Fish Creek, an approximately 25-kilometer-long tributary to Snake River, is located in Teton County in western Wyoming near the town of Wilson. Fish Creek is an important water body because it is used for irrigation, fishing, and recreation and adds scenic value to the Jackson Hole properties it runs through. Public concern about nuisance growths of aquatic plants in Fish Creek has been increasing since the early 2000s. To address these concerns, the U.S. Geological Survey conducted a study in cooperation with the Teton Conservation District to characterize the hydrology, water quality, and biologic communities of Fish Creek during 2007–11.
\n\nThe hydrology of Fish Creek is strongly affected by groundwater contributions from the area known as the Snake River west bank, which lies east of Fish Creek and west of Snake River. Because of this continuous groundwater discharge to the creek, land-use activities in the west bank area can affect the groundwater quality. Evaluation of nitrate isotopes and dissolved-nitrate concentrations in groundwater during the study indicated that nitrate was entering Fish Creek from groundwater, and that the source of nitrate was commonly a septic/sewage effluent or manure source, or multiple sources, potentially including artificial nitrogen fertilizers, natural soil organic matter, and mixtures of sources.
\n\nConcentrations of dissolved nitrate and orthophosphate, which are key nutrients for growth of aquatic plants, generally were low in Fish Creek and occasionally were less than reporting levels (not detected). One potential reason for the low nutrient concentrations is that nutrients were being consumed by aquatic plant life that increases during the summer growing season, as a result of the seasonal increase in temperature and larger number of daylight hours.
\n\nSeveral aspects of Fish Creek’s hydrology contribute to higher productivity and biovolume of aquatic plants in Fish Creek than typically observed in streams of its size in Wyoming. Especially in the winter, the proportionately large, continuous gain of groundwater into Fish Creek in the perennial section keeps most of the creek free of ice. Because sunlight can still reach the streambed in Fish Creek and the water is still flowing, aquatic plants continue to photosynthesize in the winter, albeit at a lower level of productivity. Additionally, the cobble and large gravel substrate in Fish Creek provides excellent attachment points for aquatic plants, and when combined with Fish Creek’s channel stability allows rapid growth of aquatic plants once conditions allow during the spring.
\n\nThe aquatic plant community of Fish Creek was different than most streams in Wyoming in that it contains many different macrophytes—including macroalgae such as long streamers of Cladophora, aquatic vascular plants, and moss; most other streams in the state contain predominantly algae. From the banks of Fish Creek, the bottom of the stream sometimes appeared to be a solid green carpet. A shift was observed from higher amounts of microalgae in April/May to higher amounts macrophytes in August and October, and differences in the relative abundance of microalgae and macrophytes were statistically significant between seasons.
\n\nDifferences in dissolved-nitrate concentrations and in the nitrogen-to-phosphorus ratio were significantly different between seasons, as concentrations of dissolved nitrate decreased from April/May to August and October. It is likely that dissolved-nitrate concentrations in Fish Creek were lower in August and October because macrophytes were quickly utilizing the nutrient, and a negative correlation between macro-phytes and nitrate was found.
\n\nMacroinvertebrates also were sampled because of their role as indicators of water quality and their documented responses to perturbation such as degradation of water quality and habitat. Statistically significant seasonal differences were noted in the macroinvertebrate community. Taxa richness and relative abundance of Ephemeroptera, Plecoptera, and Trichoptera, which tend to be intolerant of water-quality degradation, decreased from April/May to August; the same time period saw a corresponding increase in Diptera and noninsects, particularly Oligochaeta (worms) that are more tolerant.
\n\nSeasonal changes in macroinvertebrate functional feeding groups were significantly different. The relative abundance of gatherer-collector and scraper feeding groups decreased from April/May to August, accompanied by an increase in filterer-collector and shredders feeding groups. Seasonal changes in feeding groups might be due to the seasonal shift in aquatic plant communities, as indicated by comparison with other streams in the area that had fewer aquatic macrophytes than Fish Creek. Statistical tests of macroinvertebrate metrics indicated few differences between years or biological sampling sites on Fish Creek, although the site farthest upstream sometimes was different not only in terms of macroinvertebrates but also in streamflow, water quality, and aquatic plants.
\n\nPotential effects of contributions of additional nutrients to the Fish Creek ecosystem beyond the conditions sampled during the study period are not known. However, because virtually all of the detectable dissolved nitrate commonly was consumed by aquatic plants in August (leaving dissolved nitrate less than the reporting level in water samples), it is possible that increased nutrient contributions could cause increased growth of aquatic plants. Additional long-term monitoring of the stream, with concurrent data analysis and interpretation would be needed to determine the effects of additional nutrients on the aquatic plant community and on higher levels of the food chain.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135117","collaboration":"Prepared in cooperation with Teton Conservation District","usgsCitation":"Eddy-Miller, C., Peterson, D.A., Wheeler, J.D., Edmiston, C.S., Taylor, M.L., and Leemon, D.J., 2013, Characterization of water quality and biological communities, Fish Creek, Teton County, Wyoming, 2007-2011: U.S. Geological Survey Scientific Investigations Report 2013-5117, Report: x, 76 p.; Downloads Directory, https://doi.org/10.3133/sir20135117.","productDescription":"Report: x, 76 p.; Downloads Directory","numberOfPages":"90","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2007-01-01","temporalEnd":"2011-12-31","ipdsId":"IP-042351","costCenters":[{"id":684,"text":"Wyoming Water Science Center","active":false,"usgs":true}],"links":[{"id":278058,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135117.gif"},{"id":278055,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5117/"},{"id":278056,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5117/pdf/sir2013-5117.pdf"},{"id":278057,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2013/5117/downloads/"}],"scale":"100000","projection":"Lambert Conformal Conic projection","datum":"North American Datum of 1983","country":"United States","state":"Wyoming","county":"Teton County","otherGeospatial":"Fish Creek","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -111.045942,43.409662 ], [ -111.045942,43.899253 ], [ -110.359812,43.899253 ], [ -110.359812,43.409662 ], [ -111.045942,43.409662 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5243f7cfe4b05b217bad9fe9","contributors":{"authors":[{"text":"Eddy-Miller, Cheryl A.","contributorId":86755,"corporation":false,"usgs":true,"family":"Eddy-Miller","given":"Cheryl A.","affiliations":[],"preferred":false,"id":484534,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Peterson, David A. davep@usgs.gov","contributorId":1742,"corporation":false,"usgs":true,"family":"Peterson","given":"David","email":"davep@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":484529,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wheeler, Jerrod D. 0000-0002-0533-8700 jwheele@usgs.gov","orcid":"https://orcid.org/0000-0002-0533-8700","contributorId":1893,"corporation":false,"usgs":true,"family":"Wheeler","given":"Jerrod","email":"jwheele@usgs.gov","middleInitial":"D.","affiliations":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"preferred":true,"id":484530,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Edmiston, C. Scott","contributorId":30595,"corporation":false,"usgs":true,"family":"Edmiston","given":"C.","email":"","middleInitial":"Scott","affiliations":[],"preferred":false,"id":484531,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Taylor, Michelle L.","contributorId":35206,"corporation":false,"usgs":true,"family":"Taylor","given":"Michelle","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":484532,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Leemon, Daniel J.","contributorId":70090,"corporation":false,"usgs":true,"family":"Leemon","given":"Daniel","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":484533,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70048390,"text":"70048390 - 2013 - Plant responses, climate pivot points, and trade-offs in water-limited ecosystems","interactions":[],"lastModifiedDate":"2013-09-24T15:22:01","indexId":"70048390","displayToPublicDate":"2013-09-24T15:14:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Plant responses, climate pivot points, and trade-offs in water-limited ecosystems","docAbstract":"Plant species in dryland ecosystems are limited by water availability and may be vulnerable to increases in aridity. Methods are needed to monitor and assess the rate of change in plant abundance and composition in relation to climate, understand the potential for degradation in dryland ecosystems, and forecast future changes in plant species assemblages. I employ nearly a century of vegetation monitoring data from three North American deserts to demonstrate an approach to determine plant species responses to climate and critical points over a range of climatic conditions at which plant species shift from increases to decreases in abundance (climate pivot points). I assess these metrics from a site to regional scale and highlight how these indicators of plant performance can be modified by the physical and biotic environment. For example, shrubs were more responsive to drought and high temperatures on shallow soils with limited capacity to store water and fine-textured soils with slow percolation rates, whereas perennial grasses were more responsive to precipitation in sparse shrublands than in relatively dense grasslands and shrublands, where competition for water is likely more intense. The responses and associated climate pivot points of plant species aligned with their lifespan and structural characteristics, and the relationship between responses and climate pivot points provides evidence of the trade-off between the capacity of a plant species to increase in abundance when water is available and its drought resistance.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ecosphere","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Ecological Society of America","doi":"10.1890/ES13-00132.1","usgsCitation":"Munson, S.M., 2013, Plant responses, climate pivot points, and trade-offs in water-limited ecosystems: Ecosphere, v. 4, no. 9, 15 p., https://doi.org/10.1890/ES13-00132.1.","productDescription":"15 p.","numberOfPages":"15","ipdsId":"IP-042024","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":473524,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1890/es13-00132.1","text":"Publisher Index Page"},{"id":278051,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":278044,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1890/ES13-00132.1"}],"country":"United States","state":"Arizona;New Mexico;Texas;Utah","otherGeospatial":"Chihuahuan Desert;Colorado Plateau;Sonoran Desert","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -111.48,28.97 ], [ -111.48,38.86 ], [ -102.84,38.86 ], [ -102.84,28.97 ], [ -111.48,28.97 ] ] ] } } ] }","volume":"4","issue":"9","noUsgsAuthors":false,"publicationDate":"2013-09-23","publicationStatus":"PW","scienceBaseUri":"5242a696e4b096ee624641d0","contributors":{"authors":[{"text":"Munson, Seth M. 0000-0002-2736-6374 smunson@usgs.gov","orcid":"https://orcid.org/0000-0002-2736-6374","contributorId":1334,"corporation":false,"usgs":true,"family":"Munson","given":"Seth","email":"smunson@usgs.gov","middleInitial":"M.","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":484514,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70048392,"text":"sir20135152 - 2013 - Estimation of sediment inflows to Lake Tuscaloosa, Alabama, 2009-11","interactions":[],"lastModifiedDate":"2013-10-30T11:20:10","indexId":"sir20135152","displayToPublicDate":"2013-09-24T15:12:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-5152","title":"Estimation of sediment inflows to Lake Tuscaloosa, Alabama, 2009-11","docAbstract":"The U.S. Geological Survey, in cooperation with the City of Tuscaloosa, evaluated the concentrations, loads, and yields of suspended sediment in the tributaries to Lake Tuscaloosa in west-central Alabama, from October 1, 2008, to January 31, 2012. The collection and analysis of these data will facilitate the comparison with historical data, serve as a baseline for future sediment-collection efforts, and help to identify areas of concern. Lake Tuscaloosa, at the reservoir dam, receives runoff from a drainage area of 423 square miles (mi2). Basinwide in 2006, forested land was the primary land cover (68 percent). Comparison of historical imagery with the National Land Cover Database (2001 and 2006) indicated that the greatest temporal land-use change was timber harvest. The land cover in 2006 was indicative of this change, with shrub/scrub land (12 percent) being the secondary land use in the basin. Agricultural land use (10 percent) was represented predominantly by hay and pasture or grasslands. Urban land use was minimal, accounting for 4 percent of the entire basin. The remaining 6 percent of the basin has a land use of open water or wetlands. Storm and monthly suspended-sediment samples were collected from seven tributaries to Lake Tuscaloosa: North River, Turkey Creek, Binion Creek, Pole Bridge Creek, Tierce Creek, Carroll Creek, and Brush Creek. Suspended-sediment concentrations and streamflow measurements were statistically analyzed to estimate annual suspended-sediment loads and yields from each of these contributing watersheds. Estimated annual suspended-sediment yields in 2009 were 360, 540, and 840 tons per square mile (tons/mi2) at the North River, Turkey Creek, and Carroll Creek streamflow-gaging stations, respectively. Estimated annual suspended-sediment yields in 2010 were 120 and 86 tons/mi2 at the Binion Creek and Pole Bridge Creek streamflow-gaging stations, respectively. Estimated annual suspended-sediment yields in 2011 were 190 and 300 tons/mi2 at the Tierce Creek and Brush Creek streamflow-gaging stations, respectively. The North River watershed at the streamflow-gaging station contributes 53 percent of the drainage area for Lake Tuscaloosa. A previous study in the 1970s analyzed streamflow and historical suspended-sediment samples to estimate a long-term average suspended-sediment yield of 300 tons per year per square mile in the North River watershed. Analysis of data collected in the North River watershed during the 2009 water year (October 2008 to September 2009) estimated a sediment yield of 360 tons/mi2. The North River watershed, a major portion of the Lake Tuscaloosa drainage basin, has not experienced a substantial increase in sedimentation rates. During the 2009 water year, the Turkey Creek watershed (6.16 mi2) and the Carroll Creek watershed (20.9 mi2) produced greater suspended-sediment yields than the North River watershed but contribute a much smaller drainage area to Lake Tuscaloosa. Aerial photography and bathymetric surveys indicate that Carroll Creek has experienced increased sediment deposition in the upstream portions of the channel. Carroll Creek is also the only watershed in the current study that has a substantial percentage (11 percent) of urban","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135152","collaboration":"Prepared in cooperation with City of Tuscaloosa","usgsCitation":"Lee, K., 2013, Estimation of sediment inflows to Lake Tuscaloosa, Alabama, 2009-11: U.S. Geological Survey Scientific Investigations Report 2013-5152, viii, 65 p., https://doi.org/10.3133/sir20135152.","productDescription":"viii, 65 p.","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2009-01-01","temporalEnd":"2011-12-31","costCenters":[{"id":105,"text":"Alabama Water Science Center","active":true,"usgs":true}],"links":[{"id":278054,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135152.gif"},{"id":278049,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5152/"},{"id":278050,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5152/pdf/sir2013-5152.pdf"}],"scale":"100000","country":"United States","state":"Alabama","county":"Fayette County;Tuscaloosa County","otherGeospatial":"Lake Tuscaloosa","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -87.952094,32.636200 ], [ -87.952094,33.919871 ], [ -86.427100,33.919871 ], [ -86.427100,32.636200 ], [ -87.952094,32.636200 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5242a695e4b096ee624641c0","contributors":{"authors":[{"text":"Lee, K.G.","contributorId":28319,"corporation":false,"usgs":true,"family":"Lee","given":"K.G.","email":"","affiliations":[],"preferred":false,"id":484517,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70048387,"text":"70048387 - 2013 - A hybrid double-observer sightability model for aerial surveys","interactions":[],"lastModifiedDate":"2013-10-30T10:31:15","indexId":"70048387","displayToPublicDate":"2013-09-24T14:46:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"A hybrid double-observer sightability model for aerial surveys","docAbstract":"Raw counts from aerial surveys make no correction for undetected animals and provide no estimate of precision with which to judge the utility of the counts. Sightability modeling and double-observer (DO) modeling are 2 commonly used approaches to account for detection bias and to estimate precision in aerial surveys. We developed a hybrid DO sightability model (model MH) that uses the strength of each approach to overcome the weakness in the other, for aerial surveys of elk (Cervus elaphus). The hybrid approach uses detection patterns of 2 independent observer pairs in a helicopter and telemetry-based detections of collared elk groups. Candidate MH models reflected hypotheses about effects of recorded covariates and unmodeled heterogeneity on the separate front-seat observer pair and back-seat observer pair detection probabilities. Group size and concealing vegetation cover strongly influenced detection probabilities. The pilot's previous experience participating in aerial surveys influenced detection by the front pair of observers if the elk group was on the pilot's side of the helicopter flight path. In 9 surveys in Mount Rainier National Park, the raw number of elk counted was approximately 80–93% of the abundance estimated by model MH. Uncorrected ratios of bulls per 100 cows generally were low compared to estimates adjusted for detection bias, but ratios of calves per 100 cows were comparable whether based on raw survey counts or adjusted estimates. The hybrid method was an improvement over commonly used alternatives, with improved precision compared to sightability modeling and reduced bias compared to DO modeling.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Wildlife Management","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1002/jwmg.612","usgsCitation":"Griffin, P., Lubow, B., Jenkins, K.J., Vales, D.J., Moeller, B.J., Reid, M., Happe, P.J., Mccorquodale, S.M., Tirhi, M.J., Schaberi, J.P., and Beirne, K., 2013, A hybrid double-observer sightability model for aerial surveys: Journal of Wildlife Management, v. 77, no. 8, p. 1532-1544, https://doi.org/10.1002/jwmg.612.","productDescription":"13 p.","startPage":"1532","endPage":"1544","numberOfPages":"13","onlineOnly":"Y","ipdsId":"IP-045719","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":278043,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":278038,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/jwmg.612"}],"country":"United States","state":"Washington","otherGeospatial":"Mount Rainier National Park","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.0,46.5 ], [ -122.0,47.0 ], [ -121.25,47.0 ], [ -121.25,46.5 ], [ -122.0,46.5 ] ] ] } } ] }","volume":"77","issue":"8","noUsgsAuthors":false,"publicationDate":"2013-09-19","publicationStatus":"PW","scienceBaseUri":"5242a655e4b096ee624641b0","contributors":{"authors":[{"text":"Griffin, Paul C.","contributorId":7802,"corporation":false,"usgs":true,"family":"Griffin","given":"Paul C.","affiliations":[],"preferred":false,"id":484501,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lubow, Bruce C.","contributorId":59520,"corporation":false,"usgs":true,"family":"Lubow","given":"Bruce C.","affiliations":[],"preferred":false,"id":484506,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jenkins, Kurt J. 0000-0003-1415-6607 kurt_jenkins@usgs.gov","orcid":"https://orcid.org/0000-0003-1415-6607","contributorId":3415,"corporation":false,"usgs":true,"family":"Jenkins","given":"Kurt","email":"kurt_jenkins@usgs.gov","middleInitial":"J.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":484500,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vales, David J.","contributorId":74662,"corporation":false,"usgs":true,"family":"Vales","given":"David","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":484508,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Moeller, Barbara J.","contributorId":87446,"corporation":false,"usgs":true,"family":"Moeller","given":"Barbara","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":484510,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Reid, Mason","contributorId":51639,"corporation":false,"usgs":true,"family":"Reid","given":"Mason","affiliations":[],"preferred":false,"id":484504,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Happe, Patricia J.","contributorId":50983,"corporation":false,"usgs":false,"family":"Happe","given":"Patricia","email":"","middleInitial":"J.","affiliations":[{"id":16133,"text":"National Park Service, Olympic National Park","active":true,"usgs":false}],"preferred":false,"id":484503,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Mccorquodale, Scott M.","contributorId":62921,"corporation":false,"usgs":true,"family":"Mccorquodale","given":"Scott","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":484507,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Tirhi, Michelle J.","contributorId":36839,"corporation":false,"usgs":true,"family":"Tirhi","given":"Michelle","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":484502,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Schaberi, Jim P.","contributorId":76218,"corporation":false,"usgs":true,"family":"Schaberi","given":"Jim","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":484509,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Beirne, Katherine","contributorId":58754,"corporation":false,"usgs":true,"family":"Beirne","given":"Katherine","affiliations":[],"preferred":false,"id":484505,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70048388,"text":"ds793 - 2013 - Geospatial compilation of historical water-level altitudes in the Chicot and Evangeline aquifers 1977-2013 and Jasper aquifer 2000-13 in the Gulf Coast aquifer system, Houston-Galveston Region, Texas","interactions":[],"lastModifiedDate":"2017-03-29T16:52:39","indexId":"ds793","displayToPublicDate":"2013-09-24T14:21:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"793","title":"Geospatial compilation of historical water-level altitudes in the Chicot and Evangeline aquifers 1977-2013 and Jasper aquifer 2000-13 in the Gulf Coast aquifer system, Houston-Galveston Region, Texas","docAbstract":"The U.S. Geological Survey (USGS) in cooperation with the Harris-Galveston Subsidence District, City of Houston, Fort Bend Subsidence District, Lone Star Groundwater Conservation District, and Brazoria County Groundwater Conservation District has produced a series of annual reports depicting groundwater-level altitudes in the Chicot, Evangeline, and Jasper aquifers of the Gulf Coast aquifer system in the Houston-Galveston region, Texas. To produce these annual reports, contours of equal water-level altitudes are created from water levels measured between December and March of each year from groundwater wells screened completely within one of these three aquifers. Information obtained from maps published in the annual series of USGS reports and geospatial datasets of water-level altitude contours used to create the annual series of USGS reports were compiled into a comprehensive geodatabase. The geospatial compilation contains 88 datasets from previously published contour maps showing water-level altitudes for each primary aquifer of the Gulf Coast aquifer system, 37 for the Chicot (1977–2013), 37 for the Evangeline aquifer (1977–2013), and 14 for the Jasper aquifer (2000–13).
\nMaps were georeferenced and digitized where existing geographic information system (GIS) data were unavailable (1977–89, 1991, 1995–99). Existing GIS data available for 1990, 1992–94, and 2000–13 were included in the geodatabase. The feature classes were organized into three feature datasets by principal aquifer: Chicot, Evangeline, and Jasper aquifers.
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Changes to rule curves are often contemplated and requested by various user groups and management agencies with no information available about the actual flood risk of such requests. Methods of estimating flood risk in reservoirs are not easily available to those unfamiliar with hydrological models that track water movement through a river basin. We developed a quantile regression model that uses readily available daily water-level data to estimate risk of spilling. Our model provided a relatively simple process for estimating the maximum applicable water level under a specific flood risk for any day of the year. This water level represents an upper-limit umbrella under which water levels can be operated in a variety of ways. Our model allows the visualization of water-level management under a user-specified flood risk and provides a framework for incorporating the effect of a changing environment on water-level management in reservoirs, but is not designed to replace existing hydrological models. The model can improve communication and collaboration among agencies responsible for managing natural resources dependent on reservoir water levels.
","language":"English","publisher":"International Association of Hydraulic Engineering and Research","publisherLocation":"Madrid, Spain","doi":"10.1080/15715124.2013.823979","usgsCitation":"Mower, E., and Miranda, L.E., 2013, Evaluating changes to reservoir rule curves using historical water-level data: International Journal of River Basin Management, v. 11, no. 3, p. 323-328, https://doi.org/10.1080/15715124.2013.823979.","productDescription":"6 p.","startPage":"323","endPage":"328","numberOfPages":"6","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-048954","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":305655,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","issue":"3","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55a0ecb1e4b0183d66e43039","contributors":{"authors":[{"text":"Mower, Ethan","contributorId":143702,"corporation":false,"usgs":false,"family":"Mower","given":"Ethan","email":"","affiliations":[],"preferred":false,"id":564617,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Miranda, Leandro E. 0000-0002-2138-7924 smiranda@usgs.gov","orcid":"https://orcid.org/0000-0002-2138-7924","contributorId":531,"corporation":false,"usgs":true,"family":"Miranda","given":"Leandro","email":"smiranda@usgs.gov","middleInitial":"E.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":564293,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70048381,"text":"sir20135132 - 2013 - Chemistry and age of groundwater in bedrock aquifers of the Piceance and Yellow Creek watersheds, Rio Blanco County, Colorado, 2010-12","interactions":[],"lastModifiedDate":"2013-10-30T11:21:01","indexId":"sir20135132","displayToPublicDate":"2013-09-24T12:36:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-5132","title":"Chemistry and age of groundwater in bedrock aquifers of the Piceance and Yellow Creek watersheds, Rio Blanco County, Colorado, 2010-12","docAbstract":"Fourteen monitoring wells completed in the Uinta and Green River Formations in the Piceance Creek and Yellow Creek watersheds in Rio Blanco County, Colorado, were sampled for chemical, isotopic, and groundwater-age tracers to provide information on the overall groundwater quality, the occurrence and distribution of chemicals that could be related to the development of underlying natural-gas reservoirs, and to better understand groundwater residence times in the flow system. Methane concentrations in groundwater ranged from less than 0.0005 to 387 milligrams per liter. The methane was predominantly biogenic in origin, although the biogenic methane was mixed with thermogenic methane in water from seven wells. Three BTEX compounds (benzene, toluene, and ethylbenzene) were detected in water from six of the wells, but none of the concentrations exceeded Federal drinking-water standards. The presence of thermogenic methane in the aquifers indicates a connection and vulnerability to chemicals in deeper geologic units. Helium-4 data indicate that groundwater had ages ranging from less than 1,000 years to greater than 50,000 years. The presence of old groundwater in parts of the aquifers indicates that these aquifers may not be useful for large-scale water supply because of low recharge rates.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135132","collaboration":"Prepared in cooperation with the Bureau of Land Management, White River Field Office","usgsCitation":"McMahon, P., Thomas, J., and Hunt, A., 2013, Chemistry and age of groundwater in bedrock aquifers of the Piceance and Yellow Creek watersheds, Rio Blanco County, Colorado, 2010-12: U.S. Geological Survey Scientific Investigations Report 2013-5132, viii, 86 p., https://doi.org/10.3133/sir20135132.","productDescription":"viii, 86 p.","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":278036,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/70048381.gif"},{"id":278035,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5132/"},{"id":278034,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5132/pdf/sir2013-5132.pdf"}],"scale":"24000","projection":"Universal Transverse Mercator, Zone 13 North","country":"United States","state":"Colorado","county":"Rio Blanco County","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -108.882751,39.627375 ], [ -108.882751,40.110113 ], [ -107.998352,40.110113 ], [ -107.998352,39.627375 ], [ -108.882751,39.627375 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57f7f241e4b0bc0bec0a028c","contributors":{"authors":[{"text":"McMahon, P.B. 0000-0001-7452-2379","orcid":"https://orcid.org/0000-0001-7452-2379","contributorId":10762,"corporation":false,"usgs":true,"family":"McMahon","given":"P.B.","affiliations":[],"preferred":false,"id":484486,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thomas, J.C.","contributorId":95435,"corporation":false,"usgs":true,"family":"Thomas","given":"J.C.","affiliations":[],"preferred":false,"id":484488,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hunt, A.G.","contributorId":68691,"corporation":false,"usgs":true,"family":"Hunt","given":"A.G.","email":"","affiliations":[],"preferred":false,"id":484487,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70048380,"text":"fs20133047 - 2013 - Chemistry and age of groundwater in the Piceance structural basin, Rio Blanco county, Colorado, 2010-12","interactions":[],"lastModifiedDate":"2013-09-24T12:40:44","indexId":"fs20133047","displayToPublicDate":"2013-09-24T12:33:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-3047","title":"Chemistry and age of groundwater in the Piceance structural basin, Rio Blanco county, Colorado, 2010-12","docAbstract":"Fourteen monitoring wells were sampled by the U.S. Geological Survey, in cooperation with the Bureau of Land Management, to better understand the chemistry and age of groundwater in the Piceance structural basin in Rio Blanco County, Colorado, and how they may relate to the development of underlying natural-gas reservoirs. Natural gas extraction in the area has been ongoing since at least the 1950s, and the area contains about 960 producing, shut-in, and abandoned natural-gas wells.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20133047","usgsCitation":"McMahon, P.B., Thomas, J.C., and Hunt, A.G., 2013, Chemistry and age of groundwater in the Piceance structural basin, Rio Blanco county, Colorado, 2010-12: U.S. Geological Survey Fact Sheet 2013-3047, 6 p., https://doi.org/10.3133/fs20133047.","productDescription":"6 p.","numberOfPages":"6","onlineOnly":"N","temporalStart":"2010-01-01","temporalEnd":"2012-12-31","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":278033,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20133047.PNG"},{"id":278032,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2013/3047/pdf/fs2013-3047.pdf"},{"id":278031,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2013/3047/"}],"country":"United States","state":"Colorado","county":"Rio Blanco County","otherGeospatial":"Piceance Structural Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -108.75,39.666667 ], [ -108.75,40.166667 ], [ -107.75,40.166667 ], [ -107.75,39.666667 ], [ -108.75,39.666667 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5242a693e4b096ee624641b8","contributors":{"authors":[{"text":"McMahon, Peter B. 0000-0001-7452-2379 pmcmahon@usgs.gov","orcid":"https://orcid.org/0000-0001-7452-2379","contributorId":724,"corporation":false,"usgs":true,"family":"McMahon","given":"Peter","email":"pmcmahon@usgs.gov","middleInitial":"B.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":484483,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thomas, Judith C. 0000-0001-7883-1419 juthomas@usgs.gov","orcid":"https://orcid.org/0000-0001-7883-1419","contributorId":1468,"corporation":false,"usgs":true,"family":"Thomas","given":"Judith","email":"juthomas@usgs.gov","middleInitial":"C.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":484484,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hunt, Andrew G. 0000-0002-3810-8610 ahunt@usgs.gov","orcid":"https://orcid.org/0000-0002-3810-8610","contributorId":1582,"corporation":false,"usgs":true,"family":"Hunt","given":"Andrew","email":"ahunt@usgs.gov","middleInitial":"G.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":484485,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70048370,"text":"70048370 - 2013 - Is exposure to cyanobacteria an environmental risk factor for amyotrophic lateral sclerosis and other neurodegenerative diseases?","interactions":[],"lastModifiedDate":"2013-09-24T10:43:38","indexId":"70048370","displayToPublicDate":"2013-09-24T10:39:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":755,"text":"Amyotrophic Lateral Sclerosis and Frontotemporal Degeneration","active":true,"publicationSubtype":{"id":10}},"title":"Is exposure to cyanobacteria an environmental risk factor for amyotrophic lateral sclerosis and other neurodegenerative diseases?","docAbstract":"There is a broad scientific consensus that amyotrophic lateral sclerosis (ALS) is caused by gene-environment interactions. Mutations in genes underlying familial ALS (fALS) have been discovered in only 5–10% of the total population of ALS patients. Relatively little attention has been paid to environmental and lifestyle factors that may trigger the cascade of motor neuron death leading to the syndrome of ALS, although exposure to chemicals including lead and pesticides, and to agricultural environments, smoking, certain sports, and trauma have all been identified with an increased risk of ALS. There is a need for research to quantify the relative roles of each of the identified risk factors for ALS. Recent evidence has strengthened the theory that chronic environmental exposure to the neurotoxic amino acid β-N-methylamino-L-alanine (BMAA) produced by cyanobacteria may be an environmental risk factor for ALS. Here we describe methods that may be used to assess exposure to cyanobacteria, and hence potentially to BMAA, namely an epidemiologic questionnaire and direct and indirect methods for estimating the cyanobacterial load in ecosystems. Rigorous epidemiologic studies could determine the risks associated with exposure to cyanobacteria, and if combined with genetic analysis of ALS cases and controls could reveal etiologically important gene-environment interactions in genetically vulnerable individuals.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Amyotrophic Lateral Sclerosis and Frontotemporal Degeneration","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Informa Healthcare","doi":"10.3109/21678421.2012.750364","usgsCitation":"Bradley, W.G., Borenstein, A.R., Nelson, L.M., Codd, G.A., Rosen, B.H., Stommel, E.W., and Cox, P.A., 2013, Is exposure to cyanobacteria an environmental risk factor for amyotrophic lateral sclerosis and other neurodegenerative diseases?: Amyotrophic Lateral Sclerosis and Frontotemporal Degeneration, v. 14, no. 5-6, p. 325-333, https://doi.org/10.3109/21678421.2012.750364.","productDescription":"9 p.","startPage":"325","endPage":"333","numberOfPages":"9","ipdsId":"IP-040918","costCenters":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"links":[{"id":278028,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":278027,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.3109/21678421.2012.750364"}],"volume":"14","issue":"5-6","noUsgsAuthors":false,"publicationDate":"2013-01-04","publicationStatus":"PW","scienceBaseUri":"5242a696e4b096ee624641cc","contributors":{"authors":[{"text":"Bradley, Walter G.","contributorId":64152,"corporation":false,"usgs":true,"family":"Bradley","given":"Walter","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":484459,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Borenstein, Amy R.","contributorId":66165,"corporation":false,"usgs":true,"family":"Borenstein","given":"Amy","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":484463,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nelson, Lorene M.","contributorId":64552,"corporation":false,"usgs":true,"family":"Nelson","given":"Lorene","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":484460,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Codd, Geoffrey A.","contributorId":8757,"corporation":false,"usgs":true,"family":"Codd","given":"Geoffrey","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":484458,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rosen, Barry H. 0000-0002-8016-3939 brosen@usgs.gov","orcid":"https://orcid.org/0000-0002-8016-3939","contributorId":2844,"corporation":false,"usgs":true,"family":"Rosen","given":"Barry","email":"brosen@usgs.gov","middleInitial":"H.","affiliations":[{"id":5064,"text":"Southeast Regional Director's Office","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":5078,"text":"Southwest Regional Director's Office","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":484457,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stommel, Elijah W.","contributorId":64992,"corporation":false,"usgs":true,"family":"Stommel","given":"Elijah","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":484461,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cox, Paul Alan","contributorId":64993,"corporation":false,"usgs":true,"family":"Cox","given":"Paul","email":"","middleInitial":"Alan","affiliations":[],"preferred":false,"id":484462,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70048369,"text":"70048369 - 2013 - Diel horizontal migration in streams: juvenile fish exploit spatial heterogeneity in thermal and trophic resources","interactions":[],"lastModifiedDate":"2013-09-24T10:36:00","indexId":"70048369","displayToPublicDate":"2013-09-24T10:23:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Diel horizontal migration in streams: juvenile fish exploit spatial heterogeneity in thermal and trophic resources","docAbstract":"Vertical heterogeneity in the physical characteristics of lakes and oceans is ecologically salient and exploited by a wide range of taxa through diel vertical migration to enhance their growth and survival. Whether analogous behaviors exploit horizontal habitat heterogeneity in streams is largely unknown. We investigated fish movement behavior at daily timescales to explore how individuals integrated across spatial variation in food abundance and water temperature. Juvenile coho salmon made feeding forays into cold habitats with abundant food, and then moved long distances (350–1300 m) to warmer habitats that accelerated their metabolism and increased their assimilative capacity. This behavioral thermoregulation enabled fish to mitigate trade-offs between trophic and thermal resources by exploiting thermal heterogeneity. Fish that exploited thermal heterogeneity grew at substantially faster rates than did individuals that assumed other behaviors. Our results provide empirical support for the importance of thermal diversity in lotic systems, and emphasize the importance of considering interactions between animal behavior and habitat heterogeneity when managing and restoring ecosystems.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ecology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"The Ecological Society of America","doi":"10.1890/12-1200.1","usgsCitation":"Armstrong, J., Schindler, D.E., Ruff, C.P., Brooks, G.T., Bentley, K., and Torgersen, C., 2013, Diel horizontal migration in streams: juvenile fish exploit spatial heterogeneity in thermal and trophic resources: Ecology, v. 94, no. 9, p. 2066-2075, https://doi.org/10.1890/12-1200.1.","productDescription":"10 p.","startPage":"2066","endPage":"2075","numberOfPages":"10","ipdsId":"IP-045091","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":278026,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":278023,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1890/12-1200.1"}],"country":"United States","state":"Alaska","otherGeospatial":"Wood River Watershed","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -159.4644,58.6596 ], [ -159.4644,59.7518 ], [ -156.6125,59.7518 ], [ -156.6125,58.6596 ], [ -159.4644,58.6596 ] ] ] } } ] }","volume":"94","issue":"9","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5242a694e4b096ee624641bc","contributors":{"authors":[{"text":"Armstrong, Jonathan B.","contributorId":98567,"corporation":false,"usgs":true,"family":"Armstrong","given":"Jonathan B.","affiliations":[],"preferred":false,"id":484456,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schindler, Daniel E.","contributorId":83485,"corporation":false,"usgs":true,"family":"Schindler","given":"Daniel","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":484455,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ruff, Casey P.","contributorId":13065,"corporation":false,"usgs":true,"family":"Ruff","given":"Casey","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":484451,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brooks, Gabriel T.","contributorId":27713,"corporation":false,"usgs":true,"family":"Brooks","given":"Gabriel","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":484452,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bentley, Kale E.","contributorId":60942,"corporation":false,"usgs":true,"family":"Bentley","given":"Kale E.","affiliations":[],"preferred":false,"id":484454,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Torgersen, Christian E. 0000-0001-8325-2737","orcid":"https://orcid.org/0000-0001-8325-2737","contributorId":48143,"corporation":false,"usgs":true,"family":"Torgersen","given":"Christian E.","affiliations":[],"preferred":false,"id":484453,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70046905,"text":"70046905 - 2013 - Identification of unrecognized tundra fire events on the north slope of Alaska","interactions":[],"lastModifiedDate":"2014-01-15T10:03:19","indexId":"70046905","displayToPublicDate":"2013-09-24T09:54:07","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2320,"text":"Journal of Geophysical Research: Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Identification of unrecognized tundra fire events on the north slope of Alaska","docAbstract":"Characteristics of the natural fire regime are poorly resolved in the Arctic, even though fire may play an important role cycling carbon stored in tundra vegetation and soils to the atmosphere. In the course of studying vegetation and permafrost-terrain characteristics along a chronosequence of tundra burn sites from AD 1977, 1993, and 2007 on the North Slope of Alaska, we discovered two large, previously unrecognized tundra fires. The Meade River fire burned an estimated 500 km2 and the Ketik River fire burned an estimated 1200 km2. Based on radiocarbon dating of charred twigs, analysis of historic aerial photography, and regional climate proxy data, these fires likely occurred between AD 1880 and 1920. Together, these events double the estimated burn area on the North Slope of Alaska over the last ~100 to 130 years. Assessment of vegetation succession along the century-scale chronosequence of tundra fire disturbances demonstrates for the first time on the North Slope of Alaska that tundra fires can facilitate the invasion of tundra by shrubs. Degradation of ice-rich permafrost was also evident at the fire sites and likely aided in the presumed changes of the tundra vegetation postfire. Other previously unrecognized tundra fire events likely exist in Alaska and other Arctic regions and identification of these sites is important for better understanding disturbance regimes and carbon cycling in Arctic tundra.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Geophysical Research: Biogeosciences","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Geophysical Union","publisherLocation":"Washington, D.C.","doi":"10.1002/jgrg.20113","usgsCitation":"Jones, B.M., Breen, A.L., Gaglioti, B.V., Mann, D.H., Rocha, A.V., Grosse, G., Arp, C.D., Kunz, M.L., and Walker, D.A., 2013, Identification of unrecognized tundra fire events on the north slope of Alaska: Journal of Geophysical Research: Biogeosciences, v. 118, no. 3, p. 1334-1344, https://doi.org/10.1002/jgrg.20113.","productDescription":"11 p.","startPage":"1334","endPage":"1344","numberOfPages":"11","ipdsId":"IP-046442","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":281070,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":281069,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/jgrg.20113"}],"country":"United States","state":"Alaska","otherGeospatial":"Meade River;North Slope","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -165.0,68.0 ], [ -165.0,71.75 ], [ -147.0,71.75 ], [ -147.0,68.0 ], [ -165.0,68.0 ] ] ] } } ] }","volume":"118","issue":"3","noUsgsAuthors":false,"publicationDate":"2013-09-24","publicationStatus":"PW","scienceBaseUri":"53cd61f1e4b0b290850fddc4","contributors":{"authors":[{"text":"Jones, Benjamin M. 0000-0002-1517-4711 bjones@usgs.gov","orcid":"https://orcid.org/0000-0002-1517-4711","contributorId":2286,"corporation":false,"usgs":true,"family":"Jones","given":"Benjamin","email":"bjones@usgs.gov","middleInitial":"M.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"preferred":true,"id":480584,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Breen, Amy L.","contributorId":81396,"corporation":false,"usgs":true,"family":"Breen","given":"Amy","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":480590,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gaglioti, Benjamin V. 0000-0003-0591-5253 bgaglioti@usgs.gov","orcid":"https://orcid.org/0000-0003-0591-5253","contributorId":4521,"corporation":false,"usgs":true,"family":"Gaglioti","given":"Benjamin","email":"bgaglioti@usgs.gov","middleInitial":"V.","affiliations":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":480585,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mann, Daniel H.","contributorId":67010,"corporation":false,"usgs":true,"family":"Mann","given":"Daniel","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":480589,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rocha, Adrian V.","contributorId":25433,"corporation":false,"usgs":true,"family":"Rocha","given":"Adrian","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":480587,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Grosse, Guido","contributorId":101475,"corporation":false,"usgs":true,"family":"Grosse","given":"Guido","affiliations":[{"id":34291,"text":"University of Potsdam, Germany","active":true,"usgs":false}],"preferred":false,"id":480592,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Arp, Christopher D.","contributorId":17330,"corporation":false,"usgs":false,"family":"Arp","given":"Christopher","email":"","middleInitial":"D.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":480586,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kunz, Michael L.","contributorId":50820,"corporation":false,"usgs":true,"family":"Kunz","given":"Michael","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":480588,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Walker, Donald A.","contributorId":100022,"corporation":false,"usgs":true,"family":"Walker","given":"Donald","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":480591,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70126613,"text":"70126613 - 2013 - Response of cackling geese (Branta hutchinsii taverneri to spatial and temporal variation in production of crowberries on the Alaska Peninsula","interactions":[],"lastModifiedDate":"2018-06-12T21:18:27","indexId":"70126613","displayToPublicDate":"2013-09-24T08:58:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3093,"text":"Polar Biology","active":true,"publicationSubtype":{"id":10}},"title":"Response of cackling geese (Branta hutchinsii taverneri to spatial and temporal variation in production of crowberries on the Alaska Peninsula","docAbstract":"Arctic geese often feed on berries during premigratory fattening. We hypothesized that during autumn staging on the Alaska Peninsula, the distribution of Taverne's cackling geese (Branta hutchinsii taverneri) would be correlated with spatial variation in crowberry (Empetrum nigrum) abundance. We also predicted that daily rates of fat increase among cackling geese would be higher in years when crowberries were abundant, compared to years when the crowberry crop was poor. Apparent distribution of geese based on fecal densities mirrored patterns of berry abundance, with areas that had highest densities of crowberries being used most heavily by geese. In areas where apparent use was greatest, geese consumed approximately 30 % of the berry crop between early September and mid-October. From 1999 to 2002, annual mean crowberry density in early September ranged from 205 berries m-2 (1999) to 12 berries m-2 (2002). Daily rates of lipid increase averaged 7.6 g day-1 for juvenile and 11.4 g-1 day for adult cackling geese and did not differ among years despite a >90 % difference in annual berry abundance. Although cackling geese used areas with higher densities of berries and apparently consumed a relatively large percentage of the crowberry crop, we could not detect an effect of annual variation in berry abundance on rates of fattening. Berries may have provided relatively little metabolizable biomass due to their high (90 %) water content. However, consumption of crowberries may provide geese with other physiological benefits such as water for osmoregulation or antioxidants and fatty acids that contribute to metabolic performance during migration.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Polar Biology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","doi":"10.1007/s00300-013-1343-3","usgsCitation":"Hupp, J.W., Safine, D.E., and Nielson, R.M., 2013, Response of cackling geese (Branta hutchinsii taverneri to spatial and temporal variation in production of crowberries on the Alaska Peninsula: Polar Biology, v. 36, no. 9, p. 1243-1255, https://doi.org/10.1007/s00300-013-1343-3.","productDescription":"13 p.","startPage":"1243","endPage":"1255","ipdsId":"IP-044787","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":294406,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":294404,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s00300-013-1343-3"},{"id":294405,"type":{"id":15,"text":"Index Page"},"url":"https://link.springer.com/article/10.1007/s00300-013-1343-3"}],"country":"United States","state":"Alaska","otherGeospatial":"Alaskan Peninsula","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -162.61,55.1 ], [ -162.61,59.78 ], [ -153.42,59.78 ], [ -153.42,55.1 ], [ -162.61,55.1 ] ] ] } } ] }","volume":"36","issue":"9","noUsgsAuthors":false,"publicationDate":"2013-05-30","publicationStatus":"PW","scienceBaseUri":"5423dd23e4b037b608f9d459","contributors":{"authors":[{"text":"Hupp, Jerry W. 0000-0002-6439-3910 jhupp@usgs.gov","orcid":"https://orcid.org/0000-0002-6439-3910","contributorId":127803,"corporation":false,"usgs":true,"family":"Hupp","given":"Jerry","email":"jhupp@usgs.gov","middleInitial":"W.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":502134,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Safine, David E.","contributorId":106820,"corporation":false,"usgs":true,"family":"Safine","given":"David","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":502136,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nielson, Ryan M.","contributorId":78971,"corporation":false,"usgs":false,"family":"Nielson","given":"Ryan","email":"","middleInitial":"M.","affiliations":[{"id":6660,"text":"Western EcoSystems Technology, Inc","active":true,"usgs":false}],"preferred":false,"id":502135,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70048365,"text":"ofr20131247 - 2013 - Habitat quality and recruitment success of cui-ui in the Truckee River downstream of Marble Bluff Dam, Pyramid Lake, Nevada","interactions":[],"lastModifiedDate":"2013-09-24T07:58:59","indexId":"ofr20131247","displayToPublicDate":"2013-09-24T07:29:37","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-1247","title":"Habitat quality and recruitment success of cui-ui in the Truckee River downstream of Marble Bluff Dam, Pyramid Lake, Nevada","docAbstract":"We compared cui-ui (Chasmistes cujus) recruitment from two reaches of the Truckee River with histories of severe erosional downcutting caused by a decline in Pyramid Lake surface elevation. In 1975, Marble Bluff Dam (MBD) was constructed 5 kilometers upstream of the extant mouth of the Truckee River to stabilize the upstream reach of the river; the downstream reach of the river remained unstable and consequently unsuitable for cui-ui recruitment. By the early 2000s, there was a decrease in the Truckee River’s slope from MBD to Pyramid Lake after a series of wet years in the 1990s. This was followed by changes in river morphology and erosion abatement. These changes led to the question as to cui-ui recruitment potential in the Truckee River downstream of MBD. In 2012, more than 7,000 cui-ui spawners were passed upstream of MBD, although an indeterminate number of cui-ui spawned downstream of MBD. In this study, we compared cui-ui recruitment upstream and downstream of MBD during a Truckee River low-flow year (2012). Cui-ui larvae emigration to Pyramid Lake began earlier and ended later downstream of MBD. A greater number of cui-ui larvae was produced downstream of MBD than upstream. This also was true for native Tahoe sucker (Catostomus tahoensis) and Lahontan redside (Richardsonius egregius). The improved Truckee River stability downstream of MBD and concomitant cui-ui recruitment success is attributed to a rise in Pyramid Lake's surface elevation. A decline in lake elevation may lead to a shift in stream morphology and substrate composition to the detriment of cui-ui reproductive success as well as the reproductive success of other native fishes.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131247","usgsCitation":"Scoppettone, G.G., Rissler, P.H., Salgado, J.A., and Harry, B., 2013, Habitat quality and recruitment success of cui-ui in the Truckee River downstream of Marble Bluff Dam, Pyramid Lake, Nevada: U.S. Geological Survey Open-File Report 2013-1247, iv, 22 p., https://doi.org/10.3133/ofr20131247.","productDescription":"iv, 22 p.","numberOfPages":"30","onlineOnly":"Y","ipdsId":"IP-049986","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":278020,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1247/"},{"id":278021,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1247/pdf/ofr2013-1247.pdf"},{"id":278022,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131247.png"}],"country":"United States","state":"Nevada","otherGeospatial":"Marble Bluff Dam;Pyramid Lake","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -119.70,39.84 ], [ -119.70,40.20 ], [ -119.41,40.20 ], [ -119.41,39.84 ], [ -119.70,39.84 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5242a695e4b096ee624641c8","contributors":{"authors":[{"text":"Scoppettone, G. Gary","contributorId":61137,"corporation":false,"usgs":true,"family":"Scoppettone","given":"G.","email":"","middleInitial":"Gary","affiliations":[],"preferred":false,"id":484434,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rissler, Peter H. peter_rissler@usgs.gov","contributorId":4508,"corporation":false,"usgs":true,"family":"Rissler","given":"Peter","email":"peter_rissler@usgs.gov","middleInitial":"H.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":484431,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Salgado, J. Antonio","contributorId":33214,"corporation":false,"usgs":true,"family":"Salgado","given":"J.","email":"","middleInitial":"Antonio","affiliations":[],"preferred":false,"id":484432,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Harry, Beverly","contributorId":38889,"corporation":false,"usgs":true,"family":"Harry","given":"Beverly","email":"","affiliations":[],"preferred":false,"id":484433,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70048364,"text":"70048364 - 2013 - Response of diatoms and silicoflagellates to climate change in the Santa Barbara Basin during the past 250 years and the rise of the toxic diatom Pseudo-nitzschia australis","interactions":[],"lastModifiedDate":"2013-09-23T16:19:07","indexId":"70048364","displayToPublicDate":"2013-09-23T16:08:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3217,"text":"Quaternary International","active":true,"publicationSubtype":{"id":10}},"title":"Response of diatoms and silicoflagellates to climate change in the Santa Barbara Basin during the past 250 years and the rise of the toxic diatom Pseudo-nitzschia australis","docAbstract":"Diatoms and silicoflagellate assemblages were examined in two year-increments of varved samples spanning the interval from 1748 through 2007 in Santa Barbara Basin (SBB) box core SBBC0806 to determine the timing and impact of possible 20th century warming on several different components of the plankton. Diatoms (Thalassionema nitzschioides =TN) and silicoflagellates (Distephanus speculum s.l. =DS) indicative of cooler waters and a shallow thermocline begin to decline in the 1920s and persistently compose a lower percentage of the assemblage in the SBB by about 1940. Prior to 1940, TN constituted on average ~30% of the Chaetoceros-free diatom sediment assemblage and DS on average ~36% of the silicoflagellate assemblage. Between 1940 and 1996 these relative abundances were ~20% (TN) and ~8% (DS). These results are consistent with results from planktonic foraminifera and radiolarians that indicate an influence of 20th century warming on marine ecosystems before most scientific observations began. Cooling of surface waters coincident with the one of the strongest La Niña events of the 20th century (and a return to negative PDO conditions) in late 1998 brought about a return to pre-1940 values of these cool water taxa (TN ~31%, DS ~25%). However, this recent regional cooling appears to have been accompanied by profound changes in the diatom assemblage. Pseudo-nitzschia australis, and Pseudo-nitzschia multiseries, diatom species associated with domoic acid, a neurotoxin that causes shellfish poisoning and marine mammal deaths, rapidly became dominant in the SBB sediment record at the time of the regional cooling (1999) and increased substantially in numbers as a bloom-forming taxon (relative to Chaetoceros spores) in 2003. Prior to 2003 diatom blooms recorded in the SBB sediment record consisted predominantly of Chaetoceros spores and less commonly of Rhizosolenia-related species (Neocalyptrella robusta and R. setigera). Fecal pellets dominated by valves of P. australis, however, were particularly abundant in both the 2003 and 2006 samples, coincident with recorded incidents of domoic acid increase and widespread shellfish poisoning in the SBB.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Quaternary International","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.quaint.2012.07.002","usgsCitation":"Barron, J.A., Bukry, D., Field, D.B., and Finney, B., 2013, Response of diatoms and silicoflagellates to climate change in the Santa Barbara Basin during the past 250 years and the rise of the toxic diatom Pseudo-nitzschia australis: Quaternary International, v. 310, p. 140-154, https://doi.org/10.1016/j.quaint.2012.07.002.","productDescription":"15 p.","startPage":"140","endPage":"154","ipdsId":"IP-039021","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":278019,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":278015,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.quaint.2012.07.002"}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -130.89,19.86 ], [ -130.89,50.03 ], [ -109.85,50.03 ], [ -109.85,19.86 ], [ -130.89,19.86 ] ] ] } } ] }","volume":"310","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"524154fbe4b0ec672f073abf","contributors":{"authors":[{"text":"Barron, John A. 0000-0002-9309-1145 jbarron@usgs.gov","orcid":"https://orcid.org/0000-0002-9309-1145","contributorId":2222,"corporation":false,"usgs":true,"family":"Barron","given":"John","email":"jbarron@usgs.gov","middleInitial":"A.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":484427,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bukry, David 0000-0003-4540-890X","orcid":"https://orcid.org/0000-0003-4540-890X","contributorId":30980,"corporation":false,"usgs":true,"family":"Bukry","given":"David","affiliations":[],"preferred":false,"id":484428,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Field, David B.","contributorId":77036,"corporation":false,"usgs":true,"family":"Field","given":"David","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":484430,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Finney, Bruce","contributorId":59715,"corporation":false,"usgs":true,"family":"Finney","given":"Bruce","affiliations":[],"preferred":false,"id":484429,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70048362,"text":"sir20135075 - 2013 - Ranking contributing areas of salt and selenium in the Lower Gunnison River Basin, Colorado, using multiple linear regression models","interactions":[],"lastModifiedDate":"2013-09-23T16:01:07","indexId":"sir20135075","displayToPublicDate":"2013-09-23T15:42:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-5075","title":"Ranking contributing areas of salt and selenium in the Lower Gunnison River Basin, Colorado, using multiple linear regression models","docAbstract":"Mitigating the effects of salt and selenium on water quality in the Grand Valley and lower Gunnison River Basin in western Colorado is a major concern for land managers. Previous modeling indicated means to improve the models by including more detailed geospatial data and a more rigorous method for developing the models. After evaluating all possible combinations of geospatial variables, four multiple linear regression models resulted that could estimate irrigation-season salt yield, nonirrigation-season salt yield, irrigation-season selenium yield, and nonirrigation-season selenium yield. The adjusted r-squared and the residual standard error (in units of log-transformed yield) of the models were, respectively, 0.87 and 2.03 for the irrigation-season salt model, 0.90 and 1.25 for the nonirrigation-season salt model, 0.85 and 2.94 for the irrigation-season selenium model, and 0.93 and 1.75 for the nonirrigation-season selenium model. The four models were used to estimate yields and loads from contributing areas corresponding to 12-digit hydrologic unit codes in the lower Gunnison River Basin study area. Each of the 175 contributing areas was ranked according to its estimated mean seasonal yield of salt and selenium.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135075","collaboration":"Prepared in cooperation with the Bureau of Reclamation and the Colorado River Water Conservation District","usgsCitation":"Linard, J.I., 2013, Ranking contributing areas of salt and selenium in the Lower Gunnison River Basin, Colorado, using multiple linear regression models: U.S. Geological Survey Scientific Investigations Report 2013-5075, v, 45 p., https://doi.org/10.3133/sir20135075.","productDescription":"v, 45 p.","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":278018,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135075.gif"},{"id":278016,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5075/pdf/SIR13-5075.pdf"},{"id":278017,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5075/"}],"country":"United States","state":"Colorado","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -109.0009,37.762 ], [ -109.0009,39.5273 ], [ -107.037,39.5273 ], [ -107.037,37.762 ], [ -109.0009,37.762 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"524154fae4b0ec672f073ab7","contributors":{"authors":[{"text":"Linard, Joshua I. jilinard@usgs.gov","contributorId":1465,"corporation":false,"usgs":true,"family":"Linard","given":"Joshua","email":"jilinard@usgs.gov","middleInitial":"I.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":484420,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70047159,"text":"70047159 - 2013 - Updating the planetary time scale: focus on Mars","interactions":[],"lastModifiedDate":"2013-10-30T11:22:11","indexId":"70047159","displayToPublicDate":"2013-09-23T13:48:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1238,"text":"Ciencias Da Terra","active":true,"publicationSubtype":{"id":10}},"title":"Updating the planetary time scale: focus on Mars","docAbstract":"Formal stratigraphic systems have been developed for the surface materials of the Moon, Mars, Mercury, and the Galilean satellite Ganymede. These systems are based on geologic mapping, which establishes relative ages of surfaces delineated by superposition, morphology, impact crater densities, and other relations and features. Referent units selected from the mapping determine time-stratigraphic bases and/or representative materials characteristic of events and periods for definition of chronologic units. Absolute ages of these units in some cases can be estimated using crater size-frequency data. For the Moon, the chronologic units and cratering record are calibrated by radiometric ages measured from samples collected from the lunar surface. Model ages for other cratered planetary surfaces are constructed primarily by estimating cratering rates relative to that of the Moon. Other cratered bodies with estimated surface ages include Venus and the Galilean satellites of Jupiter. New global geologic mapping and crater dating studies of Mars are resulting in more accurate and detailed reconstructions of its geologic history.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ciencias Da Terra","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Department of Earth Sciences Lisbon University","usgsCitation":"Tanaka, K.L., and Quantin-Nataf, C., 2013, Updating the planetary time scale: focus on Mars: Ciencias Da Terra.","ipdsId":"IP-044682","costCenters":[],"links":[{"id":278011,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":278012,"type":{"id":11,"text":"Document"},"url":"https://www.cienciasdaterra.com/index.php/vol/article/view/278"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"524154fce4b0ec672f073ac7","contributors":{"authors":[{"text":"Tanaka, Kenneth L. ktanaka@usgs.gov","contributorId":610,"corporation":false,"usgs":true,"family":"Tanaka","given":"Kenneth","email":"ktanaka@usgs.gov","middleInitial":"L.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":481187,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Quantin-Nataf, Cathy","contributorId":26615,"corporation":false,"usgs":true,"family":"Quantin-Nataf","given":"Cathy","email":"","affiliations":[],"preferred":false,"id":481188,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70048358,"text":"70048358 - 2013 - SSR_pipeline: a bioinformatic infrastructure for identifying microsatellites from paired-end Illumina high-throughput DNA sequencing data","interactions":[],"lastModifiedDate":"2013-10-23T14:54:22","indexId":"70048358","displayToPublicDate":"2013-09-23T12:51:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2333,"text":"Journal of Heredity","active":true,"publicationSubtype":{"id":10}},"title":"SSR_pipeline: a bioinformatic infrastructure for identifying microsatellites from paired-end Illumina high-throughput DNA sequencing data","docAbstract":"SSR_pipeline is a flexible set of programs designed to efficiently identify simple sequence repeats (e.g., microsatellites) from paired-end high-throughput Illumina DNA sequencing data. The program suite contains 3 analysis modules along with a fourth control module that can automate analyses of large volumes of data. The modules are used to 1) identify the subset of paired-end sequences that pass Illumina quality standards, 2) align paired-end reads into a single composite DNA sequence, and 3) identify sequences that possess microsatellites (both simple and compound) conforming to user-specified parameters. The microsatellite search algorithm is extremely efficient, and we have used it to identify repeats with motifs from 2 to 25bp in length. Each of the 3 analysis modules can also be used independently to provide greater flexibility or to work with FASTQ or FASTA files generated from other sequencing platforms (Roche 454, Ion Torrent, etc.). We demonstrate use of the program with data from the brine fly Ephydra packardi (Diptera: Ephydridae) and provide empirical timing benchmarks to illustrate program performance on a common desktop computer environment. We further show that the Illumina platform is capable of identifying large numbers of microsatellites, even when using unenriched sample libraries and a very small percentage of the sequencing capacity from a single DNA sequencing run. All modules from SSR_pipeline are implemented in the Python programming language and can therefore be used from nearly any computer operating system (Linux, Macintosh, and Windows).","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Heredity","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Oxford University Press","doi":"10.1093/jhered/est056","usgsCitation":"Miller, M.P., Knaus, B.J., Mullins, T., and Haig, S.M., 2013, SSR_pipeline: a bioinformatic infrastructure for identifying microsatellites from paired-end Illumina high-throughput DNA sequencing data: Journal of Heredity, v. 104, no. 6, p. 881-885, https://doi.org/10.1093/jhered/est056.","productDescription":"5 p.","startPage":"881","endPage":"885","numberOfPages":"5","ipdsId":"IP-046152","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":473525,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/jhered/est056","text":"Publisher Index Page"},{"id":278009,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":278006,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1093/jhered/est056"},{"id":278007,"type":{"id":15,"text":"Index Page"},"url":"https://jhered.oxfordjournals.org/cgi/content/full/est056?"}],"volume":"104","issue":"6","noUsgsAuthors":false,"publicationDate":"2013-09-19","publicationStatus":"PW","scienceBaseUri":"524154fce4b0ec672f073ac3","contributors":{"authors":[{"text":"Miller, Mark P. 0000-0003-1045-1772 mpmiller@usgs.gov","orcid":"https://orcid.org/0000-0003-1045-1772","contributorId":1967,"corporation":false,"usgs":true,"family":"Miller","given":"Mark","email":"mpmiller@usgs.gov","middleInitial":"P.","affiliations":[{"id":38131,"text":"WMA - Office of Planning and Programming","active":true,"usgs":true}],"preferred":true,"id":484413,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Knaus, Brian J.","contributorId":107167,"corporation":false,"usgs":true,"family":"Knaus","given":"Brian","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":484415,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mullins, Thomas D.","contributorId":12819,"corporation":false,"usgs":true,"family":"Mullins","given":"Thomas D.","affiliations":[],"preferred":false,"id":484414,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Haig, Susan M. 0000-0002-6616-7589 susan_haig@usgs.gov","orcid":"https://orcid.org/0000-0002-6616-7589","contributorId":719,"corporation":false,"usgs":true,"family":"Haig","given":"Susan","email":"susan_haig@usgs.gov","middleInitial":"M.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":484412,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70048350,"text":"70048350 - 2013 - A fluid-driven earthquake swarm on the margin of the Yellowstone caldera","interactions":[],"lastModifiedDate":"2016-12-14T11:36:52","indexId":"70048350","displayToPublicDate":"2013-09-23T11:56:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2314,"text":"Journal of Geophysical Research B: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"A fluid-driven earthquake swarm on the margin of the Yellowstone caldera","docAbstract":"Over the past several decades, the Yellowstone caldera has experienced frequent earthquake swarms and repeated cycles of uplift and subsidence, reflecting dynamic volcanic and tectonic processes. Here, we examine the detailed spatial-temporal evolution of the 2010 Madison Plateau swarm, which occurred near the northwest boundary of the Yellowstone caldera. To fully explore the evolution of the swarm, we integrated procedures for seismic waveform-based earthquake detection with precise double-difference relative relocation. Using cross-correlation of continuous seismic data and waveform templates constructed from cataloged events, we detected and precisely located 8710 earthquakes during the three-week swarm, nearly four times the number of events included in the standard catalog. This high-resolution analysis reveals distinct migration of earthquake activity over the course of the swarm. The swarm initiated abruptly on January 17, 2010 at about 10 km depth and expanded dramatically outward (both shallower and deeper) over time, primarily along a NNW-striking, ~55º ENE-dipping structure. To explain these characteristics, we hypothesize that the swarm was triggered by the rupture of a zone of confined high-pressure aqueous fluids into a pre-existing crustal fault system, prompting release of accumulated stress. The high-pressure fluid injection may have been accommodated by hybrid shear and dilatational failure, as is commonly observed in exhumed hydrothermally affected fault zones. This process has likely occurred repeatedly in Yellowstone as aqueous fluids exsolved from magma migrate into the brittle crust, and it may be a key element in the observed cycles of caldera uplift and subsidence.","language":"English","publisher":"AGU Publications","doi":"10.1002/jgrb.50362","usgsCitation":"Shelly, D.R., Hill, D.P., Massin, F., Farrell, J., Smith, R.B., and Taira, T., 2013, A fluid-driven earthquake swarm on the margin of the Yellowstone caldera: Journal of Geophysical Research B: Solid Earth, v. 118, no. 9, p. 4872-4886, https://doi.org/10.1002/jgrb.50362.","productDescription":"15 p.","startPage":"4872","endPage":"4886","numberOfPages":"15","ipdsId":"IP-049594","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":473527,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/jgrb.50362","text":"Publisher Index Page"},{"id":278008,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":277990,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/jgrb.50362"}],"country":"United States","state":"Wyoming","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -111.196747,44.199436 ], [ -111.196747,44.999767 ], [ -110.199051,44.999767 ], [ -110.199051,44.199436 ], [ -111.196747,44.199436 ] ] ] } } ] }","volume":"118","issue":"9","noUsgsAuthors":false,"publicationDate":"2013-09-16","publicationStatus":"PW","scienceBaseUri":"524154cfe4b0ec672f073aa7","contributors":{"authors":[{"text":"Shelly, David R. dshelly@usgs.gov","contributorId":2978,"corporation":false,"usgs":true,"family":"Shelly","given":"David","email":"dshelly@usgs.gov","middleInitial":"R.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":484369,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hill, David P. hill@usgs.gov","contributorId":2600,"corporation":false,"usgs":true,"family":"Hill","given":"David","email":"hill@usgs.gov","middleInitial":"P.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":false,"id":484368,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Massin, Frederick","contributorId":27351,"corporation":false,"usgs":true,"family":"Massin","given":"Frederick","email":"","affiliations":[],"preferred":false,"id":484370,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Farrell, Jamie","contributorId":100280,"corporation":false,"usgs":true,"family":"Farrell","given":"Jamie","affiliations":[],"preferred":false,"id":484373,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Smith, Robert B.","contributorId":90824,"corporation":false,"usgs":true,"family":"Smith","given":"Robert","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":484372,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Taira, Taka'aki","contributorId":63302,"corporation":false,"usgs":true,"family":"Taira","given":"Taka'aki","affiliations":[],"preferred":false,"id":484371,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70048355,"text":"70048355 - 2013 - Baseline monitoring of the western Arctic Ocean estimates 20% of the Canadian Basin surface waters are undersaturated with respect to aragonite","interactions":[],"lastModifiedDate":"2016-09-22T12:36:32","indexId":"70048355","displayToPublicDate":"2013-09-23T11:31:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Baseline monitoring of the western Arctic Ocean estimates 20% of the Canadian Basin surface waters are undersaturated with respect to aragonite","docAbstract":"Marine surface waters are being acidified due to uptake of anthropogenic carbon dioxide, resulting in surface ocean areas of undersaturation with respect to carbonate minerals, including aragonite. In the Arctic Ocean, acidification is expected to occur at an accelerated rate with respect to the global oceans, but a paucity of baseline data has limited our understanding of the extent of Arctic undersaturation and of regional variations in rates and causes. The lack of data has also hindered refinement of models aimed at projecting future trends of ocean acidification. Here, based on more than 34,000 data records collected in 2010 and 2011, we establish a baseline of inorganic carbon data (pH, total alkalinity, dissolved inorganic carbon, partial pressure of carbon dioxide, and aragonite saturation index) for the western Arctic Ocean. This data set documents aragonite undersaturation in ~20% of the surface waters of the combined Canada and Makarov basins, an area characterized by recent acceleration of sea ice loss. Conservative tracer studies using stable oxygen isotopic data from 307 sites show that while the entire surface of this area receives abundant freshwater from meteoric sources, freshwater from sea ice melt is most closely linked to the areas of carbonate mineral undersaturation. These data link the Arctic Ocean’s largest area of aragonite undersaturation to sea ice melt and atmospheric CO2 absorption in areas of low buffering capacity. Some relatively supersaturated areas can be linked to localized biological activity. Collectively, these observations can be used to project trends of ocean acidification in higher latitude marine surface waters where inorganic carbon chemistry is largely influenced by sea ice meltwater.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"PLoS ONE","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"PLOS ONE","doi":"10.1371/journal.pone.0073796","usgsCitation":"Robbins, L.L., Wynn, J.G., Lisle, J.T., Yates, K.K., Knorr, P.O., Byrne, R., Liu, X., Patsavas, M.C., Azetsu-Scott, K., and Takahashi, T., 2013, Baseline monitoring of the western Arctic Ocean estimates 20% of the Canadian Basin surface waters are undersaturated with respect to aragonite: PLoS ONE, v. 8, no. 9, 15 p., https://doi.org/10.1371/journal.pone.0073796.","productDescription":"15 p.","numberOfPages":"15","ipdsId":"IP-036765","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":473528,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0073796","text":"Publisher Index Page"},{"id":278003,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":277996,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1371/journal.pone.0073796"}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -166.9,66.5 ], [ -166.9,77.3 ], [ -105.2,77.3 ], [ -105.2,66.5 ], [ -166.9,66.5 ] ] ] } } ] }","volume":"8","issue":"9","noUsgsAuthors":false,"publicationDate":"2013-09-11","publicationStatus":"PW","scienceBaseUri":"524154f9e4b0ec672f073aaf","contributors":{"authors":[{"text":"Robbins, Lisa L. 0000-0003-3681-1094 lrobbins@usgs.gov","orcid":"https://orcid.org/0000-0003-3681-1094","contributorId":422,"corporation":false,"usgs":true,"family":"Robbins","given":"Lisa","email":"lrobbins@usgs.gov","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":484396,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wynn, Jonathan G.","contributorId":92960,"corporation":false,"usgs":true,"family":"Wynn","given":"Jonathan","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":484403,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lisle, John T. 0000-0002-5447-2092 jlisle@usgs.gov","orcid":"https://orcid.org/0000-0002-5447-2092","contributorId":2944,"corporation":false,"usgs":true,"family":"Lisle","given":"John","email":"jlisle@usgs.gov","middleInitial":"T.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":484397,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Yates, Kimberly K. 0000-0001-8764-0358 kyates@usgs.gov","orcid":"https://orcid.org/0000-0001-8764-0358","contributorId":420,"corporation":false,"usgs":true,"family":"Yates","given":"Kimberly","email":"kyates@usgs.gov","middleInitial":"K.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":484395,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Knorr, Paul O. pknorr@usgs.gov","contributorId":3691,"corporation":false,"usgs":true,"family":"Knorr","given":"Paul","email":"pknorr@usgs.gov","middleInitial":"O.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":484398,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Byrne, Robert H.","contributorId":83260,"corporation":false,"usgs":true,"family":"Byrne","given":"Robert H.","affiliations":[],"preferred":false,"id":484401,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Liu, Xuewu","contributorId":87676,"corporation":false,"usgs":true,"family":"Liu","given":"Xuewu","email":"","affiliations":[],"preferred":false,"id":484402,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Patsavas, Mark C.","contributorId":99881,"corporation":false,"usgs":true,"family":"Patsavas","given":"Mark","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":484404,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Azetsu-Scott, Kumiko","contributorId":78636,"corporation":false,"usgs":true,"family":"Azetsu-Scott","given":"Kumiko","email":"","affiliations":[],"preferred":false,"id":484400,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Takahashi, Taro","contributorId":55319,"corporation":false,"usgs":true,"family":"Takahashi","given":"Taro","email":"","affiliations":[],"preferred":false,"id":484399,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70048351,"text":"70048351 - 2013 - Regional signatures of plant response to drought and elevated temperature across a desert ecosystem","interactions":[],"lastModifiedDate":"2013-10-30T11:33:16","indexId":"70048351","displayToPublicDate":"2013-09-23T10:56:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Regional signatures of plant response to drought and elevated temperature across a desert ecosystem","docAbstract":"The performance of many desert plant species in North America may decline with the warmer and drier conditions predicted by climate change models, thereby accelerating land degradation and reducing ecosystem productivity. We paired repeat measurements of plant canopy cover with climate at multiple sites across the Chihuahuan Desert over the last century to determine which plant species and functional types may be the most sensitive to climate change. We found that the dominant perennial grass, Bouteloua eriopoda, and species richness had nonlinear responses to summer precipitation, decreasing more in dry summers than increasing with wet summers. Dominant shrub species responded differently to the seasonality of precipitation and drought, but winter precipitation best explained changes in the cover of woody vegetation in upland grasslands and may contribute to woody-plant encroachment that is widespread throughout the southwestern United States and northern Mexico. Temperature explained additional variability of changes in cover of dominant and subdominant plant species. Using a novel empirically based approach we identified ‘‘climate pivot points’’ that were indicative of shifts from increasing to decreasing plant cover over a range of climatic conditions. Reductions in cover of annual and several perennial plant species, in addition to declines in species richness below the long-term summer precipitation mean across plant communities, indicate a decrease in the productivity for all but the most drought-tolerant perennial grasses and shrubs in the Chihuahuan Desert. Overall, our regional synthesis of long-term data provides a robust foundation for forecasting future shifts in the composition and structure of plant assemblages in the largest North American warm desert.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ecology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Ecological Society of America","doi":"10.1890/12-1586.1","usgsCitation":"Munson, S.M., Muldavin, E.H., Belnap, J., Peters, D.P., Anderson, J.P., Reiser, M.H., Gallo, K., Melgoza-Castillo, A., Herrick, J.E., and Christiansen, T.A., 2013, Regional signatures of plant response to drought and elevated temperature across a desert ecosystem: Ecology, v. 94, no. 9, p. 2030-2041, https://doi.org/10.1890/12-1586.1.","productDescription":"12 p.","startPage":"2030","endPage":"2041","numberOfPages":"12","ipdsId":"IP-040978","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":277998,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":277991,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1890/12-1586.1"}],"volume":"94","issue":"9","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"524154fbe4b0ec672f073abb","contributors":{"authors":[{"text":"Munson, Seth M. 0000-0002-2736-6374 smunson@usgs.gov","orcid":"https://orcid.org/0000-0002-2736-6374","contributorId":1334,"corporation":false,"usgs":true,"family":"Munson","given":"Seth","email":"smunson@usgs.gov","middleInitial":"M.","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":484375,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Muldavin, Esteban H.","contributorId":88260,"corporation":false,"usgs":true,"family":"Muldavin","given":"Esteban","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":484383,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Belnap, Jayne 0000-0001-7471-2279 jayne_belnap@usgs.gov","orcid":"https://orcid.org/0000-0001-7471-2279","contributorId":1332,"corporation":false,"usgs":true,"family":"Belnap","given":"Jayne","email":"jayne_belnap@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":484374,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Peters, Debra P.C.","contributorId":81007,"corporation":false,"usgs":true,"family":"Peters","given":"Debra","email":"","middleInitial":"P.C.","affiliations":[],"preferred":false,"id":484381,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Anderson, John P.","contributorId":23060,"corporation":false,"usgs":true,"family":"Anderson","given":"John","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":484376,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Reiser, M. Hildegard","contributorId":38465,"corporation":false,"usgs":true,"family":"Reiser","given":"M.","email":"","middleInitial":"Hildegard","affiliations":[],"preferred":false,"id":484378,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gallo, Kirsten","contributorId":82414,"corporation":false,"usgs":true,"family":"Gallo","given":"Kirsten","email":"","affiliations":[],"preferred":false,"id":484382,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Melgoza-Castillo, Alicia","contributorId":76639,"corporation":false,"usgs":true,"family":"Melgoza-Castillo","given":"Alicia","email":"","affiliations":[],"preferred":false,"id":484380,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Herrick, Jeffrey E.","contributorId":26054,"corporation":false,"usgs":false,"family":"Herrick","given":"Jeffrey","email":"","middleInitial":"E.","affiliations":[{"id":12627,"text":"USDA-ARS Jornada Experimental Range, New Mexico State University, Las Cruces, NM 88003-8003, USA","active":true,"usgs":false}],"preferred":false,"id":484377,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Christiansen, Tim A.","contributorId":64550,"corporation":false,"usgs":true,"family":"Christiansen","given":"Tim","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":484379,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70048325,"text":"70048325 - 2013 - A scenario and forecast model for Gulf of Mexico hypoxic area and volume","interactions":[],"lastModifiedDate":"2013-10-30T11:34:09","indexId":"70048325","displayToPublicDate":"2013-09-23T09:22:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"A scenario and forecast model for Gulf of Mexico hypoxic area and volume","docAbstract":"For almost three decades, the relative size of the hypoxic region on the Louisiana-Texas continental shelf has drawn scientific and policy attention. During that time, both simple and complex models have been used to explore hypoxia dynamics and to provide management guidance relating the size of the hypoxic zone to key drivers. Throughout much of that development, analyses had to accommodate an apparent change in hypoxic sensitivity to loads and often cull observations due to anomalous meteorological conditions. Here, we describe an adaptation of our earlier, simple biophysical model, calibrated to revised hypoxic area estimates and new hypoxic volume estimates through Bayesian estimation. This application eliminates the need to cull observations and provides revised hypoxic extent estimates with uncertainties, corresponding to different nutrient loading reduction scenarios. We compare guidance from this model application, suggesting an approximately 62% nutrient loading reduction is required to reduce Gulf hypoxia to the Action Plan goal of 5,000 km2, to that of previous applications. In addition, we describe for the first time, the corresponding response of hypoxic volume. We also analyze model results to test for increasing system sensitivity to hypoxia formation, but find no strong evidence of such change.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Environmental Science and Technology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"ACS Publications","doi":"10.1021/es4025035","usgsCitation":"Scavia, D., Evans, M.A., and Obenour, D.R., 2013, A scenario and forecast model for Gulf of Mexico hypoxic area and volume: Environmental Science & Technology, v. 47, no. 18, 6 p., https://doi.org/10.1021/es4025035.","productDescription":"6 p.","numberOfPages":"6","ipdsId":"IP-048828","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":277995,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":277970,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1021/es4025035"}],"volume":"47","issue":"18","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"524154f9e4b0ec672f073aab","contributors":{"authors":[{"text":"Scavia, Donald","contributorId":19068,"corporation":false,"usgs":true,"family":"Scavia","given":"Donald","affiliations":[],"preferred":false,"id":484320,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Evans, Mary Anne 0000-0002-1627-7210 maevans@usgs.gov","orcid":"https://orcid.org/0000-0002-1627-7210","contributorId":4883,"corporation":false,"usgs":true,"family":"Evans","given":"Mary","email":"maevans@usgs.gov","middleInitial":"Anne","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":484319,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Obenour, Daniel R.","contributorId":66588,"corporation":false,"usgs":true,"family":"Obenour","given":"Daniel","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":484321,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70048352,"text":"70048352 - 2013 - Characterizing regional soil mineral composition using spectroscopyand geostatistics","interactions":[],"lastModifiedDate":"2013-09-23T09:12:42","indexId":"70048352","displayToPublicDate":"2013-09-23T09:07:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"Characterizing regional soil mineral composition using spectroscopyand geostatistics","docAbstract":"This work aims at improving the mapping of major mineral variability at regional scale using scale-dependent spatial variability observed in remote sensing data. Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data and statistical methods were combined with laboratory-based mineral characterization of field samples to create maps of the distributions of clay, mica and carbonate minerals and their abundances. The Material Identification and Characterization Algorithm (MICA) was used to identify the spectrally-dominant minerals in field samples; these results were combined with ASTER data using multinomial logistic regression to map mineral distributions. X-ray diffraction (XRD)was used to quantify mineral composition in field samples. XRD results were combined with ASTER data using multiple linear regression to map mineral abundances. We testedwhether smoothing of the ASTER data to match the scale of variability of the target sample would improve model correlations. Smoothing was donewith Fixed Rank Kriging (FRK) to represent the mediumand long-range spatial variability in the ASTER data. Stronger correlations resulted using the smoothed data compared to results obtained with the original data. Highest model accuracies came from using both medium and long-range scaled ASTER data as input to the statistical models. High correlation coefficients were obtained for the abundances of calcite and mica (R2 = 0.71 and 0.70, respectively). Moderately-high correlation coefficients were found for smectite and kaolinite (R2 = 0.57 and 0.45, respectively). Maps of mineral distributions, obtained by relating ASTER data to MICA analysis of field samples, were found to characterize major soil mineral variability (overall accuracies for mica, smectite and kaolinite were 76%, 89% and 86% respectively). The results of this study suggest that the distributions of minerals and their abundances derived using FRK-smoothed ASTER data more closely match the spatial variability of soil and environmental properties at regional scale.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Remote Sensing of Environment","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2013.08.018","usgsCitation":"Mulder, V., de Bruin, S., Weyermann, J., Kokaly, R., and Schaepman, M., 2013, Characterizing regional soil mineral composition using spectroscopyand geostatistics: Remote Sensing of Environment, v. 139, no. December 2013, p. 415-429, https://doi.org/10.1016/j.rse.2013.08.018.","productDescription":"15 p.","startPage":"415","endPage":"429","numberOfPages":"15","ipdsId":"IP-049662","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":488159,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://zenodo.org/record/3422237","text":"External Repository"},{"id":277994,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":277992,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.rse.2013.08.018"}],"volume":"139","issue":"December 2013","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"524154fae4b0ec672f073ab3","contributors":{"authors":[{"text":"Mulder, V.L.","contributorId":12764,"corporation":false,"usgs":true,"family":"Mulder","given":"V.L.","email":"","affiliations":[],"preferred":false,"id":484385,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"de Bruin, S.","contributorId":49693,"corporation":false,"usgs":true,"family":"de Bruin","given":"S.","affiliations":[],"preferred":false,"id":484386,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Weyermann, J.","contributorId":9564,"corporation":false,"usgs":true,"family":"Weyermann","given":"J.","email":"","affiliations":[],"preferred":false,"id":484384,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kokaly, Raymond F. 0000-0003-0276-7101","orcid":"https://orcid.org/0000-0003-0276-7101","contributorId":81442,"corporation":false,"usgs":true,"family":"Kokaly","given":"Raymond F.","affiliations":[],"preferred":false,"id":484388,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schaepman, M.E.","contributorId":66466,"corporation":false,"usgs":true,"family":"Schaepman","given":"M.E.","email":"","affiliations":[],"preferred":false,"id":484387,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70048327,"text":"70048327 - 2013 - On the absolute calibration of SO2 cameras","interactions":[],"lastModifiedDate":"2013-09-23T11:20:15","indexId":"70048327","displayToPublicDate":"2013-09-22T11:05:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":926,"text":"Atmospheric Measurement Techniques","active":true,"publicationSubtype":{"id":10}},"title":"On the absolute calibration of SO2 cameras","docAbstract":"Sulphur dioxide emission rate measurements are an important tool for volcanic monitoring and eruption risk assessment. The SO2 camera technique remotely measures volcanic emissions by analysing the ultraviolet absorption of SO2 in a narrow spectral window between 300 and 320 nm using solar radiation scattered in the atmosphere. The SO2 absorption is selectively detected by mounting band-pass interference filters in front of a two-dimensional, UV-sensitive CCD detector. One important step for correct SO2 emission rate measurements that can be compared with other measurement techniques is a correct calibration. This requires conversion from the measured optical density to the desired SO2 column density (CD). The conversion factor is most commonly determined by inserting quartz cells (cuvettes) with known amounts of SO2 into the light path. Another calibration method uses an additional narrow field-of-view Differential Optical Absorption Spectroscopy system (NFOVDOAS), which measures the column density simultaneously in a small area of the camera’s field-of-view. This procedure combines the very good spatial and temporal resolution of the SO2 camera technique with the more accurate column densities obtainable from DOAS measurements.\nThis work investigates the uncertainty of results gained through the two commonly used, but quite different, calibration methods (DOAS and calibration cells). Measurements with three different instruments, an SO2 camera, a NFOVDOAS system and an Imaging DOAS (I-DOAS), are presented. We compare the calibration-cell approach with the calibration from the NFOV-DOAS system. The respective results are compared with measurements from an I-DOAS to verify the calibration curve over the spatial extent of the image. The results show that calibration cells, while working fine in some cases, can lead to an overestimation of the SO2 CD by up to 60% compared with CDs from the DOAS measurements. Besides these errors of calibration, radiative transfer effects (e.g. light dilution, multiple scattering) can significantly influence the results of both instrument types. The measurements presented in this work were taken at Popocatepetl, Mexico, between 1 March 2011 and 4 March 2011. Average SO2 emission rates between 4.00 and 14.34 kg s−1 were observed.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Atmospheric Measurement Techniques","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Atmospheric Measurement Techniques","doi":"10.5194/amt-6-677-2013","usgsCitation":"Lubcke, P., Bobrowski, N., Illing, S., Kern, C., Alvarez Nieves, J.M., Vogel, L., Zielcke, J., Delgados Granados, H., and Platt, U., 2013, On the absolute calibration of SO2 cameras: Atmospheric Measurement Techniques, v. 6, p. 677-696, https://doi.org/10.5194/amt-6-677-2013.","productDescription":"20 p.","startPage":"677","endPage":"696","numberOfPages":"20","ipdsId":"IP-042811","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":473530,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/amt-6-677-2013","text":"Publisher Index Page"},{"id":278000,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":277999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.5194/amt-6-677-2013"}],"volume":"6","noUsgsAuthors":false,"publicationDate":"2013-03-14","publicationStatus":"PW","scienceBaseUri":"524162e7e4b0ec672f073af2","contributors":{"authors":[{"text":"Lubcke, Peter","contributorId":56141,"corporation":false,"usgs":false,"family":"Lubcke","given":"Peter","email":"","affiliations":[],"preferred":false,"id":484333,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bobrowski, Nicole","contributorId":45214,"corporation":false,"usgs":true,"family":"Bobrowski","given":"Nicole","email":"","affiliations":[],"preferred":false,"id":484332,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Illing, Sebastian","contributorId":24676,"corporation":false,"usgs":true,"family":"Illing","given":"Sebastian","email":"","affiliations":[],"preferred":false,"id":484328,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kern, Christoph 0000-0002-8920-5701 ckern@usgs.gov","orcid":"https://orcid.org/0000-0002-8920-5701","contributorId":3387,"corporation":false,"usgs":true,"family":"Kern","given":"Christoph","email":"ckern@usgs.gov","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":484327,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Alvarez Nieves, Jose Manuel","contributorId":90199,"corporation":false,"usgs":true,"family":"Alvarez Nieves","given":"Jose","email":"","middleInitial":"Manuel","affiliations":[],"preferred":false,"id":484334,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Vogel, Leif","contributorId":37632,"corporation":false,"usgs":true,"family":"Vogel","given":"Leif","email":"","affiliations":[],"preferred":false,"id":484331,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Zielcke, Johannes","contributorId":107599,"corporation":false,"usgs":true,"family":"Zielcke","given":"Johannes","email":"","affiliations":[],"preferred":false,"id":484335,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Delgados Granados, Hugo","contributorId":32439,"corporation":false,"usgs":true,"family":"Delgados Granados","given":"Hugo","email":"","affiliations":[],"preferred":false,"id":484330,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Platt, Ulrich","contributorId":26609,"corporation":false,"usgs":true,"family":"Platt","given":"Ulrich","affiliations":[],"preferred":false,"id":484329,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70048337,"text":"sir20135168 - 2013 - Recent (circa 1998 to 2011) channel-migration rates of selected streams in Indiana","interactions":[],"lastModifiedDate":"2013-09-20T14:31:03","indexId":"sir20135168","displayToPublicDate":"2013-09-20T14:13:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-5168","title":"Recent (circa 1998 to 2011) channel-migration rates of selected streams in Indiana","docAbstract":"An investigation was completed to document recent (circa 1998 to 2011) channel-migration rates at 970 meander bends along 38 of the largest streams in Indiana. Data collection was completed by using the Google Earth™ platform and, for each selected site, identifying two images with capture dates separated by multiple years. Within each image, the position of the meander-bend cutbank was measured relative to a fixed local landscape feature visible in both images, and an average channel-migration rate was calculated at the point of maximum cutbank displacement. From these data it was determined that 65 percent of the measured sites have recently been migrating at a rate less than 1 ft/yr, 75 percent of the sites have been migrating at a rate less than 10 ft/yr, and while some sites are migrating in excess of 20 ft/yr, these occurrences are rare. In addition, it is shown that recent channel-migration activity is not evenly distributed across Indiana. For the stream reaches studied, far northern and much of far southern Indiana are drained by streams that recently have been relatively stationary. At the same time, this study shows that most of the largest streams in west-central Indiana and many of the largest streams in east-central Indiana have shown significant channel-migration activity during the recent past. It is anticipated that these results will support several fluvial-erosion-hazard mitigation activities currently being undertaken in Indiana.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135168","collaboration":"Prepared in cooperation with the Indiana Office of Community and Rural Affairs","usgsCitation":"Robinson, B.A., 2013, Recent (circa 1998 to 2011) channel-migration rates of selected streams in Indiana: U.S. Geological Survey Scientific Investigations Report 2013-5168, iv, 37 p., https://doi.org/10.3133/sir20135168.","productDescription":"iv, 37 p.","numberOfPages":"46","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"1998-01-01","temporalEnd":"2011-12-31","costCenters":[{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":277979,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135168.gif"},{"id":277980,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5168/"},{"id":277981,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5168/pdf/sir2013-5168.pdf"}],"scale":"100000","projection":"1983 Universal Transverse Mercator","datum":"North American Datum 1983","country":"United States","state":"Indiana","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -88.0997,37.7717 ], [ -88.0997,41.7614 ], [ -84.7846,41.7614 ], [ -84.7846,37.7717 ], [ -88.0997,37.7717 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"523d6bade4b097188d6c769e","contributors":{"authors":[{"text":"Robinson, Bret A. barobins@usgs.gov","contributorId":3897,"corporation":false,"usgs":true,"family":"Robinson","given":"Bret","email":"barobins@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":484349,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70048334,"text":"sir20105070H - 2013 - Nickel-cobalt laterites: a deposit model","interactions":[],"lastModifiedDate":"2022-12-13T17:11:43.972738","indexId":"sir20105070H","displayToPublicDate":"2013-09-20T13:48:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2010-5070","chapter":"H","title":"Nickel-cobalt laterites: a deposit model","docAbstract":"Nickel-cobalt (Ni-Co) laterite deposits are supergene enrichments of Ni±Co that form from intense chemical and mechanical weathering of ultramafic parent rocks. These regolith deposits typically form within 26 degrees of the equator, although there are a few exceptions. They form in active continental margins and stable cratonic settings. It takes as little as one million years for a laterite profile to develop. Three subtypes of Ni-Co laterite deposits are classified according to the dominant Ni-bearing mineralogy, which include hydrous magnesium (Mg)-silicate, smectite, and oxide. These minerals form in weathering horizons that begin with the unweathered protolith at the base, saprolite next, a smectite transition zone only in profiles where drainage is very poor, followed by limonite, and then capped with ferricrete at the top. The saprolite contains Ni-rich hydrous Mg-silicates, the Ni-rich clays occur in the transition horizon, and Ni-rich goethite occurs in the limonite. Although these subtypes of deposits are the more widely used terms for classification of Ni-Co laterite deposits, most deposits have economic concentrations of Ni in more than one horizon. Because of their complex mineralogy and heterogeneous concentrations, mining of these metallurgically complex deposits can be challenging. Deposits range in size from 2.5 to about 400 million tonnes, with Ni and Co grades of 0.66–2.4 percent (median 1.3) and 0.01–0.15 percent (median 0.08), respectively. Modern techniques of ore delineation and mineralogical identification are being developed to aid in streamlining the Ni-Co laterite mining process, and low-temperature and low-pressure ore processing techniques are being tested that will treat the entire weathered profile. There is evidence that the production of Ni and Co from laterites is more energy intensive than that of sulfide ores, reflecting the environmental impact of producing a Ni-Co laterite deposit. Tailings may include high levels of magnesium, sulfate, and manganese and have the potential to be physically unstable.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Mineral deposit models for resource assessment (Scientific Investigations Report 2010-5070)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20105070H","usgsCitation":"Marsh, E.E., Anderson, E.D., and Gray, F., 2013, Nickel-cobalt laterites: a deposit model: U.S. Geological Survey Scientific Investigations Report 2010-5070, vii, 38 p., https://doi.org/10.3133/sir20105070H.","productDescription":"vii, 38 p.","numberOfPages":"49","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":277977,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20105070H.png"},{"id":277975,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2010/5070/h/","linkFileType":{"id":5,"text":"html"}},{"id":277976,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2010/5070/h/pdf/SIR10-5070-H.pdf","text":"Report","size":"6.19 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"523d6bade4b097188d6c7696","contributors":{"authors":[{"text":"Marsh, Erin E. 0000-0001-5245-9532 emarsh@usgs.gov","orcid":"https://orcid.org/0000-0001-5245-9532","contributorId":1250,"corporation":false,"usgs":true,"family":"Marsh","given":"Erin","email":"emarsh@usgs.gov","middleInitial":"E.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":484346,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, Eric D. 0000-0002-0138-6166 ericanderson@usgs.gov","orcid":"https://orcid.org/0000-0002-0138-6166","contributorId":1733,"corporation":false,"usgs":true,"family":"Anderson","given":"Eric","email":"ericanderson@usgs.gov","middleInitial":"D.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":484347,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gray, Floyd 0000-0002-0223-8966 fgray@usgs.gov","orcid":"https://orcid.org/0000-0002-0223-8966","contributorId":603,"corporation":false,"usgs":true,"family":"Gray","given":"Floyd","email":"fgray@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":662,"text":"Western Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":484345,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ]}