724,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs_2012_3124.jpg"},{"id":263723,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2012/3124/pdf/Midwest_Stream_Quality_Assess_%20fs.pdf"}],"country":"United States","otherGeospatial":"Midwest","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -98.19580078125,\n              37.020098201368114\n            ],\n            [\n              -98.19580078125,\n              45.38301927899065\n            ],\n            [\n              -82.55126953124999,\n              45.38301927899065\n            ],\n            [\n              -82.55126953124999,\n              37.020098201368114\n            ],\n            [\n              -98.19580078125,\n              37.020098201368114\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50c11acde4b005831885e289","contributors":{"authors":[{"text":"Van Metre, Peter C. 0000-0001-7564-9814","orcid":"https://orcid.org/0000-0001-7564-9814","contributorId":211144,"corporation":false,"usgs":true,"family":"Van Metre","given":"Peter","email":"","middleInitial":"C.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":867130,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Frey, Jeffrey W. 0000-0002-3453-5009 jwfrey@usgs.gov","orcid":"https://orcid.org/0000-0002-3453-5009","contributorId":487,"corporation":false,"usgs":true,"family":"Frey","given":"Jeffrey","email":"jwfrey@usgs.gov","middleInitial":"W.","affiliations":[{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true},{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":867131,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tarquinio, Ellen","contributorId":303308,"corporation":false,"usgs":false,"family":"Tarquinio","given":"Ellen","email":"","affiliations":[],"preferred":false,"id":867132,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70041411,"text":"70041411 - 2012 - Detecting hidden volcanic explosions from Mt. Cleveland Volcano, Alaska with infrasound and ground-couples airwaves","interactions":[],"lastModifiedDate":"2019-05-30T11:42:18","indexId":"70041411","displayToPublicDate":"2012-12-05T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Detecting hidden volcanic explosions from Mt. Cleveland Volcano, Alaska with infrasound and ground-couples airwaves","docAbstract":"In Alaska, where many active volcanoes exist without ground-based instrumentation, the use of techniques suitable for distant monitoring is pivotal. In this study we report regional-scale seismic and infrasound observations of volcanic activity at Mt. Cleveland between December 2011 and August 2012. During this period, twenty explosions were detected by infrasound sensors as far away as 1827 km from the active vent, and ground-coupled acoustic waves were recorded at seismic stations across the Aleutian Arc. Several events resulting from the explosive disruption of small lava domes within the summit crater were confirmed by analysis of satellite remote sensing data. However, many explosions eluded initial, automated, analyses of satellite data due to poor weather conditions. Infrasound and seismic monitoring provided effective means for detecting these hidden events. We present results from the implementation of automatic infrasound and seismo-acoustic eruption detection algorithms, and review the challenges of real-time volcano monitoring operations in remote regions. We also model acoustic propagation in the Northern Pacific, showing how tropospheric ducting effects allow infrasound to travel long distances across the Aleutian Arc. The successful results of our investigation provide motivation for expanded efforts in infrasound monitoring across the Aleutians and contributes to our knowledge of the number and style of vulcanian eruptions at Mt. Cleveland.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Geophysical Research Letters","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Geophysical Union","publisherLocation":"Washington, D.C.","doi":"10.1029/2012GL053635","usgsCitation":"De Angelis, S., Fee, D., Haney, M., and Schneider, D., 2012, Detecting hidden volcanic explosions from Mt. Cleveland Volcano, Alaska with infrasound and ground-couples airwaves: Geophysical Research Letters, v. 39, L21312; 6 p., https://doi.org/10.1029/2012GL053635.","productDescription":"L21312; 6 p.","temporalStart":"2011-12-01","temporalEnd":"2012-08-31","ipdsId":"IP-042065","costCenters":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":474223,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2012gl053635","text":"Publisher Index Page"},{"id":263713,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":263712,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1029/2012GL053635"}],"country":"United States","state":"Alaska","otherGeospatial":"Mt. Cleveland","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -169.958166,52.813246 ], [ -169.958166,52.83325 ], [ -169.938151,52.83325 ], [ -169.938151,52.813246 ], [ -169.958166,52.813246 ] ] ] } } ] }","volume":"39","noUsgsAuthors":false,"publicationDate":"2012-11-13","publicationStatus":"PW","scienceBaseUri":"50bfb793e4b01744973f778e","contributors":{"authors":[{"text":"De Angelis, Slivio","contributorId":52055,"corporation":false,"usgs":true,"family":"De Angelis","given":"Slivio","email":"","affiliations":[],"preferred":false,"id":469663,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fee, David","contributorId":77761,"corporation":false,"usgs":true,"family":"Fee","given":"David","affiliations":[],"preferred":false,"id":469664,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haney, Matthew","contributorId":80555,"corporation":false,"usgs":true,"family":"Haney","given":"Matthew","affiliations":[],"preferred":false,"id":469666,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schneider, David","contributorId":78204,"corporation":false,"usgs":true,"family":"Schneider","given":"David","affiliations":[],"preferred":false,"id":469665,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70041307,"text":"sir20125156 - 2012 - Estimated probability of arsenic in groundwater from bedrock aquifers in New Hampshire, 2011","interactions":[],"lastModifiedDate":"2016-08-10T15:53:54","indexId":"sir20125156","displayToPublicDate":"2012-12-04T00:00:00","publicationYear":"2012","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":"2012-5156","title":"Estimated probability of arsenic in groundwater from bedrock aquifers in New Hampshire, 2011","docAbstract":"<p>Probabilities of arsenic occurrence in groundwater from bedrock aquifers at concentrations of 1, 5, and 10 micrograms per liter (&micro;g/L) were estimated during 2011 using multivariate logistic regression. These estimates were developed for use by the New Hampshire Environmental Public Health Tracking Program. About 39 percent of New Hampshire bedrock groundwater was identified as having at least a 50 percent chance of containing an arsenic concentration greater than or equal to 1 &micro;g/L. This compares to about 7 percent of New Hampshire bedrock groundwater having at least a 50 percent chance of containing an arsenic concentration equaling or exceeding 5 &micro;g/L and about 5 percent of the State having at least a 50 percent chance for its bedrock groundwater to contain concentrations at or above 10 &micro;g/L. The southeastern counties of Merrimack, Strafford, Hillsborough, and Rockingham have the greatest potential for having arsenic concentrations above 5 and 10 &micro;g/L in bedrock groundwater.</p>\n<p>Significant predictors of arsenic in groundwater from bedrock aquifers for all three thresholds analyzed included geologic, geochemical, land use, hydrologic, topographic, and demographic factors. Among the three thresholds evaluated, there were some differences in explanatory variables, but many variables were the same. More than 250 individual predictor variables were assembled for this study and tested as potential predictor variables for the models. More than 1,700 individual measurements of arsenic concentration from a combination of public and private water-supply wells served as the dependent (or predicted) variable in the models.</p>\n<p>The statewide maps generated by the probability models are not designed to predict arsenic concentration in any single well, but they are expected to provide useful information in areas of the State that currently contain little to no data on arsenic concentration. They also may aid in resource decision making, in determining potential risk for private wells, and in ecological-level analysis of disease outcomes. The approach for modeling arsenic in groundwater could also be applied to other environmental contaminants that have potential implications for human health, such as uranium, radon, fluoride, manganese, volatile organic compounds, nitrate, and bacteria.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125156","collaboration":"Prepared in cooperation with the New Hampshire Department of Health and Human Services and the New Hampshire Department of Environmental Services","usgsCitation":"Ayotte, J., Cahillane, M., Hayes, L., and Robinson, K.W., 2012, Estimated probability of arsenic in groundwater from bedrock aquifers in New Hampshire, 2011: U.S. Geological Survey Scientific Investigations Report 2012-5156, Report: vi, 25 p.; Geospatial Data, https://doi.org/10.3133/sir20125156.","productDescription":"Report: vi, 25 p.; Geospatial 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,{"id":70041359,"text":"sir20125246 - 2012 - Simulated effects of hydrologic, water quality, and land-use changes of the Lake Maumelle watershed, Arkansas, 2004–10","interactions":[{"subject":{"id":99012,"text":"sir20105239 - 2011 - Effects of Simulated Land-Use Changes on Water Quality of Lake Maumelle, Arkansas","indexId":"sir20105239","publicationYear":"2011","noYear":false,"title":"Effects of Simulated Land-Use Changes on Water Quality of Lake Maumelle, Arkansas"},"predicate":"SUPERSEDED_BY","object":{"id":70041359,"text":"sir20125246 - 2012 - Simulated effects of hydrologic, water quality, and land-use changes of the Lake Maumelle watershed, Arkansas, 2004–10","indexId":"sir20125246","publicationYear":"2012","noYear":false,"title":"Simulated effects of hydrologic, water quality, and land-use changes of the Lake Maumelle watershed, Arkansas, 2004–10"},"id":1}],"lastModifiedDate":"2012-12-04T11:23:00","indexId":"sir20125246","displayToPublicDate":"2012-12-04T00:00:00","publicationYear":"2012","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":"2012-5246","title":"Simulated effects of hydrologic, water quality, and land-use changes of the Lake Maumelle watershed, Arkansas, 2004–10","docAbstract":"Lake Maumelle, located in central Arkansas northwest of the cities of Little Rock and North Little Rock, is one of two principal drinking-water supplies for the Little Rock, and North Little Rock, Arkansas, metropolitan areas. Lake Maumelle and the Maumelle River (its primary tributary) are more pristine than most other reservoirs and streams in the region with 80 percent of the land area in the entire watershed being forested. However, as the Lake Maumelle watershed becomes increasingly more urbanized and timber harvesting becomes more extensive, concerns about the sustainability of the quality of the water supply also have increased.\n\nTwo hydrodynamic and water-quality models were developed to examine the hydrology and water quality in the Lake Maumelle watershed and changes that might occur as the watershed becomes more urbanized and timber harvesting becomes more extensive. A Hydrologic Simulation Program–FORTRAN watershed model was developed using continuous streamflow and discreet suspended-sediment and water-quality data collected from January 2004 through 2010. A CE–QUAL–W2 model was developed to simulate reservoir hydrodynamics and selected water-quality characteristics using the simulated output from the Hydrologic Simulation Program–FORTRAN model from January 2004 through 2010.\n\nThe calibrated Hydrologic Simulation Program–FORTRAN model and the calibrated CE–QUAL–W2 model were developed to simulate three land-use scenarios and to examine the potential effects of these land-use changes, as defined in the model, on the water quality of Lake Maumelle during the 2004 through 2010 simulation period. These scenarios included a scenario that simulated conversion of most land in the watershed to forest (scenario 1), a scenario that simulated conversion of potentially developable land to low-intensity urban land use in part of the watershed (scenario 2), and a scenario that simulated timber harvest in part of the watershed (scenario 3). Simulated land-use changes for scenarios 1 and 3 resulted in little (generally less than 10 percent) overall effect on the simulated water quality in the Hydrologic Simulation Program–FORTRAN model. The land-use change of scenario 2 affected subwatersheds that include Bringle, Reece, and Yount Creek tributaries and most other subwatersheds that drain into the northern side of Lake Maumelle; large percent increases in loading rates (generally between 10 and 25 percent) included dissolved nitrite plus nitrate nitrogen, dissolved orthophosphate, total phosphorus, suspended sediment, dissolved ammonia nitrogen, total organic carbon, and fecal coliform bacteria.\n\nFor scenario 1, the simulated changes in nutrient, suspended sediment, and total organic carbon loads from the Hydrologic Simulation Program–FORTRAN model resulted in very slight (generally less than 10 percent) changes in simulated water quality for Lake Maumelle, relative to the baseline condition. Following lake mixing in the falls of 2006 and 2007, phosphorus and nitrogen concentrations were higher than the baseline condition and chlorophyll a responded accordingly. The increased nutrient and chlorophyll a concentrations in late October and into 2007 were enough to increase concentrations, on average, for the entire simulation period (2004–10). For scenario 2, the simulated changes in nutrient, suspended sediment, total organic carbon, and fecal coliform bacteria loads from the Lake Maumelle watershed resulted in slight changes in simulated water quality for Lake Maumelle, relative to the baseline condition (total nitrogen decreased by 0.01 milligram per liter; dissolved orthophosphate increased by 0.001 milligram per liter; chlorophyll a decreased by 0.1 microgram per liter). The differences in these concentrations are approximately an order of magnitude less than the error between measured and simulated concentrations in the baseline model. During the driest summer in the simulation period (2006), phosphorus and nitrogen concentrations were lower than the baseline condition and chlorophyll a concentrations decreased during the same summer season. The decrease in nitrogen and chlorophyll a concentrations during the dry summer in 2006 was enough to decrease concentrations of these constituents very slightly, on average, for the entire simulation period (2004–10). For scenario 3, the changes in simulated nutrient, suspended sediment, total organic carbon, and fecal coliform bacteria loads from Lake Maumelle watershed resulted in very slight changes in simulated water quality within Lake Maumelle, relative to the baseline condition, for most of the reservoir.\n\nAmong the implications of the results of the modeling described in this report are those related to scale in both space and time. Spatial scales include limited size and location of land-use changes, their effects on loading rates, and resultant effects on water quality of Lake Maumelle. Temporally, the magnitude of the water-quality changes simulated by the land-use change scenarios over the 7-year period (2004–10) are not necessarily indicative of the changes that could be expected to occur with similar land-use changes persisting over a 20-, 30-, or 40- year period, for example. These implications should be tempered by realization of the described model limitations.\n\nThe Hydrologic Simulation Program–FORTRAN watershed model was calibrated to streamflow and water-quality data from five streamflow-gaging stations, and in general, these stations characterize a range of subwatershed areas with varying land-use types. The CE–QUAL–W2 reservoir model was calibrated to water-quality data collected during January 2004 through December 2010 at three reservoir stations, representing the upper, middle, and lower sections of the reservoir.\n\nIn general, the baseline simulation for the Hydrologic Simulation Program–FORTRAN and the CE–QUAL–W2 models matched reasonably well to the measured data. Simulated and measured suspended-sediment concentrations during periods of base flow (streamflows not substantially influenced by runoff) agree reasonably well for Maumelle River at Williams Junction, the station representing the upper end of the watershed (with differences—simulated minus measured value—generally ranging from -15 to 41 milligrams per liter, and percent difference—relative to the measured value—ranging from -99 to 182 percent) and Maumelle River near Wye, the station just above the reservoir at the lower end (differences generally ranging from -20 to 22 milligrams per liter, and percent difference ranging from -100 to 194 percent). In general, water temperature and dissolved-oxygen concentration simulations followed measured seasonal trends for all stations with the largest differences occurring during periods of lowest temperatures or during the periods of lowest measured dissolved-oxygen concentrations.\n\nFor the CE–QUAL–W2 model, simulated vertical distributions of water temperatures and dissolved-oxygen concentrations agreed with measured vertical distributions over time, even for the most complex water-temperature profiles. Considering the oligotrophic-mesotrophic (low to intermediate primary productivity and associated low nutrient concentrations) condition of Lake Maumelle, simulated algae, phosphorus, and nitrogen concentrations compared well with generally low measured concentrations.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125246","collaboration":"Prepared in cooperation with Central Arkansas Water","usgsCitation":"Hart, R.M., Green, W.R., Westerman, D.A., Petersen, J., and DeLanois, J.L., 2012, Simulated effects of hydrologic, water quality, and land-use changes of the Lake Maumelle watershed, Arkansas, 2004–10: U.S. Geological Survey Scientific Investigations Report 2012-5246, ix, 119 p.; col. ill.; maps (col.), https://doi.org/10.3133/sir20125246.","productDescription":"ix, 119 p.; col. ill.; maps (col.)","startPage":"i","endPage":"119","numberOfPages":"132","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2004-01-01","temporalEnd":"2010-12-31","costCenters":[{"id":129,"text":"Arkansas Water Science Center","active":true,"usgs":true}],"links":[{"id":263666,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5246.gif"},{"id":263664,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5246/"},{"id":263665,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5246/sir2012-5246.pdf"}],"country":"United States","state":"Arkansas","otherGeospatial":"Lake Maumelle","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -94.62,33.0 ], [ -94.62,36.5 ], [ -89.65,36.5 ], [ -89.65,33.0 ], [ -94.62,33.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50bfba04e4b01744973f77ae","contributors":{"authors":[{"text":"Hart, Rheannon M. 0000-0003-4657-5945 rmhart@usgs.gov","orcid":"https://orcid.org/0000-0003-4657-5945","contributorId":5516,"corporation":false,"usgs":true,"family":"Hart","given":"Rheannon","email":"rmhart@usgs.gov","middleInitial":"M.","affiliations":[{"id":129,"text":"Arkansas Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":469612,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Green, W. Reed","contributorId":87886,"corporation":false,"usgs":true,"family":"Green","given":"W.","email":"","middleInitial":"Reed","affiliations":[],"preferred":false,"id":469614,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Westerman, Drew A. 0000-0002-8522-776X dawester@usgs.gov","orcid":"https://orcid.org/0000-0002-8522-776X","contributorId":4526,"corporation":false,"usgs":true,"family":"Westerman","given":"Drew","email":"dawester@usgs.gov","middleInitial":"A.","affiliations":[{"id":129,"text":"Arkansas Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":469611,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Petersen, James C. petersen@usgs.gov","contributorId":2437,"corporation":false,"usgs":true,"family":"Petersen","given":"James C.","email":"petersen@usgs.gov","affiliations":[{"id":129,"text":"Arkansas Water Science Center","active":true,"usgs":true}],"preferred":false,"id":469610,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"DeLanois, Jeanne L.","contributorId":58531,"corporation":false,"usgs":true,"family":"DeLanois","given":"Jeanne","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":469613,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70041363,"text":"70041363 - 2012 - Hydrate morphology: Physical properties of sands with patchy hydrate saturation","interactions":[],"lastModifiedDate":"2013-03-14T11:05:33","indexId":"70041363","displayToPublicDate":"2012-12-04T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2314,"text":"Journal of Geophysical Research B: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Hydrate morphology: Physical properties of sands with patchy hydrate saturation","docAbstract":"The physical properties of gas hydrate-bearing sediments depend on the volume fraction and spatial distribution of the hydrate phase. The host sediment grain size and the state of effective stress determine the hydrate morphology in sediments; this information can be used to significantly constrain estimates of the physical properties of hydrate-bearing sediments, including the coarse-grained sands subjected to high effective stress that are of interest as potential energy resources. Reported data and physical analyses suggest hydrate-bearing sands contain a heterogeneous, patchy hydrate distribution, whereby zones with 100% pore-space hydrate saturation are embedded in hydrate-free sand. Accounting for patchy rather than homogeneous hydrate distribution yields more tightly constrained estimates of physical properties in hydrate-bearing sands and captures observed physical-property dependencies on hydrate saturation. For example, numerical modeling results of sands with patchy saturation agree with experimental observation, showing a transition in stiffness starting near the series bound at low hydrate saturations but moving toward the parallel bound at high hydrate saturations. The hydrate-patch size itself impacts the physical properties of hydrate-bearing sediments; for example, at constant hydrate saturation, we find that conductivity (electrical, hydraulic and thermal) increases as the number of hydrate-saturated patches increases. This increase reflects the larger number of conductive flow paths that exist in specimens with many small hydrate-saturated patches in comparison to specimens in which a few large hydrate saturated patches can block flow over a significant cross-section of the specimen.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Geophysical Research B: Solid Earth","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Geophysical Union","publisherLocation":"Washington, D.C.","doi":"10.1029/2012JB009667","usgsCitation":"Dai, S., Santamarina, J., Waite, W., and Kneafsey, T., 2012, Hydrate morphology: Physical properties of sands with patchy hydrate saturation: Journal of Geophysical Research B: Solid Earth, v. 117, no. B11, https://doi.org/10.1029/2012JB009667.","productDescription":"12 p.","startPage":"B11205","numberOfPages":"12","ipdsId":"IP-038897","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":474224,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hdl.handle.net/1912/5635","text":"External Repository"},{"id":263661,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":263659,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1029/2012JB009667"}],"volume":"117","issue":"B11","noUsgsAuthors":false,"publicationDate":"2012-11-14","publicationStatus":"PW","scienceBaseUri":"50bfb97ee4b01744973f77a2","contributors":{"authors":[{"text":"Dai, S.","contributorId":9757,"corporation":false,"usgs":true,"family":"Dai","given":"S.","email":"","affiliations":[],"preferred":false,"id":469623,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Santamarina, J.C.","contributorId":50283,"corporation":false,"usgs":true,"family":"Santamarina","given":"J.C.","email":"","affiliations":[],"preferred":false,"id":469625,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Waite, William F. 0000-0002-9436-4109 wwaite@usgs.gov","orcid":"https://orcid.org/0000-0002-9436-4109","contributorId":625,"corporation":false,"usgs":true,"family":"Waite","given":"William F.","email":"wwaite@usgs.gov","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":469622,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kneafsey, T.J.","contributorId":40330,"corporation":false,"usgs":true,"family":"Kneafsey","given":"T.J.","email":"","affiliations":[],"preferred":false,"id":469624,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70041306,"text":"ds733 - 2012 - Seasonal variability in the surface sediments of Mobile Bay, Alabama, recorded by geochemistry and foraminifera, 2009–2010","interactions":[],"lastModifiedDate":"2012-12-03T08:22:14","indexId":"ds733","displayToPublicDate":"2012-12-03T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"733","title":"Seasonal variability in the surface sediments of Mobile Bay, Alabama, recorded by geochemistry and foraminifera, 2009–2010","docAbstract":"A study was undertaken in order to document and quantify recent environmental change in Mobile Bay, Alabama. The study was part of the Northern Gulf of Mexico (NGOM) Ecosystem Change and Hazard Susceptibility project, a regional project funded by the Coastal and Marine Geology Program to understand how natural forcings and anthropogenic modifications influence coastal ecosystems and their susceptibility to coastal hazards. Mobile Bay is a large drowned-river estuary that has been modified significantly by humans to accommodate the Port of Mobile. Examples include repeated dredging of a large shipping channel down the central axis of the bay and construction of a causeway across the head of the bay and at the foot of the bayhead delta. In addition to modifications, the bay is also known to have episodic periods of low oxygen (hypoxia) that result in significant mortality to fish and benthic organisms (May, 1973). For this study a series of surface sediment samples were collected. Surface benthic foraminiferal and bulk geochemical data provide the modern baseline conditions of the bay and can be used as a reference to changing environmental parameters in the past (Osterman and Smith, in press) and into the future. This report archives data collected as part of the Mobile Bay Study that may be used in future environmental change studies.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds733","usgsCitation":"Umberger, D., Osterman, L., Smith, C., Frazier, J., and Richwine, K., 2012, Seasonal variability in the surface sediments of Mobile Bay, Alabama, recorded by geochemistry and foraminifera, 2009–2010: U.S. Geological Survey Data Series 733, iii, 25 p., https://doi.org/10.3133/ds733.","productDescription":"iii, 25 p.","numberOfPages":"28","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":263591,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds_733.jpg"},{"id":263589,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/733/"},{"id":263590,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/733/pdf/ds733.pdf"}],"country":"United States","state":"Alabama","otherGeospatial":"Mobile Bay","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -88.166667,30.166667 ], [ -88.166667,30.666667 ], [ -87.666667,30.666667 ], [ -87.666667,30.166667 ], [ -88.166667,30.166667 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50bd12eee4b069d93eefc4b6","contributors":{"authors":[{"text":"Umberger, D.K.","contributorId":13356,"corporation":false,"usgs":true,"family":"Umberger","given":"D.K.","email":"","affiliations":[],"preferred":false,"id":469504,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Osterman, L.E.","contributorId":53836,"corporation":false,"usgs":true,"family":"Osterman","given":"L.E.","email":"","affiliations":[],"preferred":false,"id":469506,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, C.G.","contributorId":105947,"corporation":false,"usgs":true,"family":"Smith","given":"C.G.","email":"","affiliations":[],"preferred":false,"id":469508,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Frazier, J.","contributorId":88439,"corporation":false,"usgs":true,"family":"Frazier","given":"J.","email":"","affiliations":[],"preferred":false,"id":469507,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Richwine, K.A.","contributorId":15906,"corporation":false,"usgs":true,"family":"Richwine","given":"K.A.","affiliations":[],"preferred":false,"id":469505,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70042214,"text":"70042214 - 2012 - 3-D reconstructions of subsurface Pleistocene basalt flows from paleomagnetic inclination data and <sup>40</sup>Ar/<sup>39</sup>Ar ages in the southern part of the Idaho National Laboratory (INL), Idaho (USA)","interactions":[],"lastModifiedDate":"2020-09-03T15:17:24.593109","indexId":"70042214","displayToPublicDate":"2012-12-01T14:45:00","publicationYear":"2012","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"3-D reconstructions of subsurface Pleistocene basalt flows from paleomagnetic inclination data and <sup>40</sup>Ar/<sup>39</sup>Ar ages in the southern part of the Idaho National Laboratory (INL), Idaho (USA)","docAbstract":"<p>The U. S. Geological Survey, in cooperation with the U.S. Department of Energy, is mapping the distribution of basalt flows and sedimentary interbeds at the Idaho National Laboratory in three dimensions to provide data for refining numerical models of groundwater flow and contaminant transport in the eastern Snake River Plain aquifer. Paleomagnetic inclination and polarity data from basalt samples from 47 coreholes are being used to create a three-dimensional (3-D) model of the subsurface of the southern part of the INL. Surface and sub-surface basalt flows can be identified in individual cores and traced in three dimensions on the surface and in the subsurface for distances of more than 20 km using a combination of paleomagnetic, stratigraphic, and <sup>40</sup>Ar/<sup>39</sup>Ar data. Eastern Snake River Plain olivine tholeiite basalts have K<sub>2</sub>O contents of 0.2 to 1.0 weight per cent. In spite of the low-K content, high-precision <sup>40</sup>Ar/<sup>39</sup>Ar ages were obtained by applying a protocol that employs short irradiation times (minimizing interferences from Ca derived <sup>36</sup>Ar), frequent measurement of various size atmospheric Ar pipettes to monitor and correct for temporal variation, and signal size dependent nonlinearity in spectrometer mass bias, resulting in age dates with resolution generally between 2 to 10% of the age. 3-D models of subsurface basalt flows are being used to: (1) Estimate eruption volumes; (2) locate the approximate vent areas and extent of sub-surface flows; and (3) Help locate high and low transmissivity zones. Results indicate that large basalt eruptions (&gt;3 km<sup>3</sup>) occurred at and near the Central Facilities Area between 637 ka and 360 ka; at and near the Radioactive Waste Management Complex before 540 ka; and north of the Naval Reactors Facility at about 580 ka. Since about 360 ka, large basalt flows have erupted along the Arco-Big Southern Butte Volcanic Rift Zone and the Axial Volcanic Zone, and flowed northerly towards the Central Facilities Area. Basalt eruptions shifted the course of the Big Lost River from a more southerly course to its present one.</p>","conferenceTitle":"American Geophysical Union, Fall Meeting","language":"English","publisher":"American Geophysical Union","usgsCitation":"Hodges, M., Champion, D.E., Turrin, B.D., and Swisher, C.C., 2012, 3-D reconstructions of subsurface Pleistocene basalt flows from paleomagnetic inclination data and <sup>40</sup>Ar/<sup>39</sup>Ar ages in the southern part of the Idaho National Laboratory (INL), Idaho (USA), American Geophysical Union, Fall Meeting, HTML Document.","productDescription":"HTML Document","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-042382","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":310830,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":310829,"rank":1,"type":{"id":1,"text":"Abstract"},"url":"https://abstractsearch.agu.org/meetings/2012/FM/V13B-2841.html","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Idaho","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -112.0835494995117,\n              43.48892214178582\n            ],\n            [\n              -111.99789047241211,\n              43.48892214178582\n            ],\n            [\n              -111.99789047241211,\n              43.539215993938164\n            ],\n            [\n              -112.0835494995117,\n              43.539215993938164\n            ],\n            [\n              -112.0835494995117,\n              43.48892214178582\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"563494aee4b048076347fb85","contributors":{"authors":[{"text":"Hodges, Mary K. 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,{"id":70103847,"text":"70103847 - 2012 - Priorities for IOOS<sup>®</sup> Data Management and Communications (DMAC)","interactions":[],"lastModifiedDate":"2014-05-28T13:53:18","indexId":"70103847","displayToPublicDate":"2012-12-01T13:29:00","publicationYear":"2012","noYear":false,"publicationType":{"id":4,"text":"Book"},"publicationSubtype":{"id":12,"text":"Conference publication"},"title":"Priorities for IOOS<sup>®</sup> Data Management and Communications (DMAC)","docAbstract":"Dramatic increases in the volume of online data and rapid advances in information technology have transformed many aspects of our society. In the coastal ocean, the amount of data is also growing dramatically due to new sensor and modeling technologies. Lagging behind this deluge of ocean data, however, is an effective framework of standards, protocols, tools and culture needed to transform the way we generate knowledge and value from ocean data. The Data Management and Communications (DMAC) sub-system was envisioned to provide such an information management capability for IOOS®, promoting standards and policies to be implemented by data providers across the IOOS enterprise. DMAC needs to build upon the successes and lessons learned during development of web service standards and promote a set of end-to-end standards and procedures for the entire ocean-data life cycle, including documentation through metadata, quality control and quality assurance, effective data discovery, and stewardship through archiving. Because information technology is constantly changing, a multiyear, top-down design and implementation plan is not workable. DMAC should start by promoting a set of protocols that are functional for specific use cases, creating a modular framework in which modules can be replaced as technologies change. In addition to promoting protocols, DMAC needs to support training, flexible online documentation, support, and social networking that enable users to share code, techniques and experiences. Through this bottom-up approach, trust and understanding will foster adoption by the community. Finally, a compliance and certification process should be developed that allows IOOS to ensure that they meet the needs of customers and other stakeholders while complying with regulatory requirements related to the data. If this approach is followed, we will enable breakthroughs in ocean data–driven technology similar to those common elsewhere in our society, fulfilling the broader mission of IOOS.","conferenceTitle":"U.S. Integrated Ocean Observing System (IOOS) Summit","conferenceDate":"2012-11-13T00:00:00","conferenceLocation":"Herdon, VA","language":"English","publisher":"Interagency Ocean Observation Committee","usgsCitation":"Alexander, C., Thomas, J., Benedict, K., Johnson, W., Morrison, R., Andrechik, J., Stabenau, E., Gierach, M., Casey, K., Signell, R.P., Norris, H., Proctor, R., Kirby, K., Snowden, D., de La Beaujardière, J., Howlett, E., Uczekaj, S., Narasimhan, K., Key, E., Trice, M., and Fredericks, J., 2012, Priorities for IOOS<sup>®</sup> Data Management and Communications (DMAC), 5 p.","productDescription":"5 p.","numberOfPages":"5","ipdsId":"IP-042941","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science 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