Apalachicola Bay, Florida, accounts for 90% of Florida's and 10% of the nation's eastern oyster (Crassostrea virginica) harvesting. Chlorophyll-a concentration and total suspended solids (TSS) are two important water quality variables, among other environmental factors such as salinity, for eastern oyster production in Apalachicola Bay. In this research, we developed regression models of the relationships between the reflectance of the Moderate-Resolution Imaging Spectroradiometer (MODIS) Terra 250 m data and the two water quality variables based on the Bay-wide field data collected during 14–17 October 2002, a relatively dry period, and 3–5 April 2006, a relatively wet period, respectively. Then we selected the best regression models (highest coefficient of determination, R 2) to derive Bay-wide maps of chlorophyll-a concentration and TSS for the two periods. The MODIS-derived maps revealed large spatial and temporal variations in chlorophyll-a concentration and TSS across the entire Apalachicola Bay.
Three-dimensional, finite-difference simulations of a realistic finite-fault rupture on the southern Hayward fault are used to evaluate the effects of random, correlated velocity perturbations on predicted ground motions. Velocity perturbations are added to a three-dimensional (3D) regional seismic velocity model of the San Francisco Bay Area using a 3D von Karman random medium. Velocity correlation lengths of 5 and 10 km and standard deviations in the velocity of 5% and 10% are considered. The results show that significant deviations in predicted ground velocities are seen in the calculated frequency range (≤1 Hz) for standard deviations in velocity of 5% to 10%. These results have implications for the practical limits on the accuracy of scenario ground-motion calculations and on retrieval of source parameters using higher-frequency, strong-motion data.
","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Bulletin of the Seismological Society of America","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Seismological Society of America","publisherLocation":"Stanford","doi":"10.1785/0120090060","issn":"00371106","usgsCitation":"Hartzell, S., Harmsen, S., and Frankel, A., 2010, Effects of 3D random correlated velocity perturbations on predicted ground motions: Bulletin of the Seismological Society of America, v. 100, no. 4, p. 1415-1426, https://doi.org/10.1785/0120090060.","productDescription":"12 p.","startPage":"1415","endPage":"1426","numberOfPages":"12","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[],"links":[{"id":244970,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":217058,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1785/0120090060"}],"volume":"100","issue":"4","noUsgsAuthors":false,"publicationDate":"2010-07-27","publicationStatus":"PW","scienceBaseUri":"505a0644e4b0c8380cd5119d","contributors":{"authors":[{"text":"Hartzell, S.","contributorId":12603,"corporation":false,"usgs":true,"family":"Hartzell","given":"S.","email":"","affiliations":[],"preferred":false,"id":460503,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harmsen, S.","contributorId":79600,"corporation":false,"usgs":true,"family":"Harmsen","given":"S.","affiliations":[],"preferred":false,"id":460505,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Frankel, A. 0000-0001-9119-6106","orcid":"https://orcid.org/0000-0001-9119-6106","contributorId":41593,"corporation":false,"usgs":true,"family":"Frankel","given":"A.","affiliations":[],"preferred":false,"id":460504,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70046784,"text":"dds49130 - 2010 - Attributes for MRB_E2RF1 Catchments by Major River Basins in the Conterminous United States: Average Daily Minimum Temperature, 2002","interactions":[],"lastModifiedDate":"2013-11-25T16:06:25","indexId":"dds49130","displayToPublicDate":"2010-01-01T00:00:00","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":"491-30","title":"Attributes for MRB_E2RF1 Catchments by Major River Basins in the Conterminous United States: Average Daily Minimum Temperature, 2002","docAbstract":"This tabular data set represents the average daily minimum temperature in Celsius multiplied by 100 for 2002, compiled for every MRB_E2RF1 catchment of selected Major River Basins (MRBs, Crawford and others, 2006). The source data were the Near-Real-Time High-Resolution Monthly Average Maximum/Minimum Temperature for the Conterminous United States for 2002 raster data set produced by the Spatial Climate Analysis Service at Oregon State University.\nThe MRB_E2RF1 catchments are based on a modified version of the Environmental Protection Agency's (USEPA) ERF1_2 and include enhancements to support national and regional-scale surface-water quality modeling (Nolan and others, 2002; Brakebill and others, 2011). Data were compiled for every MRB_E2RF1 catchment for the conterminous United States covering New England and Mid-Atlantic (MRB1), South Atlantic-Gulf and Tennessee (MRB2), the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy (MRB3), the Missouri (MRB4), the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf (MRB5), the Rio Grande, Colorado, and the Great basin (MRB6), the Pacific Northwest (MRB7) river basins, and California (MRB8).","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/dds49130","usgsCitation":"Wieczorek, M., and LaMotte, A.E., 2010, Attributes for MRB_E2RF1 Catchments by Major River Basins in the Conterminous United States: Average Daily Minimum Temperature, 2002: U.S. Geological Survey Data Series 491-30, Dataset, https://doi.org/10.3133/dds49130.","productDescription":"Dataset","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[],"links":[{"id":274510,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":274509,"type":{"id":16,"text":"Metadata"},"url":"https://water.usgs.gov/GIS/metadata/usgswrd/XML/mrb_e2rf1_tmin02.xml"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -127.910792,23.243486 ], [ -127.910792,51.657387 ], [ -65.327751,51.657387 ], [ -65.327751,23.243486 ], [ -127.910792,23.243486 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51dbdf67e4b0f81004b77cd4","contributors":{"authors":[{"text":"Wieczorek, Michael mewieczo@usgs.gov","contributorId":2309,"corporation":false,"usgs":true,"family":"Wieczorek","given":"Michael","email":"mewieczo@usgs.gov","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":false,"id":480246,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"LaMotte, Andrew E. 0000-0002-1434-6518 alamotte@usgs.gov","orcid":"https://orcid.org/0000-0002-1434-6518","contributorId":2842,"corporation":false,"usgs":true,"family":"LaMotte","given":"Andrew","email":"alamotte@usgs.gov","middleInitial":"E.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":480247,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70159357,"text":"70159357 - 2010 - Measurement of bedload transport in sand-bed rivers: A look at two indirect sampling methods","interactions":[],"lastModifiedDate":"2021-10-27T16:40:23.473766","indexId":"70159357","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Measurement of bedload transport in sand-bed rivers: A look at two indirect sampling methods","docAbstract":"Sand-bed rivers present unique challenges to accurate measurement of the bedload transport rate using the traditional direct sampling methods of direct traps (for example the Helley-Smith bedload sampler). The two major issues are: 1) over sampling of sand transport caused by “mining” of sand due to the flow disturbance induced by the presence of the sampler and 2) clogging of the mesh bag with sand particles reducing the hydraulic efficiency of the sampler. Indirect measurement methods hold promise in that unlike direct methods, no transport-altering flow disturbance near the bed occurs. The bedform velocimetry method utilizes a measure of the bedform geometry and the speed of bedform translation to estimate the bedload transport through mass balance. The bedform velocimetry method is readily applied for the estimation of bedload transport in large sand-bed rivers so long as prominent bedforms are present and the streamflow discharge is steady for long enough to provide sufficient bedform translation between the successive bathymetric data sets. Bedform velocimetry in small sandbed rivers is often problematic due to rapid variation within the hydrograph. The bottom-track bias feature of the acoustic Doppler current profiler (ADCP) has been utilized to accurately estimate the virtual velocities of sand-bed rivers. Coupling measurement of the virtual velocity with an accurate determination of the active depth of the streambed sediment movement is another method to measure bedload transport, which will be termed the “virtual velocity” method. Much research remains to develop methods and determine accuracy of the virtual velocity method in small sand-bed rivers.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Bedload-surrogate monitoring technologies","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, Virginia","usgsCitation":"Holmes, R., 2010, Measurement of bedload transport in sand-bed rivers: A look at two indirect sampling methods, chap. of Bedload-surrogate monitoring technologies, p. 236-252.","productDescription":"16 p.","startPage":"236","endPage":"252","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-004287","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":310567,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Missouri","city":"St. Louis","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.18264770507812,\n 38.766398104806264\n ],\n [\n -90.1702880859375,\n 38.76318574559655\n ],\n [\n -90.17715454101562,\n 38.74605072069108\n ],\n [\n -90.18539428710938,\n 38.72944724289828\n ],\n [\n -90.19157409667967,\n 38.71230412063499\n ],\n [\n -90.19569396972656,\n 38.69301319283493\n ],\n [\n -90.17990112304688,\n 38.66889221556877\n ],\n [\n -90.17578124999999,\n 38.64208159560713\n ],\n [\n -90.19020080566406,\n 38.59809045854761\n ],\n [\n -90.22796630859375,\n 38.564810956372185\n ],\n [\n -90.24650573730467,\n 38.53957267203905\n ],\n [\n -90.25474548339844,\n 38.54010974905484\n ],\n [\n -90.2471923828125,\n 38.5535353710587\n ],\n [\n -90.23483276367188,\n 38.57071650940461\n ],\n [\n -90.21697998046875,\n 38.58306291549108\n ],\n [\n -90.19157409667967,\n 38.60828592850559\n ],\n [\n -90.17921447753906,\n 38.64261790634527\n ],\n [\n -90.19500732421875,\n 38.67961365359827\n ],\n [\n -90.21286010742188,\n 38.70319516433674\n ],\n [\n -90.2149200439453,\n 38.71766178810086\n ],\n [\n -90.21148681640625,\n 38.73158984401968\n ],\n [\n -90.18951416015625,\n 38.749263851188104\n ],\n [\n -90.1812744140625,\n 38.762114927054405\n ],\n [\n -90.18264770507812,\n 38.766398104806264\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"562a08d8e4b011227bf1fd8c","contributors":{"editors":[{"text":"Gray, John R. 0000-0002-8817-3701 jrgray@usgs.gov","orcid":"https://orcid.org/0000-0002-8817-3701","contributorId":1158,"corporation":false,"usgs":true,"family":"Gray","given":"John","email":"jrgray@usgs.gov","middleInitial":"R.","affiliations":[{"id":5058,"text":"Office of the Chief Scientist for Water","active":true,"usgs":true}],"preferred":true,"id":578192,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Laronne, Jonathan B.","contributorId":8778,"corporation":false,"usgs":true,"family":"Laronne","given":"Jonathan","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":578193,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Marr, Jeffrey D. G.","contributorId":80791,"corporation":false,"usgs":false,"family":"Marr","given":"Jeffrey","email":"","middleInitial":"D. G.","affiliations":[{"id":47665,"text":"St. Anthony Falls Laboratory, University of Minnesota, Minneapolis, MN, USA","active":true,"usgs":false}],"preferred":false,"id":578194,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Holmes, Robert R. Jr. 0000-0002-5060-3999","orcid":"https://orcid.org/0000-0002-5060-3999","contributorId":149380,"corporation":false,"usgs":true,"family":"Holmes","given":"Robert R.","suffix":"Jr.","affiliations":[],"preferred":false,"id":578191,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70176252,"text":"70176252 - 2010 - Biological community structure on patch reefs in Biscayne National Park, FL, USA","interactions":[],"lastModifiedDate":"2016-09-06T11:34:10","indexId":"70176252","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1552,"text":"Environmental Monitoring and Assessment","onlineIssn":"1573-2959","printIssn":"0167-6369","active":true,"publicationSubtype":{"id":10}},"title":"Biological community structure on patch reefs in Biscayne National Park, FL, USA","docAbstract":"Coral reef ecosystem management benefits from continual quantitative assessment of the resources being managed, plus assessment of factors that affect distribution patterns of organisms in the ecosystem. In this study, we investigate the relationships among physical, benthic, and fish variables in an effort to help explain the distribution patterns of organisms on patch reefs within Biscayne National Park, FL, USA. We visited a total of 196 randomly selected sampling stations on 12 shallow (<10 m) patch reefs and measured physical variables (e.g., substratum rugosity, substratum type) and benthic and fish community variables. We also incorporated data on substratum rugosity collected remotely via airborne laser surveying (Experimental Advanced Airborne Research Lidar—EAARL). Across all stations, only weak relationships were found between physical, benthic cover, and fish assemblage variables. Much of the variance was attributable to a “reef effect,” meaning that community structure and organism abundances were more variable at stations among reefs than within reefs. However, when the reef effect was accounted for and removed statistically, patterns were detected. Within reefs, juvenile scarids were most abundant at stations with high coverage of the fleshy macroalgae Dictyota spp., and the calcified alga Halimeda tuna was most abundant at stations with low EAARL rugosity. Explanations for the overwhelming importance of “reef” in explaining variance in our dataset could include the stochastic arrangement of organisms on patch reefs related to variable larval recruitment in space and time and/or strong historical effects due to patchy disturbances (e.g., hurricanes, fishing), as well as legacy effects of prior residents (“priority” effects).
","language":"English","publisher":"Springer","doi":"10.1007/s10661-009-0910-0","usgsCitation":"Kuffner, I.B., Grober-Dunsmore, R., Brock, J., and Hickey, T.D., 2010, Biological community structure on patch reefs in Biscayne National Park, FL, USA: Environmental Monitoring and Assessment, v. 164, no. 1, p. 513-531, https://doi.org/10.1007/s10661-009-0910-0.","productDescription":"19 p.","startPage":"513","endPage":"531","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":489187,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10661-009-0910-0","text":"Publisher Index Page"},{"id":328239,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Biscayne National Park","volume":"164","issue":"1","noUsgsAuthors":false,"publicationDate":"2009-04-28","publicationStatus":"PW","scienceBaseUri":"57cfe8b0e4b04836416a0d2b","contributors":{"authors":[{"text":"Kuffner, Ilsa B. 0000-0001-8804-7847 ikuffner@usgs.gov","orcid":"https://orcid.org/0000-0001-8804-7847","contributorId":3105,"corporation":false,"usgs":true,"family":"Kuffner","given":"Ilsa","email":"ikuffner@usgs.gov","middleInitial":"B.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":648088,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grober-Dunsmore, Rikki","contributorId":71292,"corporation":false,"usgs":true,"family":"Grober-Dunsmore","given":"Rikki","email":"","affiliations":[],"preferred":false,"id":648089,"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":648090,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hickey, T. Don","contributorId":49066,"corporation":false,"usgs":true,"family":"Hickey","given":"T.","email":"","middleInitial":"Don","affiliations":[],"preferred":false,"id":648091,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70046695,"text":"dds49103 - 2010 - Attributes for MRB_E2RF1 Catchments by Major River Basins in the Conterminous United States: Basin Characteristics, 2002 Geospatial_Data_Presentation_Form: tabular digital data","interactions":[],"lastModifiedDate":"2013-11-25T16:07:26","indexId":"dds49103","displayToPublicDate":"2010-01-01T00:00:00","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":"491-03","title":"Attributes for MRB_E2RF1 Catchments by Major River Basins in the Conterminous United States: Basin Characteristics, 2002 Geospatial_Data_Presentation_Form: tabular digital data","docAbstract":"This tabular data set represents basin characteristics for the year 2002 compiled for every MRB_E2RF1 catchment of selected Major River Basins (MRBs, Crawford and others, 2006). These characteristics are reach catchment shape index, stream density, sinuosity, mean elevation, mean slope and number of road-stream crossings. The source data sets are based on a modified version of the U.S. Environmental Protection Agency's (USEPA) RF1_2 and include enhancements to support national and regional-scale surface-water quality modeling (Nolan and others, 2002; Brakebill and others, 2011) and the U.S. Census Bureau's TIGER/Line Files (U.S. Census Bureau,2006). The MRB_E2RF1 catchments are based on a modified version of the U.S. Environmental Protection Agency's (USEPA) ERF1_2 and include enhancements to support national and regional-scale surface-water quality modeling (Nolan and others, 2002; Brakebill and others, 2011). Data were compiled for every MRB_E2RF1 catchment for the conterminous United States covering New England and Mid-Atlantic (MRB1), South Atlantic-Gulf and Tennessee (MRB2), the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy (MRB3), the Missouri (MRB4), the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf (MRB5), the Rio Grande, Colorado, and the Great basin (MRB6), the Pacific Northwest (MRB7) river basins, and California (MRB8).","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/dds49103","usgsCitation":"Wieczorek, M., and LaMotte, A.E., 2010, Attributes for MRB_E2RF1 Catchments by Major River Basins in the Conterminous United States: Basin Characteristics, 2002 Geospatial_Data_Presentation_Form: tabular digital data: U.S. Geological Survey Data Series 491-03, Dataset, https://doi.org/10.3133/dds49103.","productDescription":"Dataset","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[],"links":[{"id":274193,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":274192,"type":{"id":16,"text":"Metadata"},"url":"https://water.usgs.gov/GIS/metadata/usgswrd/XML/mrb_e2rf1_bchar.xml"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -127.910792,23.243486 ], [ -127.910792,51.657387 ], [ -65.327751,51.657387 ], [ -65.327751,23.243486 ], [ -127.910792,23.243486 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51cabbe0e4b0d298e5434c30","contributors":{"authors":[{"text":"Wieczorek, Michael mewieczo@usgs.gov","contributorId":2309,"corporation":false,"usgs":true,"family":"Wieczorek","given":"Michael","email":"mewieczo@usgs.gov","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":false,"id":480028,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"LaMotte, Andrew E. 0000-0002-1434-6518 alamotte@usgs.gov","orcid":"https://orcid.org/0000-0002-1434-6518","contributorId":2842,"corporation":false,"usgs":true,"family":"LaMotte","given":"Andrew","email":"alamotte@usgs.gov","middleInitial":"E.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":480029,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70046731,"text":"dds49109 - 2010 - Attributes for MRB_E2RF1 Catchments by Major River Basins in the Conterminous United States: Level 3 Ecoregions","interactions":[],"lastModifiedDate":"2013-11-25T16:08:51","indexId":"dds49109","displayToPublicDate":"2010-01-01T00:00:00","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":"491-09","title":"Attributes for MRB_E2RF1 Catchments by Major River Basins in the Conterminous United States: Level 3 Ecoregions","docAbstract":"This tabular data set represents the estimated area of level 3 ecological landscape regions (ecoregions), as defined by Omernik (1987), compiled for every MRB_E2RF1 catchment of the Major River Basins (MRBs, Crawford and others, 2006). The source data set is Level III Ecoregions of the Continental United States (U.S. Environmental Protection Agency, 2003). The MRB_E2RF1 catchments are based on a modified version of the U.S. Environmental Protection Agency's (USEPA) ERF1_2 and include enhancements to support national and regional-scale surface-water quality modeling (Nolan and others, 2002; Brakebill and others, 2011). Data were compiled for every MRB_E2RF1 catchment for the conterminous United States covering New England and Mid-Atlantic (MRB1), South Atlantic-Gulf and Tennessee (MRB2), the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy (MRB3), the Missouri (MRB4), the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf (MRB5), the Rio Grande, Colorado, and the Great basin (MRB6), the Pacific Northwest (MRB7) river basins, and California (MRB8).","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/dds49109","usgsCitation":"Wieczorek, M., and LaMotte, A.E., 2010, Attributes for MRB_E2RF1 Catchments by Major River Basins in the Conterminous United States: Level 3 Ecoregions: U.S. Geological Survey Data Series 491-09, Dataset, https://doi.org/10.3133/dds49109.","productDescription":"Dataset","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[],"links":[{"id":274338,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":274337,"type":{"id":16,"text":"Metadata"},"url":"https://water.usgs.gov/GIS/metadata/usgswrd/XML/mrb_e2rf1_eco3.xml"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -127.910792,23.243486 ], [ -127.910792,51.657387 ], [ -65.327751,51.657387 ], [ -65.327751,23.243486 ], [ -127.910792,23.243486 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51d2a4e2e4b0ca18483389eb","contributors":{"authors":[{"text":"Wieczorek, Michael mewieczo@usgs.gov","contributorId":2309,"corporation":false,"usgs":true,"family":"Wieczorek","given":"Michael","email":"mewieczo@usgs.gov","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":false,"id":480127,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"LaMotte, Andrew E. 0000-0002-1434-6518 alamotte@usgs.gov","orcid":"https://orcid.org/0000-0002-1434-6518","contributorId":2842,"corporation":false,"usgs":true,"family":"LaMotte","given":"Andrew","email":"alamotte@usgs.gov","middleInitial":"E.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":480128,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70046730,"text":"dds49108 - 2010 - Attributes for MRB_E2RF1 Catchments by Major River Basins in the Conterminous United States: Nutrient Application (Phosphorus and Nitrogen) for Fertilizer and Manure Applied to Crops (Cropsplit), 2002","interactions":[],"lastModifiedDate":"2013-11-25T16:07:00","indexId":"dds49108","displayToPublicDate":"2010-01-01T00:00:00","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":"491-08","title":"Attributes for MRB_E2RF1 Catchments by Major River Basins in the Conterminous United States: Nutrient Application (Phosphorus and Nitrogen) for Fertilizer and Manure Applied to Crops (Cropsplit), 2002","docAbstract":"This tabular data set represents the estimated amount of phosphorus and nitrogen fertilizers applied to selected crops for the year 2002, compiled for every MRB_E2RF1 catchment of Major River Basins (MRBs, Crawford and others, 2006). The source data set is based on 2002 fertilizer data (Ruddy and others, 2006) and tabulated by crop type per county (Alexander and others, 2007). The MRB_E2RF1 catchments are based on a modified version of the U.S. Environmental Protection Agency's (USEPA) ERF1_2 and include enhancements to support national and regional-scale surface-water quality modeling (Nolan and others, 2002; Brakebill and others, 2011). Data were compiled for MRB_E2RF1 catchments for the conterminous United States covering New England and Mid-Atlantic (MRB1), South Atlantic-Gulf and Tennessee (MRB2), the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy (MRB3), the Missouri (MRB4), the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf (MRB5), the Rio Grande, Colorado, and the Great basin (MRB6), the Pacific Northwest (MRB7) river basins, and California (MRB8).","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/dds49108","usgsCitation":"Wieczorek, M., and LaMotte, A.E., 2010, Attributes for MRB_E2RF1 Catchments by Major River Basins in the Conterminous United States: Nutrient Application (Phosphorus and Nitrogen) for Fertilizer and Manure Applied to Crops (Cropsplit), 2002: U.S. Geological Survey Data Series 491-08, Dataset, https://doi.org/10.3133/dds49108.","productDescription":"Dataset","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[],"links":[{"id":274334,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":274333,"type":{"id":16,"text":"Metadata"},"url":"https://water.usgs.gov/GIS/metadata/usgswrd/XML/mrb_e2rf1_cropsplit.xml"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -127.910792,23.243486 ], [ -127.910792,51.657387 ], [ -65.327751,51.657387 ], [ -65.327751,23.243486 ], [ -127.910792,23.243486 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51d2a4e5e4b0ca1848338a0f","contributors":{"authors":[{"text":"Wieczorek, Michael mewieczo@usgs.gov","contributorId":2309,"corporation":false,"usgs":true,"family":"Wieczorek","given":"Michael","email":"mewieczo@usgs.gov","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":false,"id":480125,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"LaMotte, Andrew E. 0000-0002-1434-6518 alamotte@usgs.gov","orcid":"https://orcid.org/0000-0002-1434-6518","contributorId":2842,"corporation":false,"usgs":true,"family":"LaMotte","given":"Andrew","email":"alamotte@usgs.gov","middleInitial":"E.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":480126,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70046727,"text":"dds49105 - 2010 - Attributes for MRB_E2RF1 Catchments by Major River Basins in the Conterminous United States: Bedrock Geology","interactions":[],"lastModifiedDate":"2013-11-25T16:07:45","indexId":"dds49105","displayToPublicDate":"2010-01-01T00:00:00","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":"491-05","title":"Attributes for MRB_E2RF1 Catchments by Major River Basins in the Conterminous United States: Bedrock Geology","docAbstract":"This tabular data set represents the area of bedrock geology types in square meters compiled for every catchment of MRB_E2RF1 catchments for Major River Basins (MRBs, Crawford and others, 2006). The source data set is the \"Geology of the Conterminous United States at 1:2,500,000 Scale--A Digital Representation of the 1974 P.B. King and H.M. Beikman Map\" (Schuben and others, 1994). The MRB_E2RF1 catchments are based on a modified version of the U.S. Environmental Protection Agency's (USEPA) ERF1_2 and include enhancements to support national and regional-scale surface-water quality modeling (Nolan and others, 2002; Brakebill and others, 2011). Data were compiled for every MRB_E2RF1 catchment for the conterminous United States covering New England and Mid-Atlantic (MRB1), South Atlantic-Gulf and Tennessee (MRB2), the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy (MRB3), the Missouri (MRB4), the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf (MRB5), the Rio Grande, Colorado, and the Great basin (MRB6), the Pacific Northwest (MRB7) river basins, and California (MRB8).","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/dds49105","usgsCitation":"Wieczorek, M., and LaMotte, A.E., 2010, Attributes for MRB_E2RF1 Catchments by Major River Basins in the Conterminous United States: Bedrock Geology: U.S. Geological Survey Data Series 491-05, Dataset, https://doi.org/10.3133/dds49105.","productDescription":"Dataset","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[],"links":[{"id":274328,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":274327,"type":{"id":16,"text":"Metadata"},"url":"https://water.usgs.gov/GIS/metadata/usgswrd/XML/mrb_e2rf1_bgeol.xml"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -127.910792,23.243486 ], [ -127.910792,51.657387 ], [ -65.327751,51.657387 ], [ -65.327751,23.243486 ], [ -127.910792,23.243486 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51d2a4e2e4b0ca18483389df","contributors":{"authors":[{"text":"Wieczorek, Michael mewieczo@usgs.gov","contributorId":2309,"corporation":false,"usgs":true,"family":"Wieczorek","given":"Michael","email":"mewieczo@usgs.gov","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":false,"id":480119,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"LaMotte, Andrew E. 0000-0002-1434-6518 alamotte@usgs.gov","orcid":"https://orcid.org/0000-0002-1434-6518","contributorId":2842,"corporation":false,"usgs":true,"family":"LaMotte","given":"Andrew","email":"alamotte@usgs.gov","middleInitial":"E.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":480120,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70046729,"text":"dds49107 - 2010 - Attributes for MRB_E2RF1 Catchments in Selected Major River Basins of the Conterminous United States: Contact Time, 2002","interactions":[],"lastModifiedDate":"2013-11-25T16:05:09","indexId":"dds49107","displayToPublicDate":"2010-01-01T00:00:00","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":"491-07","title":"Attributes for MRB_E2RF1 Catchments in Selected Major River Basins of the Conterminous United States: Contact Time, 2002","docAbstract":"This tabular data set represents the average contact time, in units of days, compiled for every MRB_E2RF1 catchment of Major River Basins (MRBs, Crawford and others, 2006). Contact time, as described in Vitvar and others (2002), is defined as the baseflow residence time in the subsurface. The source data set was the U.S. Geological Survey's (USGS) 1-kilometer grid for the conterminous United States (D.M. Wolock, U.S. Geological Survey, written commun., 2008). The MRB_E2RF1 catchments are based on a modified version of the U.S. Environmental Protection Agency's (USEPA) RF1_2 and include enhancements to support national and regional-scale surface-water quality modeling (Nolan and others, 2002; Brakebill and others, 2011). Data were compiled for every MRB_E2RF1 catchment for the conterminous United States covering New England and Mid-Atlantic (MRB1), South Atlantic-Gulf and Tennessee (MRB2), the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy (MRB3), the Missouri (MRB4), the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf (MRB5), the Rio Grande, Colorado, and the Great basin (MRB6), the Pacific Northwest (MRB7) river basins, and California (MRB8).","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/dds49107","usgsCitation":"Wieczorek, M., and LaMotte, A.E., 2010, Attributes for MRB_E2RF1 Catchments in Selected Major River Basins of the Conterminous United States: Contact Time, 2002: U.S. Geological Survey Data Series 491-07, Dataset, https://doi.org/10.3133/dds49107.","productDescription":"Dataset","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[],"links":[{"id":274332,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":274331,"type":{"id":16,"text":"Metadata"},"url":"https://water.usgs.gov/GIS/metadata/usgswrd/XML/mrb_e2rf1_contact.xml"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -127.910792,23.243486 ], [ -127.910792,51.657387 ], [ -65.327751,51.657387 ], [ -65.327751,23.243486 ], [ -127.910792,23.243486 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51d2a4e6e4b0ca1848338a1f","contributors":{"authors":[{"text":"Wieczorek, Michael mewieczo@usgs.gov","contributorId":2309,"corporation":false,"usgs":true,"family":"Wieczorek","given":"Michael","email":"mewieczo@usgs.gov","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":false,"id":480123,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"LaMotte, Andrew E. 0000-0002-1434-6518 alamotte@usgs.gov","orcid":"https://orcid.org/0000-0002-1434-6518","contributorId":2842,"corporation":false,"usgs":true,"family":"LaMotte","given":"Andrew","email":"alamotte@usgs.gov","middleInitial":"E.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":480124,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70004407,"text":"70004407 - 2010 - Evaluating propagation method performance over time with Bayesian updating: An application to incubator testing","interactions":[],"lastModifiedDate":"2018-02-06T12:45:42","indexId":"70004407","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Evaluating propagation method performance over time with Bayesian updating: An application to incubator testing","docAbstract":"In captive-rearing programs, small sample sizes can limit the quality of information on performance of propagation methods. Bayesian updating can be used to increase information on method performance over time. We demonstrate an application to incubator testing at USGS Patuxent Wildlife Research Center. A new type of incubator was purchased for use in the whooping crane (Grus americana) propagation program, which produces birds for release. We tested the new incubator for reliability, using sandhill crane (Grus canadensis) eggs as surrogates. We determined that the new incubator should result in hatching rates no more than 5% lower than the available incubators, with 95% confidence, before it would be used to incubate whooping crane eggs. In 2007, 5 healthy chicks hatched from 12 eggs in the new incubator, and 2 hatched from 5 in an available incubator, for a median posterior difference of <1%, but with a large 95% credible interval (-41%, 43%). In 2008, we implemented a double-blind evaluation method, where a veterinarian determined whether eggs produced chicks that, at hatching, had no apparent health problems that would impede future release. We used the 2007 estimates as priors in the 2008 analysis. In 2008, 7 normal chicks hatched from 15 eggs in the new incubator, and 11 hatched from 15 in an available incubator, for a median posterior difference of 19%, with 95% credible interval (-8%, 44%). The increased sample size has increased our understanding of incubator performance. While additional data will be collected, at this time the new incubator does not appear adequate for use with whooping crane eggs.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the Eleventh North American Crane Workshop","largerWorkSubtype":{"id":15,"text":"Monograph"},"conferenceTitle":"Eleventh North American Crane Workshop","conferenceDate":"September 23-27, 2008","conferenceLocation":"Wisconsin Dells, WI","language":"English","publisher":"International Crane Foundation","publisherLocation":"Baraboo, WI","usgsCitation":"Converse, S.J., Chandler, J.N., Olsen, G.H., and Shafer, C.C., 2010, Evaluating propagation method performance over time with Bayesian updating: An application to incubator testing, chap. of Proceedings of the Eleventh North American Crane Workshop, p. 110-117.","productDescription":"18 p.","startPage":"110","endPage":"117","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-010829","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":326566,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"UNITED STATES","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57b43944e4b03bcb01039fb5","contributors":{"editors":[{"text":"Hartup, Barry K.","contributorId":112921,"corporation":false,"usgs":true,"family":"Hartup","given":"Barry","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":645591,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Urbanek, Richard P.","contributorId":38400,"corporation":false,"usgs":true,"family":"Urbanek","given":"Richard","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":645592,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Converse, Sarah J. 0000-0002-3719-5441 sconverse@usgs.gov","orcid":"https://orcid.org/0000-0002-3719-5441","contributorId":3513,"corporation":false,"usgs":true,"family":"Converse","given":"Sarah","email":"sconverse@usgs.gov","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":645587,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chandler, J. N.","contributorId":173705,"corporation":false,"usgs":false,"family":"Chandler","given":"J.","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":645588,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Olsen, Glenn H. 0000-0002-7188-6203 golsen@usgs.gov","orcid":"https://orcid.org/0000-0002-7188-6203","contributorId":40918,"corporation":false,"usgs":true,"family":"Olsen","given":"Glenn","email":"golsen@usgs.gov","middleInitial":"H.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":645589,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shafer, C. C.","contributorId":173706,"corporation":false,"usgs":false,"family":"Shafer","given":"C.","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":645590,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70037559,"text":"70037559 - 2010 - Analysis of elevation changes detected from multi-temporal LiDAR surveys in forested landslide terrain in western Oregon","interactions":[],"lastModifiedDate":"2012-03-12T17:22:01","indexId":"70037559","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1574,"text":"Environmental & Engineering Geoscience","printIssn":"1078-7275","active":true,"publicationSubtype":{"id":10}},"title":"Analysis of elevation changes detected from multi-temporal LiDAR surveys in forested landslide terrain in western Oregon","docAbstract":"We examined elevation changes detected from two successive sets of Light Detection and Ranging (LiDAR) data in the northern Coast Range of Oregon. The first set of LiDAR data was acquired during leafon conditions and the second set during leaf-off conditions. We were able to successfully identify and map active landslides using a differential digital elevation model (DEM) created from the two LiDAR data sets, but this required the use of thresholds (0.50 and 0.75 m) to remove noise from the differential elevation data, visual pattern recognition of landslideinduced elevation changes, and supplemental QuickBird satellite imagery. After mapping, we field-verified 88 percent of the landslides that we had mapped with high confidence, but we could not detect active landslides with elevation changes of less than 0.50 m. Volumetric calculations showed that a total of about 18,100 m3 of material was missing from landslide areas, probably as a result of systematic negative elevation errors in the differential DEM and as a result of removal of material by erosion and transport. We also examined the accuracies of 285 leaf-off LiDAR elevations at four landslide sites using Global Positioning System and total station surveys. A comparison of LiDAR and survey data indicated an overall root mean square error of 0.50 m, a maximum error of 2.21 m, and a systematic error of 0.09 m. LiDAR ground-point densities were lowest in areas with young conifer forests and deciduous vegetation, which resulted in extensive interpolations of elevations in the leaf-on, bare-earth DEM. For optimal use of multi-temporal LiDAR data in forested areas, we recommend that all data sets be flown during leaf-off seasons.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Environmental and Engineering Geoscience","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.2113/gseegeosci.16.4.315","issn":"10787275","usgsCitation":"Burns, W., Coe, J.A., Kaya, B., and Ma, L., 2010, Analysis of elevation changes detected from multi-temporal LiDAR surveys in forested landslide terrain in western Oregon: Environmental & Engineering Geoscience, v. 16, no. 4, p. 315-341, https://doi.org/10.2113/gseegeosci.16.4.315.","startPage":"315","endPage":"341","numberOfPages":"27","costCenters":[],"links":[{"id":245919,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":217946,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.2113/gseegeosci.16.4.315"}],"volume":"16","issue":"4","noUsgsAuthors":false,"publicationDate":"2010-10-26","publicationStatus":"PW","scienceBaseUri":"5059eb11e4b0c8380cd48bc5","contributors":{"authors":[{"text":"Burns, W.J.","contributorId":32019,"corporation":false,"usgs":true,"family":"Burns","given":"W.J.","email":"","affiliations":[],"preferred":false,"id":461599,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coe, J. A.","contributorId":8867,"corporation":false,"usgs":true,"family":"Coe","given":"J.","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":461597,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kaya, B.S.","contributorId":100226,"corporation":false,"usgs":true,"family":"Kaya","given":"B.S.","email":"","affiliations":[],"preferred":false,"id":461600,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ma, Liwang","contributorId":29140,"corporation":false,"usgs":true,"family":"Ma","given":"Liwang","email":"","affiliations":[],"preferred":false,"id":461598,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70037408,"text":"70037408 - 2010 - Thematic accuracy of the NLCD 2001 land cover for the conterminous United States","interactions":[],"lastModifiedDate":"2018-03-08T13:06:31","indexId":"70037408","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"Thematic accuracy of the NLCD 2001 land cover for the conterminous United States","docAbstract":"The land-cover thematic accuracy of NLCD 2001 was assessed from a probability-sample of 15,000 pixels. Nationwide, NLCD 2001 overall Anderson Level II and Level I accuracies were 78.7% and 85.3%, respectively. By comparison, overall accuracies at Level II and Level I for the NLCD 1992 were 58% and 80%. Forest and cropland were two classes showing substantial improvements in accuracy in NLCD 2001 relative to NLCD 1992. NLCD 2001 forest and cropland user's accuracies were 87% and 82%, respectively, compared to 80% and 43% for NLCD 1992. Accuracy results are reported for 10 geographic regions of the United States, with regional overall accuracies ranging from 68% to 86% for Level II and from 79% to 91% at Level I. Geographic variation in class-specific accuracy was strongly associated with the phenomenon that regionally more abundant land-cover classes had higher accuracy. Accuracy estimates based on several definitions of agreement are reported to provide an indication of the potential impact of reference data error on accuracy. Drawing on our experience from two NLCD national accuracy assessments, we discuss the use of designs incorporating auxiliary data to more seamlessly quantify reference data quality as a means to further advance thematic map accuracy assessment.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2010.01.018","issn":"00344257","usgsCitation":"Wickham, J., Stehman, S., Fry, J., Smith, J., and Homer, C.G., 2010, Thematic accuracy of the NLCD 2001 land cover for the conterminous United States: Remote Sensing of Environment, v. 114, no. 6, p. 1286-1296, https://doi.org/10.1016/j.rse.2010.01.018.","productDescription":"11 p.","startPage":"1286","endPage":"1296","numberOfPages":"11","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":245133,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":217206,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.rse.2010.01.018"}],"volume":"114","issue":"6","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505bb1f0e4b08c986b3254d5","contributors":{"authors":[{"text":"Wickham, J.D.","contributorId":28329,"corporation":false,"usgs":true,"family":"Wickham","given":"J.D.","email":"","affiliations":[],"preferred":false,"id":460920,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stehman, S.V.","contributorId":91974,"corporation":false,"usgs":false,"family":"Stehman","given":"S.V.","email":"","affiliations":[{"id":27852,"text":"State University of New York, Syracuse","active":true,"usgs":false}],"preferred":false,"id":460924,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fry, J.A. 0000-0002-8466-9582","orcid":"https://orcid.org/0000-0002-8466-9582","contributorId":69260,"corporation":false,"usgs":true,"family":"Fry","given":"J.A.","affiliations":[],"preferred":false,"id":460923,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, J.H.","contributorId":49331,"corporation":false,"usgs":true,"family":"Smith","given":"J.H.","email":"","affiliations":[],"preferred":false,"id":460922,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Homer, Collin G. 0000-0003-4755-8135 homer@usgs.gov","orcid":"https://orcid.org/0000-0003-4755-8135","contributorId":2262,"corporation":false,"usgs":true,"family":"Homer","given":"Collin","email":"homer@usgs.gov","middleInitial":"G.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":460921,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70037414,"text":"70037414 - 2010 - A physiologically based toxicokinetic model for methylmercury in female American kestrels","interactions":[],"lastModifiedDate":"2018-10-20T09:05:08","indexId":"70037414","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"A physiologically based toxicokinetic model for methylmercury in female American kestrels","docAbstract":"A physiologically based toxicokinetic (PBTK) model was developed to describe the uptake, distribution, and elimination of methylmercury (CH 3Hg) in female American kestrels. The model consists of six tissue compartments corresponding to the brain, liver, kidney, gut, red blood cells, and remaining carcass. Additional compartments describe the elimination of CH3Hg to eggs and growing feathers. Dietary uptake of CH 3Hg was modeled as a diffusion-limited process, and the distribution of CH3Hg among compartments was assumed to be mediated by the flow of blood plasma. To the extent possible, model parameters were developed using information from American kestrels. Additional parameters were based on measured values for closely related species and allometric relationships for birds. The model was calibrated using data from dietary dosing studies with American kestrels. Good agreement between model simulations and measured CH3Hg concentrations in blood and tissues during the loading phase of these studies was obtained by fitting model parameters that control dietary uptake of CH 3Hg and possible hepatic demethylation. Modeled results tended to underestimate the observed effect of egg production on circulating levels of CH3Hg. In general, however, simulations were consistent with observed patterns of CH3Hg uptake and elimination in birds, including the dominant role of feather molt. This model could be used to extrapolate CH 3Hg kinetics from American kestrels to other bird species by appropriate reassignment of parameter values. Alternatively, when combined with a bioenergetics-based description, the model could be used to simulate CH 3Hg kinetics in a long-term environmental exposure.
","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Environmental Toxicology and Chemistry","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.1002/etc.241","issn":"07307268","usgsCitation":"Nichols, J., Bennett, R., Rossmann, R., French, J.B., and Sappington, K., 2010, A physiologically based toxicokinetic model for methylmercury in female American kestrels: Environmental Toxicology and Chemistry, v. 29, no. 8, p. 1854-1867, https://doi.org/10.1002/etc.241.","productDescription":"14 p.","startPage":"1854","endPage":"1867","numberOfPages":"14","costCenters":[{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":245163,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":217235,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/etc.241"}],"volume":"29","issue":"8","noUsgsAuthors":false,"publicationDate":"2010-08-01","publicationStatus":"PW","scienceBaseUri":"5059e4d9e4b0c8380cd46994","contributors":{"authors":[{"text":"Nichols, J.W.","contributorId":97290,"corporation":false,"usgs":true,"family":"Nichols","given":"J.W.","email":"","affiliations":[],"preferred":false,"id":460949,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bennett, R.S.","contributorId":16533,"corporation":false,"usgs":true,"family":"Bennett","given":"R.S.","email":"","affiliations":[],"preferred":false,"id":460947,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rossmann, R.","contributorId":54702,"corporation":false,"usgs":true,"family":"Rossmann","given":"R.","email":"","affiliations":[],"preferred":false,"id":460948,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"French, John B. 0000-0001-8901-7092 jbfrench@usgs.gov","orcid":"https://orcid.org/0000-0001-8901-7092","contributorId":377,"corporation":false,"usgs":true,"family":"French","given":"John","email":"jbfrench@usgs.gov","middleInitial":"B.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":460946,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sappington, K.G.","contributorId":8701,"corporation":false,"usgs":true,"family":"Sappington","given":"K.G.","email":"","affiliations":[],"preferred":false,"id":460945,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70037439,"text":"70037439 - 2010 - Stable isotope analysis and satellite tracking reveal interspecific resource partitioning of nonbreeding albatrosses off Alaska","interactions":[],"lastModifiedDate":"2012-03-12T17:22:08","indexId":"70037439","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1176,"text":"Canadian Journal of Zoology","active":true,"publicationSubtype":{"id":10}},"title":"Stable isotope analysis and satellite tracking reveal interspecific resource partitioning of nonbreeding albatrosses off Alaska","docAbstract":"Albatrosses (Diomedeidae) are the most threatened family of birds globally. The three North Pacific species (Phoebastria Reichenbach, 1853) are listed as either endangered or vulnerable, with the population of Short-tailed Albatross (Phoebastria albatrus (Pallas, 1769)) less than 1% of its historical size. All North Pacific albatross species do not currently breed sympatrically, yet they do co-occur at-sea during the nonbreeding season. We incorporated stable isotope analysis with the first simultaneous satellite-tracking study of all three North Pacific albatross species while sympatric on summer (nonbreeding season) foraging grounds off Alaska. Carbon isotope ratios and tracking data identify differences in primary foraging domains of continental shelf and slope waters for Short-tailed Albatrosses and Black-footed Albatrosses (Phoebastria nigripes (Audubon, 1839)) versus oceanic waters for Laysan Albatrosses (Phoebastria immutabilis (Roths-child, 1893)). Short-tailed and Black-footed albatrosses also fed at higher trophic levels than Laysan Albatrosses. The relative trophic position of Black-footed and Laysan albatrosses, however, appears to differ between nonbreeding and breeding seasons. Spatial segregation also occurred at a broader geographic scale, with Short-tailed Albatrosses ranging more north into the Bering Sea than Black-footed Albatrosses, which ranged more to the southeast, and Laysan Albatrosses more to the southwest. Differences in carbon isotope ratios among North Pacific albatross species during the nonbreeding season likely reflect the relative proportion of neritic (more carbon enriched) versus oceanic (carbon depleted) derived nutrients, and possible differential use of fishery discards, rather than latitudinal differences in distribution.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Canadian Journal of Zoology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.1139/Z10-002","issn":"00084301","usgsCitation":"Suryan, R., and Fischer, K., 2010, Stable isotope analysis and satellite tracking reveal interspecific resource partitioning of nonbreeding albatrosses off Alaska: Canadian Journal of Zoology, v. 88, no. 3, p. 299-305, https://doi.org/10.1139/Z10-002.","startPage":"299","endPage":"305","numberOfPages":"7","costCenters":[],"links":[{"id":217351,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1139/Z10-002"},{"id":245295,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"88","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505b9669e4b08c986b31b4bb","contributors":{"authors":[{"text":"Suryan, R.M.","contributorId":52919,"corporation":false,"usgs":true,"family":"Suryan","given":"R.M.","email":"","affiliations":[],"preferred":false,"id":461075,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fischer, K.N.","contributorId":32360,"corporation":false,"usgs":true,"family":"Fischer","given":"K.N.","email":"","affiliations":[],"preferred":false,"id":461074,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70037443,"text":"70037443 - 2010 - Embryo malposition as a potential mechanism for mercury-induced hatching failure in bird eggs","interactions":[],"lastModifiedDate":"2018-10-17T17:07:17","indexId":"70037443","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Embryo malposition as a potential mechanism for mercury-induced hatching failure in bird eggs","docAbstract":"We examined the prevalence of embryo malpositions and deformities in relation to total mercury (THg) and selenium (Se) concentrations in American avocet (Recurvirostra americana), black‐necked stilt (Himantopus mexicanus), and Forster's tern (Sterna forsteri) eggs in San Francisco Bay (CA, USA) during 2005 to 2007. Overall, 11% of embryos were malpositioned in eggs ≥18 d of age (n = 282) and 2% of embryos were deformed in eggs ≥13 d of age (n = 470). Considering only those eggs that failed to hatch (n = 62), malpositions occurred in 24% of eggs ≥18 d of age and deformities occurred in 7% of eggs ≥13 d of age. The probability of an embryo being malpositioned increased with egg THg concentrations in Forster's terns, but not in avocets or stilts. The probability of embryo deformity was not related to egg THg concentrations in any species. Using a reduced dataset with both Se and THg concentrations measured in eggs (n = 87), we found no interaction between Se and THg on the probability of an embryo being malpositioned or deformed. Results of the present study indicate that embryo malpositions were prevalent in waterbird eggs that failed to hatch and the likelihood of an embryo being malpositioned increased with egg THg concentrations in Forster's terns. We hypothesize that malpositioning of avian embryos may be one reason for mercury‐related hatching failure that occurs late in incubation, but further research is needed to elucidate this potential mechanism.
","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Environmental Toxicology and Chemistry","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"SETAC","doi":"10.1002/etc.208","issn":"07307268","usgsCitation":"Herring, G., Ackerman, J., and Eagles-Smith, C.A., 2010, Embryo malposition as a potential mechanism for mercury-induced hatching failure in bird eggs: Environmental Toxicology and Chemistry, v. 29, no. 8, p. 1788-1794, https://doi.org/10.1002/etc.208.","productDescription":"7 p.","startPage":"1788","endPage":"1794","numberOfPages":"7","costCenters":[{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":476067,"rank":10000,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/etc.208","text":"Publisher Index Page"},{"id":245297,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":217353,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/etc.208"}],"volume":"29","issue":"8","noUsgsAuthors":false,"publicationDate":"2010-08-01","publicationStatus":"PW","scienceBaseUri":"505a08e3e4b0c8380cd51ceb","contributors":{"authors":[{"text":"Herring, Garth 0000-0003-1106-4731 gherring@usgs.gov","orcid":"https://orcid.org/0000-0003-1106-4731","contributorId":4403,"corporation":false,"usgs":true,"family":"Herring","given":"Garth","email":"gherring@usgs.gov","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":461085,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ackerman, Joshua T. 0000-0002-3074-8322 jackerman@usgs.gov","orcid":"https://orcid.org/0000-0002-3074-8322","contributorId":147078,"corporation":false,"usgs":true,"family":"Ackerman","given":"Joshua T.","email":"jackerman@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":461084,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Eagles-Smith, Collin A. 0000-0003-1329-5285 ceagles-smith@usgs.gov","orcid":"https://orcid.org/0000-0003-1329-5285","contributorId":505,"corporation":false,"usgs":true,"family":"Eagles-Smith","given":"Collin","email":"ceagles-smith@usgs.gov","middleInitial":"A.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":461086,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70037574,"text":"70037574 - 2010 - Inter-regional comparison of land-use effects on stream metabolism","interactions":[],"lastModifiedDate":"2012-03-12T17:22:05","indexId":"70037574","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1696,"text":"Freshwater Biology","active":true,"publicationSubtype":{"id":10}},"title":"Inter-regional comparison of land-use effects on stream metabolism","docAbstract":"1. Rates of whole-system metabolism (production and respiration) are fundamental indicators of ecosystem structure and function. Although first-order, proximal controls are well understood, assessments of the interactions between proximal controls and distal controls, such as land use and geographic region, are lacking. Thus, the influence of land use on stream metabolism across geographic regions is unknown. Further, there is limited understanding of how land use may alter variability in ecosystem metabolism across regions.2. Stream metabolism was measured in nine streams in each of eight regions (n = 72) across the United States and Puerto Rico. In each region, three streams were selected from a range of three land uses: agriculturally influenced, urban-influenced, and reference streams. Stream metabolism was estimated from diel changes in dissolved oxygen concentrations in each stream reach with correction for reaeration and groundwater input.3. Gross primary production (GPP) was highest in regions with little riparian vegetation (sagebrush steppe in Wyoming, desert shrub in Arizona/New Mexico) and lowest in forested regions (North Carolina, Oregon). In contrast, ecosystem respiration (ER) varied both within and among regions. Reference streams had significantly lower rates of GPP than urban or agriculturally influenced streams.4. GPP was positively correlated with photosynthetically active radiation and autotrophic biomass. Multiple regression models compared using Akaike's information criterion (AIC) indicated GPP increased with water column ammonium and the fraction of the catchment in urban and reference land-use categories. Multiple regression models also identified velocity, temperature, nitrate, ammonium, dissolved organic carbon, GPP, coarse benthic organic matter, fine benthic organic matter and the fraction of all land-use categories in the catchment as regulators of ER.5. Structural equation modelling indicated significant distal as well as proximal control pathways including a direct effect of land-use on GPP as well as SRP, DIN, and PAR effects on GPP; GPP effects on autotrophic biomass, organic matter, and ER; and organic matter effects on ER.6. Overall, consideration of the data separated by land-use categories showed reduced inter-regional variability in rates of metabolism, indicating that the influence of agricultural and urban land use can obscure regional differences in stream metabolism. ?? 2010 Blackwell Publishing Ltd.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Freshwater Biology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.1111/j.1365-2427.2010.02422.x","issn":"00465070","usgsCitation":"Bernot, M.J., Sobota, D.J., Hall, R., Mulholland, P.J., Dodds, W.K., Webster, J., Tank, J.L., Ashkenas, L., Cooper, L.W., Dahm, C., Gregory, S., Grimm, N.B., Hamilton, S.K., Johnson, S.L., McDowell, W.H., Meyer, J., Peterson, B., Poole, G.C., Maurice, V.H., Arango, C., Beaulieu, J.J., Burgin, A.J., Crenshaw, C., Helton, A.M., Johnson, L., Merriam, J., Niederlehner, B., O’Brien, J.M., Potter, J.D., Sheibley, R., Thomas, S.M., and Wilson, K., 2010, Inter-regional comparison of land-use effects on stream metabolism: Freshwater Biology, v. 55, no. 9, p. 1874-1890, https://doi.org/10.1111/j.1365-2427.2010.02422.x.","startPage":"1874","endPage":"1890","numberOfPages":"17","costCenters":[],"links":[{"id":246042,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":218062,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/j.1365-2427.2010.02422.x"}],"volume":"55","issue":"9","noUsgsAuthors":false,"publicationDate":"2010-08-15","publicationStatus":"PW","scienceBaseUri":"505a3ca3e4b0c8380cd62ee6","contributors":{"authors":[{"text":"Bernot, M. J.","contributorId":18593,"corporation":false,"usgs":false,"family":"Bernot","given":"M.","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":461689,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sobota, D. J.","contributorId":15419,"corporation":false,"usgs":false,"family":"Sobota","given":"D.","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":461688,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hall, R.O.","contributorId":94890,"corporation":false,"usgs":true,"family":"Hall","given":"R.O.","affiliations":[],"preferred":false,"id":461714,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mulholland, P. J.","contributorId":89081,"corporation":false,"usgs":false,"family":"Mulholland","given":"P.","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":461711,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dodds, W. K.","contributorId":21297,"corporation":false,"usgs":false,"family":"Dodds","given":"W.","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":461693,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Webster, J.R.","contributorId":74475,"corporation":false,"usgs":true,"family":"Webster","given":"J.R.","email":"","affiliations":[],"preferred":false,"id":461707,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Tank, J. L.","contributorId":100214,"corporation":false,"usgs":false,"family":"Tank","given":"J.","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":461717,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ashkenas, L. R.","contributorId":14656,"corporation":false,"usgs":false,"family":"Ashkenas","given":"L. R.","affiliations":[],"preferred":false,"id":461687,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Cooper, L. 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Seven regionally continuous high amplitude reflections are defined which bound six seismic stratigraphic units consisting of multiple regionally discontinuous depositional sequences and parasequence sets, and enable an understanding of the evolution of this margin. Data reveal the progressive eastward progradation and aggradation of the Quaternary shelf. The early Pleistocene inner shelf occurs at a depth of ca. 20-40 m beneath the western part of the modern estuarine system (Pamlico Sound). A mid- to outer shelf lowstand terrace (also early Pleistocene) with shelf sand ridge deposits comprising parasequence sets within a transgressive systems tract, occurs at a deeper level (ca. 45-70 m) beneath the modern barrier island system (the Outer Banks) and northern Pamlico Sound. Seismic and foraminiferal paleoenvironmental data from cores indicate the occurrence of lowstand strandplain shoreline deposits on the early to middle Pleistocene shelf. Middle to late Pleistocene deposits occur above a prominent unconformity and marine flooding surface that truncates underlying units, and contain numerous filled fluvial valleys that are incised into the early and middle Pleistocene deposits. The stratigraphic framework suggests margin progradation and aggradation modified by an increase in the magnitude of sea-level fluctuations during the middle to late Pleistocene, expressed as falling stage, lowstand, transgressive and highstand systems tracts. Thick stratigraphic sequences occur within the middle Pleistocene section, suggesting the occurrence of high capacity fluvial point sources debouching into the area from the west and north. Furthermore, the antecedent topography plays a significant role in the evolution of the geomorphology and stratigraphy of this marginal system. ?? 2009 Elsevier B.V.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Marine Geology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.1016/j.margeo.2009.10.007","issn":"00253227","usgsCitation":"Mallinson, D.J., Culver, S., Riggs, S., Thieler, E., Foster, D., Wehmiller, J., Farrell, K., and Pierson, J., 2010, Regional seismic stratigraphy and controls on the Quaternary evolution of the Cape Hatteras region of the Atlantic passive margin, USA: Marine Geology, v. 268, no. 1-4, p. 16-33, https://doi.org/10.1016/j.margeo.2009.10.007.","productDescription":"18 p.","startPage":"16","endPage":"33","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":244642,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":216756,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.margeo.2009.10.007"}],"volume":"268","issue":"1-4","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50e4a559e4b0e8fec6cdbe0a","contributors":{"authors":[{"text":"Mallinson, D. 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Using the Antarctic Dome C site (75°06′S, 123°21′E, elevation 3.2 km) for satellite radiometric calibration and validation (Cal/Val) is of great interest owing to its unique location and characteristics. The site surface is covered with uniformly distributed permanent snow, and the atmospheric effect is small and relatively constant. In this study, the long-term stability and spectral characteristics of this site are evaluated using well-calibrated satellite instruments such as the Moderate Resolution Imaging Spectroradiometer (MODIS) and Sea-viewing Wide Field-of-view Sensor (SeaWiFS). Preliminary results show that despite a few limitations, the site in general is stable in the long term, the bidirectional reflectance distribution function (BRDF) model works well, and the site is most suitable for the Cal/Val of reflective solar bands in the 0.4–1.0 µm range. It was found that for the past decade, the reflectivity change of the site is within 1.35% at 0.64 µm, and interannual variability is within 2%. The site is able to resolve calibration biases between instruments at a level of ~1%. The usefulness of the site is demonstrated by comparing observations from seven satellite instruments involving four space agencies, including OrbView-2–SeaWiFS, Terra–Aqua MODIS, Earth Observing 1 (EO-1) – Hyperion, Meteorological Operational satellite programme (MetOp) – Advanced Very High Resolution Radiometer (AVHRR), Envisat Medium Resolution Imaging Spectrometer (MERIS) – dvanced Along-Track Scanning Radiometer (AATSR), and Landsat 7 Enhanced Thematic Mapper Plus (ETM+). Dome C is a promising candidate site for climate quality calibration of satellite radiometers towards more consistent satellite measurements, as part of the framework for climate change detection and data quality assurance for the Global Earth Observation System of Systems (GEOSS).","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Canadian Journal of Remote Sensing","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Canadian Remote Sensing Society","doi":"10.5589/m10-075","issn":"07038992","usgsCitation":"Cao, C., Uprety, S., Xiong, J., Wu, A., Jing, P., Smith, D., Chander, G., Fox, N., and Ungar, S., 2010, Establishing the Antarctic Dome C community reference standard site towards consistent measurements from Earth observation satellites: Canadian Journal of Remote Sensing, v. 36, no. 5, p. 498-513, https://doi.org/10.5589/m10-075.","productDescription":"16 p.","startPage":"498","endPage":"513","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":218572,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.5589/m10-075"},{"id":246595,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"36","issue":"5","noUsgsAuthors":false,"publicationDate":"2014-06-02","publicationStatus":"PW","scienceBaseUri":"505a0a64e4b0c8380cd52338","contributors":{"authors":[{"text":"Cao, C.","contributorId":37944,"corporation":false,"usgs":true,"family":"Cao","given":"C.","email":"","affiliations":[],"preferred":false,"id":454680,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Uprety, S.","contributorId":65345,"corporation":false,"usgs":true,"family":"Uprety","given":"S.","affiliations":[],"preferred":false,"id":454686,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Xiong, J.","contributorId":58472,"corporation":false,"usgs":true,"family":"Xiong","given":"J.","email":"","affiliations":[],"preferred":false,"id":454684,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wu, A.","contributorId":44019,"corporation":false,"usgs":true,"family":"Wu","given":"A.","email":"","affiliations":[],"preferred":false,"id":454682,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jing, P.","contributorId":38859,"corporation":false,"usgs":true,"family":"Jing","given":"P.","email":"","affiliations":[],"preferred":false,"id":454681,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Smith, D.","contributorId":60978,"corporation":false,"usgs":true,"family":"Smith","given":"D.","affiliations":[],"preferred":false,"id":454685,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Chander, G.","contributorId":51449,"corporation":false,"usgs":true,"family":"Chander","given":"G.","affiliations":[],"preferred":false,"id":454683,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Fox, N.","contributorId":90905,"corporation":false,"usgs":true,"family":"Fox","given":"N.","email":"","affiliations":[],"preferred":false,"id":454687,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Ungar, S.","contributorId":15413,"corporation":false,"usgs":true,"family":"Ungar","given":"S.","affiliations":[],"preferred":false,"id":454679,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70037144,"text":"70037144 - 2010 - Small mammals associated with colonies of black-tailed prairie dogs (Cynomys ludovicianus) in the Southern High Plains","interactions":[],"lastModifiedDate":"2012-03-12T17:22:07","indexId":"70037144","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3451,"text":"Southwestern Naturalist","active":true,"publicationSubtype":{"id":10}},"title":"Small mammals associated with colonies of black-tailed prairie dogs (Cynomys ludovicianus) in the Southern High Plains","docAbstract":"We compared diversity and abundance of small mammals at colonies of black-tailed prairie dogs (Cynomys ludovicianus) and paired non-colony sites. Of colonies of black-tailed prairie dogs in our study area, >80 were on slopes of playa lakes; thus, we used sites of colonies and non-colonies that were on slopes of playa lakes. We trapped small mammals on 29 pairs of sites. Overall abundance did not differ between types of sites, but some taxa exhibited associations with colonies (Onychomys leucogaster) or non-colonies (Chaetodipus hispidus, Reithrodontomys, Sigmodon hispidus). Diversity and evenness of small mammals did not differ between colonies and non-colonies in 2002, but were higher on non-colonies in 2003. Although we may not have detected some rare or infrequently occurring species, our data reveal differences in diversity and evenness of more common species among the types of sites. Prairie dogs are touted as a keystone species with their colonies associated with a greater faunal diversity than adjacent lands. Our findings contradict several studies reporting greater diversity and abundance of small mammals at colonies of prairie dogs. We suggest that additional research across a wider landscape and incorporating landscape variables beyond the immediate trapping plot may further elucidate interspecific associations between black-tailed prairie dogs and species of small rodents.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Southwestern Naturalist","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.1894/CLG-23.1","issn":"00384909","usgsCitation":"Pruett, A., Boal, C.W., Wallace, M., Whitlaw, H.A., and Ray, J., 2010, Small mammals associated with colonies of black-tailed prairie dogs (Cynomys ludovicianus) in the Southern High Plains: Southwestern Naturalist, v. 55, no. 1, p. 50-56, https://doi.org/10.1894/CLG-23.1.","startPage":"50","endPage":"56","numberOfPages":"7","costCenters":[],"links":[{"id":244960,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":217049,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1894/CLG-23.1"}],"volume":"55","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505b9188e4b08c986b31996c","contributors":{"authors":[{"text":"Pruett, A.L.","contributorId":18606,"corporation":false,"usgs":true,"family":"Pruett","given":"A.L.","email":"","affiliations":[],"preferred":false,"id":459594,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boal, C. 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