The trend of decreasing permeability with depth was estimated in the fractured-rock terrain of the upper Potomac River basin in the eastern USA using model calibration on 200 water-level observations in wells and 12 base-flow observations in subwatersheds. Results indicate that permeability at the 1–10 km scale (for groundwater flowpaths) decreases by several orders of magnitude within the top 100 m of land surface. This depth range represents the transition from the weathered, fractured regolith into unweathered bedrock. This rate of decline is substantially greater than has been observed by previous investigators that have plotted in situ wellbore measurements versus depth. The difference is that regional water levels give information on kilometer-scale connectivity of the regolith and adjacent fracture networks, whereas in situ measurements give information on near-hole fractures and fracture networks. The approach taken was to calibrate model layer-to-layer ratios of hydraulic conductivity (LLKs) for each major rock type. Most rock types gave optimal LLK values of 40–60, where each layer was twice a thick as the one overlying it. Previous estimates of permeability with depth from deeper data showed less of a decline at <300 m than the regional modeling results. There was less certainty in the modeling results deeper than 200 m and for certain rock types where fewer water-level observations were available. The results have implications for improved understanding of watershed-scale groundwater flow and transport, such as for the timing of the migration of pollutants from the water table to streams.
","language":"English","publisher":"Springer","doi":"10.1007/s10040-016-1483-y","usgsCitation":"Sanford, W.E., 2017, Estimating regional-scale permeability–depth relations in a fractured-rock terrain using groundwater-flow model calibration: Hydrogeology Journal, v. 25, no. 2, p. 405-419, https://doi.org/10.1007/s10040-016-1483-y.","productDescription":"15 p.","startPage":"405","endPage":"419","ipdsId":"IP-076752","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":352927,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"25","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-11-11","publicationStatus":"PW","scienceBaseUri":"5afee8c4e4b0da30c1bfc4a6","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":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":692987,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70185031,"text":"70185031 - 2017 - Relations of alpine plant communities across environmental gradients: Multilevel versus multiscale analyses","interactions":[],"lastModifiedDate":"2017-03-14T12:20:25","indexId":"70185031","displayToPublicDate":"2017-03-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":797,"text":"Annals of the Association of American Geographers","active":true,"publicationSubtype":{"id":10}},"title":" Relations of alpine plant communities across environmental gradients: Multilevel versus multiscale analyses","docAbstract":"Alpine plant communities vary, and their environmental covariates could influence their response to climate change. A single multilevel model of how alpine plant community composition is determined by hierarchical relations is compared to a separate examination of those relations at different scales. Nonmetric multidimensional scaling of species cover for plots in four regions across the Rocky Mountains created dependent variables. Climate variables are derived for the four regions from interpolated data. Plot environmental variables are measured directly and the presence of thirty-seven site characteristics is recorded and used to create additional independent variables. Multilevel and best subsets regressions are used to determine the strength of the hypothesized relations. The ordinations indicate structure in the assembly of plant communities. The multilevel analyses, although revealing significant relations, provide little explanation; of the site variables, those related to site microclimate are most important. In multiscale analyses (whole and separate regions), different variables are better explanations within the different regions. This result indicates weak environmental niche control of community composition. The weak relations of the structure in the patterns of species association to the environment indicates that either alpine vegetation represents a case of the neutral theory of biogeography being a valid explanation or that it represents disequilibrium conditions. The implications of neutral theory and disequilibrium explanations are similar: Response to climate change will be difficult to quantify above equilibrium background turnover.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/24694452.2016.1218267","usgsCitation":"Malanson, G.P., Zimmerman, D.L., Kinney, M., and Fagre, D.B., 2017, Relations of alpine plant communities across environmental gradients: Multilevel versus multiscale analyses: Annals of the Association of American Geographers, v. 107, no. 1, p. 41-53, https://doi.org/10.1080/24694452.2016.1218267.","productDescription":"13 p.","startPage":"41","endPage":"53","ipdsId":"IP-071596","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":337500,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"107","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-09-28","publicationStatus":"PW","scienceBaseUri":"58c90123e4b0849ce97abcba","contributors":{"authors":[{"text":"Malanson, George P.","contributorId":189162,"corporation":false,"usgs":false,"family":"Malanson","given":"George","email":"","middleInitial":"P.","affiliations":[{"id":6768,"text":"University of Iowa","active":true,"usgs":false}],"preferred":false,"id":684012,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zimmerman, Dale L.","contributorId":166811,"corporation":false,"usgs":false,"family":"Zimmerman","given":"Dale","email":"","middleInitial":"L.","affiliations":[{"id":6768,"text":"University of Iowa","active":true,"usgs":false}],"preferred":false,"id":684010,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kinney, Mitch","contributorId":189163,"corporation":false,"usgs":false,"family":"Kinney","given":"Mitch","email":"","affiliations":[],"preferred":false,"id":684013,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fagre, Daniel B. 0000-0001-8552-9461 dan_fagre@usgs.gov","orcid":"https://orcid.org/0000-0001-8552-9461","contributorId":2036,"corporation":false,"usgs":true,"family":"Fagre","given":"Daniel","email":"dan_fagre@usgs.gov","middleInitial":"B.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":684011,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70186891,"text":"70186891 - 2017 - Low pathogenic avian influenza viruses in wild migratory waterfowl in a region of high poultry production, Delmarva, Maryland","interactions":[],"lastModifiedDate":"2017-04-25T16:34:18","indexId":"70186891","displayToPublicDate":"2017-03-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":948,"text":"Avian Diseases","active":true,"publicationSubtype":{"id":10}},"title":"Low pathogenic avian influenza viruses in wild migratory waterfowl in a region of high poultry production, Delmarva, Maryland","docAbstract":"Migratory waterfowl are natural reservoirs for low pathogenic avian influenza viruses (AIVs) and may contribute to the long-distance dispersal of these pathogens as well as spillover into domestic bird populations. Surveillance for AIVs is critical to assessing risks for potential spread of these viruses among wild and domestic bird populations. The Delmarva Peninsula on the east coast of the United States is both a key convergence point for migratory Atlantic waterfowl populations and a region with high poultry production (>4,700 poultry meat facilities). Sampling of key migratory waterfowl species occurred at 20 locations throughout the Delmarva Peninsula in fall and winter of 2013–14. Samples were collected from 400 hunter-harvested or live-caught birds via cloacal and oropharyngeal swabs. Fourteen of the 400 (3.5%) birds sampled tested positive for the AIV matrix gene using real-time reverse transcriptase PCR, all from five dabbling duck species. Further characterization of the 14 viral isolates identified two hemagglutinin (H3 and H4) and four neuraminidase (N2, N6, N8, and N9) subtypes, which were consistent with isolates reported in the Influenza Research Database for this region. Three of 14 isolates contained multiple HA or NA subtypes. This study adds to the limited baseline information available for AIVs in migratory waterfowl populations on the Delmarva Peninsula, particularly prior to the highly pathogenic AIV A(H5N8) and A(H5N2) introductions to the United States in late 2014.
","language":"English","publisher":"American Association of Avian Pathologists","doi":"10.1637/11476-072616-ResNote","usgsCitation":"Prosser, D.J., Densmore, C.L., Hindman, L.J., Iwanowicz, D.D., Ottinger, C.A., Iwanowicz, L., Driscoll, C.P., and Nagel, J.L., 2017, Low pathogenic avian influenza viruses in wild migratory waterfowl in a region of high poultry production, Delmarva, Maryland: Avian Diseases, v. 61, no. 1, p. 128-134, https://doi.org/10.1637/11476-072616-ResNote.","productDescription":"7 p.","startPage":"128","endPage":"134","ipdsId":"IP-080890","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":438429,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F75M63V3","text":"USGS data release","linkHelpText":"Low-pathogenic avian influenza viruses in wild migratory waterfowl in a region of high poultry production, Delmarva, Maryland"},{"id":339678,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Delaware, Maryland","otherGeospatial":"Delmarva Peninsula","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.39892578125,\n 37.98317483351337\n ],\n [\n -74.9871826171875,\n 37.98317483351337\n ],\n [\n -74.9871826171875,\n 38.8782049970615\n ],\n [\n -76.39892578125,\n 38.8782049970615\n ],\n [\n -76.39892578125,\n 37.98317483351337\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"61","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58f08e5fe4b06911a29fa846","contributors":{"authors":[{"text":"Prosser, Diann J. 0000-0002-5251-1799 dprosser@usgs.gov","orcid":"https://orcid.org/0000-0002-5251-1799","contributorId":2389,"corporation":false,"usgs":true,"family":"Prosser","given":"Diann","email":"dprosser@usgs.gov","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":690870,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Densmore, Christine L. 0000-0001-6440-0781 cdensmore@usgs.gov","orcid":"https://orcid.org/0000-0001-6440-0781","contributorId":4560,"corporation":false,"usgs":true,"family":"Densmore","given":"Christine","email":"cdensmore@usgs.gov","middleInitial":"L.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":690871,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hindman, Larry J.","contributorId":190849,"corporation":false,"usgs":false,"family":"Hindman","given":"Larry","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":690872,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Iwanowicz, Deborah D. 0000-0002-9613-8594 diwanowicz@usgs.gov","orcid":"https://orcid.org/0000-0002-9613-8594","contributorId":2253,"corporation":false,"usgs":true,"family":"Iwanowicz","given":"Deborah","email":"diwanowicz@usgs.gov","middleInitial":"D.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":690873,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ottinger, Christopher A. 0000-0003-2551-1985 cottinger@usgs.gov","orcid":"https://orcid.org/0000-0003-2551-1985","contributorId":2559,"corporation":false,"usgs":true,"family":"Ottinger","given":"Christopher","email":"cottinger@usgs.gov","middleInitial":"A.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":690874,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Iwanowicz, Luke R. 0000-0002-1197-6178 liwanowicz@usgs.gov","orcid":"https://orcid.org/0000-0002-1197-6178","contributorId":150383,"corporation":false,"usgs":true,"family":"Iwanowicz","given":"Luke R. ","email":"liwanowicz@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":690875,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Driscoll, Cindy P.","contributorId":190850,"corporation":false,"usgs":false,"family":"Driscoll","given":"Cindy","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":690876,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Nagel, Jessica L. 0000-0002-4437-0324 jnagel@usgs.gov","orcid":"https://orcid.org/0000-0002-4437-0324","contributorId":3976,"corporation":false,"usgs":true,"family":"Nagel","given":"Jessica","email":"jnagel@usgs.gov","middleInitial":"L.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":690877,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70185038,"text":"70185038 - 2017 - Autumn olive (Elaeagnus umbellata) presence and proliferation on former surface coal mines in Eastern USA","interactions":[],"lastModifiedDate":"2017-03-13T16:53:20","indexId":"70185038","displayToPublicDate":"2017-03-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1018,"text":"Biological Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Autumn olive (Elaeagnus umbellata) presence and proliferation on former surface coal mines in Eastern USA","docAbstract":"Invasive plants threaten native plant communities. Surface coal mines in the Appalachian Mountains are among the most disturbed landscapes in North America, but information about land cover characteristics of Appalachian mined lands is lacking. The invasive shrub autumn olive (Elaeagnus umbellata) occurs on these sites and interferes with ecosystem recovery by outcompeting native trees, thus inhibiting re-establishment of the native woody-plant community. We analyzed Landsat 8 satellite imagery to describe autumn olive’s distribution on post-mined lands in southwestern Virginia within the Appalachian coalfield. Eight images from April 2013 through January 2015 served as input data. Calibration and validation data obtained from high-resolution aerial imagery were used to develop a land cover classification model that identified areas where autumn olive was a primary component of land cover. Results indicate that autumn olive cover was sufficiently dense to enable detection on approximately 12.6 % of post-mined lands within the study area. The classified map had user’s and producer’s accuracies of 85.3 and 78.6 %, respectively, for the autumn olive coverage class. Overall accuracy was assessed in reference to an independent validation dataset at 96.8 %. Autumn olive was detected more frequently on mines disturbed prior to 2003, the last year of known plantings, than on lands disturbed by more recent mining. These results indicate that autumn olive growing on reclaimed coal mines in Virginia and elsewhere in eastern USA can be mapped using Landsat 8 Operational Land Imager imagery; and that autumn olive occurrence is a significant landscape vegetation feature on former surface coal mines in the southwestern Virginia segment of the Appalachian coalfield.
","language":"English","publisher":"Springer","doi":"10.1007/s10530-016-1271-6","usgsCitation":"Oliphant, A., Wynne, R., Zipper, C.E., Ford, W., Donovan, P.F., and Li, J., 2017, Autumn olive (Elaeagnus umbellata) presence and proliferation on former surface coal mines in Eastern USA: Biological Invasions, v. 19, no. 1, p. 179-195, https://doi.org/10.1007/s10530-016-1271-6.","productDescription":"17 p.","startPage":"179","endPage":"195","ipdsId":"IP-072884","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":337475,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"19","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-09-12","publicationStatus":"PW","scienceBaseUri":"58c7af98e4b0849ce9795e6a","contributors":{"authors":[{"text":"Oliphant, Adam J.","contributorId":189232,"corporation":false,"usgs":false,"family":"Oliphant","given":"Adam J.","affiliations":[],"preferred":false,"id":684165,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wynne, R.H.","contributorId":147844,"corporation":false,"usgs":false,"family":"Wynne","given":"R.H.","email":"","affiliations":[],"preferred":false,"id":684166,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zipper, Carl E.","contributorId":43683,"corporation":false,"usgs":true,"family":"Zipper","given":"Carl","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":684167,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ford, W. Mark 0000-0002-9611-594X wford@usgs.gov","orcid":"https://orcid.org/0000-0002-9611-594X","contributorId":172499,"corporation":false,"usgs":true,"family":"Ford","given":"W. Mark","email":"wford@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":684033,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Donovan, P. F.","contributorId":189233,"corporation":false,"usgs":false,"family":"Donovan","given":"P.","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":684168,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Li, Jing","contributorId":9166,"corporation":false,"usgs":true,"family":"Li","given":"Jing","email":"","affiliations":[],"preferred":false,"id":684169,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70186296,"text":"70186296 - 2017 - Advancing the match-mismatch framework for large herbivores in the Arctic: Evaluating the evidence for a trophic mismatch in caribou","interactions":[],"lastModifiedDate":"2017-04-04T11:50:35","indexId":"70186296","displayToPublicDate":"2017-03-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Advancing the match-mismatch framework for large herbivores in the Arctic: Evaluating the evidence for a trophic mismatch in caribou","docAbstract":"Climate-induced shifts in plant phenology may adversely affect animals that cannot or do not shift the timing of their reproductive cycle. The realized effect of potential trophic “mismatches” between a consumer and its food varies with the degree to which species rely on dietary income and stored capital. Large Arctic herbivores rely heavily on maternal capital to reproduce and give birth near the onset of the growing season but are they vulnerable to trophic mismatch? We evaluated the long-term changes in the temperatures and characteristics of the growing seasons (1970–2013), and compared growing conditions and dynamics of forage quality for caribou at peak parturition, peak lactation, and peak forage biomass, and plant senescence between two distinct time periods over 36 years (1977 and 2011–13). Despite advanced thaw dates (7−12 days earlier), increased growing season lengths (15−21 days longer), and consistent parturition dates, we found no decline in forage quality and therefore no evidence within this dataset for a trophic mismatch at peak parturition or peak lactation from 1977 to 2011–13. In Arctic ungulates that use stored capital for reproduction, reproductive demands are largely met by body stores deposited in the previous summer and autumn, which reduces potential adverse effects of any mismatch between food availability and timing of parturition. Climate-induced effects on forages growing in the summer and autumn ranges, however, do correspond with the demands of female caribou and their offspring to gain mass for the next reproductive cycle and winter. Therefore, we suggest the window of time to examine the match-mismatch framework in Arctic ungulates is not at parturition but in late summer-autumn, where the multiplier effects of small changes in forage quality are amplified by forage abundance, peak forage intake, and resultant mass gains in mother-offspring pairs.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0171807","usgsCitation":"Gustine, D.D., Barboza, P., Adams, L., Griffith, B., Cameron, R.D., and Whitten, K.R., 2017, Advancing the match-mismatch framework for large herbivores in the Arctic: Evaluating the evidence for a trophic mismatch in caribou: PLoS ONE, v. 12, no. 2, p. 1-18, https://doi.org/10.1371/journal.pone.0171807.","productDescription":"e0171807; 18 p.","startPage":"1","endPage":"18","ipdsId":"IP-061147","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":470052,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0171807","text":"Publisher Index Page"},{"id":339127,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -148.9306640625,\n 68.65255607018035\n ],\n [\n -147.67822265625,\n 68.65255607018035\n ],\n [\n -147.67822265625,\n 70.4257596280135\n ],\n [\n -148.9306640625,\n 70.4257596280135\n ],\n [\n -148.9306640625,\n 68.65255607018035\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"12","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-02-23","publicationStatus":"PW","scienceBaseUri":"58e4b0b1e4b09da67999777c","contributors":{"authors":[{"text":"Gustine, David D. dgustine@usgs.gov","contributorId":3776,"corporation":false,"usgs":true,"family":"Gustine","given":"David","email":"dgustine@usgs.gov","middleInitial":"D.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":688231,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barboza, Perry","contributorId":190361,"corporation":false,"usgs":false,"family":"Barboza","given":"Perry","affiliations":[],"preferred":false,"id":688232,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Adams, Layne G. 0000-0001-6212-2896 ladams@usgs.gov","orcid":"https://orcid.org/0000-0001-6212-2896","contributorId":2776,"corporation":false,"usgs":true,"family":"Adams","given":"Layne G.","email":"ladams@usgs.gov","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":688230,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Griffith, Brad","contributorId":190362,"corporation":false,"usgs":false,"family":"Griffith","given":"Brad","affiliations":[],"preferred":false,"id":688233,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cameron, Raymond D.","contributorId":190363,"corporation":false,"usgs":false,"family":"Cameron","given":"Raymond","email":"","middleInitial":"D.","affiliations":[{"id":7058,"text":"Alaska Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":688234,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Whitten, Kenneth R.","contributorId":190408,"corporation":false,"usgs":false,"family":"Whitten","given":"Kenneth","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":688370,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70189315,"text":"70189315 - 2017 - Nationwide reconnaissance of contaminants of emerging concern in source and treated drinking waters of the United States","interactions":[],"lastModifiedDate":"2017-07-11T09:43:00","indexId":"70189315","displayToPublicDate":"2017-03-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Nationwide reconnaissance of contaminants of emerging concern in source and treated drinking waters of the United States","docAbstract":"When chemical or microbial contaminants are assessed for potential effect or possible regulation in ambient and drinking waters, a critical first step is determining if the contaminants occur and if they are at concentrations that may cause human or ecological health concerns. To this end, source and treated drinking water samples from 29 drinking water treatment plants (DWTPs) were analyzed as part of a two-phase study to determine whether chemical and microbial constituents, many of which are considered contaminants of emerging concern, were detectable in the waters. Of the 84 chemicals monitored in the 9 Phase I DWTPs, 27 were detected at least once in the source water, and 21 were detected at least once in treated drinking water. In Phase II, which was a broader and more comprehensive assessment, 247 chemical and microbial analytes were measured in 25 DWTPs, with 148 detected at least once in the source water, and 121 detected at least once in the treated drinking water. The frequency of detection was often related to the analyte's contaminant class, as pharmaceuticals and anthropogenic waste indicators tended to be infrequently detected and more easily removed during treatment, while per and polyfluoroalkyl substances and inorganic constituents were both more frequently detected and, overall, more resistant to treatment. The data collected as part of this project will be used to help inform evaluation of unregulated contaminants in surface water, groundwater, and drinking water.
Understanding nitrate dynamics in groundwater systems as a function of climatic conditions, especially during contrasting patterns of drought and wet cycles, is limited by a lack of temporal and spatial data. Nitrate sensors have the capability for making accurate, high-frequency measurements of nitrate in situ, but have not yet been evaluated for long-term use in groundwater wells. We measured in situ nitrate continuously in two groundwater monitoring wells —one rural and one urban—located in the recharge zone of a productive karst aquifer in central Texas in order to resolve changes that occur over both short-term (hourly to daily) and long-term (monthly to yearly) periods. Nitrate concentrations, measured as nitrate-nitrogen in milligrams per liter (mg/L), during drought conditions showed little or no temporal change as groundwater levels declined. During aquifer recharge, extremely rapid changes in concentration occurred at both wells as documented by hourly data. At both sites, nitrate concentrations were affected by recharging surface water as evidenced by nitrate concentrations in groundwater recharge (0.8–1.3 mg/L) that were similar to previously reported values for regional recharging streams. Groundwater nitrate concentrations responded differently at urban and rural sites during groundwater recharge. Concentrations at the rural well (approximately 1.0 mg/L) increased as a result of higher nitrate concentrations in groundwater recharge relative to ambient nitrate concentrations in groundwater, whereas concentrations at the urban well (approximately 2.7 mg/L) decreased as a result of the dilution of higher ambient nitrate concentrations relative to those in groundwater recharge. Notably, nitrate concentrations decreased to as low as 0.8 mg/L at the urban site during recharge but postrecharge concentrations exceeded 3.0 mg/L. A return to higher nitrate concentrations postrecharge indicates mobilization of a localized source of elevated nitrate within the urbanized area of the aquifer. Changes in specific conductance were observed at both sites during groundwater recharge, and a significant correlation between specific conductance and nitrate (correlation coefficient [R] = 0.455) was evident at the urban site where large (3-fold) changes in nitrate occurred. Nitrate concentrations and specific conductance measured during a depth profile indicated that the water column was generally homogeneous as expected for this karst environment, but changes were observed in the most productive zone of the aquifer that might indicate some heterogeneity within the complex network of flow paths. Resolving the timing and magnitude of changes and characterizing fine-scale vertical differences would not be possible using conventional sampling techniques. The patterns observed in situ provided new insight into the dynamic nature of nitrate in a karst groundwater system.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2016.12.038","usgsCitation":"Opsahl, S.P., Musgrove, M., and Slattery, R.N., 2017, New insights into nitrate dynamics in a karst groundwater system gained from in situ high-frequency optical sensor measurements: Journal of Hydrology, v. 546, p. 179-188, https://doi.org/10.1016/j.jhydrol.2016.12.038.","productDescription":"10 p.","startPage":"179","endPage":"188","ipdsId":"IP-067710","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":347247,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas","otherGeospatial":"Edwards Aquifer","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -100.469970703125,\n 29.11857441491087\n ],\n [\n -97.55584716796875,\n 29.11857441491087\n ],\n [\n -97.55584716796875,\n 30.458144351018078\n ],\n [\n -100.469970703125,\n 30.458144351018078\n ],\n [\n -100.469970703125,\n 29.11857441491087\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"546","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59f05123e4b0220bbd9a1d9f","contributors":{"authors":[{"text":"Opsahl, Stephen P. 0000-0002-4774-0415 sopsahl@usgs.gov","orcid":"https://orcid.org/0000-0002-4774-0415","contributorId":4713,"corporation":false,"usgs":true,"family":"Opsahl","given":"Stephen","email":"sopsahl@usgs.gov","middleInitial":"P.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":713011,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Musgrove, MaryLynn 0000-0003-1607-3864 mmusgrov@usgs.gov","orcid":"https://orcid.org/0000-0003-1607-3864","contributorId":197013,"corporation":false,"usgs":true,"family":"Musgrove","given":"MaryLynn","email":"mmusgrov@usgs.gov","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":false,"id":713012,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Slattery, Richard N. 0000-0002-9141-9776 rnslatte@usgs.gov","orcid":"https://orcid.org/0000-0002-9141-9776","contributorId":2471,"corporation":false,"usgs":true,"family":"Slattery","given":"Richard","email":"rnslatte@usgs.gov","middleInitial":"N.","affiliations":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":713013,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70192616,"text":"70192616 - 2017 - The basis function approach for modeling autocorrelation in ecological data","interactions":[],"lastModifiedDate":"2017-11-10T11:17:00","indexId":"70192616","displayToPublicDate":"2017-03-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"The basis function approach for modeling autocorrelation in ecological data","docAbstract":"Analyzing ecological data often requires modeling the autocorrelation created by spatial and temporal processes. Many seemingly disparate statistical methods used to account for autocorrelation can be expressed as regression models that include basis functions. Basis functions also enable ecologists to modify a wide range of existing ecological models in order to account for autocorrelation, which can improve inference and predictive accuracy. Furthermore, understanding the properties of basis functions is essential for evaluating the fit of spatial or time-series models, detecting a hidden form of collinearity, and analyzing large data sets. We present important concepts and properties related to basis functions and illustrate several tools and techniques ecologists can use when modeling autocorrelation in ecological data.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecy.1674","usgsCitation":"Hefley, T.J., Broms, K.M., Brost, B.M., Buderman, F.E., Kay, S.L., Scharf, H., Tipton, J., Williams, P.J., and Hooten, M., 2017, The basis function approach for modeling autocorrelation in ecological data: Ecology, v. 98, no. 3, p. 632-646, https://doi.org/10.1002/ecy.1674.","productDescription":"15 p.","startPage":"632","endPage":"646","ipdsId":"IP-070118","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":470033,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://arxiv.org/abs/1606.05658","text":"External Repository"},{"id":348572,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"98","issue":"3","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a06c8cfe4b09af898c86138","contributors":{"authors":[{"text":"Hefley, Trevor J.","contributorId":147146,"corporation":false,"usgs":false,"family":"Hefley","given":"Trevor","email":"","middleInitial":"J.","affiliations":[{"id":16796,"text":"Dept Fish, Wildlife & Cons Biol, Colorado St Univ, Fort Collins, CO","active":true,"usgs":false}],"preferred":false,"id":721574,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Broms, Kristin M.","contributorId":171524,"corporation":false,"usgs":false,"family":"Broms","given":"Kristin","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":721575,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brost, Brian M.","contributorId":171484,"corporation":false,"usgs":false,"family":"Brost","given":"Brian","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":721576,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Buderman, Frances E.","contributorId":171634,"corporation":false,"usgs":false,"family":"Buderman","given":"Frances","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":721577,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kay, Shannon L.","contributorId":193049,"corporation":false,"usgs":false,"family":"Kay","given":"Shannon","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":721578,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Scharf, Henry","contributorId":200238,"corporation":false,"usgs":false,"family":"Scharf","given":"Henry","affiliations":[],"preferred":false,"id":721579,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Tipton, John","contributorId":166999,"corporation":false,"usgs":false,"family":"Tipton","given":"John","affiliations":[],"preferred":false,"id":721580,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Williams, Perry J.","contributorId":169058,"corporation":false,"usgs":false,"family":"Williams","given":"Perry","email":"","middleInitial":"J.","affiliations":[{"id":25400,"text":"U.S. Fish and Wildlife Service, Big Oaks National Wildlife Refuge","active":true,"usgs":false}],"preferred":false,"id":721581,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hooten, Mevin 0000-0002-1614-723X mhooten@usgs.gov","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":2958,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","email":"mhooten@usgs.gov","affiliations":[{"id":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":716562,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70188371,"text":"70188371 - 2017 - Subsurface volatile content of martian double-layer ejecta (DLE) craters","interactions":[],"lastModifiedDate":"2018-11-01T14:44:37","indexId":"70188371","displayToPublicDate":"2017-03-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1963,"text":"Icarus","active":true,"publicationSubtype":{"id":10}},"title":"Subsurface volatile content of martian double-layer ejecta (DLE) craters","docAbstract":"Excess ice is widespread throughout the martian mid-latitudes, particularly in Arcadia Planitia, where double-layer ejecta (DLE) craters also tend to be abundant. In this region, we observe the presence of thermokarstically-expanded secondary craters that likely form from impacts that destabilize a subsurface layer of excess ice, which subsequently sublimates. The presence of these expanded craters shows that excess ice is still preserved within the adjacent terrain. Here, we focus on a 15-km DLE crater that contains abundant superposed expanded craters in order to study the distribution of subsurface volatiles both at the time when the secondary craters formed and, by extension, remaining today. To do this, we measure the size distribution of the superposed expanded craters and use topographic data to calculate crater volumes as a proxy for the volumes of ice lost to sublimation during the expansion process. The inner ejecta layer contains craters that appear to have undergone more expansion, suggesting that excess ice was most abundant in that region. However, both of the ejecta layers had more expanded craters than the surrounding terrain. We extrapolate that the total volume of ice remaining within the entire ejecta deposit is as much as 74 km3 or more. The variation in ice content between the ejecta layers could be the result of (1) volatile preservation from the formation of the DLE crater, (2) post-impact deposition in the form of ice lenses; or (3) preferential accumulation or preservation of subsequent snowfall. We have ruled out (2) as the primary mode for ice deposition in this location based on inconsistencies with our observations, though it may operate in concert with other processes. Although none of the existing DLE formation hypotheses are completely consistent with our observations, which may merit a new or modified mechanism, we can conclude that DLE craters contain a significant quantity of excess ice today.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.icarus.2016.11.031","usgsCitation":"Viola, D., McEwen, A.S., Dundas, C.M., and Byrne, S., 2017, Subsurface volatile content of martian double-layer ejecta (DLE) craters: Icarus, v. 284, p. 325-343, https://doi.org/10.1016/j.icarus.2016.11.031.","productDescription":"19 p.","startPage":"325","endPage":"343","ipdsId":"IP-077824","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":342216,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Mars","volume":"284","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"593910abe4b0764e6c5e8850","contributors":{"authors":[{"text":"Viola, Donna","contributorId":127526,"corporation":false,"usgs":false,"family":"Viola","given":"Donna","email":"","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":697430,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McEwen, Alfred S.","contributorId":61657,"corporation":false,"usgs":false,"family":"McEwen","given":"Alfred","email":"","middleInitial":"S.","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":697431,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dundas, Colin M. 0000-0003-2343-7224 cdundas@usgs.gov","orcid":"https://orcid.org/0000-0003-2343-7224","contributorId":2937,"corporation":false,"usgs":true,"family":"Dundas","given":"Colin","email":"cdundas@usgs.gov","middleInitial":"M.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":697429,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Byrne, Shane","contributorId":192609,"corporation":false,"usgs":false,"family":"Byrne","given":"Shane","email":"","affiliations":[],"preferred":false,"id":697432,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70193265,"text":"70193265 - 2017 - Integrating multiple data sources in species distribution modeling: A framework for data fusion","interactions":[],"lastModifiedDate":"2018-12-20T12:52:54","indexId":"70193265","displayToPublicDate":"2017-03-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Integrating multiple data sources in species distribution modeling: A framework for data fusion","docAbstract":"The last decade has seen a dramatic increase in the use of species distribution models (SDMs) to characterize patterns of species’ occurrence and abundance. Efforts to parameterize SDMs often create a tension between the quality and quantity of data available to fit models. Estimation methods that integrate both standardized and non-standardized data types offer a potential solution to the tradeoff between data quality and quantity. Recently several authors have developed approaches for jointly modeling two sources of data (one of high quality and one of lesser quality). We extend their work by allowing for explicit spatial autocorrelation in occurrence and detection error using a Multivariate Conditional Autoregressive (MVCAR) model and develop three models that share information in a less direct manner resulting in more robust performance when the auxiliary data is of lesser quality. We describe these three new approaches (“Shared,” “Correlation,” “Covariates”) for combining data sources and show their use in a case study of the Brown-headed Nuthatch in the Southeastern U.S. and through simulations. All three of the approaches which used the second data source improved out-of-sample predictions relative to a single data source (“Single”). When information in the second data source is of high quality, the Shared model performs the best, but the Correlation and Covariates model also perform well. When the information quality in the second data source is of lesser quality, the Correlation and Covariates model performed better suggesting they are robust alternatives when little is known about auxiliary data collected opportunistically or through citizen scientists. Methods that allow for both data types to be used will maximize the useful information available for estimating species distributions.
","language":"English","publisher":"Wiley","doi":"10.1002/ecy.1710","usgsCitation":"Pacifici, K., Reich, B.J., Miller, D.A., Gardner, B., Stauffer, G.E., Singh, S., McKerrow, A., and Collazo, J., 2017, Integrating multiple data sources in species distribution modeling: A framework for data fusion: Ecology, v. 98, no. 3, p. 840-850, https://doi.org/10.1002/ecy.1710.","productDescription":"11 p.","startPage":"840","endPage":"850","ipdsId":"IP-073421","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true},{"id":37226,"text":"Core Science Analytics, Synthesis, and Libraries","active":true,"usgs":true},{"id":38315,"text":"GAP Analysis Project","active":true,"usgs":true}],"links":[{"id":470049,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecy.1710","text":"Publisher Index Page"},{"id":348018,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"98","issue":"3","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59fadd24e4b0531197b13cad","contributors":{"authors":[{"text":"Pacifici, Krishna","contributorId":26564,"corporation":false,"usgs":false,"family":"Pacifici","given":"Krishna","email":"","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":719048,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reich, Brian J.","contributorId":150871,"corporation":false,"usgs":false,"family":"Reich","given":"Brian","email":"","middleInitial":"J.","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":719049,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miller, David A.W. davidmiller@usgs.gov","contributorId":4043,"corporation":false,"usgs":true,"family":"Miller","given":"David","email":"davidmiller@usgs.gov","middleInitial":"A.W.","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":719050,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gardner, Beth","contributorId":91612,"corporation":false,"usgs":false,"family":"Gardner","given":"Beth","affiliations":[{"id":13553,"text":"University of Washington-Seattle","active":true,"usgs":false}],"preferred":false,"id":719051,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stauffer, Glenn E.","contributorId":171536,"corporation":false,"usgs":false,"family":"Stauffer","given":"Glenn","email":"","middleInitial":"E.","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":719052,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Singh, Susheela","contributorId":11646,"corporation":false,"usgs":false,"family":"Singh","given":"Susheela","email":"","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":719061,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McKerrow, Alexa 0000-0002-8312-2905 amckerrow@usgs.gov","orcid":"https://orcid.org/0000-0002-8312-2905","contributorId":127753,"corporation":false,"usgs":true,"family":"McKerrow","given":"Alexa","email":"amckerrow@usgs.gov","affiliations":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"preferred":true,"id":719062,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Collazo, Jaime A. 0000-0002-1816-7744 jaime_collazo@usgs.gov","orcid":"https://orcid.org/0000-0002-1816-7744","contributorId":173448,"corporation":false,"usgs":true,"family":"Collazo","given":"Jaime A.","email":"jaime_collazo@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":719063,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70194267,"text":"70194267 - 2017 - Current limitations and recommendations to improve testing for the environmental assessment of endocrine active substances","interactions":[],"lastModifiedDate":"2017-11-22T13:24:00","indexId":"70194267","displayToPublicDate":"2017-03-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2006,"text":"Integrated Environmental Assessment and Management","active":true,"publicationSubtype":{"id":10}},"title":"Current limitations and recommendations to improve testing for the environmental assessment of endocrine active substances","docAbstract":"In the present study, existing regulatory frameworks and test systems for assessing potential endocrine active chemicals are described, and associated challenges are discussed, along with proposed approaches to address these challenges. Regulatory frameworks vary somewhat across geographies, but all basically evaluate whether a chemical possesses endocrine activity and whether this activity can result in adverse outcomes either to humans or to the environment. Current test systems include in silico, in vitro, and in vivo techniques focused on detecting potential endocrine activity, and in vivo tests that collect apical data to detect possible adverse effects. These test systems are currently designed to robustly assess endocrine activity and/or adverse effects in the estrogen, androgen, and thyroid hormone signaling pathways; however, there are some limitations of current test systems for evaluating endocrine hazard and risk. These limitations include a lack of certainty regarding: 1) adequately sensitive species and life stages; 2) mechanistic endpoints that are diagnostic for endocrine pathways of concern; and 3) the linkage between mechanistic responses and apical, adverse outcomes. Furthermore, some existing test methods are resource intensive with regard to time, cost, and use of animals. However, based on recent experiences, there are opportunities to improve approaches to and guidance for existing test methods and to reduce uncertainty. For example, in vitro high-throughput screening could be used to prioritize chemicals for testing and provide insights as to the most appropriate assays for characterizing hazard and risk. Other recommendations include adding endpoints for elucidating connections between mechanistic effects and adverse outcomes, identifying potentially sensitive taxa for which test methods currently do not exist, and addressing key endocrine pathways of possible concern in addition to those associated with estrogen, androgen, and thyroid signaling.
","language":"English","publisher":"Society of Environmental Toxicology and Chemistry","doi":"10.1002/ieam.1862","usgsCitation":"Coady, K., Biever, R.C., Denslow, N., Gross, M., Guiney, P., Holbech, H., Karouna-Renier, N.K., Katsiadaki, I., Krueger, H., Levine, S., Maack, G., Williams, M., Wolf, J.C., and Ankley, G., 2017, Current limitations and recommendations to improve testing for the environmental assessment of endocrine active substances: Integrated Environmental Assessment and Management, v. 13, no. 2, p. 302-316, https://doi.org/10.1002/ieam.1862.","productDescription":"15 p.","startPage":"302","endPage":"316","ipdsId":"IP-075960","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":482067,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ieam.1862","text":"Publisher Index Page"},{"id":349281,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","issue":"2","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2016-10-28","publicationStatus":"PW","scienceBaseUri":"5a60fc05e4b06e28e9c238c2","contributors":{"authors":[{"text":"Coady, Katherine K.","contributorId":200647,"corporation":false,"usgs":false,"family":"Coady","given":"Katherine K.","affiliations":[],"preferred":false,"id":722967,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Biever, Ronald C.","contributorId":200648,"corporation":false,"usgs":false,"family":"Biever","given":"Ronald","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":722968,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Denslow, Nancy D.","contributorId":200649,"corporation":false,"usgs":false,"family":"Denslow","given":"Nancy D.","affiliations":[],"preferred":false,"id":722969,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gross, Melanie","contributorId":200650,"corporation":false,"usgs":false,"family":"Gross","given":"Melanie","email":"","affiliations":[],"preferred":false,"id":722970,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Guiney, Patrick D.","contributorId":200651,"corporation":false,"usgs":false,"family":"Guiney","given":"Patrick D.","affiliations":[],"preferred":false,"id":722971,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Holbech, Henrik","contributorId":200652,"corporation":false,"usgs":false,"family":"Holbech","given":"Henrik","email":"","affiliations":[],"preferred":false,"id":722972,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Karouna-Renier, Natalie K. 0000-0001-7127-033X nkarouna@usgs.gov","orcid":"https://orcid.org/0000-0001-7127-033X","contributorId":141213,"corporation":false,"usgs":true,"family":"Karouna-Renier","given":"Natalie","email":"nkarouna@usgs.gov","middleInitial":"K.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":722966,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Katsiadaki, Ioanna","contributorId":200653,"corporation":false,"usgs":false,"family":"Katsiadaki","given":"Ioanna","email":"","affiliations":[],"preferred":false,"id":722973,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Krueger, Hank","contributorId":200654,"corporation":false,"usgs":false,"family":"Krueger","given":"Hank","email":"","affiliations":[],"preferred":false,"id":722974,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Levine, Steven L.","contributorId":200655,"corporation":false,"usgs":false,"family":"Levine","given":"Steven L.","affiliations":[],"preferred":false,"id":722975,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Maack, Gerd","contributorId":200656,"corporation":false,"usgs":false,"family":"Maack","given":"Gerd","email":"","affiliations":[],"preferred":false,"id":722976,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Williams, Mike","contributorId":168795,"corporation":false,"usgs":false,"family":"Williams","given":"Mike","email":"","affiliations":[{"id":25361,"text":"CSIRO Land and Water, Adelaide, South Australia","active":true,"usgs":false}],"preferred":false,"id":722977,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Wolf, Jeffrey C.","contributorId":200657,"corporation":false,"usgs":false,"family":"Wolf","given":"Jeffrey","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":722978,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Ankley, Gerald T.","contributorId":177970,"corporation":false,"usgs":false,"family":"Ankley","given":"Gerald T.","affiliations":[{"id":13485,"text":"U.S. Environmental Protection Agency, Duluth, MN","active":true,"usgs":false}],"preferred":false,"id":722979,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}} ,{"id":70195175,"text":"70195175 - 2017 - In-well time-of-travel approach to evaluate optimal purge duration during low-flow sampling of monitoring wells","interactions":[],"lastModifiedDate":"2018-02-07T13:18:25","indexId":"70195175","displayToPublicDate":"2017-03-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1534,"text":"Environmental Earth Sciences","active":true,"publicationSubtype":{"id":10}},"title":"In-well time-of-travel approach to evaluate optimal purge duration during low-flow sampling of monitoring wells","docAbstract":"A common assumption with groundwater sampling is that low (<0.5 L/min) pumping rates during well purging and sampling captures primarily lateral flow from the formation through the well-screened interval at a depth coincident with the pump intake. However, if the intake is adjacent to a low hydraulic conductivity part of the screened formation, this scenario will induce vertical groundwater flow to the pump intake from parts of the screened interval with high hydraulic conductivity. Because less formation water will initially be captured during pumping, a substantial volume of water already in the well (preexisting screen water or screen storage) will be captured during this initial time until inflow from the high hydraulic conductivity part of the screened formation can travel vertically in the well to the pump intake. Therefore, the length of the time needed for adequate purging prior to sample collection (called optimal purge duration) is controlled by the in-well, vertical travel times. A preliminary, simple analytical model was used to provide information on the relation between purge duration and capture of formation water for different gross levels of heterogeneity (contrast between low and high hydraulic conductivity layers). The model was then used to compare these time–volume relations to purge data (pumping rates and drawdown) collected at several representative monitoring wells from multiple sites. Results showed that computation of time-dependent capture of formation water (as opposed to capture of preexisting screen water), which were based on vertical travel times in the well, compares favorably with the time required to achieve field parameter stabilization. If field parameter stabilization is an indicator of arrival time of formation water, which has been postulated, then in-well, vertical flow may be an important factor at wells where low-flow sampling is the sample method of choice.
","language":"English","publisher":"Springer","doi":"10.1007/s12665-017-6561-5","usgsCitation":"Harte, P.T., 2017, In-well time-of-travel approach to evaluate optimal purge duration during low-flow sampling of monitoring wells: Environmental Earth Sciences, v. 76, p. 1-13, https://doi.org/10.1007/s12665-017-6561-5.","productDescription":"Article 251; 13 p.","startPage":"1","endPage":"13","ipdsId":"IP-071519","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":351267,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"76","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2017-03-21","publicationStatus":"PW","scienceBaseUri":"5a7c1e7ce4b00f54eb229355","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":727304,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70189627,"text":"70189627 - 2017 - Broadband seismic noise attenuation versus depth at the Albuquerque Seismological Laboratory","interactions":[],"lastModifiedDate":"2018-03-29T11:32:05","indexId":"70189627","displayToPublicDate":"2017-03-01T00:00:00","publicationYear":"2017","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":"Broadband seismic noise attenuation versus depth at the Albuquerque Seismological Laboratory","docAbstract":"Seismic noise induced by atmospheric processes such as wind and pressure changes can be a major contributor to the background noise observed in many seismograph stations, especially those installed at or near the surface. Cultural noise such as vehicle traffic or nearby buildings with air handling equipment also contributes to seismic background noise. Such noise sources fundamentally limit our ability to resolve earthquake‐generated signals. Many previous seismic noise versus depth studies focused separately on either high‐frequency (
Background
Avian paramyxovirus serotype 1 (APMV-1) viruses are globally distributed, infect wild, peridomestic, and domestic birds, and sometimes lead to outbreaks of disease. Thus, the maintenance, evolution, and spread of APMV-1 viruses are relevant to avian health.
Methods
In this study we sequenced the fusion gene from 58 APMV-1 isolates recovered from thirteen species of wild birds sampled throughout the USA during 2007–2014. We analyzed sequence information with previously reported data in order to assess contemporary genetic diversity and inter-taxa/inter-region exchange of APMV-1 in wild birds sampled in North America.
Results
Our results suggest that wild birds maintain previously undescribed genetic diversity of APMV-1; however, such diversity is unlikely to be pathogenic to domestic poultry. Phylogenetic analyses revealed that APMV-1 diversity detected in wild birds of North America has been found in birds belonging to numerous taxonomic host orders and within hosts inhabiting multiple geographic regions suggesting some level of viral exchange. However, our results also provide statistical support for associations between phylogenetic tree topology and host taxonomic order/region of sample origin which supports restricted exchange among taxa and geographical regions of North America for some APMV-1 sub-genotypes.
Conclusions
We identify previously unrecognized genetic diversity of APMV-1 in wild birds in North America which is likely a function of continued viral evolution in reservoir hosts. We did not, however, find support for the emergence or maintenance of APMV-1 strains predicted to be pathogenic to poultry in wild birds of North America outside of the order Suliformes (i.e., cormorants). Furthermore, genetic evidence suggests that ecological drivers or other mechanisms may restrict viral exchange among taxa and regions of North America. Additional and more systematic sampling for APMV-1 in North America would likely provide further inference on viral dynamics for this infectious agent in wild bird populations.
A SETAC Pellston Workshop® “Environmental Hazard and Risk Assessment Approaches for Endocrine-Active Substances (EHRA)” was held in February 2016 in Pensacola, Florida, USA. The primary objective of the workshop was to provide advice, based on current scientific understanding, to regulators and policy makers; the aim being to make considered, informed decisions on whether to select an ecotoxicological hazard- or a risk-based approach for regulating a given endocrine-disrupting substance (EDS) under review. The workshop additionally considered recent developments in the identification of EDS. Case studies were undertaken on 6 endocrine-active substances (EAS—not necessarily proven EDS, but substances known to interact directly with the endocrine system) that are representative of a range of perturbations of the endocrine system and considered to be data rich in relevant information at multiple biological levels of organization for 1 or more ecologically relevant taxa. The substances selected were 17α-ethinylestradiol, perchlorate, propiconazole, 17β-trenbolone, tributyltin, and vinclozolin. The 6 case studies were not comprehensive safety evaluations but provided foundations for clarifying key issues and procedures that should be considered when assessing the ecotoxicological hazards and risks of EAS and EDS. The workshop also highlighted areas of scientific uncertainty, and made specific recommendations for research and methods-development to resolve some of the identified issues. The present paper provides broad guidance for scientists in regulatory authorities, industry, and academia on issues likely to arise during the ecotoxicological hazard and risk assessment of EAS and EDS. The primary conclusion of this paper, and of the SETAC Pellston Workshop on which it is based, is that if data on environmental exposure, effects on sensitive species and life-stages, delayed effects, and effects at low concentrations are robust, initiating environmental risk assessment of EDS is scientifically sound and sufficiently reliable and protective of the environment. In the absence of such data, assessment on the basis of hazard is scientifically justified until such time as relevant new information is available.
","language":"English","publisher":"Society of Environmental Toxicology and Chemistry","doi":"10.1002/ieam.1885","usgsCitation":"Matthiessen, P., Ankley, G.T., Biever, R.C., Bjerregaard, P., Borgert, C., Brugger, K., Blankinship, A., Chambers, J., Coady, K.K., Constantine, L., Dang, Z., Denslow, N.D., Dreier, D., Dungey, S., Gray, L.E., Gross, M., Guiney, P.D., Hecker, M., Holbech, H., Iguchi, T., Kadlec, S., Karouna-Renier, N.K., Katsiadaki, I., Kawashima, Y., Kloas, W., Krueger, H., Kumar, A., Lagadic, L., Leopold, A., Levine, S.L., Maack, G., Marty, S., Meador, J., Mihaich, E., Odum, J., Ortego, L., Parrott, J.L., Pickford, D., Roberts, M., Schaefers, C., Schwarz, T., Solomon, K., Verslycke, T., Weltje, L., Wheeler, J.R., Williams, M., Wolf, J.C., and Yamazaki, K., 2017, Recommended approaches to the scientific evaluation of ecotoxicological hazards and risks of endocrine-active substances: Integrated Environmental Assessment and Management, v. 13, no. 2, p. 267-279, https://doi.org/10.1002/ieam.1885.","productDescription":"13 p.","startPage":"267","endPage":"279","ipdsId":"IP-075958","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":470031,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ieam.1885","text":"Publisher Index Page"},{"id":349274,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","issue":"2","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2017-03-01","publicationStatus":"PW","scienceBaseUri":"5a60fc05e4b06e28e9c238bf","contributors":{"authors":[{"text":"Matthiessen, Peter","contributorId":200658,"corporation":false,"usgs":false,"family":"Matthiessen","given":"Peter","email":"","affiliations":[],"preferred":false,"id":722981,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ankley, Gerald 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Mike","contributorId":103563,"corporation":false,"usgs":true,"family":"Williams","given":"Mike","affiliations":[],"preferred":false,"id":723298,"contributorType":{"id":1,"text":"Authors"},"rank":46},{"text":"Wolf, Jeffery C.","contributorId":50770,"corporation":false,"usgs":true,"family":"Wolf","given":"Jeffery","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":723299,"contributorType":{"id":1,"text":"Authors"},"rank":47},{"text":"Yamazaki, Kunihiko","contributorId":200774,"corporation":false,"usgs":false,"family":"Yamazaki","given":"Kunihiko","email":"","affiliations":[],"preferred":false,"id":723300,"contributorType":{"id":1,"text":"Authors"},"rank":48}]}} ,{"id":70187613,"text":"70187613 - 2017 - Solving for source parameters using nested array data: A case study from the Canterbury, New Zealand earthquake sequence","interactions":[],"lastModifiedDate":"2019-12-17T09:32:50","indexId":"70187613","displayToPublicDate":"2017-03-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3208,"text":"Pure and Applied Geophysics","active":true,"publicationSubtype":{"id":10}},"title":"Solving for source parameters using nested array data: A case study from the Canterbury, New Zealand earthquake sequence","docAbstract":"The seismic spectrum can be constructed by assuming a Brune spectral model and estimating the parameters of seismic moment (M0), corner frequency (fc), and high-frequency site attenuation (κ). Using seismic data collected during the 2010–2011 Canterbury, New Zealand, earthquake sequence, we apply the non-linear least-squares Gauss–Newton method, a deterministic downhill optimization technique, to simultaneously determine the M0, fc, and κ for each event-station pair. We fit the Brune spectral acceleration model to Fourier-transformed S-wave records following application of path and site corrections to the data. For each event, we solve for a single M0 and fc, while any remaining residual kappa,
Toppling analysis of a precariously balanced rock (PBR) can provide insight into the nature of ground motion that has not occurred at that location in the past and, by extension, can constrain peak ground motions for use in engineering design. Earlier approaches have targeted 2D models of the rock or modeled the rock–pedestal contact using spring‐damper assemblies that require recalibration for each rock. Here, a method to model PBRs in 3D is presented through a case study of the Echo Cliffs PBR. The 3D model is created from a point cloud of the rock, the pedestal, and their interface, obtained using terrestrial laser scanning. The dynamic response of the model under earthquake excitation is simulated using a rigid‐body dynamics algorithm. The veracity of this approach is demonstrated through comparisons against data from shake‐table experiments. Fragility maps for toppling probability of the Echo Cliffs PBR as a function of various ground‐motion parameters, rock–pedestal interface friction coefficient, and excitation direction are presented. These fragility maps indicate that the toppling probability of this rock is low (less than 0.2) for peak ground acceleration (PGA) and peak ground velocity (PGV) lower than 3 m/s2 and 0.75 m/s, respectively, suggesting that the ground‐motion intensities at this location from earthquakes on nearby faults have most probably not exceeded the above‐mentioned PGA and PGV during the age of the PBR. Additionally, the fragility maps generated from this methodology can also be directly coupled with existing probabilistic frameworks to obtain direct constraints on unexceeded ground motion at a PBR’s location.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120160169","usgsCitation":"Veeraraghavan, S., Hudnut, K.W., and Krishnan, S., 2017, Toppling analysis of the Echo Cliffs precariously balanced rock: Bulletin of the Seismological Society of America, v. 107, no. 1, p. 72-84, https://doi.org/10.1785/0120160169.","productDescription":"13 p.","startPage":"72","endPage":"84","ipdsId":"IP-078915","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":470046,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://resolver.caltech.edu/CaltechAUTHORS:20161213-141035303","text":"External Repository"},{"id":342189,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Echo Cliffs precariously balanced rock","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -118.92706014090601,\n 34.12673669928829\n ],\n [\n -118.92706014090601,\n 34.12580082827124\n ],\n [\n -118.92597045637072,\n 34.12580082827124\n ],\n [\n -118.92597045637072,\n 34.12673669928829\n ],\n [\n -118.92706014090601,\n 34.12673669928829\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"107","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-12-13","publicationStatus":"PW","scienceBaseUri":"5937bf2de4b0f6c2d0d9c75b","contributors":{"authors":[{"text":"Veeraraghavan, Swetha","contributorId":192670,"corporation":false,"usgs":false,"family":"Veeraraghavan","given":"Swetha","email":"","affiliations":[],"preferred":false,"id":697334,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hudnut, Kenneth W. 0000-0002-3168-4797 hudnut@usgs.gov","orcid":"https://orcid.org/0000-0002-3168-4797","contributorId":2550,"corporation":false,"usgs":true,"family":"Hudnut","given":"Kenneth","email":"hudnut@usgs.gov","middleInitial":"W.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true}],"preferred":true,"id":697333,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Krishnan, Swaminathan","contributorId":192671,"corporation":false,"usgs":false,"family":"Krishnan","given":"Swaminathan","email":"","affiliations":[],"preferred":false,"id":697335,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70191859,"text":"70191859 - 2017 - Ground-rupturing earthquakes on the northern Big Bend of the San Andreas Fault, California, 800 A.D. to Present","interactions":[],"lastModifiedDate":"2017-10-18T16:09:11","indexId":"70191859","displayToPublicDate":"2017-03-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2312,"text":"Journal of Geophysical Research","active":true,"publicationSubtype":{"id":10}},"title":"Ground-rupturing earthquakes on the northern Big Bend of the San Andreas Fault, California, 800 A.D. to Present","docAbstract":"Paleoseismic data on the timing of ground-rupturing earthquakes constrain the recurrence behavior of active faults and can provide insight on the rupture history of a fault if earthquakes dated at neighboring sites overlap in age and are considered correlative. This study presents the evidence and ages for 11 earthquakes that occurred along the Big Bend section of the southern San Andreas Fault at the Frazier Mountain paleoseismic site. The most recent earthquake to rupture the site was the Mw7.7–7.9 Fort Tejon earthquake of 1857. We use over 30 trench excavations to document the structural and sedimentological evolution of a small pull-apart basin that has been repeatedly faulted and folded by ground-rupturing earthquakes. A sedimentation rate of 0.4 cm/yr and abundant organic material for radiocarbon dating contribute to a record that is considered complete since 800 A.D. and includes 10 paleoearthquakes. Earthquakes have ruptured this location on average every ~100 years over the last 1200 years, but individual intervals range from ~22 to 186 years. The coefficient of variation of the length of time between earthquakes (0.7) indicates quasiperiodic behavior, similar to other sites along the southern San Andreas Fault. Comparison with the earthquake chronology at neighboring sites along the fault indicates that only one other 1857-size earthquake could have occurred since 1350 A.D., and since 800 A.D., the Big Bend and Mojave sections have ruptured together at most 50% of the time in Mw ≥ 7.3 earthquakes.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2016JB013606","usgsCitation":"Scharer, K.M., Weldon, R.J., Biasi, G., Streig, A., and Fumal, T.E., 2017, Ground-rupturing earthquakes on the northern Big Bend of the San Andreas Fault, California, 800 A.D. to Present: Journal of Geophysical Research, v. 122, no. 3, p. 2193-2218, https://doi.org/10.1002/2016JB013606.","productDescription":"26 p.","startPage":"2193","endPage":"2218","ipdsId":"IP-079786","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":470036,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2016jb013606","text":"Publisher Index Page"},{"id":346907,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Andreas Fault","volume":"122","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-03-22","publicationStatus":"PW","scienceBaseUri":"59e86836e4b05fe04cd4d202","contributors":{"authors":[{"text":"Scharer, Katherine M. 0000-0003-2811-2496 kscharer@usgs.gov","orcid":"https://orcid.org/0000-0003-2811-2496","contributorId":3385,"corporation":false,"usgs":true,"family":"Scharer","given":"Katherine","email":"kscharer@usgs.gov","middleInitial":"M.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":713426,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Weldon, Ray J.","contributorId":175463,"corporation":false,"usgs":false,"family":"Weldon","given":"Ray","email":"","middleInitial":"J.","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":713427,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Biasi, Glenn","contributorId":175464,"corporation":false,"usgs":false,"family":"Biasi","given":"Glenn","affiliations":[],"preferred":false,"id":713428,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Streig, Ashley","contributorId":39707,"corporation":false,"usgs":true,"family":"Streig","given":"Ashley","affiliations":[],"preferred":false,"id":713429,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fumal, Thomas E.","contributorId":195091,"corporation":false,"usgs":false,"family":"Fumal","given":"Thomas","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":713430,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70194487,"text":"70194487 - 2017 - Geologic controls on submarine slope failure along the central U.S. Atlantic margin: Insights from the Currituck Slide Complex","interactions":[],"lastModifiedDate":"2017-11-29T15:36:35","indexId":"70194487","displayToPublicDate":"2017-03-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2667,"text":"Marine Geology","active":true,"publicationSubtype":{"id":10}},"title":"Geologic controls on submarine slope failure along the central U.S. Atlantic margin: Insights from the Currituck Slide Complex","docAbstract":"Multiple styles of failure, ranging from densely spaced, mass transport driven canyons to the large, slab-type slope failure of the Currituck Slide, characterize adjacent sections of the central U.S. Atlantic margin that appear to be defined by variations in geologic framework. Here we use regionally extensive, deep penetration multichannel seismic (MCS) profiles to reconstruct the influence of the antecedent margin physiography on sediment accumulation along the central U.S. Atlantic continental shelf-edge, slope, and uppermost rise from the Miocene to Present. These data are combined with high-resolution sparker MCS reflection profiles and multibeam bathymetry data across the Currituck Slide Complex. Pre-Neogene allostratigraphic horizons beneath the slope are generally characterized by low gradients and convex downslope profiles. This is followed by the development of thick, prograded deltaic clinoforms during the middle Miocene. Along-strike variations in morphology of a regional unconformity at the top of this middle Miocene unit appear to have set the stage for differing styles of mass transport along the margin. Areas north and south of the Currituck Slide are characterized by oblique margin morphology, defined by an angular shelf-edge and a relatively steep (> 8°), concave slope profile. Upper slope sediment bypass, closely spaced submarine canyons, and small, localized landslides confined to canyon heads and sidewalls characterize these sectors of the margin. In contrast, the Currituck region is defined by a sigmoidal geometry, with a rounded shelf-edge rollover and gentler slope gradient (< 6°). Thick (> 800 m), regionally continuous stratified slope deposits suggest the low gradient Currituck region was a primary depocenter for fluvial inputs during multiple sea level lowstands. These results imply that the rounded, gentle slope physiography developed during the middle Miocene allowed for a relatively high rate of subsequent sediment accumulation, thus providing a mechanism for compaction–induced overpressure that preconditioned the Currituck region for failure. Detailed examination of the regional geological framework illustrates the importance of both sediment supply and antecedent slope physiography in the development of large, potentially unstable depocenters along passive margins.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.margeo.2016.10.007","usgsCitation":"Hill, J.C., Brothers, D., Craig, B.K., ten Brink, U., Chaytor, J.D., and Flores, C., 2017, Geologic controls on submarine slope failure along the central U.S. Atlantic margin: Insights from the Currituck Slide Complex: Marine Geology, v. 385, p. 114-130, https://doi.org/10.1016/j.margeo.2016.10.007.","productDescription":"17 p.","startPage":"114","endPage":"130","ipdsId":"IP-075947","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":470092,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.margeo.2016.10.007","text":"Publisher Index Page"},{"id":349576,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.5,\n 35\n ],\n [\n -74,\n 35\n ],\n [\n -74,\n 37\n ],\n [\n -75.5,\n 37\n ],\n [\n -75.5,\n 35\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"385","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fc05e4b06e28e9c238bb","contributors":{"authors":[{"text":"Hill, Jenna C. 0000-0002-7475-357X","orcid":"https://orcid.org/0000-0002-7475-357X","contributorId":21987,"corporation":false,"usgs":true,"family":"Hill","given":"Jenna","email":"","middleInitial":"C.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":724077,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brothers, Daniel S. dbrothers@usgs.gov","contributorId":3782,"corporation":false,"usgs":true,"family":"Brothers","given":"Daniel S.","email":"dbrothers@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":724078,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Craig, Bradley K.","contributorId":201005,"corporation":false,"usgs":false,"family":"Craig","given":"Bradley","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":724079,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"ten Brink, Uri S. 0000-0001-6858-3001 utenbrink@usgs.gov","orcid":"https://orcid.org/0000-0001-6858-3001","contributorId":127560,"corporation":false,"usgs":true,"family":"ten Brink","given":"Uri S.","email":"utenbrink@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":false,"id":724080,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chaytor, Jason D. jchaytor@usgs.gov","contributorId":127559,"corporation":false,"usgs":true,"family":"Chaytor","given":"Jason","email":"jchaytor@usgs.gov","middleInitial":"D.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":724081,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Flores, Claudia cflores@usgs.gov","contributorId":4265,"corporation":false,"usgs":true,"family":"Flores","given":"Claudia","email":"cflores@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":724082,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70192856,"text":"70192856 - 2017 - LANDFIRE 2015 Remap – Utilization of Remotely Sensed Data to Classify Existing Vegetation Type and Structure to Support Strategic Planning and Tactical Response","interactions":[],"lastModifiedDate":"2017-10-30T15:08:59","indexId":"70192856","displayToPublicDate":"2017-03-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1440,"text":"Earthzine","active":true,"publicationSubtype":{"id":10}},"title":"LANDFIRE 2015 Remap – Utilization of Remotely Sensed Data to Classify Existing Vegetation Type and Structure to Support Strategic Planning and Tactical Response","docAbstract":"The LANDFIRE Program produces national scale vegetation, fuels, fire regimes, and landscape disturbance data for the entire U.S. These data products have been used to model the potential impacts of fire on the landscape [1], the wildfire risks associated with land and resource management [2, 3], and those near population centers and accompanying Wildland Urban Interface zones [4], as well as many other applications. The initial LANDFIRE National Existing Vegetation Type (EVT) and vegetation structure layers, including vegetation percent cover and height, were mapped circa 2001 and released in 2009 [5]. Each EVT is representative of the dominant plant community within a given area. The EVT layer has since been updated by identifying areas of landscape change and modifying the vegetation types utilizing a series of rules that consider the disturbance type, severity of disturbance, and time since disturbance [6, 7]. Non-disturbed areas were adjusted for vegetation growth and succession. LANDFIRE vegetation structure layers also have been updated by using data modeling techniques [see 6 for a full description]. The subsequent updated versions of LANDFIRE include LANDFIRE 2008, 2010, 2012, and LANDFIRE 2014 is being incrementally released, with all data being released in early 2017. Additionally, a comprehensive remap of the baseline data, LANDFIRE 2015 Remap, is being prototyped, and production is tentatively planned to begin in early 2017 to provide a more current baseline for future updates.
","language":"English","publisher":"IEEE","usgsCitation":"Picotte, J.J., Long, J., Peterson, B., and Nelson, K., 2017, LANDFIRE 2015 Remap – Utilization of Remotely Sensed Data to Classify Existing Vegetation Type and Structure to Support Strategic Planning and Tactical Response: Earthzine, v. March 2017, HTML Document.","productDescription":"HTML Document","ipdsId":"IP-078297","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":347731,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":347605,"type":{"id":15,"text":"Index Page"},"url":"https://earthzine.org/2017/03/20/landfire-2015-remap-utilization-of-remotely-sensed-data-to-classify-existing-vegetation-type-and-structure-to-support-strategic-planning-and-tactical-response/"}],"volume":"March 2017","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59f83a38e4b063d5d30980ec","contributors":{"authors":[{"text":"Picotte, Joshua J. 0000-0002-4021-4623 jpicotte@usgs.gov","orcid":"https://orcid.org/0000-0002-4021-4623","contributorId":4626,"corporation":false,"usgs":true,"family":"Picotte","given":"Joshua","email":"jpicotte@usgs.gov","middleInitial":"J.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":717219,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Long, Jordan 0000-0002-4814-464X jlong@usgs.gov","orcid":"https://orcid.org/0000-0002-4814-464X","contributorId":3609,"corporation":false,"usgs":true,"family":"Long","given":"Jordan","email":"jlong@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":717221,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Peterson, Birgit 0000-0002-4356-1540 bpeterson@usgs.gov","orcid":"https://orcid.org/0000-0002-4356-1540","contributorId":192353,"corporation":false,"usgs":true,"family":"Peterson","given":"Birgit","email":"bpeterson@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":717220,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nelson, Kurtis 0000-0003-4911-4511 knelson@usgs.gov","orcid":"https://orcid.org/0000-0003-4911-4511","contributorId":3602,"corporation":false,"usgs":true,"family":"Nelson","given":"Kurtis","email":"knelson@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":717222,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70193485,"text":"70193485 - 2017 - Conservation status of the American horseshoe crab, (Limulus polyphemus): A regional assessment","interactions":[],"lastModifiedDate":"2017-11-10T11:05:48","indexId":"70193485","displayToPublicDate":"2017-03-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3278,"text":"Reviews in Fish Biology and Fisheries","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Conservation status of the American horseshoe crab, (Limulus polyphemus): A regional assessment","title":"Conservation status of the American horseshoe crab, (Limulus polyphemus): A regional assessment","docAbstract":"Horseshoe crabs have persisted for more than 200 million years, and fossil forms date to 450 million years ago. The American horseshoe crab (Limulus polyphemus), one of four extant horseshoe crab species, is found along the Atlantic coastline of North America ranging from Alabama to Maine, USA with another distinct population on the coasts of Campeche, Yucatán and Quintana Roo in the Yucatán Peninsula, México. Although the American horseshoe crab tolerates broad environmental conditions, exploitation and habitat loss threaten the species. We assessed the conservation status of the American horseshoe crab by comprehensively reviewing available scientific information on its range, life history, genetic structure, population trends and analyses, major threats, and conservation. We structured the status assessment by six genetically-informed regions and accounted for sub-regional differences in environmental conditions, threats, and management. The transnational regions are Gulf of Maine (USA), Mid-Atlantic (USA), Southeast (USA), Florida Atlantic (USA), Northeast Gulf of México (USA), and Yucatán Peninsula (México). Our conclusion is that the American horseshoe crab species is vulnerable to local extirpation and that the degree and extent of risk vary among and within the regions. The risk is elevated in the Gulf of Maine region due to limited and fragmented habitat. The populations of horseshoe crabs in the Mid-Atlantic region are stable in the Delaware Bay area, and regulatory controls are in place, but the risk is elevated in the New England area as evidenced by continuing declines understood to be caused by over-harvest. The populations of horseshoe crabs in the Southeast region are stable or increasing. The populations of horseshoe crabs in the Florida Atlantic region show mixed trends among areas, and continuing population reductions at the embayment level have poorly understood causes. Within the Northeast Gulf of Mexico, causes of population trends are poorly understood and currently there is no active management of horseshoe crabs. Horseshoe crabs within México have conservation protection based on limited and fragmented habitat and geographic isolation from other regions, but elevated risk applies to the horseshoe crabs in the Yucatán Peninsula region until sufficient data can confirm population stability. Future species status throughout its range will depend on the effectiveness of conservation to mitigate habitat loss and manage for sustainable harvest among and within regions.
","language":"English","publisher":"Springer","doi":"10.1007/s11160-016-9461-y","usgsCitation":"Smith, D.R., Brockmann, H.J., Beekey, M.A., King, T.L., Millard, M., and Zaldivar-Rae, J., 2017, Conservation status of the American horseshoe crab, (Limulus polyphemus): A regional assessment: Reviews in Fish Biology and Fisheries, v. 27, no. 1, p. 135-175, https://doi.org/10.1007/s11160-016-9461-y.","productDescription":"41 p.","startPage":"135","endPage":"175","ipdsId":"IP-072969","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":470094,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s11160-016-9461-y","text":"Publisher Index Page"},{"id":348566,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"North America","volume":"27","issue":"1","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2016-12-10","publicationStatus":"PW","scienceBaseUri":"5a06c8cfe4b09af898c86135","contributors":{"authors":[{"text":"Smith, David R. 0000-0001-6074-9257 drsmith@usgs.gov","orcid":"https://orcid.org/0000-0001-6074-9257","contributorId":168442,"corporation":false,"usgs":true,"family":"Smith","given":"David","email":"drsmith@usgs.gov","middleInitial":"R.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":721551,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brockmann, H. 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To derive a relationship to predict skua numbers from better-quantified penguin numbers, we used distance sampling to estimate breeding skua numbers within 1000 m of 5 penguin nesting locations (Cape Crozier, Cape Royds, and 3 Cape Bird locations) on Ross Island in 3 consecutive years. Estimated numbers of skua breeding pairs were highest at Cape Crozier (270,000 penguin pairs; 1099 and 1347 skua pairs in 2 respective years) and lowest at Cape Royds (3000 penguin pairs; 45 skua pairs). The log–log linear relationship (R2 = 0.98) between pairs of skuas and penguins was highly significant, and most historical estimates of skua and penguin numbers in the Ross Sea were within 95 % prediction intervals of the regression. Applying our regression model to current Adélie Penguin colony sizes at 23 western Ross Sea locations predicted that 4635 pairs of skuas now breed within 1000 m of penguin colonies in the Ross Island metapopulation (including Beaufort Island) and northern Victoria Land. We estimate, using published skua estimates for elsewhere in Antarctica, that the Ross Sea South Polar Skua population comprises ~50 % of the world total, although this may be an overestimate because of incomplete data elsewhere. To improve predictions and enable measurement of future skua population change, we recommend additional South Polar Skua surveys using consistent distance-sampling methods at penguin colonies of a range of sizes.
","language":"English","publisher":"Springer","doi":"10.1007/s00300-016-1980-4","usgsCitation":"Wilson, D.J., Lyver, P.O., Greene, T.C., Whitehead, A.L., Dugger, K., Karl, B.J., Barringer, J.R., McGarry, R., Pollard, A.M., and Ainley, D.G., 2017, South Polar Skua breeding populations in the Ross Sea assessed from demonstrated relationship with Adélie Penguin numbers: Polar Biology, v. 40, no. 3, p. 577-592, https://doi.org/10.1007/s00300-016-1980-4.","productDescription":"16 p.","startPage":"577","endPage":"592","ipdsId":"IP-067093","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":346998,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":" Ross Island","volume":"40","issue":"3","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-06-08","publicationStatus":"PW","scienceBaseUri":"59e9b995e4b05fe04cd65ca2","contributors":{"authors":[{"text":"Wilson, Deborah J.","contributorId":197733,"corporation":false,"usgs":false,"family":"Wilson","given":"Deborah","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":714161,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lyver, Phil O’B.","contributorId":197706,"corporation":false,"usgs":false,"family":"Lyver","given":"Phil","email":"","middleInitial":"O’B.","affiliations":[],"preferred":false,"id":714162,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Greene, Terry C.","contributorId":197734,"corporation":false,"usgs":false,"family":"Greene","given":"Terry","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":714163,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Whitehead, Amy L.","contributorId":197735,"corporation":false,"usgs":false,"family":"Whitehead","given":"Amy","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":714164,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dugger, Katie M. 0000-0002-4148-246X cdugger@usgs.gov","orcid":"https://orcid.org/0000-0002-4148-246X","contributorId":4399,"corporation":false,"usgs":true,"family":"Dugger","given":"Katie","email":"cdugger@usgs.gov","middleInitial":"M.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":714109,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Karl, Brian J.","contributorId":197736,"corporation":false,"usgs":false,"family":"Karl","given":"Brian","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":714165,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Barringer, James R. 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The compositions of the major elements, reported as oxides (SiO2, TiO2, Al2O3, FeOT, MgO, CaO, Na2O, K2O), have been re-calibrated using a laboratory LIBS instrument, Mars-like atmospheric conditions, and a much larger set of standards (408) that span a wider compositional range than previously employed. The new calibration uses a combination of partial least squares (PLS1) and Independent Component Analysis (ICA) algorithms, together with a calibration transfer matrix to minimize differences between the conditions under which the standards were analyzed in the laboratory and the conditions on Mars. While the previous model provided good results in the compositional range near the average Mars surface composition, the new model fits the extreme compositions far better. Examples are given for plagioclase feldspars, where silicon was significantly over-estimated by the previous model, and for calcium-sulfate veins, where silicon compositions near zero were inaccurate. The uncertainties of major element abundances are described as a function of the abundances, and are overall significantly lower than the previous model, enabling important new geochemical interpretations of the data.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.sab.2016.12.003","usgsCitation":"Clegg, S.M., Wiens, R.C., Anderson, R.B., Forni, O., Frydenvang, J., Lasue, J., Cousin, A., Payre, V., Boucher, T., Dyar, M.D., McLennan, S.M., Morris, R., Graff, T.G., Mertzman, S.A., Ehlmann, B.L., Belgacem, I., Newsom, H.E., Clark, B.C., Melikechi, N., Mezzacappa, A., McInroy, R.E., Martinez, R., Gasda, P.J., Gasnault, O., and Maurice, S., 2017, Recalibration of the Mars Science Laboratory ChemCam instrument with an expanded geochemical database: Spectrochimica Acta Part B: Atomic Spectroscopy, v. 129, p. 64-85, https://doi.org/10.1016/j.sab.2016.12.003.","productDescription":"22 p.","startPage":"64","endPage":"85","ipdsId":"IP-070353","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":470038,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.osti.gov/biblio/1338777","text":"External Repository"},{"id":349013,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"129","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a60fc05e4b06e28e9c238c5","contributors":{"authors":[{"text":"Clegg, Samuel M.","contributorId":23460,"corporation":false,"usgs":false,"family":"Clegg","given":"Samuel","email":"","middleInitial":"M.","affiliations":[{"id":13447,"text":"Los Alamos National Laboratory","active":true,"usgs":false}],"preferred":false,"id":722216,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wiens, Roger C.","contributorId":140330,"corporation":false,"usgs":false,"family":"Wiens","given":"Roger","email":"","middleInitial":"C.","affiliations":[{"id":13447,"text":"Los Alamos National Laboratory","active":true,"usgs":false}],"preferred":false,"id":722217,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anderson, Ryan B. 0000-0003-4465-2871 rbanderson@usgs.gov","orcid":"https://orcid.org/0000-0003-4465-2871","contributorId":170054,"corporation":false,"usgs":true,"family":"Anderson","given":"Ryan","email":"rbanderson@usgs.gov","middleInitial":"B.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":722215,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Forni, Olivier","contributorId":72690,"corporation":false,"usgs":false,"family":"Forni","given":"Olivier","email":"","affiliations":[],"preferred":false,"id":722218,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Frydenvang, Jens","contributorId":173225,"corporation":false,"usgs":false,"family":"Frydenvang","given":"Jens","email":"","affiliations":[{"id":27196,"text":"LANL","active":true,"usgs":false}],"preferred":false,"id":722219,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lasue, Jeremie","contributorId":181504,"corporation":false,"usgs":false,"family":"Lasue","given":"Jeremie","email":"","affiliations":[],"preferred":false,"id":722220,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cousin, Agnes","contributorId":40139,"corporation":false,"usgs":false,"family":"Cousin","given":"Agnes","email":"","affiliations":[{"id":13447,"text":"Los Alamos National Laboratory","active":true,"usgs":false}],"preferred":false,"id":722221,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Payre, Valerie","contributorId":172304,"corporation":false,"usgs":false,"family":"Payre","given":"Valerie","email":"","affiliations":[{"id":27022,"text":"Universite de Lorraine","active":true,"usgs":false}],"preferred":false,"id":722222,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Boucher, Tommy","contributorId":200410,"corporation":false,"usgs":false,"family":"Boucher","given":"Tommy","email":"","affiliations":[],"preferred":false,"id":722223,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Dyar, M. 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The photographs in this report document the state of the barrier islands and other coastal features at the time of the survey.
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U.S. Geological Survey
600 4th Street South
St. Petersburg, FL 33701
(727) 502–8000
https://coastal.er.usgs.gov/
The U.S. Geological Survey (USGS), as part of the National Assessment of Coastal Change Hazards project, conducts baseline and storm-response photography missions to document and understand the changes in the vulnerability of the Nation's coasts to extreme storms. On February 18–19, 2016, the USGS conducted an oblique aerial photographic survey from the South Carolina/North Carolina border to Assateague Island, Virginia, aboard a Cessna 182 (aircraft) at an altitude of 500 feet (ft) and approximately 1,200 ft offshore. This mission was flown to collect baseline data for assessing incremental changes in the beach and nearshore area and can be used to assess future coastal change.
The photographs in this report document the state of the barrier islands and other coastal features at the time of the survey.
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U.S. Geological Survey
600 4th Street South
St. Petersburg, FL 33701
(727) 502–8000
https://coastal.er.usgs.gov/