Groundwater provides much of the fresh drinking water to more than 1.5 billion people in the world (Clarke et al., 1996) and in the United States more that 50 percent of citizens rely on groundwater for drinking water (Solley et al., 1998). As aquifer systems are developed for water supply, the hydrologic system is changed. Water pumped from the aquifer system initially can come from some combination of inducing more recharge, water permanently removed from storage, and decreased groundwater discharge. Once a new equilibrium is achieved, all of the pumpage must come from induced recharge and decreased discharge (Alley et al., 1999). Further development of groundwater resources may result in reductions of surface water runoff and base flows. Competing demands for groundwater resources require good management. Adequate data to characterize the aquifers and confining units of the system, like hydrologic boundaries, groundwater levels, streamflow, and groundwater pumping and climatic data for recharge estimation are to be collected in order to quantify the effects of groundwater withdrawals on wetlands, streams, and lakes. Once collected, three-dimensional (3D) groundwater flow models can be developed and calibrated and used as a tool for groundwater management. The main hydraulic parameters that comprise a regional or subregional model of an aquifer system are the hydraulic conductivity and storage properties of the aquifers and confining units (hydrogeologic units) that confine the system. Many 3D groundwater flow models used to help assess groundwater/surface-water interactions require calculating ?effective? or composite hydraulic properties of multilayered lithologic units within a hydrogeologic unit. The calculation of composite hydraulic properties stems from the need to characterize groundwater flow using coarse model layering in order to reduce simulation times while still representing the flow through the system accurately. The accuracy of flow models with simplified layering and hydraulic properties will depend on the effectiveness of the methods used to determine composite hydraulic properties from a number of lithologic units.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Hydraulic conductivity: Issues, determination and applications","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"InTech","publisherLocation":"Rijeka, Croatia","usgsCitation":"Kuniansky, E.L., and Sepulveda, N., 2011, Effects of model layer simplification using composite hydraulic properties, chap. of Hydraulic conductivity: Issues, determination and applications, p. 357-376.","productDescription":"20 p.","startPage":"357","endPage":"376","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-028745","costCenters":[{"id":5051,"text":"FLWSC-Orlando","active":true,"usgs":true}],"links":[{"id":308303,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Carrot Barn, Lyonia Preserve","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n 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elkunian@usgs.gov","orcid":"https://orcid.org/0000-0002-5581-0225","contributorId":932,"corporation":false,"usgs":true,"family":"Kuniansky","given":"Eve","email":"elkunian@usgs.gov","middleInitial":"L.","affiliations":[{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true},{"id":5064,"text":"Southeast Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":572756,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sepulveda, Nicasio 0000-0002-6333-1865 nsepul@usgs.gov","orcid":"https://orcid.org/0000-0002-6333-1865","contributorId":1454,"corporation":false,"usgs":true,"family":"Sepulveda","given":"Nicasio","email":"nsepul@usgs.gov","affiliations":[{"id":5051,"text":"FLWSC-Orlando","active":true,"usgs":true}],"preferred":true,"id":572757,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70033872,"text":"70033872 - 2011 - The rise and fall of Lake Bonneville between 45 and 10.5 ka","interactions":[],"lastModifiedDate":"2023-11-29T12:03:40.324623","indexId":"70033872","displayToPublicDate":"2011-01-01T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3217,"text":"Quaternary International","active":true,"publicationSubtype":{"id":10}},"title":"The rise and fall of Lake Bonneville between 45 and 10.5 ka","docAbstract":"A sediment core taken from the western edge of the Bonneville Basin has provided high-resolution proxy records of relative lake-size change for the period 45.1–10.5 calendar ka (hereafter ka). Age control was provided by a paleomagnetic secular variation (PSV)-based age model for Blue Lake core BL04-4. Continuous records of δ18O and total inorganic carbon (TIC) generally match an earlier lake-level envelope based on outcrops and geomorphic features, but with differences in the timing of some hydrologic events/states. The Stansbury Oscillation was found to consist of two oscillations centered on 25 and 24 ka. Lake Bonneville appears to have reached its geomorphic highstand and began spilling at 18.5 ka. The fall from the highstand to the Provo level occurred at 17.0 ka and the lake intermittently overflowed at the Provo level until 15.2 ka, at which time the lake fell again, bottoming out at ∼14.7 ka. The lake also fell briefly below the Provo level at ∼15.9 ka. Carbonate and δ18O data indicate that between 14.7 and 13.1 ka the lake slowly rose to the Gilbert shoreline and remained at about that elevation until 11.6 ka, when it fell again. Chemical and sedimentological data indicate that a marsh formed in the Blue Lake area at 10.5 ka.
Relatively dry periods in the BL04-4 records are associated with Heinrich events H1–H4, suggesting that either the warming that closely followed a Heinrich event increased the evaporation rate in the Bonneville Basin and (or) that the core of the polar jet stream (PJS) shifted north of the Bonneville Basin in response to massive losses of ice from the Laurentide Ice Sheet (LIS) during the Heinrich event. The second Stansbury Oscillation occurred during Heinrich event H2, and the Gilbert wet event occurred during the Younger Dryas cold interval. Several relatively wet events in BL04-4 occur during Dansgaard-Oeschger (DO) warm events.
The growth of the Bear River glacier between 32 and 17 ka paralleled changes in the values of proxy indicators of Bonneville Basin wetness and terminal moraines on the western side of the Wasatch Mountains have ages ranging from 16.9 to 15.2 ka. This suggests a near synchroneity of change in the hydrologic and cryologic balances occurring in the Bonneville drainage system and that glacial extent was linked to lake size.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.quaint.2010.12.014","issn":"10406182","usgsCitation":"Benson, L.V., Lund, S., Smoot, J.P., Rhode, D., Spencer, R.J., Verosub, K., Louderback, L., Johnson, C.A., Rye, R.O., and Negrini, R., 2011, The rise and fall of Lake Bonneville between 45 and 10.5 ka: Quaternary International, v. 235, no. 1-2, p. 57-69, https://doi.org/10.1016/j.quaint.2010.12.014.","productDescription":"13 p.","startPage":"57","endPage":"69","numberOfPages":"13","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":242173,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"235","issue":"1-2","tableOfContents":"The PEER NGA ground-motion prediction equations (GMPEs) were derived by five developer teams over several years, resulting in five sets of GMPEs. The teams used various subsets of a global database of ground motions and metadata from shallow earthquakes in tectonically active regions in the development of the equations. Since their publication, the predicted motions from these GMPEs have been compared with data from various parts of the world – data that largely were not used in the development of the GMPEs. The comparisons suggest that the NGA GMPEs are applicable globally for shallow earthquakes in tectonically active regions.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Earthquake Data in Engineering Seismology: Predictive Models, Data Management, and Networks","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","publisherLocation":"Dordrecht, NY","doi":"10.1007/978-94-007-0152-6_1","usgsCitation":"Boore, D.M., 2011, Ground-Motion Prediction Equations (GMPEs) from a global dataset: The PEER NGA equations, chap. of Earthquake Data in Engineering Seismology: Predictive Models, Data Management, and Networks, p. 3-15, https://doi.org/10.1007/978-94-007-0152-6_1.","productDescription":"13 p.","startPage":"3","endPage":"15","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-019122","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":307751,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2010-11-30","publicationStatus":"PW","scienceBaseUri":"560bb6b3e4b058f706e53cbc","contributors":{"editors":[{"text":"Akkar, Sinan","contributorId":39175,"corporation":false,"usgs":true,"family":"Akkar","given":"Sinan","email":"","affiliations":[],"preferred":false,"id":570832,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Gulkan, Polat","contributorId":78532,"corporation":false,"usgs":true,"family":"Gulkan","given":"Polat","email":"","affiliations":[],"preferred":false,"id":570833,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"van Eck, Torild","contributorId":147238,"corporation":false,"usgs":false,"family":"van Eck","given":"Torild","email":"","affiliations":[],"preferred":false,"id":570834,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Boore, David M. boore@usgs.gov","contributorId":2509,"corporation":false,"usgs":true,"family":"Boore","given":"David","email":"boore@usgs.gov","middleInitial":"M.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":false,"id":570831,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70036376,"text":"70036376 - 2011 - Sedimentary response to orogenic exhumation in the northern Rocky Mountain Basin and Range province, Flint Creek basin, west-central Montana","interactions":[],"lastModifiedDate":"2026-01-29T14:31:52.912121","indexId":"70036376","displayToPublicDate":"2011-01-01T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1168,"text":"Canadian Journal of Earth Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Sedimentary response to orogenic exhumation in the northern Rocky Mountain Basin and Range province, Flint Creek basin, west-central Montana","docAbstract":"Middle Eocene through Upper Miocene sedimentary and volcanic rocks of the Flint Creek basin in western Montana accumulated during a period of significant paleoclimatic change and extension across the northern Rocky Mountain Basin and Range province. Gravity modelling, borehole data, and geologic mapping from the Flint Creek basin indicate that subsidence was focused along an extensionally reactivated Sevier thrust fault, which accommodated up to 800 m of basin fill while relaying stress between the dextral transtensional Lewis and Clark lineament to the north and the Anaconda core complex to the south. Northwesterly paleocurrent indicators, foliated metamorphic lithics, 64 Ma (40Ar/39Ar) muscovite grains, and 76 Ma (U-Pb) zircons in a ca. 27 Ma arkosic sandstone are consistent with Oligocene exhumation and erosion of the Anaconda core complex. The core complex and volcanic and magmatic rocks in its hangingwall created an important drainage divide during the Paleogene shedding detritus to the NNW and ESE. Following a major period of Early Miocene tectonism and erosion, regional drainage networks were reorganized such that paleoflow in the Flint Creek basin flowed east into an internally drained saline lake system. Renewed tectonism during Middle to Late Miocene time reestablished a west-directed drainage that is recorded by fluvial strata within a Late Miocene paleovalley. These tectonic reorganizations and associated drainage divide explain observed discrepancies in provenance studies across the province. Regional correlation of unconformities and lithofacies mapping in the Flint Creek basin suggest that localized tectonism and relative base level fluctuations controlled lithostratigraphic architecture.","language":"English, French","publisher":"Canadian Science Publishing","doi":"10.1139/e10-107","issn":"00084077","usgsCitation":"Portner, R., Hendrix, M., Stalker, J., Miggins, D.P., and Sheriff, S., 2011, Sedimentary response to orogenic exhumation in the northern Rocky Mountain Basin and Range province, Flint Creek basin, west-central Montana: Canadian Journal of Earth Sciences, v. 48, no. 7, p. 1131-1153, https://doi.org/10.1139/e10-107.","productDescription":"23 p.","startPage":"1131","endPage":"1153","numberOfPages":"23","costCenters":[],"links":[{"id":246188,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"48","issue":"7","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505b8a38e4b08c986b3170bf","contributors":{"authors":[{"text":"Portner, R.A.","contributorId":41685,"corporation":false,"usgs":true,"family":"Portner","given":"R.A.","email":"","affiliations":[],"preferred":false,"id":455796,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hendrix, M.S.","contributorId":6300,"corporation":false,"usgs":true,"family":"Hendrix","given":"M.S.","email":"","affiliations":[],"preferred":false,"id":455794,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stalker, J.C.","contributorId":90143,"corporation":false,"usgs":true,"family":"Stalker","given":"J.C.","affiliations":[],"preferred":false,"id":455797,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miggins, D. P.","contributorId":32367,"corporation":false,"usgs":true,"family":"Miggins","given":"D.","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":455795,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sheriff, S.D.","contributorId":101001,"corporation":false,"usgs":true,"family":"Sheriff","given":"S.D.","email":"","affiliations":[],"preferred":false,"id":455798,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70046772,"text":"70046772 - 2011 - A Digital Hydrologic Network Supporting NAWQA MRB SPARROW Modeling--MRB_E2RF1WS","interactions":[],"lastModifiedDate":"2013-07-02T15:40:17","indexId":"70046772","displayToPublicDate":"2011-01-01T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":6,"text":"USGS Unnumbered Series"},"title":"A Digital Hydrologic Network Supporting NAWQA MRB SPARROW Modeling--MRB_E2RF1WS","docAbstract":"A digital hydrologic network was developed to support SPAtially Referenced Regression on Watershed attributes (SPARROW) models within selected regions of the United States. These regions correspond with the U.S. Geological Survey's National Water Quality Assessment (NAWQA) Program Major River Basin (MRB) study units 2, 3, 4, 5, and 7 (Preston and others, 2009). MRB2, covers the South Atlantic-Gulf and Tennessee River basins. MRB3, covers the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy River basins. MRB4, covers the Missouri River basins. MRB5, covers the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf River basins. MRB7, covers the Pacific Northwest River basins. The digital hydrologic network described here represents surface-water pathways (MRB_E2RF1) and associated catchments (MRB_E2RF1WS). It serves as the fundamental framework to spatially reference and summarize explanatory information supporting nutrient SPARROW models (Brakebill and others, 2011; Wieczorek and LaMotte, 2011). The principal geospatial dataset used to support this regional effort was based on an enhanced version of a 1:500,000 scale digital stream-reach network (ERF1_2) (Nolan et al., 2002). Enhancements included associating over 3,500 water-quality monitoring sites to the reach network, improving physical locations of stream reaches at or near monitoring locations, and generating drainage catchments based on 100m elevation data. A unique number (MRB_ID) identifies each reach as a single unit. This unique number is also shared by the catchment area drained by the reach, thus spatially linking the hydrologically connected streams and the respective drainage area characteristics. In addition, other relevant physical, environmental, and monitoring information can be associated to the common network and accessed using the unique identification number.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Baltimore, MA","doi":"10.3133/70046772","usgsCitation":"Brakebill, J., and Terziotti, S., 2011, A Digital Hydrologic Network Supporting NAWQA MRB SPARROW Modeling--MRB_E2RF1WS (Version 1.0), Dataset, https://doi.org/10.3133/70046772.","productDescription":"Dataset","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[],"links":[{"id":274444,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":274443,"type":{"id":16,"text":"Metadata"},"url":"https://water.usgs.gov/GIS/metadata/usgswrd/XML/mrb_e2rf1ws.xml"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -128.290499,23.033207 ], [ -128.290499,52.450082 ], [ -64.959844,52.450082 ], [ -64.959844,23.033207 ], [ -128.290499,23.033207 ] ] ] } } ] }","edition":"Version 1.0","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51d3f662e4b09630fbdc526e","contributors":{"authors":[{"text":"Brakebill, J. 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Such adjustment includes climate-bias correction, spatial refinement (\"downscaling\"), and consideration of the roles of hydrologic processes that were neglected in the climate model. Described herein is a quantitative analysis of the effects of hydrologic adjustment on the projections of runoff change associated with projected twenty-first-century climate change. In a case study including three climate models and 10 river basins in the contiguous United States, the authors find that relative (i.e., fractional or percentage) runoff change computed with hydrologic adjustment more often than not was less positive (or, equivalently, more negative) than what was projected by the climate models. The dominant contributor to this decrease in runoff was a ubiquitous change in runoff (median -11%) caused by the hydrologic model’s apparent amplification of the climate-model-implied growth in potential evapotranspiration. Analysis suggests that the hydrologic model, on the basis of the empirical, temperature-based modified Jensen–Haise formula, calculates a change in potential evapotranspiration that is typically 3 times the change implied by the climate models, which explicitly track surface energy budgets. In comparison with the amplification of potential evapotranspiration, central tendencies of other contributions from hydrologic adjustment (spatial refinement, climate-bias adjustment, and process refinement) were relatively small. The authors’ findings highlight the need for caution when projecting changes in potential evapotranspiration for use in hydrologic models or drought indices to evaluate climate-change impacts on water.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Earth Interactions","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Meteorological Society","publisherLocation":"Boston, MA","doi":"10.1175/2010EI363.1","usgsCitation":"Milly, P., and Dunne, K.A., 2011, On the Hydrologic Adjustment of Climate-Model Projections: The Potential Pitfall of Potential Evapotranspiration: Earth Interactions, v. 15, no. 1, p. 1-14, https://doi.org/10.1175/2010EI363.1.","productDescription":"15 p.","startPage":"1","endPage":"14","numberOfPages":"15","additionalOnlineFiles":"N","ipdsId":"IP-019747","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":475164,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1175/2010ei363.1","text":"Publisher Index Page"},{"id":270445,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":270444,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1175/2010EI363.1"}],"volume":"15","issue":"1","noUsgsAuthors":false,"publicationDate":"2011-01-14","publicationStatus":"PW","scienceBaseUri":"515bfdf6e4b075500ee5ca7b","contributors":{"authors":[{"text":"Milly, Paul C.D. 0000-0003-4389-3139 cmilly@usgs.gov","orcid":"https://orcid.org/0000-0003-4389-3139","contributorId":2119,"corporation":false,"usgs":true,"family":"Milly","given":"Paul C.D.","email":"cmilly@usgs.gov","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":false,"id":475759,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dunne, Krista A. kadunne@usgs.gov","contributorId":3936,"corporation":false,"usgs":true,"family":"Dunne","given":"Krista","email":"kadunne@usgs.gov","middleInitial":"A.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":475760,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70043634,"text":"70043634 - 2011 - Marine Habitat Use by Anadromous Bull Trout from the Skagit River, Washington","interactions":[],"lastModifiedDate":"2013-02-26T11:10:39","indexId":"70043634","displayToPublicDate":"2011-01-01T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2680,"text":"Marine and Coastal Fisheries: Dynamics, Management, and Ecosystem Science","active":true,"publicationSubtype":{"id":10}},"title":"Marine Habitat Use by Anadromous Bull Trout from the Skagit River, Washington","docAbstract":"Acoustic telemetry was used to describe fish positions and marine habitat use by tagged bull trout Salvelinus confluentus from the Skagit River, Washington. In March and April 2006, 20 fish were captured and tagged in the lower Skagit River, while 15 fish from the Swinomish Channel were tagged during May and June. Sixteen fish tagged in 2004 and 2005 were also detected during the study. Fish entered Skagit Bay from March to May and returned to the river from May to August. The saltwater residency for the 13 fish detected during the out-migration and return migration ranged from 36 to 133 d (mean ± SD, 75 ± 22 d). Most bull trout were detected less than 14 km (8.5 ± 4.4 km) from the Skagit River, and several bay residents used the Swinomish Channel while migrating. The bull trout detected in the bay were associated with the shoreline (distance from shore, 0.32 ± 0.27 km) and occupied shallow-water habitats (mean water column depth, <4.0 m). The modified-minimum convex polygons (MMCPs) used to describe the habitats used by 14 bay fish showed that most areas were less than 1,000 ha. The mean length of the shoreline bordering the MMCPs was 2.8 km (range, 0.01–5.7 km) for bay fish and 0.6 km for 2 channel residents. Coastal deposits, low banks, and sediment bluffs were common shoreline classes found within the MMCPs of bay fish, while modified shoreline classes usually included concrete bulkheads and riprap. Mixed fines, mixed coarse sediments, and sand were common substrate classes found within MMCPs; green algae and eelgrass (Zostera sp.) vegetation classes made up more than 70% of the area used by bull trout. Our results will help managers identify specific nearshore areas that may require further protection to sustain the unique anadromous life history of bull trout.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Marine and Coastal Fisheries: Dynamics, Management, and Ecosystem Science","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Taylor & Francis","publisherLocation":"London, UK","doi":"10.1080/19425120.2011.640893","usgsCitation":"Hayes, M.C., Rubin, S.P., Reisenbichler, R., Goetz, F.A., Jeanes, E., and McBride, A., 2011, Marine Habitat Use by Anadromous Bull Trout from the Skagit River, Washington: Marine and Coastal Fisheries: Dynamics, Management, and Ecosystem Science, v. 3, no. 1, p. 394-410, https://doi.org/10.1080/19425120.2011.640893.","productDescription":"17 p.","startPage":"394","endPage":"410","numberOfPages":"17","additionalOnlineFiles":"N","ipdsId":"IP-020827","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":475165,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1080/19425120.2011.640893","text":"External Repository"},{"id":268356,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":268353,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1080/19425120.2011.640893"}],"country":"United States","state":"Washington","otherGeospatial":"Skagit Bay;Skagit River;Swinomish Channel","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.597466,48.247083 ], [ -122.597466,48.470645 ], [ -122.334824,48.470645 ], [ -122.334824,48.247083 ], [ -122.597466,48.247083 ] ] ] } } ] }","volume":"3","issue":"1","noUsgsAuthors":false,"publicationDate":"2011-12-22","publicationStatus":"PW","scienceBaseUri":"53cd6645e4b0b29085100a22","contributors":{"authors":[{"text":"Hayes, Michael C. 0000-0002-9060-0565 mhayes@usgs.gov","orcid":"https://orcid.org/0000-0002-9060-0565","contributorId":3017,"corporation":false,"usgs":true,"family":"Hayes","given":"Michael","email":"mhayes@usgs.gov","middleInitial":"C.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":474003,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rubin, Steve P. 0000-0003-3054-7173 srubin@usgs.gov","orcid":"https://orcid.org/0000-0003-3054-7173","contributorId":3018,"corporation":false,"usgs":true,"family":"Rubin","given":"Steve","email":"srubin@usgs.gov","middleInitial":"P.","affiliations":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"preferred":false,"id":474004,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reisenbichler, Reginald","contributorId":29903,"corporation":false,"usgs":true,"family":"Reisenbichler","given":"Reginald","affiliations":[],"preferred":false,"id":474005,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Goetz, Fred A.","contributorId":53261,"corporation":false,"usgs":true,"family":"Goetz","given":"Fred","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":474006,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jeanes, Eric","contributorId":71081,"corporation":false,"usgs":true,"family":"Jeanes","given":"Eric","email":"","affiliations":[],"preferred":false,"id":474007,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McBride, Aundrea","contributorId":88630,"corporation":false,"usgs":true,"family":"McBride","given":"Aundrea","email":"","affiliations":[],"preferred":false,"id":474008,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70043451,"text":"70043451 - 2011 - Novel tetra-nucleotide microsatellite DNA markers for assessing the evolutionary genetics and demographics of Northern Snakehead (Channa argus) invading North America","interactions":[],"lastModifiedDate":"2018-03-08T12:24:59","indexId":"70043451","displayToPublicDate":"2011-01-01T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1325,"text":"Conservation Genetics Resources","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Novel tetra-nucleotide microsatellite DNA markers for assessing the evolutionary genetics and demographics of Northern Snakehead (Channa argus) invading North America","title":"Novel tetra-nucleotide microsatellite DNA markers for assessing the evolutionary genetics and demographics of Northern Snakehead (Channa argus) invading North America","docAbstract":"We document the isolation and characterization of 19 tetra-nucleotide microsatellite DNA markers in northern snakehead (Channa argus) fish that recently colonized Meadow Lake, New York City, New York. These markers displayed moderate levels of allelic diversity (averaging 6.8 alleles/locus) and heterozygosity (averaging 74.2%). Demographic analyses suggested that the Meadow Lake collection has not achieved mutation-drift equilibrium. These results were consistent with instances of deviations from Hardy–Weinberg equilibrium and the presence of some linkage disequilibrium. A comparison of individual pair-wise distances suggested the presence of multiple differentiated groups of related individuals. Results of all analyses are consistent with a pattern of multiple, recent introductions. The microsatellite markers developed for C. argus yielded sufficient genetic diversity to potentially: (1) delineate kinship; (2) elucidate fine-scale population structure; (3) define management (eradication) units; (4) estimate dispersal rates; (5) estimate population sizes; and (6) provide unique demographic perspectives of control or eradication effectiveness.
","language":"English","publisher":"Springer","doi":"10.1007/s12686-010-9256-8","usgsCitation":"King, T.L., and Johnson, R.L., 2011, Novel tetra-nucleotide microsatellite DNA markers for assessing the evolutionary genetics and demographics of Northern Snakehead (Channa argus) invading North America: Conservation Genetics Resources, v. 3, no. 1, p. 1-4, https://doi.org/10.1007/s12686-010-9256-8.","productDescription":"5 p.","startPage":"1","endPage":"4","additionalOnlineFiles":"N","ipdsId":"IP-022768","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":269176,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"3","issue":"1","noUsgsAuthors":false,"publicationDate":"2010-06-18","publicationStatus":"PW","scienceBaseUri":"51404e85e4b089809dbf44a2","contributors":{"authors":[{"text":"King, Tim L. tlking@usgs.gov","contributorId":3520,"corporation":false,"usgs":true,"family":"King","given":"Tim","email":"tlking@usgs.gov","middleInitial":"L.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":473615,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Robin L.","contributorId":68635,"corporation":false,"usgs":true,"family":"Johnson","given":"Robin","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":473616,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70044014,"text":"70044014 - 2011 - Earthquake casualty models within the USGS Prompt Assessment of Global Earthquakes for Response (PAGER) system","interactions":[],"lastModifiedDate":"2015-01-16T10:18:04","indexId":"70044014","displayToPublicDate":"2011-01-01T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Earthquake casualty models within the USGS Prompt Assessment of Global Earthquakes for Response (PAGER) system","docAbstract":"Since the launch of the USGS’s Prompt Assessment of Global Earthquakes for Response (PAGER) system in fall of 2007, the time needed for the U.S. Geological Survey (USGS) to determine and comprehend the scope of any major earthquake disaster anywhere in the world has been dramatically reduced to less than 30 min. PAGER alerts consist of estimated shaking hazard from the ShakeMap system, estimates of population exposure at various shaking intensities, and a list of the most severely shaken cities in the epicentral area. These estimates help government, scientific, and relief agencies to guide their responses in the immediate aftermath of a significant earthquake. To account for wide variability and uncertainty associated with inventory, structural vulnerability and casualty data, PAGER employs three different global earthquake fatality/loss computation models. This article describes the development of the models and demonstrates the loss estimation capability for earthquakes that have occurred since 2007. The empirical model relies on country-specific earthquake loss data from past earthquakes and makes use of calibrated casualty rates for future prediction. The semi-empirical and analytical models are engineering-based and rely on complex datasets including building inventories, time-dependent population distributions within different occupancies, the vulnerability of regional building stocks, and casualty rates given structural collapse.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Human casualties in earthquakes: progress in modelling and mitigation","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-90-481-9455-1_6","usgsCitation":"Jaiswal, K., Wald, D.J., Earle, P.S., Porter, K.A., and Hearne, M., 2011, Earthquake casualty models within the USGS Prompt Assessment of Global Earthquakes for Response (PAGER) system, chap. of Human casualties in earthquakes: progress in modelling and mitigation, v. 29, p. 83-94, https://doi.org/10.1007/978-90-481-9455-1_6.","productDescription":"12 p.","startPage":"83","endPage":"94","numberOfPages":"12","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-007955","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":271421,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"29","noUsgsAuthors":false,"publicationDate":"2010-12-08","publicationStatus":"PW","scienceBaseUri":"5178fee7e4b0d842c705f6fc","contributors":{"authors":[{"text":"Jaiswal, Kishor kjaiswal@usgs.gov","contributorId":861,"corporation":false,"usgs":true,"family":"Jaiswal","given":"Kishor","email":"kjaiswal@usgs.gov","affiliations":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":false,"id":474617,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wald, David J. 0000-0002-1454-4514 wald@usgs.gov","orcid":"https://orcid.org/0000-0002-1454-4514","contributorId":795,"corporation":false,"usgs":true,"family":"Wald","given":"David","email":"wald@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":474615,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Earle, Paul S. pearle@usgs.gov","contributorId":840,"corporation":false,"usgs":true,"family":"Earle","given":"Paul","email":"pearle@usgs.gov","middleInitial":"S.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":474613,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Porter, Keith A.","contributorId":28883,"corporation":false,"usgs":true,"family":"Porter","given":"Keith","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":474614,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hearne, Mike 0000-0002-8225-2396 mhearne@usgs.gov","orcid":"https://orcid.org/0000-0002-8225-2396","contributorId":4659,"corporation":false,"usgs":true,"family":"Hearne","given":"Mike","email":"mhearne@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":474616,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70046617,"text":"70046617 - 2011 - GAGES-II: Geospatial Attributes of Gages for Evaluating Streamflow","interactions":[],"lastModifiedDate":"2013-06-17T09:22:06","indexId":"70046617","displayToPublicDate":"2011-01-01T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":6,"text":"USGS Unnumbered Series"},"title":"GAGES-II: Geospatial Attributes of Gages for Evaluating Streamflow","docAbstract":"This dataset, termed \"GAGES II\", an acronym for Geospatial Attributes of Gages for Evaluating Streamflow, version II, provides geospatial data and classifications for 9,322 stream gages maintained by the U.S. Geological Survey (USGS). It is an update to the original GAGES, which was published as a Data Paper on the journal Ecology's website (Falcone and others, 2010b) in 2010. The GAGES II dataset consists of gages which have had either 20+ complete years (not necessarily continuous) of discharge record since 1950, or are currently active, as of water year 2009, and whose watersheds lie within the United States, including Alaska, Hawaii, and Puerto Rico. Reference gages were identified based on indicators that they were the least-disturbed watersheds within the framework of broad regions, based on 12 major ecoregions across the United States. Of the 9,322 total sites, 2,057 are classified as reference, and 7,265 as non-reference. Of the 2,057 reference sites, 1,633 have (through 2009) 20+ years of record since 1950. Some sites have very long flow records: a number of gages have been in continuous service since 1900 (at least), and have 110 years of complete record (1900-2009) to date. The geospatial data include several hundred watershed characteristics compiled from national data sources, including environmental features (e.g. climate – including historical precipitation, geology, soils, topography) and anthropogenic influences (e.g. land use, road density, presence of dams, canals, or power plants). The dataset also includes comments from local USGS Water Science Centers, based on Annual Data Reports, pertinent to hydrologic modifications and influences. The data posted also include watershed boundaries in GIS format. This overall dataset is different in nature to the USGS Hydro-Climatic Data Network (HCDN; Slack and Landwehr 1992), whose data evaluation ended with water year 1988. The HCDN identifies stream gages which at some point in their history had periods which represented natural flow, and the years in which those natural flows occurred were identified (i.e. not all HCDN sites were in reference condition even in 1988, for example, 02353500). The HCDN remains a valuable indication of historic natural streamflow data. However, the goal of this dataset was to identify watersheds which currently have near-natural flow conditions, and the 2,057 reference sites identified here were derived independently of the HCDN. A subset, however, noted in the BasinID worksheet as “HCDN-2009”, has been identified as an updated list of 743 sites for potential hydro-climatic study. The HCDN-2009 sites fulfill all of the following criteria: (a) have 20 years of complete and continuous flow record in the last 20 years (water years 1990-2009), and were thus also currently active as of 2009, (b) are identified as being in current reference condition according to the GAGES-II classification, (c) have less than 5 percent imperviousness as measured from the NLCD 2006, and (d) were not eliminated by a review from participating state Water Science Center evaluators. The data posted here consist of the following items:- This point shapefile, with summary data for the 9,322 gages.- A zip file containing basin characteristics, variable definitions, and a more detailed report.- A zip file containing shapefiles of basin boundaries, organized by classification and aggregated ecoregion.- A zip file containing mainstem stream lines (Arc line coverages) for each gage.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/70046617","usgsCitation":"Falcone, J.A., 2011, GAGES-II: Geospatial Attributes of Gages for Evaluating Streamflow, Dataset, https://doi.org/10.3133/70046617.","productDescription":"Dataset","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[],"links":[{"id":273766,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":273765,"type":{"id":16,"text":"Metadata"},"url":"https://water.usgs.gov/GIS/metadata/usgswrd/XML/gagesII_Sept2011.xml"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -180.000000,5.402082 ], [ -180.000000,90.000000 ], [ 180.000000,90.000000 ], [ 180.000000,5.402082 ], [ -180.000000,5.402082 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51c02feae4b0ee1529ed3cdc","contributors":{"authors":[{"text":"Falcone, James A. 0000-0001-7202-3592 jfalcone@usgs.gov","orcid":"https://orcid.org/0000-0001-7202-3592","contributorId":614,"corporation":false,"usgs":true,"family":"Falcone","given":"James","email":"jfalcone@usgs.gov","middleInitial":"A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":479872,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70046692,"text":"70046692 - 2011 - A Digital Hydrologic Network Supporting NAWQA MRB SPARROW Modeling--MRB_E2RF1","interactions":[],"lastModifiedDate":"2013-06-25T14:09:52","indexId":"70046692","displayToPublicDate":"2011-01-01T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":6,"text":"USGS Unnumbered Series"},"title":"A Digital Hydrologic Network Supporting NAWQA MRB SPARROW Modeling--MRB_E2RF1","docAbstract":"A digital hydrologic network was developed to support SPAtially Referenced Regression on Watershed attributes (SPARROW) models within selected regions of the United States. These regions correspond with the U.S. Geological Survey's National Water Quality Assessment (NAWQA) Program Major River Basin (MRB) study units 2, 3, 4, 5, and 7 (Preston and others, 2009). MRB2, covers the South Atlantic-Gulf and Tennessee River basins. MRB3, covers the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy River basins. MRB4, covers the Missouri River basins. MRB5, covers the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf River basins. MRB7, covers the Pacific Northwest River basins. The digital hydrologic network described here represents surface-water pathways (MRB_E2RF1) and associated catchments (MRB_E2RF1WS). It serves as the fundamental framework to spatially reference and summarize explanatory information supporting nutrient SPARROW models (Brakebill and others, 2011; Wieczorek and LaMotte, 2011). The principal geospatial dataset used to support this regional effort was based on an enhanced version of a 1:500,000 scale digital stream-reach network (ERF1_2) (Nolan et al., 2002). Enhancements included associating over 3,500 water-quality monitoring sites to the reach network, improving physical locations of stream reaches at or near monitoring locations, and generating drainage catchments based on 100m elevation data. A unique number (MRB_ID) identifies each reach as a single unit. This unique number is also shared by the catchment area drained by the reach, thus spatially linking the hydrologically connected streams and the respective drainage area characteristics. In addition, other relevant physical, environmental, and monitoring information can be associated to the common network and accessed using the unique identification number.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Baltimore, MA","doi":"10.3133/70046692","usgsCitation":"Brakebill, J., and Terziotti, S., 2011, A Digital Hydrologic Network Supporting NAWQA MRB SPARROW Modeling--MRB_E2RF1, Dataset, https://doi.org/10.3133/70046692.","productDescription":"Dataset","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[],"links":[{"id":274185,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":274184,"type":{"id":16,"text":"Metadata"},"url":"https://water.usgs.gov/GIS/metadata/usgswrd/XML/mrb_e2rf1.xml"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -127.859452,23.243486 ], [ -127.859452,51.549102 ], [ -65.377389,51.549102 ], [ -65.377389,23.243486 ], [ -127.859452,23.243486 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51cabbdfe4b0d298e5434c1d","contributors":{"authors":[{"text":"Brakebill, J. W.","contributorId":48206,"corporation":false,"usgs":true,"family":"Brakebill","given":"J. W.","affiliations":[],"preferred":false,"id":480023,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Terziotti, S.E.","contributorId":6287,"corporation":false,"usgs":true,"family":"Terziotti","given":"S.E.","email":"","affiliations":[],"preferred":false,"id":480022,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70042392,"text":"70042392 - 2011 - Biological and geochemical controls on diel dissolved inorganic carbon cycling in a low-order agricultural stream: Implications for reach scales and beyond","interactions":[],"lastModifiedDate":"2020-01-13T06:34:57","indexId":"70042392","displayToPublicDate":"2011-01-01T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1213,"text":"Chemical Geology","active":true,"publicationSubtype":{"id":10}},"title":"Biological and geochemical controls on diel dissolved inorganic carbon cycling in a low-order agricultural stream: Implications for reach scales and beyond","docAbstract":"Movement of dissolved inorganic carbon (DIC) through the hydrologic cycle is an important component of global carbon budgets, but there is considerable uncertainty about the controls of DIC transmission from landscapes to streams, and through river networks to the oceans. In this study, diel measurements of DIC, d13C-DIC, dissolved oxygen (O2), d18O-O2, alkalinity, pH, and other parameters were used to assess the relative magnitudes of biological and geochemical controls on DIC cycling and flux in a nutrient-rich, net autotrophic stream. Rates of photosynthesis (P), respiration (R), groundwater discharge, air–water exchange of CO2, and carbonate precipitation/dissolution were quantified through a time-stepping chemical/isotope (12C and 13C, 16O and 18O) mass balance model. Groundwater was the major source of DIC to the stream. Primary production and carbonate precipitation were equally important sinks for DIC removed from the water column. The stream was always super-saturated with respect to carbonate minerals, but carbonate precipitation occurred mainly during the day when P increased pH. We estimated more than half (possibly 90%) of the carbonate precipitated during the day was retained in the reach under steady baseflow conditions. The amount of DIC removed from the overlying water through carbonate precipitation was similar to the amount of DIC generated from R. Air–water exchange of CO2 was always from the stream to the atmosphere, but was the smallest component of the DIC budget. Overall, the in-stream DIC reactions reduced the amount of CO2 evasion and the downstream flux of groundwater-derived DIC by about half relative to a hypothetical scenario with groundwater discharge only. Other streams with similar characteristics are widely distributed in the major river basins of North America. Data from USGS water quality monitoring networks from the 1960s to the 1990s indicated that 40% of 652 stream monitoring stations in the contiguous USA were at or above the equilibrium saturation state for calcite, and 77% of all stations exhibited apparent increases in saturation state from the 1960/70s to the 1980/90s. Diel processes including partially irreversible carbonate precipitation may affect net carbon fluxes from many such watersheds.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.chemgeo.2010.12.012","usgsCitation":"Tobias, C., and Bohlke, J., 2011, Biological and geochemical controls on diel dissolved inorganic carbon cycling in a low-order agricultural stream: Implications for reach scales and beyond: Chemical Geology, v. 283, no. 1-2, p. 18-30, https://doi.org/10.1016/j.chemgeo.2010.12.012.","productDescription":"13 p.","startPage":"18","endPage":"30","ipdsId":"IP-022716","costCenters":[{"id":146,"text":"Branch of Regional Research-Eastern Region","active":false,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":265319,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -126.21093749999999,\n 49.49667452747045\n ],\n [\n -124.98046874999999,\n 46.07323062540835\n ],\n [\n -125.68359374999999,\n 42.032974332441405\n ],\n [\n -125.33203125,\n 39.232253141714885\n ],\n [\n -122.87109375,\n 36.1733569352216\n ],\n [\n -119.53125,\n 33.43144133557529\n ],\n [\n -116.3671875,\n 32.69486597787505\n ],\n [\n -111.4453125,\n 31.50362930577303\n ],\n [\n -106.875,\n 31.653381399664\n ],\n [\n -95.97656249999999,\n 25.005972656239187\n ],\n [\n -95.625,\n 27.68352808378776\n ],\n [\n -92.98828125,\n 29.38217507514529\n ],\n [\n -88.59374999999999,\n 28.613459424004414\n ],\n [\n -88.24218749999999,\n 29.84064389983441\n ],\n [\n -84.90234375,\n 28.613459424004414\n ],\n [\n -80.68359375,\n 24.046463999666567\n ],\n [\n -79.1015625,\n 25.48295117535531\n ],\n [\n -78.92578124999999,\n 30.751277776257812\n ],\n [\n -76.46484375,\n 34.59704151614417\n ],\n [\n -74.70703125,\n 37.020098201368114\n ],\n [\n -73.30078125,\n 38.8225909761771\n ],\n [\n -70.48828125,\n 40.84706035607122\n ],\n [\n -67.5,\n 43.83452678223682\n ],\n [\n -67.5,\n 47.27922900257082\n ],\n [\n -69.78515625,\n 47.27922900257082\n ],\n [\n -75.76171875,\n 45.82879925192134\n ],\n [\n -81.73828125,\n 42.16340342422401\n ],\n [\n -80.85937499999999,\n 45.089035564831036\n ],\n [\n -84.19921875,\n 46.92025531537451\n ],\n [\n -93.8671875,\n 49.38237278700955\n ],\n [\n -126.21093749999999,\n 49.49667452747045\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"283","issue":"1-2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50ebfc72e4b07f1501afcfc4","contributors":{"authors":[{"text":"Tobias, Craig","contributorId":90612,"corporation":false,"usgs":true,"family":"Tobias","given":"Craig","affiliations":[],"preferred":false,"id":471455,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bohlke, J.K. 0000-0001-5693-6455 jkbohlke@usgs.gov","orcid":"https://orcid.org/0000-0001-5693-6455","contributorId":191103,"corporation":false,"usgs":true,"family":"Bohlke","given":"J.K.","email":"jkbohlke@usgs.gov","affiliations":[{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":471454,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70044509,"text":"70044509 - 2011 - Measurement of net nitrogen and phosphorus mineralization in wetland soils using a modification of the resin-core technique","interactions":[],"lastModifiedDate":"2013-03-12T10:58:54","indexId":"70044509","displayToPublicDate":"2011-01-01T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1007,"text":"Biogeochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Measurement of net nitrogen and phosphorus mineralization in wetland soils using a modification of the resin-core technique","docAbstract":"A modification of the resin-core method was developed and tested for measuring in situ soil N and P net mineralization rates in wetland soils where temporal variation in bidirectional vertical water movement and saturation can complicate measurement. The modified design includes three mixed-bed ion-exchange resin bags located above and three resin bags located below soil incubating inside a core tube. The two inner resin bags adjacent to the soil capture NH4+, NO3-, and soluble reactive phosphorus (SRP) transported out of the soil during incubation; the two outer resin bags remove inorganic nutrients transported into the modified resin core; and the two middle resin bags serve as quality-control checks on the function of the inner and outer resin bags. Modified resin cores were incubated monthly for a year along the hydrogeomorphic gradient through a floodplain wetland. Only small amounts of NH4+, NO3-, and SRP were found in the two middle resin bags, indicating that the modified resin-core design was effective. Soil moisture and pH inside the modified resin cores typically tracked changes in the surrounding soil abiotic environment. In contrast, use of the closed polyethylene bag method provided substantially different net P and N mineralization rates than modified resin cores and did not track changes in soil moisture or pH. Net ammonification, nitrifi cation, N mineralization, and P mineralization rates measured using modified resin cores varied through space and time associated with hydrologic, geomorphic, and climatic gradients in the floodplain wetland. The modified resin-core technique successfully characterized spatiotemporal variation of net mineralization fluxes in situ and is a viable technique for assessing soil nutrient availability and developing ecosystem budgets.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Biogeochemistry","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Soil Science Society of America","publisherLocation":"Madison, WI","doi":"10.2136/sssaj2010.0289","usgsCitation":"Noe, G., 2011, Measurement of net nitrogen and phosphorus mineralization in wetland soils using a modification of the resin-core technique: Biogeochemistry, v. 75, no. 2, p. 760-770, https://doi.org/10.2136/sssaj2010.0289.","productDescription":"5 p.","startPage":"760","endPage":"770","numberOfPages":"5","additionalOnlineFiles":"N","ipdsId":"IP-018892","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":269134,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.2136/sssaj2010.0289"},{"id":269135,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"75","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51404e7fe4b089809dbf4482","contributors":{"authors":[{"text":"Noe, Gregory B.","contributorId":77805,"corporation":false,"usgs":true,"family":"Noe","given":"Gregory B.","affiliations":[],"preferred":false,"id":475774,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70044482,"text":"70044482 - 2011 - U.S. Geological Survey: A synopsis of Three-dimensional Modeling","interactions":[],"lastModifiedDate":"2013-06-04T11:47:27","indexId":"70044482","displayToPublicDate":"2011-01-01T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"U.S. Geological Survey: A synopsis of Three-dimensional Modeling","docAbstract":"The U.S. Geological Survey (USGS) is a multidisciplinary agency that provides assessments of natural resources (geological, hydrological, biological), the disturbances that affect those resources, and the disturbances that affect the built environment, natural landscapes, and human society. Until now, USGS map products have been generated and distributed primarily as 2-D maps, occasionally providing cross sections or overlays, but rarely allowing the ability to characterize and understand 3-D systems, how they change over time (4-D), and how they interact. And yet, technological advances in monitoring natural resources and the environment, the ever-increasing diversity of information needed for holistic assessments, and the intrinsic 3-D/4-D nature of the information obtained increases our need to generate, verify, analyze, interpret, confirm, store, and distribute its scientific information and products using 3-D/4-D visualization, analysis, modeling tools, and information frameworks. Today, USGS scientists use 3-D/4-D tools to (1) visualize and interpret geological information, (2) verify the data, and (3) verify their interpretations and models. 3-D/4-D visualization can be a powerful quality control tool in the analysis of large, multidimensional data sets. USGS scientists use 3-D/4-D technology for 3-D surface (i.e., 2.5-D) visualization as well as for 3-D volumetric analyses. Examples of geological mapping in 3-D include characterization of the subsurface for resource assessments, such as aquifer characterization in the central United States, and for input into process models, such as seismic hazards in the western United States.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Chapter 13 in Synopsis of Current Three-dimensional Geological Mapping and Modeling in Geological Survey Organizations","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"Illinois State Geological Survey","usgsCitation":"Jacobsen, L.J., Glynn, P.D., Phelps, G.A., Orndorff, R.C., Bawden, G.W., and Grauch, V.J., 2011, U.S. Geological Survey: A synopsis of Three-dimensional Modeling, chap. of Chapter 13 in Synopsis of Current Three-dimensional Geological Mapping and Modeling in Geological Survey Organizations, p. 69-79.","productDescription":"11 p.","startPage":"69","endPage":"79","ipdsId":"IP-024495","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":273203,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":273202,"type":{"id":11,"text":"Document"},"url":"https://water.usgs.gov/nrp/proj.bib/Publications/2011/jacobsen_glynn_etal_2011.pdf"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.8,24.5 ], [ -124.8,49.383333 ], [ -66.95,49.383333 ], [ -66.95,24.5 ], [ -124.8,24.5 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51af0c72e4b08a3322c2c372","contributors":{"authors":[{"text":"Jacobsen, Linda J.","contributorId":9159,"corporation":false,"usgs":true,"family":"Jacobsen","given":"Linda","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":475706,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Glynn, Pierre D. 0000-0001-8804-7003 pglynn@usgs.gov","orcid":"https://orcid.org/0000-0001-8804-7003","contributorId":2141,"corporation":false,"usgs":true,"family":"Glynn","given":"Pierre","email":"pglynn@usgs.gov","middleInitial":"D.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":475704,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Phelps, Geoff A.","contributorId":59328,"corporation":false,"usgs":true,"family":"Phelps","given":"Geoff","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":475708,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Orndorff, Randall C. 0000-0002-8956-5803 rorndorf@usgs.gov","orcid":"https://orcid.org/0000-0002-8956-5803","contributorId":2739,"corporation":false,"usgs":true,"family":"Orndorff","given":"Randall","email":"rorndorf@usgs.gov","middleInitial":"C.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":501,"text":"Office of Science Quality and Integrity","active":true,"usgs":true}],"preferred":true,"id":475705,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bawden, Gerald W. gbawden@usgs.gov","contributorId":1071,"corporation":false,"usgs":true,"family":"Bawden","given":"Gerald","email":"gbawden@usgs.gov","middleInitial":"W.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":475703,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Grauch, V. 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These regions correspond with the U.S. Geological Survey's National Water Quality Assessment (NAWQA) Program Major River Basin (MRB) study units 2, 3, 4, 5, and 7 (Preston and others, 2009). MRB2, covers the South Atlantic-Gulf and Tennessee River basins. MRB3, covers the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy River basins. MRB4, covers the Missouri River basins. MRB5, covers the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf River basins. MRB7, covers the Pacific Northwest River basins. The digital hydrologic network described here represents surface-water pathways (MRB_E2RF1) and associated catchments (MRB_E2RF1WS). It serves as the fundamental framework to spatially reference and summarize explanatory information supporting nutrient SPARROW models (Brakebill and others, 2011; Wieczorek and LaMotte, 2011). The principal geospatial dataset used to support this regional effort was based on an enhanced version of a 1:500,000 scale digital stream-reach network (ERF1_2) (Nolan et al., 2002). Enhancements included associating over 3,500 water-quality monitoring sites to the reach network, improving physical locations of stream reaches at or near monitoring locations, and generating drainage catchments based on 100m elevation data. A unique number (MRB_ID) identifies each reach as a single unit. This unique number is also shared by the catchment area drained by the reach, thus spatially linking the hydrologically connected streams and the respective drainage area characteristics. In addition, other relevant physical, environmental, and monitoring information can be associated to the common network and accessed using the unique identification number.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/70046785","usgsCitation":"Brakebill, J., and Terziotti, S., 2011, A Digital Hydrologic Network Supporting NAWQA MRB SPARROW Modeling--MRB_E2RF1WS (1.0): General Information, Dataset, https://doi.org/10.3133/70046785.","productDescription":"Dataset","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[],"links":[{"id":274631,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":274629,"type":{"id":16,"text":"Metadata"},"url":"https://water.usgs.gov/GIS/metadata/usgswrd/XML/mrb_e2rf1ws.xml"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -128.290499,23.033207 ], [ -128.290499,52.450082 ], [ -64.959844,52.450082 ], [ -64.959844,23.033207 ], [ -128.290499,23.033207 ] ] ] } } ] }","edition":"1.0","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51dbdf64e4b0f81004b77c9f","contributors":{"authors":[{"text":"Brakebill, J. W.","contributorId":48206,"corporation":false,"usgs":true,"family":"Brakebill","given":"J. W.","affiliations":[],"preferred":false,"id":480249,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Terziotti, S.E.","contributorId":6287,"corporation":false,"usgs":true,"family":"Terziotti","given":"S.E.","email":"","affiliations":[],"preferred":false,"id":480248,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70194902,"text":"70194902 - 2011 - Waste isolation and contaminant migration - Tools and techniques for monitoring the saturated zone-unsaturated zone-plant-atmosphere continuum","interactions":[],"lastModifiedDate":"2018-01-27T11:31:43","indexId":"70194902","displayToPublicDate":"2011-01-01T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"seriesNumber":"NUREG/CP-0195","chapter":"3.5.1","title":"Waste isolation and contaminant migration - Tools and techniques for monitoring the saturated zone-unsaturated zone-plant-atmosphere continuum","docAbstract":"Projected increases in aridity throughout the southwestern United States due to anthropogenic climate change will likely cause reductions in perennial vegetation cover, which leaves soil surfaces exposed to erosion. Accelerated rates of dust emission from wind erosion have large implications for ecosystems and human well-being, yet there is poor understanding of the sources and magnitude of dust emission in a hotter and drier climate. Here we use a two-stage approach to compare the susceptibility of grasslands and three different shrublands to wind erosion on the Colorado Plateau and demonstrate how climate can indirectly moderate the magnitude of aeolian sediment flux through different responses of dominant plants in these communities. First, using results from 20 y of vegetation monitoring, we found perennial grass cover in grasslands declined with increasing mean annual temperature in the previous year, whereas shrub cover in shrublands either showed no change or declined as temperature increased, depending on the species. Second, we used these vegetation monitoring results and measurements of soil stability as inputs into a field-validated wind erosion model and found that declines in perennial vegetation cover coupled with disturbance to biological soil crust resulted in an exponential increase in modeled aeolian sediment flux. Thus the effects of increased temperature on perennial plant cover and the correlation of declining plant cover with increased aeolian flux strongly suggest that sustained drought conditions across the southwest will accelerate the likelihood of dust production in the future on disturbed soil surfaces.
","language":"English","publisher":"National Academy of Sciences","publisherLocation":"Washington, D.C.","doi":"10.1073/pnas.1014947108","usgsCitation":"Munson, S.M., Belnap, J., and Okin, G.S., 2011, Responses of wind erosion to climate-induced vegetation changes on the Colorado Plateau: Proceedings of the National Academy of Sciences, v. 108, no. 10, p. 3854-3859, https://doi.org/10.1073/pnas.1014947108.","productDescription":"6 p.","startPage":"3854","endPage":"3859","numberOfPages":"6","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":475208,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1073/pnas.1014947108","text":"External Repository"},{"id":259593,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","otherGeospatial":"Colorado Plateau","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.1541748046875,\n 37.09900294387622\n ],\n [\n -109.22607421875,\n 37.09900294387622\n ],\n [\n -109.22607421875,\n 38.94659331893374\n ],\n [\n -111.1541748046875,\n 38.94659331893374\n ],\n [\n -111.1541748046875,\n 37.09900294387622\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"108","issue":"10","noUsgsAuthors":false,"publicationDate":"2011-02-22","publicationStatus":"PW","scienceBaseUri":"505aaab2e4b0c8380cd864a1","contributors":{"authors":[{"text":"Munson, Seth M. 0000-0002-2736-6374 smunson@usgs.gov","orcid":"https://orcid.org/0000-0002-2736-6374","contributorId":1334,"corporation":false,"usgs":true,"family":"Munson","given":"Seth","email":"smunson@usgs.gov","middleInitial":"M.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":466460,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Belnap, Jayne 0000-0001-7471-2279 jayne_belnap@usgs.gov","orcid":"https://orcid.org/0000-0001-7471-2279","contributorId":1332,"corporation":false,"usgs":true,"family":"Belnap","given":"Jayne","email":"jayne_belnap@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":466459,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Okin, Gregory S.","contributorId":50025,"corporation":false,"usgs":true,"family":"Okin","given":"Gregory","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":466461,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70004382,"text":"70004382 - 2011 - Introduction","interactions":[],"lastModifiedDate":"2021-10-11T18:09:58.096845","indexId":"70004382","displayToPublicDate":"2011-01-01T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Introduction","docAbstract":"Ecotoxicology is the study of the movement of environmental contaminants through ecosystems and their effects on plants and animals. Examining tissue residues of these contaminants in biota is basic to ecotoxicology, both for understanding the movement of contaminants within organisms and through food chains, and for understanding and quantifying injuries to organisms and their communities. This book provides guidance on interpreting tissue concentrations of environmental contaminants.
Tissue concentrations have long been used both to identify the cause of toxicity in animals and as a measure of the severity of toxicity. More recently, they have been incorporated into environmental models, tying together exposure, kinetics, and toxic effects. Measuring tissue concentrations is basic to studies on the kinetics of contaminants, which entails characterizing the rates of uptake and elimination in organisms, as well as redistribution (organs, lipid, and plasma) within them. Tissue concentrations are also used in ecological studies examining the movement of contaminants between organisms and within biological communities.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Environmental contaminants in biota: Interpreting tissue concentrations, Second Edition","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Taylor & Francis","doi":"10.1201/b10598-1","usgsCitation":"Beyer, W.N., and Meador, J., 2011, Introduction, chap. of Environmental contaminants in biota: Interpreting tissue concentrations, Second Edition, p. 1-6, https://doi.org/10.1201/b10598-1.","productDescription":"6 p.","startPage":"1","endPage":"6","ipdsId":"IP-020126","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":475319,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1201/b10598-1","text":"Publisher Index Page"},{"id":342737,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"edition":"2nd Edition","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"594b85b4e4b062508e382b85","contributors":{"editors":[{"text":"Beyer, W. Nelson 0000-0002-8911-9141 nbeyer@usgs.gov","orcid":"https://orcid.org/0000-0002-8911-9141","contributorId":3301,"corporation":false,"usgs":true,"family":"Beyer","given":"W.","email":"nbeyer@usgs.gov","middleInitial":"Nelson","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":825006,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Meador, James P.","contributorId":174075,"corporation":false,"usgs":false,"family":"Meador","given":"James P.","affiliations":[],"preferred":false,"id":698991,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Beyer, W. Nelson 0000-0002-8911-9141 nbeyer@usgs.gov","orcid":"https://orcid.org/0000-0002-8911-9141","contributorId":3301,"corporation":false,"usgs":true,"family":"Beyer","given":"W.","email":"nbeyer@usgs.gov","middleInitial":"Nelson","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":698989,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Meador, James P.","contributorId":174075,"corporation":false,"usgs":false,"family":"Meador","given":"James P.","affiliations":[],"preferred":false,"id":698990,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70157248,"text":"70157248 - 2011 - Swallows as a sentinel species for contaminant exposure and effect studies","interactions":[],"lastModifiedDate":"2021-11-09T17:36:53.636876","indexId":"70157248","displayToPublicDate":"2011-01-01T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Swallows as a sentinel species for contaminant exposure and effect studies","docAbstract":"Tree swallows are an important model species to study the effects of contaminants in wild bird populations and have been used extensively in studies across North America. The advantages of swallows compared to other avian species are detailed. Three case histories are provided where swallows have been successfully used in Natural Resource Damage and Ecological Risk Assessments. The final two sections of this chapter are for individuals who want more in-depth information and include a summary of the chemical classes for which there are swallow data, including effect levels when known. Information provided in this section can be used to put exposure to most classes of contaminants into context with other sites across North America. Finally, commonly used endpoints, ranging from population-level down to cellular and genetic endpoints, are discussed including considerations and pitfalls, and when further work is needed to more fully understand the role of environmental and biological variation in interpreting these endpoints.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Wildlife ecotoxicology: Forensic approaches","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","publisherLocation":"New York, NY","doi":"10.1007/978-0-387-89432-4_3","usgsCitation":"Custer, C.M., 2011, Swallows as a sentinel species for contaminant exposure and effect studies, chap. of Wildlife ecotoxicology: Forensic approaches, p. 45-91, https://doi.org/10.1007/978-0-387-89432-4_3.","productDescription":"47 p.","startPage":"45","endPage":"91","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-015056","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":308137,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2011-05-31","publicationStatus":"PW","scienceBaseUri":"55f94142e4b05d6c4e5013a9","contributors":{"editors":[{"text":"Elliott, John G. jelliott@usgs.gov","contributorId":832,"corporation":false,"usgs":true,"family":"Elliott","given":"John","email":"jelliott@usgs.gov","middleInitial":"G.","affiliations":[],"preferred":true,"id":572406,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Bishop, Christine Annette","contributorId":147717,"corporation":false,"usgs":false,"family":"Bishop","given":"Christine","email":"","middleInitial":"Annette","affiliations":[],"preferred":false,"id":572407,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Morrissey, Christy A.","contributorId":147718,"corporation":false,"usgs":false,"family":"Morrissey","given":"Christy","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":572408,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Custer, Christine M. 0000-0003-0500-1582 ccuster@usgs.gov","orcid":"https://orcid.org/0000-0003-0500-1582","contributorId":1143,"corporation":false,"usgs":true,"family":"Custer","given":"Christine","email":"ccuster@usgs.gov","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":572409,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70035060,"text":"70035060 - 2011 - Diurnal trends in methylmercury concentration in a wetland adjacent to Great Salt Lake, Utah, USA","interactions":[],"lastModifiedDate":"2020-01-11T10:49:18","indexId":"70035060","displayToPublicDate":"2011-01-01T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1213,"text":"Chemical Geology","active":true,"publicationSubtype":{"id":10}},"title":"Diurnal trends in methylmercury concentration in a wetland adjacent to Great Salt Lake, Utah, USA","docAbstract":"A 24-h field experiment was conducted during July 2008 at a wetland on the eastern shore of Great Salt Lake (GSL) to assess the diurnal cycling of methylmercury (MeHg). Dissolved (< 0.45 μm) MeHg showed a strong diurnal variation with consistently decreasing concentrations during daylight periods and increasing concentrations during non-daylight periods. The proportion of MeHg relative to total Hg in the water column consistently decreased with increasing sunlight duration, indicative of photodegradation. During the field experiment, measured MeHg photodegradation rates ranged from 0.02 to 0.06 ng L− 1 h− 1. Convective overturn of the water column driven by nighttime cooling of the water surface was hypothesized as the likely mechanism to replace the MeHg in the water column lost via photodegradation processes. A hydrodynamic model of the wetland successfully simulated convective overturn of the water column during the field experiment. Study results indicate that daytime monitoring of selected wetlands surrounding GSL may significantly underestimate the MeHg content in the water column. Wetland managers should consider practices that maximize the photodegradation of MeHg during daylight periods.
Nightlight surveys are commonly used to evaluate status and trends of crocodilian populations, but imperfect detection caused by survey- and location-specific factors makes it difficult to draw population inferences accurately from uncorrected data. We used a two-stage hierarchical model comprising population abundance and detection probability to examine recent abundance trends of American alligators (Alligator mississippiensis) in subareas of Everglades wetlands in Florida using nightlight survey data. During 2001–2008, there were declining trends in abundance of small and/or medium sized animals in a majority of subareas, whereas abundance of large sized animals had either demonstrated an increased or unclear trend. For small and large sized class animals, estimated detection probability declined as water depth increased. Detection probability of small animals was much lower than for larger size classes. The declining trend of smaller alligators may reflect a natural population response to the fluctuating environment of Everglades wetlands under modified hydrology. It may have negative implications for the future of alligator populations in this region, particularly if habitat conditions do not favor recruitment of offspring in the near term. Our study provides a foundation to improve inferences made from nightlight surveys of other crocodilian populations.
","language":"English","publisher":"Springer","publisherLocation":"Amsterdam, Netherlands","doi":"10.1007/s13157-010-0120-0","usgsCitation":"Fujisaki, I., Mazzotti, F., Dorazio, R.M., Rice, K.G., Cherkiss, M., and Jeffery, B., 2011, Estimating trends in alligator populations from nightlight survey data: Wetlands, v. 31, no. 1, p. 147-155, https://doi.org/10.1007/s13157-010-0120-0.","productDescription":"9 p.","startPage":"147","endPage":"155","temporalStart":"2001-01-01","temporalEnd":"2008-12-31","costCenters":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"links":[{"id":256864,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Everglades","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.84814453125,\n 25.110471486223346\n ],\n [\n -80.2716064453125,\n 25.110471486223346\n ],\n [\n -80.2716064453125,\n 26.559049984075532\n ],\n [\n -81.84814453125,\n 26.559049984075532\n ],\n [\n -81.84814453125,\n 25.110471486223346\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"31","issue":"1","noUsgsAuthors":false,"publicationDate":"2011-01-11","publicationStatus":"PW","scienceBaseUri":"505a0b6ae4b0c8380cd526f4","contributors":{"authors":[{"text":"Fujisaki, Ikuko","contributorId":31108,"corporation":false,"usgs":false,"family":"Fujisaki","given":"Ikuko","email":"","affiliations":[{"id":12557,"text":"University of Florida, FLREC","active":true,"usgs":false}],"preferred":false,"id":350107,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":350110,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dorazio, Robert M. 0000-0003-2663-0468 bob_dorazio@usgs.gov","orcid":"https://orcid.org/0000-0003-2663-0468","contributorId":1668,"corporation":false,"usgs":true,"family":"Dorazio","given":"Robert","email":"bob_dorazio@usgs.gov","middleInitial":"M.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":false,"id":350106,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rice, Kenneth G. 0000-0001-8282-1088 krice@usgs.gov","orcid":"https://orcid.org/0000-0001-8282-1088","contributorId":117,"corporation":false,"usgs":true,"family":"Rice","given":"Kenneth","email":"krice@usgs.gov","middleInitial":"G.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":350105,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cherkiss, Michael 0000-0002-7802-6791","orcid":"https://orcid.org/0000-0002-7802-6791","contributorId":78068,"corporation":false,"usgs":true,"family":"Cherkiss","given":"Michael","affiliations":[],"preferred":false,"id":350109,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jeffery, Brian","contributorId":55672,"corporation":false,"usgs":true,"family":"Jeffery","given":"Brian","affiliations":[],"preferred":false,"id":350108,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70004642,"text":"70004642 - 2011 - Factors associated with extirpation of sage-grouse","interactions":[],"lastModifiedDate":"2022-12-20T14:22:38.629943","indexId":"70004642","displayToPublicDate":"2011-01-01T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"18","title":"Factors associated with extirpation of sage-grouse","docAbstract":"Geographic ranges of Greater Sage-Grouse (Centrocercus urophasianus) and Gunnison Sage-Grouse (C. minimus) have contracted across large areas in response to habitat loss and detrimental land uses. However, quantitative analyses of the environmental factors most closely associated with range contraction have been lacking, results of which could be highly relevant to conservation planning. Consequently, we analyzed differences in 22 environmental variables between areas of former range (extirpated range), and areas still occupied by the two species (occupied range). Fifteen of the 22 variables, representing a broad spectrum of biotic, abiotic, and anthropogenic conditions, had mean values that were significantly different between extirpated and occupied ranges. Best discrimination between extirpated and occupied ranges, using discriminant function analysis (DFA), was provided by five of these variables: sagebrush area (Artemisia spp.); elevation; distance to transmission lines; distance to cellular towers; and land ownership. A DFA model containing these five variables correctly classified 80% of sage-grouse historical locations to extirpated and occupied ranges. We used this model to estimate the similarity between areas of occupied range with areas where extirpation has occurred. Areas currently occupied by sage-grouse, but with high similarity to extirpated range, may not support persistent populations. Model estimates showed that areas of highest similarity were concentrated in the smallest, disjunct portions of occupied range and along range peripheries. Large areas in the eastern portion of occupied range also had high similarity with extirpated range. By contrast, areas of lowest similarity with extirpated range were concentrated in the largest, most contiguous portions of occupied range that dominate Oregon, Idaho, Nevada, and western Wyoming. Our results have direct relevance to conservation planning. We describe how results can be used to identify strongholds and spatial priorities for effective landscape management of sage-grouse.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Greater Sage-Grouse: Ecology and conservation of a landscape species and Its habitats","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"University of California Press","publisherLocation":"Berkeley, CA","usgsCitation":"Wisdom, M.J., Meinke, C.W., Knick, S.T., and Schroeder, M.A., 2011, Factors associated with extirpation of sage-grouse, chap. 18 of Greater Sage-Grouse: Ecology and conservation of a landscape species and Its habitats, p. 451-474.","productDescription":"24 p.","startPage":"451","endPage":"474","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":203953,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":24568,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.ucpress.edu/book.php?isbn=9780520267114","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a05e4b07f02db5f86aa","contributors":{"authors":[{"text":"Wisdom, Michael J.","contributorId":63934,"corporation":false,"usgs":true,"family":"Wisdom","given":"Michael","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":350926,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Meinke, Cara W.","contributorId":85708,"corporation":false,"usgs":true,"family":"Meinke","given":"Cara","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":350927,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Knick, Steven T. 0000-0003-4025-1704 steve_knick@usgs.gov","orcid":"https://orcid.org/0000-0003-4025-1704","contributorId":159,"corporation":false,"usgs":true,"family":"Knick","given":"Steven","email":"steve_knick@usgs.gov","middleInitial":"T.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":350924,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schroeder, Michael A.","contributorId":26053,"corporation":false,"usgs":true,"family":"Schroeder","given":"Michael","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":350925,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70003749,"text":"70003749 - 2011 - Comparisons of watershed sulfur budgets in southeast Canada and northeast US: New approaches and implications","interactions":[],"lastModifiedDate":"2021-03-22T14:56:58.941982","indexId":"70003749","displayToPublicDate":"2011-01-01T00:00:00","publicationYear":"2011","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1007,"text":"Biogeochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Comparisons of watershed sulfur budgets in southeast Canada and northeast US: New approaches and implications","docAbstract":"Most of eastern North America receives elevated levels of atmospheric deposition of sulfur (S) that result from anthropogenic SO2 emissions from fossil fuel combustion. Atmospheric S deposition has acidified sensitive terrestrial and aquatic ecosystems in this region; however, deposition has been declining since the 1970s, resulting in some recovery in previously acidified aquatic ecosystems. Accurate watershed S mass balances help to evaluate the extent to which atmospheric S deposition is retained within ecosystems, and whether internal cycling sources and biogeochemical processes may be affecting the rate of recovery from decreasing S atmospheric loads. This study evaluated S mass balances for 15 sites with watersheds in southeastern Canada and northeastern US for the period 1985 to 2002. These 15 sites included nine in Canada (Turkey Lakes, ON; Harp Lake, ON; Plastic Lake, ON; Hermine, QC; Lake Laflamme, QC; Lake Clair, QC; Lake Tirasse, QC; Mersey, NS; Moosepit, NS) and six in the US (Arbutus Lake, NY; Biscuit Brook, NY; Sleepers River, VT; Hubbard Brook Experimental Forest, NH; Cone Pond, NH; Bear Brook Watershed, ME). Annual S wet deposition inputs were derived from measured bulk or wet-only deposition and stream export was obtained by combining drainage water fluxes with SO4 2− concentrations. Dry deposition has the greatest uncertainty of any of the mass flux calculations necessary to develop accurate watershed balances, and here we developed a new method to calculate this quantity. We utilized historical information from both the US National Emissions Inventory and the US (CASTNET) and the Canadian (CAPMoN) dry deposition networks to develop a formulation that predicted SO2 concentrations as a function of SO2 emissions, latitude and longitude. The SO2 concentrations were used to predict dry deposition using relationships between concentrations and deposition flux derived from the CASTNET or CAPMoN networks. For the year 2002, we compared the SO2 concentrations and deposition predictions with the predictions of two continental-scale air quality models, the Community Multiscale Air Quality (CMAQ) model and A Unified Regional Air-quality Modeling System (AURAMS) that utilize complete inventories of emissions and chemical budgets. The results of this comparison indicated that the predictive relationship provides an accurate representation of SO2 concentrations and S deposition for the region that is generally consistent with these models, and thus provides confidence that our approach could be used to develop accurate watershed S budgets for these 15 sites. Most watersheds showed large net losses of SO4 2− on an annual basis, and the watershed mass balances were grouped into five categories based on the relative value of mean annual net losses or net gains. The net annual fluxes of SO4 2− showed a strong relationship with hydrology; the largest net annual negative fluxes were associated with years of greatest precipitation amount and highest discharge. The important role of catchment hydrology on S budgets suggests implications for future predicted climate change as it affects patterns of precipitation and drought. The sensitivity of S budgets is likely to be greatest in watersheds with the greatest wetland area, which are particularly sensitive to drying and wetting cycles. A small number of the watersheds in this analysis were shown to have substantial S sources from mineral weathering, but most showed evidence of an internal source of SO4 2−, which is likely from the mineralization of organic S stored from decades of increased S deposition. Mobilization of this internal S appears to contribute about 1–6 kg S ha−1 year−1 to stream fluxes at these sites and is affecting the rate and extent of recovery from acidification as S deposition rates have declined in recent years. This internal S source should be considered when developing critical deposition loads that will promote ecosystem recovery from acidification and the depletion of nutrient cations in the northeastern US and southeastern Canada.
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We modeled vegetation change and the probability of occurrence of birds to project changes in winter bird distributions associated with climate change and fire management in the northern Chihuahuan Desert (southwestern U.S.A.). We simulated vegetation change in a process-based model (Landscape and Fire Simulator) in which anticipated climate change was associated with doubling of current atmospheric carbon dioxide over the next 50 years. We estimated the relative probability of bird occurrence on the basis of statistical models derived from field observations of birds and data on vegetation type, topography, and roads. We selected 3 focal species, Scaled Quail (Callipepla squamata), Loggerhead Shrike (Lanius ludovicianus), and Rock Wren (Salpinctes obsoletus), that had a range of probabilities of occurrence for our study area. Our simulations projected increases in relative probability of bird occurrence in shrubland and decreases in grassland and Yucca spp. and ocotillo (Fouquieria splendens) vegetation. Generally, the relative probability of occurrence of all 3 species was highest in shrubland because leaf-area index values were lower in shrubland. This high probability of occurrence likely is related to the species' use of open vegetation for foraging. Fire suppression had little effect on projected vegetation composition because as climate changed there was less fuel and burned area. Our results show that if future water limits on plant type are considered, models that incorporate spatial data may suggest how and where different species of birds may respond to vegetation changes.
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Actively growing forests are generally considered to be a major carbon sink, but forest wildfires lead to large releases of biomass carbon into the atmosphere. Aboveground forest biomass carbon (AFBC), an important ecological indicator, and fire-induced carbon emissions at regional scales are highly relevant to forest sustainable management and climate change. It is challenging to accurately estimate the spatial distribution of AFBC across large areas because of the spatial heterogeneity of forest cover types and canopy structure. In this study, Forest Inventory and Analysis (FIA) data, Landsat, and Landscape Fire and Resource Management Planning Tools Project (LANDFIRE) data were integrated in a regression tree model for estimating AFBC at a 30-m resolution in the Utah High Plateaus. AFBC were calculated from 225 FIA field plots and used as the dependent variable in the model. Of these plots, 10% were held out for model evaluation with stratified random sampling, and the other 90% were used as training data to develop the regression tree model. Independent variable layers included Landsat imagery and the derived spectral indicators, digital elevation model (DEM) data and derivatives, biophysical gradient data, existing vegetation cover type and vegetation structure. The cross-validation correlation coefficient (r value) was 0.81 for the training model. Independent validation using withheld plot data was similar with r value of 0.82. This validated regression tree model was applied to map AFBC in the Utah High Plateaus and then combined with burn severity information to estimate loss of AFBC in the Longston fire of Zion National Park in 2001. The final dataset represented 24 forest cover types for a 4 million ha forested area. We estimated a total of 353 Tg AFBC with an average of 87 MgC/ha in the Utah High Plateaus. We also estimated that 8054 Mg AFBC were released from 2.24 km2 burned forest area in the Longston fire. These results demonstrate that an AFBC spatial map and estimated biomass carbon consumption can readily be generated using existing database. The methodology provides a consistent, practical, and inexpensive way for estimating AFBC at 30-m resolution over large areas throughout the United States.
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