The climatic conditions of the specific time period during which peak-flow data were collected at a given streamflow-gaging station (hereinafter referred to as gaging station) can substantially affect how well the peak-flow frequency (hereinafter referred to as frequency) results represent long-term hydrologic conditions. Differences in the timing of the periods of record can result in substantial inconsistencies in frequency estimates for hydrologically similar gaging stations. Potential for inconsistency increases with decreasing peak-flow record length. The representativeness of the frequency estimates for a short-term gaging station can be adjusted by various methods including weighting the at-site results in association with frequency estimates from regional regression equations (RREs) by using the Weighted Independent Estimates (WIE) program. Also, for gaging stations that cannot be adjusted by using the WIE program because of regulation or drainage areas too large for application of RREs, frequency estimates might be improved by using record extension procedures, including a mixed-station analysis using the maintenance of variance type I (MOVE.1) procedure. The U.S. Geological Survey, in cooperation with the Montana Department of Transportation and the Montana Department of Natural Resources and Conservation, completed a study to provide adjusted frequency estimates for selected gaging stations through water year 2011.
The purpose of Chapter D of this Scientific Investigations Report is to present adjusted frequency estimates for 504 selected streamflow-gaging stations in or near Montana based on data through water year 2011. Estimates of peak-flow magnitudes for the 66.7-, 50-, 42.9-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities are reported. These annual exceedance probabilities correspond to the 1.5-, 2-, 2.33-, 5-, 10-, 25-, 50-, 100-, 200-, and 500-year recurrence intervals, respectively.
The at-site frequency estimates were adjusted by weighting with frequency estimates from RREs using the WIE program for 438 selected gaging stations in Montana. These 438 selected gaging stations (1) had periods of record less than or equal to 40 years, (2) represented unregulated or minor regulation conditions, and (3) had drainage areas less than about 2,750 square miles.
The weighted-average frequency estimates obtained by weighting with RREs generally are considered to provide improved frequency estimates. In some cases, there are substantial differences among the at-site frequency estimates, the regression-equation frequency estimates, and the weighted-average frequency estimates. In these cases, thoughtful consideration should be applied when selecting the appropriate frequency estimate. Some factors that might be considered when selecting the appropriate frequency estimate include (1) whether the specific gaging station has peak-flow characteristics that distinguish it from most other gaging stations used in developing the RREs for the hydrologic region; and (2) the length of the peak-flow record and the general climatic characteristics during the period when the peak-flow data were collected. For critical structure-design applications, a conservative approach would be to select the higher of the at-site frequency estimate and the weighted-average frequency estimate.
The mixed-station MOVE.1 procedure generally was applied in cases where three or more gaging stations were located on the same large river and some of the gaging stations could not be adjusted using the weighted-average method because of regulation or drainage areas too large for application of RREs. The mixed-station MOVE.1 procedure was applied to 66 selected gaging stations on 19 large rivers.
The general approach for using mixed-station record extension procedures to adjust at-site frequencies involved (1) determining appropriate base periods for the gaging stations on the large rivers, (2) synthesizing peak-flow data for the gaging stations with incomplete peak-flow records during the base periods by using the mixed-station MOVE.1 procedure, and (3) conducting frequency analysis on the combined recorded and synthesized peak-flow data for each gaging station. Frequency estimates for the combined recorded and synthesized datasets for 66 gaging stations with incomplete peak-flow records during the base periods are presented. The uncertainties in the mixed-station record extension results are difficult to directly quantify; thus, it is important to understand the intended use of the estimated frequencies based on analysis of the combined recorded and synthesized datasets. The estimated frequencies are considered general estimates of frequency relations among gaging stations on the same stream channel that might be expected if the gaging stations had been gaged during the same long-term base period. However, because the mixed-station record extension procedures involve secondary statistical analysis with accompanying errors, the uncertainty of the frequency estimates is larger than would be obtained by collecting systematic records for the same number of years in the base period.
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\"}}]}","edition":"Version 1.0: April 6, 2016; Version 1.1: February 26, 2018","contact":"Director, Wyoming-Montana Water Science Center
U.S. Geological Survey
3162 Bozeman Ave
Helena, MT 59601
Montana StreamStats is a Web-based geographic information system (http://water.usgs.gov/osw/streamstats/) application that provides users with access to basin and streamflow characteristics for gaged and ungaged streams in Montana. Montana StreamStats was developed by the U.S. Geological Survey (USGS) in cooperation with the Montana Departments of Transportation, Environmental Quality, and Natural Resources and Conservation. The USGS Scientific Investigations Report consists of seven independent but complementary chapters dealing with various aspects of this effort.
Chapter A describes the Montana StreamStats application, the basin and streamflow datasets, and provides a brief overview of the streamflow characteristics and regression equations used in the study. Chapters B through E document the datasets, methods, and results of analyses to determine streamflow characteristics, such as peak-flow frequencies, low-flow frequencies, and monthly and annual characteristics, for USGS streamflow-gaging stations in and near Montana. The StreamStats analytical toolsets that allow users to delineate drainage basins and solve regression equations to estimate streamflow characteristics at ungaged sites in Montana are described in Chapters F and G.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155019","collaboration":"Prepared in cooperation with the Montana Department of Environmental Quality, Montana Department of Natural Resources and Conservation, and the Montana Department of Transportation","productDescription":"Chapters A-G","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"links":[{"id":319890,"rank":2,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2015/5019/sir20155019_2.zip","text":"Complete Volume","size":"60.7 MB","linkFileType":{"id":6,"text":"zip"},"description":"SIR 2015"},{"id":319889,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5019/coverthb.jpg"}],"country":"United 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\"}}]}","contact":"Director, Wyoming-Montana Water Science Center
U.S. Geological Survey
3162 Bozeman Ave
Helena, MT 59601
Groundwater-quality data collected from 1995 through 2013 from 106 monitoring wells open to the base of the Silurian aquifer surrounding the Tunnel and Reservoir Plan (TARP) System in Cook County, Illinois, were analyzed by the U.S. Geological Survey, in cooperation with the Metropolitan Water Reclamation District of Greater Chicago, to assess the efficacy of the monitoring network and the effects of water movement from the tunnel system to the surrounding aquifer. Groundwater from the Silurian aquifer typically drains to the tunnel system so that analyte concentrations in most of the samples from most of the monitoring wells primarily reflect the concentration of the analyte in the nearby Silurian aquifer. Water quality in the Silurian aquifer is spatially variable because of a variety of natural and non-TARP anthropogenic processes. Therefore, the trends in analyte values at a given well from 1995 through 2013 are primarily a reflection of the spatial variation in the value of the analyte in groundwater within that part of the Silurian aquifer draining to the tunnels. Intermittent drainage of combined sewer flow from the tunnel system to the Silurian aquifer when flow in the tunnel systemis greater than 80 million gallons per day may affect water quality in some nearby monitoring wells. Intermittent drainage of combined sewer flow from the tunnel system to the Silurian aquifer appears to affect the values of electrical conductivity, hardness, sulfate, chloride, dissolved organic carbon, ammonia, and fecal coliform in samples from many wells but typically during less than 5 percent of the sampling events. Drainage of combined sewer flow into the aquifer is most prevalent in the downstream parts of the tunnel systems because of the hydraulic pressures elevated above background values and long residence time of combined sewer flow in those areas. Elevated values of the analytes emplaced during intermittent migration of combined sewer flow into the Silurian aquifer decrease through time as water from the aquifer drains back into the tunnels in response to typical hydraulic conditions. Of the analytes sampled, fecal coliform provides the clearest indication of the location and timing of combined sewer flow into the Silurian aquifer surrounding the tunnel system.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155186","collaboration":"Prepared in cooperation with the Metropolitan Water Reclamation District of Greater Chicago","usgsCitation":"Kay, R.T., 2016, Hydrogeology and groundwater quality at monitoring wells installed for the Tunnel and Reservoir Plan System and nearby water-supply wells, Cook County, Illinois, 1995–2013 (ver 1.1, May 2016): U.S. Geological Survey Scientific Investigations Report 2015–5186, 347 p., https://dx.doi.org/10.3133/sir20155186.","productDescription":"vi, 347 p.","numberOfPages":"357","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"1995-01-01","ipdsId":"IP-063316","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":319409,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5186/coverthb1.jpg"},{"id":321237,"rank":3,"type":{"id":25,"text":"Version 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1.0: Originally posted April 4, 2016; Version 1.1: May 16, 2016","contact":"Director Illinois Water Science Center
U.S. Geological Survey
405 N Goodwin
Urbana, IL 61801
http://il.water.usgs.gov/
Groundwater seeps in upland catchments are often enriched relative to stream waters, higher in pH, Ca2+ and sometimes NO3¯. These seeps could be a NO3¯ sink because of increased denitrification potential but may also be ‘hotspots’ for nitrification because of the relative enrichment. We compared seep soils with nearby well-drained soils in two upland forested watersheds in Vermont that are sites of ongoing biogeochemical studies. Gross N transformation rates were measured over three years along with denitrification rates in the third year. Gross ammonification rates were not different between the seep and upland soils but gross nitrification rates were about 3 × higher in the seep soils. Net nitrification rates trended higher in the upland soils and NO3¯ consumption (gross—net) was 8 times higher in the seep soils. The average denitrification rate for seep soils was about equal to the difference in NO3¯ consumption between seep and upland soils, suggesting denitrification can make up the difference. Temporal variation in seep water NO3¯ concentration was correlated with watershed outlet NO3¯ concentration. However, it is not clear that in-seep processes greatly altered seep water NO3¯ contribution to the streams. Seep soils appear to be hotspots of both nitrification and denitrification.
","language":"English","publisher":"Springer","doi":"10.1007/s13157-016-0733-z","usgsCitation":"Kaur, A.J., Ross, D., Shanley, J.B., and Yatzor, A.R., 2016, Enriched groundwater seeps in two Vermont headwater catchments are hotspots of nitrate turnover: Wetlands, v. 36, no. 2, p. 237-249, https://doi.org/10.1007/s13157-016-0733-z.","productDescription":"13 p.","startPage":"237","endPage":"249","ipdsId":"IP-070374","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":347511,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Vermont","volume":"36","issue":"2","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2016-01-15","publicationStatus":"PW","scienceBaseUri":"59f83a3ce4b063d5d309810a","contributors":{"authors":[{"text":"Kaur, Amninder J.","contributorId":198364,"corporation":false,"usgs":false,"family":"Kaur","given":"Amninder","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":715818,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ross, Donald S.","contributorId":178218,"corporation":false,"usgs":false,"family":"Ross","given":"Donald S.","affiliations":[],"preferred":false,"id":715819,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shanley, James B. 0000-0002-4234-3437 jshanley@usgs.gov","orcid":"https://orcid.org/0000-0002-4234-3437","contributorId":1953,"corporation":false,"usgs":true,"family":"Shanley","given":"James","email":"jshanley@usgs.gov","middleInitial":"B.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":715817,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Yatzor, Anna R.","contributorId":198365,"corporation":false,"usgs":false,"family":"Yatzor","given":"Anna","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":715820,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70174881,"text":"70174881 - 2016 - Evaluating potential artefacts of photo-reversal on behavioral studies with nocturnal invasive sea lamprey (Petromyzon marinus)","interactions":[],"lastModifiedDate":"2016-07-20T11:35:47","indexId":"70174881","displayToPublicDate":"2016-04-01T18:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1176,"text":"Canadian Journal of Zoology","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating potential artefacts of photo-reversal on behavioral studies with nocturnal invasive sea lamprey (Petromyzon marinus)","docAbstract":"Sea lampreys (Petromyzon marinus L., 1758) are nocturnal, so experiments evaluating their behaviour to chemosensory cues have typically been conducted at night. However, given the brief timeframe each year that adult P. marinus are available for experimentation, we investigated whether P. marinus exposed to a 12 h shifted diurnal cycle (reversed photoperiod) could be tested in a darkened arena during the day and show the same response to chemosensory cues as natural photoperiod P. marinus that were tested during the night. Ten replicates of 10 P. marinus, from each photoperiod, were exposed to deionized water (negative control), 2-phenylethylamine hydrochloride (PEA HCl, putative predator cue), or P. marinus whole-body extract (conspecific alarm cue). All P. marinus demonstrated a significant avoidance response to both cues. No significant differences were found in avoidance to PEA HCl between photoperiods. Avoidance of P. marinus whole-body extract was significantly stronger in natural compared with reversed photoperiod P. marinus. The use of reversed photoperiod subjects is suitable for examining the presence or absence of avoidance in response to novel chemosensory alarm cues, or the change in the magnitude of antipredator response. Studies investigating the natural magnitude of antipredator response should use natural photoperiod experimental subjects.
","language":"English","publisher":"NRC Research Press","doi":"10.1139/cjz-2015-0254","collaboration":"Matthew Barnett; R.T. Di Rocco; Grant E. Brown; C. Michael Wager","usgsCitation":"Barnett, M., Imre, I., Wagner, C., Di Rocco, R.T., Johnson, N., and Brown, G.E., 2016, Evaluating potential artefacts of photo-reversal on behavioral studies with nocturnal invasive sea lamprey (Petromyzon marinus): Canadian Journal of Zoology, v. 94, no. 6, p. 405-410, https://doi.org/10.1139/cjz-2015-0254.","productDescription":"5 p.","startPage":"405","endPage":"410","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-073715","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":325474,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"94","issue":"6","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5790a17ee4b030378fb47428","contributors":{"authors":[{"text":"Barnett, Matthew","contributorId":173003,"corporation":false,"usgs":false,"family":"Barnett","given":"Matthew","email":"","affiliations":[{"id":6585,"text":"Algoma University","active":true,"usgs":false}],"preferred":false,"id":642966,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Imre, Istvan","contributorId":150985,"corporation":false,"usgs":false,"family":"Imre","given":"Istvan","email":"","affiliations":[{"id":6585,"text":"Algoma University","active":true,"usgs":false}],"preferred":false,"id":642967,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wagner, C. Michael","contributorId":173006,"corporation":false,"usgs":false,"family":"Wagner","given":"C. Michael","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":642970,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Di Rocco, Richard T.","contributorId":173004,"corporation":false,"usgs":false,"family":"Di Rocco","given":"Richard","email":"","middleInitial":"T.","affiliations":[{"id":6585,"text":"Algoma University","active":true,"usgs":false}],"preferred":false,"id":642968,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Johnson, Nicholas S. 0000-0002-7419-6013 njohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-7419-6013","contributorId":150983,"corporation":false,"usgs":true,"family":"Johnson","given":"Nicholas S.","email":"njohnson@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":642965,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brown, Grant E.","contributorId":173005,"corporation":false,"usgs":false,"family":"Brown","given":"Grant","email":"","middleInitial":"E.","affiliations":[{"id":6586,"text":"Concordia University","active":true,"usgs":false}],"preferred":false,"id":642969,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70202369,"text":"70202369 - 2016 - Managing nutrients, water, and energy for producing more food with low pollution (MoFoLoPo); What would success look like?","interactions":[],"lastModifiedDate":"2019-02-26T14:56:18","indexId":"70202369","displayToPublicDate":"2016-04-01T14:56:09","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1532,"text":"Environmental Development","active":true,"publicationSubtype":{"id":10}},"title":"Managing nutrients, water, and energy for producing more food with low pollution (MoFoLoPo); What would success look like?","docAbstract":"Synthetic nitrogen (N) fertilizer has enabled modern agriculture to greatly improve human nutrition during the 20th century, but it has also created unintended human health and environmental pollution challenges for the 21st century. Averaged globally, about half of the fertilizer N applied to farms is removed with the crops, while the other half remains in the soil or is lost from farmers’ fields, resulting in water and air pollution. As human population continues to grow and food security improves in the developing world, the dual development goals of producing more nutritious food with low pollution will require both technological and socio-economic innovations in agriculture.","language":"English","publisher":"Elsevier","doi":"10.1016/j.envdev.2016.03.002","usgsCitation":"Baron, J., 2016, Managing nutrients, water, and energy for producing more food with low pollution (MoFoLoPo); What would success look like?: Environmental Development, v. 18, p. 52-53, https://doi.org/10.1016/j.envdev.2016.03.002.","productDescription":"2 p.","startPage":"52","endPage":"53","ipdsId":"IP-073940","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":361558,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"18","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Baron, Jill 0000-0002-5902-6251 jill_baron@usgs.gov","orcid":"https://orcid.org/0000-0002-5902-6251","contributorId":194124,"corporation":false,"usgs":true,"family":"Baron","given":"Jill","email":"jill_baron@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":758047,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70199158,"text":"70199158 - 2016 - Multi-laboratory survey of qPCR enterococci analysis method performance in U.S. coastal and inland surface waters","interactions":[],"lastModifiedDate":"2018-09-07T11:06:31","indexId":"70199158","displayToPublicDate":"2016-04-01T11:06:23","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2390,"text":"Journal of Microbiological Methods","active":true,"publicationSubtype":{"id":10}},"title":"Multi-laboratory survey of qPCR enterococci analysis method performance in U.S. coastal and inland surface waters","docAbstract":"Quantitative polymerase chain reaction (qPCR) has become a frequently used technique for quantifying enterococci in recreational surface waters, but there are several methodological options. Here we evaluated how three method permutations, type of mastermix, sample extract dilution and use of controls in results calculation, affect method reliability among multiple laboratories with respect to sample interference. Multiple samples from each of 22 sites representing an array of habitat types were analyzed using EPA Method 1611 and 1609 reagents with full strength and five-fold diluted extracts. The presence of interference was assessed three ways: using sample processing and PCR amplifications controls; consistency of results across extract dilutions; and relative recovery of target genes from spiked enterococci in water sample compared to control matrices with acceptable recovery defined as 50 to 200%. Method 1609, which is based on an environmental mastermix, was found to be superior to Method 1611, which is based on a universal mastermix. Method 1611 had over a 40% control assay failure rate with undiluted extracts and a 6% failure rate with diluted extracts. Method 1609 failed in only 11% and 3% of undiluted and diluted extracts analyses. Use of sample processing control assay results in the delta–delta Ct method for calculating relative target gene recoveries increased the number of acceptable recovery results. Delta–delta tended to bias recoveries from apparent partially inhibitory samples on the high side which could help in avoiding potential underestimates of enterococci — an important consideration in a public health context. Control assay and delta–delta recovery results were largely consistent across the range of habitats sampled, and among laboratories. The methodological option that best balanced acceptable estimated target gene recoveries with method sensitivity and avoidance of underestimated enterococci densities was Method 1609 without extract dilution and using the delta–delta calculation method. The applicability of this method can be extended by the analysis of diluted extracts to sites where interference is indicated but, particularly in these instances, should be confirmed by augmenting the control assays with analyses for target gene recoveries from spiked target organisms.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.mimet.2016.01.017","usgsCitation":"Haugland, R.A., Siefring, S., Varma, M., Oshima, K.H., Sivaganesan, M., Cao, Y., Raith, M., Griffith, J., Weisberg, S.B., Noble, R.T., Blackwood, A.D., Kinzelman, J., Anan’eva, T., Bushon, R.N., Stelzer, E.A., Harwood, V.J., Gordon, K.V., and Sinigalliano, C., 2016, Multi-laboratory survey of qPCR enterococci analysis method performance in U.S. coastal and inland surface waters: Journal of Microbiological Methods, v. 123, p. 114-125, https://doi.org/10.1016/j.mimet.2016.01.017.","productDescription":"12 p.","startPage":"114","endPage":"125","ipdsId":"IP-101153","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":471094,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.17615/k7h6-m925","text":"External Repository"},{"id":357113,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"123","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b98a622e4b0702d0e8430c2","contributors":{"authors":[{"text":"Haugland, Richard A.","contributorId":207703,"corporation":false,"usgs":false,"family":"Haugland","given":"Richard","email":"","middleInitial":"A.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":744463,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Siefring, Shawn","contributorId":207704,"corporation":false,"usgs":false,"family":"Siefring","given":"Shawn","email":"","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":744464,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Varma, Manju","contributorId":207705,"corporation":false,"usgs":false,"family":"Varma","given":"Manju","email":"","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":744465,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Oshima, Kevin H.","contributorId":178927,"corporation":false,"usgs":false,"family":"Oshima","given":"Kevin","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":744466,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sivaganesan, Mano","contributorId":207706,"corporation":false,"usgs":false,"family":"Sivaganesan","given":"Mano","email":"","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":744467,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cao, Yiping","contributorId":207707,"corporation":false,"usgs":false,"family":"Cao","given":"Yiping","email":"","affiliations":[{"id":13211,"text":"Southern California Coastal Water Research Project Authority","active":true,"usgs":false}],"preferred":false,"id":744468,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Raith, Meredith","contributorId":207708,"corporation":false,"usgs":false,"family":"Raith","given":"Meredith","email":"","affiliations":[{"id":13211,"text":"Southern California Coastal Water Research Project Authority","active":true,"usgs":false}],"preferred":false,"id":744469,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Griffith, John","contributorId":207709,"corporation":false,"usgs":false,"family":"Griffith","given":"John","affiliations":[{"id":13211,"text":"Southern California Coastal Water Research Project Authority","active":true,"usgs":false}],"preferred":false,"id":744470,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Weisberg, Stephen B.","contributorId":207710,"corporation":false,"usgs":false,"family":"Weisberg","given":"Stephen","email":"","middleInitial":"B.","affiliations":[{"id":13211,"text":"Southern California Coastal Water Research Project Authority","active":true,"usgs":false}],"preferred":false,"id":744471,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Noble, Rachel T.","contributorId":207711,"corporation":false,"usgs":false,"family":"Noble","given":"Rachel","email":"","middleInitial":"T.","affiliations":[{"id":37611,"text":"Institute of Marine Sciences, University of North Carolina at Chapel Hill","active":true,"usgs":false}],"preferred":false,"id":744472,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Blackwood, A. Denene","contributorId":207712,"corporation":false,"usgs":false,"family":"Blackwood","given":"A.","email":"","middleInitial":"Denene","affiliations":[{"id":37611,"text":"Institute of Marine Sciences, University of North Carolina at Chapel Hill","active":true,"usgs":false}],"preferred":false,"id":744473,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Kinzelman, Julie","contributorId":207713,"corporation":false,"usgs":false,"family":"Kinzelman","given":"Julie","affiliations":[{"id":37612,"text":"City of Racine Health Department","active":true,"usgs":false}],"preferred":false,"id":744474,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Anan’eva, Tamara","contributorId":207714,"corporation":false,"usgs":false,"family":"Anan’eva","given":"Tamara","email":"","affiliations":[{"id":37612,"text":"City of Racine Health Department","active":true,"usgs":false}],"preferred":false,"id":744475,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Bushon, Rebecca N. 0000-0003-1843-9719 rnbushon@usgs.gov","orcid":"https://orcid.org/0000-0003-1843-9719","contributorId":207702,"corporation":false,"usgs":true,"family":"Bushon","given":"Rebecca","email":"rnbushon@usgs.gov","middleInitial":"N.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":744462,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Stelzer, Erin A. 0000-0001-7645-7603 eastelzer@usgs.gov","orcid":"https://orcid.org/0000-0001-7645-7603","contributorId":1933,"corporation":false,"usgs":true,"family":"Stelzer","given":"Erin","email":"eastelzer@usgs.gov","middleInitial":"A.","affiliations":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":744476,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Harwood, Valarie J.","contributorId":207715,"corporation":false,"usgs":false,"family":"Harwood","given":"Valarie","email":"","middleInitial":"J.","affiliations":[{"id":37613,"text":"Department of Integrative Biology, University of South Florida","active":true,"usgs":false}],"preferred":false,"id":744477,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Gordon, Katrina V.","contributorId":207716,"corporation":false,"usgs":false,"family":"Gordon","given":"Katrina","email":"","middleInitial":"V.","affiliations":[{"id":37613,"text":"Department of Integrative Biology, University of South Florida","active":true,"usgs":false}],"preferred":false,"id":744478,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Sinigalliano, Christopher","contributorId":207717,"corporation":false,"usgs":false,"family":"Sinigalliano","given":"Christopher","affiliations":[{"id":37614,"text":"National Oceanic Atmospheric Administration","active":true,"usgs":false}],"preferred":false,"id":744479,"contributorType":{"id":1,"text":"Authors"},"rank":18}]}} ,{"id":70170956,"text":"70170956 - 2016 - Informing Lake Erie agriculture nutrient management via scenario evaluation","interactions":[],"lastModifiedDate":"2016-05-23T15:08:58","indexId":"70170956","displayToPublicDate":"2016-04-01T07:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Informing Lake Erie agriculture nutrient management via scenario evaluation","docAbstract":"Harmful algal blooms (HABs) have been increasing in extent and intensity in the western basin of Lake Erie. The cyanobacteria Microcystis produces toxins that pose serious threats to animal and human health, resulting in beach closures and impaired water supplies, and have even forced a “do not drink” advisory for the City of Toledo water system for several days in the summer of 2014. The main driver of Lake Erie HABs is elevated phosphorus loading from watersheds draining to the western basin, particularly from the Maumee River watershed (Obenour et al. 2014). Through the 2012 Great Lakes Water Quality Agreement (GLWQA), the U.S. and Canadian governments agreed to revise Lake Erie phosphorus loading targets to decrease HAB severity below levels representing a hazard to ecosystem and human health. New targets limit March-July loadings from the Maumee River to 186 metric tonnes of dissolved reactive phosphorus (DRP) and 860 metric tonnes of total phosphorus (TP) – a 40% reduction from 2008 loads (GLWQA 2016).
\nThe Great Lakes region must now determine what policy options are most effective and feasible for meeting those targets. While all sources are important, our focus is on agriculture because it overwhelms other sources. In a conservative ballpark estimate we found that 85% of the Maumee River’s load to Lake Erie comes from farm fertilizers and manures, even though this is only 10% of farmland fertilizer applications (Figure 1). Load targets will not be met without reductions from agriculture.
\nTherefore, the overall goal of this study was to identify potential options for agricultural management to reduce phosphorus loads and lessen future HABs in Lake Erie. We applied multiple watershed models to test the ability of a series of land management scenarios, developed in consultation with agricultural and environmental stakeholders, to reach the proposed targets.
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dzrobert@usgs.gov","orcid":"https://orcid.org/0000-0001-6799-0596","contributorId":150760,"corporation":false,"usgs":true,"family":"Robertson","given":"Dale","email":"dzrobert@usgs.gov","middleInitial":"M.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":629215,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Sowa, Scott P. 0000-0002-5425-2591 sowasp@missouri.edu","orcid":"https://orcid.org/0000-0002-5425-2591","contributorId":146672,"corporation":false,"usgs":false,"family":"Sowa","given":"Scott","email":"sowasp@missouri.edu","middleInitial":"P.","affiliations":[{"id":7041,"text":"The Nature Conservancy","active":true,"usgs":false}],"preferred":false,"id":630048,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Wang, Yu-Chen","contributorId":169563,"corporation":false,"usgs":false,"family":"Wang","given":"Yu-Chen","email":"","affiliations":[{"id":33091,"text":"University of Michigan, Ann Arbor, Michigan","active":true,"usgs":false}],"preferred":false,"id":630049,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"White, Michael","contributorId":169565,"corporation":false,"usgs":false,"family":"White","given":"Michael","affiliations":[{"id":6758,"text":"USDA-ARS","active":true,"usgs":false}],"preferred":false,"id":630050,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Yen, Haw 0000-0002-5509-8792","orcid":"https://orcid.org/0000-0002-5509-8792","contributorId":169564,"corporation":false,"usgs":false,"family":"Yen","given":"Haw","email":"","affiliations":[{"id":6747,"text":"Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":630051,"contributorType":{"id":1,"text":"Authors"},"rank":17}]}} ,{"id":70178035,"text":"70178035 - 2016 - Airborne pathogens from dairy manure aerial irrigation and the human health risk","interactions":[],"lastModifiedDate":"2016-12-19T17:44:05","indexId":"70178035","displayToPublicDate":"2016-04-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":3,"text":"Organization Series"},"title":"Airborne pathogens from dairy manure aerial irrigation and the human health risk","docAbstract":"Dairy manure, like the fecal excrement from any domesticated or wild animal, can contain pathogens capable of infecting humans and causing illness or even death. Pathogens in dairy manure can be broadly divided into categories of taxonomy or infectiousness. Dividing by taxonomy there are three pathogen groups in dairy manure: viruses (e.g., bovine rotavirus), bacteria (e.g., Salmonella species), and protozoa (e.g., Cryptosporidium parvum). There are two categories of infectiousness for pathogens found in animals: those that are zoonotic and those that are not. A zoonotic pathogen is one that can infect both human and animal hosts. Some zoonotic pathogens found in dairy manure cause illness in both hosts (e.g., Salmonella) while other zoonotic pathogens, like Escherichia coli O157:H7, (enterohemorrhagic E. coli (EHEC)) cause illness only in humans. As a general rule, the gastrointestinal viruses found in dairy manure are not zoonotic. While there are exceptions (e.g., rare reports of bovine rotavirus infecting children), for the most part the viruses in dairy manure are not a human health concern. The primary concerns are the zoonotic bacteria and protozoa in dairy manure.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Considerations for the use of manure irrigation practices","language":"English","publisher":"Wisconsin Manure Irrigation Workgroup","collaboration":"Wisconsin Department of Natural Resources","usgsCitation":"Borchardt, M.A., and Burch, T.R., 2016, Airborne pathogens from dairy manure aerial irrigation and the human health risk, C-1-C-24.","productDescription":"C-1-C-24","ipdsId":"IP-069593","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":332310,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":330596,"type":{"id":15,"text":"Index Page"},"url":"https://fyi.uwex.edu/manureirrigation/files/2016/04/Manure-Irrigation-Workgroup-Report-2016.pdf"}],"publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58590009e4b03639a6025e2d","contributors":{"authors":[{"text":"Borchardt, Mark A. 0000-0002-6471-2627","orcid":"https://orcid.org/0000-0002-6471-2627","contributorId":151033,"corporation":false,"usgs":false,"family":"Borchardt","given":"Mark","email":"","middleInitial":"A.","affiliations":[{"id":6684,"text":"USDA Forest Service, Southern Research Station, Aiken, SC","active":true,"usgs":false}],"preferred":false,"id":652579,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burch, Tucker R tburch@usgs.gov","contributorId":5689,"corporation":false,"usgs":true,"family":"Burch","given":"Tucker","email":"tburch@usgs.gov","middleInitial":"R","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":652578,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70177963,"text":"70177963 - 2016 - Municipal solid waste landfills harbor distinct microbiomes","interactions":[],"lastModifiedDate":"2018-08-07T11:52:05","indexId":"70177963","displayToPublicDate":"2016-04-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1702,"text":"Frontiers in Microbiology","onlineIssn":"1664-302X","active":true,"publicationSubtype":{"id":10}},"title":"Municipal solid waste landfills harbor distinct microbiomes","docAbstract":"Landfills are the final repository for most of the discarded material from human society and its “built environments.” Microorganisms subsequently degrade this discarded material in the landfill, releasing gases (largely CH4 and CO2) and a complex mixture of soluble chemical compounds in leachate. Characterization of “landfill microbiomes” and their comparison across several landfills should allow the identification of environmental or operational properties that influence the composition of these microbiomes and potentially their biodegradation capabilities. To this end, the composition of landfill microbiomes was characterized as part of an ongoing USGS national survey studying the chemical composition of leachates from 19 non-hazardous landfills across 16 states in the continental U.S. The landfills varied in parameters such as size, waste composition, management strategy, geography, and climate zone. The diversity and composition of bacterial and archaeal populations in leachate samples were characterized by 16S rRNA gene sequence analysis, and compared against a variety of physical and chemical parameters in an attempt to identify their impact on selection. Members of the Epsilonproteobacteria, Gammaproteobacteria, Clostridia, and candidate division OP3 were the most abundant. The distribution of the observed phylogenetic diversity could best be explained by a combination of variables and was correlated most strongly with the concentrations of chloride and barium, rate of evapotranspiration, age of waste, and the number of detected household chemicals. This study illustrates how leachate microbiomes are distinct from those of other natural or built environments, and sheds light on the major selective forces responsible for this microbial diversity.
","language":"English","publisher":"Frontiers","doi":"10.3389/fmicb.2016.00534","usgsCitation":"Stamps, B.W., Lyles, C.N., Suflita, J.M., Masoner, J.R., Cozzarelli, I.M., Kolpin, D.W., and Stevenson, B.S., 2016, Municipal solid waste landfills harbor distinct microbiomes: Frontiers in Microbiology, v. 7, p. 1-11, https://doi.org/10.3389/fmicb.2016.00534.","productDescription":"Article 534; 11 p.","startPage":"1","endPage":"11","ipdsId":"IP-062988","costCenters":[{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":471095,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fmicb.2016.00534","text":"Publisher Index Page"},{"id":330574,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2016-04-20","publicationStatus":"PW","scienceBaseUri":"5818582fe4b0bb36a4c6fa13","contributors":{"authors":[{"text":"Stamps, Blake W.","contributorId":176485,"corporation":false,"usgs":false,"family":"Stamps","given":"Blake","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":652503,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lyles, Christopher N.","contributorId":176484,"corporation":false,"usgs":false,"family":"Lyles","given":"Christopher","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":652504,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Suflita, Joseph M.","contributorId":82997,"corporation":false,"usgs":true,"family":"Suflita","given":"Joseph","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":652505,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Masoner, Jason R. 0000-0002-4829-6379 jmasoner@usgs.gov","orcid":"https://orcid.org/0000-0002-4829-6379","contributorId":3193,"corporation":false,"usgs":true,"family":"Masoner","given":"Jason","email":"jmasoner@usgs.gov","middleInitial":"R.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true}],"preferred":true,"id":652506,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cozzarelli, Isabelle M. 0000-0002-5123-1007 icozzare@usgs.gov","orcid":"https://orcid.org/0000-0002-5123-1007","contributorId":1693,"corporation":false,"usgs":true,"family":"Cozzarelli","given":"Isabelle","email":"icozzare@usgs.gov","middleInitial":"M.","affiliations":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":652507,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kolpin, Dana W. 0000-0002-3529-6505 dwkolpin@usgs.gov","orcid":"https://orcid.org/0000-0002-3529-6505","contributorId":1239,"corporation":false,"usgs":true,"family":"Kolpin","given":"Dana","email":"dwkolpin@usgs.gov","middleInitial":"W.","affiliations":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"preferred":true,"id":652508,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Stevenson, Bradley S.","contributorId":176491,"corporation":false,"usgs":false,"family":"Stevenson","given":"Bradley","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":652509,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70177907,"text":"70177907 - 2016 - Temporal, geographic, and host distribution of avian paramyxovirus 1 (Newcastle disease virus)","interactions":[],"lastModifiedDate":"2016-10-26T12:00:06","indexId":"70177907","displayToPublicDate":"2016-04-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1988,"text":"Infection, Genetics and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Temporal, geographic, and host distribution of avian paramyxovirus 1 (Newcastle disease virus)","docAbstract":"Newcastle disease is caused by virulent forms of avian paramyxovirus of serotype 1 (APMV-1) and has global economic importance. The disease reached panzootic proportions within two decades after first being identified in 1926 in the United Kingdom and Indonesia and still remains endemic in many countries across the world. Here we review information on the host, temporal, and geographic distribution of APMV-1 genetic diversity based on the evolutionary systematics of the complete coding region of the fusion gene. Strains of APMV-1 are phylogenetically separated into two classes (class I and class II) and further classified into genotypes based on genetic differences. Class I viruses are genetically less diverse, generally present in wild waterfowl, and are of low virulence. Class II viruses are genetically and phenotypically more diverse, frequently isolated from poultry with occasional spillovers into wild birds, and exhibit a wider range of virulence. Waterfowl, cormorants, and pigeons are natural reservoirs of all APMV-1 pathotypes, except viscerotropic velogenic viruses for which natural reservoirs have not been identified. Genotypes I and II within class II include isolates of high and low virulence, the latter often being used as vaccines. Viruses of genotypes III and IX that emerged decades ago are now isolated rarely, but may be found in domestic and wild birds in China. Containing only virulent viruses and responsible for the majority of recent outbreaks in poultry and wild birds, viruses from genotypes V, VI, and VII, are highly mobile and have been isolated on different continents. Conversely, virulent viruses of genotypes XI (Madagascar), XIII (mainly Southwest Asia), XVI (North America) and XIV, XVII and XVIII (Africa) appear to have a more limited geographic distribution and have been isolated predominantly from poultry.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.meegid.2016.01.008","usgsCitation":"Dimitrov, K.M., Ramey, A.M., Qiu, X., Bahl, J., and Afonso, C.L., 2016, Temporal, geographic, and host distribution of avian paramyxovirus 1 (Newcastle disease virus): Infection, Genetics and Evolution, v. 39, p. 22-34, https://doi.org/10.1016/j.meegid.2016.01.008.","productDescription":"13 p.","startPage":"22","endPage":"34","ipdsId":"IP-069077","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":471099,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.meegid.2016.01.008","text":"Publisher Index Page"},{"id":330406,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"39","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5811c0f2e4b0f497e79a5a73","chorus":{"doi":"10.1016/j.meegid.2016.01.008","url":"http://dx.doi.org/10.1016/j.meegid.2016.01.008","publisher":"Elsevier BV","authors":"Dimitrov Kiril M., Ramey Andrew M., Qiu Xueting, Bahl Justin, Afonso Claudio L.","journalName":"Infection, Genetics and Evolution","publicationDate":"4/2016"},"contributors":{"authors":[{"text":"Dimitrov, Kiril M.","contributorId":176311,"corporation":false,"usgs":false,"family":"Dimitrov","given":"Kiril","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":652158,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":652108,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Qiu, Xueting","contributorId":176312,"corporation":false,"usgs":false,"family":"Qiu","given":"Xueting","email":"","affiliations":[],"preferred":false,"id":652159,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bahl, Justin","contributorId":171803,"corporation":false,"usgs":false,"family":"Bahl","given":"Justin","affiliations":[{"id":26950,"text":"University of Texas School of Public Health, 1200 Pressler Street, Houston, TX 77030, USA","active":true,"usgs":false}],"preferred":false,"id":652160,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Afonso, Claudio L.","contributorId":171954,"corporation":false,"usgs":false,"family":"Afonso","given":"Claudio","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":652161,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70169003,"text":"70169003 - 2016 - Low soil moisture during hot periods drives apparent negative temperature sensitivity of soil respiration in a dryland ecosystem: A multi-model comparison","interactions":[],"lastModifiedDate":"2020-12-17T19:08:24.558711","indexId":"70169003","displayToPublicDate":"2016-04-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1007,"text":"Biogeochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Low soil moisture during hot periods drives apparent negative temperature sensitivity of soil respiration in a dryland ecosystem: A multi-model comparison","docAbstract":"Arid and semiarid ecosystems (drylands) may dominate the trajectory of biosphere-to-atmosphere carbon (C) exchange, and understanding dryland CO2 efflux is important for C cycling at the global-scale. However, unknowns remain regarding how temperature and moisture interact to regulate dryland soil respiration (R s ), while ‘islands of fertility’ in drylands create spatially heterogeneous R s . At a site in southeastern Utah, USA we added or removed litter (0–650 % of control) in plots associated with either shrubs or biological soil crust-dominated interspaces between vascular plants. We measured R s , soil temperature (Ts), and water content (θ) repeatedly from October 2013 to November 2014. R s was highest following rain in late summer at Ts ~30 °C, and lowest mid-summer at Ts > 40 °C, resulting in apparent negative temperature sensitivity of R s at high temperatures, and positive temperature sensitivity at low-moderate temperatures. We used Bayesian statistical methods to compare models capturing a range of hypothesized relationships between Ts, θ, and R s . The best model indicates that apparent negative temperature sensitivity of R s at high Ts reflects the control of water content, not high temperatures. Modeled Q10 ranged from 2.7 to 1.4 between 5 and 45 °C. Litter addition had no effect on Q10 or reference respiration (R ref = R s at 20 °C and optimum θ) beneath shrubs, and little effect on R ref in interspaces, yet R ref was 1.5 times higher beneath shrubs than in interspaces. Altogether, these results suggest reduced R s often observed at high Ts in drylands is dominated by the control of θ, and, on shorter-timescales, variable litter inputs exert minimal control over R s .
","language":"English","publisher":"Springer","doi":"10.1007/s10533-016-0200-1","usgsCitation":"Tucker, C., and Reed, S.C., 2016, Low soil moisture during hot periods drives apparent negative temperature sensitivity of soil respiration in a dryland ecosystem: A multi-model comparison: Biogeochemistry, v. 128, no. 1, p. 155-169, https://doi.org/10.1007/s10533-016-0200-1.","productDescription":"15 p.","startPage":"155","endPage":"169","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070711","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":322026,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"128","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-04-02","publicationStatus":"PW","scienceBaseUri":"57500769e4b0ee97d51bb679","contributors":{"authors":[{"text":"Tucker, Colin 0000-0002-4539-7780 ctucker@usgs.gov","orcid":"https://orcid.org/0000-0002-4539-7780","contributorId":167487,"corporation":false,"usgs":true,"family":"Tucker","given":"Colin","email":"ctucker@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":622468,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reed, Sasha C. 0000-0002-8597-8619 screed@usgs.gov","orcid":"https://orcid.org/0000-0002-8597-8619","contributorId":462,"corporation":false,"usgs":true,"family":"Reed","given":"Sasha","email":"screed@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":622469,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70168634,"text":"70168634 - 2016 - Increasing influence of air temperature on upper Colorado River streamflow","interactions":[],"lastModifiedDate":"2018-04-03T11:23:43","indexId":"70168634","displayToPublicDate":"2016-04-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Increasing influence of air temperature on upper Colorado River streamflow","docAbstract":"This empirical study examines the influence of precipitation, temperature, and antecedent soil moisture on upper Colorado River basin (UCRB) water year streamflow over the past century. While cool season precipitation explains most of the variability in annual flows, temperature appears to be highly influential under certain conditions, with the role of antecedent fall soil moisture less clear. In both wet and dry years, when flow is substantially different than expected given precipitation, these factors can modulate the dominant precipitation influence on streamflow. Different combinations of temperature, precipitation, and soil moisture can result in flow deficits of similar magnitude, but recent droughts have been amplified by warmer temperatures that exacerbate the effects of relatively modest precipitation deficits. Since 1988, a marked increase in the frequency of warm years with lower flows than expected, given precipitation, suggests continued warming temperatures will be an increasingly important influence in reducing future UCRB water supplies.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2015GL067613","usgsCitation":"Woodhouse, C.A., Pederson, G.T., Morino, K., McAfee, S., and McCabe, G., 2016, Increasing influence of air temperature on upper Colorado River streamflow: Geophysical Research Letters, v. 43, no. 5, p. 2174-2181, https://doi.org/10.1002/2015GL067613.","productDescription":"8 p.","startPage":"2174","endPage":"2181","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069464","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":471106,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015gl067613","text":"Publisher Index Page"},{"id":322023,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"43","issue":"5","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-03-09","publicationStatus":"PW","scienceBaseUri":"57500767e4b0ee97d51bb659","contributors":{"authors":[{"text":"Woodhouse, Connie A.","contributorId":187601,"corporation":false,"usgs":false,"family":"Woodhouse","given":"Connie","email":"","middleInitial":"A.","affiliations":[{"id":32413,"text":"University of Arizona, Tucson, AZ, USA, 85721","active":true,"usgs":false}],"preferred":false,"id":621077,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pederson, Gregory T. 0000-0002-6014-1425 gpederson@usgs.gov","orcid":"https://orcid.org/0000-0002-6014-1425","contributorId":3106,"corporation":false,"usgs":true,"family":"Pederson","given":"Gregory","email":"gpederson@usgs.gov","middleInitial":"T.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":621076,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Morino, Kiyomi","contributorId":78210,"corporation":false,"usgs":true,"family":"Morino","given":"Kiyomi","email":"","affiliations":[],"preferred":false,"id":621078,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McAfee, Stephanie A.","contributorId":167115,"corporation":false,"usgs":false,"family":"McAfee","given":"Stephanie A.","affiliations":[{"id":24618,"text":"Department of Geography, University of Nevada, Reno, Reno, NV","active":true,"usgs":false}],"preferred":false,"id":621079,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McCabe, Gregory J. 0000-0002-9258-2997 gmccabe@usgs.gov","orcid":"https://orcid.org/0000-0002-9258-2997","contributorId":167116,"corporation":false,"usgs":true,"family":"McCabe","given":"Gregory J.","email":"gmccabe@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":false,"id":621080,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70188066,"text":"70188066 - 2016 - The power of remote sensing: Global monitoring of weather, water, and crops with satellites and data integration","interactions":[],"lastModifiedDate":"2020-12-21T16:00:29.132398","indexId":"70188066","displayToPublicDate":"2016-04-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5406,"text":"Resource: Engineering and Technology for a Sustainable World","printIssn":"1076-3333","active":true,"publicationSubtype":{"id":10}},"title":"The power of remote sensing: Global monitoring of weather, water, and crops with satellites and data integration","docAbstract":"Imagine a family of six whose livelihood is based on subsistence farming on a small, maybe one hectare, parcel of land somewhere in Africa. The seasonal rainfall varies greatly, from 500 to 800 mm per year, and the land is degraded. Thus, the parcel’s total productivity is not more than 1.5 tonnes in a good year, hardly meeting the family’s food requirements. The lack of surplus grain eliminates the need for grain storage structures, and due to the high rainfall variability, drought hazard is always looming, with an average recurrence interval of five to ten years.
","language":"English","publisher":"American Society of Agricultural and Biological Engineers","usgsCitation":"Senay, G., 2016, The power of remote sensing: Global monitoring of weather, water, and crops with satellites and data integration: Resource: Engineering and Technology for a Sustainable World, v. 23, no. 2, p. 6-9.","productDescription":"4 p.","startPage":"6","endPage":"9","ipdsId":"IP-069936","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":341855,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":341853,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://elibrary.asabe.org/abstract.asp?aid=46628"}],"volume":"23","issue":"2","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"592e84b9e4b092b266f10d32","contributors":{"authors":[{"text":"Senay, Gabriel B. 0000-0002-8810-8539 senay@usgs.gov","orcid":"https://orcid.org/0000-0002-8810-8539","contributorId":166812,"corporation":false,"usgs":true,"family":"Senay","given":"Gabriel","email":"senay@usgs.gov","middleInitial":"B.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":696381,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70193182,"text":"70193182 - 2016 - NHDPlus as a geospatial framework for SPARROW modeling","interactions":[],"lastModifiedDate":"2018-03-15T10:26:24","indexId":"70193182","displayToPublicDate":"2016-04-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1975,"text":"Impact Assessment Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"NHDPlus as a geospatial framework for SPARROW modeling","docAbstract":"Successful water-resource management requires thorough knowledge and understanding of the relations among water-quality contaminate sources and the factors that affect the transport throughout a hydrologic system. Surface-water modeling is a valuable tool that can be applied to help advance and achieve the understanding of these dynamic relations. Spatially Referenced Regressions on Watershed Attributes (SPARROW) is one such model that uses nonlinear statistical methods to define conceptual and spatial relations among quantities of contaminant sources, monitored contaminant load, aquatic transport processes. NHDPlus Version 2 (V2) is a digital representation of a hydrologic network of streams and associated catchments. The dataset provides the fundamental spatial framework for SPARROW modeling.","language":"English","publisher":"American Water Resources Association","usgsCitation":"Brakebill, J.W., and Schwarz, G., 2016, NHDPlus as a geospatial framework for SPARROW modeling: Impact Assessment Bulletin, v. 18, no. 3.","ipdsId":"IP-073650","costCenters":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"links":[{"id":348610,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":347782,"type":{"id":15,"text":"Index Page"},"url":"https://www.awra.org/impact/"}],"volume":"18","issue":"3","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a07ea50e4b09af898c8cc73","contributors":{"authors":[{"text":"Brakebill, John W. 0000-0001-9235-6810 jwbrakeb@usgs.gov","orcid":"https://orcid.org/0000-0001-9235-6810","contributorId":1061,"corporation":false,"usgs":true,"family":"Brakebill","given":"John","email":"jwbrakeb@usgs.gov","middleInitial":"W.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":718136,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schwarz, Gregory E. 0000-0002-9239-4566 gschwarz@usgs.gov","orcid":"https://orcid.org/0000-0002-9239-4566","contributorId":543,"corporation":false,"usgs":true,"family":"Schwarz","given":"Gregory E.","email":"gschwarz@usgs.gov","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":5067,"text":"Northeast Regional Director's Office","active":true,"usgs":true}],"preferred":false,"id":718137,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70190336,"text":"70190336 - 2016 - Seasonal habitat use of brook trout and juvenile steelhead in a Lake Ontario tributary","interactions":[],"lastModifiedDate":"2017-08-26T13:47:28","indexId":"70190336","displayToPublicDate":"2016-04-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2299,"text":"Journal of Freshwater Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Seasonal habitat use of brook trout and juvenile steelhead in a Lake Ontario tributary","docAbstract":"Brook trout (Salvelinus fontinalis) are generally restricted to headwaters in New York tributaries of Lake Ontario. In only a few streams are brook trout abundant in lower stream reaches that are accessible to adult Pacific salmonids migrating from the lake. Consequently, because of the rarity of native brook trout populations in these lower stream reaches it is important to understand how they use stream habitat in sympatry with juvenile Pacific salmonids which are now naturalized in several Lake Ontario tributaries. In this study, we examined the seasonal (spring, summer, and fall) habitat use of brook trout and juvenile steelhead (Oncorhynchus mykiss) in Hart Brook, a tributary of eastern Lake Ontario. We found interspecific, intraspecific, and seasonal variation in habitat use. Subyearling steelhead were associated with faster water velocities than subyearling brook trout and, overall, had the least habitat similarity to the other salmonid groups examined. Overyearling brook trout and yearling steelhead exhibited the greatest degree of habitat selection and habitat selection by all four salmonid groups was greatest in summer. The availability of pool habitat for overyearling salmonids may pose the largest impediment to these species in Hart Brook.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/02705060.2015.1123655","usgsCitation":"Johnson, J.H., Abbett, R., Chalupnicki, M.A., and Verdoliva, F., 2016, Seasonal habitat use of brook trout and juvenile steelhead in a Lake Ontario tributary: Journal of Freshwater Ecology, v. 31, no. 2, p. 239-249, https://doi.org/10.1080/02705060.2015.1123655.","productDescription":"11 p.","startPage":"239","endPage":"249","ipdsId":"IP-070095","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":471366,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/02705060.2015.1123655","text":"Publisher Index Page"},{"id":345159,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"31","issue":"2","noUsgsAuthors":false,"publicationDate":"2016-01-27","publicationStatus":"PW","scienceBaseUri":"59a288c9e4b077f0056692af","contributors":{"authors":[{"text":"Johnson, James H. 0000-0002-5619-3871 jhjohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-5619-3871","contributorId":389,"corporation":false,"usgs":true,"family":"Johnson","given":"James","email":"jhjohnson@usgs.gov","middleInitial":"H.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":708508,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Abbett, Ross 0000-0001-6276-5541 rabbett@usgs.gov","orcid":"https://orcid.org/0000-0001-6276-5541","contributorId":4359,"corporation":false,"usgs":true,"family":"Abbett","given":"Ross","email":"rabbett@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":708509,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chalupnicki, Marc A. mchalupnicki@usgs.gov","contributorId":3236,"corporation":false,"usgs":true,"family":"Chalupnicki","given":"Marc","email":"mchalupnicki@usgs.gov","middleInitial":"A.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":708510,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Verdoliva, Francis","contributorId":150381,"corporation":false,"usgs":false,"family":"Verdoliva","given":"Francis","email":"","affiliations":[{"id":13678,"text":"New York State Department of Environmental Conservation","active":true,"usgs":false}],"preferred":false,"id":708511,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70189512,"text":"70189512 - 2016 - Aeshnid dragonfly larvae as bioindicators of methylmercury contamination in aquatic systems impacted by elevated sulfate loading","interactions":[],"lastModifiedDate":"2017-07-14T10:36:43","indexId":"70189512","displayToPublicDate":"2016-04-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1479,"text":"Ecotoxicology","active":true,"publicationSubtype":{"id":10}},"title":"Aeshnid dragonfly larvae as bioindicators of methylmercury contamination in aquatic systems impacted by elevated sulfate loading","docAbstract":"Methylmercury (MeHg) levels in dragonfly larvae and water were measured over two years in aquatic systems impacted to varying degrees by sulfate releases related to iron mining activity. This study examined the impact of elevated sulfate loads on MeHg concentrations and tested the use of MeHg in dragonfly larvae as an indicator of MeHg levels in a range of aquatic systems including 16 river/stream sites and two lakes. MeHg concentrations in aeshnid dragonfly larvae were positively correlated (R2 = 0.46, p < 0.01) to peak MeHg concentrations in the dissolved phase for the combined years of 2012 and 2013. This relation was strong in 2012 (R2 = 0.85, p < 0.01), but showed no correlation in 2013 (R2 = 0.02, p > 0.05). MeHg in dragonfly larvae were not elevated at the highest sulfate sites, but rather the reverse was generally observed. Record rainfall events in 2012 and above average rainfall in 2013 likely delivered the majority of Hg and MeHg to these systems via interflow and activated groundwater flow through reduced sediments. As a result, the impacts of elevated sulfate releases due to mining activities were not apparent in these systems where little of the sulfate is reduced. Lower bioaccumulation factors for MeHg in aeshnid dragonfly larvae were observed with increasing dissolved organic carbon (DOC) concentrations. This finding is consistent with previous studies showing that MeHg in high DOC systems is less bioavailable; an equilibrium model shows that more MeHg being associated with DOC rather than algae at the base of the food chain readily explains the lower bioaccumulation factors.
","language":"English","publisher":"Springer","doi":"10.1007/s10646-015-1603-9","usgsCitation":"Jeremiason, J.D., Reiser, T.K., Weitz, R.A., Berndt, M., and Aiken, G.R., 2016, Aeshnid dragonfly larvae as bioindicators of methylmercury contamination in aquatic systems impacted by elevated sulfate loading: Ecotoxicology, v. 25, no. 3, p. 456-468, https://doi.org/10.1007/s10646-015-1603-9.","productDescription":"13 p.","startPage":"456","endPage":"468","ipdsId":"IP-071234","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":343854,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"25","issue":"3","noUsgsAuthors":false,"publicationDate":"2016-01-06","publicationStatus":"PW","scienceBaseUri":"5969d82be4b0d1f9f060a18c","contributors":{"authors":[{"text":"Jeremiason, Jeffrey D.","contributorId":7146,"corporation":false,"usgs":true,"family":"Jeremiason","given":"Jeffrey","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":704977,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reiser, T. K.","contributorId":194673,"corporation":false,"usgs":false,"family":"Reiser","given":"T.","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":704978,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Weitz, R. A.","contributorId":194674,"corporation":false,"usgs":false,"family":"Weitz","given":"R.","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":704979,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Berndt, M.E.","contributorId":78487,"corporation":false,"usgs":true,"family":"Berndt","given":"M.E.","email":"","affiliations":[],"preferred":false,"id":704980,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Aiken, George R. 0000-0001-8454-0984 graiken@usgs.gov","orcid":"https://orcid.org/0000-0001-8454-0984","contributorId":1322,"corporation":false,"usgs":true,"family":"Aiken","given":"George","email":"graiken@usgs.gov","middleInitial":"R.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":704981,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70178868,"text":"70178868 - 2016 - Increased temperatures combined with lowered salinities differentially impact oyster size class growth and mortality","interactions":[],"lastModifiedDate":"2016-12-09T15:46:38","indexId":"70178868","displayToPublicDate":"2016-04-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2455,"text":"Journal of Shellfish Research","active":true,"publicationSubtype":{"id":10}},"title":"Increased temperatures combined with lowered salinities differentially impact oyster size class growth and mortality","docAbstract":"Changes in the timing and interaction of seasonal high temperatures and low salinities as predicted by climate change models could dramatically alter oyster population dynamics. Little is known explicitly about how low salinity and high temperature combinations affect spat (<25mm), seed (25–75mm), andmarket (>75mm) oyster growth and mortality. Using field and laboratory studies, this project quantified the combined effects of extremely low salinities (<5) and high temperatures (>30°C) on growth and survival of spat, seed, andmarket-sized oysters. In 2012 and 2013, hatchery-produced oysters were placed in open and closed cages at three sites in Breton Sound, LA, along a salinity gradient that typically ranged from 5 to 20. Growth and mortality were recorded monthly. Regardless of size class, oysters at the lowest salinity site (annualmean = 4.8) experienced significantly highermortality and lower growth than oysters located in higher salinity sites (annual means = 11.1 and 13.0, respectively); furthermore, all oysters in open cages at the two higher salinity sites experienced higher mortality than in closed cages, likely due to predation. To explicitly examine oyster responses to extreme low salinity and high temperature combinations, a series of laboratory studies were conducted. Oysters were placed in 18 tanks in a fully crossed temperature (25°C, 32°C) by salinity (1, 5, and 15) study with three replicates, and repeated at least twice for each oyster size class. Regardless of temperature, seed and market oysters held in low salinity tanks (salinity 1) experienced 100% mortality within 7 days. In contrast, at salinity 5, temperature significantly affected mortality; oysters in all size classes experienced greater than 50%mortality at 32°C and less than 40%mortality at 25°C. At the highest salinity tested (15), only market-sized oysters held at 32°C experienced significant mortality (>60%). These studies demonstrate that high water temperatures (>30°C) and low salinities (<5) negatively impact oyster growth and survival differentially and that high temperatures alone may negatively impact market-sized oysters. It is critical to understand the potential impacts of climate and anthropogenic changes on oyster resources to better adapt and manage for long-term sustainability.
","language":"English","publisher":"National Shellfisheries Association","doi":"10.2983/035.035.0112","usgsCitation":"LaPeyre, M.K., Rybovich, M., Hall, S., and La Peyre, J.F., 2016, Increased temperatures combined with lowered salinities differentially impact oyster size class growth and mortality: Journal of Shellfish Research, v. 35, no. 1, p. 101-113, https://doi.org/10.2983/035.035.0112.","productDescription":"13 p.","startPage":"101","endPage":"113","ipdsId":"IP-070396","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":331826,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","city":"Breton Sound","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.9945068359375,\n 29.501768632523262\n ],\n [\n -89.9945068359375,\n 29.878755346037977\n ],\n [\n -89.39849853515625,\n 29.878755346037977\n ],\n [\n -89.39849853515625,\n 29.501768632523262\n ],\n [\n -89.9945068359375,\n 29.501768632523262\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"35","issue":"1","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"584bd0dfe4b077fc20250e12","contributors":{"authors":[{"text":"LaPeyre, Megan K. 0000-0001-9936-2252 mlapeyre@usgs.gov","orcid":"https://orcid.org/0000-0001-9936-2252","contributorId":585,"corporation":false,"usgs":true,"family":"LaPeyre","given":"Megan","email":"mlapeyre@usgs.gov","middleInitial":"K.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":655385,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rybovich, Molly","contributorId":177344,"corporation":false,"usgs":false,"family":"Rybovich","given":"Molly","email":"","affiliations":[],"preferred":false,"id":655401,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hall, Steven G.","contributorId":177345,"corporation":false,"usgs":false,"family":"Hall","given":"Steven G.","affiliations":[],"preferred":false,"id":655402,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"La Peyre, Jerome F.","contributorId":34697,"corporation":false,"usgs":true,"family":"La Peyre","given":"Jerome","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":655403,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70179445,"text":"70179445 - 2016 - Slow climate velocities of mountain streams portend their role as refugia for cold-water biodiversity","interactions":[],"lastModifiedDate":"2017-01-03T11:21:55","indexId":"70179445","displayToPublicDate":"2016-04-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3165,"text":"Proceedings of the National Academy of Sciences of the United States of America","active":true,"publicationSubtype":{"id":10}},"title":"Slow climate velocities of mountain streams portend their role as refugia for cold-water biodiversity","docAbstract":"The imminent demise of montane species is a recurrent theme in the climate change literature, particularly for aquatic species that are constrained to networks and elevational rather than latitudinal retreat as temperatures increase. Predictions of widespread species losses, however, have yet to be fulfilled despite decades of climate change, suggesting that trends are much weaker than anticipated and may be too subtle for detection given the widespread use of sparse water temperature datasets or imprecise surrogates like elevation and air temperature. Through application of large water-temperature databases evaluated for sensitivity to historical air-temperature variability and computationally interpolated to provide high-resolution thermal habitat information for a 222,000-km network, we estimate a less dire thermal plight for cold-water species within mountains of the northwestern United States. Stream warming rates and climate velocities were both relatively low for 1968–2011 (average warming rate = 0.101 °C/decade; median velocity = 1.07 km/decade) when air temperatures warmed at 0.21 °C/decade. Many cold-water vertebrate species occurred in a subset of the network characterized by low climate velocities, and three native species of conservation concern occurred in extremely cold, slow velocity environments (0.33–0.48 km/decade). Examination of aggressive warming scenarios indicated that although network climate velocities could increase, they remain low in headwaters because of strong local temperature gradients associated with topographic controls. Better information about changing hydrology and disturbance regimes is needed to complement these results, but rather than being climatic cul-de-sacs, many mountain streams appear poised to be redoubts for cold-water biodiversity this century.
","language":"English","publisher":"PNAS","doi":"10.1073/pnas.1522429113","usgsCitation":"Isaak, D.J., Young, M.K., Luce, C.H., Hostetler, S.W., Wenger, S., Peterson, E.E., Ver Hoef, J., Groce, M.C., Horan, D.L., and Nagel, D.E., 2016, Slow climate velocities of mountain streams portend their role as refugia for cold-water biodiversity: Proceedings of the National Academy of Sciences of the United States of America, v. 113, no. 16, p. 4374-4379, https://doi.org/10.1073/pnas.1522429113.","productDescription":"6 p.","startPage":"4374","endPage":"4379","ipdsId":"IP-072844","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":471098,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/4843441","text":"External Repository"},{"id":332732,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"113","issue":"16","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-04-04","publicationStatus":"PW","scienceBaseUri":"586cc697e4b0f5ce109fa957","contributors":{"authors":[{"text":"Isaak, Daniel J.","contributorId":177835,"corporation":false,"usgs":false,"family":"Isaak","given":"Daniel","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":657245,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Young, Michael K.","contributorId":177836,"corporation":false,"usgs":false,"family":"Young","given":"Michael","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":657246,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Luce, Charles H.","contributorId":177837,"corporation":false,"usgs":false,"family":"Luce","given":"Charles","email":"","middleInitial":"H.","affiliations":[{"id":37389,"text":"U.S. Forest Service","active":true,"usgs":false}],"preferred":false,"id":657247,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hostetler, Steven W. 0000-0003-2272-8302 swhostet@usgs.gov","orcid":"https://orcid.org/0000-0003-2272-8302","contributorId":3249,"corporation":false,"usgs":true,"family":"Hostetler","given":"Steven","email":"swhostet@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":657244,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wenger, Seth J.","contributorId":177838,"corporation":false,"usgs":false,"family":"Wenger","given":"Seth J.","affiliations":[],"preferred":false,"id":657248,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Peterson, Erin E.","contributorId":177839,"corporation":false,"usgs":false,"family":"Peterson","given":"Erin","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":657249,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ver Hoef, Jay","contributorId":177840,"corporation":false,"usgs":false,"family":"Ver Hoef","given":"Jay","affiliations":[],"preferred":false,"id":657250,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Groce, Matthew C.","contributorId":177841,"corporation":false,"usgs":false,"family":"Groce","given":"Matthew","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":657251,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Horan, Dona L.","contributorId":36672,"corporation":false,"usgs":true,"family":"Horan","given":"Dona","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":657252,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Nagel, David E.","contributorId":86887,"corporation":false,"usgs":true,"family":"Nagel","given":"David","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":657253,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70179637,"text":"70179637 - 2016 - Basin scale controls on CO2 and CH4 emissions from the Upper Mississippi River","interactions":[],"lastModifiedDate":"2017-01-09T11:30:46","indexId":"70179637","displayToPublicDate":"2016-04-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1807,"text":"Geophysical Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Basin scale controls on CO2 and CH4 emissions from the Upper Mississippi River","docAbstract":"The Upper Mississippi River, engineered for river navigation in the 1930s, includes a series of low-head dams and navigation pools receiving elevated sediment and nutrient loads from the mostly agricultural basin. Using high-resolution, spatially resolved water quality sensor measurements along 1385 river kilometers, we show that primary productivity and organic matter accumulation affect river carbon dioxide and methane emissions to the atmosphere. Phytoplankton drive CO2to near or below atmospheric equilibrium during the growing season, while anaerobic carbon oxidation supports a large proportion of the CO2 and CH4 production. Reductions of suspended sediment load, absent of dramatic reductions in nutrients, will likely further reduce net CO2emissions from the river. Large river pools, like Lake Pepin, which removes the majority of upstream sediments, and large agricultural tributaries downstream that deliver significant quantities of sediments and nutrients, are likely to persist as major geographical drivers of greenhouse gas emissions.
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Further analysis of fine grains is typically based on the plasticity chart. Whereas pore-fluid-chemistry-dependent soil response is a salient and distinguishing characteristic of fine grains, pore-fluid chemistry is not addressed in current classification systems. Liquid limits obtained with electrically contrasting pore fluids (deionized water, 2-M NaCl brine, and kerosene) are combined to define the soil “electrical sensitivity.” Liquid limit and electrical sensitivity can be effectively used to classify fine grains according to their fluid-soil response into no-, low-, intermediate-, or high-plasticity fine grains of low, intermediate, or high electrical sensitivity. The proposed methodology benefits from the accumulated experience with liquid limit in the field and addresses the needs of a broader range of geotechnical engineering problems.
Concentrations of benzene, toluene, naphthalene, and dissolved oxygen in groundwater at a former manufactured gas plant site near Charleston, South Carolina, USA, have been monitored since the installation of a phytoremediation system of hybrid poplar trees in 1998. Between 2000 and 2014, the concentrations of benzene, toluene, and naphthalene (BT&N) in groundwater in the planted area have decreased. For example, in the monitoring well containing the highest concentrations of BT&N, benzene concentrations decreased from 10,200 µg/L to less than 4000 µg/L, toluene concentrations decreased from 2420 µg/L to less than 20 µg/L, and naphthalene concentrations decreased from 6840 µg/L to less than 3000 µg/L. Concentrations of BT&N in groundwater in all wells were observed to be lower during the summer months relative to the winter months of a particular year during the first few years after installing the phytoremediation system, most likely due to increased transpiration and contaminant uptake by the hybrid poplar trees during the warm summer months; this pathway of uptake by trees was confirmed by the detection of benzene, toluene, and naphthalene in trees during sampling events in 2002, and later in the study in 2012. These data suggest that the phytoremediation system affects the groundwater contaminants on a seasonal basis and, over multiple years, has resulted in a cumulative decrease in dissolved-phase contaminant concentrations in groundwater. The removal of dissolved organic contaminants from the aquifer has resulted in a lower demand on dissolved oxygen supplied by recharge and, as a result, the redox status of the groundwater has changed from anoxic to oxic conditions. This study provides much needed information for water managers and other scientists on the viability of the long-term effectiveness of phytoremediation in decreasing groundwater contaminants and increasing dissolved oxygen at sites contaminated by benzene, toluene, and naphthalene.
","language":"English","publisher":"Springer-Verlag","doi":"10.1007/s12665-016-5408-9","usgsCitation":"Landmeyer, J., and Effinger, T.N., 2016, Effect of phytoremediation on concentrations of benzene, toluene, naphthalene, and dissolved oxygen in groundwater at a former manufactured gas plant site, Charleston, South Carolina, USA, 1998–2014: Environmental Earth Sciences, v. 75, 605; 13 p., https://doi.org/10.1007/s12665-016-5408-9.","productDescription":"605; 13 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070997","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":330430,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"South Carolina","city":"Charleston","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -79.92934584617615,\n 32.7883749103601\n ],\n [\n -79.92934584617615,\n 32.791134828514295\n ],\n [\n -79.92491483688354,\n 32.791134828514295\n ],\n [\n -79.92491483688354,\n 32.7883749103601\n ],\n [\n -79.92934584617615,\n 32.7883749103601\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"75","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2016-03-31","publicationStatus":"PW","scienceBaseUri":"5811c0f2e4b0f497e79a5a77","chorus":{"doi":"10.1007/s12665-016-5408-9","url":"http://dx.doi.org/10.1007/s12665-016-5408-9","publisher":"Springer Nature","authors":"Landmeyer James E., Effinger Thomas N.","journalName":"Environmental Earth Sciences","publicationDate":"3/31/2016","auditedOn":"8/1/2016","publiclyAccessibleDate":"3/31/2016"},"contributors":{"authors":[{"text":"Landmeyer, James 0000-0002-5640-3816 jlandmey@usgs.gov","orcid":"https://orcid.org/0000-0002-5640-3816","contributorId":3257,"corporation":false,"usgs":true,"family":"Landmeyer","given":"James","email":"jlandmey@usgs.gov","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":652109,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Effinger, Thomas N.","contributorId":176300,"corporation":false,"usgs":false,"family":"Effinger","given":"Thomas","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":652110,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70169948,"text":"ofr20161056 - 2016 - Construction, calibration, and validation of the RBM10 water temperature model for the Trinity River, northern California","interactions":[],"lastModifiedDate":"2016-04-01T08:35:51","indexId":"ofr20161056","displayToPublicDate":"2016-03-31T17:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-1056","title":"Construction, calibration, and validation of the RBM10 water temperature model for the Trinity River, northern California","docAbstract":"We constructed a one-dimensional daily averaged water-temperature model to simulate Trinity River temperatures for 1980–2013. The purpose of this model is to assess effects of water-management actions on water temperature and to provide water temperature inputs for a salmon population dynamics model. Simulated meteorological data, observed streamflow data, and observed water temperatures were used as model inputs to simulate a continuous 34-year time series of historical daily mean water temperature at eight locations along 112.2 river miles from Lewiston Dam near Weaverville, California, downstream to the Klamath River confluence. To demonstrate the utility of the model to inform management actions, we simulated three management alternatives to assess the effects of bypass flow augmentation in a drought year, 1994, and compared those results to the simulated historical baseline, referred to as the “No Action” alternative scenario. Augmentation flows from the Lewiston Dam bypass consist of temperature-controlled releases capable of cooling downstream water temperatures in hot times of the year, which can reduce the probability of disease outbreaks in fish populations. Outputs from the Trinity River water-temperature model were then used as inputs to an existing water-temperature model of the Klamath River to evaluate the effect of augmentation flow releases on water temperatures in the lower Klamath River.
\nWe structured the Trinity River water-temperature model in River Basin Model-10 (RBM10), which uses a simple equilibrium flow model, assuming discharge in each river segment on each day is transmitted downstream instantaneously. The model uses a heat-budget formulation to quantify heat flux at the air-water interface. Inputs for the heat budget are calculated from daily mean meteorological data, including net shortwave solar radiation, net longwave atmospheric radiation, air temperature, wind speed, vapor pressure, and a psychrometric constant needed to calculate the Bowen ratio. The modeling domain was divided into eight reaches ranging in length from 8.8 to 20.6 miles, which were calibrated and validated separately with observed water temperature data collected irregularly from 1980 to 2013. Root mean square errors of observed and simulated water temperatures for the eight reaches ranged from 0.25 to 1.12 degrees Celsius (°C). Mean absolute errors ranged from 0.18 to 0.89 °C. For model validation, a k-fold cross-validation technique was used. Validation root mean square error and mean absolute error for the eight reaches ranged from 0.24 to 1.11 °C and from 0.18 to 0.89 °C, respectively.
\nAugmentation scenarios were based on historical hydrological and meteorological data, combined with prescribed flow and temperature releases from Lewiston Dam provided by the Bureau of Reclamation. Water releases were scheduled to achieve targeted flows of 2,500, 2,800, and 3,200 cubic feet per second in the lower Klamath River from mid-August through late September, coinciding with the upstream migration of adult fall-run Chinook salmon (Oncorhynchus tshawytscha). Water temperatures simulated at river mile 5.7 on the Klamath River showed a 5 °C decrease from the No Action historical baseline, which was near or greater than 23 °C when augmentation began in mid-August. Thereafter, an approximate 1 °C difference among augmentation scenarios emerged, with the decrease in water temperature commensurate to the level of augmentation. All augmentation scenarios simulated water temperatures equal to or less than 21 °C from mid-August through late September. Water temperatures equal to or greater than 23 °C are of particular interest because of a thermal threshold known to inhibit upstream migration of salmon. When temperatures exceed this approximate 23 °C threshold, Chinook salmon are known to congregate in high densities in thermal refugias and show extended residence times, which can potentially trigger epizootic outbreaks such as of Ichthyophthirius multifiliis (“Ich”) and Flavobacterium columnare (“Columnaris”) that were the causative factors of the Klamath River fish kill in 2002. A model with the ability to simulate water temperatures in response to management actions at the basin scale is a valuable asset for water managers who must make decisions about how best to use limited water resources, which directly affect the state of fisheries in the Klamath Basin.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161056","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service and the Bureau of Reclamation","usgsCitation":"Jones, E.C., Perry, R.W., Risley, J.C., Som, N.A., and Hetrick, N.J., 2016, Construction, calibration, and validation of the RBM10 water temperature model for the Trinity River, northern California: U.S. Geological Survey Open-File Report 2016–1056, 46 p., https://dx.doi.org/10.3133/ofr20161056.","productDescription":"vi, 46 p.","numberOfPages":"56","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-070848","costCenters":[{"id":654,"text":"Western Fisheries Research 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U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115
http://wfrc.usgs.gov/
In 2015, a major outbreak of highly pathogenic avian influenza virus (HPAIV) infection devastated poultry facilities in Minnesota, USA. To clarify the role of wild birds, we tested 3,139 waterfowl fecal samples and 104 sick and dead birds during March 9–June 4, 2015. HPAIV was isolated from a Cooper’s hawk but not from waterfowl.
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States","interactions":[],"lastModifiedDate":"2016-03-31T12:39:04","indexId":"70169977","displayToPublicDate":"2016-03-31T13:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2602,"text":"Landscape Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Temporal and spatial patterns of wetland extent influence variability of surface water connectivity in the Prairie Pothole Region, United States","docAbstract":"Context. Quantifying variability in landscape-scale surface water connectivity can help improve our understanding of the multiple effects of wetlands on downstream waterways. Objectives. We examined how wetland merging and the coalescence of wetlands with streams varied both spatially (among ecoregions) and interannually (from drought to deluge) across parts of the Prairie Pothole Region. Methods. Wetland extent was derived over a time series (1990-2011) using Landsat imagery. Changes in landscape-scale connectivity, generated by the physical coalescence of wetlands with other surface water features, were quantified by fusing static wetland and stream datasets with Landsat-derived wetland extent maps, and related to multiple wetness indices. The usage of Landsat allows for decadal-scale analysis, but limits the types of surface water connections that can be detected. Results. Wetland extent correlated positively with the merging of wetlands and wetlands with streams. Wetness conditions, as defined by drought indices and runoff, were positively correlated with wetland extent, but less consistently correlated with measures of surface water connectivity. The degree of wetland-wetland merging was found to depend less on total wetland area or density, and more on climate conditions, as well as the threshold for how wetland/upland was defined. In contrast, the merging of wetlands with streams was positively correlated with stream density, and inversely related to wetland density. Conclusions. Characterizing the degree of surface water connectivity within the Prairie Pothole Region in North America requires consideration of 1) climate-driven variation in wetness conditions and 2) within-region variation in wetland and stream spatial arrangements.
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