The authors investigated the chronic toxicity of aqueous Pb to the amphipod Hyalella azteca (Hyalella) in 42-d tests using 2 different diets: 1) the yeastþcereal leafþtrout pellet (YCT) diet, fed at the uniform low ration used in standard methods for sediment toxicity tests; and 2) a new diet of diatomsþTetraMin flakes (DT), fed at increasing rations over time, that has been optimized for use in Hyalella water-only tests. Test endpoints included survival, weight, biomass, fecundity, and total young. Lethal effects of Pb were similar for the DT and YCT tests (20% lethal concentration [LC20]¼13 mg/L and 15mg/L, respectively, as filterable Pb). In contrast, weight and fecundity endpoints were not significantly affected in the DT test at Pb concentrations up to 63 mg/L, but these endpoints were significantly reduced by Pb in the YCT test—and in a 2005 test in the same laboratory with a diet of conditioned Rabbit Chow (RC-2005). The fecundity and total young endpoints from the YCT and RC-2005 tests were considered unreliable because fecundity in controls did not meet test acceptability criteria, but both of these tests still produced lower Pb effect concentrations (for weight or biomass) than the test with the DT diet. The lowest biotic ligand model–normalized effect concentrations for the 3 tests ranged from 3.7mg/L (weight 20% effect concentration [EC20] for the RC-2005 test) to 8.2 mg/L (total young EC20 for the DT test), values that would rank Hyalella as the second or third most sensitive of 13 genera in a species sensitivity distribution for chronic Pb toxicity. These results demonstrate that toxicity tests with Hyalella fed optimal diets can meet more stringent test acceptability criteria for control performance, but suggest that results of these tests may underestimate sublethal toxic effects of Pb to Hyalella under suboptimal feeding regimes.
","language":"English","publisher":"Setac Press","doi":"10.1002/etc.3341","usgsCitation":"Besser, J.M., Ivey, C.D., Brumbaugh, W.G., and Ingersoll, C.G., 2016, Effect of diet quality on chronic toxicity of aqueous lead to the amphipod Hyalella azteca: Environmental Toxicology and Chemistry, v. 35, p. 1825-1834, https://doi.org/10.1002/etc.3341.","productDescription":"10 p.","startPage":"1825","endPage":"1834","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-063482","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":324365,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"35","edition":"7","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-18","publicationStatus":"PW","scienceBaseUri":"576e59aee4b07657d1a43c55","contributors":{"authors":[{"text":"Besser, John M. 0000-0002-9464-2244 jbesser@usgs.gov","orcid":"https://orcid.org/0000-0002-9464-2244","contributorId":2073,"corporation":false,"usgs":true,"family":"Besser","given":"John","email":"jbesser@usgs.gov","middleInitial":"M.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":640705,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ivey, Chris D. 0000-0002-0485-7242 civey@usgs.gov","orcid":"https://orcid.org/0000-0002-0485-7242","contributorId":3308,"corporation":false,"usgs":true,"family":"Ivey","given":"Chris","email":"civey@usgs.gov","middleInitial":"D.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":640706,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brumbaugh, William G. 0000-0003-0081-375X bbrumbaugh@usgs.gov","orcid":"https://orcid.org/0000-0003-0081-375X","contributorId":493,"corporation":false,"usgs":true,"family":"Brumbaugh","given":"William","email":"bbrumbaugh@usgs.gov","middleInitial":"G.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":640707,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ingersoll, Christopher G. 0000-0003-4531-5949 cingersoll@usgs.gov","orcid":"https://orcid.org/0000-0003-4531-5949","contributorId":2071,"corporation":false,"usgs":true,"family":"Ingersoll","given":"Christopher","email":"cingersoll@usgs.gov","middleInitial":"G.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":640708,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70170803,"text":"70170803 - 2016 - Flow management for hydropower extirpates aquatic insects, undermining river food webs","interactions":[],"lastModifiedDate":"2016-07-07T10:06:15","indexId":"70170803","displayToPublicDate":"2016-05-02T11:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":997,"text":"BioScience","active":true,"publicationSubtype":{"id":10}},"title":"Flow management for hydropower extirpates aquatic insects, undermining river food webs","docAbstract":"Dams impound the majority of rivers and provide important societal benefits, especially daily water releases that enable on-peak hydroelectricity generation. Such “hydropeaking” is common worldwide, but its downstream impacts remain unclear. We evaluated the response of aquatic insects, a cornerstone of river food webs, to hydropeaking using a life history–hydrodynamic model. Our model predicts that aquatic-insect abundance will depend on a basic life-history trait—adult egg-laying behavior—such that open-water layers will be unaffected by hydropeaking, whereas ecologically important and widespread river-edge layers, such as mayflies, will be extirpated. These predictions are supported by a more-than-2500-sample, citizen-science data set of aquatic insects from the Colorado River in the Grand Canyon and by a survey of insect diversity and hydropeaking intensity across dammed rivers of the Western United States. Our study reveals a hydropeaking-related life history bottleneck that precludes viable populations of many aquatic insects from inhabiting regulated rivers.
","language":"English","publisher":"American Institute of Biological Sciences","publisherLocation":"Washington, D.C.","doi":"10.1093/biosci/biw059","usgsCitation":"Kennedy, T.A., Muehlbauer, J.D., Yackulic, C.B., Lytle, D., Miller, S., Dibble, K.L., Kortenhoeven, E.W., Metcalfe, A.N., and Baxter, C., 2016, Flow management for hydropower extirpates aquatic insects, undermining river food webs: BioScience, v. 66, no. 7, p. 561-575, https://doi.org/10.1093/biosci/biw059.","productDescription":"15 p.","startPage":"561","endPage":"575","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069041","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":471029,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/biosci/biw059","text":"Publisher Index Page"},{"id":438616,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7WM1BH4","text":"USGS data release","linkHelpText":"Flow management for hydropower extirpates aquatic insects, undermining river food websData"},{"id":320875,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"66","issue":"7","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-02","publicationStatus":"PW","scienceBaseUri":"5729cbb2e4b0b13d3919a342","contributors":{"authors":[{"text":"Kennedy, Theodore A. 0000-0003-3477-3629 tkennedy@usgs.gov","orcid":"https://orcid.org/0000-0003-3477-3629","contributorId":167537,"corporation":false,"usgs":true,"family":"Kennedy","given":"Theodore","email":"tkennedy@usgs.gov","middleInitial":"A.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":628488,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Muehlbauer, Jeffrey D. 0000-0003-1808-580X jmuehlbauer@usgs.gov","orcid":"https://orcid.org/0000-0003-1808-580X","contributorId":5045,"corporation":false,"usgs":true,"family":"Muehlbauer","given":"Jeffrey","email":"jmuehlbauer@usgs.gov","middleInitial":"D.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":628490,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yackulic, Charles B. 0000-0001-9661-0724 cyackulic@usgs.gov","orcid":"https://orcid.org/0000-0001-9661-0724","contributorId":4662,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","email":"cyackulic@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":628489,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lytle, D.A.","contributorId":85422,"corporation":false,"usgs":true,"family":"Lytle","given":"D.A.","email":"","affiliations":[],"preferred":false,"id":628491,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Miller, S.A.","contributorId":66389,"corporation":false,"usgs":true,"family":"Miller","given":"S.A.","email":"","affiliations":[],"preferred":false,"id":628492,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dibble, Kimberly L. 0000-0003-0799-4477 kdibble@usgs.gov","orcid":"https://orcid.org/0000-0003-0799-4477","contributorId":5174,"corporation":false,"usgs":true,"family":"Dibble","given":"Kimberly","email":"kdibble@usgs.gov","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":628500,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kortenhoeven, Eric W. ekortenhoeven@usgs.gov","contributorId":5046,"corporation":false,"usgs":true,"family":"Kortenhoeven","given":"Eric","email":"ekortenhoeven@usgs.gov","middleInitial":"W.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":628493,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Metcalfe, Anya N. 0000-0002-6286-4889 ametcalfe@usgs.gov","orcid":"https://orcid.org/0000-0002-6286-4889","contributorId":5271,"corporation":false,"usgs":true,"family":"Metcalfe","given":"Anya","email":"ametcalfe@usgs.gov","middleInitial":"N.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":628494,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Baxter, Colden V.","contributorId":47334,"corporation":false,"usgs":false,"family":"Baxter","given":"Colden V.","affiliations":[{"id":13656,"text":"Idaho State Univ.","active":true,"usgs":false}],"preferred":false,"id":628501,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70170755,"text":"70170755 - 2016 - Preface: Land subsidence processes","interactions":[],"lastModifiedDate":"2019-09-06T11:12:11","indexId":"70170755","displayToPublicDate":"2016-05-02T11:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1923,"text":"Hydrogeology Journal","active":true,"publicationSubtype":{"id":10}},"title":"Preface: Land subsidence processes","docAbstract":"No abstract available.
","language":"English","publisher":"Springer","doi":"10.1007/s10040-016-1386-y","usgsCitation":"Galloway, D.L., Erkens, G., Kuniansky, E.L., and Rowland, J.C., 2016, Preface: Land subsidence processes: Hydrogeology Journal, v. 24, no. 3, p. 547-550, https://doi.org/10.1007/s10040-016-1386-y.","productDescription":"3 p.","startPage":"547","endPage":"550","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-072759","costCenters":[{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":471031,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10040-016-1386-y","text":"Publisher Index Page"},{"id":320814,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"24","issue":"3","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-03-04","publicationStatus":"PW","scienceBaseUri":"57286c1be4b0b13d3917ce10","contributors":{"authors":[{"text":"Galloway, Devin L. 0000-0003-0904-5355 dlgallow@usgs.gov","orcid":"https://orcid.org/0000-0003-0904-5355","contributorId":679,"corporation":false,"usgs":true,"family":"Galloway","given":"Devin","email":"dlgallow@usgs.gov","middleInitial":"L.","affiliations":[{"id":5078,"text":"Southwest Regional Director's Office","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5058,"text":"Office of the Chief Scientist for Water","active":true,"usgs":true},{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true}],"preferred":true,"id":628277,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Erkens, Gilles","contributorId":169045,"corporation":false,"usgs":false,"family":"Erkens","given":"Gilles","email":"","affiliations":[{"id":25398,"text":"Deltares Research Institute, The Netherlands","active":true,"usgs":false}],"preferred":false,"id":628278,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kuniansky, Eve L. 0000-0002-5581-0225 elkunian@usgs.gov","orcid":"https://orcid.org/0000-0002-5581-0225","contributorId":932,"corporation":false,"usgs":true,"family":"Kuniansky","given":"Eve","email":"elkunian@usgs.gov","middleInitial":"L.","affiliations":[{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true},{"id":5064,"text":"Southeast Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":628279,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rowland, Joel C.","contributorId":169046,"corporation":false,"usgs":false,"family":"Rowland","given":"Joel","email":"","middleInitial":"C.","affiliations":[{"id":13447,"text":"Los Alamos National Laboratory","active":true,"usgs":false}],"preferred":false,"id":628280,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70170759,"text":"70170759 - 2016 - Hydrologic exchanges and baldcypress water use on deltaic hummocks, Louisiana, USA","interactions":[],"lastModifiedDate":"2016-12-09T16:35:39","indexId":"70170759","displayToPublicDate":"2016-05-02T11:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1447,"text":"Ecohydrology","active":true,"publicationSubtype":{"id":10}},"title":"Hydrologic exchanges and baldcypress water use on deltaic hummocks, Louisiana, USA","docAbstract":"Coastal forested hummocks support clusters of trees in the saltwater–freshwater transition zone. To examine how hummocks support trees in mesohaline sites that are beyond physiological limits of the trees, we used salinity and stable isotopes (2H and 18O) of water as tracers to understand water fluxes in hummocks and uptake by baldcypress (Taxodium distichum (L.) Rich.), which is the most abundant tree species in coastal freshwater forests of the southeastern U.S. Hummocks were always partially submerged and were completely submerged 1 to 8% of the time during the two studied growing seasons, in association with high water in the estuary. Salinity, δ18O, and δ2H varied more in the shallow open water than in groundwater. Surface water and shallow groundwater were similar to throughfall in isotopic composition, which suggested dominance by rainfall. Salinity of groundwater in hummocks increased with depth, was higher than in swales, and fluctuated little over time. Isotopic composition of xylem water in baldcypress was similar to the vadose zone and unlike other measured sources, indicating that trees preferentially use unsaturated hummock tops as refugia from higher salinity and saturated soil in swales and the lower portions of hummocks. Sustained upward gradients of salinity from groundwater to surface water and vadose water, and low variation in groundwater salinity and isotopic composition, suggested long residence time, limited exchange with surface water, and that the shallow subsurface of hummocks is characterized by episodic salinization and slow dilution.
","language":"English","publisher":"Wiley","doi":"10.1002/eco.1738","usgsCitation":"Hsueh, Y., Chambers, J., Krauss, K.W., Allen, S.T., and Keim, R., 2016, Hydrologic exchanges and baldcypress water use on deltaic hummocks, Louisiana, USA: Ecohydrology, v. 9, no. 8, p. 1452-1463, https://doi.org/10.1002/eco.1738.","productDescription":"12 p.","startPage":"1452","endPage":"1463","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-067366","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":320812,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Jean Lafitte National Historical Park and Preserve","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.14,\n 29.75\n ],\n [\n -90.14,\n 29.76\n ],\n [\n -90.15,\n 29.76\n ],\n [\n -90.15,\n 29.75\n ],\n [\n -90.14,\n 29.75\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"9","issue":"8","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2016-04-28","publicationStatus":"PW","scienceBaseUri":"57286c1be4b0b13d3917ce0e","contributors":{"authors":[{"text":"Hsueh, Yu-Hsin","contributorId":169051,"corporation":false,"usgs":false,"family":"Hsueh","given":"Yu-Hsin","email":"","affiliations":[],"preferred":false,"id":628310,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chambers, Jim L.","contributorId":16498,"corporation":false,"usgs":true,"family":"Chambers","given":"Jim L.","affiliations":[],"preferred":false,"id":628311,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Krauss, Ken W. 0000-0003-2195-0729 kraussk@usgs.gov","orcid":"https://orcid.org/0000-0003-2195-0729","contributorId":2017,"corporation":false,"usgs":true,"family":"Krauss","given":"Ken","email":"kraussk@usgs.gov","middleInitial":"W.","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":628298,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Allen, Scott T.","contributorId":168409,"corporation":false,"usgs":false,"family":"Allen","given":"Scott","email":"","middleInitial":"T.","affiliations":[{"id":25282,"text":"School of Renewable Natural Resources, Louisiana State University, Baton Rouge, LA","active":true,"usgs":false}],"preferred":false,"id":628312,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Keim, Richard F.","contributorId":21858,"corporation":false,"usgs":true,"family":"Keim","given":"Richard F.","affiliations":[],"preferred":false,"id":628313,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70162383,"text":"sir20165008 - 2016 - Geology of tight oil and potential tight oil reservoirs in the lower part of the Green River Formation, Uinta, Piceance, and Greater Green River Basins, Utah, Colorado, and Wyoming","interactions":[],"lastModifiedDate":"2016-05-02T10:42:55","indexId":"sir20165008","displayToPublicDate":"2016-05-02T10:00:00","publicationYear":"2016","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":"2016-5008","title":"Geology of tight oil and potential tight oil reservoirs in the lower part of the Green River Formation, Uinta, Piceance, and Greater Green River Basins, Utah, Colorado, and Wyoming","docAbstract":"The recent successful development of a tight oil play in the Eocene-age informal Uteland Butte member of the lacustrine Green River Formation in the Uinta Basin, Utah, using modern horizontal drilling and hydraulic fracturing techniques has spurred a renewed interest in the tight oil potential of lacustrine rocks. The Green River Formation was deposited by two large lakes, Lake Uinta in the Uinta and Piceance Basins and Lake Gosiute in the Greater Green River Basin. These three basins contain the world’s largest in-place oil shale resources with recent estimates of 1.53 trillion, 1.33 trillion, and 1.44 trillion barrels of oil in place in the Piceance, Uinta, and Greater Green River Basins, respectively. The Uteland Butte member was deposited during an early freshwater stage of the lake in the Uinta Basin prior to deposition of the assessed oil shale intervals. This report only presents information on the early freshwater interval and overlying brackish-water interval in all three basins because these intervals are most likely to have tight oil potential. Burial histories of the three basins were reconstructed to study (1) variations in subsidence and lake development, and (2) post deposition burial that led to the development of a petroleum system in only the Uinta Basin. The Uteland Butte member is a successful tight oil play because it is thermally mature for hydrocarbon generation and contains organic-rich shale, brittle carbonate, and porous dolomite. Abnormally high pressure in parts of the Uteland Butte is also important to production. Variations in organic richness of the Uteland Butte were studied using Fischer assay analysis from oil shale assessments, and pressures were studied using drill-stem tests. Freshwater lacustrine intervals in the Piceance and Greater Green River Basins are immature for hydrocarbon generation and contain much less carbonate than the Uteland Butte member. The brackish-water interval in the Uinta Basin is thermally mature for hydrocarbon generation but is clay-rich and contains little carbonate, and thus is a poor prospect for tight oil development.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165008","usgsCitation":"Johnson, R.C., Birdwell, J.E., Mercier, T.J., and Brownfield, M.E., 2016, Geology of tight oil and potential tight oil reservoirs in the lower part of the Green River Formation, Uinta, Piceance, and Greater Green River Basins, Utah, Colorado, and Wyoming: U.S. Geological Survey Scientific Investigations Report 2016–5008, 63 p., https://dx.doi.org/10.3133/sir20165008.","productDescription":"Report: vii, 63 p.; Table 1; Figure 29","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-059890","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":320649,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5008/coverthb.jpg"},{"id":320650,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5008/sir20165008.pdf","text":"Report","size":"53.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5008"},{"id":320651,"rank":3,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/sir/2016/5008/sir20165008_fig29.pdf","text":"Figure 29","size":"1.02 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5008 Figure 29"},{"id":320672,"rank":4,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2016/5008/sir20165008_Table1UtelandFischerassay.xlsx","text":"Table 1","size":"68.0 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2016-5008 Table 1"}],"country":"United States","state":"Colorado, Utah, Wyoming","otherGeospatial":"Green River Basin, Piceance River Basin, Uinta River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.566162109375,\n 38.62545397209084\n ],\n [\n -111.566162109375,\n 43.30119623257966\n ],\n [\n -106.336669921875,\n 43.30119623257966\n ],\n [\n -106.336669921875,\n 38.62545397209084\n ],\n [\n -111.566162109375,\n 38.62545397209084\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Center Director, USGS Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver Federal Center
Denver, CO 80225-0046
Taiyangshan is a poorly studied copper–molybdenum deposit located in the Triassic Western Qinling collisional belt of northwest China. The intrusions exposed in the vicinity of the Taiyangshan deposit record episodic magmatism over 20–30 million years. Pre-mineralization quartz diorite porphyries, which host some of the deposit, were emplaced at 226.6 ± 6.2 Ma. Syn-collisional monzonite and quartz monzonite porphyries, which also host mineralization, were emplaced at 218.0 ± 6.1 Ma and 215.0 ± 5.8 Ma, respectively. Mineralization occurred during the transition from a syn-collisional to a post-collisional setting at ca. 208 Ma. A barren post-mineralization granite porphyry marked the end of post-collisional magmatism at 200.7 ± 5.1 Ma. The ore-bearing monzonite and quartz monzonite porphyries have a εHf(t) range from − 2.0 to + 12.5, which is much more variable than that of the slightly older quartz diorite porphyries, with TDM2 of 1.15–1.23 Ga corresponding to the positive εHf(t) values and TDM1 of 0.62–0.90 Ga corresponding to the negative εHf(t) values. Molybdenite in the Taiyangshan deposit with 27.70 to 38.43 ppm Re suggests metal sourced from a mantle–crust mixture or from mafic and ultramafic rocks in the lower crust. The δ34S values obtained for pyrite, chalcopyrite, and molybdenite from the deposit range from + 1.3‰ to + 4.0‰, + 0.2‰ to + 1.1‰, and + 5.3‰ to + 5.9‰, respectively, suggesting a magmatic source for the sulfur. Calculated δ18Ofluid values for magmatic K-feldspar from porphyries (+ 13.3‰), hydrothermal K-feldspar from stockwork veins related to potassic alteration (+ 11.6‰), and hydrothermal sericite from quartz–pyrite veins (+ 8.6 to + 10.6‰) indicate the Taiyangshan deposit formed dominantly from magmatic water. Hydrogen isotope values for hydrothermal sericite ranging from − 85 to − 50‰ may indicate that magma degassing progressively depleted residual liquid in deuterium during the life of the magmatic–hydrothermal system. Alternatively, δD variability may have been caused by a minor amount of mixing with meteoric waters. We propose that the ore-related magma was derived from partial melting of the ancient Mesoproterozoic to Neoproterozoic middle to lower continental crust. This crust was likely metasomatized during earlier subduction, and the crustal magmas may have been contaminated with lithospheric mantle derived magma triggered by MASH (e.g., melting, assimilation, storage, and homogenization) processes during collisional orogeny. In addition, a significant proportion of the metals and sulfur supplied from mafic magma were simultaneously incorporated into the resultant hybrid magmas.
","language":"English","publisher":"International Association for Gondwana Research","doi":"10.1016/j.gr.2016.03.014","usgsCitation":"Kun-Feng Qiu, Taylor, R.D., Song, Y., Yu, H., Kai-Rui Song, and Li, N., 2016, Geologic and geochemical insights into the formation of the Taiyangshan porphyry copper–molybdenum deposit, Western Qinling Orogenic Belt, China: Gondwana Research, v. 35, p. 40-58, https://doi.org/10.1016/j.gr.2016.03.014.","productDescription":"19 p.","startPage":"40","endPage":"58","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-072464","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":322044,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"China","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 102,\n 32\n ],\n [\n 102,\n 36\n ],\n [\n 107,\n 36\n ],\n [\n 107,\n 32\n ],\n [\n 102,\n 32\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"35","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57500763e4b0ee97d51bb609","contributors":{"authors":[{"text":"Kun-Feng Qiu","contributorId":169784,"corporation":false,"usgs":false,"family":"Kun-Feng Qiu","affiliations":[{"id":24737,"text":"China University of Geosciences, Beijing","active":true,"usgs":false}],"preferred":false,"id":631055,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Taylor, Ryan D. 0000-0002-8845-5290 rtaylor@usgs.gov","orcid":"https://orcid.org/0000-0002-8845-5290","contributorId":3412,"corporation":false,"usgs":true,"family":"Taylor","given":"Ryan","email":"rtaylor@usgs.gov","middleInitial":"D.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":631054,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Song, Yao-Hui","contributorId":169785,"corporation":false,"usgs":false,"family":"Song","given":"Yao-Hui","email":"","affiliations":[{"id":24737,"text":"China University of Geosciences, Beijing","active":true,"usgs":false}],"preferred":false,"id":631056,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Yu, Hao-Cheng","contributorId":169788,"corporation":false,"usgs":false,"family":"Yu","given":"Hao-Cheng","email":"","affiliations":[{"id":24737,"text":"China University of Geosciences, Beijing","active":true,"usgs":false}],"preferred":false,"id":631059,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kai-Rui Song","contributorId":169786,"corporation":false,"usgs":false,"family":"Kai-Rui Song","affiliations":[{"id":24737,"text":"China University of Geosciences, Beijing","active":true,"usgs":false}],"preferred":false,"id":631057,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Li, Nan","contributorId":169787,"corporation":false,"usgs":false,"family":"Li","given":"Nan","email":"","affiliations":[{"id":24737,"text":"China University of Geosciences, Beijing","active":true,"usgs":false}],"preferred":false,"id":631058,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70174339,"text":"70174339 - 2016 - A millennial-scale record of Pb and Hg contamination in peatlands of the Sacramento-San Joaquin Delta of California, USA","interactions":[],"lastModifiedDate":"2016-07-08T13:22:05","indexId":"70174339","displayToPublicDate":"2016-05-01T14:30:00","publicationYear":"2016","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":"A millennial-scale record of Pb and Hg contamination in peatlands of the Sacramento-San Joaquin Delta of California, USA","docAbstract":"In this paper, we provide the first record of millennial patterns of Pb and Hg concentrations on the west coast of the United States. Peat cores were collected from two micro-tidal marshes in the Sacramento-San Joaquin Delta of California. Core samples were analyzed for Pb, Hg, and Ti concentrations and dated using radiocarbon, 210Pb, and 137Cs. Pre-anthropogenic concentrations of Pb and Hg in peat ranged from 0.60 to 13.0 µg g-1and from 6.9 to 71 ng g-1, respectively. For much of the past 6000+ years, the Delta was free from anthropogenic pollution, however, beginning in ~1425 CE, Hg and Pb concentrations, Pb/Ti ratios, Pb enrichment factors (EFs), and HgEFs all increased. Pb isotope compositions of the peat suggest that this uptick was likely caused by smelting activities originating in Asia. The next increases in Pb and Hg contamination occurred during the California Gold Rush (beginning ~1850 CE), when concentrations reached their highest levels (74 µg g-1 Pb, 990 ng g-1 Hg; PbEF = 12 and HgEF = 28). Lead concentrations increased again beginning in the ~1920s with the incorporation of Pb additives in gasoline. The phase-out of lead additives in the late 1980s was reflected in Pb isotope ratios and reductions in Pb concentrations in the surface layers of the peat. The rise and fall of Hg contamination was also tracked by the peat archive, with the highest Hg concentrations occurring just before 1963 CE and then decreasing during the post-1963 period. Overall, the results show that the Delta was a pristine region for most of its ~6700-year existence; however, since ~1425 CE, it has received Pb and Hg contamination from both global and regional sources.
","language":"English","publisher":"Elsevier B.V.","doi":"10.1016/j.scitotenv.2016.01.201","collaboration":"(REPEAT II project)","usgsCitation":"Drexler, J.Z., Alpers, C.N., Neymark, L., Paces, J.B., Taylor, H.E., and Fuller, C.C., 2016, A millennial-scale record of Pb and Hg contamination in peatlands of the Sacramento-San Joaquin Delta of California, USA: Science of the Total Environment, v. 551-552, p. 738-751, https://doi.org/10.1016/j.scitotenv.2016.01.201.","productDescription":"13 p.","startPage":"738","endPage":"751","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-071457","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":324937,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento–San Joaquin Delta of California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.25537109375,\n 41.94314874732696\n ],\n [\n -124.3212890625,\n 41.73852846935917\n ],\n [\n -124.20043945312499,\n 41.65649719441145\n ],\n [\n -124.178466796875,\n 41.36856413680967\n ],\n [\n -124.31030273437499,\n 41.16211393939692\n ],\n [\n -124.222412109375,\n 40.95501133048621\n ],\n [\n -124.53002929687499,\n 40.463666324587685\n ],\n [\n -124.45312499999999,\n 40.245991504199026\n ],\n [\n -123.90380859374999,\n 39.69873414348139\n ],\n [\n -123.914794921875,\n 39.317300373271024\n ],\n [\n -123.85986328124999,\n 38.89103282648846\n ],\n [\n -123.6181640625,\n 38.7283759182398\n ],\n [\n -123.11279296875001,\n 38.08268954483802\n ],\n [\n -123.07983398437499,\n 37.94419750075404\n ],\n [\n -122.84912109375,\n 37.90953361677018\n ],\n [\n -122.78320312499999,\n 37.57070524233116\n ],\n [\n -122.56347656249999,\n 37.59682400108367\n ],\n [\n -121.10229492187501,\n 37.75334401310656\n ],\n [\n -121.322021484375,\n 38.59970036588819\n ],\n [\n -121.79443359375,\n 39.78321267821705\n ],\n [\n -121.728515625,\n 40.830436877649255\n ],\n [\n -121.89331054687499,\n 41.623655390686395\n ],\n [\n -121.92626953124999,\n 41.97582726102573\n ],\n [\n -124.25537109375,\n 41.94314874732696\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"551-552","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5780ceaee4b0811616822296","contributors":{"authors":[{"text":"Drexler, Judith Z. 0000-0002-0127-3866 jdrexler@usgs.gov","orcid":"https://orcid.org/0000-0002-0127-3866","contributorId":167492,"corporation":false,"usgs":true,"family":"Drexler","given":"Judith","email":"jdrexler@usgs.gov","middleInitial":"Z.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":641962,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Alpers, Charles N. 0000-0001-6945-7365 cnalpers@usgs.gov","orcid":"https://orcid.org/0000-0001-6945-7365","contributorId":411,"corporation":false,"usgs":true,"family":"Alpers","given":"Charles","email":"cnalpers@usgs.gov","middleInitial":"N.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":641963,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Neymark, Leonid A. 0000-0003-4190-0278 lneymark@usgs.gov","orcid":"https://orcid.org/0000-0003-4190-0278","contributorId":140338,"corporation":false,"usgs":true,"family":"Neymark","given":"Leonid A.","email":"lneymark@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":641964,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Paces, James B. 0000-0002-9809-8493 jbpaces@usgs.gov","orcid":"https://orcid.org/0000-0002-9809-8493","contributorId":2514,"corporation":false,"usgs":true,"family":"Paces","given":"James","email":"jbpaces@usgs.gov","middleInitial":"B.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":641965,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Taylor, Howard E. hetaylor@usgs.gov","contributorId":1551,"corporation":false,"usgs":true,"family":"Taylor","given":"Howard","email":"hetaylor@usgs.gov","middleInitial":"E.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":641966,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fuller, Christopher C. 0000-0002-2354-8074 ccfuller@usgs.gov","orcid":"https://orcid.org/0000-0002-2354-8074","contributorId":1831,"corporation":false,"usgs":true,"family":"Fuller","given":"Christopher","email":"ccfuller@usgs.gov","middleInitial":"C.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":641967,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70170789,"text":"70170789 - 2016 - Spectrally based mapping of riverbed composition","interactions":[],"lastModifiedDate":"2016-05-03T10:52:50","indexId":"70170789","displayToPublicDate":"2016-05-01T12:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1801,"text":"Geomorphology","active":true,"publicationSubtype":{"id":10}},"title":"Spectrally based mapping of riverbed composition","docAbstract":"Remote sensing methods provide an efficient means of characterizing fluvial systems. This study evaluated the potential to map riverbed composition based on in situ and/or remote measurements of reflectance. Field spectra and substrate photos from the Snake River, Wyoming, USA, were used to identify different sediment facies and degrees of algal development and to quantify their optical characteristics. We hypothesized that accounting for the effects of depth and water column attenuation to isolate the reflectance of the streambed would enhance distinctions among bottom types and facilitate substrate classification. A bottom reflectance retrieval algorithm adapted from coastal research yielded realistic spectra for the 450 to 700 nm range; but bottom reflectance-based substrate classifications, generated using a random forest technique, were no more accurate than classifications derived from above-water field spectra. Additional hypothesis testing indicated that a combination of reflectance magnitude (brightness) and indices of spectral shape provided the most accurate riverbed classifications. Convolving field spectra to the response functions of a multispectral satellite and a hyperspectral imaging system did not reduce classification accuracies, implying that high spectral resolution was not essential. Supervised classifications of algal density produced from hyperspectral data and an inferred bottom reflectance image were not highly accurate, but unsupervised classification of the bottom reflectance image revealed distinct spectrally based clusters, suggesting that such an image could provide additional river information. We attribute the failure of bottom reflectance retrieval to yield more reliable substrate maps to a latent correlation between depth and bottom type. Accounting for the effects of depth might have eliminated a key distinction among substrates and thus reduced discriminatory power. Although further, more systematic study across a broader range of fluvial environments is needed to substantiate our initial results, this case study suggests that bed composition in shallow, clear-flowing rivers potentially could be mapped remotely.
","language":"English","publisher":"Elsevier Science Pub. Co.","publisherLocation":"New York, NY","doi":"10.1016/j.geomorph.2016.04.006","usgsCitation":"Legleiter, C.J., Stegman, T.K., and Overstreet, B.T., 2016, Spectrally based mapping of riverbed composition: Geomorphology, v. 264, p. 61-79, https://doi.org/10.1016/j.geomorph.2016.04.006.","productDescription":"19 p.","startPage":"61","endPage":"79","numberOfPages":"19","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-073537","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":471034,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.geomorph.2016.04.006","text":"Publisher Index Page"},{"id":320883,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"264","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5729cbbae4b0b13d3919a3c6","contributors":{"authors":[{"text":"Legleiter, Carl J. 0000-0003-0940-8013 cjl@usgs.gov","orcid":"https://orcid.org/0000-0003-0940-8013","contributorId":169002,"corporation":false,"usgs":true,"family":"Legleiter","given":"Carl","email":"cjl@usgs.gov","middleInitial":"J.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":628405,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stegman, Tobin K.","contributorId":169087,"corporation":false,"usgs":false,"family":"Stegman","given":"Tobin","email":"","middleInitial":"K.","affiliations":[{"id":6656,"text":"University of Wyoming, Renewable Resources","active":true,"usgs":false}],"preferred":false,"id":628406,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Overstreet, Brandon T. 0000-0001-7845-6671","orcid":"https://orcid.org/0000-0001-7845-6671","contributorId":63257,"corporation":false,"usgs":true,"family":"Overstreet","given":"Brandon","email":"","middleInitial":"T.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":false,"id":628407,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70171438,"text":"70171438 - 2016 - Regional patterns of total nitrogen concentrations in the National Rivers and Streams Assessment","interactions":[],"lastModifiedDate":"2017-01-18T09:20:26","indexId":"70171438","displayToPublicDate":"2016-05-01T01:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2456,"text":"Journal of Soil and Water Conservation","active":true,"publicationSubtype":{"id":10}},"title":"Regional patterns of total nitrogen concentrations in the National Rivers and Streams Assessment","docAbstract":"Patterns of nitrogen (N) concentrations in streams sampled by the National Rivers and Streams Assessment (NRSA) were examined semiquantitatively to identify regional differences in stream N levels. The data were categorized and analyzed by watershed size classes to reveal patterns of the concentrations that are consistent with the spatial homogeneity in natural and anthropogenic characteristics associated with regional differences in N levels. Ecoregions and mapped information on human activities including agricultural practices were used to determine the resultant regions. Marked differences in N levels were found among the nine aggregations of ecoregions used to report the results of the NRSA. We identified distinct regional patterns of stream N concentrations within the reporting regions that are associated with the characteristics of specific Level III ecoregions, groups of Level III ecoregions, groups of Level IV ecoregions, certain geographic characteristics within ecoregions, and/or particular watershed size classes. We described each of these regions and illustrated their areal extent and median and range in N concentrations. Understanding the spatial variability of nutrient concentrations in flowing waters and the apparent contributions that human and nonhuman factors have on different sizes of streams and rivers is critical to the development of effective water quality assessment and management plans. This semi-quantitative analysis is also intended to identify areas within which more detailed quantitative work can be conducted to determine specific regional factors associated with variations in stream N concentrations.
","language":"English","publisher":"Soil and Water Conservation Society","doi":"10.2489/jswc.71.3.167","usgsCitation":"Omernik, J.M., Paulsen, S.G., Griffith, G.E., and Weber, M.H., 2016, Regional patterns of total nitrogen concentrations in the National Rivers and Streams Assessment: Journal of Soil and Water Conservation, v. 71, no. 3, p. 167-181, https://doi.org/10.2489/jswc.71.3.167.","productDescription":"15 p.","startPage":"167","endPage":"181","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057215","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":322053,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"71","issue":"3","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-09","publicationStatus":"PW","scienceBaseUri":"57500771e4b0ee97d51bb70e","contributors":{"authors":[{"text":"Omernik, James M.","contributorId":169740,"corporation":false,"usgs":false,"family":"Omernik","given":"James","email":"","middleInitial":"M.","affiliations":[{"id":25578,"text":"USGS -Volunteer","active":true,"usgs":false}],"preferred":false,"id":630982,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Paulsen, Steven G.","contributorId":169741,"corporation":false,"usgs":false,"family":"Paulsen","given":"Steven","email":"","middleInitial":"G.","affiliations":[{"id":13529,"text":"US Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":630983,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Griffith, Glenn E. 0000-0001-7966-4720 ggriffith@usgs.gov","orcid":"https://orcid.org/0000-0001-7966-4720","contributorId":4053,"corporation":false,"usgs":true,"family":"Griffith","given":"Glenn","email":"ggriffith@usgs.gov","middleInitial":"E.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":630981,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Weber, Marc H.","contributorId":169742,"corporation":false,"usgs":false,"family":"Weber","given":"Marc","email":"","middleInitial":"H.","affiliations":[{"id":13529,"text":"US Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":630984,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70176210,"text":"70176210 - 2016 - Organic petrology and geochemistry of Eocene Suzak bituminous marl, north-central Afghanistan: Depositional environment and source rock potential","interactions":[],"lastModifiedDate":"2016-09-01T16:21:44","indexId":"70176210","displayToPublicDate":"2016-05-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2682,"text":"Marine and Petroleum Geology","active":true,"publicationSubtype":{"id":10}},"title":"Organic petrology and geochemistry of Eocene Suzak bituminous marl, north-central Afghanistan: Depositional environment and source rock potential","docAbstract":"Organic geochemistry and petrology of Eocene Suzak bituminous marl outcrop samples from Madr village in north-central Afghanistan were characterized via an integrated analytical approach to evaluate depositional environment and source rock potential. Multiple proxies suggest the organic-rich (TOC ∼6 wt.%) bituminous marls are ‘immature’ for oil generation (e.g., vitrinite Ro < 0.4%, Tmax < 425 °C, PI ≤ 0.05, C29 ααα S/S + R ≤ 0.12, C29 ββS/ββS+ααR ≤ 0.10, others), yet oil seeps are present at outcrop and live oil and abundant solid bitumen were observed via optical microscopy. Whole rock sulfur content is ∼2.3 wt.% whereas sulfur content is ∼5.0–5.6 wt.% in whole rock extracts with high polar components, consistent with extraction from S-rich Type IIs organic matter which could generate hydrocarbons at low thermal maturity. Low Fe-sulfide mineral abundance and comparison of Pr/Ph ratios between saturate and whole extracts suggest limited Fe concentration resulted in sulfurization of organic matter during early diagenesis. From these observations, we infer that a Type IIs kerogen in ‘immature’ bituminous marl at Madr could be generating high sulfur viscous oil which is seeping from outcrop. However, oil-seep samples were not collected for correlation studies. Aluminum-normalized trace element concentrations indicate enrichment of redox sensitive trace elements Mo, U and V and suggest anoxic-euxinic conditions during sediment deposition. The bulk of organic matter observed via optical microscopy is strongly fluorescent amorphous bituminite grading to lamalginite, possibly representing microbial mat facies. Short chain n-alkanes peak at C14–C16 (n-C17/n-C29 > 1) indicating organic input from marine algae and/or bacterial biomass, and sterane/hopane ratios are low (0.12–0.14). Monoaromatic steroids are dominated by C28clearly indicating a marine setting. High gammacerane index values (∼0.9) are consistent with anoxia stratification and may indicate intermittent saline-hypersaline conditions. Stable C isotope ratios also suggest a marine depositional scenario for the Suzak samples, consistent with the presence of marine foraminifera including abundant planktic globigerinida(?) and rare benthic discocyclina(?) and nummulites(?). Biomarker 2α-methylhopane for photosynthetic cyanobacteria implies shallow photic zone deposition of Madr marls and 3β-methylhopane indicates presence of methanotrophic archaea in the microbial consortium. The data presented herein are consistent with deposition of Suzak bituminous marls in shallow stratified waters of a restricted marine basin associated with the southeastern incipient or proto-Paratethys. Geochemical proxies from Suzak rock extracts (S content, high polar content, C isotopes, normal (αααR) C27–29 steranes, and C29/C30 and C26/C25 hopane ratios) are similar to extant data from Paleogene oils produced to the north in the Afghan-Tajik Basin. This observation may indicate laterally equivalent strata are effective source rocks as suggested by previous workers; however, further work is needed to strengthen oil-source correlations.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.marpetgeo.2016.02.029","usgsCitation":"Hackley, P.C., and Sanfilipo, J., 2016, Organic petrology and geochemistry of Eocene Suzak bituminous marl, north-central Afghanistan: Depositional environment and source rock potential: Marine and Petroleum Geology, v. 73, p. 572-589, https://doi.org/10.1016/j.marpetgeo.2016.02.029.","productDescription":"18 p.","startPage":"572","endPage":"589","ipdsId":"IP-069387","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":328205,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"73","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57c95130e4b0f2f0cec15bfc","contributors":{"authors":[{"text":"Hackley, Paul C. 0000-0002-5957-2551 phackley@usgs.gov","orcid":"https://orcid.org/0000-0002-5957-2551","contributorId":592,"corporation":false,"usgs":true,"family":"Hackley","given":"Paul","email":"phackley@usgs.gov","middleInitial":"C.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":647807,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sanfilipo, John 0000-0002-8739-5628 jsan@usgs.gov","orcid":"https://orcid.org/0000-0002-8739-5628","contributorId":140236,"corporation":false,"usgs":true,"family":"Sanfilipo","given":"John","email":"jsan@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":647808,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70178062,"text":"70178062 - 2016 - Developing fish trophic interaction indicators of climate change for the Great Lakes","interactions":[],"lastModifiedDate":"2016-11-01T15:10:34","indexId":"70178062","displayToPublicDate":"2016-05-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":9,"text":"Other Report"},"title":"Developing fish trophic interaction indicators of climate change for the Great Lakes","docAbstract":"This project addressed regional climate change effects on aquatic food webs in the Great Lakes. We sought insights by examining Lake Erie as a representative system with a high level of anthropogenic impacts, strong nutrient gradients, seasonal hypoxia, and spatial overlap of cold- and cool-water fish guilds. In Lake Erie and in large embayments throughout the Great Lakes basin, this situation is a concern for fishery managers, as climate change may exacerbate hypoxia and reduce habitat volume for some species. We examined fish community composition, fine-scale distribution, prey availability, diets, and biochemical tracers for dominant fishes from study areas with medium-high nutrient levels (mesotrophic, Fairport study area), and low nutrient levels (oligotrophic, Erie study area). This multi-year database (2011-2013) provides the ability to contrast years with wide variation in rainfall, winter ice-cover, and thermal stratification. In addition, multiple indicators of dietary and distributional responses to environmental variability will allow resource managers to select the most informative approach for addressing specific climate change questions. Our results support the incorporation of some relatively simple and cost-efficient approaches into existing agency monitoring programs to track the near-term condition status of fish and fish community composition by functional groupings. Other metrics appear better suited for understanding longer-term changes, and may take more resources to implement on an ongoing basis. Although we hypothesized that dietary overlap and similarity in selected species would be sharply different during thermal stratification and hypoxic episodes, we found little evidence of this. Instead, to our surprise, this study found that fish tended to aggregate at the edges of hypoxia, highlighting potential spatial changes in catch efficiency of the fishery. This work has had several positive impacts on a wide range of resource management and stakeholder activities, most notably in Lake Erie. The results were instrumental in the development of an interim decision rule for dealing with data collected during hypoxic events to improve stock assessment of Yellow Perch. In addition, novel findings from this study regarding spatial and temporal variability in hypoxia have aided US-Environmental Protection Agency in the development of a modified sampling protocol to more accurately quantify the central basin hypoxic zone, and this directly addressed a goal of the Great Lakes Water Quality Agreement of 2012 to reduce the extent and severity of hypoxia. Finally, the study areas developed in this project formed the basis for food web sampling in the 2014 bi-national Coordinated Science and Monitoring Initiative work in Lake Erie.
","language":"English","publisher":"Northeast Climate Science Center","usgsCitation":"Kraus, R.T., Knight, C.T., Gorman, A.M., Kocovsky, P.M., Weidel, B., and Rogers, M.W., 2016, Developing fish trophic interaction indicators of climate change for the Great Lakes, 70 p.","productDescription":"70 p.","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":330639,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":330638,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://necsc.umass.edu/biblio/developing-fish-trophic-interaction-indicators-climate-change-great-lakes"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5819a9c4e4b0bb36a4c91029","contributors":{"authors":[{"text":"Kraus, Richard T. 0000-0003-4494-1841 rkraus@usgs.gov","orcid":"https://orcid.org/0000-0003-4494-1841","contributorId":2609,"corporation":false,"usgs":true,"family":"Kraus","given":"Richard","email":"rkraus@usgs.gov","middleInitial":"T.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":652683,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Knight, Carey T.","contributorId":56529,"corporation":false,"usgs":true,"family":"Knight","given":"Carey","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":652684,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gorman, Ann Marie","contributorId":145525,"corporation":false,"usgs":false,"family":"Gorman","given":"Ann","email":"","middleInitial":"Marie","affiliations":[],"preferred":false,"id":652685,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kocovsky, Patrick M. 0000-0003-4325-4265 pkocovsky@usgs.gov","orcid":"https://orcid.org/0000-0003-4325-4265","contributorId":3429,"corporation":false,"usgs":true,"family":"Kocovsky","given":"Patrick","email":"pkocovsky@usgs.gov","middleInitial":"M.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true},{"id":251,"text":"Ecosystems Mission Area","active":false,"usgs":true}],"preferred":true,"id":652686,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Weidel, Brian 0000-0001-6095-2773 bweidel@usgs.gov","orcid":"https://orcid.org/0000-0001-6095-2773","contributorId":2485,"corporation":false,"usgs":true,"family":"Weidel","given":"Brian","email":"bweidel@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":652687,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rogers, Mark W. 0000-0001-7205-5623 mwrogers@usgs.gov","orcid":"https://orcid.org/0000-0001-7205-5623","contributorId":4590,"corporation":false,"usgs":true,"family":"Rogers","given":"Mark","email":"mwrogers@usgs.gov","middleInitial":"W.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":652688,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70178545,"text":"70178545 - 2016 - Assessing the role of seabirds in the ecology of influenza A viruses","interactions":[],"lastModifiedDate":"2018-07-15T18:33:20","indexId":"70178545","displayToPublicDate":"2016-05-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":948,"text":"Avian Diseases","active":true,"publicationSubtype":{"id":10}},"title":"Assessing the role of seabirds in the ecology of influenza A viruses","docAbstract":"Wild waterbirds, specifically waterfowl, gulls, and shorebirds, are recognized as the primordial reservoir of influenza A viruses (IAVs). However, the role of seabirds, an abundant, diverse, and globally distributed group of birds, in the perpetuation and transmission of IAVs is less clear. Here we summarize published and publicly available data for influenza viruses in seabirds, which for the purposes of this study are defined as birds that exhibit a largely or exclusively pelagic lifestyle and exclude waterfowl, gulls, and shorebirds, and we review this collective dataset to assess the role of seabirds in the influenza A ecology. Since 1961, more than 40,000 samples have been collected worldwide from the seabirds considered here and screened, using a variety of techniques, for evidence of active or past IAV infection. From these data, the overall prevalence of active infection has been estimated to be very low; however, serological data provide evidence that some seabird species are more frequently exposed to IAVs. Sequence data for viruses from seabirds are limited, except for murres (common murre, Uria aalge, and thick-billed murre, Uria lomvia; family Alcidae) for which there are full or partial genome sequences available for more than 80 viruses. Characterization of these viruses suggests that murres are infected with Group 1 hemagglutinin subtype viruses more frequently as compared to Group 2 and also indicates that these northern, circumpolar birds are frequently infected by intercontinental reassortant viruses. Greater temporal and spatial sampling and characterization of additional viruses are required to better understand the role of seabirds in global IAV dynamics.
","language":"English","publisher":"American Association of Avian Pathologists","doi":"10.1637/11135-050815-RegR","usgsCitation":"Lang, A.S., Lebarbenchon, C., Robertson, G.J., Ramey, A.M., Waldenstrom, J., and Wille, M., 2016, Assessing the role of seabirds in the ecology of influenza A viruses: Avian Diseases, v. 60, no. 1s, p. 378-386, https://doi.org/10.1637/11135-050815-RegR.","productDescription":"9 p.","startPage":"378","endPage":"386","ipdsId":"IP-065494","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":331238,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"60","issue":"1s","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"583d5034e4b0d9329c80c59f","contributors":{"authors":[{"text":"Lang, Andrew S.","contributorId":177028,"corporation":false,"usgs":false,"family":"Lang","given":"Andrew","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":654331,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lebarbenchon, Camille","contributorId":140670,"corporation":false,"usgs":false,"family":"Lebarbenchon","given":"Camille","email":"","affiliations":[],"preferred":false,"id":654332,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ramey, Andrew M. 0000-0002-3601-8400 aramey@usgs.gov","orcid":"https://orcid.org/0000-0002-3601-8400","contributorId":1872,"corporation":false,"usgs":true,"family":"Ramey","given":"Andrew","email":"aramey@usgs.gov","middleInitial":"M.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":654336,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Robertson, Gregory J.","contributorId":173883,"corporation":false,"usgs":false,"family":"Robertson","given":"Gregory","email":"","middleInitial":"J.","affiliations":[{"id":27311,"text":"Wildlife Research Division, Science and Technology Branch, Environment and Climate","active":true,"usgs":false}],"preferred":false,"id":654333,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Waldenstrom, Jonas","contributorId":42891,"corporation":false,"usgs":true,"family":"Waldenstrom","given":"Jonas","email":"","affiliations":[],"preferred":false,"id":654334,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wille, Michelle","contributorId":173881,"corporation":false,"usgs":false,"family":"Wille","given":"Michelle","email":"","affiliations":[{"id":27309,"text":"Memorial University of Newfoundland, St. John’s, NL A1B 3X9, Canada","active":true,"usgs":false}],"preferred":false,"id":654335,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70192507,"text":"70192507 - 2016 - Trends in pesticide use on soybean, corn and cotton since the introduction of major genetically modified crops in the United States","interactions":[],"lastModifiedDate":"2017-10-26T10:27:36","indexId":"70192507","displayToPublicDate":"2016-05-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3035,"text":"Pest Management Science","active":true,"publicationSubtype":{"id":10}},"title":"Trends in pesticide use on soybean, corn and cotton since the introduction of major genetically modified crops in the United States","docAbstract":"BACKGROUND
Genetically modified (GM) varieties of soybean, corn and cotton have largely replaced conventional varieties in the United States. The most widely used applications of GM technology have been the development of crops that are resistant to a specific broad-spectrum herbicide (primarily glyphosate) or that produce insecticidal compounds within the plant itself. With the widespread adoption of GM crops, a decline in the use of conventional pesticides was expected.
RESULTS
There has been a reduction in the annual herbicide application rate to corn since the advent of GM crops, but the herbicide application rate is mostly unchanged for cotton. Herbicide use on soybean has increased. There has been a substantial reduction in the amount of insecticides used on both corn and cotton since the introduction of GM crops.
CONCLUSIONS
The observed changes in pesticide use are likely to be the result of many factors, including the introduction of GM crops, regulatory restrictions on some conventional pesticides, introduction of new pesticide technologies and changes in farming practices. In order to help protect human and environmental health and to help agriculture plan for the future, more detailed and complete documentation on pesticide use is needed on a frequent and ongoing basis.
","language":"English","publisher":"Wiley","doi":"10.1002/ps.4082","usgsCitation":"Coupe, R.H., and Capel, P.D., 2016, Trends in pesticide use on soybean, corn and cotton since the introduction of major genetically modified crops in the United States: Pest Management Science, v. 72, no. 5, p. 1013-1022, https://doi.org/10.1002/ps.4082.","productDescription":"10 p.","startPage":"1013","endPage":"1022","ipdsId":"IP-066541","costCenters":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"links":[{"id":347436,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"72","issue":"5","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2015-08-10","publicationStatus":"PW","scienceBaseUri":"5a07ea42e4b09af898c8cc70","contributors":{"authors":[{"text":"Coupe, Richard H. 0000-0001-8679-1015 rhcoupe@usgs.gov","orcid":"https://orcid.org/0000-0001-8679-1015","contributorId":551,"corporation":false,"usgs":true,"family":"Coupe","given":"Richard","email":"rhcoupe@usgs.gov","middleInitial":"H.","affiliations":[{"id":394,"text":"Mississippi Water Science Center","active":true,"usgs":true}],"preferred":true,"id":716096,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Capel, Paul D. 0000-0003-1620-5185 capel@usgs.gov","orcid":"https://orcid.org/0000-0003-1620-5185","contributorId":1002,"corporation":false,"usgs":true,"family":"Capel","given":"Paul","email":"capel@usgs.gov","middleInitial":"D.","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":716095,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70170957,"text":"70170957 - 2016 - Challenges for mapping cyanotoxin patterns from remote sensing of cyanobacteria","interactions":[],"lastModifiedDate":"2018-08-09T12:12:53","indexId":"70170957","displayToPublicDate":"2016-04-30T10:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1878,"text":"Harmful Algae","active":true,"publicationSubtype":{"id":10}},"title":"Challenges for mapping cyanotoxin patterns from remote sensing of cyanobacteria","docAbstract":"Using satellite imagery to quantify the spatial patterns of cyanobacterial toxins has several challenges. These challenges include the need for surrogate pigments – since cyanotoxins cannot be directly detected by remote sensing, the variability in the relationship between the pigments and cyanotoxins – especially microcystins (MC), and the lack of standardization of the various measurement methods. A dual-model strategy can provide an approach to address these challenges. One model uses either chlorophyll-a (Chl-a) or phycocyanin (PC) collected in situ as a surrogate to estimate the MC concentration. The other uses a remote sensing algorithm to estimate the concentration of the surrogate pigment. Where blooms are mixtures of cyanobacteria and eukaryotic algae, PC should be the preferred surrogate to Chl-a. Where cyanobacteria dominate, Chl-a is a better surrogate than PC for remote sensing. Phycocyanin is less sensitive to detection by optical remote sensing, it is less frequently measured, PC laboratory methods are still not standardized, and PC has greater intracellular variability. Either pigment should not be presumed to have a fixed relationship with MC for any water body. The MC-pigment relationship can be valid over weeks, but have considerable intra- and inter-annual variability due to changes in the amount of MC produced relative to cyanobacterial biomass. To detect pigments by satellite, three classes of algorithms (analytic, semi-analytic, and derivative) have been used. Analytical and semi-analytical algorithms are more sensitive but less robust than derivatives because they depend on accurate atmospheric correction; as a result derivatives are more commonly used. Derivatives can estimate Chl-a concentration, and research suggests they can detect and possibly quantify PC. Derivative algorithms, however, need to be standardized in order to evaluate the reproducibility of parameterizations between lakes. A strategy for producing useful estimates of microcystins from cyanobacterial biomass is described, provided cyanotoxin variability is addressed.
","language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam","doi":"10.1016/j.hal.2016.01.005","usgsCitation":"Stumpf, R.P., Davis, T.W., Wynne, T.T., Graham, J., Loftin, K.A., Johengen, T., Gossiaux, D., Palladino, D., and Burtner, A., 2016, Challenges for mapping cyanotoxin patterns from remote sensing of cyanobacteria: Harmful Algae, v. 54, p. 160-173, https://doi.org/10.1016/j.hal.2016.01.005.","productDescription":"14 p.","startPage":"160","endPage":"173","numberOfPages":"14","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070534","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":471038,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.hal.2016.01.005","text":"Publisher Index Page"},{"id":321204,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"54","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5736faade4b0dae0d5e03bf4","contributors":{"authors":[{"text":"Stumpf, Rick P","contributorId":169288,"corporation":false,"usgs":false,"family":"Stumpf","given":"Rick","email":"","middleInitial":"P","affiliations":[{"id":6637,"text":"National Oceanic and Atmospheric Administration, Northwest Fisheries Science Center, 2725 Montlake Blvd E, Seattle, WA 98112","active":true,"usgs":false}],"preferred":false,"id":629218,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Davis, Timothy W.","contributorId":169289,"corporation":false,"usgs":false,"family":"Davis","given":"Timothy","email":"","middleInitial":"W.","affiliations":[{"id":6637,"text":"National Oceanic and Atmospheric Administration, Northwest Fisheries Science Center, 2725 Montlake Blvd E, Seattle, WA 98112","active":true,"usgs":false}],"preferred":false,"id":629219,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wynne, Timothy T.","contributorId":169290,"corporation":false,"usgs":false,"family":"Wynne","given":"Timothy","email":"","middleInitial":"T.","affiliations":[{"id":6637,"text":"National Oceanic and Atmospheric Administration, Northwest Fisheries Science Center, 2725 Montlake Blvd E, Seattle, WA 98112","active":true,"usgs":false}],"preferred":false,"id":629220,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Graham, Jennifer L. 0000-0002-6420-9335 jlgraham@usgs.gov","orcid":"https://orcid.org/0000-0002-6420-9335","contributorId":150737,"corporation":false,"usgs":true,"family":"Graham","given":"Jennifer L.","email":"jlgraham@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true},{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":false,"id":629217,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Loftin, Keith A. 0000-0001-5291-876X kloftin@usgs.gov","orcid":"https://orcid.org/0000-0001-5291-876X","contributorId":868,"corporation":false,"usgs":true,"family":"Loftin","given":"Keith","email":"kloftin@usgs.gov","middleInitial":"A.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":629221,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Johengen, T.H.","contributorId":169291,"corporation":false,"usgs":false,"family":"Johengen","given":"T.H.","affiliations":[{"id":25465,"text":"Cooperative Institute for Limnology and Ecosystem Research","active":true,"usgs":false}],"preferred":false,"id":629222,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gossiaux, D.","contributorId":169292,"corporation":false,"usgs":false,"family":"Gossiaux","given":"D.","affiliations":[{"id":25466,"text":"National Oceanic and Atmostpheric Administration","active":true,"usgs":false}],"preferred":false,"id":629223,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Palladino, D.","contributorId":169293,"corporation":false,"usgs":false,"family":"Palladino","given":"D.","email":"","affiliations":[{"id":25465,"text":"Cooperative Institute for Limnology and Ecosystem Research","active":true,"usgs":false}],"preferred":false,"id":629224,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Burtner, A.","contributorId":169294,"corporation":false,"usgs":false,"family":"Burtner","given":"A.","email":"","affiliations":[{"id":25465,"text":"Cooperative Institute for Limnology and Ecosystem Research","active":true,"usgs":false}],"preferred":false,"id":629225,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70170356,"text":"fs20163026 - 2016 - Urban development and stream ecosystem health—Science capabilities of the U.S. Geological Survey","interactions":[],"lastModifiedDate":"2016-04-29T13:41:56","indexId":"fs20163026","displayToPublicDate":"2016-04-29T12:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-3026","title":"Urban development and stream ecosystem health—Science capabilities of the U.S. Geological Survey","docAbstract":"Urban development creates multiple stressors that can degrade stream ecosystems by changing stream hydrology, water quality, and physical habitat. Contaminants, habitat destruction, and increasing streamflow variability resulting from urban development have been associated with the disruption of biological communities, particularly the loss of sensitive aquatic biota. Understanding how algal, invertebrate, and fish communities respond to these physical and chemical stressors can provide important clues as to how streams should be managed to protect stream ecosystems as a watershed becomes increasingly urbanized. The U.S. Geological Survey continues to lead monitoring efforts and scientific studies on the effects of urban development on stream ecosystems in metropolitan areas across the United States.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20163026","collaboration":"Northeast Region Urban Landscape Capabilities Team","usgsCitation":"U.S. Geological Survey, 2016, Urban development and stream ecosystem health—Science capabilities of the U.S. Geological Survey: U.S. Geological Survey Fact Sheet 2016–3026, 2 p., https://dx.doi.org/10.3133/fs20163026.","productDescription":"2 p.","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-074179","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":320444,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2016/3026/fs20163026.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2016-3026"},{"id":320445,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://dx.doi.org/10.3133/fs20163023","text":"Fact Sheet 2016-3023"},{"id":320443,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2016/3026/coverthb.jpg"},{"id":320446,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://dx.doi.org/10.3133/fs20163024","text":"Fact Sheet 2016-3024"},{"id":320447,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://dx.doi.org/10.3133/fs20163025","text":"Fact Sheet 2016-3025"}],"contact":"U.S. Geological Survey
Northeast Region Urban Landscapes Capability Team
Email: GS-NE_ULCT@usgs.gov
Managing the urban-water cycle has increasingly become a challenge for water-resources planners and regulators faced with the problem of providing clean drinking water to urban residents. Sanitary and combined sanitary and storm sewer networks convey wastewater to centralized treatment plants. Impervious surfaces, which include roads, parking lots, and buildings, increase stormwater runoff and the efficiency by which runoff is conveyed to nearby stream channels; therefore, impervious surfaces increase the risk of urban flooding and alteration of natural ecosystems. These challenges will increase with the expansion of urban centers and the probable effects of climate change on precipitation patterns. Understanding the urban-water cycle is critical to effectively manage water resources and to protect people, infrastructure, and urban-stream ecosystems. As a leader in water-supply, wastewater, and stormwater assessments, the U.S. Geological Survey has the expertise and resources needed to monitor, model, and interpret data related to the urban-water cycle and thereby enable water-resources managers to make informed decisions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20163025","collaboration":"Northeast Region Urban Landscape Capabilities Team","usgsCitation":"U.S. Geological Survey, 2016, Urban infrastructure and water management—Science capabilities of the U.S. Geological Survey: U.S. Geological Survey Fact Sheet 2016–3025, 2 p., https://dx.doi.org/10.3133/fs20163025.","productDescription":"2 p.","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-074177","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":320439,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2016/3025/fs20163025.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2016-3025"},{"id":320438,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2016/3025/coverthb.jpg"},{"id":320440,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://dx.doi.org/10.3133/fs20163023","text":"Fact Sheet 2016-3023"},{"id":320441,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://dx.doi.org/10.3133/fs20163024","text":"Fact Sheet 2016-3024"},{"id":320442,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://dx.doi.org/10.3133/fs20163026","text":"Fact Sheet 2016-3026"}],"contact":"U.S. Geological Survey
Northeast Region Urban Landscapes Capability Team
Email: GS-NE_ULCT@usgs.gov
Streams and estuaries with urban watersheds commonly exhibit increased streamflow and decreased base flow; diminished stream-channel stability; excessive amounts of contaminants such as pesticides, metals, industrial and municipal waste, and combustion products; and alterations to biotic community structure. Collectively, these detrimental effects have been termed the “urban-stream syndrome.” Water-resource managers seek to lessen the effects on receiving water bodies of new urban development and remediate the effects in areas of existing urbanization. Similarly, the scientific community has produced extensive research on these topics, with researchers from the U.S. Geological Survey (USGS) leading many studies of urban streams and the processes responsible for the urban-stream syndrome. Increasingly, USGS studies are evaluating the effects of management and restoration activities to better understand how urban waters respond to the implementation of management practices. The USGS has expertise in collecting and interpreting data for many physical, chemical, and ecological processes in urban waters and, thus, provides holistic assessments to inform managers of urban water resources.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20163024","collaboration":"Northeast Region Urban Landscape Capabilities Team","usgsCitation":"U.S. Geological Survey, 2016, Contaminants in urban waters—Science capabilities of the U.S. Geological Survey: U.S. Geological Survey Fact Sheet 2016–3024, 2 p., https://dx.doi.org/10.3133/fs20163024.","productDescription":"2 p.","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-074176","costCenters":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true}],"links":[{"id":320432,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2016/3024/coverthb.jpg"},{"id":320433,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2016/3024/fs20163024.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2016-3024"},{"id":320434,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://dx.doi.org/10.3133/fs20163023","text":"Fact Sheet 2016-3023","description":"FS 2016-3024"},{"id":320435,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://dx.doi.org/10.3133/fs20163025","text":"Fact Sheet 2016-3025","description":"FS 2016-3024"},{"id":320436,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://dx.doi.org/10.3133/fs20163026","text":"Fact Sheet 2016-3026","description":"FS 2016-3024"}],"contact":"U.S. Geological Survey
Northeast Region Urban Landscapes Capability Team
Email: GS-NE_ULCT@usgs.gov
Urbanization affects streamflow characteristics, coastal flooding, and groundwater recharge. Increasing impervious areas, streamflow diversions, and groundwater pumpage are some of the ways that the natural water cycle is affected by urbanization. Assessment of the relations among these factors and changes in land use helps water-resource managers with issues such as stormwater management and vulnerability to flood and drought. Scientists with the U.S. Geological Survey (USGS) have the expertise to monitor and model urban hydrologic systems. Streamflow and groundwater data are available in national databases, and analyses of these data, including identification of long-term streamflow trends and the efficacy of management practices, are published in USGS reports.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20163023","collaboration":"Northeast Region Urban Landscape Capabilities Team ","usgsCitation":"U.S. Geological Survey, 2016, Urban hydrology—Science capabilities of the U.S. Geological Survey: U.S. Geological Survey Fact Sheet 2016–3023, 2 p., https://dx.doi.org/10.3133/fs20163023.","productDescription":"2 p.","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-074174","costCenters":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"links":[{"id":320426,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://dx.doi.org/10.3133/fs20163025","text":"Fact Sheet 2016-3025","description":"FS 2016-3023"},{"id":320425,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://dx.doi.org/10.3133/fs20163024","text":"Fact Sheet 2016-3024","description":"FS 2016-3023"},{"id":320423,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2016/3023/coverthb.jpg"},{"id":320427,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://dx.doi.org/10.3133/fs20163026","text":"Fact Sheet 2016-3026","description":"FS 2016-3023"},{"id":320424,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2016/3023/fs20163023.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2016-3023"}],"contact":"U.S. Geological Survey
Northeast Region Urban Landscapes Capability Team
Email: GS-NE_ULCT@usgs.gov
Evidence suggests that lakes are important sites for atmospheric CO2 exchange and so play a substantial role in the global carbon budget. Previous research has 2 weaknesses: (1) most data have been collected only during the open-water or summer seasons, and (2) data are concentrated principally on natural lakes in northern latitudes. Here, we report on the full annual cycle of atmospheric CO2 exchanges of 15 oligotrophic to eutrophic reservoirs in the Glacial Till Plains of the United States. With one exception, these reservoirs showed an overall loss of CO2 during the year, with most values within the lower range reported for temperate lakes. There was a strong cross-system seasonal pattern: an average of 70% of total annual CO2 efflux occurred by the end of spring mixis; some 20% of annual flux was reabsorbed during summer stratification; and the remaining 50% of efflux was lost during autumnal mixing. Net annual flux was negatively correlated with depth and positively correlated with both water residence time and DOC, with the smallest annual CO2 efflux measured in shallow fertile impoundments. Strong correlations yield relationships allowing regional up-scaling of CO2 evasion. Understanding lacustrine CO2 uptake and evasion requires seasonal analyses across the full range of lake trophic states and morphometric attributes.
","language":"English","publisher":"International Society of Limnology","doi":"10.5268/IW-6.2.982","usgsCitation":"Jones, J., Obrecht, D.V., Graham, J., Balmer, M.B., Filstrup, C.T., and Downing, J.A., 2016, Seasonal patterns in carbon dioxide in 15 mid-continent (USA) reservoirs: Inland Waters, v. 2, no. 6, p. 265-272, https://doi.org/10.5268/IW-6.2.982.","productDescription":"8 p.","startPage":"265","endPage":"272","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-074423","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":471040,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5268/iw-6.2.982","text":"Publisher Index Page"},{"id":320803,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Missouri","county":"Adair County, Chariton County, Harrison County, Linn County, Mercer County, Nodaway 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Mercury (Hg) monitoring programs are valuable for generating data that can be compiled for spatially broad syntheses to identify emergent ecosystem properties that influence fish Hg bioaccumulation. Fish total Hg (THg) concentrations were evaluated across the Western United States (US) and Canada, a region defined by extreme gradients in habitat structure and water management. A database was compiled with THg concentrations in 96,310 fish that comprised 206 species from 4262 locations, and used to evaluate the spatial distribution of fish THg across the region and effects of species, foraging guilds, habitats, and ecoregions. Areas of elevated THg exposure were identified by developing a relativized estimate of fish mercury concentrations at a watershed scale that accounted for the variability associated with fish species, fish size, and site effects. THg concentrations in fish muscle ranged between 0.001 and 28.4 (μg/g wet weight (ww)) with a geometric mean of 0.17. Overall, 30% of individual fish samples and 17% of means by location exceeded the 0.30 μg/g ww US EPA fish tissue criterion. Fish THg concentrations differed among habitat types, with riverine habitats consistently higher than lacustrine habitats. Importantly, fish THg concentrations were not correlated with sediment THg concentrations at a watershed scale, but were weakly correlated with sediment MeHg concentrations, suggesting that factors influencing MeHg production may be more important than inorganic Hg loading for determining fish MeHg exposure. There was large heterogeneity in fish THg concentrations across the landscape; THg concentrations were generally higher in semi-arid and arid regions such as the Great Basin and Desert Southwest, than in temperate forests. Results suggest that fish mercury exposure is widespread throughout Western US and Canada, and that species, habitat type, and region play an important role in influencing ecological risk of mercury in aquatic ecosystems.
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Robin, Wiener James G., Evers David C., Lepak Jesse M., Davis Jay A., Pritz Colleen Flanagan","journalName":"Science of The Total Environment","publicationDate":"10/2016"},"contributors":{"authors":[{"text":"Eagles-Smith, Collin A. 0000-0003-1329-5285 ceagles-smith@usgs.gov","orcid":"https://orcid.org/0000-0003-1329-5285","contributorId":505,"corporation":false,"usgs":true,"family":"Eagles-Smith","given":"Collin","email":"ceagles-smith@usgs.gov","middleInitial":"A.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":627015,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ackerman, Joshua T. 0000-0002-3074-8322 jackerman@usgs.gov","orcid":"https://orcid.org/0000-0002-3074-8322","contributorId":147078,"corporation":false,"usgs":true,"family":"Ackerman","given":"Joshua T.","email":"jackerman@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":627016,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Willacker, James J. jwillacker@usgs.gov","contributorId":5614,"corporation":false,"usgs":true,"family":"Willacker","given":"James","email":"jwillacker@usgs.gov","middleInitial":"J.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":627017,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tate, Michael T. 0000-0003-1525-1219 mttate@usgs.gov","orcid":"https://orcid.org/0000-0003-1525-1219","contributorId":3144,"corporation":false,"usgs":true,"family":"Tate","given":"Michael T.","email":"mttate@usgs.gov","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":627018,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lutz, Michelle A. malutz@usgs.gov","contributorId":167259,"corporation":false,"usgs":true,"family":"Lutz","given":"Michelle","email":"malutz@usgs.gov","middleInitial":"A.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":627019,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fleck, Jacob 0000-0002-3217-3972 jafleck@usgs.gov","orcid":"https://orcid.org/0000-0002-3217-3972","contributorId":168694,"corporation":false,"usgs":true,"family":"Fleck","given":"Jacob","email":"jafleck@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":627020,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Stewart, A. 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A key driver of the ecosystem affecting the distribution and abundance of organisms is the timing, distribution, and volume of water flows that result in water depth patterns across the landscape. American alligators (Alligator mississippiensis) are one of the ecological indicators being used to assess Everglades restoration because they are a keystone species and integrate biological impacts of hydrological operations through all life stages. Alligator body condition (the relative fatness of an animal) is one of the metrics being used and targets have been set to allow us to track progress. We examined trends in alligator body condition using Fulton’s K over a 15 year period (2000–2014) at seven different wetland areas within the Everglades ecosystem, assessed patterns and trends relative to restoration targets, and related those trends to hydrologic variables. We developed a series of 17 a priori hypotheses that we tested with an information theoretic approach to identify which hydrologic factors affect alligator body condition. Alligator body condition was highest throughout the Everglades during the early 2000s and is approximately 5–10% lower now (2014). Values have varied by year, area, and hydrology. Body condition was positively correlated with range in water depth and fall water depth. Our top model was the “Current” model and included variables that describe current year hydrology (spring depth, fall depth, hydroperiod, range, interaction of range and fall depth, interaction of range and hydroperiod). Across all models, interaction between range and fall water depth was the most important variable (relative weight of 1.0) followed by spring and fall water depths (0.99), range (0.96), hydroperiod (0.95) and interaction between range and hydroperiod (0.95). Our work provides additional evidence that restoring a greater range in annual water depths is important for improvement of alligator body condition and ecosystem function. This information can be incorporated into both planning and operations to assist in reaching Everglades restoration goals.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2016.03.003","usgsCitation":"Brandt, L., Beauchamp, J.S., Jeffery, B.M., Cherkiss, M.S., and Mazzotti, F., 2016, Fluctuating water depths affect American alligator (Alligator mississippiensis) body condition in the Everglades, Florida, USA: Ecological Indicators, v. 67, p. 441-450, https://doi.org/10.1016/j.ecolind.2016.03.003.","productDescription":"10 p.","startPage":"441","endPage":"450","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069792","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":471046,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolind.2016.03.003","text":"Publisher Index Page"},{"id":320585,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Everglades","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.4473876953125,\n 26.676913083105454\n ],\n [\n -80.36773681640625,\n 26.684275490019488\n ],\n [\n -80.23590087890624,\n 26.571333057252076\n ],\n [\n -80.23590087890624,\n 26.382027976025352\n ],\n [\n -80.29083251953124,\n 26.347575438494673\n ],\n [\n -80.29632568359375,\n 26.185018250078308\n ],\n [\n -80.35400390625,\n 26.118452068488097\n ],\n [\n -80.44189453125,\n 26.145576207592274\n ],\n [\n -80.43365478515625,\n 25.962983554822678\n ],\n [\n -80.48858642578125,\n 25.760319754713887\n ],\n [\n -80.57373046875,\n 25.46559428893416\n ],\n [\n -80.93353271484375,\n 25.40854689267053\n ],\n [\n -81.10382080078125,\n 25.631621577258493\n ],\n [\n -80.8428955078125,\n 25.767740402713383\n ],\n [\n -80.83740234375,\n 26.165298896316042\n ],\n [\n -80.82366943359375,\n 26.330345320410842\n ],\n [\n -80.54901123046875,\n 26.406630642556795\n ],\n [\n -80.452880859375,\n 26.458279167084125\n ],\n [\n -80.4473876953125,\n 26.676913083105454\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"67","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5721d4a3e4b0b13d39129145","contributors":{"authors":[{"text":"Brandt, Laura A.","contributorId":18608,"corporation":false,"usgs":false,"family":"Brandt","given":"Laura A.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":627656,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beauchamp, Jeffrey S.","contributorId":138880,"corporation":false,"usgs":false,"family":"Beauchamp","given":"Jeffrey","email":"","middleInitial":"S.","affiliations":[{"id":12559,"text":"University of Florida, FLEC","active":true,"usgs":false}],"preferred":false,"id":627657,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jeffery, Brian M.","contributorId":138879,"corporation":false,"usgs":false,"family":"Jeffery","given":"Brian","email":"","middleInitial":"M.","affiliations":[{"id":12558,"text":"University of Florida, Gainesville","active":true,"usgs":false}],"preferred":false,"id":627658,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cherkiss, Michael S. 0000-0002-7802-6791 mcherkiss@usgs.gov","orcid":"https://orcid.org/0000-0002-7802-6791","contributorId":4571,"corporation":false,"usgs":true,"family":"Cherkiss","given":"Michael","email":"mcherkiss@usgs.gov","middleInitial":"S.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":627655,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mazzotti, Frank J.","contributorId":12358,"corporation":false,"usgs":false,"family":"Mazzotti","given":"Frank J.","affiliations":[{"id":12604,"text":"Department of Wildlife Ecology and Conservation, Fort Lauderdale Research and Education Center, 3205 College Avenue, University of Florida, Davie, FL 33314, USA","active":true,"usgs":false}],"preferred":false,"id":627659,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70173602,"text":"70173602 - 2016 - Interactions between hatch dates, growth rates, and mortality of Age-0 native Rainbow Smelt and nonnative Alewife in Lake Champlain","interactions":[],"lastModifiedDate":"2016-06-07T16:35:26","indexId":"70173602","displayToPublicDate":"2016-04-27T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Interactions between hatch dates, growth rates, and mortality of Age-0 native Rainbow Smelt and nonnative Alewife in Lake Champlain","docAbstract":"Timing of hatch in fish populations can be critical for first-year survival and, therefore, year-class strength and subsequent species interactions. We compared hatch timing, growth rates, and subsequent mortality of age-0 Rainbow Smelt Osmerus mordax and Alewife Alosa pseudoharengus, two common open-water fish species of northern North America. In our study site, Lake Champlain, Rainbow Smelt hatched (beginning May 26) almost a month earlier than Alewives (June 20). Abundance in the sampling area was highest in July for age-0 Rainbow Smelt and August for age-0 Alewives. Late-hatching individuals of both species grew faster than those hatching earlier (0.6 mm/d versus 0.4 for Rainbow Smelt; 0.7 mm/d versus 0.6 for Alewives). Mean mortality rate during the first 45 d of life was 3.4%/d for age-0 Rainbow Smelt and was 5.5%/d for age-0 Alewives. Alewife mortality rates did not differ with hatch timing but daily mortality rates of Rainbow Smelt were highest for early-hatching fish. Cannibalism is probably the primary mortality source for age-0 Rainbow Smelt in this lake. Therefore, hatching earlier may not be advantageous because the overlap of adult and age-0 Rainbow Smelt is highest earlier in the season. However, Alewives, first documented in Lake Champlain in 2003, may increase the mortality of age-0 Rainbow Smelt in the summer, which should favor selection for earlier hatching.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/00028487.2016.1143401","usgsCitation":"Parrish, D.L., Simonin, P.W., Rudstam, L.G., Pientka, B., and Sullivan, P., 2016, Interactions between hatch dates, growth rates, and mortality of Age-0 native Rainbow Smelt and nonnative Alewife in Lake Champlain: Transactions of the American Fisheries Society, v. 145, no. 3, p. 649-656, https://doi.org/10.1080/00028487.2016.1143401.","productDescription":"8 p.","startPage":"649","endPage":"656","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064234","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":323231,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Vermont","otherGeospatial":"Lake Champlain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.223876953125,\n 44.450447876762844\n ],\n [\n -73.29666137695312,\n 44.44064372873941\n ],\n [\n -73.32206726074219,\n 44.383747221908365\n ],\n [\n -73.22250366210938,\n 44.37540429036203\n ],\n [\n -73.2183837890625,\n 44.440153478144595\n ],\n [\n -73.223876953125,\n 44.450447876762844\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"145","issue":"3","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-04-27","publicationStatus":"PW","scienceBaseUri":"5757f037e4b04f417c24daad","contributors":{"authors":[{"text":"Parrish, Donna L. 0000-0001-9693-6329 dparrish@usgs.gov","orcid":"https://orcid.org/0000-0001-9693-6329","contributorId":138661,"corporation":false,"usgs":true,"family":"Parrish","given":"Donna","email":"dparrish@usgs.gov","middleInitial":"L.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":637391,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Simonin, Paul W.","contributorId":171499,"corporation":false,"usgs":false,"family":"Simonin","given":"Paul","email":"","middleInitial":"W.","affiliations":[{"id":18160,"text":"Rubenstein School of Environment and Natural Resources, University of Vermont","active":true,"usgs":false}],"preferred":false,"id":637763,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rudstam, Lars G.","contributorId":56609,"corporation":false,"usgs":false,"family":"Rudstam","given":"Lars","email":"","middleInitial":"G.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":637764,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pientka, Bernard","contributorId":171500,"corporation":false,"usgs":false,"family":"Pientka","given":"Bernard","email":"","affiliations":[],"preferred":false,"id":637765,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sullivan, Patrick J.","contributorId":97813,"corporation":false,"usgs":true,"family":"Sullivan","given":"Patrick J.","affiliations":[],"preferred":false,"id":637766,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70171018,"text":"70171018 - 2016 - Numerical experiments to explain multiscale hydrological responses to mountain pine beetle tree mortality in a headwater watershed","interactions":[],"lastModifiedDate":"2016-05-19T10:54:17","indexId":"70171018","displayToPublicDate":"2016-04-26T12:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Numerical experiments to explain multiscale hydrological responses to mountain pine beetle tree mortality in a headwater watershed","docAbstract":"The effects of mountain pine beetle (MPB)-induced tree mortality on a headwater hydrologic system were investigated using an integrated physical modeling framework with a high-resolution computational grid. Simulations of MPB-affected and unaffected conditions, each with identical atmospheric forcing for a normal water year, were compared at multiple scales to evaluate the effects of scale on MPB-affected hydrologic systems. Individual locations within the larger model were shown to maintain hillslope-scale processes affecting snowpack dynamics, total evapotranspiration, and soil moisture that are comparable to several field-based studies and previous modeling work. Hillslope-scale analyses also highlight the influence of compensating changes in evapotranspiration and snow processes. Reduced transpiration in the Grey Phase of MPB-induced tree mortality was offset by increased late-summer evaporation, while overall snowpack dynamics were more dependent on elevation effects than MPB-induced tree mortality. At the watershed scale, unaffected areas obscured the magnitude of MPB effects. Annual water yield from the watershed increased during Grey Phase simulations by 11 percent; a difference that would be difficult to diagnose with long-term gage observations that are complicated by inter-annual climate variability. The effects on hydrology observed and simulated at the hillslope scale can be further damped at the watershed scale, which spans more life zones and a broader range of landscape properties. These scaling effects may change under extreme conditions, e.g., increased total MPB-affected area or a water year with above average snowpack.
","language":"English","publisher":"American Geophysical Union","publisherLocation":"Richmond, VA","doi":"10.1002/2015WR018300","usgsCitation":"Penn, C.A., Bearup, L.A., Maxwell, R.M., and Clow, D.W., 2016, Numerical experiments to explain multiscale hydrological responses to mountain pine beetle tree mortality in a headwater watershed: Water Resources Research, v. 52, no. 4, p. 3143-3161, https://doi.org/10.1002/2015WR018300.","productDescription":"19 p.","startPage":"3143","endPage":"3161","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070327","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":471047,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015wr018300","text":"Publisher Index Page"},{"id":321299,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"52","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-04-26","publicationStatus":"PW","scienceBaseUri":"573ee3d2e4b04a3a6a24ad3d","contributors":{"authors":[{"text":"Penn, Colin A. 0000-0002-5195-2744 cpenn@usgs.gov","orcid":"https://orcid.org/0000-0002-5195-2744","contributorId":5336,"corporation":false,"usgs":true,"family":"Penn","given":"Colin","email":"cpenn@usgs.gov","middleInitial":"A.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":629555,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bearup, Lindsay A.","contributorId":139257,"corporation":false,"usgs":false,"family":"Bearup","given":"Lindsay","email":"","middleInitial":"A.","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":629556,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Maxwell, Reed M.","contributorId":95373,"corporation":false,"usgs":true,"family":"Maxwell","given":"Reed","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":629557,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Clow, David W. 0000-0001-6183-4824 dwclow@usgs.gov","orcid":"https://orcid.org/0000-0001-6183-4824","contributorId":1671,"corporation":false,"usgs":true,"family":"Clow","given":"David","email":"dwclow@usgs.gov","middleInitial":"W.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":629558,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70170331,"text":"fs20163027 - 2016 - U.S. Geological Survey response to flooding in Texas, May–June 2015","interactions":[],"lastModifiedDate":"2016-04-26T11:33:30","indexId":"fs20163027","displayToPublicDate":"2016-04-26T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-3027","title":"U.S. Geological Survey response to flooding in Texas, May–June 2015","docAbstract":"As a Federal science agency within the Department of the Interior, the U.S. Geological Survey (USGS) collects and disseminates streamflow stage and discharge information along with other types of water information as a major part of its Water mission area. Data collected at USGS streamflow-gaging stations (hereinafter referred to as “streamgages”) are used for a variety of purposes including flood warning, engineering design, management of water resources, and scientific research.
During flood events, the need for timely, accurate, and complete streamflow data is underscored because these data are relied on by local, State, and Federal emergency management personnel for flood response purposes. For example, the National Weather Service uses the data from USGS streamgages to develop flood forecasts for specific locations on a river. Tasks that the USGS performs in response to floods include monitoring the operation of gages and responding to any interruptions in data collection, calibrating and verifying stage-discharge ratings, and documenting extreme events including peak stage and peak discharge.
Frequent, severe storms during May and June 2015 caused widespread flooding in Texas. By various measures, the storms that caused the flooding were extreme and persistent. May 2015 was the wettest month on record for Texas, with a statewide average precipitation of 9.06 inches. In comparison, the long-term statewide average monthly precipitation is 3.37 inches, with the previous record average monthly precipitation reported as 6.66 inches during June 2004. The Office of the Texas State Climatologist compiled monthly precipitation amounts for 19 selected cities throughout Texas and for 1 city in Louisiana; the total monthly precipitation amounts exceeded the monthly normal precipitation for 18 of the 19 selected cities in Texas, with 5 of these cities exceeding their previous record for the month of May.
The onset of abundant precipitation in May 2015 resulted in the National Weather Service flood stage being exceeded at USGS streamgages on numerous rivers. The widespread and prolonged nature of the flooding was unusual; most flood events in Texas are localized, typically affecting only one or two river basins and generally lasting only a few days. With the exception of the Rio Grande, flooding was widespread in all of the major rivers in Texas during May–June 2015.
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\"}}]}","contact":"Director, Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, TX 78754–4733