{"pageNumber":"708","pageRowStart":"17675","pageSize":"25","recordCount":40783,"records":[{"id":70044427,"text":"70044427 - 2012 - Stable isotopes to detect food-conditioned bears and to evaluate human-bear management","interactions":[],"lastModifiedDate":"2013-05-07T10:49:35","indexId":"70044427","displayToPublicDate":"2012-05-16T00:00:00","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":"Stable isotopes to detect food-conditioned bears and to evaluate human-bear management","docAbstract":"We used genetic and stable isotope analysis of hair from free-ranging black bears (Ursus americanus) in Yosemite National Park, California, USA to: 1) identify bears that consume human food, 2) estimate the diets of these bears, and 3) evaluate the Yosemite human–bear management program. Specifically, we analyzed the isotopic composition of hair from bears known a priori to be food-conditioned or non-food-conditioned and used these data to predict whether bears with an unknown management status were food-conditioned (FC) or non-food-conditioned (NFC). We used a stable isotope mixing model to estimate the proportional contribution of natural foods (plants and animals) versus human food in the diets of FC bears. We then used results from both analyses to evaluate proactive (population-level) and reactive (individual-level) human–bear management, and discussed new metrics to evaluate the overall human–bear management program in Yosemite. Our results indicated that 19 out of 145 (13%) unknown bears sampled from 2005 to 2007 were food-conditioned. The proportion of human food in the diets of known FC bears likely declined from 2001–2003 to 2005–2007, suggesting proactive management was successful in reducing the amount of human food available to bears. In contrast, reactive management was not successful in changing the management status of known FC bears to NFC bears, or in reducing the contribution of human food to the diets of FC bears. Nine known FC bears were recaptured on 14 occasions from 2001 to 2007; all bears were classified as FC during subsequent recaptures, and human–bear management did not reduce the amount of human food in the diets of FC bears. Based on our results, we suggest Yosemite continue implementing proactive human–bear management, reevaluate reactive management, and consider removing problem bears (those involved in repeated bear incidents) from the population.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Wildlife Management","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1002/jwmg.318","usgsCitation":"Hopkins, J.B., Koch, P.L., Schwartz, C.C., Ferguson, J.M., Greenleaf, S.S., and Kalinowski, S.T., 2012, Stable isotopes to detect food-conditioned bears and to evaluate human-bear management: Journal of Wildlife Management, v. 76, no. 4, p. 703-713, https://doi.org/10.1002/jwmg.318.","productDescription":"11 p.","startPage":"703","endPage":"713","numberOfPages":"11","ipdsId":"IP-028784","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":271941,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":271934,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/jwmg.318"}],"country":"United States","state":"California","otherGeospatial":"Yosemite National Park","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -119.88,37.49 ], [ -119.88,38.18 ], [ -119.19,38.18 ], [ -119.19,37.49 ], [ -119.88,37.49 ] ] ] } } ] }","volume":"76","issue":"4","noUsgsAuthors":false,"publicationDate":"2012-01-12","publicationStatus":"PW","scienceBaseUri":"518a227ae4b061e1bd5334c0","contributors":{"authors":[{"text":"Hopkins, John B. III","contributorId":42112,"corporation":false,"usgs":true,"family":"Hopkins","given":"John","suffix":"III","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":475576,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Koch, Paul L.","contributorId":6742,"corporation":false,"usgs":true,"family":"Koch","given":"Paul","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":475573,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schwartz, Charles C.","contributorId":55950,"corporation":false,"usgs":true,"family":"Schwartz","given":"Charles","email":"","middleInitial":"C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":false,"id":475577,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ferguson, Jake M.","contributorId":17895,"corporation":false,"usgs":true,"family":"Ferguson","given":"Jake","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":475575,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Greenleaf, Schuyler S.","contributorId":16729,"corporation":false,"usgs":true,"family":"Greenleaf","given":"Schuyler","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":475574,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kalinowski, Steven T.","contributorId":78465,"corporation":false,"usgs":true,"family":"Kalinowski","given":"Steven","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":475578,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70038371,"text":"ofr20121011 - 2012 - Logs and data from trenches across and near the Green Valley Fault at the Mason Road site, Fairfield, Solano County, California, 2006-2009","interactions":[],"lastModifiedDate":"2012-05-17T01:01:41","indexId":"ofr20121011","displayToPublicDate":"2012-05-15T20:35:00","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":"2012-1011","title":"Logs and data from trenches across and near the Green Valley Fault at the Mason Road site, Fairfield, Solano County, California, 2006-2009","docAbstract":"The primary purpose of this report is to provide drafted field logs of exploratory trenches excavated across the Green Valley Fault in 2007 and 2009 that show evidence for four surface rupturing earthquakes in the past one thousand years. The site location and site detail are shown on sheet 1. The trench logs are shown on sheets 1, 2, and 3. We also provide radiocarbon laboratory dates used for chronological modeling of the earthquake history. Sheets 4 and 5 show additional data obtained in 2006–2009 to document data obtained in our studies of the long-term geologic slip rate on the Green Valley Fault. However, that effort ultimately did not prove feasible and no slip rate estimate resulted.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121011","usgsCitation":"Lienkaemper, J.J., Sickler, R.R., Mahan, S., Brown, J., Reidy, L.M., and Kimball, M.A., 2012, Logs and data from trenches across and near the Green Valley Fault at the Mason Road site, Fairfield, Solano County, California, 2006-2009: U.S. Geological Survey Open-File Report 2012-1011, Pamphlet: iii, 5 p.; Sheet 1: 36.00 x 24.00 inches; Sheet 2: 36.00 x 18.00 inches; Sheet 3: 24.00 x 15.00 inches; Sheet 4: 24.00 x 20.00 inches; Sheet 5: 17.00 x 11.00 inches, https://doi.org/10.3133/ofr20121011.","productDescription":"Pamphlet: iii, 5 p.; Sheet 1: 36.00 x 24.00 inches; Sheet 2: 36.00 x 18.00 inches; Sheet 3: 24.00 x 15.00 inches; Sheet 4: 24.00 x 20.00 inches; Sheet 5: 17.00 x 11.00 inches","onlineOnly":"Y","temporalStart":"2006-01-01","temporalEnd":"2009-12-31","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":379,"text":"Menlo Park Science Center","active":false,"usgs":true}],"links":[{"id":256853,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1011.gif"},{"id":256850,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1011/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"California","county":"Solano","city":"Fairfield","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a494fe4b0c8380cd684de","contributors":{"authors":[{"text":"Lienkaemper, James J. 0000-0002-7578-7042 jlienk@usgs.gov","orcid":"https://orcid.org/0000-0002-7578-7042","contributorId":1941,"corporation":false,"usgs":true,"family":"Lienkaemper","given":"James","email":"jlienk@usgs.gov","middleInitial":"J.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":463999,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sickler, Robert R. 0000-0002-9141-625X rsickler@usgs.gov","orcid":"https://orcid.org/0000-0002-9141-625X","contributorId":3235,"corporation":false,"usgs":true,"family":"Sickler","given":"Robert","email":"rsickler@usgs.gov","middleInitial":"R.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":464000,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mahan, Shannon 0000-0001-5214-7774 smahan@usgs.gov","orcid":"https://orcid.org/0000-0001-5214-7774","contributorId":1215,"corporation":false,"usgs":true,"family":"Mahan","given":"Shannon","email":"smahan@usgs.gov","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":false,"id":463998,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brown, Johnathan","contributorId":56082,"corporation":false,"usgs":true,"family":"Brown","given":"Johnathan","email":"","affiliations":[],"preferred":false,"id":464001,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Reidy, Liam M.","contributorId":105372,"corporation":false,"usgs":true,"family":"Reidy","given":"Liam","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":464003,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kimball, Mindy A.","contributorId":72241,"corporation":false,"usgs":true,"family":"Kimball","given":"Mindy","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":464002,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70038370,"text":"sir20125064 - 2012 - Use of real-time monitoring to predict concentrations of select constituents in the Menomonee River drainage basin, Southeast Wisconsin, 2008-9","interactions":[],"lastModifiedDate":"2018-02-06T12:28:47","indexId":"sir20125064","displayToPublicDate":"2012-05-15T20:09:00","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":"2012-5064","title":"Use of real-time monitoring to predict concentrations of select constituents in the Menomonee River drainage basin, Southeast Wisconsin, 2008-9","docAbstract":"<p>The Menomonee River drainage basin in southeast Wisconsin is undergoing changes that may affect water quality. Several rehabilitation and flood-management projects are underway, including removal of concrete channels and the construction of floodwater retention basins. The city of Waukesha may begin discharging treated wastewater into Underwood Creek, thus approximately doubling the current base-flow discharge. In addition, the headwater basins, historically dominated by agriculture and natural areas, are becoming increasingly urbanized.</p>\n<p>In an effort to monitor these and future changes to the basin, the U.S. Geological Survey and the Milwaukee Metropolitan Sewerage District initiated a study in 2008 to develop regression models to estimate real-time concentrations and loads of selected water-quality constituents. Water-quality sensors and automated samplers were installed at five sites in the Menomonee River drainage basin. The sensors continuously measured four explanatory variables: water temperature, specific conductance, dissolved oxygen, and turbidity. Discrete water-quality samples were collected and analyzed for five response variables: chloride, total suspended solids, total phosphorus, <i>Escherichia coli</i> bacteria, and fecal coliform bacteria. Regression models were developed to continuously estimate the response variables on the basis of the explanatory variables.</p>\n<p>The models to estimate chloride concentrations all used specific conductance as the explanatory variable, except for the model for the Little Menomonee River near Freistadt, which used both specific conductance and turbidity as explanatory variables. Adjusted R<sup>2</sup> values for the chloride models ranged from 0.74 to 0.97. Models to estimate total suspended solids and total phosphorus used turbidity as the only explanatory variable. Adjusted R<sup>2</sup> values ranged from 0.77 to 0.94 for the total suspended solids models and from 0.55 to 0.75 for the total phosphorus models. Models to estimate indicator bacteria used water temperature and turbidity as the explanatory variables, with adjusted R<sup>2</sup> values from 0.54 to 0.69 for <i>Escherichia coli</i> bacteria models and from 0.54 to 0.74 for fecal coliform bacteria models. Dissolved oxygen was not used in any of the final models. These models may help managers measure the effects of land-use changes and improvement projects, establish total maximum daily loads, estimate important water-quality indicators such as bacteria concentrations, and enable informed decision making in the future.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125064","collaboration":"Prepared in cooperation with the Milwaukee Metropolitan Sewerage District","usgsCitation":"Baldwin, A.K., Graczyk, D., Robertson, D.M., Saad, D.A., and Magruder, C., 2012, Use of real-time monitoring to predict concentrations of select constituents in the Menomonee River drainage basin, Southeast Wisconsin, 2008-9: U.S. Geological Survey Scientific Investigations Report 2012-5064, viii, 18 p.; Appendices Downloads, https://doi.org/10.3133/sir20125064.","productDescription":"viii, 18 p.; Appendices Downloads","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2008-01-01","temporalEnd":"2009-12-31","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":256852,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5064.jpg"},{"id":256849,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5064/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Wisconsin","otherGeospatial":"Menomonee River Drainage Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -88.11666666666666,42.8 ], [ -88.11666666666666,43.333333333333336 ], [ -87.7,43.333333333333336 ], [ -87.7,42.8 ], [ -88.11666666666666,42.8 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505bbf68e4b08c986b329b3d","contributors":{"authors":[{"text":"Baldwin, Austin K. 0000-0002-6027-3823 akbaldwi@usgs.gov","orcid":"https://orcid.org/0000-0002-6027-3823","contributorId":4515,"corporation":false,"usgs":true,"family":"Baldwin","given":"Austin","email":"akbaldwi@usgs.gov","middleInitial":"K.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":463995,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Graczyk, David J.","contributorId":107265,"corporation":false,"usgs":true,"family":"Graczyk","given":"David J.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":false,"id":463997,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Robertson, Dale M. 0000-0001-6799-0596 dzrobert@usgs.gov","orcid":"https://orcid.org/0000-0001-6799-0596","contributorId":150760,"corporation":false,"usgs":true,"family":"Robertson","given":"Dale","email":"dzrobert@usgs.gov","middleInitial":"M.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":463993,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Saad, David A. dasaad@usgs.gov","contributorId":121,"corporation":false,"usgs":true,"family":"Saad","given":"David","email":"dasaad@usgs.gov","middleInitial":"A.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":463994,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Magruder, Christopher","contributorId":35995,"corporation":false,"usgs":true,"family":"Magruder","given":"Christopher","affiliations":[],"preferred":false,"id":463996,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70038364,"text":"sir20115228 - 2012 - Evaluation of geophysical techniques for the detection of paleochannels in the Oakland area of eastern Nebraska as part of the Eastern Nebraska Water Resource Assessment","interactions":[],"lastModifiedDate":"2012-05-15T01:01:40","indexId":"sir20115228","displayToPublicDate":"2012-05-14T15:35:00","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":"2011-5228","title":"Evaluation of geophysical techniques for the detection of paleochannels in the Oakland area of eastern Nebraska as part of the Eastern Nebraska Water Resource Assessment","docAbstract":"<p>Over the winter and spring of 2009, the U.S. Geological Survey conducted a general assessment of the capabilities of several geophysical tools to delineate buried paleochannel aquifers in the glacial terrain of eastern Nebraska. Mapping these paleochannels is an important objective for the Eastern Nebraska Water Resources Assessment group. Previous attempts at mapping these channels included a helicopter electromagnetic survey flown over an area near the town of Oakland, Nebraska, in March 2007. This survey had limited success in imaging the paleochannels due to the restricted depth of investigation of the system in the clay-rich till overburden. The purpose of this study was to investigate whether other airborne electromagnetic or surface geophysical techniques, including audio-magnetotelluric, time-domain electromagnetic, gravity, and magnetic methods, could be used to image the paleochannels in the clay-rich tills of eastern Nebraska. This report releases the results of testing the ability of selected geophysical techniques to map aquifers in glacial deposits near the town of Oakland, Nebraska.</p>\n<p>Surface audio-magnetotelluric and time-domain electromagnetic methods achieved sufficient depth of penetration and indicated that the paleochannel was much more complex than the original geological model. Simulated and observed gravity anomalies indicate that imaging sand and gravel aquifers near Oakland, Nebraska, would be difficult due to the complex basement density contrasts. Interpretation of the magnetic data indicates no magnetic sources from geologic units above the bedrock surface. Based upon the analysis and interpretation of the four methods evaluated, we suggest a large-scale survey using a high-powered time-domain airborne system. This is the most efficient and cost-effective path forward for the Eastern Nebraska Water Assessment group to map paleochannels that lie beneath thick clay-rich glacial tills.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20115228","collaboration":"Prepared in cooperation with the Eastern Nebraska Water Resource Assessment","usgsCitation":"Abraham, J., Bedrosian, P.A., Asch, T., Ball, L.B., Cannia, J.C., Phillips, J.D., and Lackey, S., 2012, Evaluation of geophysical techniques for the detection of paleochannels in the Oakland area of eastern Nebraska as part of the Eastern Nebraska Water Resource Assessment: U.S. Geological Survey Scientific Investigations Report 2011-5228, viii, 40 p., https://doi.org/10.3133/sir20115228.","productDescription":"viii, 40 p.","temporalStart":"2009-01-01","temporalEnd":"2009-12-31","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":254769,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2011_5228.gif"},{"id":254766,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2011/5228/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Nebraska","city":"Oakland","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -98,40 ], [ -98,43 ], [ -95,43 ], [ -95,40 ], [ -98,40 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a0c7de4b0c8380cd52b86","contributors":{"authors":[{"text":"Abraham, Jared D.","contributorId":42630,"corporation":false,"usgs":true,"family":"Abraham","given":"Jared D.","affiliations":[],"preferred":false,"id":463971,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bedrosian, Paul A. 0000-0002-6786-1038 pbedrosian@usgs.gov","orcid":"https://orcid.org/0000-0002-6786-1038","contributorId":839,"corporation":false,"usgs":true,"family":"Bedrosian","given":"Paul","email":"pbedrosian@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":463969,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Asch, Theodore H.","contributorId":83617,"corporation":false,"usgs":true,"family":"Asch","given":"Theodore H.","affiliations":[],"preferred":false,"id":463974,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ball, Lyndsay B. 0000-0002-6356-4693 lbball@usgs.gov","orcid":"https://orcid.org/0000-0002-6356-4693","contributorId":1138,"corporation":false,"usgs":true,"family":"Ball","given":"Lyndsay","email":"lbball@usgs.gov","middleInitial":"B.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":463970,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cannia, James C.","contributorId":94356,"corporation":false,"usgs":true,"family":"Cannia","given":"James","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":463975,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Phillips, Jeffery D.","contributorId":63489,"corporation":false,"usgs":true,"family":"Phillips","given":"Jeffery","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":463973,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lackey, Susan","contributorId":44397,"corporation":false,"usgs":true,"family":"Lackey","given":"Susan","email":"","affiliations":[],"preferred":false,"id":463972,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70038360,"text":"sir20125032 - 2012 - Microbial mineralization of cis-dichloroethene and vinyl chloride as a component of natural attenuation of chloroethene contaminants under conditions identified in the field as anoxic","interactions":[],"lastModifiedDate":"2017-01-17T17:35:11","indexId":"sir20125032","displayToPublicDate":"2012-05-14T00:00:00","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":"2012-5032","title":"Microbial mineralization of cis-dichloroethene and vinyl chloride as a component of natural attenuation of chloroethene contaminants under conditions identified in the field as anoxic","docAbstract":"Chlororespiration is a key component of remediation at many chloroethene-contaminated sites. In some instances, limited accumulation of reductive dechlorination daughter products may suggest that natural attenuation is not adequate for site remediation. This conclusion is justified when evidence for parent compound (tetrachloroethene, PCE, or trichloroethene, TCE) degradation is lacking. For many chloroethene-contaminated shallow aquifer systems, however, non-conservative losses of the parent compounds are clear but the mass balance between parent compound attenuation and accumulation of reductive dechlorination daughter products is incomplete. Incomplete mass balance indicates a failure to account for important contaminant attenuation mechanisms, and is consistent with contaminant degradation to non-diagnostic mineralization products. An ongoing technical debate over the potential for mineralization of dichloroethene (DCE) and vinyl chloride (VC) to CO<sub>2</sub> in the complete absence of diatomic oxygen has largely obscured the importance of microbial DCE/VC mineralization at dissolved oxygen (DO) concentrations below the current field standard (DO < 0.1-0.5 milligrams per liter) for nominally anoxic conditions. This study demonstrates that oxygen-based microbial mineralization of DCE and VC can be substantial under field conditions that are frequently characterized as \"anoxic.\" Because mischaracterization of operant contaminant biodegradation processes can lead to expensive and ineffective remedial actions, a modified framework for assessing the potential importance of oxygen during chloroethene biodegradation was developed.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125032","collaboration":"Prepared in cooperation with the Strategic Environmental Research and Development Program","usgsCitation":"Bradley, P.M., 2012, Microbial mineralization of cis-dichloroethene and vinyl chloride as a component of natural attenuation of chloroethene contaminants under conditions identified in the field as anoxic: U.S. Geological Survey Scientific Investigations Report 2012-5032, vi, 30 p., https://doi.org/10.3133/sir20125032.","productDescription":"vi, 30 p.","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":254767,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5032.jpg"},{"id":254762,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5032/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a5654e4b0c8380cd6d4f6","contributors":{"authors":[{"text":"Bradley, Paul M. 0000-0001-7522-8606 pbradley@usgs.gov","orcid":"https://orcid.org/0000-0001-7522-8606","contributorId":361,"corporation":false,"usgs":true,"family":"Bradley","given":"Paul","email":"pbradley@usgs.gov","middleInitial":"M.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":463961,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70045158,"text":"70045158 - 2012 - Sunspot random walk and 22-year variation","interactions":[],"lastModifiedDate":"2013-05-14T12:54:49","indexId":"70045158","displayToPublicDate":"2012-05-14T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Sunspot random walk and 22-year variation","docAbstract":"We examine two stochastic models for consistency with observed long-term secular trends in sunspot number and a faint, but semi-persistent, 22-yr signal: (1) a null hypothesis, a simple one-parameter random-walk model of sunspot-number cycle-to-cycle change, and, (2) an alternative hypothesis, a two-parameter random-walk model with an imposed 22-yr alternating amplitude. The observed secular trend in sunspots, seen from solar cycle 5 to 23, would not be an unlikely result of the accumulation of multiple random-walk steps. Statistical tests show that a 22-yr signal can be resolved in historical sunspot data; that is, the probability is low that it would be realized from random data. On the other hand, the 22-yr signal has a small amplitude compared to random variation, and so it has a relatively small effect on sunspot predictions. Many published predictions for cycle 24 sunspots fall within the dispersion of previous cycle-to-cycle sunspot differences. The probability is low that the Sun will, with the accumulation of random steps over the next few cycles, walk down to a Dalton-like minimum. Our models support published interpretations of sunspot secular variation and 22-yr variation resulting from cycle-to-cycle accumulation of dynamo-generated magnetic energy.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Geophysical Research Letters","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1029/2012GL051818","usgsCitation":"Love, J.J., and Rigler, E.J., 2012, Sunspot random walk and 22-year variation: Geophysical Research Letters, v. 39, no. 10, L10103; 6 p., https://doi.org/10.1029/2012GL051818.","productDescription":"L10103; 6 p.","ipdsId":"IP-037892","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":474507,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2012gl051818","text":"Publisher Index Page"},{"id":272244,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":272243,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1029/2012GL051818"}],"volume":"39","issue":"10","noUsgsAuthors":false,"publicationDate":"2012-05-25","publicationStatus":"PW","scienceBaseUri":"53cd755be4b0b2908510a333","contributors":{"authors":[{"text":"Love, Jeffrey J. 0000-0002-3324-0348 jlove@usgs.gov","orcid":"https://orcid.org/0000-0002-3324-0348","contributorId":760,"corporation":false,"usgs":true,"family":"Love","given":"Jeffrey","email":"jlove@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":476965,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rigler, E. Joshua","contributorId":64533,"corporation":false,"usgs":true,"family":"Rigler","given":"E.","email":"","middleInitial":"Joshua","affiliations":[],"preferred":false,"id":476966,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70038362,"text":"ofr20121084 - 2012 - National assessment of hurricane-induced coastal erosion hazards--Gulf of Mexico","interactions":[],"lastModifiedDate":"2017-07-05T10:51:06","indexId":"ofr20121084","displayToPublicDate":"2012-05-14T00:00:00","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":"2012-1084","title":"National assessment of hurricane-induced coastal erosion hazards--Gulf of Mexico","docAbstract":"Sandy beaches provide a natural barrier between the ocean and inland communities, ecosystems, and resources. However, these dynamic environments move and change in response to winds, waves, and currents. During a hurricane, these changes can be large and sometimes catastrophic. High waves and storm surge act together to erode beaches and inundate low-lying lands, putting inland communities at risk. A decade of USGS research on storm-driven coastal change hazards has provided the data and modeling capabilities to identify areas of our coastline that are likely to experience extreme and potentially hazardous erosion during a hurricane. This report defines hurricane-induced coastal erosion hazards for sandy beaches along the U.S. Gulf of Mexico coastline. The analysis is based on a storm-impact scaling model that uses observations of beach morphology combined with sophisticated hydrodynamic models to predict how the coast will respond to the direct landfall of category 1-5 hurricanes. Hurricane-induced water levels, due to both surge and waves, are compared to beach and dune elevations to determine the probabilities of three types of coastal change: collision (dune erosion), overwash, and inundation. As new beach morphology observations and storm predictions become available, this analysis will be updated to describe how coastal vulnerability to storms will vary in the future.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121084","usgsCitation":"Stockdon, H.F., Doran, K., Thompson, D.M., Sopkin, K.L., Plant, N.G., and Sallenger, A., 2012, National assessment of hurricane-induced coastal erosion hazards--Gulf of Mexico: U.S. Geological Survey Open-File Report 2012-1084, vii, 49 p.; Tables; Spatial Datasets; Metadata, https://doi.org/10.3133/ofr20121084.","productDescription":"vii, 49 p.; Tables; Spatial Datasets; Metadata","numberOfPages":"58","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":438815,"rank":101,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9N01XLQ","text":"USGS data release","linkHelpText":"National Assessment of Hurricane-Induced Coastal Erosion Hazards: Puerto Rico"},{"id":438814,"rank":101,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P99ILAB9","text":"USGS data release","linkHelpText":"National Assessment of Hurricane-Induced Coastal Erosion Hazards"},{"id":438813,"rank":101,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7GF0S0Z","text":"USGS data release","linkHelpText":"Lidar-derived Beach Morphology (Dune Crest, Dune Toe, and Shoreline) for U.S. Sandy Coastlines"},{"id":343302,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1084/pdf/ofr2012-1084.pdf","size":"1.9 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":254768,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1084.jpg"},{"id":254763,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1084/","linkFileType":{"id":5,"text":"html"}},{"id":343303,"rank":4,"type":{"id":28,"text":"Dataset"},"url":"https://olga.er.usgs.gov/data/NACCH/GOM_erosion_hazards.zip","text":"Gulf of Mexico Coastal Erosion Hazards Dataset","size":"325 KB","linkFileType":{"id":6,"text":"zip"}},{"id":343304,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7QC01KZ","text":"National Assessment of Hurricane-Induced Coastal Erosion Hazards: Gulf of Mexico Update"}],"otherGeospatial":"Gulf Of Mexico","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a625de4b0c8380cd71e98","contributors":{"authors":[{"text":"Stockdon, Hilary F. 0000-0003-0791-4676 hstockdon@usgs.gov","orcid":"https://orcid.org/0000-0003-0791-4676","contributorId":2153,"corporation":false,"usgs":true,"family":"Stockdon","given":"Hilary","email":"hstockdon@usgs.gov","middleInitial":"F.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":463962,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Doran, Kara S. 0000-0001-8050-5727 kdoran@usgs.gov","orcid":"https://orcid.org/0000-0001-8050-5727","contributorId":2496,"corporation":false,"usgs":true,"family":"Doran","given":"Kara S.","email":"kdoran@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":463963,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thompson, David M. 0000-0002-7103-5740 dthompson@usgs.gov","orcid":"https://orcid.org/0000-0002-7103-5740","contributorId":3502,"corporation":false,"usgs":true,"family":"Thompson","given":"David","email":"dthompson@usgs.gov","middleInitial":"M.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":463964,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sopkin, Kristin L. ksopkin@usgs.gov","contributorId":4437,"corporation":false,"usgs":true,"family":"Sopkin","given":"Kristin","email":"ksopkin@usgs.gov","middleInitial":"L.","affiliations":[],"preferred":true,"id":463966,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Plant, Nathaniel G. 0000-0002-5703-5672 nplant@usgs.gov","orcid":"https://orcid.org/0000-0002-5703-5672","contributorId":3503,"corporation":false,"usgs":true,"family":"Plant","given":"Nathaniel","email":"nplant@usgs.gov","middleInitial":"G.","affiliations":[{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":463965,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sallenger, Asbury H. Jr.","contributorId":27458,"corporation":false,"usgs":true,"family":"Sallenger","given":"Asbury H.","suffix":"Jr.","affiliations":[],"preferred":false,"id":463967,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70037955,"text":"70037955 - 2012 - Applications of fluorescence spectroscopy for predicting percent wastewater in an urban stream","interactions":[],"lastModifiedDate":"2012-05-12T01:01:38","indexId":"70037955","displayToPublicDate":"2012-05-11T11:04:00","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":"Applications of fluorescence spectroscopy for predicting percent wastewater in an urban stream","docAbstract":"Dissolved organic carbon (DOC) is a significant organic carbon reservoir in many ecosystems, and its characteristics and sources determine many aspects of ecosystem health and water quality. Fluorescence spectroscopy methods can quantify and characterize the subset of the DOC pool that can absorb and re-emit electromagnetic energy as fluorescence and thus provide a rapid technique for environmental monitoring of DOC in lakes and rivers. Using high resolution fluorescence techniques, we characterized DOC in the Tualatin River watershed near Portland, Oregon, and identified fluorescence parameters associated with effluent from two wastewater treatment plants and samples from sites within and outside the urban region. Using a variety of statistical approaches, we developed and validated a multivariate linear regression model to predict the amount of wastewater in the river as a function of the relative abundance of specific fluorescence excitation/emission pairs. The model was tested with independent data and predicts the percentage of wastewater in a sample within 80% confidence. Model results can be used to develop in situ instrumentation, inform monitoring programs, and develop additional water quality indicators for aquatic systems.","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/es2041114","usgsCitation":"Goldman, J.H., Rounds, S.A., and Needoba, J.A., 2012, Applications of fluorescence spectroscopy for predicting percent wastewater in an urban stream: Environmental Science & Technology, v. 46, no. 8, p. 4374-4381, https://doi.org/10.1021/es2041114.","productDescription":"8 p.","startPage":"4374","endPage":"4381","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":254746,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":254738,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1021/es2041114","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Oregon","otherGeospatial":"Tualatin River","volume":"46","issue":"8","noUsgsAuthors":false,"publicationDate":"2012-04-03","publicationStatus":"PW","scienceBaseUri":"5059ecc7e4b0c8380cd4949b","contributors":{"authors":[{"text":"Goldman, Jami H. 0000-0001-5466-912X jgoldman@usgs.gov","orcid":"https://orcid.org/0000-0001-5466-912X","contributorId":4848,"corporation":false,"usgs":true,"family":"Goldman","given":"Jami","email":"jgoldman@usgs.gov","middleInitial":"H.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":463144,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rounds, Stewart A. 0000-0002-8540-2206 sarounds@usgs.gov","orcid":"https://orcid.org/0000-0002-8540-2206","contributorId":905,"corporation":false,"usgs":true,"family":"Rounds","given":"Stewart","email":"sarounds@usgs.gov","middleInitial":"A.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":463143,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Needoba, Joseph A.","contributorId":92089,"corporation":false,"usgs":true,"family":"Needoba","given":"Joseph","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":463145,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70038354,"text":"ofr20121079 - 2012 - Evaluation of modeling for groundwater flow and tetrachloroethylene transport in the Milford-Souhegan glacial-drift aquifer at the Savage Municipal Well Superfund site, Milford, New Hampshire, 2011","interactions":[],"lastModifiedDate":"2012-05-12T01:01:38","indexId":"ofr20121079","displayToPublicDate":"2012-05-11T00:00:00","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":"2012-1079","title":"Evaluation of modeling for groundwater flow and tetrachloroethylene transport in the Milford-Souhegan glacial-drift aquifer at the Savage Municipal Well Superfund site, Milford, New Hampshire, 2011","docAbstract":"The U.S. Geological Survey and the New Hampshire Department of Environmental Services entered into a cooperative agreement to assist in the evaluation of remedy simulations of the MSGD aquifer that are being performed by various parties to track the remedial progress of the PCE plume. This report summarizes findings from this evaluation. Topics covered include description of groundwater flow and transport models used in the study of the Savage Superfund site (section 2), evaluation of models and their results (section 3), testing of several new simulations (section 4), an assessment of the representation of models to simulate field conditions (section 5), and an assessment of models as a tool in remedial operational decision making (section 6).","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121079","collaboration":"Prepared in cooperation with the New Hampshire Department of Environmental Services","usgsCitation":"Harte, P.T., 2012, Evaluation of modeling for groundwater flow and tetrachloroethylene transport in the Milford-Souhegan glacial-drift aquifer at the Savage Municipal Well Superfund site, Milford, New Hampshire, 2011: U.S. Geological Survey Open-File Report 2012-1079, v, 28 p.; XLS Download of Appendix, https://doi.org/10.3133/ofr20121079.","productDescription":"v, 28 p.; XLS Download of Appendix","startPage":"i","endPage":"28","numberOfPages":"33","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2011-01-01","temporalEnd":"2011-12-31","costCenters":[{"id":468,"text":"New Hampshire-Vermont Water Science Center","active":false,"usgs":true}],"links":[{"id":254732,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1079.gif"},{"id":254730,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1079/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"New Hampshire","city":"Milford","otherGeospatial":"Savage Municipal Well Superfund","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a0c9be4b0c8380cd52c09","contributors":{"authors":[{"text":"Harte, Philip T. 0000-0002-7718-1204 ptharte@usgs.gov","orcid":"https://orcid.org/0000-0002-7718-1204","contributorId":1008,"corporation":false,"usgs":true,"family":"Harte","given":"Philip","email":"ptharte@usgs.gov","middleInitial":"T.","affiliations":[{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":463945,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70007224,"text":"70007224 - 2012 - Regression models for estimating concentrations of atrazine plus deethylatrazine in shallow groundwater in agricultural areas of the United States","interactions":[],"lastModifiedDate":"2016-05-30T13:34:19","indexId":"70007224","displayToPublicDate":"2012-05-11T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2262,"text":"Journal of Environmental Quality","active":true,"publicationSubtype":{"id":10}},"title":"Regression models for estimating concentrations of atrazine plus deethylatrazine in shallow groundwater in agricultural areas of the United States","docAbstract":"<p>Tobit regression models were developed to predict the summed concentration of atrazine [6-chloro-<i>N</i>-ethyl-<i>N'</i>-(1-methylethyl)-1,3,5-triazine-2,4-diamine] and its degradate deethylatrazine [6-chloro-<i>N</i>-(1-methylethyl)-1,3,5,-triazine-2,4-diamine] (DEA) in shallow groundwater underlying agricultural settings across the conterminous United States. The models were developed from atrazine and DEA concentrations in samples from 1298 wells and explanatory variables that represent the source of atrazine and various aspects of the transport and fate of atrazine and DEA in the subsurface. One advantage of these newly developed models over previous national regression models is that they predict concentrations (rather than detection frequency), which can be compared with water quality benchmarks. Model results indicate that variability in the concentration of atrazine residues (atrazine plus DEA) in groundwater underlying agricultural areas is more strongly controlled by the history of atrazine use in relation to the timing of recharge (groundwater age) than by processes that control the dispersion, adsorption, or degradation of these compounds in the saturated zone. Current (1990s) atrazine use was found to be a weak explanatory variable, perhaps because it does not represent the use of atrazine at the time of recharge of the sampled groundwater and because the likelihood that these compounds will reach the water table is affected by other factors operating within the unsaturated zone, such as soil characteristics, artificial drainage, and water movement. Results show that only about 5% of agricultural areas have greater than a 10% probability of exceeding the USEPA maximum contaminant level of 3.0 &mu;g L<sup>-1</sup>. These models are not developed for regulatory purposes but rather can be used to (i) identify areas of potential concern, (ii) provide conservative estimates of the concentrations of atrazine residues in deeper potential drinking water supplies, and (iii) set priorities among areas for future groundwater monitoring.</p>","language":"English","publisher":"American Society of Agronomy","doi":"10.2134/jeq2011.0200","usgsCitation":"Stackelberg, P.E., Barbash, J.E., Gilliom, R.J., Stone, W.W., and Wolock, D.M., 2012, Regression models for estimating concentrations of atrazine plus deethylatrazine in shallow groundwater in agricultural areas of the United States: Journal of Environmental Quality, v. 41, no. 2, p. 479-494, https://doi.org/10.2134/jeq2011.0200.","productDescription":"16 p.","startPage":"479","endPage":"494","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true},{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":254754,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":254743,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.2134/jeq2011.0200","linkFileType":{"id":5,"text":"html"}}],"country":"United States","volume":"41","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50e4a5cde4b0e8fec6cdc002","contributors":{"authors":[{"text":"Stackelberg, Paul E. 0000-0002-1818-355X pestack@usgs.gov","orcid":"https://orcid.org/0000-0002-1818-355X","contributorId":1069,"corporation":false,"usgs":true,"family":"Stackelberg","given":"Paul","email":"pestack@usgs.gov","middleInitial":"E.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":356139,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barbash, Jack E. 0000-0001-9854-8880 jbarbash@usgs.gov","orcid":"https://orcid.org/0000-0001-9854-8880","contributorId":1003,"corporation":false,"usgs":true,"family":"Barbash","given":"Jack","email":"jbarbash@usgs.gov","middleInitial":"E.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":356138,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gilliom, Robert J. rgilliom@usgs.gov","contributorId":488,"corporation":false,"usgs":true,"family":"Gilliom","given":"Robert","email":"rgilliom@usgs.gov","middleInitial":"J.","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":356136,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stone, Wesley W. 0000-0003-0239-2063 wwstone@usgs.gov","orcid":"https://orcid.org/0000-0003-0239-2063","contributorId":1496,"corporation":false,"usgs":true,"family":"Stone","given":"Wesley","email":"wwstone@usgs.gov","middleInitial":"W.","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true},{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true}],"preferred":true,"id":356140,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wolock, David M. 0000-0002-6209-938X dwolock@usgs.gov","orcid":"https://orcid.org/0000-0002-6209-938X","contributorId":540,"corporation":false,"usgs":true,"family":"Wolock","given":"David","email":"dwolock@usgs.gov","middleInitial":"M.","affiliations":[{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true}],"preferred":true,"id":356137,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70007159,"text":"70007159 - 2012 - Ambystoma talpoideum (Mole Salamander). Oviposition mode and timing","interactions":[],"lastModifiedDate":"2012-05-12T01:01:38","indexId":"70007159","displayToPublicDate":"2012-05-11T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1898,"text":"Herpetological Review","active":true,"publicationSubtype":{"id":10}},"title":"Ambystoma talpoideum (Mole Salamander). Oviposition mode and timing","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Herpetological Review","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Society for the Study of Amphibians and Reptiles","publisherLocation":"www.ssarherps.org","usgsCitation":"Walls, S., Barichivich, W., and Brown, M., 2012, Ambystoma talpoideum (Mole Salamander). Oviposition mode and timing: Herpetological Review, v. 42, no. 4, p. 579-580.","productDescription":"2 p.","startPage":"579","endPage":"580","costCenters":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"links":[{"id":254755,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"42","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059e9b0e4b0c8380cd483b1","contributors":{"authors":[{"text":"Walls, S.C. 0000-0001-7391-9155","orcid":"https://orcid.org/0000-0001-7391-9155","contributorId":98273,"corporation":false,"usgs":true,"family":"Walls","given":"S.C.","affiliations":[],"preferred":false,"id":355977,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barichivich, W.J. 0000-0003-1103-6861","orcid":"https://orcid.org/0000-0003-1103-6861","contributorId":91435,"corporation":false,"usgs":true,"family":"Barichivich","given":"W.J.","affiliations":[],"preferred":false,"id":355976,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brown, M.E.","contributorId":99680,"corporation":false,"usgs":true,"family":"Brown","given":"M.E.","email":"","affiliations":[],"preferred":false,"id":355978,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70003968,"text":"70003968 - 2012 - A global earthquake discrimination scheme to optimize ground-motion prediction equation selection","interactions":[],"lastModifiedDate":"2012-05-12T01:01:38","indexId":"70003968","displayToPublicDate":"2012-05-11T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"A global earthquake discrimination scheme to optimize ground-motion prediction equation selection","docAbstract":"We present a new automatic earthquake discrimination procedure to determine in near-real time the tectonic regime and seismotectonic domain of an earthquake, its most likely source type, and the corresponding ground-motion prediction equation (GMPE) class to be used in the U.S. Geological Survey (USGS) Global ShakeMap system. This method makes use of the Flinn&ndash;Engdahl regionalization scheme, seismotectonic information (plate boundaries, global geology, seismicity catalogs, and regional and local studies), and the source parameters available from the USGS National Earthquake Information Center in the minutes following an earthquake to give the best estimation of the setting and mechanism of the event. Depending on the tectonic setting, additional criteria based on hypocentral depth, style of faulting, and regional seismicity may be applied. For subduction zones, these criteria include the use of focal mechanism information and detailed interface models to discriminate among outer-rise, upper-plate, interface, and intraslab seismicity. The scheme is validated against a large database of recent historical earthquakes. Though developed to assess GMPE selection in Global ShakeMap operations, we anticipate a variety of uses for this strategy, from real-time processing systems to any analysis involving tectonic classification of sources from seismic catalogs.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Bulletin of the Seismological Society of America","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Seismological Society of America","publisherLocation":"Albany, CA","doi":"10.1785/0120110124","usgsCitation":"Garcia, D., Wald, D.J., and Hearne, M., 2012, A global earthquake discrimination scheme to optimize ground-motion prediction equation selection: Bulletin of the Seismological Society of America, v. 102, no. 1, p. 185-203, https://doi.org/10.1785/0120110124.","productDescription":"19 p.","startPage":"185","endPage":"203","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":254745,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":254742,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1785/0120110124","linkFileType":{"id":5,"text":"html"}}],"volume":"102","issue":"1","noUsgsAuthors":false,"publicationDate":"2012-02-15","publicationStatus":"PW","scienceBaseUri":"5059e409e4b0c8380cd46383","contributors":{"authors":[{"text":"Garcia, Daniel","contributorId":80559,"corporation":false,"usgs":true,"family":"Garcia","given":"Daniel","email":"","affiliations":[],"preferred":false,"id":349781,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wald, David J. 0000-0002-1454-4514 wald@usgs.gov","orcid":"https://orcid.org/0000-0002-1454-4514","contributorId":795,"corporation":false,"usgs":true,"family":"Wald","given":"David","email":"wald@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":349780,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hearne, Michael","contributorId":91377,"corporation":false,"usgs":true,"family":"Hearne","given":"Michael","affiliations":[],"preferred":false,"id":349782,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70038348,"text":"ofr20121075 - 2012 - Fecal-indicator bacteria concentrations in the Illinois River between Hennepin and Peoria, Illinois: 2007-08","interactions":[],"lastModifiedDate":"2012-05-17T01:01:41","indexId":"ofr20121075","displayToPublicDate":"2012-05-10T00:00:00","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":"2012-1075","title":"Fecal-indicator bacteria concentrations in the Illinois River between Hennepin and Peoria, Illinois: 2007-08","docAbstract":"The Illinois Environmental Protection Agency has designated portions of the Illinois River in Peoria, Woodford, and Tazewell Counties, Illinois, as impaired owing to the presence of fecal coliform bacteria. The U.S. Geological Survey, in cooperation with the Tri-County Regional Planning Commission, examined the water quality in the Illinois River and major tributaries within a 47-mile reach between Peoria and Hennepin, Ill., during water year 2008 (October 2007&ndash;September 2008). Investigations included synoptic (snapshot) sampling at multiple locations in a 1-day period: once in October 2007 during lower streamflow conditions, and again in June 2008 during higher streamflow conditions. Five locations in the study area were monitored for the entire year at monthly or more frequent intervals. Two indicator bacteria were analyzed in each water sample: fecal coliform and <i>Escherichia coli</i> (<i>E. coli</i>). Streamflow information from previously established monitoring locations in the study area was used in the analysis. Correlation analyses were used to characterize the relation between the two fecal-indicator bacteria and the relation of either indicator to streamflow. Concentrations of the two measured fecal-indicator bacteria correlated well for all samples analyzed (r = 0.94, p <0.001), indicating a strong linear correlation. Presence of one fecal-indicator bacteria generally indicates the presence of another at a similar magnitude and may support substitution of generalized data gaps for other analyses. Hydrologic conditions during the study period can be characterized as wetter than normal, with the mean annual flow in the Illinois River about 37-percent above the long-term average. However, for the Illinois River below Peoria Lake at Peoria, a statistically significant negative correlation coefficient indicates a weak inverse relation between values of streamflow and fecal-indicator bacteria (fecal coliform rho = -0.44, p = 0.0129; <i>E. coli</i>: rho = -0.43, p = 0.0157). The correlation between fecal indicators and streamflow in tributaries or in the Illinois River at Hennepin was found to be statistically significant, yet moderate in strength with coefficient values ranging from r = 0.4 to 0.6. Indirect observations from the June 2008 higher flow synoptic event may indicate continued effects from combined storm and sanitary sewers in the vicinity of the Illinois River near Peoria, Ill., contributing to observed single-sample exceedance of the State criterion for fecal coliform.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121075","collaboration":"Prepared in cooperation with the Tri-County Regional Planning Commission","usgsCitation":"Dupre, D.H., Hortness, J., Terrio, P.J., and Sharpe, J.B., 2012, Fecal-indicator bacteria concentrations in the Illinois River between Hennepin and Peoria, Illinois: 2007-08: U.S. Geological Survey Open-File Report 2012-1075, v, 32 p., https://doi.org/10.3133/ofr20121075.","productDescription":"v, 32 p.","startPage":"i","endPage":"32","numberOfPages":"37","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":254721,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1075.gif"},{"id":254717,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1075/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Illinois","city":"Hennepin;Peoria","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a0f4ae4b0c8380cd5385e","contributors":{"authors":[{"text":"Dupre, David H. dhdupre@usgs.gov","contributorId":2782,"corporation":false,"usgs":true,"family":"Dupre","given":"David","email":"dhdupre@usgs.gov","middleInitial":"H.","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"preferred":true,"id":463923,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hortness, Jon 0000-0002-9809-2876 hortness@usgs.gov","orcid":"https://orcid.org/0000-0002-9809-2876","contributorId":3601,"corporation":false,"usgs":true,"family":"Hortness","given":"Jon","email":"hortness@usgs.gov","affiliations":[],"preferred":true,"id":463926,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Terrio, Paul J. 0000-0002-1515-9570 pjterrio@usgs.gov","orcid":"https://orcid.org/0000-0002-1515-9570","contributorId":3313,"corporation":false,"usgs":true,"family":"Terrio","given":"Paul","email":"pjterrio@usgs.gov","middleInitial":"J.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":463925,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sharpe, Jennifer B. 0000-0002-5192-7848 jbsharpe@usgs.gov","orcid":"https://orcid.org/0000-0002-5192-7848","contributorId":2825,"corporation":false,"usgs":true,"family":"Sharpe","given":"Jennifer","email":"jbsharpe@usgs.gov","middleInitial":"B.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":463924,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70038349,"text":"sir20125074 - 2012 - Development and implementation of a regression model for predicting recreational water quality in the Cuyahoga River, Cuyahoga Valley National Park, Ohio 2009-11","interactions":[],"lastModifiedDate":"2012-05-11T01:01:41","indexId":"sir20125074","displayToPublicDate":"2012-05-10T00:00:00","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":"2012-5074","title":"Development and implementation of a regression model for predicting recreational water quality in the Cuyahoga River, Cuyahoga Valley National Park, Ohio 2009-11","docAbstract":"The Cuyahoga River within Cuyahoga Valley National Park (CVNP) is at times impaired for recreational use due to elevated concentrations of Escherichia coli (E. coli), a fecal-indicator bacterium. During the recreational seasons of mid-May through September during 2009&ndash;11, samples were collected 4 days per week and analyzed for E. coli concentrations at two sites within CVNP. Other water-quality and environ-mental data, including turbidity, rainfall, and streamflow, were measured and (or) tabulated for analysis. Regression models developed to predict recreational water quality in the river were implemented during the recreational seasons of 2009&ndash;11 for one site within CVNP&ndash;Jaite. For the 2009 and 2010 seasons, the regression models were better at predicting exceedances of Ohio's single-sample standard for primary-contact recreation compared to the traditional method of using the previous day's E. coli concentration. During 2009, the regression model was based on data collected during 2005 through 2008, excluding available 2004 data. The resulting model for 2009 did not perform as well as expected (based on the calibration data set) and tended to overestimate concentrations (correct responses at 69 percent). During 2010, the regression model was based on data collected during 2004 through 2009, including all of the available data. The 2010 model performed well, correctly predicting 89 percent of the samples above or below the single-sample standard, even though the predictions tended to be lower than actual sample concentrations. During 2011, the regression model was based on data collected during 2004 through 2010 and tended to overestimate concentrations. The 2011 model did not perform as well as the traditional method or as expected, based on the calibration dataset (correct responses at 56 percent). At a second site&mdash;Lock 29, approximately 5 river miles upstream from Jaite, a regression model based on data collected at the site during the recreational seasons of 2008&ndash;10 also did not perform as well as the traditional method or as well as expected (correct responses at 60 percent). Above normal precipitation in the region and a delayed start to the 2011 sampling season (sampling began mid-June) may have affected how well the 2011 models performed. With these new data, however, updated regression models may be better able to predict recreational water quality conditions due to the increased amount of diverse water quality conditions included in the calibration data. Daily recreational water-quality predictions for Jaite were made available on the Ohio Nowcast Web site at www.ohionowcast.info. Other public outreach included signage at trailheads in the park, articles in the park's quarterly-published schedule of events and volunteer newsletters. A U.S. Geological Survey Fact Sheet was also published to bring attention to water-quality issues in the park.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125074","usgsCitation":"Brady, A., and Plona, M.B., 2012, Development and implementation of a regression model for predicting recreational water quality in the Cuyahoga River, Cuyahoga Valley National Park, Ohio 2009-11: U.S. Geological Survey Scientific Investigations Report 2012-5074, iv, 14 p., https://doi.org/10.3133/sir20125074.","productDescription":"iv, 14 p.","startPage":"i","endPage":"14","numberOfPages":"18","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2009-05-15","temporalEnd":"2011-09-30","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":254722,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5074.gif"},{"id":254718,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5074/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Ohio","otherGeospatial":"Cuyahoga River;Cuyahoga Valley National Park","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a0024e4b0c8380cd4f5ed","contributors":{"authors":[{"text":"Brady, Amie M. G.","contributorId":29774,"corporation":false,"usgs":true,"family":"Brady","given":"Amie M. G.","affiliations":[],"preferred":false,"id":463927,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Plona, Meg B.","contributorId":46470,"corporation":false,"usgs":true,"family":"Plona","given":"Meg","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":463928,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70038338,"text":"70038338 - 2012 - What are plants doing and when? Using plant phenology to facilitate sustainable natural resources management","interactions":[],"lastModifiedDate":"2013-07-17T12:58:15","indexId":"70038338","displayToPublicDate":"2012-05-09T08:38:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":3,"text":"Organization Series"},"seriesTitle":{"id":234,"text":"WLCI Fact Sheet","active":false,"publicationSubtype":{"id":3}},"seriesNumber":"3","title":"What are plants doing and when? Using plant phenology to facilitate sustainable natural resources management","docAbstract":"Climate change models for the northern Rocky Mountains predict changes in temperature and water availability that in turn will alter vegetation. Changes include timing of plant life-history events, or phenology, such as green-up, flowering and senescence, and shifts in species composition. Moreover, climate changes may favor different species, such as nonnative, annual grasses over native species. Changes in vegetation could make forage for ungulates, sage-grouse, and livestock available earlier in the growing season, but shifts in species composition and phenology may also result in earlier senescence (die-off or dormancy) and reduced overall forage production.","language":"English","publisher":"Wyoming Landscape Conservation Initiative","publisherLocation":"Rock Springs, WY","usgsCitation":"Chong, G.W., and Allen, L., 2012, What are plants doing and when? Using plant phenology to facilitate sustainable natural resources management: WLCI Fact Sheet 3, 2 p.","productDescription":"2 p.","costCenters":[{"id":545,"text":"Rocky Mountain Area Regional Executive","active":false,"usgs":true}],"links":[{"id":254714,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/70038338.gif"},{"id":254711,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/wlci/fs/3/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Wyoming","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505bd02fe4b08c986b32ecf9","contributors":{"authors":[{"text":"Chong, Geneva W. 0000-0003-3883-5153 geneva_chong@usgs.gov","orcid":"https://orcid.org/0000-0003-3883-5153","contributorId":419,"corporation":false,"usgs":true,"family":"Chong","given":"Geneva","email":"geneva_chong@usgs.gov","middleInitial":"W.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":463904,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Allen, Leslie A. laallen@usgs.gov","contributorId":358,"corporation":false,"usgs":true,"family":"Allen","given":"Leslie A.","email":"laallen@usgs.gov","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":false,"id":463903,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70156810,"text":"70156810 - 2012 - Extending a prototype knowledge and object based image analysis model to coarser spatial resolution imagery: An example from the Missouri River","interactions":[],"lastModifiedDate":"2022-11-08T17:23:01.519834","indexId":"70156810","displayToPublicDate":"2012-05-09T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Extending a prototype knowledge and object based image analysis model to coarser spatial resolution imagery: An example from the Missouri River","docAbstract":"<p><span>A prototype knowledge- and object-based image analysis model was developed to inventory and map least tern and piping plover habitat on the Missouri River, USA. The model has been used to inventory the state of sandbars annually for 4 segments of the Missouri River since 2006 using QuickBird imagery. Interpretation of the state of sandbars is difficult when images for the segment are acquired at different river stages and different states of vegetation phenology and canopy cover. Concurrent QuickBird and RapidEye images were classified using the model and the spatial correspondence of classes in the land cover and sandbar maps were analysed for the spatial extent of the images and at nest locations for both bird species. Omission and commission errors were low for unvegetated land cover classes used for nesting by both bird species and for land cover types with continuous vegetation cover and water. Errors were larger for land cover classes characterized by a mixture of sand and vegetation. Sandbar classification decisions are made using information on land cover class proportions and disagreement between sandbar classes was resolved using fuzzy membership possibilities. Regression analysis of area for a paired sample of 47 sandbars indicated an average positive bias, 1.15 ha, for RapidEye that did not vary with sandbar size. RapidEye has potential to reduce temporal uncertainty about least tern and piping plover habitat but would not be suitable for mapping sandbar erosion, and characterization of sandbar shapes or vegetation patches at fine spatial resolution.</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the 4th Conference on GEographic Object-Based Image Analysis - GEOBIA 2012","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"Conference on Geographic Object-Bsed Image Analysis (GEOBIA) 2012","conferenceDate":"May 7-9, 2012","conferenceLocation":"Rio de Janerio, Brazil","language":"English","publisher":"Instituto Nacional de Pesquisas Espaciais - INPE","usgsCitation":"Strong, L.L., 2012, Extending a prototype knowledge and object based image analysis model to coarser spatial resolution imagery: An example from the Missouri River, <i>in</i> Proceedings of the 4th Conference on GEographic Object-Based Image Analysis - GEOBIA 2012, Rio 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,{"id":70159021,"text":"70159021 - 2012 - Spectroscopic remote sensing for material identification, vegetation characterization, and mapping","interactions":[],"lastModifiedDate":"2021-10-27T16:51:18.36347","indexId":"70159021","displayToPublicDate":"2012-05-08T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Spectroscopic remote sensing for material identification, vegetation characterization, and mapping","docAbstract":"<p><span>Identifying materials by measuring and analyzing their reflectance spectra has been an important procedure in analytical chemistry for decades. Airborne and space-based imaging spectrometers allow materials to be mapped across the landscape. With many existing airborne sensors and new satellite-borne sensors planned for the future, robust methods are needed to fully exploit the information content of hyperspectral remote sensing data. A method of identifying and mapping materials using spectral feature analyses of reflectance data in an expert-system framework called MICA (Material Identification and Characterization Algorithm) is described. MICA is a module of the PRISM (Processing Routines in IDL for Spectroscopic Measurements) software, available to the public from the U.S. Geological Survey (USGS) at http://pubs.usgs.gov/of/2011/1155/. The core concepts of MICA include continuum removal and linear regression to compare key diagnostic absorption features in reference laboratory/field spectra and the spectra being analyzed. The reference spectra, diagnostic features, and threshold constraints are defined within a user-developed MICA command file (MCF). Building on several decades of experience in mineral mapping, a broadly-applicable MCF was developed to detect a set of minerals frequently occurring on the Earth's surface and applied to map minerals in the country-wide coverage of the 2007 Afghanistan HyMap data set. MICA has also been applied to detect sub-pixel oil contamination in marshes impacted by the Deepwater Horizon incident by discriminating the C-H absorption features in oil residues from background vegetation. These two recent examples demonstrate the utility of a spectroscopic approach to remote sensing for identifying and mapping the distributions of materials in imaging spectrometer data.</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Algorithms and technologies for multispectral, hyperspectral, and ultraspectral imagery XVIII: 23-27 April 2012, Baltimore, Maryland, United States","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"Algorithms and technologies for multispectral, hyperspectral, and ultraspectral imagery XVIII","conferenceDate":"April 23-27 2012","conferenceLocation":"Baltimore, Maryland","language":"English","publisher":"SPIE","doi":"10.1117/12.919121","usgsCitation":"Kokaly, R., 2012, Spectroscopic remote sensing for material identification, vegetation characterization, and mapping, <i>in</i> Algorithms and technologies for multispectral, hyperspectral, and ultraspectral imagery XVIII: 23-27 April 2012, Baltimore, Maryland, United States, v. 8390, Baltimore, Maryland, April 23-27 2012, 839014, https://doi.org/10.1117/12.919121.","productDescription":"839014","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-037432","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":309852,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8390","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"561e2b39e4b0cdb063e59cee","contributors":{"editors":[{"text":"Lewis, Paul E.","contributorId":149198,"corporation":false,"usgs":false,"family":"Lewis","given":"Paul","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":577278,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Shen, Sylvia S.","contributorId":149199,"corporation":false,"usgs":false,"family":"Shen","given":"Sylvia","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":577279,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Kokaly, Raymond F. 0000-0003-0276-7101 raymond@usgs.gov","orcid":"https://orcid.org/0000-0003-0276-7101","contributorId":1785,"corporation":false,"usgs":true,"family":"Kokaly","given":"Raymond F.","email":"raymond@usgs.gov","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":false,"id":577280,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70038308,"text":"ofr20111051 - 2012 - National assessment of shoreline change: Historical shoreline change in the Hawaiian Islands","interactions":[],"lastModifiedDate":"2016-08-31T17:43:07","indexId":"ofr20111051","displayToPublicDate":"2012-05-07T00:00:00","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":"2011-1051","title":"National assessment of shoreline change: Historical shoreline change in the Hawaiian Islands","docAbstract":"<p>Sandy beaches of the United States are some of the most popular tourist and recreational destinations. Coastal property constitutes some of the most valuable real estate in the country. Beaches are an ephemeral environment between water and land with unique and fragile natural ecosystems that have evolved in equilibrium with the ever-changing winds, waves, and water levels. Beachfront lands are the site of intense residential and commercial development even though they are highly vulnerable to several natural hazards, including marine inundation, flooding and drainage problems, effects of storms, sea-level rise, and coastal erosion. Because the U.S. population continues to shift toward the coast where valuable coastal property is vulnerable to erosion, the U.S. Geological Survey (USGS) is conducting a national assessment of coastal change. One aspect of this effort, the National Assessment of Shoreline Change, uses shoreline position as a proxy for coastal change because shoreline position is one of the most commonly monitored indicators of environmental change (for example, Fletcher, 1992; Dolan and others, 1991; Douglas and others, 1998; Galgano and others, 1998). Additionally, the National Research Council (1990) recommended the use of historical shoreline analysis in the absence of a widely accepted model of shoreline change.</p>\n<p>A principal purpose of the USGS shoreline change research is to develop a common methodology so that shoreline change analyses for the continental U.S., portions of Hawaii, and Alaska can be updated periodically in a consistent and systematic manner. The primary objectives of this study were to (1) develop and implement improved methods of assessing and monitoring shoreline movement, and (2) improve current understanding of the processes controlling shoreline movement.</p>\n<p>Achieving these ongoing long-term objectives requires research that (1) examines the original sources of shoreline data (for example, maps, air photos, global positioning system (GPS), Light Detection and Ranging (lidar)); (2) evaluates the utility of different shoreline proxies (for example, geomorphic feature, water mark, tidal datum, elevation), including the errors associated with each; (3) investigates bias and potential errors associated with integrating different shoreline proxies from different sources; (4) develops standard, uniform methods of shoreline change analysis; (5) examines the effects of human activities on shoreline movement and rates of change; and (6) investigates alternative mathematical methods for calculating historical rates of change and uncertainties associated with them.</p>\n<p>This report summarizes historical shoreline changes on the three most densely populated islands of the eight main Hawaiian Islands: Kauai, Oahu, and Maui. The report emphasizes the hazard from &ldquo;chronic&rdquo; (decades to centuries) erosion at regional scales and strives to relate this hazard to the body of knowledge regarding coastal geology of Hawaii because of its potential impact on natural resources, the economy, and society. Results are organized by coastal regions (island side) and sub-regions (common littoral characteristics). This report of Hawaii coasts is part of a series of reports that include text summarizing methods, results, and implications of the results. In addition, geographic information system (GIS) data used in the analyses are made available for download (Romine and others, 2012). The rates of shoreline change and products presented in this report are not intended for site-specific analysis of shoreline movement, nor are they intended to replace any official source of shoreline change information identified by local or State government agencies, or other Federal entities that are used for regulatory purposes.</p>\n<p>Rates of shoreline change presented herein may differ from other published rates, and differences do not necessarily indicate that the other rates are inaccurate. Some discrepancies are to be expected, considering the many possible ways of determining shoreline positions and rates of change, and the inherent uncertainty in calculating these rates. 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]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a625fe4b0c8380cd71ea2","contributors":{"authors":[{"text":"Fletcher, Charles H.","contributorId":30286,"corporation":false,"usgs":true,"family":"Fletcher","given":"Charles H.","affiliations":[],"preferred":false,"id":647713,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Romine, Bradley M.","contributorId":78972,"corporation":false,"usgs":true,"family":"Romine","given":"Bradley","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":647714,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Genz, Ayesha S.","contributorId":104319,"corporation":false,"usgs":true,"family":"Genz","given":"Ayesha S.","affiliations":[],"preferred":false,"id":647715,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barbee, Matthew M.","contributorId":98151,"corporation":false,"usgs":true,"family":"Barbee","given":"Matthew","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":647716,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dyer, Matthew","contributorId":70222,"corporation":false,"usgs":true,"family":"Dyer","given":"Matthew","email":"","affiliations":[],"preferred":false,"id":647717,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Anderson, Tiffany R.","contributorId":97358,"corporation":false,"usgs":true,"family":"Anderson","given":"Tiffany","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":647718,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lim, S. Chyn","contributorId":86203,"corporation":false,"usgs":true,"family":"Lim","given":"S.","email":"","middleInitial":"Chyn","affiliations":[],"preferred":false,"id":647719,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Vitousek, Sean 0000-0002-3369-4673 svitousek@usgs.gov","orcid":"https://orcid.org/0000-0002-3369-4673","contributorId":149065,"corporation":false,"usgs":true,"family":"Vitousek","given":"Sean","email":"svitousek@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":647720,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Bochicchio, Christopher","contributorId":45553,"corporation":false,"usgs":true,"family":"Bochicchio","given":"Christopher","email":"","affiliations":[],"preferred":false,"id":647721,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Richmond, Bruce M. brichmond@usgs.gov","contributorId":172564,"corporation":false,"usgs":true,"family":"Richmond","given":"Bruce","email":"brichmond@usgs.gov","middleInitial":"M.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":647722,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70038310,"text":"sir20125033 - 2012 - Bioaccumulation and toxicity of selenium during a life-cycle exposure with desert pupfish (Cyprinodon macularius)","interactions":[],"lastModifiedDate":"2016-10-26T11:10:25","indexId":"sir20125033","displayToPublicDate":"2012-05-07T00:00:00","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":"2012-5033","title":"Bioaccumulation and toxicity of selenium during a life-cycle exposure with desert pupfish (Cyprinodon macularius)","docAbstract":"<p>Populations of desert pupfish (<i>Cyprinodon macularius</i>; pupfish), a federally-listed endangered species, inhabit irrigation drains in the Imperial Valley agricultural area of southern California. These drains have varying degrees of selenium (Se) contamination of water, sediment, and aquatic biota. Published Se toxicity studies suggest that these levels of Se contamination may pose risk of chronic toxicity to Se-sensitive fish, but until recently there have been no studies of the chronic toxicity of Se to desert pupfish.</p><p>A life-cycle Se exposure with pupfish was conducted to estimate dietary and tissue thresholds for toxic effects of Se on all life stages. The dietary exposure was based on live oligochaete worms (<i>Lumbriculus variegatus</i>) dosed with Se by a laboratory food chain based on selenized yeast. Oligochaetes readily accumulated Se from mixtures of selenized and control yeasts. The protocol for dosing oligochaetes for pupfish feeding studies included long-term (at least 28 days) feeding of a low-ration of yeast mixtures to large batches of oligochaetes. Oligochaetes were dosed at five Se levels in a 50-percent dilution series. Pupfish were simultaneously fed Se-dosed oligochaetes and exposed to a series of Se concentrations in water (consisting of 85 percent selenate and 15 percent selenite) to produce exposures that were consistent with Se concentrations and speciation in pupfish habitats. The nutritional characteristics of oligochaete diets were consistent across the range of oligochaete Se concentrations tested.</p><p>The life-cycle exposure started with laboratory-cultured juvenile pupfish that were exposed to Se through sexual maturation and reproduction (150 days; F0 exposure). The Se exposure continued with eggs, larvae, and juveniles produced by Se-exposed parents (79 days; F1 exposure). Selenium exposure (water and diets), Se bioaccumulation (whole-body and eggs), and toxicity endpoints (juvenile and adult survival and growth; egg production and hatching success, larval survival and deformities) were documented throughout the life-cycle study.</p><p>Selenium concentrations in water (as much as 52 micrograms per liter [μg/L]) and diets (as much as 53 micrograms per gram [μg/g], on a dry weight basis) bracketed concentrations reported in pupfish habitats. Juvenile F0 pupfish rapidly accumulated Se and bioaccumulation models indicated that pupfish had reached more than 97 percent of maximum whole-body Se concentrations by the time they reached reproductive maturity. Adult pupfish accumulated whole-body Se concentrations that averaged about 40 percent of those in the oligochaete diets. Selenium concentrations in eggs and F1 juveniles were similar to or slightly greater than Se concentrations in F0 adults. Juvenile F0 pupfish contained selenomethionine fractions (62–71 percent of whole-body Se) greater than the average reported for wild pupfish from the Imperial Valley (53 percent).</p><p>Selenium exposure had minimal effects on survival or growth of juvenile and adult pupfish. There was evidence of toxic effects on pupfish in the highest Se treatment (Se–5), including reduced growth of F0 and F1 juvenile pupfish (17–21 percent less than controls) on some sampling dates. These growth reductions did not persist to subsequent sampling dates, but reduced growth of F1 pupfish in the Se–5 treatment was associated with reduced survival (12 percent less than controls).</p><p>Egg production was greatest in the controls and decreased with increasing Se exposure, reaching a minimum (51 percent less than controls) in the Se–4 treatment, but egg production was reduced by only 24 percent in the Se–5 treatment, a lesser reduction than in other Se treatments except Se–1. There was no statistically significant overall effect of Se treatment on mean pupfish egg production, reflecting large variation among replicates and among sampling dates. However, comparisons of daily mean egg production for 23 sampling dates indicated that egg production in each of 5 Se treatments was significantly less than controls on multiple (3–7) sampling dates, but no mean for any Se treatment was significantly greater than controls on any date. Significant reductions in daily egg production occurred mainly during the middle of the study and egg production increased in several Se treatments during the final 2 weeks of the study. These results suggest that pupfish egg production, although a highly variable endpoint, was adversely affected by elevated Se exposure.</p><p>Neither egg hatching success nor survival of F1 larvae indicated clear evidence of Se toxicity. Egg hatching success did not differ significantly among treatments, with means ranging from 84–91 percent. The frequency of morphological deformities (primarily spinal deformities) was greater in larvae 10 days post-fertilization (dpf) from a preliminary reproduction study than in older larvae (14 dpf) from the main reproduction study. The frequency of larval deformities was generally greater in Se treatments than controls, but mean frequencies did not differ significantly among treatments. Survival of F1 larvae to 21 dpf was not reduced significantly by parental Se exposure, but the Se–5 treatment had the lowest larval survival (84 percent), and lowest combined egg hatching and larval survival (76 percent).</p><p>Results of the Se treatments indicate that pupfish were insensitive to Se toxicity through most of their life cycle. Consistent toxic effects on survival and growth of juvenile and adult pupfish (defined as at least 10 percent reduction compared to controls) occurred only in treatment Se–5, which had a mean dietary Se concentration of 52 μg/g and a mean pupfish whole-body Se concentration of 27 μg/g. These apparent toxicity thresholds for growth and survival rank among the least sensitive chronic Se toxicity values reported for nonreproductive endpoints in freshwater fish. Comparisons of these thresholds to surveys of Se concentrations in the Imperial Valley suggest that risks of Se toxicity are low in pupfish habitats. The dietary threshold was about twice as high as the greatest mean Se concentrations reported in midge larvae from seven sites in the Imperial Valley. Whole-body thresholds were greater than mean whole-body Se concentrations reported for field-collected pupfish from three sites and for the sailfin molly (Poecilia latipinna), a potential bioaccumulation surrogate for pupfish, from seven sites.</p><p>Reduced egg production, although highly variable, was the most sensitive response of pupfish to Se exposure. Toxic effects on egg production (reductions of 24–51 percent relative to controls) occurred in the four highest Se treatments, corresponding to reproductive toxicity thresholds of 7.3 μg/g for Se in diet, 3.4 μg/g in pupfish (whole body), and 4.4 μg/g in pupfish eggs. These thresholds are substantially lower than published Se toxicity values for reproductive effects in other freshwater fish (for example, 17–24 μg/g in eggs). Reduced egg production has not been reported as a sensitive endpoint in Se toxicity studies, although abnormal ovarian development has been reported in Se-exposed fish, and reduced egg production has been reported as a sensitive response of other Cyprinodon pupfish to other environmental stressors.</p><p>Selenium concentrations in tissues of pupfish, mollies, and diet items from Imperial Valley sites frequently exceeded concentrations associated with reduced pupfish egg production in the laboratory study. Reduced egg production may limit the ability of pupfish populations to persist and recover in Se-contaminated habitats in the Imperial Valley and elsewhere in their limited range. However, these apparent risks of Se toxicity are not supported by recent surveys of desert pupfish populations in the Imperial Valley. These surveys indicated that desert pupfish made up a small, but variable, component of fish communities in Imperial Valley habitats, including sites with increased levels of Se exposure, and that pupfish distribution and population density indicated no clear relationships with Se concentrations in diets or fish tissues. Additional studies could determine the role of egg production in the maintenance and recovery of desert pupfish populations in Se-contaminated habitats.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125033","usgsCitation":"Besser, J.M., Brumbaugh, W.G., Papoulias, D.M., Ivey, C.D., Kunz, J.L., Annis, M., and Ingersoll, C.G., 2012, Bioaccumulation and toxicity of selenium during a life-cycle exposure with desert pupfish (Cyprinodon macularius): U.S. Geological Survey Scientific Investigations Report 2012-5033, Report: vi, 24 p.; Appendix, https://doi.org/10.3133/sir20125033.","productDescription":"Report: vi, 24 p.; Appendix","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":254693,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5033.gif"},{"id":254689,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5033/","linkFileType":{"id":5,"text":"html"}},{"id":330396,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5033/sir2012-5033.pdf"},{"id":330397,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2012/5033/downloads/appendix-e.xlsx","text":"Appendix E","linkFileType":{"id":3,"text":"xlsx"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059f137e4b0c8380cd4aad8","contributors":{"authors":[{"text":"Besser, John M. 0000-0002-9464-2244 jbesser@usgs.gov","orcid":"https://orcid.org/0000-0002-9464-2244","contributorId":2073,"corporation":false,"usgs":true,"family":"Besser","given":"John","email":"jbesser@usgs.gov","middleInitial":"M.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":652128,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brumbaugh, William G. 0000-0003-0081-375X bbrumbaugh@usgs.gov","orcid":"https://orcid.org/0000-0003-0081-375X","contributorId":493,"corporation":false,"usgs":true,"family":"Brumbaugh","given":"William","email":"bbrumbaugh@usgs.gov","middleInitial":"G.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":652129,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Papoulias, Diana M. 0000-0002-5106-2469 dpapoulias@usgs.gov","orcid":"https://orcid.org/0000-0002-5106-2469","contributorId":2726,"corporation":false,"usgs":true,"family":"Papoulias","given":"Diana","email":"dpapoulias@usgs.gov","middleInitial":"M.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":652130,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ivey, Chris D. 0000-0002-0485-7242 civey@usgs.gov","orcid":"https://orcid.org/0000-0002-0485-7242","contributorId":3308,"corporation":false,"usgs":true,"family":"Ivey","given":"Chris","email":"civey@usgs.gov","middleInitial":"D.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":652131,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kunz, James L. 0000-0002-1027-158X jkunz@usgs.gov","orcid":"https://orcid.org/0000-0002-1027-158X","contributorId":3309,"corporation":false,"usgs":true,"family":"Kunz","given":"James","email":"jkunz@usgs.gov","middleInitial":"L.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":652132,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Annis, Mandy mannis@usgs.gov","contributorId":150368,"corporation":false,"usgs":true,"family":"Annis","given":"Mandy","email":"mannis@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":652133,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ingersoll, Christopher G. 0000-0003-4531-5949 cingersoll@usgs.gov","orcid":"https://orcid.org/0000-0003-4531-5949","contributorId":2071,"corporation":false,"usgs":true,"family":"Ingersoll","given":"Christopher","email":"cingersoll@usgs.gov","middleInitial":"G.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":652134,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70042420,"text":"70042420 - 2012 - Integrated geophysical and hydrothermal models of flank degassing and fluid flow at Masaya Volcano, Nicaragua","interactions":[],"lastModifiedDate":"2013-01-14T11:21:48","indexId":"70042420","displayToPublicDate":"2012-05-05T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1757,"text":"Geochemistry, Geophysics, Geosystems","active":true,"publicationSubtype":{"id":10}},"title":"Integrated geophysical and hydrothermal models of flank degassing and fluid flow at Masaya Volcano, Nicaragua","docAbstract":"We investigate geologic controls on circulation in the shallow hydrothermal system of Masaya volcano, Nicaragua, and their relationship to surface diffuse degassing. On a local scale (~250 m), relatively impermeable normal faults dipping at ~60&deg; control the flowpath of water vapor and other gases in the vadose zone. These shallow normal faults are identified by modeling of a NE-SW trending magnetic anomaly of up to 2300 nT that corresponds to a topographic offset. Elevated SP and CO2 to the NW of the faults and an absence of CO2 to the SE suggest that these faults are barriers to flow. TOUGH2 numerical models of fluid circulation show enhanced flow through the footwalls of the faults, and corresponding increased mass flow and temperature at the surface (diffuse degassing zones). On a larger scale, TOUGH2 modeling suggests that groundwater convection may be occurring in a 3-4 km radial fracture zone transecting the entire flank of the volcano. Hot water rising uniformly into the base of the model at 1 x 10-5 kg/m2s results in convection that focuses heat and fluid and can explain the three distinct diffuse degassing zones distributed along the fracture. Our data and models suggest that the unusually active surface degassing zones at Masaya volcano can result purely from uniform heat and fluid flux at depth that is complicated by groundwater convection and permeability variations in the upper few km. Therefore isolating the effects of subsurface geology is vital when trying to interpret diffuse degassing in light of volcanic activity.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Geochemistry, Geophysics, Geosystems","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Geophysical Union","publisherLocation":"Washington, D.C.","doi":"10.1029/2012GC004117","usgsCitation":"Sanford, W.E., Pearson, S., Kiyosugi, K., Lehto, H., Saballos, J., and Connor, C., 2012, Integrated geophysical and hydrothermal models of flank degassing and fluid flow at Masaya Volcano, Nicaragua: Geochemistry, Geophysics, Geosystems, v. 13, no. 5, 21 p., https://doi.org/10.1029/2012GC004117.","productDescription":"21 p.","ipdsId":"IP-021856","costCenters":[{"id":146,"text":"Branch of Regional Research-Eastern Region","active":false,"usgs":true}],"links":[{"id":474510,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2012gc004117","text":"Publisher Index Page"},{"id":265616,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":265615,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1029/2012GC004117"}],"country":"Nicaragua","otherGeospatial":"Masaya Volcano","volume":"13","issue":"5","noUsgsAuthors":false,"publicationDate":"2012-05-15","publicationStatus":"PW","scienceBaseUri":"50f53708e4b0114312ab0220","contributors":{"authors":[{"text":"Sanford, Ward E. 0000-0002-6624-0280 wsanford@usgs.gov","orcid":"https://orcid.org/0000-0002-6624-0280","contributorId":2268,"corporation":false,"usgs":true,"family":"Sanford","given":"Ward","email":"wsanford@usgs.gov","middleInitial":"E.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":471498,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pearson, S.C.P.","contributorId":58535,"corporation":false,"usgs":true,"family":"Pearson","given":"S.C.P.","email":"","affiliations":[],"preferred":false,"id":471500,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kiyosugi, K.","contributorId":84644,"corporation":false,"usgs":true,"family":"Kiyosugi","given":"K.","email":"","affiliations":[],"preferred":false,"id":471502,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lehto, H.L.","contributorId":98150,"corporation":false,"usgs":true,"family":"Lehto","given":"H.L.","email":"","affiliations":[],"preferred":false,"id":471503,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Saballos, J.A.","contributorId":73091,"corporation":false,"usgs":true,"family":"Saballos","given":"J.A.","email":"","affiliations":[],"preferred":false,"id":471501,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Connor, C.B.","contributorId":41653,"corporation":false,"usgs":true,"family":"Connor","given":"C.B.","email":"","affiliations":[],"preferred":false,"id":471499,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70156774,"text":"70156774 - 2012 - Examining wildlife responses to phenology and wildfire using a landscape-scale camera trap network","interactions":[],"lastModifiedDate":"2021-10-28T15:40:11.522319","indexId":"70156774","displayToPublicDate":"2012-05-05T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Examining wildlife responses to phenology and wildfire using a landscape-scale camera trap network","docAbstract":"<p><span>Between 2001 and 2009, the Borderlands Jaguar Detection Project deployed 174 camera traps in the mountains of southern Arizona to record jaguar activity. In addition to jaguars, the motion-activated cameras, placed along known wildlife travel routes, recorded occurrences of ~ 20 other animal species. We examined temporal relationships of white-tailed deer (Odocoileus virginianus) and javelina (Pecari tajacu) to landscape phenology (as measured by monthly Normalized Difference Vegetation Index data) and the timing of wildfire (Alambre Fire of 2007). Mixed model analyses suggest that temporal dynamics of these two species were related to vegetation phenology and natural disturbance in the Sky Island region, information important for wildlife managers faced with uncertainty regarding changing climate and disturbance regimes.</span></p>","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"RMRS-P-67","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"Merging science and management in a rapidly changing world: Biodiversity and management of the Madrean Archipelago III and 7th Conference on Research and Resource Management in the Southwestern Deserts","conferenceDate":"May 1-5, 2012","conferenceLocation":"Tucson, Arizona","language":"English","publisher":"U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station","usgsCitation":"Villarreal, M., Gass, L., Norman, L., Sankeya, J.B., Wallace, C., McMacken, D., Childs, J.L., and Petrakis, R., 2012, Examining wildlife responses to phenology and wildfire using a landscape-scale camera trap network, <i>in</i> RMRS-P-67, Tucson, Arizona, May 1-5, 2012, p. 503-505.","productDescription":"3 p.","startPage":"503","endPage":"505","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-037464","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":307648,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.treesearch.fs.fed.us/pubs/43871"},{"id":307649,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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L.","contributorId":147124,"corporation":false,"usgs":false,"family":"Childs","given":"Jack","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":570476,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Petrakis, Roy E.","contributorId":46868,"corporation":false,"usgs":true,"family":"Petrakis","given":"Roy E.","affiliations":[],"preferred":false,"id":570477,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70038297,"text":"sir20125046 - 2012 - Isotropic, anisotropic, and borehole washout analyses in Gulf of Mexico Gas Hydrate Joint Industry Project Leg II, Alaminos Canyon well 21-A","interactions":[],"lastModifiedDate":"2012-05-05T01:01:37","indexId":"sir20125046","displayToPublicDate":"2012-05-04T00:00:00","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":"2012-5046","title":"Isotropic, anisotropic, and borehole washout analyses in Gulf of Mexico Gas Hydrate Joint Industry Project Leg II, Alaminos Canyon well 21-A","docAbstract":"Through the use of three-dimensional seismic amplitude mapping, several gas hydrate prospects were identified in the Alaminos Canyon area of the Gulf of Mexico. Two of the prospects were drilled as part of the Gulf of Mexico Gas Hydrate Joint Industry Program Leg II in May 2009, and a suite of logging-while-drilling logs was acquired at each well site. Logging-while-drilling logs at the Alaminos Canyon 21&ndash;A site indicate that resistivities of approximately 2 ohm-meter and P-wave velocities of approximately 1.9 kilometers per second were measured in a possible gas-hydrate-bearing target sand interval between 540 and 632 feet below the sea floor. These values are slightly elevated relative to those measured in the hydrate-free sediment surrounding the sands. The initial well log analysis is inconclusive in determining the presence of gas hydrate in the logged sand interval, mainly because large washouts in the target interval degraded well log measurements. To assess gas-hydrate saturations, a method of compensating for the effect of washouts on the resistivity and acoustic velocities is required. To meet this need, a method is presented that models the washed-out portion of the borehole as a vertical layer filled with seawater (drilling fluid). Owing to the anisotropic nature of this geometry, the apparent anisotropic resistivities and velocities caused by the vertical layer are used to correct measured log values. By incorporating the conventional marine seismic data into the well log analysis of the washout-corrected well logs, the gas-hydrate saturation at well site AC21&ndash;A was estimated to be in the range of 13 percent. Because gas hydrates in the vertical fractures were observed, anisotropic rock physics models were also applied to estimate gas-hydrate saturations.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125046","usgsCitation":"Lee, M.W., 2012, Isotropic, anisotropic, and borehole washout analyses in Gulf of Mexico Gas Hydrate Joint Industry Project Leg II, Alaminos Canyon well 21-A: U.S. Geological Survey Scientific Investigations Report 2012-5046, iv, 21 p.; Appendix, https://doi.org/10.3133/sir20125046.","productDescription":"iv, 21 p.; Appendix","startPage":"i","endPage":"23","numberOfPages":"27","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":254683,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5046.png"},{"id":254677,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5046/","linkFileType":{"id":5,"text":"html"}}],"otherGeospatial":"Gulf Of Mexico;Alaminos Canyon","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a3fc2e4b0c8380cd647d0","contributors":{"authors":[{"text":"Lee, Myung W. mlee@usgs.gov","contributorId":779,"corporation":false,"usgs":true,"family":"Lee","given":"Myung","email":"mlee@usgs.gov","middleInitial":"W.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":463814,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70038280,"text":"sir20125062 - 2012 - Groundwater simulation and management models for the upper Klamath Basin, Oregon and California","interactions":[],"lastModifiedDate":"2012-05-05T01:01:37","indexId":"sir20125062","displayToPublicDate":"2012-05-04T00:00:00","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":"2012-5062","title":"Groundwater simulation and management models for the upper Klamath Basin, Oregon and California","docAbstract":"The upper Klamath Basin encompasses about 8,000 square miles, extending from the Cascade Range east to the Basin and Range geologic province in south-central Oregon and northern California. The geography of the basin is dominated by forested volcanic uplands separated by broad interior basins. Most of the interior basins once held broad shallow lakes and extensive wetlands, but most of these areas have been drained or otherwise modified and are now cultivated. Major parts of the interior basins are managed as wildlife refuges, primarily for migratory waterfowl. The permeable volcanic bedrock of the upper Klamath Basin hosts a substantial regional groundwater system that provides much of the flow to major streams and lakes that, in turn, provide water for wildlife habitat and are the principal source of irrigation water for the basin's agricultural economy. Increased allocation of surface water for endangered species in the past decade has resulted in increased groundwater pumping and growing interest in the use of groundwater for irrigation. The potential effects of increased groundwater pumping on groundwater levels and discharge to springs and streams has caused concern among groundwater users, wildlife and Tribal interests, and State and Federal resource managers. To provide information on the potential impacts of increased groundwater development and to aid in the development of a groundwater management strategy, the U.S. Geological Survey, in collaboration with the Oregon Water Resources Department and the Bureau of Reclamation, has developed a groundwater model that can simulate the response of the hydrologic system to these new stresses. The groundwater model was developed using the U.S. Geological Survey MODFLOW finite-difference modeling code and calibrated using inverse methods to transient conditions from 1989 through 2004 with quarterly stress periods. Groundwater recharge and agricultural and municipal pumping are specified for each stress period. All major streams and most major tributaries for which a substantial part of the flow comes from groundwater discharge are included in the model. Groundwater discharge to agricultural drains, evapotranspiration from aquifers in areas of shallow groundwater, and groundwater flow to and from adjacent basins also are simulated in key areas. The model has the capability to calculate the effects of pumping and other external stresses on groundwater levels, discharge to streams, and other boundary fluxes, such as discharge to drains. Historical data indicate that the groundwater system in the upper Klamath Basin fluctuates in response to decadal climate cycles, with groundwater levels and spring flows rising and declining in response to wet and dry periods. Data also show that groundwater levels fluctuate seasonally and interannually in response to groundwater pumping. The most prominent response is to the marked increase in groundwater pumping starting in 2001. The calibrated model is able to simulate observed decadal-scale climate-driven fluctuations in the groundwater system as well as observed shorter-term pumping-related fluctuations. Example model simulations show that the timing and location of the effects of groundwater pumping vary markedly depending on the pumping location. Pumping from wells close (within a few miles) to groundwater discharge features, such as springs, drains, and certain streams, can affect those features within weeks or months of the onset of pumping, and the impacts can be essentially fully manifested in several years. Simulations indicate that seasonal variations in pumping rates are buffered by the groundwater system, and peak impacts are closer to mean annual pumping rates than to instantaneous rates. Thus, pumping effects are, to a large degree, spread out over the entire year. When pumping locations are distant (more than several miles) from discharge features, the effects take many years or decades to fully impact those features, and much of the pumped water comes from groundwater storage over a broad geographic area even after two decades. Moreover, because the effects are spread out over a broad area, the impacts to individual features are much smaller than in the case of nearby pumping. Simulations show that the discharge features most affected by pumping in the area of the Bureau of Reclamation's Klamath Irrigation Project are agricultural drains, and impacts to other surface-water features are small in comparison. A groundwater management model was developed that uses techniques of constrained optimization along with the groundwater flow model to identify the optimal strategy to meet water user needs while not violating defined constraints on impacts to groundwater levels and streamflows. The coupled groundwater simulation-optimization models were formulated to help identify strategies to meet water demand in the upper Klamath Basin. The models maximize groundwater pumping while simultaneously keeping the detrimental impacts of pumping on groundwater levels and groundwater discharge within prescribed limits. Total groundwater withdrawals were calculated under alternative constraints for drawdown, reductions in groundwater discharge to surface water, and water demand to understand the potential benefits and limitations for groundwater development in the upper Klamath Basin. The simulation-optimization model for the upper Klamath Basin provides an improved understanding of how the groundwater and surface-water system responds to sustained groundwater pumping within the Bureau of Reclamation's Klamath Project. Optimization model results demonstrate that a certain amount of supplemental groundwater pumping can occur without exceeding defined limits on drawdown and stream capture. The results of the different applications of the model demonstrate the importance of identifying constraint limits in order to better define the amount and distribution of groundwater withdrawal that is sustainable.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125062","collaboration":"Prepared in cooperation with the Bureau of Reclamation and the Oregon Water Resources Department?","usgsCitation":"Gannett, M.W., Wagner, B.J., and Lite, K.E., 2012, Groundwater simulation and management models for the upper Klamath Basin, Oregon and California: U.S. Geological Survey Scientific Investigations Report 2012-5062, x, 92 p.; Figures; Tables; HTML Document, https://doi.org/10.3133/sir20125062.","productDescription":"x, 92 p.; Figures; Tables; HTML Document","startPage":"i","endPage":"92","numberOfPages":"102","additionalOnlineFiles":"N","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":254685,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5062.jpg"},{"id":254675,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5062/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Oregon;California","otherGeospatial":"Upper Klamath Basin","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a2dc2e4b0c8380cd5bffa","contributors":{"authors":[{"text":"Gannett, Marshall W. 0000-0003-2498-2427 mgannett@usgs.gov","orcid":"https://orcid.org/0000-0003-2498-2427","contributorId":2942,"corporation":false,"usgs":true,"family":"Gannett","given":"Marshall","email":"mgannett@usgs.gov","middleInitial":"W.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":463788,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wagner, Brian J. bjwagner@usgs.gov","contributorId":427,"corporation":false,"usgs":true,"family":"Wagner","given":"Brian","email":"bjwagner@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":true,"id":463787,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lite, Kenneth E. Jr.","contributorId":37373,"corporation":false,"usgs":true,"family":"Lite","given":"Kenneth","suffix":"Jr.","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":463789,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70038299,"text":"ofr20121015 - 2012 - Seismic hazard assessment for Guam and the Northern Mariana Islands","interactions":[],"lastModifiedDate":"2012-05-05T01:01:37","indexId":"ofr20121015","displayToPublicDate":"2012-05-04T00:00:00","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":"2012-1015","title":"Seismic hazard assessment for Guam and the Northern Mariana Islands","docAbstract":"We present the results of a new probabilistic seismic hazard assessment for Guam and the Northern Mariana Islands. The Mariana island arc has formed in response to northwestward subduction of the Pacific plate beneath the Philippine Sea plate, and this process controls seismic activity in the region. Historical seismicity, the Mariana megathrust, and two crustal faults on Guam were modeled as seismic sources, and ground motions were estimated by using published relations for a firm-rock site condition. Maps of peak ground acceleration, 0.2-second spectral acceleration for 5 percent critical damping, and 1.0-second spectral acceleration for 5 percent critical damping were computed for exceedance probabilities of 2 percent and 10 percent in 50 years. For 2 percent probability of exceedance in 50 years, probabilistic peak ground acceleration is 0.94 gravitational acceleration at Guam and 0.57 gravitational acceleration at Saipan, 0.2-second spectral acceleration is 2.86 gravitational acceleration at Guam and 1.75 gravitational acceleration at Saipan, and 1.0-second spectral acceleration is 0.61 gravitational acceleration at Guam and 0.37 gravitational acceleration at Saipan. For 10 percent probability of exceedance in 50 years, probabilistic peak ground acceleration is 0.49 gravitational acceleration at Guam and 0.29 gravitational acceleration at Saipan, 0.2-second spectral acceleration is 1.43 gravitational acceleration at Guam and 0.83 gravitational acceleration at Saipan, and 1.0-second spectral acceleration is 0.30 gravitational acceleration at Guam and 0.18 gravitational acceleration at Saipan. The dominant hazard source at the islands is upper Benioff-zone seismicity (depth 40&ndash;160 kilometers). The large probabilistic ground motions reflect the strong concentrations of this activity below the arc, especially near Guam.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121015","usgsCitation":"Mueller, C.S., Haller, K., Luco, N., Petersen, M.D., and Frankel, A.D., 2012, Seismic hazard assessment for Guam and the Northern Mariana Islands: U.S. Geological Survey Open-File Report 2012-1015, iv, 33 p.; Appendix, https://doi.org/10.3133/ofr20121015.","productDescription":"iv, 33 p.; Appendix","startPage":"i","endPage":"52","numberOfPages":"56","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":254684,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1015.bmp"},{"id":254678,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1015/","linkFileType":{"id":5,"text":"html"}}],"otherGeospatial":"Guam;Northern Mariana Islands","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505b8b16e4b08c986b3175a0","contributors":{"authors":[{"text":"Mueller, Charles S. 0000-0002-1868-9710 cmueller@usgs.gov","orcid":"https://orcid.org/0000-0002-1868-9710","contributorId":955,"corporation":false,"usgs":true,"family":"Mueller","given":"Charles","email":"cmueller@usgs.gov","middleInitial":"S.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":463815,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haller, Kathleen M. haller@usgs.gov","contributorId":1331,"corporation":false,"usgs":true,"family":"Haller","given":"Kathleen M.","email":"haller@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":false,"id":463817,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Luco, Nicholas 0000-0002-5763-9847","orcid":"https://orcid.org/0000-0002-5763-9847","contributorId":9895,"corporation":false,"usgs":true,"family":"Luco","given":"Nicholas","affiliations":[],"preferred":false,"id":463819,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Petersen, Mark D. 0000-0001-8542-3990 mpetersen@usgs.gov","orcid":"https://orcid.org/0000-0001-8542-3990","contributorId":1163,"corporation":false,"usgs":true,"family":"Petersen","given":"Mark","email":"mpetersen@usgs.gov","middleInitial":"D.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":463816,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Frankel, Arthur D. 0000-0001-9119-6106 afrankel@usgs.gov","orcid":"https://orcid.org/0000-0001-9119-6106","contributorId":1363,"corporation":false,"usgs":true,"family":"Frankel","given":"Arthur","email":"afrankel@usgs.gov","middleInitial":"D.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":false,"id":463818,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70038283,"text":"70038283 - 2012 - A framework for inference about carnivore density from unstructured spatial sampling of scat using detector dogs","interactions":[],"lastModifiedDate":"2012-05-09T01:01:39","indexId":"70038283","displayToPublicDate":"2012-05-02T16:52:00","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":"A framework for inference about carnivore density from unstructured spatial sampling of scat using detector dogs","docAbstract":"Wildlife management often hinges upon an accurate assessment of population density. Although undeniably useful, many of the traditional approaches to density estimation such as visual counts, livetrapping, or mark&ndash;recapture suffer from a suite of methodological and analytical weaknesses. Rare, secretive, or highly mobile species exacerbate these problems through the reality of small sample sizes and movement on and off study sites. In response to these difficulties, there is growing interest in the use of non-invasive survey techniques, which provide the opportunity to collect larger samples with minimal increases in effort, as well as the application of analytical frameworks that are not reliant on large sample size arguments. One promising survey technique, the use of scat detecting dogs, offers a greatly enhanced probability of detection while at the same time generating new difficulties with respect to non-standard survey routes, variable search intensity, and the lack of a fixed survey point for characterizing non-detection. In order to account for these issues, we modified an existing spatially explicit, capture&ndash;recapture model for camera trap data to account for variable search intensity and the lack of fixed, georeferenced trap locations. We applied this modified model to a fisher (<i>Martes pennanti</i>) dataset from the Sierra National Forest, California, and compared the results (12.3 fishers/100 km<sup>2</sup>) to more traditional density estimates. We then evaluated model performance using simulations at 3 levels of population density. Simulation results indicated that estimates based on the posterior mode were relatively unbiased. We believe that this approach provides a flexible analytical framework for reconciling the inconsistencies between detector dog survey data and density estimation procedures.","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.317","usgsCitation":"Thompson, C.M., Royle, J., and Garner, J., 2012, A framework for inference about carnivore density from unstructured spatial sampling of scat using detector dogs: Journal of Wildlife Management, v. 76, no. 4, p. 863-871, https://doi.org/10.1002/jwmg.317.","productDescription":"9 p.","startPage":"863","endPage":"871","numberOfPages":"9","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":254706,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":254704,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://dx.doi.org/10.1002/jwmg.317","linkFileType":{"id":5,"text":"html"}}],"volume":"76","issue":"4","noUsgsAuthors":false,"publicationDate":"2011-12-29","publicationStatus":"PW","scienceBaseUri":"5059e3e3e4b0c8380cd46295","contributors":{"authors":[{"text":"Thompson, Craig M.","contributorId":57303,"corporation":false,"usgs":true,"family":"Thompson","given":"Craig","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":463796,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Royle, J. Andrew 0000-0003-3135-2167","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":80808,"corporation":false,"usgs":true,"family":"Royle","given":"J. Andrew","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":463798,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Garner, James D.","contributorId":62060,"corporation":false,"usgs":true,"family":"Garner","given":"James D.","affiliations":[],"preferred":false,"id":463797,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
]}