Populations of the once abundant Lost River (Deltistes luxatus) and shortnose suckers (Chasmistes brevirostris) of the Upper Klamath Basin, decreased so substantially throughout the 20th century that they were listed under the Endangered Species Act in 1988. Major landscape alterations, deterioration of water quality, and competition with and predation by exotic species are listed as primary causes of the decreases in populations. Upper Klamath Lake populations are decreasing because fish lost due to adult mortality, which is relatively low for adult Lost River suckers and variable for adult shortnose suckers, are not replaced by new young adult suckers recruiting into known adult spawning aggregations. Catch-at-age and size data indicate that most adult suckers presently in Upper Klamath Lake spawning populations were hatched around 1991. While, a lack of egg production and emigration of young fish (especially larvae) may contribute, catch-at-length and age data indicate high mortality during the first summer or winter of life may be the primary limitation to the recruitment of young adults. The causes of juvenile sucker mortality are unknown.
We compiled and analyzed catch, length, age, and species data on juvenile suckers from Upper Klamath Lake from eight prior studies conducted from 2001 to 2015 to examine annual variation in apparent production, survival, and growth of young suckers. We used a combination of qualitative assessments, general linear models, and linear regression to make inferences about annual differences in juvenile sucker dynamics. The intent of this exercise is to provide information that can be compared to annual variability in environmental conditions with the hopes of understanding what drives juvenile sucker population dynamics.
Age-0 Lost River suckers generally grew faster than age-0 shortnose suckers, but the difference in growth rates between the two species varied among years. This unsynchronized annual variation in daily growth may be an indication that environmental conditions are affecting growth rates of these species in different ways.
The combined evidence outlined in this report and in Simon and others (2012) indicates that years of relatively high age-0 sucker production occurred in the late 1990s through at least 2000, in 2006, and in 2011. Our analysis of annual age-0 sucker catch per unit effort (CPUE), which accounted for zero inflated data and annual variation in sampling gears and locations, indicated that 2006 had the greatest apparent relative production of age-0 suckers ≥ 45 mm standard length (SL) during the time period examined. Midsummer trap net effort by the U.S. Geological Survey (USGS) was too sparse to examine age-0 sucker CPUE from 2011 to 2013. Relatively frequent catches of age-1 suckers in 2001, 2007, and 2012 corroborated relatively high CPUE for age-0 suckers during 1999–2000, 2006, and 2011, as reported by USGS or Simon and others (2012).
There were several indications in the data that juvenile sucker survival is low from at least midsummer of the first year of life through mid-September of the second year of life. Our estimated index of relative apparent age-0 sucker late-summer survival, which accounted for zero inflated data and variations in sampling gears and locations, was higher in 2009 than in 2004. Our index of apparent age-0 sucker mortality for all other years from 2001 to 2015 was similar among years. Seventy-five percent of age-1 suckers were captured prior to July 17 each year. In 2007, the one year with substantial age-1 sucker summertime catches, the proportion of nets to capture age-1 suckers decreased from July to mid-September. Maximum annual age-2+ sucker CPUE was 0.02 fish per net, 10,000 times less than the maximum annual age-0 sucker CPUE.
Analysis of species data indicated that juvenile Lost River suckers may have greater apparent mortality than shortnose suckers. Lost River suckers made up a smaller proportion of age-0 suckers captured in July each year than would be expected, based on the abundance of adult Lost River suckers relative to shortnose suckers, and higher Lost River than shortnose sucker fecundity. The proportion of age-0 suckers captured that were Lost River suckers decreased from July to September in several years. Only 14 percent of age-1 or older juvenile suckers identified to species over the 15-year time period were Lost River suckers.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171069","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Burdick, S.M., and Martin, B.A., 2017, Inter-annual variability in apparent relative production, survival, and growth of juvenile Lost River and shortnose suckers in Upper Klamath Lake, Oregon, 2001–15: U.S. Geological Survey Open-File Report 2017–1069, 55 p., https://doi.org/10.3133/ofr20171069.","productDescription":"Report: vi, 55 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-082248","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":342516,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1069/ofr20171069.pdf","text":"Report","size":"3.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1069"},{"id":342517,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7ZC812F","text":"USGS data release","description":"USGS data release","linkHelpText":"Data for trap net captured juvenile Lost River and shortnose suckers from Upper Klamath Lake, Oregon"},{"id":342515,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1069/coverthb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Upper Klamath Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.14,\n 42.20\n ],\n [\n -121.7,\n 42.20\n ],\n [\n -121.7,\n 42.64\n ],\n [\n -122.14,\n 42.64\n ],\n [\n -122.14,\n 42.20\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115
Coral barium to calcium (Ba/Ca) ratios have been used to reconstruct records of upwelling, river and groundwater discharge, and sediment and dust input to the coastal ocean. However, this proxy has not yet been explicitly tested to determine if Ba inclusion in the coral skeleton is directly proportional to seawater Ba concentration and to further determine how additional factors such as temperature and calcification rate control coral Ba/Ca ratios. We measured the inclusion of Ba within aquaria reared juvenile corals (Favia fragum) at three temperatures (∼27.7, 24.6 and 22.5 °C) and three seawater Ba concentrations (73, 230 and 450 nmol kg−1). Coral polyps were settled on tiles conditioned with encrusting coralline algae, which complicated chemical analysis of the coral skeletal material grown during the aquaria experiments. We utilized Sr/Ca ratios of encrusting coralline algae (as low as 3.4 mmol mol−1) to correct coral Ba/Ca for this contamination, which was determined to be 26 ± 11% using a two end member mixing model. Notably, there was a large range in Ba/Ca across all treatments, however, we found that Ba inclusion was linear across the full concentration range. The temperature sensitivity of the distribution coefficient is within the range of previously reported values. Finally, calcification rate, which displayed large variability, was not correlated to the distribution coefficient. The observed temperature dependence predicts a change in coral Ba/Ca ratios of 1.1 μmol mol−1 from 20 to 28 °C for typical coastal ocean Ba concentrations of 50 nmol kg−1. Given the linear uptake of Ba by corals observed in this study, coral proxy records that demonstrate peaks of 10–25 μmol mol−1 would require coastal seawater Ba of between 60 and 145 nmol kg−1. Further validation of the coral Ba/Ca proxy requires evaluation of changes in seawater chemistry associated with the environmental perturbation recorded by the coral as well as verification of these results for Porites species, which are widely used in paleo reconstructions.
","language":"English","publisher":"Geochemical Society","doi":"10.1016/j.gca.2017.04.006","usgsCitation":"Gonneea Eagle, M., Cohen, A.L., DeCarlo, T.M., and Charette, M.A., 2017, Relationship between water and aragonite barium concentrations in aquaria reared juvenile corals: Geochimica et Cosmochimica Acta, v. 209, p. 123-134, https://doi.org/10.1016/j.gca.2017.04.006.","productDescription":"12 p.","startPage":"123","endPage":"134","ipdsId":"IP-079452","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":469749,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hdl.handle.net/1912/9163","text":"External Repository"},{"id":342424,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"209","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5965b1c8e4b0d1f9f05b37b0","contributors":{"authors":[{"text":"Gonneea Eagle, Meagan 0000-0001-5072-2755 mgonneea@usgs.gov","orcid":"https://orcid.org/0000-0001-5072-2755","contributorId":174590,"corporation":false,"usgs":true,"family":"Gonneea Eagle","given":"Meagan","email":"mgonneea@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":697917,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cohen, Anne L.","contributorId":190716,"corporation":false,"usgs":false,"family":"Cohen","given":"Anne","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":697918,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DeCarlo, Thomas M.","contributorId":190720,"corporation":false,"usgs":false,"family":"DeCarlo","given":"Thomas","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":697919,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Charette, Matthew A.","contributorId":92355,"corporation":false,"usgs":true,"family":"Charette","given":"Matthew","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":697920,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70188610,"text":"70188610 - 2017 - Quantifying drivers of wild pig movement across multiple spatial and temporal scales","interactions":[],"lastModifiedDate":"2017-06-17T11:53:46","indexId":"70188610","displayToPublicDate":"2017-06-15T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2792,"text":"Movement Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Quantifying drivers of wild pig movement across multiple spatial and temporal scales","docAbstract":"Background\nThe movement behavior of an animal is determined by extrinsic and intrinsic factors that operate at multiple spatio-temporal scales, yet much of our knowledge of animal movement comes from studies that examine only one or two scales concurrently. Understanding the drivers of animal movement across multiple scales is crucial for understanding the fundamentals of movement ecology, predicting changes in distribution, describing disease dynamics, and identifying efficient methods of wildlife conservation and management.\n\nMethods\nWe obtained over 400,000 GPS locations of wild pigs from 13 different studies spanning six states in southern U.S.A., and quantified movement rates and home range size within a single analytical framework. We used a generalized additive mixed model framework to quantify the effects of five broad predictor categories on movement: individual-level attributes, geographic factors, landscape attributes, meteorological conditions, and temporal variables. We examined effects of predictors across three temporal scales: daily, monthly, and using all data during the study period. We considered both local environmental factors such as daily weather data and distance to various resources on the landscape, as well as factors acting at a broader spatial scale such as ecoregion and season.\n\nResults\nWe found meteorological variables (temperature and pressure), landscape features (distance to water sources), a broad-scale geographic factor (ecoregion), and individual-level characteristics (sex-age class), drove wild pig movement across all scales, but both the magnitude and shape of covariate relationships to movement differed across temporal scales.\n\nConclusions\nThe analytical framework we present can be used to assess movement patterns arising from multiple data sources for a range of species while accounting for spatio-temporal correlations. Our analyses show the magnitude by which reaction norms can change based on the temporal scale of response data, illustrating the importance of appropriately defining temporal scales of both the movement response and covariates depending on the intended implications of research (e.g., predicting effects of movement due to climate change versus planning local-scale management). We argue that consideration of multiple spatial scales within the same framework (rather than comparing across separate studies post-hoc) gives a more accurate quantification of cross-scale spatial effects by appropriately accounting for error correlation.","language":"English","publisher":"BioMedCentral","doi":"10.1186/s40462-017-0105-1","usgsCitation":"Kay, S.L., Fischer, J.W., Monaghan, A.J., Beasley, J.C., Boughton, R., Campbell, T.A., Cooper, S.M., Ditchkoff, S.S., Hartley, S.B., Kilgo, J.C., Wisely, S.M., Wyckoff, A.C., Vercauteren, K.C., and Pipen, K.M., 2017, Quantifying drivers of wild pig movement across multiple spatial and temporal scales: Movement Ecology, v. 5, no. 14, p. 1-15, https://doi.org/10.1186/s40462-017-0105-1.","productDescription":" 15 p. ","startPage":"1","endPage":"15","ipdsId":"IP-078294","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":469747,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s40462-017-0105-1","text":"Publisher Index Page"},{"id":342619,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"5","issue":"14","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2017-06-15","publicationStatus":"PW","scienceBaseUri":"59463fa3e4b062508e34408f","contributors":{"authors":[{"text":"Kay, Shannon L.","contributorId":193049,"corporation":false,"usgs":false,"family":"Kay","given":"Shannon","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":698585,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fischer, Justin W.","contributorId":171828,"corporation":false,"usgs":false,"family":"Fischer","given":"Justin","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":698586,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Monaghan, Andrew J.","contributorId":179216,"corporation":false,"usgs":false,"family":"Monaghan","given":"Andrew","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":698587,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Beasley, James C","contributorId":193050,"corporation":false,"usgs":false,"family":"Beasley","given":"James","email":"","middleInitial":"C","affiliations":[],"preferred":false,"id":698588,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Boughton, Raoul","contributorId":172817,"corporation":false,"usgs":false,"family":"Boughton","given":"Raoul","affiliations":[{"id":27096,"text":"Wildlife Ecology and Conservation, Range Cattle Research and Education Center, University of Florida, 3401 Experiment Station, Ona, Florida 33865 USA","active":true,"usgs":false}],"preferred":false,"id":698589,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Campbell, Tyler A","contributorId":193051,"corporation":false,"usgs":false,"family":"Campbell","given":"Tyler","email":"","middleInitial":"A","affiliations":[],"preferred":false,"id":698590,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cooper, Susan M","contributorId":193052,"corporation":false,"usgs":false,"family":"Cooper","given":"Susan","email":"","middleInitial":"M","affiliations":[],"preferred":false,"id":698591,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Ditchkoff, Stephen S.","contributorId":193053,"corporation":false,"usgs":false,"family":"Ditchkoff","given":"Stephen","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":698592,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Hartley, Stephen B. 0000-0003-1380-2769 hartleys@usgs.gov","orcid":"https://orcid.org/0000-0003-1380-2769","contributorId":4164,"corporation":false,"usgs":true,"family":"Hartley","given":"Stephen","email":"hartleys@usgs.gov","middleInitial":"B.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":698584,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Kilgo, John C","contributorId":193054,"corporation":false,"usgs":false,"family":"Kilgo","given":"John","email":"","middleInitial":"C","affiliations":[],"preferred":false,"id":698593,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Wisely, Samantha M","contributorId":193055,"corporation":false,"usgs":false,"family":"Wisely","given":"Samantha","email":"","middleInitial":"M","affiliations":[],"preferred":false,"id":698594,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Wyckoff, A Christy","contributorId":193056,"corporation":false,"usgs":false,"family":"Wyckoff","given":"A","email":"","middleInitial":"Christy","affiliations":[],"preferred":false,"id":698595,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Vercauteren, Kurt C.","contributorId":193057,"corporation":false,"usgs":false,"family":"Vercauteren","given":"Kurt","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":698596,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Pipen, Kim M","contributorId":193058,"corporation":false,"usgs":false,"family":"Pipen","given":"Kim","email":"","middleInitial":"M","affiliations":[],"preferred":false,"id":698597,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}} ,{"id":70188579,"text":"70188579 - 2017 - Nearly 400 million people are at higher risk of schistosomiasis because dams block the migration of snail-eating river prawns","interactions":[],"lastModifiedDate":"2017-06-15T16:13:29","indexId":"70188579","displayToPublicDate":"2017-06-15T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3048,"text":"Philosophical Transactions of the Royal Society B: Biological Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Nearly 400 million people are at higher risk of schistosomiasis because dams block the migration of snail-eating river prawns","docAbstract":"Dams have long been associated with elevated burdens of human schistosomiasis, but how dams increase disease is not always clear, in part because dams have many ecological and socio-economic effects. A recent hypothesis argues that dams block reproduction of the migratory river prawns that eat the snail hosts of schistosomiasis. In the Senegal River Basin, there is evidence that prawn populations declined and schistosomiasis increased after completion of the Diama Dam. Restoring prawns to a water-access site upstream of the dam reduced snail density and reinfection rates in people. However, whether a similar cascade of effects (from dams to prawns to snails to human schistosomiasis) occurs elsewhere is unknown. Here, we examine large dams worldwide and identify where their catchments intersect with endemic schistosomiasis and the historical habitat ranges of large, migratory Macrobrachium spp. prawns. River prawn habitats are widespread, and we estimate that 277–385 million people live within schistosomiasis-endemic regions where river prawns are or were present (out of the 800 million people who are at risk of schistosomiasis). Using a published repository of schistosomiasis studies in sub-Saharan Africa, we compared infection before and after the construction of 14 large dams for people living in: (i) upstream catchments within historical habitats of native prawns, (ii) comparable undammed watersheds, and (iii) dammed catchments beyond the historical reach of migratory prawns. Damming was followed by greater increases in schistosomiasis within prawn habitats than outside prawn habitats. We estimate that one third to one half of the global population-at-risk of schistosomiasis could benefit from restoration of native prawns. Because dams block prawn migrations, our results suggest that prawn extirpation contributes to the sharp increase of schistosomiasis after damming, and points to prawn restoration as an ecological solution for reducing human disease.","language":"English","publisher":"The Royal Society","doi":"10.1098/rstb.2016.0127","usgsCitation":"Sokolow, S.H., Jones, I.J., Jocque, M.M., La, D., Cords, O., Knight, A., Lund, A., Wood, C.L., Lafferty, K.D., Hoover, C.M., Collender, P.A., Remais, J.V., Lopez-Carr, D., Fisk, J.J., Kuris, A.M., and De Leo, G.A., 2017, Nearly 400 million people are at higher risk of schistosomiasis because dams block the migration of snail-eating river prawns: Philosophical Transactions of the Royal Society B: Biological Sciences, v. 372, no. 1722, 20160127; 12 p., https://doi.org/10.1098/rstb.2016.0127.","productDescription":"20160127; 12 p.","ipdsId":"IP-077017","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":469751,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1098/rstb.2016.0127","text":"Publisher Index Page"},{"id":342576,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"372","issue":"1722","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2017-04-24","publicationStatus":"PW","scienceBaseUri":"59439c90e4b062508e31a96d","contributors":{"authors":[{"text":"Sokolow, Susanne H.","contributorId":52503,"corporation":false,"usgs":false,"family":"Sokolow","given":"Susanne","email":"","middleInitial":"H.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":698419,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jones, Isabel J.","contributorId":173135,"corporation":false,"usgs":false,"family":"Jones","given":"Isabel","email":"","middleInitial":"J.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":698420,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jocque, Merlijn M. T.","contributorId":178115,"corporation":false,"usgs":false,"family":"Jocque","given":"Merlijn","email":"","middleInitial":"M. T.","affiliations":[],"preferred":false,"id":698421,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"La, Diana","contributorId":192996,"corporation":false,"usgs":false,"family":"La","given":"Diana","email":"","affiliations":[],"preferred":false,"id":698422,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cords, Olivia","contributorId":192997,"corporation":false,"usgs":false,"family":"Cords","given":"Olivia","email":"","affiliations":[],"preferred":false,"id":698423,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Knight, Anika","contributorId":192998,"corporation":false,"usgs":false,"family":"Knight","given":"Anika","email":"","affiliations":[],"preferred":false,"id":698424,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lund, Andrea","contributorId":192999,"corporation":false,"usgs":false,"family":"Lund","given":"Andrea","affiliations":[],"preferred":false,"id":698425,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wood, Chelsea L.","contributorId":192504,"corporation":false,"usgs":false,"family":"Wood","given":"Chelsea","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":698426,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Lafferty, Kevin D. 0000-0001-7583-4593 klafferty@usgs.gov","orcid":"https://orcid.org/0000-0001-7583-4593","contributorId":1415,"corporation":false,"usgs":true,"family":"Lafferty","given":"Kevin","email":"klafferty@usgs.gov","middleInitial":"D.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":698418,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Hoover, Christopher M.","contributorId":193000,"corporation":false,"usgs":false,"family":"Hoover","given":"Christopher","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":698427,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Collender, Phillip A.","contributorId":193001,"corporation":false,"usgs":false,"family":"Collender","given":"Phillip","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":698428,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Remais, Justin V.","contributorId":193002,"corporation":false,"usgs":false,"family":"Remais","given":"Justin","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":698429,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Lopez-Carr, David","contributorId":193003,"corporation":false,"usgs":false,"family":"Lopez-Carr","given":"David","email":"","affiliations":[],"preferred":false,"id":698430,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Fisk, Jonathan J.","contributorId":193004,"corporation":false,"usgs":false,"family":"Fisk","given":"Jonathan","middleInitial":"J.","affiliations":[],"preferred":false,"id":698431,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Kuris, Armand M.","contributorId":189859,"corporation":false,"usgs":false,"family":"Kuris","given":"Armand","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":698432,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"De Leo, Giulio A.","contributorId":146323,"corporation":false,"usgs":false,"family":"De Leo","given":"Giulio","email":"","middleInitial":"A.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":698433,"contributorType":{"id":1,"text":"Authors"},"rank":16}]}} ,{"id":70187693,"text":"sir20175050 - 2017 - Hydrologic characterization of Bushy Park Reservoir, South Carolina, 2013–15","interactions":[],"lastModifiedDate":"2017-06-14T15:42:31","indexId":"sir20175050","displayToPublicDate":"2017-06-14T12:15:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-5050","title":"Hydrologic characterization of Bushy Park Reservoir, South Carolina, 2013–15","docAbstract":"The Bushy Park Reservoir is a relatively shallow impoundment in a semi-tropical climate and is the principal water supply for the 400,000 people of the city of Charleston, South Carolina, and the surrounding areas including the Bushy Park Industrial Complex. Although there is an adequate supply of freshwater in the reservoir, taste-and-odor water-quality issues are a concern. The U.S. Geological Survey conducted an investigation in cooperation with the Charleston Water System to study the hydrology and hydrodynamics of the Bushy Park Reservoir to identify factors affecting water-quality conditions. Specifically, five areas for monitoring and (or) analysis were addressed: (1) hydrologic monitoring of the reservoir to establish a water budget, (2) flow monitoring in the tunnels to compute flow from Bushy Park Reservoir and at critical distribution junctions, (3) water-quality sampling, profiling, and continuous monitoring to identify the causes of taste-and-odor occurrence, (4) technical evaluation of appropriate hydrodynamic and water-quality simulation models for the reservoir, and (5) preliminary evaluation of alternative reservoir operations scenarios.
This report describes the hydrodynamic and hydrologic data collected from 2013 to 2015 to support the application and calibration of a three-dimensional hydrodynamic model and the water-quality monitoring and analysis to gain insight into the principal causes of the Bushy Park Reservoir taste-and-odor episodes. The existing U.S. Geological Survey real-time network on the West Branch of the Cooper River was augmented with a tidal flow gage on Durham Canal Back River, and Foster Creek. The Charleston Water System intake structure was instrumented to collect water-level, water temperature (top and bottom probes), specific conductance (top and bottom probes), wind speed and direction, and photosynthetically active radiation data. In addition to the gages attached to fixed structures, four bottom-mounted velocity profilers were deployed at six locations over different periods. The deployment period for the velocity profiler ranged from 2 weeks to 4 months. During the investigation, tidal cycle (13-hour) streamflow measurements were made at 30-minute intervals at five locations.
The Williams Station is a coal-fired powerplant that withdraws water from Bushy Park Reservoir for cooling purposes. The magnitude of the withdrawal (approximately 550 million gallons per day) is the major factor controlling the circulation in the reservoir. The net flow in Durham Canal to the reservoir is comparable to the withdrawal rates of the powerplant. When the Williams Station is not withdrawing water, the net flow in Durham Canal quickly goes to zero or reverses with a net flow away from the reservoir and to the Cooper River. Plan views of the velocity vectors for the tidal cycle streamflow measurements and rose diagram of the velocity profilers created with the Williams Station withdrawing and not withdrawing water show substantial effects of the distribution of magnitude and direction of the water velocities.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175050","collaboration":"Prepared in cooperation with Charleston Water System","usgsCitation":"Conrads, P.A., Petkewich, M.D., Falls, W.F., and Lanier, T.H., 2017, Hydrologic characterization of Bushy Park Reservoir, South Carolina, 2013–15: U.S. Geological Survey Scientific Investigations Report 2017–5050, 83 p., https://doi.org/10.3133/sir20175050.","productDescription":"Report: ix, 83 p.; Data Release","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-077941","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":342449,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7GB2274","text":"USGS data release","description":"USGS data release","linkHelpText":"Hydrodynamic data of Bushy Park Reservoir, South Carolina 2013–15"},{"id":342447,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5050/coverthb.jpg"},{"id":342448,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5050/sir20175050.pdf","text":"Report","size":"10.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5050"}],"country":"United States","state":"South Carolina","otherGeospatial":"Santee-Cooper River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.5,\n 32.68\n ],\n [\n -79.7,\n 32.68\n ],\n [\n -79.7,\n 33.56\n ],\n [\n -80.5,\n 33.56\n ],\n [\n -80.5,\n 32.68\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, South Atlantic Water Science Center
U.S. Geological Survey
720 Gracern Road
Stephenson Center, Suite 129
Columbia, SC 29210
Stratigraphic analysis, coupled with geochronologic techniques, indicates that a rich history of large Tennessee River floods is preserved in the Tennessee River Gorge area. Deposits of flood sediment from the 1867 peak discharge of record (460,000 cubic feet per second at Chattanooga, Tennessee) are preserved at many locations throughout the study area at sites with flood-sediment accumulation. Small exposures at two boulder overhangs reveal evidence of three to four other floods similar in size, or larger, than the 1867 flood in the last 3,000 years—one possibly as much or more than 50 percent larger. Records of floods also are preserved in stratigraphic sections at the mouth of the gorge at Williams Island and near Eaves Ferry, about 70 river miles upstream of the gorge. These stratigraphic records may extend as far back as about 9,000 years ago, giving a long history of Tennessee River floods. Although more evidence is needed to confirm these findings, a more in-depth comprehensive paleoflood study is feasible for the Tennessee River.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175052","collaboration":"Prepared in cooperation with the Nuclear Regulatory Commission","usgsCitation":"Harden, T.M., and O’Connor, J.E., 2017, Prehistoric floods on the Tennessee River—Assessing the use of stratigraphic records of past floods for improved flood-frequency analysis: U.S. Geological Survey Scientific Investigations Report 2017–5052, 15 p., https://doi.org/10.3133/sir20175052.","productDescription":"iv, 15 p.","numberOfPages":"24","onlineOnly":"Y","ipdsId":"IP-081426","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":342450,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5052/coverthb.jpg"},{"id":342451,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5052/sir20175052.pdf","text":"Report","size":"3.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5052"}],"country":"United States","state":"Tennessee","otherGeospatial":"Tennessee River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -85.68649291992186,\n 35.10024874332443\n ],\n [\n -85.6940460205078,\n 34.98837848142154\n ],\n [\n -85.26145935058594,\n 34.99231621532155\n ],\n [\n -85.25871276855467,\n 35.12271673061634\n ],\n [\n -85.2593994140625,\n 35.18952235197259\n ],\n [\n -85.67344665527342,\n 35.184471743812225\n ],\n [\n -85.68649291992186,\n 35.185594128309006\n ],\n [\n -85.68649291992186,\n 35.10024874332443\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201
Molluscs possess a number of attributes that make them an excellent source of past environmental conditions in estuaries: they are common in estuarine environments; they typically have hard shells and are usually well preserved in sediments; they are relatively easy to detect in the environment; they have limited mobility as adults; they grow by incremental addition of layers to their shells; and they are found in all the major environments surrounding estuaries—terrestrial, freshwater, brackish, and marine waters. Analysis of molluscan assemblages can contribute information about past changes in sea level, climate, land use patterns, anthropogenic alterations, salinity, and other parameters of the benthic habitat and water chemistry within the estuary. High-resolution (from less than a day to annual) records of changes in environmental parameters can be obtained by analyzing the incremental growth layers in mollusc shells (sclerochronology). The shell layers retain information on changes in water temperature, salinity, seasonality, climate, river discharge, productivity, pollution and human activity. Isotopic analyses of mollusc shell growth layers can be problematic in estuaries where water temperatures and isotopic ratios can vary simultaneously; however, methods are being developed to overcome these problems. In addition to sclerochronology, molluscs are important to Holocene and Pleistocene estuarine palaeoenvironmental studies because of their use in the development of age models through radiocarbon dating, amino acid racemization, uranium-thorium series dating, and electron spin resonance (ESR) dating.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Applications of Paleoenvironmental Techniques in Estuarine Studies","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","publisherLocation":"Dordrecht","doi":"10.1007/978-94-024-0990-1_15","usgsCitation":"Wingard, G.L., and Surge, D., 2017, Application of molluscan analyses to the reconstruction of past environmental conditions in estuaries, chap. 15 of Applications of Paleoenvironmental Techniques in Estuarine Studies, v. 20, p. 357-387, https://doi.org/10.1007/978-94-024-0990-1_15.","productDescription":"31 p.","startPage":"357","endPage":"387","ipdsId":"IP-056056","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":342502,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"20","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-02-15","publicationStatus":"PW","scienceBaseUri":"59424b36e4b0764e6c65dc10","contributors":{"authors":[{"text":"Wingard, G. Lynn 0000-0002-3833-5207 lwingard@usgs.gov","orcid":"https://orcid.org/0000-0002-3833-5207","contributorId":605,"corporation":false,"usgs":true,"family":"Wingard","given":"G.","email":"lwingard@usgs.gov","middleInitial":"Lynn","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":698056,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Surge, Donna","contributorId":192887,"corporation":false,"usgs":false,"family":"Surge","given":"Donna","email":"","affiliations":[],"preferred":false,"id":698208,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70188151,"text":"ofr20171067 - 2017 - A new seamless, high-resolution digital elevation model of the San Francisco Bay-Delta Estuary, California","interactions":[],"lastModifiedDate":"2017-06-22T16:14:38","indexId":"ofr20171067","displayToPublicDate":"2017-06-14T00:00:00","publicationYear":"2017","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":"2017-1067","title":"A new seamless, high-resolution digital elevation model of the San Francisco Bay-Delta Estuary, California","docAbstract":"Climate change, sea-level rise, and human development have contributed to the changing geomorphology of the San Francisco Bay - Delta (Bay-Delta) Estuary system. The need to predict scenarios of change led to the development of a new seamless, high-resolution digital elevation model (DEM) of the Bay – Delta that can be used by modelers attempting to understand potential future changes to the estuary system. This report details the three phases of the creation of this DEM. The first phase took a bathymetric-only DEM created in 2005 by the U.S. Geological Survey (USGS), refined it with additional data, and identified areas that would benefit from new surveys. The second phase began a USGS collaboration with the California Department of Water Resources (DWR) that updated a 2012 DWR seamless bathymetric/topographic DEM of the Bay-Delta with input from the USGS and modifications to fit the specific needs of USGS modelers. The third phase took the work from phase 2 and expanded the coverage area in the north to include the Yolo Bypass up to the Fremont Weir, the Sacramento River up to Knights Landing, and the American River up to the Nimbus Dam, and added back in the elevations for interior islands. The constant evolution of the Bay-Delta will require continuous updates to the DEM of the Delta, and there still are areas with older data that would benefit from modern surveys. As a result, DWR plans to continue updating the DEM.
Pacific Coastal and Marine Science Center
U.S. Geological Survey
2885 Mission St.
Santa Cruz, CA 95060
Cambarus cryptodytes (Dougherty Plain Cave Crayfish) is an obligate inhabitant of groundwater habitats (i.e., a stygobiont) with troglomorphic adaptations in the Floridan aquifer system of southwestern Georgia and adjacent Florida panhandle, particularly in the Dougherty Plain and Marianna Lowlands. Documented occurrences of Dougherty Plain Cave Crayfish are spatially distributed as 2 primary clusters separated by a region where few caves and springs have been documented; however, the paucity of humanly accessible karst features in this intermediate region has inhibited investigation of the species' distribution. To work around this constraint, we employed bottle traps to sample for Dougherty Plain Cave Crayfish and other groundwater fauna in 18 groundwater-monitoring wells that access the Floridan aquifer system in 10 counties in southwestern Georgia. We captured 32 Dougherty Plain Cave Crayfish in 9 wells in 8 counties between September 2014 and August 2015. We detected crayfish at depths ranging from 17.9 m to 40.6 m, and established new county records for Early, Miller, Mitchell, and Seminole counties in Georgia, increasing the number of occurrences in Georgia from 8 to 17 sites. In addition, a new US Geological Survey (USGS) Hydrologic Unit Code 8 (HUC8) watershed record was established for the Spring Creek watershed. These new records fill in the distribution gap between the 2 previously known clusters in Georgia and Jackson County, FL. Furthermore, this study demonstrates that deployment of bottle traps in groundwater-monitoring wells can be an effective approach to presence—absence surveys of stygobionts, especially in areas where surface access to groundwater is limited.
","language":"English","publisher":"Eagle Hill Institute","doi":"10.1656/058.016.0205","usgsCitation":"Fenolio, D.B., Niemiller, M.L., Gluesenkamp, A.G., McKee, A.M., and Taylor, S.J., 2017, New distributional records of the stygobitic crayfish Cambarus cryptodytes (Decapoda: Cambaridae) in the Floridan Aquifer System of southwestern Georgia: Southeastern Naturalist, v. 16, no. 2, p. 163-181, https://doi.org/10.1656/058.016.0205.","productDescription":"19 p.","startPage":"163","endPage":"181","ipdsId":"IP-073657","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":344852,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Geogia","otherGeospatial":"Florida Aquifer System","volume":"16","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-06-08","publicationStatus":"PW","scienceBaseUri":"59b76ef0e4b08b1644ddfadc","contributors":{"authors":[{"text":"Fenolio, Dante B.","contributorId":167680,"corporation":false,"usgs":false,"family":"Fenolio","given":"Dante","email":"","middleInitial":"B.","affiliations":[{"id":24805,"text":"Department of Conservation and Research, San Antonio Zoo","active":true,"usgs":false}],"preferred":false,"id":707742,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Niemiller, Matthew L.","contributorId":167679,"corporation":false,"usgs":false,"family":"Niemiller","given":"Matthew","email":"","middleInitial":"L.","affiliations":[{"id":24804,"text":"Illinois Natural History Survey, Prairie Research Institute, University of Illinois Urbana-Champaign","active":true,"usgs":false}],"preferred":false,"id":707743,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gluesenkamp, Andrew G.","contributorId":195638,"corporation":false,"usgs":false,"family":"Gluesenkamp","given":"Andrew","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":707744,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McKee, Anna M. 0000-0003-2790-5320 amckee@usgs.gov","orcid":"https://orcid.org/0000-0003-2790-5320","contributorId":166725,"corporation":false,"usgs":true,"family":"McKee","given":"Anna","email":"amckee@usgs.gov","middleInitial":"M.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":707741,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Taylor, Steven J.","contributorId":167682,"corporation":false,"usgs":false,"family":"Taylor","given":"Steven","email":"","middleInitial":"J.","affiliations":[{"id":24804,"text":"Illinois Natural History Survey, Prairie Research Institute, University of Illinois Urbana-Champaign","active":true,"usgs":false}],"preferred":false,"id":707745,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70181758,"text":"ofr20171018 - 2017 - Five hydrologic and landscape databases for selected National Wildlife Refuges in the Southeastern United States","interactions":[],"lastModifiedDate":"2017-06-12T10:19:48","indexId":"ofr20171018","displayToPublicDate":"2017-06-12T09:45:00","publicationYear":"2017","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":"2017-1018","title":"Five hydrologic and landscape databases for selected National Wildlife Refuges in the Southeastern United States","docAbstract":"This report serves as metadata and a user guide for five out of six hydrologic and landscape databases developed by the U.S. Geological Survey, in cooperation with the U.S. Fish and Wildlife Service, to describe data-collection, data-reduction, and data-analysis methods used to construct the databases and provides statistical and graphical descriptions of the databases. Six hydrologic and landscape databases were developed: (1) the Cache River and White River National Wildlife Refuges (NWRs) and contributing watersheds in Arkansas, Missouri, and Oklahoma, (2) the Cahaba River NWR and contributing watersheds in Alabama, (3) the Caloosahatchee and J.N. “Ding” Darling NWRs and contributing watersheds in Florida, (4) the Clarks River NWR and contributing watersheds in Kentucky, Tennessee, and Mississippi, (5) the Lower Suwannee NWR and contributing watersheds in Georgia and Florida, and (6) the Okefenokee NWR and contributing watersheds in Georgia and Florida. Each database is composed of a set of ASCII files, Microsoft Access files, and Microsoft Excel files. The databases were developed as an assessment and evaluation tool for use in examining NWR-specific hydrologic patterns and trends as related to water availability and water quality for NWR ecosystems, habitats, and target species. The databases include hydrologic time-series data, summary statistics on landscape and hydrologic time-series data, and hydroecological metrics that can be used to assess NWR hydrologic conditions and the availability of aquatic and riparian habitat. Landscape data that describe the NWR physiographic setting and the locations of hydrologic data-collection stations were compiled and mapped. Categories of landscape data include land cover, soil hydrologic characteristics, physiographic features, geographic and hydrographic boundaries, hydrographic features, and regional runoff estimates. The geographic extent of each database covers an area within which human activities, climatic variation, and hydrologic processes can potentially affect the hydrologic regime of the NWRs and adjacent areas.
The hydrologic and landscape database for the Cache and White River NWRs and contributing watersheds in Arkansas, Missouri, and Oklahoma has been described and documented in detail (Buell and others, 2012). This report serves as a companion to the Buell and others (2012) report to describe and document the five subsequent hydrologic and landscape databases that were developed: Chapter A—the Cahaba River NWR and contributing watersheds in Alabama, Chapter B—the Caloosahatchee and J.N. “Ding” Darling NWRs and contributing watersheds in Florida, Chapter C—the Clarks River NWR and contributing watersheds in Kentucky, Tennessee, and Mississippi, Chapter D—the Lower Suwannee NWR and contributing watersheds in Georgia and Florida, and Chapter E—the Okefenokee NWR and contributing watersheds in Georgia and Florida.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171018","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Buell, G.R., Gurley, L.N., Calhoun, D.L., and Hunt, A.M., 2017, Five hydrologic and landscape databases for selected National Wildlife Refuges in Southeastern United States: U.S. Geological Survey Open-File Report 2017–1018, 366 p., https://doi.org/10.3133/ofr20171018.","productDescription":"Report: xvi, 386 p. 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\"}}]}","contact":"Director, South Atlantic Water Science Center
U.S. Geological Survey
720 Gracern Road
Stephenson Center, Suite 129
Columbia, SC 29210
Combining the synoptic mass balance approach with principal components analysis (PCA) can be an effective method for discretising the chemistry of inflows and source areas in watersheds where contamination is diffuse in nature and/or complicated by groundwater interactions. This paper presents a field-scale study in which synoptic sampling and PCA are employed in a mineralized watershed (Lion Creek, Colorado, USA) under low flow conditions to (i) quantify the impacts of mining activity on stream water quality; (ii) quantify the spatial pattern of constituent loading; and (iii) identify inflow sources most responsible for observed changes in stream chemistry and constituent loading. Several of the constituents investigated (Al, Cd, Cu, Fe, Mn, Zn) fail to meet chronic aquatic life standards along most of the study reach. The spatial pattern of constituent loading suggests four primary sources of contamination under low flow conditions. Three of these sources are associated with acidic (pH <3.1) seeps that enter along the left bank of Lion Creek. Investigation of inflow water (trace metal and major ion) chemistry using PCA suggests a hydraulic connection between many of the left bank inflows and mine water in the Minnesota Mine shaft located to the north-east of the river channel. In addition, water chemistry data during a rainfall-runoff event suggests the spatial pattern of constituent loading may be modified during rainfall due to dissolution of efflorescent salts or erosion of streamside tailings. These data point to the complexity of contaminant mobilisation processes and constituent loading in mining-affected watersheds but the combined synoptic sampling and PCA approach enables a conceptual model of contaminant dynamics to be developed to inform remediation.
","language":"English","publisher":"Springer","doi":"10.1007/s11356-017-9038-x","usgsCitation":"Byrne, P., Runkel, R.L., and Walton-Day, K., 2017, Synoptic sampling and principal components analysis to identify sources of water and metals to an acid mine drainage stream: Environmental Science and Pollution Research, v. 24, no. 20, p. 17220-17240, https://doi.org/10.1007/s11356-017-9038-x.","productDescription":"21 p.","startPage":"17220","endPage":"17240","ipdsId":"IP-080091","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":469759,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s11356-017-9038-x","text":"Publisher Index Page"},{"id":342403,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"24","issue":"20","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-06-06","publicationStatus":"PW","scienceBaseUri":"593fa830e4b0764e6c627943","contributors":{"authors":[{"text":"Byrne, Patrick","contributorId":192845,"corporation":false,"usgs":false,"family":"Byrne","given":"Patrick","affiliations":[],"preferred":false,"id":697867,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Runkel, Robert L. 0000-0003-3220-481X runkel@usgs.gov","orcid":"https://orcid.org/0000-0003-3220-481X","contributorId":685,"corporation":false,"usgs":true,"family":"Runkel","given":"Robert","email":"runkel@usgs.gov","middleInitial":"L.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":697866,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Walton-Day, Katherine 0000-0002-9146-6193 kwaltond@usgs.gov","orcid":"https://orcid.org/0000-0002-9146-6193","contributorId":184043,"corporation":false,"usgs":true,"family":"Walton-Day","given":"Katherine","email":"kwaltond@usgs.gov","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":697868,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70188459,"text":"70188459 - 2017 - Migration trends of Sockeye Salmon at the northern edge of their distribution","interactions":[],"lastModifiedDate":"2017-06-12T13:18:09","indexId":"70188459","displayToPublicDate":"2017-06-12T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Migration trends of Sockeye Salmon at the northern edge of their distribution","docAbstract":"Climate change is affecting arctic and subarctic ecosystems, and anadromous fish such as Pacific salmon Oncorhynchus spp. are particularly susceptible due to the physiological challenge of spawning migrations. Predicting how migratory timing will change under Arctic warming scenarios requires an understanding of how environmental factors drive salmon migrations. Multiple mechanisms exist by which environmental conditions may influence migrating salmon, including altered migration cues from the ocean and natal river. We explored relationships between interannual variability and annual migration timing (2003–2014) of Sockeye Salmon O. nerka in a subarctic watershed with environmental conditions at broad, intermediate, and local spatial scales. Low numbers of Sockeye Salmon have returned to this high-latitude watershed in recent years, and run size has been a dominant influence on the migration duration and the midpoint date of the run. The duration of the migration upriver varied by as much as 25 d across years, and shorter run durations were associated with smaller run sizes. The duration of the migration was also extended with warmer sea surface temperatures in the staging area and lower values of the North Pacific Index. The midpoint date of the total run was earlier when the run size was larger, whereas the midpoint date was delayed during years in which river temperatures warmed earlier in the season. Documenting factors related to the migration of Sockeye Salmon near the northern limit of their range provides insights into the determinants of salmon migrations and suggests processes that could be important for determining future changes in arctic and subarctic ecosystems.
","language":"English","publisher":"American Fisheries Society","doi":"10.1080/00028487.2017.1302992","usgsCitation":"Carey, M.P., Zimmerman, C.E., Keith, K.D., Schelske, M., Lean, C., and Douglas, D.C., 2017, Migration trends of Sockeye Salmon at the northern edge of their distribution: Transactions of the American Fisheries Society, v. 146, no. 4, p. 791-802, https://doi.org/10.1080/00028487.2017.1302992.","productDescription":"12 p.","startPage":"791","endPage":"802","ipdsId":"IP-080815","costCenters":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"links":[{"id":438300,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F71834PF","text":"USGS data release","linkHelpText":"Count of Sockeye Salmon (Oncorhynchus nerka), River Temperature, and River Height in the Pilgrim River, Nome, Alaska, 2003-2014"},{"id":342405,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -175.95703125,\n 48.04870994288686\n ],\n [\n -122.78320312499999,\n 48.04870994288686\n ],\n [\n -122.78320312499999,\n 65.44000165965534\n ],\n [\n -175.95703125,\n 65.44000165965534\n ],\n [\n -175.95703125,\n 48.04870994288686\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"146","issue":"4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-06-08","publicationStatus":"PW","scienceBaseUri":"593fa82fe4b0764e6c62793c","contributors":{"authors":[{"text":"Carey, Michael P. 0000-0002-3327-8995 mcarey@usgs.gov","orcid":"https://orcid.org/0000-0002-3327-8995","contributorId":5397,"corporation":false,"usgs":true,"family":"Carey","given":"Michael","email":"mcarey@usgs.gov","middleInitial":"P.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":true,"id":697870,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zimmerman, Christian E. 0000-0002-3646-0688 czimmerman@usgs.gov","orcid":"https://orcid.org/0000-0002-3646-0688","contributorId":410,"corporation":false,"usgs":true,"family":"Zimmerman","given":"Christian","email":"czimmerman@usgs.gov","middleInitial":"E.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":true,"id":697869,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Keith, Kevin D.","contributorId":192846,"corporation":false,"usgs":false,"family":"Keith","given":"Kevin","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":697871,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schelske, Merlyn","contributorId":192847,"corporation":false,"usgs":false,"family":"Schelske","given":"Merlyn","email":"","affiliations":[],"preferred":false,"id":697872,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lean, Charles","contributorId":189274,"corporation":false,"usgs":false,"family":"Lean","given":"Charles","email":"","affiliations":[],"preferred":false,"id":697873,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Douglas, David C. 0000-0003-0186-1104 ddouglas@usgs.gov","orcid":"https://orcid.org/0000-0003-0186-1104","contributorId":2388,"corporation":false,"usgs":true,"family":"Douglas","given":"David","email":"ddouglas@usgs.gov","middleInitial":"C.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":697874,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70187444,"text":"sir20175032 - 2017 - Groundwater quality in the Western San Joaquin Valley study unit, 2010: California GAMA Priority Basin Project","interactions":[],"lastModifiedDate":"2019-12-30T14:45:28","indexId":"sir20175032","displayToPublicDate":"2017-06-09T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-5032","title":"Groundwater quality in the Western San Joaquin Valley study unit, 2010: California GAMA Priority Basin Project","docAbstract":"Water quality in groundwater resources used for public drinking-water supply in the Western San Joaquin Valley (WSJV) was investigated by the USGS in cooperation with the California State Water Resources Control Board (SWRCB) as part of its Groundwater Ambient Monitoring and Assessment (GAMA) Program Priority Basin Project. The WSJV includes two study areas: the Delta–Mendota and Westside subbasins of the San Joaquin Valley groundwater basin. Study objectives for the WSJV study unit included two assessment types: (1) a status assessment yielding quantitative estimates of the current (2010) status of groundwater quality in the groundwater resources used for public drinking water, and (2) an evaluation of natural and anthropogenic factors that could be affecting the groundwater quality. The assessments characterized the quality of untreated groundwater, not the quality of treated drinking water delivered to consumers by water distributors.
The status assessment was based on data collected from 43 wells sampled by the U.S. Geological Survey for the GAMA Priority Basin Project (USGS-GAMA) in 2010 and data compiled in the SWRCB Division of Drinking Water (SWRCB-DDW) database for 74 additional public-supply wells sampled for regulatory compliance purposes between 2007 and 2010. To provide context, concentrations of constituents measured in groundwater were compared to U.S. Environmental Protection Agency (EPA) and SWRCB-DDW regulatory and non-regulatory benchmarks for drinking-water quality. The status assessment used a spatially weighted, grid-based method to estimate the proportion of the groundwater resources used for public drinking water that has concentrations for particular constituents or class of constituents approaching or above benchmark concentrations. This method provides statistically unbiased results at the study-area scale within the WSJV study unit, and permits comparison of the two study areas to other areas assessed by the GAMA Priority Basin Project statewide.
Groundwater resources used for public drinking water in the WSJV study unit are among the most saline and most affected by high concentrations of inorganic constituents of all groundwater resources used for public drinking water that have been assessed by the GAMA Priority Basin Project statewide. Among the 82 GAMA Priority Basin Project study areas statewide, the Delta–Mendota study area ranked above the 90th percentile for aquifer-scale proportions of groundwater resources having concentrations of total dissolved solids (TDS), sulfate, chloride, manganese, boron, chromium(VI), selenium, and strontium above benchmarks, and the Westside study area ranked above the 90th percentile for TDS, sulfate, manganese, and boron.
In the WSJV study unit as a whole, one or more inorganic constituents with regulatory or non-regulatory, health-based benchmarks were present at concentrations above benchmarks in about 53 percent of the groundwater resources used for public drinking water, and one or more organic constituents with regulatory health-based benchmarks were detected at concentrations above benchmarks in about 3 percent of the resource. Individual constituents present at concentrations greater than health-based benchmarks in greater than 2 percent of groundwater resources used for public drinking water included: boron (51 percent, SWRCB-DDW notification level), chromium(VI) (25 percent, SWRCB-DDW maximum contaminant level (MCL)), arsenic (10 percent, EPA MCL), strontium (5.1 percent, EPA Lifetime health advisory level (HAL)), nitrate (3.9 percent, EPA MCL), molybdenum (3.8 percent, EPA HAL), selenium (2.6 percent, EPA MCL), and benzene (2.6 percent, SWRCB-DDW MCL). In addition, 50 percent of the resource had TDS concentrations greater than non-regulatory, aesthetic-based SWRCB-DDW upper secondary maximum contaminant level (SMCL), and 44 percent had manganese concentrations greater than the SWRCB-DDW SMCL.
Natural and anthropogenic factors that could affect the groundwater quality were evaluated by using results from statistical testing of associations between constituent concentrations and values of potential explanatory factors, inferences from geochemical and age-dating tracer results, and by considering the water-quality results in the context of the hydrogeologic setting of the WSJV study unit.
Natural factors, particularly the lithologies of the source areas for groundwater recharge and of the aquifers, were the dominant factors affecting groundwater quality in most of the WSJV study unit. However, where groundwater resources used for public supply included groundwater recharged in the modern era, mobilization of constituents by recharge of water used for irrigation also affected groundwater quality. Public-supply wells in the Westside study area had a median depth of 305 m and primarily tapped groundwater recharged hundreds to thousands of years ago, whereas public-supply wells in the Delta–Mendota study area had a median depth of 85 m and primarily tapped either groundwater recharged within the last 60 years or groundwater consisting of mixtures of this modern recharge and older recharge.
Public-supply wells in the WSJV study unit are screened in the Tulare Formation and zones above and below the Corcoran Clay Member are used. The Tulare Formation primarily consists of alluvial sediments derived from the Coast Ranges to the west, except along the valley trough at the eastern margin of the WSJV study unit where the Tulare Formation consists of fluvial sands derived from the Sierra Nevada to the east. Groundwater from wells screened in the Sierra Nevada sands had manganese-reducing or manganese- and iron-reducing oxidation-reduction (redox) conditions. These redox conditions commonly were associated with elevated arsenic or molybdenum concentrations, and the dominance of arsenic(III) in the dissolved arsenic supports reductive dissolution of iron and manganese oxyhydroxides as the mechanism. In addition, groundwater from many wells screened in Sierra Nevada sands contained low concentrations of nitrite or ammonium, indicating reduction of nitrate by denitrification or dissimilatory processes, respectively.
Geology of the Coast Ranges westward of the study unit strongly affects groundwater quality in the WSJV. Elevated concentrations of TDS, sulfate, boron, selenium and strontium in groundwater were primarily associated with aquifer sediments and recharge derived from areas of the Coast Ranges dominated by Cretaceous-to-Miocene age, organic-rich, reduced marine shales, known as the source of selenium in WSJV soils, surface water, and groundwater. Low sulfur-isotopic values (δ34S) of dissolved sulfate indicate that the sulfate was largely derived from oxidation of biogenic pyrite from the shales, and correlations with trace element concentrations, geologic setting, and groundwater geochemical modeling indicated that distributions of sulfate, strontium, and selenium in groundwater were controlled by dissolution of secondary sulfate minerals in soils and sediments.
Elevated concentrations of chromium(VI) were primarily associated with aquifer sediments and recharge derived from areas of the Coast Ranges dominated by the Franciscan Complex and ultramafic rocks. The Franciscan Complex also has boron-rich, sodium-chloride dominated hydrothermal fluids that contribute to elevated concentrations of boron and TDS.
Groundwater from wells screened in Coast Ranges alluvium was primarily oxic and relatively alkaline (median pH value of 7.55) in the Delta–Mendota study area, and primarily nitrate-reducing or suboxic and alkaline (median pH value of 8.4) in the Westside study area. Many groundwater samples from those wells have elevated concentrations of arsenic(V), molybdenum, selenium, or chromium(VI), consistent with desorption of metal oxyanions from mineral surfaces under those geochemical conditions.
High concentrations of benzene were associated with deep wells located in the vicinity of petroleum deposits at the southern end of the Westside study area. Groundwater from these wells had premodern age and anoxic geochemical conditions, and the ratios among concentrations of hydrocarbon constituents were different from ratios found in fuels and combustion products, which is consistent with a geogenic source for the benzene rather than contamination from anthropogenic sources.
Water stable-isotope compositions, groundwater recharge temperatures, and groundwater ages were used to infer four types of groundwater: (1) groundwater derived from natural recharge of water from major rivers draining the Sierra Nevada; (2) groundwater primarily derived from natural recharge of water from Coast Ranges runoff; (3) groundwater derived from recharge of pumped groundwater applied to the land surface for irrigation; and (4) groundwater derived from recharge during a period of much cooler paleoclimate. Water previously used for irrigation was found both above and below the Corcoran Clay, supporting earlier inferences that this clay member is no longer a robust confining unit.
Recharge of water used for irrigation has direct and indirect effects on groundwater quality. Elevated nitrate concentrations and detections of herbicides and fumigants in the Delta–Mendota study area generally were associated with greater agricultural land use near the well and with water recharged during the last 60 years. However, the extent of the groundwater resource affected by agricultural sources of nitrate was limited by groundwater redox conditions sufficient to reduce nitrate. The detection frequency of perchlorate in Delta–Mendota groundwater was greater than expected for natural conditions. Perchlorate, nitrate, selenium, and strontium concentrations were correlated with one another and were greater in groundwater inferred to be recharge of previously pumped groundwater used for irrigation. The source of the perchlorate, selenium, and strontium appears to be salts deposited in the soils and sediments of the arid WSJV that are dissolved and flushed into groundwater by the increased amount of recharge caused by irrigation. In the Delta–Mendota study area, the groundwater with elevated concentrations of selenium was found deeper in the aquifer system than it was reported by a previous study 25 years earlier, suggesting that this transient front of groundwater with elevated concentrations of constituents derived from dissolution of soil salts by irrigation recharge is moving down through the aquifer system and is now reaching the depth zone used for public drinking water supply.
California Water Science Center
California GAMA
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
The use of freshwater diversions (river reintroductions) from the Mississippi River as a restoration tool to rehabilitate Louisiana coastal wetlands has been promoted widely since the first such diversion at Caernarvon became operational in the early 1990s. To date, aside from the Bonnet Carré Spillway (which is designed and operated for flood control), there are only four operational Mississippi River freshwater diversions (two gated structures and two siphons) in coastal Louisiana, and they all target salinity intrusion, shellfish management, and (or) the enhancement of the integrity of marsh habitat. River reintroductions carry small sediment loads for various design reasons, but they can be effective in delivering freshwater to combat saltwater intrusion and increase the delivery of nutrients and suspended fine-grained sediments to receiving wetlands. River reintroductions may be an ideal restoration tool for targeting coastal swamp forest habitat; much of the area of swamp forest habitat in coastal Louisiana is undergoing saltwater intrusion, high rates of submergence, and lack of riverine flow leading to reduced concentrations of important nutrients and suspended sediments, which sustain growth and regeneration, help to aerate swamp soils, and remove toxic compounds from the rhizosphere.
The State of Louisiana Coastal Protection and Restoration Authority (CPRA) has made it a priority to establish a small freshwater river diversion into a coastal swamp forest located between Baton Rouge and New Orleans, Louisiana, to reintroduce Mississippi River water to Maurepas Swamp. While a full understanding of how a coastal swamp forest will respond to new freshwater loading through a Mississippi River reintroduction is unknown, this report provides guidance based on the available literature for establishing performance measures that can be used for evaluating the effectiveness of a Mississippi River reintroduction into the forested wetlands of Maurepas Swamp (project PO-29 of the Coastal Wetlands Planning, Protection and Restoration Act) and aid in adaptive management of the project. PO-29 is a small river reintroduction in scope, and through its operation, it will provide information about the feasibility and reasonable expectations for future river reintroduction projects targeting coastal swamp forests in Louisiana.
Located near Garyville, Louisiana, the Mississippi River reintroduction into Maurepas Swamp project is being designed to deliver a maximum flow of 57 cubic meters per second (m3/s) (or about 2,000 cubic feet per second [ft3/s]) directly from the river, but with a maximum flow through the outflow channel of 42 m3/s (or 1,500 ft3/s) available for at least half of the year. The river reintroduction will divert Mississippi River water through channelized flow and surface water to impact approximately 16,583 hectares (ha) of wetland habitat, much of which is swamp forest and swamp forest transitioning into marsh habitat. The Mississippi River reintroduction into Maurepas Swamp and associated outfall management features collectively should facilitate connectivity of water between the Mississippi River and the entire project area.
At any given location, hydrologic connectivity should occur at intervals between twice yearly and once per decade, and hydrologic management must allow the potential for water drawdowns to foster tree regeneration every 3–13 years. The river reintroduction is also anticipated to maintain salinity in swamp forests dominated by Taxodium distichum (baldcypress) to less than 1.3 practical salinity units (psu) and maintain salinity in mixed baldcypress and Nyssa aquatica (water tupelo) swamp forests to less than 0.8 psu. The river reintroduction should promote soil surface elevation gains of 8–9 millimeters per year (mm/yr) (range, 4.9–12.1 mm/yr) to offset relative sea-level rise and keep total river water nitrate (NO3-) loading into Maurepas Swamp to about 11.25 grams (g) of nitrogen (N) per square meter per year (m-2 yr-1 ) (range, 7.1–15.4 g N m-2 yr-1) to promote near complete uptake of NO3- by the vegetation in the receiving wetlands and reduce impacts to water quality in adjacent and connected water ways (for example, Blind River) and Lake Maurepas. With these performance measures maintained over time, we further expect swamp forest stands to realize improvements in stand density index of as much as 30–45 percent of maximum values for the stand type while maintaining an overstory leaf area index of 2.0–2.9 square meters per square meter or higher as swamp forests recover from decades of low flow, saltwater intrusion, reduced nutrients, and surface elevation deficits associated with isolation from the Mississippi River.
Associated with these performance measures are two major uncertainties: (1) an assumption that we can rely on existing data, literature, and modeling from coastal swamp forests to establish these performance measures and (2) an unknown time frame for evaluating these performance measures. Some performance measures can be assessed quickly, such as those associated with hydrology and nutrient uptake. Some performance measures, such as changes in soil surface elevation and forest structural integrity, could take longer to assess. Once performance measures are assessed across different time scales, however, adjustments to operations of the Mississippi River reintroduction into Maurepas Swamp can be swift. The proposed performance measures are ideal targets, mostly without specific consideration of practical, operational constraints. The measures are intended to be the basis by which adaptive management of the diversion structures can be evaluated. The measures are defined without regard to current conditions so that project success can be evaluated on net outcomes rather than specific change from existing conditions. We expect that the Mississippi River reintroduction into Maurepas Swamp will slow degradation and extend the life of the swamp for decades to centuries.
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U.S. Geological Survey
700 Cajundome Blvd.
Lafayette, LA 70506
Groundwater provides more than 40 percent of California’s drinking water. To protect this vital resource, the State of California created the Groundwater Ambient Monitoring and Assessment (GAMA) Program. The Priority Basin Project of the GAMA Program provides a comprehensive assessment of the State’s groundwater quality and increases public access to groundwater-quality information. The Western San Joaquin Valley is one of the study units being evaluated.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20173028","collaboration":"Prepared in cooperation with the California State Water Resources Control Board","usgsCitation":"Fram, M.S., 2017, Groundwater quality in the western San Joaquin Valley, California: U.S. Geological Survey Fact Sheet 2017–3028, 4 p., https://doi.org/10.3133/fs20173028.","productDescription":"4 p.","onlineOnly":"Y","ipdsId":"IP-041662","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":342308,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2017/3028/coverthb.jpg"},{"id":342309,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2017/3028/fs20173028.pdf","text":"Report","size":"2 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"California","otherGeospatial":"Western San Joaquin Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.9814453125,\n 37.61858263247881\n ],\n [\n -121.2176513671875,\n 37.48793540168987\n ],\n [\n -121.1077880859375,\n 37.36579146999664\n ],\n [\n -121.08032226562499,\n 37.21283151445594\n ],\n [\n -121.08581542968751,\n 37.07928445197303\n ],\n [\n -120.90866088867186,\n 36.98939086733937\n ],\n [\n -120.89492797851561,\n 36.94989178681327\n ],\n [\n -120.93612670898438,\n 36.910372213522535\n ],\n [\n -120.81527709960936,\n 36.90707799098376\n ],\n [\n -120.79639434814452,\n 36.87852210415612\n ],\n [\n -120.82969665527344,\n 36.873304009242545\n ],\n [\n -120.84754943847655,\n 36.865064186202645\n ],\n [\n -120.85166931152345,\n 36.8557246457806\n ],\n [\n -120.8396530151367,\n 36.837591691585295\n ],\n [\n -120.82523345947264,\n 36.832920385709144\n ],\n [\n -120.82660675048827,\n 36.85599935443738\n ],\n [\n -120.81184387207031,\n 36.86588820849843\n ],\n [\n -120.78678131103516,\n 36.86094394142341\n ],\n [\n -120.77579498291016,\n 36.84281222525469\n ],\n [\n -120.69717407226562,\n 36.66070786821854\n ],\n [\n -120.72189331054686,\n 36.61222072017988\n ],\n [\n -120.66009521484374,\n 36.55929085774001\n ],\n [\n -120.3936767578125,\n 36.328402729422656\n ],\n [\n -120.12451171875,\n 36.02244668175846\n ],\n [\n -119.96383666992189,\n 35.94799468798152\n ],\n [\n -119.6905517578125,\n 35.94243575255426\n ],\n [\n -119.5806884765625,\n 36.01356058518153\n ],\n [\n -119.60266113281249,\n 36.301845303684324\n ],\n [\n -119.783935546875,\n 36.42570252039198\n ],\n [\n -120.13549804687501,\n 36.54936246839778\n ],\n [\n -120.091552734375,\n 36.59347887826919\n ],\n [\n -120.11352539062499,\n 36.6640126988417\n ],\n [\n -120.30578613281251,\n 36.76969233214548\n ],\n [\n -120.39916992187499,\n 36.92135192790115\n ],\n [\n -120.45959472656249,\n 37.004746084814784\n ],\n [\n -120.53924560546874,\n 37.131855694734625\n ],\n [\n -120.63812255859375,\n 37.21283151445594\n ],\n [\n -120.84960937499999,\n 37.30682947124943\n ],\n [\n -120.91552734375,\n 37.33304051804567\n ],\n [\n -120.95947265624999,\n 37.413800350662896\n ],\n [\n -121.00616455078124,\n 37.51844023887861\n ],\n [\n -120.9814453125,\n 37.61858263247881\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"California Water Science Center
California GAMA
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Collection of water-quality samples that accurately characterize average particle concentrations and distributions in channels can be complicated by large sources of variability. The U.S. Geological Survey (USGS) developed a fully automated Depth-Integrated Sample Arm (DISA) as a way to reduce bias and improve accuracy in water-quality concentration data. The DISA was designed to integrate with existing autosampler configurations commonly used for the collection of water-quality samples in vertical profile thereby providing a better representation of average suspended sediment and sediment-associated pollutant concentrations and distributions than traditional fixed-point samplers. In controlled laboratory experiments, known concentrations of suspended sediment ranging from 596 to 1,189 mg/L were injected into a 3 foot diameter closed channel (circular pipe) with regulated flows ranging from 1.4 to 27.8 ft3 /s. Median suspended sediment concentrations in water-quality samples collected using the DISA were within 7 percent of the known, injected value compared to 96 percent for traditional fixed-point samplers. Field evaluation of this technology in open channel fluvial systems showed median differences between paired DISA and fixed-point samples to be within 3 percent. The range of particle size measured in the open channel was generally that of clay and silt. Differences between the concentration and distribution measured between the two sampler configurations could potentially be much larger in open channels that transport larger particles, such as sand.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the 5th Federal Interagency Hydrologic Modeling Conference and the 10th Federal Interagency Sedimentation Conference","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"Joint Federal Interagency Conference 2015","conferenceDate":"April 19-23, 2015","conferenceLocation":"Reno, NV","language":"English","publisher":"Department of Interior","publisherLocation":"Reston, VA","usgsCitation":"Selbig, W.R., 2017, Collecting a better water-quality sample: Reducing vertical stratification bias in open and closed channels, in Proceedings of the 5th Federal Interagency Hydrologic Modeling Conference and the 10th Federal Interagency Sedimentation Conference, Reno, NV, April 19-23, 2015, 11 p.","productDescription":"11 p.","ipdsId":"IP-060694","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":342312,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":342311,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://acwi.gov/sos/pubs/3rdJFIC/"}],"publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"593ad6e1e4b0764e6c602147","contributors":{"authors":[{"text":"Selbig, William R. 0000-0003-1403-8280 wrselbig@usgs.gov","orcid":"https://orcid.org/0000-0003-1403-8280","contributorId":877,"corporation":false,"usgs":true,"family":"Selbig","given":"William","email":"wrselbig@usgs.gov","middleInitial":"R.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":697626,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70188420,"text":"70188420 - 2017 - Marine ferromanganese encrustations: Archives of changing oceans","interactions":[],"lastModifiedDate":"2017-06-09T09:50:09","indexId":"70188420","displayToPublicDate":"2017-06-08T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1490,"text":"Elements","active":true,"publicationSubtype":{"id":10}},"title":"Marine ferromanganese encrustations: Archives of changing oceans","docAbstract":"Marine iron–manganese oxide coatings occur in many shallow and deep-water areas of the global ocean and can form in three ways: 1) Fe–Mn crusts can precipitate from seawater onto rocks on seamounts; 2) Fe–Mn nodules can form on the sediment surface around a nucleus by diagenetic processes in sediment pore water; 3) encrustations can precipitate from hydrothermal fluids. These oxide coatings have been growing for thousands to tens of millions of years. They represent a vast archive of how oceans have changed, including variations of climate, ocean currents, geological activity, erosion processes on land, and even anthropogenic impact. A growing toolbox of age-dating methods and element and isotopic signatures are being used to exploit these archives.
","language":"English","publisher":"Mineralogical Society of America","doi":"10.2113/gselements.13.3.177","usgsCitation":"Koschinsky, A., and Hein, J.R., 2017, Marine ferromanganese encrustations: Archives of changing oceans: Elements, v. 13, no. 3, p. 177-182, https://doi.org/10.2113/gselements.13.3.177.","productDescription":"6 p.","startPage":"177","endPage":"182","ipdsId":"IP-081254","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":342316,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-06-01","publicationStatus":"PW","scienceBaseUri":"593ad6e0e4b0764e6c602143","contributors":{"authors":[{"text":"Koschinsky, Andrea","contributorId":83813,"corporation":false,"usgs":true,"family":"Koschinsky","given":"Andrea","affiliations":[],"preferred":false,"id":697668,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hein, James R. 0000-0002-5321-899X jhein@usgs.gov","orcid":"https://orcid.org/0000-0002-5321-899X","contributorId":140835,"corporation":false,"usgs":true,"family":"Hein","given":"James","email":"jhein@usgs.gov","middleInitial":"R.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":697667,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70187489,"text":"sir20175041 - 2017 - Hydrogeologic framework and hydrologic conditions of the Piney Point aquifer in Virginia","interactions":[],"lastModifiedDate":"2017-06-07T14:28:18","indexId":"sir20175041","displayToPublicDate":"2017-06-07T14:15:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-5041","title":"Hydrogeologic framework and hydrologic conditions of the Piney Point aquifer in Virginia","docAbstract":"The Piney Point aquifer in Virginia is newly described and delineated as being composed of six geologic units, in a study conducted by the U.S. Geological Survey in cooperation with the Virginia Department of Environmental Quality (VA DEQ). The eastward-dipping geologic units include, in stratigraphically ascending order, the
Identification of geologic units is based on typical sediment lithologies of geologic formations. Fine-grained sediments that compose confining units positioned immediately above and below the Piney Point aquifer are also described.
The Piney Point aquifer is one of several confined aquifers within the Virginia Coastal Plain and includes a highly porous and solution-channeled indurated limestone within the Piney Point Formation from which withdrawals are made. The limestone is relatively continuous laterally across central parts of the Northern Neck, Middle Peninsula, and York-James Peninsula. Other geologic units are of variable extent. The configurations of most of the geologic units are further affected by newly identified faults that are aligned radially from the Chesapeake Bay impact crater and create constrictions or barriers to groundwater flow. Some geologic units are also truncated beneath the lower Rappahannock River by a resurge channel associated with the impact crater.
Groundwater withdrawals from the Piney Point aquifer increased from approximately 1 million gallons per day (Mgal/d) during 1900 to 7.35 Mgal/d during 2004. As a result, a water-level cone of depression in James City and northern York Counties was estimated to be as low as 70 feet (ft) below the National Geodetic Vertical Datum of 1929 (NGVD 29) by 2005. Withdrawals decreased to 5.01 Mgal/d by 2009 as withdrawals were shifted toward other sources, and by 2015 water levels had recovered to approximately 50 ft below NGVD 29.
The mean estimated transmissivity of the Piney Point aquifer in York and James City Counties is 16,300 feet squared per day (ft2/d), but farther north it is only 925 ft2/d. The mean well specific capacity in York and James City Counties is 11.4 gallons per minute per foot (gal/min/ft). Farther north in Virginia, mean specific capacity is only 2.26 gal/min/ft, and in Maryland it is 0.99 gal/min/ft. The northward decrease in specific capacity probably reflects the northward decrease in transmissivity, which results from poor development of the solution-channeled limestone.
An aquifer test in northern York County induced vertical leakage to the solution-channeled limestone from overlying silty sand and a change in response of the aquifer to pumping from a single layer to two layers. Transmissivity of the limestone of approximately 19,800 ft2/d was distinguished from the silty sand of approximately 2,500 ft2/d.
Most of the water in the Piney Point aquifer is slightly alkaline with moderate concentrations primarily of sodium and bicarbonate that are slightly undersaturated with respect to calcite. Iron concentrations are generally less than 0.3 milligrams per liter (mg/L). Mixing of freshwater with seawater has elevated chloride concentrations to the southeast to as much as 7,120 mg/L.
Information on the Piney Point aquifer can benefit water-resource management in siting production wells, predicting likely well yield, and anticipating water-level response to withdrawals. Models that vertically discretize individual geologic units can potentially be used to evaluate groundwater flow in greater detail by representing lateral flow and vertical leakage among the geologic units.
Because groundwater withdrawals are made primarily from the limestone and sand of the Piney Point Formation, the VA DEQ has considered regarding the limestone and sand singly as a regulated aquifer apart from the other geologic units. Under current policy in Virginia, if only the limestone and sand were regarded as a regulated aquifer, a greater amount of drawdown would be allowed than is allowed for the Piney Point aquifer consisting of six geologic units. Some production wells intercept multiple geologic units, and the units can undergo water-level decline and vertical leakage induced by pumping from the limestone and sand. Whether the other geologic units are to be regarded as regulated aquifers is an additional consideration for the VA DEQ.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175041","collaboration":"Prepared in cooperation with the Virginia Department of Environmental Quality","usgsCitation":"McFarland, E.R., 2017, Hydrogeologic framework and hydrologic conditions of the Piney Point aquifer in Virginia: U.S. Geological Survey Scientific Investigations Report 2017–5041, 63 p., 2 pl., and CD-ROM, https://doi.org/10.3133/sir20175041.","productDescription":"Report: vii, 62 p.; 2 Plates: 24 x 36 inches and 36 x 24 inches; Appendixes 1-2; Data Release; Read Me","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-075864","costCenters":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true}],"links":[{"id":342072,"rank":7,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sir/2017/5041/readme.txt","size":"1.27 KB","linkFileType":{"id":2,"text":"txt"}},{"id":342068,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2017/5041/sir20175041_appendix1.xlsx","text":"Appendix 1","size":"36.2 KB","linkFileType":{"id":3,"text":"xlsx"},"linkHelpText":"- Borehole Geologic-Unit Top-Surface Altitudes, Piney Point Aquifer, Virginia"},{"id":342066,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5041/coverthb.jpg"},{"id":342069,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2017/5041/sir20175041_appendix2.xlsx","text":"Appendix 2 ","size":"23.1 MB","linkFileType":{"id":3,"text":"xlsx"},"linkHelpText":"- Aquifer-Component Test data, Piney Point Aquifer, Virginia"},{"id":342071,"rank":6,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2017/5041/sir20175041_plate2.pdf","text":"Plate 2 ","size":"397 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Hydrogeologic Sections A–A’, B–B’, and C–C’ of the Piney Point Aquifer in Virginia"},{"id":342076,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7BV7DV5","text":"USGS data release","description":"USGS data release","linkHelpText":"Hydrogeologic Framework and Hydrologic Conditions of the Piney Point Aquifer in Virginia"},{"id":342067,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5041/sir20175041.pdf","text":"Report","size":"8.09 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5041"},{"id":342070,"rank":5,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2017/5041/sir20175041_plate1.pdf","text":"Plate 1 ","size":"444 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Locations of Boreholes and Extent of Productive Limestone in the Piney Point Aquifer in Virginia"}],"country":"United States","state":"Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.291667,\n 38.291667\n ],\n [\n -76.208333,\n 38.291667\n ],\n [\n -76.208333,\n 37.125\n ],\n [\n -77.291667,\n 37.125\n ],\n [\n -77.291667,\n 38.291667\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Virginia Water Science Center
U.S. Geological Survey
1730 East Parham Road
Richmond, VA 23228
Drylands occur world-wide and are particularly vulnerable to climate change since dryland ecosystems depend directly on soil water availability that may become increasingly limited as temperatures rise. Climate change will both directly impact soil water availability, and also change plant biomass, with resulting indirect feedbacks on soil moisture. Thus, the net impact of direct and indirect climate change effects on soil moisture requires better understanding.
We used the ecohydrological simulation model SOILWAT at sites from temperate dryland ecosystems around the globe to disentangle the contributions of direct climate change effects and of additional indirect, climate change-induced changes in vegetation on soil water availability. We simulated current and future climate conditions projected by 16 GCMs under RCP 4.5 and RCP 8.5 for the end of the century. We determined shifts in water availability due to climate change alone and due to combined changes of climate and the growth form and biomass of vegetation.
Vegetation change will mostly exacerbate low soil water availability in regions already expected to suffer from negative direct impacts of climate change (with the two RCP scenarios giving us qualitatively similar effects). By contrast, in regions that will likely experience increased water availability due to climate change alone, vegetation changes will counteract these increases due to increased water losses by interception. In only a small minority of locations, climate change induced vegetation changes may lead to a net increase in water availability. These results suggest that changes in vegetation in response to climate change may exacerbate drought conditions and may dampen the effects of increased precipitation, i.e. leading to more ecological droughts despite higher precipitation in some regions. Our results underscore the value of considering indirect effects of climate change on vegetation when assessing future soil moisture conditions in water-limited ecosystems.
","language":"English","publisher":"Wiley","doi":"10.1111/gcb.13598","usgsCitation":"Tietjen, B., Schlaepfer, D., Bradford, J.B., Laurenroth, W.K., Hall, S.A., Duniway, M.C., Hochstrasser, T., Jia, G., Munson, S.M., Pyke, D.A., and Wilson, S.D., 2017, Climate change-induced vegetation shifts lead to more ecological droughts despite projected rainfall increases in many global temperate drylands: Global Change Biology, v. 23, no. 7, p. 2743-2754, https://doi.org/10.1111/gcb.13598.","productDescription":"12 p.","startPage":"2743","endPage":"2754","ipdsId":"IP-079913","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true}],"links":[{"id":335892,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"23","issue":"7","noUsgsAuthors":false,"publicationDate":"2017-03-06","publicationStatus":"PW","scienceBaseUri":"58ad5fc2e4b01ccd54f8b521","chorus":{"doi":"10.1111/gcb.13598","url":"http://dx.doi.org/10.1111/gcb.13598","publisher":"Wiley-Blackwell","authors":"Tietjen Britta, Schlaepfer Daniel R., Bradford John B., Lauenroth William K., Hall Sonia A., Duniway Michael C., Hochstrasser Tamara, Jia Gensuo, Munson Seth M., Pyke David A., Wilson Scott D.","journalName":"Global Change Biology","publicationDate":"3/2017","publiclyAccessibleDate":"3/6/2017"},"contributors":{"authors":[{"text":"Tietjen, Britta","contributorId":181517,"corporation":false,"usgs":false,"family":"Tietjen","given":"Britta","email":"","affiliations":[],"preferred":false,"id":670060,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schlaepfer, Daniel R.","contributorId":105189,"corporation":false,"usgs":false,"family":"Schlaepfer","given":"Daniel R.","affiliations":[{"id":7098,"text":"University of Wyoming, Department of Botany, 1000 E. University Avenue, Laramie, WY 82071, USA","active":true,"usgs":false}],"preferred":false,"id":670061,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bradford, John B. 0000-0001-9257-6303 jbradford@usgs.gov","orcid":"https://orcid.org/0000-0001-9257-6303","contributorId":611,"corporation":false,"usgs":true,"family":"Bradford","given":"John","email":"jbradford@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":670062,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Laurenroth, William K.","contributorId":175203,"corporation":false,"usgs":false,"family":"Laurenroth","given":"William","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":670063,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hall, Sonia A.","contributorId":181518,"corporation":false,"usgs":false,"family":"Hall","given":"Sonia","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":670064,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Duniway, Michael C. 0000-0002-9643-2785 mduniway@usgs.gov","orcid":"https://orcid.org/0000-0002-9643-2785","contributorId":4212,"corporation":false,"usgs":true,"family":"Duniway","given":"Michael","email":"mduniway@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":670065,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hochstrasser, Tamara","contributorId":181931,"corporation":false,"usgs":false,"family":"Hochstrasser","given":"Tamara","email":"","affiliations":[{"id":18091,"text":"University College Dublin","active":true,"usgs":false}],"preferred":false,"id":670066,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Jia, Gensuo","contributorId":181520,"corporation":false,"usgs":false,"family":"Jia","given":"Gensuo","email":"","affiliations":[],"preferred":false,"id":670067,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Munson, Seth M. 0000-0002-2736-6374 smunson@usgs.gov","orcid":"https://orcid.org/0000-0002-2736-6374","contributorId":1334,"corporation":false,"usgs":true,"family":"Munson","given":"Seth","email":"smunson@usgs.gov","middleInitial":"M.","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":670068,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Pyke, David A. 0000-0002-4578-8335 david_a_pyke@usgs.gov","orcid":"https://orcid.org/0000-0002-4578-8335","contributorId":3118,"corporation":false,"usgs":true,"family":"Pyke","given":"David","email":"david_a_pyke@usgs.gov","middleInitial":"A.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":670069,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Wilson, Scott D.","contributorId":181519,"corporation":false,"usgs":false,"family":"Wilson","given":"Scott","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":670070,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70188385,"text":"70188385 - 2017 - Denitrifying woodchip bioreactor and phosphorus filter pairing to minimize pollution swapping","interactions":[],"lastModifiedDate":"2017-06-07T15:26:26","indexId":"70188385","displayToPublicDate":"2017-06-07T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3716,"text":"Water Research","onlineIssn":"1879-2448","printIssn":"0043-1354","active":true,"publicationSubtype":{"id":10}},"title":"Denitrifying woodchip bioreactor and phosphorus filter pairing to minimize pollution swapping","docAbstract":"Pairing denitrifying woodchip bioreactors and phosphorus-sorbing filters provides a unique, engineered approach for dual nutrient removal from waters impaired with both nitrogen (N) and phosphorus (P). This column study aimed to test placement of two P-filter media (acid mine drainage treatment residuals and steel slag) relative to a denitrifying system to maximize N and P removal and minimize pollution swapping under varying flow conditions (i.e., woodchip column hydraulic retention times (HRTs) of 7.2, 18, and 51 h; P-filter HRTs of 7.6–59 min). Woodchip denitrification columns were placed either upstream or downstream of P-filters filled with either medium. The configuration with woodchip denitrifying systems placed upstream of the P-filters generally provided optimized dissolved P removal efficiencies and removal rates. The P-filters placed upstream of the woodchip columns exhibited better P removal than downstream-placed P-filters only under overly long (i.e., N-limited) retention times when highly reduced effluent exited the woodchip bioreactors. The paired configurations using mine drainage residuals provided significantly greater P removal than the steel slag P-filters (e.g., 25–133 versus 8.8–48 g P removed m−3 filter media d−1, respectively), but there were no significant differences in N removal between treatments (removal rates: 8.0–18 g N removed m−3 woodchips d−1; N removal efficiencies: 18–95% across all HRTs). The range of HRTs tested here resulted in various undesirable pollution swapping by-products from the denitrifying bioreactors: nitrite production when nitrate removal was not complete and sulfate reduction, chemical oxygen demand production and decreased pH during overly long retention times. The downstream P-filter placement provided a polishing step for removal of chemical oxygen demand and nitrite.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.watres.2017.05.026","usgsCitation":"Christianson, L.E., Lepine, C., Sibrell, P., Penn, C.J., and Summerfelt, S.T., 2017, Denitrifying woodchip bioreactor and phosphorus filter pairing to minimize pollution swapping: Water Research, v. 121, p. 129-139, https://doi.org/10.1016/j.watres.2017.05.026.","productDescription":"11 p.","startPage":"129","endPage":"139","ipdsId":"IP-084848","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":469766,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.watres.2017.05.026","text":"Publisher Index Page"},{"id":342275,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"121","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"593910a7e4b0764e6c5e883c","contributors":{"authors":[{"text":"Christianson, Laura E.","contributorId":192714,"corporation":false,"usgs":false,"family":"Christianson","given":"Laura","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":697484,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lepine, Christine","contributorId":192715,"corporation":false,"usgs":false,"family":"Lepine","given":"Christine","email":"","affiliations":[],"preferred":false,"id":697485,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sibrell, Philip 0000-0001-5666-1228 psibrell@usgs.gov","orcid":"https://orcid.org/0000-0001-5666-1228","contributorId":168582,"corporation":false,"usgs":true,"family":"Sibrell","given":"Philip","email":"psibrell@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":697483,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Penn, Chad J.","contributorId":116060,"corporation":false,"usgs":false,"family":"Penn","given":"Chad","email":"","middleInitial":"J.","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":697486,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Summerfelt, Steven T.","contributorId":192709,"corporation":false,"usgs":false,"family":"Summerfelt","given":"Steven","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":697487,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70188379,"text":"70188379 - 2017 - Performance and application of a fluidized bed limestone reactor designed for control of alkalinity, hardness and pH at the Warm Springs Regional Fisheries Center","interactions":[],"lastModifiedDate":"2017-06-07T14:59:57","indexId":"70188379","displayToPublicDate":"2017-06-07T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":852,"text":"Aquacultural Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Performance and application of a fluidized bed limestone reactor designed for control of alkalinity, hardness and pH at the Warm Springs Regional Fisheries Center","docAbstract":"Springs serving the Warm Springs Regional Fisheries Center, Warm Springs, Georgia, have pH, alkalinity, and hardness levels thatlie under the range required for successful fish propagation while free CO2 is well above allowable targets. We evaluate a pretreatment process that exploits limestone’s (CaCO3) ability to react away hydrogen ions (H+) and carbon dioxide (CO2) while increasing alkalinity (HCO3−) and calcium (Ca2+) concentrations, i.e.
CaCO3 + H+ ↔ HCO3− + Ca2+
CaCO3 + CO2 + H2O ↔ Ca2+ + 2HCO3−
Limestone sand was tested in both pilot and full scale fluidized bed reactors (CycloBio®). We first established the bed expansion characteristics of three commercial limestone products then evaluated the effect of hydraulic flux and bed height on dissolution rate of a single selected product (Type A16 × 120). Pilot scale testing at 18C showed limestone dissolution rates were relatively insensitive to flux over the range 1.51–3.03 m3/min/m2 but were sensitive (P < 0.001; R2 = 0.881) to changes in bed height (BH, cm) over the range 83–165 cm following the relation: (Alkalinity, mg/L) = 123.51 − (3788.76 (BH)). Differences between filtered and non-filtered alkalinity were small(P > 0.05) demonstrating that limestone was present in the reactor effluent primarily in the form of dissolved Ca(HCO3)2. Effluent alkalinity exceeded our target level of 50 mg/L under most operating conditions evaluated with typical pilot scale values falling within the range of 90–100 mg/L despite influent concentrations of about 4 mg/L. Concurrently, CO2 fell from an average of 50.6 mg/L to 8.3 mg/L (90%), providing for an increase in pH from 5.27 to a mean of 7.71. The ability of the test reactor to provide changes in water chemistry variables that exceeded required changes allowed for a dilution ratio of 0.6. Here, alkalinity still exceeded 50 mg/L, the CO2 concentration remained well below our limit of 20 mg/L (15.4 mg/L) and the pH was near neutral (7.17). Applying the dilution ratio of 0.6 in a full scale treatment plant at the site reduced by 40% the volume of spring water that is directed through each of three parallel reactors that combined react away 49,000 kg of limestone/yr.
","language":"English","publisher":"Aquacultural Engineering Society","doi":"10.1016/j.aquaeng.2017.03.003","usgsCitation":"Watten, B.J., Mudrak, V.A., Echevarria, C., Sibrell, P., Summerfelt, S.T., and Boyd, C.E., 2017, Performance and application of a fluidized bed limestone reactor designed for control of alkalinity, hardness and pH at the Warm Springs Regional Fisheries Center: Aquacultural Engineering, v. 77, p. 97-106, https://doi.org/10.1016/j.aquaeng.2017.03.003.","productDescription":"10 p.","startPage":"97","endPage":"106","ipdsId":"IP-081684","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":461513,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.aquaeng.2017.03.003","text":"Publisher Index Page"},{"id":342266,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"77","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"593910a8e4b0764e6c5e8840","contributors":{"authors":[{"text":"Watten, Barnaby J. 0000-0002-2227-8623 bwatten@usgs.gov","orcid":"https://orcid.org/0000-0002-2227-8623","contributorId":2002,"corporation":false,"usgs":true,"family":"Watten","given":"Barnaby","email":"bwatten@usgs.gov","middleInitial":"J.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":697462,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mudrak, Vincent A.","contributorId":192707,"corporation":false,"usgs":false,"family":"Mudrak","given":"Vincent","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":697463,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Echevarria, Carlos","contributorId":192708,"corporation":false,"usgs":false,"family":"Echevarria","given":"Carlos","email":"","affiliations":[],"preferred":false,"id":697464,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sibrell, Philip 0000-0001-5666-1228 psibrell@usgs.gov","orcid":"https://orcid.org/0000-0001-5666-1228","contributorId":168582,"corporation":false,"usgs":true,"family":"Sibrell","given":"Philip","email":"psibrell@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":697465,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Summerfelt, Steven T.","contributorId":192709,"corporation":false,"usgs":false,"family":"Summerfelt","given":"Steven","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":697466,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Boyd, Claude E.","contributorId":192710,"corporation":false,"usgs":false,"family":"Boyd","given":"Claude","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":697467,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70188355,"text":"70188355 - 2017 - Perturbational and nonperturbational inversion of Rayleigh-wave velocities","interactions":[],"lastModifiedDate":"2017-06-07T08:33:59","indexId":"70188355","displayToPublicDate":"2017-06-07T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1808,"text":"Geophysics","active":true,"publicationSubtype":{"id":10}},"title":"Perturbational and nonperturbational inversion of Rayleigh-wave velocities","docAbstract":"The inversion of Rayleigh-wave dispersion curves is a classic geophysical inverse problem. We have developed a set of MATLAB codes that performs forward modeling and inversion of Rayleigh-wave phase or group velocity measurements. We describe two different methods of inversion: a perturbational method based on finite elements and a nonperturbational method based on the recently developed Dix-type relation for Rayleigh waves. In practice, the nonperturbational method can be used to provide a good starting model that can be iteratively improved with the perturbational method. Although the perturbational method is well-known, we solve the forward problem using an eigenvalue/eigenvector solver instead of the conventional approach of root finding. Features of the codes include the ability to handle any mix of phase or group velocity measurements, combinations of modes of any order, the presence of a surface water layer, computation of partial derivatives due to changes in material properties and layer boundaries, and the implementation of an automatic grid of layers that is optimally suited for the depth sensitivity of Rayleigh waves.
The southern portion of New Zealand's South Island is a productive area for mallards (Anas platyrhynchos) despite a notable lack of permanent or semi-permanent wetlands. Most broods are reared in pastures that may or may not be flooded with ephemeral water. In recent years, there has been an increased conversion from continuous to sporadic grazing that has resulted in a functional change in the emergent and upland vegetation available for broods. In 2014, we investigated mallard duckling survival on different pastures relative to a suite of characteristics pertaining to the adult female, clutch, brood, weather, and habitat. We monitored 438 ducklings from 50 radio-marked females to 30 days post-hatch. Duckling survival was unaffected by pasture type but increased with duckling age, the presence of ephemeral water, and with greater distance from the nearest anthropogenic structure. Survival was lower for broods of second year (SY) females than for broods of after-second year (ASY) females, in areas with more dense cover, and when ducklings moved, on average, greater daily distances. Cumulative 30-day duckling survival ranged from 0.11 for ducklings of SY females without ephemeral water present to 0.46 for ducklings of ASY females with ephemeral water present. Therefore, increasing available seasonal water sources may increase duckling survival. Further, narrow, linear patches of dense cover present in our study could support a greater abundance of predators or increase their foraging efficiency. As such, managers could consider increasing patch sizes of dense cover to reduce predator efficiency, and employing predator removal in these areas to improve duckling survival.
","language":"English","publisher":"Wildlife Society","doi":"10.1002/jwmg.21256","usgsCitation":"Garrick, E., Amundson, C.L., and Seddon, P.J., 2017, Duckling survival of mallards in Southland, New Zealand: Journal of Wildlife Management, v. 81, no. 5, p. 858-867, https://doi.org/10.1002/jwmg.21256.","productDescription":"10 p.","startPage":"858","endPage":"867","ipdsId":"IP-079621","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":342193,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"New Zealand","otherGeospatial":"Southland","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 167.552490234375,\n -46.86019101567025\n ],\n [\n 169.87060546875,\n -46.86019101567025\n ],\n [\n 169.87060546875,\n -46.30140615437331\n ],\n [\n 167.552490234375,\n -46.30140615437331\n ],\n [\n 167.552490234375,\n -46.86019101567025\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"81","issue":"5","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-03-29","publicationStatus":"PW","scienceBaseUri":"593910aae4b0764e6c5e884a","contributors":{"authors":[{"text":"Garrick, Erin","contributorId":192685,"corporation":false,"usgs":false,"family":"Garrick","given":"Erin","email":"","affiliations":[],"preferred":false,"id":697364,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Amundson, Courtney L. 0000-0002-0166-7224 camundson@usgs.gov","orcid":"https://orcid.org/0000-0002-0166-7224","contributorId":4833,"corporation":false,"usgs":true,"family":"Amundson","given":"Courtney","email":"camundson@usgs.gov","middleInitial":"L.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":697363,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Seddon, Phillip J.","contributorId":147258,"corporation":false,"usgs":false,"family":"Seddon","given":"Phillip","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":697365,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70188156,"text":"sir20175029 - 2017 - Flood of July 2016 in northern Wisconsin and the Bad River Reservation","interactions":[],"lastModifiedDate":"2017-06-07T09:34:07","indexId":"sir20175029","displayToPublicDate":"2017-06-06T12:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-5029","title":"Flood of July 2016 in northern Wisconsin and the Bad River Reservation","docAbstract":"Heavy rain fell across northern Wisconsin and the Bad River Reservation on July 11, 2016, as a result of several rounds of thunderstorms. The storms caused major flooding in the Bad River Basin and nearby tributaries along the south shore of Lake Superior. Rainfall totals were 8–10 inches or more and most of the rain fell in an 8-hour period. A streamgage on the Bad River near Odanah, Wisconsin, rose from 300 cubic feet per second to a record peak streamflow of 40,000 cubic feet per second in only 15 hours. Following the storms and through September 2016, personnel from the U.S. Geological Survey and Bad River Tribe Natural Resources Department recovered and documented 108 high-water marks near the Bad River Reservation. Many of these high-water marks were used to create three flood-inundation maps for the Bad River, Beartrap Creek, and Denomie Creek for the Bad River Reservation in the vicinity of the community of Odanah.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175029","collaboration":"Prepared in cooperation with the Bad River Band of the Lake Superior Chippewa Tribe","usgsCitation":"Fitzpatrick, F.A., Dantoin, E.D., Tillison, Naomi, Watson, K.M., Waschbusch, R.J., and Blount, J.D., 2017, Flood of July 2016 in northern Wisconsin and the Bad River Reservation: U.S. Geological Survey Scientific Investigations Report 2017–5029, 21 p., 1 app., https://doi.org/10.3133/sir20175029.","productDescription":"Report: vi, 27 p.; Data Release","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-080637","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":342093,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://www.sciencebase.gov/catalog/item/get/592eda03e4b092b266f13e44","text":"USGS data release","description":"USGS data release","linkHelpText":"Flood Inundation, Flood Depth, and High-Water Marks Associated with the Flood of July 2016 in Northern Wisconsin and the Bad River Reservation "},{"id":438305,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F78C9THZ","text":"USGS data release","linkHelpText":"Flood Inundation, Flood Depth, and High-Water Marks Associated with the Flood of July 2016 in Northern Wisconsin and the Bad River Reservation"},{"id":342095,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5029/sir20175029.pdf","text":"Report","size":"7.14 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5029"},{"id":342094,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5029/coverthb.jpg"}],"country":"United States","state":"Wisconsin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.3333,\n 45.955\n ],\n [\n -90.25,\n 45.955\n ],\n [\n -90.25,\n 47.166667\n ],\n [\n -92.3333,\n 47.166667\n ],\n [\n -92.3333,\n 45.955\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Wisconsin Water Science Center
U.S. Geological Survey
8505 Research Way
Middleton, WI 53562