The Integrated Ocean Drilling Program (IODP) Expedition 310 recovered drill cores from the drowned reefs around the island of Tahiti (17°40′S, 149°30′W), many of which contained samples of massive corals from the genus Porites. Herein we report on one well-preserved fossil coral sample: a 13.6 cm long Porites sp. dated by uranium series techniques at 9523 ± 33 years. Monthly δ18O and Sr/Ca determinations reveal nine clear and robust annual cycles. Coral δ18O and Sr/Ca determinations estimate a mean temperature of ∼24.3°C (∼3.2°C colder than modern) for Tahiti at 9.5 ka; however, this estimate is viewed with caution since potential sources of cold bias in coral geochemistry remain to be resolved. The interannual variability in coral δ18O is similar between the 9.5 ka coral record and a modern record from nearby Moorea. The seasonal cycle in coral Sr/Ca is approximately the same or greater in the 9.5 ka coral record than in modern coral records from Tahiti. Paired analysis of coral δ18O and Sr/Ca indicates cold/wet (warm/dry) interannual anomalies, opposite from those observed in the modern instrumental record.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2009GC002758","usgsCitation":"DeLong, K.L., Quinn, T., Shen, C., and Lin, K., 2010, A snapshot of climate variability at Tahiti ~ 9 ka using a fossil coral from IODP Expedition 310: Geochemistry, Geophysics, Geosystems, v. 11, no. 6, Q06005, 14 p., https://doi.org/10.1029/2009GC002758.","productDescription":"Q06005, 14 p.","ipdsId":"IP-014561","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":417103,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Tahiti","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -149.97340625761515,\n -17.37818620895858\n ],\n [\n -149.97340625761515,\n -17.956825850324933\n ],\n [\n -149.0404249716099,\n -17.956825850324933\n ],\n [\n -149.0404249716099,\n -17.37818620895858\n ],\n [\n -149.97340625761515,\n -17.37818620895858\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"11","issue":"6","noUsgsAuthors":false,"publicationDate":"2010-06-08","publicationStatus":"PW","contributors":{"authors":[{"text":"DeLong, Kristine L","contributorId":305465,"corporation":false,"usgs":true,"family":"DeLong","given":"Kristine","email":"","middleInitial":"L","affiliations":[],"preferred":true,"id":872848,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Quinn, Terrence M.","contributorId":305466,"corporation":false,"usgs":false,"family":"Quinn","given":"Terrence M.","affiliations":[{"id":13603,"text":"University of Texas, Austin","active":true,"usgs":false}],"preferred":false,"id":872849,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shen, Chuan-Chou","contributorId":305467,"corporation":false,"usgs":false,"family":"Shen","given":"Chuan-Chou","affiliations":[{"id":30216,"text":"National Taiwan University","active":true,"usgs":false}],"preferred":false,"id":872850,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lin, Ke","contributorId":305468,"corporation":false,"usgs":false,"family":"Lin","given":"Ke","affiliations":[{"id":30216,"text":"National Taiwan University","active":true,"usgs":false}],"preferred":false,"id":872851,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70118902,"text":"70118902 - 2010 - Modeling the dynamic geochemistry of prairie pothole wetlands","interactions":[],"lastModifiedDate":"2014-07-31T09:06:24","indexId":"70118902","displayToPublicDate":"2010-06-07T09:05:48","publicationYear":"2010","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":18,"text":"Abstract or summary"},"title":"Modeling the dynamic geochemistry of prairie pothole wetlands","docAbstract":"No abstract available.","largerWorkTitle":"3rd USGS Modeling Conference","language":"English","publisher":"Geological Society of America","publisherLocation":"Boulder, CO","usgsCitation":"Goldhaber, M., Mills, C., Stricker, C.A., LaBaugh, J.W., Mushet, D., and Euliss, N., 2010, Modeling the dynamic geochemistry of prairie pothole wetlands, in 3rd USGS Modeling Conference.","costCenters":[],"links":[{"id":291447,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53db5846e4b0fba533fa358d","contributors":{"authors":[{"text":"Goldhaber, M.C.","contributorId":6772,"corporation":false,"usgs":true,"family":"Goldhaber","given":"M.C.","email":"","affiliations":[],"preferred":false,"id":497372,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mills, C.T.","contributorId":77395,"corporation":false,"usgs":true,"family":"Mills","given":"C.T.","email":"","affiliations":[],"preferred":false,"id":497376,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stricker, Craig A. 0000-0002-5031-9437 cstricker@usgs.gov","orcid":"https://orcid.org/0000-0002-5031-9437","contributorId":1097,"corporation":false,"usgs":true,"family":"Stricker","given":"Craig","email":"cstricker@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":497371,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"LaBaugh, J. W.","contributorId":23484,"corporation":false,"usgs":true,"family":"LaBaugh","given":"J.","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":497373,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mushet, D. 0000-0002-5910-2744","orcid":"https://orcid.org/0000-0002-5910-2744","contributorId":72723,"corporation":false,"usgs":true,"family":"Mushet","given":"D.","affiliations":[],"preferred":false,"id":497375,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Euliss, N.H.","contributorId":27836,"corporation":false,"usgs":true,"family":"Euliss","given":"N.H.","affiliations":[],"preferred":false,"id":497374,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":98424,"text":"ds511 - 2010 - EAARL Coastal Topography-Chandeleur Islands, Louisiana, 2010: Bare Earth","interactions":[],"lastModifiedDate":"2012-02-10T00:11:52","indexId":"ds511","displayToPublicDate":"2010-06-02T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"511","title":"EAARL Coastal Topography-Chandeleur Islands, Louisiana, 2010: Bare Earth","docAbstract":"These remotely sensed, geographically referenced elevation measurements of lidar-derived bare-earth (BE) and submerged topography datasets were produced collaboratively by the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center, St. Petersburg, FL, and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA.\r\n\r\nThis project provides highly detailed and accurate datasets of a portion of the Chandeleur Islands, acquired March 3, 2010. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative airborne lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multispectral color-infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for sub-meter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. \r\n\r\nElevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of lidar data in an interactive or batch mode. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or sub-aerial topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation from a point cloud of last return elevations.\r\n\r\nFor more information about similar projects, please visit the Decision Support for Coastal Science and Management website.\r\n\r\n","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/ds511","usgsCitation":"Nayegandhi, A., Bonisteel-Cormier, J.M., Brock, J., Sallenger, A., Wright, C.W., Nagle, D.B., Vivekanandan, S., Yates, X., and Klipp, E.S., 2010, EAARL Coastal Topography-Chandeleur Islands, Louisiana, 2010: Bare Earth: U.S. Geological Survey Data Series 511, DVD, https://doi.org/10.3133/ds511.","productDescription":"DVD","onlineOnly":"N","additionalOnlineFiles":"Y","costCenters":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"links":[{"id":199365,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":13676,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/511/","linkFileType":{"id":5,"text":"html"}}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -88.75,30.083333333333332 ], [ -88.75,29.75 ], [ -88.91666666666667,29.75 ], [ -88.91666666666667,30.083333333333332 ], [ -88.75,30.083333333333332 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4afde4b07f02db6971f6","contributors":{"authors":[{"text":"Nayegandhi, Amar","contributorId":37292,"corporation":false,"usgs":true,"family":"Nayegandhi","given":"Amar","affiliations":[],"preferred":false,"id":305264,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bonisteel-Cormier, Jamie M.","contributorId":18085,"corporation":false,"usgs":true,"family":"Bonisteel-Cormier","given":"Jamie","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":305263,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brock, John 0000-0002-5289-9332 jbrock@usgs.gov","orcid":"https://orcid.org/0000-0002-5289-9332","contributorId":2261,"corporation":false,"usgs":true,"family":"Brock","given":"John","email":"jbrock@usgs.gov","affiliations":[{"id":5061,"text":"National Cooperative Geologic Mapping and Landslide Hazards","active":true,"usgs":true}],"preferred":true,"id":305260,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sallenger, A. H.","contributorId":78290,"corporation":false,"usgs":true,"family":"Sallenger","given":"A. H.","affiliations":[],"preferred":false,"id":305266,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wright, C. Wayne wwright@usgs.gov","contributorId":57422,"corporation":false,"usgs":true,"family":"Wright","given":"C.","email":"wwright@usgs.gov","middleInitial":"Wayne","affiliations":[],"preferred":false,"id":305265,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nagle, David B. 0000-0002-2306-6147 dnagle@usgs.gov","orcid":"https://orcid.org/0000-0002-2306-6147","contributorId":3380,"corporation":false,"usgs":true,"family":"Nagle","given":"David","email":"dnagle@usgs.gov","middleInitial":"B.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":305262,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Vivekanandan, Saisudha","contributorId":84325,"corporation":false,"usgs":true,"family":"Vivekanandan","given":"Saisudha","email":"","affiliations":[],"preferred":false,"id":305268,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Yates, Xan","contributorId":78291,"corporation":false,"usgs":true,"family":"Yates","given":"Xan","email":"","affiliations":[],"preferred":false,"id":305267,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Klipp, Emily S. eklipp@usgs.gov","contributorId":2754,"corporation":false,"usgs":true,"family":"Klipp","given":"Emily","email":"eklipp@usgs.gov","middleInitial":"S.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":305261,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":98423,"text":"sir20105027 - 2010 - Simulation of streamflow, evapotranspiration, and groundwater recharge in the lower San Antonio River Watershed, South-Central Texas, 2000-2007","interactions":[],"lastModifiedDate":"2016-08-11T16:39:01","indexId":"sir20105027","displayToPublicDate":"2010-06-02T00:00:00","publicationYear":"2010","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":"2010-5027","title":"Simulation of streamflow, evapotranspiration, and groundwater recharge in the lower San Antonio River Watershed, South-Central Texas, 2000-2007","docAbstract":"The U.S. Geological Survey (USGS), in cooperation with the San Antonio River Authority, the Evergreen Underground Water Conservation District, and the Goliad County Groundwater Conservation District, configured, calibrated, and tested a watershed model for a study area consisting of about 2,150 square miles of the lower San Antonio River watershed in Bexar, Guadalupe, Wilson, Karnes, DeWitt, Goliad, Victoria, and Refugio Counties in south-central Texas. The model simulates streamflow, evapotranspiration (ET), and groundwater recharge using rainfall, potential ET, and upstream discharge data obtained from National Weather Service meteorological stations and USGS streamflow-gaging stations. Additional time-series inputs to the model include wastewater treatment-plant discharges, withdrawals for cropland irrigation, and estimated inflows from springs. Model simulations of streamflow, ET, and groundwater recharge were done for 2000-2007. Because of the complexity of the study area, the lower San Antonio River watershed was divided into four subwatersheds; separate HSPF models were developed for each subwatershed. Simulation of the overall study area involved running simulations of the three upstream models, then running the downstream model. The surficial geology was simplified as nine contiguous water-budget zones to meet model computational limitations and also to define zones for which ET, recharge, and other water-budget information would be output by the model. The model was calibrated and tested using streamflow data from 10 streamflow-gaging stations; additionally, simulated ET was compared with measured ET from a meteorological station west of the study area. The model calibration is considered very good; streamflow volumes were calibrated to within 10 percent of measured streamflow volumes. During 2000-2007, the estimated annual mean rainfall for the water-budget zones ranged from 33.7 to 38.5 inches per year; the estimated annual mean rainfall for the entire watershed was 34.3 inches. Using the HSPF model it was estimated that for 2000-2007, less than 10 percent of the annual mean rainfall on the study watershed exited the watershed as streamflow, whereas about 82 percent, or an average of 28.2 inches per year, exited the watershed as ET. Estimated annual mean groundwater recharge for the entire study area was 3.0 inches, or about 9 percent of annual mean rainfall. Estimated annual mean recharge was largest in water-budget zone 3, the zone where the Carrizo Sand outcrops. In water-budget zone 3, the estimated annual mean recharge was 5.1 inches or about 15 percent of annual mean rainfall. Estimated annual mean recharge was smallest in water-budget zone 6, about 1.1 inches or about 3 percent of annual mean rainfall. The Cibolo Creek subwatershed and the subwatershed of the San Antonio River upstream from Cibolo Creek had the largest and smallest basin yields, about 4.8 inches and 1.2 inches, respectively. Estimated annual ET and annual recharge generally increased with increasing annual rainfall. Also, ET was larger in zones 8 and 9, the most downstream zones in the watershed. Model limitations include possible errors related to model conceptualization and parameter variability, lack of data to quantify certain model inputs, and measurement errors. Uncertainty regarding the degree to which available rainfall data represent actual rainfall is potentially the most serious source of measurement error.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, Virginia","doi":"10.3133/sir20105027","collaboration":"In cooperation with the San Antonio River Authority, the Evergreen Underground Water Conservation District, and the Goliad County Groundwater Conservation District","usgsCitation":"Lizarraga, J.S., and Ockerman, D.J., 2010, Simulation of streamflow, evapotranspiration, and groundwater recharge in the lower San Antonio River Watershed, South-Central Texas, 2000-2007: U.S. Geological Survey Scientific Investigations Report 2010-5027, v, 41 p., https://doi.org/10.3133/sir20105027.","productDescription":"v, 41 p.","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"2000-01-01","temporalEnd":"2007-12-31","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":118469,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2010_5027.jpg"},{"id":13675,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2010/5027/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Texas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -98.63525390624999,\n 29.578234494739206\n ],\n [\n -96.932373046875,\n 29.377388403478992\n ],\n [\n -97.27294921875,\n 28.724313406473463\n ],\n [\n -98.72863769531249,\n 29.16655229520015\n ],\n [\n -98.734130859375,\n 29.516110386062277\n ],\n [\n -98.63525390624999,\n 29.578234494739206\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e49f8e4b07f02db5f2f32","contributors":{"authors":[{"text":"Lizarraga, Joy S.","contributorId":43735,"corporation":false,"usgs":true,"family":"Lizarraga","given":"Joy","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":305259,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ockerman, Darwin J. 0000-0003-1958-1688 ockerman@usgs.gov","orcid":"https://orcid.org/0000-0003-1958-1688","contributorId":1579,"corporation":false,"usgs":true,"family":"Ockerman","given":"Darwin","email":"ockerman@usgs.gov","middleInitial":"J.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":305258,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":98418,"text":"sir20105071 - 2010 - Selected Hydrologic, Water-Quality, Biological, and Sedimentation Characteristics of Laguna Grande, Fajardo, Puerto Rico, March 2007-February 2009","interactions":[],"lastModifiedDate":"2012-03-08T17:16:29","indexId":"sir20105071","displayToPublicDate":"2010-06-02T00:00:00","publicationYear":"2010","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":"2010-5071","title":"Selected Hydrologic, Water-Quality, Biological, and Sedimentation Characteristics of Laguna Grande, Fajardo, Puerto Rico, March 2007-February 2009","docAbstract":"Laguna Grande is a 50-hectare lagoon in the municipio of Fajardo, located in the northeasternmost part of Puerto Rico. Hydrologic, water-quality, and biological data were collected in the lagoon between March 2007 and February 2009 to establish baseline conditions and determine the health of Laguna Grande on the basis of preestablished standards. In addition, a core of bottom material was obtained at one site within the lagoon to establish sediment depositional rates.\r\n\r\n\r\nWater-quality properties measured onsite (temperature, pH, dissolved oxygen, specific conductance, and water transparency) varied temporally rather than areally. All physical properties were in compliance with current regulatory standards established for Puerto Rico. Nutrient concentrations were very low and in compliance with current regulatory standards (less than 5.0 and 1.0 milligrams per liter for total nitrogen and total phosphorus, respectively). The average total nitrogen concentration was 0.28 milligram per liter, and the average total phosphorus concentration was 0.02 milligram per liter. Chlorophyll a was the predominant form of photosynthetic pigment in the water. The average chlorophyll-a concentration was 6.2 micrograms per liter. \r\n\r\nBottom sediment accumulation rates were determined in sediment cores by modeling the downcore activities of lead-210 and cesium-137. Results indicated a sediment depositional rate of about 0.44 centimeter per year. At this rate of sediment accretion, the lagoon may become a marshland in about 700 to 900 years.\r\n\r\nAbout 86 percent of the community primary productivity in Laguna Grande was generated by periphyton, primarily algal mats and seagrasses, and the remaining 14 percent was generated by phytoplankton in the water column. Based on the diel studies the total average net community productivity equaled 5.7 grams of oxygen per cubic meter per day (2.1 grams of carbon per cubic meter per day). Most of this productivity was ascribed to periphyton and macrophytes, which produced 4.9 grams of oxygen per cubic meter per day (1.8 grams of carbon per cubic meter per day). Phytoplankton, the plant and algal component of plankton, produced about 0.8 gram of oxygen per cubic meter per day (0.3 gram of carbon per cubic meter per day).\r\n\r\nThe total diel community respiration rate was 23.4 grams of oxygen per cubic meter per day. The respiration rate ascribed to plankton, which consists of all free floating and swimming organisms in the water column, composed 10 percent of this rate (2.9 grams of oxygen per cubic meter per day); respiration by all other organisms composed the remaining 90 percent (20.5 grams of oxygen per cubic meter per day). Plankton gross productivity was 3.7 grams of oxygen per cubic meter per day, equivalent to about 13 percent of the average gross productivity for the entire community (29.1 grams of oxygen per cubic meter per day). \r\n\r\nThe average phytoplankton biomass values in Laguna Grande ranged from 6.0 to 13.6 milligrams per liter. During the study, Laguna Grande contained a phytoplankton standing crop of approximately 5.8 metric tons. Phytoplankton community had a turnover (renewal) rate of about 153 times per year, or roughly about once every 2.5 days. \r\n\r\nFecal indicator bacteria concentrations ranged from 160 to 60,000 colonies per 100 milliliters. Concentrations generally were greatest in areas near residential and commercial establishments, and frequently exceeded current regulatory standards established for Puerto Rico. \r\n","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/sir20105071","collaboration":"Prepared in cooperation with the\r\nPuerto Rico Environmental Quality Board for the Conservation Trust of Puerto Rico","usgsCitation":"Soler-Lopez, L.R., and Santos, C.R., 2010, Selected Hydrologic, Water-Quality, Biological, and Sedimentation Characteristics of Laguna Grande, Fajardo, Puerto Rico, March 2007-February 2009: U.S. Geological Survey Scientific Investigations Report 2010-5071, ix, 51 p. , https://doi.org/10.3133/sir20105071.","productDescription":"ix, 51 p. ","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"2007-03-01","temporalEnd":"2009-02-28","costCenters":[{"id":156,"text":"Caribbean Water Science Center","active":true,"usgs":true}],"links":[{"id":118472,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2010_5071.jpg"},{"id":13670,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2010/5071/","linkFileType":{"id":5,"text":"html"}}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -65.9,18 ], [ -65.9,18.450833333333332 ], [ -65.55,18.450833333333332 ], [ -65.55,18 ], [ -65.9,18 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a09e4b07f02db5fa837","contributors":{"authors":[{"text":"Soler-Lopez, Luis R.","contributorId":27501,"corporation":false,"usgs":true,"family":"Soler-Lopez","given":"Luis","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":305245,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Santos, Carlos R. crsantos@usgs.gov","contributorId":3812,"corporation":false,"usgs":true,"family":"Santos","given":"Carlos","email":"crsantos@usgs.gov","middleInitial":"R.","affiliations":[],"preferred":true,"id":305244,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70221804,"text":"70221804 - 2010 - Integration of tectonic, sedimentary, and geohydrologic processes leading to a small-scale extension model for the Mormon Mountains area north of Lake Mead, Lincoln County, Nevada","interactions":[],"lastModifiedDate":"2021-07-07T19:31:52.481576","indexId":"70221804","displayToPublicDate":"2010-06-01T14:12:49","publicationYear":"2010","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Integration of tectonic, sedimentary, and geohydrologic processes leading to a small-scale extension model for the Mormon Mountains area north of Lake Mead, Lincoln County, Nevada","docAbstract":"Scattered remnants of highly diverse stratigraphic sections of Tertiary lacustrine limestone, andesite flows, and 23.8–18.2 Ma regional ash-flow tuffs on the north flank of the Mormon Mountains record previously unrecognized deformation, which we interpret as pre–17 Ma uplift and possibly weak extension on the north flank of a growing dome. Directly to the north of the Mormon dome, 17–14 Ma ash-flow tuffs and rhyolite are interstratified with landslides, debris avalanches, debris flows, and alluvial-fan deposits that accumulated to a thickness of more than 2 km in an extension-parallel basin. The source for the landslides and debris avalanche deposits is unknown, but it was probably an adjacent scarp along a transverse fault bounding an early part of the Mormon dome. An average 45° of easterly tilt of the entire Tertiary basin-fill succession represents the major post–14 Ma deformation event in the region. We question the basis for the published estimate of 22 km of westerly displacement on the Mormon Peak detachment fault and, on the basis of landslides in the upper plate having a probable source in the adjacent Mormon dome, constrain the heave to ~4 km. We interpret the dome and basin as coupled strains similar to others in the region and suggest that these strains reflect a waveform pattern of extension-normal lateral midcrustal ductile flow. Previously, doming was interpreted as an isostatic response to tectonic unloading by large-displacement detachment faults or as pseudo-structural highs stranded by removal of middle crust from adjacent areas. Moreover, we argue that the strong thinning of upper-plate rock successions throughout the Mormon Mountains and Tule Springs Hills resulted from a loss of rock volume by protracted fluid flow, dissolution, and collapse, seriously limiting the usefulness of upper-plate strain in evaluating extension magnitude. We present a geohydrologic model that couples uplift driven by ductile inflow with dissolution driven by fluid infiltration, possibly augmented by mantle-derived CO2-rich fluids. Karsting in the uplands led to carbonate sedimentation in adjacent lowlands. Whether or not our downward revision of extension in the Mormon Mountains is valid, extension at that latitude is isolated from extension in the Lake Mead area by a low-strain corridor between the two areas. Recognition of the isolated and potentially diminished strain impacts estimates of maximum finite elongation of the Basin and Range Province because one of three vector paths used in those estimates passes through the Mormon Mountains.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Miocene tectonics of the Lake Mead Region, central basin and range","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Geological Society of America","doi":"10.1130/2010.2463(18)","usgsCitation":"Anderson, R.E., Felger, T.J., Diehl, S.F., Page, W.R., and Workman, J.B., 2010, Integration of tectonic, sedimentary, and geohydrologic processes leading to a small-scale extension model for the Mormon Mountains area north of Lake Mead, Lincoln County, Nevada, chap. of Miocene tectonics of the Lake Mead Region, central basin and range, v. 463, p. 395-426, https://doi.org/10.1130/2010.2463(18).","productDescription":"32 p.","startPage":"395","endPage":"426","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":387000,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada","otherGeospatial":"Mormon Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.80163574218751,\n 36.71687068791304\n ],\n [\n -114.31549072265625,\n 36.71687068791304\n ],\n [\n -114.31549072265625,\n 37.29153547292737\n ],\n [\n -114.80163574218751,\n 37.29153547292737\n ],\n [\n -114.80163574218751,\n 36.71687068791304\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"463","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"editors":[{"text":"Umhoefer, Paul J.","contributorId":73483,"corporation":false,"usgs":true,"family":"Umhoefer","given":"Paul J.","affiliations":[],"preferred":false,"id":818786,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Beard, L. Sue 0000-0001-9552-1893 sbeard@usgs.gov","orcid":"https://orcid.org/0000-0001-9552-1893","contributorId":152,"corporation":false,"usgs":true,"family":"Beard","given":"L.","email":"sbeard@usgs.gov","middleInitial":"Sue","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":818787,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Lamb, Melissa","contributorId":260799,"corporation":false,"usgs":false,"family":"Lamb","given":"Melissa","email":"","affiliations":[],"preferred":false,"id":818788,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Anderson, R. Ernest","contributorId":104484,"corporation":false,"usgs":true,"family":"Anderson","given":"R.","email":"","middleInitial":"Ernest","affiliations":[],"preferred":false,"id":818781,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Felger, Tracey J. 0000-0003-0841-4235 tfelger@usgs.gov","orcid":"https://orcid.org/0000-0003-0841-4235","contributorId":1117,"corporation":false,"usgs":true,"family":"Felger","given":"Tracey","email":"tfelger@usgs.gov","middleInitial":"J.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":818782,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Diehl, Sharon F. diehl@usgs.gov","contributorId":1089,"corporation":false,"usgs":true,"family":"Diehl","given":"Sharon","email":"diehl@usgs.gov","middleInitial":"F.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":818783,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Page, William R. 0000-0002-0722-9911 rpage@usgs.gov","orcid":"https://orcid.org/0000-0002-0722-9911","contributorId":1628,"corporation":false,"usgs":true,"family":"Page","given":"William","email":"rpage@usgs.gov","middleInitial":"R.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":818784,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Workman, Jeremiah B. 0000-0001-7816-6420 jworkman@usgs.gov","orcid":"https://orcid.org/0000-0001-7816-6420","contributorId":714,"corporation":false,"usgs":true,"family":"Workman","given":"Jeremiah","email":"jworkman@usgs.gov","middleInitial":"B.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":818785,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70236355,"text":"70236355 - 2010 - The northwestern margin of the Basin and Range province: Part 2: Structural setting of a developing basin from seismic and potential field data","interactions":[],"lastModifiedDate":"2022-09-02T18:44:23.421585","indexId":"70236355","displayToPublicDate":"2010-06-01T13:35:08","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3525,"text":"Tectonophysics","active":true,"publicationSubtype":{"id":10}},"title":"The northwestern margin of the Basin and Range province: Part 2: Structural setting of a developing basin from seismic and potential field data","docAbstract":"Surprise Valley in northeastern California offers an ideal opportunity to examine the structural setting of a developing extensional basin due to its late Miocene to recent activity in isolation from other major normal fault-bound basins. Seismic velocity and potential field modeling help determine the nature of basin fill and identify intra-basin faults. Based on a detailed gravity and magnetic profile, we identify shallow subsurface basalt flows and several faults within the valley that may accommodate hundreds of meters of vertical offset, possibly cutting and offsetting the ~ 30° east-dipping Surprise Valley fault that rotated during footwall tilting of the adjacent Warner Mountains. Some of these intra-basin faults correspond with mapped Quaternary fault scarps, but others have no surface expression. These faults may represent the currently active fault system within the basin. If so, they would indicate that basin development is transitioning away from the main range-front normal fault to a new set of steep intra-basin faults that are more favorable for accommodating regional transtensional strain.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.tecto.2009.05.029","usgsCitation":"Egger, A.E., Glen, J.M., and Ponce, D.A., 2010, The northwestern margin of the Basin and Range province: Part 2: Structural setting of a developing basin from seismic and potential field data: Tectonophysics, v. 488, no. 1-4, p. 150-161, https://doi.org/10.1016/j.tecto.2009.05.029.","productDescription":"12 p.","startPage":"150","endPage":"161","costCenters":[],"links":[{"id":406167,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Surprise Valley, Warner Range","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.27557373046876,\n 41.9921602333763\n ],\n [\n -120.37994384765624,\n 41.80817277478235\n ],\n [\n -120.39642333984374,\n 41.47977575214487\n ],\n [\n -120.34973144531249,\n 41.43449030894922\n ],\n [\n -120.30853271484375,\n 41.42419375330273\n ],\n [\n -120.30303955078124,\n 41.265420628926684\n ],\n [\n -120.2838134765625,\n 41.20758898181025\n ],\n [\n -120.18218994140626,\n 41.017210578228436\n ],\n [\n -120.00091552734375,\n 41.01513821521511\n ],\n [\n -119.9981689453125,\n 41.99624282178583\n ],\n [\n -120.27557373046876,\n 41.9921602333763\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"488","issue":"1-4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Egger, Anne E.","contributorId":48669,"corporation":false,"usgs":true,"family":"Egger","given":"Anne","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":850738,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Glen, Jonathan M.G. 0000-0002-3502-3355 jglen@usgs.gov","orcid":"https://orcid.org/0000-0002-3502-3355","contributorId":176530,"corporation":false,"usgs":true,"family":"Glen","given":"Jonathan","email":"jglen@usgs.gov","middleInitial":"M.G.","affiliations":[{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":850739,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ponce, David A. 0000-0003-4785-7354 ponce@usgs.gov","orcid":"https://orcid.org/0000-0003-4785-7354","contributorId":1049,"corporation":false,"usgs":true,"family":"Ponce","given":"David","email":"ponce@usgs.gov","middleInitial":"A.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":850740,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70236352,"text":"70236352 - 2010 - Upper mantle rheology from GRACE and GPS postseismic deformation after the 2004 Sumatra-Andaman earthquake","interactions":[],"lastModifiedDate":"2022-09-02T17:43:28.635127","indexId":"70236352","displayToPublicDate":"2010-06-01T11:58:51","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1757,"text":"Geochemistry, Geophysics, Geosystems","active":true,"publicationSubtype":{"id":10}},"title":"Upper mantle rheology from GRACE and GPS postseismic deformation after the 2004 Sumatra-Andaman earthquake","docAbstract":"Mantle rheology is one of the essential, yet least understood, material properties of our planet, controlling the dynamic processes inside the Earth's mantle and the Earth's response to various forces. With the advent of GRACE satellite gravity, measurements of mass displacements associated with many processes are now available. In the case of mass displacements related to postseismic deformation, these data may provide new constraints on the mantle rheology. We consider the postseismic deformation due to the Mw = 9.2 Sumatra 26 December 2004 and Mw = 8.7 Nias 28 March 2005 earthquakes. Applying wavelet analyses to enhance those local signals in the GRACE time varying geoids up to September 2007, we detect a clear postseismic gravity signal. We supplement these gravity variations with GPS measurements of postseismic crustal displacements to constrain postseismic relaxation processes throughout the upper mantle. The observed GPS displacements and gravity variations are well explained by a model of viscoelastic relaxation plus a small amount of afterslip at the downdip extension of the coseismically ruptured fault planes. Our model uses a 60 km thick elastic layer above a viscoelastic asthenosphere with Burgers body rheology. The mantle below depth 220 km has a Maxwell rheology. Assuming a low transient viscosity in the 60–220 km depth range, the GRACE data are best explained by a constant steady state viscosity throughout the ductile portion of the upper mantle (e.g., 60–660 km). This suggests that the localization of relatively low viscosity in the asthenosphere is chiefly in the transient viscosity rather than the steady state viscosity. We find a 8.1018 Pa s mantle viscosity in the 220–660 km depth range. This may indicate a transient response of the upper mantle to the high amount of stress released by the earthquakes. To fit the remaining misfit to the GRACE data, larger at the smaller spatial scales, cumulative afterslip of about 75 cm at depth should be added over the period spanned by the GRACE models. It produces only small crustal displacements. Our results confirm that satellite gravity data are an essential complement to ground geodetic and geophysical networks in order to understand the seismic cycle and the Earth's inner structure.
New three-dimensional (3D) lithologic and stratigraphic models of the Santa Rosa Plain (California, USA) delineate the thickness, extent, and distribution of subsurface geologic units and allow integration of diverse data sets to produce a lithologic, stratigraphic, and structural architecture for the region. This framework can be used to predict pathways of groundwater flow beneath the Santa Rosa Plain and potential areas of enhanced or focused seismic shaking.
Lithologic descriptions from 2683 wells were simplified to 19 internally consistent lithologic classes. These distinctive lithologic classes were used to construct a 3D model of lithologic variations within the basin by extrapolating data away from drill holes using a nearest-neighbor approach. Subsurface stratigraphy was defined through the identification of distinctive lithologic packages tied, where possible, to high-quality well control and to surface exposures. The 3D stratigraphic model consists of three bounding components: fault surfaces, stratigraphic surfaces, and a surface representing the top of pre-Cenozoic basement, derived from inversion of regional gravity data.
The 3D lithologic model displays a west to east transition from dominantly marine sands to heterogeneous continental sediments. In contrast to previous stratigraphic studies, the new models emphasize the prevalence of the clay-rich Petaluma Formation and its heterogeneous nature. Isopach maps of the Glen Ellen Formation and the 3D stratigraphic model show the influence of the Trenton Ridge, a concealed basement ridge that bisects the plain, on sedimentation; the thickest deposits of the Glen Ellen Formation are confined to north of the Trenton Ridge.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES00513.1","usgsCitation":"Sweetkind, D.S., Taylor, E.M., McCabe, C.A., Langenheim, V., and McLaughlin, R.J., 2010, Three-dimensional geologic modeling of the Santa Rosa Plain, California : Geosphere, v. 6, no. 3, p. 237-274, https://doi.org/10.1130/GES00513.1.","productDescription":"38 p.","startPage":"237","endPage":"274","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":475718,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges00513.1","text":"Publisher Index Page"},{"id":374232,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Santa Rosa Plain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.97134399414061,\n 38.21444607848999\n ],\n [\n -122.4755859375,\n 38.21444607848999\n ],\n [\n -122.4755859375,\n 38.634036452919226\n ],\n [\n -122.97134399414061,\n 38.634036452919226\n ],\n [\n -122.97134399414061,\n 38.21444607848999\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"6","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Sweetkind, Donald S. 0000-0003-0892-4796 dsweetkind@usgs.gov","orcid":"https://orcid.org/0000-0003-0892-4796","contributorId":139913,"corporation":false,"usgs":true,"family":"Sweetkind","given":"Donald","email":"dsweetkind@usgs.gov","middleInitial":"S.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":787809,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Taylor, Emily M. 0000-0003-1152-5761 emtaylor@usgs.gov","orcid":"https://orcid.org/0000-0003-1152-5761","contributorId":127802,"corporation":false,"usgs":true,"family":"Taylor","given":"Emily","email":"emtaylor@usgs.gov","middleInitial":"M.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":787810,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McCabe, Craig A.","contributorId":69256,"corporation":false,"usgs":true,"family":"McCabe","given":"Craig","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":787811,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Langenheim, Victoria E. 0000-0003-2170-5213","orcid":"https://orcid.org/0000-0003-2170-5213","contributorId":206978,"corporation":false,"usgs":true,"family":"Langenheim","given":"Victoria E.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":787812,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McLaughlin, Robert J. 0000-0002-4390-2288 rjmcl@usgs.gov","orcid":"https://orcid.org/0000-0002-4390-2288","contributorId":1428,"corporation":false,"usgs":true,"family":"McLaughlin","given":"Robert","email":"rjmcl@usgs.gov","middleInitial":"J.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":787813,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70118931,"text":"70118931 - 2010 - A cost-benefit analysis of preventative management for zebra and quagga mussels in the Colorado-Big Thompson System","interactions":[],"lastModifiedDate":"2018-01-12T12:30:52","indexId":"70118931","displayToPublicDate":"2010-06-01T11:33:56","publicationYear":"2010","noYear":false,"publicationType":{"id":21,"text":"Thesis"},"publicationSubtype":{"id":28,"text":"Thesis"},"title":"A cost-benefit analysis of preventative management for zebra and quagga mussels in the Colorado-Big Thompson System","docAbstract":"Zebra and quagga mussels are fresh water invaders that have the potential to \ncause severe ecological and economic damage. It is estimated that mussels cause $1 \nbillion dollars per year in damages to water infrastructure and industries in the \nUnited States (Pimentel et al., 2004). Following their introduction to the Great \nLakes in the late 1980s, mussels spread rapidly throughout the Mississippi River \nBasin and the Eastern U.S. The mussel invasion in the West is young. Mussels were \nfirst identified in Nevada in 2007, and have since been identified in California, \nArizona, Colorado, Utah, and Texas.
\nWestern water systems are very different from those found in the East. The \nrapid spread of mussels through the eastern system was facilitated by connected \nand navigable waterways. Western water systems are less connected and are \ncharacterized by man-made reservoirs and canals. The main vector of spread for \nmussels in the West is overland on recreational boats (Bossenbroek et al., 2001). In \nresponse to the invasion, many western water managers have implemented \npreventative management programs to slow the overland spread of mussels on \nrecreational boats. In Colorado, the Colorado Department of Wildlife (CDOW) has \nimplemented a mandatory boat inspection program that requires all trailered boats \nto be inspected before launching in any Colorado water body. The objective of this \nstudy is to analyze the costs and benefits of the CDOW boat inspection program in Colorado, and to identify variables that affect the net benefits of preventative \nmanagement.
\nPredicting the potential economic benefits of slowing the spread of mussels \nrequires integrating information about mussel dispersal potential with estimates of \ncontrol costs (Keller et al., 2009). Uncertainty surrounding the probabilities of \nestablishment, the timing of invasions, and the damage costs associated with an \ninvasion make a simulation model an excellent tool for addressing \"what if\" \nscenarios and shedding light on the net benefits of preventative management \nstrategies. This study builds a bioeconomic simulation model to predict and compare the expected economic costs of the CDOW boat inspection program ot the benefits of reduced expected control costs to water conveyance systems, hydropower generation stations, and minicipal water treatment facilities. The model is based on a case study water delivery and storage system, the Colorado-Big Thompson system. The Colorado-Big Thomspon system is an excellent example of water systems in the Rocky Mountain West. The system is nearly entirely man-made, with all of its reservoirs and delivery points connected via pipelines, tunnels, and canals. The structures and hydropower systems of the Colorado-Big Thompson system are common to other western storage and delivery systems, making the methods and insight developed from this case study transferal to other western systems.
\nThe model developed in this study contributes to the bioeconomic literature in several ways. Foremost, the model predicts the spread of dreissena mussels and associated damage costs for a connected water system in the Rocky Mountain West. Very few zebra mussel studies have focused on western water systems. Another distinguishing factor is the simultaneous consideration of spread from propagules introduced by boats and by flows. Most zebra mussel dispersal models consider boater movement patterns combined with limnological characteristics as predictors of spread. A separate set of studies have addressed mussel spread via downstream flows. To the author's knowledge, this is the first study that builds a zebra mussel spread model that specifically accounts for propagule pressure from boat introductions and from downstream flow introductions. By modeling an entire connected system, the study highlights how the spatial layout of a system, and the risk of invasion within a system affect the benefits of preventative management.
\nThis report is presented in five chapters. The first chapter provides background information including a history of the zebra mussel invasion in the U.S. and in the West, and details about the Colorado preventative management program and the Colorado-Big Thompson system. The chapter also includes a literature review of mussel dispersal models and economic studies that address control costs and preventative management for aquatic invasive species. Chapter 2 presents the methodological approach used to analyze the costs and benefits of preventative management in the Colorado-Big Thompson system and provides details of the bioeconomic simulation model used to predict invasion patterns and the net benefits of preventative management. Results of the analysis and sensitivity testing of model parameters are presented in Chapter 3. Chapter 4 provides a summary of the analysis and conclusions. A discussion of the limitations of the model and areas for future research is presented in Chapter 5.
","language":"English","publisher":"Colorado State University","publisherLocation":"Fort Collins, CO","usgsCitation":"Thomas, C.M., 2010, A cost-benefit analysis of preventative management for zebra and quagga mussels in the Colorado-Big Thompson System, xi, 185 p.","productDescription":"xi, 185 p.","numberOfPages":"194","costCenters":[],"links":[{"id":291487,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg","text":"https://pubs.er.usgs.gov/manager/#bibliodata-pane"},{"id":350426,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://dspace.library.colostate.edu/handle/10217/39343"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53db583fe4b0fba533fa355f","contributors":{"authors":[{"text":"Thomas, Catherine M. 0000-0001-8168-1271","orcid":"https://orcid.org/0000-0001-8168-1271","contributorId":29331,"corporation":false,"usgs":true,"family":"Thomas","given":"Catherine","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":497522,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70148185,"text":"70148185 - 2010 - Interactive effects of senescence and natural disturbance on the annual survival probabilities of snail kites","interactions":[],"lastModifiedDate":"2015-05-26T10:23:44","indexId":"70148185","displayToPublicDate":"2010-06-01T11:30:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2939,"text":"Oikos","active":true,"publicationSubtype":{"id":10}},"title":"Interactive effects of senescence and natural disturbance on the annual survival probabilities of snail kites","docAbstract":"Individuals in wild populations face risks associated with both intrinsic (i.e. aging) and external (i.e. environmental) sources of mortality. Condition-dependent mortality occurs when there is an interaction between such factors; however, few studies have clearly demonstrated condition-dependent mortality and some have even argued that condition-dependent mortality does not occur in wild avian populations. Using large sample sizes (2084 individuals, 3746 re-sights) of individual-based longitudinal data collected over a 33 year period (1976-2008) on multiple cohorts, we used a capture-mark-recapture framework to model age-dependent survival in the snail kite Rostrhamus sociabilis plumbeus population in Florida. Adding to the growing amount of evidence for actuarial senescence in wild populations, we found evidence of senescent declines in survival probabilities in adult kites. We also tested the hypothesis that older kites experienced condition-dependent mortality during a range-wide drought event (2000-2002). The results provide convincing evidence that the annual survival probability of senescent kites was disproportionately affected by the drought relative to the survival probability of prime-aged adults. To our knowledge, this is the first evidence of condition-dependent mortality to be demonstrated in a wild avian population, a finding which challenges recent conclusions drawn in the literature. Our study suggests that senescence and condition-dependent mortality can affect the demography of wild avian populations. Accounting for these sources of variation may be particularly important to appropriately compute estimates of population growth rate, and probabilities of quasi-extinctions.
","language":"English","publisher":"Scandinavian Society Oikos","publisherLocation":"Copenhagen","doi":"10.1111/j.1600-0706.2010.18366.x","collaboration":"US Army Corps of Engineers; US Fish and Wildlife Service; St Johns River Water Management District; USGS","usgsCitation":"Reichert, B.E., Martin, J., Kendall, W.L., Cattau, C.E., and Kitchens, W.M., 2010, Interactive effects of senescence and natural disturbance on the annual survival probabilities of snail kites: Oikos, v. 119, no. 6, p. 972-979, https://doi.org/10.1111/j.1600-0706.2010.18366.x.","productDescription":"8 p.","startPage":"972","endPage":"979","numberOfPages":"8","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-015221","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":300775,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"119","issue":"6","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2010-03-19","publicationStatus":"PW","scienceBaseUri":"5565994be4b0d9246a9eb62d","contributors":{"authors":[{"text":"Reichert, Brian E. 0000-0002-9640-0695","orcid":"https://orcid.org/0000-0002-9640-0695","contributorId":22166,"corporation":false,"usgs":true,"family":"Reichert","given":"Brian","email":"","middleInitial":"E.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":547592,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Martin, J.","contributorId":18871,"corporation":false,"usgs":true,"family":"Martin","given":"J.","affiliations":[],"preferred":false,"id":547593,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kendall, William L. wkendall@usgs.gov","contributorId":406,"corporation":false,"usgs":true,"family":"Kendall","given":"William","email":"wkendall@usgs.gov","middleInitial":"L.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":547594,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cattau, Christopher E.","contributorId":54406,"corporation":false,"usgs":true,"family":"Cattau","given":"Christopher","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":547595,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kitchens, Wiley M. kitchensw@usgs.gov","contributorId":2851,"corporation":false,"usgs":true,"family":"Kitchens","given":"Wiley","email":"kitchensw@usgs.gov","middleInitial":"M.","affiliations":[],"preferred":true,"id":547544,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70176786,"text":"70176786 - 2010 - When parasites become prey: ecological and epidemiological significance of eating parasites","interactions":[],"lastModifiedDate":"2017-04-27T10:33:03","indexId":"70176786","displayToPublicDate":"2010-06-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3653,"text":"Trends in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"When parasites become prey: ecological and epidemiological significance of eating parasites","docAbstract":"Recent efforts to include parasites in food webs have drawn attention to a previously ignored facet of foraging ecology: parasites commonly function as prey within ecosystems. Because of the high productivity of parasites, their unique nutritional composition and their pathogenicity in hosts, their consumption affects both food-web topology and disease risk in humans and wildlife. Here, we evaluate the ecological, evolutionary and epidemiological significance of feeding on parasites, including concomitant predation, grooming, predation on free-living stages and intraguild predation. Combining empirical data and theoretical models, we show that consumption of parasites is neither rare nor accidental, and that it can sharply affect parasite transmission and food web properties. Broader consideration of predation on parasites will enhance our understanding of disease control, food web structure and energy transfer, and the evolution of complex life cycles.
","language":"English","publisher":"Cell Press","doi":"10.1016/j.tree.2010.01.005","usgsCitation":"Johnson, P.T., Dobson, A.P., Lafferty, K.D., Marcogliese, D.J., Memmott, J., Orlofske, S.A., Poulin, R., and Thieltges, D.W., 2010, When parasites become prey: ecological and epidemiological significance of eating parasites: Trends in Ecology and Evolution, v. 25, no. 6, p. 362-371, https://doi.org/10.1016/j.tree.2010.01.005.","productDescription":"10 p.","startPage":"362","endPage":"371","ipdsId":"IP-016988","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":329348,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"25","issue":"6","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57fe8150e4b0824b2d1480ac","contributors":{"authors":[{"text":"Johnson, Pieter T.J.","contributorId":28508,"corporation":false,"usgs":true,"family":"Johnson","given":"Pieter","email":"","middleInitial":"T.J.","affiliations":[],"preferred":false,"id":650300,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dobson, Andrew P.","contributorId":63693,"corporation":false,"usgs":true,"family":"Dobson","given":"Andrew","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":650301,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lafferty, Kevin D. 0000-0001-7583-4593 klafferty@usgs.gov","orcid":"https://orcid.org/0000-0001-7583-4593","contributorId":1415,"corporation":false,"usgs":true,"family":"Lafferty","given":"Kevin","email":"klafferty@usgs.gov","middleInitial":"D.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":650302,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Marcogliese, David J.","contributorId":175161,"corporation":false,"usgs":false,"family":"Marcogliese","given":"David","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":650303,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Memmott, Jane","contributorId":175162,"corporation":false,"usgs":false,"family":"Memmott","given":"Jane","email":"","affiliations":[],"preferred":false,"id":650304,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Orlofske, Sarah A.","contributorId":175163,"corporation":false,"usgs":false,"family":"Orlofske","given":"Sarah","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":650305,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Poulin, Robert","contributorId":106813,"corporation":false,"usgs":true,"family":"Poulin","given":"Robert","email":"","affiliations":[],"preferred":false,"id":650306,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Thieltges, David W.","contributorId":56163,"corporation":false,"usgs":true,"family":"Thieltges","given":"David","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":650307,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70192601,"text":"70192601 - 2010 - Locations and magnitudes of historical earthquakes in the Sierra of Ecuador (1587–1996)","interactions":[],"lastModifiedDate":"2017-10-31T14:01:26","indexId":"70192601","displayToPublicDate":"2010-06-01T00:00:00","publicationYear":"2010","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":"Locations and magnitudes of historical earthquakes in the Sierra of Ecuador (1587–1996)","docAbstract":"The whole territory of Ecuador is exposed to seismic hazard. Great earthquakes can occur in the subduction zone (e.g. Esmeraldas, 1906, Mw8.8), whereas lower magnitude but shallower and potentially more destructive earthquakes can occur in the highlands. This study focuses on the historical crustal earthquakes of the Andean Cordillera. Several large cities are located in the Interandean Valley, among them Quito, the capital (∼2.5 millions inhabitants). A total population of ∼6 millions inhabitants currently live in the highlands, raising the seismic risk. At present, precise instrumental data for the Ecuadorian territory is not available for periods earlier than 1990 (beginning date of the revised instrumental Ecuadorian seismic catalogue); therefore historical data are of utmost importance for assessing seismic hazard. In this study, the Bakun & Wentworth method is applied in order to determine magnitudes, locations, and associated uncertainties for historical earthquakes of the Sierra over the period 1587–1976. An intensity-magnitude equation is derived from the four most reliable instrumental earthquakes (Mwbetween 5.3 and 7.1). Intensity data available per historical earthquake vary between 10 (Quito, 1587, Intensity ≥VI) and 117 (Riobamba, 1797, Intensity ≥III). The bootstrap resampling technique is coupled to the B&W method for deriving geographical confidence contours for the intensity centre depending on the data set of each earthquake, as well as confidence intervals for the magnitude. The extension of the area delineating the intensity centre location at the 67 per cent confidence level (±1σ) depends on the amount of intensity data, on their internal coherence, on the number of intensity degrees available, and on their spatial distribution. Special attention is dedicated to the few earthquakes described by intensities reaching IX, X and XI degrees. Twenty-five events are studied, and nineteen new epicentral locations are obtained, yielding equivalent moment magnitudes between 5.0 and 7.6. Large earthquakes seem to be related to strike slip faults between the North Andean Block and stable South America to the east, while moderate earthquakes (Mw≤ 6) seem to be associated with to thrust faults located on the western internal slopes of the Interandean Valley.
","language":"English","publisher":"Oxford Academic","doi":"10.1111/j.1365-246X.2010.04569.x","usgsCitation":"Beauval, C., Yepes, H., Bakun, W.H., Egred, J., Alvarado, A., and Singaucho, J., 2010, Locations and magnitudes of historical earthquakes in the Sierra of Ecuador (1587–1996): Geophysical Journal International, v. 181, no. 3, p. 1613-1633, https://doi.org/10.1111/j.1365-246X.2010.04569.x.","productDescription":"21 p.","startPage":"1613","endPage":"1633","ipdsId":"IP-016703","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":475719,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/j.1365-246x.2010.04569.x","text":"Publisher Index Page"},{"id":347879,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Ecuador","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -79.65087890624999,\n -2.7345569512697794\n ],\n [\n -77.135009765625,\n -2.7345569512697794\n ],\n [\n -77.135009765625,\n 1.2962761196418218\n ],\n [\n -79.65087890624999,\n 1.2962761196418218\n ],\n [\n -79.65087890624999,\n -2.7345569512697794\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"181","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59f98bc3e4b0531197afa096","contributors":{"authors":[{"text":"Beauval, Celine","contributorId":198594,"corporation":false,"usgs":false,"family":"Beauval","given":"Celine","email":"","affiliations":[],"preferred":false,"id":718627,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yepes, Hugo","contributorId":54463,"corporation":false,"usgs":true,"family":"Yepes","given":"Hugo","affiliations":[],"preferred":false,"id":718628,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bakun, William H.","contributorId":39361,"corporation":false,"usgs":true,"family":"Bakun","given":"William","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":718629,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Egred, Jose","contributorId":198596,"corporation":false,"usgs":false,"family":"Egred","given":"Jose","email":"","affiliations":[],"preferred":false,"id":718630,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Alvarado, Alexandra","contributorId":21416,"corporation":false,"usgs":true,"family":"Alvarado","given":"Alexandra","email":"","affiliations":[],"preferred":false,"id":718631,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Singaucho, Juan-Carlos","contributorId":198597,"corporation":false,"usgs":false,"family":"Singaucho","given":"Juan-Carlos","email":"","affiliations":[],"preferred":false,"id":718632,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70188016,"text":"70188016 - 2010 - Soil quality assessment using weighted fuzzy association rules","interactions":[],"lastModifiedDate":"2017-05-26T13:38:04","indexId":"70188016","displayToPublicDate":"2010-06-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3025,"text":"Pedosphere","active":true,"publicationSubtype":{"id":10}},"title":"Soil quality assessment using weighted fuzzy association rules","docAbstract":"Fuzzy association rules (FARs) can be powerful in assessing regional soil quality, a critical step prior to land planning and utilization; however, traditional FARs mined from soil quality database, ignoring the importance variability of the rules, can be redundant and far from optimal. In this study, we developed a method applying different weights to traditional FARs to improve accuracy of soil quality assessment. After the FARs for soil quality assessment were mined, redundant rules were eliminated according to whether the rules were significant or not in reducing the complexity of the soil quality assessment models and in improving the comprehensibility of FARs. The global weights, each representing the importance of a FAR in soil quality assessment, were then introduced and refined using a gradient descent optimization method. This method was applied to the assessment of soil resources conditions in Guangdong Province, China. The new approach had an accuracy of 87%, when 15 rules were mined, as compared with 76% from the traditional approach. The accuracy increased to 96% when 32 rules were mined, in contrast to 88% from the traditional approach. These results demonstrated an improved comprehensibility of FARs and a high accuracy of the proposed method.
","language":"English","publisher":"Elsevier","doi":"10.1016/S1002-0160(10)60022-7","usgsCitation":"Xue, Y., Liu, S., Hu, Y., and Yang, J., 2010, Soil quality assessment using weighted fuzzy association rules: Pedosphere, v. 20, no. 3, p. 334-341, https://doi.org/10.1016/S1002-0160(10)60022-7.","productDescription":"8 p.","startPage":"334","endPage":"341","ipdsId":"IP-010167","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":341805,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"20","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59293e9ae4b016f7a9407718","contributors":{"authors":[{"text":"Xue, Yue-Ju","contributorId":44346,"corporation":false,"usgs":true,"family":"Xue","given":"Yue-Ju","email":"","affiliations":[],"preferred":false,"id":696187,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Liu, Shu-Guang sliu@usgs.gov","contributorId":984,"corporation":false,"usgs":true,"family":"Liu","given":"Shu-Guang","email":"sliu@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":696188,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hu, Yue-Ming","contributorId":192310,"corporation":false,"usgs":false,"family":"Hu","given":"Yue-Ming","affiliations":[],"preferred":false,"id":696189,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Yang, Jing","contributorId":192311,"corporation":false,"usgs":false,"family":"Yang","given":"Jing","affiliations":[],"preferred":false,"id":696190,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70210253,"text":"70210253 - 2010 - Comparative analysis of Mourning Dove population change in North America","interactions":[],"lastModifiedDate":"2020-05-27T12:11:47.772599","indexId":"70210253","displayToPublicDate":"2010-05-26T14:00:55","publicationYear":"2010","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":"Comparative analysis of Mourning Dove population change in North America","docAbstract":"Mourning doves (Zenaida macroura) are surveyed in North America with a Call-Count Survey (CCS) and the North American Breeding Bird Survey (BBS). Analyses in recent years have identified inconsistencies in results between surveys, and a need exists to analyze the surveys using modern methods and examine possible causes of differences in survey results. Call-Count Survey observers collect separate information on number of doves heard and number of doves seen during counting, whereas BBS observers record one index containing all doves observed. We used hierarchical log-linear models to estimate trend and annual indices of abundance for 1966–2007 from BBS data, CCS-heard data, and CCS-seen data. Trend estimates from analyses provided inconsistent results for several states and for eastern and central dovemanagement units. We examined differential effects of change in land use and noise-related disturbance on the CCS indices. Changes in noiserelated disturbance along CCS routes had a larger influence on the heard index than on the seen index, but association analyses among states of changes in temperature and of amounts of developed land suggest that CCS indices are differentially influenced by changes in these environmental features. Our hierarchical model should be used to estimate population change from dove surveys, because it provides an efficient framework for estimating population trends from dove indices while controlling for environmental features that differentially influence the indices.
","language":"English","publisher":"BioOne","doi":"10.2193/2008-459","usgsCitation":"Sauer, J.R., Link, W.A., Kendall, W.L., and Dolton, D., 2010, Comparative analysis of Mourning Dove population change in North America: Journal of Wildlife Management, v. 74, no. 5, p. 1059-1069, https://doi.org/10.2193/2008-459.","productDescription":"11 p.","startPage":"1059","endPage":"1069","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":375039,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"74","issue":"5","noUsgsAuthors":false,"publicationDate":"2010-12-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Sauer, John R. 0000-0002-4557-3019 jrsauer@usgs.gov","orcid":"https://orcid.org/0000-0002-4557-3019","contributorId":146917,"corporation":false,"usgs":true,"family":"Sauer","given":"John","email":"jrsauer@usgs.gov","middleInitial":"R.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":789767,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Link, William A. 0000-0002-9913-0256 wlink@usgs.gov","orcid":"https://orcid.org/0000-0002-9913-0256","contributorId":146920,"corporation":false,"usgs":true,"family":"Link","given":"William","email":"wlink@usgs.gov","middleInitial":"A.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":789768,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kendall, William L. 0000-0003-0084-9891","orcid":"https://orcid.org/0000-0003-0084-9891","contributorId":204844,"corporation":false,"usgs":true,"family":"Kendall","given":"William","email":"","middleInitial":"L.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":789769,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dolton, David D.","contributorId":100452,"corporation":false,"usgs":true,"family":"Dolton","given":"David D.","affiliations":[],"preferred":false,"id":789770,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":98414,"text":"ofr20081099 - 2010 - Gulf of Mexico dead zone - 1000 year record","interactions":[],"lastModifiedDate":"2014-04-10T15:11:02","indexId":"ofr20081099","displayToPublicDate":"2010-05-26T07:00:00","publicationYear":"2010","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":"2008-1099","title":"Gulf of Mexico dead zone - 1000 year record","docAbstract":"An area of oxygen-depleted bottom- and subsurfacewater (hypoxia = dissolved oxygen < 2 mg per Liter) occurs seasonally on the Louisiana shelf near the Mississippi River. The area of hypoxia, also known as the 'dead zone,' forms when spring and early summer freshwater flow from the Mississippi River supplies a large amount of nutrients to the shelf while creating a freshwater lens, or cap, above the shelf water. The excess nutrients cause phytoplankton blooms in the shallow shelf water. After the bloom ceases, the organic material sinks in the water column and uses up oxygen during decomposition. Thus, the subsurface waters become oxygen depleted. The seasonal dead zone exists until a reduction in freshwater flow, or overturning by storms, allows mixing of the water column to restore normal oxygen conditions.
\nSince systematic measurement of the extent of the dead zone was begun in 1985, the overall pattern indicates that the area of the dead zone is increasing. Several studies have concluded that the expansion of the Louisiana shelf dead zone is related to increased nutrients (primarily nitrogen, but possibly also phosphorous) in the Mississippi River drainage basin and is responsible for the degradation of Gulf of Mexico marine habitats. The goal of this research is to augment information on the recent expansion of Louisiana shelf hypoxia and to investigate the temporal and geographic extent of the lowoxygen bottom-water conditions prior to 1985 in sediment cores collected from the Louisiana shelf.
\nWe use a specific low-oxygen faunal proxy termed the PEB index based on the cumulative percentage of three foraminifers (= % Protononion atlanticum, + % Epistominella vitrea, + % Buliminella morgani) that has been shown statistically to represent the modern seasonal Louisiana hypoxia zone. Our hypothesis is that the increased relative abundance of PEB species in dated sediment cores accurately tracks past seasonal low-oxygen conditions on the Louisiana shelf.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20081099","usgsCitation":"Osterman, L., Poore, R., and Swarzenski, P., 2010, Gulf of Mexico dead zone - 1000 year record: U.S. Geological Survey Open-File Report 2008-1099, 2 p., https://doi.org/10.3133/ofr20081099.","productDescription":"2 p.","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"links":[{"id":118466,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2008_1099.jpg"},{"id":13666,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2008/1099/","linkFileType":{"id":5,"text":"html"}}],"country":"Mexico","otherGeospatial":"Gulf Of Mexico","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -93.5,28.5 ], [ -93.5,29.5 ], [ -89.5,29.5 ], [ -89.5,28.5 ], [ -93.5,28.5 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a81e4b07f02db64a242","contributors":{"authors":[{"text":"Osterman, L.E.","contributorId":53836,"corporation":false,"usgs":true,"family":"Osterman","given":"L.E.","email":"","affiliations":[],"preferred":false,"id":305239,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Poore, R.Z.","contributorId":35314,"corporation":false,"usgs":true,"family":"Poore","given":"R.Z.","email":"","affiliations":[],"preferred":false,"id":305238,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Swarzenski, P.W. 0000-0003-0116-0578","orcid":"https://orcid.org/0000-0003-0116-0578","contributorId":29487,"corporation":false,"usgs":true,"family":"Swarzenski","given":"P.W.","affiliations":[],"preferred":false,"id":305237,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":98411,"text":"sir20105054 - 2010 - Changes in groundwater flow and volatile organic compound concentrations at the Fischer and Porter Superfund Site, Warminster Township, Bucks County, Pennsylvania, 1993-2009","interactions":[],"lastModifiedDate":"2024-06-13T21:56:59.253815","indexId":"sir20105054","displayToPublicDate":"2010-05-26T00:00:00","publicationYear":"2010","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":"2010-5054","title":"Changes in groundwater flow and volatile organic compound concentrations at the Fischer and Porter Superfund Site, Warminster Township, Bucks County, Pennsylvania, 1993-2009","docAbstract":"The 38-acre Fischer and Porter Company Superfund Site is in Warminster Township, Bucks County, Pa. Historically, as part of the manufacturing process, trichloroethylene (TCE) degreasers were used for parts cleaning. In 1979, the Bucks County Health Department detected TCE and other volatile organic compounds (VOCs) in water from the Fischer and Porter on-site supply wells and nearby public-supply wells. The Fischer and Porter Site was designated as a Superfund Site and placed on the National Priorities List in September 1983. A 1984 Record of Decision for the site required the Fischer and Porter Company to pump and treat groundwater contaminated by VOCs from three on-site wells at a combined rate of 75 gallons per minute to contain groundwater contamination on the property. Additionally, the Record of Decision recognized the need for treatment of the water from two nearby privately owned supply wells operated by the Warminster Heights Home Ownership Association. In 2004, the Warminster Heights Home Ownership Association sold its water distribution system, and both wells were taken out of service. The report describes changes in groundwater levels and contaminant concentrations and migration caused by the shutdown of the Warminster Heights supply wells and presents a delineation of the off-site groundwater-contamination plume. The U.S. Geological Survey (USGS) conducted this study (2006-09) in cooperation with the U.S. Environmental Protection Agency (USEPA).
The Fischer and Porter Site and surrounding area are underlain by sedimentary rocks of the Stockton Formation of Late Triassic age. The rocks are chiefly interbedded arkosic sandstone and siltstone. The Stockton aquifer system is comprised of a series of gently dipping lithologic units with different hydraulic properties. A three-dimensional lithostratigraphic model was developed for the site on the basis of rock cores and borehole geophysical logs. The model was simplified by combining individual lithologic units into generalized units representing upward fining sedimentary cycles capped by a siltstone bed. These cycles were labeled units 1 through 8 and are called stratigraphic units in this report. Groundwater in the unweathered zone mainly moves through a network of interconnecting secondary openings--bedding-plane fractures and joints. Groundwater generally is unconfined in the shallower part of the aquifer and confined or semiconfined in the deeper part of the aquifer.
The migration of VOCs from the Fischer and Porter Site source area is influenced by geologic and hydrologic controls. The hydrologic controls have changed with time. Stratigraphic units 2 and 3 crop out beneath the former Fischer and Porter plant. VOCs originating at the plant source area entered these stratigraphic units and moved downdip to the northwest. When the wells at and in the vicinity of the site were initially sampled in 1979-80, three public-supply wells (BK-366, BK-367, MG-946) and three industrial-supply wells (BK-368, BK-370, and BK-371) were pumping. Groundwater contaminated with VOCs flowed downdip and then northeast along strike toward well BK-366, downdip toward well BK-368, and downdip and then west along strike toward well MG-946. The long axis of the TCE plume is oriented about N. 18° W. in the direction of dip. In 1979-80, the leading edge of the plume was about 3,500 feet wide. With the cessation of pumping of the supply wells in 2004, the size of the plume has decreased. In 2007-09, the plume was approximately 2,000 feet long and 2,000 feet wide at the leading edge.
On the western side of the site, TCE and tetrachloroethylene (PCE) appear to be moving downdip though stratigraphic unit 3. The downdip extent of TCE and PCE migration extended approximately 550 feet off-site to the northwest and 750 feet off-site to the north. TCE concentrations in water samples from wells at the western site boundary increased from 1996 to 2007. On the northern side of the site, TCE and PCE appeared to be moving downward and laterally though stratigraphic units 2, 3, and 4.
Groundwater-flow directions shifted to the northwest in the intermediate and deep zones after cessation of pumping of well BK-366 in 2004. The shutdown of the Warminster Heights wells had little effect on the direction of groundwater flow in the shallow zone.
In 2007, TCE concentrations measured in water samples from the three remediation wells by the USGS ranged from less than 340 to 3,000 µg/L, and PCE concentrations ranged from less than 8.4 to 51 µg/L. TCE concentrations in water samples from the source-area remediation wells have decreased with time but remain highly variable. From 2001 to 2008, the TCE and PCE concentrations in water samples from wells BK-370 and BK-371 showed a linear decreasing trend. TCE and PCE concentrations in water samples from well BK-1324 showed an exponentially decreasing trend.
In 2007, TCE concentrations measured in water samples from shallow wells ranged from less than 0.1 to 14,000 µg/L, and PCE concentrations ranged from less than 0.1 to 340 µg/L. The TCE and PCE plumes followed the hydraulic gradient in the shallow zone. In 2007, TCE concentrations measured in water samples from on-site intermediate-depth monitor wells ranged from less than 0.1 to 500 µg/L, and PCE concentrations ranged from 1.3 to 28 µg/L. The TCE and PCE plumes followed the hydraulic gradient in the intermediate zone and extended off-site to the north and northwest of the source area. Concentrations of TCE in water samples north and west of the source area increased from 1996 to 2007.
In 2007, the TCE concentrations measured in water samples from on-site monitor wells in the deep zone ranged from 1.1 to 86 µg/L, and PCE concentrations ranged from less than 0.1 to 8.4 µg/L. The TCE and PCE plumes generally followed the hydraulic gradient in the deep zone and extended off-site to the northwest of the source area. In general, concentrations of TCE in water samples from monitor wells outside the source area increased between 1996 and 2005 and decreased between 2005 and 2007; concentrations were less in 2007 than in 1996.
","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/sir20105054","collaboration":"In cooperation with the U.S. Environmental Protection Agency","usgsCitation":"Sloto, R.A., 2010, Changes in groundwater flow and volatile organic compound concentrations at the Fischer and Porter Superfund Site, Warminster Township, Bucks County, Pennsylvania, 1993-2009: U.S. Geological Survey Scientific Investigations Report 2010-5054, viii, 115 p., https://doi.org/10.3133/sir20105054.","productDescription":"viii, 115 p.","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":430169,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_93247.htm","linkFileType":{"id":5,"text":"html"}},{"id":118461,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2010_5054.jpg"},{"id":13661,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2010/5054/","linkFileType":{"id":5,"text":"html"}}],"projection":"Albers Equal-Area Conic","country":"United States","state":"Pennsylvania","county":"Bucks County","otherGeospatial":"Fischer and Porter Superfund Site","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.1,\n 40.1894\n ],\n [\n -75.1,\n 40.1817\n ],\n [\n -75.0869,\n 40.1817\n ],\n [\n -75.0869,\n 40.1894\n ],\n [\n -75.1,\n 40.1894\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e49e5e4b07f02db5e6d90","contributors":{"authors":[{"text":"Sloto, Ronald A. rasloto@usgs.gov","contributorId":424,"corporation":false,"usgs":true,"family":"Sloto","given":"Ronald","email":"rasloto@usgs.gov","middleInitial":"A.","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":305229,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70209741,"text":"70209741 - 2010 - Flood hazard awareness and hydrologic modelling at Ambos Nogales, United States–Mexico border","interactions":[],"lastModifiedDate":"2020-04-23T15:46:51.335573","indexId":"70209741","displayToPublicDate":"2010-05-18T10:40:25","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2289,"text":"Journal of Flood Risk Management","active":true,"publicationSubtype":{"id":10}},"title":"Flood hazard awareness and hydrologic modelling at Ambos Nogales, United States–Mexico border","docAbstract":"Appropriate land‐use, watershed‐management, and flood‐attenuation plans are critical in the cross‐border urban environment known collectively as Ambos Nogales. This paper summarizes methodologies for predicting the watershed response associated with land‐use change within a spatial and temporal context through the use of a hydrological model in a cross‐border setting. The KINEROS2 model is implemented via the Automated Geospatial Watershed Assessment 2.0 geographic information system interface to evaluate the watershed of Nogales, Arizona, and Nogales, Sonora, Mexico, to assess flood vulnerability by quantifying volumes of runoff and peak flow, based on alternative land‐use scenarios. Cross‐border geospatial data acquisition and input to models are described. Discussions about the KINEROS2 model results identify flood‐prone areas, simulate the impact of land‐use change, and evaluate the impact of potential flood‐control interventions in the Ambos Nogales watershed. Products from this research are being used in a comprehensive plan for sustainable development in Ambos Nogales.
","language":"English","publisher":"Wiley","doi":"10.1111/j.1753-318X.2010.01066.x","usgsCitation":"Norman, L.M., Huth, H., Levick, L., Burns, I.S., Guertin, D.P., Lara-Valencia, F., and Semmens, D.J., 2010, Flood hazard awareness and hydrologic modelling at Ambos Nogales, United States–Mexico border: Journal of Flood Risk Management, v. 3, no. 2, p. 151-165, https://doi.org/10.1111/j.1753-318X.2010.01066.x.","productDescription":"15 p.","startPage":"151","endPage":"165","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":374225,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico, United States","city":"Ambos Nogales watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.14593505859375,\n 31.09998179374943\n ],\n [\n -110.48675537109375,\n 31.09998179374943\n ],\n [\n -110.48675537109375,\n 31.468496379205966\n ],\n [\n -111.14593505859375,\n 31.468496379205966\n ],\n [\n -111.14593505859375,\n 31.09998179374943\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"3","issue":"2","noUsgsAuthors":false,"publicationDate":"2010-05-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Norman, Laura M. 0000-0002-3696-8406 lnorman@usgs.gov","orcid":"https://orcid.org/0000-0002-3696-8406","contributorId":967,"corporation":false,"usgs":true,"family":"Norman","given":"Laura","email":"lnorman@usgs.gov","middleInitial":"M.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":787774,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Huth, H.","contributorId":224328,"corporation":false,"usgs":false,"family":"Huth","given":"H.","email":"","affiliations":[],"preferred":false,"id":787775,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Levick, L.","contributorId":224329,"corporation":false,"usgs":false,"family":"Levick","given":"L.","email":"","affiliations":[],"preferred":false,"id":787776,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Burns, I. Shea","contributorId":224330,"corporation":false,"usgs":false,"family":"Burns","given":"I.","email":"","middleInitial":"Shea","affiliations":[],"preferred":false,"id":787777,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Guertin, D. Phillip","contributorId":46062,"corporation":false,"usgs":false,"family":"Guertin","given":"D.","email":"","middleInitial":"Phillip","affiliations":[{"id":12625,"text":"School of Natural Resources and the Environment, University of Arizona, Tucson, AZ, 85721, USA","active":true,"usgs":false}],"preferred":false,"id":787778,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lara-Valencia, Francisco","contributorId":77409,"corporation":false,"usgs":true,"family":"Lara-Valencia","given":"Francisco","email":"","affiliations":[],"preferred":false,"id":787779,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Semmens, Darius J. 0000-0001-7924-6529 dsemmens@usgs.gov","orcid":"https://orcid.org/0000-0001-7924-6529","contributorId":1714,"corporation":false,"usgs":true,"family":"Semmens","given":"Darius","email":"dsemmens@usgs.gov","middleInitial":"J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":787780,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":98397,"text":"fs20103023 - 2010 - A magnitude 7.1 earthquake in the Tacoma Fault Zone— A plausible scenario for the southern Puget Sound region, Washington","interactions":[],"lastModifiedDate":"2021-08-19T20:17:45.671238","indexId":"fs20103023","displayToPublicDate":"2010-05-18T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2010-3023","title":"A magnitude 7.1 earthquake in the Tacoma Fault Zone— A plausible scenario for the southern Puget Sound region, Washington","docAbstract":"The U.S. Geological Survey and cooperating scientists have recently assessed the effects of a magnitude 7.1 earthquake on the Tacoma Fault Zone in Pierce County, Washington. A quake of comparable magnitude struck the southern Puget Sound region about 1,100 years ago, and similar earthquakes are almost certain to occur in the future. The region is now home to hundreds of thousands of people, who would be at risk from the shaking, liquefaction, landsliding, and tsunamis caused by such an earthquake. The modeled effects of this scenario earthquake will help emergency planners and residents of the region prepare for future quakes.","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/fs20103023","collaboration":"In cooperation with Pacific Northwest Seismic Network, Dept. of Earth and Space Sciences, University of Washington, and Washington State Department of Natural Resources","usgsCitation":"Gomberg, J., Sherrod, B.L., Weaver, C., and Frankel, A., 2010, A magnitude 7.1 earthquake in the Tacoma Fault Zone— A plausible scenario for the southern Puget Sound region, Washington: U.S. Geological Survey Fact Sheet 2010-3023, 4 p., https://doi.org/10.3133/fs20103023.","productDescription":"4 p.","onlineOnly":"N","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":125549,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs_2010_3023.jpg"},{"id":388188,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_93238.htm"},{"id":13648,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2010/3023/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Washington","otherGeospatial":"Tacoma fault zone","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.06335449218749,\n 46.86394700508323\n ],\n [\n -122.33551025390625,\n 46.86394700508323\n ],\n [\n -122.33551025390625,\n 47.368594345213374\n ],\n [\n -123.06335449218749,\n 47.368594345213374\n ],\n [\n -123.06335449218749,\n 46.86394700508323\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd495ae4b0b290850ef16d","contributors":{"authors":[{"text":"Gomberg, Joan","contributorId":77919,"corporation":false,"usgs":true,"family":"Gomberg","given":"Joan","affiliations":[],"preferred":false,"id":305202,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sherrod, Brian L. 0000-0002-4492-8631 bsherrod@usgs.gov","orcid":"https://orcid.org/0000-0002-4492-8631","contributorId":2834,"corporation":false,"usgs":true,"family":"Sherrod","given":"Brian","email":"bsherrod@usgs.gov","middleInitial":"L.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":305199,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Weaver, Craig","contributorId":55523,"corporation":false,"usgs":true,"family":"Weaver","given":"Craig","affiliations":[],"preferred":false,"id":305201,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Frankel, Art","contributorId":18083,"corporation":false,"usgs":true,"family":"Frankel","given":"Art","email":"","affiliations":[],"preferred":false,"id":305200,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":98396,"text":"sir20105020 - 2010 - Application of AFINCH as a tool for evaluating the effects of streamflow-gaging-network size and composition on the accuracy and precision of streamflow estimates at ungaged locations in the southeast Lake Michigan hydrologic subregion","interactions":[],"lastModifiedDate":"2023-03-20T20:09:14.851195","indexId":"sir20105020","displayToPublicDate":"2010-05-18T00:00:00","publicationYear":"2010","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":"2010-5020","title":"Application of AFINCH as a tool for evaluating the effects of streamflow-gaging-network size and composition on the accuracy and precision of streamflow estimates at ungaged locations in the southeast Lake Michigan hydrologic subregion","docAbstract":"Bootstrapping techniques employing random subsampling were used with the AFINCH (Analysis of Flows In Networks of CHannels) model to gain insights into the effects of variation in streamflow-gaging-network size and composition on the accuracy and precision of streamflow estimates at ungaged locations in the 0405 (Southeast Lake Michigan) hydrologic subregion. AFINCH uses stepwise-regression techniques to estimate monthly water yields from catchments based on geospatial-climate and land-cover data in combination with available streamflow and water-use data. Calculations are performed on a hydrologic-subregion scale for each catchment and stream reach contained in a National Hydrography Dataset Plus (NHDPlus) subregion. Water yields from contributing catchments are multiplied by catchment areas and resulting flow values are accumulated to compute streamflows in stream reaches which are referred to as flow lines. AFINCH imposes constraints on water yields to ensure that observed streamflows are conserved at gaged locations.
Data from the 0405 hydrologic subregion (referred to as Southeast Lake Michigan) were used for the analyses. Daily streamflow data were measured in the subregion for 1 or more years at a total of 75 streamflow-gaging stations during the analysis period which spanned water years 1971–2003. The number of streamflow gages in operation each year during the analysis period ranged from 42 to 56 and averaged 47. Six sets (one set for each censoring level), each composed of 30 random subsets of the 75 streamflow gages, were created by censoring (removing) approximately 10, 20, 30, 40, 50, and 75 percent of the streamflow gages (the actual percentage of operating streamflow gages censored for each set varied from year to year, and within the year from subset to subset, but averaged approximately the indicated percentages).
Streamflow estimates for six flow lines each were aggregated by censoring level, and results were analyzed to assess (a) how the size and composition of the streamflow-gaging network affected the average apparent errors and variability of the estimated flows and (b) whether results for certain months were more variable than for others. The six flow lines were categorized into one of three types depending upon their network topology and position relative to operating streamflow-gaging stations.
Statistical analysis of the model results indicates that (1) less precise (that is, more variable) estimates resulted from smaller streamflow-gaging networks as compared to larger streamflow-gaging networks, (2) precision of AFINCH flow estimates at an ungaged flow line is improved by operation of one or more streamflow gages upstream and (or) downstream in the enclosing basin, (3) no consistent seasonal trend in estimate variability was evident, and (4) flow lines from ungaged basins appeared to exhibit the smallest absolute apparent percent errors (APEs) and smallest changes in average APE as a function of increasing censoring level. The counterintuitive results described in item (4) above likely reflect both the nature of the base-streamflow estimate from which the errors were computed and insensitivity in the average model-derived estimates to changes in the streamflow-gaging-network size and composition. Another analysis demonstrated that errors for flow lines in ungaged basins have the potential to be much larger than indicated by their APEs if measured relative to their true (but unknown) flows.
“Missing gage” analyses, based on examination of censoring subset results where the streamflow gage of interest was omitted from the calibration data set, were done to better understand the true error characteristics for ungaged flow lines as a function of network size. Results examined for 2 water years indicated that the probability of computing a monthly streamflow estimate within 10 percent of the true value with AFINCH decreased from greater than 0.9 at about a 10-percent network-censoring level to less than 0.6 as the censoring level approached 75 percent. In addition, estimates for typically dry months tended to be characterized by larger percent errors than typically wetter months.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20105020","collaboration":"National Water Availability and Use Pilot Program","usgsCitation":"Koltun, G., and Holtschlag, D.J., 2010, Application of AFINCH as a tool for evaluating the effects of streamflow-gaging-network size and composition on the accuracy and precision of streamflow estimates at ungaged locations in the southeast Lake Michigan hydrologic subregion: U.S. Geological Survey Scientific Investigations Report 2010-5020, iv, 14 p., https://doi.org/10.3133/sir20105020.","productDescription":"iv, 14 p.","onlineOnly":"N","costCenters":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true},{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"links":[{"id":125548,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2010_5020.jpg"},{"id":414378,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_93244.htm","linkFileType":{"id":5,"text":"html"}},{"id":13647,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2010/5020/","linkFileType":{"id":5,"text":"html"}}],"scale":"0","country":"United States","state":"Indiana, Michigan","otherGeospatial":"southeast Lake Michigan hydrologic subregion","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -86.5667,\n 43.5417\n ],\n [\n -86.5667,\n 41.2944\n ],\n [\n -84,\n 41.2944\n ],\n [\n -84,\n 43.5417\n ],\n [\n -86.5667,\n 43.5417\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4ac7e4b07f02db67abfa","contributors":{"authors":[{"text":"Koltun, G. F. 0000-0003-0255-2960","orcid":"https://orcid.org/0000-0003-0255-2960","contributorId":49817,"corporation":false,"usgs":true,"family":"Koltun","given":"G. F.","affiliations":[],"preferred":false,"id":305198,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Holtschlag, David J. 0000-0001-5185-4928 dholtschlag@usgs.gov","orcid":"https://orcid.org/0000-0001-5185-4928","contributorId":5447,"corporation":false,"usgs":true,"family":"Holtschlag","given":"David","email":"dholtschlag@usgs.gov","middleInitial":"J.","affiliations":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true}],"preferred":true,"id":305197,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":98385,"text":"sir20095244 - 2010 - Model Refinement and Simulation of Groundwater Flow in Clinton, Eaton, and Ingham Counties, Michigan","interactions":[],"lastModifiedDate":"2012-03-08T17:16:30","indexId":"sir20095244","displayToPublicDate":"2010-05-15T00:00:00","publicationYear":"2010","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":"2009-5244","title":"Model Refinement and Simulation of Groundwater Flow in Clinton, Eaton, and Ingham Counties, Michigan","docAbstract":"A groundwater-flow model that was constructed in 1996 of the Saginaw aquifer was refined to better represent the regional hydrologic system in the Tri-County region, which consists of Clinton, Eaton, and Ingham Counties, Michigan. With increasing demand for groundwater, the need to manage withdrawals from the Saginaw aquifer has become more important, and the 1996 model could not adequately address issues of water quality and quantity. An updated model was needed to better address potential effects of drought, locally high water demands, reduction of recharge by impervious surfaces, and issues affecting water quality, such as contaminant sources, on water resources and the selection of pumping rates and locations. The refinement of the groundwater-flow model allows simulations to address these issues of water quantity and quality and provides communities with a tool that will enable them to better plan for expansion and protection of their groundwater-supply systems. Model refinement included representation of the system under steady-state and transient conditions, adjustments to the estimated regional groundwater-recharge rates to account for both temporal and spatial differences, adjustments to the representation and hydraulic characteristics of the glacial deposits and Saginaw Formation, and updates to groundwater-withdrawal rates to reflect changes from the early 1900s to 2005.\r\n\r\nSimulations included steady-state conditions (in which stresses remained constant and changes in storage were not included) and transient conditions (in which stresses changed in annual and monthly time scales and changes in storage within the system were included). These simulations included investigation of the potential effects of reduced recharge due to impervious areas or to low-rainfall/drought conditions, delineation of contributing areas with recent pumping rates, and optimization of pumping subject to various quantity and quality constraints. Simulation results indicate potential declines in water levels in both the upper glacial aquifer and the upper sandstone bedrock aquifer under steady-state and transient conditions when recharge was reduced by 20 and 50 percent in urban areas. Transient simulations were done to investigate reduced recharge due to low rainfall and increased pumping to meet anticipated future demand with 24 months (2 years) of modified recharge or modified recharge and pumping rates. During these two simulation years, monthly recharge rates were reduced by about 30 percent, and monthly withdrawal rates for Lansing area production wells were increased by 15 percent. The reduction in the amount of water available to recharge the groundwater system affects the upper model layers representing the glacial aquifers more than the deeper bedrock layers. However, with a reduction in recharge and an increase in withdrawals from the bedrock aquifer, water levels in the bedrock layers are affected more than those in the glacial layers. Differences in water levels between simulations with reduced recharge and reduced recharge with increased pumping are greatest in the Lansing area and least away from pumping centers, as expected. Additionally, the increases in pumping rates had minimal effect on most simulated streamflows. \r\n\r\nAdditional simulations included updating the estimated 10-year wellhead-contributing areas for selected Lansing-area wells under 2006-7 pumping conditions. Optimization of groundwater withdrawals with a water-resource management model was done to determine withdrawal rates while minimizing operational costs and to determine withdrawal locations to achieve additional capacity while meeting specified head constraints. In these optimization scenarios, the desired groundwater withdrawals are achieved by simulating managed wells (where pumping rates can be optimized) and unmanaged wells (where pumping rates are not optimized) and by using various combinations of existing and proposed well locations. \r\n","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/sir20095244","collaboration":"In cooperation with the Tri-County Regional Planning Commission","usgsCitation":"Luukkonen, C.L., 2010, Model Refinement and Simulation of Groundwater Flow in Clinton, Eaton, and Ingham Counties, Michigan: U.S. Geological Survey Scientific Investigations Report 2009-5244, vii, 53 p. , https://doi.org/10.3133/sir20095244.","productDescription":"vii, 53 p. ","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true}],"links":[{"id":118672,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2009_5244.jpg"},{"id":13636,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2009/5244/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b05e4b07f02db699a87","contributors":{"authors":[{"text":"Luukkonen, Carol L. clluukko@usgs.gov","contributorId":3489,"corporation":false,"usgs":true,"family":"Luukkonen","given":"Carol","email":"clluukko@usgs.gov","middleInitial":"L.","affiliations":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true}],"preferred":true,"id":305154,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":98391,"text":"ofr20091028 - 2010 - A Review of Land-Cover Mapping Activities in Coastal Alabama and Mississippi","interactions":[],"lastModifiedDate":"2012-02-10T00:11:53","indexId":"ofr20091028","displayToPublicDate":"2010-05-15T00:00:00","publicationYear":"2010","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":"2009-1028","title":"A Review of Land-Cover Mapping Activities in Coastal Alabama and Mississippi","docAbstract":"INTRODUCTION\r\nLand-use and land-cover (LULC) data provide important information for environmental management. Data pertaining to land-cover and land-management activities are a common requirement for spatial analyses, such as watershed modeling, climate change, and hazard assessment. In coastal areas, land development, storms, and shoreline modification amplify the need for frequent and detailed land-cover datasets. The northern Gulf of Mexico coastal area is no exception. The impact of severe storms, increases in urban area, dramatic changes in land cover, and loss of coastal-wetland habitat all indicate a vital need for reliable and comparable land-cover data. \r\n\r\nFour main attributes define a land-cover dataset: the date/time of data collection, the spatial resolution, the type of classification, and the source data. The source data are the foundation dataset used to generate LULC classification and are typically remotely sensed data, such as aerial photography or satellite imagery. These source data have a large influence on the final LULC data product, so much so that one can classify LULC datasets into two general groups: LULC data derived from aerial photography and LULC data derived from satellite imagery. The final LULC data can be converted from one format to another (for instance, vector LULC data can be converted into raster data for analysis purposes, and vice versa), but each subsequent dataset maintains the imprint of the source medium within its spatial accuracy and data features. The source data will also influence the spatial and temporal resolution, as well as the type of classification.\r\n\r\nThe intended application of the LULC data typically defines the type of source data and methodology, with satellite imagery being selected for large landscapes (state-wide, national data products) and repeatability (environmental monitoring and change analysis). The coarse spatial scale and lack of refined land-use categories are typical drawbacks to satellite-based land-use classifications. Aerial photography is typically selected for smaller landscapes (watershed-basin scale), for greater definition of the land-use categories, and for increased spatial resolution. Disadvantages of using photography include time-consuming digitization, high costs for imagery collection, and lack of seasonal data. Recently, the availability of high-resolution satellite imagery has generated a new category of LULC data product. These new datasets have similar strengths to the aerial-photo-based LULC in that they possess the potential for refined definition of land-use categories and increased spatial resolution but also have the benefit of satellite-based classifications, such as repeatability for change analysis. LULC classification based on high-resolution satellite imagery is still in the early stages of development but merits greater attention because environmental-monitoring and landscape-modeling programs rely heavily on LULC data.\r\n\r\nThis publication summarizes land-use and land-cover mapping activities for Alabama and Mississippi coastal areas within the U.S. Geological Survey (USGS) Northern Gulf of Mexico (NGOM) Ecosystem Change and Hazard Susceptibility Project boundaries. Existing LULC datasets will be described, as well as imagery data sources and ancillary data that may provide ground-truth or satellite training data for a forthcoming land-cover classification. Finally, potential areas for a high-resolution land-cover classification in the Alabama-Mississippi region will be identified.\r\n","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/ofr20091028","usgsCitation":"Smith, K., Nayegandhi, A., and Brock, J., 2010, A Review of Land-Cover Mapping Activities in Coastal Alabama and Mississippi: U.S. Geological Survey Open-File Report 2009-1028, iv, 19 p. , https://doi.org/10.3133/ofr20091028.","productDescription":"iv, 19 p. ","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":118680,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2009_1028.jpg"},{"id":13642,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2009/1028/","linkFileType":{"id":5,"text":"html"}}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -90.33333333333333,29.666666666666668 ], [ -90.33333333333333,31.416666666666668 ], [ -87,31.416666666666668 ], [ -87,29.666666666666668 ], [ -90.33333333333333,29.666666666666668 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd4967e4b0b290850ef21d","contributors":{"authors":[{"text":"Smith, Kathryn E. L.","contributorId":20860,"corporation":false,"usgs":true,"family":"Smith","given":"Kathryn E. L.","affiliations":[],"preferred":false,"id":305167,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nayegandhi, Amar","contributorId":37292,"corporation":false,"usgs":true,"family":"Nayegandhi","given":"Amar","affiliations":[],"preferred":false,"id":305168,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brock, John 0000-0002-5289-9332 jbrock@usgs.gov","orcid":"https://orcid.org/0000-0002-5289-9332","contributorId":2261,"corporation":false,"usgs":true,"family":"Brock","given":"John","email":"jbrock@usgs.gov","affiliations":[{"id":5061,"text":"National Cooperative Geologic Mapping and Landslide Hazards","active":true,"usgs":true}],"preferred":true,"id":305166,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":98377,"text":"fs20103035 - 2010 - Filtering NetCDF Files by Using the EverVIEW Slice and Dice Tool","interactions":[],"lastModifiedDate":"2012-02-02T00:15:03","indexId":"fs20103035","displayToPublicDate":"2010-05-13T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2010-3035","title":"Filtering NetCDF Files by Using the EverVIEW Slice and Dice Tool","docAbstract":"Network Common Data Form (NetCDF) is a self-describing, machine-independent file format for storing array-oriented scientific data. It was created to provide a common interface between applications and real-time meteorological and other scientific data. Over the past few years, there has been a growing movement within the community of natural resource managers in The Everglades, Fla., to use NetCDF as the standard data container for datasets based on multidimensional arrays. As a consequence, a need surfaced for additional tools to view and manipulate NetCDF datasets, specifically to filter the files by creating subsets of large NetCDF files. The U.S. Geological Survey (USGS) and the Joint Ecosystem Modeling (JEM) group are working to address these needs with applications like the EverVIEW Slice and Dice Tool, which allows users to filter grid-based NetCDF files, thus targeting those data most important to them. The major functions of this tool are as follows: (1) to create subsets of NetCDF files temporally, spatially, and by data value; (2) to view the NetCDF data in table form; and (3) to export the filtered data to a comma-separated value (CSV) file format. The USGS and JEM will continue to work with scientists and natural resource managers across The Everglades to solve complex restoration problems through technological advances.\r\n","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/fs20103035","usgsCitation":"Conzelmann, C., and Romañach, S., 2010, Filtering NetCDF Files by Using the EverVIEW Slice and Dice Tool: U.S. Geological Survey Fact Sheet 2010-3035, 2 p., https://doi.org/10.3133/fs20103035.","productDescription":"2 p.","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"links":[{"id":125386,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs_2010_3035.bmp"},{"id":13627,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2010/3035/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e49fee4b07f02db5f72b8","contributors":{"authors":[{"text":"Conzelmann, Craig 0000-0002-4227-8719 conzelmannc@usgs.gov","orcid":"https://orcid.org/0000-0002-4227-8719","contributorId":2361,"corporation":false,"usgs":true,"family":"Conzelmann","given":"Craig","email":"conzelmannc@usgs.gov","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":305129,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Romañach, Stephanie S. 0000-0003-0271-7825 sromanach@usgs.gov","orcid":"https://orcid.org/0000-0003-0271-7825","contributorId":2331,"corporation":false,"usgs":true,"family":"Romañach","given":"Stephanie S.","email":"sromanach@usgs.gov","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":false,"id":305128,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70211110,"text":"70211110 - 2010 - Vertical movements of ocean island volcanoes: Insights from a stationary plate environment","interactions":[],"lastModifiedDate":"2020-07-14T22:23:53.624575","indexId":"70211110","displayToPublicDate":"2010-05-10T17:15:44","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2667,"text":"Marine Geology","active":true,"publicationSubtype":{"id":10}},"title":"Vertical movements of ocean island volcanoes: Insights from a stationary plate environment","docAbstract":"Uplift reconstructions based on the Cape Verde's geological record provide a unique opportunity to study the long-term isostatic movements associated with hotspot activity on a stationary plate environment. The archipelago is considered stationary with respect to its melting source so the hotspot-driven isostatic effects affecting the ocean islands are expected to be enhanced. In this study, Ar–Ar and U–Th geochronology techniques were used to date a set of palaeo-markers of sea-level from Santiago's and São Nicolau's edifices, two of the main Cape Verde Islands. A comparison between relative sea-level and eustatic sea-level (from a modern eustatic curve) was established to extract the vertical displacement undergone by the markers, and to reconstruct the uplift/subsidence history of each island. The resulting uplift reconstructions confirm that both Santiago and São Nicolau experienced a general uplift trend over the last 6 Ma, seemingly synchronous with the vigorous volcanic activity that built their exposed edifices. These islands, however, exhibit different uplift histories despite their common uplift trend. Several uplift mechanisms were tested and a local rather than regional mechanism is proposed as the main cause of uplift, generally unrelated with far-field effects of surface loading. This mechanism is probably associated with magmatic additions at crustal level.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.margeo.2010.04.009","usgsCitation":"Ramalho, R., Helffrich, G., Cosca, M.A., Vance, D., Hoffman, D., and Schmidt, D.N., 2010, Vertical movements of ocean island volcanoes: Insights from a stationary plate environment: Marine Geology, v. 275, no. 1-4, p. 84-95, https://doi.org/10.1016/j.margeo.2010.04.009.","productDescription":"12 p.","startPage":"84","endPage":"95","ipdsId":"IP-016970","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":376395,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Cape Verde","otherGeospatial":"Cape Verde Archipelago","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -25.5487060546875,\n 14.615478234145261\n ],\n [\n -22.4395751953125,\n 14.615478234145261\n ],\n [\n -22.4395751953125,\n 17.429269667952468\n ],\n [\n -25.5487060546875,\n 17.429269667952468\n ],\n [\n -25.5487060546875,\n 14.615478234145261\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"275","issue":"1-4","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ramalho, Ricardo","contributorId":193475,"corporation":false,"usgs":false,"family":"Ramalho","given":"Ricardo","email":"","affiliations":[],"preferred":false,"id":792795,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Helffrich, George","contributorId":193476,"corporation":false,"usgs":false,"family":"Helffrich","given":"George","email":"","affiliations":[],"preferred":false,"id":792796,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cosca, Michael A 0000-0002-0600-7663","orcid":"https://orcid.org/0000-0002-0600-7663","contributorId":229009,"corporation":false,"usgs":true,"family":"Cosca","given":"Michael","email":"","middleInitial":"A","affiliations":[],"preferred":true,"id":792794,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vance, D.","contributorId":74866,"corporation":false,"usgs":false,"family":"Vance","given":"D.","email":"","affiliations":[],"preferred":false,"id":792797,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Hoffman, D.","contributorId":72895,"corporation":false,"usgs":true,"family":"Hoffman","given":"D.","affiliations":[],"preferred":false,"id":792798,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Schmidt, Daniela N.","contributorId":229010,"corporation":false,"usgs":false,"family":"Schmidt","given":"Daniela","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":792799,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}} ]}