{"pageNumber":"630","pageRowStart":"15725","pageSize":"25","recordCount":46883,"records":[{"id":70038468,"text":"70038468 - 2012 - Elk migration patterns and human activity influence wolf habitat use in the Greater Yellowstone Ecosystem","interactions":[],"lastModifiedDate":"2017-05-05T11:13:30","indexId":"70038468","displayToPublicDate":"2012-07-27T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Elk migration patterns and human activity influence wolf habitat use in the Greater Yellowstone Ecosystem","docAbstract":"<p>Identifying the ecological dynamics underlying human&ndash;wildlife conflicts is important for the management and conservation of wildlife populations. In landscapes still occupied by large carnivores, many ungulate prey species migrate seasonally, yet little empirical research has explored the relationship between carnivore distribution and ungulate migration strategy. In this study, we evaluate the influence of elk (<i>Cervus elaphus</i>) distribution and other landscape features on wolf (<i>Canis lupus</i>) habitat use in an area of chronic wolf&ndash;livestock conflict in the Greater Yellowstone Ecosystem, USA. Using three years of fine-scale wolf (<i>n</i> = 14) and elk (<i>n</i> = 81) movement data, we compared the seasonal habitat use of wolves in an area dominated by migratory elk with that of wolves in an adjacent area dominated by resident elk. Most migratory elk vacate the associated winter wolf territories each summer via a 40&ndash;60 km migration, whereas resident elk remain accessible to wolves year-round. We used a generalized linear model to compare the relative probability of wolf use as a function of GIS-based habitat covariates in the migratory and resident elk areas. Although wolves in both areas used elk-rich habitat all year, elk density in summer had a weaker influence on the habitat use of wolves in the migratory elk area than the resident elk area. Wolves employed a number of alternative strategies to cope with the departure of migratory elk. Wolves in the two areas also differed in their disposition toward roads. In winter, wolves in the migratory elk area used habitat close to roads, while wolves in the resident elk area avoided roads. In summer, wolves in the migratory elk area were indifferent to roads, while wolves in resident elk areas strongly avoided roads, presumably due to the location of dens and summering elk combined with different traffic levels. Study results can help wildlife managers to anticipate the movements and establishment of wolf packs as they expand into areas with migratory or resident prey populations, varying levels of human activity, and front-country rangelands with potential for conflicts with livestock.</p>","language":"English","publisher":"ESA","doi":"10.1890/11-1829.1","usgsCitation":"Nelson, A., Kauffman, M., Middleton, A., Jimenez, M., McWhirter, D., Barber, J., and Gerow, K., 2012, Elk migration patterns and human activity influence wolf habitat use in the Greater Yellowstone Ecosystem: Ecological Applications, v. 22, no. 8, p. 2293-2307, https://doi.org/10.1890/11-1829.1.","productDescription":"15 p.","startPage":"2293","endPage":"2307","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-033306","costCenters":[{"id":683,"text":"Wyoming Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true}],"links":[{"id":259201,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":259197,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1890/11-1829.1","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Wyoming","city":"Cody","otherGeospatial":"Yellowstone National Park","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -110.4985,44.3159 ], [ -110.4985,45.0003 ], [ -108.9289,45.0003 ], [ -108.9289,44.3159 ], [ -110.4985,44.3159 ] ] ] } } ] }","volume":"22","issue":"8","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a08dde4b0c8380cd51cd7","contributors":{"authors":[{"text":"Nelson, Abigail","contributorId":47258,"corporation":false,"usgs":true,"family":"Nelson","given":"Abigail","affiliations":[],"preferred":false,"id":464304,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kauffman, Matthew J. 0000-0003-0127-3900 mkauffman@usgs.gov","orcid":"https://orcid.org/0000-0003-0127-3900","contributorId":2963,"corporation":false,"usgs":true,"family":"Kauffman","given":"Matthew J.","email":"mkauffman@usgs.gov","affiliations":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"preferred":false,"id":464300,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Middleton, Arthur D.","contributorId":99440,"corporation":false,"usgs":true,"family":"Middleton","given":"Arthur D.","affiliations":[],"preferred":false,"id":464306,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jimenez, Mike","contributorId":33785,"corporation":false,"usgs":true,"family":"Jimenez","given":"Mike","email":"","affiliations":[],"preferred":false,"id":464302,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McWhirter, Douglas","contributorId":7577,"corporation":false,"usgs":true,"family":"McWhirter","given":"Douglas","affiliations":[],"preferred":false,"id":464301,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Barber, Jarrett","contributorId":94935,"corporation":false,"usgs":true,"family":"Barber","given":"Jarrett","affiliations":[],"preferred":false,"id":464305,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gerow, Ken","contributorId":40870,"corporation":false,"usgs":true,"family":"Gerow","given":"Ken","email":"","affiliations":[],"preferred":false,"id":464303,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70038169,"text":"70038169 - 2012 - Hybrid analysis of multiaxis electromagnetic data for discrimination of munitions and explosives of concern","interactions":[],"lastModifiedDate":"2012-07-28T01:01:41","indexId":"70038169","displayToPublicDate":"2012-07-27T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1803,"text":"Geophysical Journal International","active":true,"publicationSubtype":{"id":10}},"title":"Hybrid analysis of multiaxis electromagnetic data for discrimination of munitions and explosives of concern","docAbstract":"The remediation of land containing munitions and explosives of concern, otherwise known as unexploded ordnance, is an ongoing problem facing the U.S. Department of Defense and similar agencies worldwide that have used or are transferring training ranges or munitions disposal areas to civilian control. The expense associated with cleanup of land previously used for military training and war provides impetus for research towards enhanced discrimination of buried unexploded ordnance. Towards reducing that expense, a multiaxis electromagnetic induction data collection and software system, called ALLTEM, was designed and tested with support from the U.S. Department of Defense Environmental Security Technology Certification Program. ALLTEM is an on-time time-domain system that uses a continuous triangle-wave excitation to measure the target-step response rather than traditional impulse response. The system cycles through three orthogonal transmitting loops and records a total of 19 different transmitting and receiving loop combinations with a nominal spatial data sampling interval of 20 cm. Recorded data are pre-processed and then used in a hybrid discrimination scheme involving both data-driven and numerical classification techniques. The data-driven classification scheme is accomplished in three steps. First, field observations are used to train a type of unsupervised artificial neural network, a self-organizing map (SOM). Second, the SOM is used to simultaneously estimate target parameters (depth, azimuth, inclination, item type and weight) by iterative minimization of the topographic error vectors. Third, the target classification is accomplished by evaluating histograms of the estimated parameters. The numerical classification scheme is also accomplished in three steps. First, the Biot&ndash;Savart law is used to model the primary magnetic fields from the transmitter coils and the secondary magnetic fields generated by currents induced in the target materials in the ground. Second, the target response is modelled by three orthogonal dipoles from prolate, oblate and triaxial ellipsoids with one long axis and two shorter axes. Each target consists of all three dipoles. Third, unknown target parameters are determined by comparing modelled to measured target responses. By comparing the rms error among the self-organizing map and numerical classification results, we achieved greater than 95 per cent detection and correct classification of the munitions and explosives of concern at the direct fire and indirect fire test areas at the UXO Standardized Test Site at the Aberdeen Proving Ground, Maryland in 2010.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Geophysical Journal International","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","publisherLocation":"Hoboken, NJ","doi":"10.1111/j.1365-246X.2012.05522.x","usgsCitation":"Friedel, M., Asch, T., and Oden, C., 2012, Hybrid analysis of multiaxis electromagnetic data for discrimination of munitions and explosives of concern: Geophysical Journal International, v. 190, no. 2, p. 960-980, https://doi.org/10.1111/j.1365-246X.2012.05522.x.","productDescription":"21 p.","startPage":"960","endPage":"980","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":474402,"rank":10000,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/j.1365-246x.2012.05522.x","text":"Publisher Index Page"},{"id":259230,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":259223,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/j.1365-246X.2012.05522.x","linkFileType":{"id":5,"text":"html"}}],"volume":"190","issue":"2","noUsgsAuthors":false,"publicationDate":"2012-05-25","publicationStatus":"PW","scienceBaseUri":"505a32bde4b0c8380cd5ea29","contributors":{"authors":[{"text":"Friedel, M.J.","contributorId":90823,"corporation":false,"usgs":true,"family":"Friedel","given":"M.J.","email":"","affiliations":[],"preferred":false,"id":463582,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Asch, T.H.","contributorId":90552,"corporation":false,"usgs":true,"family":"Asch","given":"T.H.","email":"","affiliations":[],"preferred":false,"id":463581,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Oden, C.","contributorId":87796,"corporation":false,"usgs":true,"family":"Oden","given":"C.","email":"","affiliations":[],"preferred":false,"id":463580,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70039212,"text":"ds695 - 2012 - Concentrations of selected metals in Quaternary-age fluvial deposits along the lower Cheyenne and middle Belle Fourche Rivers, western South Dakota, 2009-10","interactions":[],"lastModifiedDate":"2022-06-08T19:11:34.250622","indexId":"ds695","displayToPublicDate":"2012-07-26T00:00:00","publicationYear":"2012","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":"695","title":"Concentrations of selected metals in Quaternary-age fluvial deposits along the lower Cheyenne and middle Belle Fourche Rivers, western South Dakota, 2009-10","docAbstract":"The headwaters of the Cheyenne and Belle Fourche Rivers drain the Black Hills of South Dakota and Wyoming, an area that has been affected by mining and ore-milling operations since the discovery of gold in 1875. A tributary to the Belle Fourche River is Whitewood Creek, which drains the area of the Homestake Mine, a gold mine that operated from 1876 to 2001. Tailings discharged into Whitewood Creek contained arsenopyrite, an arsenic-rich variety of pyrite associated with gold ore, and mercury used as an amalgam during the gold-extraction process. Approximately 18 percent of the tailings that were discharged remain in fluvial deposits on the flood plain along Whitewood Creek, and approximately 25 percent remain in fluvial deposits on the flood plain along the Belle Fourche River, downstream from Whitewood Creek. In 1983, a 29-kilometer (18-mile) reach of Whitewood Creek and the adjacent flood plain was included in the U.S. Environmental Protection Agency's National Priority List of the Comprehensive Environmental Response, Compensation, and Liability Act of 1980, commonly referred to as a \"Superfund site.\" Listing of this reach of Whitewood Creek was primarily in response to arsenic toxicity of fluvial deposits on the flood plain. Lands along the lower Cheyenne River were transferred to adjoining States and Tribes in response to the Water Resources Development Act (WRDA) of 1999. An amendment in 2000 to WRDA required a study of sediment contamination of the Cheyenne River. In response to the WRDA amendment, the U.S. Geological Survey completed field sampling of reference sites (not affected by mine-tailing disposal) along the lower Belle Fourche and lower Cheyenne Rivers. Reference sites were located on stream terraces that were elevated well above historical stream stages to ensure no contamination from historical mining activity. Sampling of potentially contaminated sites was performed on transects of the active flood plain and adjacent terraces that could potentially be inundated during high-flow events. Sampling began in 2009 and was completed in 2010. A total of 74 geochemical samples were collected from fluvial deposits at reference sites, and 473 samples were collected from potentially contaminated sites. Sediment samples collected were analyzed for 23 metals, including arsenic and mercury. Sequential replicate, split duplicate, and field quality-control samples were analyzed for quality assurance of data-collection methods. The metal concentrations in sediment samples and location information are presented in this report in electronic format (Microsoft Excel), along with non-parametric summary statistics of those data. Cross-sectional topography is graphed with arsenic and mercury concentrations on transects at the potentially contaminated sites. The mean arsenic concentration in reference sediment samples was 8 milligrams per kilogram (mg/kg), compared to 250, 650, and 76 mg/kg for potentially contaminated sediment samples at the surface of the middle Belle Fourche River site, the subsurface of the middle Belle Fourche River site, and the surface of the lower Cheyenne River site, respectively. The mean mercury concentration in reference sediment samples was 16 micrograms per kilogram (&mu;g/kg), compared to 130, 370, and 71 &mu;g/kg for potentially contaminated sediment samples at the surface of the middle Belle Fourche River site, the subsurface of the middle Belle Fourche River site, and the surface of the lower Cheyenne River site, respectively.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds695","collaboration":"Prepared in cooperation with the Cheyenne River Sioux Tribe","usgsCitation":"Stamm, J., and Hoogestraat, G., 2012, Concentrations of selected metals in Quaternary-age fluvial deposits along the lower Cheyenne and middle Belle Fourche Rivers, western South Dakota, 2009-10: U.S. Geological Survey Data Series 695, Report: vi, 29 p.; Table 1: Excel file; Table 2: Excel file, https://doi.org/10.3133/ds695.","productDescription":"Report: vi, 29 p.; Table 1: Excel file; Table 2: Excel file","onlineOnly":"Y","costCenters":[{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":259158,"rank":299,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/695/ds695.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":259164,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds_695.JPG"},{"id":259157,"rank":99,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/695/","linkFileType":{"id":5,"text":"html"}}],"projection":"Universal Transverse Mercator, Zone 13","country":"United States","state":"South Dakota","otherGeospatial":"Belle Fourche River;Cheyenne River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -103.11749999999999,44.06666666666667 ], [ -103.11749999999999,44.56666666666667 ], [ -100,44.56666666666667 ], [ -100,44.06666666666667 ], [ -103.11749999999999,44.06666666666667 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059f99ae4b0c8380cd4d6bf","contributors":{"authors":[{"text":"Stamm, John F. 0000-0002-3404-2933 jstamm@usgs.gov","orcid":"https://orcid.org/0000-0002-3404-2933","contributorId":2859,"corporation":false,"usgs":true,"family":"Stamm","given":"John F.","email":"jstamm@usgs.gov","affiliations":[{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true}],"preferred":false,"id":465791,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hoogestraat, Galen K.","contributorId":22442,"corporation":false,"usgs":true,"family":"Hoogestraat","given":"Galen K.","affiliations":[],"preferred":false,"id":465792,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70038265,"text":"70038265 - 2012 - Combined sewer overflows: an environmental source of hormones and wastewater micropollutants","interactions":[],"lastModifiedDate":"2012-07-27T01:01:50","indexId":"70038265","displayToPublicDate":"2012-07-26T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Combined sewer overflows: an environmental source of hormones and wastewater micropollutants","docAbstract":"Data were collected at a wastewater treatment plant (WWTP) in Burlington, Vermont, USA, (serving 30,000 people) to assess the relative contribution of CSO (combined sewer overflow) bypass flows and treated wastewater effluent to the load of steroid hormones and other wastewater micropollutants (WMPs) from a WWTP to a lake. Flow-weighted composite samples were collected over a 13 month period at this WWTP from CSO bypass flows or plant influent flows (<i>n</i> = 28) and treated effluent discharges (<i>n</i> = 22). Although CSO discharges represent 10% of the total annual water discharge (CSO plus treated plant effluent discharges) from the WWTP, CSO discharges contribute 40&ndash;90% of the annual load for hormones and WMPs with high (>90%) wastewater treatment removal efficiency. By contrast, compounds with low removal efficiencies (<90%) have less than 10% of annual load contributed by CSO discharges. Concentrations of estrogens, androgens, and WMPs generally are 10 times higher in CSO discharges compared to treated wastewater discharges. Compound concentrations in samples of CSO discharges generally decrease with increasing flow because of wastewater dilution by rainfall runoff. By contrast, concentrations of hormones and many WMPs in samples from treated discharges can increase with increasing flow due to decreasing removal efficiency.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Environmental Science and Technology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"ACS Publications","publisherLocation":"Washington, D.C.","doi":"10.1021/es3001294","usgsCitation":"Phillips, P.J., Chalmers, A., Gray, J., Kolpin, D., Foreman, W., and Wall, G.R., 2012, Combined sewer overflows: an environmental source of hormones and wastewater micropollutants: Environmental Science & Technology, v. 46, no. 10, p. 5336-5343, https://doi.org/10.1021/es3001294.","productDescription":"8 p.","startPage":"5336","endPage":"5343","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":474406,"rank":10000,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1021/es3001294","text":"Publisher Index Page"},{"id":259179,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":259171,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1021/es3001294","linkFileType":{"id":5,"text":"html"}}],"volume":"46","issue":"10","noUsgsAuthors":false,"publicationDate":"2012-04-27","publicationStatus":"PW","scienceBaseUri":"5059f7dae4b0c8380cd4cd27","contributors":{"authors":[{"text":"Phillips, P. J.","contributorId":31728,"corporation":false,"usgs":true,"family":"Phillips","given":"P.","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":463774,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chalmers, A.T. 0000-0002-5199-8080","orcid":"https://orcid.org/0000-0002-5199-8080","contributorId":63576,"corporation":false,"usgs":true,"family":"Chalmers","given":"A.T.","affiliations":[],"preferred":false,"id":463775,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gray, J.L.","contributorId":18566,"corporation":false,"usgs":true,"family":"Gray","given":"J.L.","email":"","affiliations":[],"preferred":false,"id":463773,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kolpin, D.W.","contributorId":87565,"corporation":false,"usgs":true,"family":"Kolpin","given":"D.W.","email":"","affiliations":[],"preferred":false,"id":463776,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Foreman, W.T.","contributorId":94684,"corporation":false,"usgs":true,"family":"Foreman","given":"W.T.","email":"","affiliations":[],"preferred":false,"id":463778,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wall, G. R.","contributorId":93652,"corporation":false,"usgs":true,"family":"Wall","given":"G.","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":463777,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70003559,"text":"70003559 - 2012 - By the numbers: how is recovery defined by the U.S. Endangered Species Act?","interactions":[],"lastModifiedDate":"2015-06-05T11:33:26","indexId":"70003559","displayToPublicDate":"2012-07-26T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":997,"text":"BioScience","active":true,"publicationSubtype":{"id":10}},"title":"By the numbers: how is recovery defined by the U.S. Endangered Species Act?","docAbstract":"<p>Nearly 40 years after passage of the US Endangered Species Act, the prospects for listed species remain dim because they are too severely imperiled by the time they receive the act's protection. Even if threats are abated, the low abundances required for recovery often preclude a high probability of persistence. The lack of sufficient data for setting recovery objectives also remains a barrier. Delisting is considered possible for only 74% of the 1173 species with recovery plans&mdash;92% of threatened and 69% of endangered species. The median number of populations required for delisting (8) was at or below the historical numbers for 64% and at or below the numbers at listing for 37% of the species. The median number of individuals required for recovery (2400) exceeded the abundances at listing for 93% of the species, but most were below the levels considered necessary for long-term persistence, especially in changing environments.</p>","language":"English","publisher":"University of California Press","doi":"10.1525/bio.2012.62.7.7","usgsCitation":"Neel, M.C., Leidner, A., Haines, A., Goble, D.D., and Scott, J.M., 2012, By the numbers: how is recovery defined by the U.S. Endangered Species Act?: BioScience, v. 62, no. 7, p. 646-657, https://doi.org/10.1525/bio.2012.62.7.7.","productDescription":"12 p.","startPage":"646","endPage":"657","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[],"links":[{"id":474403,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1525/bio.2012.62.7.7","text":"Publisher Index Page"},{"id":259173,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"62","issue":"7","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059f2bee4b0c8380cd4b331","contributors":{"authors":[{"text":"Neel, Maile C.","contributorId":26052,"corporation":false,"usgs":true,"family":"Neel","given":"Maile","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":347735,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Leidner, Allison K.","contributorId":92909,"corporation":false,"usgs":true,"family":"Leidner","given":"Allison K.","affiliations":[],"preferred":false,"id":347737,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haines, Aaron","contributorId":37593,"corporation":false,"usgs":true,"family":"Haines","given":"Aaron","affiliations":[],"preferred":false,"id":347736,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Goble, Dale D.","contributorId":95323,"corporation":false,"usgs":true,"family":"Goble","given":"Dale","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":347738,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Scott, J. Michael","contributorId":98877,"corporation":false,"usgs":true,"family":"Scott","given":"J.","email":"","middleInitial":"Michael","affiliations":[],"preferred":false,"id":347739,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70039197,"text":"sim3216 - 2012 - Flood-inundation maps for the West Branch Delaware River, Delhi, New York, 2012","interactions":[],"lastModifiedDate":"2012-07-26T01:02:11","indexId":"sim3216","displayToPublicDate":"2012-07-25T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3216","title":"Flood-inundation maps for the West Branch Delaware River, Delhi, New York, 2012","docAbstract":"Digital flood-inundation maps for a 5-mile reach of the West Branch Delaware River through the Village and part of the Town of Delhi, New York, were created by the U.S. Geological Survey (USGS) in cooperation with the Village of Delhi, the Delaware County Soil and Water Conservation District, and the Delaware County Planning Department. The inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation/ and the Federal Flood Inundation Mapper Web site at http://wim.usgs.gov/FIMI/FloodInundationMapper.html, depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) referenced to the USGS streamgage at West Branch Delaware River upstream from Delhi, N.Y. (station number 01421900).\r\nIn this study, flood profiles were computed for the stream reach by means of a one-dimensional step-backwater model that had been used to produce the flood insurance rate maps for the most recent flood insurance study for the Town and Village of Delhi. This hydraulic model was used to compute 10 water-surface profiles for flood stages at 1-foot (ft) intervals referenced to the streamgage datum and ranging from 7 ft or near bankfull to 16 ft, which exceeds the stages that correspond to both the estimated 0.2-percent annual-exceedance-probability flood (500-year recurrence interval flood) and the maximum recorded peak flow. The simulated water-surface profiles were then combined with a geographic information system (GIS) digital elevation model, which was derived from Light Detection and Ranging (LiDAR) data with a 1.2-ft (0.61-ft root mean squared error) vertical accuracy and 3.3-ft (1-meter) horizontal resolution, to delineate the area flooded at each water level. A map that was produced using this method to delineate the inundated area for the flood that occurred on August 28, 2011, agreed well with highwater marks that had been located in the field using a global positioning system. The availability of the 10 flood-inundation maps on the USGS Flood Inundation Mapping Science Web site, along with Internet information regarding current stage from the USGS streamgage, will provide emergency management personnel and residents with information that is critical for flood-response activities, such as evacuations and road closures, as well as for post-flood recovery efforts.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3216","usgsCitation":"Coon, W.F., and Breaker, B.K., 2012, Flood-inundation maps for the West Branch Delaware River, Delhi, New York, 2012: U.S. Geological Survey Scientific Investigations Map 3216, Pamphlet: vi, 9 p.; 10 Sheets; Sheet 1: 17 inches x 22 inches, Sheet 2: 17 inches x 22 inches, Sheet 3: 17 inches x 22 inches, Sheet 4: 17 inches x 22 inches, Sheet 5: 17 inches x 22 inches, Sheet 6: 17 inches x 22 inches, Sheet 7: 17 inches x 22 inches, Sheet 8: 17 inches x 22 inches, Sheet 9: 17 inches x 22 inches, Sheet 10: 17 inches x 22 inches; Downloads Directory, https://doi.org/10.3133/sim3216.","productDescription":"Pamphlet: vi, 9 p.; 10 Sheets; Sheet 1: 17 inches x 22 inches, Sheet 2: 17 inches x 22 inches, Sheet 3: 17 inches x 22 inches, Sheet 4: 17 inches x 22 inches, Sheet 5: 17 inches x 22 inches, Sheet 6: 17 inches x 22 inches, Sheet 7: 17 inches x 22 inches, Sheet 8: 17 inches x 22 inches, Sheet 9: 17 inches x 22 inches, Sheet 10: 17 inches x 22 inches; Downloads Directory","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":259150,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim_3216.png"},{"id":259153,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3216/pdf/sim3216-pamphlet.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":259140,"rank":400,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3216/pdf/sim3216-sheet01.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":259142,"rank":401,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3216/pdf/sim3216-sheet03.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":259143,"rank":402,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3216/pdf/sim3216-sheet04.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":259144,"rank":403,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3216/pdf/sim3216-sheet05.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":259145,"rank":404,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3216/pdf/sim3216-sheet06.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":259149,"rank":405,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3216/pdf/sim3216-sheet10.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":259138,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3216/","linkFileType":{"id":5,"text":"html"}},{"id":259139,"rank":9999,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sim/3216/downloads/","linkFileType":{"id":5,"text":"html"}},{"id":259141,"rank":401,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3216/pdf/sim3216-sheet02.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":259146,"rank":406,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3216/pdf/sim3216-sheet07.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":259147,"rank":407,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3216/pdf/sim3216-sheet08.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":259148,"rank":408,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3216/pdf/sim3216-sheet09.pdf","linkFileType":{"id":1,"text":"pdf"}}],"datum":"North American Datum of 1983","country":"United States","state":"New York","county":"Delaware;Schoharie","city":"Delhi","otherGeospatial":"Catskill Mountain;Elk Creek;Falls Creek;Steele Brook","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -74.930086,42.258028 ], [ -74.930086,42.303232 ], [ -74.872077,42.303232 ], [ -74.872077,42.258028 ], [ -74.930086,42.258028 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a1169e4b0c8380cd53fb4","contributors":{"authors":[{"text":"Coon, William F. 0000-0002-7007-7797 wcoon@usgs.gov","orcid":"https://orcid.org/0000-0002-7007-7797","contributorId":1765,"corporation":false,"usgs":true,"family":"Coon","given":"William","email":"wcoon@usgs.gov","middleInitial":"F.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":465765,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Breaker, Brian K. 0000-0002-1985-4992 bbreaker@usgs.gov","orcid":"https://orcid.org/0000-0002-1985-4992","contributorId":4331,"corporation":false,"usgs":true,"family":"Breaker","given":"Brian","email":"bbreaker@usgs.gov","middleInitial":"K.","affiliations":[{"id":129,"text":"Arkansas Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":false,"id":465766,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70039199,"text":"fs20123103 - 2012 - Integrated monitoring of ecological conditions in wetland-upland landscapes","interactions":[],"lastModifiedDate":"2012-07-26T01:02:11","indexId":"fs20123103","displayToPublicDate":"2012-07-25T00:00:00","publicationYear":"2012","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":"2012-3103","title":"Integrated monitoring of ecological conditions in wetland-upland landscapes","docAbstract":"Landscapes of interwoven wetlands and uplands offer a rich set of ecosystem goods and services. Managing lands to maximize ecosystem services requires information that distinguishes change caused by local actions from broader-scale shifts in climate, land use, and other forms of global change. Satellite and airborne sensors collect valuable data for this purpose, especially when the data are analyzed along with data collected from ground-based sensors. The U.S. Geological Survey (USGS) is using remote sensing technology in this way as part of the Terrestrial Wetland Global Change Research Network to assess effects of climate change interacting with land-use change and other potential stressors along environmental gradients of wetland-upland landscapes in the United States and Canada.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20123103","usgsCitation":"Gallant, A., and Sadinski, W., 2012, Integrated monitoring of ecological conditions in wetland-upland landscapes: U.S. Geological Survey Fact Sheet 2012-3103, 2 p., https://doi.org/10.3133/fs20123103.","productDescription":"2 p.","onlineOnly":"Y","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":259154,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs_2012_3103.JPG"},{"id":259151,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2012/3103/fs12-3103.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":259152,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2012/3103/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a3c68e4b0c8380cd62cf1","contributors":{"authors":[{"text":"Gallant, Alisa 0000-0002-3029-6637","orcid":"https://orcid.org/0000-0002-3029-6637","contributorId":85280,"corporation":false,"usgs":true,"family":"Gallant","given":"Alisa","affiliations":[],"preferred":false,"id":465768,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sadinski, Walt","contributorId":33969,"corporation":false,"usgs":true,"family":"Sadinski","given":"Walt","affiliations":[],"preferred":false,"id":465767,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70039185,"text":"sir20125130 - 2012 - Development of regional skews for selected flood durations for the Central Valley Region, California, based on data through water year 2008","interactions":[],"lastModifiedDate":"2012-07-25T01:02:05","indexId":"sir20125130","displayToPublicDate":"2012-07-24T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-5130","title":"Development of regional skews for selected flood durations for the Central Valley Region, California, based on data through water year 2008","docAbstract":"Flood-frequency information is important in the Central Valley region of California because of the high risk of catastrophic flooding. Most traditional flood-frequency studies focus on peak flows, but for the assessment of the adequacy of reservoirs, levees, other flood control structures, sustained flood flow (flood duration) frequency data are needed. This study focuses on rainfall or rain-on-snow floods, rather than the annual maximum, because rain events produce the largest floods in the region. A key to estimating flood-duration frequency is determining the regional skew for such data. Of the 50 sites used in this study to determine regional skew, 28 sites were considered to have little to no significant regulated flows, and for the 22 sites considered significantly regulated, unregulated daily flow data were synthesized by using reservoir storage changes and diversion records. The unregulated, annual maximum rainfall flood flows for selected durations (1-day, 3-day, 7-day, 15-day, and 30-day) for all 50 sites were furnished by the U.S. Army Corps of Engineers. Station skew was determined by using the expected moments algorithm program for fitting the Pearson Type 3 flood-frequency distribution to the logarithms of annual flood-duration data.\r\nBayesian generalized least squares regression procedures used in earlier studies were modified to address problems caused by large cross correlations among concurrent rainfall floods in California and to address the extensive censoring of low outliers at some sites, by using the new expected moments algorithm for fitting the LP3 distribution to rainfall flood-duration data. To properly account for these problems and to develop suitable regional-skew regression models and regression diagnostics, a combination of ordinary least squares, weighted least squares, and Bayesian generalized least squares regressions were adopted. This new methodology determined that a nonlinear model relating regional skew to mean basin elevation was the best model for each flood duration. The regional-skew values ranged from -0.74 for a flood duration of 1-day and a mean basin elevation less than 2,500 feet to values near 0 for a flood duration of 7-days and a mean basin elevation greater than 4,500 feet. This relation between skew and elevation reflects the interaction of snow and rain, which increases with increased elevation. The regional skews are more accurate, and the mean squared errors are less than in the Interagency Advisory Committee on Water Data's National skew map of Bulletin 17B.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125130","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Lamontagne, J.R., Stedinger, J.R., Berenbrock, C., Veilleux, A.G., Ferris, J.C., and Knifong, D.L., 2012, Development of regional skews for selected flood durations for the Central Valley Region, California, based on data through water year 2008: U.S. Geological Survey Scientific Investigations Report 2012-5130, viii, 35 p. Appendices, https://doi.org/10.3133/sir20125130.","productDescription":"viii, 35 p. Appendices","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":259128,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5130.gif"},{"id":259123,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5130/","linkFileType":{"id":5,"text":"html"}},{"id":259124,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5130/pdf/sir20125130.pdf","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"California","otherGeospatial":"Central Valley;Sierra Nevada Basins;North Coast Ranges Basins;South Coast Ranges Basins","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.54,34.28 ], [ -124.54,42.01 ], [ -116.33,42.01 ], [ -116.33,34.28 ], [ -124.54,34.28 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a0061e4b0c8380cd4f725","contributors":{"authors":[{"text":"Lamontagne, Jonathan R. 0000-0003-3976-1678","orcid":"https://orcid.org/0000-0003-3976-1678","contributorId":31640,"corporation":false,"usgs":true,"family":"Lamontagne","given":"Jonathan","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":465752,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stedinger, Jery R.","contributorId":76198,"corporation":false,"usgs":true,"family":"Stedinger","given":"Jery","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":465753,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Berenbrock, Charles","contributorId":30598,"corporation":false,"usgs":true,"family":"Berenbrock","given":"Charles","email":"","affiliations":[],"preferred":false,"id":465751,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Veilleux, Andrea G. aveilleux@usgs.gov","contributorId":4404,"corporation":false,"usgs":true,"family":"Veilleux","given":"Andrea","email":"aveilleux@usgs.gov","middleInitial":"G.","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":true,"id":465750,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ferris, Justin C. jcferris@usgs.gov","contributorId":4186,"corporation":false,"usgs":true,"family":"Ferris","given":"Justin","email":"jcferris@usgs.gov","middleInitial":"C.","affiliations":[],"preferred":true,"id":465749,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Knifong, Donna L. dknifong@usgs.gov","contributorId":1517,"corporation":false,"usgs":true,"family":"Knifong","given":"Donna","email":"dknifong@usgs.gov","middleInitial":"L.","affiliations":[],"preferred":true,"id":465748,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70039168,"text":"fs20123101 - 2012 - Hydrologic conditions in Georgia, 2010","interactions":[],"lastModifiedDate":"2016-12-07T11:29:15","indexId":"fs20123101","displayToPublicDate":"2012-07-23T00:00:00","publicationYear":"2012","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":"2012-3101","title":"Hydrologic conditions in Georgia, 2010","docAbstract":"The United States Geological Survey (USGS) Georgia Water Science Center (GaWSC) maintains a long-term hydrologic monitoring network of more than 320 real-time streamgages, including 10 real-time lake-level monitoring stations and 63 real-time water-quality monitors. Additionally, the GaWSC operates more than 180 groundwater wells, 41 of which are real-time. One of the many benefits from this monitoring network is that the data analysis provides an overview of the hydrologic conditions of rivers, creeks, reservoirs, and aquifers in Georgia.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20123101","usgsCitation":"Knaak, A.E., Ankcorn, P.D., and Peck, M., 2012, Hydrologic conditions in Georgia, 2010: U.S. Geological Survey Fact Sheet 2012-3101, 6 p., https://doi.org/10.3133/fs20123101.","productDescription":"6 p.","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":13634,"text":"South Atlantic Water Science 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mfpeck@usgs.gov","contributorId":1467,"corporation":false,"usgs":true,"family":"Peck","given":"Michael F.","email":"mfpeck@usgs.gov","affiliations":[],"preferred":false,"id":465716,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70039166,"text":"sir20125113 - 2012 - Methods for determining magnitude and frequency of floods in California, based on data through water year 2006","interactions":[],"lastModifiedDate":"2012-07-24T01:01:47","indexId":"sir20125113","displayToPublicDate":"2012-07-23T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-5113","title":"Methods for determining magnitude and frequency of floods in California, based on data through water year 2006","docAbstract":"Methods for estimating the magnitude and frequency of floods in California that are not substantially affected by regulation or diversions have been updated. Annual peak-flow data through water year 2006 were analyzed for 771 streamflow-gaging stations (streamgages) in California having 10 or more years of data. Flood-frequency estimates were computed for the streamgages by using the expected moments algorithm to fit a Pearson Type III distribution to logarithms of annual peak flows for each streamgage. Low-outlier and historic information were incorporated into the flood-frequency analysis, and a generalized Grubbs-Beck test was used to detect multiple potentially influential low outliers. Special methods for fitting the distribution were developed for streamgages in the desert region in southeastern California. Additionally, basin characteristics for the streamgages were computed by using a geographical information system.\r\nRegional regression analysis, using generalized least squares regression, was used to develop a set of equations for estimating flows with 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities for ungaged basins in California that are outside of the southeastern desert region. Flood-frequency estimates and basin characteristics for 630 streamgages were combined to form the final database used in the regional regression analysis. Five hydrologic regions were developed for the area of California outside of the desert region. The final regional regression equations are functions of drainage area and mean annual precipitation for four of the five regions. In one region, the Sierra Nevada region, the final equations are functions of drainage area, mean basin elevation, and mean annual precipitation. Average standard errors of prediction for the regression equations in all five regions range from 42.7 to 161.9 percent.\r\nFor the desert region of California, an analysis of 33 streamgages was used to develop regional estimates of all three parameters (mean, standard deviation, and skew) of the log-Pearson Type III distribution. The regional estimates were then used to develop a set of equations for estimating flows with 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities for ungaged basins. The final regional regression equations are functions of drainage area. Average standard errors of prediction for these regression equations range from 214.2 to 856.2 percent.\r\nAnnual peak-flow data through water year 2006 were analyzed for eight streamgages in California having 10 or more years of data considered to be affected by urbanization. Flood-frequency estimates were computed for the urban streamgages by fitting a Pearson Type III distribution to logarithms of annual peak flows for each streamgage. Regression analysis could not be used to develop flood-frequency estimation equations for urban streams because of the limited number of sites. Flood-frequency estimates for the eight urban sites were graphically compared to flood-frequency estimates for 630 non-urban sites.\r\nThe regression equations developed from this study will be incorporated into the U.S. Geological Survey (USGS) StreamStats program. The StreamStats program is a Web-based application that provides streamflow statistics and basin characteristics for USGS streamgages and ungaged sites of interest. StreamStats can also compute basin characteristics and provide estimates of streamflow statistics for ungaged sites when users select the location of a site along any stream in California.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125113","collaboration":"Prepared in cooperation with the Federal Emergency Management Agency","usgsCitation":"Gotvald, A.J., Barth, N.A., Veilleux, A.G., and Parrett, C., 2012, Methods for determining magnitude and frequency of floods in California, based on data through water year 2006: U.S. Geological Survey Scientific Investigations Report 2012-5113, vi, 30 p.; Appendix, https://doi.org/10.3133/sir20125113.","productDescription":"vi, 30 p.; Appendix","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":259103,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5113.jpg"},{"id":259098,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5113/","linkFileType":{"id":5,"text":"html"}},{"id":259099,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5113/pdf/sir2012-5113.pdf","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"California","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a55aee4b0c8380cd6d269","contributors":{"authors":[{"text":"Gotvald, Anthony J. 0000-0002-9019-750X agotvald@usgs.gov","orcid":"https://orcid.org/0000-0002-9019-750X","contributorId":1970,"corporation":false,"usgs":true,"family":"Gotvald","given":"Anthony","email":"agotvald@usgs.gov","middleInitial":"J.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":465707,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barth, Nancy A. nabarth@usgs.gov","contributorId":3276,"corporation":false,"usgs":true,"family":"Barth","given":"Nancy","email":"nabarth@usgs.gov","middleInitial":"A.","affiliations":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":true,"id":465708,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Veilleux, Andrea G. aveilleux@usgs.gov","contributorId":4404,"corporation":false,"usgs":true,"family":"Veilleux","given":"Andrea","email":"aveilleux@usgs.gov","middleInitial":"G.","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":true,"id":465709,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Parrett, Charles","contributorId":9635,"corporation":false,"usgs":true,"family":"Parrett","given":"Charles","email":"","affiliations":[],"preferred":false,"id":465710,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70039170,"text":"ofr20121148 - 2012 - Probability and volume of potential postwildfire debris flows in the 2012 High Park Burn Area near Fort Collins, Colorado","interactions":[],"lastModifiedDate":"2012-07-24T01:01:47","indexId":"ofr20121148","displayToPublicDate":"2012-07-23T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-1148","title":"Probability and volume of potential postwildfire debris flows in the 2012 High Park Burn Area near Fort Collins, Colorado","docAbstract":"This report presents a preliminary emergency assessment of the debris-flow hazards from drainage basins burned by the 2012 High Park fire near Fort Collins in Larimer County, Colorado. Empirical models derived from statistical evaluation of data collected from recently burned basins throughout the intermountain western United States were used to estimate the probability of debris-flow occurrence and volume of debris flows along the burned area drainage network and to estimate the same for 44 selected drainage basins along State Highway 14 and the perimeter of the burned area. Input data for the models included topographic parameters, soil characteristics, burn severity, and rainfall totals and intensities for a (1) 2-year-recurrence, 1-hour-duration rainfall (25 millimeters); (2) 10-year-recurrence, 1-hour-duration rainfall (43 millimeters); and (3) 25-year-recurrence, 1-hour-duration rainfall (51 millimeters). Estimated debris-flow probabilities along the drainage network and throughout the drainage basins of interest ranged from 1 to 84 percent in response to the 2-year-recurrence, 1-hour-duration rainfall; from 2 to 95 percent in response to the 10-year-recurrence, 1-hour-duration rainfall; and from 3 to 97 in response to the 25-year-recurrence, 1-hour-duration rainfall. Basins and drainage networks with the highest probabilities tended to be those on the eastern edge of the burn area where soils have relatively high clay contents and gradients are steep. Estimated debris-flow volumes range from a low of 1,600 cubic meters to a high of greater than 100,000 cubic meters. Estimated debris-flow volumes increase with basin size and distance along the drainage network, but some smaller drainages were also predicted to produce substantial volumes of material. The predicted probabilities and some of the volumes predicted for the modeled storms indicate a potential for substantial debris-flow impacts on structures, roads, bridges, and culverts located both within and immediately downstream from the burned area. Colorado State Highway 14 is also susceptible to impacts from debris flows.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121148","collaboration":"Prepared in cooperation with Colorado Department of Transportation","usgsCitation":"Verdin, K.L., Dupree, J.A., and Elliott, J.G., 2012, Probability and volume of potential postwildfire debris flows in the 2012 High Park Burn Area near Fort Collins, Colorado: U.S. Geological Survey Open-File Report 2012-1148, vi, 9 p.; 2 Plates: 87 x 56 cm., https://doi.org/10.3133/ofr20121148.","productDescription":"vi, 9 p.; 2 Plates: 87 x 56 cm.","numberOfPages":"15","onlineOnly":"Y","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":259113,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1148.gif"},{"id":259106,"rank":400,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2012/1148/Plate1.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":259104,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1148/","linkFileType":{"id":5,"text":"html"}},{"id":259105,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1148/OF12-1148.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":259107,"rank":401,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2012/1148/Plate2.pdf","linkFileType":{"id":1,"text":"pdf"}}],"projection":"Universal Transverse Mercator, Zone 13 North","datum":"North American Datum 1983","country":"United States","state":"Colorado","county":"Larimer","city":"Fort Collins","otherGeospatial":"High Park","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -105.53333333333333,40.55 ], [ -105.53333333333333,40.75 ], [ -105.18333333333334,40.75 ], [ -105.18333333333334,40.55 ], [ -105.53333333333333,40.55 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a8ca8e4b0c8380cd7e7f3","contributors":{"authors":[{"text":"Verdin, Kristine L. 0000-0002-6114-4660 kverdin@usgs.gov","orcid":"https://orcid.org/0000-0002-6114-4660","contributorId":3070,"corporation":false,"usgs":true,"family":"Verdin","given":"Kristine","email":"kverdin@usgs.gov","middleInitial":"L.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":465721,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dupree, Jean A. dupree@usgs.gov","contributorId":2563,"corporation":false,"usgs":true,"family":"Dupree","given":"Jean","email":"dupree@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":465720,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Elliott, John G. jelliott@usgs.gov","contributorId":832,"corporation":false,"usgs":true,"family":"Elliott","given":"John","email":"jelliott@usgs.gov","middleInitial":"G.","affiliations":[],"preferred":true,"id":465719,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70039135,"text":"tm4F3 - 2012 - TracerLPM (Version 1): An Excel&reg; workbook for interpreting groundwater age distributions from environmental tracer data","interactions":[],"lastModifiedDate":"2023-08-17T19:04:09.341631","indexId":"tm4F3","displayToPublicDate":"2012-07-20T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"4-F3","title":"TracerLPM (Version 1): An Excel&reg; workbook for interpreting groundwater age distributions from environmental tracer data","docAbstract":"TracerLPM is an interactive Excel&reg; (2007 or later) workbook program for evaluating groundwater age distributions from environmental tracer data by using lumped parameter models (LPMs). Lumped parameter models are mathematical models of transport based on simplified aquifer geometry and flow configurations that account for effects of hydrodynamic dispersion or mixing within the aquifer, well bore, or discharge area. Five primary LPMs are included in the workbook: piston-flow model (PFM), exponential mixing model (EMM), exponential piston-flow model (EPM), partial exponential model (PEM), and dispersion model (DM). Binary mixing models (BMM) can be created by combining primary LPMs in various combinations. Travel time through the unsaturated zone can be included as an additional parameter. TracerLPM also allows users to enter age distributions determined from other methods, such as particle tracking results from numerical groundwater-flow models or from other LPMs not included in this program. Tracers of both young groundwater (anthropogenic atmospheric gases and isotopic substances indicating post-1940s recharge) and much older groundwater (carbon-14 and helium-4) can be interpreted simultaneously so that estimates of the groundwater age distribution for samples with a wide range of ages can be constrained. TracerLPM is organized to permit a comprehensive interpretive approach consisting of hydrogeologic conceptualization, visual examination of data and models, and best-fit parameter estimation. Groundwater age distributions can be evaluated by comparing measured and modeled tracer concentrations in two ways: (1) multiple tracers analyzed simultaneously can be evaluated against each other for concordance with modeled concentrations (tracer-tracer application) or (2) tracer time-series data can be evaluated for concordance with modeled trends (tracer-time application). Groundwater-age estimates can also be obtained for samples with a single tracer measurement at one point in time; however, prior knowledge of an appropriate LPM is required because the mean age is often non-unique. LPM output concentrations depend on model parameters and sample date. All of the LPMs have a parameter for mean age. The EPM, PEM, and DM have an additional parameter that characterizes the degree of age mixing in the sample. BMMs have a parameter for the fraction of the first component in the mixture. An LPM, together with its parameter values, provides a description of the age distribution or the fractional contribution of water for every age of recharge contained within a sample. For the PFM, the age distribution is a unit pulse at one distinct age. For the other LPMs, the age distribution can be much broader and span decades, centuries, millennia, or more. For a sample with a mixture of groundwater ages, the reported interpretation of tracer data includes the LPM name, the mean age, and the values of any other independent model parameters. TracerLPM also can be used for simulating the responses of wells, springs, streams, or other groundwater discharge receptors to nonpoint-source contaminants that are introduced in recharge, such as nitrate. This is done by combining an LPM or user-defined age distribution with information on contaminant loading at the water table. Information on historic contaminant loading can be used to help evaluate a model's ability to match real world conditions and understand observed contaminant trends, while information on future contaminant loading scenarios can be used to forecast potential contaminant trends.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm4F3","collaboration":"National Research Program; National Water-Quality Assessment Program","usgsCitation":"Jurgens, B., Böhlke, J., and Eberts, S., 2012, TracerLPM (Version 1): An Excel&reg; workbook for interpreting groundwater age distributions from environmental tracer data: U.S. Geological Survey Techniques and Methods 4-F3, viii, 60 p., https://doi.org/10.3133/tm4F3.","productDescription":"viii, 60 p.","onlineOnly":"Y","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":259039,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/4-f3/pdf/tm4-F3.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":259056,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/tm_4_f3.jpg"},{"id":259038,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/tm/4-f3/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505bb68be4b08c986b326d21","contributors":{"authors":[{"text":"Jurgens, Bryant C. 0000-0002-1572-113X","orcid":"https://orcid.org/0000-0002-1572-113X","contributorId":22454,"corporation":false,"usgs":true,"family":"Jurgens","given":"Bryant C.","affiliations":[],"preferred":false,"id":465667,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Böhlke, J.K. 0000-0001-5693-6455","orcid":"https://orcid.org/0000-0001-5693-6455","contributorId":96696,"corporation":false,"usgs":true,"family":"Böhlke","given":"J.K.","affiliations":[],"preferred":false,"id":465668,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Eberts, Sandra M. smeberts@usgs.gov","contributorId":2264,"corporation":false,"usgs":true,"family":"Eberts","given":"Sandra M.","email":"smeberts@usgs.gov","affiliations":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"preferred":false,"id":465666,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70039117,"text":"70039117 - 2012 - Hatching and fledging times from grassland passerine nests","interactions":[],"lastModifiedDate":"2018-03-30T12:27:32","indexId":"70039117","displayToPublicDate":"2012-07-20T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"seriesTitle":{"id":5103,"text":"Studies in Avian Biology","printIssn":"0197-9922","active":true,"publicationSubtype":{"id":24}},"seriesNumber":"43","chapter":"4","title":"Hatching and fledging times from grassland passerine nests","docAbstract":"<p><span data-sheets-value=\"{&quot;1&quot;:2,&quot;2&quot;:&quot;Accurate estimates of fledging age are needed in field studies to avoid inducing premature fledging or missing the fledging event. Both may lead to misinterpretation of nest fate. Correctly assessing nest fate and length of the nestling period can be critical for accurate calculation of nest survival rates. For researchers who mark nestlings, knowing the age at which their activities may cause young to leave nests prematurely could prevent introducing bias to their studies. We obtained estimates of fledging age using data from grassland bird nests monitored from hatching through fledging with video-surveillance systems in North Dakota and Minnesota during 1996&amp;ndash;2001. We compared these values to those obtained from traditional nest visits and from available literature. Mean and modal fledging ages for video-monitored nests were generally similar to those for visited nests, although Clay-colored Sparrows (Spizella pallida) typically fledged 1 day earlier from visited nests. Average fledging ages from both video and nest visits occurred within ranges reported in the literature, but expanded by 1&amp;ndash;2 days the upper age limit for Clay-colored Sparrows and the lower age limit for Bobolinks (Dolichonyx oryzivorus). Video showed that eggs hatched throughout the day whereas most young fledged in the morning (06:30&amp;ndash;12:30 CDT). Length of the hatching period for a clutch was usually >1 day and was positively correlated with clutch size. Length of the fledging period for a brood was usually <1 day, and in nearly half the nests, fledging was completed within <2 hr. Video surveillance has proven to be a useful tool for providing new information and for corroborating published statements related to hatching and fledging chronology. Comparison of data collected from video and nest visits showed that carefully conducted nest visits generally can provide reliable data for deriving estimates of survival.&quot;}\" data-sheets-userformat=\"{&quot;2&quot;:8403202,&quot;4&quot;:[null,2,16777215],&quot;11&quot;:4,&quot;14&quot;:[null,2,0],&quot;15&quot;:&quot;Inconsolata, monospace, arial, sans, sans-serif&quot;,&quot;16&quot;:11,&quot;26&quot;:400}\" data-sheets-formula=\"=VLOOKUP(R[0]C[-5],Fixed!R2C[-6]:C[-4],3,false)\">Accurate estimates of fledging age are needed in field studies to avoid inducing premature fledging or missing the fledging event. Both may lead to misinterpretation of nest fate. Correctly assessing nest fate and length of the nestling period can be critical for accurate calculation of nest survival rates. For researchers who mark nestlings, knowing the age at which their activities may cause young to leave nests prematurely could prevent introducing bias to their studies. We obtained estimates of fledging age using data from grassland bird nests monitored from hatching through fledging with video-surveillance systems in North Dakota and Minnesota during 1996&amp;ndash;2001. We compared these values to those obtained from traditional nest visits and from available literature. Mean and modal fledging ages for video-monitored nests were generally similar to those for visited nests, although Clay-colored Sparrows (Spizella pallida) typically fledged 1 day earlier from visited nests. Average fledging ages from both video and nest visits occurred within ranges reported in the literature, but expanded by 1&amp;ndash;2 days the upper age limit for Clay-colored Sparrows and the lower age limit for Bobolinks (Dolichonyx oryzivorus). Video showed that eggs hatched throughout the day whereas most young fledged in the morning (06:30&amp;ndash;12:30 CDT). Length of the hatching period for a clutch was usually &gt;1 day and was positively correlated with clutch size. Length of the fledging period for a brood was usually &lt;1 day, and in nearly half the nests, fledging was completed within &lt;2 hr. Video surveillance has proven to be a useful tool for providing new information and for corroborating published statements related to hatching and fledging chronology. Comparison of data collected from video and nest visits showed that carefully conducted nest visits generally can provide reliable data for deriving estimates of survival.</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Video surveillance of nesting birds (Studies in Avian Biology no. 43)","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"University of California Press","publisherLocation":"Berkeley, CA","isbn":"9780520273139","usgsCitation":"Pietz, P., Granfors, D.A., and Grant, T.A., 2012, Hatching and fledging times from grassland passerine nests, chap. 4 <i>of</i> Video surveillance of nesting birds (Studies in Avian Biology no. 43): Studies in Avian Biology, v. 43, p. 47-60.","productDescription":"14 p.","startPage":"47","endPage":"60","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":259082,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":259074,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://www.ucpress.edu/book.php?isbn=9780520273139","linkFileType":{"id":5,"text":"html"}}],"volume":"43","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a2f86e4b0c8380cd5ce76","contributors":{"editors":[{"text":"Ribic, Christine A. caribic@usgs.gov","contributorId":831,"corporation":false,"usgs":true,"family":"Ribic","given":"Christine","email":"caribic@usgs.gov","middleInitial":"A.","affiliations":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"preferred":false,"id":509024,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Thompson, Frank R. III","contributorId":12608,"corporation":false,"usgs":true,"family":"Thompson","given":"Frank","suffix":"III","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":509026,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Pietz, Pamela J. ppietz@usgs.gov","contributorId":2382,"corporation":false,"usgs":true,"family":"Pietz","given":"Pamela J.","email":"ppietz@usgs.gov","affiliations":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"preferred":false,"id":509025,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Pietz, Pamela J. ppietz@usgs.gov","contributorId":2382,"corporation":false,"usgs":true,"family":"Pietz","given":"Pamela J.","email":"ppietz@usgs.gov","affiliations":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"preferred":false,"id":465641,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Granfors, Diane A.","contributorId":174567,"corporation":false,"usgs":false,"family":"Granfors","given":"Diane","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":465643,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Grant, Todd A.","contributorId":194194,"corporation":false,"usgs":false,"family":"Grant","given":"Todd","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":465642,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70039119,"text":"ofr20121139 - 2012 - Airborne digital-image data for monitoring the Colorado River corridor below Glen Canyon Dam, Arizona, 2009 - Image-mosaic production and comparison with 2002 and 2005 image mosaics","interactions":[],"lastModifiedDate":"2012-07-21T01:01:57","indexId":"ofr20121139","displayToPublicDate":"2012-07-19T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-1139","title":"Airborne digital-image data for monitoring the Colorado River corridor below Glen Canyon Dam, Arizona, 2009 - Image-mosaic production and comparison with 2002 and 2005 image mosaics","docAbstract":"Airborne digital-image data were collected for the Arizona part of the Colorado River ecosystem below Glen Canyon Dam in 2009. These four-band image data are similar in wavelength band (blue, green, red, and near infrared) and spatial resolution (20 centimeters) to image collections of the river corridor in 2002 and 2005. These periodic image collections are used by the Grand Canyon Monitoring and Research Center (GCMRC) of the U.S. Geological Survey to monitor the effects of Glen Canyon Dam operations on the downstream ecosystem. The 2009 collection used the latest model of the Leica ADS40 airborne digital sensor (the SH52), which uses a single optic for all four bands and collects and stores band radiance in 12-bits, unlike the image sensors that GCMRC used in 2002 and 2005. This study examined the performance of the SH52 sensor, on the basis of the collected image data, and determined that the SH52 sensor provided superior data relative to the previously employed sensors (that is, an early ADS40 model and Zeiss Imaging's Digital Mapping Camera) in terms of band-image registration, dynamic range, saturation, linearity to ground reflectance, and noise level. The 2009 image data were provided as orthorectified segments of each flightline to constrain the size of the image files; each river segment was covered by 5 to 6 overlapping, linear flightlines. Most flightline images for each river segment had some surface-smear defects and some river segments had cloud shadows, but these two conditions did not generally coincide in the majority of the overlapping flightlines for a particular river segment. Therefore, the final image mosaic for the 450-kilometer (km)-long river corridor required careful selection and editing of numerous flightline segments (a total of 513 segments, each 3.2 km long) to minimize surface defects and cloud shadows. The final image mosaic has a total of only 3 km of surface defects. The final image mosaic for the western end of the corridor has areas of cloud shadow because of persistent inclement weather during data collection. This report presents visual comparisons of the 2002, 2005, and 2009 digital-image mosaics for various physical, biological, and cultural resources within the Colorado River ecosystem. All of the comparisons show the superior quality of the 2009 image data. In fact, the 2009 four-band image mosaic is perhaps the best image dataset that exists for the entire Arizona part of the Colorado River.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121139","collaboration":"In cooperation with the Western Area Power Authority and the Bureau of Reclamation","usgsCitation":"Davis, P.A., 2012, Airborne digital-image data for monitoring the Colorado River corridor below Glen Canyon Dam, Arizona, 2009 - Image-mosaic production and comparison with 2002 and 2005 image mosaics: U.S. Geological Survey Open-File Report 2012-1139, vi, 82 p., https://doi.org/10.3133/ofr20121139.","productDescription":"vi, 82 p.","onlineOnly":"Y","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":259021,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1139.JPG"},{"id":259017,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1139/","linkFileType":{"id":5,"text":"html"}},{"id":259018,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1139/of2012-1139.pdf","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Arizona","otherGeospatial":"Colorado River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -114,35 ], [ -114,37 ], [ -111,37 ], [ -111,35 ], [ -114,35 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059e91de4b0c8380cd480e2","contributors":{"authors":[{"text":"Davis, Philip A. pdavis@usgs.gov","contributorId":692,"corporation":false,"usgs":true,"family":"Davis","given":"Philip","email":"pdavis@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":465644,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70039113,"text":"ofr20121121 - 2012 - Thermal and hydrological observations near Twelvemile Lake in discontinuous permafrost, Yukon Flats, interior Alaska, September 2010-August 2011","interactions":[],"lastModifiedDate":"2018-06-19T19:50:30","indexId":"ofr20121121","displayToPublicDate":"2012-07-19T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-1121","title":"Thermal and hydrological observations near Twelvemile Lake in discontinuous permafrost, Yukon Flats, interior Alaska, September 2010-August 2011","docAbstract":"A series of ground-based observations were made between September 2010 and August 2011 near Twelvemile Lake, 19 kilometers southwest of Fort Yukon, Alaska, for use in ongoing hydrological analyses of watersheds in this region of discontinuous permafrost. Measurements include depth to ground ice, depth to water table, soil texture, soil moisture, soil temperature, and water pressure above the permafrost table. In the drained basin of subsiding Twelvemile Lake, we generally find an absence of newly formed permafrost and an undetectable slope of the water table; however, a sloping water table was observed in the low-lying channels extending into and away from the lake watershed. Datasets for these observations are summarized in this report and can be accessed by clicking on the links in each section or from the Downloads folder of the report Web page.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121121","usgsCitation":"Jepsen, S.M., Koch, J.C., Rose, J.R., Voss, C.I., and Walvoord, M.A., 2012, Thermal and hydrological observations near Twelvemile Lake in discontinuous permafrost, Yukon Flats, interior Alaska, September 2010-August 2011: U.S. Geological Survey Open-File Report 2012-1121, iv, 25 p.; Downloads Directory, https://doi.org/10.3133/ofr20121121.","productDescription":"iv, 25 p.; Downloads Directory","onlineOnly":"Y","costCenters":[{"id":145,"text":"Branch of Regional Research-Central Region","active":false,"usgs":true}],"links":[{"id":259012,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1121.JPG"},{"id":259008,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1121/OF12-1121.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":259007,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1121/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Alaska","otherGeospatial":"Buddy Lake;Twelvemile Lake","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -145.6,66.41666666666667 ], [ -145.6,66.48333333333333 ], [ -145.33333333333334,66.48333333333333 ], [ -145.33333333333334,66.41666666666667 ], [ -145.6,66.41666666666667 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505bb20ee4b08c986b325586","contributors":{"authors":[{"text":"Jepsen, Steven M. sjepsen@usgs.gov","contributorId":3892,"corporation":false,"usgs":true,"family":"Jepsen","given":"Steven","email":"sjepsen@usgs.gov","middleInitial":"M.","affiliations":[],"preferred":true,"id":465634,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Koch, Joshua C. 0000-0001-7180-6982 jkoch@usgs.gov","orcid":"https://orcid.org/0000-0001-7180-6982","contributorId":202532,"corporation":false,"usgs":true,"family":"Koch","given":"Joshua","email":"jkoch@usgs.gov","middleInitial":"C.","affiliations":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":465633,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rose, Joshua R.","contributorId":90147,"corporation":false,"usgs":true,"family":"Rose","given":"Joshua","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":465635,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Voss, Clifford I. 0000-0001-5923-2752 cvoss@usgs.gov","orcid":"https://orcid.org/0000-0001-5923-2752","contributorId":1559,"corporation":false,"usgs":true,"family":"Voss","given":"Clifford","email":"cvoss@usgs.gov","middleInitial":"I.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":465632,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Walvoord, Michelle Ann 0000-0003-4269-8366 walvoord@usgs.gov","orcid":"https://orcid.org/0000-0003-4269-8366","contributorId":147211,"corporation":false,"usgs":true,"family":"Walvoord","given":"Michelle","email":"walvoord@usgs.gov","middleInitial":"Ann","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":465636,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70039116,"text":"sir20125129 - 2012 - Fate and transport of cyanobacteria and associated toxins and taste-and-odor compounds from upstream reservoir releases in the Kansas River, Kansas, September and October 2011","interactions":[],"lastModifiedDate":"2012-07-20T01:01:46","indexId":"sir20125129","displayToPublicDate":"2012-07-19T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-5129","title":"Fate and transport of cyanobacteria and associated toxins and taste-and-odor compounds from upstream reservoir releases in the Kansas River, Kansas, September and October 2011","docAbstract":"Cyanobacteria cause a multitude of water-quality concerns, including the potential to produce toxins and taste-and-odor compounds. Toxins and taste-and-odor compounds may cause substantial economic and public health concerns and are of particular interest in lakes, reservoirs, and rivers that are used for drinking-water supply, recreation, or aquaculture. The Kansas River is a primary source of drinking water for about 800,000 people in northeastern Kansas. Water released from Milford Lake to the Kansas River during a toxic cyanobacterial bloom in late August 2011 prompted concerns about cyanobacteria and associated toxins and taste-and-odor compounds in downstream drinking-water supplies. During September and October 2011 water-quality samples were collected to characterize the transport of cyanobacteria and associated compounds from upstream reservoirs to the Kansas River. This study is one of the first to quantitatively document the transport of cyanobacteria and associated compounds during reservoir releases and improves understanding of the fate and transport of cyanotoxins and taste-and-odor compounds downstream from reservoirs. Milford Lake was the only reservoir in the study area with an ongoing cyanobacterial bloom during reservoir releases. Concentrations of cyanobacteria and associated toxins and taste-and-odor compounds in Milford Lake (upstream from the dam) were not necessarily indicative of outflow conditions (below the dam). Total microcystin concentrations, one of the most commonly occurring cyanobacterial toxins, in Milford Lake were 650 to 7,500 times higher than the Kansas Department of Health and Environment guidance level for a public health warning (20 micrograms per liter) for most of September 2011. By comparison, total microcystin concentrations in the Milford Lake outflow generally were less than 10 percent of the concentrations in surface accumulations, and never exceeded 20 micrograms per liter. The Republican River, downstream from Milford Lake, was the only Kansas River tributary with detectable microcystin concentrations throughout the study period, and concentrations exceeded 1 microgram per liter for most of September 2011. Microcystin was detected periodically in other tributaries, but concentrations were low (less than 0.3 micrograms per liter). In contrast, the taste-and-odor compounds geosmin and 2-methylisoborneol (MIB) were detected in all tributaries located immediately downstream from reservoirs and total concentrations generally exceeded the human detection threshold (5 to 10 nanograms per liter) from September through mid-October. Microcystin, geosmin, and MIB were not detected in the Smoky Hill River upstream from the confluence with the Republican River that forms the Kansas River. Within a week after initial reservoir releases, microcystin, geosmin, and MIB were detected throughout a 173-mile reach of the Kansas River; these compounds remained detectable throughout the reach until mid-October. Losses to groundwater when streamflows in the Kansas River were increasing indicate the potential for reservoir releases to affect groundwater quality as well as surface-water quality. Total microcystin concentrations in the Kansas River generally were highest within about 24 miles of the confluence of the Smoky Hill and Republican Rivers, and decreased downstream; concentrations exceeded 1 microgram per liter in the Kansas River upstream from Topeka during the first 2 weeks of September. Patterns in microcystin occurrence and concentration at Kansas River tributary and main-stem sites indicate that Milford Lake was the source of microcystin in the Kansas River; however, the source of taste-and-odor compounds was not as evident, possibly because multiple tributaries contributed taste-and-odor compounds to the Kansas River. Microcystin and taste-and-odor compounds co-occurred in 56 percent of samples collected, indicating co-occurrence was common. Despite frequent co-occurrence, the spatial and temporal patterns in microcystin, geosmin, and MIB were unique and did not necessarily match patterns in cyanobacterial abundance. Use of a single compound or cyanobacterial abundance alone cannot necessarily be used as an indicator of the presence or concentration of these compounds. Measured concentrations of cyanobacteria and associated compounds were substantially higher than expected concentrations based on simple dilution models at some sites and substantially lower at others, though spatial and temporal patterns were unique for individual compounds. Data were not collected in such a way to determine whether differences between measured and expected concentrations were statistically significant. Results, however, indicate that simple dilution models were not sufficient to describe the downstream transport of cyanobacteria and associated compounds in the Kansas River.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125129","collaboration":"Prepared in cooperation with the City of Lawrence, the City of Topeka, Johnson County WaterOne, the Kansas Water Office, and the Kansas Department of Health and Environment","usgsCitation":"Graham, J.L., Ziegler, A., Loving, B.L., and Loftin, K.A., 2012, Fate and transport of cyanobacteria and associated toxins and taste-and-odor compounds from upstream reservoir releases in the Kansas River, Kansas, September and October 2011: U.S. Geological Survey Scientific Investigations Report 2012-5129, vi, 65 p.; appendices, https://doi.org/10.3133/sir20125129.","productDescription":"vi, 65 p.; appendices","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":259019,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5129.JPG"},{"id":259016,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5129/sir2012-5129.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":259014,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5129/","linkFileType":{"id":5,"text":"html"}}],"scale":"2000000","projection":"Albers Equal-area Conic","country":"United States","state":"Kansas","otherGeospatial":"Kansas River;Milford Lake;Republican River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -97.5,38.5 ], [ -97.5,40 ], [ -94.75,40 ], [ -94.75,38.5 ], [ -97.5,38.5 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a0f08e4b0c8380cd5371c","contributors":{"authors":[{"text":"Graham, Jennifer L. 0000-0002-6420-9335 jlgraham@usgs.gov","orcid":"https://orcid.org/0000-0002-6420-9335","contributorId":1769,"corporation":false,"usgs":true,"family":"Graham","given":"Jennifer","email":"jlgraham@usgs.gov","middleInitial":"L.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":465639,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ziegler, Andrew C. aziegler@usgs.gov","contributorId":433,"corporation":false,"usgs":true,"family":"Ziegler","given":"Andrew C.","email":"aziegler@usgs.gov","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":false,"id":465637,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Loving, Brian L. bloving@usgs.gov","contributorId":4565,"corporation":false,"usgs":true,"family":"Loving","given":"Brian","email":"bloving@usgs.gov","middleInitial":"L.","affiliations":[],"preferred":true,"id":465640,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Loftin, Keith A. 0000-0001-5291-876X kloftin@usgs.gov","orcid":"https://orcid.org/0000-0001-5291-876X","contributorId":868,"corporation":false,"usgs":true,"family":"Loftin","given":"Keith","email":"kloftin@usgs.gov","middleInitial":"A.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":465638,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70039128,"text":"ofr20111044 - 2012 - Preliminary surficial geologic map of the Newberry Springs 30' x 60' quadrangle, California","interactions":[],"lastModifiedDate":"2022-04-15T20:06:14.07065","indexId":"ofr20111044","displayToPublicDate":"2012-07-19T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2011-1044","title":"Preliminary surficial geologic map of the Newberry Springs 30' x 60' quadrangle, California","docAbstract":"The Newberry Springs 30' x 60' quadrangle is located in the central Mojave Desert of southern California. It is split approximately into northern and southern halves by I-40, with the city of Barstow at its western edge and the town of Ludlow near its eastern edge. The map area spans lat 34&deg;30 to 35&deg; N. to long -116 &deg;to -117&deg; W. and covers over 1,000 km<super>2</super>. We integrate the results of surficial geologic mapping conducted during 2002-2005 with compilations of previous surficial mapping and bedrock geologic mapping. Quaternary units are subdivided in detail on the map to distinguish variations in age, process of formation, pedogenesis, lithology, and spatial interdependency, whereas pre-Quaternary bedrock units are grouped into generalized assemblages that emphasize their attributes as hillslope-forming materials and sources of parent material for the Quaternary units. The spatial information in this publication is presented in two forms: a spatial database and a geologic map. The geologic map is a <i>view</i> (the display of an extracted subset of the database at a given time) of the spatial database; it highlights key aspects of the database and necessarily does not show all of the data contained therein. The database contains detailed information about Quaternary geologic unit composition, authorship, and notes regarding geologic units, faults, contacts, and local vegetation. The amount of information contained in the database is too large to show on a single map, so a restricted subset of the information was chosen to summarize the overall nature of the geology. Refer to the database for additional information. Accompanying the spatial data are the map documentation and spatial metadata. The map documentation (this document) describes the geologic setting and history of the Newberry Springs map sheet, summarizes the age and physical character of each map unit, and describes principal faults and folds. The Federal Geographic Data Committee (FGDC) compliant metadata provides detailed information about the digital files and file structure of the spatial data.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20111044","usgsCitation":"Phelps, G.A., Bedford, D.R., Lidke, D., Miller, D., and Schmidt, K., 2012, Preliminary surficial geologic map of the Newberry Springs 30' x 60' quadrangle, California: U.S. Geological Survey Open-File Report 2011-1044, Pamplet: v, 68 p.; 1 Plate: 66 x 32 inches; Readme; Metadata; GIS Database, https://doi.org/10.3133/ofr20111044.","productDescription":"Pamplet: v, 68 p.; 1 Plate: 66 x 32 inches; Readme; Metadata; GIS Database","onlineOnly":"Y","costCenters":[{"id":671,"text":"Western Region Geology and Geophysics Science Center","active":false,"usgs":true}],"links":[{"id":259033,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2011_1044.JPG"},{"id":398866,"rank":5,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_97108.htm"},{"id":259029,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2011/1044/","linkFileType":{"id":5,"text":"html"}},{"id":259030,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2011/1044/OFR2011-1044_pamphlet.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":259031,"rank":400,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2011/1044/OFR2011-1044_sheet.pdf","linkFileType":{"id":1,"text":"pdf"}}],"scale":"100000","projection":"Universal Transverse Mercator, zone 11","datum":"North American Datum of 1927","country":"United States","state":"California","otherGeospatial":"Newberry Springs 30' x 60' quadrangle","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -117,34.5 ], [ -117,35 ], [ -116,35 ], [ -116,34.5 ], [ -117,34.5 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a8ad7e4b0c8380cd7e10d","contributors":{"authors":[{"text":"Phelps, G. A.","contributorId":67107,"corporation":false,"usgs":true,"family":"Phelps","given":"G.","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":465655,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bedford, D. R.","contributorId":9734,"corporation":false,"usgs":true,"family":"Bedford","given":"D.","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":465652,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lidke, D. J.","contributorId":10857,"corporation":false,"usgs":true,"family":"Lidke","given":"D. J.","affiliations":[],"preferred":false,"id":465653,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miller, D. M. 0000-0003-3711-0441","orcid":"https://orcid.org/0000-0003-3711-0441","contributorId":104422,"corporation":false,"usgs":true,"family":"Miller","given":"D. M.","affiliations":[],"preferred":false,"id":465656,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schmidt, K. M. 0000-0003-2365-8035","orcid":"https://orcid.org/0000-0003-2365-8035","contributorId":59830,"corporation":false,"usgs":true,"family":"Schmidt","given":"K. M.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":false,"id":465654,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70190224,"text":"70190224 - 2012 - Effects of chronic wasting disease on reproduction and fawn harvest vulnerability in Wisconsin white-tailed deer","interactions":[],"lastModifiedDate":"2017-08-20T09:59:43","indexId":"70190224","displayToPublicDate":"2012-07-19T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2507,"text":"Journal of Wildlife Diseases","active":true,"publicationSubtype":{"id":10}},"title":"Effects of chronic wasting disease on reproduction and fawn harvest vulnerability in Wisconsin white-tailed deer","docAbstract":"<p><span>Chronic wasting disease (CWD) is a fatal, transmissible spongiform encephalopathy that affects free-ranging and captive North American cervids. Although the impacts of CWD on cervid survival have been documented, little is known about the disease impacts on reproduction and recruitment. We used genetic methods and harvest data (2002–04) to reconstruct parentage for a cohort of white-tailed deer (</span><i>Odocoileus virginianus</i><span>) fawns born in spring 2002 and evaluate the effects of CWD infection on reproduction and fawn harvest vulnerability. There was no difference between CWD-positive and CWD-negative male deer in the probability of being a parent. However, CWD-positive females were more likely to be parents than CWD-negative females. Because our results are based on harvested animals, we evaluated the hypothesis that higher parentage rates occurred because fawns with CWD-positive mothers were more vulnerable to harvest. Male fawns with CWD-positive mothers were harvested earlier (&gt;1 mo relative to their mother’s date of harvest) and farther away from their mothers than male fawns with CWD-negative mothers. Male fawns with CWD-positive mothers were also harvested much earlier and farther away than female fawns from CWD-positive mothers. Most female fawns (86%) with CWD-positive mothers were harvested from the same section as their mothers, while almost half of male and female fawns with CWD-negative mothers were farther away. We conclude that preclinical stages of CWD infection do not prohibit white-tailed deer from successfully reproducing. However, apparently higher harvest vulnerability of male fawns with CWD-positive mothers suggests that CWD infection may make females less capable of providing adequate parental care to ensure the survival and recruitment of their fawns.</span></p>","language":"English","publisher":"Wildlife Disease Association","doi":"10.7589/0090-3558-48.2.361","usgsCitation":"Blanchong, J.A., Grear, D.A., Weckworth, B.V., Keane, D.P., Scribner, K.T., and Samuel, M.D., 2012, Effects of chronic wasting disease on reproduction and fawn harvest vulnerability in Wisconsin white-tailed deer: Journal of Wildlife Diseases, v. 48, no. 2, p. 361-370, https://doi.org/10.7589/0090-3558-48.2.361.","productDescription":"10 p.","startPage":"361","endPage":"370","ipdsId":"IP-028429","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":474409,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.7589/0090-3558-48.2.361","text":"Publisher Index Page"},{"id":344974,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"48","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"599a9fb7e4b0b589267d58bb","contributors":{"authors":[{"text":"Blanchong, Julie A.","contributorId":6030,"corporation":false,"usgs":false,"family":"Blanchong","given":"Julie","email":"","middleInitial":"A.","affiliations":[{"id":13018,"text":"Department of Forest and Wildlife Ecology, University of Wisconsin, Madison","active":true,"usgs":false}],"preferred":false,"id":708085,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grear, Daniel A. 0000-0002-5478-1549 dgrear@usgs.gov","orcid":"https://orcid.org/0000-0002-5478-1549","contributorId":149047,"corporation":false,"usgs":true,"family":"Grear","given":"Daniel","email":"dgrear@usgs.gov","middleInitial":"A.","affiliations":[{"id":5068,"text":"Midwest Regional Director's Office","active":true,"usgs":true},{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":false,"id":708086,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Weckworth, Byron V.","contributorId":195766,"corporation":false,"usgs":false,"family":"Weckworth","given":"Byron","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":708087,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Keane, Delwyn P.","contributorId":195767,"corporation":false,"usgs":false,"family":"Keane","given":"Delwyn","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":708088,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Scribner, Kim T.","contributorId":146113,"corporation":false,"usgs":false,"family":"Scribner","given":"Kim","email":"","middleInitial":"T.","affiliations":[{"id":16582,"text":"Department of Fisheries and Wildlife and Department of Zoology, 480 Wilson Rd. 13 Natural Resources Building, Michigan State University, East Lansing, MI 48824","active":true,"usgs":false},{"id":135,"text":"Biological Resources Division","active":false,"usgs":true}],"preferred":false,"id":708089,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Samuel, Michael D. msamuel@usgs.gov","contributorId":1419,"corporation":false,"usgs":true,"family":"Samuel","given":"Michael","email":"msamuel@usgs.gov","middleInitial":"D.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":708026,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70188563,"text":"70188563 - 2012 - Sediment entrainment by debris flows: In situ measurements from the headwaters of a steep catchment","interactions":[],"lastModifiedDate":"2017-06-15T12:38:38","indexId":"70188563","displayToPublicDate":"2012-07-18T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2318,"text":"Journal of Geophysical Research F: Earth Surface","active":true,"publicationSubtype":{"id":10}},"title":"Sediment entrainment by debris flows: In situ measurements from the headwaters of a steep catchment","docAbstract":"<p><span>Debris flows can dramatically increase their volume, and hence their destructive potential, by entraining sediment. Yet quantitative constraints on rates and mechanics of sediment entrainment by debris flows are limited. Using an in situ sensor network in the headwaters of a natural catchment we measured flow and bed properties during six erosive debris-flow events. Despite similar flow properties and thicknesses of bed sediment entrained across all events, time-averaged entrainment rates were significantly faster for bed sediment that was saturated prior to flow arrival compared with rates for sediment that was dry. Bed sediment was entrained from the sediment-surface downward in a progressive fashion and occurred during passage of dense granular fronts as well as water-rich, inter-surge flow.</span><i>En masse</i><span>failure of bed sediment along the sediment-bedrock interface was never observed. Large-magnitude, high-frequency fluctuations in total normal basal stress were dissipated within the upper 5 cm of bed sediment. Within this near surface layer, concomitant fluctuations in Coulomb frictional resistance are expected, irrespective of the influence of pore fluid pressure or fluctuations in shear stress. If the near-surface sediment was wet as it was overridden by a flow, additional large-magnitude, high-frequency pore pressure fluctuations were measured in the near-surface bed sediment. These pore pressure fluctuations propagated to depth at subsonic rates and in a diffusive manner. The depth to which large excess pore pressures propagated was typically less than 10 cm, but scaled as (</span><i>D</i><span>/</span><i>f</i><sub><i>i</i></sub><span>)</span><sup>0.5</sup><span>, in which </span><i>D</i><span> is the hydraulic diffusivity and </span><i>f</i><sub><i>i&nbsp;</i></sub><span>is the frequency of a particular pore pressure fluctuation. Shallow penetration depths of granular-normal-stress fluctuations and excess pore pressures demonstrate that only near-surface bed sediment experiences the full dynamic range of effective-stress fluctuations, and as a result, can be more easily entrained than deeper sediment. These data provide robust tests for mechanical models of entrainment and demonstrate that a debris flow over wet bed sediment will be larger than the same flow over dry bed sediment.</span></p>","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2011JF002278","usgsCitation":"McCoy, S., Kean, J.W., Coe, J.A., Tucker, G., Staley, D.M., and Wasklewicz, T., 2012, Sediment entrainment by debris flows: In situ measurements from the headwaters of a steep catchment: Journal of Geophysical Research F: Earth Surface, v. 117, no. F3, 25 p., https://doi.org/10.1029/2011JF002278.","productDescription":"25 p.","ipdsId":"IP-037498","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":474410,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2011jf002278","text":"Publisher Index Page"},{"id":342549,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Chalk Cliffs","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -106.45820617675781,\n              38.493369048060764\n            ],\n            [\n              -106.0400390625,\n              38.493369048060764\n            ],\n            [\n              -106.0400390625,\n              38.79690830348427\n            ],\n            [\n              -106.45820617675781,\n              38.79690830348427\n            ],\n            [\n              -106.45820617675781,\n              38.493369048060764\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"117","issue":"F3","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2012-08-10","publicationStatus":"PW","scienceBaseUri":"59439c95e4b062508e31a9d5","contributors":{"authors":[{"text":"McCoy, S.W.","contributorId":192978,"corporation":false,"usgs":false,"family":"McCoy","given":"S.W.","email":"","affiliations":[],"preferred":false,"id":698350,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kean, Jason W. 0000-0003-3089-0369 jwkean@usgs.gov","orcid":"https://orcid.org/0000-0003-3089-0369","contributorId":1654,"corporation":false,"usgs":true,"family":"Kean","given":"Jason","email":"jwkean@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":698349,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Coe, Jeffrey A. 0000-0002-0842-9608 jcoe@usgs.gov","orcid":"https://orcid.org/0000-0002-0842-9608","contributorId":1333,"corporation":false,"usgs":true,"family":"Coe","given":"Jeffrey","email":"jcoe@usgs.gov","middleInitial":"A.","affiliations":[{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":698348,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tucker, G.E.","contributorId":150423,"corporation":false,"usgs":false,"family":"Tucker","given":"G.E.","email":"","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":698351,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Staley, Dennis M. 0000-0002-2239-3402 dstaley@usgs.gov","orcid":"https://orcid.org/0000-0002-2239-3402","contributorId":4134,"corporation":false,"usgs":true,"family":"Staley","given":"Dennis","email":"dstaley@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":698347,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wasklewicz, T.A.","contributorId":64922,"corporation":false,"usgs":true,"family":"Wasklewicz","given":"T.A.","affiliations":[],"preferred":false,"id":698352,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70188517,"text":"70188517 - 2012 - Patterns and controlling factors of species diversity in the Arctic Ocean","interactions":[],"lastModifiedDate":"2019-12-17T09:49:05","indexId":"70188517","displayToPublicDate":"2012-07-18T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2193,"text":"Journal of Biogeography","active":true,"publicationSubtype":{"id":10}},"title":"Patterns and controlling factors of species diversity in the Arctic Ocean","docAbstract":"<p><strong>Aim </strong> The Arctic Ocean is one of the last near-pristine regions on Earth, and, although human activities are expected to impact on Arctic ecosystems, we know very little about baseline patterns of Arctic Ocean biodiversity. This paper aims to describe Arctic Ocean-wide patterns of benthic biodiversity and to explore factors related to the large-scale species diversity patterns.</p><p><strong>Location </strong> Arctic Ocean.</p><p><strong>Methods </strong> We used large ostracode and foraminiferal datasets to describe the biodiversity patterns and applied comprehensive ecological modelling to test the degree to which these patterns are potentially governed by environmental factors, such as temperature, productivity, seasonality, ice cover and others. To test environmental control of the observed diversity patterns, subsets of samples for which all environmental parameters were available were analysed with multiple regression and model averaging.</p><p><strong>Results </strong> Well-known negative latitudinal species diversity gradients (LSDGs) were found in metazoan Ostracoda, but the LSDGs were unimodal with an intermediate maximum with respect to latitude in protozoan foraminifera. Depth species diversity gradients were unimodal, with peaks in diversity shallower than those in other oceans. Our modelling results showed that several factors are significant predictors of diversity, but the significant predictors were different among shallow marine ostracodes, deep-sea ostracodes and deep-sea foraminifera.</p><p><strong>Main conclusions </strong> On the basis of these Arctic Ocean-wide comprehensive datasets, we document large-scale diversity patterns with respect to latitude and depth. Our modelling results suggest that the underlying mechanisms causing these species diversity patterns are unexpectedly complex. The environmental parameters of temperature, surface productivity, seasonality of productivity, salinity and ice cover can all play a role in shaping large-scale diversity patterns, but their relative importance may depend on the ecological preferences of taxa and the oceanographic context of regions. These results suggest that a multiplicity of variables appear to be related to community structure in this system.</p>","language":"English","publisher":"Wiley","doi":"10.1111/j.1365-2699.2012.02758.x","usgsCitation":"Yasuhara, M., Hunt, G., van Dijken, G., Arrigo, K.R., Cronin, T.M., and Wollenburg, J.E., 2012, Patterns and controlling factors of species diversity in the Arctic Ocean: Journal of Biogeography, v. 39, no. 11, p. 2081-2088, https://doi.org/10.1111/j.1365-2699.2012.02758.x.","productDescription":"8 p.","startPage":"2081","endPage":"2088","ipdsId":"IP-042007","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":342494,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Arctic Ocean","volume":"39","issue":"11","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2012-08-17","publicationStatus":"PW","scienceBaseUri":"59424b3de4b0764e6c65dc7e","contributors":{"authors":[{"text":"Yasuhara, Moriaki","contributorId":178705,"corporation":false,"usgs":false,"family":"Yasuhara","given":"Moriaki","email":"","affiliations":[],"preferred":false,"id":698119,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hunt, Gene","contributorId":178704,"corporation":false,"usgs":false,"family":"Hunt","given":"Gene","email":"","affiliations":[],"preferred":false,"id":698117,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"van Dijken, Gert","contributorId":192909,"corporation":false,"usgs":false,"family":"van Dijken","given":"Gert","email":"","affiliations":[],"preferred":false,"id":698120,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Arrigo, Kevin R.","contributorId":192907,"corporation":false,"usgs":false,"family":"Arrigo","given":"Kevin","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":698116,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cronin, Thomas M. 0000-0002-2643-0979 tcronin@usgs.gov","orcid":"https://orcid.org/0000-0002-2643-0979","contributorId":2579,"corporation":false,"usgs":true,"family":"Cronin","given":"Thomas","email":"tcronin@usgs.gov","middleInitial":"M.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":698115,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wollenburg, Jutta E.","contributorId":192908,"corporation":false,"usgs":false,"family":"Wollenburg","given":"Jutta","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":698118,"contributorType":{"id":1,"text":"Authors"},"rank":15}]}}
,{"id":70039089,"text":"70039089 - 2012 - Floods in Central Texas, September 7-14, 2010","interactions":[],"lastModifiedDate":"2012-07-19T01:01:49","indexId":"70039089","displayToPublicDate":"2012-07-18T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3536,"text":"Texas Water Journal","active":true,"publicationSubtype":{"id":10}},"title":"Floods in Central Texas, September 7-14, 2010","docAbstract":"Severe flooding occurred near the Austin metropolitan area in central Texas September 7&ndash;14, 2010, because of heavy rainfall associated with Tropical Storm Hermine. The U.S. Geological Survey, in cooperation with the Upper Brushy Creek Water Control and Improvement District, determined rainfall amounts and annual exceedance probabilities for rainfall resulting in flooding in Bell, Williamson, and Travis counties in central Texas during September 2010. We documented peak streamflows and the annual exceedance probabilities for peak streamflows recorded at several streamflow-gaging stations in the study area. The 24-hour rainfall total exceeded 12 inches at some locations, with one report of 14.57 inches at Lake Georgetown. Rainfall probabilities were estimated using previously published depth-duration frequency maps for Texas. At 4 sites in Williamson County, the 24-hour rainfall had an annual exceedance probability of 0.002. Streamflow measurement data and flood-peak data from U.S. Geological Survey surface-water monitoring stations (streamflow and reservoir gaging stations) are presented, along with a comparison of September 2010 flood peaks to previous known maximums in the periods of record. Annual exceedance probabilities for peak streamflow were computed for 20 streamflow-gaging stations based on an analysis of streamflow-gaging station records. The annual exceedance probability was 0.03 for the September 2010 peak streamflow at the Geological Survey's streamflow-gaging stations 08104700 North Fork San Gabriel River near Georgetown, Texas, and 08154700 Bull Creek at Loop 360 near Austin, Texas. The annual exceedance probability was 0.02 for the peak streamflow for Geological Survey's streamflow-gaging station 08104500 Little River near Little River, Texas. The lack of similarity in the annual exceedance probabilities computed for precipitation and streamflow might be attributed to the small areal extent of the heaviest rainfall over these and the other gaged watersheds.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Texas Water Journal","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Texas Water Resources Institute","publisherLocation":"Austin, TX","usgsCitation":"Winters, K.E., 2012, Floods in Central Texas, September 7-14, 2010: Texas Water Journal, v. 3, no. 1, HTML Document.","productDescription":"HTML Document","numberOfPages":"12","temporalStart":"2010-09-07","temporalEnd":"2010-09-14","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":259000,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":258986,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://journals.tdl.org/twj/article/view/3292","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Texas","volume":"3","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a119ee4b0c8380cd5405b","contributors":{"authors":[{"text":"Winters, Karl E. kwinters@usgs.gov","contributorId":3554,"corporation":false,"usgs":true,"family":"Winters","given":"Karl","email":"kwinters@usgs.gov","middleInitial":"E.","affiliations":[],"preferred":true,"id":465598,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70039098,"text":"70039098 - 2012 - Evaluating the ability of regional models to predict local avian abundance","interactions":[],"lastModifiedDate":"2012-08-02T17:16:17","indexId":"70039098","displayToPublicDate":"2012-07-18T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating the ability of regional models to predict local avian abundance","docAbstract":"Spatial modeling over broad scales can potentially direct conservation efforts to areas with high species-specific abundances. We examined the performance of regional models for predicting bird abundance at spatial scales typically addressed in conservation planning. Specifically, we used point count data on wood thrush (Hylocichla mustelina) and blue-winged warbler (Vermivora cyanoptera) from 2 time periods (1995-1998 and 2006-2007) to evaluate the ability of regional models derived via Bayesian hierarchical techniques to predict bird abundance. We developed models for each species within Bird Conservation Region (BCR) 23 in the upper midwestern United States at 800-ha, 8,000-ha, and approximately 80,000-ha scales. We obtained count data from the Breeding Bird Survey and land cover data from the National Land Cover Dataset (1992). We evaluated predictions from the best models, as defined by an information-theoretic criterion, using point count data collected within an ecological subregion of BCR 23 at 131 count stations in the 1990s and again in 2006-2007. Competing (Deviance Information Criteria <5) blue-winged warbler models accounted for 67% of the variability and suggested positive associations with forest edge and proportion of forest at the 8,000-ha scale, and negative associations with forest patch area (800 ha) and wetness (800 ha and 80,000 ha). The regional model performed best for blue-winged warbler predicted abundances from point counts conducted in Iowa during 1995-1996 (<i>r</i><sub>s</sub> = 0.57; <i>P</i> = 0.14), the survey period that most closely aligned with the time period of data used for regional model construction. Wood thrush models exhibited positive correlations with point count data for all survey areas and years combined (<i>r</i><sub>s</sub> = 0.58, <i>P</i> &le; 0.001). In comparison, blue-winged warbler models performed worse as time increased between the point count surveys and vintage of the model building data (<i>r</i><sub>s</sub> = 0.03, <i>P</i> = 0.92 for Iowa and <i>r</i><sub>s</sub> = 0.13, <i>P</i> = 0.51 for all areas, 2006-2007), likely related to the ephemeral nature of their preferred early successional habitat. Species abundance and sensitivity to changing habitat conditions seems to be an important factor in determining the predictive ability of regional models. Hierarchical models can be a useful tool for concentrating efforts at the scale of management units and should be one of many tools used by land managers, but we caution that the utility of such models may decrease over time for species preferring relatively ephemeral habitats if model inputs are not updated accordingly.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Wildlife Management","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"The Wildlife Society","publisherLocation":"Bethesda, MD","doi":"10.1002/jwmg.374","usgsCitation":"LeBrun, J.J., Thogmartin, W.E., and Miller, J.R., 2012, Evaluating the ability of regional models to predict local avian abundance: Journal of Wildlife Management, v. 76, no. 6, p. 1177-1187, https://doi.org/10.1002/jwmg.374.","productDescription":"11 p.","startPage":"1177","endPage":"1187","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":258998,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":258991,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/jwmg.374","linkFileType":{"id":5,"text":"html"}}],"country":"United States","volume":"76","issue":"6","noUsgsAuthors":false,"publicationDate":"2012-05-21","publicationStatus":"PW","scienceBaseUri":"505a0bf5e4b0c8380cd5297a","contributors":{"authors":[{"text":"LeBrun, Jaymi J.","contributorId":7959,"corporation":false,"usgs":true,"family":"LeBrun","given":"Jaymi","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":465614,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thogmartin, Wayne E. 0000-0002-2384-4279 wthogmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":2545,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","email":"wthogmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":465612,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miller, James R.","contributorId":6706,"corporation":false,"usgs":true,"family":"Miller","given":"James","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":465613,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70039093,"text":"sir20125103 - 2012 - Effects of urban best management practices on streamflow and phosphorus and suspended-sediment transport on Englesby Brook in Burlington, Vermont, 2000-2010","interactions":[],"lastModifiedDate":"2012-07-19T01:01:49","indexId":"sir20125103","displayToPublicDate":"2012-07-18T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-5103","title":"Effects of urban best management practices on streamflow and phosphorus and suspended-sediment transport on Englesby Brook in Burlington, Vermont, 2000-2010","docAbstract":"An assessment of the effectiveness of several urban best management practice structures, including a wet extended detention facility and a shallow marsh wetland (together the \"wet extended detention ponds\"), was made using data collected from 2000 through 2010 at Englesby Brook in Burlington, Vermont. The purpose of the best management practices was to reduce high streamflows and phosphorus and suspended-sediment loads and concentrations and to increase low streamflows. Englesby Brook was monitored for streamflow, phosphorus, and suspended-sediment concentrations at a streamgage downstream of the best management practice structures for 5 years before the wet extended detention ponds were constructed in 2005 and for 4 years (phosphorus and suspended-sediment concentrations) or 5 years (streamflow) after they were constructed. The period after construction of the best management practice structures was wetter and had higher discharges than the period before construction. Despite the wetter conditions, streamflow duration curves provided evidence that the streamflow regime appeared to have shifted so that the percentages of low streamflows have increased and those of high streamflows may have slightly decreased. Two other hydrologic measures showed improvements in the years following construction of the best management practices: the percentage of annual discharge transported during the 3 days with highest discharges and the number of days with zero streamflow have both decreased. Evidence was mixed for the effectiveness of the best management practices in reducing phosphorus and suspended-sediment concentrations and loads. Annual phosphorus and suspended-sediment loads, monthly loads, low-streamflow concentrations, storm-averaged streamflow-adjusted concentrations, and total storm loads either did not change significantly or increased in the period after construction. These results likely were because of the wetter conditions in the period after construction. For example, monthly loads assessed using analysis of covariance, which compensated for the effects of streamflow on loads, suggested no difference in phosphorus or suspended-sediment loads between the two periods, whereas the comparison of monthly loads without factoring in streamflow showed an increase. This result could be viewed as evidence that the ponds may have mitigated the effect of greater discharges in the period after construction by preventing a corresponding increase in loads. In another analysis used to adjust for the difference in discharge between the two comparison periods, annual and monthly load results were grouped into dry and wet years. Large (50 percent) reductions in annual loads were observed when data from dry (or wet) years before construction were compared with data from dry (or wet) years after construction. When paired monthly loads of each constituent were grouped into dry and wet years, approximately the same number of months had increases as did decreases with the magnitudes of the decreases generally larger than the magnitudes of the increases. These differences in magnitude explain the decrease in annual loads for dry and wet years. The close association of phosphorus with suspended-sediment data suggested that most of the phosphorus was in the particulate form and was controlled by suspended-sediment dynamics.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125103","collaboration":"Prepared in cooperation with the Vermont Department of Environmental Conservation","usgsCitation":"Medalie, L., 2012, Effects of urban best management practices on streamflow and phosphorus and suspended-sediment transport on Englesby Brook in Burlington, Vermont, 2000-2010: U.S. Geological Survey Scientific Investigations Report 2012-5103, vii, 26 p., https://doi.org/10.3133/sir20125103.","productDescription":"vii, 26 p.","onlineOnly":"Y","temporalStart":"2000-01-01","temporalEnd":"2010-12-31","costCenters":[{"id":468,"text":"New Hampshire-Vermont Water Science Center","active":false,"usgs":true}],"links":[{"id":258993,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5103.JPG"},{"id":258982,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5103/pdf/sir2012-5103_report_508.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":258981,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5103/","linkFileType":{"id":5,"text":"html"}}],"scale":"24000","datum":"North American Datum 1983","country":"United States","state":"Vermont","county":"Burlington","otherGeospatial":"Englesby Brook Watershed","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -73.33333333333333,44 ], [ -73.33333333333333,44.833333333333336 ], [ -72.66666666666667,44.833333333333336 ], [ -72.66666666666667,44 ], [ -73.33333333333333,44 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a081fe4b0c8380cd519b2","contributors":{"authors":[{"text":"Medalie, Laura 0000-0002-2440-2149 lmedalie@usgs.gov","orcid":"https://orcid.org/0000-0002-2440-2149","contributorId":3657,"corporation":false,"usgs":true,"family":"Medalie","given":"Laura","email":"lmedalie@usgs.gov","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":465609,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70039081,"text":"70039081 - 2012 - Processes affecting geochemistry and contaminant movement in the middle Claiborne aquifer of the Mississippi embayment aquifer system","interactions":[],"lastModifiedDate":"2013-01-17T21:12:53","indexId":"70039081","displayToPublicDate":"2012-07-18T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1534,"text":"Environmental Earth Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Processes affecting geochemistry and contaminant movement in the middle Claiborne aquifer of the Mississippi embayment aquifer system","docAbstract":"Groundwater chemistry and tracer-based age data were used to assess contaminant movement and geochemical processes in the middle Claiborne aquifer (MCA) of the Mississippi embayment aquifer system. Water samples were collected from 30 drinking-water wells (mostly domestic and public supply) and analyzed for nutrients, major ions, pesticides, volatile organic compounds (VOCs), and transient age tracers (chlorofluorocarbons, tritium and helium-3, and sulfur hexafluoride). Redox conditions are highly variable throughout the MCA. However, mostly oxic groundwater with low dissolved solids is more vulnerable to nitrate contamination in the outcrop areas east of the Mississippi River in Mississippi and west Tennessee than in mostly anoxic groundwater in downgradient areas in western parts of the study area. Groundwater in the outcrop area was relatively young (apparent age of less than 40 years) with significantly (<i>p</i> < 0.05) higher dissolved oxygen and nitrate&ndash;N concentrations and higher detections of pesticides and VOCs compared to water samples from wells in downgradient areas. Oxygen reduction and denitrification rates were low compared to other aquifers in the United States (zero order rate constants for oxygen reduction and denitrification were 4.7 and 5&ndash;10 &mu;mol/L/year, respectively). Elevated concentrations of nitrate&ndash;N, and detections of pesticides and VOCs in some deep public supply wells (>50 m depth) indicated contaminant movement from shallow parts of the aquifer into deeper oxic zones. Given the persistence of nitrate in young oxic groundwater that was recharged several decades ago, and the lack of a confining unit, the downward movement of young contaminated water may result in higher nitrate concentrations over time in deeper parts of the aquifer containing older oxic water.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Environmental Earth Sciences","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","publisherLocation":"Amsterdam, Netherlands","doi":"10.1007/s12665-011-1157-y","usgsCitation":"Katz, B.G., Kingsbury, J.A., Welch, H.L., and Tollett, R.W., 2012, Processes affecting geochemistry and contaminant movement in the middle Claiborne aquifer of the Mississippi embayment aquifer system: Environmental Earth Sciences, v. 65, no. 6, p. 1759-1780, https://doi.org/10.1007/s12665-011-1157-y.","productDescription":"22 p.","startPage":"1759","endPage":"1780","costCenters":[{"id":288,"text":"Florida Water Science Center-Tallahassee","active":false,"usgs":true}],"links":[{"id":259003,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":258990,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s12665-011-1157-y","linkFileType":{"id":5,"text":"html"}}],"country":"United States","otherGeospatial":"Claiborne Aquifer;Mississippi Embayment","volume":"65","issue":"6","noUsgsAuthors":false,"publicationDate":"2011-08-17","publicationStatus":"PW","scienceBaseUri":"505a8da7e4b0c8380cd7ed47","contributors":{"authors":[{"text":"Katz, Brian G. bkatz@usgs.gov","contributorId":1093,"corporation":false,"usgs":true,"family":"Katz","given":"Brian","email":"bkatz@usgs.gov","middleInitial":"G.","affiliations":[],"preferred":true,"id":465596,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kingsbury, James A. 0000-0003-4985-275X jakingsb@usgs.gov","orcid":"https://orcid.org/0000-0003-4985-275X","contributorId":883,"corporation":false,"usgs":true,"family":"Kingsbury","given":"James","email":"jakingsb@usgs.gov","middleInitial":"A.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true}],"preferred":true,"id":465595,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Welch, Heather L. 0000-0001-8370-7711 hllott@usgs.gov","orcid":"https://orcid.org/0000-0001-8370-7711","contributorId":552,"corporation":false,"usgs":true,"family":"Welch","given":"Heather","email":"hllott@usgs.gov","middleInitial":"L.","affiliations":[{"id":105,"text":"Alabama Water Science Center","active":true,"usgs":true}],"preferred":true,"id":465594,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tollett, Roland W. 0000-0002-4726-5845 rtollett@usgs.gov","orcid":"https://orcid.org/0000-0002-4726-5845","contributorId":1896,"corporation":false,"usgs":true,"family":"Tollett","given":"Roland","email":"rtollett@usgs.gov","middleInitial":"W.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":465597,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70039045,"text":"70039045 - 2012 - Cyclic biogeochemical processes and nitrogen fate beneath a subtropical stormwater infiltration basin","interactions":[],"lastModifiedDate":"2012-07-19T01:01:49","indexId":"70039045","displayToPublicDate":"2012-07-18T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2233,"text":"Journal of Contaminant Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Cyclic biogeochemical processes and nitrogen fate beneath a subtropical stormwater infiltration basin","docAbstract":"A stormwater infiltration basin in north&ndash;central Florida, USA, was monitored from 2007 through 2008 to identify subsurface biogeochemical processes, with emphasis on N cycling, under the highly variable hydrologic conditions common in humid, subtropical climates. Cyclic variations in biogeochemical processes generally coincided with wet and dry hydrologic conditions. Oxidizing conditions in the subsurface persisted for about one month or less at the beginning of wet periods with dissolved O<sub>2</sub> and NO<sub>3</sub>- showing similar temporal patterns. Reducing conditions in the subsurface evolved during prolonged flooding of the basin. At about the same time O<sub>2</sub> and NO<sub>3</sub>- reduction concluded, Mn, Fe and SO<sub>4</sub><sup>2</sup>- reduction began, with the onset of methanogenesis one month later. Reducing conditions persisted up to six months, continuing into subsequent dry periods until the next major oxidizing infiltration event. Evidence of denitrification in shallow groundwater at the site is supported by median NO<sub>3</sub>-&ndash;N less than 0.016 mg L<sup>-1</sup>, excess N<sub>2</sub> up to 3 mg L<sup>-1</sup> progressively enriched in &delta;<sup>15</sup>N during prolonged basin flooding, and isotopically heavy &delta;<sup>15</sup>N and &delta;<sup>18</sup>O of NO<sub>3</sub>- (up to 25&permil; and 15&permil;, respectively). Isotopic enrichment of newly infiltrated stormwater suggests denitrification was partially completed within two days. Soil and water chemistry data suggest that a biogeochemically active zone exists in the upper 1.4 m of soil, where organic carbon was the likely electron donor supplied by organic matter in soil solids or dissolved in infiltrating stormwater. The cyclic nature of reducing conditions effectively controlled the N cycle, switching N fate beneath the basin from NO<sub>3</sub>- leaching to reduction in the shallow saturated zone. Results can inform design of functionalized soil amendments that could replace the native soil in a stormwater infiltration basin and mitigate potential NO<sub>3</sub>- leaching to groundwater by replicating the biogeochemical conditions under the observed basin.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Contaminant Hydrology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.jconhyd.2012.03.005","usgsCitation":"O’Reilly, A.M., Chang, N., and Wanielista, M.P., 2012, Cyclic biogeochemical processes and nitrogen fate beneath a subtropical stormwater infiltration basin: Journal of Contaminant Hydrology, v. 133, p. 53-75, https://doi.org/10.1016/j.jconhyd.2012.03.005.","productDescription":"23 p.","startPage":"53","endPage":"75","costCenters":[{"id":287,"text":"Florida Water Science Center-Orlando","active":false,"usgs":true}],"links":[{"id":501645,"rank":10000,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://stars.library.ucf.edu/facultybib2010/3101","text":"External Repository"},{"id":258996,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":258987,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.jconhyd.2012.03.005","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Florida","volume":"133","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059fd22e4b0c8380cd4e655","contributors":{"authors":[{"text":"O’Reilly, Andrew M. 0000-0003-3220-1248 aoreilly@usgs.gov","orcid":"https://orcid.org/0000-0003-3220-1248","contributorId":2184,"corporation":false,"usgs":true,"family":"O’Reilly","given":"Andrew","email":"aoreilly@usgs.gov","middleInitial":"M.","affiliations":[{"id":5051,"text":"FLWSC-Orlando","active":true,"usgs":true}],"preferred":true,"id":465515,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chang, Ni-Bin","contributorId":20205,"corporation":false,"usgs":false,"family":"Chang","given":"Ni-Bin","email":"","affiliations":[{"id":12564,"text":"Department of Biology, University of Central Florida","active":true,"usgs":false}],"preferred":false,"id":465516,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wanielista, Martin P.","contributorId":62069,"corporation":false,"usgs":false,"family":"Wanielista","given":"Martin","email":"","middleInitial":"P.","affiliations":[{"id":12564,"text":"Department of Biology, University of Central Florida","active":true,"usgs":false}],"preferred":false,"id":465517,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
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