Semipalmated Sandpipers (Calidris pusilla) are among the most common North American shorebirds. Breeding in Arctic North America, this species displays regional differences in migratory pathways and possesses longitudinal bill length variation. Previous investigations suggested that genetic structure may occur within Semipalmated Sandpipers and that three subspecies corresponding to western, central, and eastern breeding groups exist. In this study, mitochondrial control region sequences and nuclear microsatellite loci were used to analyze DNA of birds (microsatellites: n = 120; mtDNA: n = 114) sampled from seven North American locations. Analyses designed to quantify genetic structure and diversity patterns, evaluate genetic evidence for population size changes, and determine if genetic data support the existence of Semipalmated Sandpiper subspecies were performed. Genetic structure based only on the mtDNA data was observed, whereas the microsatellite loci provided no evidence of genetic differentiation. Differentiation among locations and regions reflected allele frequency differences rather than separate phylogenetic groups, and similar levels of genetic diversity were noted. Combined, the two data sets provided no evidence to support the existence of subspecies and were not useful for determining migratory connectivity between breeding sites and wintering grounds. Birds from western and central groups displayed signatures of population expansions, whereas the eastern group was more consistent with a stable overall population. Results of this analysis suggest that the eastern group was the source of individuals that colonized the central and western regions currently utilized by Semipalmated Sandpipers.
","language":"English","publisher":"The Waterbird Society","doi":"10.1675/063.036.0206","usgsCitation":"Miller, M.P., Gratto-Trevor, C., Haig, S.M., Mizrahi, D.S., Mitchell, M.M., and Mullins, T., 2013, Population genetics and evaluation of genetic evidence for subspecies in the Semipalmated Sandpiper (Calidris pusilla): Waterbirds, v. 36, no. 2, p. 166-178, https://doi.org/10.1675/063.036.0206.","productDescription":"13 p.","startPage":"166","endPage":"178","ipdsId":"IP-042836","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":473660,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1675/063.036.0206","text":"Publisher Index Page"},{"id":381723,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"North America","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -178.8,25.3 ], [ -178.8,83.2 ], [ -51.3,83.2 ], [ -51.3,25.3 ], [ -178.8,25.3 ] ] ] } } ] }","volume":"36","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51ef97d6e4b0b09fbe58f159","contributors":{"authors":[{"text":"Miller, Mark P. 0000-0003-1045-1772 mpmiller@usgs.gov","orcid":"https://orcid.org/0000-0003-1045-1772","contributorId":1967,"corporation":false,"usgs":true,"family":"Miller","given":"Mark","email":"mpmiller@usgs.gov","middleInitial":"P.","affiliations":[{"id":38131,"text":"WMA - Office of Planning and Programming","active":true,"usgs":true}],"preferred":true,"id":480555,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gratto-Trevor, Cheri","contributorId":58539,"corporation":false,"usgs":true,"family":"Gratto-Trevor","given":"Cheri","affiliations":[],"preferred":false,"id":480559,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haig, Susan M. 0000-0002-6616-7589 susan_haig@usgs.gov","orcid":"https://orcid.org/0000-0002-6616-7589","contributorId":719,"corporation":false,"usgs":true,"family":"Haig","given":"Susan","email":"susan_haig@usgs.gov","middleInitial":"M.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":480554,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mizrahi, David S.","contributorId":11100,"corporation":false,"usgs":true,"family":"Mizrahi","given":"David","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":480556,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mitchell, Melanie M.","contributorId":38045,"corporation":false,"usgs":true,"family":"Mitchell","given":"Melanie","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":480558,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mullins, Thomas D.","contributorId":12819,"corporation":false,"usgs":true,"family":"Mullins","given":"Thomas D.","affiliations":[],"preferred":false,"id":480557,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70047141,"text":"ds775 - 2013 - High-water marks from tropical storm Irene for selected river reaches in northwestern Massachusetts, August 2011","interactions":[],"lastModifiedDate":"2013-07-22T14:32:20","indexId":"ds775","displayToPublicDate":"2013-07-22T14:10:00","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":"775","title":"High-water marks from tropical storm Irene for selected river reaches in northwestern Massachusetts, August 2011","docAbstract":"A Presidential Disaster Declaration was issued for Massachusetts, with a focus on the northwestern counties, following flooding from tropical storm Irene on August 28–29, 2011. Three to 10 inches of rain fell during the storm on soils that were susceptible to flash flooding because of wet antecedent conditions. The gage height at one U.S. Geological Survey (USGS) streamgage rose nearly 20 feet in less than 4 hours because of the combination of saturated soils and intense rainfall. Eight of 16 USGS long-term streamgages in western Massachusetts set new peaks of record on August 28 or 29, 2011. To document the historic water levels of the streamflows from tropical storm Irene, the USGS identified, flagged, and surveyed 323 high-water marks in the Deerfield and Hudson- Hoosic River basins in northwestern Massachusetts. Areas targeted for high-water marks were generally upstream and downstream from structures along selected river reaches. Elevations from high-water marks can be used to confirm peak river stages or help compute peak streamflows, to calibrate hydraulic models, or to update flood-inundation and recovery maps. For areas in western Massachusetts that flooded as a result of tropical storm Irene, high-water marks surveyed for this study have helped to confirm or determine instantaneous peak river gage heights at several USGS streamgages.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds775","collaboration":"Prepared in cooperation with the Federal Emergency Management Agency","usgsCitation":"Bent, G.C., Medalie, L., and Nielsen, M.G., 2013, High-water marks from tropical storm Irene for selected river reaches in northwestern Massachusetts, August 2011: U.S. Geological Survey Data Series 775, Report: iv, 13 p.; Appendix 1: XLS file; Appendix 2: KMZ file, https://doi.org/10.3133/ds775.","productDescription":"Report: iv, 13 p.; Appendix 1: XLS file; Appendix 2: KMZ file","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":275237,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds775.jpg"},{"id":275234,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/775/"},{"id":275235,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/775/appendix/USGS_Data_Series_775_Appendix_1.xlsx"},{"id":275236,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/775/appendix/USGS_Data_Series_775_Appendix_2_HWMs.kmz"},{"id":275233,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/775/pdf/ds775_report_508.pdf"}],"country":"United States","state":"Massachusetts","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -73.493042,42.012571 ], [ -73.493042,42.710696 ], [ -72.463074,42.710696 ], [ -72.463074,42.012571 ], [ -73.493042,42.012571 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51ee4655e4b00ffbed48f84d","contributors":{"authors":[{"text":"Bent, Gardner C. 0000-0002-5085-3146 gbent@usgs.gov","orcid":"https://orcid.org/0000-0002-5085-3146","contributorId":1864,"corporation":false,"usgs":true,"family":"Bent","given":"Gardner","email":"gbent@usgs.gov","middleInitial":"C.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":481153,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Medalie, Laura 0000-0002-2440-2149 lmedalie@usgs.gov","orcid":"https://orcid.org/0000-0002-2440-2149","contributorId":3657,"corporation":false,"usgs":true,"family":"Medalie","given":"Laura","email":"lmedalie@usgs.gov","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":481154,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nielsen, Martha G. 0000-0003-3038-9400 mnielsen@usgs.gov","orcid":"https://orcid.org/0000-0003-3038-9400","contributorId":4169,"corporation":false,"usgs":true,"family":"Nielsen","given":"Martha","email":"mnielsen@usgs.gov","middleInitial":"G.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":481155,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70046965,"text":"70046965 - 2013 - Relating Yellow Rail (Coturnicops noveboracensis) occupancy to habitat and landscape features in the context of fire","interactions":[],"lastModifiedDate":"2017-09-08T09:12:23","indexId":"70046965","displayToPublicDate":"2013-07-22T13:44:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3731,"text":"Waterbirds","onlineIssn":"19385390","printIssn":"15244695","active":true,"publicationSubtype":{"id":10}},"title":"Relating Yellow Rail (Coturnicops noveboracensis) occupancy to habitat and landscape features in the context of fire","docAbstract":"The Yellow Rail (Coturnicops noveboracensis) is a focal species of concern associated with shallowly flooded emergent wetlands, most commonly sedge (Carex spp.) meadows. Their populations are believed to be limited by loss or degradation of wetland habitat due to drainage, altered hydrology, and fire suppression, factors that have often resulted in encroachment of shrubs into sedge meadows and change in vegetative cover. Nocturnal call-playback surveys for Yellow Rails were conducted over 3 years at Seney National Wildlife Refuge in the Upper Peninsula of Michigan. Effects of habitat structure and landscape variables on the probability of use by Yellow Rails were assessed at two scales, representing a range of home range sizes, using generalized linear mixed models. At the 163-m (8-ha) scale, year with quadratic models of maximum and mean water depths best explained the data. At the 300-m (28-ha) scale, the best model contained year and time since last fire (≤ 1, 2–5, and > 10 years). The probability of use by Yellow Rails was 0.285 ± 0.132 (SE) for points burned 2-5 years ago, 0.253 ± 0.097 for points burned ≤ 1 year ago, and 0.028 ± 0.019 for points burned > 10 years ago. Habitat differences relative to fire history and comparisons between sites with and without Yellow Rails indicated that Yellow Rails used areas with the deepest litter and highest ground cover, and relatively low shrub cover and heights, as well as landscapes having greater sedge-grass cover and less lowland woody or upland cover types. Burning every 2-5 years appears to provide the litter, ground-level cover, and woody conditions attractive to Yellow Rails. Managers seeking to restore and sustain these wetland systems would benefit from further investigations into how flooding and fire create habitat conditions attractive to breeding Yellow Rails","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Waterbirds","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"The Waterbird Society","doi":"10.1675/063.036.0209","usgsCitation":"Austin, J., and Buhl, D., 2013, Relating Yellow Rail (Coturnicops noveboracensis) occupancy to habitat and landscape features in the context of fire: Waterbirds, v. 36, no. 2, p. 199-213, https://doi.org/10.1675/063.036.0209.","productDescription":"15 p.","startPage":"199","endPage":"213","ipdsId":"IP-039078","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":473663,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1675/063.036.0209","text":"Publisher Index Page"},{"id":275190,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":274839,"type":{"id":15,"text":"Index Page"},"url":"https://www.bioone.org/doi/pdf/10.1675/063.036.0209"},{"id":275184,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1675/063.036.0209"}],"country":"United States","state":"Michigan","otherGeospatial":"Seney National Wildlife Refuge","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -86.27,46.16 ], [ -86.27,46.77 ], [ -84.95,46.77 ], [ -84.95,46.16 ], [ -86.27,46.16 ] ] ] } } ] }","volume":"36","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51ee465be4b00ffbed48f875","contributors":{"authors":[{"text":"Austin, Jane E.","contributorId":43094,"corporation":false,"usgs":true,"family":"Austin","given":"Jane E.","affiliations":[],"preferred":false,"id":480725,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Buhl, Deborah A. 0000-0002-8563-5990","orcid":"https://orcid.org/0000-0002-8563-5990","contributorId":26250,"corporation":false,"usgs":true,"family":"Buhl","given":"Deborah A.","affiliations":[],"preferred":false,"id":480724,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70045973,"text":"70045973 - 2013 - Predicting locations of rare aquatic species’ habitat with a combination of species-specific and assemblage-based models","interactions":[],"lastModifiedDate":"2013-07-22T11:47:36","indexId":"70045973","displayToPublicDate":"2013-07-22T11:34:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1399,"text":"Diversity and Distributions","active":true,"publicationSubtype":{"id":10}},"title":"Predicting locations of rare aquatic species’ habitat with a combination of species-specific and assemblage-based models","docAbstract":"Aim: Rare aquatic species are a substantial component of biodiversity, and their conservation is a major objective of many management plans. However, they are difficult to assess, and their optimal habitats are often poorly known. Methods to effectively predict the likely locations of suitable rare aquatic species habitats are needed. We combine two modelling approaches to predict occurrence and general abundance of several rare fish species. Location: Allegheny watershed of western New York State (USA) Methods: Our method used two empirical neural network modelling approaches (species specific and assemblage based) to predict stream-by-stream occurrence and general abundance of rare darters, based on broad-scale habitat conditions. Species-specific models were developed for longhead darter (Percina macrocephala), spotted darter (Etheostoma maculatum) and variegate darter (Etheostoma variatum) in the Allegheny drainage. An additional model predicted the type of rare darter-containing assemblage expected in each stream reach. Predictions from both models were then combined inclusively and exclusively and compared with additional independent data. Results Example rare darter predictions demonstrate the method's effectiveness. Models performed well (R2 ≥ 0.79), identified where suitable darter habitat was most likely to occur, and predictions matched well to those of collection sites. Additional independent data showed that the most conservative (exclusive) model slightly underestimated the distributions of these rare darters or predictions were displaced by one stream reach, suggesting that new darter habitat types were detected in the later collections. Main conclusions Broad-scale habitat variables can be used to effectively identify rare species' habitats. Combining species-specific and assemblage-based models enhances our ability to make use of the sparse data on rare species and to identify habitat units most likely and least likely to support those species. This hybrid approach may assist managers with the prioritization of habitats to be examined or conserved for rare species.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Diversity and Distributions","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1111/ddi.12059","usgsCitation":"McKenna, J., Carlson, D.M., and Payne-Wynne, M.L., 2013, Predicting locations of rare aquatic species’ habitat with a combination of species-specific and assemblage-based models: Diversity and Distributions, v. 19, no. 5-6, p. 503-517, https://doi.org/10.1111/ddi.12059.","productDescription":"15 p.","startPage":"503","endPage":"517","numberOfPages":"15","ipdsId":"IP-039413","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":473665,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ddi.12059","text":"Publisher Index Page"},{"id":275216,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":275215,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/ddi.12059"}],"country":"United States","state":"New York","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -79.881592,41.459195 ], [ -79.881592,42.228517 ], [ -78.222656,42.228517 ], [ -78.222656,41.459195 ], [ -79.881592,41.459195 ] ] ] } } ] }","volume":"19","issue":"5-6","noUsgsAuthors":false,"publicationDate":"2013-05-06","publicationStatus":"PW","scienceBaseUri":"51ee465be4b00ffbed48f871","contributors":{"authors":[{"text":"McKenna, James E.","contributorId":9217,"corporation":false,"usgs":true,"family":"McKenna","given":"James E.","affiliations":[],"preferred":false,"id":478619,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carlson, Douglas M.","contributorId":91001,"corporation":false,"usgs":false,"family":"Carlson","given":"Douglas","email":"","middleInitial":"M.","affiliations":[{"id":13678,"text":"New York State Department of Environmental Conservation","active":true,"usgs":false}],"preferred":false,"id":478621,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Payne-Wynne, Molly L.","contributorId":33604,"corporation":false,"usgs":true,"family":"Payne-Wynne","given":"Molly","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":478620,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70047133,"text":"70047133 - 2013 - Influence of multi-source and multi-temporal remotely sensed and ancillary data on the accuracy of random forest classification of wetlands in northern Minnesota","interactions":[],"lastModifiedDate":"2013-07-22T11:19:03","indexId":"70047133","displayToPublicDate":"2013-07-22T11:08:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Influence of multi-source and multi-temporal remotely sensed and ancillary data on the accuracy of random forest classification of wetlands in northern Minnesota","docAbstract":"Wetland mapping at the landscape scale using remotely sensed data requires both affordable data and an efficient accurate classification method. Random forest classification offers several advantages over traditional land cover classification techniques, including a bootstrapping technique to generate robust estimations of outliers in the training data, as well as the capability of measuring classification confidence. Though the random forest classifier can generate complex decision trees with a multitude of input data and still not run a high risk of over fitting, there is a great need to reduce computational and operational costs by including only key input data sets without sacrificing a significant level of accuracy. Our main questions for this study site in Northern Minnesota were: (1) how does classification accuracy and confidence of mapping wetlands compare using different remote sensing platforms and sets of input data; (2) what are the key input variables for accurate differentiation of upland, water, and wetlands, including wetland type; and (3) which datasets and seasonal imagery yield the best accuracy for wetland classification. Our results show the key input variables include terrain (elevation and curvature) and soils descriptors (hydric), along with an assortment of remotely sensed data collected in the spring (satellite visible, near infrared, and thermal bands; satellite normalized vegetation index and Tasseled Cap greenness and wetness; and horizontal-horizontal (HH) and horizontal-vertical (HV) polarization using L-band satellite radar). We undertook this exploratory analysis to inform decisions by natural resource managers charged with monitoring wetland ecosystems and to aid in designing a system for consistent operational mapping of wetlands across landscapes similar to those found in Northern Minnesota.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Remote Sensing","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"MDPI AG","doi":"10.3390/rs5073212","usgsCitation":"Corcoran, J.M., Knight, J.F., and Gallant, A.L., 2013, Influence of multi-source and multi-temporal remotely sensed and ancillary data on the accuracy of random forest classification of wetlands in northern Minnesota: Remote Sensing, v. 5, no. 7, p. 3212-3238, https://doi.org/10.3390/rs5073212.","productDescription":"27 p.","startPage":"3212","endPage":"3238","ipdsId":"IP-042123","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":473666,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs5073212","text":"Publisher Index Page"},{"id":275209,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":275208,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.3390/rs5073212"}],"country":"United States","state":"Minnesota","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -97.24,43.5 ], [ -97.24,49.38 ], [ -89.49,49.38 ], [ -89.49,43.5 ], [ -97.24,43.5 ] ] ] } } ] }","volume":"5","issue":"7","noUsgsAuthors":false,"publicationDate":"2013-07-04","publicationStatus":"PW","scienceBaseUri":"51ee4655e4b00ffbed48f851","contributors":{"authors":[{"text":"Corcoran, Jennifer M.","contributorId":66575,"corporation":false,"usgs":true,"family":"Corcoran","given":"Jennifer","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":481152,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Knight, Joseph F.","contributorId":55311,"corporation":false,"usgs":true,"family":"Knight","given":"Joseph","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":481151,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gallant, Alisa L. 0000-0002-3029-6637 gallant@usgs.gov","orcid":"https://orcid.org/0000-0002-3029-6637","contributorId":2940,"corporation":false,"usgs":true,"family":"Gallant","given":"Alisa","email":"gallant@usgs.gov","middleInitial":"L.","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":481150,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70047129,"text":"ofr20131136 - 2013 - Review of revised Klamath River Total Maximum Daily Load models from Link River Dam to Keno Dam, Oregon","interactions":[],"lastModifiedDate":"2013-07-22T09:29:47","indexId":"ofr20131136","displayToPublicDate":"2013-07-22T09:22:00","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":"2013-1136","title":"Review of revised Klamath River Total Maximum Daily Load models from Link River Dam to Keno Dam, Oregon","docAbstract":"Flow and water-quality models are being used to support the development of Total Maximum Daily Load (TMDL) plans for the Klamath River downstream of Upper Klamath Lake (UKL) in south-central Oregon. For riverine reaches, the RMA-2 and RMA-11 models were used, whereas the CE-QUAL-W2 model was used to simulate pooled reaches. The U.S. Geological Survey (USGS) was asked to review the most upstream of these models, from Link River Dam at the outlet of UKL downstream through the first pooled reach of the Klamath River from Lake Ewauna to Keno Dam. Previous versions of these models were reviewed in 2009 by USGS. Since that time, important revisions were made to correct several problems and address other issues. This review documents an assessment of the revised models, with emphasis on the model revisions and any remaining issues.\n\nThe primary focus of this review is the 19.7-mile Lake Ewauna to Keno Dam reach of the Klamath River that was simulated with the CE-QUAL-W2 model. Water spends far more time in the Lake Ewauna to Keno Dam reach than in the 1-mile Link River reach that connects UKL to the Klamath River, and most of the critical reactions affecting water quality upstream of Keno Dam occur in that pooled reach. This model review includes assessments of years 2000 and 2002 current conditions scenarios, which were used to calibrate the model, as well as a natural conditions scenario that was used as the reference condition for the TMDL and was based on the 2000 flow conditions. The natural conditions scenario included the removal of Keno Dam, restoration of the Keno reef (a shallow spot that was removed when the dam was built), removal of all point-source inputs, and derivation of upstream boundary water-quality inputs from a previously developed UKL TMDL model.\n\nThis review examined the details of the models, including model algorithms, parameter values, and boundary conditions; the review did not assess the draft Klamath River TMDL or the TMDL allocations. Attention to the details of a model is one of the best ways to identify potential problems, correct them if possible, and begin to assess the magnitude of potential model errors and uncertainty. Model users need to determine the level of acceptable uncertainty associated with their objectives, identify all sources of potential uncertainty (model uncertainty, data uncertainty, etc.), and assess their approach and results accordingly. In the draft Klamath River TMDL, the Oregon Department of Environmental Quality identified the upstream boundary conditions as the largest source of uncertainty for both the current and natural conditions scenarios, not the model algorithms or choice of model parameters. We agree that the upstream boundary conditions are one of the largest, if not the largest, source of model uncertainty; therefore, the derivation of upstream boundary conditions may be more important to the TMDL than some other model-related issues identified in this review.\n\nThe revised models contain a number of changes, some of which were done to solve small problems and are largely inconsequential to model results, but others of which are important and affect model predictions of instream concentrations. A consistent version of the model is now applied to all scenarios, and an error in the source code was corrected that had inadvertently discarded 20 percent of the incoming solar radiation in the original model. The baseline light-extinction coefficient for water was decreased and set to a consistent and defensible value across all models of reservoir reaches. Inconsistencies among the values of certain parameters in the original models, such as the ammonia nitrification rate and the decomposition rates of organic matter, have been eliminated, although the reasoning behind the final selections was not documented. The dependence of the rate of sediment oxygen demand (SOD) on temperature was modified such that the SOD rate was substantially decreased at temperatures less than 20°C, causing the model to predict higher dissolved oxygen (DO) concentrations in spring, autumn, and winter. Although that change to the temperature dependence function was done to make the function more similar to the model’s default, this change was not accompanied by any documentation of recalibration or sensitivity exercises. The maximum SOD rate for the 2002 current conditions scenario was decreased from 3.0 grams per square meter per day (g/m2/d) in the original model to 2.0 g/m2/d in the revised model, a considerable adjustment that appears to have been needed to offset effects of a change to another variable (O2LIM) that would have resulted in a substantial increase in the effective SOD rate for 2002. A 50-percent decrease in the SOD rate over a 2-year period, however, is not likely to be mirrored by field measurements, so this change may be compensating for some process that is not represented correctly in the DO budget for the current conditions scenarios.\n\nSeveral important changes were made to the natural conditions scenario. First, the elevation of the Keno reef was corrected; the elevation specified in the original model was 1 foot too high, which affected the volume of the pooled reach and the travel time through it. The most important changes to this scenario were to the upstream boundary inputs of organic matter and algae, which affect incoming fluxes of nitrogen and phosphorus. Algal biomass inputs were increased by approximately 60 percent during summer because of a change in the way those inputs were derived from results of the UKL TMDL model. Non-algal organic matter inputs were decreased, particularly in summer to correct a problem attributed to double-counting of phosphorus in the original inputs. The distribution of non-algal organic matter was changed from 20 percent dissolved in the original model to 90 percent dissolved in the revised model in response to review comments and published data. The overall sum of algal biomass and non-living organic matter was decreased, which resulted in lower inputs of total phosphorus and nitrogen. Total phosphorus inputs were less than 0.03 mg/L, and although the inputs were derived from selected results of the UKL TMDL model, these concentrations seem too low to be representative of a historically eutrophic system surrounded by extensive wetlands, peat soils, and a groundwater system high in phosphorus. The draft TMDL states that the upstream boundary conditions are the greatest source of uncertainty, greater than any uncertainty associated with the models. Efforts to improve existing models of algal growth and nutrient cycling in UKL, therefore, would provide a substantial benefit to downstream modeling efforts on the Klamath River.\n\nAlthough many improvements were made in revising the Klamath River TMDL models, some issues and uncertainties remain. Several errors in the model source code remain, but do not affect model results for this application as long as certain options and rates are not changed; future users of these models should be aware of these issues. Although the distribution of dissolved and particulate organic matter was modified for the natural conditions scenario, that distribution was not changed for the current conditions scenarios. Recent data on that distribution and the likely rates of organic matter decomposition could be used to improve these models in the future. Nitrate predictions at Keno (Highway 66) still are too high for the current conditions scenarios; future efforts should re-evaluate the model’s denitrification rates and the release rate of ammonia from anoxic sediments. Possibly the most important of the remaining issues are tied to the two-state (healthy/unhealthy) hypothesis for the algae population that was coded into the model. Some of the rates and conversion functions could be refined to make them more acceptable; currently, the published literature does not support the concept of moderately low dissolved-oxygen concentrations as a stressor of algae in the ranges used by the model. More research is needed before these algorithms can be truly tested. The algorithms currently appear to help the model fit the patterns in the available data, and that is useful and perhaps sufficient for some purposes, but those algorithms are not truly predictive or reliable for certain purposes until they can be tested through well-designed experiments and research.\n\nIn summary, the TMDL models used to simulate Link and Klamath Rivers from Link River Dam to Keno Dam were revised to fix several problems and address various issues. The resulting models are an improvement over those that were reviewed by USGS in 2009, and represent a useful advance in the simulation of a complex system that is difficult to model. However, several issues remain that cause increased uncertainty in the model results. Depending on the objectives of the modeling, now or in the future, these remaining issues could be more or less important. For the Klamath River TMDL, the upstream boundary conditions may be a larger source of uncertainty than the concerns with model algorithms and model parameters identified in this review. Efforts to re-evaluate the available models of algal growth and nutrient cycling in UKL would be highly beneficial to downstream modeling efforts in the Klamath River.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131136","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Rounds, S.A., and Sullivan, A.B., 2013, Review of revised Klamath River Total Maximum Daily Load models from Link River Dam to Keno Dam, Oregon: U.S. Geological Survey Open-File Report 2013-1136, vi, 31 p., https://doi.org/10.3133/ofr20131136.","productDescription":"vi, 31 p.","numberOfPages":"37","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":275196,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131136.PNG"},{"id":275195,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1136/pdf/ofr20131136.pdf"},{"id":275194,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1136/"}],"country":"United States","state":"Oregon;California","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.5,40.5 ], [ -124.5,43.0 ], [ -120.75,43.0 ], [ -120.75,40.5 ], [ -124.5,40.5 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51ee465be4b00ffbed48f879","contributors":{"authors":[{"text":"Rounds, Stewart A. 0000-0002-8540-2206 sarounds@usgs.gov","orcid":"https://orcid.org/0000-0002-8540-2206","contributorId":905,"corporation":false,"usgs":true,"family":"Rounds","given":"Stewart","email":"sarounds@usgs.gov","middleInitial":"A.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":481136,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sullivan, Annett B. 0000-0001-7783-3906 annett@usgs.gov","orcid":"https://orcid.org/0000-0001-7783-3906","contributorId":56317,"corporation":false,"usgs":true,"family":"Sullivan","given":"Annett","email":"annett@usgs.gov","middleInitial":"B.","affiliations":[],"preferred":false,"id":481137,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70047092,"text":"70047092 - 2013 - Uranium(VI) interactions with mackinawite in the presence and absence of bicarbonate and oxygen","interactions":[],"lastModifiedDate":"2013-07-22T09:10:19","indexId":"70047092","displayToPublicDate":"2013-07-22T09:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Uranium(VI) interactions with mackinawite in the presence and absence of bicarbonate and oxygen","docAbstract":"Mackinawite, Fe(II)S, samples loaded with uranium (10-5, 10-4, and 10-3 mol U/g FeS) at pH 5, 7, and 9, were characterized using X-ray absorption spectroscopy and X-ray diffraction to determine the effects of pH, bicarbonate, and oxidation on uptake. Under anoxic conditions, a 5 g/L suspension of mackinawite lowered 5 × 10-5 M uranium(VI) to below 30 ppb (1.26 × 10-7 M) U. Between 82 and 88% of the uranium removed from solution by mackinawite was U(IV) and was nearly completely reduced to U(IV) when 0.012 M bicarbonate was added. Near-neighbor coordination consisting of uranium–oxygen and uranium-uranium distances indicates the formation of uraninite in the presence and absence of bicarbonate, suggesting reductive precipitation as the dominant removal mechanism. Following equilibration in air, mackinawite was oxidized to mainly goethite and sulfur and about 76% of U(IV) was reoxidized to U(VI) with coordination of uranium to axial and equatorial oxygen, similar to uranyl. Additionally, uranium-iron distances, typical of coprecipitation of uranium with iron oxides, and uranium-sulfur distances indicating bidentate coordination of U(VI) to sulfate were evident. The affinity of mackinawite and its oxidation products for U(VI) provides impetus for further study of mackinawite as a potential reactive medium for remediation of uranium-contaminated water.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Environmental Science and Technology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Environmental Science and Technology","doi":"10.1021/es400450z","usgsCitation":"Gallegos, T.J., Fuller, C.C., Webb, S.M., and Betterton, W.J., 2013, Uranium(VI) interactions with mackinawite in the presence and absence of bicarbonate and oxygen: Environmental Science & Technology, v. 47, no. 13, p. 7357-7364, https://doi.org/10.1021/es400450z.","productDescription":"8 p.","startPage":"7357","endPage":"7364","numberOfPages":"8","ipdsId":"IP-043688","costCenters":[],"links":[{"id":275193,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":275124,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1021/es400450z"}],"volume":"47","issue":"13","noUsgsAuthors":false,"publicationDate":"2013-06-21","publicationStatus":"PW","scienceBaseUri":"51ee465ce4b00ffbed48f881","contributors":{"authors":[{"text":"Gallegos, Tanya J. 0000-0003-3350-6473 tgallegos@usgs.gov","orcid":"https://orcid.org/0000-0003-3350-6473","contributorId":2206,"corporation":false,"usgs":true,"family":"Gallegos","given":"Tanya","email":"tgallegos@usgs.gov","middleInitial":"J.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":481035,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fuller, Christopher C. 0000-0002-2354-8074 ccfuller@usgs.gov","orcid":"https://orcid.org/0000-0002-2354-8074","contributorId":1831,"corporation":false,"usgs":true,"family":"Fuller","given":"Christopher","email":"ccfuller@usgs.gov","middleInitial":"C.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":481034,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Webb, Samuel M.","contributorId":62088,"corporation":false,"usgs":true,"family":"Webb","given":"Samuel","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":481037,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Betterton, William J. wbettert@usgs.gov","contributorId":2572,"corporation":false,"usgs":true,"family":"Betterton","given":"William","email":"wbettert@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":true,"id":481036,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70047128,"text":"70047128 - 2013 - Land loss due to recent hurricanes in coastal Louisiana, U.S.A.","interactions":[],"lastModifiedDate":"2013-07-22T08:55:49","indexId":"70047128","displayToPublicDate":"2013-07-22T08:43:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2220,"text":"Journal of Coastal Research","active":true,"publicationSubtype":{"id":10}},"title":"Land loss due to recent hurricanes in coastal Louisiana, U.S.A.","docAbstract":"The aim of this study is to improve estimates of wetland land loss in two study regions of coastal Louisiana, U.S.A., due to the extreme storms that impacted the region between 2004 and 2009. The estimates are based on change-detection-mapping analysis that incorporates pre and postlandfall (Hurricanes Katrina, Rita, Gustav, and Ike) fractional-water classifications using a combination of high-resolution (<5 m) QuickBird, IKONOS, and GeoEye-1, and medium-resolution (30 m) Landsat Thematic Mapper satellite imagery. This process was applied in two study areas: the Hackberry area located in the southwestern part of chenier plain that was impacted by Hurricanes Rita (September 24, 2005) and Ike (September 13, 2008), and the Delacroix area located in the eastern delta plain that was impacted by Hurricanes Katrina (August 29, 2005) and Gustav (September 1, 2008). In both areas, effects of the hurricanes include enlargement of existing bodies of open water and erosion of fringing marsh areas. Surge-removed marsh was easily identified in stable marshes but was difficult to identify in degraded or flooded marshes. Persistent land loss in the Hackberry area due to Hurricane Rita was approximately 5.8% and increased by an additional 7.9% due to Hurricane Ike, although this additional area may yet recover. About 80% of the Hackberry study area remained unchanged since 2003. In the Delacroix area, persistent land loss due to Hurricane Katrina measured approximately 4.9% of the study area, while Hurricane Gustav caused minimal impact of 0.6% land loss by November 2009. Continued recovery in this area may further erase Hurricane Gustav's impact in the absence of new storm events.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Coastal Research","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Coastal Education and Research Foundation","doi":"10.2112/SI63-009.1","usgsCitation":"Palaseanu-Lovejoy, M., Kranenburg, C., Barras, J., and Brock, J., 2013, Land loss due to recent hurricanes in coastal Louisiana, U.S.A.: Journal of Coastal Research, no. 63, p. 97-109, https://doi.org/10.2112/SI63-009.1.","productDescription":"14 p.","startPage":"97","endPage":"109","numberOfPages":"14","ipdsId":"IP-035278","costCenters":[],"links":[{"id":275192,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":275191,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.2112/SI63-009.1"}],"country":"United States","state":"Louisiana","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -90.491638,29.75484 ], [ -90.491638,30.071471 ], [ -90.129089,30.071471 ], [ -90.129089,29.75484 ], [ -90.491638,29.75484 ] ] ] } } ] }","issue":"63","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51ee4656e4b00ffbed48f855","contributors":{"authors":[{"text":"Palaseanu-Lovejoy, Monica 0000-0002-3786-5118 mpal@usgs.gov","orcid":"https://orcid.org/0000-0002-3786-5118","contributorId":3639,"corporation":false,"usgs":true,"family":"Palaseanu-Lovejoy","given":"Monica","email":"mpal@usgs.gov","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":5061,"text":"National Cooperative Geologic Mapping and Landslide Hazards","active":true,"usgs":true}],"preferred":true,"id":481134,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kranenburg, Christine J. ckranenburg@usgs.gov","contributorId":3924,"corporation":false,"usgs":true,"family":"Kranenburg","given":"Christine J.","email":"ckranenburg@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":481135,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Barras, John A. jbarras@usgs.gov","contributorId":2425,"corporation":false,"usgs":true,"family":"Barras","given":"John A.","email":"jbarras@usgs.gov","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":false,"id":481133,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brock, John 0000-0002-5289-9332 jbrock@usgs.gov","orcid":"https://orcid.org/0000-0002-5289-9332","contributorId":2261,"corporation":false,"usgs":true,"family":"Brock","given":"John","email":"jbrock@usgs.gov","affiliations":[{"id":5061,"text":"National Cooperative Geologic Mapping and Landslide Hazards","active":true,"usgs":true}],"preferred":true,"id":481132,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70047122,"text":"ofr20131106 - 2013 - Streamflow characterization and summary of water-quality data collection during the Mississippi River flood, April through July 2011","interactions":[],"lastModifiedDate":"2013-07-19T10:16:02","indexId":"ofr20131106","displayToPublicDate":"2013-07-19T09:55:00","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":"2013-1106","title":"Streamflow characterization and summary of water-quality data collection during the Mississippi River flood, April through July 2011","docAbstract":"From April through July 2011, the U.S. Geological Survey collected surface-water samples from 69 water-quality stations and 3 flood-control structures in 4 major subbasins of the Mississippi River Basin to characterize the water quality during the 2011 Mississippi River flood. Most stations were sampled at least monthly for field parameters suspended sediment, nutrients, and selected pesticides. Samples were collected at daily to biweekly frequencies at selected sites in the case of suspended sediment. Hydro-carbon analysis was performed on samples collected at two sites in the Atchafalaya River Basin to assess the water-quality implications of opening the Morganza Floodway. Water-quality samples obtained during the flood period were collected at flows well above normal streamflow conditions at the majority of the stations throughout the Mississippi River Basin and its subbasins.\n\nHeavy rainfall and snowmelt resulted in high streamflow in the Mississippi River Basin from April through July 2011. The Ohio River Subbasin contributed to most of the flow in the lower Mississippi-Atchafalaya River Subbasin during the months of April and May because of widespread rainfall, whereas snowmelt and precipitation from the Missouri River Subbasin and the upper Mississippi River Subbasin contributed to most of the flow in the lower Mississippi-Atchafalaya River Subbasin during June and July. Peak streamflows from the 2011 flood were higher than peak streamflow during previous historic floods at most the selected streamgages in the Mississippi River Basin. In the Missouri River Subbasin, the volume of water moved during the 1952 flood was greater than the amount move during the 2011 flood.\n\nMedian concentrations of suspended sediment and total phosphorus were higher in the Missouri River Subbasin during the flood when compared to the other three subbasins. Surface water in the upper Mississippi River Subbasin contained higher median concentrations of total nitrogen, nitrate, orthophosphate, and atrazine during the flood period.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131106","collaboration":"National Stream Quality Accounting Network; National Water-Quality Assessment Program","usgsCitation":"Welch, H.L., and Barnes, K., 2013, Streamflow characterization and summary of water-quality data collection during the Mississippi River flood, April through July 2011: U.S. Geological Survey Open-File Report 2013-1106, v, 27 p.; 8 Appendixes, https://doi.org/10.3133/ofr20131106.","productDescription":"v, 27 p.; 8 Appendixes","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2011-03-01","temporalEnd":"2011-07-31","costCenters":[{"id":394,"text":"Mississippi Water Science Center","active":true,"usgs":true}],"links":[{"id":275179,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131106.gif"},{"id":275171,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2013/1106/appendix/Appendix01.xlsx"},{"id":275169,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1106/"},{"id":275170,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1106/pdf/ofr2013-1106.pdf"},{"id":275172,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2013/1106/appendix/Appendix02.xlsx"},{"id":275173,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2013/1106/appendix/Appendix03.xlsx"},{"id":275174,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2013/1106/appendix/Appendix04.xlsx"},{"id":275175,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2013/1106/appendix/Appendix05.xlsx"},{"id":275176,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2013/1106/appendix/Appendix06.xlsx"},{"id":275177,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2013/1106/appendix/Appendix07.xlsx"},{"id":275178,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2013/1106/appendix/Appendix08.xlsx"}],"country":"United States;Canada","otherGeospatial":"Mississippi River Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -130.0,20.0 ], [ -130.0,55.0 ], [ -65.0,55.0 ], [ -65.0,20.0 ], [ -130.0,20.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51ea86c5e4b03397884d3984","contributors":{"authors":[{"text":"Welch, Heather L. 0000-0001-8370-7711 hllott@usgs.gov","orcid":"https://orcid.org/0000-0001-8370-7711","contributorId":552,"corporation":false,"usgs":true,"family":"Welch","given":"Heather","email":"hllott@usgs.gov","middleInitial":"L.","affiliations":[{"id":105,"text":"Alabama Water Science Center","active":true,"usgs":true}],"preferred":true,"id":481128,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barnes, Kimberlee K.","contributorId":41476,"corporation":false,"usgs":true,"family":"Barnes","given":"Kimberlee K.","affiliations":[],"preferred":false,"id":481129,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70047113,"text":"ofr20131124 - 2013 - Topographic and hydrographic GIS datasets for the Afghan Geological Survey and U.S. Geological Survey 2013 mineral areas of interest","interactions":[],"lastModifiedDate":"2013-07-18T15:35:59","indexId":"ofr20131124","displayToPublicDate":"2013-07-18T15:27:00","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":"2013-1124","title":"Topographic and hydrographic GIS datasets for the Afghan Geological Survey and U.S. Geological Survey 2013 mineral areas of interest","docAbstract":"Afghanistan is endowed with a vast amount of mineral resources, and it is believed that the current economic state of the country could be greatly improved through investment in the extraction and production of these resources. In 2007, the “Preliminary Non-Fuel Resource Assessment of Afghanistan 2007” was completed by members of the U.S. Geological Survey and Afghan Geological Survey (Peters and others, 2007). The assessment delineated 20 mineralized areas for further study using a geologic-based methodology. In 2011, a follow-on data product, “Summaries and Data Packages of Important Areas for Mineral Investment and Production Opportunities of Nonfuel Minerals in Afghanistan,” was released (Peters and others, 2011). As part of this more recent work, geologic, geohydrologic, and hyperspectral studies were carried out in the areas of interest (AOIs) to assess the location and characteristics of the mineral resources. The 2011 publication included a dataset of 24 identified AOIs containing subareas, a corresponding digital elevation model (DEM), elevation contours, areal extent, and hydrography for each AOI. In 2012, project scientists identified five new AOIs and two subareas in Afghanistan. These new areas are Ahankashan, Kandahar, Parwan, North Bamyan, and South Bamyan. The two identified subareas include Obatu-Shela and Sekhab-ZamtoKalay, both located within the larger Kandahar AOI. In addition, an extended Kandahar AOI is included in the project for water resource modeling purposes. The dataset presented in this publication consists of the areal extent of the five new AOIs, two subareas, and the extended Kandahar AOI, elevation contours at 100-, 50-, and 25-meter intervals, an enhanced DEM, and a hydrographic dataset covering the extent of the new study area. The resulting raster and vector layers are intended for use by government agencies, developmental organizations, and private companies in Afghanistan to assist with mineral assessments, monitoring, management, and investment.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131124","collaboration":"Prepared in cooperation with the Afghan Geological Survey under the auspices of the U.S. Department of Defense Task Force for Business and Stability Operations","usgsCitation":"Casey, B.N., and Chirico, P., 2013, Topographic and hydrographic GIS datasets for the Afghan Geological Survey and U.S. Geological Survey 2013 mineral areas of interest: U.S. Geological Survey Open-File Report 2013-1124, Report: vi, 18 p.; Downloads Directory, https://doi.org/10.3133/ofr20131124.","productDescription":"Report: vi, 18 p.; Downloads Directory","numberOfPages":"26","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":275158,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2013/1124/Downloads"},{"id":275159,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131124.gif"},{"id":275156,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1124/"},{"id":275157,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1124/pdf/ofr2013-1124.pdf"}],"country":"Afghanistan","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 60.52,29.38 ], [ 60.52,38.49 ], [ 74.89,38.49 ], [ 74.89,29.38 ], [ 60.52,29.38 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51e90055e4b0e157e9e86eea","contributors":{"authors":[{"text":"Casey, Brittany N.","contributorId":69037,"corporation":false,"usgs":true,"family":"Casey","given":"Brittany","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":481085,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chirico, Peter G.","contributorId":27086,"corporation":false,"usgs":true,"family":"Chirico","given":"Peter G.","affiliations":[],"preferred":false,"id":481084,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70047100,"text":"70047100 - 2013 - Nonstructural leaf carbohydrates dynamics of Pinus edulis during drought-induced tree mortality reveal role for carbon metabolism in mortality mechanism","interactions":[],"lastModifiedDate":"2013-07-18T10:52:55","indexId":"70047100","displayToPublicDate":"2013-07-18T10:43:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2863,"text":"New Phytologist","active":true,"publicationSubtype":{"id":10}},"title":"Nonstructural leaf carbohydrates dynamics of Pinus edulis during drought-induced tree mortality reveal role for carbon metabolism in mortality mechanism","docAbstract":"* Vegetation change is expected with global climate change, potentially altering ecosystem function and climate feedbacks. However, causes of plant mortality, which are central to vegetation change, are understudied, and physiological mechanisms remain unclear, particularly the roles of carbon metabolism and xylem function.\n* We report analysis of foliar nonstructural carbohydrates (NSCs) and associated physiology from a previous experiment where earlier drought-induced mortality of Pinus edulis at elevated temperatures was associated with greater cumulative respiration. Here, we predicted faster NSC decline for warmed trees than for ambient-temperature trees.\n* Foliar NSC in droughted trees declined by 30% through mortality and was lower than in watered controls. NSC decline resulted primarily from decreased sugar concentrations. Starch initially declined, and then increased above pre-drought concentrations before mortality. Although temperature did not affect NSC and sugar, starch concentrations ceased declining and increased earlier with higher temperatures.\n* Reduced foliar NSC during lethal drought indicates a carbon metabolism role in mortality mechanism. Although carbohydrates were not completely exhausted at mortality, temperature differences in starch accumulation timing suggest that carbon metabolism changes are associated with time to death. Drought mortality appears to be related to temperature-dependent carbon dynamics concurrent with increasing hydraulic stress in P. edulis and potentially other similar species.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"New Phytologist","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"New Phytologist Trust","doi":"10.1111/nph.12102","usgsCitation":"Adams, H., Germino, M., Breshears, D.D., Barron-Gafford, G.A., Guardiola-Claramonte, M., Zou, C., and Huxman, T.E., 2013, Nonstructural leaf carbohydrates dynamics of Pinus edulis during drought-induced tree mortality reveal role for carbon metabolism in mortality mechanism: New Phytologist, v. 197, no. 4, p. 1142-1151, https://doi.org/10.1111/nph.12102.","productDescription":"10 p.","startPage":"1142","endPage":"1151","ipdsId":"IP-041844","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":473669,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/nph.12102","text":"Publisher Index Page"},{"id":275141,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":275140,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/nph.12102"}],"volume":"197","issue":"4","noUsgsAuthors":false,"publicationDate":"2013-01-11","publicationStatus":"PW","scienceBaseUri":"51e90055e4b0e157e9e86ee6","contributors":{"authors":[{"text":"Adams, Henry D.","contributorId":105619,"corporation":false,"usgs":true,"family":"Adams","given":"Henry D.","affiliations":[],"preferred":false,"id":481056,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Germino, Matthew J.","contributorId":50029,"corporation":false,"usgs":true,"family":"Germino","given":"Matthew J.","affiliations":[],"preferred":false,"id":481052,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Breshears, David D.","contributorId":51620,"corporation":false,"usgs":false,"family":"Breshears","given":"David","email":"","middleInitial":"D.","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":481053,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barron-Gafford, Greg A.","contributorId":19058,"corporation":false,"usgs":false,"family":"Barron-Gafford","given":"Greg","email":"","middleInitial":"A.","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":481050,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Guardiola-Claramonte, Maite","contributorId":54092,"corporation":false,"usgs":true,"family":"Guardiola-Claramonte","given":"Maite","email":"","affiliations":[],"preferred":false,"id":481055,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Zou, Chris B.","contributorId":31657,"corporation":false,"usgs":true,"family":"Zou","given":"Chris B.","affiliations":[],"preferred":false,"id":481051,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Huxman, Travis E.","contributorId":53898,"corporation":false,"usgs":false,"family":"Huxman","given":"Travis","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":481054,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70047099,"text":"70047099 - 2013 - Hydrologic connectivity to streams increases nitrogen and phosphorus inputs and cycling in soils of created and natural floodplain wetlands","interactions":[],"lastModifiedDate":"2013-07-18T09:56:56","indexId":"70047099","displayToPublicDate":"2013-07-18T09:52:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2262,"text":"Journal of Environmental Quality","active":true,"publicationSubtype":{"id":10}},"title":"Hydrologic connectivity to streams increases nitrogen and phosphorus inputs and cycling in soils of created and natural floodplain wetlands","docAbstract":"Greater connectivity to stream surface water may result in greater inputs of allochthonous nutrients that could stimulate internal nitrogen (N) and phosphorus (P) cycling in natural, restored, and created riparian wetlands. This study investigated the effects of hydrologic connectivity to stream water on soil nutrient fluxes in plots (n = 20) located among four created and two natural freshwater wetlands of varying hydrology in the Piedmont physiographic province of Virginia. Surface water was slightly deeper; hydrologic inputs of sediment, sediment-N, and ammonium were greater; and soil net ammonification, N mineralization, and N turnover were greater in plots with stream water classified as their primary water source compared with plots with precipitation or groundwater as their primary water source. Soil water-filled pore space, inputs of nitrate, and soil net nitrification, P mineralization, and denitrification enzyme activity (DEA) were similar among plots. Soil ammonification, N mineralization, and N turnover rates increased with the loading rate of ammonium to the soil surface. Phosphorus mineralization and ammonification also increased with sedimentation and sediment-N loading rate. Nitrification flux and DEA were positively associated in these wetlands. In conclusion, hydrologic connectivity to stream water increased allochthonous inputs that stimulated soil N and P cycling and that likely led to greater retention of sediment and nutrients in created and natural wetlands. Our findings suggest that wetland creation and restoration projects should be designed to allow connectivity with stream water if the goal is to optimize the function of water quality improvement in a watershed.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Environmental Quality","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Crop Science Society of America","doi":"10.2134/jeq2012.0466","usgsCitation":"Wolf, K.L., Noe, G., and Ahn, C., 2013, Hydrologic connectivity to streams increases nitrogen and phosphorus inputs and cycling in soils of created and natural floodplain wetlands: Journal of Environmental Quality, v. 42, no. 4, p. 1245-1255, https://doi.org/10.2134/jeq2012.0466.","productDescription":"11 p.","startPage":"1245","endPage":"1255","costCenters":[{"id":434,"text":"National Research Program","active":false,"usgs":true}],"links":[{"id":275139,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":275138,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.2134/jeq2012.0466"}],"volume":"42","issue":"4","noUsgsAuthors":false,"publicationDate":"2013-07-01","publicationStatus":"PW","scienceBaseUri":"51e90054e4b0e157e9e86ee2","contributors":{"authors":[{"text":"Wolf, Kristin L.","contributorId":92151,"corporation":false,"usgs":true,"family":"Wolf","given":"Kristin","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":481049,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Noe, Gregory B.","contributorId":77805,"corporation":false,"usgs":true,"family":"Noe","given":"Gregory B.","affiliations":[],"preferred":false,"id":481048,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ahn, Changwoo","contributorId":38047,"corporation":false,"usgs":true,"family":"Ahn","given":"Changwoo","affiliations":[],"preferred":false,"id":481047,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70047098,"text":"sir20135103 - 2013 - Application of the SPARROW model to assess surface-water nutrient conditions and sources in the United States Pacific Northwest","interactions":[],"lastModifiedDate":"2013-07-18T09:40:14","indexId":"sir20135103","displayToPublicDate":"2013-07-18T09:27:00","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":"2013-5103","title":"Application of the SPARROW model to assess surface-water nutrient conditions and sources in the United States Pacific Northwest","docAbstract":"The watershed model SPARROW (Spatially Referenced Regressions on Watershed attributes) was used to estimate mean annual surface-water nutrient conditions (total nitrogen and total phosphorus) and to identify important nutrient sources in catchments of the Pacific Northwest region of the United States for 2002. Model-estimated nutrient yields were generally higher in catchments on the wetter, western side of the Cascade Range than in catchments on the drier, eastern side. The largest source of locally generated total nitrogen stream load in most catchments was runoff from forestland, whereas the largest source of locally generated total phosphorus stream load in most catchments was either geologic material or livestock manure (primarily from grazing livestock). However, the highest total nitrogen and total phosphorus yields were predicted in the relatively small number of catchments where urban sources were the largest contributor to local stream load. Two examples are presented that show how SPARROW results can be applied to large rivers—the relative contribution of different nutrient sources to the total nitrogen load in the Willamette River and the total phosphorus load in the Snake River. The results from this study provided an understanding of the regional patterns in surface-water nutrient conditions and should be useful to researchers and water-quality managers performing local nutrient assessments.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135103","usgsCitation":"Wise, D.R., and Johnson, H.M., 2013, Application of the SPARROW model to assess surface-water nutrient conditions and sources in the United States Pacific Northwest: U.S. Geological Survey Scientific Investigations Report 2013-5103, vi, 32 p.; 2 Appendixes; ASCII Data File, https://doi.org/10.3133/sir20135103.","productDescription":"vi, 32 p.; 2 Appendixes; ASCII Data File","numberOfPages":"42","additionalOnlineFiles":"Y","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":275137,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135103.jpg"},{"id":275133,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5103/pdf/sir20135103.pdf"},{"id":275134,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2013/5103/pdf/sir20135103_appendix_a.pdf"},{"id":275135,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2013/5103/pdf/sir20135103_appendix_b.pdf"},{"id":275136,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2013/5103/sir20135103_PNW_SPARROW_NHD_predict_data.txt"},{"id":275132,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5103/"}],"country":"United States","otherGeospatial":"Pacific Northwest","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -126.0,41.0 ], [ -126.0,50.0 ], [ -109.0,50.0 ], [ -109.0,41.0 ], [ -126.0,41.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51e9004ee4b0e157e9e86ed6","contributors":{"authors":[{"text":"Wise, Daniel R. 0000-0002-1215-9612 dawise@usgs.gov","orcid":"https://orcid.org/0000-0002-1215-9612","contributorId":29891,"corporation":false,"usgs":true,"family":"Wise","given":"Daniel","email":"dawise@usgs.gov","middleInitial":"R.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":false,"id":481045,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Henry M. 0000-0002-7571-4994","orcid":"https://orcid.org/0000-0002-7571-4994","contributorId":105291,"corporation":false,"usgs":true,"family":"Johnson","given":"Henry","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":481046,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70182711,"text":"70182711 - 2013 - Nutrient enrichment and fish nutrient tolerance: Assessing biologically relevant nutrient criteria","interactions":[],"lastModifiedDate":"2017-02-27T11:52:27","indexId":"70182711","displayToPublicDate":"2013-07-18T00:00:00","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":"Nutrient enrichment and fish nutrient tolerance: Assessing biologically relevant nutrient criteria","docAbstract":"Relationships between nutrient concentrations and fish nutrient tolerance were assessed relative to established nutrient criteria. Fish community, nitrate plus nitrite (nitrate), and total phosphorus (TP) data were collected during summer low-flow periods in 2003 and 2004 at stream sites along a nutrient-enrichment gradient in an agricultural basin in Indiana and Ohio and an urban basin in the Atlanta, Georgia, area. Tolerance indicator values for nitrate and TP were assigned for each species and averaged separately for fish communities at each site (TIVo). Models were used to predict fish species expected to occur at a site under minimally disturbed conditions and average tolerance indicator values were determined for nitrate and TP separately for expected communities (TIVe). In both areas, tolerance scores (TIVo/TIVe) for nitrate increased significantly with increased nitrate concentrations whereas no significant relationships were detected between TP tolerance scores and TP concentrations. A 0% increase in the tolerance score (TIVo/TIVe = 1) for nitrate corresponded to a nitrate concentration of 0.19 mg/l (compared with a USEPA summer nitrate criterion of 0.17 mg/l) in the urban area and 0.31 mg/l (compared with a USEPA summer nitrate criterion of 0.86 mg/l) in the agricultural area. Fish nutrient tolerance values offer the ability to evaluate nutrient enrichment based on a quantitative approach that can provide insights into biologically relevant nutrient criteria.
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2013 - The airspace is habitat","interactions":[],"lastModifiedDate":"2016-08-11T16:24:53","indexId":"70175452","displayToPublicDate":"2013-07-17T17:30:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3653,"text":"Trends in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"The airspace is habitat","docAbstract":"A preconception concerning habitat persists and has gone unrecognized since use of the term first entered the lexicon of ecological and evolutionary biology many decades ago. Specifically, land and water are considered habitats, while the airspace is not. This might at first seem a reasonable, if unintended, demarcation, since years of education and personal experience as well as limits to perception predispose a traditional view of habitat. Nevertheless, the airspace satisfies the definition and functional role of a habitat, and its recognition as habitat may have implications for policy where expanding anthropogenic development of airspace could impact the conservation of species and subject parts of the airspace to formalized legal protection.
","language":"English","publisher":"Elsevier Science Publishers","publisherLocation":"Amsterdam","doi":"10.1016/j.tree.2013.02.015","usgsCitation":"Diehl, R.H., 2013, The airspace is habitat: Trends in Ecology and Evolution, v. 28, no. 7, p. 377-379, https://doi.org/10.1016/j.tree.2013.02.015.","startPage":"377","endPage":"379","numberOfPages":"3","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-038601","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":326423,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"28","issue":"7","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57ada21ae4b0f412a62dfb12","contributors":{"authors":[{"text":"Diehl, Robert H. 0000-0001-9141-1734 rhdiehl@usgs.gov","orcid":"https://orcid.org/0000-0001-9141-1734","contributorId":3396,"corporation":false,"usgs":true,"family":"Diehl","given":"Robert","email":"rhdiehl@usgs.gov","middleInitial":"H.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":645293,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70046561,"text":"70046561 - 2013 - Revision of Fontes & Garnier's model for the initial 14C content of dissolved inorganic carbon used in groundwater dating","interactions":[],"lastModifiedDate":"2018-03-21T15:11:41","indexId":"70046561","displayToPublicDate":"2013-07-17T16:04:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1213,"text":"Chemical Geology","active":true,"publicationSubtype":{"id":10}},"title":"Revision of Fontes & Garnier's model for the initial 14C content of dissolved inorganic carbon used in groundwater dating","docAbstract":"The widely applied model for groundwater dating using 14C proposed by Fontes and Garnier (F&G) (Fontes and Garnier, 1979) estimates the initial 14C content in waters from carbonate-rock aquifers affected by isotopic exchange. Usually, the model of F&G is applied in one of two ways: (1) using a single 13C fractionation factor of gaseous CO2 with respect to a solid carbonate mineral, εg/s, regardless of whether the carbon isotopic exchange is controlled by soil CO2 in the unsaturated zone, or by solid carbonate mineral in the saturated zone; or (2) using different fractionation factors if the exchange process is dominated by soil CO2 gas as opposed to solid carbonate mineral (typically calcite). An analysis of the F&G model shows an inadequate conceptualization, resulting in underestimation of the initial 14C values (14C0) for groundwater systems that have undergone isotopic exchange. The degree to which the 14C0 is underestimated increases with the extent of isotopic exchange. Examples show that in extreme cases, the error in calculated adjusted initial 14C values can be more than 20% modern carbon (pmc). A model is derived that revises the mass balance method of F&G by using a modified model conceptualization. The derivation yields a “global” model both for carbon isotopic exchange dominated by gaseous CO2 in the unsaturated zone, and for carbon isotopic exchange dominated by solid carbonate mineral in the saturated zone. However, the revised model requires different parameters for exchange dominated by gaseous CO2 as opposed to exchange dominated by solid carbonate minerals. The revised model for exchange dominated by gaseous CO2 is shown to be identical to the model of Mook (Mook, 1976). For groundwater systems where exchange occurs both in the unsaturated zone and saturated zone, the revised model can still be used; however, 14C0 will be slightly underestimated. Finally, in carbonate systems undergoing complex geochemical reactions, such as oxidation of organic carbon, radiocarbon ages are best estimated by inverse geochemical modeling techniques.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Chemical Geology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.chemgeo.2013.05.011","usgsCitation":"Han, L., and Plummer, N., 2013, Revision of Fontes & Garnier's model for the initial 14C content of dissolved inorganic carbon used in groundwater dating: Chemical Geology, v. 351, p. 105-114, https://doi.org/10.1016/j.chemgeo.2013.05.011.","productDescription":"10 p.","startPage":"105","endPage":"114","ipdsId":"IP-045165","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":473674,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.chemgeo.2013.05.011","text":"Publisher Index Page"},{"id":275107,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":273714,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.chemgeo.2013.05.011"}],"country":"United States","volume":"351","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51e7aed7e4b080b82b09c616","contributors":{"authors":[{"text":"Han, Liang-Feng","contributorId":101537,"corporation":false,"usgs":true,"family":"Han","given":"Liang-Feng","affiliations":[],"preferred":false,"id":479806,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Plummer, Niel 0000-0002-4020-1013 nplummer@usgs.gov","orcid":"https://orcid.org/0000-0002-4020-1013","contributorId":190100,"corporation":false,"usgs":true,"family":"Plummer","given":"Niel","email":"nplummer@usgs.gov","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":479805,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70047088,"text":"70047088 - 2013 - U.S. Geological Survey water-resource monitoring activities in support of the Wyoming Landscape Conservation Initiative","interactions":[],"lastModifiedDate":"2013-07-17T13:01:18","indexId":"70047088","displayToPublicDate":"2013-07-17T12:53:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":3,"text":"Organization Series"},"seriesTitle":{"id":234,"text":"WLCI Fact Sheet","active":false,"publicationSubtype":{"id":3}},"seriesNumber":"4","title":"U.S. Geological Survey water-resource monitoring activities in support of the Wyoming Landscape Conservation Initiative","docAbstract":"The quality of the Nation’s water resources are vital to the health and well-being of both our communities and the natural landscapes we value. The U.S. Geological Survey investigates the occurrence, quantity, quality, distribution, and movement of surface water and groundwater and provides this information to engineers, scientists, managers, educators, and the general public. This information also supplements current (2013) and historical water data provided by the National Water Information System. The U.S. Geological Survey collects and shares data nationwide, but how those data are used is often site specific; this variety of data assists natural-resource managers in addressing unique, local, and regional challenges.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","usgsCitation":"Soileau, S., and Miller, K., 2013, U.S. Geological Survey water-resource monitoring activities in support of the Wyoming Landscape Conservation Initiative: WLCI Fact Sheet 4, 2 p.","productDescription":"2 p.","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":275119,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/70047088.gif"},{"id":275117,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/wlci/fs/4/"},{"id":275118,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/wlci/fs/4/WLCI_fs_4.pdf"}],"country":"United States","state":"Wyoming","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -111.0569,40.9947 ], [ -111.0569,45.0059 ], [ -104.0522,45.0059 ], [ -104.0522,40.9947 ], [ -111.0569,40.9947 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51e7aed8e4b080b82b09c61e","contributors":{"authors":[{"text":"Soileau, Suzanna 0000-0002-4331-0098","orcid":"https://orcid.org/0000-0002-4331-0098","contributorId":57349,"corporation":false,"usgs":true,"family":"Soileau","given":"Suzanna","affiliations":[],"preferred":false,"id":481032,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Miller, Kirk","contributorId":81891,"corporation":false,"usgs":true,"family":"Miller","given":"Kirk","affiliations":[],"preferred":false,"id":481033,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70046875,"text":"70046875 - 2013 - Impact of Late Holocene climate variability and anthropogenic activities on Biscayne Bay (Florida, U.S.A.): Evidence from diatoms","interactions":[],"lastModifiedDate":"2020-03-27T06:31:01","indexId":"70046875","displayToPublicDate":"2013-07-17T11:23:00","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":"Impact of Late Holocene climate variability and anthropogenic activities on Biscayne Bay (Florida, U.S.A.): Evidence from diatoms","docAbstract":"Shallow marine ecosystems are experiencing significant environmental alterations as a result of changing climate and increasing human activities along coasts. Intensive urbanization of the southeast Florida coast and intensification of climate change over the last few centuries changed the character of coastal ecosystems in the semi-enclosed Biscayne Bay, Florida. In order to develop management policies for the Bay, it is vital to obtain reliable scientific evidence of past ecological conditions. The long-term records of subfossil diatoms obtained from No Name Bank and Featherbed Bank in the Central Biscayne Bay, and from the Card Sound Bank in the neighboring Card Sound, were used to study the magnitude of the environmental change caused by climate variability and water management over the last ~ 600 yr. Analyses of these records revealed that the major shifts in the diatom assemblage structures at No Name Bank occurred in 1956, at Featherbed Bank in 1966, and at Card Sound Bank in 1957. Smaller magnitude shifts were also recorded at Featherbed Bank in 1893, 1942, 1974 and 1983. Most of these changes coincided with severe drought periods that developed during the cold phases of El Niño Southern Oscillation (ENSO), Atlantic Multidecadal Oscillation (AMO) and Pacific Decadal Oscillation (PDO), or when AMO was in warm phase and PDO was in the cold phase. Only the 1983 change coincided with an unusually wet period that developed during the warm phases of ENSO and PDO. Quantitative reconstructions of salinity using the weighted averaging partial least squares (WA-PLS) diatom-based salinity model revealed a gradual increase in salinity at the three coring locations over the last ~ 600 yr, which was primarily caused by continuously rising sea level and in the last several decades also by the reduction of the amount of freshwater inflow from the mainland. Concentration of sediment total nitrogen (TN), total phosphorus (TP) and total organic carbon (TOC) increased in the second half of the 20th century, which coincided with the construction of canals, landfills, marinas and water treatment plants along the western margin of Biscayne Bay. Increased magnitude and rate of the diatom assemblage restructuring in the mid- and late-1900s, suggest that large environmental changes are occurring more rapidly now than in the past.","language":"English","publisher":"Elsevier","doi":"10.1016/j.palaeo.2012.12.020","usgsCitation":"Wachnicka, A., Gaiser, E., Wingard, G.L., Briceno, H., and Harlem, P., 2013, Impact of Late Holocene climate variability and anthropogenic activities on Biscayne Bay (Florida, U.S.A.): Evidence from diatoms: Palaeogeography, Palaeoclimatology, Palaeoecology, v. 371, p. 80-92, https://doi.org/10.1016/j.palaeo.2012.12.020.","productDescription":"13 p.","startPage":"80","endPage":"92","ipdsId":"IP-038980","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":563,"text":"South Florida Information Access","active":false,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":275111,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Biscayne Bay","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -80.313083,25.414719 ], [ -80.313083,25.920597 ], [ -80.125669,25.920597 ], [ -80.125669,25.414719 ], [ -80.313083,25.414719 ] ] ] } } ] }","volume":"371","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51e7aed6e4b080b82b09c60a","chorus":{"doi":"10.1016/j.palaeo.2012.12.020","url":"http://dx.doi.org/10.1016/j.palaeo.2012.12.020","publisher":"Elsevier BV","authors":"Wachnicka Anna, Gaiser Evelyn, Wingard Lynn, Briceo Henry, Harlem Peter","journalName":"Palaeogeography, Palaeoclimatology, Palaeoecology","publicationDate":"2/2013","auditedOn":"11/1/2014"},"contributors":{"authors":[{"text":"Wachnicka, Anna","contributorId":15500,"corporation":false,"usgs":true,"family":"Wachnicka","given":"Anna","email":"","affiliations":[],"preferred":false,"id":480539,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gaiser, Evelyn","contributorId":61727,"corporation":false,"usgs":true,"family":"Gaiser","given":"Evelyn","affiliations":[],"preferred":false,"id":480541,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wingard, G. Lynn 0000-0002-3833-5207 lwingard@usgs.gov","orcid":"https://orcid.org/0000-0002-3833-5207","contributorId":605,"corporation":false,"usgs":true,"family":"Wingard","given":"G.","email":"lwingard@usgs.gov","middleInitial":"Lynn","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":480540,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Briceno, Henry","contributorId":94191,"corporation":false,"usgs":true,"family":"Briceno","given":"Henry","email":"","affiliations":[],"preferred":false,"id":480543,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Harlem, Peter","contributorId":83421,"corporation":false,"usgs":true,"family":"Harlem","given":"Peter","email":"","affiliations":[],"preferred":false,"id":480542,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70046847,"text":"70046847 - 2013 - Hysteresis in suspended sediment to turbidity relations due to changing particle size distributions","interactions":[],"lastModifiedDate":"2013-10-23T13:59:24","indexId":"70046847","displayToPublicDate":"2013-07-17T11:11:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Hysteresis in suspended sediment to turbidity relations due to changing particle size distributions","docAbstract":"Turbidity (T) is the most ubiquitous of surrogate technologies used to estimate suspended-sediment concentration (SSC). The effects of sediment size on turbidity are well documented; however, effects from changes in particle size distributions (PSD) are rarely evaluated. Hysteresis in relations of SSC-to-turbidity (SSC~T) for single stormflow events was observed and quantified for a data set of 195 concurrent measurements of SSC, turbidity, discharge, velocity, and volumetric PSD collected during five stormflows in 2009–2010 on Yellow River at Gees Mill Road in metropolitan Atlanta, Georgia. Regressions of SSC-normalized turbidity (T/SSC) on concurrently measured PSD percentiles show an inverse, exponential influence of particle size on turbidity that is not constant across the size range of the PSD. The majority of the influence of PSD on T/SSC is from particles of fine-silt and smaller sizes (finer than 16 microns). This study shows that small changes in the often assumed stability of the PSD are significant to SSC~T relations. Changes of only 5 microns in the fine silt and smaller size fractions of suspended sediment PSD can produce hysteresis in the SSC~T rating that can increase error and produce bias. Observed SSC~T hysteresis may be an indicator of changes in sediment properties during stormflows and of potential changes in sediment sources. Trends in the PSD time series indicate that sediment transport is capacity-limited for sand-sized sediment in the channel and supply-limited for fine silt and smaller sediment from the hillslope.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Water Resources Research","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Geophysical Union","doi":"10.1002/wrcr.20394","usgsCitation":"Landers, M.N., and Sturm, T.W., 2013, Hysteresis in suspended sediment to turbidity relations due to changing particle size distributions: Water Resources Research, v. 49, no. 9, p. 5487-5500, https://doi.org/10.1002/wrcr.20394.","productDescription":"14 p.","startPage":"5487","endPage":"5500","numberOfPages":"14","ipdsId":"IP-040416","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":275109,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":275108,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/wrcr.20394"}],"scale":"100000","country":"United States","state":"Georgia","otherGeospatial":"Yellow River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -84.256897,33.648922 ], [ -84.256897,34.100434 ], [ -83.909626,34.100434 ], [ -83.909626,33.648922 ], [ -84.256897,33.648922 ] ] ] } } ] }","volume":"49","issue":"9","noUsgsAuthors":false,"publicationDate":"2013-09-09","publicationStatus":"PW","scienceBaseUri":"51e7aed6e4b080b82b09c606","contributors":{"authors":[{"text":"Landers, Mark N. 0000-0002-3014-0480 landers@usgs.gov","orcid":"https://orcid.org/0000-0002-3014-0480","contributorId":1103,"corporation":false,"usgs":true,"family":"Landers","given":"Mark","email":"landers@usgs.gov","middleInitial":"N.","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":true,"id":480452,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sturm, Terry W.","contributorId":36445,"corporation":false,"usgs":true,"family":"Sturm","given":"Terry","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":480453,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70047083,"text":"fs20133044 - 2013 - Development of a geodatabase for springs within and surrounding outcrops of the Trinity aquifer in northern Bexar County, Texas, 2010-11","interactions":[],"lastModifiedDate":"2016-08-05T13:47:01","indexId":"fs20133044","displayToPublicDate":"2013-07-17T09:40:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-3044","title":"Development of a geodatabase for springs within and surrounding outcrops of the Trinity aquifer in northern Bexar County, Texas, 2010-11","docAbstract":"The Trinity aquifer is an important source of groundwater in central Texas, including Bexar County, where population growth has resulted in an increased demand for water (Ashworth, 1983; Mace and others, 2000). Numerous springs issue from rock outcrops within and surrounding the Trinity aquifer in northern Bexar County (fig. 1). The effects of increased groundwater withdrawals from the Trinity aquifer on springflow in the area are not well documented, but because the total amount of water entering, leaving, and being stored in a groundwater system must be conserved, increased groundwater withdrawals will result in decreases in springflow (Alley and others, 1999). Documenting the location, discharge, and basic water-quality information of the springs in northern Bexar County can provide a baseline assessment for comparison to future conditions. Accordingly, the U.S. Geological Survey (USGS), in cooperation with the Trinity Glen Rose Groundwater Conservation District, the Edwards Aquifer Authority, and the San Antonio River Authority, developed a geodatabase populated with data associated with springs within and surrounding outcrops of the Trinity aquifer in northern Bexar County during 2010–11. A geodatabase provides a framework for organizing spatial and tabular data (such as the geographic location and water-quality characteristics, respectively) in a relational database environment, making it easier and more intuitive to evaluate changes over time.
\nData for 141 springs within and surrounding the Trinity aquifer outcrops in northern Bexar County were compiled from existing reports and databases. These data were augmented with selected data collected onsite, including the location, discharge, and water-quality characteristics of selected springs, and were entered into the geodatabase. The Trinity aquifer in central Texas is commonly divided into the upper, middle, and lower Trinity aquifers; all of the information that was compiled pertaining to the aquifer is for the upper and middle Trinity aquifers.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20133044","collaboration":"Prepared in cooperation with Trinity Glen Rose Groundwater Conservation District, Edwards Aquifer Authority, and San Antonio River Authority","usgsCitation":"Clark, A.K., and Pedraza, D.E., 2013, Development of a geodatabase for springs within and surrounding outcrops of the Trinity aquifer in northern Bexar County, Texas, 2010-11: U.S. Geological Survey Fact Sheet 2013-3044, 4 p., https://doi.org/10.3133/fs20133044.","productDescription":"4 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-048945","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":275106,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20133044.gif"},{"id":275102,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2013/3044/"},{"id":275105,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2013/3044/FS_2013-3044.pdf"}],"country":"United States","state":"Texas","county":"Bexar County","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -98.833333,29.5 ], [ -98.833333,29.8 ], [ -98.333333,29.8 ], [ -98.333333,29.5 ], [ -98.833333,29.5 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51e7aed0e4b080b82b09c5fe","contributors":{"authors":[{"text":"Clark, Allan K. 0000-0003-0099-1521 akclark@usgs.gov","orcid":"https://orcid.org/0000-0003-0099-1521","contributorId":1279,"corporation":false,"usgs":true,"family":"Clark","given":"Allan","email":"akclark@usgs.gov","middleInitial":"K.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":481025,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pedraza, Diane E.","contributorId":67788,"corporation":false,"usgs":true,"family":"Pedraza","given":"Diane","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":481026,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70047082,"text":"sir20135030 - 2013 - Software for analysis of chemical mixtures--composition, occurrence, distribution, and possible toxicity","interactions":[],"lastModifiedDate":"2013-07-17T09:37:11","indexId":"sir20135030","displayToPublicDate":"2013-07-17T09:32:00","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":"2013-5030","title":"Software for analysis of chemical mixtures--composition, occurrence, distribution, and possible toxicity","docAbstract":"The composition, occurrence, distribution, and possible toxicity of chemical mixtures in the environment are research concerns of the U.S. Geological Survey and others. The presence of specific chemical mixtures may serve as indicators of natural phenomena or human-caused events. Chemical mixtures may also have ecological, industrial, geochemical, or toxicological effects. Chemical-mixture occurrences vary by analyte composition and concentration. Four related computer programs have been developed by the National Water-Quality Assessment Program of the U.S. Geological Survey for research of chemical-mixture compositions, occurrences, distributions, and possible toxicities. The compositions and occurrences are identified for the user-supplied data, and therefore the resultant counts are constrained by the user’s choices for the selection of chemicals, reporting limits for the analytical methods, spatial coverage, and time span for the data supplied. The distribution of chemical mixtures may be spatial, temporal, and (or) related to some other variable, such as chemical usage. Possible toxicities optionally are estimated from user-supplied benchmark data.\n\nThe software for the analysis of chemical mixtures described in this report is designed to work with chemical-analysis data files retrieved from the U.S. Geological Survey National Water Information System but can also be used with appropriately formatted data from other sources. Installation and usage of the mixture software are documented. This mixture software was designed to function with minimal changes on a variety of computer-operating systems. To obtain the software described herein and other U.S. Geological Survey software, visit http://water.usgs.gov/software/.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135030","collaboration":"National Water-Quality Assessment Program","usgsCitation":"Scott, J.C., Skach, K.A., and Toccalino, P., 2013, Software for analysis of chemical mixtures--composition, occurrence, distribution, and possible toxicity: U.S. Geological Survey Scientific Investigations Report 2013-5030, iv, 27 p., https://doi.org/10.3133/sir20135030.","productDescription":"iv, 27 p.","numberOfPages":"35","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-041335","costCenters":[{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true}],"links":[{"id":275104,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135030.gif"},{"id":275101,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5030/"},{"id":275103,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5030/sir2013-5030.pdf"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51e7aed8e4b080b82b09c61a","contributors":{"authors":[{"text":"Scott, Jonathon C. jcscott@usgs.gov","contributorId":5449,"corporation":false,"usgs":true,"family":"Scott","given":"Jonathon","email":"jcscott@usgs.gov","middleInitial":"C.","affiliations":[],"preferred":true,"id":481023,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Skach, Kenneth A. kaskach@usgs.gov","contributorId":1894,"corporation":false,"usgs":true,"family":"Skach","given":"Kenneth","email":"kaskach@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":481022,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Toccalino, Patricia L. 0000-0003-1066-1702","orcid":"https://orcid.org/0000-0003-1066-1702","contributorId":41089,"corporation":false,"usgs":true,"family":"Toccalino","given":"Patricia L.","affiliations":[{"id":5079,"text":"Pacific Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":481024,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70190122,"text":"70190122 - 2013 - Variability common to first leaf dates and snowpack in the western conterminous United States","interactions":[],"lastModifiedDate":"2017-08-12T08:34:55","indexId":"70190122","displayToPublicDate":"2013-07-17T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1421,"text":"Earth Interactions","active":true,"publicationSubtype":{"id":10}},"title":"Variability common to first leaf dates and snowpack in the western conterminous United States","docAbstract":"Singular value decomposition is used to identify the common variability in first leaf dates (FLDs) and 1 April snow water equivalent (SWE) for the western United States during the period 1900–2012. Results indicate two modes of joint variability that explain 57% of the variability in FLD and 69% of the variability in SWE. The first mode of joint variability is related to widespread late winter–spring warming or cooling across the entire west. The second mode can be described as a north–south dipole in temperature for FLD, as well as in cool season temperature and precipitation for SWE, that is closely correlated to the El Niño–Southern Oscillation. Additionally, both modes of variability indicate a relation with the Pacific–North American atmospheric pattern. These results indicate that there is a substantial amount of common variance in FLD and SWE that is related to large-scale modes of climate variability.
","language":"English","publisher":"American Meteorological Society","doi":"10.1175/2013EI000549.1","usgsCitation":"McCabe, G., Betancourt, J.L., Pederson, G.T., and Schwartz, M., 2013, Variability common to first leaf dates and snowpack in the western conterminous United States: Earth Interactions, v. 17, Paper 26: 18 p., https://doi.org/10.1175/2013EI000549.1.","productDescription":"Paper 26: 18 p.","ipdsId":"IP-049239","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":473677,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1175/2013ei000549.1","text":"Publisher Index Page"},{"id":344780,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -127.35351562499999,\n 28.69058765425071\n ],\n [\n -103.095703125,\n 28.69058765425071\n ],\n [\n -103.095703125,\n 49.38237278700955\n ],\n [\n -127.35351562499999,\n 49.38237278700955\n ],\n [\n -127.35351562499999,\n 28.69058765425071\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"17","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2013-11-26","publicationStatus":"PW","scienceBaseUri":"5990139ae4b09fa1cb178931","contributors":{"authors":[{"text":"McCabe, Gregory J. 0000-0002-9258-2997 gmccabe@usgs.gov","orcid":"https://orcid.org/0000-0002-9258-2997","contributorId":167116,"corporation":false,"usgs":true,"family":"McCabe","given":"Gregory J.","email":"gmccabe@usgs.gov","affiliations":[{"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":false,"id":707571,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Betancourt, Julio L. 0000-0002-7165-0743 jlbetanc@usgs.gov","orcid":"https://orcid.org/0000-0002-7165-0743","contributorId":3376,"corporation":false,"usgs":true,"family":"Betancourt","given":"Julio","email":"jlbetanc@usgs.gov","middleInitial":"L.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":707572,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pederson, Gregory T. 0000-0002-6014-1425 gpederson@usgs.gov","orcid":"https://orcid.org/0000-0002-6014-1425","contributorId":3106,"corporation":false,"usgs":true,"family":"Pederson","given":"Gregory","email":"gpederson@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":707573,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schwartz, Mark D.","contributorId":11092,"corporation":false,"usgs":true,"family":"Schwartz","given":"Mark D.","affiliations":[],"preferred":false,"id":707574,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70190142,"text":"70190142 - 2013 - Water resources: Implications of changes in temperature and precipitation: Chapter 3","interactions":[],"lastModifiedDate":"2017-08-13T11:57:09","indexId":"70190142","displayToPublicDate":"2013-07-17T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Water resources: Implications of changes in temperature and precipitation: Chapter 3","docAbstract":"No abstract available.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Climate change in the Northwest: Implications for our landscapes, waters, and communities","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Island Press","publisherLocation":"Washington, D.C.","isbn":"978-1-61091-512-0","usgsCitation":"Raymondi, R., Cuhaciyan, J.E., Glick, P., Capalbo, S.M., Houston, L.L., Shafer, S., and Grah, O., 2013, Water resources: Implications of changes in temperature and precipitation: Chapter 3, chap. of Climate change in the Northwest: Implications for our landscapes, waters, and communities, p. 41-66.","productDescription":"26 p.","startPage":"41","endPage":"66","ipdsId":"IP-041973","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":344786,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59b774dee4b08b1644ddfbb1","contributors":{"authors":[{"text":"Raymondi, Rick R.","contributorId":23848,"corporation":false,"usgs":true,"family":"Raymondi","given":"Rick R.","affiliations":[],"preferred":false,"id":707668,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cuhaciyan, Jennifer E.","contributorId":195615,"corporation":false,"usgs":false,"family":"Cuhaciyan","given":"Jennifer","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":707666,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Glick, Patty","contributorId":195616,"corporation":false,"usgs":false,"family":"Glick","given":"Patty","email":"","affiliations":[],"preferred":false,"id":707667,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Capalbo, Susan M.","contributorId":48864,"corporation":false,"usgs":true,"family":"Capalbo","given":"Susan","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":707665,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Houston, Laurie L.","contributorId":11935,"corporation":false,"usgs":true,"family":"Houston","given":"Laurie","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":707669,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Shafer, Sarah 0000-0003-3739-2637 sshafer@usgs.gov","orcid":"https://orcid.org/0000-0003-3739-2637","contributorId":149866,"corporation":false,"usgs":true,"family":"Shafer","given":"Sarah","email":"sshafer@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":707664,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Grah, Oliver","contributorId":195619,"corporation":false,"usgs":false,"family":"Grah","given":"Oliver","email":"","affiliations":[],"preferred":false,"id":707670,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70098177,"text":"70098177 - 2013 - Controls on recent Alaskan lake changes identified from water isotopes and remote sensing","interactions":[],"lastModifiedDate":"2017-04-06T15:18:38","indexId":"70098177","displayToPublicDate":"2013-07-16T16:03:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Controls on recent Alaskan lake changes identified from water isotopes and remote sensing","docAbstract":"High-latitude lakes are important for terrestrial carbon\ndynamics and waterfowl habitat driving a need to better\nunderstand controls on lake area changes. To identify the\nexistence and cause of recent lake area changes in the\nYukon Flats, a region of discontinuous permafrost in north\ncentral Alaska, we evaluate remotely sensed imagery with\nlake water isotope compositions and hydroclimatic\nparameters. Isotope compositions indicate that mixtures of\nprecipitation, river water, and groundwater source ~95% of\nthe studied lakes. The remaining minority are more\ndominantly sourced by snowmelt and/or permafrost thaw.\nIsotope-based water balance estimates indicate 58% of\nlakes lose more than half of inflow by evaporation. For\n26% of the lakes studied, evaporative losses exceeded\nsupply. Surface area trend analysis indicates that most lakes\nwere near their maximum extent in the early 1980s during a\nrelatively cool and wet period. Subsequent reductions can\nbe explained by moisture deficits and greater evaporation.","language":"English","publisher":"American Geophysical Union","doi":"10.1002/grl.50672","usgsCitation":"Anderson, L., Birks, J., Rover, J.R., and Guldager, N., 2013, Controls on recent Alaskan lake changes identified from water isotopes and remote sensing: Geophysical Research Letters, v. 40, no. 13, p. 3413-3418, https://doi.org/10.1002/grl.50672.","productDescription":"6 p.","startPage":"3413","endPage":"3418","numberOfPages":"6","ipdsId":"IP-044101","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":473678,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/grl.50672","text":"Publisher Index Page"},{"id":284109,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":284106,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/grl.50672"}],"country":"United States","state":"Alaska","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -149.9854,64.9933 ], [ -149.9854,67.5170 ], [ -141.9763,67.5170 ], [ -141.9763,64.9933 ], [ -149.9854,64.9933 ] ] ] } } ] }","volume":"40","issue":"13","noUsgsAuthors":false,"publicationDate":"2013-07-12","publicationStatus":"PW","scienceBaseUri":"53cd532ce4b0b290850f4fbb","contributors":{"authors":[{"text":"Anderson, Lesleigh 0000-0002-5264-089X land@usgs.gov","orcid":"https://orcid.org/0000-0002-5264-089X","contributorId":436,"corporation":false,"usgs":true,"family":"Anderson","given":"Lesleigh","email":"land@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":491668,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Birks, Jean","contributorId":87856,"corporation":false,"usgs":true,"family":"Birks","given":"Jean","email":"","affiliations":[],"preferred":false,"id":491670,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rover, Jennifer R. 0000-0002-3437-4030 jrover@usgs.gov","orcid":"https://orcid.org/0000-0002-3437-4030","contributorId":2941,"corporation":false,"usgs":true,"family":"Rover","given":"Jennifer","email":"jrover@usgs.gov","middleInitial":"R.","affiliations":[],"preferred":false,"id":491669,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Guldager, Nikki","contributorId":101981,"corporation":false,"usgs":true,"family":"Guldager","given":"Nikki","email":"","affiliations":[],"preferred":false,"id":491671,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70046953,"text":"fs20133038 - 2013 - The National Water-Quality Assessment (NAWQA) Program planned monitoring and modeling activities for Texas, 2013–23","interactions":[],"lastModifiedDate":"2016-08-05T13:48:14","indexId":"fs20133038","displayToPublicDate":"2013-07-16T15:50:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-3038","title":"The National Water-Quality Assessment (NAWQA) Program planned monitoring and modeling activities for Texas, 2013–23","docAbstract":"The U.S. Geological Survey’s (USGS) National Water-Quality Assessment (NAWQA) Program was established by Congress in 1992 to answer the following question: What is the status of the Nation’s water quality and is it getting better or worse? Since 1992, NAWQA has been a primary source of nationally consistent data and information on the quality of the Nation’s streams and groundwater. Data and information obtained from objective and nationally consistent water-quality monitoring and modeling activities provide answers to where, when, and why the Nation’s water quality is degraded and what can be done to improve and protect it for human and ecosystem needs. For NAWQA’s third decade (2013–23), a new strategic Science Plan has been developed that describes a strategy for building upon and enhancing the USGS’s ongoing assessment of the Nation’s freshwater quality and aquatic ecosystems.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20133038","usgsCitation":"Ging, P., 2013, The National Water-Quality Assessment (NAWQA) Program planned monitoring and modeling activities for Texas, 2013–23: U.S. Geological Survey Fact Sheet 2013-3038, 2 p., https://doi.org/10.3133/fs20133038.","productDescription":"2 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-046123","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":275099,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20133038.gif"},{"id":275097,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2013/3038/"},{"id":275098,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2013/3038/FS2013-3038.pdf"}],"country":"United States","state":"Texas","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51e65d5ae4b017be1ba34744","contributors":{"authors":[{"text":"Ging, Patricia","contributorId":77027,"corporation":false,"usgs":true,"family":"Ging","given":"Patricia","affiliations":[],"preferred":false,"id":480672,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ]}