The U.S. Geological Survey (USGS) Coastal and Marine Science Center in Woods Hole, Massachusetts, is leading an effort to understand the regional sediment dynamics along the coastline of North and South Carolina. As part of the Carolinas Coastal Change Processes Project, a geologic framework study in June of 2008 by the Woods Hole Coastal and Marine Science Center's Sea Floor Mapping Group focused on the seaward limit of Diamond Shoals and provided high resolution bathymetric data, surficial sediment characteristics, and subsurface geologic stratigraphy. These data also provided unprecedented guidance to identify deployment locations for tripods and moorings to investigate the processes that control sediment transport at Diamond Shoals. Equipment was deployed at three sites from early January, 2009 through early May, 2009: north and south of the shoals at 15 m depth, and at the tip at 24 m depth. Many strong storm systems were recorded during that time period. Mounted on the tripods were instruments to measure surface waves, pressure, current velocity, bottom turbulence, suspended-sediment profiles, and sea-floor sand-ripple bedforms. Many instruments were designed and programmed to sample in high resolution in time and space, as fast as 8 Hz hourly bursts and as small as 6 cm bin sizes in near bottom profiles. A second tripod at the north site also held a visual camera system and sonar imaging system which document seafloor bedforms. The region is known for its dynamics, and one of the tripods tipped over towards the end of the experiment. A preliminary look at the data suggests the region is characterized by high energy. Raw data from a burst recorded at the south site on Mar. 26th show instantaneous flow speed at 150 cm/s at 0.5 m above the seabed. This paper reports preliminary highlights of the observations, based on raw data, and lessons learned from a deployment of large tripod systems in such a dynamic location.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"OCEANS 2009, MTS/IEEE Biloxi - Marine Technology for Our Future: Global and Local Challenges","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"OCEANS 2009, MTS/IEEE Biloxi - Marine Technology for Our Future: Global and Local Challenges","conferenceDate":"Biloxi, MS","conferenceLocation":"October 26-29, 2009","language":"English","publisher":"IEEE","doi":"10.23919/OCEANS.2009.5422403","usgsCitation":"Martini, M.A., Armstrong, B., and Warner, J., 2010, High resolution near-bed observations in winter near Cape Hatteras, North Carolina, in OCEANS 2009, MTS/IEEE Biloxi - Marine Technology for Our Future: Global and Local Challenges, October 26-29, 2009, Biloxi, MS, 10 p., https://doi.org/10.23919/OCEANS.2009.5422403.","productDescription":"10 p.","ipdsId":"IP-015260","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":345361,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina","otherGeospatial":"Cape Hatteras","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59a7ced5e4b0fd9b77d092c7","contributors":{"authors":[{"text":"Martini, Marinna A. 0000-0002-7757-5158 mmartini@usgs.gov","orcid":"https://orcid.org/0000-0002-7757-5158","contributorId":2456,"corporation":false,"usgs":true,"family":"Martini","given":"Marinna","email":"mmartini@usgs.gov","middleInitial":"A.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":709075,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Armstrong, Brandy N. barmstrong@usgs.gov","contributorId":5897,"corporation":false,"usgs":true,"family":"Armstrong","given":"Brandy N.","email":"barmstrong@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":709076,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Warner, John C. 0000-0002-3734-8903 jcwarner@usgs.gov","orcid":"https://orcid.org/0000-0002-3734-8903","contributorId":2681,"corporation":false,"usgs":true,"family":"Warner","given":"John C.","email":"jcwarner@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":709077,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70037677,"text":"70037677 - 2010 - Forest responses to increasing aridity and warmth in the southwestern United States","interactions":[],"lastModifiedDate":"2018-01-23T12:30:17","indexId":"70037677","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2982,"text":"PNAS","active":true,"publicationSubtype":{"id":10}},"title":"Forest responses to increasing aridity and warmth in the southwestern United States","docAbstract":"In recent decades, intense droughts, insect outbreaks, and wildfires have led to decreasing tree growth and increasing mortality in many temperate forests. We compared annual tree-ring width data from 1,097 populations in the coterminous United States to climate data and evaluated site-specific tree responses to climate variations throughout the 20th century. For each population, we developed a climate-driven growth equation by using climate records to predict annual ring widths. Forests within the southwestern United States appear particularly sensitive to drought and warmth. We input 21st century climate projections to the equations to predict growth responses. Our results suggest that if temperature and aridity rise as they are projected to, southwestern trees will experience substantially reduced growth during this century. As tree growth declines, mortality rates may increase at many sites. Increases in wildfires and bark-beetle outbreaks in the most recent decade are likely related to extreme drought and high temperatures during this period. Using satellite imagery and aerial survey data, we conservatively calculate that ≈2.7% of southwestern forest and woodland area experienced substantial mortality due to wildfires from 1984 to 2006, and ≈7.6% experienced mortality associated with bark beetles from 1997 to 2008. We estimate that up to ≈18% of southwestern forest area (excluding woodlands) experienced mortality due to bark beetles or wildfire during this period. Expected climatic changes will alter future forest productivity, disturbance regimes, and species ranges throughout the Southwest. Emerging knowledge of these impending transitions informs efforts to adaptively manage southwestern forests.
","language":"English","publisher":"National Academy of Sciences of the United States of America","doi":"10.1073/pnas.0914211107","usgsCitation":"Williams, A., Allen, C.D., Millar, C.I., Swetnam, T., Michaelsen, J., Still, C., and Leavitt, S.W., 2010, Forest responses to increasing aridity and warmth in the southwestern United States: PNAS, v. 107, no. 50, p. 21289-21294, https://doi.org/10.1073/pnas.0914211107.","productDescription":"6 p.","startPage":"21289","endPage":"21294","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":475789,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://europepmc.org/articles/pmc3003095","text":"External Repository"},{"id":246075,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"107","issue":"50","noUsgsAuthors":false,"publicationDate":"2010-12-13","publicationStatus":"PW","scienceBaseUri":"505a1336e4b0c8380cd54577","contributors":{"authors":[{"text":"Williams, A.P.","contributorId":70226,"corporation":false,"usgs":true,"family":"Williams","given":"A.P.","email":"","affiliations":[],"preferred":false,"id":462246,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Allen, Craig D. 0000-0002-8777-5989 craig_allen@usgs.gov","orcid":"https://orcid.org/0000-0002-8777-5989","contributorId":2597,"corporation":false,"usgs":true,"family":"Allen","given":"Craig","email":"craig_allen@usgs.gov","middleInitial":"D.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":462243,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Millar, C. 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We monitored six line-intercept transects, three in previously high ungulate use areas and three in previously low ungulate use areas. We measured nine cover categories with the line-intercept method: native ferns; native woody plants; bryophytes; lichens; alien grasses; alien herbs; litter; exposed soil; and coarse woody debris. Vegetation surveys were repeated four times over a 16-year period. Vegetation monitoring revealed a strong increase in native fern cover and slight decreases in cover of bryophytes and exposed soil. Mean cover of native plants was generally higher in locations that were formerly lightly grazed, while alien grass and herb cover was generally higher in areas that were heavily grazed, although these effects were not statistically significant. These responses may represent early serai processes in forest regeneration following the reduction of feral ungulate populations. In contrast to many other Hawaiian forests which have become invaded by alien grasses and herbs after ungulate removal, HFNWR has not experienced this effect.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Pacific Conservation Biology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","issn":"10382097","usgsCitation":"Hess, S., Jeffrey, J., Pratt, L., and Ball, D., 2010, Effects of ungulate management on vegetation at Hakalau Forest National Wildlife Refuge, Hawai'i Island: Pacific Conservation Biology, v. 16, no. 2, p. 144-150.","startPage":"144","endPage":"150","numberOfPages":"7","costCenters":[],"links":[{"id":246100,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"16","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a081be4b0c8380cd5199a","contributors":{"authors":[{"text":"Hess, S.C. 0000-0001-6403-9922","orcid":"https://orcid.org/0000-0001-6403-9922","contributorId":86081,"corporation":false,"usgs":true,"family":"Hess","given":"S.C.","affiliations":[],"preferred":false,"id":462084,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jeffrey, J.J.","contributorId":46646,"corporation":false,"usgs":true,"family":"Jeffrey","given":"J.J.","email":"","affiliations":[],"preferred":false,"id":462082,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pratt, L.W.","contributorId":68499,"corporation":false,"usgs":true,"family":"Pratt","given":"L.W.","email":"","affiliations":[],"preferred":false,"id":462083,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ball, D.L.","contributorId":31241,"corporation":false,"usgs":true,"family":"Ball","given":"D.L.","email":"","affiliations":[],"preferred":false,"id":462081,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70193761,"text":"70193761 - 2010 - Use of induced polarization to characterize the hydrogeologic framework of the zone of surface‐water/groundwater exchange at the Hanford 300 Area, WA","interactions":[],"lastModifiedDate":"2020-03-10T14:37:11","indexId":"70193761","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Use of induced polarization to characterize the hydrogeologic framework of the zone of surface‐water/groundwater exchange at the Hanford 300 Area, WA","docAbstract":"An extensive continuous waterborne electrical imaging (CWEI) survey was conducted along the Columbia River corridor adjacent to the U.S. Department of Energy (DOE) Hanford 300 Area, WA, in order to improve the conceptual model for exchange between surface water and U‐contaminated groundwater. The primary objective was to determine spatial variability in the depth to the Hanford‐Ringold (H‐R) contact, an important lithologic boundary that limits vertical transport of groundwater along the river corridor. Resistivity and induced polarization (IP) measurements were performed along six survey lines parallel to the shore (each greater than 2.5 km in length), with a measurement recorded every 0.5–3.0 m depending on survey speed, resulting in approximately 65,000 measurements. The H‐R contact was clearly resolved in images of the normalized chargeability along the river corridor due to the large contrast in surface area (hence polarizability) of the granular material between the two lithologic units. Cross sections of the lithologic structure along the river corridor reveal a large variation in the thickness of the overlying Hanford unit (the aquifer through which contaminated groundwater discharges to the river) and clearly identify locations along the river corridor where the underlying Ringold unit is exposed to the riverbed. Knowing the distribution of the Hanford and Ringold units along the river corridor substantially improves the conceptual model for the hydrogeologic framework regulating U exchange between groundwater and Columbia River water relative to current models based on projections of data from boreholes on land into the river.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Symposium on the Application of Geophysics to Engineering and Environmental Problems 2010","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"Society of Exploration Geophysicists","doi":"10.4133/1.3445539","usgsCitation":"Slater, L., Ntarlagiannis, D., Day-Lewis, F.D., Mwakanyamale, K., Lane, J.W., Ward, A., and Versteeg, R.J., 2010, Use of induced polarization to characterize the hydrogeologic framework of the zone of surface‐water/groundwater exchange at the Hanford 300 Area, WA, in Symposium on the Application of Geophysics to Engineering and Environmental Problems 2010, p. 955-960, https://doi.org/10.4133/1.3445539.","productDescription":"6 p.","startPage":"955","endPage":"960","ipdsId":"IP-018653","costCenters":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":350805,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Hanford 300 site","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.28319931030273,\n 46.35699885440808\n ],\n [\n -119.26620483398438,\n 46.35699885440808\n ],\n [\n -119.26620483398438,\n 46.37547772047758\n ],\n [\n -119.28319931030273,\n 46.37547772047758\n ],\n [\n -119.28319931030273,\n 46.35699885440808\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2010-05-17","publicationStatus":"PW","scienceBaseUri":"5a719270e4b0a9a2e9dbde20","contributors":{"authors":[{"text":"Slater, Lee","contributorId":55707,"corporation":false,"usgs":false,"family":"Slater","given":"Lee","affiliations":[{"id":12727,"text":"Rutgers University","active":true,"usgs":false}],"preferred":false,"id":720289,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ntarlagiannis, Dimitrios","contributorId":150729,"corporation":false,"usgs":false,"family":"Ntarlagiannis","given":"Dimitrios","affiliations":[{"id":12727,"text":"Rutgers University","active":true,"usgs":false}],"preferred":false,"id":720288,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Day-Lewis, Frederick D. 0000-0003-3526-886X daylewis@usgs.gov","orcid":"https://orcid.org/0000-0003-3526-886X","contributorId":1672,"corporation":false,"usgs":true,"family":"Day-Lewis","given":"Frederick","email":"daylewis@usgs.gov","middleInitial":"D.","affiliations":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":720285,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mwakanyamale, Kisa","contributorId":75847,"corporation":false,"usgs":true,"family":"Mwakanyamale","given":"Kisa","email":"","affiliations":[],"preferred":false,"id":726190,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lane, John W. 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In previous interpretations of these analyses, data were expressed in weight percent and parts per million, and thus were subject to the effect of the constant-sum phenomenon. In a new approach to the data, this effect was removed by using centered log-ratio transformations to 'open' the mineralogical and geochemical arrays. Multivariate analyses, including principal component and linear discriminant analyses, of the centered log-ratio data reveal the effects of soil-forming processes, including soil parent material, weathering, and soil age, at the continental-scale of the data arrays that were not readily apparent in the more conventionally presented data. Linear discriminant analysis of the data arrays indicates that the majority of the soil samples collected along the transects can be more successfully classified with Level 1 ecological regional-scale classification by the soil geochemistry than soil mineralogy. A primary objective of this study is to discover and describe, in a parsimonious way, geochemical processes that are both independent and inter-dependent and manifested through compositional data including estimates of the elements and corresponding mineralogy. ?? 2010.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Science of the Total Environment","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.1016/j.scitotenv.2010.08.004","issn":"00489697","usgsCitation":"Drew, L., Grunsky, E., Sutphin, D.M., and Woodruff, L.G., 2010, Multivariate analysis of the geochemistry and mineralogy of soils along two continental-scale transects in North America: Science of the Total Environment, v. 409, no. 1, p. 218-227, https://doi.org/10.1016/j.scitotenv.2010.08.004.","startPage":"218","endPage":"227","numberOfPages":"10","costCenters":[],"links":[{"id":217996,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.scitotenv.2010.08.004"},{"id":245971,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"409","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a60b5e4b0c8380cd7163a","contributors":{"authors":[{"text":"Drew, L.J.","contributorId":69157,"corporation":false,"usgs":true,"family":"Drew","given":"L.J.","email":"","affiliations":[],"preferred":false,"id":462167,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grunsky, E.C.","contributorId":91718,"corporation":false,"usgs":true,"family":"Grunsky","given":"E.C.","email":"","affiliations":[],"preferred":false,"id":462168,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sutphin, D. 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These experiments, dubbed StreamLab06, involved 25 researchers and volunteers from academia, government, and the private sector. The research channel was equipped with a sediment-recirculation system and a sediment-flux monitoring system that allowed continuous measurement of sediment flux in the flume and provided a data set by which samplers were evaluated. Selected bedload-measurement technologies were tested under a range of flow and sediment-transport conditions. The experiment was conducted in two phases. The bed material in phase I was well-sorted siliceous sand (0.6-1.8 mm median diameter). A gravel mixture (1-32 mm median diameter) composed the bed material in phase II. Four conventional bedload samplers – a standard Helley-Smith, Elwha, BLH-84, and Toutle River II (TR-2) sampler – were manually deployed as part of both experiment phases. Bedload traps were deployed in study Phase II. Two surrogate bedload samplers – stationarymounted down-looking 600 kHz and 1200 kHz acoustic Doppler current profilers – were deployed in experiment phase II. This paper presents an overview of the experiment including the specific data-collection technologies used and the ambient hydraulic, sediment-transport and environmental conditions measured as part of the experiment. All data collected as part of the StreamLab06 experiments are, or will be available to the research community.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Bedload-surrogate monitoring technologies","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"U.S. Geological Survey","usgsCitation":"Marr, J.D., Gray, J.R., Davis, B.E., Ellis, C., and Johnson, S., 2010, Large-scale laboratory testing of bedload-monitoring technologies: Overview of the StreamLab06 Experiments, chap. of Bedload-surrogate monitoring technologies, p. 266-282.","productDescription":"17 p.","startPage":"266","endPage":"282","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-004286","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":307692,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":307691,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2010/5091/papers/Marr.pdf"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57fe82cce4b0824b2d1487a5","contributors":{"editors":[{"text":"Gray, John R. 0000-0002-8817-3701 jrgray@usgs.gov","orcid":"https://orcid.org/0000-0002-8817-3701","contributorId":1158,"corporation":false,"usgs":true,"family":"Gray","given":"John","email":"jrgray@usgs.gov","middleInitial":"R.","affiliations":[{"id":5058,"text":"Office of the Chief Scientist for Water","active":true,"usgs":true}],"preferred":true,"id":570689,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Laronne, Jonathan B.","contributorId":8778,"corporation":false,"usgs":true,"family":"Laronne","given":"Jonathan","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":570690,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Marr, Jeffrey D. 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G.","affiliations":[{"id":47665,"text":"St. Anthony Falls Laboratory, University of Minnesota, Minneapolis, MN, USA","active":true,"usgs":false}],"preferred":false,"id":570681,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gray, John R. 0000-0002-8817-3701 jrgray@usgs.gov","orcid":"https://orcid.org/0000-0002-8817-3701","contributorId":1158,"corporation":false,"usgs":true,"family":"Gray","given":"John","email":"jrgray@usgs.gov","middleInitial":"R.","affiliations":[{"id":5058,"text":"Office of the Chief Scientist for Water","active":true,"usgs":true}],"preferred":true,"id":570682,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Davis, Broderick E.","contributorId":23394,"corporation":false,"usgs":true,"family":"Davis","given":"Broderick","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":570683,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ellis, Chris","contributorId":147185,"corporation":false,"usgs":false,"family":"Ellis","given":"Chris","email":"","affiliations":[],"preferred":false,"id":570684,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Johnson, Sara","contributorId":147186,"corporation":false,"usgs":false,"family":"Johnson","given":"Sara","email":"","affiliations":[],"preferred":false,"id":570685,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70037657,"text":"70037657 - 2010 - Effects of exploitation on black bear populations at White River National Wildlife Refuge","interactions":[],"lastModifiedDate":"2016-04-13T16:23:57","indexId":"70037657","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Effects of exploitation on black bear populations at White River National Wildlife Refuge","docAbstract":"We live-trapped American black bears (Ursus americanus) and sampled DNA from hair at White River National Wildlife Refuge, Arkansas, USA, to estimate annual population size (N), growth (λ), and density. We estimated N and λ with open population models, based on live-trapping data collected from 1998 through 2006, and robust design models for genotyped hair samples collected from 2004 through 2007. Population growth was weakly negative (i.e., 95% CI included 1.0) for males (0.901, 95% CI = 0.645–1.156) and strongly negative (i.e., 95% CI excluded 1.0) for females (0.846, 95% CI = 0.711–0.981), based on live-trapping data, with N from 1999 to 2006 ranging from 94.1 (95% CI = 70.3–137.1) to 45.2 (95% CI = 27.1–109.3), respectively, for males and from 151.4 (95% CI = 127.6–185.8) to 47.1 (95% CI = 24.4–140.4), respectively, for females. Likewise, mean annual λ based on hair-sampling data was weakly negative for males (0.742, 95% CI = 0.043–1.441) and strongly negative for females (0.782, 95% CI = 0.661–0.903), with abundance estimates from 2004 to 2007 ranging from 29.1 (95% CI = 21.2–65.8) to 11.9 (95% CI = 11.0–26.9), respectively, for males and from 54.4 (95% CI = 44.3–77.1) to 27.4 (95% CI = 24.9–36.6), respectively, for females. We attribute the decline in the number of females in this isolated population to a decrease in survival caused by a past translocation program and by hunting adjacent to the refuge. We suggest that managers restructure the quota-based harvest limits until these growth rates recover.
","language":"English","publisher":"Wildlife Society","doi":"10.2193/2009-529","issn":"0022541X","usgsCitation":"Clark, J.D., Eastridge, R., and Hooker, M., 2010, Effects of exploitation on black bear populations at White River National Wildlife Refuge: Journal of Wildlife Management, v. 74, no. 7, p. 1448-1456, https://doi.org/10.2193/2009-529.","startPage":"1448","endPage":"1456","numberOfPages":"9","costCenters":[],"links":[{"id":245938,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":217965,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.2193/2009-529"}],"country":"United States","state":"Arkansas","otherGeospatial":"White River National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.27716064453125,\n 34.67161743636362\n ],\n [\n -91.25244140624999,\n 34.610605760914666\n ],\n [\n -91.1590576171875,\n 34.55407346090556\n ],\n [\n -91.16455078125,\n 34.511083202999714\n ],\n [\n -91.0382080078125,\n 34.4069096565206\n ],\n [\n -90.99426269531249,\n 34.39104576945997\n ],\n [\n -91.02996826171875,\n 34.15045403191448\n ],\n [\n -91.0272216796875,\n 34.10498222546687\n ],\n [\n -91.065673828125,\n 34.03672867489511\n ],\n [\n -91.0601806640625,\n 34.00258128543371\n ],\n [\n -91.0931396484375,\n 33.970697997361626\n ],\n [\n -91.11785888671875,\n 33.959308210392024\n ],\n [\n -91.1590576171875,\n 33.96386430820156\n ],\n [\n -91.1920166015625,\n 33.99347299511967\n ],\n [\n -91.22222900390625,\n 34.048108084909835\n ],\n [\n -91.19476318359375,\n 34.129994745824746\n ],\n [\n -91.21673583984375,\n 34.14136162745489\n ],\n [\n -91.25518798828125,\n 34.2594865145062\n ],\n [\n -91.23321533203125,\n 34.29579932143427\n ],\n [\n -91.19476318359375,\n 34.288991865037524\n ],\n [\n -91.17279052734375,\n 34.332096438353915\n ],\n [\n -91.18377685546875,\n 34.384246040152206\n ],\n [\n -91.22772216796875,\n 34.40917568058836\n ],\n [\n -91.27716064453125,\n 34.46127728843708\n ],\n [\n -91.33209228515625,\n 34.54502472496434\n ],\n [\n -91.395263671875,\n 34.6015631772409\n ],\n [\n -91.38702392578125,\n 34.66258150231496\n ],\n [\n -91.33209228515625,\n 34.68291096793206\n ],\n [\n -91.27716064453125,\n 34.67161743636362\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"74","issue":"7","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a06e8e4b0c8380cd51490","contributors":{"authors":[{"text":"Clark, J. 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This study uses a variety of methods to identify mixtures and a modified concentration-addition approach to estimate their potential toxicity at 845 stream sites across the United States sampled between 1992 and 2001 for organochlorine pesticides and polychlorinated biphenyls (PCBs) in bed sediment. Principal-component (PC) analysis identified five PCs that account for 77% of the total variance in 14 organochlorine compounds in the original dataset. The five PCs represent: (1) chlordane-related compounds and dieldrin; (2) p,p′-DDT and its degradates; (3) o,p′-DDT and its degradates; (4) the pesticide degradates oxychlordane and heptachlor epoxide; and (5) PCBs. The PC analysis grouped compounds that have similar chemical structure (such as parent compound and degradate), common origin (in the same technical pesticide mixture), and(or) similar relation of concentrations to land use. For example, the highest concentrations of chlordane compounds and dieldrin occurred at urban sites, reflecting past use of parent pesticides for termite control. Two approaches to characterizing mixtures—PC-based mixtures and unique mixtures—were applied to all 299 samples with a detection of two or more organochlorine compounds. PC-based mixtures are defined by the presence (in the sample) of one or more compounds associated with that PC. Unique mixtures are defined as a specific combination of two or more compounds detected in a sample, regardless of how many other compounds were also detected in that sample. The simplest PC-based mixtures (containing compounds from 1 or 2 PCs) commonly occurred in a variety of land use settings. Complex mixtures (containing compounds from 3 or more PCs) were most common in samples from urban and mixed/urban sites, especially in the Northeast, reflecting high concentrations of multiple chlordane, dieldrin, DDT-related compounds, and(or) PCBs. The most commonly occurring unique mixture (p,p′-DDE, p,p′-DDD) occurred in both simple and complex PC-based mixtures, and at both urban and agricultural sites. Mean Probable Effect Concentration Quotients (PEC-Q) values, which estimate the potential toxicity of organochlorine contaminant mixtures, were highest for complex mixtures. Mean PEC-Q values were highest for urban sites in the Northeast, followed by mixed/urban sites in the Northeast and agricultural sites in cotton growing areas. These results demonstrate that the PEC-Q approach can be used in combination with PC-based and unique mixture analyses to relate potential aquatic toxicity of contaminant mixtures to mixture complexity, land use, and other surrogates for contaminant sources.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2009.09.052","usgsCitation":"Phillips, P., Nowell, L.H., Gilliom, R.J., Nakagaki, N., Riva-Murray, K., and VanAlstyne, C., 2010, Composition, distribution, and potential toxicity of organochlorine mixtures in bed sediments of streams: Science of the Total Environment, v. 408, no. 3, p. 594-606, https://doi.org/10.1016/j.scitotenv.2009.09.052.","productDescription":"13 p.","startPage":"594","endPage":"606","ipdsId":"IP-009456","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":345465,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"408","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59afb7a0e4b0e9bde135114b","contributors":{"authors":[{"text":"Phillips, Patrick J. pjphilli@usgs.gov","contributorId":856,"corporation":false,"usgs":true,"family":"Phillips","given":"Patrick J.","email":"pjphilli@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":false,"id":709537,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nowell, Lisa H. 0000-0001-5417-7264 lhnowell@usgs.gov","orcid":"https://orcid.org/0000-0001-5417-7264","contributorId":490,"corporation":false,"usgs":true,"family":"Nowell","given":"Lisa","email":"lhnowell@usgs.gov","middleInitial":"H.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":709538,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gilliom, Robert J. rgilliom@usgs.gov","contributorId":488,"corporation":false,"usgs":true,"family":"Gilliom","given":"Robert","email":"rgilliom@usgs.gov","middleInitial":"J.","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":709539,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nakagaki, Naomi 0000-0003-3653-0540 nakagaki@usgs.gov","orcid":"https://orcid.org/0000-0003-3653-0540","contributorId":1067,"corporation":false,"usgs":true,"family":"Nakagaki","given":"Naomi","email":"nakagaki@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":709540,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Riva-Murray, Karen 0000-0001-6683-2238 krmurray@usgs.gov","orcid":"https://orcid.org/0000-0001-6683-2238","contributorId":168876,"corporation":false,"usgs":true,"family":"Riva-Murray","given":"Karen","email":"krmurray@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":709541,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"VanAlstyne, Carolyn","contributorId":196180,"corporation":false,"usgs":false,"family":"VanAlstyne","given":"Carolyn","email":"","affiliations":[],"preferred":false,"id":709542,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70037507,"text":"70037507 - 2010 - Seismic imaging of a fractured gas hydrate system in the Krishna-Godavari Basin offshore India","interactions":[],"lastModifiedDate":"2012-03-12T17:22:05","indexId":"70037507","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2682,"text":"Marine and Petroleum Geology","active":true,"publicationSubtype":{"id":10}},"title":"Seismic imaging of a fractured gas hydrate system in the Krishna-Godavari Basin offshore India","docAbstract":"Gas hydrate was discovered in the Krishna-Godavari (KG) Basin during the India National Gas Hydrate Program (NGHP) Expedition 1 at Site NGHP-01-10 within a fractured clay-dominated sedimentary system. Logging-while-drilling (LWD), coring, and wire-line logging confirmed gas hydrate dominantly in fractures at four borehole sites spanning a 500m transect. Three-dimensional (3D) seismic data were subsequently used to image the fractured system and explain the occurrence of gas hydrate associated with the fractures. A system of two fault-sets was identified, part of a typical passive margin tectonic setting. The LWD-derived fracture network at Hole NGHP-01-10A is to some extent seen in the seismic data and was mapped using seismic coherency attributes. The fractured system around Site NGHP-01-10 extends over a triangular-shaped area of ~2.5 km2 defined using seismic attributes of the seafloor reflection, as well as \" seismic sweetness\" at the base of the gas hydrate occurrence zone. The triangular shaped area is also showing a polygonal (nearly hexagonal) fault pattern, distinct from other more rectangular fault patterns observed in the study area. The occurrence of gas hydrate at Site NGHP-01-10 is the result of a specific combination of tectonic fault orientations and the abundance of free gas migration from a deeper gas source. The triangular-shaped area of enriched gas hydrate occurrence is bound by two faults acting as migration conduits. Additionally, the fault-associated sediment deformation provides a possible migration pathway for the free gas from the deeper gas source into the gas hydrate stability zone. It is proposed that there are additional locations in the KG Basin with possible gas hydrate accumulation of similar tectonic conditions, and one such location was identified from the 3D seismic data ~6 km NW of Site NGHP-01-10. ?? 2010.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Marine and Petroleum Geology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.1016/j.marpetgeo.2010.06.002","issn":"02648172","usgsCitation":"Riedel, M., Collett, T.S., Kumar, P., Sathe, A., and Cook, A., 2010, Seismic imaging of a fractured gas hydrate system in the Krishna-Godavari Basin offshore India: Marine and Petroleum Geology, v. 27, no. 7, p. 1476-1493, https://doi.org/10.1016/j.marpetgeo.2010.06.002.","startPage":"1476","endPage":"1493","numberOfPages":"18","costCenters":[],"links":[{"id":218058,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.marpetgeo.2010.06.002"},{"id":246038,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"27","issue":"7","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505b8b24e4b08c986b317610","contributors":{"authors":[{"text":"Riedel, M.","contributorId":65268,"corporation":false,"usgs":true,"family":"Riedel","given":"M.","email":"","affiliations":[],"preferred":false,"id":461372,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Collett, T. S. 0000-0002-7598-4708","orcid":"https://orcid.org/0000-0002-7598-4708","contributorId":86342,"corporation":false,"usgs":true,"family":"Collett","given":"T.","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":461373,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kumar, P.","contributorId":45476,"corporation":false,"usgs":true,"family":"Kumar","given":"P.","affiliations":[],"preferred":false,"id":461371,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sathe, A.V.","contributorId":11454,"corporation":false,"usgs":true,"family":"Sathe","given":"A.V.","email":"","affiliations":[],"preferred":false,"id":461370,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cook, A.","contributorId":88174,"corporation":false,"usgs":true,"family":"Cook","given":"A.","affiliations":[],"preferred":false,"id":461374,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70037571,"text":"70037571 - 2010 - Probabilistic seismic hazard estimates incorporating site effects - An example from Indiana, U.S.A","interactions":[],"lastModifiedDate":"2012-03-12T17:22:06","indexId":"70037571","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1574,"text":"Environmental & Engineering Geoscience","printIssn":"1078-7275","active":true,"publicationSubtype":{"id":10}},"title":"Probabilistic seismic hazard estimates incorporating site effects - An example from Indiana, U.S.A","docAbstract":"The U.S. Geological Survey (USGS) has published probabilistic earthquake hazard maps for the United States based on current knowledge of past earthquake activity and geological constraints on earthquake potential. These maps for the central and eastern United States assume standard site conditions with Swave velocities of 760 m/s in the top 30 m. For urban and infrastructure planning and long-term budgeting, the public is interested in similar probabilistic seismic hazard maps that take into account near-surface geological materials. We have implemented a probabilistic method for incorporating site effects into the USGS seismic hazard analysis that takes into account the first-order effects of the surface geologic conditions. The thicknesses of sediments, which play a large role in amplification, were derived from a P-wave refraction database with over 13, 000 profiles, and a preliminary geology-based velocity model was constructed from available information on S-wave velocities. An interesting feature of the preliminary hazard maps incorporating site effects is the approximate factor of two increases in the 1-Hz spectral acceleration with 2 percent probability of exceedance in 50 years for parts of the greater Indianapolis metropolitan region and surrounding parts of central Indiana. This effect is primarily due to the relatively thick sequence of sediments infilling ancient bedrock topography that has been deposited since the Pleistocene Epoch. As expected, the Late Pleistocene and Holocene depositional systems of the Wabash and Ohio Rivers produce additional amplification in the southwestern part of Indiana. Ground motions decrease, as would be expected, toward the bedrock units in south-central Indiana, where motions are significantly lower than the values on the USGS maps.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Environmental and Engineering Geoscience","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.2113/gseegeosci.16.4.369","issn":"10787275","usgsCitation":"Hasse, J., Park, C., Nowack, R., and Hill, J., 2010, Probabilistic seismic hazard estimates incorporating site effects - An example from Indiana, U.S.A: Environmental & Engineering Geoscience, v. 16, no. 4, p. 369-388, https://doi.org/10.2113/gseegeosci.16.4.369.","startPage":"369","endPage":"388","numberOfPages":"20","costCenters":[],"links":[{"id":218033,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.2113/gseegeosci.16.4.369"},{"id":246010,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"16","issue":"4","noUsgsAuthors":false,"publicationDate":"2010-10-26","publicationStatus":"PW","scienceBaseUri":"505a8c9ce4b0c8380cd7e7b3","contributors":{"authors":[{"text":"Hasse, J.S.","contributorId":77779,"corporation":false,"usgs":true,"family":"Hasse","given":"J.S.","affiliations":[],"preferred":false,"id":461670,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Park, C.H.","contributorId":24606,"corporation":false,"usgs":true,"family":"Park","given":"C.H.","email":"","affiliations":[],"preferred":false,"id":461668,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nowack, R.L.","contributorId":78594,"corporation":false,"usgs":true,"family":"Nowack","given":"R.L.","affiliations":[],"preferred":false,"id":461671,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hill, J.R.","contributorId":40834,"corporation":false,"usgs":true,"family":"Hill","given":"J.R.","email":"","affiliations":[],"preferred":false,"id":461669,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70037722,"text":"70037722 - 2010 - Land use and small mammal predation effects on shortgrass prairie birds","interactions":[],"lastModifiedDate":"2012-04-30T16:43:35","indexId":"70037722","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Land use and small mammal predation effects on shortgrass prairie birds","docAbstract":"Grassland birds endemic to the central shortgrass prairie ecoregion of the United States have experienced steep and widespread declines over the last 3 decades, and factors influencing reproductive success have been implicated. Nest predation is the major cause of nest failure in passerines, and nesting success for some shortgrass prairie birds is exceptionally low. The 3 primary land uses in the central shortgrass prairie ecoregion are native shortgrass prairie rangeland (62), irrigated and nonirrigated cropland (29), and Conservation Reserve Program (CRP, 8). Because shortgrasscropland edges and CRP may alter the community of small mammal predators of grassland bird nests, I sampled multiple sites on and near the Pawnee National Grasslands in northeast Colorado, USA, to evaluate 1) whether small mammal species richness and densities were greater in CRP fields and shortgrass prairiecropland edges compared to shortgrass prairie habitats, and 2) whether daily survival probabilities of ground-nesting grassland bird nests were negatively correlated with densities of small mammals. Small mammal species richness and densities, estimated using trapping webs, were generally greater along edges and on CRP sites compared to shortgrass sites. Vegetation did not differ among edges and shortgrass sites but did differ among CRP and shortgrass sites. Daily survival probabilities of artificial nests at edge and CRP sites and natural nests at edge sites did not differ from shortgrass sites, and for natural nests small mammal densities did not affect nest survival. However, estimated daily survival probability of artificial nests was inversely proportional to thirteen-lined ground squirrel (Spermophilus tridecemlineatus) densities. In conclusion, these data suggest that although land-use patterns on the shortgrass prairie area in my study have substantial effects on the small mammal community, insufficient data existed to determine whether land-use patterns or small mammal density were affecting grassland bird nest survival. These findings will be useful to managers for predicting the effects of land-use changes in the shortgrass prairie on small mammal communities and avian nest success. ?? 2010 The Wildlife Society.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Wildlife Management","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.2193/2009-396","issn":"0022541X","usgsCitation":"Stanley, T., 2010, Land use and small mammal predation effects on shortgrass prairie birds: Journal of Wildlife Management, v. 74, no. 8, p. 1825-1833, https://doi.org/10.2193/2009-396.","startPage":"1825","endPage":"1833","numberOfPages":"9","costCenters":[],"links":[{"id":217969,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.2193/2009-396"},{"id":245942,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"74","issue":"8","noUsgsAuthors":false,"publicationDate":"2010-12-13","publicationStatus":"PW","scienceBaseUri":"505a4382e4b0c8380cd663c0","contributors":{"authors":[{"text":"Stanley, T.R.","contributorId":61379,"corporation":false,"usgs":true,"family":"Stanley","given":"T.R.","affiliations":[],"preferred":false,"id":462493,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70037694,"text":"70037694 - 2010 - Locating non-volcanic tremor along the San Andreas Fault using a multiple array source imaging technique","interactions":[],"lastModifiedDate":"2012-04-30T16:43:34","indexId":"70037694","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1803,"text":"Geophysical Journal International","active":true,"publicationSubtype":{"id":10}},"title":"Locating non-volcanic tremor along the San Andreas Fault using a multiple array source imaging technique","docAbstract":"Non-volcanic tremor (NVT) has been observed at several subduction zones and at the San Andreas Fault (SAF). Tremor locations are commonly derived by cross-correlating envelope-transformed seismic traces in combination with source-scanning techniques. Recently, they have also been located by using relative relocations with master events, that is low-frequency earthquakes that are part of the tremor; locations are derived by conventional traveltime-based methods. Here we present a method to locate the sources of NVT using an imaging approach for multiple array data. The performance of the method is checked with synthetic tests and the relocation of earthquakes. We also applied the method to tremor occurring near Cholame, California. A set of small-aperture arrays (i.e. an array consisting of arrays) installed around Cholame provided the data set for this study. We observed several tremor episodes and located tremor sources in the vicinity of SAF. During individual tremor episodes, we observed a systematic change of source location, indicating rapid migration of the tremor source along SAF. ?? 2010 The Authors Geophysical Journal International ?? 2010 RAS.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Geophysical Journal International","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.1111/j.1365-246X.2010.04805.x","issn":"0956540X","usgsCitation":"Ryberg, T., Haberland, C., Fuis, G., Ellsworth, W., and Shelly, D., 2010, Locating non-volcanic tremor along the San Andreas Fault using a multiple array source imaging technique: Geophysical Journal International, v. 183, no. 3, p. 1485-1500, https://doi.org/10.1111/j.1365-246X.2010.04805.x.","startPage":"1485","endPage":"1500","numberOfPages":"16","costCenters":[],"links":[{"id":475851,"rank":10000,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/j.1365-246x.2010.04805.x","text":"Publisher Index Page"},{"id":218012,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/j.1365-246X.2010.04805.x"},{"id":245988,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"183","issue":"3","noUsgsAuthors":false,"publicationDate":"2010-10-14","publicationStatus":"PW","scienceBaseUri":"505a48ffe4b0c8380cd682b3","contributors":{"authors":[{"text":"Ryberg, T.","contributorId":91643,"corporation":false,"usgs":true,"family":"Ryberg","given":"T.","email":"","affiliations":[],"preferred":false,"id":462335,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haberland, C.H.","contributorId":53636,"corporation":false,"usgs":true,"family":"Haberland","given":"C.H.","email":"","affiliations":[],"preferred":false,"id":462333,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fuis, G. S.","contributorId":83131,"corporation":false,"usgs":true,"family":"Fuis","given":"G. S.","affiliations":[],"preferred":false,"id":462334,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ellsworth, W.L.","contributorId":48541,"corporation":false,"usgs":true,"family":"Ellsworth","given":"W.L.","email":"","affiliations":[],"preferred":false,"id":462331,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Shelly, D.R.","contributorId":53179,"corporation":false,"usgs":true,"family":"Shelly","given":"D.R.","email":"","affiliations":[],"preferred":false,"id":462332,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70037583,"text":"70037583 - 2010 - Predicting species distributions from checklist data using site-occupancy models","interactions":[],"lastModifiedDate":"2012-03-12T17:22:00","indexId":"70037583","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2193,"text":"Journal of Biogeography","active":true,"publicationSubtype":{"id":10}},"title":"Predicting species distributions from checklist data using site-occupancy models","docAbstract":"Aim: (1) To increase awareness of the challenges induced by imperfect detection, which is a fundamental issue in species distribution modelling; (2) to emphasize the value of replicate observations for species distribution modelling; and (3) to show how 'cheap' checklist data in faunal/floral databases may be used for the rigorous modelling of distributions by site-occupancy models. Location: Switzerland. Methods: We used checklist data collected by volunteers during 1999 and 2000 to analyse the distribution of the blue hawker, Aeshna cyanea (Odonata, Aeshnidae), a common dragonfly in Switzerland. We used data from repeated visits to 1-ha pixels to derive 'detection histories' and apply site-occupancy models to estimate the 'true' species distribution, i.e. corrected for imperfect detection. We modelled blue hawker distribution as a function of elevation and year and its detection probability of elevation, year and season. Results: The best model contained cubic polynomial elevation effects for distribution and quadratic effects of elevation and season for detectability. We compared the site-occupancy model with a conventional distribution model based on a generalized linear model, which assumes perfect detectability (p = 1). The conventional distribution map looked very different from the distribution map obtained using site-occupancy models that accounted for the imperfect detection. The conventional model underestimated the species distribution by 60%, and the slope parameters of the occurrence-elevation relationship were also underestimated when assuming p = 1. Elevation was not only an important predictor of blue hawker occurrence, but also of the detection probability, with a bell-shaped relationship. Furthermore, detectability increased over the season. The average detection probability was estimated at only 0.19 per survey. Main conclusions: Conventional species distribution models do not model species distributions per se but rather the apparent distribution, i.e. an unknown proportion of species distributions. That unknown proportion is equivalent to detectability. Imperfect detection in conventional species distribution models yields underestimates of the extent of distributions and covariate effects that are biased towards zero. In addition, patterns in detectability will erroneously be ascribed to species distributions. In contrast, site-occupancy models applied to replicated detection/non-detection data offer a powerful framework for making inferences about species distributions corrected for imperfect detection. The use of 'cheap' checklist data greatly enhances the scope of applications of this useful class of models. ?? 2010 Blackwell Publishing Ltd.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Biogeography","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.1111/j.1365-2699.2010.02345.x","issn":"03050270","usgsCitation":"Kery, M., Gardner, B., and Monnerat, C., 2010, Predicting species distributions from checklist data using site-occupancy models: Journal of Biogeography, v. 37, no. 10, p. 1851-1862, https://doi.org/10.1111/j.1365-2699.2010.02345.x.","startPage":"1851","endPage":"1862","numberOfPages":"12","costCenters":[],"links":[{"id":475807,"rank":10000,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/j.1365-2699.2010.02345.x","text":"Publisher Index Page"},{"id":245878,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":217905,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/j.1365-2699.2010.02345.x"}],"volume":"37","issue":"10","noUsgsAuthors":false,"publicationDate":"2010-06-22","publicationStatus":"PW","scienceBaseUri":"505a81cae4b0c8380cd7b723","contributors":{"authors":[{"text":"Kery, M.","contributorId":46637,"corporation":false,"usgs":true,"family":"Kery","given":"M.","affiliations":[],"preferred":false,"id":461751,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gardner, B.","contributorId":26793,"corporation":false,"usgs":true,"family":"Gardner","given":"B.","email":"","affiliations":[],"preferred":false,"id":461750,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Monnerat, C.","contributorId":66945,"corporation":false,"usgs":true,"family":"Monnerat","given":"C.","email":"","affiliations":[],"preferred":false,"id":461752,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70037592,"text":"70037592 - 2010 - Comparison of watershed disturbance predictive models for stream benthic macroinvertebrates for three distinct ecoregions in western US","interactions":[],"lastModifiedDate":"2018-06-01T14:11:44","indexId":"70037592","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Comparison of watershed disturbance predictive models for stream benthic macroinvertebrates for three distinct ecoregions in western US","docAbstract":"The successful use of macroinvertebrates as indicators of stream condition in bioassessments has led to heightened interest throughout the scientific community in the prediction of stream condition. For example, predictive models are increasingly being developed that use measures of watershed disturbance, including urban and agricultural land-use, as explanatory variables to predict various metrics of biological condition such as richness, tolerance, percent predators, index of biotic integrity, functional species traits, or even ordination axes scores. Our primary intent was to determine if effective models could be developed using watershed characteristics of disturbance to predict macroinvertebrate metrics among disparate and widely separated ecoregions. We aggregated macroinvertebrate data from universities and state and federal agencies in order to assemble stream data sets of high enough density appropriate for modeling in three distinct ecoregions in Oregon and California. Extensive review and quality assurance of macroinvertebrate sampling protocols, laboratory subsample counts and taxonomic resolution was completed to assure data comparability. We used widely available digital coverages of land-use and land-cover data summarized at the watershed and riparian scale as explanatory variables to predict macroinvertebrate metrics commonly used by state resource managers to assess stream condition. The “best” multiple linear regression models from each region required only two or three explanatory variables to model macroinvertebrate metrics and explained 41–74% of the variation. In each region the best model contained some measure of urban and/or agricultural land-use, yet often the model was improved by including a natural explanatory variable such as mean annual precipitation or mean watershed slope. Two macroinvertebrate metrics were common among all three regions, the metric that summarizes the richness of tolerant macroinvertebrates (RICHTOL) and some form of EPT (Ephemeroptera, Plecoptera, and Trichoptera) richness. Best models were developed for the same two invertebrate metrics even though the geographic regions reflect distinct differences in precipitation, geology, elevation, slope, population density, and land-use. With further development, models like these can be used to elicit better causal linkages to stream biological attributes or condition and can be used by researchers or managers to predict biological indicators of stream condition at unsampled sites.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2010.03.011","issn":"1470160X","usgsCitation":"Waite, I.R., Brown, L.R., Kennen, J., May, J.T., Cuffney, T.F., Orlando, J.L., and Jones, K.A., 2010, Comparison of watershed disturbance predictive models for stream benthic macroinvertebrates for three distinct ecoregions in western US: Ecological Indicators, v. 10, no. 6, p. 1125-1136, https://doi.org/10.1016/j.ecolind.2010.03.011.","productDescription":"12 p.","startPage":"1125","endPage":"1136","numberOfPages":"12","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":245935,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":217962,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.ecolind.2010.03.011"}],"volume":"10","issue":"6","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059f8bde4b0c8380cd4d277","contributors":{"authors":[{"text":"Waite, Ian R. 0000-0003-1681-6955 iwaite@usgs.gov","orcid":"https://orcid.org/0000-0003-1681-6955","contributorId":616,"corporation":false,"usgs":true,"family":"Waite","given":"Ian","email":"iwaite@usgs.gov","middleInitial":"R.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":461789,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brown, Larry R. 0000-0001-6702-4531 lrbrown@usgs.gov","orcid":"https://orcid.org/0000-0001-6702-4531","contributorId":1717,"corporation":false,"usgs":true,"family":"Brown","given":"Larry","email":"lrbrown@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":461790,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kennen, Jonathan G. 0000-0002-5426-4445 jgkennen@usgs.gov","orcid":"https://orcid.org/0000-0002-5426-4445","contributorId":574,"corporation":false,"usgs":true,"family":"Kennen","given":"Jonathan G.","email":"jgkennen@usgs.gov","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":461787,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"May, Jason T. 0000-0002-5699-2112 jasonmay@usgs.gov","orcid":"https://orcid.org/0000-0002-5699-2112","contributorId":617,"corporation":false,"usgs":true,"family":"May","given":"Jason","email":"jasonmay@usgs.gov","middleInitial":"T.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":461791,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cuffney, Thomas F. 0000-0003-1164-5560 tcuffney@usgs.gov","orcid":"https://orcid.org/0000-0003-1164-5560","contributorId":517,"corporation":false,"usgs":true,"family":"Cuffney","given":"Thomas","email":"tcuffney@usgs.gov","middleInitial":"F.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":461792,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Orlando, James L. 0000-0002-0099-7221 jorlando@usgs.gov","orcid":"https://orcid.org/0000-0002-0099-7221","contributorId":1368,"corporation":false,"usgs":true,"family":"Orlando","given":"James","email":"jorlando@usgs.gov","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":461786,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jones, Kimberly A. kjones@usgs.gov","contributorId":937,"corporation":false,"usgs":true,"family":"Jones","given":"Kimberly","email":"kjones@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":461788,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70037550,"text":"70037550 - 2010 - Laboratory-based maximum slip rates in earthquake rupture zones and radiated energy","interactions":[],"lastModifiedDate":"2012-03-12T17:22:06","indexId":"70037550","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","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":"Laboratory-based maximum slip rates in earthquake rupture zones and radiated energy","docAbstract":"Laboratory stick-slip friction experiments indicate that peak slip rates increase with the stresses loading the fault to cause rupture. If this applies also to earthquake fault zones, then the analysis of rupture processes is simplified inasmuch as the slip rates depend only on the local yield stress and are independent of factors specific to a particular event, including the distribution of slip in space and time. We test this hypothesis by first using it to develop an expression for radiated energy that depends primarily on the seismic moment and the maximum slip rate. From laboratory results, the maximum slip rate for any crustal earthquake, as well as various stress parameters including the yield stress, can be determined based on its seismic moment and the maximum slip within its rupture zone. After finding that our new equation for radiated energy works well for laboratory stick-slip friction experiments, we used it to estimate radiated energies for five earthquakes with magnitudes near 2 that were induced in a deep gold mine, an M 2.1 repeating earthquake near the San Andreas Fault Observatory at Depth (SAFOD) site and seven major earthquakes in California and found good agreement with energies estimated independently from spectra of local and regional ground-motion data. Estimates of yield stress for the earthquakes in our study range from 12 MPa to 122 MPa with a median of 64 MPa. The lowest value was estimated for the 2004 M 6 Parkfield, California, earthquake whereas the nearby M 2.1 repeating earthquake, as recorded in the SAFOD pilot hole, showed a more typical yield stress of 64 MPa.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Bulletin of the Seismological Society of America","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.1785/0120100043","issn":"00371106","usgsCitation":"McGarr, A., Fletcher, J.B., Boettcher, M., Beeler, N., and Boatwright, J., 2010, Laboratory-based maximum slip rates in earthquake rupture zones and radiated energy: Bulletin of the Seismological Society of America, v. 100, no. 6, p. 3250-3260, https://doi.org/10.1785/0120100043.","startPage":"3250","endPage":"3260","numberOfPages":"11","costCenters":[],"links":[{"id":246108,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":218124,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1785/0120100043"}],"volume":"100","issue":"6","noUsgsAuthors":false,"publicationDate":"2010-12-06","publicationStatus":"PW","scienceBaseUri":"505a4123e4b0c8380cd65319","contributors":{"authors":[{"text":"McGarr, Art 0000-0001-9769-4093","orcid":"https://orcid.org/0000-0001-9769-4093","contributorId":43491,"corporation":false,"usgs":true,"family":"McGarr","given":"Art","affiliations":[],"preferred":false,"id":461561,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fletcher, Joe B.","contributorId":8850,"corporation":false,"usgs":true,"family":"Fletcher","given":"Joe","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":461559,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Boettcher, M.","contributorId":28828,"corporation":false,"usgs":true,"family":"Boettcher","given":"M.","email":"","affiliations":[],"preferred":false,"id":461560,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Beeler, N.","contributorId":69753,"corporation":false,"usgs":true,"family":"Beeler","given":"N.","email":"","affiliations":[],"preferred":false,"id":461562,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Boatwright, J.","contributorId":87297,"corporation":false,"usgs":true,"family":"Boatwright","given":"J.","email":"","affiliations":[],"preferred":false,"id":461563,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70037637,"text":"70037637 - 2010 - A simple physical model for deep moonquake occurrence times","interactions":[],"lastModifiedDate":"2012-03-12T17:22:06","indexId":"70037637","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3071,"text":"Physics of the Earth and Planetary Interiors","active":true,"publicationSubtype":{"id":10}},"title":"A simple physical model for deep moonquake occurrence times","docAbstract":"The physical process that results in moonquakes is not yet fully understood. The periodic occurrence times of events from individual clusters are clearly related to tidal stress, but also exhibit departures from the temporal regularity this relationship would seem to imply. Even simplified models that capture some of the relevant physics require a large number of variables. However, a single, easily accessible variable - the time interval I(n) between events - can be used to reveal behavior not readily observed using typical periodicity analyses (e.g., Fourier analyses). The delay-coordinate (DC) map, a particularly revealing way to display data from a time series, is a map of successive intervals: I(n+. 1) plotted vs. I(n). We use a DC approach to characterize the dynamics of moonquake occurrence. Moonquake-like DC maps can be reproduced by combining sequences of synthetic events that occur with variable probability at tidal periods. Though this model gives a good description of what happens, it has little physical content, thus providing only little insight into why moonquakes occur. We investigate a more mechanistic model. In this study, we present a series of simple models of deep moonquake occurrence, with consideration of both tidal stress and stress drop during events. We first examine the behavior of inter-event times in a delay-coordinate context, and then examine the output, in that context, of a sequence of simple models of tidal forcing and stress relief. We find, as might be expected, that the stress relieved by moonquakes influences their occurrence times. Our models may also provide an explanation for the opposite-polarity events observed at some clusters. ?? 2010.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Physics of the Earth and Planetary Interiors","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.1016/j.pepi.2010.07.009","issn":"00319201","usgsCitation":"Weber, R., Bills, B., and Johnson, C., 2010, A simple physical model for deep moonquake occurrence times: Physics of the Earth and Planetary Interiors, v. 182, no. 3-4, p. 152-160, https://doi.org/10.1016/j.pepi.2010.07.009.","startPage":"152","endPage":"160","numberOfPages":"9","costCenters":[],"links":[{"id":246045,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":218065,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.pepi.2010.07.009"}],"volume":"182","issue":"3-4","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059e591e4b0c8380cd46e28","contributors":{"authors":[{"text":"Weber, R.C.","contributorId":103111,"corporation":false,"usgs":true,"family":"Weber","given":"R.C.","affiliations":[],"preferred":false,"id":462030,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bills, B.G.","contributorId":107867,"corporation":false,"usgs":true,"family":"Bills","given":"B.G.","email":"","affiliations":[],"preferred":false,"id":462031,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, C.L.","contributorId":98546,"corporation":false,"usgs":true,"family":"Johnson","given":"C.L.","email":"","affiliations":[],"preferred":false,"id":462029,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70037687,"text":"70037687 - 2010 - Determining the effects of dams on subdaily variation in river flows at a whole-basin scale","interactions":[],"lastModifiedDate":"2012-04-30T16:43:35","indexId":"70037687","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3301,"text":"River Research and Applications","active":true,"publicationSubtype":{"id":10}},"title":"Determining the effects of dams on subdaily variation in river flows at a whole-basin scale","docAbstract":"River regulation can alter the frequency and magnitude of subdaily flow variations causing major impacts on ecological structure and function. We developed an approach to quantify subdaily flow variation for multiple sites across a large watershed to assess the potential impacts of different dam operations (flood control, run-of-river hydropower and peaking hydropower) on natural communities. We used hourly flow data over a 9-year period from 30 stream gages throughout the Connecticut River basin to calculate four metrics of subdaily flow variation and to compare sites downstream of dams with unregulated sites. Our objectives were to (1) determine the temporal scale of data needed to characterize subdaily variability; (2) compare the frequency of days with high subdaily flow variation downstream of dams and unregulated sites; (3) analyse the magnitude of subdaily variation at all sites and (4) identify individual sites that had subdaily variation significantly higher than unregulated locations. We found that estimates of flow variability based on daily mean flow data were not sufficient to characterize subdaily flow patterns. Alteration of subdaily flows was evident in the number of days natural ranges of variability were exceeded, rather than in the magnitude of subdaily variation, suggesting that all rivers may exhibit highly variable subdaily flows, but altered rivers exhibit this variability more frequently. Peaking hydropower facilities had the most highly altered subdaily flows; however, we observed significantly altered ranges of subdaily variability downstream of some flood-control and run-of-river hydropower dams. Our analysis can be used to identify situations where dam operating procedures could be modified to reduce the level of hydrologic alteration. ?? 2009 John Wiley & Sons, Ltd.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"River Research and Applications","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.1002/rra.1324","issn":"15351459","usgsCitation":"Zimmerman, J.K., Letcher, B., Nislow, K., Lutz, K., and Magilligan, F., 2010, Determining the effects of dams on subdaily variation in river flows at a whole-basin scale: River Research and Applications, v. 26, no. 10, p. 1246-1260, https://doi.org/10.1002/rra.1324.","startPage":"1246","endPage":"1260","numberOfPages":"15","costCenters":[],"links":[{"id":217966,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/rra.1324"},{"id":245939,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"26","issue":"10","noUsgsAuthors":false,"publicationDate":"2010-11-24","publicationStatus":"PW","scienceBaseUri":"5059fff6e4b0c8380cd4f4d3","contributors":{"authors":[{"text":"Zimmerman, J. K. H.","contributorId":105898,"corporation":false,"usgs":false,"family":"Zimmerman","given":"J.","email":"","middleInitial":"K. H.","affiliations":[],"preferred":false,"id":462296,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Letcher, B. H. 0000-0003-0191-5678","orcid":"https://orcid.org/0000-0003-0191-5678","contributorId":48132,"corporation":false,"usgs":true,"family":"Letcher","given":"B.","middleInitial":"H.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":462294,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nislow, K.H.","contributorId":66477,"corporation":false,"usgs":true,"family":"Nislow","given":"K.H.","affiliations":[],"preferred":false,"id":462295,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lutz, K.A.","contributorId":42069,"corporation":false,"usgs":true,"family":"Lutz","given":"K.A.","email":"","affiliations":[],"preferred":false,"id":462293,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Magilligan, F.J.","contributorId":12298,"corporation":false,"usgs":true,"family":"Magilligan","given":"F.J.","affiliations":[],"preferred":false,"id":462292,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70037635,"text":"70037635 - 2010 - Determining sources of dissolved organic carbon and disinfection byproduct precursors to the McKenzie River, Oregon","interactions":[],"lastModifiedDate":"2018-01-23T11:45:13","indexId":"70037635","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2262,"text":"Journal of Environmental Quality","active":true,"publicationSubtype":{"id":10}},"title":"Determining sources of dissolved organic carbon and disinfection byproduct precursors to the McKenzie River, Oregon","docAbstract":"This study was conducted to determine the main sources of dissolved organic carbon (DOC) and disinfection byproduct (DBP) precursors to the McKenzie River, Oregon (USA). Water samples collected from the mainstem, tributaries, and reservoir outflows were analyzed for DOC concentration and DBP formation potentials (trihalomethanes [THMFPs] and haloacetic acids [HAAFPs]). In addition, optical properties (absorbance and fluorescence) of dissolved organic matter (DOM) were measured to provide insight into DOM composition and assess whether optical properties are useful proxies for DOC and DBP precursor concentrations. Optical properties indicative of composition suggest that DOM in the McKenzie River mainstem was primarily allochthonous - derived from soils and plant material in the upstream watershed. Downstream tributaries had higher DOC concentrations than mainstem sites (1.6 ?? 0.4 vs. 0.7 ?? 0.3 mg L-1) but comprised <5% of mainstem flows and had minimal effect on overall DBP precursor loads. Water exiting two large upstream reservoirs also had higher DOC concentrations than the mainstem site upstream of the reservoirs, but optical data did not support in situ algal production as a source of the added DOC during the study. Results suggest that the first major rain event in the fall contributes DOM with high DBP precursor content. Although there was interference in the absorbance spectra in downstream tributary samples, fluorescence data were strongly correlated to DOC concentration (R 2 = 0.98), THMFP (R2 = 0.98), and HAAFP (R2 = 0.96). These results highlight the value of using optical measurements for identifying the concentration and sources of DBP precursors in watersheds, which will help drinking water utilities improve source water monitoring and management programs. Copyright ?? 2010 by the American Society of Agronomy.","language":"English","publisher":"ACSESS","doi":"10.2134/jeq2010.0030","issn":"00472425","usgsCitation":"Kraus, T.E., Anderson, C., Morgenstern, K., Downing, B.D., Pellerin, B.A., and Bergamaschi, B., 2010, Determining sources of dissolved organic carbon and disinfection byproduct precursors to the McKenzie River, Oregon: Journal of Environmental Quality, v. 39, no. 6, p. 2100-2112, https://doi.org/10.2134/jeq2010.0030.","productDescription":"13 p.","startPage":"2100","endPage":"2112","numberOfPages":"13","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":246030,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":218050,"rank":2,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.2134/jeq2010.0030"}],"volume":"39","issue":"6","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059fff4e4b0c8380cd4f4ca","contributors":{"authors":[{"text":"Kraus, Tamara E.C. 0000-0002-5187-8644 tkraus@usgs.gov","orcid":"https://orcid.org/0000-0002-5187-8644","contributorId":1452,"corporation":false,"usgs":true,"family":"Kraus","given":"Tamara","email":"tkraus@usgs.gov","middleInitial":"E.C.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":462020,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, Chauncey W. 0000-0002-1016-3781 chauncey@usgs.gov","orcid":"https://orcid.org/0000-0002-1016-3781","contributorId":1151,"corporation":false,"usgs":true,"family":"Anderson","given":"Chauncey W.","email":"chauncey@usgs.gov","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":false,"id":462025,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Morgenstern, Karl","contributorId":57716,"corporation":false,"usgs":true,"family":"Morgenstern","given":"Karl","email":"","affiliations":[],"preferred":false,"id":462021,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Downing, Bryan D. 0000-0002-2007-5304 bdowning@usgs.gov","orcid":"https://orcid.org/0000-0002-2007-5304","contributorId":1449,"corporation":false,"usgs":true,"family":"Downing","given":"Bryan","email":"bdowning@usgs.gov","middleInitial":"D.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":462023,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pellerin, Brian A. bpeller@usgs.gov","contributorId":1451,"corporation":false,"usgs":true,"family":"Pellerin","given":"Brian","email":"bpeller@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":462024,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bergamaschi, Brian A. 0000-0002-9610-5581 bbergama@usgs.gov","orcid":"https://orcid.org/0000-0002-9610-5581","contributorId":1448,"corporation":false,"usgs":true,"family":"Bergamaschi","given":"Brian A.","email":"bbergama@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":462022,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70190570,"text":"70190570 - 2010 - Colony attendance patterns by mated Forster's Terns Sterna forsteri using an automated data-logging receiver system","interactions":[],"lastModifiedDate":"2017-09-07T14:25:57","indexId":"70190570","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":900,"text":"Ardea","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Colony attendance patterns by mated Forster's Terns Sterna forsteri using an automated data-logging receiver system","title":"Colony attendance patterns by mated Forster's Terns Sterna forsteri using an automated data-logging receiver system","docAbstract":"In order to examine 24-hour colony attendance patterns by mated Forster's Terns Sterna forsteri in South San Francisco Bay, California, during incubation and chick-rearing stages, we radio-marked 10 individuals consisting of five pairs and recorded colony attendance using an automated data-logging receiver system. We calculated and analyzed five variables: the total attendance time by pairs and individuals, the duration of individual attendance bouts, and the duration both members of a pair either overlapped in colony attendance or were both absent from the colony. The percentage of time spent on the colony by at least one individual of a pair was highest during incubation and declined during chick rearing. Overall, male terns spent a greater proportion of time diurnally attending the colony than females. Females spent a greater proportion of time on colony at night, and without these nocturnal records, we would have reported overall female colony attendance rates as being much lower. Despite sex-specific differences in attendance rates, the length of attendance bouts did not differ between the sexes. Simultaneous colony attendance by both members of a pair was high at night, but during the day, pairs infrequently overlapped in their colony attendance and both members were frequently absent. Our datalogging system functioned well, and our data illustrates the importance of collecting 24-hour records when considering attendance rates.
","language":"English","publisher":"Netherlands Ornithologists' Union","doi":"10.5253/078.098.0108","usgsCitation":"Bluso-Demers, J.D., Ackerman, J., and Takekawa, J.Y., 2010, Colony attendance patterns by mated Forster's Terns Sterna forsteri using an automated data-logging receiver system: Ardea, v. 98, no. 1, p. 59-65, https://doi.org/10.5253/078.098.0108.","productDescription":"7 p.","startPage":"59","endPage":"65","ipdsId":"IP-007592","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":475905,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5253/078.098.0108","text":"Publisher Index Page"},{"id":345556,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"98","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59b25b02e4b020cdf7db1fda","contributors":{"authors":[{"text":"Bluso-Demers, Jill D.","contributorId":62440,"corporation":false,"usgs":true,"family":"Bluso-Demers","given":"Jill","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":709842,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ackerman, Joshua T. 0000-0002-3074-8322 jackerman@usgs.gov","orcid":"https://orcid.org/0000-0002-3074-8322","contributorId":147078,"corporation":false,"usgs":true,"family":"Ackerman","given":"Joshua T.","email":"jackerman@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":709843,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Takekawa, John Y. 0000-0003-0217-5907 john_takekawa@usgs.gov","orcid":"https://orcid.org/0000-0003-0217-5907","contributorId":176168,"corporation":false,"usgs":true,"family":"Takekawa","given":"John","email":"john_takekawa@usgs.gov","middleInitial":"Y.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":709844,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70037601,"text":"70037601 - 2010 - National ecosystem assessments supported by scientific and local knowledge","interactions":[],"lastModifiedDate":"2017-11-17T15:57:26","indexId":"70037601","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1701,"text":"Frontiers in Ecology and the Environment","active":true,"publicationSubtype":{"id":10}},"title":"National ecosystem assessments supported by scientific and local knowledge","docAbstract":"An understanding of the extent of land degradation and recovery is necessary to guide land-use policy and management, yet currently available land-quality assessments are widely known to be inadequate. Here, we present the results of the first statistically based application of a new approach to national assessments that integrates scientific and local knowledge. Qualitative observations completed at over 10 000 plots in the United States showed that while soil degradation remains an issue, loss of biotic integrity is more widespread. Quantitative soil and vegetation data collected at the same locations support the assessments and serve as a baseline for monitoring the effectiveness of policy and management initiatives, including responses to climate change. These results provide the information necessary to support strategic decisions by land managers and policy makers. ?? The Ecological Society of America.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Frontiers in Ecology and the Environment","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.1890/100017","issn":"15409295","usgsCitation":"Herrick, J.E., Lessard, V., Spaeth, K., Shaver, P., Dayton, R., Pyke, D., Jolley, L., and Goebel, J., 2010, National ecosystem assessments supported by scientific and local knowledge: Frontiers in Ecology and the Environment, v. 8, no. 8, p. 403-408, https://doi.org/10.1890/100017.","startPage":"403","endPage":"408","numberOfPages":"6","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":245998,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":218021,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1890/100017"}],"volume":"8","issue":"8","noUsgsAuthors":false,"publicationDate":"2010-07-27","publicationStatus":"PW","scienceBaseUri":"505a6268e4b0c8380cd71ecb","contributors":{"authors":[{"text":"Herrick, J. E.","contributorId":84709,"corporation":false,"usgs":true,"family":"Herrick","given":"J.","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":461868,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lessard, V.C.","contributorId":65308,"corporation":false,"usgs":true,"family":"Lessard","given":"V.C.","email":"","affiliations":[],"preferred":false,"id":461866,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Spaeth, K.E.","contributorId":75490,"corporation":false,"usgs":true,"family":"Spaeth","given":"K.E.","email":"","affiliations":[],"preferred":false,"id":461867,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shaver, P.L.","contributorId":8705,"corporation":false,"usgs":true,"family":"Shaver","given":"P.L.","email":"","affiliations":[],"preferred":false,"id":461862,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dayton, R.S.","contributorId":105570,"corporation":false,"usgs":true,"family":"Dayton","given":"R.S.","email":"","affiliations":[],"preferred":false,"id":461869,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Pyke, D.A.","contributorId":62713,"corporation":false,"usgs":true,"family":"Pyke","given":"D.A.","email":"","affiliations":[],"preferred":false,"id":461865,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jolley, L.","contributorId":49219,"corporation":false,"usgs":true,"family":"Jolley","given":"L.","email":"","affiliations":[],"preferred":false,"id":461863,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Goebel, J.J.","contributorId":49220,"corporation":false,"usgs":true,"family":"Goebel","given":"J.J.","email":"","affiliations":[],"preferred":false,"id":461864,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70037605,"text":"70037605 - 2010 - Dynamics and spatio-temporal variability of environmental factors in Eastern Australia using functional principal component analysis","interactions":[],"lastModifiedDate":"2012-03-12T17:22:03","indexId":"70037605","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2196,"text":"Journal of Biological Systems","active":true,"publicationSubtype":{"id":10}},"title":"Dynamics and spatio-temporal variability of environmental factors in Eastern Australia using functional principal component analysis","docAbstract":"This paper introduces a new technique in ecology to analyze spatial and temporal variability in environmental variables. By using simple statistics, we explore the relations between abiotic and biotic variables that influence animal distributions. However, spatial and temporal variability in rainfall, a key variable in ecological studies, can cause difficulties to any basic model including time evolution. The study was of a landscape scale (three million square kilometers in eastern Australia), mainly over the period of 19982004. We simultaneously considered qualitative spatial (soil and habitat types) and quantitative temporal (rainfall) variables in a Geographical Information System environment. In addition to some techniques commonly used in ecology, we applied a new method, Functional Principal Component Analysis, which proved to be very suitable for this case, as it explained more than 97% of the total variance of the rainfall data, providing us with substitute variables that are easier to manage and are even able to explain rainfall patterns. The main variable came from a habitat classification that showed strong correlations with rainfall values and soil types. ?? 2010 World Scientific Publishing Company.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Biological Systems","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","doi":"10.1142/S0218339010003500","issn":"02183390","usgsCitation":"Szabo, J., Fedriani, E., Segovia-Gonzalez, M.M., Astheimer, L., and Hooper, M., 2010, Dynamics and spatio-temporal variability of environmental factors in Eastern Australia using functional principal component analysis: Journal of Biological Systems, v. 18, no. 4, p. 763-785, https://doi.org/10.1142/S0218339010003500.","startPage":"763","endPage":"785","numberOfPages":"23","costCenters":[],"links":[{"id":502618,"rank":10000,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://figshare.com/articles/journal_contribution/Dynamics_and_spatio-temporal_variability_of_environmental_factors_in_Eastern_Australia_using_functional_principal_component_analysis/20926360","text":"External Repository"},{"id":218048,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1142/S0218339010003500"},{"id":246028,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"18","issue":"4","noUsgsAuthors":false,"publicationDate":"2011-11-21","publicationStatus":"PW","scienceBaseUri":"505a042ce4b0c8380cd50826","contributors":{"authors":[{"text":"Szabo, J.K.","contributorId":38347,"corporation":false,"usgs":true,"family":"Szabo","given":"J.K.","email":"","affiliations":[],"preferred":false,"id":461879,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fedriani, E.M.","contributorId":80126,"corporation":false,"usgs":true,"family":"Fedriani","given":"E.M.","email":"","affiliations":[],"preferred":false,"id":461882,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Segovia-Gonzalez, M. M.","contributorId":74611,"corporation":false,"usgs":true,"family":"Segovia-Gonzalez","given":"M.","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":461881,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Astheimer, L.B.","contributorId":12723,"corporation":false,"usgs":true,"family":"Astheimer","given":"L.B.","email":"","affiliations":[],"preferred":false,"id":461878,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hooper, M.J.","contributorId":70581,"corporation":false,"usgs":true,"family":"Hooper","given":"M.J.","email":"","affiliations":[],"preferred":false,"id":461880,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70037610,"text":"70037610 - 2010 - A methodology for ecosystem-scale modeling of selenium","interactions":[],"lastModifiedDate":"2018-10-10T16:52:22","indexId":"70037610","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2010","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":"A methodology for ecosystem-scale modeling of selenium","docAbstract":"The main route of exposure for selenium (Se) is dietary, yet regulations lack biologically based protocols for evaluations of risk. We propose here an ecosystem-scale model that conceptualizes and quantifies the variables that determinehow Se is processed from water through diet to predators. This approach uses biogeochemical and physiological factors from laboratory and field studies and considers loading, speciation, transformation to particulate material, bioavailability, bioaccumulation in invertebrates, and trophic transfer to predators. Validation of the model is through data sets from 29 historic and recent field case studies of Se-exposed sites. The model links Se concentrations across media (water, particulate, tissue of different food web species). It can be used to forecast toxicity under different management or regulatory proposals or as a methodology for translating a fish-tissue (or other predator tissue) Se concentration guideline to a dissolved Se concentration. The model illustrates some critical aspects of implementing a tissue criterion: 1) the choice of fish species determines the food web through which Se should be modeled, 2) the choice of food web is critical because the particulate material to prey kinetics of bioaccumulation differs widely among invertebrates, 3) the characterization of the type and phase of particulate material is important to quantifying Se exposure to prey through the base of the food web, and 4) the metric describing partitioning between particulate material and dissolved Se concentrations allows determination of a site-specific dissolved Se concentration that would be responsible for that fish body burden in the specific environment. The linked approach illustrates that environmentally safe dissolved Se concentrations will differ among ecosystems depending on the ecological pathways and biogeochemical conditions in that system. Uncertainties and model sensitivities can be directly illustrated by varying exposure scenarios based on site-specific knowledge. The model can also be used to facilitate site-specific regulation and to present generic comparisons to illustrate limitations imposed by ecosystem setting and inhabitants. Used optimally, the model provides a tool for framing a site-specific ecological problem or occurrence of Se exposure, quantify exposure within that ecosystem, and narrow uncertainties abouthowto protect it by understanding the specifics of the underlying system ecology, biogeochemistry, and hydrology.
","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Integrated Environmental Assessment and Management","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Society of Environmental Toxicology and Chemistry","doi":"10.1002/ieam.101","issn":"15513793","usgsCitation":"Presser, T.S., and Luoma, S.N., 2010, A methodology for ecosystem-scale modeling of selenium: Integrated Environmental Assessment and Management, v. 6, no. 4, p. 685-710, https://doi.org/10.1002/ieam.101.","productDescription":"26 p.","startPage":"685","endPage":"710","costCenters":[{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":218077,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/ieam.101"},{"id":246058,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","issue":"4","noUsgsAuthors":false,"publicationDate":"2010-10-01","publicationStatus":"PW","scienceBaseUri":"5059e460e4b0c8380cd46605","contributors":{"authors":[{"text":"Presser, Theresa S. 0000-0001-5643-0147 tpresser@usgs.gov","orcid":"https://orcid.org/0000-0001-5643-0147","contributorId":2467,"corporation":false,"usgs":true,"family":"Presser","given":"Theresa","email":"tpresser@usgs.gov","middleInitial":"S.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":461903,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Luoma, Samuel N. 0000-0001-5443-5091 snluoma@usgs.gov","orcid":"https://orcid.org/0000-0001-5443-5091","contributorId":2287,"corporation":false,"usgs":true,"family":"Luoma","given":"Samuel","email":"snluoma@usgs.gov","middleInitial":"N.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":461902,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ]}