Performance of wild (W) and hatchery (H) spring Chinook salmon (Oncorhynchus tshawytscha) was evaluated for a sixth generation hatchery program. Management techniques to minimize genetic divergence from the wild stock included regular use of wild broodstock and volitional releases of juveniles. Performance of HH, WW, and HW (hatchery female spawned with wild male) crosses was compared in hatchery and stream environments. The WW juveniles emigrated from the hatchery at two to three times the rate of HH fish in the fall (HW intermediate) and 35% more HH than WW adults returned (27% more HW than WW adults). Performance in the stream did not differ statistically between HH and WW fish, but outmigrants (38% WW, 30% HW, and 32% HH fish) during the first 39 days of the 16-month sampling period composed 74% of total outmigrants. Differences among hatchery-reared crosses were partially due to additive genetic effects, were consistent with domestication (increased fitness for the hatchery population in the hatchery program), and suggested that selection against fall emigration from the hatchery was a possible mechanism of domestication.
","language":"English","publisher":"NRC Research Press","doi":"10.1139/cjfas-2012-0138","usgsCitation":"Hayes, M.C., Reisenbichler, R.R., Rubin, S.P., Drake, D., Stenberg, K.D., and Young, S.F., 2013, Effectiveness of an integrated hatchery program: Can genetic-based performance differences between hatchery and wild Chinook salmon be avoided?: Canadian Journal of Fisheries and Aquatic Sciences, v. 70, no. 2, p. 147-158, https://doi.org/10.1139/cjfas-2012-0138.","productDescription":"12 p.","startPage":"147","endPage":"158","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-026265","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":272129,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"70","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"518cb75ce4b05ebc8f7cc0e4","contributors":{"authors":[{"text":"Hayes, Michael C. 0000-0002-9060-0565 mhayes@usgs.gov","orcid":"https://orcid.org/0000-0002-9060-0565","contributorId":3017,"corporation":false,"usgs":true,"family":"Hayes","given":"Michael","email":"mhayes@usgs.gov","middleInitial":"C.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":474531,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reisenbichler, Reginald R.","contributorId":20623,"corporation":false,"usgs":true,"family":"Reisenbichler","given":"Reginald","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":474534,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rubin, Stephen P. 0000-0003-3054-7173","orcid":"https://orcid.org/0000-0003-3054-7173","contributorId":38037,"corporation":false,"usgs":true,"family":"Rubin","given":"Stephen","email":"","middleInitial":"P.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":474535,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Drake, Deanne C.","contributorId":71462,"corporation":false,"usgs":true,"family":"Drake","given":"Deanne C.","affiliations":[],"preferred":false,"id":474536,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stenberg, Karl D. 0000-0001-9802-2707 kstenberg@usgs.gov","orcid":"https://orcid.org/0000-0001-9802-2707","contributorId":3747,"corporation":false,"usgs":true,"family":"Stenberg","given":"Karl","email":"kstenberg@usgs.gov","middleInitial":"D.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":474532,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Young, Sewall F.","contributorId":15499,"corporation":false,"usgs":true,"family":"Young","given":"Sewall","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":474533,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70044642,"text":"70044642 - 2013 - Effects of historical lead–zinc mining on riffle-dwelling benthic fish and crayfish in the Big River of southeastern Missouri, USA","interactions":[],"lastModifiedDate":"2013-05-09T13:53:26","indexId":"70044642","displayToPublicDate":"2013-05-09T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1479,"text":"Ecotoxicology","active":true,"publicationSubtype":{"id":10}},"title":"Effects of historical lead–zinc mining on riffle-dwelling benthic fish and crayfish in the Big River of southeastern Missouri, USA","docAbstract":"The Big River (BGR) drains much of the Old Lead Belt mining district (OLB) in southeastern Missouri, USA, which was historically among the largest producers of lead–zinc (Pb–Zn) ore in the world. We sampled benthic fish and crayfish in riffle habitats at eight sites in the BGR and conducted 56-day in situ exposures to the woodland crayfish (Orconectes hylas) and golden crayfish (Orconectes luteus) in cages at four sites affected to differing degrees by mining. Densities of fish and crayfish, physical habitat and water quality, and the survival and growth of caged crayfish were examined at sites with no known upstream mining activities (i.e., reference sites) and at sites downstream of mining areas (i.e., mining and downstream sites). Lead, zinc, and cadmium were analyzed in surface and pore water, sediment, detritus, fish, crayfish, and other benthic macro-invertebrates. Metals concentrations in all materials analyzed were greater at mining and downstream sites than at reference sites. Ten species of fish and four species of crayfish were collected. Fish and crayfish densities were significantly greater at reference than mining or downstream sites, and densities were greater at downstream than mining sites. Survival of caged crayfish was significantly lower at mining sites than reference sites; downstream sites were not tested. Chronic toxic-unit scores and sediment probable effects quotients indicated significant risk of toxicity to fish and crayfish, and metals concentrations in crayfish were sufficiently high to represent a risk to wildlife at mining and downstream sites. Collectively, the results provided direct evidence that metals associated with historical mining activities in the OLB continue to affect aquatic life in the BGR.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ecotoxicology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","doi":"10.1007/s10646-013-1043-3","usgsCitation":"Allert, A., DiStefano, R., Fairchild, J., Schmitt, C., McKee, M., Girondo, J., Brumbaugh, W.G., and May, T., 2013, Effects of historical lead–zinc mining on riffle-dwelling benthic fish and crayfish in the Big River of southeastern Missouri, USA: Ecotoxicology, v. 22, no. 3, p. 506-521, https://doi.org/10.1007/s10646-013-1043-3.","productDescription":"16 p.","startPage":"506","endPage":"521","ipdsId":"IP-039152","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":272154,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":272153,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s10646-013-1043-3"}],"country":"United States","state":"Missouri","otherGeospatial":"Big River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -95.77,36.0 ], [ -95.77,40.61 ], [ -89.1,40.61 ], [ -89.1,36.0 ], [ -95.77,36.0 ] ] ] } } ] }","volume":"22","issue":"3","noUsgsAuthors":false,"publicationDate":"2013-02-23","publicationStatus":"PW","scienceBaseUri":"518cb75fe4b05ebc8f7cc0ec","contributors":{"authors":[{"text":"Allert, A.L.","contributorId":55987,"corporation":false,"usgs":true,"family":"Allert","given":"A.L.","email":"","affiliations":[],"preferred":false,"id":476115,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"DiStefano, R.J.","contributorId":72581,"corporation":false,"usgs":true,"family":"DiStefano","given":"R.J.","affiliations":[],"preferred":false,"id":476117,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fairchild, J.F.","contributorId":88891,"corporation":false,"usgs":true,"family":"Fairchild","given":"J.F.","email":"","affiliations":[],"preferred":false,"id":476120,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schmitt, C. J. 0000-0001-6804-2360","orcid":"https://orcid.org/0000-0001-6804-2360","contributorId":56339,"corporation":false,"usgs":true,"family":"Schmitt","given":"C. J.","affiliations":[],"preferred":false,"id":476116,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McKee, M.J.","contributorId":53365,"corporation":false,"usgs":true,"family":"McKee","given":"M.J.","affiliations":[],"preferred":false,"id":476114,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Girondo, J.A.","contributorId":75423,"corporation":false,"usgs":true,"family":"Girondo","given":"J.A.","affiliations":[],"preferred":false,"id":476118,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Brumbaugh, W. G.","contributorId":106441,"corporation":false,"usgs":true,"family":"Brumbaugh","given":"W.","email":"","middleInitial":"G.","affiliations":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"preferred":false,"id":476121,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"May, T.W.","contributorId":75878,"corporation":false,"usgs":true,"family":"May","given":"T.W.","email":"","affiliations":[],"preferred":false,"id":476119,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70045885,"text":"ofr20131076 - 2013 - Characterization of mercury contamination in the Androscoggin River, Coos County, New Hampshire","interactions":[],"lastModifiedDate":"2013-05-08T09:21:26","indexId":"ofr20131076","displayToPublicDate":"2013-05-08T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-1076","title":"Characterization of mercury contamination in the Androscoggin River, Coos County, New Hampshire","docAbstract":"The former chloralkali facility in Berlin, New Hampshire, was designated a Superfund site in 2005. Historic paper mill activities resulted in the contamination of groundwater, surface water, and sediments with many organic compounds and mercury (Hg). Hg continues to seep into the Androscoggin River in elemental form through bedrock fractures. The objective of this study was to spatially characterize (1) the extent of Hg contamination in water, sediment, and biota; (2) Hg speciation and methylmercury (MeHg) production potential rates in sediment; (3) the availability of inorganic divalent Hg (Hg(II)) for Hg(II)-methylation (MeHg production); and (4) ancillary sediment geochemistry necessary to better understand Hg speciation and MeHg production potential rates in this system.\nConcentrations of total mercury (THg) and MeHg in sediment, pore water, and biota in the Androscoggin River were elevated downstream from the former chloralkali facility compared with those upstream from reference sites. Sequential extraction of surface sediment showed a distinct difference in Hg speciation upstream compared with downstream from the contamination site. An upstream site was dominated by potassium hydroxide-extractable forms (for example, organic-Hg or particle-bound Hg(II)), whereas sites downstream from the point source were dominated by more chemically recalcitrant forms (largely concentrated nitric acid-extractable), indicative of elemental mercury or mercurous chloride. At all sites, only a minor fraction (less than 0.1 percent) of THg existed in chemically labile forms (for example, water extractable or weak acid extractable). All metrics indicated that a greater percentage of mercury at an upstream site was available for Hg(II)-methylation compared with sites downstream from the point source, but the absolute concentration of bioavailable Hg(II) was greater downstream from the point source. In addition, the concentration of tin-reducible inorganic reactive mercury, a surrogate measure of bioavailable Hg(II) generally increased with distance downstream from the point source. Whereas concentrations of mercury species on a sediment-dry-weight basis generally reflected the relative location of the sample to the point source, river-reach integrated mercury-species inventories and MeHg production potential (MPP) rates reflected the amount of fine-grained sediment in a given reach. THg concentrations in biota were significantly higher downstream from the point source compared with upstream reference sites for smallmouth bass, white sucker, crayfish, oligochaetes, bat fur, nestling tree swallow blood and feathers, adult tree swallow blood, and tree swallow eggs. As with tin-reducible inorganic reactive mercury, THg in smallmouth bass also increased with distance downstream from the point source. Toxicity tests and invertebrate community assessments suggested that invertebrates were not impaired at the current (2009 and 2010) levels of mercury contamination downstream from the point source. Concentrations of THg and MeHg in most water and sediment samples from the Androscoggin River were below U.S. Environmental Protection Agency (USEPA), the Canadian Council of Ministers of the Environment, and probable effects level guidelines. Surface-water and sediment samples from the Androscoggin River had similar THg concentrations but lower MeHg concentrations compared with other rivers in the region. Concentrations of THg in fish tissue were all above regional and U.S. Environmental Protection Agency guidelines. Moreover, median THg concentrations in smallmouth bass from the Androscoggin River were significantly higher than those reported in regional surveys of river and streams nationwide and in the Northeastern United States and Canada. The higher concentrations of mercury in smallmouth bass suggest conditions may be more favorable for Hg(II)-methylation and bioaccumulation in the Androscoggin River compared with many other rivers in the United States and Canada.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131076","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency","usgsCitation":"Chalmers, A., Marvin-DiPasquale, M.C., Degnan, J.R., Coles, J., Agee, J.L., and Luce, D., 2013, Characterization of mercury contamination in the Androscoggin River, Coos County, New Hampshire: U.S. Geological Survey Open-File Report 2013-1076, Report: vii, 58 p.; 2 XLS Appendices, https://doi.org/10.3133/ofr20131076.","productDescription":"Report: vii, 58 p.; 2 XLS Appendices","numberOfPages":"68","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":272063,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131076.gif"},{"id":272059,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1076/"},{"id":272061,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2013/1076/appendix/ofr_chalmers_append1_final.xlsx"},{"id":272060,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1076/pdf/ofr2013-1076_report_508.pdf"},{"id":272062,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2013/1076/appendix/ofr_chalmers_append2_final.xlsx"}],"country":"United States","state":"New Hampshire","county":"Coos County","otherGeospatial":"Androscoggin River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -71.19,44.39 ], [ -71.19,44.40 ], [ -71.18,44.40 ], [ -71.18,44.39 ], [ -71.19,44.39 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"518b65d2e4b0037667dbc7df","contributors":{"authors":[{"text":"Chalmers, Ann","contributorId":23604,"corporation":false,"usgs":true,"family":"Chalmers","given":"Ann","affiliations":[],"preferred":false,"id":478481,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Marvin-DiPasquale, Mark C. 0000-0002-8186-9167 mmarvin@usgs.gov","orcid":"https://orcid.org/0000-0002-8186-9167","contributorId":1485,"corporation":false,"usgs":true,"family":"Marvin-DiPasquale","given":"Mark","email":"mmarvin@usgs.gov","middleInitial":"C.","affiliations":[{"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":478479,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Degnan, James R. 0000-0002-5665-9010 jrdegnan@usgs.gov","orcid":"https://orcid.org/0000-0002-5665-9010","contributorId":498,"corporation":false,"usgs":true,"family":"Degnan","given":"James","email":"jrdegnan@usgs.gov","middleInitial":"R.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":478478,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Coles, James","contributorId":93795,"corporation":false,"usgs":true,"family":"Coles","given":"James","affiliations":[],"preferred":false,"id":478483,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Agee, Jennifer L. 0000-0002-5964-5079 jlagee@usgs.gov","orcid":"https://orcid.org/0000-0002-5964-5079","contributorId":2586,"corporation":false,"usgs":true,"family":"Agee","given":"Jennifer","email":"jlagee@usgs.gov","middleInitial":"L.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"preferred":true,"id":478480,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Luce, Darryl","contributorId":72520,"corporation":false,"usgs":true,"family":"Luce","given":"Darryl","email":"","affiliations":[],"preferred":false,"id":478482,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70045914,"text":"sir20135086 - 2013 - Methods for estimating annual exceedance-probability discharges for streams in Iowa, based on data through water year 2010","interactions":[],"lastModifiedDate":"2013-05-08T20:55:26","indexId":"sir20135086","displayToPublicDate":"2013-05-08T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-5086","title":"Methods for estimating annual exceedance-probability discharges for streams in Iowa, based on data through water year 2010","docAbstract":"A statewide study was performed to develop regional regression equations for estimating selected annual exceedance-probability statistics for ungaged stream sites in Iowa. The study area comprises streamgages located within Iowa and 50 miles beyond the State’s borders. Annual exceedance-probability estimates were computed for 518 streamgages by using the expected moments algorithm to fit a Pearson Type III distribution to the logarithms of annual peak discharges for each streamgage using annual peak-discharge data through 2010. The estimation of the selected statistics included a Bayesian weighted least-squares/generalized least-squares regression analysis to update regional skew coefficients for the 518 streamgages. Low-outlier and historic information were incorporated into the annual exceedance-probability analyses, and a generalized Grubbs-Beck test was used to detect multiple potentially influential low flows. Also, geographic information system software was used to measure 59 selected basin characteristics for each streamgage.\n\nRegional regression analysis, using generalized least-squares regression, was used to develop a set of equations for each flood region in Iowa for estimating discharges for ungaged stream sites with 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities, which are equivalent to annual flood-frequency recurrence intervals of 2, 5, 10, 25, 50, 100, 200, and 500 years, respectively. A total of 394 streamgages were included in the development of regional regression equations for three flood regions (regions 1, 2, and 3) that were defined for Iowa based on landform regions and soil regions.\n\nAverage standard errors of prediction range from 31.8 to 45.2 percent for flood region 1, 19.4 to 46.8 percent for flood region 2, and 26.5 to 43.1 percent for flood region 3. The pseudo coefficients of determination for the generalized least-squares equations range from 90.8 to 96.2 percent for flood region 1, 91.5 to 97.9 percent for flood region 2, and 92.4 to 96.0 percent for flood region 3. The regression equations are applicable only to stream sites in Iowa with flows not significantly affected by regulation, diversion, channelization, backwater, or urbanization and with basin characteristics within the range of those used to develop the equations.\n\nThese regression equations will be implemented within the U.S. Geological Survey StreamStats Web-based geographic information system tool. StreamStats allows users to click on any ungaged site on a river and compute estimates of the eight selected statistics; in addition, 90-percent prediction intervals and the measured basin characteristics for the ungaged sites also are provided by the Web-based tool. StreamStats also allows users to click on any streamgage in Iowa and estimates computed for these eight selected statistics are provided for the streamgage.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135086","collaboration":"Prepared in cooperation with the Iowa Department of Transportation and the Iowa Highway Research Board (Project TR-519)","usgsCitation":"Eash, D.A., Barnes, K., and Veilleux, A.G., 2013, Methods for estimating annual exceedance-probability discharges for streams in Iowa, based on data through water year 2010: U.S. Geological Survey Scientific Investigations Report 2013-5086, viii, 63 p.; Downloads Directory, https://doi.org/10.3133/sir20135086.","productDescription":"viii, 63 p.; Downloads Directory","numberOfPages":"76","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalEnd":"2010-10-01","ipdsId":"IP-032892","costCenters":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"links":[{"id":272115,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135086.gif"},{"id":272113,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5086/sir13_5086web.pdf"},{"id":272114,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2013/5086/downloads/"},{"id":272112,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5086/"}],"country":"United States","state":"Iowa","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -96.64,40.38 ], [ -96.64,43.5 ], [ -90.14,43.5 ], [ -90.14,40.38 ], [ -96.64,40.38 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"518b65e6e4b0037667dbc7e7","contributors":{"authors":[{"text":"Eash, David A. 0000-0002-2749-8959 daeash@usgs.gov","orcid":"https://orcid.org/0000-0002-2749-8959","contributorId":1887,"corporation":false,"usgs":true,"family":"Eash","given":"David","email":"daeash@usgs.gov","middleInitial":"A.","affiliations":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"preferred":true,"id":478528,"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":478530,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Veilleux, Andrea G. aveilleux@usgs.gov","contributorId":4404,"corporation":false,"usgs":true,"family":"Veilleux","given":"Andrea","email":"aveilleux@usgs.gov","middleInitial":"G.","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":true,"id":478529,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70045890,"text":"ofr20121215 - 2013 - Remote sensing survey of Chinese tallow tree in the Toledo Bend Reservoir area, Louisiana and Texas","interactions":[],"lastModifiedDate":"2018-01-05T10:27:56","indexId":"ofr20121215","displayToPublicDate":"2013-05-08T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-1215","title":"Remote sensing survey of Chinese tallow tree in the Toledo Bend Reservoir area, Louisiana and Texas","docAbstract":"We applied Hyperion sensor satellite data acquired by the National Aeronautics and Space Administration’s Earth Observing-1 (EO-1) satellite in conjunction with reconnaissance surveys to map the occurrences of the invasive Chinese tallow tree (Triadica sebifera) in the Toledo Bend Reservoir study area of northwestern Louisiana and northeastern Texas. The rationale for application of high spectral resolution EO-1 Hyperion data was based on the successful use of Hyperion data in the mapping of Chinese tallow tree in southwestern Louisiana in 2005. In contrast to the single Hyperion image used in the 2005 project, more than 20 EO-1 Hyperion and Advanced Land Imager (ALI) images of the study area were collected in 2009 and 2010 during the fall senescence when Chinese tallow tree leaves turn red. Atmospherically corrected reflectance spectra of Hyperion imagery collected at ground and aerial observation locations provided the input datasets used in the program for spectral discrimination analysis. Discrimination analysis was used to identify spectral indicator sets to best explain variance contained in the input databases. The expectation was that at least one set of Hyperion-based indicator spectra would uniquely identify occurrences of red-leaf Chinese tallow tree; however, no combination of Hyperion-based reflectance datasets produced a unique identifier.\n\nThe inability to discover a unique spectral indicator resulted primarily from relatively sparse coverage by red-leaf Chinese tallow tree within the study area (percentage of coverage was less than 5 percent per 30- by 30-meter Hyperion pixel). To enhance the performance of the spectral discrimination analysis, leaf and canopy spectra of Chinese tallow tree were added to the input datasets to guide the indicator selection. In addition, input databases were segregated by land class obtained from an ALI-based landcover classification in order to reduce the input variance and to promote spectral discrimination of red-leaf Chinese tallow tree. Although no unique spectral identifier for red-leaf Chinese tallow tree was uncovered with these enhanced methods, in some cases predicted spatial patterns throughout the Hyperion images revealed alignment with vegetation associations within each land class that was often observed to contain Chinese tallow trees. These instances were associated particularly with the addition of helicopter-based spectra to the input databases. It was attempted to extend such predictions of likely occurrences of Chinese tallow tree by mapping six of the nine Hyperion swaths and four of the nine land classes, but this attempt produced uncertain results that could not be fully evaluated for accuracy. Even though the final mapping showed promise in identifying likely Chinese tallow tree occurrences, the low percentage of occurrences hindered mapping performance and validation. Results of the mapping suggested that successful detection of Chinese tallow tree in the study area would require a spectral sensor similar to the Hyperion but with a higher ground-level spatial resolution.\n\nAlthough the Hyperion-based spectral mapping did not provide the desired results, the associated field (ground and aerial) surveys did provide for a qualitative assessment of the overall Chinese tallow tree distribution within the study area. Ground and aerial surveys suggested that Chinese tallow tree occurrences were uncommon and were without an observed pattern in relation to proximity to the Toledo Bend Reservoir. Although uncommon and scattered, Chinese tallow trees and shrubs most commonly existed along forest edges, water edges, and fence lines, probably most in line with seed dispersal by birds. Chinese tallow trees were observed to be more densely dispersed within some scrublands and grasslands than were observed in pine, hardwood, and mixed forests.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121215","collaboration":"Prepared in cooperation with the Toledo Bend Project","usgsCitation":"Ramsey, E., Rangoonwala, A., Bannister, T., and Suzuoki, Y., 2013, Remote sensing survey of Chinese tallow tree in the Toledo Bend Reservoir area, Louisiana and Texas: U.S. Geological Survey Open-File Report 2012-1215, xi, 74 p.; Table 14; Database, https://doi.org/10.3133/ofr20121215.","productDescription":"xi, 74 p.; Table 14; Database","numberOfPages":"89","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":272068,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20121215.gif"},{"id":272066,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2012/1215/Table14_RedTallowMapping.xlsx"},{"id":272064,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1215/"},{"id":272067,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/of/2012/1215/Database/ToledoBend_click"},{"id":272065,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1215/OFR%202012-1215.pdf"}],"country":"United States","state":"Louisiana;Texas","county":"Toledo Bend Reservoir","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -94.1,31.1 ], [ -94.1,32.0 ], [ -93.5,32.0 ], [ -93.5,31.1 ], [ -94.1,31.1 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"518b65e6e4b0037667dbc7eb","contributors":{"authors":[{"text":"Ramsey, Elijah W. III 0000-0002-4518-5796","orcid":"https://orcid.org/0000-0002-4518-5796","contributorId":72769,"corporation":false,"usgs":true,"family":"Ramsey","given":"Elijah W.","suffix":"III","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":false,"id":478492,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rangoonwala, Amina 0000-0002-0556-0598 rangoonwalaa@usgs.gov","orcid":"https://orcid.org/0000-0002-0556-0598","contributorId":3455,"corporation":false,"usgs":true,"family":"Rangoonwala","given":"Amina","email":"rangoonwalaa@usgs.gov","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":478490,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bannister, Terri","contributorId":82836,"corporation":false,"usgs":true,"family":"Bannister","given":"Terri","email":"","affiliations":[],"preferred":false,"id":478493,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Suzuoki, Yukihiro","contributorId":25283,"corporation":false,"usgs":true,"family":"Suzuoki","given":"Yukihiro","email":"","affiliations":[],"preferred":false,"id":478491,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70045891,"text":"i2600Q - 2013 - Coastal-change and glaciological map of the Amery Ice Shelf area, Antarctica: 1961–2004","interactions":[],"lastModifiedDate":"2013-05-08T20:59:54","indexId":"i2600Q","displayToPublicDate":"2013-05-08T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":320,"text":"IMAP","code":"I","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"2600","chapter":"Q","title":"Coastal-change and glaciological map of the Amery Ice Shelf area, Antarctica: 1961–2004","docAbstract":"Reduction in the area and volume of Earth’s two polar ice sheets is intricately linked to changes in global climate and to the resulting rise in sea level. Measurement of changes in area and mass balance of the Antarctic ice sheet was given a very high priority in recommendations by the Polar Research Board of the National Research Council. On the basis of these recommendations, the U.S. Geological Survey used its archive of satellite images to document changes in the cryospheric coastline of Antarctica and analyze the glaciological features of the coastal regions.\n\nAmery Ice Shelf, lying between 67.5° and 75° East longitude and 68.5° and 73.2° South latitude, is the largest ice shelf in East Antarctica. The latest measurements of the area of the ice shelf range between 62,620 and 71,260 square kilometers. The ice shelf is fed primarily by Lambert, Mellor, and Fisher Glaciers; its thickness ranges from 3,000 meters in the center of the grounding line to less than 300 meters at the ice front. Lambert Glacier is considered to be the largest glacier in the world, and its drainage basin is more than 1 million square kilometers in area. It is possible to see some coastal change on the outlet glaciers along the coast, but most of the noticeable change occurs on the Amery Ice Shelf front.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/i2600Q","collaboration":"Prepared in cooperation with the Scott Polar Research Institute, University of Cambridge, United Kingdom","usgsCitation":"Foley, K.M., Ferrigno, J.G., Swithinbank, C., Williams, R., and Orndorff, A.L., 2013, Coastal-change and glaciological map of the Amery Ice Shelf area, Antarctica: 1961–2004: U.S. Geological Survey IMAP 2600, Pamphlet: iii, 8 p.; Map: 1 Sheet: 50 x 42 inches; Downloads, https://doi.org/10.3133/i2600Q.","productDescription":"Pamphlet: iii, 8 p.; Map: 1 Sheet: 50 x 42 inches; Downloads","onlineOnly":"N","additionalOnlineFiles":"Y","temporalStart":"1961-01-01","temporalEnd":"2004-12-31","costCenters":[{"id":180,"text":"Climate and Land Use Change Program","active":false,"usgs":true}],"links":[{"id":272069,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/imap/2600/Q/"},{"id":272070,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/imap/2600/Q/pdf/AmeryMap.pdf"},{"id":272071,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/imap/2600/Q/pdf/imap_I-2600-Q_pamphlet.pdf"},{"id":272072,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/imap/2600/Q/Downloads"},{"id":272073,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/i2600q.gif"}],"otherGeospatial":"Antarctica","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 55,-75.0 ], [ 55,-67.0 ], [ 80,-67.0 ], [ 80,-75.0 ], [ 55,-75.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"518b65e5e4b0037667dbc7e3","contributors":{"authors":[{"text":"Foley, Kevin M. 0000-0003-1013-462X kfoley@usgs.gov","orcid":"https://orcid.org/0000-0003-1013-462X","contributorId":2543,"corporation":false,"usgs":true,"family":"Foley","given":"Kevin","email":"kfoley@usgs.gov","middleInitial":"M.","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":478494,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ferrigno, Jane G. jferrign@usgs.gov","contributorId":39825,"corporation":false,"usgs":true,"family":"Ferrigno","given":"Jane","email":"jferrign@usgs.gov","middleInitial":"G.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":false,"id":478496,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Swithinbank, Charles","contributorId":26368,"corporation":false,"usgs":true,"family":"Swithinbank","given":"Charles","email":"","affiliations":[],"preferred":false,"id":478495,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Williams, Richard S. Jr.","contributorId":90679,"corporation":false,"usgs":true,"family":"Williams","given":"Richard S.","suffix":"Jr.","affiliations":[],"preferred":false,"id":478497,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Orndorff, Audrey L.","contributorId":94578,"corporation":false,"usgs":true,"family":"Orndorff","given":"Audrey","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":478498,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70045856,"text":"70045856 - 2013 - Investigating the effects of point source and nonpoint source pollution on the water quality of the East River (Dongjiang) in South China","interactions":[],"lastModifiedDate":"2013-05-07T14:25:21","indexId":"70045856","displayToPublicDate":"2013-05-07T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Investigating the effects of point source and nonpoint source pollution on the water quality of the East River (Dongjiang) in South China","docAbstract":"Understanding the physical processes of point source (PS) and nonpoint source (NPS) pollution is critical to evaluate river water quality and identify major pollutant sources in a watershed. In this study, we used the physically-based hydrological/water quality model, Soil and Water Assessment Tool, to investigate the influence of PS and NPS pollution on the water quality of the East River (Dongjiang in Chinese) in southern China. Our results indicate that NPS pollution was the dominant contribution (>94%) to nutrient loads except for mineral phosphorus (50%). A comprehensive Water Quality Index (WQI) computed using eight key water quality variables demonstrates that water quality is better upstream than downstream despite the higher level of ammonium nitrogen found in upstream waters. Also, the temporal (seasonal) and spatial distributions of nutrient loads clearly indicate the critical time period (from late dry season to early wet season) and pollution source areas within the basin (middle and downstream agricultural lands), which resource managers can use to accomplish substantial reduction of NPS pollutant loadings. Overall, this study helps our understanding of the relationship between human activities and pollutant loads and further contributes to decision support for local watershed managers to protect water quality in this region. In particular, the methods presented such as integrating WQI with watershed modeling and identifying the critical time period and pollutions source areas can be valuable for other researchers worldwide.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ecological Indicators","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2013.04.002","usgsCitation":"Wu, Y., and Chen, J., 2013, Investigating the effects of point source and nonpoint source pollution on the water quality of the East River (Dongjiang) in South China: Ecological Indicators, v. 32, p. 294-304, https://doi.org/10.1016/j.ecolind.2013.04.002.","productDescription":"11 p.","startPage":"294","endPage":"304","ipdsId":"IP-044856","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":272033,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":272011,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.ecolind.2013.04.002"}],"country":"China","otherGeospatial":"Dongjiang","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 73.5,18.2 ], [ 73.5,53.6 ], [ 134.8,53.6 ], [ 134.8,18.2 ], [ 73.5,18.2 ] ] ] } } ] }","volume":"32","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"518a145be4b061e1bd53333f","contributors":{"authors":[{"text":"Wu, Yiping ywu@usgs.gov","contributorId":987,"corporation":false,"usgs":true,"family":"Wu","given":"Yiping","email":"ywu@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":478440,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chen, Ji","contributorId":101960,"corporation":false,"usgs":true,"family":"Chen","given":"Ji","email":"","affiliations":[],"preferred":false,"id":478441,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70045851,"text":"sir20135071 - 2013 - Continuous real-time water-quality monitoring and regression analysis to compute constituent concentrations and loads in the North Fork Ninnescah River upstream from Cheney Reservoir, south-central Kansas, 1999–2012","interactions":[],"lastModifiedDate":"2013-05-07T13:25:37","indexId":"sir20135071","displayToPublicDate":"2013-05-07T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-5071","title":"Continuous real-time water-quality monitoring and regression analysis to compute constituent concentrations and loads in the North Fork Ninnescah River upstream from Cheney Reservoir, south-central Kansas, 1999–2012","docAbstract":"Cheney Reservoir, located in south-central Kansas, is the primary water supply for the city of Wichita. The U.S. Geological Survey has operated a continuous real-time water-quality monitoring station since 1998 on the North Fork Ninnescah River, the main source of inflow to Cheney Reservoir. Continuously measured water-quality physical properties include streamflow, specific conductance, pH, water temperature, dissolved oxygen, and turbidity. Discrete water-quality samples were collected during 1999 through 2009 and analyzed for sediment, nutrients, bacteria, and other water-quality constituents. Regression models were developed to establish relations between discretely sampled constituent concentrations and continuously measured physical properties to compute concentrations of those constituents of interest that are not easily measured in real time because of limitations in sensor technology and fiscal constraints. Regression models were published in 2006 that were based on data collected during 1997 through 2003. This report updates those models using discrete and continuous data collected during January 1999 through December 2009. Models also were developed for four new constituents, including additional nutrient species and indicator bacteria. In addition, a conversion factor of 0.68 was established to convert the Yellow Springs Instruments (YSI) model 6026 turbidity sensor measurements to the newer YSI model 6136 sensor at the North Ninnescah River upstream from Cheney Reservoir site. Newly developed models and 14 years of hourly continuously measured data were used to calculate selected constituent concentrations and loads during January 1999 through December 2012. The water-quality information in this report is important to the city of Wichita because it allows the concentrations of many potential pollutants of interest to Cheney Reservoir, including nutrients and sediment, to be estimated in real time and characterized over conditions and time scales that would not be possible otherwise. In general, model forms and the amount of variance explained by the models was similar between the original and updated models. The amount of variance explained by the updated models changed by 10 percent or less relative to the original models. Total nitrogen, nitrate, organic nitrogen, E. coli bacteria, and total organic carbon models were newly developed for this report. Additional data collection over a wider range of hydrological conditions facilitated the development of these models. The nitrate model is particularly important because it allows for comparison to Cheney Reservoir Task Force goals. Mean hourly computed total suspended solids concentration during 1999 through 2012 was 54 milligrams per liter (mg/L). The total suspended solids load during 1999 through 2012 was 174,031 tons. On an average annual basis, the Cheney Reservoir Task Force runoff (550 mg/L) and long-term (100 mg/L) total suspended solids goals were never exceeded, but the base flow goal was exceeded every year during 1999 through 2012. Mean hourly computed nitrate concentration was 1.08 mg/L during 1999 through 2012. The total nitrate load during 1999 through 2012 was 1,361 tons. On an annual average basis, the Cheney Reservoir Task Force runoff (6.60 mg/L) nitrate goal was never exceeded, the long-term goal (1.20 mg/L) was exceeded only in 2012, and the base flow goal of 0.25 mg/L was exceeded every year. Mean nitrate concentrations that were higher during base flow, rather than during runoff conditions, suggest that groundwater sources are the main contributors of nitrate to the North Fork Ninnescah River above Cheney Reservoir. Mean hourly computed phosphorus concentration was 0.14 mg/L during 1999 through 2012. The total phosphorus load during 1999 through 2012 was 328 tons. On an average annual basis, the Cheney Reservoir Task Force runoff goal of 0.40 mg/L for total phosphorus was exceeded in 2002, the year with the largest yearly mean turbidity, and the long-term goal (0.10 mg/L) was exceeded in every year except 2011 and 2012, the years with the smallest mean streamflows. The total phosphorus base flow goal of 0.05 mg/L was exceeded every year. Given that base flow goals for total suspended solids, nitrate, and total phosphorus were exceeded every year despite hydrologic conditions, the established base flow goals are either unattainable or substantially more best management practices will need to be implemented to attain them. On an annual average basis, no discernible patterns were evident in total suspended sediment, nitrate, and total phosphorus concentrations or loads over time, in large part because of hydrologic variability. However, more rigorous statistical analyses are required to evaluate temporal trends. A more rigorous analysis of temporal trends will allow evaluation of watershed investments in best management practices.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135071","collaboration":"Prepared in cooperation with the city of Wichita, Kansas","usgsCitation":"Stone, M.L., Graham, J.L., and Gatotho, J.W., 2013, Continuous real-time water-quality monitoring and regression analysis to compute constituent concentrations and loads in the North Fork Ninnescah River upstream from Cheney Reservoir, south-central Kansas, 1999–2012: U.S. Geological Survey Scientific Investigations Report 2013-5071, viii, 46 p., https://doi.org/10.3133/sir20135071.","productDescription":"viii, 46 p.","numberOfPages":"54","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":272007,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135071.gif"},{"id":272005,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5071/"},{"id":272006,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5071/sir13-5071.pdf"}],"country":"United States","state":"Kansas","otherGeospatial":"Cheney Reservoir;North Fork Ninnescah River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -99.25,37.5 ], [ -99.25,38.16 ], [ -97.75,38.16 ], [ -97.75,37.5 ], [ -99.25,37.5 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"518a145be4b061e1bd53333b","contributors":{"authors":[{"text":"Stone, Mandy L. 0000-0002-6711-1536 mstone@usgs.gov","orcid":"https://orcid.org/0000-0002-6711-1536","contributorId":4409,"corporation":false,"usgs":true,"family":"Stone","given":"Mandy","email":"mstone@usgs.gov","middleInitial":"L.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":478424,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Graham, Jennifer L. 0000-0002-6420-9335 jlgraham@usgs.gov","orcid":"https://orcid.org/0000-0002-6420-9335","contributorId":1769,"corporation":false,"usgs":true,"family":"Graham","given":"Jennifer","email":"jlgraham@usgs.gov","middleInitial":"L.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":478423,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gatotho, Jackline W.","contributorId":76616,"corporation":false,"usgs":true,"family":"Gatotho","given":"Jackline","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":478425,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70045859,"text":"70045859 - 2013 - Analyzing the water budget and hydrological characteristics and responses to land use in a monsoonal climate river basin in South China","interactions":[],"lastModifiedDate":"2013-06-17T09:24:06","indexId":"70045859","displayToPublicDate":"2013-05-07T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1547,"text":"Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Analyzing the water budget and hydrological characteristics and responses to land use in a monsoonal climate river basin in South China","docAbstract":"Hydrological models have been increasingly used by hydrologists and water resource managers to understand natural processes and human activities that affect watersheds. In this study, we use the physically based model, Soil and Water Assessment Tool (SWAT), to investigate the hydrological processes in the East River Basin in South China, a coastal area dominated by monsoonal climate. The SWAT model was calibrated using 8-year (1973–1980) record of the daily streamflow at the basin outlet (Boluo station), and then validated using data collected during the subsequent 8 years (1981–1988). Statistical evaluation shows that SWAT can consistently simulate the streamflow of the East River with monthly Nash–Sutcliffe efficiencies of 0.93 for calibration and 0.90 for validation at the Boluo station. We analyzed the model simulations with calibrated parameters, presented the spatiotemporal distribution of the key hydrological components, and quantified their responses to different land uses. Watershed managers can use the results of this study to understand hydrological features and evaluate water resources of the East River in terms of sustainable development and effective management.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Environmental Management","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","doi":"10.1007/s00267-013-0045-5","usgsCitation":"Wu, Y., and Chen, J., 2013, Analyzing the water budget and hydrological characteristics and responses to land use in a monsoonal climate river basin in South China: Environmental Management, v. 51, no. 6, p. 1174-1186, https://doi.org/10.1007/s00267-013-0045-5.","productDescription":"13 p.","startPage":"1174","endPage":"1186","ipdsId":"IP-042191","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":272031,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":272012,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s00267-013-0045-5"}],"country":"China","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 73.5,18.2 ], [ 73.5,53.6 ], [ 134.8,53.6 ], [ 134.8,18.2 ], [ 73.5,18.2 ] ] ] } } ] }","volume":"51","issue":"6","noUsgsAuthors":false,"publicationDate":"2013-04-23","publicationStatus":"PW","scienceBaseUri":"518a1451e4b061e1bd533337","contributors":{"authors":[{"text":"Wu, Yiping ywu@usgs.gov","contributorId":987,"corporation":false,"usgs":true,"family":"Wu","given":"Yiping","email":"ywu@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":478445,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chen, Ji","contributorId":101960,"corporation":false,"usgs":true,"family":"Chen","given":"Ji","email":"","affiliations":[],"preferred":false,"id":478446,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70042647,"text":"70042647 - 2013 - Practical guidance on characterizing availability in resource selection functions under a use-availability design","interactions":[],"lastModifiedDate":"2013-07-15T09:20:03","indexId":"70042647","displayToPublicDate":"2013-05-07T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1465,"text":"Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Practical guidance on characterizing availability in resource selection functions under a use-availability design","docAbstract":"Habitat selection is a fundamental aspect of animal ecology, the understanding of which is critical to management and conservation. Global positioning system data from animals allow fine-scale assessments of habitat selection and typically are analyzed in a use-availability framework, whereby animal locations are contrasted with random locations (the availability sample). Although most use-availability methods are in fact spatial point process models, they often are fit using logistic regression. This framework offers numerous methodological challenges, for which the literature provides little guidance. Specifically, the size and spatial extent of the availability sample influences coefficient estimates potentially causing interpretational bias. We examined the influence of availability on statistical inference through simulations and analysis of serially correlated mule deer GPS data. Bias in estimates arose from incorrectly assessing and sampling the spatial extent of availability. Spatial autocorrelation in covariates, which is common for landscape characteristics, exacerbated the error in availability sampling leading to increased bias. These results have strong implications for habitat selection analyses using GPS data, which are increasingly prevalent in the literature. We recommend researchers assess the sensitivity of their results to their availability sample and, where bias is likely, take care with interpretations and use cross validation to assess robustness.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ecology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Ecological Society of America","doi":"10.1890/12-1688.1","usgsCitation":"Northrup, J.M., Hooten, M., Anderson, C.R., and Wittemyer, G., 2013, Practical guidance on characterizing availability in resource selection functions under a use-availability design: Ecology, v. 94, no. 7, p. 1456-1463, https://doi.org/10.1890/12-1688.1.","productDescription":"8 p.","startPage":"1456","endPage":"1463","ipdsId":"IP-040982","costCenters":[{"id":189,"text":"Colorado Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true}],"links":[{"id":473839,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1890/12-1688.1","text":"Publisher Index Page"},{"id":271952,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":271946,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1890/12-1688.1"}],"volume":"94","issue":"7","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"518a145de4b061e1bd53334b","contributors":{"authors":[{"text":"Northrup, Joseph M.","contributorId":101965,"corporation":false,"usgs":true,"family":"Northrup","given":"Joseph","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":471981,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hooten, Mevin 0000-0002-1614-723X mhooten@usgs.gov","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":2958,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","email":"mhooten@usgs.gov","affiliations":[{"id":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":471978,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anderson, Charles R. Jr.","contributorId":75042,"corporation":false,"usgs":true,"family":"Anderson","given":"Charles","suffix":"Jr.","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":471980,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wittemyer, George","contributorId":25058,"corporation":false,"usgs":true,"family":"Wittemyer","given":"George","affiliations":[],"preferred":false,"id":471979,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70045855,"text":"70045855 - 2013 - Parallelization of a hydrological model using the message passing interface","interactions":[],"lastModifiedDate":"2013-05-07T14:33:07","indexId":"70045855","displayToPublicDate":"2013-05-07T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1551,"text":"Environmental Modelling and Software","active":true,"publicationSubtype":{"id":10}},"title":"Parallelization of a hydrological model using the message passing interface","docAbstract":"With the increasing knowledge about the natural processes, hydrological models such as the Soil and Water Assessment Tool (SWAT) are becoming larger and more complex with increasing computation time. Additionally, other procedures such as model calibration, which may require thousands of model iterations, can increase running time and thus further reduce rapid modeling and analysis. Using the widely-applied SWAT as an example, this study demonstrates how to parallelize a serial hydrological model in a Windows® environment using a parallel programing technology—Message Passing Interface (MPI). With a case study, we derived the optimal values for the two parameters (the number of processes and the corresponding percentage of work to be distributed to the master process) of the parallel SWAT (P-SWAT) on an ordinary personal computer and a work station. Our study indicates that model execution time can be reduced by 42%–70% (or a speedup of 1.74–3.36) using multiple processes (two to five) with a proper task-distribution scheme (between the master and slave processes). Although the computation time cost becomes lower with an increasing number of processes (from two to five), this enhancement becomes less due to the accompanied increase in demand for message passing procedures between the master and all slave processes. Our case study demonstrates that the P-SWAT with a five-process run may reach the maximum speedup, and the performance can be quite stable (fairly independent of a project size). Overall, the P-SWAT can help reduce the computation time substantially for an individual model run, manual and automatic calibration procedures, and optimization of best management practices. In particular, the parallelization method we used and the scheme for deriving the optimal parameters in this study can be valuable and easily applied to other hydrological or environmental models.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Environmental Modelling and Software","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.envsoft.2013.02.002","usgsCitation":"Wu, Y., Li, T., Sun, L., and Chen, J., 2013, Parallelization of a hydrological model using the message passing interface: Environmental Modelling and Software, v. 43, p. 124-132, https://doi.org/10.1016/j.envsoft.2013.02.002.","productDescription":"9 p.","startPage":"124","endPage":"132","ipdsId":"IP-044027","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":272036,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":272010,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.envsoft.2013.02.002"}],"volume":"43","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"518a145de4b061e1bd533347","contributors":{"authors":[{"text":"Wu, Yiping ywu@usgs.gov","contributorId":987,"corporation":false,"usgs":true,"family":"Wu","given":"Yiping","email":"ywu@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":478436,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Li, Tiejian","contributorId":25437,"corporation":false,"usgs":true,"family":"Li","given":"Tiejian","email":"","affiliations":[],"preferred":false,"id":478438,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sun, Liqun","contributorId":18249,"corporation":false,"usgs":true,"family":"Sun","given":"Liqun","email":"","affiliations":[],"preferred":false,"id":478437,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chen, Ji","contributorId":101960,"corporation":false,"usgs":true,"family":"Chen","given":"Ji","email":"","affiliations":[],"preferred":false,"id":478439,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70045161,"text":"70045161 - 2013 - Survival and behavior of Chinese mystery snails (Bellamya chinensis) in response to simulated water body drawdowns and extended air exposure","interactions":[],"lastModifiedDate":"2013-07-01T09:45:32","indexId":"70045161","displayToPublicDate":"2013-05-07T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2655,"text":"Management of Biological Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Survival and behavior of Chinese mystery snails (Bellamya chinensis) in response to simulated water body drawdowns and extended air exposure","docAbstract":"Nonnative invasive mollusks degrade aquatic ecosystems and induce economic losses worldwide. Extended air exposure through water body drawdown is one management action used for control. In North America, the Chinese mystery snail (Bellamya chinensis) is an invasive aquatic snail with an expanding range, but eradication methods for this species are not well documented. We assessed the ability of B. chinensis to survive different durations of air exposure, and observed behavioral responses prior to, during, and following desiccation events. Individual B. chinensis specimens survived air exposure in a laboratory setting for > 9 weeks, and survivorship was greater among adults than juveniles. Several B. chinensis specimens responded to desiccation by sealing their opercula and/or burrowing in mud substrate. Our results indicate that drawdowns alone may not be an effective means of eliminating B. chinensis. This study lays the groundwork for future management research that may determine the effectiveness of drawdowns when combined with factors such as extreme temperatures, predation, or molluscicides.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Management of Biological Invasions","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"REABIC","doi":"10.3391/mbi.2013.4.2.04","usgsCitation":"Unstad, K.M., Uden, D.R., Allen, C.R., Chaine, N.M., Haak, D.M., Kill, R.A., Pope, K.L., Stephen, B., and Wong, A., 2013, Survival and behavior of Chinese mystery snails (Bellamya chinensis) in response to simulated water body drawdowns and extended air exposure: Management of Biological Invasions, v. 4, no. 2, p. 123-127, https://doi.org/10.3391/mbi.2013.4.2.04.","productDescription":"5 p.","startPage":"123","endPage":"127","ipdsId":"IP-044849","costCenters":[{"id":463,"text":"Nebraska Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true}],"links":[{"id":473835,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3391/mbi.2013.4.2.04","text":"Publisher Index Page"},{"id":272050,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":274326,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.3391/mbi.2013.4.2.04"}],"volume":"4","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"518a1460e4b061e1bd53335f","contributors":{"authors":[{"text":"Unstad, Kody M.","contributorId":28491,"corporation":false,"usgs":true,"family":"Unstad","given":"Kody","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":476973,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Uden, Daniel R.","contributorId":74258,"corporation":false,"usgs":true,"family":"Uden","given":"Daniel","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":476977,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Allen, Craig R. 0000-0001-8655-8272 allencr@usgs.gov","orcid":"https://orcid.org/0000-0001-8655-8272","contributorId":1979,"corporation":false,"usgs":true,"family":"Allen","given":"Craig","email":"allencr@usgs.gov","middleInitial":"R.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":476972,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chaine, Noelle M.","contributorId":48456,"corporation":false,"usgs":true,"family":"Chaine","given":"Noelle","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":476974,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Haak, Danielle M.","contributorId":73078,"corporation":false,"usgs":true,"family":"Haak","given":"Danielle","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":476976,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kill, Robert A.","contributorId":103538,"corporation":false,"usgs":true,"family":"Kill","given":"Robert","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":476979,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pope, Kevin L. 0000-0003-1876-1687 kpope@usgs.gov","orcid":"https://orcid.org/0000-0003-1876-1687","contributorId":1574,"corporation":false,"usgs":true,"family":"Pope","given":"Kevin","email":"kpope@usgs.gov","middleInitial":"L.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":476971,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Stephen, Bruce J.","contributorId":54862,"corporation":false,"usgs":true,"family":"Stephen","given":"Bruce J.","affiliations":[],"preferred":false,"id":476975,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Wong, Alec","contributorId":79005,"corporation":false,"usgs":true,"family":"Wong","given":"Alec","email":"","affiliations":[],"preferred":false,"id":476978,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70045818,"text":"70045818 - 2013 - Present, future, and novel bioclimates of the San Francisco, California region","interactions":[],"lastModifiedDate":"2018-09-27T10:54:26","indexId":"70045818","displayToPublicDate":"2013-05-07T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Present, future, and novel bioclimates of the San Francisco, California region","docAbstract":"Bioclimates are syntheses of climatic variables into biologically relevant categories that facilitate comparative studies of biotic responses to climate conditions. Isobioclimates, unique combinations of bioclimatic indices (continentality, ombrotype, and thermotype), were constructed for northern California coastal ranges based on the Rivas-Martinez worldwide bioclimatic classification system for the end of the 20th century climatology (1971–2000) and end of the 21st century climatology (2070–2099) using two models, Geophysical Fluid Dynamics Laboratory (GFDL) model and the Parallel Climate Model (PCM), under the medium-high A2 emission scenario. The digitally mapped results were used to 1) assess the relative redistribution of isobioclimates and their magnitude of change, 2) quantify the loss of isobioclimates into the future, 3) identify and locate novel isobioclimates projected to appear, and 4) explore compositional change in vegetation types among analog isobioclimate patches. This study used downscaled climate variables to map the isobioclimates at a fine spatial resolution −270 m grid cells. Common to both models of future climate was a large change in thermotype. Changes in ombrotype differed among the two models. The end of 20th century climatology has 83 isobioclimates covering the 63,000 km2 study area. In both future projections 51 of those isobioclimates disappear over 40,000 km2. The ordination of vegetation-bioclimate relationships shows very strong correlation of Rivas-Martinez indices with vegetation distribution and composition. Comparisons of vegetation composition among analog patches suggest that vegetation change will be a local rearrangement of species already in place rather than one requiring long distance dispersal. The digitally mapped results facilitate comparison with other Mediterranean regions. Major remaining challenges include predicting vegetation composition of novel isobioclimates and developing metrics to compare differences in climate space.","language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pone.0058450","usgsCitation":"Torregrosa, A.A., Taylor, M.D., Flint, L.E., and Flint, A.L., 2013, Present, future, and novel bioclimates of the San Francisco, California region: PLoS ONE, v. 8, no. 3, p. 1-14, https://doi.org/10.1371/journal.pone.0058450.","productDescription":"e58450; 14 p.","startPage":"1","endPage":"14","ipdsId":"IP-039134","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":473836,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0058450","text":"Publisher Index Page"},{"id":271907,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":271906,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1371/journal.pone.0058450"}],"country":"United States","state":"California","city":"San Francisco","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.4,32.5 ], [ -124.4,42.0 ], [ -114.1,42.0 ], [ -114.1,32.5 ], [ -124.4,32.5 ] ] ] } } ] }","volume":"8","issue":"3","noUsgsAuthors":false,"publicationDate":"2013-03-20","publicationStatus":"PW","scienceBaseUri":"518a145ee4b061e1bd53334f","contributors":{"authors":[{"text":"Torregrosa, Alicia A. 0000-0001-7361-2241 atorregrosa@usgs.gov","orcid":"https://orcid.org/0000-0001-7361-2241","contributorId":3471,"corporation":false,"usgs":true,"family":"Torregrosa","given":"Alicia","email":"atorregrosa@usgs.gov","middleInitial":"A.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":478389,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Taylor, Maxwell D.","contributorId":6360,"corporation":false,"usgs":true,"family":"Taylor","given":"Maxwell","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":478390,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Flint, Lorraine E. 0000-0002-7868-441X lflint@usgs.gov","orcid":"https://orcid.org/0000-0002-7868-441X","contributorId":1184,"corporation":false,"usgs":true,"family":"Flint","given":"Lorraine","email":"lflint@usgs.gov","middleInitial":"E.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":478387,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Flint, Alan L. 0000-0002-5118-751X aflint@usgs.gov","orcid":"https://orcid.org/0000-0002-5118-751X","contributorId":1492,"corporation":false,"usgs":true,"family":"Flint","given":"Alan","email":"aflint@usgs.gov","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":478388,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70044625,"text":"70044625 - 2013 - Occurrence and partitioning of antibiotic compounds found in the water column and bottom sediments from a stream receiving two wastewater treatment plant effluents in northern New Jersey, 2008.","interactions":[],"lastModifiedDate":"2019-06-03T11:43:40","indexId":"70044625","displayToPublicDate":"2013-05-07T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Occurrence and partitioning of antibiotic compounds found in the water column and bottom sediments from a stream receiving two wastewater treatment plant effluents in northern New Jersey, 2008.","docAbstract":"An urban watershed in northern New Jersey was studied to determine the presence of four classes of antibiotic compounds (macrolides, fluoroquinolones, sulfonamides, and tetracyclines) and six degradates in the water column and bottom sediments upstream and downstream from the discharges of two wastewater treatment plants (WWTPs) and a drinking-water intake (DWI). Many antibiotic compounds in the four classes not removed by conventional WWTPs enter receiving waters and partition to stream sediments. Samples were collected at nine sampling locations on 2 days in September 2008. Two of the nine sampling locations were background sites upstream from two WWTP discharges on Hohokus Brook. Another background site was located upstream from a DWI on the Saddle River above the confluence with Hohokus Brook. Because there is a weir downstream of the confluence of Hohokus Brook and Saddle River, the DWI receives water from Hohokus Brook at low stream flows. Eight antibiotic compounds (azithromycin (maximum concentration 0.24 μg/L), ciprofloxacin (0.08 μg/L), enrofloxacin (0.015 μg/L), erythromycin (0.024 μg/L), ofloxacin (0.92 μg/L), sulfamethazine (0.018 μg/L), sulfamethoxazole (0.25 μg/L), and trimethoprim (0.14 μg/L)) and a degradate (erythromycin-H2O (0.84 μg/L)) were detected in the water samples from the sites downstream from the WWTP discharges. The concentrations of six of the eight detected compounds and the detected degradate compound decreased with increasing distance downstream from the WWTP discharges. Azithromycin, ciprofloxacin, ofloxacin, and trimethoprim were detected in stream-bottom sediments. The concentrations of three of the four compounds detected in sediments were highest at a sampling site located downstream from the WWTP discharges. Trimethoprim was detected in the sediments from a background site. Pseudo-partition coefficients normalized for streambed sediment organic carbon concentration were calculated for azithromycin, ciprofloxacin, and ofloxacin. Generally, there was good agreement between the decreasing order of the pseudo-partition coefficients in this study and the order reported in the literature.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Science of the Total Environment","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2013.03.076","usgsCitation":"Gibs, J., Heckathorn, H.A., Meyer, M.T., Klapinski, F.R., Alebus, M., and Lippincott, R., 2013, Occurrence and partitioning of antibiotic compounds found in the water column and bottom sediments from a stream receiving two wastewater treatment plant effluents in northern New Jersey, 2008.: Science of the Total Environment, v. 458-460, p. 107-116, https://doi.org/10.1016/j.scitotenv.2013.03.076.","productDescription":"10 p.","startPage":"107","endPage":"116","numberOfPages":"10","temporalStart":"2008-01-01","temporalEnd":"2008-12-31","ipdsId":"IP-035723","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":271932,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":271919,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.scitotenv.2013.03.076"}],"country":"United States","state":"New Jersey","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -74.149647,40.827449 ], [ -74.149647,41.079998 ], [ -73.999958,41.079998 ], [ -73.999958,40.827449 ], [ -74.149647,40.827449 ] ] ] } } ] }","volume":"458-460","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"518a145ce4b061e1bd533343","contributors":{"authors":[{"text":"Gibs, Jacob jgibs@usgs.gov","contributorId":1729,"corporation":false,"usgs":true,"family":"Gibs","given":"Jacob","email":"jgibs@usgs.gov","affiliations":[],"preferred":true,"id":476034,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Heckathorn, Heather A. haheck@usgs.gov","contributorId":1728,"corporation":false,"usgs":true,"family":"Heckathorn","given":"Heather","email":"haheck@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":476033,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Meyer, Michael T. 0000-0001-6006-7985 mmeyer@usgs.gov","orcid":"https://orcid.org/0000-0001-6006-7985","contributorId":866,"corporation":false,"usgs":true,"family":"Meyer","given":"Michael","email":"mmeyer@usgs.gov","middleInitial":"T.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":476032,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Klapinski, Frank R.","contributorId":102767,"corporation":false,"usgs":true,"family":"Klapinski","given":"Frank","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":476036,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Alebus, Marzooq","contributorId":15497,"corporation":false,"usgs":true,"family":"Alebus","given":"Marzooq","email":"","affiliations":[],"preferred":false,"id":476035,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lippincott, Robert","contributorId":103550,"corporation":false,"usgs":true,"family":"Lippincott","given":"Robert","email":"","affiliations":[],"preferred":false,"id":476037,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70042106,"text":"70042106 - 2013 - Reconciling resource utilization and resource selection functions","interactions":[],"lastModifiedDate":"2013-10-30T10:08:14","indexId":"70042106","displayToPublicDate":"2013-05-07T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2158,"text":"Journal of Animal Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Reconciling resource utilization and resource selection functions","docAbstract":"Summary: 1. Analyses based on utilization distributions (UDs) have been ubiquitous in animal space use studies, largely because they are computationally straightforward and relatively easy to employ. Conventional applications of resource utilization functions (RUFs) suggest that estimates of UDs can be used as response variables in a regression involving spatial covariates of interest. 2. It has been claimed that contemporary implementations of RUFs can yield inference about resource selection, although to our knowledge, an explicit connection has not been described. 3. We explore the relationships between RUFs and resource selection functions from a hueristic and simulation perspective. We investigate several sources of potential bias in the estimation of resource selection coefficients using RUFs (e.g. the spatial covariance modelling that is often used in RUF analyses). 4. Our findings illustrate that RUFs can, in fact, serve as approximations to RSFs and are capable of providing inference about resource selection, but only with some modification and under specific circumstances. 5. Using real telemetry data as an example, we provide guidance on which methods for estimating resource selection may be more appropriate and in which situations. In general, if telemetry data are assumed to arise as a point process, then RSF methods may be preferable to RUFs; however, modified RUFs may provide less biased parameter estimates when the data are subject to location error.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Animal Ecology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1111/1365-2656.12080","usgsCitation":"Hooten, M., Hanks, E., Johnson, D., and Alldredge, M.W., 2013, Reconciling resource utilization and resource selection functions: Journal of Animal Ecology, v. 52, no. 6, p. 1146-1154, https://doi.org/10.1111/1365-2656.12080.","productDescription":"9 p.","startPage":"1146","endPage":"1154","numberOfPages":"9","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-038934","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":473837,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/1365-2656.12080","text":"Publisher Index Page"},{"id":271989,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":271986,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/1365-2656.12080"}],"volume":"52","issue":"6","noUsgsAuthors":false,"publicationDate":"2013-04-09","publicationStatus":"PW","scienceBaseUri":"518a145ee4b061e1bd533353","contributors":{"authors":[{"text":"Hooten, Mevin 0000-0002-1614-723X mhooten@usgs.gov","orcid":"https://orcid.org/0000-0002-1614-723X","contributorId":2958,"corporation":false,"usgs":true,"family":"Hooten","given":"Mevin","email":"mhooten@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":12963,"text":"Colorado Cooperative Fish and Wildlife Research Unit, Fort Collins, CO","active":true,"usgs":false}],"preferred":true,"id":470778,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hanks, Ephraim M.","contributorId":104630,"corporation":false,"usgs":true,"family":"Hanks","given":"Ephraim M.","affiliations":[],"preferred":false,"id":470781,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Devin S.","contributorId":47524,"corporation":false,"usgs":true,"family":"Johnson","given":"Devin S.","affiliations":[],"preferred":false,"id":470779,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Alldredge, Mat W.","contributorId":65361,"corporation":false,"usgs":true,"family":"Alldredge","given":"Mat","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":470780,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70045884,"text":"sir20125242 - 2013 - Simulations of groundwater flow, transport, and age in Albuquerque, New Mexico, for a study of transport of anthropogenic and natural contaminants (TANC) to public-supply wells","interactions":[],"lastModifiedDate":"2013-05-07T21:26:46","indexId":"sir20125242","displayToPublicDate":"2013-05-07T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012-5242","title":"Simulations of groundwater flow, transport, and age in Albuquerque, New Mexico, for a study of transport of anthropogenic and natural contaminants (TANC) to public-supply wells","docAbstract":"Vulnerability to contamination from manmade and natural sources can be characterized by the groundwater-age distribution measured in a supply well and the associated implications for the source depths of the withdrawn water. Coupled groundwater flow and transport models were developed to simulate the transport of the geochemical age-tracers carbon-14, tritium, and three chlorofluorocarbon species to public-supply wells in Albuquerque, New Mexico. A separate, regional-scale simulation of transport of carbon-14 that used the flow-field computed by a previously documented regional groundwater flow model was calibrated and used to specify the initial concentrations of carbon-14 in the local-scale transport model. Observations of the concentrations of each of the five chemical species, in addition to water-level observations and measurements of intra-borehole flow within a public-supply well, were used to calibrate parameters of the local-scale groundwater flow and transport models.\n\nThe calibrated groundwater flow model simulates the mixing of “young” groundwater, which entered the groundwater flow system after 1950 as recharge at the water table, with older resident groundwater that is more likely associated with natural contaminants. Complexity of the aquifer system in the zone of transport between the water table and public-supply well screens was simulated with a geostatistically generated stratigraphic realization based upon observed lithologic transitions at borehole control locations. Because effective porosity was simulated as spatially uniform, the simulated age tracers are more efficiently transported through the portions of the simulated aquifer with relatively higher simulated hydraulic conductivity. Non-pumping groundwater wells with long screens that connect aquifer intervals having different hydraulic heads can provide alternate pathways for contaminant transport that are faster than the advective transport through the aquifer material. Simulation of flow and transport through these wells requires time discretization that adequately represents periods of pumping and non-pumping. The effects of intra-borehole flow are not fully represented in the simulation because it employs seasonal stress periods, which are longer than periods of pumping and non-pumping. Further simulations utilizing daily pumpage data and model stress periods may help quantify the relative effects of intra-borehole versus advective aquifer flow on the transport of contaminants near the public-supply wells. The fraction of young water withdrawn from the studied supply well varies with simulated pumping rates due to changes in the relative contributions to flow from different aquifer intervals.\n\nThe advective transport of dissolved solutes from a known contaminant source to the public-supply wells was simulated by using particle-tracking. Because of the transient groundwater flow field, scenarios with alternative contaminant release times result in different simulated-particle fates, most of which are withdrawn from the aquifer at wells that are between the source and the studied supply well. The relatively small effective porosity required to simulate advective transport from the simulated contaminant source to the studied supply well is representative of a preferential pathway and not the predominant aquifer effective porosity that was estimated by the calibration of the model to observed chemical-tracer concentrations.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125242","collaboration":"National Water-Quality Assessment Program","usgsCitation":"Heywood, C.E., 2013, Simulations of groundwater flow, transport, and age in Albuquerque, New Mexico, for a study of transport of anthropogenic and natural contaminants (TANC) to public-supply wells: U.S. Geological Survey Scientific Investigations Report 2012-5242, ix, 51 p., https://doi.org/10.3133/sir20125242.","productDescription":"ix, 51 p.","numberOfPages":"65","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true}],"links":[{"id":272049,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20125242.gif"},{"id":272047,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5242/"},{"id":272048,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5242/pdf/sir2012-5242.pdf"}],"country":"United States","state":"New Mexico","city":"Albuquerque","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -106.088,34.95 ], [ -106.088,35.22 ], [ -106.47,35.22 ], [ -106.47,34.95 ], [ -106.088,34.95 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"518a145fe4b061e1bd533357","contributors":{"authors":[{"text":"Heywood, Charles E. cheywood@usgs.gov","contributorId":2043,"corporation":false,"usgs":true,"family":"Heywood","given":"Charles","email":"cheywood@usgs.gov","middleInitial":"E.","affiliations":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":478477,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70045873,"text":"ofr20131017 - 2013 - Water-quality, bed-sediment, and biological data (October 2010 through September 2011) and statistical summaries of data for streams in the Clark Fork basin, Montana","interactions":[],"lastModifiedDate":"2013-05-07T15:55:52","indexId":"ofr20131017","displayToPublicDate":"2013-05-07T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-1017","title":"Water-quality, bed-sediment, and biological data (October 2010 through September 2011) and statistical summaries of data for streams in the Clark Fork basin, Montana","docAbstract":"Water, bed sediment, and biota were sampled in streams from Butte to near Missoula, Montana, as part of a monitoring program in the upper Clark Fork basin of western Montana; additional water samples were collected from near Galen to near Missoula at select sites as part of a supplemental sampling program. The sampling program was conducted by the U.S. Geological Survey in cooperation with the U.S. Environmental Protection Agency to characterize aquatic resources in the Clark Fork basin, with emphasis on trace elements associated with historic mining and smelting activities. Sampling sites were located on the Clark Fork and selected tributaries. Water samples were collected periodically at 20 sites from October 2010 through September 2011. Bed-sediment and biota samples were collected once at 14 sites during August 2011. This report presents the analytical results and quality-assurance data for water-quality, bed-sediment, and biota samples collected at sites from October 2010 through September 2011. Water-quality data include concentrations of selected major ions, trace elements, and suspended sediment. Turbidity was analyzed for water samples collected at the four sites where seasonal daily values of turbidity were being determined. Daily values of suspended-sediment concentration and suspended-sediment discharge were determined for four sites. Bed-sediment data include trace-element concentrations in the fine-grained fraction. Biological data include trace-element concentrations in whole-body tissue of aquatic benthic insects. Statistical summaries of water-quality, bed-sediment, and biological data for sites in the upper Clark Fork basin are provided for the period of record since 1985.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131017","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency","usgsCitation":"Dodge, K.A., Hornberger, M.I., and Dyke, J., 2013, Water-quality, bed-sediment, and biological data (October 2010 through September 2011) and statistical summaries of data for streams in the Clark Fork basin, Montana: U.S. Geological Survey Open-File Report 2013-1017, vi, 134 p., https://doi.org/10.3133/ofr20131017.","productDescription":"vi, 134 p.","numberOfPages":"142","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":400,"text":"Montana Water Science Center","active":false,"usgs":true}],"links":[{"id":272046,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131017.gif"},{"id":272044,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1017/"},{"id":272045,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1017/OF13-1017_508.pdf"}],"country":"United States","state":"Montana","otherGeospatial":"Clark Fork Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -0.01638888888888889,0.0011111111111111111 ], [ -0.01638888888888889,0.0011111111111111111 ], [ -0.01638888888888889,0.0011111111111111111 ], [ -0.01638888888888889,0.0011111111111111111 ], [ -0.01638888888888889,0.0011111111111111111 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"518a1460e4b061e1bd533363","contributors":{"authors":[{"text":"Dodge, Kent A. kdodge@usgs.gov","contributorId":1036,"corporation":false,"usgs":true,"family":"Dodge","given":"Kent","email":"kdodge@usgs.gov","middleInitial":"A.","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":478475,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hornberger, Michelle I. 0000-0002-7787-3446 mhornber@usgs.gov","orcid":"https://orcid.org/0000-0002-7787-3446","contributorId":1037,"corporation":false,"usgs":true,"family":"Hornberger","given":"Michelle","email":"mhornber@usgs.gov","middleInitial":"I.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":478476,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dyke, Jessica jldyke@usgs.gov","contributorId":1035,"corporation":false,"usgs":true,"family":"Dyke","given":"Jessica","email":"jldyke@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":false,"id":478474,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70045819,"text":"ds709T - 2013 - Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Herat mineral district in Afghanistan: Chapter T in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan","interactions":[],"lastModifiedDate":"2013-05-06T21:08:57","indexId":"ds709T","displayToPublicDate":"2013-05-06T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"709","chapter":"T","title":"Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Herat mineral district in Afghanistan: Chapter T in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan","docAbstract":"The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Herat mineral district, which has barium and limestone deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA,2007,2008,2009), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. For this particular area, PRISM image orthorectification was performed by the Alaska Satellite Facility, applying its photogrammetric software to PRISM stereo images with vertical control points obtained from the digital elevation database produced by the Shuttle Radar Topography Mission (Farr and others, 2007) and horizontal adjustments based on a controlled Landsat image base (Davis, 2006). The 10-m AVNIR multispectral imagery was then coregistered to the orthorectified PRISM images and individual multispectral and panchromatic images were mosaicked into single images of the entire area of interest. The image coregistration was facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band's picture element based on the digital values of all picture elements within a 1,000-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area's local zone (41 for Herat) and the WGS84 datum. The final image mosaics were subdivided into eight overlapping tiles or quadrants because of the large size of the target area. The eight image tiles (or quadrants) for the Herat area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image. Within the Herat study area, one subarea was designated for detailed field investigations (that is, the Barium-Limestone subarea); this subarea was extracted from the area's image mosaic and is provided as separate embedded geotiff images.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan (DS 709)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds709T","collaboration":"Prepared in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations and the Afghanistan Geological Survey. This report is Chapter T in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan. For more information, see: Data Series 709.","usgsCitation":"Davis, P.A., Arko, S.A., and Harbin, M., 2013, Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Herat mineral district in Afghanistan: Chapter T in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan: U.S. Geological Survey Data Series 709, Readme; 2 Maps: 11 x 8.5 inches and 97.39 x 69.63 inches; 18 Image Files; 18 Metadata Files; 1 Shapefile; DS 709, https://doi.org/10.3133/ds709T.","productDescription":"Readme; 2 Maps: 11 x 8.5 inches and 97.39 x 69.63 inches; 18 Image Files; 18 Metadata Files; 1 Shapefile; DS 709","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2006-01-24","costCenters":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"links":[{"id":271905,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":271896,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/709/t/"},{"id":271898,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/t/index_maps/Herat_Area-of-Interest_Index_Map.pdf"},{"id":271899,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/t/index_maps/Herat_Image_Index_Map.pdf"},{"id":271897,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/ds/709/t/1_readme.txt"},{"id":271900,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/709/t/index_maps/index_maps.html"},{"id":271901,"type":{"id":14,"text":"Image"},"url":"https://pubs.usgs.gov/ds/709/t/image_files/image_files.html"},{"id":271902,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/ds/709/t/metadata/metadata.html"},{"id":271903,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/ds/709/t/shapefiles/shapefiles.html"},{"id":271904,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/ds/709/index.html"}],"country":"Afghanistan","state":"Herat","otherGeospatial":"Herat Mineral District","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 60.9,34.25 ], [ 60.9,35.5 ], [ 63.1,35.5 ], [ 63.1,34.25 ], [ 60.9,34.25 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5188d465e4b023d2d75b9a38","contributors":{"authors":[{"text":"Davis, Philip A. pdavis@usgs.gov","contributorId":692,"corporation":false,"usgs":true,"family":"Davis","given":"Philip","email":"pdavis@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":478391,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Arko, Scott A.","contributorId":101929,"corporation":false,"usgs":true,"family":"Arko","given":"Scott","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":478393,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Harbin, Michelle L.","contributorId":20590,"corporation":false,"usgs":true,"family":"Harbin","given":"Michelle L.","affiliations":[],"preferred":false,"id":478392,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70045803,"text":"ofr20131097 - 2013 - Mercury and water-quality data from Rink Creek, Salmon River, and Good River, Glacier Bay National Park and Preserve, Alaska, November 2009-October 2011","interactions":[],"lastModifiedDate":"2013-05-06T12:39:33","indexId":"ofr20131097","displayToPublicDate":"2013-05-06T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-1097","title":"Mercury and water-quality data from Rink Creek, Salmon River, and Good River, Glacier Bay National Park and Preserve, Alaska, November 2009-October 2011","docAbstract":"Glacier Bay National Park and Preserve (GBNPP), Alaska, like many pristine high latitude areas, is exposed to atmospherically deposited contaminants such as mercury (Hg). Although the harmful effects of Hg are well established, information on this contaminant in southeast Alaska is scarce. Here, we assess the level of this contaminant in several aquatic components (water, sediments, and biological tissue) in three adjacent, small streams in GBNPP that drain contrasting landscapes but receive similar atmospheric inputs: Rink Creek, Salmon River, and Good River.\n\nTwenty water samples were collected from 2009 to 2011 and processed and analyzed for total mercury and methylmercury (filtered and particulate), and dissolved organic carbon quantity and quality. Ancillary stream water parameters (discharge, pH, dissolved oxygen, specific conductance, and temperature) were measured at the time of sampling. Major cations, anions, and nutrients were measured four times. In addition, total mercury was analyzed in streambed sediment in 2010 and in juvenile coho salmon and several taxa of benthic macroinvertebrates in the early summer of 2010 and 2011.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131097","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Nagorski, S.A., Neal, E., and Brabets, T.P., 2013, Mercury and water-quality data from Rink Creek, Salmon River, and Good River, Glacier Bay National Park and Preserve, Alaska, November 2009-October 2011: U.S. Geological Survey Open-File Report 2013-1097, vi, 20 p., https://doi.org/10.3133/ofr20131097.","productDescription":"vi, 20 p.","numberOfPages":"30","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2009-11-01","temporalEnd":"2011-10-31","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":271881,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131097.jpg"},{"id":271879,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1097/"},{"id":271880,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1097/pdf/ofr20131097.pdf"}],"country":"United States","state":"Alaska","otherGeospatial":"Glacier Bay National Park","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -138.22,58.43 ], [ -138.22,59.24 ], [ -135.78,59.24 ], [ -135.78,58.43 ], [ -138.22,58.43 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5188d46ce4b023d2d75b9a3c","contributors":{"authors":[{"text":"Nagorski, Sonia A.","contributorId":32940,"corporation":false,"usgs":true,"family":"Nagorski","given":"Sonia","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":478374,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Neal, Edward G.","contributorId":68775,"corporation":false,"usgs":true,"family":"Neal","given":"Edward G.","affiliations":[],"preferred":false,"id":478375,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brabets, Timothy P. tbrabets@usgs.gov","contributorId":2087,"corporation":false,"usgs":true,"family":"Brabets","given":"Timothy","email":"tbrabets@usgs.gov","middleInitial":"P.","affiliations":[],"preferred":true,"id":478373,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70173425,"text":"70173425 - 2013 - Microhabitat use of the diamond darter","interactions":[],"lastModifiedDate":"2016-06-16T15:44:18","indexId":"70173425","displayToPublicDate":"2013-05-06T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1471,"text":"Ecology of Freshwater Fish","active":true,"publicationSubtype":{"id":10}},"title":"Microhabitat use of the diamond darter","docAbstract":"The only known extant population of the diamond darter (Crystallaria cincotta) exists in the lower 37 km of Elk River, WV, USA. Our understanding of diamond darter habitat use was previously limited, because few individuals have been observed during sampling with conventional gears. We quantified microhabitat use of diamond darters based on measurements of water depth, water velocity and per cent substrate composition. Using spotlights at night-time, we sampled 16 sites within the lower 133 km of Elk River and observed a total of 82 diamond darters at 10 of 11 sampling sites within the lower 37 km. Glides, located immediately upstream of riffles, were the primary habitats sampled for diamond darters, which included relatively shallow depths (<1 m), moderate-to-low water velocities (often < 0.5 m·s−1) and a smooth water surface. Microhabitat use (mean ± SE) of diamond darters was estimated for depth (0.47 ± 0.02 m), average velocity (0.27 ± 0.01 m·s−1) and bottom velocity (0.15 ± 0.01 m·s−1). Substrate used (mean ± SE) by diamond darters was predominantly sand intermixed with lesser amounts of gravel and cobble: % sand (52.1 ± 1.6), % small gravel (12.2 ± 0.78), % large gravel (14.2 ± 0.83), % cobble (19.8 ± 0.96) and % boulder (1.6 ± 0.36). Based on our microhabitat use data, conservation and management efforts for this species should consider preserving glide habitats within Elk River. Spotlighting, a successful sampling method for diamond darters, should be considered for study designs of population estimation and long-term monitoring.
","language":"English","publisher":"Wiley","doi":"10.1111/eff.12062","usgsCitation":"Welsh, S., Smith, D.M., and Taylor, N.D., 2013, Microhabitat use of the diamond darter: Ecology of Freshwater Fish, v. 22, no. 4, p. 587-595, https://doi.org/10.1111/eff.12062.","productDescription":"9 p.","startPage":"587","endPage":"595","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-043471","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":473842,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/eff.12062","text":"Publisher Index Page"},{"id":323796,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"West Virginia","otherGeospatial":"Elk River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.62704467773438,\n 38.37019391098433\n ],\n [\n -81.53915405273438,\n 38.430463025162666\n ],\n [\n -81.35856628417967,\n 38.501967316378874\n ],\n [\n -81.19171142578125,\n 38.517549061739984\n ],\n [\n -81.12510681152344,\n 38.484769753492536\n ],\n [\n -81.04133605957031,\n 38.55031345037904\n ],\n [\n -80.91087341308594,\n 38.60560305052739\n ],\n [\n -80.86851596832275,\n 38.60919137718264\n ],\n [\n -80.86379528045654,\n 38.619184088742585\n ],\n [\n -80.86770057678223,\n 38.62635920407884\n ],\n [\n -80.86641311645508,\n 38.627800846245115\n ],\n [\n -80.86246490478516,\n 38.62733147755926\n ],\n [\n -80.85671424865723,\n 38.62357641746297\n ],\n [\n -80.8564567565918,\n 38.614389102209635\n ],\n [\n -80.86461067199707,\n 38.60332252537733\n ],\n [\n -80.8868408203125,\n 38.58520989992523\n ],\n [\n -80.8926773071289,\n 38.5580995115263\n ],\n [\n -80.93353271484375,\n 38.55434082866844\n ],\n [\n -80.96134185791014,\n 38.53876704899609\n ],\n [\n -80.98846435546875,\n 38.53339599812303\n ],\n [\n -81.01043701171875,\n 38.52372709602293\n ],\n [\n -81.02657318115234,\n 38.50384805076651\n ],\n [\n -81.03687286376953,\n 38.48342602101765\n ],\n [\n -81.09661102294922,\n 38.43449710809626\n ],\n [\n -81.14982604980469,\n 38.422663159088394\n ],\n [\n -81.20304107666014,\n 38.42642871684965\n ],\n [\n -81.21917724609375,\n 38.47267525933593\n ],\n [\n -81.2607192993164,\n 38.47294404791815\n ],\n [\n -81.37470245361328,\n 38.4546641418137\n ],\n [\n -81.4529800415039,\n 38.43422817624596\n ],\n [\n -81.58721923828125,\n 38.37692286554253\n ],\n [\n -81.6170883178711,\n 38.3564649034123\n ],\n [\n -81.62704467773438,\n 38.37019391098433\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"22","issue":"4","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2013-05-06","publicationStatus":"PW","scienceBaseUri":"5763cdb7e4b07657d19ba783","contributors":{"authors":[{"text":"Welsh, Stuart A. 0000-0003-0362-054X swelsh@usgs.gov","orcid":"https://orcid.org/0000-0003-0362-054X","contributorId":152088,"corporation":false,"usgs":true,"family":"Welsh","given":"Stuart A.","email":"swelsh@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":637109,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Dustin M.","contributorId":171829,"corporation":false,"usgs":false,"family":"Smith","given":"Dustin","email":"","middleInitial":"M.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":639404,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Taylor, Nate D.","contributorId":172042,"corporation":false,"usgs":false,"family":"Taylor","given":"Nate","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":639405,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70147457,"text":"70147457 - 2013 - Effects of food availability on yolk androgen deposition in the black-legged kittiwake (Rissa tridactyla), a seabird with facultative brood reduction","interactions":[],"lastModifiedDate":"2017-07-20T12:31:00","indexId":"70147457","displayToPublicDate":"2013-05-06T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Effects of food availability on yolk androgen deposition in the black-legged kittiwake (Rissa tridactyla), a seabird with facultative brood reduction","title":"Effects of food availability on yolk androgen deposition in the black-legged kittiwake (Rissa tridactyla), a seabird with facultative brood reduction","docAbstract":"In birds with facultative brood reduction, survival of the junior chick is thought to be regulated primarily by food availability. In black-legged kittiwakes (Rissa tridactyla) where parents and chicks are provided with unlimited access to supplemental food during the breeding season, brood reduction still occurs and varies interannually. Survival of the junior chick is therefore affected by factors in addition to the amount of food directly available to them. Maternally deposited yolk androgens affect competitive dynamics within a brood, and may be one of the mechanisms by which mothers mediate brood reduction in response to a suite of environmental and physiological cues. The goal of this study was to determine whether food supplementation during the pre-lay period affected patterns of yolk androgen deposition in free-living kittiwakes in two years (2003 and 2004) that varied in natural food availability. Chick survival was measured concurrently in other nests where eggs were not collected. In both years, supplemental feeding increased female investment in eggs by increasing egg mass. First-laid (“A”) eggs were heavier but contained less testosterone and androstenedione than second-laid (“B”) eggs across years and treatments. Yolk testosterone was higher in 2003 (the year with higher B chick survival) across treatments. The difference in yolk testosterone levels between eggs within a clutch varied among years and treatments such that it was relatively small when B chick experienced the lowest and the highest survival probabilities, and increased with intermediate B chick survival probabilities. The magnitude of testosterone asymmetry in a clutch may allow females to optimize fitness by either predisposing a brood for reduction or facilitating survival of younger chicks.
","language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pone.0062949","usgsCitation":"Benowitz-Fredericks, Z., Kitaysky, A.S., Welcker, J., and Hatch, S.A., 2013, Effects of food availability on yolk androgen deposition in the black-legged kittiwake (Rissa tridactyla), a seabird with facultative brood reduction: PLoS ONE, v. 8, no. 5, e62949: 8 p., https://doi.org/10.1371/journal.pone.0062949.","productDescription":"e62949: 8 p.","ipdsId":"IP-015797","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":473841,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0062949","text":"Publisher Index Page"},{"id":344123,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Middleton Island","geographicExtents":"{\n \"type\": 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S.","contributorId":13884,"corporation":false,"usgs":true,"family":"Kitaysky","given":"Alexander","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":705840,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Welcker, Jorg","contributorId":25441,"corporation":false,"usgs":true,"family":"Welcker","given":"Jorg","email":"","affiliations":[],"preferred":false,"id":705841,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hatch, Scott A. 0000-0002-0064-8187 shatch@usgs.gov","orcid":"https://orcid.org/0000-0002-0064-8187","contributorId":2625,"corporation":false,"usgs":true,"family":"Hatch","given":"Scott","email":"shatch@usgs.gov","middleInitial":"A.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":545968,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70060519,"text":"70060519 - 2013 - Salamander colonization of Chase Lake, Stutsman County, North Dakota","interactions":[],"lastModifiedDate":"2018-01-04T12:17:19","indexId":"70060519","displayToPublicDate":"2013-05-05T13:25:08","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3580,"text":"The Prairie Naturalist","active":true,"publicationSubtype":{"id":10}},"title":"Salamander colonization of Chase Lake, Stutsman County, North Dakota","docAbstract":"Salt concentrations in lakes are dynamic. In the western United States, water diversions have caused significant declines in lake levels resulting in increased salinity, placing many aquatic species at risk (Galat and Robinson 1983, Beutel et al. 2001). Severe droughts can have similar effects on salt concentrations and aquatic communities (Swanson et al. 2003). Conversely, large inputs of water can dilute salt concentrations and contribute to community shifts (Euliss et al. 2004).","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"The Prairie Naturalist","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"South Dakota State University","usgsCitation":"Mushet, D.M., McLean, K., and Stockwell, C., 2013, Salamander colonization of Chase Lake, Stutsman County, North Dakota: The Prairie Naturalist, v. 45, p. 106-108.","productDescription":"3 p.","startPage":"106","endPage":"108","ipdsId":"IP-041798","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":287145,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Dakota","county":"Stutsman County","otherGeospatial":"Chase Lake","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -99.48,46.63 ], [ -99.48,47.33 ], [ -98.44,47.33 ], [ -98.44,46.63 ], [ -99.48,46.63 ] ] ] } } ] }","volume":"45","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53749075e4b0870f4d23cfec","contributors":{"authors":[{"text":"Mushet, David M. 0000-0002-5910-2744 dmushet@usgs.gov","orcid":"https://orcid.org/0000-0002-5910-2744","contributorId":1299,"corporation":false,"usgs":true,"family":"Mushet","given":"David","email":"dmushet@usgs.gov","middleInitial":"M.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":487891,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McLean, Kyle I.","contributorId":63316,"corporation":false,"usgs":true,"family":"McLean","given":"Kyle I.","affiliations":[],"preferred":false,"id":487893,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stockwell, Craig A.","contributorId":55257,"corporation":false,"usgs":true,"family":"Stockwell","given":"Craig A.","affiliations":[],"preferred":false,"id":487892,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70045768,"text":"70045768 - 2013 - Floral ecology and insect visitation in riparian Tamarix sp. (saltcedar)","interactions":[],"lastModifiedDate":"2013-05-05T16:11:37","indexId":"70045768","displayToPublicDate":"2013-05-05T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2183,"text":"Journal of Arid Environments","active":true,"publicationSubtype":{"id":10}},"title":"Floral ecology and insect visitation in riparian Tamarix sp. (saltcedar)","docAbstract":"Climate change projections for semiarid and arid North America include reductions in stream discharge that could adversely affect riparian plant species dependent on stream-derived ground water. In order to better understand this potential impact, we used a space-for-time substitution to test the hypotheses that increasing depth-to-groundwater (DGW) is inversely related to Tamarix sp. (saltcedar) flower abundance (F) and nectar production per flower (N). We also assessed whether DGW affected the richness or abundance of insects visiting flowers. We examined Tamarix floral attributes and insect visitation patterns during 2010 and 2011 at three locations along a deep DWG gradient (3.2–4.1 m) on a floodplain terrace adjacent to Las Vegas Wash, an effluent-dominated Mojave Desert stream. Flower abundance and insect visitation patterns differed between years, but no effect from DGW on either F or N was detected. An eruption of a novel non-native herbivore, the splendid tamarisk weevil (Coniatus splendidulus), likely reduced flower production in 2011.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Arid Environments","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.jaridenv.2013.03.009","usgsCitation":"Andersen, D., and Nelson, S.M., 2013, Floral ecology and insect visitation in riparian Tamarix sp. (saltcedar): Journal of Arid Environments, v. 94, p. 1-5-112, https://doi.org/10.1016/j.jaridenv.2013.03.009.","productDescription":"8 p.","startPage":"1-5","endPage":"112","ipdsId":"IP-045358","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":271826,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.jaridenv.2013.03.009"},{"id":271827,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"94","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5187716ae4b078fc9c244b53","contributors":{"authors":[{"text":"Andersen, D.C.","contributorId":19119,"corporation":false,"usgs":true,"family":"Andersen","given":"D.C.","email":"","affiliations":[],"preferred":false,"id":478322,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nelson, S. M.","contributorId":81853,"corporation":false,"usgs":false,"family":"Nelson","given":"S.","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":478323,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70045775,"text":"sir20135037 - 2013 - Plankton communities and summertime declines in algal abundance associated with low dissolved oxygen in the Tualatin River, Oregon","interactions":[],"lastModifiedDate":"2013-05-05T16:03:22","indexId":"sir20135037","displayToPublicDate":"2013-05-05T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-5037","title":"Plankton communities and summertime declines in algal abundance associated with low dissolved oxygen in the Tualatin River, Oregon","docAbstract":"Phytoplankton populations in the Tualatin River in northwestern Oregon are an important component of the dissolved oxygen (DO) budget of the river and are critical for maintaining DO levels in summer. During the low-flow summer period, sufficient nutrients and a long residence time typically combine with ample sunshine and warm water to fuel blooms of cryptophyte algae, diatoms, green and blue-green algae in the low-gradient, slow-moving reservoir reach of the lower river. Algae in the Tualatin River generally drift with the water rather than attach to the river bottom as a result of moderate water depths, slightly elevated turbidity caused by suspended colloidal material, and dominance of silty substrates. Growth of algae occurs as if on a “conveyor belt” of streamflow, a dynamic system that is continually refreshed with inflowing water. Transit through the system can take as long as 2 weeks during the summer low-flow period. Photosynthetic production of DO during algal blooms is important in offsetting oxygen consumption at the sediment-water interface caused by the decomposition of organic matter from primarily terrestrial sources, and the absence of photosynthesis can lead to low DO concentrations that can harm aquatic life. \n\nThe periods with the lowest DO concentrations in recent years (since 2003) typically occur in August following a decline in algal abundance and activity, when DO concentrations often decrease to less than State standards for extended periods (nearly 80 days). Since 2003, algal populations have tended to be smaller and algal blooms have terminated earlier compared to conditions in the 1990s, leading to more frequent declines in DO to levels that do not meet State standards. This study was developed to document the current abundance and species composition of phytoplankton in the Tualatin River, identify the possible causes of the general decline in algae, and evaluate hypotheses to explain why algal blooms diminish in midsummer. \n\nPlankton and water-quality sample data from 2006 to 2008 were combined with parts of a larger discrete-sample and continuous water-quality monitoring dataset and examined to identify patterns in water-quality and algal conditions since 1991, with a particular emphasis on 2003–08. Longitudinal plankton surveys were conducted in 2006–08 at six sites between river miles (RM) 24.5 and 3.4 at 2- to 3-week intervals, or 5–6 per season, and in-situ bioassay experiments were conducted in 2008 to examine the potential effects of wastewater treatment facility (WWTF) effluent and phosphorus additions on phytoplankton biomass and algal photosynthesis. Phytoplankton and zooplankton community composition, streamflow, and water-quality data were analyzed using multivariate statistical techniques to gain insights into plankton dynamics to determine what factors might be most tied to the abundance and characteristics of the phytoplankton assemblages, and identify possible causes of their declines.\n\nThe connection between low-DO events and algal declines was clearly evident, as bloom crashes were nearly always followed by periods of low DO. Algal blooms occurred each year during 2006–08, producing maximum chlorophyll-a (Chl-a) values in June or July generally in the range of 50–80 micrograms per liter (µg/L). Bloom crashes and absence of sufficient algal photosynthesis in mid- to late-summer contributed to minimum DO concentrations that were less than the State standard of 6.5 milligrams per liter (mg/L) based on the 30-day mean daily concentration, for 62–74 days each year. At times, the absolute minimum State standard (4 mg/L DO) also was not met. To learn more about why low-DO events occurred, specific algal declines during 2003–08 were scrutinized to determine their likely causal factors. From this information, a series of hypotheses were formulated and evaluated in terms of their ability to explain recent declines in algal populations in the river in late summer.\n\nMeteorological, streamflow, turbidity, water temperature, and conductance conditions in the Tualatin River during the 2006–08 summer seasons were not atypical. Natural flow comprised the majority (70–80 percent) of flow each year during spring, but then reduced to 38–40 percent during midsummer when WWTF effluent—which contributed as much as 36 percent—and flow augmentation releases comprised a greater fraction of the flow. Summer 2008 was unusual, however, in the prolonged influence from the Wapato Lake agricultural area near Gaston in the upper part of the basin. The previous winter flooding and levee breach at Wapato Lake caused a much greater area of inundation. As a result, drainage from this area continued into July, much later than normal. A subsequent algal bloom in Wapato Lake then seeded the upper Tualatin River, and this drainage had a profound effect on the downstream plankton community. A large blue-green algae bloom developed—the largest in recent memory—prompting a public health advisory for recreational contact for about two weeks.\n\nAlgal growths and surface blooms are a common feature of the Tualatin River. Most of the dominant algae have growth forms and morphologies that are well suited for planktonic life, employing spines and gas vacuoles to resist settling, forming colonies, and producing mucilage (or toxins) to resist zooplankton grazing. In 2006–08, 143 algal taxa were identified in 117 main-stem samples; diatoms and green algae were more diverse than blue-green, golden, and cryptophyte algae, although these later groups sometimes dominated the overall volumetric abundance (biovolume). The most frequently occurring taxa, occurring in 97–99 percent of samples, were flagellated cryptophytes Cryptomonas erosa and Rhodomonas minuta. Other important algal taxa included centric diatoms Stephanodiscus, Cyclotella, and Melosira species and colonial green algae Scenedesmus and Actinastrum. These taxa comprised the majority of the algal biovolume during much of the growing season. A general seasonal trend in the phytoplankton assemblages was observed, with dominance by filamentous centric diatoms Stephanodiscus and Melosira in spring and early summer, and flagellated cryptophytes and green algae, particularly Chlamydomonas sp., in late-summer; or, in 2008, dominance by blue-green algae Anabaena flos-aquae and Aphanizomenon flos-aquae during the Wapato Lake bloom event.\n\nThere were 99 zooplankton taxa identified from the Tualatin River in 2006–08, composed primarily of cladocerans, copepods, and rotifers. A seasonal increase in zooplankton abundance was observed in early summer just as or shortly after the phytoplankton population began to increase, with populations growing to 15,000−120,000 organisms per cubic meter in the lower river. Zooplankton abundance showed a predictable and distinct longitudinal downstream increase, particularly downstream of Highway 99W (RM 11.6). Although grazing rates were not measured, the data suggest that, at times, zooplankton grazing may affect algal abundance and species composition in the Tualatin River, with diatoms becoming relatively less abundant and flagellated cryptophytes and green algae relatively more abundant during periods when zooplankton densities were highest.\n\nMultivariate statistical analyses identified soluble reactive phosphorus (SRP), natural flow, flow augmentation, and WWTF effluent as important factors influencing Tualatin River phytoplankton populations, with zooplankton density (particularly rotifers and copepods), specific conductance, chloride, and water temperature also having an important influence. Although SRP was highly correlated with the plankton communities, that correlation was likely the result of high or low algal activity (uptake) as SRP concentrations were often reduced to low levels during blooms. While previous studies have already established that phosphorus, among other factors such as flow, places a theoretical cap on the size of the phytoplankton population in the river, sometimes algal declines occur when SRP concentrations are apparently sufficient. To identify alternative causal factors, additional analyses were performed without SRP to focus on other water-quality parameters, zooplankton density, and flow factors. Considering data for all 3 years and including just those samples from the lower Tualatin River not affected by the 2008 Wapato Lake drainage event, three factors (percentage of reservoir flow augmentation, total natural flow, and rotifer density) best explained variations in the phytoplankton assemblages.\n\nAnalyses focusing on the possible causes of algal declines included the above multivariate analyses, scrutiny of 10 specific instances of declines in algal populations during 2003–08 including several bloom–crash sequences, and analyses of historic routine watershed monitoring data from Clean Water Services. Six factors were hypothesized to be important in causing bloom crashes or impeding blooms from rebounding in August: (1) light limitation from cloudy weather, (2) a reduction in the plankton inocula or “seed” entering the lower river from upstream sources, (3) increased summer streamflows, (4) changes in the dominant sources of flow as the percentage of flow augmentation and WWTF discharges have increased, (5) zooplankton grazing, and (6) low concentrations of bioavailable phosphorus (<0.015 milligram per liter). All of these hypotheses are supported in some fashion by the available data and statistical analyses. Zooplankton grazing, short-term declines in photosynthesis from cloudy weather, total flow as it affects residence time, and the dominant source of flow are primary factors responsible for the low-DO events caused by declines in algae in the lower Tualatin River during late summer.\n\nCloudy weather and increased turbidity are known to inhibit algal growth in the Tualatin River, and slight increases in turbidity in recent years may be a problem. Upstream sources of algae are critical in determining the characteristics and size of downstream populations, as illustrated by the Wapato Lake bloom in 2008, but more data are needed from upstream to fully define the importance of this connection. The sources of flow, through their differential contribution of plankton inocula (quality and amount), were, at times, important factors affecting phytoplankton populations. While SRP concentrations were often most highly correlated with phytoplankton species community, the bioavailability of phosphorus is still somewhat unknown and there are several sources to consider. Preliminary bioassay tests suggested that while treated wastewater effluent may stimulate algae at 30 percent concentrations, negative effects (or decreased stimulation) on Chl-a and DO production may occur at concentrations of 50 percent. Targeted data collection and future research will be needed to further understand the importance of these factors on Tualatin River phytoplankton.\n\nWhile the data and analysis completed for this report provide insights into future research and monitoring that would be useful to continue, additional monitoring of turbidity, Chl-a, and plankton abundance and species composition in the upper part of the basin would enhance our understanding of plankton dynamics and factors affecting phytoplankton abundance in the lower river. Assessment of the key upstream sources of algal inocula via surveys of the major flow sources as well as tributaries and wetlands would provide useful information for the management of river water quality. Other studies that could prove useful for developing management strategies include targeted experiments to evaluate the bioavailability of phosphorus from a variety of sources. New research on phytoplankton–zooplankton interactions, and studies of planktivorous fish, might also provide insight about food web dynamics and potential “top-down” effects of fish predation on the plankton communities. In addition, further development of neural-network or other water-quality models would help to evaluate management strategies and provide forecasts of water-quality conditions. Finally, periodic future reassessments of the available data with the multivariate statistical tools used in this study would be helpful to assess whether and how plankton communities are changing, and to continue to shed light on the importance of factors shaping the plankton. Although certain types and sizes of algal blooms are undesirable, minimum phytoplankton populations are an important part of aquatic food webs and are needed to maintain healthy levels of DO in the river. By understanding the sources, characteristics, causal factors, and responses of the plankton communities, management strategies can be developed to improve DO conditions in the lower Tualatin River during the important summer low-flow period.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135037","collaboration":"Prepared in cooperation with Clean Water Services","usgsCitation":"Carpenter, K., and Rounds, S.A., 2013, Plankton communities and summertime declines in algal abundance associated with low dissolved oxygen in the Tualatin River, Oregon: U.S. Geological Survey Scientific Investigations Report 2013-5037, x, 78 p.; Appendixes A-C; Table 10, https://doi.org/10.3133/sir20135037.","productDescription":"x, 78 p.; Appendixes A-C; Table 10","additionalOnlineFiles":"Y","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":271825,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135037.jpg"},{"id":271821,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2013/5037/appendixes/sir20135037_appendixA.xlsx"},{"id":271822,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2013/5037/appendixes/sir20135037_appendixB.xlsx"},{"id":271823,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2013/5037/appendixes/sir20135037_appendixC.xlsx"},{"id":271824,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2013/5037/appendixes/sir20135037_table10.pdf"},{"id":271819,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5037/"},{"id":271820,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5037/pdf/sir20135037.pdf"}],"country":"United States","state":"Oregon","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.6,42.0 ], [ -124.6,46.3 ], [ -116.5,46.3 ], [ -116.5,42.0 ], [ -124.6,42.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5187716ce4b078fc9c244b63","contributors":{"authors":[{"text":"Carpenter, Kurt D. kdcar@usgs.gov","contributorId":1372,"corporation":false,"usgs":true,"family":"Carpenter","given":"Kurt D.","email":"kdcar@usgs.gov","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":false,"id":478342,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":478341,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ]}