{"pageNumber":"610","pageRowStart":"15225","pageSize":"25","recordCount":40828,"records":[{"id":70094151,"text":"sir20145028 - 2014 - Surface-water and karst groundwater interactions and streamflow-response simulations of the karst-influenced upper Lost River watershed, Orange County, Indiana","interactions":[],"lastModifiedDate":"2014-04-07T09:53:30","indexId":"sir20145028","displayToPublicDate":"2014-03-18T14:43:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-5028","title":"Surface-water and karst groundwater interactions and streamflow-response simulations of the karst-influenced upper Lost River watershed, Orange County, Indiana","docAbstract":"The U.S. Geological Survey (USGS), in cooperation with the U.S. Army Corps of Engineers (USACE) and the Indiana Office of Community and Rural Affairs (OCRA), conducted a study of the upper Lost River watershed in Orange County, Indiana, from 2012 to 2013. Streamflow and groundwater data were collected at 10 data-collection sites from at least October 2012 until April 2013, and a preliminary Water Availability Tool for Environmental Resources (WATER)-TOPMODEL based hydrologic model was created to increase understanding of the complex, karstic hydraulic and hydrologic system present in the upper Lost River watershed, Orange County, Ind. Statistical assessment of the optimized hydrologic-model results were promising and returned correlation coefficients for simulated and measured stream discharge of 0.58 and 0.60 and Nash-Sutcliffe efficiency values of 0.56 and 0.39 for USGS streamflow-gaging stations 03373530 (Lost River near Leipsic, Ind.), and 03373560 (Lost River near Prospect, Ind.), respectively. Additional information to refine drainage divides is needed before applying the model to the entire karst region of south-central Indiana. Surface-water and groundwater data were used to tentatively quantify the complex hydrologic processes taking place within the watershed and provide increased understanding for future modeling and management applications. The data indicate that during wet-weather periods and after certain intense storms, the hydraulic capacity of swallow holes and subsurface conduits is overwhelmed with excess water that flows onto the surface in dry-bed relic stream channels and karst paleovalleys. Analysis of discharge data collected at USGS streamflow-gaging station 03373550 (Orangeville Rise, at Orangeville, Ind.), and other ancillary data-collection sites in the watershed, indicate that a bounding condition is likely present, and drainage from the underlying karst conduit system is potentially limited to near 200 cubic feet per second. This information will direct future studies and assist managers in understanding when the subsurface conduits may become overwhelmed.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145028","issn":"2328-0328","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers and the Indiana Office of Community and Rural Affairs (OCRA)","usgsCitation":"Bayless, E.R., Cinotto, P.J., Ulery, R.L., Taylor, C.J., McCombs, G.K., Kim, M.H., and Nelson, H.L., 2014, Surface-water and karst groundwater interactions and streamflow-response simulations of the karst-influenced upper Lost River watershed, Orange County, Indiana (Originally posted March 18, 2014; Revised April 7, 2014): U.S. Geological Survey Scientific Investigations Report 2014-5028, viii, 39 p., https://doi.org/10.3133/sir20145028.","productDescription":"viii, 39 p.","numberOfPages":"52","onlineOnly":"Y","ipdsId":"IP-040755","costCenters":[{"id":354,"text":"Kentucky Water Science Center","active":true,"usgs":true}],"links":[{"id":284186,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145028.jpg"},{"id":284185,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5028/pdf/sir2014-5028.pdf"},{"id":284184,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5028/"}],"scale":"100000","country":"United States","state":"Indiana","county":"Orange County","otherGeospatial":"Upper Lost River Watershed","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -86.66,38.416 ], [ -86.66,38.766 ], [ -86.166,38.766 ], [ -86.166,38.416 ], [ -86.66,38.416 ] ] ] } } ] }","edition":"Originally posted March 18, 2014; Revised April 7, 2014","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53517065e4b05569d805a3d3","contributors":{"authors":[{"text":"Bayless, E. Randall 0000-0002-0357-3635","orcid":"https://orcid.org/0000-0002-0357-3635","contributorId":42586,"corporation":false,"usgs":true,"family":"Bayless","given":"E.","email":"","middleInitial":"Randall","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":490455,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cinotto, Peter J. pcinotto@usgs.gov","contributorId":451,"corporation":false,"usgs":true,"family":"Cinotto","given":"Peter","email":"pcinotto@usgs.gov","middleInitial":"J.","affiliations":[{"id":354,"text":"Kentucky Water Science Center","active":true,"usgs":true}],"preferred":true,"id":490450,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ulery, Randy L. rlulery@usgs.gov","contributorId":4679,"corporation":false,"usgs":true,"family":"Ulery","given":"Randy","email":"rlulery@usgs.gov","middleInitial":"L.","affiliations":[],"preferred":true,"id":490453,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Taylor, Charles J.","contributorId":93100,"corporation":false,"usgs":true,"family":"Taylor","given":"Charles","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":490456,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McCombs, Gregory K. gmccombs@usgs.gov","contributorId":5429,"corporation":false,"usgs":true,"family":"McCombs","given":"Gregory","email":"gmccombs@usgs.gov","middleInitial":"K.","affiliations":[],"preferred":true,"id":490454,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kim, Moon H. 0000-0002-4328-8409 mkim@usgs.gov","orcid":"https://orcid.org/0000-0002-4328-8409","contributorId":3211,"corporation":false,"usgs":true,"family":"Kim","given":"Moon","email":"mkim@usgs.gov","middleInitial":"H.","affiliations":[{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true}],"preferred":true,"id":490451,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Nelson, Hugh L. hlnelson@usgs.gov","contributorId":4158,"corporation":false,"usgs":true,"family":"Nelson","given":"Hugh","email":"hlnelson@usgs.gov","middleInitial":"L.","affiliations":[{"id":354,"text":"Kentucky Water Science Center","active":true,"usgs":true}],"preferred":true,"id":490452,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70098176,"text":"70098176 - 2014 - Ocean-atmosphere forcing of centennial hydroclimatic variability in the Pacific Northwest","interactions":[],"lastModifiedDate":"2014-05-02T17:03:59","indexId":"70098176","displayToPublicDate":"2014-03-17T15:52:00","publicationYear":"2014","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":"Ocean-atmosphere forcing of centennial hydroclimatic variability in the Pacific Northwest","docAbstract":"Reconstructing centennial timescale hydroclimate variability during the late Holocene is critically important for understanding large-scale patterns of drought and their relationship with climate dynamics. We present sediment oxygen isotope records spanning the last two millennia from 10 lakes, as well as climate model simulations, indicating that the Little Ice Age was dry relative to the Medieval Climate Anomaly in much of the Pacific Northwest of North America. This pattern is consistent with observed associations between the El Niño Southern Oscillation (ENSO), the Northern Annular Mode and drought as well as with proxy-based reconstructions of Pacific ocean-atmosphere variations over the past 1000 years. The large amplitude of centennial variability indicated by the lake data suggests that regional hydroclimate is characterized by longer-term shifts in ENSO-like dynamics, and that an improved understanding of the centennial timescale relationship between external forcing and drought conditions is necessary for projecting future hydroclimatic conditions in western North America.","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":"10.1002/2014GL059499","usgsCitation":"Steinman, B.A., Abbott, M.B., Mann, M.E., Ortiz, J., Feng, S., Pompeani, D.P., Stansell, N.D., Anderson, L., Finney, B., and Bird, B., 2014, Ocean-atmosphere forcing of centennial hydroclimatic variability in the Pacific Northwest: Geophysical Research Letters, v. 41, no. 7, p. 2553-2560, https://doi.org/10.1002/2014GL059499.","productDescription":"8 p.","startPage":"2553","endPage":"2560","numberOfPages":"8","ipdsId":"IP-051490","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":473103,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2014gl059499","text":"Publisher Index Page"},{"id":284102,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":284098,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/2014GL059499"}],"country":"Canada;United States","otherGeospatial":"Pacific Northwest","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -140.89,29.99 ], [ -140.89,64.96 ], [ -89.82,64.96 ], [ -89.82,29.99 ], [ -140.89,29.99 ] ] ] } } ] }","volume":"41","issue":"7","noUsgsAuthors":false,"publicationDate":"2014-04-14","publicationStatus":"PW","scienceBaseUri":"53517059e4b05569d805a354","contributors":{"authors":[{"text":"Steinman, Byron A.","contributorId":87064,"corporation":false,"usgs":true,"family":"Steinman","given":"Byron","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":491663,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Abbott, Mark B.","contributorId":97733,"corporation":false,"usgs":true,"family":"Abbott","given":"Mark","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":491665,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mann, Michael E.","contributorId":71876,"corporation":false,"usgs":true,"family":"Mann","given":"Michael","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":491662,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ortiz, Joseph D.","contributorId":103175,"corporation":false,"usgs":true,"family":"Ortiz","given":"Joseph D.","affiliations":[],"preferred":false,"id":491667,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Feng, Song","contributorId":101978,"corporation":false,"usgs":true,"family":"Feng","given":"Song","email":"","affiliations":[],"preferred":false,"id":491666,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pompeani, David P.","contributorId":42130,"corporation":false,"usgs":true,"family":"Pompeani","given":"David","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":491661,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Stansell, Nathan D.","contributorId":11936,"corporation":false,"usgs":true,"family":"Stansell","given":"Nathan","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":491659,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Anderson, Lesleigh 0000-0002-5264-089X land@usgs.gov","orcid":"https://orcid.org/0000-0002-5264-089X","contributorId":436,"corporation":false,"usgs":true,"family":"Anderson","given":"Lesleigh","email":"land@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":491658,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Finney, Bruce P.","contributorId":88074,"corporation":false,"usgs":true,"family":"Finney","given":"Bruce P.","affiliations":[],"preferred":false,"id":491664,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Bird, Broxton W.","contributorId":26219,"corporation":false,"usgs":true,"family":"Bird","given":"Broxton W.","affiliations":[],"preferred":false,"id":491660,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70098133,"text":"70098133 - 2014 - Accounting for unsearched areas in estimating wind turbine-caused fatality","interactions":[],"lastModifiedDate":"2014-03-18T08:18:39","indexId":"70098133","displayToPublicDate":"2014-03-17T15:49:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Accounting for unsearched areas in estimating wind turbine-caused fatality","docAbstract":"With wind energy production expanding rapidly, concerns about turbine-induced bird and bat fatality have grown and the demand for accurate estimation of fatality is increasing. Estimation typically involves counting carcasses observed below turbines and adjusting counts by estimated detection probabilities. Three primary sources of imperfect detection are 1) carcasses fall into unsearched areas, 2) carcasses are removed or destroyed before sampling, and 3) carcasses present in the searched area are missed by observers. Search plots large enough to comprise 100% of turbine-induced fatality are expensive to search and may nonetheless contain areas unsearchable because of dangerous terrain or impenetrable brush. We evaluated models relating carcass density to distance from the turbine to estimate the proportion of carcasses expected to fall in searched areas and evaluated the statistical cost of restricting searches to areas near turbines where carcass density is highest and search conditions optimal. We compared 5 estimators differing in assumptions about the relationship of carcass density to distance from the turbine. We tested them on 6 different carcass dispersion scenarios at each of 3 sites under 2 different search regimes. We found that even simple distance-based carcass-density models were more effective at reducing bias than was a 5-fold expansion of the search area. Estimators incorporating fitted rather than assumed models were least biased, even under restricted searches. Accurate estimates of fatality at wind-power facilities will allow critical comparisons of rates among turbines, sites, and regions and contribute to our understanding of the potential environmental impact of this technology.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Wildlife Management","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"The Wildlife Society","doi":"10.1002/jwmg.663","usgsCitation":"Huso, M., and Dalthorp, D., 2014, Accounting for unsearched areas in estimating wind turbine-caused fatality: Journal of Wildlife Management, v. 78, no. 2, p. 347-358, https://doi.org/10.1002/jwmg.663.","productDescription":"12 p.","startPage":"347","endPage":"358","numberOfPages":"12","ipdsId":"IP-051624","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":284104,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":284083,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/jwmg.663"}],"volume":"78","issue":"2","noUsgsAuthors":false,"publicationDate":"2014-02-18","publicationStatus":"PW","scienceBaseUri":"53516f28e4b05569d805a01e","contributors":{"authors":[{"text":"Huso, Manuela M.P.","contributorId":80566,"corporation":false,"usgs":true,"family":"Huso","given":"Manuela M.P.","affiliations":[],"preferred":false,"id":491566,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dalthorp, Dan","contributorId":51197,"corporation":false,"usgs":true,"family":"Dalthorp","given":"Dan","email":"","affiliations":[],"preferred":false,"id":491565,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70098139,"text":"70098139 - 2014 - Modeling marbled murrelet (Brachyramphus marmoratus) habitat using LiDAR-derived canopy data","interactions":[],"lastModifiedDate":"2021-04-22T19:41:45.20453","indexId":"70098139","displayToPublicDate":"2014-03-17T15:06:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3779,"text":"Wildlife Society Bulletin","onlineIssn":"1938-5463","printIssn":"0091-7648","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Modeling marbled murrelet (<i>Brachyramphus marmoratus</i>) habitat using LiDAR-derived canopy data","title":"Modeling marbled murrelet (Brachyramphus marmoratus) habitat using LiDAR-derived canopy data","docAbstract":"LiDAR (Light Detection And Ranging) is an emerging remote-sensing tool that can provide fine-scale data describing vertical complexity of vegetation relevant to species that are responsive to forest structure. We used LiDAR data to estimate occupancy probability for the federally threatened marbled murrelet (<i>Brachyramphus marmoratus</i>) in the Oregon Coast Range of the United States. Our goal was to address the need identified in the Recovery Plan for a more accurate estimate of the availability of nesting habitat by developing occupancy maps based on refined measures of nest-strand structure. We used murrelet occupancy data collected by the Bureau of Land Management Coos Bay District, and canopy metrics calculated from discrete return airborne LiDAR data, to fit a logistic regression model predicting the probability of occupancy. Our final model for stand-level occupancy included distance to coast, and 5 LiDAR-derived variables describing canopy structure. With an area under the curve value (AUC) of 0.74, this model had acceptable discrimination and fair agreement (Cohen's κ = 0.24), especially considering that all sites in our sample were regarded by managers as potential habitat. The LiDAR model provided better discrimination between occupied and unoccupied sites than did a model using variables derived from Gradient Nearest Neighbor maps that were previously reported as important predictors of murrelet occupancy (AUC = 0.64, κ = 0.12). We also evaluated LiDAR metrics at 11 known murrelet nest sites. Two LiDAR-derived variables accurately discriminated nest sites from random sites (average AUC = 0.91). LiDAR provided a means of quantifying 3-dimensional canopy structure with variables that are ecologically relevant to murrelet nesting habitat, and have not been as accurately quantified by other mensuration methods.","language":"English","publisher":"Wildlife Society","doi":"10.1002/wsb.407","usgsCitation":"Hagar, J.C., Eskelson, B., Haggerty, P., Nelson, S.K., and Vesely, D.G., 2014, Modeling marbled murrelet (Brachyramphus marmoratus) habitat using LiDAR-derived canopy data: Wildlife Society Bulletin, v. 38, no. 2, p. 237-249, https://doi.org/10.1002/wsb.407.","productDescription":"13 p.","startPage":"237","endPage":"249","numberOfPages":"13","ipdsId":"IP-050749","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":499898,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doaj.org/article/fa328953e7c44ef8b47dae994fe72d41","text":"External Repository"},{"id":438769,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ONYT0B","text":"USGS data release","linkHelpText":"Forest stands and LiDAR derived model estimates of marbled murrelet (Brachyramphus marmoratus) occupancy in the Coos Bay BLM District, Southwestern Oregon"},{"id":438768,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9472SZW","text":"USGS data release","linkHelpText":"Estimated Probabilities from Lidar Models for Marbled Murrelet (Brachyramphus marmoratus) Occupancy in Forest Vegetation Stands in the Siuslaw National Forest, Oregon"},{"id":284094,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Oregon Coast Range","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -125.2222,41.7795 ], [ -125.2222,44.0718 ], [ -123.0908,44.0718 ], [ -123.0908,41.7795 ], [ -125.2222,41.7795 ] ] ] } } ] }","volume":"38","issue":"2","noUsgsAuthors":false,"publicationDate":"2014-02-12","publicationStatus":"PW","scienceBaseUri":"53517055e4b05569d805a333","contributors":{"authors":[{"text":"Hagar, Joan C. 0000-0002-3044-6607 joan_hagar@usgs.gov","orcid":"https://orcid.org/0000-0002-3044-6607","contributorId":57034,"corporation":false,"usgs":true,"family":"Hagar","given":"Joan","email":"joan_hagar@usgs.gov","middleInitial":"C.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":false,"id":491631,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Eskelson, Bianca","contributorId":7556,"corporation":false,"usgs":true,"family":"Eskelson","given":"Bianca","email":"","affiliations":[],"preferred":false,"id":491628,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haggerty, Patricia K.","contributorId":50815,"corporation":false,"usgs":true,"family":"Haggerty","given":"Patricia K.","affiliations":[],"preferred":false,"id":491630,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nelson, S. Kim","contributorId":86680,"corporation":false,"usgs":false,"family":"Nelson","given":"S.","email":"","middleInitial":"Kim","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":491632,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vesely, David G.","contributorId":41328,"corporation":false,"usgs":true,"family":"Vesely","given":"David","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":491629,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70055555,"text":"tm4A9 - 2014 - HydroClimATe: hydrologic and climatic analysis toolkit","interactions":[],"lastModifiedDate":"2018-04-02T15:21:11","indexId":"tm4A9","displayToPublicDate":"2014-03-17T14:53:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"4-A9","title":"HydroClimATe: hydrologic and climatic analysis toolkit","docAbstract":"The potential consequences of climate variability and climate change have been identified as major issues for the sustainability and availability of the worldwide water resources. Unlike global climate change, climate variability represents deviations from the long-term state of the climate over periods of a few years to several decades. Currently, rich hydrologic time-series data are available, but the combination of data preparation and statistical methods developed by the U.S. Geological Survey as part of the Groundwater Resources Program is relatively unavailable to hydrologists and engineers who could benefit from estimates of climate variability and its effects on periodic recharge and water-resource availability. This report documents HydroClimATe, a computer program for assessing the relations between variable climatic and hydrologic time-series data. HydroClimATe was developed for a Windows operating system. The software includes statistical tools for (1) time-series preprocessing, (2) spectral analysis, (3) spatial and temporal analysis, (4) correlation analysis, and (5) projections. The time-series preprocessing tools include spline fitting, standardization using a normal or gamma distribution, and transformation by a cumulative departure. The spectral analysis tools include discrete Fourier transform, maximum entropy method, and singular spectrum analysis. The spatial and temporal analysis tool is empirical orthogonal function analysis. The correlation analysis tools are linear regression and lag correlation. The projection tools include autoregressive time-series modeling and generation of many realizations. These tools are demonstrated in four examples that use stream-flow discharge data, groundwater-level records, gridded time series of precipitation data, and the Multivariate ENSO Index.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Section A: Statistical analysis in Book 4 <i>Hydrologic Analysis and Interpretation</i>","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm4A9","collaboration":"Groundwater Resources Program. This report is Chapter 9 of Section A: Statistical analysis in Book 4 <i>Hydrologic Analysis and Interpretation</i>.","usgsCitation":"Dickinson, J.E., Hanson, R.T., and Predmore, S.K., 2014, HydroClimATe: hydrologic and climatic analysis toolkit: U.S. Geological Survey Techniques and Methods 4-A9, x, 48 p., https://doi.org/10.3133/tm4A9.","productDescription":"x, 48 p.","numberOfPages":"62","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-035956","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":284093,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/tm4A9.jpg"},{"id":284091,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/tm/tm4a9/"},{"id":284092,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/tm4a9/pdf/tm4-a9.pdf"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd60efe4b0b290850fd3b7","contributors":{"authors":[{"text":"Dickinson, Jesse E. 0000-0002-0048-0839 jdickins@usgs.gov","orcid":"https://orcid.org/0000-0002-0048-0839","contributorId":152545,"corporation":false,"usgs":true,"family":"Dickinson","given":"Jesse","email":"jdickins@usgs.gov","middleInitial":"E.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":486143,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hanson, Randall T. 0000-0002-9819-7141 rthanson@usgs.gov","orcid":"https://orcid.org/0000-0002-9819-7141","contributorId":801,"corporation":false,"usgs":true,"family":"Hanson","given":"Randall","email":"rthanson@usgs.gov","middleInitial":"T.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":486142,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Predmore, Steven K. spredmor@usgs.gov","contributorId":1512,"corporation":false,"usgs":true,"family":"Predmore","given":"Steven","email":"spredmor@usgs.gov","middleInitial":"K.","affiliations":[],"preferred":true,"id":486144,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70058522,"text":"sir20135227 - 2014 - Simulation of groundwater flow in the \"1,500-foot\" sand and \"2,000-foot\" sand, with scenarios to mitigate saltwater migration in the \"2,000-foot\" sand of the Baton Rouge area, Louisiana","interactions":[],"lastModifiedDate":"2014-06-11T15:46:22","indexId":"sir20135227","displayToPublicDate":"2014-03-17T10:46:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-5227","title":"Simulation of groundwater flow in the \"1,500-foot\" sand and \"2,000-foot\" sand, with scenarios to mitigate saltwater migration in the \"2,000-foot\" sand of the Baton Rouge area, Louisiana","docAbstract":"<p>Groundwater withdrawals have caused saltwater to encroach into freshwater-bearing aquifers beneath Baton Rouge, Louisiana. Groundwater investigations in the 1960s identified a freshwater-saltwater interface located at the Baton Rouge Fault, across which abrupt changes in water levels occur. Aquifers south of the fault generally contain saltwater, and aquifers north of the fault contain freshwater, though limited saltwater encroachment has been detected within 7 of the 10 aquifers north of the fault. The 10 aquifers beneath the Baton Rouge area, which includes East and West Baton Rouge Parishes, Pointe Coupee Parish, and East and West Feliciana Parishes, provided about 167 million gallons per day (Mgal/d) for public supply and industrial use in 2010. Groundwater withdrawals from the “2,000-foot” sand in East Baton Rouge Parish have caused water-level drawdown as great as 356 feet (ft) and induced saltwater movement northward across the fault. Saltwater encroachment threatens industrial wells that are located about 3 miles north of the fault. Constant and variable-density groundwater models were developed with the MODFLOW and SEAWAT groundwater modeling codes to evaluate strategies to control saltwater migration, including changes in the distribution of groundwater withdrawals and installation of “scavenger” wells to intercept saltwater before it reaches existing production wells.</p>\n<br/>\n<p>Six hypothetical scenarios simulated the effects of different groundwater withdrawal options on groundwater levels within the “1,500-foot” sand and the “2,000-foot” sand and the transport of saltwater within the “2,000-foot” sand during 2008–47. Scenario 1 is considered a base case for comparison to the other five scenarios and simulates continuation of 2007 reported groundwater withdrawals. Scenario 2 simulates discontinuation of withdrawals from seven selected industrial wells located in the northwest corner of East Baton Rouge Parish and predicts that water levels within the “1,500-foot” sand will be about 10 to 12 ft higher with this withdrawal reduction than under scenario 1. Scenario 3 simulates the effects of a scavenger well on water levels and chloride concentrations within the “2,000-foot” sand. The scavenger well, which withdraws water from the base of the “2,000-foot” sand at a rate of 2.0 Mgal/d, is simulated at two possible locations. In comparison to the concentrations simulated in scenario 1, operation of the scavenger well at the locations specified in scenario 3 reduces the chloride concentrations at all existing chloride-observation well locations. Scenario 4 simulates a 3.6 Mgal/d reduction in total groundwater withdrawals from selected wells screened in the “2,000-foot” sand that are located in the Baton Rouge industrial district. Under scenario 4, chloride concentrations decrease in the leading portion of the plume south of the industrial district but increase in areas farther east. Scenario 5 simulates the effects of total cessation of withdrawals from the “2,000-foot” sand in the industrial district, which causes a change in the groundwater-flow direction toward municipal supply wells and increased chloride concentrations in the area where municipal supply wells are located. Scenario 6 simulates the combined effect of withdrawal reductions from the “2,000-foot” sand and operation of a scavenger well and was most effective at decreasing the size of the plume area and median and mean chloride concentrations within the “2000-foot” sand in the Baton Rouge area.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135227","issn":"2328-0328","collaboration":"Prepared in cooperation with the Capital Area Groundwater Conservation Commission; the Louisiana Department of Transportation and Development, Public Works and Water Resources Division; and the City of Baton Rouge and Parish of East Baton Rouge","usgsCitation":"Heywood, C.E., Griffith, J.M., and Lovelace, J.K., 2014, Simulation of groundwater flow in the \"1,500-foot\" sand and \"2,000-foot\" sand, with scenarios to mitigate saltwater migration in the \"2,000-foot\" sand of the Baton Rouge area, Louisiana (Version 1.0 March 17, 2014; Version 1.1 April 28, 2014; Version 1.2 June 11, 2014): U.S. Geological Survey Scientific Investigations Report 2013-5227, x, 63 p., https://doi.org/10.3133/sir20135227.","productDescription":"x, 63 p.","numberOfPages":"76","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-051040","costCenters":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"links":[{"id":284058,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135227.PNG"},{"id":284056,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5227/"},{"id":284057,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5227/pdf/sir2013-5227.pdf"}],"projection":"Universal Transverse Mercator","datum":"North American Datum of 1983","country":"United States","state":"Louisiana","county":"East Baton Rouge Parish;East Feliciana Parish;Pointe Coupee Parish;West Baton Rouge Parish;West Feliciana Parish","city":"Baton Rouge","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -92.0709,30.1641 ], [ -92.0709,31.4978 ], [ -90.2496,31.4978 ], [ -90.2496,30.1641 ], [ -92.0709,30.1641 ] ] ] } } ] }","edition":"Version 1.0 March 17, 2014; Version 1.1 April 28, 2014; Version 1.2 June 11, 2014","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53517062e4b05569d805a3ae","contributors":{"authors":[{"text":"Heywood, Charles E. cheywood@usgs.gov","contributorId":2043,"corporation":false,"usgs":true,"family":"Heywood","given":"Charles","email":"cheywood@usgs.gov","middleInitial":"E.","affiliations":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":487138,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Griffith, Jason M. 0000-0002-8942-0380 jmgriff@usgs.gov","orcid":"https://orcid.org/0000-0002-8942-0380","contributorId":2923,"corporation":false,"usgs":true,"family":"Griffith","given":"Jason","email":"jmgriff@usgs.gov","middleInitial":"M.","affiliations":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":487139,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lovelace, John K. 0000-0002-8532-2599 jlovelac@usgs.gov","orcid":"https://orcid.org/0000-0002-8532-2599","contributorId":999,"corporation":false,"usgs":true,"family":"Lovelace","given":"John","email":"jlovelac@usgs.gov","middleInitial":"K.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":487137,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70099966,"text":"70099966 - 2014 - ListingAnalyst: A program for analyzing the main output file from MODFLOW","interactions":[],"lastModifiedDate":"2014-03-28T08:59:09","indexId":"70099966","displayToPublicDate":"2014-03-17T08:56:03","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1861,"text":"Ground Water","active":true,"publicationSubtype":{"id":10}},"title":"ListingAnalyst: A program for analyzing the main output file from MODFLOW","docAbstract":"ListingAnalyst is a Windows® program for viewing the main output file from MODFLOW-2005, MODFLOW-NWT, or MODFLOW-LGR. It organizes and displays large files quickly without using excessive memory. The sections and subsections of the file are displayed in a tree-view control, which allows the user to navigate quickly to desired locations in the files. ListingAnalyst gathers error and warning messages scattered throughout the main output file and displays them all together in an error and a warning tab. A grid view displays tables in a readable format and allows the user to copy the table into a spreadsheet. The user can also search the file for terms of interest.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ground Water","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1111/gwat.12054","usgsCitation":"Winston, R.B., and Paulinski, S., 2014, ListingAnalyst: A program for analyzing the main output file from MODFLOW: Ground Water, v. 52, no. 2, p. 317-321, https://doi.org/10.1111/gwat.12054.","productDescription":"5 p.","startPage":"317","endPage":"321","ipdsId":"IP-043055","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":438770,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9O0IL7V","text":"USGS data release","linkHelpText":"ListingAnalyst version 1.2"},{"id":285085,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":285078,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/gwat.12054"}],"volume":"52","issue":"2","noUsgsAuthors":false,"publicationDate":"2013-04-12","publicationStatus":"PW","scienceBaseUri":"53517053e4b05569d805a30a","contributors":{"authors":[{"text":"Winston, Richard B. 0000-0002-6287-8834 rbwinst@usgs.gov","orcid":"https://orcid.org/0000-0002-6287-8834","contributorId":3567,"corporation":false,"usgs":true,"family":"Winston","given":"Richard","email":"rbwinst@usgs.gov","middleInitial":"B.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":492071,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Paulinski, Scott 0000-0001-6548-8164 spaulinski@usgs.gov","orcid":"https://orcid.org/0000-0001-6548-8164","contributorId":4269,"corporation":false,"usgs":true,"family":"Paulinski","given":"Scott","email":"spaulinski@usgs.gov","affiliations":[],"preferred":true,"id":492072,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70074413,"text":"70074413 - 2014 - Crustal migration of CO2-rich magmatic fluids recorded by tree-ring radiocarbon and seismicity at Mammoth Mountain, CA, USA","interactions":[],"lastModifiedDate":"2019-03-11T10:06:07","indexId":"70074413","displayToPublicDate":"2014-03-15T15:42:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1427,"text":"Earth and Planetary Science Letters","active":true,"publicationSubtype":{"id":10}},"title":"Crustal migration of CO2-rich magmatic fluids recorded by tree-ring radiocarbon and seismicity at Mammoth Mountain, CA, USA","docAbstract":"Unrest at Mammoth Mountain over the past several decades, manifest by seismicity, ground deformation, diffuse CO<sub>2</sub> emissions, and elevated <sup>3</sup>He/<sup>4</sup>He ratios in fumarolic gases has been driven by the release of CO<sub>2</sub>-rich fluids from basaltic intrusions in the middle to lower crust. Recent unrest included the occurrence of three lower-crustal (32–19 km depth) seismic swarms beneath Mammoth Mountain in 2006, 2008 and 2009 that were consistently followed by peaks in the occurrence rate of shallow (≤10 km depth) earthquakes. We measured <sup>14</sup>C in the growth rings (1998–2012) of a tree growing in the largest (∼0.3 km<sup>2</sup>) area of diffuse CO<sub>2</sub> emissions on Mammoth Mountain (the Horseshoe Lake tree kill; HLTK) and applied atmospheric CO<sub>2</sub> concentration source area modeling to confirm that the tree was a reliable integrator of magmatic CO<sub>2</sub> emissions over most of this area. The tree-ring <sup>14</sup>C record implied that magmatic CO<sub>2</sub> emissions from the HLTK were relatively stable from 1998 to 2009, nearly doubled from 2009 to 2011, and then declined by the 2012 growing season. The initial increase in CO<sub>2</sub> emissions was detected during the growing season that immediately followed the largest (February 2010) peak in the occurrence rate of shallow earthquakes. Migration of CO<sub>2</sub>-rich magmatic fluids may have driven observed patterns of elevated deep, then shallow seismicity, while the relationship between pore fluid pressures within a shallow (upper 3 km of crust) fluid reservoir and permeability structure of the reservoir cap rock may have controlled the temporal pattern of surface CO<sub>2</sub> emissions.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Earth and Planetary Science Letters","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.epsl.2013.12.035","usgsCitation":"Lewicki, J.L., Hilley, G.E., Shelly, D.R., King, J.C., McGeehin, J., Mangan, M.T., and Evans, W.C., 2014, Crustal migration of CO2-rich magmatic fluids recorded by tree-ring radiocarbon and seismicity at Mammoth Mountain, CA, USA: Earth and Planetary Science Letters, v. 390, p. 52-58, https://doi.org/10.1016/j.epsl.2013.12.035.","productDescription":"7 p.","startPage":"52","endPage":"58","numberOfPages":"7","ipdsId":"IP-050739","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"links":[{"id":281681,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Mammoth Mountain","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -119.1,37.58 ], [ -119.1,37.66 ], [ -119.0,37.66 ], [ -119.0,37.58 ], [ -119.1,37.58 ] ] ] } } ] }","volume":"390","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52ea22e5e4b0444d1ce67815","contributors":{"authors":[{"text":"Lewicki, Jennifer L. 0000-0003-1994-9104 jlewicki@usgs.gov","orcid":"https://orcid.org/0000-0003-1994-9104","contributorId":5071,"corporation":false,"usgs":true,"family":"Lewicki","given":"Jennifer","email":"jlewicki@usgs.gov","middleInitial":"L.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":489578,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hilley, George E.","contributorId":85484,"corporation":false,"usgs":true,"family":"Hilley","given":"George","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":489580,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shelly, David R. dshelly@usgs.gov","contributorId":2978,"corporation":false,"usgs":true,"family":"Shelly","given":"David","email":"dshelly@usgs.gov","middleInitial":"R.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":489575,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"King, John C.","contributorId":60949,"corporation":false,"usgs":true,"family":"King","given":"John","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":489579,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McGeehin, John P. 0000-0002-5320-6091 mcgeehin@usgs.gov","orcid":"https://orcid.org/0000-0002-5320-6091","contributorId":3444,"corporation":false,"usgs":true,"family":"McGeehin","given":"John P.","email":"mcgeehin@usgs.gov","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":489577,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mangan, Margaret T. 0000-0002-5273-8053 mmangan@usgs.gov","orcid":"https://orcid.org/0000-0002-5273-8053","contributorId":3343,"corporation":false,"usgs":true,"family":"Mangan","given":"Margaret","email":"mmangan@usgs.gov","middleInitial":"T.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":489576,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Evans, William C. 0000-0001-5942-3102 wcevans@usgs.gov","orcid":"https://orcid.org/0000-0001-5942-3102","contributorId":2353,"corporation":false,"usgs":true,"family":"Evans","given":"William","email":"wcevans@usgs.gov","middleInitial":"C.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":489574,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70095233,"text":"70095233 - 2014 - Comparison of smoothing methods for the development of a smoothed seismicity model for Alaska and the implications for seismic hazard","interactions":[],"lastModifiedDate":"2014-07-04T11:56:52","indexId":"70095233","displayToPublicDate":"2014-03-14T11:53:27","publicationYear":"2014","noYear":false,"publicationType":{"id":4,"text":"Book"},"publicationSubtype":{"id":12,"text":"Conference publication"},"title":"Comparison of smoothing methods for the development of a smoothed seismicity model for Alaska and the implications for seismic hazard","docAbstract":"<p>In anticipation of the update of the Alaska seismic hazard maps (ASHMs) by the U. S. Geological Survey, we report progress on the comparison of smoothed seismicity models developed using fixed and adaptive smoothing algorithms, and investigate the sensitivity of seismic hazard to the models. While fault-based sources, such as those for great earthquakes in the Alaska-Aleutian subduction zone and for the ~10 shallow crustal faults within Alaska, dominate the seismic hazard estimates for locations near to the sources, smoothed seismicity rates make important contributions to seismic hazard away from fault-based sources and where knowledge of recurrence and magnitude is not sufficient for use in hazard studies. Recent developments in adaptive smoothing methods and statistical tests for evaluating and comparing rate models prompt us to investigate the appropriateness of adaptive smoothing for the ASHMs. We develop smoothed seismicity models for Alaska using fixed and adaptive smoothing methods and compare the resulting models by calculating and evaluating the joint likelihood test. We use the earthquake catalog, and associated completeness levels, developed for the 2007 ASHM to produce fixed-bandwidth-smoothed models with smoothing distances varying from 10 to 100 km and adaptively smoothed models. Adaptive smoothing follows the method of Helmstetter et al. and defines a unique smoothing distance for each earthquake epicenter from the distance to the nth nearest neighbor. The consequence of the adaptive smoothing methods is to reduce smoothing distances, causing locally increased seismicity rates, where seismicity rates are high and to increase smoothing distances where seismicity is sparse. We follow guidance from previous studies to optimize the neighbor number (n-value) by comparing model likelihood values, which estimate the likelihood that the observed earthquake epicenters from the recent catalog are derived from the smoothed rate models. We compare likelihood values from all rate models to rank the smoothing methods. We find that adaptively smoothed seismicity models yield better likelihood values than the fixed smoothing models. Holding all other (source and ground motion) models constant, we calculate seismic hazard curves for all points across Alaska on a 0.1 degree grid, using the adaptively smoothed and fixed smoothed seismicity models separately. Because adaptively smoothed models concentrate seismicity near the earthquake epicenters where seismicity rates are high, the corresponding hazard values are higher, locally, but reduced with distance from observed seismicity, relative to the hazard from fixed-bandwidth models. We suggest that adaptively smoothed seismicity models be considered for implementation in the update to the ASHMs because of their improved likelihood estimates relative to fixed smoothing methods; however, concomitant increases in seismic hazard will cause significant changes in regions of high seismicity, such as near the subduction zone, northeast of Kotzebue, and along the NNE trending zone of seismicity in the Alaskan interior.</p>","largerWorkTitle":"American Geophysical Union, Fall Meeting 2013","conferenceTitle":"American Geophysical Union, Fall Meeting 2013","conferenceDate":"2013-12-01T00:00:00","conferenceLocation":"San Francisco, CA","language":"English","publisher":"American Geophysical Union","publisherLocation":"Washington, D.C.","usgsCitation":"Moschetti, M.P., Mueller, C.S., Boyd, O.S., and Petersen, M.D., 2014, Comparison of smoothing methods for the development of a smoothed seismicity model for Alaska and the implications for seismic hazard.","ipdsId":"IP-055149","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":289435,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 172.4,51.2 ], [ 172.4,71.4 ], [ -130.0,71.4 ], [ -130.0,51.2 ], [ 172.4,51.2 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53b7b0cfe4b0388651d91682","contributors":{"authors":[{"text":"Moschetti, Morgan P. 0000-0001-7261-0295 mmoschetti@usgs.gov","orcid":"https://orcid.org/0000-0001-7261-0295","contributorId":1662,"corporation":false,"usgs":true,"family":"Moschetti","given":"Morgan","email":"mmoschetti@usgs.gov","middleInitial":"P.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":491137,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mueller, Charles S. 0000-0002-1868-9710 cmueller@usgs.gov","orcid":"https://orcid.org/0000-0002-1868-9710","contributorId":955,"corporation":false,"usgs":true,"family":"Mueller","given":"Charles","email":"cmueller@usgs.gov","middleInitial":"S.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":491134,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Boyd, Oliver S. olboyd@usgs.gov","contributorId":956,"corporation":false,"usgs":true,"family":"Boyd","given":"Oliver","email":"olboyd@usgs.gov","middleInitial":"S.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":491135,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Petersen, Mark D. 0000-0001-8542-3990 mpetersen@usgs.gov","orcid":"https://orcid.org/0000-0001-8542-3990","contributorId":1163,"corporation":false,"usgs":true,"family":"Petersen","given":"Mark","email":"mpetersen@usgs.gov","middleInitial":"D.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":491136,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70093931,"text":"ofr20141018 - 2014 - Sea-floor geology in northwestern Block Island Sound, Rhode Island","interactions":[],"lastModifiedDate":"2017-11-10T18:30:05","indexId":"ofr20141018","displayToPublicDate":"2014-03-14T07:22:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-1018","title":"Sea-floor geology in northwestern Block Island Sound, Rhode Island","docAbstract":"Multibeam-echosounder and sidescan-sonar data, collected by the National Oceanic and Atmospheric Administration in a 69-square-kilometer area of northwestern Block Island Sound, are used with sediment samples, and still and video photography of the sea floor, collected by the U.S. Geological Survey at 43 stations within this area, to interpret the sea-floor features and sedimentary environments. Features on the sea floor include boulders, sand waves, scour depressions, modern marine sediments, and trawl marks. Boulders, which are often several meters wide, are found in patches in the shallower depths and tend to be overgrown with sessile flora and fauna. They are lag deposits of winnowed glacial drift, and reflect high-energy environments characterized by processes associated with erosion and nondeposition. Sand waves and megaripples tend to have crests that either trend parallel to shore with 20- to 50-meter (m) wavelengths or trend perpendicular to shore with several-hundred-meter wavelengths. The sand waves reflect sediment transport directions perpendicular to shore by waves, and parallel to shore by tidal or wind-driven currents, respectively. Scour depressions, which are about 0.5 m lower than the surrounding sea floor, have floors of gravel and coarser sand than bounding modern marine sediments. These scour depressions, which are conspicuous in the sidescan-sonar data because of their more highly reflective coarser sediment floors, are likely formed by storm-generated, seaward-flowing currents and maintained by the turbulence in bottom currents caused by their coarse sediments. Areas of the sea floor with modern marine sediments tend to be relatively flat to current-rippled and sandy.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141018","collaboration":"Prepared in cooperation with the National Oceanic and Atmospheric Administration","usgsCitation":"McMullen, K.Y., Poppe, L., Ackerman, S.D., Blackwood, D.S., and Woods, D., 2014, Sea-floor geology in northwestern Block Island Sound, Rhode Island: U.S. Geological Survey Open-File Report 2014-1018, HTML Index, https://doi.org/10.3133/ofr20141018.","productDescription":"HTML Index","additionalOnlineFiles":"Y","ipdsId":"IP-049305","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":283993,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141018.jpg"},{"id":283991,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1018/title_page.html"},{"id":283992,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1018/"}],"country":"United States","state":"Rhode Island","otherGeospatial":"Block Island Sound","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -71.666667,41.333333 ], [ -71.666667,41.666667 ], [ -71.0,41.666667 ], [ -71.0,41.333333 ], [ -71.666667,41.333333 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd719ce4b0b29085107c85","contributors":{"authors":[{"text":"McMullen, Katherine Y. kmcmullen@usgs.gov","contributorId":24036,"corporation":false,"usgs":true,"family":"McMullen","given":"Katherine","email":"kmcmullen@usgs.gov","middleInitial":"Y.","affiliations":[],"preferred":false,"id":490357,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Poppe, Lawrence J. lpoppe@usgs.gov","contributorId":2149,"corporation":false,"usgs":true,"family":"Poppe","given":"Lawrence J.","email":"lpoppe@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":490353,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ackerman, Seth D. 0000-0003-0945-2794 sackerman@usgs.gov","orcid":"https://orcid.org/0000-0003-0945-2794","contributorId":178676,"corporation":false,"usgs":true,"family":"Ackerman","given":"Seth","email":"sackerman@usgs.gov","middleInitial":"D.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":490356,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Blackwood, Dann S. dblackwood@usgs.gov","contributorId":2457,"corporation":false,"usgs":true,"family":"Blackwood","given":"Dann","email":"dblackwood@usgs.gov","middleInitial":"S.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":490354,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Woods, D.A.","contributorId":11941,"corporation":false,"usgs":true,"family":"Woods","given":"D.A.","email":"","affiliations":[],"preferred":false,"id":490355,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70093921,"text":"ofr20141012 - 2014 - Combined multibeam and bathymetry data from Rhode Island Sound and Block Island Sound: a regional perspective","interactions":[],"lastModifiedDate":"2014-03-18T08:32:20","indexId":"ofr20141012","displayToPublicDate":"2014-03-14T07:03:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-1012","title":"Combined multibeam and bathymetry data from Rhode Island Sound and Block Island Sound: a regional perspective","docAbstract":"Detailed bathymetric maps of the sea floor in Rhode Island and Block Island Sounds are of great interest to the New York, Rhode Island, and Massachusetts research and management communities because of this area's ecological, recreational, and commercial importance. Geologically interpreted digital terrain models from individual surveys provide important benthic environmental information, yet many applications of this information require a geographically broader perspective. For example, individual surveys are of limited use for the planning and construction of cross-sound infrastructure, such as cables and pipelines, or for the testing of regional circulation models. To address this need, we integrated 14 contiguous multibeam bathymetric datasets that were produced by the National Oceanic and Atmospheric Administration during charting operations into one digital terrain model that covers much of Block Island Sound and extends eastward across Rhode Island Sound. The new dataset, which covers over 1244 square kilometers, is adjusted to mean lower low water, gridded to 4-meter resolution, and provided in Universal Transverse Mercator Zone 19, North American Datum  of 1983 and geographic World Geodetic Survey of 1984 projections. This resolution is adequate for sea-floor feature and process interpretation but is small enough to be queried and manipulated with standard Geographic Information System programs and to allow for future growth. Natural features visible in the data include boulder lag deposits of winnowed Pleistocene strata, sand-wave fields, and scour depressions that reflect the strength of oscillating tidal currents and scour by storm-induced waves. Bedform asymmetry allows interpretations of net sediment transport. Anthropogenic features visible in the data include shipwrecks and dredged channels. Together the merged data reveal a larger, more continuous perspective of bathymetric topography than previously available, providing a fundamental framework for research and resource management activities offshore of Rhode Island.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141012","collaboration":"Prepared in cooperation with the National Oceanic and Atmospheric Administration","usgsCitation":"Poppe, L., McMullen, K.Y., Danforth, W.W., Blankenship, M.R., Clos, A.R., Glomb, K.A., Lewit, P.G., Nadeau, M.A., Wood, D.A., and Parker, C.E., 2014, Combined multibeam and bathymetry data from Rhode Island Sound and Block Island Sound: a regional perspective: U.S. Geological Survey Open-File Report 2014-1012, HTML Index, https://doi.org/10.3133/ofr20141012.","productDescription":"HTML Index","additionalOnlineFiles":"Y","ipdsId":"IP-051771","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":283988,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1012/title_page.html"},{"id":283990,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141012.jpg"},{"id":283989,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1012/"}],"projection":"Universal Transverse Mercator Zone 19","datum":"NAD 83","country":"United States","state":"Rhode Island","otherGeospatial":"Block Island Sound;Rhode Island Sound","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -72.0,41.083333 ], [ -72.0,41.416667 ], [ -71.0,41.416667 ], [ -71.0,41.083333 ], [ -72.0,41.083333 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd51dae4b0b290850f4286","contributors":{"authors":[{"text":"Poppe, Lawrence J. lpoppe@usgs.gov","contributorId":2149,"corporation":false,"usgs":true,"family":"Poppe","given":"Lawrence J.","email":"lpoppe@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":490305,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McMullen, Katherine Y. kmcmullen@usgs.gov","contributorId":24036,"corporation":false,"usgs":true,"family":"McMullen","given":"Katherine","email":"kmcmullen@usgs.gov","middleInitial":"Y.","affiliations":[],"preferred":false,"id":490308,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Danforth, William W. 0000-0002-6382-9487 bdanforth@usgs.gov","orcid":"https://orcid.org/0000-0002-6382-9487","contributorId":3292,"corporation":false,"usgs":true,"family":"Danforth","given":"William","email":"bdanforth@usgs.gov","middleInitial":"W.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":490306,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Blankenship, Mark R.","contributorId":43270,"corporation":false,"usgs":true,"family":"Blankenship","given":"Mark","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":490311,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Clos, Andrew R.","contributorId":101987,"corporation":false,"usgs":true,"family":"Clos","given":"Andrew","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":490314,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Glomb, Kimberly A.","contributorId":70283,"corporation":false,"usgs":true,"family":"Glomb","given":"Kimberly","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":490313,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lewit, Peter G.","contributorId":69885,"corporation":false,"usgs":true,"family":"Lewit","given":"Peter","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":490312,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Nadeau, Megan A.","contributorId":32450,"corporation":false,"usgs":true,"family":"Nadeau","given":"Megan","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":490309,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Wood, Douglas A.","contributorId":23415,"corporation":false,"usgs":true,"family":"Wood","given":"Douglas","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":490307,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Parker, Castleton E.","contributorId":41334,"corporation":false,"usgs":true,"family":"Parker","given":"Castleton","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":490310,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70094383,"text":"ds828 - 2014 - Spatial mapping and attribution of Wyoming wind turbines, 2012","interactions":[],"lastModifiedDate":"2014-03-13T13:00:15","indexId":"ds828","displayToPublicDate":"2014-03-13T12:48:00","publicationYear":"2014","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":"828","title":"Spatial mapping and attribution of Wyoming wind turbines, 2012","docAbstract":"<p>These data represent locations of wind turbines found within Wyoming as of August 2012. We assigned each wind turbine to a wind farm and, in these data, provide information about each turbine’s potential megawatt output, rotor diameter, hub height, rotor height, the status of the land ownership where the turbine exists, the county each turbine is located in, wind farm power capacity, the number of units currently associated with each wind farm, the wind turbine manufacturer and model, the wind farm developer, the owner of the wind farm, the current purchaser of power from the wind farm, the year the wind farm went online, and the status of its operation. Some of the attributes are estimates based on the information we found via the American Wind Energy Association and other on-line reports. The locations are derived from National Agriculture Imagery Program (2009 and 2012) true color aerial photographs and have a positional accuracy of approximately +/-5 meters.</p>\n<br/>\n<p>These data will provide a planning tool for wildlife- and habitat-related projects underway at the U.S. Geological Survey’s Fort Collins Science Center and other government and non-government organizations. Specifically, we will use these data to support quantifying disturbances of the landscape as related to wind energy as well as to quantify indirect disturbances to flora and fauna. This data set represents an update to a previous version by O’Donnell and Fancher (2010). </p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds828","usgsCitation":"O'Donnell, M., and Fancher, T., 2014, Spatial mapping and attribution of Wyoming wind turbines, 2012: U.S. Geological Survey Data Series 828, Downloads Directory, https://doi.org/10.3133/ds828.","productDescription":"Downloads Directory","onlineOnly":"Y","ipdsId":"IP-052557","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":283944,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds828.GIF"},{"id":283942,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/828/"},{"id":283943,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/828/downloads/"}],"country":"United States","state":"Wyoming","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -111.0569,40.9947 ], [ -111.0569,45.0059 ], [ -104.0522,45.0059 ], [ -104.0522,40.9947 ], [ -111.0569,40.9947 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd738fe4b0b29085109044","contributors":{"authors":[{"text":"O'Donnell, Michael S.","contributorId":40667,"corporation":false,"usgs":true,"family":"O'Donnell","given":"Michael S.","affiliations":[],"preferred":false,"id":490595,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fancher, Tammy S.","contributorId":17689,"corporation":false,"usgs":true,"family":"Fancher","given":"Tammy S.","affiliations":[],"preferred":false,"id":490594,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70094917,"text":"fs20143014 - 2014 - The 3D Elevation Program: summary for Oregon","interactions":[],"lastModifiedDate":"2016-08-17T15:49:05","indexId":"fs20143014","displayToPublicDate":"2014-03-12T11:49:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-3014","title":"The 3D Elevation Program: summary for Oregon","docAbstract":"<p>Elevation data are essential to a broad range of business uses, including forest resources management, wildlife and habitat management, national security, recreation, and many others. In the State of Oregon, elevation data are critical for river and stream resource management; forest resources management; water supply and quality; infrastructure and construction management; wildfire management, planning and response; natural resources conservation; and other business uses. Today, high-density light detection and ranging (lidar) data are the primary source for deriving elevation models and other datasets. The Oregon Lidar Consortium (OLC), led by the Oregon Department of Geology and Mineral Industries (DOGAMI), has developed partnerships with Federal, State, Tribal, and local agencies to acquire quality level 1 data in areas of shared interest. The goal of OLC partners is to acquire consistent, high-resolution and high-quality statewide coverage to support existing and emerging applications enabled by lidar data.</p>\n<p>The National Enhanced Elevation Assessment evaluated multiple elevation data acquisition options to determine the optimal data quality and data replacement cycle relative to cost to meet the identified requirements of the user community. The evaluation demonstrated that lidar acquisition at quality level 2 for the conterminous United States and quality level 5 ifsar data for Alaska with a 6- to 10-year acquisition cycle provided the highest benefit/cost ratios. The 3D Elevation Program (3DEP) initiative selected an 8-year acquisition cycle for the respective quality levels. 3DEP, managed by the U.S. Geological Survey (USGS), the Office of Management and Budget Circular A&ndash;16 lead agency for terrestrial elevation data, responds to the growing need for high-quality topographic data and a wide range of other 3D representations of the Nation&rsquo;s natural and constructed features.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20143014","usgsCitation":"Carswell, W., 2014, The 3D Elevation Program: summary for Oregon: U.S. Geological Survey Fact Sheet 2014-3014, 2 p., https://doi.org/10.3133/fs20143014.","productDescription":"2 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-054086","costCenters":[{"id":423,"text":"National Geospatial 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William J. Jr. carswell@usgs.gov","contributorId":1787,"corporation":false,"usgs":true,"family":"Carswell","given":"William J.","suffix":"Jr.","email":"carswell@usgs.gov","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":false,"id":490947,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70094916,"text":"fs20143012 - 2014 - The 3D Elevation Program: summary for Kentucky","interactions":[],"lastModifiedDate":"2016-08-17T15:50:18","indexId":"fs20143012","displayToPublicDate":"2014-03-12T11:36:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-3012","title":"The 3D Elevation Program: summary for Kentucky","docAbstract":"<p>Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, national security, recreation, and many others. For the Commonwealth of Kentucky, elevation data are critical for agriculture and precision farming, natural resources conservation, flood risk management, infrastructure and construction management, forest resources management, geologic resource assessment and hazards mitigation, and other business uses. Today, high-density light detection and ranging (lidar) data are the primary sources for deriving elevation models and other datasets. Federal, State, Tribal, and local agencies work in partnership to (1) replace data that are older and of lower quality and (2) provide coverage where publicly accessible data do not exist. A joint goal of State and Federal partners is to acquire consistent, statewide coverage to support existing and emerging applications enabled by lidar data. &ldquo;Kentucky from Above,&rdquo; the Kentucky Aerial Photography and Elevation Data Program (<a href=\"http://kygeonet.ky.gov/kyfromabove/\" target=\"_blank\">http://kygeonet.ky.gov/kyfromabove/</a>), provides statewide lidar coordination with local, Commonwealth, and national groups in support of 3DEP for the Commonwealth.</p>\n<p>The National Enhanced Elevation Assessment evaluated multiple elevation data acquisition options to determine the optimal data quality and data replacement cycle relative to cost to meet the identified requirements of the user community. The evaluation demonstrated that lidar acquisition at quality level 2 for the conterminous United States and quality level 5 ifsar data for Alaska with a 6- to 10-year acquisition cycle provided the highest benefit/cost ratios. The 3D Elevation Program (3DEP) initiative selected an 8-year acquisition cycle for the respective quality levels. 3DEP, managed by the U.S. Geological Survey (USGS), the Office of Management and Budget Circular A&ndash;16 lead agency for terrestrial elevation data, responds to the growing need for high-quality topographic data and a wide range of other 3D representations of the Nation&rsquo;s natural and constructed features.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20143012","usgsCitation":"Carswell, W., 2014, The 3D Elevation Program: summary for Kentucky: U.S. Geological Survey Fact Sheet 2014-3012, 2 p., https://doi.org/10.3133/fs20143012.","productDescription":"2 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-052813","costCenters":[{"id":423,"text":"National Geospatial 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,{"id":70094155,"text":"fs20143008 - 2014 - The 3D Elevation Program: summary for Tennessee","interactions":[],"lastModifiedDate":"2016-08-17T15:51:26","indexId":"fs20143008","displayToPublicDate":"2014-03-12T11:29:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-3008","title":"The 3D Elevation Program: summary for Tennessee","docAbstract":"<p>Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, national security, recreation, and many others. For the State of Tennessee, elevation data are critical for agriculture and precision farming, flood risk management, natural resources conservation, infrastructure and construction management, forest resources management, aviation navigation and safety, and other business uses. Today, high-density light detection and ranging (lidar) data are the primary sources for deriving elevation models and other datasets. Federal, State, Tribal, and local agencies work in partnership to (1) replace data that are older and of lower quality and (2) provide coverage where publicly accessible data do not exist. A joint goal of State and Federal partners is to acquire consistent, statewide coverage to support existing and emerging applications enabled by lidar data.</p>\n<p>The National Enhanced Elevation Assessment evaluated multiple elevation data acquisition options to determine the optimal data quality and data replacement cycle relative to cost to meet the identified requirements of the user community. The evaluation demonstrated that lidar acquisition at quality level 2 for the conterminous United States and quality level 5 ifsar data for Alaska with a 6- to 10-year acquisition cycle provided the highest benefit/cost ratios. The 3D Elevation Program (3DEP) initiative selected an 8-year acquisition cycle for the respective quality levels. 3DEP, managed by the U.S. Geological Survey (USGS), the Office of Management and Budget Circular A&ndash;16 lead agency for terrestrial elevation data, responds to the growing need for high-quality topographic data and a wide range of other 3D representations of the Nation&rsquo;s natural and constructed features.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20143008","usgsCitation":"Carswell, W., 2014, The 3D Elevation Program: summary for Tennessee: U.S. Geological Survey Fact Sheet 2014-3008, 2 p., https://doi.org/10.3133/fs20143008.","productDescription":"2 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-052819","costCenters":[{"id":423,"text":"National Geospatial 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Jr. carswell@usgs.gov","contributorId":1787,"corporation":false,"usgs":true,"family":"Carswell","given":"William J.","suffix":"Jr.","email":"carswell@usgs.gov","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":false,"id":490476,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70095719,"text":"70095719 - 2014 - Ecological feedbacks can reduce population-level efficacy of wildlife fertility control","interactions":[],"lastModifiedDate":"2014-03-11T13:39:10","indexId":"70095719","displayToPublicDate":"2014-03-11T13:32:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2163,"text":"Journal of Applied Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Ecological feedbacks can reduce population-level efficacy of wildlife fertility control","docAbstract":"<p>1. Anthropogenic stress on natural systems, particularly the fragmentation of landscapes and the extirpation of predators from food webs, has intensified the need to regulate abundance of wildlife populations with management. Controlling population growth using fertility control has been considered for almost four decades, but nearly all research has focused on understanding effects of fertility control agents on individual animals. Questions about the efficacy of fertility control as a way to control populations remain largely unanswered.</p>\n<br/>\n<p>2. Collateral consequences of contraception can produce unexpected changes in birth rates, survival, immigration and emigration that may reduce the effectiveness of regulating animal abundance. The magnitude and frequency of such effects vary with species-specific social and reproductive systems, as well as connectivity of populations. Developing models that incorporate static demographic parameters from populations not controlled by contraception may bias predictions of fertility control efficacy.</p>\n<br/>\n<p>3. Many population-level studies demonstrate that changes in survival and immigration induced by fertility control can compensate for the reduction in births caused by contraception. The most successful cases of regulating populations using fertility control come from applications of contraceptives to small, closed populations of gregarious and easily accessed species.</p>\n<br/>\n<p>4. Fertility control can result in artificial selection pressures on the population and may lead to long-term unintentional genetic consequences. The magnitude of such selection is dependent on individual heritability and behavioural traits, as well as environmental variation.</p>\n<br/>\n<p>5. <i>Synthesis and applications</i>. Understanding species' life-history strategies, biology, behavioural ecology and ecological context is critical to developing realistic expectations of regulating populations using fertility control. Before time, effort and funding are invested in wildlife contraception, managers may need to consider the possibility that many species and populations can compensate for reduction in fecundity, and this could minimize any reduction in population growth rate.</p>","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Applied Ecology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Blackwell Scientific Publications","publisherLocation":"Oxford","doi":"10.1111/1365-2664.12166","usgsCitation":"Ransom, J.I., Powers, J.G., Hobbs, N., and Baker, D.L., 2014, Ecological feedbacks can reduce population-level efficacy of wildlife fertility control: Journal of Applied Ecology, v. 51, no. 1, p. 259-269, https://doi.org/10.1111/1365-2664.12166.","productDescription":"11 p.","startPage":"259","endPage":"269","numberOfPages":"11","ipdsId":"IP-050888","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":473109,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2664.12166","text":"Publisher Index Page"},{"id":283839,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/1365-2664.12166"},{"id":283840,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"51","issue":"1","noUsgsAuthors":false,"publicationDate":"2013-10-15","publicationStatus":"PW","scienceBaseUri":"53517035e4b05569d805a1d8","contributors":{"authors":[{"text":"Ransom, Jason I. 0000-0002-5930-4004","orcid":"https://orcid.org/0000-0002-5930-4004","contributorId":71645,"corporation":false,"usgs":true,"family":"Ransom","given":"Jason","email":"","middleInitial":"I.","affiliations":[],"preferred":false,"id":491381,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Powers, Jenny G.","contributorId":10710,"corporation":false,"usgs":true,"family":"Powers","given":"Jenny","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":491379,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hobbs, N. Thompson","contributorId":35031,"corporation":false,"usgs":true,"family":"Hobbs","given":"N. Thompson","affiliations":[],"preferred":false,"id":491380,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Baker, Dan L.","contributorId":7995,"corporation":false,"usgs":true,"family":"Baker","given":"Dan","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":491378,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70095606,"text":"70095606 - 2014 - Diffuse migratory connectivity in two species of shrubland birds: evidence from stable isotopes","interactions":[],"lastModifiedDate":"2014-03-11T13:25:14","indexId":"70095606","displayToPublicDate":"2014-03-11T13:18:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2932,"text":"Oecologia","active":true,"publicationSubtype":{"id":10}},"title":"Diffuse migratory connectivity in two species of shrubland birds: evidence from stable isotopes","docAbstract":"Connecting seasonal ranges of migratory birds is important for understanding the annual template of stressors that influence their populations. Brewer’s sparrows (<i>Spizella breweri</i>) and sagebrush sparrows (<i>Artemisiospiza nevadensis</i>) share similar sagebrush (<i>Artemisia</i> spp.) habitats for breeding but have different population trends that might be related to winter location. To link breeding and winter ranges, we created isoscapes of deuterium [stable isotope ratio (δ) of deuterium; δ<sup>2</sup>H] and nitrogen (δ<sup>15</sup>N) for each species modeled from isotope ratios measured in feathers of 264 Brewer’s and 82 sagebrush sparrows and environmental characteristics at capture locations across their breeding range. We then used feather δ<sup>2</sup>H<sub>f</sub> and δ<sup>15</sup>N<sub>f</sub> measured in 1,029 Brewer’s and 527 sagebrush sparrows captured on winter locations in southwestern United States to assign probable breeding ranges. Intraspecies population mixing from across the breeding range was strong for both Brewer’s and sagebrush sparrows on winter ranges. Brewer’s sparrows but not sagebrush sparrows were linked to more northerly breeding locations in the eastern part of their winter range. Winter location was not related to breeding population trends estimated from US Geological Survey Breeding Bird Survey routes for either Brewer’s or sagebrush sparrows. Primary drivers of population dynamics are likely independent for each species; Brewer’s and sagebrush sparrows captured at the same winter location did not share predicted breeding locations or population trends. The diffuse migratory connectivity displayed by Brewer’s and sagebrush sparrows measured at the coarse spatial resolution in our analysis also suggests that local environments rather than broad regional characteristics are primary drivers of annual population trends.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Oecologia","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer Berlin Heidelberg","doi":"10.1007/s00442-013-2791-8","usgsCitation":"Knick, S.T., Leu, M., Rotenberry, J.T., Hanser, S.E., and Fesenmyer, K., 2014, Diffuse migratory connectivity in two species of shrubland birds: evidence from stable isotopes: Oecologia, v. 174, no. 2, p. 595-608, https://doi.org/10.1007/s00442-013-2791-8.","productDescription":"14 p.","startPage":"595","endPage":"608","numberOfPages":"14","ipdsId":"IP-043572","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":473110,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://escholarship.org/uc/item/5xv473nm","text":"External Repository"},{"id":283838,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":283432,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s00442-013-2791-8"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -125.73,30.86 ], [ -125.73,53.38 ], [ -100.2,53.38 ], [ -100.2,30.86 ], [ -125.73,30.86 ] ] ] } } ] }","volume":"174","issue":"2","noUsgsAuthors":false,"publicationDate":"2013-10-12","publicationStatus":"PW","scienceBaseUri":"53517033e4b05569d805a1bf","contributors":{"authors":[{"text":"Knick, Steven T. 0000-0003-4025-1704 steve_knick@usgs.gov","orcid":"https://orcid.org/0000-0003-4025-1704","contributorId":159,"corporation":false,"usgs":true,"family":"Knick","given":"Steven","email":"steve_knick@usgs.gov","middleInitial":"T.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":491308,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Leu, Matthias","contributorId":68393,"corporation":false,"usgs":true,"family":"Leu","given":"Matthias","affiliations":[],"preferred":false,"id":491310,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rotenberry, John T.","contributorId":60121,"corporation":false,"usgs":true,"family":"Rotenberry","given":"John","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":491309,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hanser, Steven E.","contributorId":99273,"corporation":false,"usgs":true,"family":"Hanser","given":"Steven","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":491311,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fesenmyer, Kurt","contributorId":105640,"corporation":false,"usgs":true,"family":"Fesenmyer","given":"Kurt","affiliations":[],"preferred":false,"id":491312,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70095788,"text":"70095788 - 2014 - Applying downscaled global climate model data to a hydrodynamic surface-water and groundwater model","interactions":[],"lastModifiedDate":"2014-03-11T12:58:56","indexId":"70095788","displayToPublicDate":"2014-03-11T12:53:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":725,"text":"American Journal of Climate Change","active":true,"publicationSubtype":{"id":10}},"title":"Applying downscaled global climate model data to a hydrodynamic surface-water and groundwater model","docAbstract":"Precipitation data from Global Climate Models have been downscaled to smaller regions. Adapting this downscaled precipitation data to a coupled hydrodynamic surface-water/groundwater model of southern Florida allows an examination of future conditions and their effect on groundwater levels, inundation patterns, surface-water stage and flows, and salinity. The downscaled rainfall data include the 1996-2001 time series from the European Center for Medium-Range Weather Forecasting ERA-40 simulation and both the 1996-1999 and 2038-2057 time series from two global climate models: the Community Climate System Model (CCSM) and the Geophysical Fluid Dynamic Laboratory (GFDL). Synthesized surface-water inflow datasets were developed for the 2038-2057 simulations. The resulting hydrologic simulations, with and without a 30-cm sea-level rise, were compared with each other and field data to analyze a range of projected conditions. Simulations predicted generally higher future stage and groundwater levels and surface-water flows, with sea-level rise inducing higher coastal salinities. A coincident rise in sea level, precipitation and surface-water flows resulted in a narrower inland saline/fresh transition zone. The inland areas were affected more by the rainfall difference than the sea-level rise, and the rainfall differences make little difference in coastal inundation, but a larger difference in coastal salinities.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"American Journal of Climate Change","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Scientific Research Publishing Inc.","publisherLocation":"Irvine, CA","doi":"10.4236/ajcc.2014.31004","usgsCitation":"Swain, E., Stefanova, L., and Smith, T., 2014, Applying downscaled global climate model data to a hydrodynamic surface-water and groundwater model: American Journal of Climate Change, v. 3, no. 1, p. 33-49, https://doi.org/10.4236/ajcc.2014.31004.","productDescription":"17 p.","startPage":"33","endPage":"49","numberOfPages":"17","ipdsId":"IP-038872","costCenters":[{"id":285,"text":"Florida Water Science Center","active":false,"usgs":true}],"links":[{"id":473113,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.4236/ajcc.2014.31004","text":"Publisher Index Page"},{"id":283835,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":283834,"type":{"id":15,"text":"Index Page"},"url":"https://www.scirp.org/journal/PaperInformation.aspx?PaperID=43632#.Ux9OwPRDuVM"},{"id":283774,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.4236/ajcc.2014.31004"}],"country":"United States","state":"Florida","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -82.8998,24.5211 ], [ -82.8998,27.8146 ], [ 24.5211,27.8146 ], [ 24.5211,24.5211 ], [ -82.8998,24.5211 ] ] ] } } ] }","volume":"3","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5351701ee4b05569d805a156","contributors":{"authors":[{"text":"Swain, Eric 0000-0001-7168-708X","orcid":"https://orcid.org/0000-0001-7168-708X","contributorId":23347,"corporation":false,"usgs":true,"family":"Swain","given":"Eric","affiliations":[],"preferred":false,"id":491434,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stefanova, Lydia","contributorId":48300,"corporation":false,"usgs":true,"family":"Stefanova","given":"Lydia","email":"","affiliations":[],"preferred":false,"id":491436,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, Thomas","contributorId":46416,"corporation":false,"usgs":true,"family":"Smith","given":"Thomas","affiliations":[],"preferred":false,"id":491435,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70057463,"text":"sir20135217 - 2014 - Water-quality trends for selected sampling sites in the upper Clark Fork Basin, Montana, water years 1996-2010","interactions":[],"lastModifiedDate":"2014-03-11T10:37:01","indexId":"sir20135217","displayToPublicDate":"2014-03-11T10:28:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-5217","title":"Water-quality trends for selected sampling sites in the upper Clark Fork Basin, Montana, water years 1996-2010","docAbstract":"<p>A large-scale trend analysis was done on specific conductance, selected trace elements (arsenic, cadmium, copper, iron, lead, manganese, and zinc), and suspended-sediment data for 22 sites in the upper Clark Fork Basin for water years 1996–2010. Trend analysis was conducted by using two parametric methods: a time-series model (TSM) and multiple linear regression on time, streamflow, and season (MLR). Trend results for 1996–2010 indicate moderate to large decreases in flow-adjusted concentrations (FACs) and loads of copper (and other metallic elements) and suspended sediment in Silver Bow Creek upstream from Warm Springs. Deposition of metallic elements and suspended sediment within Warm Springs Ponds substantially reduces the downstream transport of those constituents. However, mobilization of copper and suspended sediment from floodplain tailings and stream banks in the Clark Fork reach from Galen to Deer Lodge is a large source of metallic elements and suspended sediment, which also affects downstream transport of those constituents. Copper and suspended-sediment loads mobilized from within this reach accounted for about 40 and 20 percent, respectively, of the loads for Clark Fork at Turah Bridge (site 20); whereas, streamflow contributed from within this reach only accounted for about 8 percent of the streamflow at Turah Bridge. Minor changes in FACs and loads of copper and suspended sediment are indicated for this reach during 1996–2010.</p>\n<br/>\n<p>Clark Fork reaches downstream from Deer Lodge are relatively smaller sources of metallic elements than the reach from Galen to Deer Lodge. In general, small decreases in loads and FACs of copper and suspended sediment are indicated for Clark Fork sites downstream from Deer Lodge during 1996–2010. Thus, although large decreases in FACs and loads of copper and suspended sediment are indicated for Silver Bow Creek upstream from Warm Springs, those large decreases are not translated to the more downstream reaches largely because of temporal stationarity in constituent transport relations in the Clark Fork reach from Galen to Deer Lodge.</p>\n<br/>\n<p>Unlike metallic elements, arsenic (a metalloid element) in streams in the upper Clark Fork Basin typically is mostly in dissolved phase, has less variability in concentrations, and has weaker direct relations with suspended-sediment concentrations and streamflow. Arsenic trend results for 1996–2010 indicate generally moderate decreases in FACs and loads in Silver Bow Creek upstream from Opportunity. In general, small temporal changes in loads and FACs of arsenic are indicated for Silver Bow Creek and Clark Fork reaches downstream from Opportunity during 1996–2010. Contribution of arsenic (from Warm Springs Ponds, the Mill-Willow bypass, and groundwater sources) in the Silver Bow Creek reach from Opportunity to Warm Springs is a relatively large source of arsenic. Arsenic loads originating from within this reach accounted for about 11 percent of the load for Clark Fork at Turah Bridge; whereas, streamflow contributed from within this reach only accounted for about 2 percent of the streamflow at Turah Bridge.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135217","usgsCitation":"Sando, S.K., Vecchia, A.V., Lorenz, D.L., and Barnhart, E.P., 2014, Water-quality trends for selected sampling sites in the upper Clark Fork Basin, Montana, water years 1996-2010: U.S. Geological Survey Scientific Investigations Report 2013-5217, xiii, 162 p., https://doi.org/10.3133/sir20135217.","productDescription":"xiii, 162 p.","numberOfPages":"180","temporalStart":"1995-10-01","temporalEnd":"2010-09-30","ipdsId":"IP-045334","costCenters":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"links":[{"id":283807,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135217.jpg"},{"id":283806,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5217/pdf/sir13-5217.pdf"},{"id":283770,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5217/"}],"projection":"Universal Transverse Mercator Projection","datum":"North American Datum of 1927","country":"United States","state":"Montana","otherGeospatial":"Clark Fork Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -114.071,45.7493 ], [ -114.071,47.532 ], [ -112.1814,47.532 ], [ -112.1814,45.7493 ], [ -114.071,45.7493 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd7d32e4b0b2908510f3b3","contributors":{"authors":[{"text":"Sando, Steven K. 0000-0003-1206-1030 sksando@usgs.gov","orcid":"https://orcid.org/0000-0003-1206-1030","contributorId":1016,"corporation":false,"usgs":true,"family":"Sando","given":"Steven","email":"sksando@usgs.gov","middleInitial":"K.","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":486776,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vecchia, Aldo V. 0000-0002-2661-4401","orcid":"https://orcid.org/0000-0002-2661-4401","contributorId":41810,"corporation":false,"usgs":true,"family":"Vecchia","given":"Aldo","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":486779,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lorenz, David L. 0000-0003-3392-4034 lorenz@usgs.gov","orcid":"https://orcid.org/0000-0003-3392-4034","contributorId":1384,"corporation":false,"usgs":true,"family":"Lorenz","given":"David","email":"lorenz@usgs.gov","middleInitial":"L.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":486777,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barnhart, Elliott P. 0000-0002-8788-8393 epbarnhart@usgs.gov","orcid":"https://orcid.org/0000-0002-8788-8393","contributorId":5385,"corporation":false,"usgs":true,"family":"Barnhart","given":"Elliott","email":"epbarnhart@usgs.gov","middleInitial":"P.","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":486778,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70048055,"text":"70048055 - 2014 - Antecedent flow conditions and nitrate concentrations in the Mississippi River basin","interactions":[],"lastModifiedDate":"2014-06-04T11:15:54","indexId":"70048055","displayToPublicDate":"2014-03-10T09:35:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1928,"text":"Hydrology and Earth System Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Antecedent flow conditions and nitrate concentrations in the Mississippi River basin","docAbstract":"The relationship between antecedent flow conditions and nitrate concentrations was explored at eight sites in the 2.9 million square kilometers (km<sup>2</sup>) Mississippi River basin, USA. Antecedent flow conditions were quantified as the ratio between the mean daily flow of the previous year and the mean daily flow from the period of record (Qratio), and the Qratio was statistically related to nitrate anomalies (the unexplained variability in nitrate concentration after filtering out season, long-term trend, and contemporaneous flow effects) at each site. Nitrate anomaly and Qratio were negatively related at three of the four major tributary sites and upstream in the Mississippi River, indicating that when mean daily streamflow during the previous year was lower than average, nitrate concentrations were higher than expected. The strength of these relationships increased when data were subdivided by contemporaneous flow conditions. Five of the eight sites had significant negative relationships (<i>p</i> ≤ 0.05) at high or moderately high contemporaneous flows, suggesting nitrate that accumulates in these basins during a drought is flushed during subsequent high flows. At half of the sites, when mean daily flow during the previous year was 50 percent lower than average, nitrate concentration can be from 9 to 27 percent higher than nitrate concentrations that follow a year with average mean daily flow. Conversely, nitrate concentration can be from 8 to 21 percent lower than expected when flow during the previous year was 50 percent higher than average. Previously documented for small, relatively homogenous basins, our results suggest that relationships between antecedent flows and nitrate concentrations are also observable at a regional scale. Relationships were not observed (using all contemporaneous flow data together) for basins larger than 1 million km<sup>2</sup>, suggesting that above this limit the overall size and diversity within these basins may necessitate the use of more complicated statistical approaches or that there may be no discernible basin-wide relationship with antecedent flow. The relationships between nitrate concentration and Qratio identified in this study serve as the basis for future studies that can better define specific hydrologic processes occurring during and after a drought (or high flow period) which influence nitrate concentration, such as the duration or magnitude of low flows, and the timing of low and high flows.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Hydrology and Earth System Sciences","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Hydrology and Earth System Science","doi":"10.5194/hessd-10-11451-2013","usgsCitation":"Murphy, J.C., Hirsch, R.M., and Sprague, L.A., 2014, Antecedent flow conditions and nitrate concentrations in the Mississippi River basin: Hydrology and Earth System Sciences, p. 967-979, https://doi.org/10.5194/hessd-10-11451-2013.","productDescription":"13 p.","startPage":"967","endPage":"979","ipdsId":"IP-045515","costCenters":[{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true}],"links":[{"id":473114,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/hessd-10-11451-2013","text":"Publisher Index Page"},{"id":288062,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":277439,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.5194/hessd-10-11451-2013"}],"country":"United States","otherGeospatial":"Mississippi River Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.8,24.5 ], [ -124.8,49.383333 ], [ -66.95,49.383333 ], [ -66.95,24.5 ], [ -124.8,24.5 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53903fe4e4b04eea98bf84ed","contributors":{"authors":[{"text":"Murphy, Jennifer C. 0000-0002-0881-0919 jmurphy@usgs.gov","orcid":"https://orcid.org/0000-0002-0881-0919","contributorId":4281,"corporation":false,"usgs":true,"family":"Murphy","given":"Jennifer","email":"jmurphy@usgs.gov","middleInitial":"C.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":483677,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hirsch, Robert M. 0000-0002-4534-075X rhirsch@usgs.gov","orcid":"https://orcid.org/0000-0002-4534-075X","contributorId":2005,"corporation":false,"usgs":true,"family":"Hirsch","given":"Robert","email":"rhirsch@usgs.gov","middleInitial":"M.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":483676,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sprague, Lori A. 0000-0003-2832-6662 lsprague@usgs.gov","orcid":"https://orcid.org/0000-0003-2832-6662","contributorId":726,"corporation":false,"usgs":true,"family":"Sprague","given":"Lori","email":"lsprague@usgs.gov","middleInitial":"A.","affiliations":[{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":483675,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70126307,"text":"70126307 - 2014 - Biological soil crusts (biocrusts) as a model system in community, landscape and ecosystem ecology","interactions":[],"lastModifiedDate":"2014-09-23T09:43:09","indexId":"70126307","displayToPublicDate":"2014-03-09T09:42:03","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1006,"text":"Biodiversity and Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Biological soil crusts (biocrusts) as a model system in community, landscape and ecosystem ecology","docAbstract":"Model systems have had a profound influence on the development of ecological theory and general principles. Compared to alternatives, the most effective models share some combination of the following characteristics: simpler, smaller, faster, general, idiosyncratic or manipulable. We argue that biological soil crusts (biocrusts) have unique combinations of these features that should be more widely exploited in community, landscape and ecosystem ecology. In community ecology, biocrusts are elucidating the importance of biodiversity and spatial pattern for maintaining ecosystem multifunctionality due to their manipulability in experiments. Due to idiosyncrasies in their modes of facilitation and competition, biocrusts have led to new models on the interplay between environmental stress and biotic interactions and on the maintenance of biodiversity by competitive processes. Biocrusts are perhaps one of the best examples of micro-landscapes—real landscapes that are small in size. Although they exhibit varying patch heterogeneity, aggregation, connectivity and fragmentation, like macro-landscapes, they are also compatible with well-replicated experiments (unlike macro-landscapes). In ecosystem ecology, a number of studies are imposing small-scale, low cost manipulations of global change or state factors in biocrust micro-landscapes. The versatility of biocrusts to inform such disparate lines of inquiry suggests that they are an especially useful model system that can enable researchers to see ecological principles more clearly and quickly.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Biodiversity and Conservation","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Chapman & Hall","publisherLocation":"Andover, Hants, UK","doi":"10.1007/s10531-014-0658-x","usgsCitation":"Bowker, M.A., Maestre, F.T., Eldridge, D., Belnap, J., Castillo-Monroy, A., Escolar, C., and Soliveres, S., 2014, Biological soil crusts (biocrusts) as a model system in community, landscape and ecosystem ecology: Biodiversity and Conservation, v. 23, no. 7, p. 1619-1637, https://doi.org/10.1007/s10531-014-0658-x.","productDescription":"19 p.","startPage":"1619","endPage":"1637","numberOfPages":"19","ipdsId":"IP-053108","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":488369,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://dspace.utpl.edu.ec/handle/123456789/19144","text":"External Repository"},{"id":294289,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":294258,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s10531-014-0658-x"},{"id":294259,"type":{"id":15,"text":"Index Page"},"url":"https://link.springer.com/article/10.1007%2Fs10531-014-0658-x"}],"volume":"23","issue":"7","noUsgsAuthors":false,"publicationDate":"2014-03-09","publicationStatus":"PW","scienceBaseUri":"5422bb18e4b08312ac7cef45","contributors":{"authors":[{"text":"Bowker, Matthew A. mbowker@usgs.gov","contributorId":2875,"corporation":false,"usgs":true,"family":"Bowker","given":"Matthew","email":"mbowker@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":501978,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Maestre, Fernando T.","contributorId":62450,"corporation":false,"usgs":true,"family":"Maestre","given":"Fernando","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":501980,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Eldridge, David","contributorId":103595,"corporation":false,"usgs":true,"family":"Eldridge","given":"David","email":"","affiliations":[],"preferred":false,"id":501983,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Belnap, Jayne 0000-0001-7471-2279 jayne_belnap@usgs.gov","orcid":"https://orcid.org/0000-0001-7471-2279","contributorId":1332,"corporation":false,"usgs":true,"family":"Belnap","given":"Jayne","email":"jayne_belnap@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":501977,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Castillo-Monroy, Andrea","contributorId":69904,"corporation":false,"usgs":true,"family":"Castillo-Monroy","given":"Andrea","affiliations":[],"preferred":false,"id":501981,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Escolar, Cristina","contributorId":70241,"corporation":false,"usgs":true,"family":"Escolar","given":"Cristina","email":"","affiliations":[],"preferred":false,"id":501982,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Soliveres, Santiago","contributorId":37194,"corporation":false,"usgs":true,"family":"Soliveres","given":"Santiago","email":"","affiliations":[],"preferred":false,"id":501979,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70095536,"text":"70095536 - 2014 - Wetland Reserve Program enhances site occupancy and species richness in assemblages of anuran amphibians in the Mississippi Alluvial Valley, USA","interactions":[],"lastModifiedDate":"2019-06-05T14:59:18","indexId":"70095536","displayToPublicDate":"2014-03-06T14:39:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3750,"text":"Wetlands","onlineIssn":"1943-6246","printIssn":"0277-5212","active":true,"publicationSubtype":{"id":10}},"title":"Wetland Reserve Program enhances site occupancy and species richness in assemblages of anuran amphibians in the Mississippi Alluvial Valley, USA","docAbstract":"We measured amphibian habitat use to quantify the effectiveness of conservation practices implemented under the Wetland Reserve Program (WRP), an initiative of the U.S. Department of Agriculture’s Natural Resources Conservation Service. From February to June 2007, we quantified calling male anurans in cultivated cropland, former cultivated cropland restored through the WRP, and mature bottomland hardwood forest. Sites were located in two watersheds within the Mississippi Alluvial Valley of Arkansas and Louisiana, USA. We estimated detection probability and site occupancy within each land use category using a Bayesian hierarchical model of community species occurrence, and derived an estimate of species richness at each site. Relative to sites in cultivated cropland, nine of 1 l species detected were significantly more likely to occur at WRP sites and six were more likely to occur at forested sites. Species richness estimates were also higher for WRP and forested sites, compared to those in cultivated cropland. Almost half (45 %) of the species responded positively to both WRP and forested sites, indicating that patches undergoing restoration may be important transitional habitats. Wetland Reserve Program conservation practices are successful in restoring suitable habitat and reducing the impact of cultivation-induced habitat loss on amphibians in the Mississippi Alluvial Valley.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Wetlands","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer Netherlands","doi":"10.1007/s13157-013-0498-6","usgsCitation":"Walls, S., Waddle, J., and Faulkner, S.P., 2014, Wetland Reserve Program enhances site occupancy and species richness in assemblages of anuran amphibians in the Mississippi Alluvial Valley, USA: Wetlands, v. 34, no. 1, p. 197-207, https://doi.org/10.1007/s13157-013-0498-6.","productDescription":"11 p.","startPage":"197","endPage":"207","numberOfPages":"11","ipdsId":"IP-049031","costCenters":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"links":[{"id":283433,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":283431,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s13157-013-0498-6"}],"country":"United States","state":"Arkansas;Louisiana","otherGeospatial":"Mississippi Alluvial Valley","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -93.47,29.48 ], [ -93.47,35.85 ], [ -87.91,35.85 ], [ -87.91,29.48 ], [ -93.47,29.48 ] ] ] } } ] }","volume":"34","issue":"1","noUsgsAuthors":false,"publicationDate":"2013-12-03","publicationStatus":"PW","scienceBaseUri":"5351706fe4b05569d805a451","contributors":{"authors":[{"text":"Walls, Susan C. 0000-0001-7391-9155","orcid":"https://orcid.org/0000-0001-7391-9155","contributorId":52284,"corporation":false,"usgs":true,"family":"Walls","given":"Susan C.","affiliations":[],"preferred":false,"id":491277,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Waddle, J. Hardin 0000-0003-1940-2133","orcid":"https://orcid.org/0000-0003-1940-2133","contributorId":89982,"corporation":false,"usgs":true,"family":"Waddle","given":"J. Hardin","affiliations":[],"preferred":false,"id":491278,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Faulkner, Stephen P. 0000-0001-5295-1383 faulkners@usgs.gov","orcid":"https://orcid.org/0000-0001-5295-1383","contributorId":374,"corporation":false,"usgs":true,"family":"Faulkner","given":"Stephen","email":"faulkners@usgs.gov","middleInitial":"P.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":491276,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70101352,"text":"70101352 - 2014 - A missing dimension in measures of vaccination impacts","interactions":[],"lastModifiedDate":"2021-02-04T19:25:08.908463","indexId":"70101352","displayToPublicDate":"2014-03-06T13:21:58","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2981,"text":"PLoS Pathogens","active":true,"publicationSubtype":{"id":10}},"title":"A missing dimension in measures of vaccination impacts","docAbstract":"<p><span>Immunological protection, acquired from either natural infection or vaccination, varies among hosts, reflecting underlying biological variation and affecting population-level protection. Owing to the nature of resistance mechanisms, distributions of susceptibility and protection entangle with pathogen dose in a way that can be decoupled by adequately representing the dose dimension. Any infectious processes must depend in some fashion on dose, and empirical evidence exists for an effect of exposure dose on the probability of transmission to mumps-vaccinated hosts&nbsp;</span><a class=\"ref-tip\" href=\"https://journals.plos.org/plospathogens/article?id=10.1371/journal.ppat.1003849#ppat.1003849-Barskey1\" data-mce-href=\"https://journals.plos.org/plospathogens/article?id=10.1371/journal.ppat.1003849#ppat.1003849-Barskey1\">[1]</a><span>, the case-fatality ratio of measles&nbsp;</span><a class=\"ref-tip\" href=\"https://journals.plos.org/plospathogens/article?id=10.1371/journal.ppat.1003849#ppat.1003849-Aaby1\" data-mce-href=\"https://journals.plos.org/plospathogens/article?id=10.1371/journal.ppat.1003849#ppat.1003849-Aaby1\">[2]</a><span>, and the probability of infection and, given infection, of symptoms in cholera&nbsp;</span><a class=\"ref-tip\" href=\"https://journals.plos.org/plospathogens/article?id=10.1371/journal.ppat.1003849#ppat.1003849-Hornick1\" data-mce-href=\"https://journals.plos.org/plospathogens/article?id=10.1371/journal.ppat.1003849#ppat.1003849-Hornick1\">[3]</a><span>. Extreme distributions of vaccine protection have been termed leaky (partially protects all hosts) and all-or-nothing (totally protects a proportion of hosts)&nbsp;</span><a class=\"ref-tip\" href=\"https://journals.plos.org/plospathogens/article?id=10.1371/journal.ppat.1003849#ppat.1003849-Halloran1\" data-mce-href=\"https://journals.plos.org/plospathogens/article?id=10.1371/journal.ppat.1003849#ppat.1003849-Halloran1\">[4]</a><span>. These distributions can be distinguished in vaccine field trials from the time dependence of infections&nbsp;</span><a class=\"ref-tip\" href=\"https://journals.plos.org/plospathogens/article?id=10.1371/journal.ppat.1003849#ppat.1003849-Smith1\" data-mce-href=\"https://journals.plos.org/plospathogens/article?id=10.1371/journal.ppat.1003849#ppat.1003849-Smith1\">[5]</a><span>. Frailty mixing models have also been proposed to estimate the distribution of protection from time to event data&nbsp;</span><a class=\"ref-tip\" href=\"https://journals.plos.org/plospathogens/article?id=10.1371/journal.ppat.1003849#ppat.1003849-Halloran2\" data-mce-href=\"https://journals.plos.org/plospathogens/article?id=10.1371/journal.ppat.1003849#ppat.1003849-Halloran2\">[6]</a><span>,&nbsp;</span><a class=\"ref-tip\" href=\"https://journals.plos.org/plospathogens/article?id=10.1371/journal.ppat.1003849#ppat.1003849-Longini1\" data-mce-href=\"https://journals.plos.org/plospathogens/article?id=10.1371/journal.ppat.1003849#ppat.1003849-Longini1\">[7]</a><span>, although the results are not comparable across regions unless there is explicit control for baseline transmission&nbsp;</span><a class=\"ref-tip\" href=\"https://journals.plos.org/plospathogens/article?id=10.1371/journal.ppat.1003849#ppat.1003849-Struchiner1\" data-mce-href=\"https://journals.plos.org/plospathogens/article?id=10.1371/journal.ppat.1003849#ppat.1003849-Struchiner1\">[8]</a><span>. Distributions of host susceptibility and acquired protection can be estimated from dose-response data generated under controlled experimental conditions&nbsp;</span><a class=\"ref-tip\" href=\"https://journals.plos.org/plospathogens/article?id=10.1371/journal.ppat.1003849#ppat.1003849-Furumoto1\" data-mce-href=\"https://journals.plos.org/plospathogens/article?id=10.1371/journal.ppat.1003849#ppat.1003849-Furumoto1\">[9]</a><span>–</span><a class=\"ref-tip\" href=\"https://journals.plos.org/plospathogens/article?id=10.1371/journal.ppat.1003849#ppat.1003849-Haas1\" data-mce-href=\"https://journals.plos.org/plospathogens/article?id=10.1371/journal.ppat.1003849#ppat.1003849-Haas1\">[11]</a><span>&nbsp;and natural settings&nbsp;</span><a class=\"ref-tip\" href=\"https://journals.plos.org/plospathogens/article?id=10.1371/journal.ppat.1003849#ppat.1003849-Smith2\" data-mce-href=\"https://journals.plos.org/plospathogens/article?id=10.1371/journal.ppat.1003849#ppat.1003849-Smith2\">[12]</a><span>,&nbsp;</span><a class=\"ref-tip\" href=\"https://journals.plos.org/plospathogens/article?id=10.1371/journal.ppat.1003849#ppat.1003849-Gomes1\" data-mce-href=\"https://journals.plos.org/plospathogens/article?id=10.1371/journal.ppat.1003849#ppat.1003849-Gomes1\">[13]</a><span>. These distributions can guide research on mechanisms of protection, as well as enable model validity across the entire range of transmission intensities. We argue for a shift to a dose-dimension paradigm in infectious disease science and community health.</span></p>","language":"English","publisher":"PLoS Pathogens","doi":"10.1371/journal.ppat.1003849","usgsCitation":"Gomes, M., Wargo, A., Lipsitch, M., Kurath, G., Rebelo, C., Medley, G.F., and Coutinho, A., 2014, A missing dimension in measures of vaccination impacts: PLoS Pathogens, v. 10, no. 3, e1003849, 3 p., https://doi.org/10.1371/journal.ppat.1003849.","productDescription":"e1003849, 3 p.","ipdsId":"IP-051994","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":473122,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.ppat.1003849","text":"Publisher Index Page"},{"id":383027,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","issue":"3","noUsgsAuthors":false,"publicationDate":"2014-03-06","publicationStatus":"PW","scienceBaseUri":"53516ef2e4b05569d8059f27","contributors":{"authors":[{"text":"Gomes, M. Gabriela M.","contributorId":67409,"corporation":false,"usgs":true,"family":"Gomes","given":"M. Gabriela M.","affiliations":[],"preferred":false,"id":809841,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wargo, Andrew","contributorId":73480,"corporation":false,"usgs":true,"family":"Wargo","given":"Andrew","affiliations":[],"preferred":false,"id":809842,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lipsitch, Marc","contributorId":201198,"corporation":false,"usgs":false,"family":"Lipsitch","given":"Marc","email":"","affiliations":[],"preferred":false,"id":809843,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kurath, Gael 0000-0003-3294-560X gkurath@usgs.gov","orcid":"https://orcid.org/0000-0003-3294-560X","contributorId":2629,"corporation":false,"usgs":true,"family":"Kurath","given":"Gael","email":"gkurath@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":518711,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rebelo, Carlota","contributorId":13135,"corporation":false,"usgs":true,"family":"Rebelo","given":"Carlota","email":"","affiliations":[],"preferred":false,"id":809844,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Medley, Graham F.","contributorId":80581,"corporation":false,"usgs":true,"family":"Medley","given":"Graham","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":809845,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Coutinho, Antonio","contributorId":54111,"corporation":false,"usgs":true,"family":"Coutinho","given":"Antonio","email":"","affiliations":[],"preferred":false,"id":809846,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70124417,"text":"70124417 - 2014 - Rate of tree carbon accumulation increases continuously with tree size","interactions":[],"lastModifiedDate":"2017-02-13T15:07:53","indexId":"70124417","displayToPublicDate":"2014-03-06T11:43:38","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2840,"text":"Nature","active":true,"publicationSubtype":{"id":10}},"title":"Rate of tree carbon accumulation increases continuously with tree size","docAbstract":"<p>Forests are major components of the global carbon cycle, providing substantial feedback to atmospheric greenhouse gas concentrations. Our ability to understand and predict changes in the forest carbon cycle—particularly net primary productivity and carbon storage - increasingly relies on models that represent biological processes across several scales of biological organization, from tree leaves to forest stands. Yet, despite advances in our understanding of productivity at the scales of leaves and stands, no consensus exists about the nature of productivity at the scale of the individual tree, in part because we lack a broad empirical assessment of whether rates of absolute tree mass growth (and thus carbon accumulation) decrease, remain constant, or increase as trees increase in size and age. Here we present a global analysis of 403 tropical and temperate tree species, showing that for most species mass growth rate increases continuously with tree size. Thus, large, old trees do not act simply as senescent carbon reservoirs but actively fix large amounts of carbon compared to smaller trees; at the extreme, a single big tree can add the same amount of carbon to the forest within a year as is contained in an entire mid-sized tree. The apparent paradoxes of individual tree growth increasing with tree size despite declining leaf-level and stand-level productivity can be explained, respectively, by increases in a tree’s total leaf area that outpace declines in productivity per unit of leaf area and, among other factors, age-related reductions in population density. Our results resolve conflicting assumptions about the nature of tree growth, inform efforts to understand and model forest carbon dynamics, and have additional implications for theories of resource allocation and plant senescence.</p>","language":"English","publisher":"Nature Publishing Group","doi":"10.1038/nature12914","usgsCitation":"Stephenson, N., Das, A., Condit, R., Russo, S., Baker, P., Beckman, N., Coomes, D., Lines, E., Morris, W., Rüger, N., Alvarez, E., Blundo, C., Bunyavejchewin, S., Chuyong, G., Davies, S., Duque, A., Ewango, C., Flores, O., Franklin, J., Grau, H., Hao, Z., Harmon, M.E., Hubbell, S., Kenfack, D., Lin, Y., Makana, J., Malizia, A., Malizia, L., Pabst, R., Pongpattananurak, N., Su, S., Sun, I., Tan, S., Thomas, D., van Mantgem, P.J., Wang, X., Wiser, S., and Zavala, M., 2014, Rate of tree carbon accumulation increases continuously with tree size: Nature, v. 507, p. 90-93, https://doi.org/10.1038/nature12914.","productDescription":"4 p.","startPage":"90","endPage":"93","numberOfPages":"4","ipdsId":"IP-050838","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true}],"links":[{"id":473123,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/11336/12757","text":"External Repository"},{"id":293820,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":293769,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1038/nature12914"}],"volume":"507","noUsgsAuthors":false,"publicationDate":"2014-01-15","publicationStatus":"PW","scienceBaseUri":"54140b25e4b082fed288b956","contributors":{"authors":[{"text":"Stephenson, 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