In cooperation with the Harris–Galveston Subsidence District, Fort Bend Subsidence District, and Lone Star Groundwater Conservation District, the U.S. Geological Survey developed and calibrated the Houston Area Groundwater Model (HAGM), which simulates groundwater flow and land-surface subsidence in the northern part of the Gulf Coast aquifer system in Texas from predevelopment (before 1891) through 2009. Withdrawal of groundwater since development of the aquifer system has resulted in potentiometric surface (hydraulic head, or head) declines in the Gulf Coast aquifer system and land-surface subsidence (primarily in the Houston area) from depressurization and compaction of clay layers interbedded in the aquifer sediments.
\nThe MODFLOW-2000 groundwater flow model described in this report comprises four layers, one for each of the hydrogeologic units of the aquifer system except the Catahoula confining system, the assumed no-flow base of the system. The HAGM is composed of 137 rows and 245 columns of 1-square-mile grid cells with lateral no-flow boundaries at the extent of each hydrogeologic unit to the northwest, at groundwater divides associated with large rivers to the southwest and northeast, and at the downdip limit of freshwater to the southeast. The model was calibrated within the specified criteria by using trial-and-error adjustment of selected model-input data in a series of transient simulations until the model output (potentiometric surfaces, land-surface subsidence, and selected water-budget components) acceptably reproduced field measured (or estimated) aquifer responses including water level and subsidence. The HAGM-simulated subsidence generally compared well to 26 Predictions Relating Effective Stress to Subsidence (PRESS) models in Harris, Galveston, and Fort Bend Counties. Simulated HAGM results indicate that as much as 10 feet (ft) of subsidence has occurred in southeastern Harris County. Measured subsidence and model results indicate that a larger geographic area encompassing this area of maximum subsidence and much of central to southeastern Harris County has subsided at least 6 ft. For the western part of the study area, the HAGM simulated as much as 3 ft of subsidence in Wharton, Jackson, and Matagorda Counties. For the eastern part of the study area, the HAGM simulated as much as 3 ft of subsidence at the boundary of Hardin and Jasper Counties. Additionally, in the southeastern part of the study area in Orange County, the HAGM simulated as much as 3 ft of subsidence. Measured subsidence for these areas in the western and eastern parts of the HAGM has not been documented.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125154","collaboration":"Prepared in cooperation with the Harris–Galveston Subsidence District, the Fort Bend Subsidence District, and the Lone Star Groundwater Conservation District","usgsCitation":"Kasmarek, M.C., 2012, Hydrogeology and simulation of groundwater flow and land-surface subsidence in the northern part of the Gulf Coast aquifer system, Texas, 1891-2009 (Originally posted July 31, 2012; Revised December 2, 2013): U.S. Geological Survey Scientific Investigations Report 2012-5154, ix, 55 p., https://doi.org/10.3133/sir20125154.","productDescription":"ix, 55 p.","numberOfPages":"69","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":404562,"rank":3,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5154/","linkFileType":{"id":5,"text":"html"}},{"id":259327,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5154.gif"},{"id":259324,"rank":299,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5154/pdf/sir2012-5154.pdf","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Texas","otherGeospatial":"Gulf Coast Aquifer System","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -96.38,29.03 ], [ -96.38,31.18 ], [ -93.51,31.18 ], [ -93.51,29.03 ], [ -96.38,29.03 ] ] ] } } ] }","edition":"Originally posted July 31, 2012; Revised December 2, 2013","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a345ce4b0c8380cd5f6ea","contributors":{"authors":[{"text":"Kasmarek, Mark C. 0000-0003-2808-2506 mckasmar@usgs.gov","orcid":"https://orcid.org/0000-0003-2808-2506","contributorId":1968,"corporation":false,"usgs":true,"family":"Kasmarek","given":"Mark","email":"mckasmar@usgs.gov","middleInitial":"C.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":465965,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70039285,"text":"ofr20121156 - 2012 - Model of whooping crane energetics as foundation for development of a method to assess potential take during migration","interactions":[],"lastModifiedDate":"2018-01-04T12:49:37","indexId":"ofr20121156","displayToPublicDate":"2012-07-31T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-1156","title":"Model of whooping crane energetics as foundation for development of a method to assess potential take during migration","docAbstract":"A whooping crane energetic model was developed as a component of a larger effort to ascertain potential take, as defined by the Endangered Species Act, of whooping cranes from proposed development of wind-energy infrastructure in the Great Plains of North America. The primary objectives of this energetic model were to (1) predict extra flight energy that whooping cranes may require to find suitable migration stopover sites if they are unable to use a primary site; and (2) express energy expended as additional time required to replenish lipid reserves used to fuel flight. The energetic model is based on three elements related to energy: expenditure of energy, intake of energy, and constraints to energy intake. The energetic model estimates each element and recognizes interactions among them. This framework will be most useful when integrated into a migration model that predicts incidence of avoidance of wind towers by whooping cranes and distances they might fly to find alternative stopover habitat. This report details work conducted in accordance with the U.S. Geological Survey and U.S. Fish and Wildlife Service Quick Response Program funded in fiscal year 2011 and will serve as a final report.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121156","collaboration":"Prepared in collaboration with the U.S. Fish and Wildlife Service","usgsCitation":"Pearse, A.T., and Selbo, S.M., 2012, Model of whooping crane energetics as foundation for development of a method to assess potential take during migration: U.S. Geological Survey Open-File Report 2012-1156, iv, 13 p.; Appendix, https://doi.org/10.3133/ofr20121156.","productDescription":"iv, 13 p.; Appendix","startPage":"i","endPage":"13","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":259335,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":259321,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1156/","linkFileType":{"id":5,"text":"html"}},{"id":259322,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1156/of12-1156.pdf","linkFileType":{"id":1,"text":"pdf"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a5bb1e4b0c8380cd6f733","contributors":{"authors":[{"text":"Pearse, Aaron T. 0000-0002-6137-1556 apearse@usgs.gov","orcid":"https://orcid.org/0000-0002-6137-1556","contributorId":1772,"corporation":false,"usgs":true,"family":"Pearse","given":"Aaron","email":"apearse@usgs.gov","middleInitial":"T.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":465963,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Selbo, Sarena M.","contributorId":85027,"corporation":false,"usgs":true,"family":"Selbo","given":"Sarena","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":465964,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70039284,"text":"sim3210 - 2012 - Flood-inundation maps for the Driftwood River and Sugar Creek near Edinburgh, Indiana","interactions":[],"lastModifiedDate":"2012-08-01T01:01:41","indexId":"sim3210","displayToPublicDate":"2012-07-31T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3210","title":"Flood-inundation maps for the Driftwood River and Sugar Creek near Edinburgh, Indiana","docAbstract":"Digital flood-inundation maps for an 11.2 mile reach of the Driftwood River and a 5.2 mile reach of Sugar Creek, both near Edinburgh, Indiana, were created by the U.S. Geological Survey (USGS) in cooperation with the Camp Atterbury Joint Maneuver Training Center, Edinburgh, Indiana. The inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation/, depict estimates of the areal extent of flooding corresponding to selected water levels (stages) at the USGS streamgage 03363000 Driftwood River near Edinburgh, Ind. Current conditions at the USGS streamgage in Indiana may be obtained on the Internet at http://waterdata.usgs.gov/in/nwis/current/?type=flow. In addition, the information has been provided to the National Weather Service (NWS) for incorporation into their Advanced Hydrologic Prediction Service (AHPS) flood warning system at http://water.weather.gov/ahps/. The NWS forecasts flood hydrographs at many places that are often collocated at USGS streamgages. That forecasted peak-stage information, also available on the Internet, may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation. For this study, flood profiles were computed for the stream reaches by means of a one-dimensional step-backwater model. The model was calibrated using the most current stage-discharge relations at the USGS streamgage 03363000 Driftwood River near Edinburgh, Ind. The hydraulic model was then used to determine elevations throughout the study reaches for nine water-surface profiles for flood stages at 1-ft intervals referenced to the streamgage datum and ranging from bankfull to nearly the highest recorded water level at the USGS streamgage 03363000 Driftwood River near Edinburgh, Ind. The simulated water-surface profiles were then combined with a geospatial digital elevation model (derived from Light Detection and Ranging (LiDAR) data) in order to delineate the area flooded at each water level. The availability of these maps along with real-time information available online regarding current stage from USGS streamgages and forecasted stream stages from the NWS provide emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures as well as for post flood recovery efforts.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3210","collaboration":"Prepared in cooperation with Camp Atterbury Joint Maneuver Training Center, Edinburgh, Indiana","usgsCitation":"Fowler, K.K., Kim, M.H., and Menke, C.D., 2012, Flood-inundation maps for the Driftwood River and Sugar Creek near Edinburgh, Indiana: U.S. Geological Survey Scientific Investigations Map 3210, v, 8 p.; map (col.); 8 MB PDF Downloads of Sheets 1-9: 17 x 22 inches; 1.1 MB PDF Downloads of Sheets 1-9: 17 x 22 inches; Downloads Directory, https://doi.org/10.3133/sim3210.","productDescription":"v, 8 p.; map (col.); 8 MB PDF Downloads of Sheets 1-9: 17 x 22 inches; 1.1 MB PDF Downloads of Sheets 1-9: 17 x 22 inches; Downloads Directory","startPage":"i","endPage":"8","numberOfPages":"17","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":259330,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim_3210.gif"},{"id":259318,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3210/SIM3210_Pamphlet.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":259317,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3210/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Indiana","city":"Edinburgh","otherGeospatial":"Sugar Creek;Driftwood River","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a1167e4b0c8380cd53fa7","contributors":{"authors":[{"text":"Fowler, Kathleen K. 0000-0002-0107-3848 kkfowler@usgs.gov","orcid":"https://orcid.org/0000-0002-0107-3848","contributorId":2439,"corporation":false,"usgs":true,"family":"Fowler","given":"Kathleen","email":"kkfowler@usgs.gov","middleInitial":"K.","affiliations":[{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true},{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":465960,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kim, Moon H. 0000-0002-4328-8409 mkim@usgs.gov","orcid":"https://orcid.org/0000-0002-4328-8409","contributorId":3211,"corporation":false,"usgs":true,"family":"Kim","given":"Moon","email":"mkim@usgs.gov","middleInitial":"H.","affiliations":[{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true}],"preferred":true,"id":465962,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Menke, Chad D. cdmenke@usgs.gov","contributorId":3209,"corporation":false,"usgs":true,"family":"Menke","given":"Chad","email":"cdmenke@usgs.gov","middleInitial":"D.","affiliations":[],"preferred":true,"id":465961,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70038692,"text":"70038692 - 2012 - Patterns in species richness and assemblage structure of native mussels in the Upper Mississippi River","interactions":[],"lastModifiedDate":"2020-12-30T13:29:22.514524","indexId":"70038692","displayToPublicDate":"2012-07-30T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":862,"text":"Aquatic Conservation: Marine and Freshwater Ecosystems","active":true,"publicationSubtype":{"id":10}},"title":"Patterns in species richness and assemblage structure of native mussels in the Upper Mississippi River","docAbstract":"1. To evaluate patterns in mussel assemblages in the Upper Mississippi River (UMR), data from systematic surveys of mussels conducted in three large reaches (Navigation Pools 5, 6, and 18) from 2005–2007 were analysed. 2. Nonmetric multi-dimensional scaling analyses and permutation tests indicated that assemblages differed among reaches. The mussel assemblage in Pool 18 was substantially different from the assemblage in Pool 5 and moderately different from the assemblage in Pool 6, whereas assemblages in Pools 5 and 6 were similar. Assemblages in broadly defined, flowing aquatic habitats did not substantially differ. 3. The dissimilarity of Pool 18 was primarily the result of Pool 18 having higher abundances of three Quadrula species (Q. quadrula, Q. pustulosa, and Q. nodulata), and lower abundances of Amblema plicata and Fusconaia flava. 4. Rarefaction analyses showed that species richness and species density were higher in Pool 18 compared with the other two pools. 5. Large-scale patterns in mussel assemblages may be related to other longitudinal trends in the system including geomorphology, water quality, and abundances of fish species that serve as hosts for glochidial larvae. 6. The results suggest that management goals and actions in the UMR may need to account for important differences in mussel assemblages that occur among reaches.","language":"English","publisher":"Wiley","doi":"10.1002/aqc.2255","usgsCitation":"Zigler, S.J., Newton, T., Davis, M., and Rogala, J.T., 2012, Patterns in species richness and assemblage structure of native mussels in the Upper Mississippi River: Aquatic Conservation: Marine and Freshwater Ecosystems, v. 22, no. 5, p. 577-587, https://doi.org/10.1002/aqc.2255.","productDescription":"11 p.","startPage":"577","endPage":"587","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":381726,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Illinois, Iowa, Minnesota, Wisconsin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.646484375,\n 48.922499263758255\n ],\n [\n -96.85546875,\n 45.213003555993964\n ],\n [\n -96.6796875,\n 43.26120612479979\n ],\n [\n -95.537109375,\n 40.38002840251183\n ],\n [\n -91.669921875,\n 40.58058466412761\n ],\n [\n -89.912109375,\n 38.13455657705411\n ],\n [\n -89.296875,\n 37.020098201368114\n ],\n [\n -87.802734375,\n 38.20365531807149\n ],\n [\n -87.5390625,\n 41.50857729743935\n ],\n [\n -87.36328125,\n 45.1510532655634\n ],\n [\n -89.736328125,\n 46.195042108660154\n ],\n [\n -90.791015625,\n 46.86019101567027\n ],\n [\n -89.736328125,\n 48.3416461723746\n ],\n [\n -95.2734375,\n 49.03786794532644\n ],\n [\n -97.646484375,\n 48.922499263758255\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"22","issue":"5","noUsgsAuthors":false,"publicationDate":"2012-05-29","publicationStatus":"PW","scienceBaseUri":"505a75bfe4b0c8380cd77d07","contributors":{"authors":[{"text":"Zigler, Steven J. 0000-0002-4153-0652 szigler@usgs.gov","orcid":"https://orcid.org/0000-0002-4153-0652","contributorId":2410,"corporation":false,"usgs":true,"family":"Zigler","given":"Steven","email":"szigler@usgs.gov","middleInitial":"J.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":464710,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Newton, Teresa J. 0000-0001-9351-5852","orcid":"https://orcid.org/0000-0001-9351-5852","contributorId":78696,"corporation":false,"usgs":true,"family":"Newton","given":"Teresa J.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":464713,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Davis, Mike","contributorId":50284,"corporation":false,"usgs":true,"family":"Davis","given":"Mike","affiliations":[],"preferred":false,"id":464712,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rogala, James T. 0000-0002-1954-4097 jrogala@usgs.gov","orcid":"https://orcid.org/0000-0002-1954-4097","contributorId":2651,"corporation":false,"usgs":true,"family":"Rogala","given":"James","email":"jrogala@usgs.gov","middleInitial":"T.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":464711,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70039266,"text":"ofr20121158 - 2012 - Probability and volume of potential postwildfire debris flows in the 2012 Waldo Canyon Burn Area near Colorado Springs, Colorado","interactions":[],"lastModifiedDate":"2012-07-31T01:01:47","indexId":"ofr20121158","displayToPublicDate":"2012-07-30T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-1158","title":"Probability and volume of potential postwildfire debris flows in the 2012 Waldo Canyon Burn Area near Colorado Springs, Colorado","docAbstract":"This report presents a preliminary emergency assessment of the debris-flow hazards from drainage basins burned by the 2012 Waldo Canyon fire near Colorado Springs in El Paso County, Colorado. Empirical models derived from statistical evaluation of data collected from recently burned basins throughout the intermountain western United States were used to estimate the probability of debris-flow occurrence and potential volume of debris flows along the drainage network of the burned area and to estimate the same for 22 selected drainage basins along U.S. Highway 24 and the perimeter of the burned area. Input data for the models included topographic parameters, soil characteristics, burn severity, and rainfall totals and intensities for a (1) 2-year-recurrence, 1-hour-duration rainfall, referred to as a 2-year storm (29 millimeters); (2) 10-year-recurrence, 1-hour-duration rainfall, referred to as a 10-year storm (42 millimeters); and (3) 25-year-recurrence, 1-hour-duration rainfall, referred to as a 25-year storm (48 millimeters). Estimated debris-flow probabilities at the pour points of the the drainage basins of interest ranged from less than 1 to 54 percent in response to the 2-year storm; from less than 1 to 74 percent in response to the 10-year storm; and from less than 1 to 82 percent in response to the 25-year storm. Basins and drainage networks with the highest probabilities tended to be those on the southern and southeastern edge of the burn area where soils have relatively high clay contents and gradients are steep. Nine of the 22 drainage basins of interest have greater than a 40-percent probability of producing a debris flow in response to the 10-year storm. Estimated debris-flow volumes for all rainfalls modeled range from a low of 1,500 cubic meters to a high of greater than 100,000 cubic meters. Estimated debris-flow volumes increase with basin size and distance along the drainage network, but some smaller drainages were also predicted to produce substantial volumes of material. The predicted probabilities and some of the volumes predicted for the modeled storms indicate a potential for substantial debris-flow impacts on structures, reservoirs, roads, bridges, and culverts located both within and immediately downstream from the burned area. U.S. Highway 24, on the southern edge of the burn area, is also susceptible to impacts from debris flows.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121158","collaboration":"Prepared in cooperation with Colorado Department of Transportation","usgsCitation":"Verdin, K.L., Dupree, J.A., and Elliott, J.G., 2012, Probability and volume of potential postwildfire debris flows in the 2012 Waldo Canyon Burn Area near Colorado Springs, Colorado: U.S. Geological Survey Open-File Report 2012-1158, vi, 8 p.; maps (col.); 2 Plates: 34 x 22 inches, https://doi.org/10.3133/ofr20121158.","productDescription":"vi, 8 p.; maps (col.); 2 Plates: 34 x 22 inches","startPage":"i","endPage":"8","numberOfPages":"14","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2012-06-23","temporalEnd":"2012-07-30","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":259246,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1158.gif"},{"id":259244,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1158/OF12-1158.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":259243,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1158/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Colorado","county":"El Paso County","city":"Colorado Springs","otherGeospatial":"Waldo Canyon","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a8ca9e4b0c8380cd7e7fc","contributors":{"authors":[{"text":"Verdin, Kristine L. 0000-0002-6114-4660 kverdin@usgs.gov","orcid":"https://orcid.org/0000-0002-6114-4660","contributorId":3070,"corporation":false,"usgs":true,"family":"Verdin","given":"Kristine","email":"kverdin@usgs.gov","middleInitial":"L.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":465892,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dupree, Jean A. dupree@usgs.gov","contributorId":2563,"corporation":false,"usgs":true,"family":"Dupree","given":"Jean","email":"dupree@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":465891,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":465890,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70038834,"text":"70038834 - 2012 - Nest survival of piping plovers at a dynamic reservoir indicates an ecological trap for a threatened population","interactions":[],"lastModifiedDate":"2017-08-31T10:52:54","indexId":"70038834","displayToPublicDate":"2012-07-30T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2932,"text":"Oecologia","active":true,"publicationSubtype":{"id":10}},"title":"Nest survival of piping plovers at a dynamic reservoir indicates an ecological trap for a threatened population","docAbstract":"In the past 60 years, reservoirs have reshaped riverine ecosystems and transformed breeding habitats used by the threatened piping plover (Charadrius melodus; hereafter plover). Currently, 29% of the Northern Great Plains plover population nests at reservoirs that might function as ecological traps because reservoirs have more diverse habitat features and greater dynamics in water levels than habitats historically used by breeding plovers. We examined factors influencing daily survival rates (DSR) of 346 plover nests at Lake Sakakawea (SAK; reservoir) during 2006–2009 by evaluating multiple a priori models, and we used our best model to hindcast nest success of plovers during 1985–2009. Our observed and hindcast estimates of nest success were low compared to published estimates. Previous findings indicate that plovers prefer nest sites that are low relative to water level. We found that elevation of nests above the water level had a strong positive correlation with DSR because water levels of SAK typically increased throughout the nesting period. Habitat characteristics on the reservoir differ from those that shaped nest-site selection for plovers. Accordingly, extraordinary nest loss occurs there in many years, largely due to inundation of nests, and based on low fledging rates those losses were not compensated by potential changes in chick survival. Therefore, our example supports the concept of ecological traps in birds because it addresses quantitative assessments of habitat preference and productivity over 25 years (since species listing) and affects a large portion of the population.
","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Oecologia","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","publisherLocation":"Amsterdam, Netherlands","doi":"10.1007/s00442-012-2384-y","usgsCitation":"Anteau, M.J., Shaffer, T.L., Sherfy, M.H., Sovada, M.A., Stucker, J.H., and Wiltermuth, M.T., 2012, Nest survival of piping plovers at a dynamic reservoir indicates an ecological trap for a threatened population: Oecologia, v. 170, no. 4, p. 1167-1179, https://doi.org/10.1007/s00442-012-2384-y.","productDescription":"13 p.","startPage":"1167","endPage":"1179","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":259271,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":259249,"rank":9999,"type":{"id":10,"text":"Digital Object 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msherfy@usgs.gov","orcid":"https://orcid.org/0000-0003-3016-4105","contributorId":125,"corporation":false,"usgs":true,"family":"Sherfy","given":"Mark","email":"msherfy@usgs.gov","middleInitial":"H.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":465042,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sovada, Marsha A. msovada@usgs.gov","contributorId":2601,"corporation":false,"usgs":true,"family":"Sovada","given":"Marsha","email":"msovada@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":465044,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stucker, Jennifer H. jstucker@usgs.gov","contributorId":3183,"corporation":false,"usgs":true,"family":"Stucker","given":"Jennifer","email":"jstucker@usgs.gov","middleInitial":"H.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research 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model","interactions":[],"lastModifiedDate":"2012-07-31T01:01:47","indexId":"sir20125099","displayToPublicDate":"2012-07-30T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-5099","title":"Evaluation of effects of changes in canal management and precipitation patterns on salinity in Biscayne Bay, Florida, using an integrated surface-water/groundwater model","docAbstract":"Biscayne National Park, located in Biscayne Bay in southeast Florida, is one of the largest marine parks in the country and sustains a large natural marine fishery where numerous threatened and endangered species reproduce. In recent years, the bay has experienced hypersaline conditions (salinity greater than 35 practical salinity units) of increasing magnitude and duration. Hypersalinity events were particularly pronounced during April to August 2004 in nearshore areas along the southern and middle parts of the bay. Prolonged hypersaline conditions can cause degradation of water quality and permanent damage to, or loss of, brackish nursery habitats for multiple species of fish and crustaceans as well as damage to certain types of seagrasses that are not tolerant of extreme changes in salinity. To evaluate the factors that contribute to hypersalinity events and to test the effects of possible changes in precipitation patterns and canal flows into Biscayne Bay on salinity in the bay, the U.S. Geological Survey constructed a coupled surface-water/groundwater numerical flow model. The model is designed to account for freshwater flows into Biscayne Bay through the canal system, leakage of salty bay water into the underlying Biscayne aquifer, discharge of fresh and salty groundwater from the Biscayne aquifer into the bay, direct effects of precipitation on bay salinity, indirect effects of precipitation on recharge to the Biscayne aquifer, direct effects of evapotranspiration (ET) on bay salinity, indirect effects of ET on recharge to the Biscayne aquifer, and maintenance of mass balance of both water and solute. The model was constructed using the Flow and Transport in a Linked Overland/Aquifer Density Dependent System (FTLOADDS) simulator, version 3.3, which couples the two-dimensional, surface-water flow and solute-transport simulator SWIFT2D with the density-dependent, groundwater flow an solute-transport simulator SEAWAT. The model was calibrated by a trial-and-error method to fit observed groundwater heads, estimated base flow, and measured bay salinity and temperatures from 1996 to 2004, as well as the location of the freshwater-saltwater interface in the aquifer, by adjusting ET rate limiters, canal vertical hydraulic conductance, leakage rate coefficients (transition-layer thickness and hydraulic conductivity), Manning's n value, and delineation of rainfall zones. Although flow budget calculations indicate that precipitation, ET, and groundwater flux into the bay represent a small portion of the overall budget, these factors may be important in controlling salinity in some parts of the bay, for example the southern parts of the bay where the canal system is not extensively developed or controlled. The balance of precipitation and ET during the wet season generally results in a reduction of bay salinity, whereas the balance of precipitation and ET during the dry season generally results in an increase in bay salinity. During years when wet season precipitation is lower than average, for example less than 70 percent total precipitation for an average year, ET could outweigh precipitation over the bay for essentially the entire year. Hypersaline conditions are prone to occur near the end of the dry season because precipitation rates are generally lower, canal discharge rates (which are strongly correlated to precipitation rates) are also generally lower, and ET rates are higher than during the rest of the year. The hypersalinity event of 2004 followed several years of relatively low precipitation and correspondingly reduced canal structure releases and was unusually extensive, continuing into July. Thus, hypersalinity is ultimately the result of a cumulative deficit of precipitation. The model was used to test the effects of possible changes in canal flux and precipitation. Simulation results showed that by increasing, reducing, or modifying canal discharge rates, the effects on salinity in the bay were more pronounced in the northern part of the bay where there are more canals and canal-control structures. By doubling and halving precipitation, the effects on bay salinity were more pronounced in the southern part of the bay than in the northern part of the bay where there are fewer canals and canal-control structures. The model is designed to quantify factors that contribute to hypersaline conditions in Biscayne Bay and may be less appropriate for addressing other issues or examining conditions substantially different from those described in this report. Model results must be interpreted in light of model limitations, which include representation of the system and conceptual model, uncertainty in physical properties used to describe the system or processes, the scale and discretization of the system, and representation of the boundary conditions.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125099","collaboration":"Prepared in cooperation with the South Florida Water Management District Science on the DOI Landscape Initiative","usgsCitation":"Lohmann, M.A., Swain, E.D., Wang, J.D., and Dixon, J., 2012, Evaluation of effects of changes in canal management and precipitation patterns on salinity in Biscayne Bay, Florida, using an integrated surface-water/groundwater model: U.S. Geological Survey Scientific Investigations Report 2012-5099, ix, 94 p.; col. ill.; maps (col.), https://doi.org/10.3133/sir20125099.","productDescription":"ix, 94 p.; col. ill.; maps (col.)","numberOfPages":"108","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":285,"text":"Florida Water Science Center","active":false,"usgs":true}],"links":[{"id":259245,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5099.gif"},{"id":259241,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5099/","linkFileType":{"id":5,"text":"html"}},{"id":259242,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5099/pdf/sir_2012_5099_v3.pdf","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Florida","otherGeospatial":"Biscyne Bay;Biscayne National Park","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a0c6de4b0c8380cd52b40","contributors":{"authors":[{"text":"Lohmann, Melinda A.","contributorId":80133,"corporation":false,"usgs":true,"family":"Lohmann","given":"Melinda","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":465889,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Swain, Eric D. 0000-0001-7168-708X edswain@usgs.gov","orcid":"https://orcid.org/0000-0001-7168-708X","contributorId":1538,"corporation":false,"usgs":true,"family":"Swain","given":"Eric","email":"edswain@usgs.gov","middleInitial":"D.","affiliations":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"preferred":true,"id":465886,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wang, John D.","contributorId":75224,"corporation":false,"usgs":true,"family":"Wang","given":"John","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":465888,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dixon, Joann","contributorId":19981,"corporation":false,"usgs":true,"family":"Dixon","given":"Joann","affiliations":[],"preferred":false,"id":465887,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70038315,"text":"70038315 - 2012 - Predictions and retrodictions of the hierarchical representation of habitat in heterogeneous environments","interactions":[],"lastModifiedDate":"2017-05-10T09:44:29","indexId":"70038315","displayToPublicDate":"2012-07-30T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"title":"Predictions and retrodictions of the hierarchical representation of habitat in heterogeneous environments","docAbstract":"Interaction between habitat and species is central in ecology. Habitat structure may be conceived as being hierarchical, where larger, more diverse, portions or categories contain smaller, more homogeneous portions. When this conceptualization is combined with the observation that species have different abilities to relate to portions of the habitat that differ in their characteristics, a number of known patterns can be derived and new patterns hypothesized. We propose a quantitative form of this habitat–species relationship by considering species abundance to be a function of habitat specialization, habitat fragmentation, amount of habitat, and adult body mass. The model reproduces and explains patterns such as variation in rank–abundance curves, greater variation and extinction probabilities of habitat specialists, discontinuities in traits (abundance, ecological range, pattern of variation, body size) among species sharing a community or area, and triangular distribution of body sizes, among others. The model has affinities to Holling's textural discontinuity hypothesis and metacommunity theory but differs from both by offering a more general perspective. In support of the model, we illustrate its general potential to capture and explain several empirical observations that historically have been treated independently.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolmodel.2012.03.030","usgsCitation":"Kolasa, J., Allen, C.R., Sendzimir, J., and Stow, C., 2012, Predictions and retrodictions of the hierarchical representation of habitat in heterogeneous environments: Ecological Modelling, v. 245, p. 199-207, https://doi.org/10.1016/j.ecolmodel.2012.03.030.","productDescription":"9 p.","startPage":"199","endPage":"207","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-037250","costCenters":[],"links":[{"id":259276,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":259259,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.ecolmodel.2012.03.030","linkFileType":{"id":5,"text":"html"}}],"volume":"245","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a81f8e4b0c8380cd7b829","contributors":{"authors":[{"text":"Kolasa, Jurek","contributorId":34767,"corporation":false,"usgs":true,"family":"Kolasa","given":"Jurek","email":"","affiliations":[],"preferred":false,"id":463848,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Allen, Craig R. 0000-0001-8655-8272 allencr@usgs.gov","orcid":"https://orcid.org/0000-0001-8655-8272","contributorId":1979,"corporation":false,"usgs":true,"family":"Allen","given":"Craig","email":"allencr@usgs.gov","middleInitial":"R.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":463847,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sendzimir, Jan","contributorId":57315,"corporation":false,"usgs":true,"family":"Sendzimir","given":"Jan","email":"","affiliations":[],"preferred":false,"id":463850,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stow, Craig A.","contributorId":49733,"corporation":false,"usgs":true,"family":"Stow","given":"Craig A.","affiliations":[],"preferred":false,"id":463849,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70003779,"text":"70003779 - 2012 - Population dynamics of king eiders breeding in northern Alaska","interactions":[],"lastModifiedDate":"2012-07-31T01:01:47","indexId":"70003779","displayToPublicDate":"2012-07-30T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Population dynamics of king eiders breeding in northern Alaska","docAbstract":"The North American population of king eiders (Somateria spectabilis) has declined by more than 50% since the late 1970s for unknown reasons. King eiders spend most of their lives in remote areas, forcing managers to make regulatory and conservation decisions based on very little information. We incorporated available published estimates of vital rates with new estimates to build a female, stage-based matrix population model for king eiders and examine the processes underlying population dynamics of king eiders breeding at 2 sites, Teshekpuk and Kuparuk, on the coastal plain of northern Alaska and wintering around the Bering Sea (2001–2010). We predicted a decreasing population (λ = 0.981, 95% CI: 0.978–0.985), and that population growth was most sensitive to changes in adult female survival (sensitivity = 0.92). Low duckling survival may be a bottleneck to productivity (variation in ducking survival accounted for 66% of retrospective variation in λ). Adult survival was high (0.94) and invariant (σ = 0.0002, 95% CI: 0.0000–0.0007); however, catastrophic events could have a major impact and we need to consider how to mitigate and manage threats to adult survival. A hypothetical oil spill affecting breeding females in a primary spring staging area resulted in a severe population decline; although, transient population dynamics were relatively stable. However, if no catastrophic events occur, the more variable reproductive parameters (duckling and nest survival) may be more responsive to management actions.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Wildlife Management","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"The Wildlife Society","publisherLocation":"Bethesda, MD","doi":"10.1002/jwmg.335","usgsCitation":"Bentzen, R., and Powell, A., 2012, Population dynamics of king eiders breeding in northern Alaska: Journal of Wildlife Management, v. 76, no. 5, p. 1011-1020, https://doi.org/10.1002/jwmg.335.","productDescription":"10 p.","startPage":"1011","endPage":"1020","costCenters":[{"id":108,"text":"Alaska Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true}],"links":[{"id":259268,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":259257,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/jwmg.335","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Alaska","volume":"76","issue":"5","noUsgsAuthors":false,"publicationDate":"2012-02-06","publicationStatus":"PW","scienceBaseUri":"505a7d4de4b0c8380cd79e86","contributors":{"authors":[{"text":"Bentzen, Rebecca L.","contributorId":62070,"corporation":false,"usgs":true,"family":"Bentzen","given":"Rebecca L.","affiliations":[],"preferred":false,"id":348809,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Powell, Abby N. abby_powell@usgs.gov","contributorId":2534,"corporation":false,"usgs":false,"family":"Powell","given":"Abby N.","email":"abby_powell@usgs.gov","affiliations":[{"id":13117,"text":"Institute of Arctic Biology, University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":348808,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70003798,"text":"70003798 - 2012 - Nest predation risk and growth strategies of passerine species: grow fast or develop traits to escape risk?","interactions":[],"lastModifiedDate":"2015-06-05T12:56:51","indexId":"70003798","displayToPublicDate":"2012-07-30T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":740,"text":"American Naturalist","active":true,"publicationSubtype":{"id":10}},"title":"Nest predation risk and growth strategies of passerine species: grow fast or develop traits to escape risk?","docAbstract":"Different body components are thought to trade off in their growth and development rates, but the causes for relative prioritization of any trait remains a critical question. Offspring of species at higher risk of predation might prioritize development of locomotor traits that facilitate escaping risky environments over growth of mass. We tested this possibility in 12 altricial passerine species that differed in their risk of nest predation. We found that rates of growth and development of mass, wings, and endothermy increased with nest predation risk across species. In particular, species with higher nest predation risk exhibited relatively faster growth of wings than of mass, fledged with relatively larger wing sizes and smaller mass, and developed endothermy earlier at relatively smaller mass. This differential development can facilitate both escape from predators and survival outside of the nest environment. Tarsus growth was not differentially prioritized with respect to nest predation risk, and instead all species achieved adult tarsus size by age of fledging. We also tested whether different foraging modes (aerial, arboreal, and ground foragers) might explain the variation of differential growth of locomotor modules, but we found that little residual variation was explained. Our results suggest that differences in nest predation risk among species are associated with relative prioritization of body components to facilitate escape from the risky nest environment.
","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"American Naturalist","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"University of Chicago Press","publisherLocation":"Chicago, IL","doi":"10.1086/667214","usgsCitation":"Cheng, Y., and Martin, T.E., 2012, Nest predation risk and growth strategies of passerine species: grow fast or develop traits to escape risk?: American Naturalist, v. 180, no. 3, p. 285-295, https://doi.org/10.1086/667214.","productDescription":"11 p.","startPage":"285","endPage":"295","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[],"links":[{"id":259269,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"180","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a6481e4b0c8380cd729e7","contributors":{"authors":[{"text":"Cheng, Yi-Ru","contributorId":23803,"corporation":false,"usgs":true,"family":"Cheng","given":"Yi-Ru","email":"","affiliations":[],"preferred":false,"id":348941,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Martin, Thomas E. 0000-0002-4028-4867 tmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-4028-4867","contributorId":1208,"corporation":false,"usgs":true,"family":"Martin","given":"Thomas","email":"tmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":348940,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70037927,"text":"70037927 - 2012 - Molecular responses differ between sensitive silver carp and tolerant bighead carp and bigmouth buffalo exposed to rotenone","interactions":[],"lastModifiedDate":"2012-09-21T17:16:41","indexId":"70037927","displayToPublicDate":"2012-07-28T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1651,"text":"Fish Physiology and Biochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Molecular responses differ between sensitive silver carp and tolerant bighead carp and bigmouth buffalo exposed to rotenone","docAbstract":"Some species of fish are more tolerant of rotenone, a commonly used non-specific piscicide, than others. This species-specific tolerance to rotenone has been thought to be associated with the uptake and the efficiency at which the chemical is detoxified. However, rotenone stimulates oxidative stress and superoxides, which are also toxic. Understanding the modes in which fish physiologically respond to rotenone is important in developing improved protocols for its application in controlling aquatic nuisance species. Using a molecular approach, we investigated the physiological and molecular mechanisms of rotenone resistance. Species-specific responses were observed when rotenone-sensitive silver, Hypophthalmichthys molitrix, and both rotenone-resistant bighead carp, Hypophthalmichthys nobilis, and bigmouth buffalo, Ictiobus cyprinellus, were exposed to rotenone. Rotenone levels in plasma were highest 90 min after exposure in both silver carp and bigmouth buffalo, but bigmouth buffalo tolerated over twice the burden (ng mL-1 g-1) than silver carp. Expression of genes related with detoxification (cyp1a and gst) increased in silver carp, but either decreased or remained the same in bighead carp. Genes linked with oxidative stress in the cytosol (gpx, cat and sod1) and hsp70 increased only in silver carp after a 6-h exposure. Expression of genes associated with oxidative stress in the mitochondria (sod2 and ucp2) differed between silver carp and bighead carp. Expression of sod2 changed minimally in bighead carp, but expression of ucp2 linearly increased to nearly 85-fold of the level prior to exposure. Expression of sod2 and ucp2 did not change until 6 h in silver carp. Use of sod1 and sod2 to combat oxidative stress results in hydrogen peroxide production, while use of ucp2 produces nitric oxide, a chemical known to inhibit apoptosis. We conclude that the mechanism at which a fish handles oxidative stress plays an important role in the tolerance to rotenone.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Fish Physiology and Biochemistry","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","publisherLocation":"Amsterdam, Netherlands","doi":"10.1007/s10695-012-9625-1","usgsCitation":"Amberg, J., Schreier, T.M., and Gaikowski, M.P., 2012, Molecular responses differ between sensitive silver carp and tolerant bighead carp and bigmouth buffalo exposed to rotenone: Fish Physiology and Biochemistry, v. 38, no. 5, p. 1379-1391, https://doi.org/10.1007/s10695-012-9625-1.","productDescription":"13 p.","startPage":"1379","endPage":"1391","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":259240,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":257281,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://dx.doi.org/10.1007/s10695-012-9625-1","linkFileType":{"id":5,"text":"html"}}],"volume":"38","issue":"5","noUsgsAuthors":false,"publicationDate":"2012-03-25","publicationStatus":"PW","scienceBaseUri":"505a5d11e4b0c8380cd70133","contributors":{"authors":[{"text":"Amberg, Jon J. jamberg@usgs.gov","contributorId":797,"corporation":false,"usgs":true,"family":"Amberg","given":"Jon J.","email":"jamberg@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":false,"id":463066,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schreier, Theresa M. 0000-0001-7722-6292 tschreier@usgs.gov","orcid":"https://orcid.org/0000-0001-7722-6292","contributorId":3344,"corporation":false,"usgs":true,"family":"Schreier","given":"Theresa","email":"tschreier@usgs.gov","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":463067,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gaikowski, Mark P. 0000-0002-6507-9341 mgaikowski@usgs.gov","orcid":"https://orcid.org/0000-0002-6507-9341","contributorId":796,"corporation":false,"usgs":true,"family":"Gaikowski","given":"Mark","email":"mgaikowski@usgs.gov","middleInitial":"P.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":false,"id":463065,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70038468,"text":"70038468 - 2012 - Elk migration patterns and human activity influence wolf habitat use in the Greater Yellowstone Ecosystem","interactions":[],"lastModifiedDate":"2017-05-05T11:13:30","indexId":"70038468","displayToPublicDate":"2012-07-27T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Elk migration patterns and human activity influence wolf habitat use in the Greater Yellowstone Ecosystem","docAbstract":"Identifying the ecological dynamics underlying human–wildlife conflicts is important for the management and conservation of wildlife populations. In landscapes still occupied by large carnivores, many ungulate prey species migrate seasonally, yet little empirical research has explored the relationship between carnivore distribution and ungulate migration strategy. In this study, we evaluate the influence of elk (Cervus elaphus) distribution and other landscape features on wolf (Canis lupus) habitat use in an area of chronic wolf–livestock conflict in the Greater Yellowstone Ecosystem, USA. Using three years of fine-scale wolf (n = 14) and elk (n = 81) movement data, we compared the seasonal habitat use of wolves in an area dominated by migratory elk with that of wolves in an adjacent area dominated by resident elk. Most migratory elk vacate the associated winter wolf territories each summer via a 40–60 km migration, whereas resident elk remain accessible to wolves year-round. We used a generalized linear model to compare the relative probability of wolf use as a function of GIS-based habitat covariates in the migratory and resident elk areas. Although wolves in both areas used elk-rich habitat all year, elk density in summer had a weaker influence on the habitat use of wolves in the migratory elk area than the resident elk area. Wolves employed a number of alternative strategies to cope with the departure of migratory elk. Wolves in the two areas also differed in their disposition toward roads. In winter, wolves in the migratory elk area used habitat close to roads, while wolves in the resident elk area avoided roads. In summer, wolves in the migratory elk area were indifferent to roads, while wolves in resident elk areas strongly avoided roads, presumably due to the location of dens and summering elk combined with different traffic levels. Study results can help wildlife managers to anticipate the movements and establishment of wolf packs as they expand into areas with migratory or resident prey populations, varying levels of human activity, and front-country rangelands with potential for conflicts with livestock.
","language":"English","publisher":"ESA","doi":"10.1890/11-1829.1","usgsCitation":"Nelson, A., Kauffman, M., Middleton, A., Jimenez, M., McWhirter, D., Barber, J., and Gerow, K., 2012, Elk migration patterns and human activity influence wolf habitat use in the Greater Yellowstone Ecosystem: Ecological Applications, v. 22, no. 8, p. 2293-2307, https://doi.org/10.1890/11-1829.1.","productDescription":"15 p.","startPage":"2293","endPage":"2307","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-033306","costCenters":[{"id":683,"text":"Wyoming Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true}],"links":[{"id":259201,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":259197,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1890/11-1829.1","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Wyoming","city":"Cody","otherGeospatial":"Yellowstone National Park","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -110.4985,44.3159 ], [ -110.4985,45.0003 ], [ -108.9289,45.0003 ], [ -108.9289,44.3159 ], [ -110.4985,44.3159 ] ] ] } } ] }","volume":"22","issue":"8","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a08dde4b0c8380cd51cd7","contributors":{"authors":[{"text":"Nelson, Abigail","contributorId":47258,"corporation":false,"usgs":true,"family":"Nelson","given":"Abigail","affiliations":[],"preferred":false,"id":464304,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kauffman, Matthew J. 0000-0003-0127-3900 mkauffman@usgs.gov","orcid":"https://orcid.org/0000-0003-0127-3900","contributorId":2963,"corporation":false,"usgs":true,"family":"Kauffman","given":"Matthew J.","email":"mkauffman@usgs.gov","affiliations":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"preferred":false,"id":464300,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Middleton, Arthur D.","contributorId":99440,"corporation":false,"usgs":true,"family":"Middleton","given":"Arthur D.","affiliations":[],"preferred":false,"id":464306,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jimenez, Mike","contributorId":33785,"corporation":false,"usgs":true,"family":"Jimenez","given":"Mike","email":"","affiliations":[],"preferred":false,"id":464302,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McWhirter, Douglas","contributorId":7577,"corporation":false,"usgs":true,"family":"McWhirter","given":"Douglas","affiliations":[],"preferred":false,"id":464301,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Barber, Jarrett","contributorId":94935,"corporation":false,"usgs":true,"family":"Barber","given":"Jarrett","affiliations":[],"preferred":false,"id":464305,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gerow, Ken","contributorId":40870,"corporation":false,"usgs":true,"family":"Gerow","given":"Ken","email":"","affiliations":[],"preferred":false,"id":464303,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70038535,"text":"70038535 - 2012 - Field information links permafrost carbon to physical vulnerabilities of thawing","interactions":[],"lastModifiedDate":"2017-11-02T12:00:11","indexId":"70038535","displayToPublicDate":"2012-07-27T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Field information links permafrost carbon to physical vulnerabilities of thawing","docAbstract":"Deep soil profiles containing permafrost (Gelisols) were characterized for organic carbon (C) and total nitrogen (N) stocks to 3m depths. Using the Community Climate System Model (CCSM4) we calculate cumulative probability functions (PDFs) for active layer depths under current and future climates. The difference in PDFs over time was multiplied by C and N contents of soil horizons in Gelisol suborders to calculate newly thawed C and N, Thawing ranged from 147 PgC with 10 PgN by 2050 (representative concentration pathway RCP scenario 4.5) to 436 PgC with 29 PgN by 2100 (RCP 8.5). Organic horizons that thaw are vulnerable to combustion, and all horizon types are vulnerable to shifts in hydrology and decomposition. The rates and extent of such losses are unknown and can be further constrained by linking field and modelling approaches. These changes have the potential for strong additional loading to our atmosphere, water resources, and ecosystems.","language":"English","publisher":"American Geophysical Union","publisherLocation":"Washington, D.C.","doi":"10.1029/2012GL051958","usgsCitation":"Harden, J.W., Koven, C., Ping, C., Hugelius, G., McGuire, A., Camill, P., Jorgenson, T., Kuhry, P., Michaelson, G., O’Donnell, J.A., Schuur, E.A., Tamocai, C., Johnson, K., and Grosse, G., 2012, Field information links permafrost carbon to physical vulnerabilities of thawing: Geophysical Research Letters, v. 39, 6 p.; L15704, https://doi.org/10.1029/2012GL051958.","productDescription":"6 p.; L15704","ipdsId":"IP-041567","costCenters":[{"id":108,"text":"Alaska Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":259211,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":259204,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1029/2012GL051958","linkFileType":{"id":5,"text":"html"}}],"volume":"39","noUsgsAuthors":false,"publicationDate":"2012-08-07","publicationStatus":"PW","scienceBaseUri":"505a0fc0e4b0c8380cd539da","contributors":{"authors":[{"text":"Harden, Jennifer W. 0000-0002-6570-8259 jharden@usgs.gov","orcid":"https://orcid.org/0000-0002-6570-8259","contributorId":1971,"corporation":false,"usgs":true,"family":"Harden","given":"Jennifer","email":"jharden@usgs.gov","middleInitial":"W.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":464517,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Koven, Charles","contributorId":51143,"corporation":false,"usgs":true,"family":"Koven","given":"Charles","affiliations":[],"preferred":false,"id":464523,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ping, Chien-Lu","contributorId":12726,"corporation":false,"usgs":true,"family":"Ping","given":"Chien-Lu","email":"","affiliations":[],"preferred":false,"id":464519,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hugelius, Gustaf 0000-0002-8096-1594","orcid":"https://orcid.org/0000-0002-8096-1594","contributorId":73863,"corporation":false,"usgs":false,"family":"Hugelius","given":"Gustaf","email":"","affiliations":[{"id":25546,"text":"Stockholm University, Sweden","active":true,"usgs":false},{"id":17850,"text":"Dept of Earth System Science, Stanford University, Stanford, CA 94305","active":true,"usgs":false}],"preferred":false,"id":464525,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McGuire, A. David","contributorId":18494,"corporation":false,"usgs":true,"family":"McGuire","given":"A. 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The focus of the modeling study was the Paleocene and Eocene Wilcox Formation, which contains the youngest source rock interval in the Gulf Coast Province. Stratigraphic input to the models included thicknesses and ages of deposition, lithologies, amounts and ages of erosion, and ages for periods of nondeposition. Oil-generation potential of the Wilcox Formation was modeled using an initial total organic carbon of 2 weight percent and an initial hydrogen index of 261 milligrams of hydrocarbon per grams of total organic carbon. Isothermal, hydrous-pyrolysis kinetics determined experimentally was used to simulate oil generation from coal, which is the primary source of oil in Eocene rocks. Model simulations indicate that generation of oil commenced in the Wilcox Formation during a fairly wide age range, from 37 million years ago to the present day. Differences in maturity with respect to oil generation occur across the Lower Cretaceous shelf edge. Source rocks that are thermally immature and have not generated oil (depths less than about 5,000 feet) lie updip and north of the shelf edge; source rocks that have generated all of their oil and are overmature (depths greater than about 13,000 feet) are present downdip and south of the shelf edge. High rates of sediment deposition coupled with increased accommodation space at the Cretaceous shelf margin led to deep burial of Cretaceous and Tertiary source rocks and, in turn, rapid generation of petroleum and, ultimately, cracking of oil to gas.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121046","usgsCitation":"Pitman, J.K., and Rowan, E., 2012, Temperature and petroleum generation history of the Wilcox Formation, Louisiana: U.S. Geological Survey Open-File Report 2012-1046, iv, 51 p.; ill. (col.); col. map, https://doi.org/10.3133/ofr20121046.","productDescription":"iv, 51 p.; ill. (col.); col. map","startPage":"i","endPage":"51","numberOfPages":"55","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":259192,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1046.png"},{"id":259186,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1046/","linkFileType":{"id":5,"text":"html"}},{"id":259187,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1046/report/OF12-1046.pdf","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Louisiana","otherGeospatial":"Wilcox Formation","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505ba4bae4b08c986b32053a","contributors":{"authors":[{"text":"Pitman, Janet K. 0000-0002-0441-779X jpitman@usgs.gov","orcid":"https://orcid.org/0000-0002-0441-779X","contributorId":767,"corporation":false,"usgs":true,"family":"Pitman","given":"Janet","email":"jpitman@usgs.gov","middleInitial":"K.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":465831,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rowan, Elisabeth L. 0000-0001-5753-6189","orcid":"https://orcid.org/0000-0001-5753-6189","contributorId":80533,"corporation":false,"usgs":true,"family":"Rowan","given":"Elisabeth L.","affiliations":[],"preferred":false,"id":465832,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70038077,"text":"70038077 - 2012 - Drought and cooler temperatures are associated with higher nest survival in Mountain Plovers","interactions":[],"lastModifiedDate":"2012-07-28T01:01:41","indexId":"70038077","displayToPublicDate":"2012-07-27T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":947,"text":"Avian Conservation and Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Drought and cooler temperatures are associated with higher nest survival in Mountain Plovers","docAbstract":"Native grasslands have been altered to a greater extent than any other biome in North America. The habitats and resources needed to support breeding performance of grassland birds endemic to prairie ecosystems are currently threatened by land management practices and impending climate change. Climate models for the Great Plains prairie region predict a future of hotter and drier summers with strong multiyear droughts and more frequent and severe precipitation events. We examined how fluctuations in weather conditions in eastern Colorado influenced nest survival of an avian species that has experienced recent population declines, the Mountain Plover (Charadrius montanus). Nest survival averaged 27.2% over a 7-yr period (n = 936 nests) and declined as the breeding season progressed. Nest survival was favored by dry conditions and cooler temperatures. Projected changes in regional precipitation patterns will likely influence nest survival, with positive influences of predicted declines in summer rainfall yet negative effects of more intense rain events. The interplay of climate change and land use practices within prairie ecosystems may result in Mountain Plovers shifting their distribution, changing local abundance, and adjusting fecundity to adapt to their changing environment.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Avian Conservation and Ecology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Resillience Alliance","publisherLocation":"Wolfville, Nova Scotia","doi":"10.5751/ACE-00519-070106","usgsCitation":"Dreitz, V., Conrey, R., and Skagen, S., 2012, Drought and cooler temperatures are associated with higher nest survival in Mountain Plovers: Avian Conservation and Ecology, v. 7, no. 1, 13 p.; Article 6, https://doi.org/10.5751/ACE-00519-070106.","productDescription":"13 p.; Article 6","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":474401,"rank":10000,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5751/ace-00519-070106","text":"Publisher Index Page"},{"id":259194,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":259189,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.5751/ACE-00519-070106","linkFileType":{"id":5,"text":"html"}}],"country":"United States","volume":"7","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a03f4e4b0c8380cd50700","contributors":{"authors":[{"text":"Dreitz, V.J.","contributorId":65432,"corporation":false,"usgs":true,"family":"Dreitz","given":"V.J.","affiliations":[],"preferred":false,"id":463412,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conrey, R.Y.","contributorId":43222,"corporation":false,"usgs":true,"family":"Conrey","given":"R.Y.","email":"","affiliations":[],"preferred":false,"id":463411,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Skagen, S. K. 0000-0002-6744-1244","orcid":"https://orcid.org/0000-0002-6744-1244","contributorId":31348,"corporation":false,"usgs":true,"family":"Skagen","given":"S. K.","affiliations":[],"preferred":false,"id":463410,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70037880,"text":"70037880 - 2012 - GFDL's ESM2 global coupled climate-carbon Earth System Models. Part I: physical formulation and baseline simulation characteristics","interactions":[],"lastModifiedDate":"2012-10-09T17:16:16","indexId":"70037880","displayToPublicDate":"2012-07-27T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2216,"text":"Journal of Climate","active":true,"publicationSubtype":{"id":10}},"title":"GFDL's ESM2 global coupled climate-carbon Earth System Models. Part I: physical formulation and baseline simulation characteristics","docAbstract":"We describe the physical climate formulation and simulation characteristics of two new global coupled carbon-climate Earth System Models, ESM2M and ESM2G. These models demonstrate similar climate fidelity as the Geophysical Fluid Dynamics Laboratory's previous CM2.1 climate model while incorporating explicit and consistent carbon dynamics. The two models differ exclusively in the physical ocean component; ESM2M uses Modular Ocean Model version 4.1 with vertical pressure layers while ESM2G uses Generalized Ocean Layer Dynamics with a bulk mixed layer and interior isopycnal layers. Differences in the ocean mean state include the thermocline depth being relatively deep in ESM2M and relatively shallow in ESM2G compared to observations. The crucial role of ocean dynamics on climate variability is highlighted in the El Niño-Southern Oscillation being overly strong in ESM2M and overly weak ESM2G relative to observations. Thus, while ESM2G might better represent climate changes relating to: total heat content variability given its lack of long term drift, gyre circulation and ventilation in the North Pacific, tropical Atlantic and Indian Oceans, and depth structure in the overturning and abyssal flows, ESM2M might better represent climate changes relating to: surface circulation given its superior surface temperature, salinity and height patterns, tropical Pacific circulation and variability, and Southern Ocean dynamics. Our overall assessment is that neither model is fundamentally superior to the other, and that both models achieve sufficient fidelity to allow meaningful climate and earth system modeling applications. This affords us the ability to assess the role of ocean configuration on earth system interactions in the context of two state-of-the-art coupled carbon-climate models.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Climate","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Meteorological Society","publisherLocation":"Boston, MA","doi":"10.1175/JCLI-D-11-00560.1","usgsCitation":"Dunne, J.P., John, J.G., Adcroft, A.J., Griffies, S.M., Hallberg, R., Shevalikova, E., Stouffer, R., Cooke, W., Dunne, K.A., Harrison, M., Krasting, J.P., Malyshev, S.L., Milly, P., Phillipps, P.J., Sentman, L., Samuels, B.L., Spelman, M.J., Winton, M., Wittenberg, A., and Zadeh, N., 2012, GFDL's ESM2 global coupled climate-carbon Earth System Models. Part I: physical formulation and baseline simulation characteristics: Journal of Climate, v. 25, no. 19, p. 6646-6665, https://doi.org/10.1175/JCLI-D-11-00560.1.","productDescription":"20 p.","startPage":"6646","endPage":"6665","costCenters":[{"id":146,"text":"Branch of Regional Research-Eastern Region","active":false,"usgs":true}],"links":[{"id":474398,"rank":10000,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1175/jcli-d-11-00560.1","text":"Publisher Index Page"},{"id":259219,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":257619,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1175/JCLI-D-11-00560.1","linkFileType":{"id":5,"text":"html"}}],"volume":"25","issue":"19","noUsgsAuthors":false,"publicationDate":"2012-04-05","publicationStatus":"PW","scienceBaseUri":"505a145ee4b0c8380cd549fa","contributors":{"authors":[{"text":"Dunne, John P.","contributorId":88995,"corporation":false,"usgs":true,"family":"Dunne","given":"John","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":462962,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"John, Jasmin G.","contributorId":15058,"corporation":false,"usgs":true,"family":"John","given":"Jasmin","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":462947,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Adcroft, Alistair J.","contributorId":45166,"corporation":false,"usgs":true,"family":"Adcroft","given":"Alistair","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":462954,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Griffies, Stephen M.","contributorId":69003,"corporation":false,"usgs":true,"family":"Griffies","given":"Stephen","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":462958,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hallberg, Robert W.","contributorId":83380,"corporation":false,"usgs":true,"family":"Hallberg","given":"Robert W.","affiliations":[],"preferred":false,"id":462961,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Shevalikova, Elena","contributorId":21398,"corporation":false,"usgs":true,"family":"Shevalikova","given":"Elena","email":"","affiliations":[],"preferred":false,"id":462950,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Stouffer, Ronald J.","contributorId":54841,"corporation":false,"usgs":true,"family":"Stouffer","given":"Ronald J.","affiliations":[],"preferred":false,"id":462955,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Cooke, William","contributorId":65706,"corporation":false,"usgs":true,"family":"Cooke","given":"William","affiliations":[],"preferred":false,"id":462957,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"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":462946,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Harrison, Matthew J.","contributorId":34765,"corporation":false,"usgs":true,"family":"Harrison","given":"Matthew J.","affiliations":[],"preferred":false,"id":462953,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Krasting, John P.","contributorId":99416,"corporation":false,"usgs":true,"family":"Krasting","given":"John","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":462964,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Malyshev, Sergey L.","contributorId":90148,"corporation":false,"usgs":true,"family":"Malyshev","given":"Sergey","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":462963,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Milly, P. 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D.","affiliations":[],"preferred":false,"id":462965,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Phillipps, Peter J.","contributorId":24617,"corporation":false,"usgs":true,"family":"Phillipps","given":"Peter","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":462952,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Sentman, Lori A.","contributorId":17466,"corporation":false,"usgs":true,"family":"Sentman","given":"Lori A.","affiliations":[],"preferred":false,"id":462948,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Samuels, Bonita L.","contributorId":20201,"corporation":false,"usgs":true,"family":"Samuels","given":"Bonita","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":462949,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Spelman, Michael J.","contributorId":55681,"corporation":false,"usgs":true,"family":"Spelman","given":"Michael","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":462956,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Winton, Michael","contributorId":80947,"corporation":false,"usgs":true,"family":"Winton","given":"Michael","email":"","affiliations":[],"preferred":false,"id":462960,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Wittenberg, Andrew T.","contributorId":72246,"corporation":false,"usgs":true,"family":"Wittenberg","given":"Andrew T.","affiliations":[],"preferred":false,"id":462959,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Zadeh, Niki","contributorId":23800,"corporation":false,"usgs":true,"family":"Zadeh","given":"Niki","email":"","affiliations":[],"preferred":false,"id":462951,"contributorType":{"id":1,"text":"Authors"},"rank":20}]}} ,{"id":70038620,"text":"70038620 - 2012 - Freshwater DOM quantity and quality from a two-component model of UV absorbance","interactions":[],"lastModifiedDate":"2012-07-31T01:01:47","indexId":"70038620","displayToPublicDate":"2012-07-27T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3716,"text":"Water Research","onlineIssn":"1879-2448","printIssn":"0043-1354","active":true,"publicationSubtype":{"id":10}},"title":"Freshwater DOM quantity and quality from a two-component model of UV absorbance","docAbstract":"We present a model that considers UV-absorbing dissolved organic matter (DOM) to consist of two components (A and B), each with a distinct and constant spectrum. Component A absorbs UV light strongly, and is therefore presumed to possess aromatic chromophores and hydrophobic character, whereas B absorbs weakly and can be assumed hydrophilic. We parameterised the model with dissolved organic carbon concentrations [DOC] and corresponding UV spectra for c. 1700 filtered surface water samples from North America and the United Kingdom, by optimising extinction coefficients for A and B, together with a small constant concentration of non-absorbing DOM (0.80 mg DOC L-1). Good unbiased predictions of [DOC] from absorbance data at 270 and 350 nm were obtained (r2 = 0.98), the sum of squared residuals in [DOC] being reduced by 66% compared to a regression model fitted to absorbance at 270 nm alone. The parameterised model can use measured optical absorbance values at any pair of suitable wavelengths to calculate both [DOC] and the relative amounts of A and B in a water sample, i.e. measures of quantity and quality. Blind prediction of [DOC] was satisfactory for 9 of 11 independent data sets (181 of 213 individual samples).","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Water Research","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.watres.2012.05.021","usgsCitation":"Carter, H.T., Tipping, E., Koprivnjak, J., Miller, M.P., Cookson, B., and Hamilton-Taylor, J., 2012, Freshwater DOM quantity and quality from a two-component model of UV absorbance: Water Research, v. 46, no. 14, p. 4532-4542, https://doi.org/10.1016/j.watres.2012.05.021.","productDescription":"11 p.","startPage":"4532","endPage":"4542","costCenters":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":474395,"rank":10000,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1016/j.watres.2012.05.021","text":"External Repository"},{"id":259215,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":259206,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.watres.2012.05.021","linkFileType":{"id":5,"text":"html"}}],"volume":"46","issue":"14","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a13dbe4b0c8380cd547e9","contributors":{"authors":[{"text":"Carter, Heather T.","contributorId":19826,"corporation":false,"usgs":true,"family":"Carter","given":"Heather","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":464543,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tipping, Edward","contributorId":36405,"corporation":false,"usgs":true,"family":"Tipping","given":"Edward","email":"","affiliations":[],"preferred":false,"id":464545,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Koprivnjak, Jean-Francois","contributorId":52020,"corporation":false,"usgs":true,"family":"Koprivnjak","given":"Jean-Francois","email":"","affiliations":[],"preferred":false,"id":464546,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miller, Matthew P. 0000-0002-2537-1823 mamiller@usgs.gov","orcid":"https://orcid.org/0000-0002-2537-1823","contributorId":3919,"corporation":false,"usgs":true,"family":"Miller","given":"Matthew","email":"mamiller@usgs.gov","middleInitial":"P.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":464541,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cookson, Brenda","contributorId":33960,"corporation":false,"usgs":true,"family":"Cookson","given":"Brenda","email":"","affiliations":[],"preferred":false,"id":464544,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hamilton-Taylor, John","contributorId":12729,"corporation":false,"usgs":true,"family":"Hamilton-Taylor","given":"John","email":"","affiliations":[],"preferred":false,"id":464542,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70038169,"text":"70038169 - 2012 - Hybrid analysis of multiaxis electromagnetic data for discrimination of munitions and explosives of concern","interactions":[],"lastModifiedDate":"2012-07-28T01:01:41","indexId":"70038169","displayToPublicDate":"2012-07-27T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1803,"text":"Geophysical Journal International","active":true,"publicationSubtype":{"id":10}},"title":"Hybrid analysis of multiaxis electromagnetic data for discrimination of munitions and explosives of concern","docAbstract":"The remediation of land containing munitions and explosives of concern, otherwise known as unexploded ordnance, is an ongoing problem facing the U.S. Department of Defense and similar agencies worldwide that have used or are transferring training ranges or munitions disposal areas to civilian control. The expense associated with cleanup of land previously used for military training and war provides impetus for research towards enhanced discrimination of buried unexploded ordnance. Towards reducing that expense, a multiaxis electromagnetic induction data collection and software system, called ALLTEM, was designed and tested with support from the U.S. Department of Defense Environmental Security Technology Certification Program. ALLTEM is an on-time time-domain system that uses a continuous triangle-wave excitation to measure the target-step response rather than traditional impulse response. The system cycles through three orthogonal transmitting loops and records a total of 19 different transmitting and receiving loop combinations with a nominal spatial data sampling interval of 20 cm. Recorded data are pre-processed and then used in a hybrid discrimination scheme involving both data-driven and numerical classification techniques. The data-driven classification scheme is accomplished in three steps. First, field observations are used to train a type of unsupervised artificial neural network, a self-organizing map (SOM). Second, the SOM is used to simultaneously estimate target parameters (depth, azimuth, inclination, item type and weight) by iterative minimization of the topographic error vectors. Third, the target classification is accomplished by evaluating histograms of the estimated parameters. The numerical classification scheme is also accomplished in three steps. First, the Biot–Savart law is used to model the primary magnetic fields from the transmitter coils and the secondary magnetic fields generated by currents induced in the target materials in the ground. Second, the target response is modelled by three orthogonal dipoles from prolate, oblate and triaxial ellipsoids with one long axis and two shorter axes. Each target consists of all three dipoles. Third, unknown target parameters are determined by comparing modelled to measured target responses. By comparing the rms error among the self-organizing map and numerical classification results, we achieved greater than 95 per cent detection and correct classification of the munitions and explosives of concern at the direct fire and indirect fire test areas at the UXO Standardized Test Site at the Aberdeen Proving Ground, Maryland in 2010.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Geophysical Journal International","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","publisherLocation":"Hoboken, NJ","doi":"10.1111/j.1365-246X.2012.05522.x","usgsCitation":"Friedel, M., Asch, T., and Oden, C., 2012, Hybrid analysis of multiaxis electromagnetic data for discrimination of munitions and explosives of concern: Geophysical Journal International, v. 190, no. 2, p. 960-980, https://doi.org/10.1111/j.1365-246X.2012.05522.x.","productDescription":"21 p.","startPage":"960","endPage":"980","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":474402,"rank":10000,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/j.1365-246x.2012.05522.x","text":"Publisher Index Page"},{"id":259230,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":259223,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/j.1365-246X.2012.05522.x","linkFileType":{"id":5,"text":"html"}}],"volume":"190","issue":"2","noUsgsAuthors":false,"publicationDate":"2012-05-25","publicationStatus":"PW","scienceBaseUri":"505a32bde4b0c8380cd5ea29","contributors":{"authors":[{"text":"Friedel, M.J.","contributorId":90823,"corporation":false,"usgs":true,"family":"Friedel","given":"M.J.","email":"","affiliations":[],"preferred":false,"id":463582,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Asch, T.H.","contributorId":90552,"corporation":false,"usgs":true,"family":"Asch","given":"T.H.","email":"","affiliations":[],"preferred":false,"id":463581,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Oden, C.","contributorId":87796,"corporation":false,"usgs":true,"family":"Oden","given":"C.","email":"","affiliations":[],"preferred":false,"id":463580,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70004604,"text":"70004604 - 2012 - Insight on invasions and resilience derived from spatiotemporal discontinuities of biomass at local and regional scales","interactions":[],"lastModifiedDate":"2017-05-10T09:44:50","indexId":"70004604","displayToPublicDate":"2012-07-27T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1468,"text":"Ecology and Society","active":true,"publicationSubtype":{"id":10}},"title":"Insight on invasions and resilience derived from spatiotemporal discontinuities of biomass at local and regional scales","docAbstract":"Understanding the social and ecological consequences of species invasions is complicated by nonlinearities in processes, and differences in process and structure as scale is changed. Here we use discontinuity analyses to investigate nonlinear patterns in the distribution of biomass of an invasive nuisance species that could indicate scale-specific organization. We analyze biomass patterns in the flagellate Gonyostomum semen (Raphidophyta) in 75 boreal lakes during an 11-year period (1997-2007). With simulations using a unimodal null model and cluster analysis, we identified regional groupings of lakes based on their biomass patterns. We evaluated the variability of membership of individual lakes in regional biomass groups. Temporal trends in local and regional discontinuity patterns were analyzed using regressions and correlations with environmental variables that characterize nutrient conditions, acidity status, temperature variability, and water clarity. Regionally, there was a significant increase in the number of biomass groups over time, indicative of an increased number of scales at which algal biomass organizes across lakes. This increased complexity correlated with the invasion history of G. semen and broad-scale environmental change (recovery from acidification). Locally, no consistent patterns of lake membership to regional biomass groups were observed, and correlations with environmental variables were lake specific. The increased complexity of regional biomass patterns suggests that processes that act within or between scales reinforce the presence of G. semen and its potential to develop high-biomass blooms in boreal lakes. Emergent regional patterns combined with locally stochastic dynamics suggest a bleak future for managing G. semen, and more generally why invasive species can be ecologically successful.
","language":"English","publisher":"The Resilience Alliance","doi":"10.5751/ES-04928-170232","usgsCitation":"Angeler, D., Allen, C.R., and Johnson, R.K., 2012, Insight on invasions and resilience derived from spatiotemporal discontinuities of biomass at local and regional scales: Ecology and Society, v. 17, no. 2, 15 p.; Article 32, https://doi.org/10.5751/ES-04928-170232.","productDescription":"15 p.; Article 32","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-037249","costCenters":[{"id":463,"text":"Nebraska Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true}],"links":[{"id":488008,"rank":10000,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5751/es-04928-170232","text":"Publisher Index Page"},{"id":259236,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":259227,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.5751/ES-04928-170232","linkFileType":{"id":5,"text":"html"}}],"volume":"17","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a3c1ee4b0c8380cd62aa3","contributors":{"authors":[{"text":"Angeler, David G.","contributorId":25027,"corporation":false,"usgs":true,"family":"Angeler","given":"David G.","affiliations":[],"preferred":false,"id":350832,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Allen, Criag R.","contributorId":72247,"corporation":false,"usgs":true,"family":"Allen","given":"Criag","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":350833,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Richard K.","contributorId":21810,"corporation":false,"usgs":true,"family":"Johnson","given":"Richard","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":350831,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70003663,"text":"70003663 - 2012 - Effects of soil-engineering properties on the failure mode of shallow landslides","interactions":[],"lastModifiedDate":"2012-07-28T01:01:41","indexId":"70003663","displayToPublicDate":"2012-07-27T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2604,"text":"Landslides","active":true,"publicationSubtype":{"id":10}},"title":"Effects of soil-engineering properties on the failure mode of shallow landslides","docAbstract":"Some landslides mobilize into flows, while others slide and deposit material immediately down slope. An index based on initial dry density and fine-grained content of soil predicted failure mode of 96 landslide initiation sites in Oregon and Colorado with 79% accuracy. These material properties can be used to identify potential sources for debris flows and for slides. Field data suggest that loose soils can evolve from dense soils that dilate upon shearing. The method presented herein to predict failure mode is most applicable for shallow (depth <5 m), well-graded soils (coefficient of uniformity >8), with few to moderate fines (fine-grained content <18%), and with liquid limits <40.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Landslides","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","publisherLocation":"Amsterdam, Netherlands","doi":"10.1007/s10346-011-0295-3","usgsCitation":"McKenna, J.P., Santi, P.M., Amblard, X., and Negri, J., 2012, Effects of soil-engineering properties on the failure mode of shallow landslides: Landslides, v. 9, no. 2, p. 215-228, https://doi.org/10.1007/s10346-011-0295-3.","productDescription":"14 p.","startPage":"215","endPage":"228","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":259198,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":259196,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s10346-011-0295-3","linkFileType":{"id":5,"text":"html"}}],"volume":"9","issue":"2","noUsgsAuthors":false,"publicationDate":"2011-09-23","publicationStatus":"PW","scienceBaseUri":"505a07d1e4b0c8380cd51859","contributors":{"authors":[{"text":"McKenna, Jonathan Peter","contributorId":50398,"corporation":false,"usgs":true,"family":"McKenna","given":"Jonathan","email":"","middleInitial":"Peter","affiliations":[],"preferred":false,"id":348226,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Santi, Paul Michael","contributorId":61696,"corporation":false,"usgs":true,"family":"Santi","given":"Paul","email":"","middleInitial":"Michael","affiliations":[],"preferred":false,"id":348228,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Amblard, Xavier","contributorId":61290,"corporation":false,"usgs":true,"family":"Amblard","given":"Xavier","email":"","affiliations":[],"preferred":false,"id":348227,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Negri, Jacquelyn","contributorId":49650,"corporation":false,"usgs":true,"family":"Negri","given":"Jacquelyn","affiliations":[],"preferred":false,"id":348225,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70009700,"text":"70009700 - 2012 - Evaluation of SNODAS snow depth and snow water equivalent estimates for the Colorado Rocky Mountains, USA","interactions":[],"lastModifiedDate":"2012-08-08T17:16:36","indexId":"70009700","displayToPublicDate":"2012-07-27T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of SNODAS snow depth and snow water equivalent estimates for the Colorado Rocky Mountains, USA","docAbstract":"The National Weather Service's Snow Data Assimilation (SNODAS) program provides daily, gridded estimates of snow depth, snow water equivalent (SWE), and related snow parameters at a 1-km2 resolution for the conterminous USA. In this study, SNODAS snow depth and SWE estimates were compared with independent, ground-based snow survey data in the Colorado Rocky Mountains to assess SNODAS accuracy at the 1-km2 scale. Accuracy also was evaluated at the basin scale by comparing SNODAS model output to snowmelt runoff in 31 headwater basins with US Geological Survey stream gauges. Results from the snow surveys indicated that SNODAS performed well in forested areas, explaining 72% of the variance in snow depths and 77% of the variance in SWE. However, SNODAS showed poor agreement with measurements in alpine areas, explaining 16% of the variance in snow depth and 30% of the variance in SWE. At the basin scale, snowmelt runoff was moderately correlated (R2 = 0.52) with SNODAS model estimates. A simple method for adjusting SNODAS SWE estimates in alpine areas was developed that uses relations between prevailing wind direction, terrain, and vegetation to account for wind redistribution of snow in alpine terrain. The adjustments substantially improved agreement between measurements and SNODAS estimates, with the R2 of measured SWE values against SNODAS SWE estimates increasing from 0.42 to 0.63 and the root mean square error decreasing from 12 to 6 cm. Results from this study indicate that SNODAS can provide reliable data for input to moderate-scale to large-scale hydrologic models, which are essential for creating accurate runoff forecasts. Refinement of SNODAS SWE estimates for alpine areas to account for wind redistribution of snow could further improve model performance. Published 2011. This article is a US Government work and is in the public domain in the USA.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Hydrological Processes","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","publisherLocation":"Hoboken, NJ","doi":"10.1002/hyp.9385","usgsCitation":"Clow, D.W., Nanus, L., Verdin, K.L., and Schmidt, J., 2012, Evaluation of SNODAS snow depth and snow water equivalent estimates for the Colorado Rocky Mountains, USA: Hydrological Processes, v. 26, no. 17, p. 2583-2591, https://doi.org/10.1002/hyp.9385.","productDescription":"9 p.","startPage":"2583","endPage":"2591","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":257800,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://dx.doi.org/10.1002/hyp.9385","linkFileType":{"id":5,"text":"html"}},{"id":259212,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Rocky Mountains","volume":"26","issue":"17","noUsgsAuthors":false,"publicationDate":"2012-06-05","publicationStatus":"PW","scienceBaseUri":"505a0c21e4b0c8380cd52a4d","contributors":{"authors":[{"text":"Clow, David W. 0000-0001-6183-4824 dwclow@usgs.gov","orcid":"https://orcid.org/0000-0001-6183-4824","contributorId":1671,"corporation":false,"usgs":true,"family":"Clow","given":"David","email":"dwclow@usgs.gov","middleInitial":"W.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":356873,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nanus, Leora","contributorId":27930,"corporation":false,"usgs":true,"family":"Nanus","given":"Leora","email":"","affiliations":[],"preferred":false,"id":356875,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Verdin, Kristine L. 0000-0002-6114-4660 kverdin@usgs.gov","orcid":"https://orcid.org/0000-0002-6114-4660","contributorId":3070,"corporation":false,"usgs":true,"family":"Verdin","given":"Kristine","email":"kverdin@usgs.gov","middleInitial":"L.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":356874,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schmidt, Jeffrey","contributorId":90972,"corporation":false,"usgs":true,"family":"Schmidt","given":"Jeffrey","email":"","affiliations":[],"preferred":false,"id":356876,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70009627,"text":"70009627 - 2012 - Habitat use by a freshwater dolphin in the low-water season","interactions":[],"lastModifiedDate":"2018-01-08T12:22:50","indexId":"70009627","displayToPublicDate":"2012-07-27T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":862,"text":"Aquatic Conservation: Marine and Freshwater Ecosystems","active":true,"publicationSubtype":{"id":10}},"title":"Habitat use by a freshwater dolphin in the low-water season","docAbstract":"1. Many river dolphin populations are most vulnerable during the low-water season when habitat is limited. Indus River dolphin habitat selection in the dry season was investigated using Generalized Linear Models of dolphin distribution and abundance in relation to physical features of river geomorphology and channel geometry in cross-section. 2. Dolphins selected locations in the river with significantly greater mean depth, maximum depth, cross-sectional area, and hydraulic radius, and significantly narrower river width and a lower degree of braiding than areas where dolphins were absent. They were also recorded with higher frequency at river constrictions and at confluences. 3. Channel cross-sectional area was the most important factor affecting dolphin presence and abundance, with the area of water below 1 m in depth exerting the greatest influence. Indus dolphins avoided channels with small cross-sectional area (<700 m2), presumably owing to the risk of entrapment and reduced foraging opportunities. 4. Channel geometry had a greater ability to explain dolphin distribution than river geomorphology; however, both analyses indicated similar types of habitat selection. The dolphin–habitat relationships identified in the river geomorphology analysis were scale-dependent, indicating that dolphin distribution is driven by the occurrence of discrete small-scale features, such as confluences and constrictions, as well as by broader-scale habitat complexes. 5. There are numerous plans to impound or extract more water from the Indus River system. If low-water season flows are allowed to decrease further, the amount of deeper habitat will decline, there may be insufficient patches of suitable habitat to support the dolphin population through the low-water season, and dolphins may become isolated within deeper river sections, unable or unwilling to traverse through shallows between favourable patches of habitat.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Aquatic Conservation: Marine and Freshwater Ecosystems","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","publisherLocation":"Hoboken, NJ","doi":"10.1002/aqc.2246","usgsCitation":"Braulik, G.T., Reichert, A.P., Ehsan, T., Khan, S., Northridge, S.P., Alexander, J.S., and Garstang, R., 2012, Habitat use by a freshwater dolphin in the low-water season: Aquatic Conservation: Marine and Freshwater Ecosystems, v. 22, no. 4, p. 533-546, https://doi.org/10.1002/aqc.2246.","productDescription":"14 p.","startPage":"533","endPage":"546","costCenters":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"links":[{"id":259218,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":259208,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/aqc.2246","linkFileType":{"id":5,"text":"html"}}],"otherGeospatial":"Indus River","volume":"22","issue":"4","noUsgsAuthors":false,"publicationDate":"2012-05-04","publicationStatus":"PW","scienceBaseUri":"505a2f3de4b0c8380cd5cbea","contributors":{"authors":[{"text":"Braulik, Gill T.","contributorId":28472,"corporation":false,"usgs":true,"family":"Braulik","given":"Gill","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":356763,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reichert, Albert P.","contributorId":10655,"corporation":false,"usgs":true,"family":"Reichert","given":"Albert","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":356762,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ehsan, Tahir","contributorId":58504,"corporation":false,"usgs":true,"family":"Ehsan","given":"Tahir","email":"","affiliations":[],"preferred":false,"id":356766,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Khan, Samiullah","contributorId":49644,"corporation":false,"usgs":true,"family":"Khan","given":"Samiullah","email":"","affiliations":[],"preferred":false,"id":356765,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Northridge, Simon P.","contributorId":106362,"corporation":false,"usgs":true,"family":"Northridge","given":"Simon","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":356768,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Alexander, Jason S. 0000-0002-1602-482X jalexand@usgs.gov","orcid":"https://orcid.org/0000-0002-1602-482X","contributorId":2802,"corporation":false,"usgs":true,"family":"Alexander","given":"Jason","email":"jalexand@usgs.gov","middleInitial":"S.","affiliations":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"preferred":false,"id":356767,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Garstang, Richard","contributorId":45165,"corporation":false,"usgs":true,"family":"Garstang","given":"Richard","email":"","affiliations":[],"preferred":false,"id":356764,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70006298,"text":"70006298 - 2012 - Evaluating changes in matrix based, recovery-adjusted concentrations in paired data for pesticides in groundwater","interactions":[],"lastModifiedDate":"2012-07-28T01:01:42","indexId":"70006298","displayToPublicDate":"2012-07-27T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2262,"text":"Journal of Environmental Quality","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating changes in matrix based, recovery-adjusted concentrations in paired data for pesticides in groundwater","docAbstract":"Pesticide concentration data for waters from selected carbonate-rock aquifers in agricultural areas of Pennsylvania were collected in 1993–2009 for occurrence and distribution assessments. A set of 30 wells was visited once in 1993–1995 and again in 2008–2009 to assess concentration changes. The data include censored matched pairs (nondetections of a compound in one or both samples of a pair). A potentially improved approach for assessing concentration changes is presented where (i) concentrations are adjusted with models of matrix-spike recovery and (ii) area-wide temporal change is tested by use of the paired Prentice-Wilcoxon (PPW) statistical test. The PPW results for atrazine, simazine, metolachlor, prometon, and an atrazine degradate, deethylatrazine (DEA), are compared using recovery-adjusted and unadjusted concentrations. Results for adjusted compared with unadjusted concentrations in 2008–2009 compared with 1993–1995 were similar for atrazine and simazine (significant decrease; 95% confidence level) and metolachlor (no change) but differed for DEA (adjusted, decrease; unadjusted, increase) and prometon (adjusted, decrease; unadjusted, no change). The PPW results were different on recovery-adjusted compared with unadjusted concentrations. Not accounting for variability in recovery can mask a true change, misidentify a change when no true change exists, or assign a direction opposite of the true change in concentration that resulted from matrix influences on extraction and laboratory method performance. However, matrix-based models of recovery derived from a laboratory performance dataset from multiple studies for national assessment, as used herein, rather than time- and study-specific recoveries may introduce uncertainty in recovery adjustments for individual samples that should be considered in assessing change.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Environmental Quality","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"ACSESS DL","publisherLocation":"Madison, WI","doi":"10.2134/jeq2011.0271","usgsCitation":"Zimmerman, T.M., and Breen, K.J., 2012, Evaluating changes in matrix based, recovery-adjusted concentrations in paired data for pesticides in groundwater: Journal of Environmental Quality, v. 41, no. 4, p. 1238-1245, https://doi.org/10.2134/jeq2011.0271.","productDescription":"8 p.","startPage":"1238","endPage":"1245","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":259216,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":259202,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.2134/jeq2011.0271","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Pennsylvania","volume":"41","issue":"4","noUsgsAuthors":false,"publicationDate":"2012-07-01","publicationStatus":"PW","scienceBaseUri":"505a0bdce4b0c8380cd528fa","contributors":{"authors":[{"text":"Zimmerman, Tammy M. 0000-0003-0842-6981 tmzimmer@usgs.gov","orcid":"https://orcid.org/0000-0003-0842-6981","contributorId":2359,"corporation":false,"usgs":true,"family":"Zimmerman","given":"Tammy","email":"tmzimmer@usgs.gov","middleInitial":"M.","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":false,"id":354257,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Breen, Kevin J. 0000-0002-9447-6469 kjbreen@usgs.gov","orcid":"https://orcid.org/0000-0002-9447-6469","contributorId":219,"corporation":false,"usgs":true,"family":"Breen","given":"Kevin","email":"kjbreen@usgs.gov","middleInitial":"J.","affiliations":[{"id":501,"text":"Office of Science Quality and Integrity","active":true,"usgs":true}],"preferred":true,"id":354256,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70039213,"text":"sir20125123 - 2012 - Groundwater quality in the Columbia Plateau, Snake River Plain, and Oahu basaltic-rock and basin-fill aquifers in the Northwestern United States and Hawaii, 1992-2010","interactions":[],"lastModifiedDate":"2016-08-31T17:31:58","indexId":"sir20125123","displayToPublicDate":"2012-07-26T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-5123","subseriesTitle":"National Water-Quality Assessment Program","title":"Groundwater quality in the Columbia Plateau, Snake River Plain, and Oahu basaltic-rock and basin-fill aquifers in the Northwestern United States and Hawaii, 1992-2010","docAbstract":"This assessment of groundwater-quality conditions of the Columbia Plateau, Snake River Plain, and Oahu for the period 1992–2010 is part of the U.S. Geological Survey’s National Water Quality Assessment (NAWQA) program. It shows where, when, why, and how specific water-quality conditions occur in groundwater of the three study areas and yields science-based implications for assessing and managing the quality of these water resources. The primary aquifers in the Columbia Plateau, Snake River Plain, and Oahu are mostly composed of fractured basalt, which makes their hydrology and geochemistry similar. In spite of the hydrogeologic similarities, there are climatic differences that affect the agricultural practices overlying the aquifers, which in turn affect the groundwater quality. Understanding groundwater-quality conditions and the natural and human factors that control groundwater quality is important because of the implications to human health, the sustainability of rural agricultural economies, and the substantial costs associated with land and water management, conservation, and regulation.
\nThe principal regional aquifers of the Columbia Plateau, Snake River Plain, and Oahu are highly vulnerable to contamination by chemicals applied at the land surface; essentially, they are as vulnerable as many shallow surficial aquifers elsewhere. The permeable and largely unconfined character of principal aquifers in the Columbia Plateau, Snake River Plain, and Oahu allow water and chemicals to infiltrate to the water table despite depths to water commonly in the hundreds of feet. The aquifers are essentially unconfined over large areas, having few extensive clay layers to impede infiltration through permeable volcanic rock and alluvial sediments. Agriculture is intensive in all three study areas, and heavy irrigation has imposed large artificial flows of irrigation recharge that rival or exceed natural recharge rates. Fertilizers and pesticides applied at land surface are leached from soil and transported to deep water tables with the infiltrating irrigation recharge, resulting in a layer of degraded water quality overlying better quality regional groundwater beneath. This “irrigation-recharge layer” is best known on Oahu, where it has been studied since the 1960s; however, the extent of nitrate and pesticide contamination in the Columbia Plateau and Snake River Plain indicate that the same situation exists in those areas. Contamination from agricultural and urban activities is present not only at shallow depths in surficial materials of the three areas, but extends regionally in the deep, principal bedrock aquifers that are tapped for drinking water by domestic and public-supply wells.
\nNaturally occurring constituents and nitrate concentrations above human-health benchmarks—Maximum Contaminant Levels (MCLs), and Health-Based Screening Levels (HBSLs)—were more common in the Columbia Plateau and the Snake River Plain than in Oahu. Concentrations of anthropogenic constituents (constituents related to human activities) above human-health benchmarks were more common in Oahu. Naturally occurring contaminants, such as arsenic and radon, may be present in groundwater at concentrations of potential concern for human health in relatively undeveloped settings that otherwise may not be perceived as susceptible to contamination. Even though the median depth to groundwater in Oahu is more than 300 feet, the common occurrence of anthropogenic compounds in groundwater indicates that Oahu has a high susceptibility to contamination.
\nNitrate concentrations in groundwater were above the national background concentrations of 1 milligram per liter (mg/L) in all three study areas. In the Columbia Plateau, nitrate exceeded the human-health benchmark of 10 mg/L in 20 percent of the wells sampled. In the Snake River Plain, nitrate exceeded the human-health benchmark of 10 mg/L in 3 percent of the wells sampled. Nitrate can persist in groundwater for years and even decades in the oxygen-rich groundwater of the Columbia Plateau and the Snake River Plain, so prudent groundwater protection measures are critical to protect drinking water resources by reducing nitrate leaching from the land surface.
\nNitrate logistic regression models indicated that areas with a high percentage of land in crops (such as potatoes or sugarcane) and soils with low amounts of organic matter are most likely to have elevated nitrate concentrations in the groundwater. Areas where agricultural activities were absent had much lower probabilities of detecting elevated nitrate concentrations. The Columbia Plateau had a much higher probability of having elevated nitrate concentrations, with most of the land area having greater than a 50 percent probability of elevated nitrate concentrations. Oahu and the Snake River Plain had a much lower probability of having elevated nitrate concentrations because of their lower percentage of agricultural land.
\nPesticides were detected at many sites in groundwater of the Columbia Plateau, Snake River Plain, and Oahu but generally at low concentrations below human-health benchmarks. Atrazine and its degradate (a compound produced from the breakdown of a parent pesticide), deethylatrazine, were the most commonly detected pesticides in groundwater sampled in the Columbia Plateau and Snake River Plain. Bromacil was the most commonly detected pesticide on Oahu. The other pesticides most commonly detected in the study areas include simazine, hexazinone, metribuzin, diuron, prometon, metolachlor, p,p’-DDE, dieldrin, 2-4-D, and alachlor. DDE (a degradate of DDT) and dieldrin are still being detected in groundwater despite having been banned for more than 30 years. Codetection of multiple pesticides in water from a single well was common. The widespread occurrence of pesticides in groundwater in the study areas indicates that the groundwater is highly susceptible to pesticide contamination.
\nSome pesticides were detected in groundwater samples from all three study areas, but other pesticides were detected only in samples from Oahu, or only in samples from the Columbia Plateau and Snake River Plain. This is because some pesticides (such as atrazine) are broad-spectrum pesticides that are used on many crops in many different areas of the United States. Other pesticides (such as simazine, metribuzin, and metolachlor) are used on row crops (such as potatoes, barley, and alfalfa) grown in the Columbia Plateau and Snake River Plain, but not on pineapple or sugarcane grown in Oahu.
\nAtrazine logistic-regression models indicate that areas with a high percentage of land in crops (such as potatoes or sugarcane), a low percentage of fallow land, and highly permeable soils with low amounts of organic matter are most likely to have atrazine detected in the groundwater. Areas where agricultural activities were absent had much lower probabilities of atrazine being detected. The Snake River Plain had a much higher probability of atrazine detections, with more than 50 percent of the land area having greater than a 50 percent probability of atrazine contamination. Oahu had a much lower probability of atrazine contamination, with only 24 percent of the land area having greater than a 50 percent probability of atrazine contamination.
\nOahu and the Columbia Plateau had some of the highest percentages of soil fumigant detections in groundwater in the United States. Soil fumigants are volatile organic compounds (VOCs) used as pesticides, which are applied to soils to reduce populations of plant parasitic nematodes (harmful rootworms), weeds, fungal pathogens, and other soil-borne microorganisms. They are used in Oahu and the Columbia Plateau on crops such as pineapple and potatoes. All three areas (Columbia Plateau, Snake River Plain, and Oahu) had fumigant concentrations exceeding human-health benchmarks for drinking water.
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The inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation/ and the Federal Flood Inundation Mapper Web site at http://wim.usgs.gov/FIMI/FloodInundationMapper.html, depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) referenced to the USGS streamgage at West Branch Delaware River upstream from Delhi, N.Y. (station number 01421900).\r\nIn this study, flood profiles were computed for the stream reach by means of a one-dimensional step-backwater model that had been used to produce the flood insurance rate maps for the most recent flood insurance study for the Town and Village of Delhi. This hydraulic model was used to compute 10 water-surface profiles for flood stages at 1-foot (ft) intervals referenced to the streamgage datum and ranging from 7 ft or near bankfull to 16 ft, which exceeds the stages that correspond to both the estimated 0.2-percent annual-exceedance-probability flood (500-year recurrence interval flood) and the maximum recorded peak flow. The simulated water-surface profiles were then combined with a geographic information system (GIS) digital elevation model, which was derived from Light Detection and Ranging (LiDAR) data with a 1.2-ft (0.61-ft root mean squared error) vertical accuracy and 3.3-ft (1-meter) horizontal resolution, to delineate the area flooded at each water level. A map that was produced using this method to delineate the inundated area for the flood that occurred on August 28, 2011, agreed well with highwater marks that had been located in the field using a global positioning system. The availability of the 10 flood-inundation maps on the USGS Flood Inundation Mapping Science Web site, along with Internet information regarding current stage from the USGS streamgage, will provide emergency management personnel and residents with information that is critical for flood-response activities, such as evacuations and road closures, as well as for post-flood recovery efforts.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3216","usgsCitation":"Coon, W.F., and Breaker, B.K., 2012, Flood-inundation maps for the West Branch Delaware River, Delhi, New York, 2012: U.S. Geological Survey Scientific Investigations Map 3216, Pamphlet: vi, 9 p.; 10 Sheets; Sheet 1: 17 inches x 22 inches, Sheet 2: 17 inches x 22 inches, Sheet 3: 17 inches x 22 inches, Sheet 4: 17 inches x 22 inches, Sheet 5: 17 inches x 22 inches, Sheet 6: 17 inches x 22 inches, Sheet 7: 17 inches x 22 inches, Sheet 8: 17 inches x 22 inches, Sheet 9: 17 inches x 22 inches, Sheet 10: 17 inches x 22 inches; 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