{"pageNumber":"643","pageRowStart":"16050","pageSize":"25","recordCount":40807,"records":[{"id":70103857,"text":"70103857 - 2013 - A wetting and drying scheme for ROMS","interactions":[],"lastModifiedDate":"2018-02-08T09:38:15","indexId":"70103857","displayToPublicDate":"2013-08-01T14:08:10","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1315,"text":"Computers & Geosciences","printIssn":"0098-3004","active":true,"publicationSubtype":{"id":10}},"title":"A wetting and drying scheme for ROMS","docAbstract":"The processes of wetting and drying have many important physical and biological impacts on shallow water systems. Inundation and dewatering effects on coastal mud flats and beaches occur on various time scales ranging from storm surge, periodic rise and fall of the tide, to infragravity wave motions. To correctly simulate these physical processes with a numerical model requires the capability of the computational cells to become inundated and dewatered. In this paper, we describe a method for wetting and drying based on an approach consistent with a cell-face blocking algorithm. The method allows water to always flow into any cell, but prevents outflow from a cell when the total depth in that cell is less than a user defined critical value. We describe the method, the implementation into the three-dimensional Regional Oceanographic Modeling System (ROMS), and exhibit the new capability under three scenarios: an analytical expression for shallow water flows, a dam break test case, and a realistic application to part of a wetland area along the Georgia Coast, USA.","language":"English","publisher":"Elsevier","doi":"10.1016/j.cageo.2013.05.004","usgsCitation":"Warner, J., Defne, Z., Haas, K., and Arango, H.G., 2013, A wetting and drying scheme for ROMS: Computers & Geosciences, v. 58, p. 54-61, https://doi.org/10.1016/j.cageo.2013.05.004.","productDescription":"8 p.","startPage":"54","endPage":"61","numberOfPages":"8","ipdsId":"IP-041410","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":473620,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hdl.handle.net/1912/6207","text":"External Repository"},{"id":287000,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":286993,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.cageo.2013.05.004"}],"country":"United States","state":"Georgia","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -81.85,30.6 ], [ -81.85,32.4 ], [ -80.6,32.4 ], [ -80.6,30.6 ], [ -81.85,30.6 ] ] ] } } ] }","volume":"58","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"536ca760e4b060efff280d98","contributors":{"authors":[{"text":"Warner, John C. 0000-0002-3734-8903 jcwarner@usgs.gov","orcid":"https://orcid.org/0000-0002-3734-8903","contributorId":2681,"corporation":false,"usgs":true,"family":"Warner","given":"John C.","email":"jcwarner@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":493502,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Defne, Zafer 0000-0003-4544-4310 zdefne@usgs.gov","orcid":"https://orcid.org/0000-0003-4544-4310","contributorId":5520,"corporation":false,"usgs":true,"family":"Defne","given":"Zafer","email":"zdefne@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":493503,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haas, Kevin","contributorId":23832,"corporation":false,"usgs":true,"family":"Haas","given":"Kevin","affiliations":[],"preferred":false,"id":493504,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Arango, Hernan G.","contributorId":35241,"corporation":false,"usgs":true,"family":"Arango","given":"Hernan","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":493505,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70093724,"text":"70093724 - 2013 - Lidar-derived estimate and uncertainty of carbon sink in successional phases of woody encroachment","interactions":[],"lastModifiedDate":"2014-02-12T13:59:28","indexId":"70093724","displayToPublicDate":"2013-08-01T13:53:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2320,"text":"Journal of Geophysical Research: Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Lidar-derived estimate and uncertainty of carbon sink in successional phases of woody encroachment","docAbstract":"Woody encroachment is a globally occurring phenomenon that contributes to the global carbon sink. The magnitude of this contribution needs to be estimated at regional and local scales to address uncertainties present in the global- and continental-scale estimates, and guide regional policy and management in balancing restoration activities, including removal of woody plants, with greenhouse gas mitigation goals. The objective of this study was to estimate carbon stored in various successional phases of woody encroachment. Using lidar measurements of individual trees, we present high-resolution estimates of aboveground carbon storage in juniper woodlands. Segmentation analysis of lidar point cloud data identified a total of 60,628 juniper tree crowns across four watersheds. Tree heights, canopy cover, and density derived from lidar were strongly correlated with field measurements of 2613 juniper stems measured in 85 plots (30 × 30 m). Aboveground total biomass of individual trees was estimated using a regression model with lidar-derived height and crown area as predictors (Adj. R2 = 0.76, p < 0.001, RMSE = 0.58 kg). The predicted mean aboveground woody carbon storage for the study area was 677 g/m2. Uncertainty in carbon storage estimates was examined with a Monte Carlo approach that addressed major error sources. Ranges predicted with uncertainty analysis in the mean, individual tree, aboveground woody C, and associated standard deviation were 0.35 – 143.6 kg and 0.5 – 1.25 kg, respectively. Later successional phases of woody encroachment had, on average, twice the aboveground carbon relative to earlier phases. Woody encroachment might be more successfully managed and balanced with carbon storage goals by identifying priority areas in earlier phases of encroachment where intensive treatments are most effective.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Geophysical Research: Biogeosciences","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1002/jgrg.20088","usgsCitation":"Sankey, T., Shrestha, R., Sankey, J.B., Hardgree, S., and Strand, E., 2013, Lidar-derived estimate and uncertainty of carbon sink in successional phases of woody encroachment: Journal of Geophysical Research: Biogeosciences, v. 118, no. 3, p. 1144-1155, https://doi.org/10.1002/jgrg.20088.","productDescription":"12 p.","startPage":"1144","endPage":"1155","numberOfPages":"12","ipdsId":"IP-036687","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":282317,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":282290,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/jgrg.20088"}],"country":"United States","state":"Idaho","otherGeospatial":"South Mountain","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -117.0204,42.1646 ], [ -117.0204,43.35 ], [ -115.7938,43.35 ], [ -115.7938,42.1646 ], [ -117.0204,42.1646 ] ] ] } } ] }","volume":"118","issue":"3","noUsgsAuthors":false,"publicationDate":"2013-08-29","publicationStatus":"PW","scienceBaseUri":"53cd6497e4b0b290850ff8cf","contributors":{"authors":[{"text":"Sankey, Temuulen","contributorId":97000,"corporation":false,"usgs":true,"family":"Sankey","given":"Temuulen","affiliations":[],"preferred":false,"id":490180,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shrestha, Rupesh","contributorId":65382,"corporation":false,"usgs":true,"family":"Shrestha","given":"Rupesh","email":"","affiliations":[],"preferred":false,"id":490178,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sankey, Joel B. 0000-0003-3150-4992 jsankey@usgs.gov","orcid":"https://orcid.org/0000-0003-3150-4992","contributorId":3935,"corporation":false,"usgs":true,"family":"Sankey","given":"Joel","email":"jsankey@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":490176,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hardgree, Stuart","contributorId":44830,"corporation":false,"usgs":true,"family":"Hardgree","given":"Stuart","email":"","affiliations":[],"preferred":false,"id":490177,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Strand, Eva","contributorId":82611,"corporation":false,"usgs":false,"family":"Strand","given":"Eva","affiliations":[{"id":6711,"text":"University of Idaho, Moscow ID","active":true,"usgs":false}],"preferred":false,"id":490179,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70048866,"text":"70048866 - 2013 - Mapping risk of avian influenza transmission at the interface of domestic poultry and wild birds","interactions":[],"lastModifiedDate":"2017-08-23T09:25:02","indexId":"70048866","displayToPublicDate":"2013-08-01T13:15:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1704,"text":"Frontiers in Public Health","onlineIssn":"2296-2565","active":true,"publicationSubtype":{"id":10}},"title":"Mapping risk of avian influenza transmission at the interface of domestic poultry and wild birds","docAbstract":"Emergence of avian influenza viruses with high lethality to humans, such as the currently circulating highly pathogenic A(H5N1) (emerged in 1996) and A(H7N9) cause serious concern for the global economic and public health sectors. Understanding the spatial and temporal interface between wild and domestic populations, from which these viruses emerge, is fundamental to taking action. This information, however, is rarely considered in influenza risk models, partly due to a lack of data. We aim to identify areas of high transmission risk between domestic poultry and wild waterfowl in China, the epicenter of both viruses. Two levels of models were developed: one that predicts hotspots of novel virus emergence between domestic and wild birds, and one that incorporates H5N1 risk factors, for which input data exists. Models were produced at 1 and 30 km spatial resolution, and two temporal seasons. Patterns of risk varied between seasons with higher risk in the northeast, central-east, and western regions of China during spring and summer, and in the central and southeastern regions during winter. Monte-Carlo uncertainty analyses indicated varying levels of model confidence, with lowest errors in the densely populated regions of eastern and southern China. Applications and limitations of the models are discussed within.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Frontiers in Public Health","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Frontiers Media","doi":"10.3389/fpubh.2013.00028","usgsCitation":"Prosser, D.J., Hungerford, L.L., Erwin, R.M., Ottinger, M.A., Takekawa, J.Y., and Ellis, E.C., 2013, Mapping risk of avian influenza transmission at the interface of domestic poultry and wild birds: Frontiers in Public Health, v. 1, no. 28, 11 p., https://doi.org/10.3389/fpubh.2013.00028.","productDescription":"11 p.","numberOfPages":"11","ipdsId":"IP-049511","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":473623,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fpubh.2013.00028","text":"Publisher Index Page"},{"id":438783,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9P163QI","text":"USGS data release","linkHelpText":"Spatial models indicating avian influenza transmission risk at the interface of domestic poultry and wild birds in China"},{"id":278983,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":278982,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.3389/fpubh.2013.00028"}],"country":"China","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 73.5,18.15 ], [ 73.5,53.56 ], [ 134.77,53.56 ], [ 134.77,18.15 ], [ 73.5,18.15 ] ] ] } } ] }","volume":"1","issue":"28","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"527e586ce4b02d2057dd95ea","contributors":{"authors":[{"text":"Prosser, Diann J. 0000-0002-5251-1799 dprosser@usgs.gov","orcid":"https://orcid.org/0000-0002-5251-1799","contributorId":2389,"corporation":false,"usgs":true,"family":"Prosser","given":"Diann","email":"dprosser@usgs.gov","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":485770,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hungerford, Laura L.","contributorId":14291,"corporation":false,"usgs":true,"family":"Hungerford","given":"Laura","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":485771,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Erwin, R. Michael 0000-0003-2108-9502","orcid":"https://orcid.org/0000-0003-2108-9502","contributorId":57125,"corporation":false,"usgs":true,"family":"Erwin","given":"R.","email":"","middleInitial":"Michael","affiliations":[],"preferred":false,"id":485773,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ottinger, Mary Ann","contributorId":26422,"corporation":false,"usgs":false,"family":"Ottinger","given":"Mary","email":"","middleInitial":"Ann","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":485772,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Takekawa, John Y. 0000-0003-0217-5907 john_takekawa@usgs.gov","orcid":"https://orcid.org/0000-0003-0217-5907","contributorId":176168,"corporation":false,"usgs":true,"family":"Takekawa","given":"John","email":"john_takekawa@usgs.gov","middleInitial":"Y.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":485769,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ellis, Erle C.","contributorId":67400,"corporation":false,"usgs":true,"family":"Ellis","given":"Erle","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":485774,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70114614,"text":"70114614 - 2013 - Food-web dynamics in a large river discontinuum","interactions":[],"lastModifiedDate":"2014-06-26T13:27:30","indexId":"70114614","displayToPublicDate":"2013-08-01T13:14:50","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1459,"text":"Ecological Monographs","active":true,"publicationSubtype":{"id":10}},"title":"Food-web dynamics in a large river discontinuum","docAbstract":"

Nearly all ecosystems have been altered by human activities, and most communities are now composed of interacting species that have not co-evolved. These changes may modify species interactions, energy and material flows, and food-web stability. Although structural changes to ecosystems have been widely reported, few studies have linked such changes to dynamic food-web attributes and patterns of energy flow. Moreover, there have been few tests of food-web stability theory in highly disturbed and intensely managed freshwater ecosystems. Such synthetic approaches are needed for predicting the future trajectory of ecosystems, including how they may respond to natural or anthropogenic perturbations.

\n
\n

We constructed flow food webs at six locations along a 386-km segment of the Colorado River in Grand Canyon (Arizona, USA) for three years. We characterized food-web structure and production, trophic basis of production, energy efficiencies, and interaction-strength distributions across a spatial gradient of perturbation (i.e., distance from Glen Canyon Dam), as well as before and after an experimental flood. We found strong longitudinal patterns in food-web characteristics that strongly correlated with the spatial position of large tributaries. Above tributaries, food webs were dominated by nonnative New Zealand mudsnails (62% of production) and nonnative rainbow trout (100% of fish production). The simple structure of these food webs led to few dominant energy pathways (diatoms to few invertebrate taxa to rainbow trout), large energy inefficiencies (i.e., <20% of invertebrate production consumed by fishes), and right-skewed interaction-strength distributions, consistent with theoretical instability.

\n
\n

Below large tributaries, invertebrate production declined ∼18-fold, while fish production remained similar to upstream sites and comprised predominately native taxa (80–100% of production). Sites below large tributaries had increasingly reticulate and detritus-based food webs with a higher prevalence of omnivory, as well as interaction strength distributions more typical of theoretically stable food webs (i.e., nearly twofold higher proportion of weak interactions). Consistent with theory, downstream food webs were less responsive to the experimental flood than sites closest to the dam. We show how human-induced shifts to food-web structure can affect energy flow and interaction strengths, and we show that these changes have consequences for food-web function and response to perturbations.

","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ecological Monographs","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Ecological Society of America","doi":"10.1890/12-1727.1","usgsCitation":"Cross, W.F., Baxter, C., Rosi-Marshall, E.J., Hall, R., Kennedy, T., Donner, K.C., Kelly, H., Seegert, S.E., Behn, K.E., and Yard, M., 2013, Food-web dynamics in a large river discontinuum: Ecological Monographs, v. 83, no. 3, p. 311-337, https://doi.org/10.1890/12-1727.1.","productDescription":"27 p.","startPage":"311","endPage":"337","numberOfPages":"27","ipdsId":"IP-041379","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":473624,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1890/12-1727.1","text":"Publisher Index Page"},{"id":289091,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":289090,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1890/12-1727.1"}],"country":"United States","state":"Arizona","otherGeospatial":"Colorado River;Grand Canyon","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -114.3553,35.2411 ], [ -114.3553,37.7707 ], [ -110.8026,37.7707 ], [ -110.8026,35.2411 ], [ -114.3553,35.2411 ] ] ] } } ] }","volume":"83","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53ad40efe4b0729c154181c1","contributors":{"authors":[{"text":"Cross, Wyatt F.","contributorId":70881,"corporation":false,"usgs":true,"family":"Cross","given":"Wyatt","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":495346,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Baxter, Colden V.","contributorId":47334,"corporation":false,"usgs":false,"family":"Baxter","given":"Colden V.","affiliations":[{"id":13656,"text":"Idaho State Univ.","active":true,"usgs":false}],"preferred":false,"id":495344,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rosi-Marshall, Emma J.","contributorId":17722,"corporation":false,"usgs":true,"family":"Rosi-Marshall","given":"Emma","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":495342,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hall, Robert O. Jr.","contributorId":104182,"corporation":false,"usgs":true,"family":"Hall","given":"Robert O.","suffix":"Jr.","affiliations":[],"preferred":false,"id":495349,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kennedy, Theodore A. 0000-0003-3477-3629","orcid":"https://orcid.org/0000-0003-3477-3629","contributorId":50227,"corporation":false,"usgs":true,"family":"Kennedy","given":"Theodore A.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":495345,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Donner, Kevin C.","contributorId":105427,"corporation":false,"usgs":true,"family":"Donner","given":"Kevin","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":495350,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kelly, Holly A. Wellard","contributorId":26974,"corporation":false,"usgs":true,"family":"Kelly","given":"Holly A. Wellard","affiliations":[],"preferred":false,"id":495343,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Seegert, Sarah E.Z.","contributorId":88272,"corporation":false,"usgs":true,"family":"Seegert","given":"Sarah","email":"","middleInitial":"E.Z.","affiliations":[],"preferred":false,"id":495348,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Behn, Kathrine E.","contributorId":83839,"corporation":false,"usgs":true,"family":"Behn","given":"Kathrine","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":495347,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Yard, Michael D. 0000-0002-6580-6027","orcid":"https://orcid.org/0000-0002-6580-6027","contributorId":8577,"corporation":false,"usgs":true,"family":"Yard","given":"Michael D.","affiliations":[],"preferred":false,"id":495341,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70048125,"text":"70048125 - 2013 - On the twenty-first-century wet season projections over the Southeastern United States","interactions":[],"lastModifiedDate":"2013-09-12T13:14:13","indexId":"70048125","displayToPublicDate":"2013-08-01T13:02:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3242,"text":"Regional Environmental Change","active":true,"publicationSubtype":{"id":10}},"title":"On the twenty-first-century wet season projections over the Southeastern United States","docAbstract":"This paper reconciles the difference in the projections of the wet season over the Southeastern United States (SEUS) from a global climate model (the Community Climate System Model Version 3 [CCSM3]) and from a regional climate model (the Regional Spectral Model [RSM]) nested in the CCSM3. The CCSM3 projects a dipole in the summer precipitation anomaly: peninsular Florida dries in the future climate, and the remainder of the SEUS region becomes wetter. The RSM forced with CCSM3 projects a universal drying of the SEUS in the late twenty-first century relative to the corresponding twentieth-century summer. The CCSM3 pattern is attributed to the “upped-ante” mechanism, whereby the atmospheric boundary layer moisture required for convection increases in a warm, statically stable global tropical environment. This criterion becomes harder to meet along convective margins, which include peninsular Florida, resulting in its drying. CCSM3 also projects a southwestward expansion of the North Atlantic subtropical high that leads to further stabilizing of the atmosphere above Florida, inhibiting convection. The RSM, because of its high (10-km grid) resolution, simulates diurnal variations in summer rainfall over SEUS reasonably well. The RSM improves upon CCSM3 through the RSM’s depiction of the diurnal variance of precipitation, which according to observations accounts for up to 40 % of total seasonal precipitation variance. In the future climate, the RSM projects a significant reduction in the diurnal variability of convection. The reduction is attributed to large-scale stabilization of the atmosphere in the CCSM3 projections.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Regional Environmental Change","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","doi":"10.1007/s10113-013-0477-8","usgsCitation":"Selman, C., Misra, V., Stefanova, L., Dinapoli, S., and Smith, T.J., 2013, On the twenty-first-century wet season projections over the Southeastern United States: Regional Environmental Change, v. 13, no. suppl. 1, p. 153-164, https://doi.org/10.1007/s10113-013-0477-8.","productDescription":"12 p.","startPage":"153","endPage":"164","numberOfPages":"12","ipdsId":"IP-038643","costCenters":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"links":[{"id":277517,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":277516,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s10113-013-0477-8"}],"country":"United States","state":"Alabama;Arkansas;Florida;Georgia;Kentucky;Louisiana;Mississippi;Missouri;North Carolina;South Carolina;Tennessee;Virginia","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -91.0,24.0 ], [ -91.0,37.0 ], [ -76.0,37.0 ], [ -76.0,24.0 ], [ -91.0,24.0 ] ] ] } } ] }","volume":"13","issue":"suppl. 1","noUsgsAuthors":false,"publicationDate":"2013-05-22","publicationStatus":"PW","scienceBaseUri":"5232e262e4b0b7ac626cfa53","contributors":{"authors":[{"text":"Selman, Christopher","contributorId":101549,"corporation":false,"usgs":true,"family":"Selman","given":"Christopher","email":"","affiliations":[],"preferred":false,"id":483801,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Misra, Vasu","contributorId":89048,"corporation":false,"usgs":true,"family":"Misra","given":"Vasu","email":"","affiliations":[],"preferred":false,"id":483800,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stefanova, Lydia","contributorId":48300,"corporation":false,"usgs":true,"family":"Stefanova","given":"Lydia","email":"","affiliations":[],"preferred":false,"id":483799,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dinapoli, Steven","contributorId":103958,"corporation":false,"usgs":true,"family":"Dinapoli","given":"Steven","email":"","affiliations":[],"preferred":false,"id":483802,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Smith, Thomas J. III tom_j_smith@usgs.gov","contributorId":1615,"corporation":false,"usgs":true,"family":"Smith","given":"Thomas","suffix":"III","email":"tom_j_smith@usgs.gov","middleInitial":"J.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":false,"id":483798,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70047340,"text":"70047340 - 2013 - Comparison of age distributions estimated from environmental tracers by using binary-dilution and numerical models of fractured and folded karst: Shenandoah Valley of Virginia and West Virginia, USA","interactions":[],"lastModifiedDate":"2018-03-21T15:11:21","indexId":"70047340","displayToPublicDate":"2013-08-01T11:47:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1923,"text":"Hydrogeology Journal","active":true,"publicationSubtype":{"id":10}},"title":"Comparison of age distributions estimated from environmental tracers by using binary-dilution and numerical models of fractured and folded karst: Shenandoah Valley of Virginia and West Virginia, USA","docAbstract":"Measured concentrations of environmental tracers in spring discharge from a karst aquifer in the Shenandoah Valley, USA, were used to refine a numerical groundwater flow model. The karst aquifer is folded and faulted carbonate bedrock dominated by diffuse flow along fractures. The numerical model represented bedrock structure and discrete features (fault zones and springs). Concentrations of 3H, 3He, 4He, and CFC-113 in spring discharge were interpreted as binary dilutions of young (0–8 years) water and old (tracer-free) water. Simulated mixtures of groundwater are derived from young water flowing along shallow paths, with the addition of old water flowing along deeper paths through the model domain that discharge to springs along fault zones. The simulated median age of young water discharged from springs (5.7 years) is slightly older than the median age estimated from 3H/3He data (4.4 years). The numerical model predicted a fraction of old water in spring discharge (0.07) that was half that determined by the binary-dilution model using the 3H/3He apparent age and 3H and CFC-113 data (0.14). This difference suggests that faults and lineaments are more numerous or extensive than those mapped and included in the numerical model.","language":"English","publisher":"Springer","doi":"10.1007/s10040-013-0997-9","usgsCitation":"Yager, R.M., Plummer, N., Kauffman, L.J., Doctor, D.H., Nelms, D.L., and Schlosser, P., 2013, Comparison of age distributions estimated from environmental tracers by using binary-dilution and numerical models of fractured and folded karst: Shenandoah Valley of Virginia and West Virginia, USA: Hydrogeology Journal, v. 21, no. 6, p. 1193-1217, https://doi.org/10.1007/s10040-013-0997-9.","productDescription":"25 p.","startPage":"1193","endPage":"1217","numberOfPages":"25","ipdsId":"IP-042757","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":275681,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":275663,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/DOI 10.1007/s10040-013-0997-9"}],"country":"United States","state":"Virginia;West Virginia","otherGeospatial":"Shenandoah Valley","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -80.33,37.4237 ], [ -80.33,39.6857 ], [ -77.7252,39.6857 ], [ -77.7252,37.4237 ], [ -80.33,37.4237 ] ] ] } } ] }","volume":"21","issue":"6","noUsgsAuthors":false,"publicationDate":"2013-06-28","publicationStatus":"PW","scienceBaseUri":"51fb7554e4b04b00e3d78567","contributors":{"authors":[{"text":"Yager, Richard M. 0000-0001-7725-1148 ryager@usgs.gov","orcid":"https://orcid.org/0000-0001-7725-1148","contributorId":950,"corporation":false,"usgs":true,"family":"Yager","given":"Richard","email":"ryager@usgs.gov","middleInitial":"M.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true},{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":481743,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Plummer, Niel 0000-0002-4020-1013 nplummer@usgs.gov","orcid":"https://orcid.org/0000-0002-4020-1013","contributorId":190100,"corporation":false,"usgs":true,"family":"Plummer","given":"Niel","email":"nplummer@usgs.gov","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":481747,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kauffman, Leon J. 0000-0003-4564-0362 lkauff@usgs.gov","orcid":"https://orcid.org/0000-0003-4564-0362","contributorId":1094,"corporation":false,"usgs":true,"family":"Kauffman","given":"Leon","email":"lkauff@usgs.gov","middleInitial":"J.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":481744,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Doctor, Daniel H. 0000-0002-8338-9722 dhdoctor@usgs.gov","orcid":"https://orcid.org/0000-0002-8338-9722","contributorId":2037,"corporation":false,"usgs":true,"family":"Doctor","given":"Daniel","email":"dhdoctor@usgs.gov","middleInitial":"H.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":481746,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nelms, David L. 0000-0001-5747-642X dlnelms@usgs.gov","orcid":"https://orcid.org/0000-0001-5747-642X","contributorId":1892,"corporation":false,"usgs":true,"family":"Nelms","given":"David","email":"dlnelms@usgs.gov","middleInitial":"L.","affiliations":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true},{"id":37759,"text":"VA/WV Water Science Center","active":true,"usgs":true}],"preferred":true,"id":481745,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schlosser, Peter","contributorId":50936,"corporation":false,"usgs":true,"family":"Schlosser","given":"Peter","email":"","affiliations":[],"preferred":false,"id":481748,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70047679,"text":"70047679 - 2013 - On the insignificance of Herschel's sunspot correlation","interactions":[],"lastModifiedDate":"2018-10-26T14:16:34","indexId":"70047679","displayToPublicDate":"2013-08-01T11:24:00","publicationYear":"2013","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":"On the insignificance of Herschel's sunspot correlation","docAbstract":"We examine William Herschel's hypothesis that solar-cycle variation of the Sun's irradiance has a modulating effect on the Earth's climate and that this is, specifically, manifested as an anticorrelation between sunspot number and the market price of wheat. Since Herschel first proposed his hypothesis in 1801, it has been regarded with both interest and skepticism. Recently, reports have been published that either support Herschel's hypothesis or rely on its validity. As a test of Herschel's hypothesis, we seek to reject a null hypothesis of a statistically random correlation between historical sunspot numbers, wheat prices in London and the United States, and wheat farm yields in the United States. We employ binary-correlation, Pearson-correlation, and frequency-domain methods. We test our methods using a historical geomagnetic activity index, well known to be causally correlated with sunspot number. As expected, the measured correlation between sunspot number and geomagnetic activity would be an unlikely realization of random data; the correlation is “statistically significant.” On the other hand, measured correlations between sunspot number and wheat price and wheat yield data would be very likely realizations of random data; these correlations are “insignificant.” Therefore, Herschel's hypothesis must be regarded with skepticism. We compare and contrast our results with those of other researchers. We discuss procedures for evaluating hypotheses that are formulated from historical data.","language":"English","publisher":"Wiley","doi":"10.1002/grl.50846","usgsCitation":"Love, J.J., 2013, On the insignificance of Herschel's sunspot correlation: Geophysical Research Letters, v. 40, no. 16, p. 4171-4176, https://doi.org/10.1002/grl.50846.","productDescription":"6 p.","startPage":"4171","endPage":"4176","numberOfPages":"6","ipdsId":"IP-050651","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":313,"text":"Geomagnetism Program","active":false,"usgs":true}],"links":[{"id":280736,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":276748,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/grl.50846"}],"volume":"40","issue":"16","noUsgsAuthors":false,"publicationDate":"2013-08-27","publicationStatus":"PW","scienceBaseUri":"53cd69e7e4b0b29085102e8d","contributors":{"authors":[{"text":"Love, Jeffrey J. 0000-0002-3324-0348 jlove@usgs.gov","orcid":"https://orcid.org/0000-0002-3324-0348","contributorId":760,"corporation":false,"usgs":true,"family":"Love","given":"Jeffrey","email":"jlove@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":482703,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70048423,"text":"70048423 - 2013 - Quantifying wetland–aquifer interactions in a humid subtropical climate region: An integrated approach","interactions":[],"lastModifiedDate":"2013-09-26T10:38:34","indexId":"70048423","displayToPublicDate":"2013-08-01T10:24:14","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Quantifying wetland–aquifer interactions in a humid subtropical climate region: An integrated approach","docAbstract":"Wetlands are widely recognized as sentinels of global climate change. Long-term monitoring data combined with process-based modeling has the potential to shed light on key processes and how they change over time. This paper reports the development and application of a simple water balance model based on long-term climate, soil, vegetation and hydrological dynamics to quantify groundwater–surface water (GW–SW) interactions at the Norman landfill research site in Oklahoma, USA. Our integrated approach involved model evaluation by means of the following independent measurements: (a) groundwater inflow calculation using stable isotopes of oxygen and hydrogen (16O, 18O, 1H, 2H); (b) seepage flux measurements in the wetland hyporheic sediment; and (c) pan evaporation measurements on land and in the wetland. The integrated approach was useful for identifying the dominant hydrological processes at the site, including recharge and subsurface flows. Simulated recharge compared well with estimates obtained using isotope methods from previous studies and allowed us to identify specific annual signatures of this important process during the period of study (1997–2007). Similarly, observations of groundwater inflow and outflow rates to and from the wetland using seepage meters and isotope methods were found to be in good agreement with simulation results. Results indicate that subsurface flow components in the system are seasonal and readily respond to rainfall events. The wetland water balance is dominated by local groundwater inputs and regional groundwater flow contributes little to the overall water balance.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Hydrology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2013.06.022","usgsCitation":"Mendoza-Sanchez, I., Phanikumar, M., Niu, J., Masoner, J.R., Cozzarelli, I.M., and McGuire, J., 2013, Quantifying wetland–aquifer interactions in a humid subtropical climate region: An integrated approach: Journal of Hydrology, v. 498, p. 237-253, https://doi.org/10.1016/j.jhydrol.2013.06.022.","productDescription":"17 p.","startPage":"237","endPage":"253","ipdsId":"IP-014582","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true}],"links":[{"id":278116,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":278115,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.jhydrol.2013.06.022"}],"country":"United States","state":"Oklahoma","city":"Norman","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -97.55,35.14 ], [ -97.55,35.35 ], [ -97.18,35.35 ], [ -97.18,35.14 ], [ -97.55,35.14 ] ] ] } } ] }","volume":"498","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52455769e4b0b3d37307e1b4","contributors":{"authors":[{"text":"Mendoza-Sanchez, Itza","contributorId":20246,"corporation":false,"usgs":true,"family":"Mendoza-Sanchez","given":"Itza","email":"","affiliations":[],"preferred":false,"id":484612,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Phanikumar, Mantha S.","contributorId":17888,"corporation":false,"usgs":true,"family":"Phanikumar","given":"Mantha S.","affiliations":[],"preferred":false,"id":484611,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Niu, Jie","contributorId":30535,"corporation":false,"usgs":true,"family":"Niu","given":"Jie","affiliations":[],"preferred":false,"id":484613,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Masoner, Jason R. 0000-0002-4829-6379 jmasoner@usgs.gov","orcid":"https://orcid.org/0000-0002-4829-6379","contributorId":3193,"corporation":false,"usgs":true,"family":"Masoner","given":"Jason","email":"jmasoner@usgs.gov","middleInitial":"R.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true}],"preferred":true,"id":484610,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cozzarelli, Isabelle M. 0000-0002-5123-1007 icozzare@usgs.gov","orcid":"https://orcid.org/0000-0002-5123-1007","contributorId":1693,"corporation":false,"usgs":true,"family":"Cozzarelli","given":"Isabelle","email":"icozzare@usgs.gov","middleInitial":"M.","affiliations":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":484609,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McGuire, Jennifer T.","contributorId":53979,"corporation":false,"usgs":true,"family":"McGuire","given":"Jennifer T.","affiliations":[],"preferred":false,"id":484614,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70048367,"text":"70048367 - 2013 - Climate downscaling effects on predictive ecological models: a case study for threatened and endangered vertebrates in the southeastern United States","interactions":[],"lastModifiedDate":"2013-09-24T10:20:54","indexId":"70048367","displayToPublicDate":"2013-08-01T10:11:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3242,"text":"Regional Environmental Change","active":true,"publicationSubtype":{"id":10}},"title":"Climate downscaling effects on predictive ecological models: a case study for threatened and endangered vertebrates in the southeastern United States","docAbstract":"High-resolution (downscaled) projections of future climate conditions are critical inputs to a wide variety of ecological and socioeconomic models and are created using numerous different approaches. Here, we conduct a sensitivity analysis of spatial predictions from climate envelope models for threatened and endangered vertebrates in the southeastern United States to determine whether two different downscaling approaches (with and without the use of a regional climate model) affect climate envelope model predictions when all other sources of variation are held constant. We found that prediction maps differed spatially between downscaling approaches and that the variation attributable to downscaling technique was comparable to variation between maps generated using different general circulation models (GCMs). Precipitation variables tended to show greater discrepancies between downscaling techniques than temperature variables, and for one GCM, there was evidence that more poorly resolved precipitation variables contributed relatively more to model uncertainty than more well-resolved variables. Our work suggests that ecological modelers requiring high-resolution climate projections should carefully consider the type of downscaling applied to the climate projections prior to their use in predictive ecological modeling. The uncertainty associated with alternative downscaling methods may rival that of other, more widely appreciated sources of variation, such as the general circulation model or emissions scenario with which future climate projections are created.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Regional Environmental Change","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","doi":"10.1007/s10113-012-0389-z","usgsCitation":"Bucklin, D.N., Watling, J., Speroterra, C., Brandt, L., Mazzotti, F., and Romañach, S., 2013, Climate downscaling effects on predictive ecological models: a case study for threatened and endangered vertebrates in the southeastern United States: Regional Environmental Change, v. 13, no. 1 Suppl., p. 57-68, https://doi.org/10.1007/s10113-012-0389-z.","productDescription":"12 p.","startPage":"57","endPage":"68","numberOfPages":"12","ipdsId":"IP-040975","costCenters":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"links":[{"id":278024,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s10113-012-0389-z"},{"id":278025,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alabama;Florida;Georgia;Mississippi;South Carolina","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -90.0,25.0 ], [ -90.0,35.0 ], [ -75.0,35.0 ], [ -75.0,25.0 ], [ -90.0,25.0 ] ] ] } } ] }","volume":"13","issue":"1 Suppl.","noUsgsAuthors":false,"publicationDate":"2012-12-27","publicationStatus":"PW","scienceBaseUri":"5242b462e4b096ee624641dd","contributors":{"authors":[{"text":"Bucklin, David N.","contributorId":44812,"corporation":false,"usgs":true,"family":"Bucklin","given":"David","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":484443,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Watling, James I.","contributorId":101963,"corporation":false,"usgs":true,"family":"Watling","given":"James I.","affiliations":[],"preferred":false,"id":484447,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Speroterra, Carolina","contributorId":54089,"corporation":false,"usgs":true,"family":"Speroterra","given":"Carolina","affiliations":[],"preferred":false,"id":484444,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brandt, Laura A.","contributorId":18608,"corporation":false,"usgs":false,"family":"Brandt","given":"Laura A.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":484442,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mazzotti, Frank J.","contributorId":100018,"corporation":false,"usgs":false,"family":"Mazzotti","given":"Frank J.","affiliations":[{"id":12557,"text":"University of Florida, FLREC","active":true,"usgs":false}],"preferred":false,"id":484446,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Romañach, Stephanie S.","contributorId":76064,"corporation":false,"usgs":true,"family":"Romañach","given":"Stephanie S.","affiliations":[],"preferred":false,"id":484445,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70045907,"text":"70045907 - 2013 - Modelling interactions of toxicants and density dependence in wildlife populations","interactions":[],"lastModifiedDate":"2014-02-19T09:38:52","indexId":"70045907","displayToPublicDate":"2013-08-01T10:01:00","publicationYear":"2013","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":"Modelling interactions of toxicants and density dependence in wildlife populations","docAbstract":"

1. A major challenge in the conservation of threatened and endangered species is to predict population decline and design appropriate recovery measures. However, anthropogenic impacts on wildlife populations are notoriously difficult to predict due to potentially nonlinear responses and interactions with natural ecological processes like density dependence.

\n
\n

2. Here, we incorporated both density dependence and anthropogenic stressors in a stage-based matrix population model and parameterized it for a density-dependent population of peregrine falcons Falco peregrinus exposed to two anthropogenic toxicants [dichlorodiphenyldichloroethylene (DDE) and polybrominated diphenyl ethers (PBDEs)]. Log-logistic exposure–response relationships were used to translate toxicant concentrations in peregrine falcon eggs to effects on fecundity. Density dependence was modelled as the probability of a nonbreeding bird acquiring a breeding territory as a function of the current number of breeders.

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\n

3. The equilibrium size of the population, as represented by the number of breeders, responded nonlinearly to increasing toxicant concentrations, showing a gradual decrease followed by a relatively steep decline. Initially, toxicant-induced reductions in population size were mitigated by an alleviation of the density limitation, that is, an increasing probability of territory acquisition. Once population density was no longer limiting, the toxicant impacts were no longer buffered by an increasing proportion of nonbreeders shifting to the breeding stage, resulting in a strong decrease in the equilibrium number of breeders.

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4. Median critical exposure concentrations, that is, median toxicant concentrations in eggs corresponding with an equilibrium population size of zero, were 33 and 46 μg g−1 fresh weight for DDE and PBDEs, respectively.

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\n

5. Synthesis and applications. Our modelling results showed that particular life stages of a density-limited population may be relatively insensitive to toxicant impacts until a critical threshold is crossed. In our study population, toxicant-induced changes were observed in the equilibrium number of nonbreeding rather than breeding birds, suggesting that monitoring efforts including both life stages are needed to timely detect population declines. Further, by combining quantitative exposure–response relationships with a wildlife demographic model, we provided a method to quantify critical toxicant thresholds for wildlife population persistence.

","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Applied Ecology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.1111/1365-2664.12142","usgsCitation":"Schipper, A.M., Hendriks, H.W., Kauffman, M., Hendriks, A.J., and Huijbregts, M.A., 2013, Modelling interactions of toxicants and density dependence in wildlife populations: Journal of Applied Ecology, v. 50, no. 6, p. 1469-1478, https://doi.org/10.1111/1365-2664.12142.","productDescription":"10 p.","startPage":"1469","endPage":"1478","onlineOnly":"Y","ipdsId":"IP-042612","costCenters":[],"links":[{"id":473627,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2664.12142","text":"Publisher Index Page"},{"id":282517,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":282516,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/1365-2664.12142"}],"country":"United States","state":"California","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.41,32.53 ], [ -124.41,42.01 ], [ -114.13,42.01 ], [ -114.13,32.53 ], [ -124.41,32.53 ] ] ] } } ] }","volume":"50","issue":"6","noUsgsAuthors":false,"publicationDate":"2013-08-08","publicationStatus":"PW","scienceBaseUri":"53cd67f4e4b0b29085101b83","contributors":{"authors":[{"text":"Schipper, Aafke M.","contributorId":76645,"corporation":false,"usgs":true,"family":"Schipper","given":"Aafke","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":478520,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hendriks, Harrie W.M.","contributorId":94210,"corporation":false,"usgs":true,"family":"Hendriks","given":"Harrie","email":"","middleInitial":"W.M.","affiliations":[],"preferred":false,"id":478521,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kauffman, Matthew J. 0000-0003-0127-3900 mkauffman@usgs.gov","orcid":"https://orcid.org/0000-0003-0127-3900","contributorId":2963,"corporation":false,"usgs":true,"family":"Kauffman","given":"Matthew J.","email":"mkauffman@usgs.gov","affiliations":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"preferred":false,"id":478517,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hendriks, A. Jan","contributorId":18673,"corporation":false,"usgs":true,"family":"Hendriks","given":"A.","email":"","middleInitial":"Jan","affiliations":[],"preferred":false,"id":478518,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Huijbregts, Mark A.J.","contributorId":68215,"corporation":false,"usgs":true,"family":"Huijbregts","given":"Mark","email":"","middleInitial":"A.J.","affiliations":[],"preferred":false,"id":478519,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70093728,"text":"70093728 - 2013 - Phenology-based, remote sensing of post-burn disturbance windows in rangelands","interactions":[],"lastModifiedDate":"2014-02-12T09:32:09","indexId":"70093728","displayToPublicDate":"2013-08-01T08:57:51","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Phenology-based, remote sensing of post-burn disturbance windows in rangelands","docAbstract":"Wildland fire activity has increased in many parts of the world in recent decades. Ecological disturbance by fire can accelerate ecosystem degradation processes such as erosion due to combustion of vegetation that otherwise provides protective cover to the soil surface. This study employed a novel ecological indicator based on remote sensing of vegetation greenness dynamics (phenology) to estimate variability in the window of time between fire and the reemergence of green vegetation. The indicator was applied as a proxy for short-term, post-fire disturbance windows in rangelands; where a disturbance window is defined as the time required for an ecological or geomorphic process that is altered to return to pre-disturbance levels. We examined variability in the indicator determined for time series of MODIS and AVHRR NDVI remote sensing data for a database of ∼100 historical wildland fires, with associated post-fire reseeding treatments, that burned 1990–2003 in cold desert shrub steppe of the Great Basin and Columbia Plateau of the western USA. The indicator-based estimates of disturbance window length were examined relative to the day of the year that fires burned and seeding treatments to consider effects of contemporary variability in fire regime and management activities in this environment. A key finding was that contemporary changes of increased length of the annual fire season could have indirect effects on ecosystem degradation, as early season fires appeared to result in longer time that soils remained relatively bare of the protective cover of vegetation after fires. Also important was that reemergence of vegetation did not occur more quickly after fire in sites treated with post-fire seeding, which is a strategy commonly employed to accelerate post-fire vegetation recovery and stabilize soil. Future work with the indicator could examine other ecological factors that are dynamic in space and time following disturbance – such as nutrient cycling, carbon storage, microbial community composition, or soil hydrology – as a function of disturbance windows, possibly using simulation modeling and historical wildfire information.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ecological Indicators","largerWorkSubtype":{"id":10,"text":"Journal Article"},"publisher":"Elsevier","doi":"10.1016/j.ecolind.2013.02.004","usgsCitation":"Sankeya, J.B., Wallace, C., and Ravi, S., 2013, Phenology-based, remote sensing of post-burn disturbance windows in rangelands: Ecological Indicators, v. 30, p. 35-44, https://doi.org/10.1016/j.ecolind.2013.02.004.","productDescription":"10 p.","startPage":"35","endPage":"44","ipdsId":"IP-043510","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":282293,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":282292,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.ecolind.2013.02.004"}],"country":"United States","state":"California;Idaho;Nevada;Oregon;Utah;Washington","otherGeospatial":"Great Basin;Columbia Plateau","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -120.11,34.92 ], [ -120.11,46.83 ], [ -114.13,46.83 ], [ -114.13,34.92 ], [ -120.11,34.92 ] ] ] } } ] }","volume":"30","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd6b1fe4b0b29085103b13","chorus":{"doi":"10.1016/j.ecolind.2013.02.004","url":"http://dx.doi.org/10.1016/j.ecolind.2013.02.004","publisher":"Elsevier BV","authors":"Sankey Joel B., Wallace Cynthia S.A., Ravi Sujith","journalName":"Ecological Indicators","publicationDate":"7/2013","auditedOn":"11/1/2014"},"contributors":{"authors":[{"text":"Sankeya, Joel B.","contributorId":86687,"corporation":false,"usgs":true,"family":"Sankeya","given":"Joel","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":490183,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wallace, Cynthia S.A.","contributorId":70487,"corporation":false,"usgs":true,"family":"Wallace","given":"Cynthia S.A.","affiliations":[],"preferred":false,"id":490182,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ravi, Sujith","contributorId":40844,"corporation":false,"usgs":true,"family":"Ravi","given":"Sujith","affiliations":[],"preferred":false,"id":490181,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70048420,"text":"70048420 - 2013 - Geologic effects on groundwater salinity and discharge into an estuary","interactions":[],"lastModifiedDate":"2018-03-05T16:17:18","indexId":"70048420","displayToPublicDate":"2013-08-01T08:40:39","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Geologic effects on groundwater salinity and discharge into an estuary","docAbstract":"

Submarine groundwater discharge (SGD) can be an important pathway for transport of nutrients and contaminants to estuaries. A better understanding of the geologic and hydrologic controls on these fluxes is critical for their estimation and management. We examined geologic features, porewater salinity, and SGD rates and patterns at an estuarine study site. Seismic data showed the existence of paleovalleys infilled with estuarine mud and peat that extend hundreds of meters offshore. A low-salinity groundwater plume beneath this low-permeability fill was mapped with continuous resistivity profiling. Extensive direct SGD measurements with seepage meters (n = 551) showed fresh groundwater discharge patterns that correlated well with shallow porewater salinity and the hydrogeophysical framework. Small-scale variability in fresh and saline discharge indicates influence of meter-scale geologic heterogeneity, while site-scale discharge patterns are evidence of the influence of the paleovalley feature. Beneath the paleovalley fill, fresh groundwater flows offshore and mixes with saltwater before discharging along paleovalley flanks. On the adjacent drowned interfluve where low-permeability fill is absent, fresh groundwater discharge is focused at the shoreline. Shallow saltwater exchange was greatest across sandy sediments and where fresh SGD was low. The geologic control of groundwater flowpaths and discharge salinity demonstrated in this work are likely to affect geochemical reactions and the chemical loads delivered by SGD to coastal surface waters. Because similar processes are likely to exist in other estuaries where drowned paleovalleys commonly cross modern shorelines, the existence and implications of complex hydrogeology are important considerations for studies of groundwater fluxes and related management decisions.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2013.05.049","usgsCitation":"Russonielloa, C.J., Fernandeza, C., Bratton, J.F., Banaszakc, J.F., Krantzc, D.E., Andresd, S., Konikow, L.F., and Michaela, H.A., 2013, Geologic effects on groundwater salinity and discharge into an estuary: Journal of Hydrology, v. 498, p. 1-12, https://doi.org/10.1016/j.jhydrol.2013.05.049.","productDescription":"12 p.","startPage":"1","endPage":"12","ipdsId":"IP-044951","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":278179,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Delaware","otherGeospatial":"Indian River Bay","volume":"498","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5246e918e4b035b7f35addd0","contributors":{"authors":[{"text":"Russonielloa, Christopher J.","contributorId":92963,"corporation":false,"usgs":true,"family":"Russonielloa","given":"Christopher","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":484575,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fernandeza, Cristina","contributorId":94963,"corporation":false,"usgs":true,"family":"Fernandeza","given":"Cristina","email":"","affiliations":[],"preferred":false,"id":484576,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bratton, John F. 0000-0003-0376-4981 jbratton@usgs.gov","orcid":"https://orcid.org/0000-0003-0376-4981","contributorId":92757,"corporation":false,"usgs":true,"family":"Bratton","given":"John","email":"jbratton@usgs.gov","middleInitial":"F.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":484571,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Banaszakc, Joel F.","contributorId":102369,"corporation":false,"usgs":true,"family":"Banaszakc","given":"Joel","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":484578,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Krantzc, David E.","contributorId":84259,"corporation":false,"usgs":true,"family":"Krantzc","given":"David","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":484573,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Andresd, Scott","contributorId":97413,"corporation":false,"usgs":true,"family":"Andresd","given":"Scott","email":"","affiliations":[],"preferred":false,"id":484577,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Konikow, Leonard F. 0000-0002-0940-3856 lkonikow@usgs.gov","orcid":"https://orcid.org/0000-0002-0940-3856","contributorId":158,"corporation":false,"usgs":true,"family":"Konikow","given":"Leonard","email":"lkonikow@usgs.gov","middleInitial":"F.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":484574,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Michaela, Holly A.","contributorId":57357,"corporation":false,"usgs":true,"family":"Michaela","given":"Holly","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":484572,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70047986,"text":"70047986 - 2013 - Sex difference in polychlorinated biphenyl concentrations of burbot Lota lota from Lake Erie","interactions":[],"lastModifiedDate":"2013-10-30T14:18:54","indexId":"70047986","displayToPublicDate":"2013-08-01T08:22:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":887,"text":"Archives of Environmental Contamination and Toxicology","active":true,"publicationSubtype":{"id":10}},"title":"Sex difference in polychlorinated biphenyl concentrations of burbot Lota lota from Lake Erie","docAbstract":"Whole-fish polychlorinated biphenyl (PCB) concentrations were determined for 25 female and 25 male burbot Lota lota from Lake Erie. Bioenergetics modeling was used to investigate whether the sex difference in growth rate resulted in a difference in gross growth efficiency (GGE) between the sexes. For ages 6–13 years, male burbot averaged 28 % greater PCB concentrations than female burbot. The sex difference in PCB concentrations widened for ages 14–17 years, with male burbot having, on average, 71 % greater PCB concentrations than female burbot. Bioenergetics modeling results showed that the faster growth rate exhibited by female burbot did not lead to greater GGE in female individuals of the younger burbot and that the faster growth by female fish led to female GGE being only 2 % greater than male GGE in older burbot. Although our bioenergetics modeling could not explain the observed sex difference in PCB concentrations, we concluded that a sex difference in GGE was the most plausible explanation for the sex difference in PCB concentrations of burbot ages 6–13 years. Not only are male fish likely to be more active than female fish, but the resting metabolic rate of male fish may be greater than that of female fish. We also concluded that the widening of the sex difference in PCB concentrations for the older burbot may be due to many of the older male burbot spending a substantial amount of time in the vicinity of mouths of rivers contaminated with PCBs.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Archives of Environmental Contamination and Toxicology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","doi":"10.1007/s00244-013-9901-9","usgsCitation":"Madenjian, C., Stapanian, M., Rediske, R., and O’Keefe, J.P., 2013, Sex difference in polychlorinated biphenyl concentrations of burbot Lota lota from Lake Erie: Archives of Environmental Contamination and Toxicology, v. 65, no. 2, p. 300-308, https://doi.org/10.1007/s00244-013-9901-9.","productDescription":"9 p.","startPage":"300","endPage":"308","ipdsId":"IP-049237","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":277303,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":277302,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s00244-013-9901-9"}],"country":"United States","state":"New York;Ohio;Pennsylvania","otherGeospatial":"Lake Erie","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -81,41.11 ], [ -81,42.15 ], [ -78.13,42.15 ], [ -78.13,41.11 ], [ -81,41.11 ] ] ] } } ] }","volume":"65","issue":"2","noUsgsAuthors":false,"publicationDate":"2013-04-17","publicationStatus":"PW","scienceBaseUri":"5229a7e8e4b0f33a3916778a","contributors":{"authors":[{"text":"Madenjian, C.P.","contributorId":64175,"corporation":false,"usgs":true,"family":"Madenjian","given":"C.P.","affiliations":[],"preferred":false,"id":483510,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stapanian, M.A.","contributorId":65437,"corporation":false,"usgs":true,"family":"Stapanian","given":"M.A.","email":"","affiliations":[],"preferred":false,"id":483511,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rediske, R.R.","contributorId":47148,"corporation":false,"usgs":true,"family":"Rediske","given":"R.R.","affiliations":[],"preferred":false,"id":483508,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"O’Keefe, J. P.","contributorId":52478,"corporation":false,"usgs":true,"family":"O’Keefe","given":"J.","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":483509,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70193597,"text":"70193597 - 2013 - Constraints on magma processes, subsurface conditions, and total volatile flux at Bezymianny Volcano in 2007–2010 from direct and remote volcanic gas measurements","interactions":[],"lastModifiedDate":"2019-12-21T08:50:42","indexId":"70193597","displayToPublicDate":"2013-08-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2499,"text":"Journal of Volcanology and Geothermal Research","active":true,"publicationSubtype":{"id":10}},"title":"Constraints on magma processes, subsurface conditions, and total volatile flux at Bezymianny Volcano in 2007–2010 from direct and remote volcanic gas measurements","docAbstract":"

Direct and remote measurements of volcanic gas composition, SO2 flux, and eruptive SO2 mass from Bezymianny Volcano were acquired between July 2007 and July 2010. Chemical composition of fumarolic gases, plume SO2 flux from ground and air-based ultraviolet remote sensing (FLYSPEC), and eruptive SO2 mass from Ozone Monitoring Instrument (OMI) satellite observations were used along with eruption timing to elucidate magma processes and subsurface conditions, and to constrain total volatile flux. Bezymianny Volcano had five explosive magmatic eruptions between May 2007 and June 2010. The most complete volcanic gas datasets were acquired for the October 2007, December 2009, and May 2010 eruptions. Gas measurements collected prior to the October 2007 eruption have a relatively high ratio of H2O/CO2 (81.2), a moderate ratio of CO2/S (5.47), and a low ratio of S/HCl (0.338), along with moderate SO2 and CO2 fluxes of 280 and 980 t/d, respectively, and high H2O and HCl fluxes of ~ 45,000 and ~ 440 t/d, respectively. These results suggest degassing of shallow magma (consistent with observations of lava extrusion) along with potential minor degassing of a deeper magma source. Gas measurements collected prior to the December 2009 eruption are characterized by relatively low H2O/CO2 (4.13), moderate CO2/S (6.84), and high S/HCl (18.7) ratios, along with moderate SO2 and CO2 fluxes of ~ 220 and ~ 1000 t/d, respectively, and low H2O and HCl fluxes of ~ 1700 and ~ 7 t/d, respectively. These trends are consistent with degassing of a deeper magma source. Fumarole samples collected ~ 1.5 months following the May 2010 eruption are characterized by high H2O/CO2 (63.0), low CO2/S (0.986), and moderate S/HCl (6.09) ratios. These data are consistent with degassing of a shallow, volatile-rich magma source, likely related to the May eruption. Passive and eruptive SO2 measurements are used to calculate a total annual SO2 mass of 109 kt emitted in 2007, with passive emissions comprising ~ 87–95% of the total. Total annual volatile masses for the study period are estimated to range from 1.1 × 106 to 18 × 106 t/year. Annual CO2 masses are ~ 8 to 40 times larger than can be explained by degassing of dissolved CO2 within eruptive magma, suggesting that the eruptive magma contained a significant quantity of exsolved volatiles sourced either from the eruptive melt or unerupted magma at depth. Variable total volatile fluxes ranging from ~ 3000 t/d in 2009 to ~ 49,000 t/d in 2007 are attributed to variations in the depth of gas exsolution and separation from the melt under open-system degassing conditions. We propose that exsolved volatiles are quickly transported to the surface from ascending magma via permeable flow through a bubble and/or fracture network within the conduit and thus retain their equilibrium composition at the time of segregation from melt. The composition of surface CO2 and H2O emissions from 2007 to 2009 are compared with modeled exsolved fluid compositions for a magma body ascending from entrapment depths to estimate depth of fluid exsolution and separation from the melt. We find that at the time of sample collection magma had already begun ascent from the mid-crustal storage region and was located at maximum depths of ~ 3.7 km in August 2007, approximately 2 months prior to the next magmatic eruption, and ~ 4.6 km in July of 2009 approximately five months prior to the next magmatic eruption. These findings suggest that the exsolved gas composition at Bezymianny Volcano may be used to detect magma ascent prior to eruption.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2012.10.015","usgsCitation":"Lopez, T., Ushakov, S., Izbekov, P., Tassi, F., Cahill, C., Neill, O., and Werner, C.A., 2013, Constraints on magma processes, subsurface conditions, and total volatile flux at Bezymianny Volcano in 2007–2010 from direct and remote volcanic gas measurements: Journal of Volcanology and Geothermal Research, v. 263, p. 92-107, https://doi.org/10.1016/j.jvolgeores.2012.10.015.","productDescription":"16 p.","startPage":"92","endPage":"107","ipdsId":"IP-042711","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":473629,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.openaccessrepository.it/record/25641","text":"Publisher Index Page"},{"id":348148,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Russia","otherGeospatial":"Bezymianny Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 159.521484375,\n 55.178867663281984\n ],\n [\n 161.60888671875,\n 55.178867663281984\n ],\n [\n 161.60888671875,\n 57.028773851491124\n ],\n [\n 159.521484375,\n 57.028773851491124\n ],\n [\n 159.521484375,\n 55.178867663281984\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"263","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59fc2eace4b0531197b27fbb","contributors":{"authors":[{"text":"Lopez, Taryn","contributorId":146828,"corporation":false,"usgs":false,"family":"Lopez","given":"Taryn","affiliations":[{"id":16753,"text":"University of Alaska Geophysical Institute","active":true,"usgs":false}],"preferred":false,"id":719977,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ushakov, Sergey","contributorId":12135,"corporation":false,"usgs":true,"family":"Ushakov","given":"Sergey","email":"","affiliations":[],"preferred":false,"id":719978,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Izbekov, Pavel","contributorId":85950,"corporation":false,"usgs":true,"family":"Izbekov","given":"Pavel","affiliations":[],"preferred":false,"id":719979,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tassi, Franco","contributorId":95776,"corporation":false,"usgs":true,"family":"Tassi","given":"Franco","email":"","affiliations":[],"preferred":false,"id":719980,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cahill, Cathy","contributorId":199768,"corporation":false,"usgs":false,"family":"Cahill","given":"Cathy","email":"","affiliations":[],"preferred":false,"id":719981,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Neill, Owen","contributorId":199769,"corporation":false,"usgs":false,"family":"Neill","given":"Owen","affiliations":[],"preferred":false,"id":719982,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Werner, Cynthia A. cwerner@usgs.gov","contributorId":2540,"corporation":false,"usgs":true,"family":"Werner","given":"Cynthia","email":"cwerner@usgs.gov","middleInitial":"A.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":719983,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70173475,"text":"70173475 - 2013 - Air - water temperature relationships in the trout streams of southeastern Minnesota’s carbonate - sandstone landscape","interactions":[],"lastModifiedDate":"2016-06-16T16:20:51","indexId":"70173475","displayToPublicDate":"2013-08-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Air - water temperature relationships in the trout streams of southeastern Minnesota’s carbonate - sandstone landscape","docAbstract":"

Carbonate-sandstone geology in southeastern Minnesota creates a heterogeneous landscape of springs, seeps, and sinkholes that supply groundwater into streams. Air temperatures are effective predictors of water temperature in surface-water dominated streams. However, no published work investigates the relationship between air and water temperatures in groundwater-fed streams (GWFS) across watersheds. We used simple linear regressions to examine weekly air-water temperature relationships for 40 GWFS in southeastern Minnesota. A 40-stream, composite linear regression model has a slope of 0.38, an intercept of 6.63, and R2 of 0.83. The regression models for GWFS have lower slopes and higher intercepts in comparison to surface-water dominated streams. Regression models for streams with high R2 values offer promise for use as predictive tools for future climate conditions. Climate change is expected to alter the thermal regime of groundwater-fed systems, but will do so at a slower rate than surface-water dominated systems. A regression model of intercept vs. slope can be used to identify streams for which water temperatures are more meteorologically than groundwater controlled, and thus more vulnerable to climate change. Such relationships can be used to guide restoration vs. management strategies to protect trout streams.

","language":"English","publisher":"Wiley","doi":"10.1111/jawr.12046","usgsCitation":"Krider, L.A., Magner, J.A., Perry, J., Vondracek, B.C., and Ferrington, L.C., 2013, Air - water temperature relationships in the trout streams of southeastern Minnesota’s carbonate - sandstone landscape: Journal of the American Water Resources Association, v. 49, no. 4, p. 896-907, https://doi.org/10.1111/jawr.12046.","productDescription":"12 p.","startPage":"896","endPage":"907","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-036165","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":323823,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.01599121093749,\n 44.38669150215206\n ],\n [\n -92.9718017578125,\n 44.35920579433503\n ],\n [\n -93.1585693359375,\n 44.24126379833979\n ],\n [\n -93.0706787109375,\n 43.93350594453702\n ],\n [\n -92.3895263671875,\n 43.91372326852401\n ],\n [\n -92.1478271484375,\n 43.69965122967144\n ],\n [\n -92.0379638671875,\n 43.492782808225\n ],\n [\n -91.241455078125,\n 43.492782808225\n ],\n [\n -91.263427734375,\n 43.74728909225906\n ],\n [\n -91.38427734374999,\n 43.96514454266273\n ],\n [\n -91.6644287109375,\n 44.071800467511565\n ],\n [\n -91.8841552734375,\n 44.22158376545796\n ],\n [\n -91.9500732421875,\n 44.37098696297173\n ],\n [\n -92.01599121093749,\n 44.38669150215206\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"49","issue":"4","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5763cdace4b07657d19ba748","contributors":{"authors":[{"text":"Krider, Lori A.","contributorId":172050,"corporation":false,"usgs":false,"family":"Krider","given":"Lori","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":639450,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Magner, Joseph A.","contributorId":172051,"corporation":false,"usgs":false,"family":"Magner","given":"Joseph","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":639451,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Perry, Jim","contributorId":111771,"corporation":false,"usgs":true,"family":"Perry","given":"Jim","affiliations":[],"preferred":false,"id":639452,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vondracek, Bruce C. bcv@usgs.gov","contributorId":904,"corporation":false,"usgs":true,"family":"Vondracek","given":"Bruce","email":"bcv@usgs.gov","middleInitial":"C.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":637177,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ferrington, Leonard C. Jr.","contributorId":172049,"corporation":false,"usgs":false,"family":"Ferrington","given":"Leonard","suffix":"Jr.","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":639453,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70187700,"text":"70187700 - 2013 - Modeling spatially explicit fire impact on gross primary production in interior Alaska using satellite images coupled with eddy covariance","interactions":[],"lastModifiedDate":"2017-05-15T14:37:25","indexId":"70187700","displayToPublicDate":"2013-08-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"Modeling spatially explicit fire impact on gross primary production in interior Alaska using satellite images coupled with eddy covariance","docAbstract":"

In interior Alaska, wildfires change gross primary production (GPP) after the initial disturbance. The impact of fires on GPP is spatially heterogeneous, which is difficult to evaluate by limited point-based comparisons or is insufficient to assess by satellite vegetation index. The direct prefire and postfire comparison is widely used, but the recovery identification may become biased due to interannual climate variability. The objective of this study is to propose a method to quantify the spatially explicit GPP change caused by fires and succession. We collected three Landsat images acquired on 13 July 2004, 5 August 2004, and 6 September 2004 to examine the GPP recovery of burned area from 1987 to 2004. A prefire Landsat image acquired in 1986 was used to reconstruct satellite images assuming that the fires of 1987–2004 had not occurred. We used a light-use efficiency model to estimate the GPP. This model was driven by maximum light-use efficiency (Emax) and fraction of photosynthetically active radiation absorbed by vegetation (FPAR). We applied this model to two scenarios (i.e., an actual postfire scenario and an assuming-no-fire scenario), where the changes in Emax and FPAR were taken into account. The changes in Emax were represented by the change in land cover of evergreen needleleaf forest, deciduous broadleaf forest, and shrub/grass mixed, whose Emax was determined from three fire chronosequence flux towers as 1.1556, 1.3336, and 0.5098 gC/MJ PAR. The changes in FPAR were inferred from NDVI change between the actual postfire NDVI and the reconstructed NDVI. After GPP quantification for July, August, and September 2004, we calculated the difference between the two scenarios in absolute and percent GPP changes. Our results showed rapid recovery of GPP post-fire with a 24% recovery immediately after burning and 43% one year later. For the fire scars with an age range of 2–17 years, the recovery rate ranged from 54% to 95%. In addition to the averaging, our approach further revealed the spatial heterogeneity of fire impact on GPP, allowing one to examine the spatially explicit GPP change caused by fires.

","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2013.04.003","usgsCitation":"Huang, S., Liu, H., Dahal, D., Jin, S., Welp, L.R., Liu, J., and Liu, S., 2013, Modeling spatially explicit fire impact on gross primary production in interior Alaska using satellite images coupled with eddy covariance: Remote Sensing of Environment, v. 135, p. 178-188, https://doi.org/10.1016/j.rse.2013.04.003.","productDescription":"11 p.","startPage":"178","endPage":"188","ipdsId":"IP-045013","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":341315,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"135","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"591abe3ae4b0a7fdb43c8c03","contributors":{"authors":[{"text":"Huang, Shengli shuang@usgs.gov","contributorId":1926,"corporation":false,"usgs":true,"family":"Huang","given":"Shengli","email":"shuang@usgs.gov","affiliations":[],"preferred":true,"id":695166,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Liu, Heping","contributorId":117909,"corporation":false,"usgs":true,"family":"Liu","given":"Heping","affiliations":[],"preferred":false,"id":695170,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dahal, Devendra 0000-0001-9594-1249 ddahal@usgs.gov","orcid":"https://orcid.org/0000-0001-9594-1249","contributorId":5622,"corporation":false,"usgs":true,"family":"Dahal","given":"Devendra","email":"ddahal@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":695169,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jin, Suming 0000-0001-9919-8077 sjin@usgs.gov","orcid":"https://orcid.org/0000-0001-9919-8077","contributorId":4397,"corporation":false,"usgs":true,"family":"Jin","given":"Suming","email":"sjin@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":695167,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Welp, Lisa R.","contributorId":192025,"corporation":false,"usgs":false,"family":"Welp","given":"Lisa","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":695171,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Liu, Jinxun 0000-0003-0561-8988 jxliu@usgs.gov","orcid":"https://orcid.org/0000-0003-0561-8988","contributorId":3414,"corporation":false,"usgs":true,"family":"Liu","given":"Jinxun","email":"jxliu@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":695165,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Liu, Shuguang 0000-0002-6027-3479 sliu@usgs.gov","orcid":"https://orcid.org/0000-0002-6027-3479","contributorId":147403,"corporation":false,"usgs":true,"family":"Liu","given":"Shuguang","email":"sliu@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":695168,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70147410,"text":"70147410 - 2013 - The uses and limitations of the square‐root‐impedance method for computing site amplification","interactions":[],"lastModifiedDate":"2015-05-01T11:54:29","indexId":"70147410","displayToPublicDate":"2013-08-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"The uses and limitations of the square‐root‐impedance method for computing site amplification","docAbstract":"

The square‐root‐impedance (SRI) method is a fast way of computing approximate site amplification that does not depend on the details from velocity models. The SRI method underestimates the peak response of models with large impedance contrasts near their base, but the amplifications for those models is often close to or equal to the root mean square of the theoretical full resonant (FR) response of the higher modes. On the other hand, for velocity models made up of gradients, with no significant impedance changes across small ranges of depth, the SRI method systematically underestimates the theoretical FR response over a wide frequency range. For commonly used gradient models for generic rock sites, the SRI method underestimates the FR response by about 20%–30%. Notwithstanding the persistent underestimation of amplifications from theoretical FR calculations, however, amplifications from the SRI method may often provide more useful estimates of amplifications than the FR method, because the SRI amplifications are not sensitive to details of the models and will not exhibit the many peaks and valleys characteristic of theoretical full resonant amplifications (jaggedness sometimes not seen in amplifications based on averages of site response from multiple recordings at a given site). The lack of sensitivity to details of the velocity models also makes the SRI method useful in comparing the response of various velocity models, in spite of any systematic underestimation of the response. The quarter‐wavelength average velocity, which is fundamental to the SRI method, is useful by itself in site characterization, and as such, is the fundamental parameter used to characterize the site response in a number of recent ground‐motion prediction equations.

","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120120283","usgsCitation":"Boore, D., 2013, The uses and limitations of the square‐root‐impedance method for computing site amplification: Bulletin of the Seismological Society of America, v. 103, no. 4, p. 2356-2368, https://doi.org/10.1785/0120120283.","productDescription":"13 p.","startPage":"2356","endPage":"2368","numberOfPages":"13","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-041471","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":300022,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"103","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2013-07-31","publicationStatus":"PW","scienceBaseUri":"5544a3b7e4b0a658d79478d2","contributors":{"authors":[{"text":"Boore, David 0000-0002-8605-9673 boore@usgs.gov","orcid":"https://orcid.org/0000-0002-8605-9673","contributorId":140502,"corporation":false,"usgs":true,"family":"Boore","given":"David","email":"boore@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":545921,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70039319,"text":"70039319 - 2013 - Energy cost of vessel disturbance to Kittlitz's Murrelets Brachyramphus brevirostris","interactions":[],"lastModifiedDate":"2015-06-19T10:01:06","indexId":"70039319","displayToPublicDate":"2013-08-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2675,"text":"Marine Ornithology: Journal of Seabird Research and Conservation","onlineIssn":"2074-1235","printIssn":"1018-3337","active":true,"publicationSubtype":{"id":10}},"title":"Energy cost of vessel disturbance to Kittlitz's Murrelets Brachyramphus brevirostris","docAbstract":"

We evaluated the energy cost of vessel disturbance for individual Kittlitz’s Murrelets Brachyramphus brevirostris in Glacier Bay National Park and Preserve in Alaska, USA. We used Monte Carlo simulations to model the daily energy expense associated with flight from vessels by both breeding and non-breeding birds and evaluated risk based on both the magnitude of costs incurred and the degree to which the costs may be chronic. We used two scenarios of vessel disturbance for average- and peak-vessel traffic. Because they are more likely to fly away from vessels, non-breeding birds had a greater increase in energy expenditure when disturbed (up to 30% increase under the average scenario and >50% increase under the peak scenario) than breeders (up to 10% and 30% increases under the average and peak scenarios, respectively). Likewise, non-breeding birds were more likely to experience chronic increases in energy expense (i.e. a greater percentage of days with an increase in energy expenditure) than breeding birds. Our modeling results indicated that breeding and non-breeding birds were both susceptible to fitness consequences (e.g. reduced reproductive success and survival) resulting from the energy cost.

","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Marine Ornithology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Marine Ornithology","usgsCitation":"Agness, A.M., Marshall, K.N., Piatt, J.F., Ha, J.C., and VanBlaricom, G., 2013, Energy cost of vessel disturbance to Kittlitz's Murrelets Brachyramphus brevirostris: Marine Ornithology: Journal of Seabird Research and Conservation, v. 41, no. 1, p. 13-21.","productDescription":"9 p.","startPage":"13","endPage":"21","numberOfPages":"9","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-034051","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":277411,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":301338,"type":{"id":15,"text":"Index Page"},"url":"https://www.marineornithology.org/cgi-bin/getpage.cgi?vol=41&no=1"}],"country":"United States","state":"Alaska","otherGeospatial":"Glacier Bay National Park","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -138.4141,58.1591 ], [ -138.4141,59.483 ], [ -135.3167,59.483 ], [ -135.3167,58.1591 ], [ -138.4141,58.1591 ] ] ] } } ] }","volume":"41","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"522af964e4b08fd0132e799a","contributors":{"authors":[{"text":"Agness, Alison M.","contributorId":17520,"corporation":false,"usgs":true,"family":"Agness","given":"Alison","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":466065,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Marshall, Kristin N.","contributorId":27178,"corporation":false,"usgs":true,"family":"Marshall","given":"Kristin","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":466066,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Piatt, John F. 0000-0002-4417-5748 jpiatt@usgs.gov","orcid":"https://orcid.org/0000-0002-4417-5748","contributorId":3025,"corporation":false,"usgs":true,"family":"Piatt","given":"John","email":"jpiatt@usgs.gov","middleInitial":"F.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":466064,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ha, James C.","contributorId":69457,"corporation":false,"usgs":true,"family":"Ha","given":"James","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":466068,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"VanBlaricom, Glenn R.","contributorId":39273,"corporation":false,"usgs":true,"family":"VanBlaricom","given":"Glenn R.","affiliations":[],"preferred":false,"id":466067,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70046700,"text":"cir1386 - 2013 - National assessment of geologic carbon dioxide storage resources: results","interactions":[],"lastModifiedDate":"2017-08-29T16:18:28","indexId":"cir1386","displayToPublicDate":"2013-08-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":307,"text":"Circular","code":"CIR","onlineIssn":"2330-5703","printIssn":"1067-084X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1386","title":"National assessment of geologic carbon dioxide storage resources: results","docAbstract":"In 2012, the U.S. Geological Survey (USGS) completed an assessment of the technically accessible storage resources (TASR) for carbon dioxide (CO2) in geologic formations underlying the onshore and State waters area of the United States. The formations assessed are at least 3,000 feet (914 meters) below the ground surface. The TASR is an estimate of the CO2 storage resource that may be available for CO2 injection and storage that is based on present-day geologic and hydrologic knowledge of the subsurface and current engineering practices. Individual storage assessment units (SAUs) for 36 basins were defined on the basis of geologic and hydrologic characteristics outlined in the assessment methodology of Brennan and others (2010, USGS Open-File Report 2010–1127) and the subsequent methodology modification and implementation documentation of Blondes, Brennan, and others (2013, USGS Open-File Report 2013–1055). The mean national TASR is approximately 3,000 metric gigatons (Gt). The estimate of the TASR includes buoyant trapping storage resources (BSR), where CO2 can be trapped in structural or stratigraphic closures, and residual trapping storage resources, where CO2 can be held in place by capillary pore pressures in areas outside of buoyant traps. The mean total national BSR is 44 Gt. The residual storage resource consists of three injectivity classes based on reservoir permeability: residual trapping class 1 storage resource (R1SR) represents storage in rocks with permeability greater than 1 darcy (D); residual trapping class 2 storage resource (R2SR) represents storage in rocks with moderate permeability, defined as permeability between 1 millidarcy (mD) and 1 D; and residual trapping class 3 storage resource (R3SR) represents storage in rocks with low permeability, defined as permeability less than 1 mD. The mean national storage resources for rocks in residual trapping classes 1, 2, and 3 are 140 Gt, 2,700 Gt, and 130 Gt, respectively. The known recovery replacement storage resource (KRRSR) is a conservative estimate that represents only the amount of CO2 at subsurface conditions that could replace the volume of known hydrocarbon production. The mean national KRRSR, determined from production volumes rather than the geologic model of buoyant and residual traps that make up TASR, is 13 Gt. The estimated storage resources are dominated by residual trapping class 2, which accounts for 89 percent of the total resources. The Coastal Plains Region of the United States contains the largest storage resource of any region. Within the Coastal Plains Region, the resources from the U.S. Gulf Coast area represent 59 percent of the national CO2 storage capacity.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1386","usgsCitation":"U.S. Geological Survey Geologic Carbon Dioxide Storage Resources Assessment Team, 2013, National assessment of geologic carbon dioxide storage resources: results (Version 1: Originally posted June 2013; Version 1.1: September 2013): U.S. Geological Survey Circular 1386, ix, 41 p., https://doi.org/10.3133/cir1386.","productDescription":"ix, 41 p.","numberOfPages":"54","onlineOnly":"N","additionalOnlineFiles":"Y","costCenters":[{"id":241,"text":"Eastern Energy Resources Science 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Geological Survey Geologic Carbon Dioxide Storage Resources Assessment Team","id":535561,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70199861,"text":"70199861 - 2013 - Fine-scale hydrologic modeling for regional landscape applications: the California Basin Characterization Model development and performance","interactions":[],"lastModifiedDate":"2018-10-01T15:22:10","indexId":"70199861","displayToPublicDate":"2013-07-31T15:22:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1460,"text":"Ecological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Fine-scale hydrologic modeling for regional landscape applications: the California Basin Characterization Model development and performance","docAbstract":"

Introduction

Resource managers need spatially explicit models of hydrologic response to changes in key climatic drivers across variable landscape conditions. We demonstrate the utility of a Basin Characterization Model for California (CA-BCM) to integrate high-resolution data on physical watershed characteristics with historical or projected climate data to predict watershed-specific hydrologic responses.

Methods

The CA-BCM applies a monthly regional water-balance model to simulate hydrologic responses to climate at the spatial resolution of a 270-m grid. The model has been calibrated using a total of 159 relatively unimpaired watersheds for the California region.

Results

As a result of calibration, predicted basin discharge closely matches measured data for validation watersheds. The CA-BCM recharge and runoff estimates, combined with estimates of snowpack and timing of snowmelt, provide a basis for assessing variations in water availability. Another important output variable, climatic water deficit, integrates the combined effects of temperature and rainfall on site-specific soil moisture, a factor that plants may respond to more directly than air temperature and precipitation alone. Model outputs are calculated for each grid cell, allowing results to be summarized for a variety of planning units including hillslopes, watersheds, ecoregions, or political boundaries.

Conclusions

The ability to confidently calculate hydrologic outputs at fine spatial scales provides a new suite of hydrologic predictor variables that can be used for a variety of purposes, such as projections of changes in water availability, environmental demand, or distribution of plants and habitats. Here we present the framework of the CA-BCM model for the California hydrologic region, a test of model performance on 159 watersheds, summary results for the region for the 1981–2010 time period, and changes since the 1951–1980 time period.

","language":"English","publisher":"Springer","doi":"10.1186/2192-1709-2-25","usgsCitation":"Flint, L.E., Flint, A.L., Thorne, J.H., and Boynton, R., 2013, Fine-scale hydrologic modeling for regional landscape applications: the California Basin Characterization Model development and performance: Ecological Processes, v. 2, p. 1-21, https://doi.org/10.1186/2192-1709-2-25.","productDescription":"Article 25; 21 p.","startPage":"1","endPage":"21","ipdsId":"IP-033531","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":473632,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/2192-1709-2-25","text":"Publisher Index Page"},{"id":357985,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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Florida","interactions":[],"lastModifiedDate":"2022-03-22T13:14:01.550005","indexId":"70047316","displayToPublicDate":"2013-07-31T13:02:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2220,"text":"Journal of Coastal Research","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Possible return of Acropora cervicornis at Pulaski Shoal, Dry Tortugas National Park, Florida","title":"Possible return of Acropora cervicornis at Pulaski Shoal, Dry Tortugas National Park, Florida","docAbstract":"

Seabed classification is essential to assessing environmental associations and physical status in coral reef ecosystems. At Pulaski Shoal in Dry Tortugas National Park, Florida, nearly continuous underwater-image coverage was acquired in 15.5 hours in 2009 along 70.2 km of transect lines spanning ~0.2 km2. The Along-Track Reef-Imaging System (ATRIS), a boat-based, high-speed, digital imaging system, was used. ATRIS-derived benthic classes were merged with a QuickBird satellite image to create a habitat map that defines areas of senile coral reef, carbonate sand, seagrasses, and coral rubble. This atypical approach of starting with extensive, high-resolution in situ imagery and extrapolating between transect lines using satellite imagery leverages the strengths of each remote-sensing modality. The ATRIS images also captured the spatial distribution of two species once common on now-degraded Florida-Caribbean coral reefs: the stony staghorn coral Acropora cervicornis, a designated threatened species, and the long-spined urchin Diadema antillarum. This article documents the utility of ATRIS imagery for quantifying number and estimating age of A. cervicornis colonies (n = 400, age range, 5–11 y) since the severe hypothermic die-off in the Dry Tortugas in 1976–77. This study is also the first to document the largest number of new colonies of A. cervicornis tabulated in an area of the park where coral-monitoring stations maintained by the Fish and Wildlife Research Institute have not been established. The elevated numbers provide an updated baseline for tracking revival of this species at Pulaski Shoal.

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A total of 164 observed anglers fished for 541 h and caught 74 Chinook Salmon. Fifty-eight fish were harvested and 16 were released. Anglers reported fishing for 604 h, an overestimate of 63 h. Anglers reported catching 66 fish; four less harvested and four less released fish were reported than observed. A Monte Carlo simulation revealed that when angler-reported data were used, total catch was underestimated by 14–15 fish (19–20%) using the ratio-of-means estimator to calculate mean catch rate. Negative bias was reduced to six fish (8%) when the means-of-ratio estimator was used. Multiple linear regression models to predict reporting bias in time fished had poor predictive value. However, actual time fished and a categorical covariate indicating whether the angler fished continuously during their fishing trip were two variables that were present in all of the top a priori models evaluated. Underreporting of catch and overreporting of time fished by anglers present challenges when managing Chinook Salmon sport fisheries. However, confidence intervals were near target levels and using more liberal definitions of angling when estimating effort in creel surveys may decrease sensitivity to bias in angler-reported data.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"North American Journal of Fisheries Management","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Taylor & Francis","doi":"10.1080/02755947.2013.808293","usgsCitation":"McCormick, J.L., Quist, M.C., and Schill, D.J., 2013, Self-reporting bias in Chinook salmon sport fisheries in Idaho: implications for roving creel surveys: North American Journal of Fisheries Management, v. 33, no. 4, p. 723-731, https://doi.org/10.1080/02755947.2013.808293.","productDescription":"9 p.","startPage":"723","endPage":"731","ipdsId":"IP-042902","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":275623,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":275622,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1080/02755947.2013.808293"}],"country":"United States","volume":"33","issue":"4","noUsgsAuthors":false,"publicationDate":"2013-07-15","publicationStatus":"PW","scienceBaseUri":"51fa2c80e4b076c3a8d8262b","contributors":{"authors":[{"text":"McCormick, Joshua L.","contributorId":105193,"corporation":false,"usgs":true,"family":"McCormick","given":"Joshua","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":475918,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Quist, Michael C. mquist@usgs.gov","contributorId":4042,"corporation":false,"usgs":true,"family":"Quist","given":"Michael","email":"mquist@usgs.gov","middleInitial":"C.","affiliations":[{"id":350,"text":"Iowa Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true}],"preferred":false,"id":475916,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schill, Daniel J.","contributorId":66562,"corporation":false,"usgs":true,"family":"Schill","given":"Daniel","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":475917,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70047312,"text":"70047312 - 2013 - Emerging methods for the study of coastal ecosystem landscape structure and change","interactions":[],"lastModifiedDate":"2017-04-06T15:31:11","indexId":"70047312","displayToPublicDate":"2013-07-31T10:15:04","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2068,"text":"International Journal of Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Emerging methods for the study of coastal ecosystem landscape structure and change","docAbstract":"Coastal landscapes are heterogeneous, dynamic, and evolve over a range of time scales due to intertwined climatic, geologic, hydrologic, biologic, and meteorological processes, and are also heavily impacted by human development, commercial activities, and resource extraction. A diversity of complex coastal systems around the globe, spanning glaciated shorelines to tropical atolls, wetlands, and barrier islands are responding to multiple human and natural drivers. Interdisciplinary research based on remote-sensing observations linked to process studies and models is required to understand coastal ecosystem landscape structure and change. Moreover, new techniques for coastal mapping and monitoring are increasingly serving the needs of policy-makers and resource managers across local, regional, and national scales. Emerging remote-sensing methods associated with a diversity of instruments and platforms are a key enabling element of integrated coastal ecosystem studies. These investigations require both targeted and synoptic mapping, and involve the monitoring of formative processes such as hydrodynamics, sediment transport, erosion, accretion, flooding, habitat modification, land-cover change, and biogeochemical fluxes.","language":"English","publisher":"Taylor & Francis","doi":"10.1080/01431161.2013.810445","usgsCitation":"Brock, J., Danielson, J.J., and Purkis, S., 2013, Emerging methods for the study of coastal ecosystem landscape structure and change: International Journal of Remote Sensing, v. 34, no. 18, p. 6283-6285, https://doi.org/10.1080/01431161.2013.810445.","productDescription":"3 p.","startPage":"6283","endPage":"6285","ipdsId":"IP-045935","costCenters":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":275618,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":275617,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1080/01431161.2013.810445"}],"volume":"34","issue":"18","noUsgsAuthors":false,"publicationDate":"2013-06-28","publicationStatus":"PW","scienceBaseUri":"51fa2c7fe4b076c3a8d82617","contributors":{"authors":[{"text":"Brock, John 0000-0002-5289-9332 jbrock@usgs.gov","orcid":"https://orcid.org/0000-0002-5289-9332","contributorId":2261,"corporation":false,"usgs":true,"family":"Brock","given":"John","email":"jbrock@usgs.gov","affiliations":[{"id":5061,"text":"National Cooperative Geologic Mapping and Landslide Hazards","active":true,"usgs":true}],"preferred":true,"id":481695,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Danielson, Jeffrey J. 0000-0003-0907-034X daniels@usgs.gov","orcid":"https://orcid.org/0000-0003-0907-034X","contributorId":3996,"corporation":false,"usgs":true,"family":"Danielson","given":"Jeffrey","email":"daniels@usgs.gov","middleInitial":"J.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":481696,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Purkis, Sam","contributorId":95363,"corporation":false,"usgs":true,"family":"Purkis","given":"Sam","affiliations":[],"preferred":false,"id":481697,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70047310,"text":"70047310 - 2013 - A new dry hypothesis for the formation of Martian linear gullies","interactions":[],"lastModifiedDate":"2018-11-01T15:40:11","indexId":"70047310","displayToPublicDate":"2013-07-31T08:22:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1963,"text":"Icarus","active":true,"publicationSubtype":{"id":10}},"title":"A new dry hypothesis for the formation of Martian linear gullies","docAbstract":"Long, narrow grooves found on the slopes of martian sand dunes have been cited as evidence of liquid water via the hypothesis that melt-water initiated debris flows eroded channels and deposited lateral levées. However, this theory has several short-comings for explaining the observed morphology and activity of these linear gullies. We present an alternative hypothesis that is consistent with the observed morphology, location, and current activity: that blocks of CO2 ice break from over-steepened cornices as sublimation processes destabilize the surface in the spring, and these blocks move downslope, carving out levéed grooves of relatively uniform width and forming terminal pits. To test this hypothesis, we describe experiments involving water and CO2 blocks on terrestrial dunes and then compare results with the martian features. Furthermore, we present a theoretical model of the initiation of block motion due to sublimation and use this to quantitatively compare the expected behavior of blocks on the Earth and Mars. The model demonstrates that CO2 blocks can be expected to move via our proposed mechanism on the Earth and Mars, and the experiments show that the motion of these blocks will naturally create the main morphological features of linear gullies seen on Mars.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Icarus","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.icarus.2013.04.006","usgsCitation":"Diniega, S., Hansen, C.J., McElwaine, J.N., Hugenholtz, C., Dundas, C.M., McEwen, A.S., and Bourke, M.C., 2013, A new dry hypothesis for the formation of Martian linear gullies: Icarus, v. 225, p. 526-537, https://doi.org/10.1016/j.icarus.2013.04.006.","productDescription":"12 p.","startPage":"526","endPage":"537","numberOfPages":"12","ipdsId":"IP-039273","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":488139,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://durham-repository.worktribe.com/output/1475116","text":"External Repository"},{"id":275606,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":275605,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.icarus.2013.04.006"}],"otherGeospatial":"Mars","volume":"225","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51fa2c7ae4b076c3a8d82613","contributors":{"authors":[{"text":"Diniega, Serina","contributorId":80532,"corporation":false,"usgs":true,"family":"Diniega","given":"Serina","affiliations":[],"preferred":false,"id":481689,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hansen, Candice J.","contributorId":70235,"corporation":false,"usgs":false,"family":"Hansen","given":"Candice","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":481688,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McElwaine, Jim N.","contributorId":58923,"corporation":false,"usgs":true,"family":"McElwaine","given":"Jim","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":481685,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hugenholtz, C.H.","contributorId":69041,"corporation":false,"usgs":true,"family":"Hugenholtz","given":"C.H.","email":"","affiliations":[],"preferred":false,"id":481687,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dundas, Colin M. 0000-0003-2343-7224 cdundas@usgs.gov","orcid":"https://orcid.org/0000-0003-2343-7224","contributorId":2937,"corporation":false,"usgs":true,"family":"Dundas","given":"Colin","email":"cdundas@usgs.gov","middleInitial":"M.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":481684,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McEwen, Alfred S.","contributorId":61657,"corporation":false,"usgs":false,"family":"McEwen","given":"Alfred","email":"","middleInitial":"S.","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":481686,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bourke, Mary C.","contributorId":105992,"corporation":false,"usgs":true,"family":"Bourke","given":"Mary","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":481690,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70044213,"text":"70044213 - 2013 - Multi-scale habitat selection of the endangered Hawaiian Goose","interactions":[],"lastModifiedDate":"2013-11-15T10:24:10","indexId":"70044213","displayToPublicDate":"2013-07-30T16:24:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1318,"text":"Condor","active":true,"publicationSubtype":{"id":10}},"title":"Multi-scale habitat selection of the endangered Hawaiian Goose","docAbstract":"After a severe population reduction during the mid-20th century, the endangered Hawaiian Goose (Branta sandvicensis), or Nēnē, has only recently re-established its seasonal movement patterns on Hawai‘i Island. Little is currently understood about its movements and habitat use during the nonbreeding season. The objectives of this research were to identify habitats preferred by two subpopulations of the Nēnē and how preferences shift seasonally at both meso-and fine scales. From 2009 to 2011, ten Nēnē ganders were outfitted with 40-to 45-g satellite transmitters with GPS capability. We used binary logistic regression to compare habitat use versus availability and an information-theoretic approach for model selection. Meso-scale habitat modeling revealed that Nēnē preferred exotic grass and human-modified landscapes during the breeding and molting seasons and native subalpine shrubland during the nonbreeding season. Fine-scale habitat modeling further indicated preference for exotic grass, bunch grass, and absence of trees. Proximity to water was important during molt, suggesting that the presence of water may provide escape from introduced mammalian predators while Nēnē are flightless. Finescale species-composition data added relatively little to understanding of Nēnē habitat preferences modeled at the meso scale, suggesting that the meso-scale is appropriate for management planning. Habitat selection during our study was consistent with historical records, although dissimilar from more recent studies of other subpopulations. 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