As the only extant deepwater cisco in Lake Michigan, bloater is currently at record low levels of abundance. Several mechanisms to regulate their recruitment have been proposed, including skewed sex ratios, predation on their larvae by adult alewife, and climatic factors during early life history stages, but none has unequivocal support. In this research, we evaluated an alternative mechanism of egg predation that was supported by an inverse relationship between bloater recruitment and biomass of slimy sculpin, which are known to be effective egg predators. To that end, we used a combination of field sampling, laboratory experiments, and modeling to estimate the proportion of bloater eggs consumed by sculpins each year between 1973 and 2008. Monthly field sampling between January through May 2009-2010 (when bloater eggs were incubating) offshore of Frankfort (Michigan), Sturgeon Bay (Wisconsin), Two Rivers (Wisconsin), and Muskegon (Michigan) provided benthivore diets for subsequent laboratory processing. Identification and enumeration of stomach contents and subsequent genetic analyses of eggs revealed that the mean proportion of bloater eggs in slimy sculpin diets (N = 1016) equaled 0.04. Bloater eggs also were consumed by deepwater sculpins (N = 699) at a slightly lower mean proportion (0.02), and only one round goby diet among 552 enumerated revealed a bloater egg. Based on the diet results, we developed daily ration models to estimate consumption for both deepwater and slimy sculpins. We conducted feeding experiments to estimate gastric evacuation (GEVAC) for water temperatures ranging 2-5 °C, similar to those observed during egg incubation. GEVAC rates equaled 0.0115/ h for slimy sculpin and 0.0147/h for deepwater sculpin, and did not vary between 2.7 and 5.1 °C for either species or between prey types (Mysis relicta and fish eggs) for slimy sculpin. Index of fullness [(g prey/g fish weight)100%] was estimated from sculpins sampled in bottom trawls in the same seasons and years as the diets, and varied with fish size (averaging 1.93% and 1.85% for slimy and deepwater sculpins, respectively). Estimates of daily consumption ranged from 0.2-0.8% of sculpin body weight. Annual estimates of bloater egg consumption predicted higher values for deepwater sculpin than slimy sculpin between 1973 and 2005. This pattern was reversed in 2006, 2008, 2009, 2010 as slimy sculpin abundance increased while that of deepwater sculpin declined. The sum of sculpin consumption of bloater eggs exceeded 25% of bloater population egg production early (1975-1980) and late (2008-2010) in the time series. Despite the strong field pattern implicating egg predation by slimy sculpin, our consumption models failed to fully support this hypothesis. In particular, our results were unable to explain why bloater recruitment was relatively poor during 1995-2005 when the proportion of bloater eggs consumed was very low (< 0.06). The results did, however, demonstrate that bloater recruitment was consistently poor when the proportion of eggs consumed was relatively high. In conclusion, consumption by native benthivores can be a contributing factor to poor recruitment of bloater, especially when slimy sculpin reach high levels of abundance. This result exemplifies the importance of ecosystem-based fishery management, given that the maintenance of healthy lake trout populations in the Great Lakes should control the abundance of slimy sculpin egg predators. In addition, future research will be required to fully understand the primary bottleneck to bloater recruitment in Lake Michigan so that efforts to stock and restore bloater in Lake Ontario have a greater probability of resulting in naturalized and sustainable populations.
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Paper","code":"PP","onlineIssn":"2330-7102","printIssn":"1044-9612","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1794-A-2","title":"Puget Lowland Ecoregion: Chapter 2 in Status and trends of land change in the Western United States--1973 to 2000","docAbstract":"The Puget Lowland Ecoregion covers an area of approximately 18,009 km² (6,953 mi²) within northwestern Washington (fig. 1) (Omernik, 1987; U.S. Environmental Protection Agency, 1997). The ecoregion is located between the Coast Range Ecoregion to the west, which includes the Olympic Mountains, and the North Cascades and the Cascades Ecoregions to the east, which include the Cascade Range. From the north, the ecoregion follows the Interstate 5 corridor, from the Canadian border south through Bellingham, Seattle, Olympia, and Longview, Washington, to the northern border of the Willamette Valley Ecoregion. The Puget Lowland Ecoregion borders the shoreline of the greater Puget Sound, a complex bay and saltwater estuary fed by spring freshwater runoff from the Olympic Mountains and Cascade Range watersheds. The ecoregion is situated in a continental glacial trough that has many islands, peninsulas, and bays. Relief is moderate, with elevations ranging from sea level to 460 m but averaging approximately 150 m (DellaSala and others, 2001). Proximity to the Pacific Ocean gives the Puget Lowland Ecoregion its mild maritime climate (U.S. Environmental Protection Agency, 1999). Mean annual temperature is 10.5°C, with an average of 4.1°C in January and 17.7°C in July (Guttman and Quayle, 1996). Average annual precipitation ranges from 800 to 900 mm, but some areas in the rain shadow of the Olympic Mountains receive as little as 460 mm (DellaSala and others, 2001). Varying annual average precipitation greatly influences vegetation and soil type in the ecoregion. In the Puget Lowland Ecoregion, soils are dominated by Inceptisols in the north and Ultisols in the south (Jones, 2003). Before European settlement, most of the ecoregion was covered by coniferous forests, with species composition dependent on local climate (U.S. Environmental Protection Agency, 1999). The World Wildlife Fund places the Puget Lowland Ecoregion in the Western Hemlock Vegetation Zone. Although this vegetation zone is named after the western hemlock (Tsuga heterophylla), Douglas-fir (Pseudotsuga menziesii) is the dominant tree species. Seattle, which had an estimated population of 563,376 in 2000, is the largest city in the Puget Lowland Ecoregion (Puget Sound Regional Council, 2001). The greater Seattle metropolitan area, comprising Seattle, Tacoma, Bellevue, and Bremerton, had an estimated population of 3.5 million people in 2000 (U.S. Census Bureau, 2000). Other sizable cities in the ecoregion include the state capital Olympia, as well as Tacoma, Bellingham, and Everett, Washington. The center of the Puget Lowland Ecoregion is dominated by the Seattle metropolitan area and developed land cover, whereas agriculture occurs mainly on river floodplains in the north and south. The remainder of the ecoregion area is dominated by forest land cover (fig. 1).","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Status and trends of land change in the Western United States--1973 to 2000: Volume A in Status and trends of land change in the United States--1973 to 2000 (PP 1794-A)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1794A2","collaboration":"This publication is Chapter 2 in Status and trends of land change in the Western United States--1973 to 2000, which is Volume A in Status and trends of land change in the United States--1973 to 2000, PP 1794. Volume A consists of 30 chapters. For access to other chapters, please visit PP 1794-A.","usgsCitation":"Sorenson, D.G., 2012, Puget Lowland Ecoregion: Chapter 2 in Status and trends of land change in the Western United States--1973 to 2000: U.S. Geological Survey Professional Paper 1794-A-2, Chapter 2: 8 p., https://doi.org/10.3133/pp1794A2.","productDescription":"Chapter 2: 8 p.","startPage":"43","endPage":"50","additionalOnlineFiles":"Y","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":263820,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/pp_1794_A_2.jpg"},{"id":263819,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/pp/1794/a/chapters"},{"id":263817,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1794/a/chapters/pp1794a_chapter02.pdf"},{"id":263818,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/pp/1794/a/"}],"country":"United States","state":"Washington","otherGeospatial":"Cascades;Puget","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.0,46.0 ], [ -124.0,49.0 ], [ -121.5,49.0 ], [ -121.5,46.0 ], [ -124.0,46.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50c31e71e4b0b57f2415d20a","contributors":{"authors":[{"text":"Sorenson, Daniel G. 0000-0003-0365-9444 dsorenson@usgs.gov","orcid":"https://orcid.org/0000-0003-0365-9444","contributorId":2898,"corporation":false,"usgs":true,"family":"Sorenson","given":"Daniel","email":"dsorenson@usgs.gov","middleInitial":"G.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":469903,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70041367,"text":"70041367 - 2012 - Influences on Bythotrephes longimanus life-history characteristics in the Great Lakes","interactions":[],"lastModifiedDate":"2012-12-04T11:38:59","indexId":"70041367","displayToPublicDate":"2012-12-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Influences on Bythotrephes longimanus life-history characteristics in the Great Lakes","docAbstract":"We compared Bythotrephes population demographics and dynamics to predator (planktivorous fish) and prey (small-bodied crustacean zooplankton) densities at a site sampled through the growing season in Lakes Michigan, Huron, and Erie. Although seasonal average densities of Bythotrephes were similar across lakes (222/m2 Erie, 247/m2 Huron, 162/m2 Michigan), temporal trends in abundance differed among lakes. In central Lake Erie where Bythotrephes' prey assemblage was dominated by small individuals (60%), where planktivorous fish densities were high (14,317/ha), and where a shallow water column limited availability of a deepwater refuge, the Bythotrephes population was characterized by a small mean body size, large broods with small neonates, allocation of length increases mainly to the spine rather than to the body, and a late summer population decline. By contrast, in Lake Michigan where Bythotrephes' prey assemblage was dominated by large individuals (72%) and planktivorous fish densities were lower (5052/ha), the Bythotrephes population was characterized by a large mean body size (i.e., 37–55% higher than in Erie), small broods with large neonates, nearly all growth in body length occurring between instars 1 and 2, and population persistence into fall. Life-history characteristics in Lake Huron tended to be intermediate to those found in Lakes Michigan and Erie, reflecting lower overall prey and predator densities (1224/ha) relative to the other lakes. Because plasticity in life history can affect interactions with other species, our findings point to the need to understand life-history variation among Great Lakes populations to improve our ability to model the dynamics of these ecosystems.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Great Lakes Research","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.jglr.2011.10.003","usgsCitation":"Pothoven, S.A., Vanderploeg, H., Warner, D.M., Schaeffer, J.S., Ludsin, S.A., Claramunt, R., and Nalepa, T., 2012, Influences on Bythotrephes longimanus life-history characteristics in the Great Lakes: Journal of Great Lakes Research, v. 38, no. 1, p. 134-141, https://doi.org/10.1016/j.jglr.2011.10.003.","productDescription":"8 p.","startPage":"134","endPage":"141","ipdsId":"IP-030718","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":263670,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":263668,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.jglr.2011.10.003"}],"country":"United States;Canada","otherGeospatial":"Great Lakes","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -92.11,41.4 ], [ -92.11,48.88 ], [ -76.0002,48.88 ], [ -76.0002,41.4 ], [ -92.11,41.4 ] ] ] } } ] }","volume":"38","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50bfbd9ce4b01744973f780c","contributors":{"authors":[{"text":"Pothoven, Steven A.","contributorId":92998,"corporation":false,"usgs":false,"family":"Pothoven","given":"Steven","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":469636,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vanderploeg, Henry A.","contributorId":85929,"corporation":false,"usgs":true,"family":"Vanderploeg","given":"Henry A.","affiliations":[],"preferred":false,"id":469634,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Warner, David M. 0000-0003-4939-5368 dmwarner@usgs.gov","orcid":"https://orcid.org/0000-0003-4939-5368","contributorId":2986,"corporation":false,"usgs":true,"family":"Warner","given":"David","email":"dmwarner@usgs.gov","middleInitial":"M.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":469631,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schaeffer, Jeffrey S.","contributorId":89083,"corporation":false,"usgs":true,"family":"Schaeffer","given":"Jeffrey","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":469635,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ludsin, Stuart A.","contributorId":96978,"corporation":false,"usgs":true,"family":"Ludsin","given":"Stuart","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":469637,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Claramunt, Randall M.","contributorId":19047,"corporation":false,"usgs":true,"family":"Claramunt","given":"Randall M.","affiliations":[],"preferred":false,"id":469632,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Nalepa, Thomas F.","contributorId":28212,"corporation":false,"usgs":true,"family":"Nalepa","given":"Thomas F.","affiliations":[],"preferred":false,"id":469633,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70041079,"text":"70041079 - 2012 - Molecular detection of hematozoa infections in tundra swans relative to migration patterns and ecological conditions at breeding grounds","interactions":[],"lastModifiedDate":"2018-07-15T18:36:44","indexId":"70041079","displayToPublicDate":"2012-12-01T00:00:00","publicationYear":"2012","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":"Molecular detection of hematozoa infections in tundra swans relative to migration patterns and ecological conditions at breeding grounds","docAbstract":"Tundra swans (Cygnus columbianus) are broadly distributed in North America, use a wide variety of habitats, and exhibit diverse migration strategies. We investigated patterns of hematozoa infection in three populations of tundra swans that breed in Alaska using satellite tracking to infer host movement and molecular techniques to assess the prevalence and genetic diversity of parasites. We evaluated whether migratory patterns and environmental conditions at breeding areas explain the prevalence of blood parasites in migratory birds by contrasting the fit of competing models formulated in an occupancy modeling framework and calculating the detection probability of the top model using Akaike Information Criterion (AIC). We described genetic diversity of blood parasites in each population of swans by calculating the number of unique parasite haplotypes observed. Blood parasite infection was significantly different between populations of Alaska tundra swans, with the highest estimated prevalence occurring among birds occupying breeding areas with lower mean daily wind speeds and higher daily summer temperatures. Models including covariates of wind speed and temperature during summer months at breeding grounds better predicted hematozoa prevalence than those that included annual migration distance or duration. Genetic diversity of blood parasites in populations of tundra swans appeared to be relative to hematozoa prevalence. Our results suggest ecological conditions at breeding grounds may explain differences of hematozoa infection among populations of tundra swans that breed in Alaska.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"PLoS ONE","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Public Library of Science","publisherLocation":"San Francisco, CA","doi":"10.1371/journal.pone.0045789","usgsCitation":"Ramey, A.M., Ely, C.R., Schmutz, J.A., Pearce, J.M., and Heard, D.J., 2012, Molecular detection of hematozoa infections in tundra swans relative to migration patterns and ecological conditions at breeding grounds: PLoS ONE, v. 7, no. 9, e45789; 12 p., https://doi.org/10.1371/journal.pone.0045789.","productDescription":"e45789; 12 p.","ipdsId":"IP-039618","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":474240,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0045789","text":"Publisher Index Page"},{"id":263569,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":263568,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1371/journal.pone.0045789"}],"country":"United States","state":"Alaska","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 172.5,51.2 ], [ 172.5,71.4 ], [ -130.0,71.4 ], [ -130.0,51.2 ], [ 172.5,51.2 ] ] ] } } ] }","volume":"7","issue":"9","noUsgsAuthors":false,"publicationDate":"2012-09-25","publicationStatus":"PW","scienceBaseUri":"50e06fa0e4b0fec3206ed1bd","contributors":{"authors":[{"text":"Ramey, Andrew M. 0000-0002-3601-8400 aramey@usgs.gov","orcid":"https://orcid.org/0000-0002-3601-8400","contributorId":1872,"corporation":false,"usgs":true,"family":"Ramey","given":"Andrew","email":"aramey@usgs.gov","middleInitial":"M.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":469367,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ely, Craig R. 0000-0003-4262-0892 cely@usgs.gov","orcid":"https://orcid.org/0000-0003-4262-0892","contributorId":3214,"corporation":false,"usgs":true,"family":"Ely","given":"Craig","email":"cely@usgs.gov","middleInitial":"R.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":469366,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schmutz, Joel A. 0000-0002-6516-0836 jschmutz@usgs.gov","orcid":"https://orcid.org/0000-0002-6516-0836","contributorId":1805,"corporation":false,"usgs":true,"family":"Schmutz","given":"Joel","email":"jschmutz@usgs.gov","middleInitial":"A.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":469365,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pearce, John M. 0000-0002-8503-5485 jpearce@usgs.gov","orcid":"https://orcid.org/0000-0002-8503-5485","contributorId":181766,"corporation":false,"usgs":true,"family":"Pearce","given":"John","email":"jpearce@usgs.gov","middleInitial":"M.","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":469364,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Heard, Darryl J.","contributorId":90998,"corporation":false,"usgs":true,"family":"Heard","given":"Darryl","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":469368,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70042368,"text":"70042368 - 2012 - Evaluation of modal pushover-based scaling of one component of ground motion: Tall buildings","interactions":[],"lastModifiedDate":"2013-02-14T12:58:00","indexId":"70042368","displayToPublicDate":"2012-12-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1436,"text":"Earthquake Spectra","active":true,"publicationSubtype":{"id":10}},"title":"Evaluation of modal pushover-based scaling of one component of ground motion: Tall buildings","docAbstract":"Nonlinear response history analysis (RHA) is now increasingly used for performance-based seismic design of tall buildings. Required for nonlinear RHAs is a set of ground motions selected and scaled appropriately so that analysis results would be accurate (unbiased) and efficient (having relatively small dispersion). This paper evaluates accuracy and efficiency of recently developed modal pushover–based scaling (MPS) method to scale ground motions for tall buildings. The procedure presented explicitly considers structural strength and is based on the standard intensity measure (IM) of spectral acceleration in a form convenient for evaluating existing structures or proposed designs for new structures. Based on results presented for two actual buildings (19 and 52 stories, respectively), it is demonstrated that the MPS procedure provided a highly accurate estimate of the engineering demand parameters (EDPs), accompanied by significantly reduced record-to-record variability of the responses. In addition, the MPS procedure is shown to be superior to the scaling procedure specified in the ASCE/SEI 7-05 document.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Earthquake Spectra","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Earthquake Engineering Research Institute","doi":"10.1193/1.4000091","usgsCitation":"Kalkan, E., and Chopra, A.K., 2012, Evaluation of modal pushover-based scaling of one component of ground motion: Tall buildings: Earthquake Spectra, v. 28, no. 4, p. 1469-1493, https://doi.org/10.1193/1.4000091.","startPage":"1469","endPage":"1493","ipdsId":"IP-022400","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":267396,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":267394,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1193/1.4000091"},{"id":267395,"type":{"id":11,"text":"Document"},"url":"https://nsmp.wr.usgs.gov/ekalkan/PDFs/A85_Kalkan_Chopra.pdf"}],"country":"United States","volume":"28","issue":"4","noUsgsAuthors":false,"publicationDate":"2012-11-01","publicationStatus":"PW","scienceBaseUri":"511e1586e4b071e86a19a440","contributors":{"authors":[{"text":"Kalkan, Erol 0000-0002-9138-9407 ekalkan@usgs.gov","orcid":"https://orcid.org/0000-0002-9138-9407","contributorId":1218,"corporation":false,"usgs":true,"family":"Kalkan","given":"Erol","email":"ekalkan@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":471389,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chopra, Anil K.","contributorId":79202,"corporation":false,"usgs":true,"family":"Chopra","given":"Anil","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":471390,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70148135,"text":"70148135 - 2012 - A Bayesian spawning habitat suitability model for American shad in southeastern United States rivers","interactions":[],"lastModifiedDate":"2015-05-27T10:43:42","indexId":"70148135","displayToPublicDate":"2012-12-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"A Bayesian spawning habitat suitability model for American shad in southeastern United States rivers","docAbstract":"Habitat suitability index models for American shad Alosa sapidissima were developed by Stier and Crance in 1985. These models, which were based on a combination of published information and expert opinion, are often used to make decisions about hydropower dam operations and fish passage. The purpose of this study was to develop updated habitat suitability index models for spawning American shad in the southeastern United States, building on the many field and laboratory studies completed since 1985. We surveyed biologists who had knowledge about American shad spawning grounds, assembled a panel of experts to discuss important habitat variables, and used raw data from published and unpublished studies to develop new habitat suitability curves. The updated curves are based on resource selection functions, which can model habitat selectivity based on use and availability of particular habitats. Using field data collected in eight rivers from Virginia to Florida (Mattaponi, Pamunkey, Roanoke, Tar, Neuse, Cape Fear, Pee Dee, St. Johns), we obtained new curves for temperature, current velocity, and depth that were generally similar to the original models. Our new suitability function for substrate was also similar to the original pattern, except that sand (optimal in the original model) has a very low estimated suitability. The Bayesian approach that we used to develop habitat suitability curves provides an objective framework for updating the model as new studies are completed and for testing the model's applicability in other parts of the species' range.
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Low-quality locations (Argos classes A, 0, B and Z) dominate animal tracking data. Standard-quality animal tracking locations (Argos classes 3, 2 and 1) have larger errors than those reported in Argos manuals.\n2. The Douglas Argos-filter (DAF) algorithm flags implausible locations based on user-defined thresholds that allow the algorithm's performance to be tuned to species' movement behaviours and study objectives. The algorithm is available in Movebank – a free online infrastructure for storing, managing, sharing and analysing animal movement data.\n3. We compared 21,044 temporally paired global positioning system (GPS) locations with Argos location estimates collected from Argos transmitters on free-ranging waterfowl and condors (13 species, 314 individuals, 54,895 animal-tracking days). The 95th error percentiles for unfiltered Argos locations 0, A, B and Z were within 35·8, 59·6, 163·2 and 220·2 km of the true location, respectively. After applying DAF with liberal thresholds, roughly 20% of the class 0 and A locations and 45% of the class B and Z locations were excluded, and the 95th error percentiles were reduced to 17·2, 15·0, 20·9 and 18·6 km for classes 0, A, B and Z, respectively. As thresholds were applied more conservatively, fewer locations were retained, but they possessed higher overall accuracy.\n4. Douglas Argos-filter can improve data accuracy by 50–90% and is an effective and flexible tool for preparing Argos data for direct biological interpretation or subsequent modelling.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Methods in Ecology and Evolution","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","publisherLocation":"Hoboken, NJ","doi":"10.1111/j.2041-210X.2012.00245.x","usgsCitation":"Douglas, D.C., Weinziert, R., Davidson, S.C., Kays, R., Wikelski, M., and Bohrer, G., 2012, Moderating Argos location errors in animal tracking data: Methods in Ecology and Evolution, v. 3, no. 6, p. 999-1007, https://doi.org/10.1111/j.2041-210X.2012.00245.x.","productDescription":"8 p.","startPage":"999","endPage":"1007","ipdsId":"IP-039258","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":474238,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/j.2041-210x.2012.00245.x","text":"Publisher Index Page"},{"id":263567,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":263566,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/j.2041-210X.2012.00245.x"}],"volume":"3","issue":"6","noUsgsAuthors":false,"publicationDate":"2012-10-10","publicationStatus":"PW","scienceBaseUri":"50d20c82e4b08b071e771baf","contributors":{"authors":[{"text":"Douglas, David C. 0000-0003-0186-1104 ddouglas@usgs.gov","orcid":"https://orcid.org/0000-0003-0186-1104","contributorId":2388,"corporation":false,"usgs":true,"family":"Douglas","given":"David","email":"ddouglas@usgs.gov","middleInitial":"C.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":469315,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Weinziert, Rolf","contributorId":24665,"corporation":false,"usgs":true,"family":"Weinziert","given":"Rolf","email":"","affiliations":[],"preferred":false,"id":469316,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Davidson, Sarah C.","contributorId":31651,"corporation":false,"usgs":true,"family":"Davidson","given":"Sarah","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":469317,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kays, Roland","contributorId":83815,"corporation":false,"usgs":true,"family":"Kays","given":"Roland","affiliations":[],"preferred":false,"id":469320,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wikelski, Martin","contributorId":76451,"corporation":false,"usgs":true,"family":"Wikelski","given":"Martin","affiliations":[],"preferred":false,"id":469319,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bohrer, Gil","contributorId":66569,"corporation":false,"usgs":true,"family":"Bohrer","given":"Gil","affiliations":[],"preferred":false,"id":469318,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70045239,"text":"70045239 - 2012 - The past as prelude to the future for understanding 21st-century climate effects on Rocky Mountain Trout","interactions":[],"lastModifiedDate":"2013-04-25T11:19:04","indexId":"70045239","displayToPublicDate":"2012-12-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1657,"text":"Fisheries","onlineIssn":"1548-8446","printIssn":"0363-2415","active":true,"publicationSubtype":{"id":10}},"title":"The past as prelude to the future for understanding 21st-century climate effects on Rocky Mountain Trout","docAbstract":"Bioclimatic models predict large reductions in native trout across the Rocky Mountains in the 21st century but lack details about how changes will occur. Through five case histories across the region, we explore how a changing climate has been affecting streams and the potential consequences for trout. Monitoring records show trends in temperature and hydrographs consistent with a warming climate in recent decades. Biological implications include upstream shifts in thermal habitats, risk of egg scour, increased wildfire disturbances, and declining summer habitat volumes. The importance of these factors depends on the context, but temperature increases are most relevant where population boundaries are mediated by thermal constraints. Summer flow declines and wildfires will be important where trout populations are fragmented and constrained to small refugia. A critical information gap is evidence documenting how populations are adjusting to long-term habitat trends, so biological monitoring is a priority. Biological, temperature, and discharge data from monitoring networks could be used to develop accurate vulnerability assessments that provide information regarding where conservation actions would best improve population resilience. Even with better information, future uncertainties will remain large due to unknowns regarding Earth's ultimate warming trajectory and how effects translate across scales. Maintaining or increasing the size of habitats could provide a buffer against these uncertainties.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Fisheries","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Taylor & Francis","doi":"10.1080/03632415.2012.742808","usgsCitation":"Isaak, D.J., Muhlfeld, C.C., Todd, A., Al-chokhachy, R., Roberts, J., Kershner, J.L., Fausch, K., and Hostetler, S.W., 2012, The past as prelude to the future for understanding 21st-century climate effects on Rocky Mountain Trout: Fisheries, v. 37, no. 12, p. 542-556, https://doi.org/10.1080/03632415.2012.742808.","productDescription":"15 p.","startPage":"542","endPage":"556","numberOfPages":"15","ipdsId":"IP-036943","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":271460,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1080/03632415.2012.742808"},{"id":271461,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -123.43,33.09 ], [ -123.43,49.46 ], [ -103.25,49.46 ], [ -103.25,33.09 ], [ -123.43,33.09 ] ] ] } } ] }","volume":"37","issue":"12","noUsgsAuthors":false,"publicationDate":"2012-12-11","publicationStatus":"PW","scienceBaseUri":"517a506ee4b072c16ef14b61","contributors":{"authors":[{"text":"Isaak, Daniel J.","contributorId":57202,"corporation":false,"usgs":true,"family":"Isaak","given":"Daniel","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":477109,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Muhlfeld, Clint C. 0000-0002-4599-4059 cmuhlfeld@usgs.gov","orcid":"https://orcid.org/0000-0002-4599-4059","contributorId":924,"corporation":false,"usgs":true,"family":"Muhlfeld","given":"Clint","email":"cmuhlfeld@usgs.gov","middleInitial":"C.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":477104,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Todd, Andrew S.","contributorId":33162,"corporation":false,"usgs":true,"family":"Todd","given":"Andrew S.","affiliations":[],"preferred":false,"id":477108,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Al-chokhachy, Robert","contributorId":90194,"corporation":false,"usgs":true,"family":"Al-chokhachy","given":"Robert","affiliations":[],"preferred":false,"id":477110,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Roberts, James","contributorId":17509,"corporation":false,"usgs":true,"family":"Roberts","given":"James","affiliations":[],"preferred":false,"id":477106,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kershner, Jeffrey L. 0000-0002-7093-9860 jkershner@usgs.gov","orcid":"https://orcid.org/0000-0002-7093-9860","contributorId":310,"corporation":false,"usgs":true,"family":"Kershner","given":"Jeffrey","email":"jkershner@usgs.gov","middleInitial":"L.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":477103,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Fausch, Kurt D. 0000-0001-5825-7560","orcid":"https://orcid.org/0000-0001-5825-7560","contributorId":29370,"corporation":false,"usgs":false,"family":"Fausch","given":"Kurt D.","affiliations":[],"preferred":false,"id":477107,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hostetler, Steven W. 0000-0003-2272-8302 swhostet@usgs.gov","orcid":"https://orcid.org/0000-0003-2272-8302","contributorId":3249,"corporation":false,"usgs":true,"family":"Hostetler","given":"Steven","email":"swhostet@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":477105,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70042663,"text":"70042663 - 2012 - Individual condition and stream temperature influence early maturation of rainbow and steelhead trout, ncorhynchus mykiss","interactions":[],"lastModifiedDate":"2017-02-21T14:38:38","indexId":"70042663","displayToPublicDate":"2012-12-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1528,"text":"Environmental Biology of Fishes","active":true,"publicationSubtype":{"id":10}},"title":"Individual condition and stream temperature influence early maturation of rainbow and steelhead trout, ncorhynchus mykiss","docAbstract":"Alternative male phenotypes in salmonine fishes arise from individuals that mature as larger and older anadromous marine-migrants or as smaller and younger freshwater residents. To better understand the processes influencing the expression of these phenotypes we examined the influences of growth in length (fork length) and whole body lipid content in rainbow trout (Oncorhynchus mykiss). Fish were sampled from the John Day River basin in northeast Oregon where both anadromous (\"steelhead\") and freshwater resident rainbow trout coexist. Larger males with higher lipid levels had a greater probability of maturing as a resident at age-1+. Among males, 38% were maturing overall, and the odds ratios of the logistic model indicated that the probability of a male maturing early as a resident at age-1+ increased 49% (95% confidence interval (CI) = 23-81%) for every 5 mm increase in length and 33% (95% CI = 10-61%) for every 0.5% increase in whole body lipid content. There was an inverse association between individual condition and water temperature as growth was greater in warmer streams while whole body lipid content was higher in cooler streams. Our results support predictions from life history theory and further suggest that relationships between individual condition, maturation, and environmental variables (e.g., water temperature) are shaped by complex developmental and evolutionary influences.
","language":"English","publisher":"Springer","doi":"10.1007/s10641-011-9921-0","usgsCitation":"McMillan, J.R., Dunham, J., Reeves, G.H., Mills, J.S., and Jordan, C.E., 2012, Individual condition and stream temperature influence early maturation of rainbow and steelhead trout, ncorhynchus mykiss: Environmental Biology of Fishes, v. 93, no. 3, p. 343-355, https://doi.org/10.1007/s10641-011-9921-0.","productDescription":"13 p.","startPage":"343","endPage":"355","ipdsId":"IP-034205","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":267975,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"John Day River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.78369140624999,\n 43.644025847699496\n ],\n [\n -117.80639648437499,\n 43.644025847699496\n ],\n [\n -117.80639648437499,\n 45.71385093029221\n ],\n [\n -120.78369140624999,\n 45.71385093029221\n ],\n [\n -120.78369140624999,\n 43.644025847699496\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"93","issue":"3","noUsgsAuthors":false,"publicationDate":"2011-09-07","publicationStatus":"PW","scienceBaseUri":"5129f32de4b04edf7e93f8e8","contributors":{"authors":[{"text":"McMillan, John R.","contributorId":27905,"corporation":false,"usgs":true,"family":"McMillan","given":"John","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":472020,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dunham, Jason B. 0000-0002-6268-0633 jdunham@usgs.gov","orcid":"https://orcid.org/0000-0002-6268-0633","contributorId":1808,"corporation":false,"usgs":true,"family":"Dunham","given":"Jason B.","email":"jdunham@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":false,"id":472023,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reeves, Gordon H.","contributorId":101521,"corporation":false,"usgs":false,"family":"Reeves","given":"Gordon","email":"","middleInitial":"H.","affiliations":[{"id":527,"text":"Pacific Northwest Research Station","active":false,"usgs":true}],"preferred":false,"id":472021,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mills, Justin S.","contributorId":56944,"corporation":false,"usgs":true,"family":"Mills","given":"Justin","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":472019,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jordan, Chris E.","contributorId":88233,"corporation":false,"usgs":true,"family":"Jordan","given":"Chris","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":472022,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70042602,"text":"70042602 - 2012 - Scriptaid and 5-aza-2'deoxycytidine enhanced expression of pluripotent genes and in vitro developmental competence in interspecies Black-footed cat cloned embryos","interactions":[],"lastModifiedDate":"2013-02-28T11:29:27","indexId":"70042602","displayToPublicDate":"2012-12-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3260,"text":"Reproduction in Domestic Animals","active":true,"publicationSubtype":{"id":10}},"title":"Scriptaid and 5-aza-2'deoxycytidine enhanced expression of pluripotent genes and in vitro developmental competence in interspecies Black-footed cat cloned embryos","docAbstract":"Somatic cell nuclear transfer offers the possibility of preserving endangered species including the black-footed cat, which is threatened with extinction. The effectiveness and efficiency of somatic cell nuclear transfer (SCNT) depends on a variety of factors, but 'inappropriate epigenetic reprogramming of the transplanted nucleus is the primary cause of the developmental failure of cloned embryos. Abnormal epigenetic events such as DNA methylation and histone modifications during SCNT perturb the expression of imprinted and pluripotent-related genes that, consequently, may result in foetal and neonatal abnormalities. We have demonstrated that pregnancies can be established after transfer of black-footed cat cloned embryos into domestic cat recipients, but none of the implanted embryos developed to term and the foetal failure has been associated to aberrant reprogramming in cloned embryos. There is growing evidence that modifying the epigenetic pattern of the chromatin template of both donor cells and reconstructed embryos with a combination of inhibitors of histone deacetylases and DNA methyltransferases results in enhanced gene reactivation and improved in vitro and in vivo developmental competence. Epigenetic modifications of the chromatin template of black-footed cat donor cells and reconstructed embryos with epigenetic-modifying compounds enhanced in vitro development, and regulated the expression of pluripotent genes, but these epigenetic modifications did not improve in vivo developmental competence.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Reproduction in Domestic Animals","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisherLocation":"Berlin, Germany","doi":"10.1111/rda.12027","usgsCitation":"Gomez, M.C., Biancardi, M., Jenkins, J., Dumas, C., Galiguis, J., Wang, G., and Earle Pope, C., 2012, Scriptaid and 5-aza-2'deoxycytidine enhanced expression of pluripotent genes and in vitro developmental competence in interspecies Black-footed cat cloned embryos: Reproduction in Domestic Animals, v. 47, no. Suppl. 6, p. 130-135, https://doi.org/10.1111/rda.12027.","productDescription":"6 p.","startPage":"130","endPage":"135","numberOfPages":"6","ipdsId":"IP-038422","costCenters":[],"links":[{"id":474243,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/rda.12027","text":"Publisher Index Page"},{"id":268544,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":265636,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/rda.12027"}],"country":"United States","volume":"47","issue":"Suppl. 6","noUsgsAuthors":false,"publicationDate":"2012-12-24","publicationStatus":"PW","scienceBaseUri":"51308a9ce4b04c194073ae4c","contributors":{"authors":[{"text":"Gomez, M. C.","contributorId":12341,"corporation":false,"usgs":true,"family":"Gomez","given":"M.","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":471911,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Biancardi, M.N.","contributorId":90610,"corporation":false,"usgs":true,"family":"Biancardi","given":"M.N.","email":"","affiliations":[],"preferred":false,"id":471915,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jenkins, J.A. 0000-0002-5087-0894","orcid":"https://orcid.org/0000-0002-5087-0894","contributorId":51703,"corporation":false,"usgs":true,"family":"Jenkins","given":"J.A.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":false,"id":471912,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dumas, C.","contributorId":103939,"corporation":false,"usgs":true,"family":"Dumas","given":"C.","email":"","affiliations":[],"preferred":false,"id":471916,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Galiguis, J.","contributorId":88228,"corporation":false,"usgs":true,"family":"Galiguis","given":"J.","email":"","affiliations":[],"preferred":false,"id":471914,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wang, G.","contributorId":11034,"corporation":false,"usgs":true,"family":"Wang","given":"G.","email":"","affiliations":[],"preferred":false,"id":471910,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Earle Pope, C.","contributorId":69857,"corporation":false,"usgs":true,"family":"Earle Pope","given":"C.","email":"","affiliations":[],"preferred":false,"id":471913,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70041063,"text":"70041063 - 2012 - Bioenergetics model for estimating food requirements of female Pacific walruses (Odobenus rosmarus divergens)","interactions":[],"lastModifiedDate":"2018-08-20T20:04:51","indexId":"70041063","displayToPublicDate":"2012-11-30T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2663,"text":"Marine Ecology Progress Series","active":true,"publicationSubtype":{"id":10}},"title":"Bioenergetics model for estimating food requirements of female Pacific walruses (Odobenus rosmarus divergens)","docAbstract":"Pacific walruses Odobenus rosmarus divergens use sea ice as a platform for resting, nursing, and accessing extensive benthic foraging grounds. The extent of summer sea ice in the Chukchi Sea has decreased substantially in recent decades, causing walruses to alter habitat use and activity patterns which could affect their energy requirements. We developed a bioenergetics model to estimate caloric demand of female walruses, accounting for maintenance, growth, activity (active in-water and hauled-out resting), molt, and reproductive costs. Estimates for non-reproductive females 0–12 yr old (65−810 kg) ranged from 16359 to 68960 kcal d−1 (74−257 kcal d−1 kg−1) for years with readily available sea ice for which we assumed animals spent 83% of their time in water. This translated into the energy content of 3200–5960 clams per day, equivalent to 7–8% and 14–9% of body mass per day for 5–12 and 2–4 yr olds, respectively. Estimated consumption rates of 12 yr old females were minimally affected by pregnancy, but lactation had a large impact, increasing consumption rates to 15% of body mass per day. Increasing the proportion of time in water to 93%, as might happen if walruses were required to spend more time foraging during ice-free periods, increased daily caloric demand by 6–7% for non-lactating females. We provide the first bioenergetics-based estimates of energy requirements for walruses and a first step towards establishing bioenergetic linkages between demography and prey requirements that can ultimately be used in predicting this population’s response to environmental change.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Marine Ecology Progress Series","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Inter-Research","publisherLocation":"Oldendorf/Luhe, Germany","doi":"10.3354/meps09706","usgsCitation":"Noren, S., Udevitz, M.S., and Jay, C., 2012, Bioenergetics model for estimating food requirements of female Pacific walruses (Odobenus rosmarus divergens): Marine Ecology Progress Series, v. 460, p. 261-275, https://doi.org/10.3354/meps09706.","productDescription":"15 p.","startPage":"261","endPage":"275","ipdsId":"IP-036187","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":474253,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3354/meps09706","text":"Publisher Index Page"},{"id":263526,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":263525,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.3354/meps09706"}],"volume":"460","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50d89a7ce4b0af4069e415c1","contributors":{"authors":[{"text":"Noren, S.R.","contributorId":78218,"corporation":false,"usgs":true,"family":"Noren","given":"S.R.","email":"","affiliations":[],"preferred":false,"id":469313,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Udevitz, Mark S. 0000-0003-4659-138X mudevitz@usgs.gov","orcid":"https://orcid.org/0000-0003-4659-138X","contributorId":3189,"corporation":false,"usgs":true,"family":"Udevitz","given":"Mark","email":"mudevitz@usgs.gov","middleInitial":"S.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":469314,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jay, C.V. 0000-0002-9559-2189","orcid":"https://orcid.org/0000-0002-9559-2189","contributorId":67827,"corporation":false,"usgs":true,"family":"Jay","given":"C.V.","affiliations":[],"preferred":false,"id":469312,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70041045,"text":"70041045 - 2012 - A multi-sensor lidar, multi-spectral and multi-angular approach for mapping canopy height in boreal forest regions","interactions":[],"lastModifiedDate":"2017-04-06T14:41:10","indexId":"70041045","displayToPublicDate":"2012-11-30T00:00:00","publicationYear":"2012","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":"A multi-sensor lidar, multi-spectral and multi-angular approach for mapping canopy height in boreal forest regions","docAbstract":"Spatially explicit representations of vegetation canopy height over large regions are necessary for a wide variety of inventory, monitoring, and modeling activities. Although airborne lidar data has been successfully used to develop vegetation canopy height maps in many regions, for vast, sparsely populated regions such as the boreal forest biome, airborne lidar is not widely available. An alternative approach to canopy height mapping in areas where airborne lidar data is limited is to use spaceborne lidar measurements in combination with multi-angular and multi-spectral remote sensing data to produce comprehensive canopy height maps for the entire region. This study uses spaceborne lidar data from the Geosciences Laser Altimeter System (GLAS) as training data for regression tree models that incorporate multi-angular and multi-spectral data from the Multi-Angle Imaging Spectroradiometer (MISR) and the Moderate Resolution Imaging SpectroRadiometer (MODIS) to map vegetation canopy height across a 1,300,000 km2 swath of boreal forest in Interior Alaska. Results are compared to in situ height measurements as well as airborne lidar data. Although many of the GLAS-derived canopy height estimates are inaccurate, applying a series of filters incorporating both data associated with the GLAS shots as well as ancillary data such as land cover can identify the majority of height estimates with significant errors, resulting in a filtered dataset with much higher accuracy. Results from the regression tree models indicate that late winter MISR imagery acquired under snow-covered conditions is effective for mapping canopy heights ranging from 5 to 15 m, which includes the vast majority of forests in the region. It appears that neither MISR nor MODIS imagery acquired during the growing season is effective for canopy height mapping, although including summer multi-spectral MODIS data along with winter MISR imagery does appear to provide a slight increase in the accuracy of resulting height maps. The finding that winter, snow-covered MISR imagery can be used to map canopy height is important because clear sky days are nearly three times as common during the late winter period as during the growing season. The increased odds of acquiring cloud-free imagery during the target acquisition period make regularly updated forest height inventories for Interior Alaska much more feasible. A major advantage of the GLAS–MISR–MODIS canopy height mapping methodology described here is that this approach uses only data that is freely available worldwide, making the approach potentially applicable across the entire circumpolar boreal forest region.
","language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.rse.2012.02.020","usgsCitation":"Selkowitz, D.J., Green, G., Peterson, B.E., and Wylie, B., 2012, A multi-sensor lidar, multi-spectral and multi-angular approach for mapping canopy height in boreal forest regions: Remote Sensing of Environment, v. 121, p. 458-471, https://doi.org/10.1016/j.rse.2012.02.020.","productDescription":"14 p.","startPage":"458","endPage":"471","ipdsId":"IP-035645","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":263516,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":263515,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.rse.2012.02.020"}],"volume":"121","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50d59e83e4b0ba654692b9b6","contributors":{"authors":[{"text":"Selkowitz, David J. 0000-0003-0824-7051 dselkowitz@usgs.gov","orcid":"https://orcid.org/0000-0003-0824-7051","contributorId":3259,"corporation":false,"usgs":true,"family":"Selkowitz","given":"David","email":"dselkowitz@usgs.gov","middleInitial":"J.","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":469248,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Green, Gordon","contributorId":65738,"corporation":false,"usgs":true,"family":"Green","given":"Gordon","email":"","affiliations":[],"preferred":false,"id":469250,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Peterson, Birgit E. 0000-0002-4356-1540 bpeterson@usgs.gov","orcid":"https://orcid.org/0000-0002-4356-1540","contributorId":3599,"corporation":false,"usgs":true,"family":"Peterson","given":"Birgit","email":"bpeterson@usgs.gov","middleInitial":"E.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":469249,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wylie, Bruce 0000-0002-7374-1083","orcid":"https://orcid.org/0000-0002-7374-1083","contributorId":107996,"corporation":false,"usgs":true,"family":"Wylie","given":"Bruce","affiliations":[],"preferred":false,"id":469251,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70178820,"text":"70178820 - 2012 - The impact of antecedent fire area on burned area in southern California coastal ecosystems","interactions":[],"lastModifiedDate":"2019-12-14T07:17:58","indexId":"70178820","displayToPublicDate":"2012-11-30T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2258,"text":"Journal of Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"The impact of antecedent fire area on burned area in southern California coastal ecosystems","docAbstract":"Frequent wildfire disasters in southern California highlight the need for risk reduction strategies for the region, of which fuel reduction via prescribed burning is one option. However, there is no consensus about the effectiveness of prescribed fire in reducing the area of wildfire. Here, we use 29 years of historical fire mapping to quantify the relationship between annual wildfire area and antecedent fire area in predominantly shrub and grassland fuels in seven southern California counties, controlling for annual variation in weather patterns. This method has been used elsewhere to measure leverage: the reduction in wildfire area resulting from one unit of prescribed fire treatment. We found little evidence for a leverage effect (leverage = zero). Specifically our results showed no evidence that wildfire area was negatively influenced by previous fires, and only weak relationships with weather variables rainfall and Santa Ana wind occurrences, which were variables included to control for inter-annual variation. We conclude that this is because only 2% of the vegetation burns each year and so wildfires rarely encounter burned patches and chaparral shrublands can carry a fire within 1 or 2 years after previous fire. Prescribed burning is unlikely to have much influence on fire regimes in this area, though targeted treatment at the urban interface may be effective at providing defensible space for protecting assets. These results fit an emerging global model of fire leverage which position California at the bottom end of a continuum, with tropical savannas at the top (leverage = 1: direct replacement of wildfire by prescribed fire) and Australian eucalypt forests in the middle (leverage ∼ 0.25).
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jenvman.2012.08.042","usgsCitation":"Price, O.F., Bradstock, R.A., Keeley, J.E., and Syphard, A.D., 2012, The impact of antecedent fire area on burned area in southern California coastal ecosystems: Journal of Environmental Management, v. 113, p. 301-307, https://doi.org/10.1016/j.jenvman.2012.08.042.","productDescription":"7 p.","startPage":"301","endPage":"307","ipdsId":"IP-039843","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":331696,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","county":"Los Angeles County, Orange County, Riverside County, San Diego County, San Luis Obispo County, Santa Barbara County, Ventura County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.93847656250001,\n 32.509761735919426\n ],\n [\n -115.75195312499999,\n 32.58384932565662\n ],\n [\n -117.8173828125,\n 35.53222622770337\n ],\n [\n -119.61914062499999,\n 37.020098201368114\n ],\n [\n -121.201171875,\n 37.85750715625203\n ],\n [\n -122.51953124999999,\n 37.3002752813443\n ],\n [\n -121.9482421875,\n 36.421282443649496\n ],\n [\n -121.1572265625,\n 34.08906131584994\n ],\n [\n -119.0478515625,\n 33.32134852669881\n ],\n [\n -117.5537109375,\n 33.247875947924385\n ],\n [\n -116.93847656250001,\n 32.509761735919426\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"113","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"584a7f7de4b07e29c706dd39","contributors":{"authors":[{"text":"Price, Owen F.","contributorId":177305,"corporation":false,"usgs":false,"family":"Price","given":"Owen","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":655257,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bradstock, Ross A.","contributorId":42826,"corporation":false,"usgs":false,"family":"Bradstock","given":"Ross","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":655258,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Keeley, Jon E. 0000-0002-4564-6521 jon_keeley@usgs.gov","orcid":"https://orcid.org/0000-0002-4564-6521","contributorId":1268,"corporation":false,"usgs":true,"family":"Keeley","given":"Jon","email":"jon_keeley@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":655256,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Syphard, Alexandra D.","contributorId":8977,"corporation":false,"usgs":false,"family":"Syphard","given":"Alexandra","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":655259,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70041248,"text":"ds709D - 2012 - Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the North Takhar mineral district in Afghanistan: Chapter D in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan","interactions":[],"lastModifiedDate":"2013-02-01T11:11:27","indexId":"ds709D","displayToPublicDate":"2012-11-30T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"709","chapter":"D","title":"Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the North Takhar mineral district in Afghanistan: Chapter D in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan","docAbstract":"The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the North Takhar mineral district, which has placer gold deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2006,2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. Therefore, it was necessary to (1) register the 10-m AVNIR multispectral imagery to a well-controlled Landsat image base, (2) mosaic the individual multispectral images into a single image of the entire area of interest, (3) register each panchromatic image to the registered multispectral image base, and (4) mosaic the individual panchromatic images into a single image of the entire area of interest. The two image-registration steps were facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band’s picture element based on the digital values of all picture elements within a 315-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area’s local zone (42 for North Takhar) and the WGS84 datum. The final image mosaics were subdivided into nine overlapping tiles or quadrants because of the large size of the target area. The nine image tiles (or quadrants) for the North Takhar area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan (DS 709)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds709D","collaboration":"Prepared in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations and the Afghanistan Geological Survey. This report is Chapter D in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan. For more information, see: Data Series 709.","usgsCitation":"Davis, P.A., and Cagney, L.E., 2012, Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the North Takhar mineral district in Afghanistan: Chapter D in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan: U.S. Geological Survey Data Series 709, Readme File; 2 Maps: 11 x 8.5 and 41.76 x 48.21 inches; 18 Image Files: 18 Metadata Files; Shapefiles; DS 709, https://doi.org/10.3133/ds709D.","productDescription":"Readme File; 2 Maps: 11 x 8.5 and 41.76 x 48.21 inches; 18 Image Files: 18 Metadata Files; Shapefiles; DS 709","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-032347","costCenters":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"links":[{"id":263529,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds_709_D.jpg"},{"id":263609,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/d/index_maps/North_Takhar_Image_Index_Map.pdf"},{"id":263610,"type":{"id":14,"text":"Image"},"url":"https://pubs.usgs.gov/ds/709/d/image_files/image_files.html"},{"id":263611,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/ds/709/d/metadata/metadata.html"},{"id":263612,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/709/d/shapefiles/shapefiles.html"},{"id":263613,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/ds/709/index.html"},{"id":263606,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/709/d/"},{"id":263607,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/ds/709/d/1_readme.txt"},{"id":263608,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/d/index_maps/North_Takhar_Area-of-Interest_Index_Map.pdf"}],"country":"Afghanistan","otherGeospatial":"North Takhar","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 60.5,29.25 ], [ 60.5,38.5 ], [ 75.0,38.5 ], [ 75.0,29.25 ], [ 60.5,29.25 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50bfbdabe4b01744973f7817","contributors":{"authors":[{"text":"Davis, Philip A. pdavis@usgs.gov","contributorId":692,"corporation":false,"usgs":true,"family":"Davis","given":"Philip","email":"pdavis@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":469453,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cagney, Laura E. 0000-0003-3282-2458 lcagney@usgs.gov","orcid":"https://orcid.org/0000-0003-3282-2458","contributorId":4744,"corporation":false,"usgs":true,"family":"Cagney","given":"Laura","email":"lcagney@usgs.gov","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":469454,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70041128,"text":"ofr20121227 - 2012 - Hydrostratigraphic interpretation of test-hole and surface geophysical data, Elkhorn and Loup River Basins, Nebraska, 2008 to 2011","interactions":[],"lastModifiedDate":"2012-11-29T14:36:20","indexId":"ofr20121227","displayToPublicDate":"2012-11-29T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-1227","title":"Hydrostratigraphic interpretation of test-hole and surface geophysical data, Elkhorn and Loup River Basins, Nebraska, 2008 to 2011","docAbstract":"The Elkhorn-Loup Model (ELM) was begun in 2006 to understand the effect of various groundwater-management scenarios on surface-water resources. During phase one of the ELM study, a lack of subsurface geological information was identified as a data gap. Test holes drilled to the base of the aquifer in the ELM study area are spaced as much as 25 miles apart, especially in areas of the western Sand Hills. Given the variable character of the hydrostratigraphic units that compose the High Plains aquifer system, substantial variation in aquifer thickness and characteristics can exist between test holes. To improve the hydrogeologic understanding of the ELM study area, the U.S. Geological Survey, in cooperation with the Nebraska Department of Natural Resources, multiple Natural Resources Districts participating in the ELM study, and the University of Nebraska-Lincoln Conservation and Survey Division, described the subsurface lithology at six test holes drilled in 2010 and concurrently collected borehole geophysical data to identify the base of the High Plains aquifer system. A total of 124 time-domain electromagnetic (TDEM) soundings of resistivity were collected at and between selected test-hole locations during 2008-11 as a quick, non-invasive means of identifying the base of the High Plains aquifer system. Test-hole drilling and geophysical logging indicated the base-of-aquifer elevation was less variable in the central ELM area than in previously reported results from the western part of the ELM study area, where deeper paleochannels were eroded into the Brule Formation. In total, more than 435 test holes were examined and compared with the modeled-TDEM soundings. Even where present, individual stratigraphic units could not always be identified in modeled-TDEM sounding results if sufficient resistivity contrast was not evident; however, in general, the base of aquifer [top of the aquifer confining unit (ACU)] is one of the best-resolved results from the TDEM-based models, and estimates of the base-of-aquifer elevation are in good accordance with those from existing test-hole data. Differences between ACU elevations based on modeled-TDEM and test-hole data ranged from 2 to 113 feet (0.6 to 34 meters). The modeled resistivity results reflect the eastward thinning of Miocene-age and older stratigraphic units, and generally allowed confident identification of the accompanying change in the stratigraphic unit forming the ACU. The differences in elevation of the top of the Ogallala, estimated on the basis of the modeled-TDEM resistivity, and the test-hole data ranged from 11 to 251 feet (3.4 to 77 meters), with two-thirds of model results being within 60 feet of the test-hole contact elevation. The modeled-TDEM soundings also provided information regarding the distribution of Plio-Pleistocene gravel deposits, which had an average thickness of 100 feet (30 meters) in the study area; however, in many cases the contact between the Plio-Pleistocene deposits and the overlying Quaternary deposits cannot be reliably distinguished using TDEM soundings alone because of insufficient thickness or resistivity contrast.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121227","collaboration":"Prepared in cooperation with the Nebraska Department of Natural Resources; and the Upper Elkhorn, Lower Elkhorn, Upper Loup, Lower Loup, Middle Niobrara, Lower Niobrara, Lewis and Clark, and Lower Platte North Natural Resources Districts; and the University of Nebraska-Lincoln Conservation and Survey Division","usgsCitation":"Hobza, C.M., Bedrosian, P.A., and Bloss, B., 2012, Hydrostratigraphic interpretation of test-hole and surface geophysical data, Elkhorn and Loup River Basins, Nebraska, 2008 to 2011: U.S. Geological Survey Open-File Report 2012-1227, Report: x, 95 p.; Supplemental Data, https://doi.org/10.3133/ofr20121227.","productDescription":"Report: x, 95 p.; Supplemental Data","numberOfPages":"110","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-037355","costCenters":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"links":[{"id":263482,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1227.gif"},{"id":263481,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2012/1227/downloads/Supplemental_Data.xlsx"},{"id":263478,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1227/"},{"id":263479,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1227/of2012-1227.pdf"}],"scale":"100000","projection":"Lambert Conformal Conic projection","datum":"North American Datum of 1983","country":"United States","state":"Nebraska","otherGeospatial":"Elkhorn And Loup River Basins","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -102.5,40.0 ], [ -102.5,43.0 ], [ -97.0,43.0 ], [ -97.0,40.0 ], [ -102.5,40.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50df06b5e4b0dfbe79e687ab","contributors":{"authors":[{"text":"Hobza, Christopher M. 0000-0002-6239-934X cmhobza@usgs.gov","orcid":"https://orcid.org/0000-0002-6239-934X","contributorId":2393,"corporation":false,"usgs":true,"family":"Hobza","given":"Christopher","email":"cmhobza@usgs.gov","middleInitial":"M.","affiliations":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"preferred":true,"id":469443,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bedrosian, Paul A. 0000-0002-6786-1038 pbedrosian@usgs.gov","orcid":"https://orcid.org/0000-0002-6786-1038","contributorId":839,"corporation":false,"usgs":true,"family":"Bedrosian","given":"Paul","email":"pbedrosian@usgs.gov","middleInitial":"A.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":469442,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bloss, Benjamin R.","contributorId":19446,"corporation":false,"usgs":true,"family":"Bloss","given":"Benjamin R.","affiliations":[],"preferred":false,"id":469444,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70041141,"text":"ofr20121245 - 2012 - Linking physical monitoring to coho and Chinook salmon populations in the Redwood Creek Watershed, California—Summary of May 3–4, 2012 Workshop","interactions":[],"lastModifiedDate":"2018-03-21T14:40:08","indexId":"ofr20121245","displayToPublicDate":"2012-11-29T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-1245","title":"Linking physical monitoring to coho and Chinook salmon populations in the Redwood Creek Watershed, California—Summary of May 3–4, 2012 Workshop","docAbstract":"On Thursday, May 3, 2012, a science workshop was held at the Redwood National and State Parks (RNSP) office in Arcata, California, with researchers and resource managers working in RNSP to share data and expert opinions concerning salmon populations and habitat in the Redwood Creek watershed. The focus of the workshop was to discuss how best to synthesize physical and biological data related to the freshwater and estuarine phases of salmon life cycles in order to increase the understanding of constraints on salmon populations. The workshop was hosted by the U.S. Geological Survey (USGS) Status and Trends (S&T) Program National Park Monitoring Project (http://www.fort.usgs.gov/brdscience/ParkMonitoring.htm), which supports USGS research on priority topics (themes) identified by the National Park Service (NPS) Inventory and Monitoring Program (I&M) and S&T. The NPS has organized more than 270 parks with significant natural resources into 32 Inventory and Monitoring (I&M) Networks (http://science.nature.nps.gov/im/networks.cfm) that share funding and core professional staff to monitor the status and long-term trends of selected natural resources (http://science.nature.nps.gov/im/monitor). All 32 networks have completed vital signs monitoring plans (available at http://science.nature.nps.gov/im/monitor/MonitoringPlans.cfm), containing background information on the important resources of each park, conceptual models behind the selection of vital signs for monitoring the condition of natural resources, and the selection of high priority vital signs for monitoring. Vital signs are particular physical, chemical, and biological elements and processes of park ecosystems that represent the overall health or condition of the park, known or hypothesized effects of stressors, or elements that have important human values (Fancy and others, 2009). Beginning in 2009, the I&M program funded projects to analyze and synthesize the biotic and abiotic data generated by vital signs monitoring and previous in-park natural resource monitoring and inventories to provide useful information, models, and tools to park managers for addressing resource management issues. The workshop described in this report is an element of the project funded by USGS NPS-I&M program to conduct a synthesis of salmon-related datasets in the Klamath (KLMN) and San Francisco Bay Area (SFAN) networks of national parks. The synthesis focused on four park units: Redwood National Park (KLMN), Point Reyes National Seashore, Muir Woods National Monument, and Golden Gate National Recreation Area (SFAN).","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121245","usgsCitation":"Madej, M.A., Torregrosa, A.A., and Woodward, A., 2012, Linking physical monitoring to coho and Chinook salmon populations in the Redwood Creek Watershed, California—Summary of May 3–4, 2012 Workshop: U.S. Geological Survey Open-File Report 2012-1245, iv, 24 p., https://doi.org/10.3133/ofr20121245.","productDescription":"iv, 24 p.","numberOfPages":"32","additionalOnlineFiles":"N","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":263490,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1245.jpg"},{"id":263488,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1245/"},{"id":263489,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1245/pdf/ofr20121245.pdf"}],"country":"United States","state":"California","city":"Arcata;Orick","otherGeospatial":"Olema Creek;Redwood National And State Parks","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.16,41.0 ], [ -124.16,41.84 ], [ -123.85,41.84 ], [ -123.85,41.0 ], [ -124.16,41.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50df8f40e4b0dfbe79e6d863","contributors":{"authors":[{"text":"Madej, Mary Ann 0000-0003-2831-3773 mary_ann_madej@usgs.gov","orcid":"https://orcid.org/0000-0003-2831-3773","contributorId":40304,"corporation":false,"usgs":true,"family":"Madej","given":"Mary","email":"mary_ann_madej@usgs.gov","middleInitial":"Ann","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":469447,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Torregrosa, Alicia A. 0000-0001-7361-2241 atorregrosa@usgs.gov","orcid":"https://orcid.org/0000-0001-7361-2241","contributorId":3471,"corporation":false,"usgs":true,"family":"Torregrosa","given":"Alicia","email":"atorregrosa@usgs.gov","middleInitial":"A.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":469446,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Woodward, Andrea 0000-0003-0604-9115 awoodward@usgs.gov","orcid":"https://orcid.org/0000-0003-0604-9115","contributorId":3028,"corporation":false,"usgs":true,"family":"Woodward","given":"Andrea","email":"awoodward@usgs.gov","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":469445,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70041035,"text":"70041035 - 2012 - Predicted eelgrass response to sea level rise and its availability to foraging Black Brant in Pacific coast estuaries","interactions":[],"lastModifiedDate":"2012-11-29T16:02:34","indexId":"70041035","displayToPublicDate":"2012-11-29T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Predicted eelgrass response to sea level rise and its availability to foraging Black Brant in Pacific coast estuaries","docAbstract":"Managers need to predict how animals will respond to habitat redistributions caused by climate change. Our objective was to model the effects of sea level rise on total eelgrass (Zostera marina) habitat area and on the amount of that area that is accessible to Brant geese (Branta bernicla), specialist grazers of eelgrass. Digital elevation models were developed for seven estuaries from Alaska, Washington, California (USA), and Mexico. Scenarios of future total eelgrass area were derived from combinations of estuarine specific sediment and tectonic rates (i.e., bottom change rate) with three rates of eustatic sea level rise (ESLR). Percentages of total eelgrass areas that were accessible to foraging Brant were determined for December when the birds overwinter at more southerly sites and in April as they move north to sites where they build body stores on their way to nesting areas in Alaska. The modeling showed that accessible eelgrass area could be lower than total area due to how daytime low-tide height, eelgrass shoot length, and the upper elevation of eelgrass determined Brant-reaching depth. Projections of future eelgrass area indicated that present-day ESLR (2.8 mm/yr) and bottom change rates should sustain the current pattern of estuarine use by Brant except in Morro Bay, where use should decrease because eelgrass is being ejected from this estuary by a positive bottom change rate. Higher ESLR rates (6.3 and 12.7 mm/yr) should result in less Brant use of estuaries at the northern and southern ends of the flyway, particularly during the winter, but more use of mid-latitude estuaries. The capacity of mid-latitude estuaries to function as Brant feeding refugia, or for these estuaries and Izembek Lagoon to provide drift rather than attached leaves, is eventually limited by the decrease in total eelgrass area, which is a result of a light extinction affect on the eelgrass, or the habitat being pushed out of the estuary by positive tectonic rates. Management responses are limited to the increase or decrease of sediment supply and the relocation of levees to allow for upslope migration of eelgrass habitat.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ecological Applications","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Ecological Society of America","publisherLocation":"Ithaca, NY","doi":"10.1890/11-1083.1","usgsCitation":"Shaughnessy, F.J., Gilkerson, W., Black, J.M., Ward, D.H., and Petrie, M., 2012, Predicted eelgrass response to sea level rise and its availability to foraging Black Brant in Pacific coast estuaries: Ecological Applications, v. 22, no. 6, p. 1743-1761, https://doi.org/10.1890/11-1083.1.","productDescription":"19 p.","startPage":"1743","endPage":"1761","ipdsId":"IP-037026","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":263499,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":263498,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1890/11-1083.1"}],"country":"Mexico;United States","state":"Alaska;California;Washington","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 173,14.5 ], [ 173,71.9 ], [ -86.7,71.9 ], [ -86.7,14.5 ], [ 173,14.5 ] ] ] } } ] }","volume":"22","issue":"6","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50e17ddee4b0ff1e7c57860e","contributors":{"authors":[{"text":"Shaughnessy, Frank J.","contributorId":75831,"corporation":false,"usgs":true,"family":"Shaughnessy","given":"Frank","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":469219,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gilkerson, Whelan","contributorId":94946,"corporation":false,"usgs":true,"family":"Gilkerson","given":"Whelan","email":"","affiliations":[],"preferred":false,"id":469221,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Black, Jeffrey M.","contributorId":77822,"corporation":false,"usgs":true,"family":"Black","given":"Jeffrey","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":469220,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ward, David H. 0000-0002-5242-2526 dward@usgs.gov","orcid":"https://orcid.org/0000-0002-5242-2526","contributorId":3247,"corporation":false,"usgs":true,"family":"Ward","given":"David","email":"dward@usgs.gov","middleInitial":"H.","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":469217,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Petrie, Mark","contributorId":18245,"corporation":false,"usgs":true,"family":"Petrie","given":"Mark","affiliations":[],"preferred":false,"id":469218,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70040996,"text":"fs20123112 - 2012 - Slope-Area Computation Program Graphical User Interface 1.0—A Preprocessing and Postprocessing Tool for Estimating Peak Flood Discharge Using the Slope-Area Method","interactions":[],"lastModifiedDate":"2012-11-28T10:18:37","indexId":"fs20123112","displayToPublicDate":"2012-11-28T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-3112","title":"Slope-Area Computation Program Graphical User Interface 1.0—A Preprocessing and Postprocessing Tool for Estimating Peak Flood Discharge Using the Slope-Area Method","docAbstract":"The slope-area method is a technique for estimating the peak discharge of a flood after the water has receded (Dalrymple and Benson, 1967). This type of discharge estimate is called an “indirect measurement” because it relies on evidence left behind by the flood, such as high-water marks (HWMs) on trees or buildings. These indicators of flood stage are combined with measurements of the cross-sectional geometry of the stream, estimates of channel roughness, and a mathematical model that balances the total energy of the flow between cross sections. This is in contrast to a “direct” measurement of discharge during the flood where cross-sectional area is measured and a current meter or acoustic equipment is used to measure the water velocity. When a direct discharge measurement cannot be made at a gage during high flows because of logistics or safety reasons, an indirect measurement of a peak discharge is useful for defining the high-flow section of the stage-discharge relation (rating curve) at the stream gage, resulting in more accurate computation of high flows. The Slope-Area Computation program (SAC; Fulford, 1994) is an implementation of the slope-area method that computes a peak-discharge estimate from inputs of water-surface slope (from surveyed HWMs), channel geometry, and estimated channel roughness. SAC is a command line program written in Fortran that reads input data from a formatted text file and prints results to another formatted text file. Preparing the input file can be time-consuming and prone to errors. This document describes the SAC graphical user interface (GUI), a crossplatform “wrapper” application that prepares the SAC input file, executes the program, and helps the user interpret the output. The SAC GUI is an update and enhancement of the slope-area method (SAM; Hortness, 2004; Berenbrock, 1996), an earlier spreadsheet tool used to aid field personnel in the completion of a slope-area measurement. The SAC GUI reads survey data, develops a plan-view plot, water-surface profile, cross-section plots, and develops the SAC input file. The SAC GUI also develops HEC-2 files that can be imported into HEC–RAS.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20123112","usgsCitation":"Bradley, D.N., 2012, Slope-Area Computation Program Graphical User Interface 1.0—A Preprocessing and Postprocessing Tool for Estimating Peak Flood Discharge Using the Slope-Area Method: U.S. Geological Survey Fact Sheet 2012-3112, 4 p., https://doi.org/10.3133/fs20123112.","productDescription":"4 p.","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":306,"text":"Geology Research and Information","active":false,"usgs":true}],"links":[{"id":263443,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs_2012_3112.gif"},{"id":263442,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2012/3112/fs2012-3112.pdf"},{"id":263441,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2012/3112/"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50e4c921e4b0e8fec6ce1663","contributors":{"authors":[{"text":"Bradley, D. Nathan","contributorId":79776,"corporation":false,"usgs":true,"family":"Bradley","given":"D.","email":"","middleInitial":"Nathan","affiliations":[],"preferred":false,"id":469194,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70048348,"text":"70048348 - 2012 - Application of empirical predictive modeling using conventional and alternative fecal indicator bacteria in eastern North Carolina waters","interactions":[],"lastModifiedDate":"2016-11-30T13:30:53","indexId":"70048348","displayToPublicDate":"2012-11-27T11:41:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3716,"text":"Water Research","onlineIssn":"1879-2448","printIssn":"0043-1354","active":true,"publicationSubtype":{"id":10}},"title":"Application of empirical predictive modeling using conventional and alternative fecal indicator bacteria in eastern North Carolina waters","docAbstract":"Coastal and estuarine waters are the site of intense anthropogenic influence with concomitant use for recreation and seafood harvesting. Therefore, coastal and estuarine water quality has a direct impact on human health. In eastern North Carolina (NC) there are over 240 recreational and 1025 shellfish harvesting water quality monitoring sites that are regularly assessed. Because of the large number of sites, sampling frequency is often only on a weekly basis. This frequency, along with an 18–24 h incubation time for fecal indicator bacteria (FIB) enumeration via culture-based methods, reduces the efficiency of the public notification process. In states like NC where beach monitoring resources are limited but historical data are plentiful, predictive models may offer an improvement for monitoring and notification by providing real-time FIB estimates. In this study, water samples were collected during 12 dry (n = 88) and 13 wet (n = 66) weather events at up to 10 sites. Statistical predictive models for Escherichiacoli (EC), enterococci (ENT), and members of the Bacteroidales group were created and subsequently validated. Our results showed that models for EC and ENT (adjusted R2 were 0.61 and 0.64, respectively) incorporated a range of antecedent rainfall, climate, and environmental variables. The most important variables for EC and ENT models were 5-day antecedent rainfall, dissolved oxygen, and salinity. These models successfully predicted FIB levels over a wide range of conditions with a 3% (EC model) and 9% (ENT model) overall error rate for recreational threshold values and a 0% (EC model) overall error rate for shellfish threshold values. Though modeling of members of the Bacteroidales group had less predictive ability (adjusted R2 were 0.56 and 0.53 for fecal Bacteroides spp. and human Bacteroides spp., respectively), the modeling approach and testing provided information on Bacteroidales ecology. This is the first example of a set of successful statistical predictive models appropriate for assessment of both recreational and shellfish harvesting water quality in estuarine waters.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Water Research","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.watres.2012.07.050","usgsCitation":"Gonzalez, R., Conn, K., Crosswell, J., and Noble, R., 2012, Application of empirical predictive modeling using conventional and alternative fecal indicator bacteria in eastern North Carolina waters: Water Research, v. 46, no. 18, p. 5871-5882, https://doi.org/10.1016/j.watres.2012.07.050.","productDescription":"12 p.","startPage":"5871","endPage":"5882","ipdsId":"IP-036574","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":278005,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":278004,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.watres.2012.07.050"}],"country":"United States","state":"North Carolina","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -76.709756,34.769892 ], [ -76.709756,34.78618 ], [ -76.669006,34.78618 ], [ -76.669006,34.769892 ], [ -76.709756,34.769892 ] ] ] } } ] }","volume":"46","issue":"18","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"524162e2e4b0ec672f073ad1","contributors":{"authors":[{"text":"Gonzalez, Raul","contributorId":17131,"corporation":false,"usgs":true,"family":"Gonzalez","given":"Raul","email":"","affiliations":[],"preferred":false,"id":484361,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conn, Kathleen E. 0000-0002-2334-6536 kconn@usgs.gov","orcid":"https://orcid.org/0000-0002-2334-6536","contributorId":3923,"corporation":false,"usgs":true,"family":"Conn","given":"Kathleen E.","email":"kconn@usgs.gov","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":484360,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Crosswell, Joey","contributorId":75437,"corporation":false,"usgs":true,"family":"Crosswell","given":"Joey","affiliations":[],"preferred":false,"id":484362,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Noble, Rachel","contributorId":82212,"corporation":false,"usgs":true,"family":"Noble","given":"Rachel","affiliations":[],"preferred":false,"id":484363,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70041089,"text":"70041089 - 2012 - Salinity adaptation of the invasive New Zealand mud snail (Potamopyrgus antipodarum) in the Columbia River estuary (Pacific Northwest, USA): Physiological and molecular studies","interactions":[],"lastModifiedDate":"2016-05-03T13:30:57","indexId":"70041089","displayToPublicDate":"2012-11-27T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":863,"text":"Aquatic Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Salinity adaptation of the invasive New Zealand mud snail (Potamopyrgus antipodarum) in the Columbia River estuary (Pacific Northwest, USA): Physiological and molecular studies","docAbstract":"In this study, we examine salinity stress tolerances of two populations of the invasive species New Zealand mud snail Potamopyrgus antipodarum, one population from a high salinity environment in the Columbia River estuary and the other from a fresh water lake. In 1996, New Zealand mud snails were discovered in the tidal reaches of the Columbia River estuary that is routinely exposed to salinity at near full seawater concentrations. In contrast, in their native habitat and throughout its spread in the western US, New Zealand mud snails are found only in fresh water ecosystems. Our aim was to determine whether the Columbia River snails have become salt water adapted. Using a modification of the standard amphipod sediment toxicity test, salinity tolerance was tested using a range of concentrations up to undiluted seawater, and the snails were sampled for mortality at daily time points. Our results show that the Columbia River snails were more tolerant of acute salinity stress with the LC50 values averaging 38 and 22 Practical Salinity Units for the Columbia River and freshwater snails, respectively. DNA sequence analysis and morphological comparisons of individuals representing each population indicate that they were all P. antipodarum. These results suggest that this species is salt water adaptable and in addition, this investigation helps elucidate the potential of this aquatic invasive organism to adapt to adverse environmental conditions.
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High flows on the gravel-bedded Cedar River in Washington are important to the geomorphic function of the river; however, high flows can deleteriously affect salmon embryos incubating in streambed gravels. A geomorphic analysis of the Cedar River showed evidence of historical changes in river form over time and quantified the effects of anthropogenic alterations to the river corridor. Field measurements with accelerometer scour monitors buried in the streambed provided insight into the depth and timing of streambed scour during high-flow events. Combined with a two-dimensional hydrodynamic model, the recorded accelerometer disturbances allowed the prediction of streambed disturbance at the burial depth of Chinook and sockeye salmon egg pockets for different peak discharges. 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In humans, acute exposure causes a neurotoxic illness known as amnesic shellfish poisoning characterized by seizures, memory loss, coma and death. Regular monitoring for high DA levels in edible shellfish tissues has been effective in protecting human consumers from acute DA exposure. However, chronic low-level DA exposure remains a concern, particularly in coastal and tribal communities that subsistence harvest shellfish known to contain low levels of the toxin. Domoic acid exposure via consumption of planktivorous fish also has a profound health impact on California sea lions (Zalophus californianus) affecting hundreds of animals yearly. Due to increasing algal toxin exposure threats globally, there is a critical need for reliable diagnostic tests for assessing chronic DA exposure in humans and wildlife. Here we report the discovery of a novel DA-specific antibody response that is a signature of chronic low-level exposure identified initially in a zebrafish exposure model and confirmed in naturally exposed wild sea lions. Additionally, we found that chronic exposure in zebrafish caused increased neurologic sensitivity to DA, revealing that repetitive exposure to DA well below the threshold for acute behavioral toxicity has underlying neurotoxic consequences. The discovery that chronic exposure to low levels of a small, water-soluble single amino acid triggers a detectable antibody response is surprising and has profound implications for the development of diagnostic tests for exposure to other pervasive environmental toxins.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"PLoS ONE","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"PLOS ONE","publisherLocation":"San Francisco, CA","doi":"10.1371/journal.pone.0036213","usgsCitation":"Lefebvre, K.A., Frame, E.R., Gulland, F., Hansen, J.D., Kendrick, P.S., Beyer, R.P., Bammler, T.K., Farin, F.M., Hiolski, E.M., Smith, D.R., and Marcinek, D.J., 2012, A novel antibody-based biomarker for chronic algal toxin exposure and sub-acute neurotoxicity: PLoS ONE, v. 7, no. 5, https://doi.org/10.1371/journal.pone.0036213.","productDescription":"7 p.","startPage":"e36213","ipdsId":"IP-036349","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":474257,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0036213","text":"Publisher Index Page"},{"id":263487,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":263484,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1371/journal.pone.0036213"}],"country":"United States","volume":"7","issue":"5","noUsgsAuthors":false,"publicationDate":"2012-05-02","publicationStatus":"PW","scienceBaseUri":"50d5aac7e4b0ba654692bcae","contributors":{"authors":[{"text":"Lefebvre, Kathi A.","contributorId":12349,"corporation":false,"usgs":true,"family":"Lefebvre","given":"Kathi","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":469411,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Frame, Elizabeth R.","contributorId":57741,"corporation":false,"usgs":true,"family":"Frame","given":"Elizabeth","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":469414,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gulland, Frances","contributorId":36441,"corporation":false,"usgs":true,"family":"Gulland","given":"Frances","affiliations":[],"preferred":false,"id":469413,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hansen, John D. 0000-0002-3006-2734 jhansen@usgs.gov","orcid":"https://orcid.org/0000-0002-3006-2734","contributorId":3440,"corporation":false,"usgs":true,"family":"Hansen","given":"John","email":"jhansen@usgs.gov","middleInitial":"D.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":469410,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kendrick, Preston S.","contributorId":36031,"corporation":false,"usgs":true,"family":"Kendrick","given":"Preston","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":469412,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Beyer, Richard P.","contributorId":93792,"corporation":false,"usgs":true,"family":"Beyer","given":"Richard","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":469418,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bammler, Theo K.","contributorId":62494,"corporation":false,"usgs":true,"family":"Bammler","given":"Theo","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":469415,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Farin, Frederico M.","contributorId":93793,"corporation":false,"usgs":true,"family":"Farin","given":"Frederico","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":469419,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hiolski, Emma M.","contributorId":106778,"corporation":false,"usgs":true,"family":"Hiolski","given":"Emma","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":469420,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Smith, Donald R.","contributorId":75408,"corporation":false,"usgs":true,"family":"Smith","given":"Donald","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":469416,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Marcinek, David J.","contributorId":75409,"corporation":false,"usgs":true,"family":"Marcinek","given":"David","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":469417,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70040866,"text":"sim3235 - 2012 - Bathymetry of the Hong and Luoc River Junction, Red River Delta, Vietnam, 2010","interactions":[],"lastModifiedDate":"2012-11-26T15:05:57","indexId":"sim3235","displayToPublicDate":"2012-11-26T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3235","title":"Bathymetry of the Hong and Luoc River Junction, Red River Delta, Vietnam, 2010","docAbstract":"The U.S. Geological Survey, in collaboration with the Water Resources University in Hanoi, Vietnam, conducted a bathymetric survey of the junction of the Hong and Luoc Rivers. The survey was done to characterize the channel morphology of this delta distributary network and provide input for hydrodynamic and sediment transport models. The survey was carried out in December 2010 using a boat-mounted multibeam echo sounder integrated with a global positioning system. A bathymetric map of the Hong and Luoc River junction was produced which was referenced to the datum of the Trieu Duong tide gage on the Luoc River.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3235","collaboration":"Prepared in collaboration with the Water Resources University, Hanoi, Vietnam","usgsCitation":"Kinzel, P.J., Nelson, J.M., Toan, D.D., Thanh, M.D., and Shimizu, Y., 2012, Bathymetry of the Hong and Luoc River Junction, Red River Delta, Vietnam, 2010: U.S. Geological Survey Scientific Investigations Map 3235, 1 Map: 41.11 x 26 inches, https://doi.org/10.3133/sim3235.","productDescription":"1 Map: 41.11 x 26 inches","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":145,"text":"Branch of Regional Research-Central Region","active":false,"usgs":true}],"links":[{"id":263382,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim_3235.gif"},{"id":263380,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3235/"},{"id":263381,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3235/SIM3235.pdf"}],"country":"Vietnam","otherGeospatial":"Hong River;Luoc River;Red River Delta","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 106.075,20.575 ], [ 106.075,20.654167 ], [ 106.141667,20.654167 ], [ 106.141667,20.575 ], [ 106.075,20.575 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50b48f81e4b0b3fb1a229138","contributors":{"authors":[{"text":"Kinzel, Paul J. 0000-0002-6076-9730 pjkinzel@usgs.gov","orcid":"https://orcid.org/0000-0002-6076-9730","contributorId":743,"corporation":false,"usgs":true,"family":"Kinzel","given":"Paul","email":"pjkinzel@usgs.gov","middleInitial":"J.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":469160,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nelson, Jonathan M. 0000-0002-7632-8526 jmn@usgs.gov","orcid":"https://orcid.org/0000-0002-7632-8526","contributorId":2812,"corporation":false,"usgs":true,"family":"Nelson","given":"Jonathan","email":"jmn@usgs.gov","middleInitial":"M.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":469161,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Toan, Duong Duc","contributorId":85059,"corporation":false,"usgs":true,"family":"Toan","given":"Duong","email":"","middleInitial":"Duc","affiliations":[],"preferred":false,"id":469164,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thanh, Mung Dinh","contributorId":30113,"corporation":false,"usgs":true,"family":"Thanh","given":"Mung","email":"","middleInitial":"Dinh","affiliations":[],"preferred":false,"id":469163,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Shimizu, Yasuyuki","contributorId":28875,"corporation":false,"usgs":false,"family":"Shimizu","given":"Yasuyuki","affiliations":[{"id":25249,"text":"Univ. of Hokkaido, Sapporo,Japan","active":true,"usgs":false}],"preferred":false,"id":469162,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70040857,"text":"sir20125256 - 2012 - Alluvial diamond resource potential and production capacity assessment of Guinea","interactions":[],"lastModifiedDate":"2022-05-27T15:40:31.211434","indexId":"sir20125256","displayToPublicDate":"2012-11-26T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-5256","title":"Alluvial diamond resource potential and production capacity assessment of Guinea","docAbstract":"In May of 2000, a meeting was convened in Kimberley, South Africa, by representatives of the diamond industry and leaders of African governments to develop a certification process intended to assure that export shipments of rough diamonds were free of conflict concerns. Outcomes of the meeting were formally supported later in December of 2000 by the United Nations in a resolution adopted by the General Assembly. By 2002, the Kimberley Process Certification Scheme (KPCS) was ratified and signed by diamond-producing and diamond-importing countries. The goal of this study was to estimate the alluvial diamond resource endowment and the current production capacity of the alluvial diamond mining sector of Guinea. A modified volume and grade methodology was used to estimate the remaining diamond reserves within Guinea's diamondiferous regions, while the diamond-production capacity of these zones was estimated by inputting the number of artisanal miners, the number of days artisans work per year, and the average grade of the deposits into a formulaic expression. Guinea's resource potential was estimated to be approximately 40 million carats, while the production capacity was estimated to lie within a range of 480,000 to 720,000 carats per year. While preliminary results have been produced by integrating historical documents, five fieldwork campaigns, and remote sensing and GIS analysis, significant data gaps remain. The artisanal mining sector is dynamic and is affected by a variety of internal and external factors. Estimates of the number of artisans and deposit variables, such as grade, vary from site to site and from zone to zone. This report has been developed on the basis of the most detailed information available at this time. However, continued fieldwork and evaluation of artisanally mined deposits would increase the accuracy of the results.","language":"English, French","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125256","collaboration":"Prepared in cooperation with the Ministère des Mines et de la Géologie of Guinea under the auspices of the U.S. Department of State","usgsCitation":"Chirico, P., Malpeli, K., Van Bockstael, M., Diaby, M., Cisse, K., Diallo, T.A., and Sano, M., 2012, Alluvial diamond resource potential and production capacity assessment of Guinea (Originally posted November 26, 2012; French Translation April 30, 2014): U.S. Geological Survey Scientific Investigations Report 2012-5256, vi, 49 p., https://doi.org/10.3133/sir20125256.","productDescription":"vi, 49 p.","numberOfPages":"59","additionalOnlineFiles":"N","costCenters":[{"id":240,"text":"Eastern Earth Surface Processes Team","active":false,"usgs":true}],"links":[{"id":263366,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20125256.gif"},{"id":263364,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5256/","linkFileType":{"id":5,"text":"html"}},{"id":263365,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5256/pdf/sir2012-5256.pdf","text":"Report (English)","linkFileType":{"id":1,"text":"pdf"}},{"id":286835,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5256/french/pdf/sir2012-5256_frenchversion.pdf","text":"Report (French)","linkFileType":{"id":1,"text":"pdf"}}],"country":"Guinea","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -15.0,7.0 ], [ -15.0,13.0 ], [ -7.25,13.0 ], [ -7.25,7.0 ], [ -15.0,7.0 ] ] ] } } ] }","edition":"Originally posted November 26, 2012; French Translation April 30, 2014","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"50b48f69e4b0b3fb1a22912c","contributors":{"authors":[{"text":"Chirico, Peter G.","contributorId":27086,"corporation":false,"usgs":true,"family":"Chirico","given":"Peter G.","affiliations":[],"preferred":false,"id":469146,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Malpeli, Katherine C.","contributorId":55106,"corporation":false,"usgs":true,"family":"Malpeli","given":"Katherine C.","affiliations":[],"preferred":false,"id":469148,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Van Bockstael, Mark","contributorId":8351,"corporation":false,"usgs":true,"family":"Van Bockstael","given":"Mark","email":"","affiliations":[],"preferred":false,"id":469144,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Diaby, Mamadou","contributorId":50057,"corporation":false,"usgs":true,"family":"Diaby","given":"Mamadou","email":"","affiliations":[],"preferred":false,"id":469147,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cisse, Kabinet","contributorId":66140,"corporation":false,"usgs":true,"family":"Cisse","given":"Kabinet","email":"","affiliations":[],"preferred":false,"id":469149,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Diallo, Thierno Amadou","contributorId":80987,"corporation":false,"usgs":true,"family":"Diallo","given":"Thierno","email":"","middleInitial":"Amadou","affiliations":[],"preferred":false,"id":469150,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sano, Mahmoud","contributorId":23406,"corporation":false,"usgs":true,"family":"Sano","given":"Mahmoud","email":"","affiliations":[],"preferred":false,"id":469145,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ]}