{"pageNumber":"589","pageRowStart":"14700","pageSize":"25","recordCount":46688,"records":[{"id":70043097,"text":"ds735 - 2013 - Seafloor video footage and still-frame grabs from U.S. Geological Survey cruises in Hawaiian nearshore waters","interactions":[],"lastModifiedDate":"2013-02-12T10:22:28","indexId":"ds735","displayToPublicDate":"2013-02-05T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"735","title":"Seafloor video footage and still-frame grabs from U.S. Geological Survey cruises in Hawaiian nearshore waters","docAbstract":"Underwater video footage was collected in nearshore waters (<60-meter depth) off the Hawaiian Islands from 2002 to 2011 as part of the U.S. Geological Survey (USGS) Coastal and Marine Geology Program's Pacific Coral Reef Project, to improve seafloor characterization and for the development and ground-truthing of benthic-habitat maps. This report includes nearly 53 hours of digital underwater video footage collected during four USGS cruises and more than 10,200 still images extracted from the videos, including still frames from every 10 seconds along transect lines, and still frames showing both an overview and a near-bottom view from fixed stations. Environmental Systems Research Institute (ESRI) shapefiles of individual video and still-image locations, and Google Earth kml files with explanatory text and links to the video and still images, are included. This report documents the various camera systems and methods used to collect the videos, and the techniques and software used to convert the analog video tapes into digital data in order to process the images for optimum viewing and to extract the still images, along with a brief summary of each survey cruise.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds735","usgsCitation":"Gibbs, A.E., Cochran, S., and Tierney, P.W., 2013, Seafloor video footage and still-frame grabs from U.S. Geological Survey cruises in Hawaiian nearshore waters: U.S. Geological Survey Data Series 735, Report: iv, 11 p.; Videos; Stills; Shapefiles; Google Earth kml files, https://doi.org/10.3133/ds735.","productDescription":"Report: iv, 11 p.; Videos; Stills; Shapefiles; Google Earth kml files","numberOfPages":"20","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":266972,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds_735.gif"},{"id":267266,"type":{"id":14,"text":"Image"},"url":"https://pubs.usgs.gov/ds/735/VideoStills"},{"id":267267,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/735/shapefiles"},{"id":267268,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/735/kml"},{"id":267265,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/735/Video"},{"id":266971,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/735/ds735_text.pdf"},{"id":266970,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/735/"}],"country":"United States","state":"Hawai'i","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -157.8186,20.4836 ], [ -157.8186,21.4224 ], [ -156.3629,21.4224 ], [ -156.3629,20.4836 ], [ -157.8186,20.4836 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51122a00e4b0ebe69d7eb608","contributors":{"authors":[{"text":"Gibbs, Ann E. 0000-0002-0883-3774 agibbs@usgs.gov","orcid":"https://orcid.org/0000-0002-0883-3774","contributorId":2644,"corporation":false,"usgs":true,"family":"Gibbs","given":"Ann","email":"agibbs@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":472945,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cochran, Susan A.","contributorId":27533,"corporation":false,"usgs":true,"family":"Cochran","given":"Susan A.","affiliations":[],"preferred":false,"id":472946,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tierney, Peter W.","contributorId":68187,"corporation":false,"usgs":true,"family":"Tierney","given":"Peter","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":472947,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70043094,"text":"ofr20131002 - 2013 - New vitrinite reflectance data for the Wind River Basin, Wyoming","interactions":[],"lastModifiedDate":"2013-02-12T10:27:15","indexId":"ofr20131002","displayToPublicDate":"2013-02-05T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-1002","title":"New vitrinite reflectance data for the Wind River Basin, Wyoming","docAbstract":"The Wind River Basin is a large Laramide (Late Cretaceous through Eocene) structural and sedimentary basin that encompasses about 7,400 square miles in central Wyoming. The basin is bounded by the Washakie Range and Owl Creek and southern Bighorn Mountains on the north, the Casper arch on the east and northeast, and the Granite Mountains on the south, and Wind River Range on the west. The purpose of this report is to present new vitrinite reflectance data collected mainly from Cretaceous marine shales in the Wind River Basin to better characterize their thermal maturity and hydrocarbon potential.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131002","usgsCitation":"Pawlewicz, M.J., and Finn, T.M., 2013, New vitrinite reflectance data for the Wind River Basin, Wyoming: U.S. Geological Survey Open-File Report 2013-1002, iii, 11 p., https://doi.org/10.3133/ofr20131002.","productDescription":"iii, 11 p.","numberOfPages":"14","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-040666","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":266975,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2013_1002.gif"},{"id":266973,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1002/"},{"id":266974,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1002/OF13-1002.pdf"}],"country":"United States","state":"Arizona;Colorado;Idaho;Montana;Nebraska;New Mexico;North Dakota;South Dakota;Wyoming","otherGeospatial":"Wind River Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -112.37,35.87 ], [ -112.37,46.07 ], [ -102.46,46.07 ], [ -102.46,35.87 ], [ -112.37,35.87 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"511229fee4b0ebe69d7eb604","contributors":{"authors":[{"text":"Pawlewicz, Mark J. pawlewicz@usgs.gov","contributorId":752,"corporation":false,"usgs":true,"family":"Pawlewicz","given":"Mark","email":"pawlewicz@usgs.gov","middleInitial":"J.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":472943,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Finn, Thomas M. 0000-0001-6396-9351 finn@usgs.gov","orcid":"https://orcid.org/0000-0001-6396-9351","contributorId":778,"corporation":false,"usgs":true,"family":"Finn","given":"Thomas","email":"finn@usgs.gov","middleInitial":"M.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":472944,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70047357,"text":"70047357 - 2013 - Deep subsurface drip irrigation using coal-bed sodic water: part I. water and solute movement","interactions":[],"lastModifiedDate":"2013-08-01T15:34:53","indexId":"70047357","displayToPublicDate":"2013-02-01T15:26:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":680,"text":"Agricultural Water Management","active":true,"publicationSubtype":{"id":10}},"title":"Deep subsurface drip irrigation using coal-bed sodic water: part I. water and solute movement","docAbstract":"Water co-produced with coal-bed methane (CBM) in the semi-arid Powder River Basin of Wyoming and Montana commonly has relatively low salinity and high sodium adsorption ratios that can degrade soil permeability where used for irrigation. Nevertheless, a desire to derive beneficial use from the water and a need to dispose of large volumes of it have motivated the design of a deep subsurface drip irrigation (SDI) system capable of utilizing that water. Drip tubing is buried 92 cm deep and irrigates at a relatively constant rate year-round, while evapotranspiration by the alfalfa and grass crops grown is seasonal. We use field data from two sites and computer simulations of unsaturated flow to understand water and solute movements in the SDI fields. Combined irrigation and precipitation exceed potential evapotranspiration by 300-480 mm annually. Initially, excess water contributes to increased storage in the unsaturated zone, and then drainage causes cyclical rises in the water table beneath the fields. Native chloride and nitrate below 200 cm depth are leached by the drainage. Some CBM water moves upward from the drip tubing, drawn by drier conditions above. Chloride from CBM water accumulates there as root uptake removes the water. Year over year accumulations indicated by computer simulations illustrate that infiltration of precipitation water from the surface only partially leaches such accumulations away. Field data show that 7% and 27% of added chloride has accumulated above the drip tubing in an alfalfa and grass field, respectively, following 6 years of irrigation. Maximum chloride concentrations in the alfalfa field are around 45 cm depth but reach the surface in parts of the grass field, illustrating differences driven by crop physiology. Deep SDI offers a means of utilizing marginal quality irrigation waters and managing the accumulation of their associated solutes in the crop rooting zone.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Agricultural Water Management","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.agwat.2012.11.014","usgsCitation":"Bern, C., Breit, G.N., Healy, R.W., Zupancic, J.W., and Hammack, R., 2013, Deep subsurface drip irrigation using coal-bed sodic water: part I. water and solute movement: Agricultural Water Management, v. 118, p. 122-134, https://doi.org/10.1016/j.agwat.2012.11.014.","productDescription":"13 p.","startPage":"122","endPage":"134","numberOfPages":"13","ipdsId":"IP-036926","costCenters":[{"id":218,"text":"Denver Federal Center","active":false,"usgs":true}],"links":[{"id":275891,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":275800,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.agwat.2012.11.014"},{"id":275801,"type":{"id":15,"text":"Index Page"},"url":"https://www.sciencedirect.com/science/article/pii/S0378377412003071"}],"country":"United States","state":"Wyoming","otherGeospatial":"Powder River Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -106.858878,44.690745 ], [ -106.858878,44.955734 ], [ -106.269986,44.955734 ], [ -106.269986,44.690745 ], [ -106.858878,44.690745 ] ] ] } } ] }","volume":"118","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51fbca70e4b04b00e3d88fa0","chorus":{"doi":"10.1016/j.agwat.2012.11.014","url":"http://dx.doi.org/10.1016/j.agwat.2012.11.014","publisher":"Elsevier BV","authors":"Bern Carleton R., Breit George N., Healy Richard W., Zupancic John W., Hammack Richard","journalName":"Agricultural Water Management","publicationDate":"2/2013","auditedOn":"11/1/2014"},"contributors":{"authors":[{"text":"Bern, Carleton R.","contributorId":59325,"corporation":false,"usgs":true,"family":"Bern","given":"Carleton R.","affiliations":[],"preferred":false,"id":481812,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Breit, George N. 0000-0003-2188-6798 gbreit@usgs.gov","orcid":"https://orcid.org/0000-0003-2188-6798","contributorId":1480,"corporation":false,"usgs":true,"family":"Breit","given":"George","email":"gbreit@usgs.gov","middleInitial":"N.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":481810,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Healy, Richard W. 0000-0002-0224-1858 rwhealy@usgs.gov","orcid":"https://orcid.org/0000-0002-0224-1858","contributorId":658,"corporation":false,"usgs":true,"family":"Healy","given":"Richard","email":"rwhealy@usgs.gov","middleInitial":"W.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":481809,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zupancic, John W.","contributorId":73885,"corporation":false,"usgs":true,"family":"Zupancic","given":"John","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":481813,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hammack, Richard","contributorId":44449,"corporation":false,"usgs":true,"family":"Hammack","given":"Richard","affiliations":[],"preferred":false,"id":481811,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70199859,"text":"70199859 - 2013 - Modeling plant species distributions under future climates: how fine scale do climate projections need to be?","interactions":[],"lastModifiedDate":"2018-10-01T14:47:22","indexId":"70199859","displayToPublicDate":"2013-02-01T14:46:36","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"Modeling plant species distributions under future climates: how fine scale do climate projections need to be?","docAbstract":"<p><span>Recent studies suggest that species distribution models (SDMs) based on fine‐scale climate data may provide markedly different estimates of climate‐change impacts than coarse‐scale models. However, these studies disagree in their conclusions of how scale influences projected species distributions. In rugged terrain, coarse‐scale climate grids may not capture topographically controlled climate variation at the scale that constitutes microhabitat or refugia for some species. Although finer scale data are therefore considered to better reflect climatic conditions experienced by species, there have been few formal analyses of how modeled distributions differ with scale. We modeled distributions for 52 plant species endemic to the California Floristic Province of different life forms and range sizes under recent and future climate across a 2000‐fold range of spatial scales (0.008–16&nbsp;km</span><sup>2</sup><span>). We produced unique current and future climate datasets by separately downscaling 4 km climate models to three finer resolutions based on 800, 270, and 90&nbsp;m digital elevation models and deriving bioclimatic predictors from them. As climate‐data resolution became coarser, SDMs predicted larger habitat area with diminishing spatial congruence between fine‐ and coarse‐scale predictions. These trends were most pronounced at the coarsest resolutions and depended on climate scenario and species' range size. On average, SDMs projected onto 4 km climate data predicted 42% more stable habitat (the amount of spatial overlap between predicted current and future climatically suitable habitat) compared with 800&nbsp;m data. We found only modest agreement between areas predicted to be stable by 90 m models generalized to 4 km grids compared with areas classified as stable based on 4&nbsp;km models, suggesting that some climate refugia captured at finer scales may be missed using coarser scale data. These differences in projected locations of habitat change may have more serious implications than net habitat area when predictive maps form the basis of conservation decision making.</span></p>","language":"English","publisher":"Wiley","doi":"10.1111/gcb.12051","usgsCitation":"Franklin, J., Davis, F.W., Ikegami, M., Syphard, A.D., Flint, L.E., Flint, A.L., and Hannah, L., 2013, Modeling plant species distributions under future climates: how fine scale do climate projections need to be?: Global Change Biology, v. 19, no. 2, p. 473-483, https://doi.org/10.1111/gcb.12051.","productDescription":"11 p.","startPage":"473","endPage":"483","ipdsId":"IP-041557","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":473956,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://escholarship.org/uc/item/75k42636","text":"External 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aflint@usgs.gov","orcid":"https://orcid.org/0000-0002-5118-751X","contributorId":1492,"corporation":false,"usgs":true,"family":"Flint","given":"Alan","email":"aflint@usgs.gov","middleInitial":"L.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":746936,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hannah, Lee","contributorId":208392,"corporation":false,"usgs":false,"family":"Hannah","given":"Lee","email":"","affiliations":[{"id":16938,"text":"Conservation International","active":true,"usgs":false}],"preferred":false,"id":746941,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70048507,"text":"70048507 - 2013 - Dynamics of seabird colonies vulnerable to sea-level rise at French Frigate Shoals, Hawai`i","interactions":[],"lastModifiedDate":"2016-10-19T13:57:41","indexId":"70048507","displayToPublicDate":"2013-02-01T14:21:10","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"seriesTitle":{"id":257,"text":"Hawai‘i Cooperative Studies Unit Technical Report","active":false,"publicationSubtype":{"id":3}},"seriesNumber":"HCSU-037","title":"Dynamics of seabird colonies vulnerable to sea-level rise at French Frigate Shoals, Hawai`i","docAbstract":"Globally, seabirds are vulnerable to anthropogenic threats both at sea and on land. Seabirds \ntypically nest colonially and show strong site fidelity; therefore, conservation strategies could \nbenefit from an understanding of the population dynamics and vulnerability of breeding colonies \nto climate change. More than 350 atolls exist across the Pacific Ocean; while they provide \nnesting habitat for many seabirds, they are also vulnerable to sea-level rise. We used French \nFrigate Shoals, the largest atoll in the Hawaiian Archipelago, as a case study to explore seabird \ncolony dynamics and the potential consequences of sea-level rise. We compiled a unique \ncombination of data sets: historical observations of islands and seabirds, a 30-year time series \nof population abundance, LiDAR- (light detection and ranging) derived elevations, and satellite\nimagery. To model population dynamics for ten species at Tern Island from 1980 to 2009, we \nused the Gompertz model with parameters for the population growth rate, density dependence, \nprocess variation, and observation error. We used a Bayesian approach to estimate the \nparameters. All species increased in a pattern that provided evidence of density dependence. \nDensity dependence may exacerbate the consequences of sea-level rise on seabirds because \nspecies that are already near the carrying capacity of the nesting habitat will be limited more \nthan species that still have space for population growth. Laysan Albatross (<i>Phoebastria \nimmutabilis</i>), Great Frigatebird (<i>Fregata minor</i>), Red-tailed Tropicbird (<i>Phaethon rubricauda</i>),\nMasked Booby (<i>Sula dactylatra</i>), Gray-backed Tern (<i>Onychoprion lunatus</i>), and White Tern\n(<i>Gygis alba</i>) are likely already at carrying capacity at Tern Island and therefore are most likely \nto be negatively impacted by sea-level rise. We project 12% of French Frigate Shoals (excluding \nLa Perouse Pinnacle) will be inundated with +1.0 m sea-level rise or 32% with +2.0 m. Gray-backed Terns that nest along the coastal perimeters of islands and shrub-nesting species that \nare habitat limited are especially vulnerable to sea-level rise. However, at Tern Island, seawalls\nand habitat creation may mitigate projected seabird population declines due to habitat loss. We \npredict substantial losses in seabird nesting habitat across the low-lying Hawaiian Islands by \n2100 and emphasize the need to restore higher elevation seabird colonies.","language":"English","publisher":"University of Hawai‘i at Hilo","publisherLocation":"Hilo, HI","usgsCitation":"Reynolds, M.H., Courtot, K., Krause, C.M., Seavy, N., Hartzell, P., and Hatfield, J.S., 2013, Dynamics of seabird colonies vulnerable to sea-level rise at French Frigate Shoals, Hawai`i: Hawai‘i Cooperative Studies Unit Technical Report HCSU-037, iv, 32 p.","productDescription":"iv, 32 p.","numberOfPages":"38","ipdsId":"IP-042488","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":279192,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":279191,"type":{"id":15,"text":"Index Page"},"url":"https://hilo.hawaii.edu/hcsu/publications.php"}],"country":"United States","state":"Hawai'i","otherGeospatial":"French Frigate Shoals","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -179.89,14.96 ], [ -179.89,35.48 ], [ -151.24,35.48 ], [ -151.24,14.96 ], [ -179.89,14.96 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"528c96ace4b0c629af44dda3","contributors":{"authors":[{"text":"Reynolds, Michelle H. 0000-0001-7253-8158 mreynolds@usgs.gov","orcid":"https://orcid.org/0000-0001-7253-8158","contributorId":3871,"corporation":false,"usgs":true,"family":"Reynolds","given":"Michelle","email":"mreynolds@usgs.gov","middleInitial":"H.","affiliations":[{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true},{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"preferred":true,"id":484874,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Courtot, Karen N.","contributorId":26909,"corporation":false,"usgs":true,"family":"Courtot","given":"Karen N.","affiliations":[],"preferred":false,"id":484876,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Krause, Crystal M.","contributorId":101919,"corporation":false,"usgs":true,"family":"Krause","given":"Crystal","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":484879,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Seavy, Nathaniel E.","contributorId":19829,"corporation":false,"usgs":true,"family":"Seavy","given":"Nathaniel E.","affiliations":[],"preferred":false,"id":484875,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hartzell, Paula","contributorId":69050,"corporation":false,"usgs":true,"family":"Hartzell","given":"Paula","email":"","affiliations":[],"preferred":false,"id":484877,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hatfield, Jeff S.","contributorId":95187,"corporation":false,"usgs":true,"family":"Hatfield","given":"Jeff","email":"","middleInitial":"S.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":484878,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70046974,"text":"70046974 - 2013 - Regional contingencies in the relationship between aboveground Bbomass and litter in the world’s grasslands","interactions":[],"lastModifiedDate":"2013-07-12T12:47:17","indexId":"70046974","displayToPublicDate":"2013-02-01T12:39:11","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Regional contingencies in the relationship between aboveground Bbomass and litter in the world’s grasslands","docAbstract":"Based on regional-scale studies, aboveground production and litter decomposition are thought to positively covary, because they are driven by shared biotic and climatic factors. Until now we have been unable to test whether production and decomposition are generally coupled across climatically dissimilar regions, because we lacked replicated data collected within a single vegetation type across multiple regions, obfuscating the drivers and generality of the association between production and decomposition. Furthermore, our understanding of the relationships between production and decomposition rests heavily on separate meta-analyses of each response, because no studies have simultaneously measured production and the accumulation or decomposition of litter using consistent methods at globally relevant scales. Here, we use a multi-country grassland dataset collected using a standardized protocol to show that live plant biomass (an estimate of aboveground net primary production) and litter disappearance (represented by mass loss of aboveground litter) do not strongly covary. Live biomass and litter disappearance varied at different spatial scales. There was substantial variation in live biomass among continents, sites and plots whereas among continent differences accounted for most of the variation in litter disappearance rates. Although there were strong associations among aboveground biomass, litter disappearance and climatic factors in some regions (e.g. U.S. Great Plains), these relationships were inconsistent within and among the regions represented by this study. These results highlight the importance of replication among regions and continents when characterizing the correlations between ecosystem processes and interpreting their global-scale implications for carbon flux. We must exercise caution in parameterizing litter decomposition and aboveground production in future regional and global carbon models as their relationship is complex.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"PLoS ONE","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"PLoS ONE","doi":"10.1371/journal.pone.0054988","usgsCitation":"O’Halloran, L., Borer, E.T., Seabloom, E.W., MacDougall, A.S., Cleland, E., McCulley, R.L., Hobbie, S., Harpole, W.S., DeCrappeo, N.M., Chu, C., Bakker, J.D., Davies, K.F., Du, G., Firn, J., Hagenah, N., Hofmockel, K.S., Knops, J.M., Li, W., Melbourne, B.A., Morgan, J.W., Orrock, J., Prober, S.M., and Stevens, C.J., 2013, Regional contingencies in the relationship between aboveground Bbomass and litter in the world’s grasslands: PLoS ONE, v. 8, no. 2, e54988, 9 p., https://doi.org/10.1371/journal.pone.0054988.","productDescription":"e54988, 9 p.","ipdsId":"IP-044989","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":473961,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0054988","text":"Publisher Index Page"},{"id":274924,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":274869,"type":{"id":15,"text":"Index Page"},"url":"https://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0054988"},{"id":274923,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1371/journal.pone.0054988"}],"otherGeospatial":"Earth","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -180.0,-90.0 ], [ -180.0,90.0 ], [ 180.0,90.0 ], [ 180.0,-90.0 ], [ -180.0,-90.0 ] ] ] } } ] }","volume":"8","issue":"2","noUsgsAuthors":false,"publicationDate":"2013-02-06","publicationStatus":"PW","scienceBaseUri":"51e1256fe4b02f5cae2b73ce","contributors":{"authors":[{"text":"O’Halloran, Lydia R.","contributorId":72280,"corporation":false,"usgs":true,"family":"O’Halloran","given":"Lydia R.","affiliations":[],"preferred":false,"id":480761,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Borer, Elizabeth T.","contributorId":45049,"corporation":false,"usgs":false,"family":"Borer","given":"Elizabeth","email":"","middleInitial":"T.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":480755,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Seabloom, Eric W.","contributorId":60762,"corporation":false,"usgs":false,"family":"Seabloom","given":"Eric","email":"","middleInitial":"W.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":480757,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"MacDougall, Andrew S.","contributorId":39509,"corporation":false,"usgs":true,"family":"MacDougall","given":"Andrew","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":480754,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cleland, Elsa E.","contributorId":92790,"corporation":false,"usgs":true,"family":"Cleland","given":"Elsa E.","affiliations":[],"preferred":false,"id":480768,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McCulley, Rebecca L.","contributorId":102197,"corporation":false,"usgs":true,"family":"McCulley","given":"Rebecca","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":480770,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hobbie, Sarah","contributorId":64973,"corporation":false,"usgs":true,"family":"Hobbie","given":"Sarah","affiliations":[],"preferred":false,"id":480758,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Harpole, W. Stan","contributorId":27340,"corporation":false,"usgs":true,"family":"Harpole","given":"W.","email":"","middleInitial":"Stan","affiliations":[],"preferred":false,"id":480752,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"DeCrappeo, Nicole M.","contributorId":92383,"corporation":false,"usgs":true,"family":"DeCrappeo","given":"Nicole","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":480767,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Chu, Cheng-Jin","contributorId":45820,"corporation":false,"usgs":true,"family":"Chu","given":"Cheng-Jin","email":"","affiliations":[],"preferred":false,"id":480756,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Bakker, Jonathan D.","contributorId":15754,"corporation":false,"usgs":true,"family":"Bakker","given":"Jonathan","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":480749,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Davies, Kendi F.","contributorId":30346,"corporation":false,"usgs":true,"family":"Davies","given":"Kendi","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":480753,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Du, Guozhen","contributorId":89429,"corporation":false,"usgs":true,"family":"Du","given":"Guozhen","email":"","affiliations":[],"preferred":false,"id":480765,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Firn, Jennifer","contributorId":66405,"corporation":false,"usgs":false,"family":"Firn","given":"Jennifer","email":"","affiliations":[],"preferred":false,"id":480759,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Hagenah, Nicole","contributorId":95998,"corporation":false,"usgs":true,"family":"Hagenah","given":"Nicole","affiliations":[],"preferred":false,"id":480769,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Hofmockel, Kirsten S.","contributorId":69038,"corporation":false,"usgs":false,"family":"Hofmockel","given":"Kirsten","email":"","middleInitial":"S.","affiliations":[{"id":12468,"text":"Department of Ecology, Evolution and Organismal Biology, Iowa State University, Ames, IA","active":true,"usgs":false}],"preferred":false,"id":480760,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Knops, Johannes M.H.","contributorId":105843,"corporation":false,"usgs":true,"family":"Knops","given":"Johannes","email":"","middleInitial":"M.H.","affiliations":[],"preferred":false,"id":480771,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Li, Wei","contributorId":22894,"corporation":false,"usgs":true,"family":"Li","given":"Wei","email":"","affiliations":[],"preferred":false,"id":480751,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Melbourne, Brett A.","contributorId":86473,"corporation":false,"usgs":true,"family":"Melbourne","given":"Brett","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":480763,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Morgan, John W.","contributorId":88077,"corporation":false,"usgs":true,"family":"Morgan","given":"John","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":480764,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Orrock, John L.","contributorId":18101,"corporation":false,"usgs":true,"family":"Orrock","given":"John L.","affiliations":[],"preferred":false,"id":480750,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Prober, Suzanne M.","contributorId":74498,"corporation":false,"usgs":false,"family":"Prober","given":"Suzanne","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":480762,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Stevens, Carly J.","contributorId":89658,"corporation":false,"usgs":true,"family":"Stevens","given":"Carly","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":480766,"contributorType":{"id":1,"text":"Authors"},"rank":23}]}}
,{"id":70118057,"text":"70118057 - 2013 - VisTrails SAHM: visualization and workflow management for species habitat modeling","interactions":[],"lastModifiedDate":"2018-09-21T11:22:56","indexId":"70118057","displayToPublicDate":"2013-02-01T11:48:13","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1446,"text":"Ecography: Pattern and Diversity in Ecology","active":true,"publicationSubtype":{"id":10}},"title":"VisTrails SAHM: visualization and workflow management for species habitat modeling","docAbstract":"The Software for Assisted Habitat Modeling (SAHM) has been created to both expedite habitat modeling and help maintain a record of the various input data, pre- and post-processing steps and modeling options incorporated in the construction of a species distribution model through the established workflow management and visualization VisTrails software. This paper provides an overview of the VisTrails:SAHM software including a link to the open source code, a table detailing the current SAHM modules, and a simple example modeling an invasive weed species in Rocky Mountain National Park, USA.","language":"English","publisher":"Wiley","doi":"10.1111/j.1600-0587.2012.07815.x","usgsCitation":"Morisette, J.T., Jarnevich, C.S., Holcombe, T.R., Talbert, C., Ignizio, D.A., Talbert, M., Silva, C., Koop, D., Swanson, A., and Young, N.E., 2013, VisTrails SAHM: visualization and workflow management for species habitat modeling: Ecography: Pattern and Diversity in Ecology, v. 36, no. 2, p. 129-135, https://doi.org/10.1111/j.1600-0587.2012.07815.x.","productDescription":"7 p.","startPage":"129","endPage":"135","numberOfPages":"7","ipdsId":"IP-037234","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":477,"text":"North Central Climate Science Center","active":true,"usgs":true},{"id":37226,"text":"Core Science Analytics, Synthesis, and Libraries","active":true,"usgs":true}],"links":[{"id":291001,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":291000,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/j.1600-0587.2012.07815.x"}],"volume":"36","issue":"2","noUsgsAuthors":false,"publicationDate":"2013-01-25","publicationStatus":"PW","scienceBaseUri":"57f7f357e4b0bc0bec0a090f","contributors":{"authors":[{"text":"Morisette, Jeffrey T. 0000-0002-0483-0082 morisettej@usgs.gov","orcid":"https://orcid.org/0000-0002-0483-0082","contributorId":307,"corporation":false,"usgs":true,"family":"Morisette","given":"Jeffrey","email":"morisettej@usgs.gov","middleInitial":"T.","affiliations":[{"id":477,"text":"North Central Climate Science Center","active":true,"usgs":true},{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":496200,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jarnevich, Catherine S. 0000-0002-9699-2336 jarnevichc@usgs.gov","orcid":"https://orcid.org/0000-0002-9699-2336","contributorId":3424,"corporation":false,"usgs":true,"family":"Jarnevich","given":"Catherine","email":"jarnevichc@usgs.gov","middleInitial":"S.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":496201,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Holcombe, Tracy R. holcombet@usgs.gov","contributorId":3694,"corporation":false,"usgs":true,"family":"Holcombe","given":"Tracy","email":"holcombet@usgs.gov","middleInitial":"R.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":496202,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Talbert, Colin B. talbertc@usgs.gov","contributorId":147948,"corporation":false,"usgs":true,"family":"Talbert","given":"Colin B.","email":"talbertc@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":496209,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ignizio, Drew A. 0000-0001-8054-5139 dignizio@usgs.gov","orcid":"https://orcid.org/0000-0001-8054-5139","contributorId":139842,"corporation":false,"usgs":true,"family":"Ignizio","given":"Drew","email":"dignizio@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":496207,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Talbert, Marian mtalbert@usgs.gov","contributorId":5180,"corporation":false,"usgs":true,"family":"Talbert","given":"Marian","email":"mtalbert@usgs.gov","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":477,"text":"North Central Climate Science Center","active":true,"usgs":true}],"preferred":false,"id":496203,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Silva, Claudio","contributorId":48486,"corporation":false,"usgs":true,"family":"Silva","given":"Claudio","email":"","affiliations":[],"preferred":false,"id":496204,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Koop, David","contributorId":83845,"corporation":false,"usgs":true,"family":"Koop","given":"David","email":"","affiliations":[],"preferred":false,"id":496206,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Swanson, Alan","contributorId":99054,"corporation":false,"usgs":true,"family":"Swanson","given":"Alan","email":"","affiliations":[],"preferred":false,"id":496208,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Young, Nicholas E.","contributorId":58572,"corporation":false,"usgs":true,"family":"Young","given":"Nicholas","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":496205,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}}
,{"id":70118043,"text":"70118043 - 2013 - Valuing morbidity from wildfire smoke exposure: a comparison of revealed and stated preference techniques","interactions":[],"lastModifiedDate":"2014-07-25T10:55:51","indexId":"70118043","displayToPublicDate":"2013-02-01T10:45:49","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2598,"text":"Land Economics","active":true,"publicationSubtype":{"id":10}},"title":"Valuing morbidity from wildfire smoke exposure: a comparison of revealed and stated preference techniques","docAbstract":"<p>Estimating the economic benefits of reduced health damages due to improvements in environmental quality continues to challenge economists. We review welfare measures associated with reduced wildfire smoke exposure, and a unique dataset from California’s Station Fire of 2009 allows for a comparison of cost of illness (COI) estimates with willingness to pay (WTP) measures. The WTP for one less symptom day is estimated to be $87 and $95, using the defensive behavior and contingent valuation methods, respectively. These WTP estimates are not statistically different but do differ from a $3 traditional daily COI estimate and $17 comprehensive daily COI estimate.</p>","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Land Economics","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"University of Wisconsin Press","publisherLocation":"Madison, WI","usgsCitation":"Richardson, L., Loomis, J., and Champ, P.A., 2013, Valuing morbidity from wildfire smoke exposure: a comparison of revealed and stated preference techniques: Land Economics, v. 89, no. 1, p. 76-100.","productDescription":"25 p.","startPage":"76","endPage":"100","numberOfPages":"25","costCenters":[],"links":[{"id":290986,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"89","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57f7f357e4b0bc0bec0a0911","contributors":{"authors":[{"text":"Richardson, Leslie","contributorId":35584,"corporation":false,"usgs":true,"family":"Richardson","given":"Leslie","affiliations":[],"preferred":false,"id":496174,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Loomis, John B.","contributorId":27560,"corporation":false,"usgs":true,"family":"Loomis","given":"John B.","affiliations":[],"preferred":false,"id":496173,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Champ, Patricia A.","contributorId":97011,"corporation":false,"usgs":true,"family":"Champ","given":"Patricia","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":496175,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70048536,"text":"70048536 - 2013 - Monitoring the status of forests and rangelands in the Western United States using ecosystem performance anomalies","interactions":[],"lastModifiedDate":"2013-10-24T10:39:43","indexId":"70048536","displayToPublicDate":"2013-02-01T10:28:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2068,"text":"International Journal of Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Monitoring the status of forests and rangelands in the Western United States using ecosystem performance anomalies","docAbstract":"The effects of land management and disturbance on ecosystem performance (i.e. biomass production) are often confounded by those of weather and site potential. The current study overcomes this issue by calculating the difference between actual and expected ecosystem performance (EEP) to generate ecosystem performance anomalies (EPA). This study aims to delineate and quantify average EPA from 2000–2009 within the Greater Platte and Upper Colorado River Basins, USA. Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI) images averaged over the growing season (GSN) served as a proxy of actual ecosystem performance. Yearly EEP was determined with rule-based piecewise regression tree models of abiotic data (climate, soils, elevation, etc.), independently created for each land cover. EPA were calculated as the residuals of the EEP to GSN relationship, and characterized as normal performing, underperforming, and overperforming at the 90% confidence level. Validation revealed that EPA values were related to biomass production (R<sup>2</sup> = 0.56, P = 0.02) and likely to the proportion of biomass removed by livestock in the Nebraska Sandhills. Overall, 60.6% of the study area was (normal) performing near its EEP, 3.0% was severely underperforming, 5.0% was highly overperforming, and the remainder was slightly underperforming or overperforming. Generally, disturbances such as fires, floods, and insect damage, in addition to high grazing intensity, result in a negative EPA. Conversely, mature stands and appropriate management often result in positive EPA values. This method provides information critical to land managers to evaluate the appropriateness of previous management practices and restoration efforts and quantify disturbance impacts. Results are at a scale sufficient for many of the large management units of the region and for locating areas needing further investigation. Applications of EPA data to monitoring invasive species, grazing impacts, and vulnerability to plant community shifts have been suggested by land management professionals.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"International Journal of Remote Sensing","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Taylor & Francis","doi":"10.1080/01431161.2013.772311","usgsCitation":"Rigge, M.B., Wylie, B., Gu, Y., Belnap, J., Phuyal, K.P., and Tieszen, L., 2013, Monitoring the status of forests and rangelands in the Western United States using ecosystem performance anomalies: International Journal of Remote Sensing, v. 34, no. 11, p. 4049-4068, https://doi.org/10.1080/01431161.2013.772311.","productDescription":"20 p.","startPage":"4049","endPage":"4068","numberOfPages":"20","ipdsId":"IP-037558","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":278369,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":278368,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1080/01431161.2013.772311"}],"country":"United States","state":"Arizona;Colorado;Kansas;Nebraska;New Mexico;South Dakota;Utah;Wyoming","otherGeospatial":"Greater Platte;Upper Colorado River Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -112.27,33.33 ], [ -112.27,43.68 ], [ -96.09,43.68 ], [ -96.09,33.33 ], [ -112.27,33.33 ] ] ] } } ] }","volume":"34","issue":"11","noUsgsAuthors":false,"publicationDate":"2013-02-27","publicationStatus":"PW","scienceBaseUri":"526a4172e4b0c0d229f9f682","contributors":{"authors":[{"text":"Rigge, Matthew B. 0000-0003-4471-8009 mrigge@usgs.gov","orcid":"https://orcid.org/0000-0003-4471-8009","contributorId":751,"corporation":false,"usgs":true,"family":"Rigge","given":"Matthew","email":"mrigge@usgs.gov","middleInitial":"B.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":484995,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":484999,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gu, Yingxin 0000-0002-3544-1856 ygu@usgs.gov","orcid":"https://orcid.org/0000-0002-3544-1856","contributorId":409,"corporation":false,"usgs":true,"family":"Gu","given":"Yingxin","email":"ygu@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":484994,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Belnap, Jayne 0000-0001-7471-2279 jayne_belnap@usgs.gov","orcid":"https://orcid.org/0000-0001-7471-2279","contributorId":1332,"corporation":false,"usgs":true,"family":"Belnap","given":"Jayne","email":"jayne_belnap@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":484996,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Phuyal, Khem P.","contributorId":28517,"corporation":false,"usgs":true,"family":"Phuyal","given":"Khem","email":"","middleInitial":"P.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":484997,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Tieszen, Larry","contributorId":63907,"corporation":false,"usgs":true,"family":"Tieszen","given":"Larry","affiliations":[],"preferred":false,"id":484998,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70058739,"text":"70058739 - 2013 - Limitation and facilitation of one of the world's most invasive fish: an intercontinental comparison","interactions":[],"lastModifiedDate":"2013-12-13T09:13:45","indexId":"70058739","displayToPublicDate":"2013-02-01T09:10:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Limitation and facilitation of one of the world's most invasive fish: an intercontinental comparison","docAbstract":"Purposeful species introductions offer opportunities to inform our understanding of both invasion success and conservation hurdles. We evaluated factors determining the energetic limitations of brown trout (Salmo trutta) in both their native and introduced ranges. Our focus was on brown trout because they are nearly globally distributed, considered one of the world's worst invaders, yet imperiled in much of their native habitat. We synthesized and compared data describing temperature regime, diet, growth, and maximum body size across multiple spatial and temporal scales, from country (both exotic and native habitats) and major geographic area (MGA) to rivers and years within MGA. Using these data as inputs, we next used bioenergetic efficiency (BioEff), a relative scalar representing a realized percentage of maximum possible consumption (0–100%) as our primary response variable and a multi-scale, nested, mixed statistical model (GLIMMIX) to evaluate variation among and within spatial scales and as a function of density and elevation. MGA and year (the residual) explained the greatest proportion of variance in BioEff. Temperature varied widely among MGA and was a strong driver of variation in BioEff. We observed surprisingly little variation in the diet of brown trout, except the overwhelming influence of the switch to piscivory observed only in exotic MGA. We observed only a weak signal of density-dependent effects on BioEff; however, BioEff remained <50% at densities >2.5 fish/m2. The trajectory of BioEff across the life span of the fish elucidated the substantial variation in performance among MGAs; the maximum body size attained by brown trout was consistently below 400 mm in native habitat but reached 600 mm outside their native range, where brown trout grew rapidly, feeding in part on naive prey fishes. The integrative, physiological approach, in combination with the intercontinental and comparative nature of our study, allowed us to overcome challenges associated with context-dependent variation in determining invasion success. Overall our results indicate “growth plasticity across the life span” was important for facilitating invasion, and should be added to lists of factors characterizing successful invaders.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ecology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Ecological Society of America","doi":"10.1890/12-0628.1","usgsCitation":"Budy, P.E., Thiede, G.P., Lobon-Cervia, J., Fernandez, G.G., McHugh, P., McIntosh, A., Vollestad, L.A., Becares, E., and Jellyman, P., 2013, Limitation and facilitation of one of the world's most invasive fish: an intercontinental comparison: Ecology, v. 94, no. 2, p. 356-367, https://doi.org/10.1890/12-0628.1.","productDescription":"12 p.","startPage":"356","endPage":"367","numberOfPages":"12","ipdsId":"IP-033914","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":488200,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/10261/126144","text":"External Repository"},{"id":280287,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":280286,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1890/12-0628.1"}],"volume":"94","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd64a0e4b0b290850ff930","contributors":{"authors":[{"text":"Budy, Phaedra E. pbudy@usgs.gov","contributorId":2232,"corporation":false,"usgs":true,"family":"Budy","given":"Phaedra","email":"pbudy@usgs.gov","middleInitial":"E.","affiliations":[{"id":322,"text":"Grand Canyon Monitoring and Research Center","active":false,"usgs":true}],"preferred":false,"id":487315,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thiede, Gary P.","contributorId":9154,"corporation":false,"usgs":true,"family":"Thiede","given":"Gary","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":487317,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lobon-Cervia, Javier","contributorId":69052,"corporation":false,"usgs":true,"family":"Lobon-Cervia","given":"Javier","email":"","affiliations":[],"preferred":false,"id":487322,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fernandez, Gustavo Gonzolez","contributorId":7173,"corporation":false,"usgs":true,"family":"Fernandez","given":"Gustavo","email":"","middleInitial":"Gonzolez","affiliations":[],"preferred":false,"id":487316,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McHugh, Peter","contributorId":12313,"corporation":false,"usgs":true,"family":"McHugh","given":"Peter","affiliations":[],"preferred":false,"id":487319,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McIntosh, Angus","contributorId":47630,"corporation":false,"usgs":true,"family":"McIntosh","given":"Angus","email":"","affiliations":[],"preferred":false,"id":487321,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Vollestad, Lief Asbjorn","contributorId":97417,"corporation":false,"usgs":true,"family":"Vollestad","given":"Lief","email":"","middleInitial":"Asbjorn","affiliations":[],"preferred":false,"id":487323,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Becares, Eloy","contributorId":10712,"corporation":false,"usgs":true,"family":"Becares","given":"Eloy","email":"","affiliations":[],"preferred":false,"id":487318,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Jellyman, Phillip","contributorId":19465,"corporation":false,"usgs":true,"family":"Jellyman","given":"Phillip","email":"","affiliations":[],"preferred":false,"id":487320,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}}
,{"id":70176182,"text":"70176182 - 2013 - Mapping river bathymetry with a small footprint green LiDAR:  Applications and challenges","interactions":[],"lastModifiedDate":"2016-09-07T14:45:13","indexId":"70176182","displayToPublicDate":"2013-02-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Mapping river bathymetry with a small footprint green LiDAR:  Applications and challenges","docAbstract":"Airborne bathymetric Light Detection And Ranging (LiDAR) systems designed for coastal and marine surveys are increasingly sought after for high-resolution mapping of fluvial systems. To evaluate the potential utility of bathymetric LiDAR for applications of this kind, we compared detailed surveys collected using wading and sonar techniques with measurements from the United States Geological Survey’s hybrid topographic⁄ bathymetric Experimental Advanced Airborne Research LiDAR (EAARL). These comparisons, based upon data collected from the Trinity and Klamath Rivers, California, and the Colorado River, Colorado, demonstrated\nthat environmental conditions and postprocessing algorithms can influence the accuracy and utility of these surveys and must be given consideration. These factors can lead to mapping errors that can have a direct bearing on derivative analyses such as hydraulic modeling and habitat assessment. We discuss the water and substrate characteristics of the sites, compare the conventional and remotely sensed river-bed topographies, and investigate the laser waveforms reflected from submerged targets to provide an evaluation as to the suitability and accuracy of the EAARL system and associated processing algorithms for riverine mapping applications.","language":"English","publisher":"Journal of the American Water Resources Association","doi":"10.1111/jawr.12008","usgsCitation":"Kinzel, P.J., Legleiter, C.J., and Nelson, J.M., 2013, Mapping river bathymetry with a small footprint green LiDAR:  Applications and challenges: Journal of the American Water Resources Association, v. 49, no. 1, p. 183-204, https://doi.org/10.1111/jawr.12008.","productDescription":"12 p.","startPage":"183","endPage":"204","ipdsId":"IP-038143","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":328152,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"49","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2012-12-03","publicationStatus":"PW","scienceBaseUri":"57c7ffbae4b0f2f0cebfc2f5","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":647631,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Legleiter, Carl J. 0000-0003-0940-8013 cjl@usgs.gov","orcid":"https://orcid.org/0000-0003-0940-8013","contributorId":169002,"corporation":false,"usgs":true,"family":"Legleiter","given":"Carl","email":"cjl@usgs.gov","middleInitial":"J.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":647632,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":647630,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70193602,"text":"70193602 - 2013 - The utility of atmospheric analyses for the mitigation of artifacts in InSAR","interactions":[],"lastModifiedDate":"2017-11-02T16:06:14","indexId":"70193602","displayToPublicDate":"2013-02-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2314,"text":"Journal of Geophysical Research B: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"The utility of atmospheric analyses for the mitigation of artifacts in InSAR","docAbstract":"<p><span>The numerical weather models (NWMs) developed by the meteorological community are able to provide accurate analyses of the current state of the atmosphere in addition to the predictions of the future state. To date, most attempts to apply the NWMs to estimate the refractivity of the atmosphere at the time of satellite synthetic aperture radar (SAR) data acquisitions have relied on predictive models. We test the hypothesis that performing a final assimilative routine, ingesting all available meteorological observations for the times of SAR acquisitions, and generating customized analyses of the atmosphere at those times will better mitigate atmospheric artifacts in differential interferograms. We find that, for our study area around Mount St. Helens (Amboy, Washington, USA), this approach is unable to model the refractive changes and provides no mean benefit for interferogram analysis. The performance is improved slightly by ingesting atmospheric delay estimates derived from the limited local GPS network; however, the addition of water vapor products from the GOES satellites reduces the quality of the corrections. We interpret our results to indicate that, even with this advanced approach, NWMs are not a reliable mitigation technique for regions such as Mount St. Helens with highly variable moisture fields and complex topography and atmospheric dynamics. It is possible, however, that the addition of more spatially dense meteorological data to constrain the analyses might significantly improve the performance of weather modeling of atmospheric artifacts in satellite radar interferograms.</span></p>","language":"English","publisher":"AGU","doi":"10.1002/jgrb.50093","usgsCitation":"Foster, J., Kealy, J., Cherubini, T., Businger, S., Lu, Z., and Murphy, M., 2013, The utility of atmospheric analyses for the mitigation of artifacts in InSAR: Journal of Geophysical Research B: Solid Earth, v. 118, no. 2, p. 748-758, https://doi.org/10.1002/jgrb.50093.","productDescription":"11 p.","startPage":"748","endPage":"758","ipdsId":"IP-044768","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":496358,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/11603/40220","text":"External Repository"},{"id":348134,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"118","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2013-02-26","publicationStatus":"PW","scienceBaseUri":"59fc2eaee4b0531197b27fe4","contributors":{"authors":[{"text":"Foster, James","contributorId":38598,"corporation":false,"usgs":true,"family":"Foster","given":"James","affiliations":[],"preferred":false,"id":719963,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kealy, John","contributorId":199761,"corporation":false,"usgs":false,"family":"Kealy","given":"John","email":"","affiliations":[],"preferred":false,"id":719964,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cherubini, Tiziana","contributorId":199762,"corporation":false,"usgs":false,"family":"Cherubini","given":"Tiziana","email":"","affiliations":[],"preferred":false,"id":719965,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Businger, S.","contributorId":65331,"corporation":false,"usgs":true,"family":"Businger","given":"S.","affiliations":[],"preferred":false,"id":719966,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lu, Zhong 0000-0001-9181-1818 lu@usgs.gov","orcid":"https://orcid.org/0000-0001-9181-1818","contributorId":901,"corporation":false,"usgs":true,"family":"Lu","given":"Zhong","email":"lu@usgs.gov","affiliations":[],"preferred":true,"id":719967,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Murphy, Michael","contributorId":199763,"corporation":false,"usgs":false,"family":"Murphy","given":"Michael","affiliations":[],"preferred":false,"id":719968,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70043177,"text":"70043177 - 2013 - Mapping grassland productivity with 250-m eMODIS NDVI and SSURGO database over the Greater Platte River Basin, USA","interactions":[],"lastModifiedDate":"2013-04-07T08:04:12","indexId":"70043177","displayToPublicDate":"2013-02-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Mapping grassland productivity with 250-m eMODIS NDVI and SSURGO database over the Greater Platte River Basin, USA","docAbstract":"This study assessed and described a relationship between satellite-derived growing season averaged Normalized Difference Vegetation Index (NDVI) and annual productivity for grasslands within the Greater Platte River Basin (GPRB) of the United States. We compared growing season averaged NDVI (GSN) with Soil Survey Geographic (SSURGO) database rangeland productivity and flux tower Gross Primary Productivity (GPP) for grassland areas. The GSN was calculated for each of nine years (2000–2008) using the 7-day composite 250-m eMODIS (expedited Moderate Resolution Imaging Spectroradiometer) NDVI data. Strong correlations exist between the nine-year mean GSN (MGSN) and SSURGO annual productivity for grasslands (R2 = 0.74 for approximately 8000 pixels randomly selected from eight homogeneous regions within the GPRB; R2 = 0.96 for the 14 cluster-averaged points). Results also reveal a strong correlation between GSN and flux tower growing season averaged GPP (R2 = 0.71). Finally, we developed an empirical equation to estimate grassland productivity based on the MGSN. Spatially explicit estimates of grassland productivity over the GPRB were generated, which improved the regional consistency of SSURGO grassland productivity data and can help scientists and land managers to better understand the actual biophysical and ecological characteristics of grassland systems in the GPRB. This final estimated grassland production map can also be used as an input for biogeochemical, ecological, and climate change models.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ecological Indicators","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2012.05.024","usgsCitation":"Gu, Y., Wylie, B.K., and Bliss, N.B., 2013, Mapping grassland productivity with 250-m eMODIS NDVI and SSURGO database over the Greater Platte River Basin, USA: Ecological Indicators, v. 24, p. 31-36, https://doi.org/10.1016/j.ecolind.2012.05.024.","startPage":"31","endPage":"36","ipdsId":"IP-030210","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":270619,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":270618,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.ecolind.2012.05.024"}],"country":"United States","volume":"24","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5162956fe4b0c25842758d03","contributors":{"authors":[{"text":"Gu, Yingxin 0000-0002-3544-1856 ygu@usgs.gov","orcid":"https://orcid.org/0000-0002-3544-1856","contributorId":409,"corporation":false,"usgs":true,"family":"Gu","given":"Yingxin","email":"ygu@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":473107,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wylie, Bruce K. 0000-0002-7374-1083 wylie@usgs.gov","orcid":"https://orcid.org/0000-0002-7374-1083","contributorId":750,"corporation":false,"usgs":true,"family":"Wylie","given":"Bruce","email":"wylie@usgs.gov","middleInitial":"K.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":473108,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bliss, Norman B. 0000-0003-2409-5211 bliss@usgs.gov","orcid":"https://orcid.org/0000-0003-2409-5211","contributorId":1921,"corporation":false,"usgs":true,"family":"Bliss","given":"Norman","email":"bliss@usgs.gov","middleInitial":"B.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":473109,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70043348,"text":"70043348 - 2013 - Biodiversity losses and conservation trade-offs: Assessing future urban growth scenarios for a North American trade corridor","interactions":[],"lastModifiedDate":"2018-03-27T11:11:06","indexId":"70043348","displayToPublicDate":"2013-02-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2029,"text":"International Journal of Biodiversity Science, Ecosystem Services and Management","active":true,"publicationSubtype":{"id":10}},"title":"Biodiversity losses and conservation trade-offs: Assessing future urban growth scenarios for a North American trade corridor","docAbstract":"The Sonoran Desert and Apache Highlands ecoregions of North America are areas of exceptionally high plant and vertebrate biodiversity. However, much of the vertebrate biodiversity is supported by only a few vegetation types with limited distributions, some of which are increasingly threatened by changing land uses. We assessed the impacts of two future urban growth scenarios on biodiversity in a binational watershed in Arizona, USA and Sonora, Mexico. We quantified and mapped terrestrial vertebrate species richness using Wildlife Habitat Relation models and validated the results with data from National Park Service biological inventories. Future urban growth, based on historical trends, was projected to the year 2050 for 1) a “Current Trends” scenario and, 2) a “Megalopolis” scenario that represented a transnational growth corridor with open-space conservation attributes. Based on Current Trends, 45% of existing riparian woodland (267 of 451species), and 34% of semi-desert grasslands (215 of 451 species) will be lost, whereas, in the Megalopolis scenario, these types would decline by 44% and 24% respectively. Outcomes of the two models suggest a trade-off at the taxonomic class level: Current Trends would reduce and fragment mammal and herpetofauna habitat, while Megalopolis would result in loss of avian-rich riparian habitat.","language":"English","publisher":"Taylor and Francis","doi":"10.1080/21513732.2013.770800","usgsCitation":"Villarreal, M.L., Norman, L.M., Wallace, C., and Boykin, K.G., 2013, Biodiversity losses and conservation trade-offs: Assessing future urban growth scenarios for a North American trade corridor: International Journal of Biodiversity Science, Ecosystem Services and Management, v. 9, no. 2, p. 90-103, https://doi.org/10.1080/21513732.2013.770800.","productDescription":"14 p.","startPage":"90","endPage":"103","ipdsId":"IP-035555","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":473964,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/21513732.2013.770800","text":"Publisher Index Page"},{"id":267585,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":269905,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1080/21513732.2013.770800"}],"volume":"9","issue":"2","noUsgsAuthors":false,"publicationDate":"2013-03-07","publicationStatus":"PW","scienceBaseUri":"511f6709e4b03b29402c5da0","contributors":{"authors":[{"text":"Villarreal, Miguel L. 0000-0003-0720-1422 mvillarreal@usgs.gov","orcid":"https://orcid.org/0000-0003-0720-1422","contributorId":1424,"corporation":false,"usgs":true,"family":"Villarreal","given":"Miguel","email":"mvillarreal@usgs.gov","middleInitial":"L.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":473455,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Norman, Laura M. 0000-0002-3696-8406 lnorman@usgs.gov","orcid":"https://orcid.org/0000-0002-3696-8406","contributorId":967,"corporation":false,"usgs":true,"family":"Norman","given":"Laura","email":"lnorman@usgs.gov","middleInitial":"M.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":473454,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wallace, Cynthia S.A. cwallace@usgs.gov","contributorId":3335,"corporation":false,"usgs":true,"family":"Wallace","given":"Cynthia S.A.","email":"cwallace@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":false,"id":473456,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Boykin, Kenneth G. 0000-0001-6381-0463","orcid":"https://orcid.org/0000-0001-6381-0463","contributorId":43651,"corporation":false,"usgs":false,"family":"Boykin","given":"Kenneth","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":473457,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70043780,"text":"70043780 - 2013 - Rapid increases and time-lagged declines in amphibian occupancy after wildfire","interactions":[],"lastModifiedDate":"2013-06-07T10:14:21","indexId":"70043780","displayToPublicDate":"2013-02-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1321,"text":"Conservation Biology","active":true,"publicationSubtype":{"id":10}},"title":"Rapid increases and time-lagged declines in amphibian occupancy after wildfire","docAbstract":"Climate change is expected to increase the frequency and severity of drought and wildfire. Aquatic and moisture-sensitive species, such as amphibians, may be particularly vulnerable to these modified disturbance regimes because large wildfires often occur during extended droughts and thus may compound environmental threats. However, understanding of the effects of wildfires on amphibians in forests with long fire-return intervals is limited. Numerous stand-replacing wildfires have occurred since 1988 in Glacier National Park (Montana, U.S.A.), where we have conducted long-term monitoring of amphibians. We measured responses of 3 amphibian species to fires of different sizes, severity, and age in a small geographic area with uniform management. We used data from wetlands associated with 6 wildfires that burned between 1988 and 2003 to evaluate whether burn extent and severity and interactions between wildfire and wetland isolation affected the distribution of breeding populations. We measured responses with models that accounted for imperfect detection to estimate occupancy during prefire (0-4 years) and different postfire recovery periods. For the long-toed salamander (Ambystoma macrodactylum) and Columbia spotted frog (Rana luteiventris), occupancy was not affected for 6 years after wildfire. But 7-21 years after wildfire, occupancy for both species decreased ≥ 25% in areas where >50% of the forest within 500 m of wetlands burned. In contrast, occupancy of the boreal toad (Anaxyrus boreas) tripled in the 3 years after low-elevation forests burned. This increase in occupancy was followed by a gradual decline. Our results show that accounting for magnitude of change and time lags is critical to understanding population dynamics of amphibians after large disturbances. Our results also inform understanding of the potential threat of increases in wildfire frequency or severity to amphibians in the region.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Conservation Biology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1111/j.1523-1739.2012.01921.x","usgsCitation":"Hossack, B.R., Lowe, W., and Corn, P., 2013, Rapid increases and time-lagged declines in amphibian occupancy after wildfire: Conservation Biology, v. 27, no. 1, p. 219-228, https://doi.org/10.1111/j.1523-1739.2012.01921.x.","productDescription":"10 p.","startPage":"219","endPage":"228","ipdsId":"IP-035616","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":273437,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":273436,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/j.1523-1739.2012.01921.x"}],"country":"United States","state":"Montana","otherGeospatial":"Glacier National Park","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -11.067777777777778,4.133888888888889 ], [ -11.067777777777778,0.0011111111111111111 ], [ -11.050555555555556,0.0011111111111111111 ], [ -11.050555555555556,4.133888888888889 ], [ -11.067777777777778,4.133888888888889 ] ] ] } } ] }","volume":"27","issue":"1","noUsgsAuthors":false,"publicationDate":"2012-09-14","publicationStatus":"PW","scienceBaseUri":"51b300e5e4b01368e589e3ea","contributors":{"authors":[{"text":"Hossack, Blake R. 0000-0001-7456-9564 blake_hossack@usgs.gov","orcid":"https://orcid.org/0000-0001-7456-9564","contributorId":1177,"corporation":false,"usgs":true,"family":"Hossack","given":"Blake","email":"blake_hossack@usgs.gov","middleInitial":"R.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":474229,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lowe, Winsor H.","contributorId":64532,"corporation":false,"usgs":false,"family":"Lowe","given":"Winsor H.","affiliations":[{"id":5097,"text":"University of Montana, Division of Biological Sciences","active":true,"usgs":false}],"preferred":false,"id":474230,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Corn, Paul Stephen 0000-0002-4106-6335","orcid":"https://orcid.org/0000-0002-4106-6335","contributorId":107379,"corporation":false,"usgs":true,"family":"Corn","given":"Paul Stephen","affiliations":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"preferred":false,"id":474231,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70043370,"text":"70043370 - 2013 - Towards integration of GLAS data into a national fuels mapping program","interactions":[],"lastModifiedDate":"2013-05-30T12:17:31","indexId":"70043370","displayToPublicDate":"2013-02-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3052,"text":"Photogrammetric Engineering and Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Towards integration of GLAS data into a national fuels mapping program","docAbstract":"Comprehensive canopy structure and fuel data are critical for understanding and modeling wildland fire. The LANDFIRE project produces such data nationwide based on a collection of field observations, Landsat imagery, and other geospatial data. Where field data are not available, alternate strategies are being investigated. In this study, vegetation structure data available from GLAS were used to fill this data gap for the Yukon Flats Ecoregion of interior Alaska. The GLAS-derived structure and fuel layers and the original LANDFIRE layers were subsequently used as inputs into a fire behavior model to determine what effect the revised inputs would have on the model outputs. The outputs showed that inclusion of the GLAS data enabled better landscape-level characterization of\nvegetation structure and therefore enabled a broader wildland fire modeling capability. The results of this work underscore how GLAS data can be incorporated into LANDFIRE canopy structure and fuel mapping.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Photogrammetric Engineering and Remote Sensing","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Society for Photogrammetry","usgsCitation":"Peterson, B.E., Nelson, K., and Wylie, B., 2013, Towards integration of GLAS data into a national fuels mapping program: Photogrammetric Engineering and Remote Sensing, v. 79, no. 2, p. 175-183.","productDescription":"9 p.","startPage":"175","endPage":"183","ipdsId":"IP-038047","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":273015,"type":{"id":11,"text":"Document"},"url":"https://www.conservationgateway.org/ConservationPractices/FireLandscapes/LANDFIRE/Documents/Peterson%20et%20all%20GLAS%20and%20Fuel%20Mapping.pdf"},{"id":273016,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Yukon Flats Ecoregion","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -149.55,65.47 ], [ -149.55,67.47 ], [ -142.43,67.47 ], [ -142.43,65.47 ], [ -149.55,65.47 ] ] ] } } ] }","volume":"79","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51a874ece4b082d85d5ed90a","contributors":{"authors":[{"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":473475,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nelson, Kurtis 0000-0003-4911-4511 knelson@usgs.gov","orcid":"https://orcid.org/0000-0003-4911-4511","contributorId":3602,"corporation":false,"usgs":true,"family":"Nelson","given":"Kurtis","email":"knelson@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":473476,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":473477,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70043201,"text":"70043201 - 2013 - Use of classification trees to apportion single echo detections to species: Application to the pelagic fish community of Lake Superior","interactions":[],"lastModifiedDate":"2013-06-03T10:56:30","indexId":"70043201","displayToPublicDate":"2013-02-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1661,"text":"Fisheries Research","active":true,"publicationSubtype":{"id":10}},"title":"Use of classification trees to apportion single echo detections to species: Application to the pelagic fish community of Lake Superior","docAbstract":"Acoustic methods are used to estimate the density of pelagic fish in large lakes with results of midwater trawling used to assign species composition. Apportionment in lakes having mixed species can be challenging because only a small fraction of the water sampled acoustically is sampled with trawl gear. Here we describe a new method where single echo detections (SEDs) are assigned to species based on classification tree models developed from catch data that separate species based on fish size and the spatial habitats they occupy. During the summer of 2011, we conducted a spatially-balanced lake-wide acoustic and midwater trawl survey of Lake Superior. A total of 51 sites in four bathymetric depth strata (0–30 m, 30–100 m, 100–200 m, and >200 m) were sampled. We developed classification tree models for each stratum and found fish length was the most important variable for separating species. To apply these trees to the acoustic data, we needed to identify a target strength to length (TS-to-L) relationship appropriate for all abundant Lake Superior pelagic species. We tested performance of 7 general (i.e., multi-species) relationships derived from three published studies. The best-performing relationship was identified by comparing predicted and observed catch compositions using a second independent Lake Superior data set. Once identified, the relationship was used to predict lengths of SEDs from the lake-wide survey, and the classification tree models were used to assign each SED to a species. Exotic rainbow smelt (Osmerus mordax) were the most common species at bathymetric depths <100 m with their population estimated at 755 million (3.4 kt). Kiyi (Coregonus kiyi) were the most abundant species at depths >100 m (384 million; 6.0 kt). Cisco (Coregonus artedi) were widely distributed over all strata with their population estimated at 182 million (44 kt). The apportionment method we describe should be transferable to other large lakes provided fish are not tightly aggregated, and an appropriate TS-to-L relationship for abundant pelagic fish species can be determined.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Fisheries Research","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.fishres.2012.12.012","usgsCitation":"Yule, D., Adams, J.V., Hrabik, T.R., Vinson, M., Woiak, Z., and Ahrenstroff, T.D., 2013, Use of classification trees to apportion single echo detections to species: Application to the pelagic fish community of Lake Superior: Fisheries Research, v. 140, p. 123-132, https://doi.org/10.1016/j.fishres.2012.12.012.","productDescription":"10 p.","startPage":"123","endPage":"132","ipdsId":"IP-043013","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":273087,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":273085,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.fishres.2012.12.012"}],"country":"United States","otherGeospatial":"Lake Superior","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -89.562,46.4146 ], [ -89.562,48.8488 ], [ -84.354,48.8488 ], [ -84.354,46.4146 ], [ -89.562,46.4146 ] ] ] } } ] }","volume":"140","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51adbaebe4b07c214e64bd4b","contributors":{"authors":[{"text":"Yule, Daniel L.","contributorId":92130,"corporation":false,"usgs":true,"family":"Yule","given":"Daniel L.","affiliations":[],"preferred":false,"id":473158,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Adams, Jean V. 0000-0002-9101-068X jvadams@usgs.gov","orcid":"https://orcid.org/0000-0002-9101-068X","contributorId":3140,"corporation":false,"usgs":true,"family":"Adams","given":"Jean","email":"jvadams@usgs.gov","middleInitial":"V.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":473153,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hrabik, Thomas R.","contributorId":35614,"corporation":false,"usgs":false,"family":"Hrabik","given":"Thomas","email":"","middleInitial":"R.","affiliations":[{"id":6915,"text":"University of Minnesota - Duluth","active":true,"usgs":false}],"preferred":false,"id":473154,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vinson, Mark R.","contributorId":91774,"corporation":false,"usgs":true,"family":"Vinson","given":"Mark R.","affiliations":[],"preferred":false,"id":473157,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Woiak, Zebadiah","contributorId":37232,"corporation":false,"usgs":true,"family":"Woiak","given":"Zebadiah","affiliations":[],"preferred":false,"id":473155,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ahrenstroff, Tyler D.","contributorId":64540,"corporation":false,"usgs":true,"family":"Ahrenstroff","given":"Tyler","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":473156,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70043063,"text":"ofr20121006 - 2013 - High-Resolution geophysical data from the inner continental shelf at Vineyard Sound, Massachusetts","interactions":[],"lastModifiedDate":"2017-11-10T18:25:04","indexId":"ofr20121006","displayToPublicDate":"2013-02-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-1006","title":"High-Resolution geophysical data from the inner continental shelf at Vineyard Sound, Massachusetts","docAbstract":"The U.S. Geological Survey (USGS) and the Massachusetts Office of Coastal Zone Management (CZM) have mapped approximately 340 square kilometers of the inner continental shelf in Vineyard Sound, Massachusetts, under a cooperative mapping program. The geophysical data collected between 2009 and 2011 by the U.S. Geological Survey as part of this program are published in this report. The data include (1) swath bathymetry from interferometric sonar, (2) acoustic backscatter from sidescan sonar, and (3) seismic-reflection profiles from a chirp subbottom profiler. These data were collected to support research on the influence of sea-level change and sediment supply on coastal evolution and sediment transport processes and to provide baseline seabed characterization information required for management of coastal and offshore resources within the coastal zone of Massachusetts.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121006","collaboration":"Prepared in cooperation with the Massachusetts Office of Coastal Zone Management.  This publication is available online and in DVD format. See <a href=\"http://pubs.usgs.gov/of/2012/1006/title_page.html\" target=\"_blank\">Open-File Report 2012-1006</a> for ordering information.","usgsCitation":"Andrews, B., Ackerman, S.D., Baldwin, W.E., Foster, D.S., and Schwab, W.C., 2013, High-Resolution geophysical data from the inner continental shelf at Vineyard Sound, Massachusetts (Version 1: Originally posted February 1, 2013; Version 2.0: September 17, 2014): U.S. Geological Survey Open-File Report 2012-1006, HTML Document; PDF: v, 18 p.;  DVD-ROM, https://doi.org/10.3133/ofr20121006.","productDescription":"HTML Document; PDF: v, 18 p.;  DVD-ROM","numberOfPages":"23","additionalOnlineFiles":"Y","costCenters":[{"id":680,"text":"Woods Hole Science Center","active":false,"usgs":true}],"links":[{"id":294065,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20121006.jpg"},{"id":266903,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1006/"},{"id":266904,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1006/title_page.html"}],"country":"United States","state":"Massachusetts","otherGeospatial":"Vineyard Sound","geographicExtents":"{\"crs\": {\"type\": \"name\", \"properties\": {\"name\": \"urn:ogc:def:crs:OGC:1.3:CRS84\"}}, \"geometry\": {\"type\": \"Polygon\", \"coordinates\": [[[-70.68878484430002, 41.524042809940255], [-70.67456470331092, 41.52270173623828], [-70.66824267621348, 41.51257120958017], [-70.65476233359948, 41.51388068063943], [-70.626357995829, 41.53498084749281], [-70.51278915226429, 41.54271750820077], [-70.465035280998, 41.53818222433749], [-70.46049999713472, 41.53257981485944], [-70.51090883461882, 41.52705371235446], [-70.5166858102478, 41.53170281337986], [-70.56027624212697, 41.521641777306776], [-70.45062908519702, 41.5096366141392], [-70.44582701993001, 41.45441286356873], [-70.43280311804654, 41.45165344458456], [-70.43277832251425, 41.44543548804172], [-70.45404160275525, 41.43494493095665], [-70.54800429755568, 41.43987327706577], [-70.54476917092946, 41.47040547804572], [-70.58509399652377, 41.47436595198792], [-70.60762994128771, 41.48789392973587], [-70.63457486306362, 41.488427492543344], [-70.65224203199979, 41.47814640438741], [-70.64066377373075, 41.47604670752018], [-70.67006416474004, 41.454743603819395], [-70.67325816660338, 41.44520890514024], [-70.70696858102052, 41.43287098636544], [-70.74886401641834, 41.38022095519347], [-70.78887838300881, 41.36896333866024], [-70.78057211854423, 41.356803934586424], [-70.78487950592086, 41.35362284924228], [-70.79535915855065, 41.366983101689065], [-70.86196712939825, 41.35762198146197], [-70.86232717248403, 41.347900818149085], [-70.8486455352288, 41.34916096894881], [-70.80886077426305, 41.31729715586756], [-70.8011198479213, 41.303255475526775], [-70.80021974020718, 41.28921379518601], [-70.82380256231806, 41.286513472043495], [-70.81786185140464, 41.275352136388], [-70.8223622931439, 41.26931992566591], [-70.86682771105478, 41.34232015032131], [-70.88068936985275, 41.3370995255792], [-70.86131237808739, 41.2938638148085], [-70.88532270442244, 41.333614243963034], [-70.9568201206201, 41.31867448535468], [-71.02945801001431, 41.36747452002408], [-71.00220391126385, 41.3848052344295], [-71.00778457909155, 41.391466031514256], [-71.00341975230106, 41.39461694854372], [-70.99963853591747, 41.389972371475565], [-70.91800342637845, 41.40944741394724], [-70.918796122449, 41.41930579669626], [-70.88645005922335, 41.41513886439644], [-70.84774542751454, 41.42431996308096], [-70.83718076151074, 41.43564918802013], [-70.82905850637741, 41.42937598480528], [-70.8112010543199, 41.43314101867961], [-70.80280721625111, 41.44625174694089], [-70.79265883540825, 41.443762289706626], [-70.75485431141368, 41.46410472404663], [-70.75025127971776, 41.47373023152448], [-70.7305094558423, 41.48120011082856], [-70.73184336286089, 41.48760286451797], [-70.71056901187711, 41.489577772357336], [-70.67464542990274, 41.5096366141392], [-70.67510476793933, 41.51820119766745], [-70.69678828641175, 41.522175340114245], [-70.70608612280728, 41.549149477299444], [-70.68878484430002, 41.524042809940255]], [[-70.53620886189378, 41.490774532655685], [-70.49341895542483, 41.48326282493689], [-70.48845586282499, 41.48353110021264], [-70.56545086694149, 41.50244450714711], [-70.53620886189378, 41.490774532655685]]]}, \"properties\": {\"extentType\": \"Custom\", \"code\": \"\", \"name\": \"\", \"notes\": \"\", \"promotedForReuse\": false, \"abbreviation\": \"\", \"shortName\": \"\", \"description\": \"\"}, \"bbox\": [-71.02945801001431, 41.26931992566591, -70.43277832251425, 41.549149477299444], \"type\": \"Feature\", \"id\": \"3091975\"}","edition":"Version 1: Originally posted February 1, 2013; Version 2.0: September 17, 2014","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"510ce3efe4b0ae2ee50d95eb","contributors":{"authors":[{"text":"Andrews, Brian D.","contributorId":54180,"corporation":false,"usgs":true,"family":"Andrews","given":"Brian D.","affiliations":[],"preferred":false,"id":472901,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ackerman, Seth D. 0000-0003-0945-2794 sackerman@usgs.gov","orcid":"https://orcid.org/0000-0003-0945-2794","contributorId":178676,"corporation":false,"usgs":true,"family":"Ackerman","given":"Seth","email":"sackerman@usgs.gov","middleInitial":"D.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":472900,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Baldwin, Wayne E. 0000-0001-5886-0917 wbaldwin@usgs.gov","orcid":"https://orcid.org/0000-0001-5886-0917","contributorId":1321,"corporation":false,"usgs":true,"family":"Baldwin","given":"Wayne","email":"wbaldwin@usgs.gov","middleInitial":"E.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":472899,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Foster, David S. 0000-0003-1205-0884 dfoster@usgs.gov","orcid":"https://orcid.org/0000-0003-1205-0884","contributorId":1320,"corporation":false,"usgs":true,"family":"Foster","given":"David","email":"dfoster@usgs.gov","middleInitial":"S.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":472898,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schwab, William C. 0000-0001-9274-5154 bschwab@usgs.gov","orcid":"https://orcid.org/0000-0001-9274-5154","contributorId":417,"corporation":false,"usgs":true,"family":"Schwab","given":"William","email":"bschwab@usgs.gov","middleInitial":"C.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":472897,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70038472,"text":"70038472 - 2013 - Late quaternary slip-rate variations along the Warm Springs Valley fault system, northern Walker Lane, California-Nevada border","interactions":[],"lastModifiedDate":"2020-09-11T17:08:53.632551","indexId":"70038472","displayToPublicDate":"2013-02-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Late quaternary slip-rate variations along the Warm Springs Valley fault system, northern Walker Lane, California-Nevada border","docAbstract":"<p>The extent to which faults exhibit temporally varying slip rates has important consequences for models of fault mechanics and probabilistic seismic hazard. Here, we explore the temporal behavior of the dextral‐slip Warm Springs Valley fault system, which is part of a network of closely spaced (10–20 km) faults in the northern Walker Lane (California–Nevada border). We develop a late Quaternary slip record for the fault using Quaternary mapping and high‐resolution topographic data from airborne Light Distance and Ranging (LiDAR). The faulted Fort Sage alluvial fan (40.06° N, 119.99° W) is dextrally displaced 98+42/-43 m, and we estimate the age of the alluvial fan to be 41.4+10.0/-4.8 to 55.7±9.2  ka, based on a terrestrial cosmogenic <sup>10</sup>Be depth profile and <sup>36</sup>Cl analyses on basalt boulders, respectively. The displacement and age constraints for the fan yield a slip rate of 1.8 +0.8/-0.8 mm/yr to 2.4 +1.2/-1.1 mm/yr (2σ) along the northern Warm Springs Valley fault system for the past 41.4–55.7 ka. In contrast to this longer‐term slip rate, shorelines associated with the Sehoo highstand of Lake Lahontan (~15.8  ka) adjacent to the Fort Sage fan are dextrally faulted at most 3 m, which limits a maximum post‐15.8 ka slip rate to 0.2  mm/yr. These relations indicate that the post‐Lahontan slip rate on the fault is only about one‐tenth the longer‐term (41–56 ka) average slip rate. This apparent slip‐rate variation may be related to co‐dependent interaction with the nearby Honey Lake fault system, which shows evidence of an accelerated period of mid‐Holocene earthquakes.</p>","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120120020","usgsCitation":"Gold, R., dePolo, C., Briggs, R.W., Crone, A., and Goss, J., 2013, Late quaternary slip-rate variations along the Warm Springs Valley fault system, northern Walker Lane, California-Nevada border: Bulletin of the Seismological Society of America, v. 103, no. 1, p. 542-558, https://doi.org/10.1785/0120120020.","productDescription":"17 p.","startPage":"542","endPage":"558","ipdsId":"IP-038135","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":267417,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Nevada","otherGeospatial":"Walker Lane","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -120.28106689453125,\n              39.74943369178247\n            ],\n            [\n              -119.74822998046875,\n              39.74943369178247\n            ],\n            [\n              -119.74822998046875,\n              40.02551125229787\n            ],\n            [\n              -120.28106689453125,\n              40.02551125229787\n            ],\n            [\n              -120.28106689453125,\n              39.74943369178247\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"103","issue":"1","noUsgsAuthors":false,"publicationDate":"2013-02-05","publicationStatus":"PW","scienceBaseUri":"511e158de4b071e86a19a463","contributors":{"authors":[{"text":"Gold, Ryan","contributorId":97400,"corporation":false,"usgs":true,"family":"Gold","given":"Ryan","affiliations":[],"preferred":false,"id":464324,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"dePolo, Craig","contributorId":87433,"corporation":false,"usgs":true,"family":"dePolo","given":"Craig","affiliations":[],"preferred":false,"id":464323,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Briggs, Richard W. 0000-0001-8108-0046 rbriggs@usgs.gov","orcid":"https://orcid.org/0000-0001-8108-0046","contributorId":4136,"corporation":false,"usgs":true,"family":"Briggs","given":"Richard","email":"rbriggs@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":464321,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Crone, Anthony","contributorId":20624,"corporation":false,"usgs":true,"family":"Crone","given":"Anthony","affiliations":[],"preferred":false,"id":464322,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Goss, John","contributorId":240591,"corporation":false,"usgs":false,"family":"Goss","given":"John","email":"","affiliations":[],"preferred":false,"id":798516,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70044050,"text":"70044050 - 2013 - Rupture history of the 2008 <i>M</i><sub>w</sub> 7.9 Wenchuan, China, earthquake: Evaluation of separate and joint inversions of geodetic, teleseismic, and strong-motion data","interactions":[],"lastModifiedDate":"2016-01-27T16:01:18","indexId":"70044050","displayToPublicDate":"2013-02-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Rupture history of the 2008 <i>M</i><sub>w</sub> 7.9 Wenchuan, China, earthquake: Evaluation of separate and joint inversions of geodetic, teleseismic, and strong-motion data","docAbstract":"<p>An extensive data set of teleseismic and strong-motion waveforms and geodetic offsets is used to study the rupture history of the 2008 Wenchuan, China, earthquake. A linear multiple-time-window approach is used to parameterize the rupture. Because of the complexity of the Wenchuan faulting, three separate planes are used to represent the rupturing surfaces. This earthquake clearly demonstrates the strengths and limitations of geodetic, teleseismic, and strong-motion data sets. Geodetic data (static offsets) are valuable for determining the distribution of shallower slip but are insensitive to deeper faulting and reveal nothing about the timing of slip. Teleseismic data in the distance range 30&deg;&ndash;90&deg; generally involve no modeling difficulties because of simple ray paths and can distinguish shallow from deep slip. Teleseismic data, however, cannot distinguish between different slip scenarios when multiple fault planes are involved because steep takeoff angles lead to ambiguity in timing. Local strong-motion data, on the other hand, are ideal for determining the direction of rupture from directivity but can easily be over modeled with inaccurate Green&rsquo;s functions, leading to misinterpretation of the slip distribution. We show that all three data sets are required to give an accurate description of the Wenchuan rupture. The moment is estimated to be approximately 1.0 &times; 10<sup>21</sup> N &middot; m with the slip characterized by multiple large patches with slips up to 10 m. Rupture initiates on the southern end of the Pengguan fault and proceeds unilaterally to the northeast. Upon reaching the cross-cutting Xiaoyudong fault, rupture of the adjacent Beichuan fault starts at this juncture and proceeds bilaterally to the northeast and southwest.</p>","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Bulletin of the Seismological Society of America","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Seismological Society of America","publisherLocation":"Stanford","doi":"10.1785/0120120108","usgsCitation":"Hartzell, S.H., Mendoza, C., Ramírez-Guzmán, L., Zeng, Y., and Mooney, W., 2013, Rupture history of the 2008 <i>M</i><sub>w</sub> 7.9 Wenchuan, China, earthquake: Evaluation of separate and joint inversions of geodetic, teleseismic, and strong-motion data: Bulletin of the Seismological Society of America, v. 103, no. 1, p. 353-370, https://doi.org/10.1785/0120120108.","productDescription":"18 p.","startPage":"353","endPage":"370","numberOfPages":"18","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-038915","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":273330,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":273328,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1785/0120120108"}],"country":"China","otherGeospatial":"Wenchuan","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              101.8487548828125,\n              31.891550612684366\n            ],\n            [\n              102.89794921875,\n              32.43561304116276\n            ],\n            [\n              103.612060546875,\n              32.52365781569917\n            ],\n            [\n              104.23278808593749,\n              32.25462006000722\n            ],\n            [\n              104.6173095703125,\n              31.83089906339438\n            ],\n            [\n              104.0240478515625,\n              31.31140838620163\n            ],\n            [\n              103.45275878906249,\n              30.779598396611537\n            ],\n            [\n              103.2989501953125,\n              30.37761431777479\n            ],\n            [\n              102.227783203125,\n              30.443937998291165\n            ],\n            [\n              101.876220703125,\n              30.954057859276126\n            ],\n            [\n              101.8487548828125,\n              31.891550612684366\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"103","issue":"1","noUsgsAuthors":false,"publicationDate":"2013-02-05","publicationStatus":"PW","scienceBaseUri":"51b05dede4b030b5198012ed","contributors":{"authors":[{"text":"Hartzell, Stephen H. 0000-0003-0858-9043 shartzell@usgs.gov","orcid":"https://orcid.org/0000-0003-0858-9043","contributorId":2594,"corporation":false,"usgs":true,"family":"Hartzell","given":"Stephen","email":"shartzell@usgs.gov","middleInitial":"H.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":474703,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mendoza, Carlos","contributorId":10313,"corporation":false,"usgs":true,"family":"Mendoza","given":"Carlos","affiliations":[],"preferred":false,"id":474704,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ramírez-Guzmán, Leonardo","contributorId":45946,"corporation":false,"usgs":true,"family":"Ramírez-Guzmán","given":"Leonardo","affiliations":[],"preferred":false,"id":474706,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zeng, Yuesha","contributorId":52068,"corporation":false,"usgs":true,"family":"Zeng","given":"Yuesha","email":"","affiliations":[],"preferred":false,"id":474707,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mooney, Walter","contributorId":40952,"corporation":false,"usgs":true,"family":"Mooney","given":"Walter","affiliations":[],"preferred":false,"id":474705,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70044793,"text":"70044793 - 2013 - Identification of contamination in a lake sediment core using Hg and Pb isotopic compositions, Lake Ballinger, Washington, USA","interactions":[],"lastModifiedDate":"2013-05-30T09:04:46","indexId":"70044793","displayToPublicDate":"2013-02-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":835,"text":"Applied Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Identification of contamination in a lake sediment core using Hg and Pb isotopic compositions, Lake Ballinger, Washington, USA","docAbstract":"Concentrations and isotopic compositions of Hg and Pb were measured in a sediment core collected from Lake Ballinger, near Seattle, Washington, USA. Lake Ballinger has been affected by input of metal contaminants emitted from the Tacoma smelter, which operated from 1887 to 1986 and was located about 53 km south of the lake. Concentrations and loadings of Hg and Pb in Lake Ballinger increased by as much as three orders of magnitude during the period of smelting as compared to the pre-smelting period. Concentrations and loadings of Hg and Pb then decreased by about 55% and 75%, respectively, after smelting ended. Isotopic compositions of Hg changed considerably during the period of smelting (δ<sup>202</sup>Hg = −2.29‰ to −0.38‰, mean −1.23‰, n = 9) compared to the pre-smelting period (δ<sup>202</sup>Hg = −2.91‰ to −2.50‰, mean −2.75‰, n = 4). Variations were also observed in <sup>206</sup>Pb/<sup>207</sup>Pb and <sup>208</sup>Pb/<sup>207</sup>Pb isotopic compositions during these periods. Data for Δ<sup>199</sup>Hg and Δ<sup>201</sup>Hg indicate mass independent fractionation (MIF) of Hg isotopes in Lake Ballinger sediment during the smelting and post-smelting period and suggest MIF in the ore smelted, during the smelting process, or chemical modification at some point in the past. Negative values for Δ<sup>199</sup>Hg and Δ<sup>201</sup>Hg for the pre-smelting period are similar to those previously reported for soil, peat, and lichen, likely suggesting some component of atmospheric Hg. Variations in the concentrations and isotopic compositions of Hg and Pb were useful in tracing contaminant sources and the understanding of the depositional history of sedimentation in Lake Ballinger.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Applied Geochemistry","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.apgeochem.2012.12.001","usgsCitation":"Gray, J.E., Pribil, M., Van Metre, P., Borrok, D.M., and Thapalia, A., 2013, Identification of contamination in a lake sediment core using Hg and Pb isotopic compositions, Lake Ballinger, Washington, USA: Applied Geochemistry, v. 29, p. 1-12, https://doi.org/10.1016/j.apgeochem.2012.12.001.","productDescription":"12 p.","startPage":"1","endPage":"12","ipdsId":"IP-026930","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":273001,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.apgeochem.2012.12.001"},{"id":273002,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Hall Creek;Lake Ballinger;Tacoma Smelter","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.82,47.16 ], [ -122.82,48.22 ], [ -121.98,48.22 ], [ -121.98,47.16 ], [ -122.82,47.16 ] ] ] } } ] }","volume":"29","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51a874e6e4b082d85d5ed8a4","chorus":{"doi":"10.1016/j.apgeochem.2012.12.001","url":"http://dx.doi.org/10.1016/j.apgeochem.2012.12.001","publisher":"Elsevier BV","authors":"Gray John E., Pribil Michael J., Van Metre Peter C., Borrok David M., Thapalia Anita","journalName":"Applied Geochemistry","publicationDate":"2/2013","auditedOn":"11/1/2014"},"contributors":{"authors":[{"text":"Gray, John E. jgray@usgs.gov","contributorId":1275,"corporation":false,"usgs":true,"family":"Gray","given":"John","email":"jgray@usgs.gov","middleInitial":"E.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":476320,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pribil, Michael J.","contributorId":62115,"corporation":false,"usgs":true,"family":"Pribil","given":"Michael J.","affiliations":[],"preferred":false,"id":476324,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Van Metre, Peter C.","contributorId":34104,"corporation":false,"usgs":true,"family":"Van Metre","given":"Peter C.","affiliations":[],"preferred":false,"id":476322,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Borrok, David M.","contributorId":26056,"corporation":false,"usgs":true,"family":"Borrok","given":"David","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":476321,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Thapalia, Anita","contributorId":38270,"corporation":false,"usgs":true,"family":"Thapalia","given":"Anita","email":"","affiliations":[],"preferred":false,"id":476323,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70043022,"text":"sir20135005 - 2013 - Water quality, streamflow conditions, and annual flow-duration curves for streams of the San Juan–Chama Project, southern Colorado and northern New Mexico, 1935-2010","interactions":[],"lastModifiedDate":"2013-01-31T09:06:42","indexId":"sir20135005","displayToPublicDate":"2013-01-31T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-5005","title":"Water quality, streamflow conditions, and annual flow-duration curves for streams of the San Juan–Chama Project, southern Colorado and northern New Mexico, 1935-2010","docAbstract":"The Albuquerque–Bernalillo County Water Utility Authority supplements the municipal water supply for the Albuquerque metropolitan area, in central New Mexico, with water diverted from the Rio Grande. Water diverted from the Rio Grande for municipal use is derived from the San Juan–Chama Project, which delivers water from streams in the southern San Juan Mountains in the Colorado River Basin in southern Colorado to the Rio Chama watershed and the Rio Grande Basin in northern New Mexico. The U.S. Geological Survey, in cooperation with Albuquerque–Bernalillo County Water Utility Authority, has compiled historical streamflow and water-quality data and collected new water-quality data to characterize the water quality and streamflow conditions and annual flow variability, as characterized by annual flow-duration curves, of streams of the San Juan–Chama Project. Nonparametric statistical methods were applied to calculate annual and monthly summary statistics of streamflow, trends in streamflow conditions were evaluated with the Mann–Kendall trend test, and annual variation in streamflow conditions was evaluated with annual flow-duration curves. The study area is located in northern New Mexico and southern Colorado and includes the Rio Blanco, Little Navajo River, and Navajo River, tributaries of the San Juan River in the Colorado River Basin located in the southern San Juan Mountains, and Willow Creek and Horse Lake Creek, tributaries of the Rio Chama in the Rio Grande Basin. The quality of water in the streams in the study area generally varied by watershed on the basis of the underlying geology and the volume and source of the streamflow. Water from the Rio Blanco and Little Navajo River watersheds, primarily underlain by volcanic deposits, volcaniclastic sediments and landslide deposits derived from these materials, was compositionally similar and had low specific-conductance values relative to the other streams in the study area. Water from the Navajo River, Horse Lake Creek, and Willow Creek watersheds, which are underlain mostly by Cretaceous-aged marine shale, was compositionally similar and had large concentrations of sulfate relative to the other streams in the study area, though the water from the Navajo River had lower specific-conductance values than did the water from Horse Lake Creek above Heron Reservoir and Willow Creek above Azotea Creek. Generally, surface-water quality varied with streamflow conditions throughout the year. Streamflow in spring and summer is generally a mixture of base flow (the component of streamflow derived from groundwater discharged to the stream channel) diluted with runoff from snowmelt and precipitation events, whereas streamflow in fall and winter is generally solely base flow. Major- and trace-element concentrations in the streams sampled were lower than U.S. Environmental Protection Agency primary and secondary drinking-water standards and New Mexico Environment Department surface-water standards for the streams. In general, years with increased annual discharge, compared to years with decreased annual discharge, had a smaller percentage of discharge in March, a larger percentage of discharge in June, an interval of discharge derived from snowmelt runoff that occurred later in the year, and a larger discharge in June. Additionally, years with increased annual discharge generally had a longer duration of runoff, and the streamflow indicators occurred at dates later in the year than the years with less snowmelt runoff. Additionally, the seasonal distribution of streamflow was more strongly controlled by the change in the amount of annual discharge than by changes in streamflow over time. The variation of streamflow conditions over time at one streamflow-gaging station in the study area, Navajo River at Banded Peak Ranch, was not significantly monotonic over the period of record with a Kendall’s tau of 0.0426 and with a p-value of 0.5938 for 1937 to 2009 (a trend was considered statistically significant at a p-value ≤ 0.05). There was a relation, however, such that annual discharge was generally lower than the median during a negative Pacific Decadal Oscillation interval and higher than the median during a positive Pacific Decadal Oscillation interval. Streamflow conditions at Navajo River at Banded Peak Ranch varied nonmonotonically over time and were likely a function of complex climate pattern interactions. Similarly, the monthly distribution of streamflow varied nonmonotonically over time and was likely a function of complex climate pattern interactions that cause variation over time. Study results indicated that the median of the sum of the streamflow available above the minimum monthly bypass requirement from Rio Blanco, Little Navajo River, and Navajo River was 126,240 acre-feet. The results also indicated that diversion of water for the San Juan–Chama Project has been possible for most months of most years.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135005","isbn":"978-1-4113-3552-3","collaboration":"Prepared in cooperation with the Albuquerque–Bernalillo County Water Utility Authority","usgsCitation":"Falk, S.E., Anderholm, S.K., and Hafich, K.A., 2013, Water quality, streamflow conditions, and annual flow-duration curves for streams of the San Juan–Chama Project, southern Colorado and northern New Mexico, 1935-2010: U.S. Geological Survey Scientific Investigations Report 2013-5005, Report: x, 50 p.; 1 Appendix, https://doi.org/10.3133/sir20135005.","productDescription":"Report: x, 50 p.; 1 Appendix","numberOfPages":"63","additionalOnlineFiles":"Y","temporalStart":"1935-01-01","temporalEnd":"2010-12-31","ipdsId":"IP-034463","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":266785,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2013_5005.gif"},{"id":266784,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2013/5005/app1.xlsx"},{"id":266782,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5005/"},{"id":266783,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5005/sir2013-5005.pdf"}],"projection":"Geographic projection","datum":"North American Datum of 1983","country":"United States","state":"Colorado;New Mexico","county":"Archuleta;Conejos;Mineral;Rio Arriba;Rio Grande","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -107.0,36.5 ], [ -107.0,37.5 ], [ -106.5,37.5 ], [ -106.5,36.5 ], [ -107.0,36.5 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"510b9281e4b0947afa3c8558","contributors":{"authors":[{"text":"Falk, Sarah E. sefalk@usgs.gov","contributorId":1056,"corporation":false,"usgs":true,"family":"Falk","given":"Sarah","email":"sefalk@usgs.gov","middleInitial":"E.","affiliations":[],"preferred":true,"id":472798,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderholm, Scott K.","contributorId":94270,"corporation":false,"usgs":true,"family":"Anderholm","given":"Scott","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":472800,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hafich, Katya A.","contributorId":45604,"corporation":false,"usgs":true,"family":"Hafich","given":"Katya","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":472799,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70042722,"text":"ds706 - 2013 - Groundwater-quality data in the Western San Joaquin Valley study unit, 2010 - Results from the California GAMA Program","interactions":[],"lastModifiedDate":"2013-01-31T15:01:03","indexId":"ds706","displayToPublicDate":"2013-01-31T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"706","title":"Groundwater-quality data in the Western San Joaquin Valley study unit, 2010 - Results from the California GAMA Program","docAbstract":"Groundwater quality in the approximately 2,170-square-mile Western San Joaquin Valley (WSJV) study unit was investigated by the U.S. Geological Survey (USGS) from March to July 2010, as part of the California State Water Resources Control Board (SWRCB) Groundwater Ambient Monitoring and Assessment (GAMA) Program's Priority Basin Project (PBP). The GAMA-PBP was developed in response to the California Groundwater Quality Monitoring Act of 2001 and is being conducted in collaboration with the SWRCB and Lawrence Livermore National Laboratory (LLNL). The WSJV study unit was the twenty-ninth study unit to be sampled as part of the GAMA-PBP. The GAMA Western San Joaquin Valley study was designed to provide a spatially unbiased assessment of untreated-groundwater quality in the primary aquifer system, and to facilitate statistically consistent comparisons of untreated groundwater quality throughout California. The primary aquifer system is defined as parts of aquifers corresponding to the perforation intervals of wells listed in the California Department of Public Health (CDPH) database for the WSJV study unit. Groundwater quality in the primary aquifer system may differ from the quality in the shallower or deeper water-bearing zones; shallow groundwater may be more vulnerable to surficial contamination. In the WSJV study unit, groundwater samples were collected from 58 wells in 2 study areas (Delta-Mendota subbasin and Westside subbasin) in Stanislaus, Merced, Madera, Fresno, and Kings Counties. Thirty-nine of the wells were selected by using a spatially distributed, randomized grid-based method to provide statistical representation of the study unit (grid wells), and 19 wells were selected to aid in the understanding of aquifer-system flow and related groundwater-quality issues (understanding wells). The groundwater samples were analyzed for organic constituents (volatile organic compounds [VOCs], low-level fumigants, and pesticides and pesticide degradates), constituents of special interest (perchlorate, <i>N</i>-nitrosodimethylamine [NDMA], and 1,2,3-trichloropropane [1,2,3-TCP]), and naturally occurring inorganic constituents (trace elements, nutrients, dissolved organic carbon [DOC], major and minor ions, silica, total dissolved solids [TDS], alkalinity, total arsenic and iron [unfiltered] and arsenic, chromium, and iron species [filtered]). Isotopic tracers (stable isotopes of hydrogen, oxygen, and boron in water, stable isotopes of nitrogen and oxygen in dissolved nitrate, stable isotopes of sulfur in dissolved sulfate, isotopic ratios of strontium in water, stable isotopes of carbon in dissolved inorganic carbon, activities of tritium, and carbon-14 abundance), dissolved standard gases (methane, carbon dioxide, nitrogen, oxygen, and argon), and dissolved noble gases (argon, helium-4, krypton, neon, and xenon) were measured to help identify sources and ages of sampled groundwater. In total, 245 constituents and 8 water-quality indicators were measured. Quality-control samples (blanks, replicates, or matrix spikes) were collected at 16 percent of the wells in the WSJV study unit, and the results for these samples were used to evaluate the quality of the data from the groundwater samples. Blanks rarely contained detectable concentrations of any constituent, suggesting that contamination from sample collection procedures was not a significant source of bias in the data for the groundwater samples. Replicate samples all were within acceptable limits of variability. Matrix-spike recoveries were within the acceptable range (70 to 130 percent) for approximately 87 percent of the compounds. This study did not evaluate the quality of water delivered to consumers. After withdrawal, groundwater typically is treated, disinfected, and (or) blended with other waters to maintain water quality. Regulatory benchmarks apply to water that is delivered to the consumer, not to untreated groundwater. However, to provide some context for the results, concentrations of constituents measured in the untreated groundwater were compared with regulatory and non-regulatory health-based benchmarks established by the U.S. Environmental Protection Agency (USEPA) and CDPH, and to non-regulatory benchmarks established for aesthetic concerns by CDPH. Comparisons between data collected for this study and benchmarks for drinking water are for illustrative purposes only and are not indicative of compliance or non-compliance with those benchmarks. Most inorganic constituents detected in groundwater samples from the 39 grid wells were detected at concentrations less than health-based benchmarks. Detections of organic and special-interest constituents from grid wells sampled in the WSJV study unit also were less than health-based benchmarks. In total, VOCs were detected in 12 of the 39 grid wells sampled (approximately 31 percent), pesticides and pesticide degradates were detected in 9 grid wells (approximately 23 percent), and perchlorate was detected in 15 grid wells (approximately 38 percent). Trace elements, major and minor ions, and nutrients were sampled for at 39 grid wells; most concentrations were less than health-based benchmarks. Exceptions include two detections of arsenic greater than the USEPA maximum contaminant level (MCL-US) of 10 micrograms per liter (&mu;g/L), 20 detections of boron greater than the CDPH notification level (NL-CA) of 1,000 &mu;g/L, 2 detections of molybdenum greater than the USEPA lifetime health advisory level (HAL-US) of 40 &mu;g/L, 1 detection of selenium greater than the MCL-US of 50 &mu;g/L, 2 detections of strontium greater than the HAL-US of 4,000 &mu;g/L, and 3 detections of nitrate greater than the MCL-US of 10 &mu;g/L. Results for inorganic constituents with non-health-based benchmarks (iron, manganese, chloride, sulfate, and TDS) showed that iron concentrations greater than the CDPH secondary maximum contaminant level (SMCL-CA) of 300 &mu;g/L were detected in five grid wells. Manganese concentrations greater than the SMCL-CA of 50 &mu;g/L were detected in 16 grid wells. Chloride concentrations greater than the recommended SMCL-CA benchmark of 250 milligrams per liter (mg/L) were detected in 14 grid wells, and concentrations in 5 of these wells also were greater than the upper SMCL-CA benchmark of 500 mg/L. Sulfate concentrations greater than the recommended SMCL-CA benchmark of 250 mg/L were measured in 21 grid wells, and concentrations in 13 of these wells also were greater than the SMCL-CA upper benchmark of 500 mg/L. TDS concentrations greater than the SMCL-CA recommended benchmark of 500 mg/L were measured in 36 grid wells, and concentrations in 20 of these wells also were greater than the SMCL-CA upper benchmark of 1,000 mg/L.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds706","collaboration":"A product of the California Groundwater Ambient Monitoring and Assessment (GAMA) Program; Prepared in cooperation with the California State Water Resources Control Board","usgsCitation":"Mathany, T., Landon, M.K., Shelton, J.L., and Belitz, K., 2013, Groundwater-quality data in the Western San Joaquin Valley study unit, 2010 - Results from the California GAMA Program: U.S. Geological Survey Data Series 706, x, 104 p., https://doi.org/10.3133/ds706.","productDescription":"x, 104 p.","numberOfPages":"116","ipdsId":"IP-027484","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":266862,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds_706.jpg"},{"id":266861,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/706/pdf/ds706.pdf"},{"id":266860,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/706/"}],"country":"United States","state":"California","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -0.01611111111111111,8.333333333333334E-4 ], [ -0.01611111111111111,0.0011111111111111111 ], [ -0.01638888888888889,0.0011111111111111111 ], [ -0.01638888888888889,8.333333333333334E-4 ], [ -0.01611111111111111,8.333333333333334E-4 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"510b9279e4b0947afa3c8540","contributors":{"authors":[{"text":"Mathany, Timothy M. 0000-0002-4747-5113","orcid":"https://orcid.org/0000-0002-4747-5113","contributorId":99949,"corporation":false,"usgs":true,"family":"Mathany","given":"Timothy M.","affiliations":[],"preferred":false,"id":472117,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Landon, Matthew K. 0000-0002-5766-0494 landon@usgs.gov","orcid":"https://orcid.org/0000-0002-5766-0494","contributorId":392,"corporation":false,"usgs":true,"family":"Landon","given":"Matthew","email":"landon@usgs.gov","middleInitial":"K.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":472114,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shelton, Jennifer L. 0000-0001-8508-0270 jshelton@usgs.gov","orcid":"https://orcid.org/0000-0001-8508-0270","contributorId":1155,"corporation":false,"usgs":true,"family":"Shelton","given":"Jennifer","email":"jshelton@usgs.gov","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":472116,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Belitz, Kenneth 0000-0003-4481-2345 kbelitz@usgs.gov","orcid":"https://orcid.org/0000-0003-4481-2345","contributorId":442,"corporation":false,"usgs":true,"family":"Belitz","given":"Kenneth","email":"kbelitz@usgs.gov","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true}],"preferred":true,"id":472115,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70043032,"text":"ds709L - 2013 - Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Nalbandon mineral district in Afghanistan: Chapter L in <i>Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan</i>","interactions":[],"lastModifiedDate":"2013-02-01T11:11:56","indexId":"ds709L","displayToPublicDate":"2013-01-31T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"709","chapter":"L","title":"Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Nalbandon mineral district in Afghanistan: Chapter L in <i>Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan</i>","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 Nalbandon mineral district, which has lead and zinc 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, 2007, 2008, 2010), 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 500-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 (41 for Nalbandon) and the WGS84 datum. The final image mosaics were subdivided into ten overlapping tiles or quadrants because of the large size of the target area. The ten image tiles (or quadrants) for the Nalbandon 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. Within the Nalbandon study area, two subareas were designated for detailed field investigations (that is, the Nalbandon District and Gharghananaw-Gawmazar subareas); these subareas were extracted from the area’s image mosaic and are provided as separate embedded geotiff images.","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/ds709L","collaboration":"Prepared in cooperation with the U.S. Department of Defense <a href=\"http://tfbso.defense.gov/www/\" target=\"_blank\">Task Force for Business and Stability Operations</a> and the <a href=\"http://www.bgs.ac.uk/AfghanMinerals/\" target=\"_blank\">Afghanistan Geological Survey</a>.  This report is Chapter L in <i>Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan</i>. For more information, see: <a href=\"http://pubs.er.usgs.gov/publication/ds709\" target=\"_blank\">Data Series 709</a>.","usgsCitation":"Davis, P.A., and Cagney, L.E., 2013, Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Nalbandon mineral district in Afghanistan: Chapter L in <i>Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan</i>: U.S. Geological Survey Data Series 709, Readme; 2 Maps: 11 x 8.5 inches and 68.21 x 31.13 inches; 24 Image Files; 24 Metadata Files; 1 Shapefile; DS 709, https://doi.org/10.3133/ds709L.","productDescription":"Readme; 2 Maps: 11 x 8.5 inches and 68.21 x 31.13 inches; 24 Image Files; 24 Metadata Files; 1 Shapefile; DS 709","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2006-01-24","costCenters":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"links":[{"id":266830,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds_709_l.jpg"},{"id":266825,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/709/l/index_maps/index_maps.html"},{"id":266819,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/709/l/"},{"id":266821,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/ds/709/l/1_readme.txt"},{"id":266826,"type":{"id":14,"text":"Image"},"url":"https://pubs.usgs.gov/ds/709/l/image_files/image_files.html"},{"id":266823,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/l/index_maps/Nalbandon_Area-of-Interest_Index_Map.pdf"},{"id":266824,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/l/index_maps/Nalbandon_Image_Index_Map.pdf"},{"id":266827,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/ds/709/l/metadata/metadata.html"},{"id":266828,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/ds/709/l/shapefiles/shapefiles.html"},{"id":266829,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/ds/709/index.html"}],"country":"Afghanistan","otherGeospatial":"Nalbandon Mineral District","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 63.5,33.9 ], [ 63.5,34.5 ], [ 65.0,34.5 ], [ 65.0,33.9 ], [ 63.5,33.9 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"510b927ee4b0947afa3c8548","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":472807,"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":472808,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70188522,"text":"70188522 - 2013 - Diatom evidence for the onset of Pliocene cooling from AND-1B, McMurdo Sound, Antarctica","interactions":[],"lastModifiedDate":"2018-03-23T12:22:36","indexId":"70188522","displayToPublicDate":"2013-01-31T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2996,"text":"Palaeogeography, Palaeoclimatology, Palaeoecology","printIssn":"0031-0182","active":true,"publicationSubtype":{"id":10}},"title":"Diatom evidence for the onset of Pliocene cooling from AND-1B, McMurdo Sound, Antarctica","docAbstract":"<p><span>The late Pliocene, ~</span><span>&nbsp;</span><span>3.3–3.0</span><span>&nbsp;</span><span>Ma, is the most recent interval of sustained global warmth in the geologic past. This window is the focus of climate reconstruction efforts by the U.S. Geological Survey's Pliocene Research, Interpretation, and Synoptic Mapping (PRISM) Data/Model Cooperative, and may provide a useful climate analog for the coming century. Reconstructions of past surface ocean conditions proximal to the Antarctic continent are essential to understanding the sensitivity of the cryosphere to this key interval in Earth's climate evolution. An exceptional marine sediment core collected from the southwestern Ross Sea (78° S), Antarctica, during ANDRILL's McMurdo Ice Shelf Project preserves evidence of dramatic fluctuations between grounded ice and productive, open ocean conditions during the late Pliocene, reflecting orbitally-paced glacial/interglacial cycling. In this near-shore record, diatom-rich sediments are recovered from interglacial intervals; two of these diatomites, from ~</span><span>&nbsp;</span><span>3.2</span><span>&nbsp;</span><span>Ma and 3.03</span><span>&nbsp;</span><span>Ma, are within the PRISM chronologic window. The diatom assemblages identified in PRISM-age late Pliocene diatom-rich sediments are distinct from those in mid-Pliocene and later Pliocene/Pleistocene intervals recovered from AND-1B, and comprise both extant taxa with well-constrained ecological preferences and a diverse extinct flora, some members of which are previously undescribed from Antarctic sediments. Both units are dominated by </span><i>Chaetoceros</i><span> resting spores, an indicator of high productivity and stratification that is present at much lower abundance in materials both older and younger than the PRISM-age sediments. Newly described species of the genus </span><i>Fragilariopsis</i><span>, which first appear in the AND-1B record at 3.2</span><span>&nbsp;</span><span>Ma, are the most abundant extinct members of the PRISM-age assemblages. Other extant species with established environmental affinities, such as </span><i>Fragilariopsis sublinearis</i><span>, </span><i>F</i><span>. </span><i>curta</i><span>, </span><i>Stellarima microtrias</i><span>, and </span><i>Thalassiothrix antarctica</i><span>, are present at lower abundances. Environmental inferences drawn from extant diatom assemblages are in good agreement with those from </span><i>Chaetoceros</i><span> resting spores and the </span><i>Fragilariopsis</i><span> radiation. All three lines of evidence indicate the onset of late Pliocene cooling in the Ross Sea near-shore environment at 3.2</span><span>&nbsp;</span><span>Ma, with intensification and possible regional persistence of summer sea ice by 3.03</span><span>&nbsp;</span><span>Ma. An important implication of this research is the indication that the Ross Ice Shelf fluctuated dramatically on orbital timescales at a time when nearshore Antarctic conditions were only modestly warmer than present.</span></p>","language":"English","publisher":"Palaeogeography, Palaeoclimatology, Palaeoecology","doi":"10.1016/j.palaeo.2012.10.014","usgsCitation":"Riesselman, C., and Dunbar, R.B., 2013, Diatom evidence for the onset of Pliocene cooling from AND-1B, McMurdo Sound, Antarctica: Palaeogeography, Palaeoclimatology, Palaeoecology, v. 369, p. 136-153, https://doi.org/10.1016/j.palaeo.2012.10.014.","productDescription":"18 p. ","startPage":"136","endPage":"153","ipdsId":"IP-033564","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":342499,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Antarctica, McMurdo Sound, Ross Ice Shelf, Ross Sea","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -210.9375,\n              -80.70399666821143\n            ],\n            [\n              -38.3203125,\n              -80.70399666821143\n            ],\n            [\n              -38.3203125,\n              -65.21989393613208\n            ],\n            [\n              -210.9375,\n              -65.21989393613208\n            ],\n            [\n              -210.9375,\n              -80.70399666821143\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"369","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59424b3ce4b0764e6c65dc71","contributors":{"authors":[{"text":"Riesselman, Christina 0000-0002-2436-4306 criesselman@usgs.gov","orcid":"https://orcid.org/0000-0002-2436-4306","contributorId":4290,"corporation":false,"usgs":true,"family":"Riesselman","given":"Christina","email":"criesselman@usgs.gov","affiliations":[],"preferred":true,"id":698131,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dunbar, R. B.","contributorId":192914,"corporation":false,"usgs":false,"family":"Dunbar","given":"R.","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":698132,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
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