This project addressed regional climate change effects on aquatic food webs in the Great Lakes. We sought insights by examining Lake Erie as a representative system with a high level of anthropogenic impacts, strong nutrient gradients, seasonal hypoxia, and spatial overlap of cold- and cool-water fish guilds. In Lake Erie and in large embayments throughout the Great Lakes basin, this situation is a concern for fishery managers, as climate change may exacerbate hypoxia and reduce habitat volume for some species. We examined fish community composition, fine-scale distribution, prey availability, diets, and biochemical tracers for dominant fishes from study areas with medium-high nutrient levels (mesotrophic, Fairport study area), and low nutrient levels (oligotrophic, Erie study area). This multi-year database (2011-2013) provides the ability to contrast years with wide variation in rainfall, winter ice-cover, and thermal stratification. In addition, multiple indicators of dietary and distributional responses to environmental variability will allow resource managers to select the most informative approach for addressing specific climate change questions. Our results support the incorporation of some relatively simple and cost-efficient approaches into existing agency monitoring programs to track the near-term condition status of fish and fish community composition by functional groupings. Other metrics appear better suited for understanding longer-term changes, and may take more resources to implement on an ongoing basis. Although we hypothesized that dietary overlap and similarity in selected species would be sharply different during thermal stratification and hypoxic episodes, we found little evidence of this. Instead, to our surprise, this study found that fish tended to aggregate at the edges of hypoxia, highlighting potential spatial changes in catch efficiency of the fishery. This work has had several positive impacts on a wide range of resource management and stakeholder activities, most notably in Lake Erie. The results were instrumental in the development of an interim decision rule for dealing with data collected during hypoxic events to improve stock assessment of Yellow Perch. In addition, novel findings from this study regarding spatial and temporal variability in hypoxia have aided US-Environmental Protection Agency in the development of a modified sampling protocol to more accurately quantify the central basin hypoxic zone, and this directly addressed a goal of the Great Lakes Water Quality Agreement of 2012 to reduce the extent and severity of hypoxia. Finally, the study areas developed in this project formed the basis for food web sampling in the 2014 bi-national Coordinated Science and Monitoring Initiative work in Lake Erie.
","language":"English","publisher":"Northeast Climate Science Center","usgsCitation":"Kraus, R.T., Knight, C.T., Gorman, A.M., Kocovsky, P.M., Weidel, B., and Rogers, M.W., 2016, Developing fish trophic interaction indicators of climate change for the Great Lakes, 70 p.","productDescription":"70 p.","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":330639,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":330638,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://necsc.umass.edu/biblio/developing-fish-trophic-interaction-indicators-climate-change-great-lakes"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5819a9c4e4b0bb36a4c91029","contributors":{"authors":[{"text":"Kraus, Richard T. 0000-0003-4494-1841 rkraus@usgs.gov","orcid":"https://orcid.org/0000-0003-4494-1841","contributorId":2609,"corporation":false,"usgs":true,"family":"Kraus","given":"Richard","email":"rkraus@usgs.gov","middleInitial":"T.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":652683,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Knight, Carey T.","contributorId":56529,"corporation":false,"usgs":true,"family":"Knight","given":"Carey","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":652684,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gorman, Ann Marie","contributorId":145525,"corporation":false,"usgs":false,"family":"Gorman","given":"Ann","email":"","middleInitial":"Marie","affiliations":[],"preferred":false,"id":652685,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kocovsky, Patrick M. 0000-0003-4325-4265 pkocovsky@usgs.gov","orcid":"https://orcid.org/0000-0003-4325-4265","contributorId":3429,"corporation":false,"usgs":true,"family":"Kocovsky","given":"Patrick","email":"pkocovsky@usgs.gov","middleInitial":"M.","affiliations":[{"id":251,"text":"Ecosystems Mission Area","active":false,"usgs":true},{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":652686,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Weidel, Brian 0000-0001-6095-2773 bweidel@usgs.gov","orcid":"https://orcid.org/0000-0001-6095-2773","contributorId":2485,"corporation":false,"usgs":true,"family":"Weidel","given":"Brian","email":"bweidel@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":652687,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rogers, Mark W. 0000-0001-7205-5623 mwrogers@usgs.gov","orcid":"https://orcid.org/0000-0001-7205-5623","contributorId":4590,"corporation":false,"usgs":true,"family":"Rogers","given":"Mark","email":"mwrogers@usgs.gov","middleInitial":"W.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":652688,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70176210,"text":"70176210 - 2016 - Organic petrology and geochemistry of Eocene Suzak bituminous marl, north-central Afghanistan: Depositional environment and source rock potential","interactions":[],"lastModifiedDate":"2016-09-01T16:21:44","indexId":"70176210","displayToPublicDate":"2016-05-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2682,"text":"Marine and Petroleum Geology","active":true,"publicationSubtype":{"id":10}},"title":"Organic petrology and geochemistry of Eocene Suzak bituminous marl, north-central Afghanistan: Depositional environment and source rock potential","docAbstract":"Organic geochemistry and petrology of Eocene Suzak bituminous marl outcrop samples from Madr village in north-central Afghanistan were characterized via an integrated analytical approach to evaluate depositional environment and source rock potential. Multiple proxies suggest the organic-rich (TOC ∼6 wt.%) bituminous marls are ‘immature’ for oil generation (e.g., vitrinite Ro < 0.4%, Tmax < 425 °C, PI ≤ 0.05, C29 ααα S/S + R ≤ 0.12, C29 ββS/ββS+ααR ≤ 0.10, others), yet oil seeps are present at outcrop and live oil and abundant solid bitumen were observed via optical microscopy. Whole rock sulfur content is ∼2.3 wt.% whereas sulfur content is ∼5.0–5.6 wt.% in whole rock extracts with high polar components, consistent with extraction from S-rich Type IIs organic matter which could generate hydrocarbons at low thermal maturity. Low Fe-sulfide mineral abundance and comparison of Pr/Ph ratios between saturate and whole extracts suggest limited Fe concentration resulted in sulfurization of organic matter during early diagenesis. From these observations, we infer that a Type IIs kerogen in ‘immature’ bituminous marl at Madr could be generating high sulfur viscous oil which is seeping from outcrop. However, oil-seep samples were not collected for correlation studies. Aluminum-normalized trace element concentrations indicate enrichment of redox sensitive trace elements Mo, U and V and suggest anoxic-euxinic conditions during sediment deposition. The bulk of organic matter observed via optical microscopy is strongly fluorescent amorphous bituminite grading to lamalginite, possibly representing microbial mat facies. Short chain n-alkanes peak at C14–C16 (n-C17/n-C29 > 1) indicating organic input from marine algae and/or bacterial biomass, and sterane/hopane ratios are low (0.12–0.14). Monoaromatic steroids are dominated by C28clearly indicating a marine setting. High gammacerane index values (∼0.9) are consistent with anoxia stratification and may indicate intermittent saline-hypersaline conditions. Stable C isotope ratios also suggest a marine depositional scenario for the Suzak samples, consistent with the presence of marine foraminifera including abundant planktic globigerinida(?) and rare benthic discocyclina(?) and nummulites(?). Biomarker 2α-methylhopane for photosynthetic cyanobacteria implies shallow photic zone deposition of Madr marls and 3β-methylhopane indicates presence of methanotrophic archaea in the microbial consortium. The data presented herein are consistent with deposition of Suzak bituminous marls in shallow stratified waters of a restricted marine basin associated with the southeastern incipient or proto-Paratethys. Geochemical proxies from Suzak rock extracts (S content, high polar content, C isotopes, normal (αααR) C27–29 steranes, and C29/C30 and C26/C25 hopane ratios) are similar to extant data from Paleogene oils produced to the north in the Afghan-Tajik Basin. This observation may indicate laterally equivalent strata are effective source rocks as suggested by previous workers; however, further work is needed to strengthen oil-source correlations.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.marpetgeo.2016.02.029","usgsCitation":"Hackley, P.C., and Sanfilipo, J., 2016, Organic petrology and geochemistry of Eocene Suzak bituminous marl, north-central Afghanistan: Depositional environment and source rock potential: Marine and Petroleum Geology, v. 73, p. 572-589, https://doi.org/10.1016/j.marpetgeo.2016.02.029.","productDescription":"18 p.","startPage":"572","endPage":"589","ipdsId":"IP-069387","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":328205,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"73","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57c95130e4b0f2f0cec15bfc","contributors":{"authors":[{"text":"Hackley, Paul C. 0000-0002-5957-2551 phackley@usgs.gov","orcid":"https://orcid.org/0000-0002-5957-2551","contributorId":592,"corporation":false,"usgs":true,"family":"Hackley","given":"Paul","email":"phackley@usgs.gov","middleInitial":"C.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":647807,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sanfilipo, John 0000-0002-8739-5628 jsan@usgs.gov","orcid":"https://orcid.org/0000-0002-8739-5628","contributorId":140236,"corporation":false,"usgs":true,"family":"Sanfilipo","given":"John","email":"jsan@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":647808,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70192507,"text":"70192507 - 2016 - Trends in pesticide use on soybean, corn and cotton since the introduction of major genetically modified crops in the United States","interactions":[],"lastModifiedDate":"2017-10-26T10:27:36","indexId":"70192507","displayToPublicDate":"2016-05-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3035,"text":"Pest Management Science","active":true,"publicationSubtype":{"id":10}},"title":"Trends in pesticide use on soybean, corn and cotton since the introduction of major genetically modified crops in the United States","docAbstract":"BACKGROUND
Genetically modified (GM) varieties of soybean, corn and cotton have largely replaced conventional varieties in the United States. The most widely used applications of GM technology have been the development of crops that are resistant to a specific broad-spectrum herbicide (primarily glyphosate) or that produce insecticidal compounds within the plant itself. With the widespread adoption of GM crops, a decline in the use of conventional pesticides was expected.
RESULTS
There has been a reduction in the annual herbicide application rate to corn since the advent of GM crops, but the herbicide application rate is mostly unchanged for cotton. Herbicide use on soybean has increased. There has been a substantial reduction in the amount of insecticides used on both corn and cotton since the introduction of GM crops.
CONCLUSIONS
The observed changes in pesticide use are likely to be the result of many factors, including the introduction of GM crops, regulatory restrictions on some conventional pesticides, introduction of new pesticide technologies and changes in farming practices. In order to help protect human and environmental health and to help agriculture plan for the future, more detailed and complete documentation on pesticide use is needed on a frequent and ongoing basis.
","language":"English","publisher":"Wiley","doi":"10.1002/ps.4082","usgsCitation":"Coupe, R.H., and Capel, P.D., 2016, Trends in pesticide use on soybean, corn and cotton since the introduction of major genetically modified crops in the United States: Pest Management Science, v. 72, no. 5, p. 1013-1022, https://doi.org/10.1002/ps.4082.","productDescription":"10 p.","startPage":"1013","endPage":"1022","ipdsId":"IP-066541","costCenters":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"links":[{"id":347436,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"72","issue":"5","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2015-08-10","publicationStatus":"PW","scienceBaseUri":"5a07ea42e4b09af898c8cc70","contributors":{"authors":[{"text":"Coupe, Richard H. 0000-0001-8679-1015 rhcoupe@usgs.gov","orcid":"https://orcid.org/0000-0001-8679-1015","contributorId":551,"corporation":false,"usgs":true,"family":"Coupe","given":"Richard","email":"rhcoupe@usgs.gov","middleInitial":"H.","affiliations":[{"id":394,"text":"Mississippi Water Science Center","active":true,"usgs":true}],"preferred":true,"id":716096,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Capel, Paul D. 0000-0003-1620-5185 capel@usgs.gov","orcid":"https://orcid.org/0000-0003-1620-5185","contributorId":1002,"corporation":false,"usgs":true,"family":"Capel","given":"Paul","email":"capel@usgs.gov","middleInitial":"D.","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":716095,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70178545,"text":"70178545 - 2016 - Assessing the role of seabirds in the ecology of influenza A viruses","interactions":[],"lastModifiedDate":"2018-07-15T18:33:20","indexId":"70178545","displayToPublicDate":"2016-05-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":948,"text":"Avian Diseases","active":true,"publicationSubtype":{"id":10}},"title":"Assessing the role of seabirds in the ecology of influenza A viruses","docAbstract":"Wild waterbirds, specifically waterfowl, gulls, and shorebirds, are recognized as the primordial reservoir of influenza A viruses (IAVs). However, the role of seabirds, an abundant, diverse, and globally distributed group of birds, in the perpetuation and transmission of IAVs is less clear. Here we summarize published and publicly available data for influenza viruses in seabirds, which for the purposes of this study are defined as birds that exhibit a largely or exclusively pelagic lifestyle and exclude waterfowl, gulls, and shorebirds, and we review this collective dataset to assess the role of seabirds in the influenza A ecology. Since 1961, more than 40,000 samples have been collected worldwide from the seabirds considered here and screened, using a variety of techniques, for evidence of active or past IAV infection. From these data, the overall prevalence of active infection has been estimated to be very low; however, serological data provide evidence that some seabird species are more frequently exposed to IAVs. Sequence data for viruses from seabirds are limited, except for murres (common murre, Uria aalge, and thick-billed murre, Uria lomvia; family Alcidae) for which there are full or partial genome sequences available for more than 80 viruses. Characterization of these viruses suggests that murres are infected with Group 1 hemagglutinin subtype viruses more frequently as compared to Group 2 and also indicates that these northern, circumpolar birds are frequently infected by intercontinental reassortant viruses. Greater temporal and spatial sampling and characterization of additional viruses are required to better understand the role of seabirds in global IAV dynamics.
","language":"English","publisher":"American Association of Avian Pathologists","doi":"10.1637/11135-050815-RegR","usgsCitation":"Lang, A.S., Lebarbenchon, C., Robertson, G.J., Ramey, A.M., Waldenstrom, J., and Wille, M., 2016, Assessing the role of seabirds in the ecology of influenza A viruses: Avian Diseases, v. 60, no. 1s, p. 378-386, https://doi.org/10.1637/11135-050815-RegR.","productDescription":"9 p.","startPage":"378","endPage":"386","ipdsId":"IP-065494","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":331238,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"60","issue":"1s","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"583d5034e4b0d9329c80c59f","contributors":{"authors":[{"text":"Lang, Andrew S.","contributorId":177028,"corporation":false,"usgs":false,"family":"Lang","given":"Andrew","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":654331,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lebarbenchon, Camille","contributorId":140670,"corporation":false,"usgs":false,"family":"Lebarbenchon","given":"Camille","email":"","affiliations":[],"preferred":false,"id":654332,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ramey, Andrew M. 0000-0002-3601-8400 aramey@usgs.gov","orcid":"https://orcid.org/0000-0002-3601-8400","contributorId":1872,"corporation":false,"usgs":true,"family":"Ramey","given":"Andrew","email":"aramey@usgs.gov","middleInitial":"M.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":654336,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Robertson, Gregory J.","contributorId":173883,"corporation":false,"usgs":false,"family":"Robertson","given":"Gregory","email":"","middleInitial":"J.","affiliations":[{"id":27311,"text":"Wildlife Research Division, Science and Technology Branch, Environment and Climate","active":true,"usgs":false}],"preferred":false,"id":654333,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Waldenstrom, Jonas","contributorId":42891,"corporation":false,"usgs":true,"family":"Waldenstrom","given":"Jonas","email":"","affiliations":[],"preferred":false,"id":654334,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wille, Michelle","contributorId":173881,"corporation":false,"usgs":false,"family":"Wille","given":"Michelle","email":"","affiliations":[{"id":27309,"text":"Memorial University of Newfoundland, St. John’s, NL A1B 3X9, Canada","active":true,"usgs":false}],"preferred":false,"id":654335,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70170957,"text":"70170957 - 2016 - Challenges for mapping cyanotoxin patterns from remote sensing of cyanobacteria","interactions":[],"lastModifiedDate":"2018-08-09T12:12:53","indexId":"70170957","displayToPublicDate":"2016-04-30T10:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1878,"text":"Harmful Algae","active":true,"publicationSubtype":{"id":10}},"title":"Challenges for mapping cyanotoxin patterns from remote sensing of cyanobacteria","docAbstract":"Using satellite imagery to quantify the spatial patterns of cyanobacterial toxins has several challenges. These challenges include the need for surrogate pigments – since cyanotoxins cannot be directly detected by remote sensing, the variability in the relationship between the pigments and cyanotoxins – especially microcystins (MC), and the lack of standardization of the various measurement methods. A dual-model strategy can provide an approach to address these challenges. One model uses either chlorophyll-a (Chl-a) or phycocyanin (PC) collected in situ as a surrogate to estimate the MC concentration. The other uses a remote sensing algorithm to estimate the concentration of the surrogate pigment. Where blooms are mixtures of cyanobacteria and eukaryotic algae, PC should be the preferred surrogate to Chl-a. Where cyanobacteria dominate, Chl-a is a better surrogate than PC for remote sensing. Phycocyanin is less sensitive to detection by optical remote sensing, it is less frequently measured, PC laboratory methods are still not standardized, and PC has greater intracellular variability. Either pigment should not be presumed to have a fixed relationship with MC for any water body. The MC-pigment relationship can be valid over weeks, but have considerable intra- and inter-annual variability due to changes in the amount of MC produced relative to cyanobacterial biomass. To detect pigments by satellite, three classes of algorithms (analytic, semi-analytic, and derivative) have been used. Analytical and semi-analytical algorithms are more sensitive but less robust than derivatives because they depend on accurate atmospheric correction; as a result derivatives are more commonly used. Derivatives can estimate Chl-a concentration, and research suggests they can detect and possibly quantify PC. Derivative algorithms, however, need to be standardized in order to evaluate the reproducibility of parameterizations between lakes. A strategy for producing useful estimates of microcystins from cyanobacterial biomass is described, provided cyanotoxin variability is addressed.
","language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam","doi":"10.1016/j.hal.2016.01.005","usgsCitation":"Stumpf, R.P., Davis, T.W., Wynne, T.T., Graham, J., Loftin, K.A., Johengen, T., Gossiaux, D., Palladino, D., and Burtner, A., 2016, Challenges for mapping cyanotoxin patterns from remote sensing of cyanobacteria: Harmful Algae, v. 54, p. 160-173, https://doi.org/10.1016/j.hal.2016.01.005.","productDescription":"14 p.","startPage":"160","endPage":"173","numberOfPages":"14","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070534","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":471038,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.hal.2016.01.005","text":"Publisher Index Page"},{"id":321204,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"54","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5736faade4b0dae0d5e03bf4","contributors":{"authors":[{"text":"Stumpf, Rick P","contributorId":169288,"corporation":false,"usgs":false,"family":"Stumpf","given":"Rick","email":"","middleInitial":"P","affiliations":[{"id":6637,"text":"National Oceanic and Atmospheric Administration, Northwest Fisheries Science Center, 2725 Montlake Blvd E, Seattle, WA 98112","active":true,"usgs":false}],"preferred":false,"id":629218,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Davis, Timothy W.","contributorId":169289,"corporation":false,"usgs":false,"family":"Davis","given":"Timothy","email":"","middleInitial":"W.","affiliations":[{"id":6637,"text":"National Oceanic and Atmospheric Administration, Northwest Fisheries Science Center, 2725 Montlake Blvd E, Seattle, WA 98112","active":true,"usgs":false}],"preferred":false,"id":629219,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wynne, Timothy T.","contributorId":169290,"corporation":false,"usgs":false,"family":"Wynne","given":"Timothy","email":"","middleInitial":"T.","affiliations":[{"id":6637,"text":"National Oceanic and Atmospheric Administration, Northwest Fisheries Science Center, 2725 Montlake Blvd E, Seattle, WA 98112","active":true,"usgs":false}],"preferred":false,"id":629220,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Graham, Jennifer L. 0000-0002-6420-9335 jlgraham@usgs.gov","orcid":"https://orcid.org/0000-0002-6420-9335","contributorId":150737,"corporation":false,"usgs":true,"family":"Graham","given":"Jennifer L.","email":"jlgraham@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true},{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":false,"id":629217,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Loftin, Keith A. 0000-0001-5291-876X kloftin@usgs.gov","orcid":"https://orcid.org/0000-0001-5291-876X","contributorId":868,"corporation":false,"usgs":true,"family":"Loftin","given":"Keith","email":"kloftin@usgs.gov","middleInitial":"A.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":629221,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Johengen, T.H.","contributorId":169291,"corporation":false,"usgs":false,"family":"Johengen","given":"T.H.","affiliations":[{"id":25465,"text":"Cooperative Institute for Limnology and Ecosystem Research","active":true,"usgs":false}],"preferred":false,"id":629222,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gossiaux, D.","contributorId":169292,"corporation":false,"usgs":false,"family":"Gossiaux","given":"D.","affiliations":[{"id":25466,"text":"National Oceanic and Atmostpheric Administration","active":true,"usgs":false}],"preferred":false,"id":629223,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Palladino, D.","contributorId":169293,"corporation":false,"usgs":false,"family":"Palladino","given":"D.","email":"","affiliations":[{"id":25465,"text":"Cooperative Institute for Limnology and Ecosystem Research","active":true,"usgs":false}],"preferred":false,"id":629224,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Burtner, A.","contributorId":169294,"corporation":false,"usgs":false,"family":"Burtner","given":"A.","email":"","affiliations":[{"id":25465,"text":"Cooperative Institute for Limnology and Ecosystem Research","active":true,"usgs":false}],"preferred":false,"id":629225,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70170354,"text":"fs20163024 - 2016 - Contaminants in urban waters—Science capabilities of the U.S. Geological Survey","interactions":[],"lastModifiedDate":"2016-04-29T13:40:15","indexId":"fs20163024","displayToPublicDate":"2016-04-29T12:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-3024","title":"Contaminants in urban waters—Science capabilities of the U.S. Geological Survey","docAbstract":"Streams and estuaries with urban watersheds commonly exhibit increased streamflow and decreased base flow; diminished stream-channel stability; excessive amounts of contaminants such as pesticides, metals, industrial and municipal waste, and combustion products; and alterations to biotic community structure. Collectively, these detrimental effects have been termed the “urban-stream syndrome.” Water-resource managers seek to lessen the effects on receiving water bodies of new urban development and remediate the effects in areas of existing urbanization. Similarly, the scientific community has produced extensive research on these topics, with researchers from the U.S. Geological Survey (USGS) leading many studies of urban streams and the processes responsible for the urban-stream syndrome. Increasingly, USGS studies are evaluating the effects of management and restoration activities to better understand how urban waters respond to the implementation of management practices. The USGS has expertise in collecting and interpreting data for many physical, chemical, and ecological processes in urban waters and, thus, provides holistic assessments to inform managers of urban water resources.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20163024","collaboration":"Northeast Region Urban Landscape Capabilities Team","usgsCitation":"U.S. Geological Survey, 2016, Contaminants in urban waters—Science capabilities of the U.S. Geological Survey: U.S. Geological Survey Fact Sheet 2016–3024, 2 p., https://dx.doi.org/10.3133/fs20163024.","productDescription":"2 p.","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-074176","costCenters":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true}],"links":[{"id":320432,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2016/3024/coverthb.jpg"},{"id":320433,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2016/3024/fs20163024.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2016-3024"},{"id":320434,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://dx.doi.org/10.3133/fs20163023","text":"Fact Sheet 2016-3023","description":"FS 2016-3024"},{"id":320435,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://dx.doi.org/10.3133/fs20163025","text":"Fact Sheet 2016-3025","description":"FS 2016-3024"},{"id":320436,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://dx.doi.org/10.3133/fs20163026","text":"Fact Sheet 2016-3026","description":"FS 2016-3024"}],"contact":"U.S. Geological Survey
Northeast Region Urban Landscapes Capability Team
Email: GS-NE_ULCT@usgs.gov
Urban development creates multiple stressors that can degrade stream ecosystems by changing stream hydrology, water quality, and physical habitat. Contaminants, habitat destruction, and increasing streamflow variability resulting from urban development have been associated with the disruption of biological communities, particularly the loss of sensitive aquatic biota. Understanding how algal, invertebrate, and fish communities respond to these physical and chemical stressors can provide important clues as to how streams should be managed to protect stream ecosystems as a watershed becomes increasingly urbanized. The U.S. Geological Survey continues to lead monitoring efforts and scientific studies on the effects of urban development on stream ecosystems in metropolitan areas across the United States.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20163026","collaboration":"Northeast Region Urban Landscape Capabilities Team","usgsCitation":"U.S. Geological Survey, 2016, Urban development and stream ecosystem health—Science capabilities of the U.S. Geological Survey: U.S. Geological Survey Fact Sheet 2016–3026, 2 p., https://dx.doi.org/10.3133/fs20163026.","productDescription":"2 p.","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-074179","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":320444,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2016/3026/fs20163026.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2016-3026"},{"id":320445,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://dx.doi.org/10.3133/fs20163023","text":"Fact Sheet 2016-3023"},{"id":320443,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2016/3026/coverthb.jpg"},{"id":320446,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://dx.doi.org/10.3133/fs20163024","text":"Fact Sheet 2016-3024"},{"id":320447,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://dx.doi.org/10.3133/fs20163025","text":"Fact Sheet 2016-3025"}],"contact":"U.S. Geological Survey
Northeast Region Urban Landscapes Capability Team
Email: GS-NE_ULCT@usgs.gov
Urbanization affects streamflow characteristics, coastal flooding, and groundwater recharge. Increasing impervious areas, streamflow diversions, and groundwater pumpage are some of the ways that the natural water cycle is affected by urbanization. Assessment of the relations among these factors and changes in land use helps water-resource managers with issues such as stormwater management and vulnerability to flood and drought. Scientists with the U.S. Geological Survey (USGS) have the expertise to monitor and model urban hydrologic systems. Streamflow and groundwater data are available in national databases, and analyses of these data, including identification of long-term streamflow trends and the efficacy of management practices, are published in USGS reports.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20163023","collaboration":"Northeast Region Urban Landscape Capabilities Team ","usgsCitation":"U.S. Geological Survey, 2016, Urban hydrology—Science capabilities of the U.S. Geological Survey: U.S. Geological Survey Fact Sheet 2016–3023, 2 p., https://dx.doi.org/10.3133/fs20163023.","productDescription":"2 p.","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-074174","costCenters":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"links":[{"id":320426,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://dx.doi.org/10.3133/fs20163025","text":"Fact Sheet 2016-3025","description":"FS 2016-3023"},{"id":320425,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://dx.doi.org/10.3133/fs20163024","text":"Fact Sheet 2016-3024","description":"FS 2016-3023"},{"id":320423,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2016/3023/coverthb.jpg"},{"id":320427,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://dx.doi.org/10.3133/fs20163026","text":"Fact Sheet 2016-3026","description":"FS 2016-3023"},{"id":320424,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2016/3023/fs20163023.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2016-3023"}],"contact":"U.S. Geological Survey
Northeast Region Urban Landscapes Capability Team
Email: GS-NE_ULCT@usgs.gov
Managing the urban-water cycle has increasingly become a challenge for water-resources planners and regulators faced with the problem of providing clean drinking water to urban residents. Sanitary and combined sanitary and storm sewer networks convey wastewater to centralized treatment plants. Impervious surfaces, which include roads, parking lots, and buildings, increase stormwater runoff and the efficiency by which runoff is conveyed to nearby stream channels; therefore, impervious surfaces increase the risk of urban flooding and alteration of natural ecosystems. These challenges will increase with the expansion of urban centers and the probable effects of climate change on precipitation patterns. Understanding the urban-water cycle is critical to effectively manage water resources and to protect people, infrastructure, and urban-stream ecosystems. As a leader in water-supply, wastewater, and stormwater assessments, the U.S. Geological Survey has the expertise and resources needed to monitor, model, and interpret data related to the urban-water cycle and thereby enable water-resources managers to make informed decisions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20163025","collaboration":"Northeast Region Urban Landscape Capabilities Team","usgsCitation":"U.S. Geological Survey, 2016, Urban infrastructure and water management—Science capabilities of the U.S. Geological Survey: U.S. Geological Survey Fact Sheet 2016–3025, 2 p., https://dx.doi.org/10.3133/fs20163025.","productDescription":"2 p.","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-074177","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":320439,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2016/3025/fs20163025.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2016-3025"},{"id":320438,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2016/3025/coverthb.jpg"},{"id":320440,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://dx.doi.org/10.3133/fs20163023","text":"Fact Sheet 2016-3023"},{"id":320441,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://dx.doi.org/10.3133/fs20163024","text":"Fact Sheet 2016-3024"},{"id":320442,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://dx.doi.org/10.3133/fs20163026","text":"Fact Sheet 2016-3026"}],"contact":"U.S. Geological Survey
Northeast Region Urban Landscapes Capability Team
Email: GS-NE_ULCT@usgs.gov
Evidence suggests that lakes are important sites for atmospheric CO2 exchange and so play a substantial role in the global carbon budget. Previous research has 2 weaknesses: (1) most data have been collected only during the open-water or summer seasons, and (2) data are concentrated principally on natural lakes in northern latitudes. Here, we report on the full annual cycle of atmospheric CO2 exchanges of 15 oligotrophic to eutrophic reservoirs in the Glacial Till Plains of the United States. With one exception, these reservoirs showed an overall loss of CO2 during the year, with most values within the lower range reported for temperate lakes. There was a strong cross-system seasonal pattern: an average of 70% of total annual CO2 efflux occurred by the end of spring mixis; some 20% of annual flux was reabsorbed during summer stratification; and the remaining 50% of efflux was lost during autumnal mixing. Net annual flux was negatively correlated with depth and positively correlated with both water residence time and DOC, with the smallest annual CO2 efflux measured in shallow fertile impoundments. Strong correlations yield relationships allowing regional up-scaling of CO2 evasion. Understanding lacustrine CO2 uptake and evasion requires seasonal analyses across the full range of lake trophic states and morphometric attributes.
","language":"English","publisher":"International Society of Limnology","doi":"10.5268/IW-6.2.982","usgsCitation":"Jones, J., Obrecht, D.V., Graham, J., Balmer, M.B., Filstrup, C.T., and Downing, J.A., 2016, Seasonal patterns in carbon dioxide in 15 mid-continent (USA) reservoirs: Inland Waters, v. 2, no. 6, p. 265-272, https://doi.org/10.5268/IW-6.2.982.","productDescription":"8 p.","startPage":"265","endPage":"272","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-074423","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":471040,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5268/iw-6.2.982","text":"Publisher Index Page"},{"id":320803,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Missouri","county":"Adair County, Chariton County, Harrison County, Linn County, Mercer County, Nodaway 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We analyzed climate-related changes using direct human observations of ice freeze dates (1443–2014) for Lake Suwa, Japan, and of ice breakup dates (1693–2013) for Torne River, Finland. We found a rich array of changes in ice seasonality of two inland waters from geographically distant regions: namely a shift towards later ice formation for Suwa and earlier spring melt for Torne, increasing frequencies of years with warm extremes, changing inter-annual variability, waning of dominant inter-decadal quasi-periodic dynamics, and stronger correlations of ice seasonality with atmospheric CO2 concentration and air temperature after the start of the Industrial Revolution. Although local factors, including human population growth, land use change, and water management influence Suwa and Torne, the general patterns of ice seasonality are similar for both systems, suggesting that global processes including climate change and variability are driving the long-term changes in ice seasonality.
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across the Western United States and Canada","docAbstract":"Methylmercury contamination of fish is a global threat to environmental health. Mercury (Hg) monitoring programs are valuable for generating data that can be compiled for spatially broad syntheses to identify emergent ecosystem properties that influence fish Hg bioaccumulation. Fish total Hg (THg) concentrations were evaluated across the Western United States (US) and Canada, a region defined by extreme gradients in habitat structure and water management. A database was compiled with THg concentrations in 96,310 fish that comprised 206 species from 4262 locations, and used to evaluate the spatial distribution of fish THg across the region and effects of species, foraging guilds, habitats, and ecoregions. Areas of elevated THg exposure were identified by developing a relativized estimate of fish mercury concentrations at a watershed scale that accounted for the variability associated with fish species, fish size, and site effects. THg concentrations in fish muscle ranged between 0.001 and 28.4 (μg/g wet weight (ww)) with a geometric mean of 0.17. Overall, 30% of individual fish samples and 17% of means by location exceeded the 0.30 μg/g ww US EPA fish tissue criterion. Fish THg concentrations differed among habitat types, with riverine habitats consistently higher than lacustrine habitats. Importantly, fish THg concentrations were not correlated with sediment THg concentrations at a watershed scale, but were weakly correlated with sediment MeHg concentrations, suggesting that factors influencing MeHg production may be more important than inorganic Hg loading for determining fish MeHg exposure. There was large heterogeneity in fish THg concentrations across the landscape; THg concentrations were generally higher in semi-arid and arid regions such as the Great Basin and Desert Southwest, than in temperate forests. Results suggest that fish mercury exposure is widespread throughout Western US and Canada, and that species, habitat type, and region play an important role in influencing ecological risk of mercury in aquatic ecosystems.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2016.03.229","usgsCitation":"Eagles-Smith, C.A., Ackerman, J., Willacker, J.J., Tate, M., Lutz, M.A., Fleck, J., Stewart, A.R., Wiener, J.G., Evers, D.C., Lepak, J.M., Davis, J., and Pritz, C.F., 2016, Spatial and temporal patterns of mercury concentrations in freshwater fish across the Western United States and Canada: Science of the Total Environment, v. 568, p. 1171-1184, https://doi.org/10.1016/j.scitotenv.2016.03.229.","productDescription":"14 p.","startPage":"1171","endPage":"1184","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-070592","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true},{"id":34983,"text":"Contaminant Biology Program","active":true,"usgs":true}],"links":[{"id":482076,"rank":4,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2016.03.229","text":"Publisher Index Page"},{"id":320593,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":354415,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ja/70170374/70170374_appendix.pdf","text":"USGS open-access version of article appendix","size":"1.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Open-access journal article appendix"},{"id":354414,"rank":2,"type":{"id":42,"text":"Open Access USGS Document"},"url":"https://pubs.usgs.gov/ja/70170374/70170374.pdf","text":"USGS open-access version of article","size":"1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Open-access journal article"}],"volume":"568","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5721d4a4e4b0b13d3912914b","chorus":{"doi":"10.1016/j.scitotenv.2016.03.229","url":"http://dx.doi.org/10.1016/j.scitotenv.2016.03.229","publisher":"Elsevier BV","authors":"Eagles-Smith Collin A., Ackerman Joshua T., Willacker James J., Tate Michael T., Lutz Michelle A., Fleck Jacob A., Stewart A. Robin, Wiener James G., Evers David C., Lepak Jesse M., Davis Jay A., Pritz Colleen Flanagan","journalName":"Science of The Total Environment","publicationDate":"10/2016"},"contributors":{"authors":[{"text":"Eagles-Smith, Collin A. 0000-0003-1329-5285 ceagles-smith@usgs.gov","orcid":"https://orcid.org/0000-0003-1329-5285","contributorId":505,"corporation":false,"usgs":true,"family":"Eagles-Smith","given":"Collin","email":"ceagles-smith@usgs.gov","middleInitial":"A.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":627015,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ackerman, Joshua T. 0000-0002-3074-8322 jackerman@usgs.gov","orcid":"https://orcid.org/0000-0002-3074-8322","contributorId":147078,"corporation":false,"usgs":true,"family":"Ackerman","given":"Joshua T.","email":"jackerman@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":627016,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Willacker, James J. jwillacker@usgs.gov","contributorId":5614,"corporation":false,"usgs":true,"family":"Willacker","given":"James","email":"jwillacker@usgs.gov","middleInitial":"J.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":627017,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tate, Michael T. 0000-0003-1525-1219 mttate@usgs.gov","orcid":"https://orcid.org/0000-0003-1525-1219","contributorId":3144,"corporation":false,"usgs":true,"family":"Tate","given":"Michael T.","email":"mttate@usgs.gov","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":627018,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lutz, Michelle A. malutz@usgs.gov","contributorId":167259,"corporation":false,"usgs":true,"family":"Lutz","given":"Michelle","email":"malutz@usgs.gov","middleInitial":"A.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":627019,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fleck, Jacob 0000-0002-3217-3972 jafleck@usgs.gov","orcid":"https://orcid.org/0000-0002-3217-3972","contributorId":168694,"corporation":false,"usgs":true,"family":"Fleck","given":"Jacob","email":"jafleck@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":627020,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Stewart, A. 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A key driver of the ecosystem affecting the distribution and abundance of organisms is the timing, distribution, and volume of water flows that result in water depth patterns across the landscape. American alligators (Alligator mississippiensis) are one of the ecological indicators being used to assess Everglades restoration because they are a keystone species and integrate biological impacts of hydrological operations through all life stages. Alligator body condition (the relative fatness of an animal) is one of the metrics being used and targets have been set to allow us to track progress. We examined trends in alligator body condition using Fulton’s K over a 15 year period (2000–2014) at seven different wetland areas within the Everglades ecosystem, assessed patterns and trends relative to restoration targets, and related those trends to hydrologic variables. We developed a series of 17 a priori hypotheses that we tested with an information theoretic approach to identify which hydrologic factors affect alligator body condition. Alligator body condition was highest throughout the Everglades during the early 2000s and is approximately 5–10% lower now (2014). Values have varied by year, area, and hydrology. Body condition was positively correlated with range in water depth and fall water depth. Our top model was the “Current” model and included variables that describe current year hydrology (spring depth, fall depth, hydroperiod, range, interaction of range and fall depth, interaction of range and hydroperiod). Across all models, interaction between range and fall water depth was the most important variable (relative weight of 1.0) followed by spring and fall water depths (0.99), range (0.96), hydroperiod (0.95) and interaction between range and hydroperiod (0.95). Our work provides additional evidence that restoring a greater range in annual water depths is important for improvement of alligator body condition and ecosystem function. This information can be incorporated into both planning and operations to assist in reaching Everglades restoration goals.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2016.03.003","usgsCitation":"Brandt, L., Beauchamp, J.S., Jeffery, B.M., Cherkiss, M.S., and Mazzotti, F., 2016, Fluctuating water depths affect American alligator (Alligator mississippiensis) body condition in the Everglades, Florida, USA: Ecological Indicators, v. 67, p. 441-450, https://doi.org/10.1016/j.ecolind.2016.03.003.","productDescription":"10 p.","startPage":"441","endPage":"450","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069792","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":471046,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolind.2016.03.003","text":"Publisher Index Page"},{"id":320585,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Everglades","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.4473876953125,\n 26.676913083105454\n ],\n [\n -80.36773681640625,\n 26.684275490019488\n ],\n [\n -80.23590087890624,\n 26.571333057252076\n ],\n [\n -80.23590087890624,\n 26.382027976025352\n ],\n [\n -80.29083251953124,\n 26.347575438494673\n ],\n [\n -80.29632568359375,\n 26.185018250078308\n ],\n [\n -80.35400390625,\n 26.118452068488097\n ],\n [\n -80.44189453125,\n 26.145576207592274\n ],\n [\n -80.43365478515625,\n 25.962983554822678\n ],\n [\n -80.48858642578125,\n 25.760319754713887\n ],\n [\n -80.57373046875,\n 25.46559428893416\n ],\n [\n -80.93353271484375,\n 25.40854689267053\n ],\n [\n -81.10382080078125,\n 25.631621577258493\n ],\n [\n -80.8428955078125,\n 25.767740402713383\n ],\n [\n -80.83740234375,\n 26.165298896316042\n ],\n [\n -80.82366943359375,\n 26.330345320410842\n ],\n [\n -80.54901123046875,\n 26.406630642556795\n ],\n [\n -80.452880859375,\n 26.458279167084125\n ],\n [\n -80.4473876953125,\n 26.676913083105454\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"67","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5721d4a3e4b0b13d39129145","contributors":{"authors":[{"text":"Brandt, Laura A.","contributorId":18608,"corporation":false,"usgs":false,"family":"Brandt","given":"Laura A.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":627656,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beauchamp, Jeffrey S.","contributorId":138880,"corporation":false,"usgs":false,"family":"Beauchamp","given":"Jeffrey","email":"","middleInitial":"S.","affiliations":[{"id":12559,"text":"University of Florida, FLEC","active":true,"usgs":false}],"preferred":false,"id":627657,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jeffery, Brian M.","contributorId":138879,"corporation":false,"usgs":false,"family":"Jeffery","given":"Brian","email":"","middleInitial":"M.","affiliations":[{"id":12558,"text":"University of Florida, Gainesville","active":true,"usgs":false}],"preferred":false,"id":627658,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cherkiss, Michael S. 0000-0002-7802-6791 mcherkiss@usgs.gov","orcid":"https://orcid.org/0000-0002-7802-6791","contributorId":4571,"corporation":false,"usgs":true,"family":"Cherkiss","given":"Michael","email":"mcherkiss@usgs.gov","middleInitial":"S.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":627655,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mazzotti, Frank J.","contributorId":12358,"corporation":false,"usgs":false,"family":"Mazzotti","given":"Frank J.","affiliations":[{"id":12604,"text":"Department of Wildlife Ecology and Conservation, Fort Lauderdale Research and Education Center, 3205 College Avenue, University of Florida, Davie, FL 33314, USA","active":true,"usgs":false}],"preferred":false,"id":627659,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70173602,"text":"70173602 - 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We compared hatch timing, growth rates, and subsequent mortality of age-0 Rainbow Smelt Osmerus mordax and Alewife Alosa pseudoharengus, two common open-water fish species of northern North America. In our study site, Lake Champlain, Rainbow Smelt hatched (beginning May 26) almost a month earlier than Alewives (June 20). Abundance in the sampling area was highest in July for age-0 Rainbow Smelt and August for age-0 Alewives. Late-hatching individuals of both species grew faster than those hatching earlier (0.6 mm/d versus 0.4 for Rainbow Smelt; 0.7 mm/d versus 0.6 for Alewives). Mean mortality rate during the first 45 d of life was 3.4%/d for age-0 Rainbow Smelt and was 5.5%/d for age-0 Alewives. Alewife mortality rates did not differ with hatch timing but daily mortality rates of Rainbow Smelt were highest for early-hatching fish. Cannibalism is probably the primary mortality source for age-0 Rainbow Smelt in this lake. Therefore, hatching earlier may not be advantageous because the overlap of adult and age-0 Rainbow Smelt is highest earlier in the season. However, Alewives, first documented in Lake Champlain in 2003, may increase the mortality of age-0 Rainbow Smelt in the summer, which should favor selection for earlier hatching.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/00028487.2016.1143401","usgsCitation":"Parrish, D.L., Simonin, P.W., Rudstam, L.G., Pientka, B., and Sullivan, P., 2016, Interactions between hatch dates, growth rates, and mortality of Age-0 native Rainbow Smelt and nonnative Alewife in Lake Champlain: Transactions of the American Fisheries Society, v. 145, no. 3, p. 649-656, https://doi.org/10.1080/00028487.2016.1143401.","productDescription":"8 p.","startPage":"649","endPage":"656","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064234","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":323231,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Vermont","otherGeospatial":"Lake Champlain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.223876953125,\n 44.450447876762844\n ],\n [\n -73.29666137695312,\n 44.44064372873941\n ],\n [\n -73.32206726074219,\n 44.383747221908365\n ],\n [\n -73.22250366210938,\n 44.37540429036203\n ],\n [\n -73.2183837890625,\n 44.440153478144595\n ],\n [\n -73.223876953125,\n 44.450447876762844\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"145","issue":"3","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-04-27","publicationStatus":"PW","scienceBaseUri":"5757f037e4b04f417c24daad","contributors":{"authors":[{"text":"Parrish, Donna L. 0000-0001-9693-6329 dparrish@usgs.gov","orcid":"https://orcid.org/0000-0001-9693-6329","contributorId":138661,"corporation":false,"usgs":true,"family":"Parrish","given":"Donna","email":"dparrish@usgs.gov","middleInitial":"L.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":637391,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Simonin, Paul W.","contributorId":171499,"corporation":false,"usgs":false,"family":"Simonin","given":"Paul","email":"","middleInitial":"W.","affiliations":[{"id":18160,"text":"Rubenstein School of Environment and Natural Resources, University of Vermont","active":true,"usgs":false}],"preferred":false,"id":637763,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rudstam, Lars G.","contributorId":56609,"corporation":false,"usgs":false,"family":"Rudstam","given":"Lars","email":"","middleInitial":"G.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":637764,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pientka, Bernard","contributorId":171500,"corporation":false,"usgs":false,"family":"Pientka","given":"Bernard","email":"","affiliations":[],"preferred":false,"id":637765,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sullivan, Patrick J.","contributorId":97813,"corporation":false,"usgs":true,"family":"Sullivan","given":"Patrick J.","affiliations":[],"preferred":false,"id":637766,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70171018,"text":"70171018 - 2016 - Numerical experiments to explain multiscale hydrological responses to mountain pine beetle tree mortality in a headwater watershed","interactions":[],"lastModifiedDate":"2016-05-19T10:54:17","indexId":"70171018","displayToPublicDate":"2016-04-26T12:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Numerical experiments to explain multiscale hydrological responses to mountain pine beetle tree mortality in a headwater watershed","docAbstract":"The effects of mountain pine beetle (MPB)-induced tree mortality on a headwater hydrologic system were investigated using an integrated physical modeling framework with a high-resolution computational grid. Simulations of MPB-affected and unaffected conditions, each with identical atmospheric forcing for a normal water year, were compared at multiple scales to evaluate the effects of scale on MPB-affected hydrologic systems. Individual locations within the larger model were shown to maintain hillslope-scale processes affecting snowpack dynamics, total evapotranspiration, and soil moisture that are comparable to several field-based studies and previous modeling work. Hillslope-scale analyses also highlight the influence of compensating changes in evapotranspiration and snow processes. Reduced transpiration in the Grey Phase of MPB-induced tree mortality was offset by increased late-summer evaporation, while overall snowpack dynamics were more dependent on elevation effects than MPB-induced tree mortality. At the watershed scale, unaffected areas obscured the magnitude of MPB effects. Annual water yield from the watershed increased during Grey Phase simulations by 11 percent; a difference that would be difficult to diagnose with long-term gage observations that are complicated by inter-annual climate variability. The effects on hydrology observed and simulated at the hillslope scale can be further damped at the watershed scale, which spans more life zones and a broader range of landscape properties. These scaling effects may change under extreme conditions, e.g., increased total MPB-affected area or a water year with above average snowpack.
","language":"English","publisher":"American Geophysical Union","publisherLocation":"Richmond, VA","doi":"10.1002/2015WR018300","usgsCitation":"Penn, C.A., Bearup, L.A., Maxwell, R.M., and Clow, D.W., 2016, Numerical experiments to explain multiscale hydrological responses to mountain pine beetle tree mortality in a headwater watershed: Water Resources Research, v. 52, no. 4, p. 3143-3161, https://doi.org/10.1002/2015WR018300.","productDescription":"19 p.","startPage":"3143","endPage":"3161","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070327","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":471047,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2015wr018300","text":"Publisher Index Page"},{"id":321299,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"52","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-04-26","publicationStatus":"PW","scienceBaseUri":"573ee3d2e4b04a3a6a24ad3d","contributors":{"authors":[{"text":"Penn, Colin A. 0000-0002-5195-2744 cpenn@usgs.gov","orcid":"https://orcid.org/0000-0002-5195-2744","contributorId":5336,"corporation":false,"usgs":true,"family":"Penn","given":"Colin","email":"cpenn@usgs.gov","middleInitial":"A.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":629555,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bearup, Lindsay A.","contributorId":139257,"corporation":false,"usgs":false,"family":"Bearup","given":"Lindsay","email":"","middleInitial":"A.","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":629556,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Maxwell, Reed M.","contributorId":95373,"corporation":false,"usgs":true,"family":"Maxwell","given":"Reed","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":629557,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Clow, David W. 0000-0001-6183-4824 dwclow@usgs.gov","orcid":"https://orcid.org/0000-0001-6183-4824","contributorId":1671,"corporation":false,"usgs":true,"family":"Clow","given":"David","email":"dwclow@usgs.gov","middleInitial":"W.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":629558,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70170331,"text":"fs20163027 - 2016 - U.S. Geological Survey response to flooding in Texas, May–June 2015","interactions":[],"lastModifiedDate":"2016-04-26T11:33:30","indexId":"fs20163027","displayToPublicDate":"2016-04-26T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-3027","title":"U.S. Geological Survey response to flooding in Texas, May–June 2015","docAbstract":"As a Federal science agency within the Department of the Interior, the U.S. Geological Survey (USGS) collects and disseminates streamflow stage and discharge information along with other types of water information as a major part of its Water mission area. Data collected at USGS streamflow-gaging stations (hereinafter referred to as “streamgages”) are used for a variety of purposes including flood warning, engineering design, management of water resources, and scientific research.
During flood events, the need for timely, accurate, and complete streamflow data is underscored because these data are relied on by local, State, and Federal emergency management personnel for flood response purposes. For example, the National Weather Service uses the data from USGS streamgages to develop flood forecasts for specific locations on a river. Tasks that the USGS performs in response to floods include monitoring the operation of gages and responding to any interruptions in data collection, calibrating and verifying stage-discharge ratings, and documenting extreme events including peak stage and peak discharge.
Frequent, severe storms during May and June 2015 caused widespread flooding in Texas. By various measures, the storms that caused the flooding were extreme and persistent. May 2015 was the wettest month on record for Texas, with a statewide average precipitation of 9.06 inches. In comparison, the long-term statewide average monthly precipitation is 3.37 inches, with the previous record average monthly precipitation reported as 6.66 inches during June 2004. The Office of the Texas State Climatologist compiled monthly precipitation amounts for 19 selected cities throughout Texas and for 1 city in Louisiana; the total monthly precipitation amounts exceeded the monthly normal precipitation for 18 of the 19 selected cities in Texas, with 5 of these cities exceeding their previous record for the month of May.
The onset of abundant precipitation in May 2015 resulted in the National Weather Service flood stage being exceeded at USGS streamgages on numerous rivers. The widespread and prolonged nature of the flooding was unusual; most flood events in Texas are localized, typically affecting only one or two river basins and generally lasting only a few days. With the exception of the Rio Grande, flooding was widespread in all of the major rivers in Texas during May–June 2015.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20163027","usgsCitation":"East, J.W., 2016, U.S. Geological Survey response to flooding in Texas, May–June 2015: U.S. Geological Survey Fact Sheet 2016–3027, 4 p., https://dx.doi.org/10.3133/fs20163027.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-073206","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":320544,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2016/3027/coverthb.jpg"},{"id":320545,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2016/3027/fs20163027.pdf","text":"Fact Sheet","size":"2.75 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Fact Sheet 2016–3027"}],"country":"United 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\"}}]}","contact":"Director, Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, TX 78754–4733
Stable isotope delta values (δ18O and δ2H) of precipitation can vary with elevation, and quantification of the precipitation elevation gradient can be used to predict recharge elevation within a watershed. Precipitation samples were analyzed for stable isotope delta values between 2003 and 2014 from the Verde River watershed of north-central Arizona. Results indicate a significant decrease in summer isotopic values overtime at 3,100-, 4,100-, 6,100-, 7,100-, and 8,100-feet elevation. The updated local meteoric water line for the area is δ2H = 7.11 δ18O + 3.40. Equations to predict stable isotopic values based on elevation were updated from previous publications in Blasch and others (2006), Blasch and Bryson (2007), and Bryson and others (2007). New equations were separated for samples from the Camp Verde to Flagstaff transect and the Prescott to Chino Valley transect. For the Camp Verde to Flagstaff transect, the new equations for winter precipitation are δ18O = -0.0004z − 8.87 and δ2H = -0.0029z − 59.8 (where z represents elevation in feet) and the summer precipitation equations were not statistically significant. For the Prescott to Chino Valley transect, the new equations for summer precipitation are δ18O = -0.0005z − 3.22 and δ2H = -0.0022z − 27.9; the winter precipitation equations were not statistically significant and, notably, stable isotope values were similar across all elevations. Interpretation of elevation of recharge contributing to surface and groundwaters in the Verde River watershed using the updated equations for the Camp Verde to Flagstaff transect will give lower elevation values compared with interpretations presented in the previous studies. For waters in the Prescott and Chino Valley area, more information is needed to understand local controls on stable isotope values related to elevation.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161053","collaboration":"Prepared in cooperation with Yavapai County Water Advisory Committee and Arizona Department of Water Resources","usgsCitation":"Beisner, K.R., Paretti, N.V., and Tucci, R.S., 2016, Analysis of stable isotope ratios (δ18O and δ2H) in precipitation of the Verde River watershed, Arizona, 2003 through 2014: U.S. Geological Survey Open-File Report 2016–1053, 11 p., https://dx.doi.org/10.3133/ofr20161053.","productDescription":"Report: iv, 9 p.; Stable Isotope Data","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-070405","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":320392,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1053/ofr20161053.pdf","text":"Report","size":"10.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1053"},{"id":320393,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2016/1053/ofr20161053_appendix_tables.xlsx","text":"Stable Isotope Data","size":"31.1 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2016-1053"},{"id":320391,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1053/coverthbr.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Verde River Watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.6,\n 34.4\n ],\n [\n -112.6,\n 35.3\n ],\n [\n -111.3,\n 35.3\n ],\n [\n -111.3,\n 34.4\n ],\n [\n -112.6,\n 34.4\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Arizona Water Science Center
520 N. Park Avenue
Tucson, AZ 85719
(520) 670-6671
http://az.water.usgs.gov/
Hardwood forests of eastern North America have experienced decades of acidic deposition, leading to soil acidification where base cation supply was insufficient to neutralize acid inputs. Negative impacts of soil acidity on amphibians include disrupted embryonic development, lower growth rates, and habitat loss. However, some amphibians exhibit intraspecific variation in acid tolerance, suggesting the potential for local adaptation in areas where soils are naturally acidic. The eastern red-backed salamander (Plethodon cinereus) is a highly abundant top predator of the northern hardwood forest floor. Early research found that P. cinereus was sensitive to acidic soils, avoiding substrates with pH < 3.8 and experiencing decreased growth rates in acidic habitats. However, recent studies have documented P. cinereus populations in lower pH conditions than previously observed, suggesting some populations may persist in acidic conditions. Here, we evaluated relationships between organic horizon soil pH and P. cinereus abundance, adult health (body size and condition), and microhabitat selection, based on surveys of 34 hardwood forests in northeastern United States that encompass a regional soil pH gradient. We found no associations between soil pH and P. cinereus abundance or health, and observed that this salamander used substrates with pH similar to that available, suggesting that pH does not mediate their fine-scale distributions. The strongest negative predictor of P. cinereus abundance was the presence of dusky salamanders (Desmognathus spp.), which were most abundant in the western Adirondacks. Our results indicate that P. cinereus occupies a wider range of soil pH than has been previously thought, which has implications for their functional role in forest food webs and nutrient cycles in acid-impaired ecosystems. Tolerance of P. cinereus for more acidic habitats, including anthropogenically acidified forests, may be due to local adaptation in reproductively isolated populations and/or generalist life history traits that allow them to exploit a wider resource niche.
","language":"English","publisher":"Ecological Society of America","publisherLocation":"Washington, DC","doi":"10.1002/ecs2.1318","usgsCitation":"Bondi, C.A., Beier, C.M., Ducey, P.K., Lawrence, G.B., and Bailey, S.W., 2016, Can the eastern red-backed salamander (Plethodon cinereus) persist in an acidified landscape?: Ecosphere, v. 7, no. 4, e01318, 15 p., https://doi.org/10.1002/ecs2.1318.","productDescription":"e01318, 15 p.","numberOfPages":"15","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065102","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":471051,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.1318","text":"Publisher Index Page"},{"id":320413,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.2783203125,\n 42.867912483915305\n ],\n [\n -75.2783203125,\n 44.97645666320777\n ],\n [\n -70.9716796875,\n 44.97645666320777\n ],\n [\n -70.9716796875,\n 42.867912483915305\n ],\n [\n -75.2783203125,\n 42.867912483915305\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"7","issue":"4","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2016-04-22","publicationStatus":"PW","scienceBaseUri":"571b3d19e4b071321fe26eb3","contributors":{"authors":[{"text":"Bondi, Cheryl A","contributorId":168843,"corporation":false,"usgs":false,"family":"Bondi","given":"Cheryl","email":"","middleInitial":"A","affiliations":[{"id":25369,"text":"SUNY Environmental Science and Forestry","active":true,"usgs":false}],"preferred":false,"id":627460,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Beier, Colin M.","contributorId":17107,"corporation":false,"usgs":true,"family":"Beier","given":"Colin","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":627461,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ducey, Peter K","contributorId":168844,"corporation":false,"usgs":false,"family":"Ducey","given":"Peter","email":"","middleInitial":"K","affiliations":[{"id":25370,"text":"SUNY Cortland","active":true,"usgs":false}],"preferred":false,"id":627462,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lawrence, Gregory B. 0000-0002-8035-2350 glawrenc@usgs.gov","orcid":"https://orcid.org/0000-0002-8035-2350","contributorId":867,"corporation":false,"usgs":true,"family":"Lawrence","given":"Gregory","email":"glawrenc@usgs.gov","middleInitial":"B.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":627459,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bailey, Scott W. 0000-0002-9160-156X","orcid":"https://orcid.org/0000-0002-9160-156X","contributorId":36840,"corporation":false,"usgs":true,"family":"Bailey","given":"Scott","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":627463,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70170545,"text":"70170545 - 2016 - A new look at liming as an approach to accelerate recovery from acidic deposition effects","interactions":[],"lastModifiedDate":"2016-04-25T09:56:35","indexId":"70170545","displayToPublicDate":"2016-04-22T11:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"A new look at liming as an approach to accelerate recovery from acidic deposition effects","docAbstract":"Acidic deposition caused by fossil fuel combustion has degraded aquatic and terrestrial ecosystems in North America for over four decades. The only management option other than emissions reductions for combating the effects of acidic deposition has been the application of lime to neutralize acidity after it has been deposited on the landscape. For this reason, liming has been a part of acid rain science from the beginning. However, continued declines in acidic deposition have led to partial recovery of surface water chemistry, and the start of soil recovery. Liming is therefore no longer needed to prevent further damage, so the question becomes whether liming would be useful for accelerating recovery of systems where improvement has lagged. As more is learned about recovering ecosystems, it has become clear that recovery rates vary with watershed characteristics and among ecosystem components. Lakes appear to show the strongest recovery, but recovery in streams is sluggish and recovery of soils appears to be in the early stages. The method in which lime is applied is therefore critical in achieving the goal of accelerated recovery. Application of lime to a watershed provides the advantage of increasing Ca availability and reducing or preventing mobilization of toxic Al, an outcome that is beneficial to both terrestrial and aquatic ecosystems. However, the goal should not be complete neutralization of soil acidity, which is naturally produced. Liming of naturally acidic areas such as wetlands should also be avoided to prevent damage to indigenous species that rely on an acidic environment.
","language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam","doi":"10.1016/j.scitotenv.2016.03.176","collaboration":"New York State Energy Research and Development Authority; USGS","usgsCitation":"Lawrence, G.B., Burns, D.A., and Riva-Murray, K., 2016, A new look at liming as an approach to accelerate recovery from acidic deposition effects: Science of the Total Environment, v. 562, p. 35-46, https://doi.org/10.1016/j.scitotenv.2016.03.176.","productDescription":"12 p.","startPage":"35","endPage":"46","numberOfPages":"12","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-071306","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":471052,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2016.03.176","text":"Publisher Index Page"},{"id":320503,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"562","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"571f3face4b071321fe569f6","chorus":{"doi":"10.1016/j.scitotenv.2016.03.176","url":"http://dx.doi.org/10.1016/j.scitotenv.2016.03.176","publisher":"Elsevier BV","authors":"Lawrence Gregory B., Burns Douglas A., Riva-Murray Karen","journalName":"Science of The Total Environment","publicationDate":"8/2016"},"contributors":{"authors":[{"text":"Lawrence, Gregory B. 0000-0002-8035-2350 glawrenc@usgs.gov","orcid":"https://orcid.org/0000-0002-8035-2350","contributorId":867,"corporation":false,"usgs":true,"family":"Lawrence","given":"Gregory","email":"glawrenc@usgs.gov","middleInitial":"B.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":627557,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burns, Douglas A. 0000-0001-6516-2869 daburns@usgs.gov","orcid":"https://orcid.org/0000-0001-6516-2869","contributorId":1237,"corporation":false,"usgs":true,"family":"Burns","given":"Douglas","email":"daburns@usgs.gov","middleInitial":"A.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":627558,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Riva-Murray, Karen 0000-0001-6683-2238 krmurray@usgs.gov","orcid":"https://orcid.org/0000-0001-6683-2238","contributorId":168876,"corporation":false,"usgs":true,"family":"Riva-Murray","given":"Karen","email":"krmurray@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":627559,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70170333,"text":"fs20163021 - 2016 - The Northeast Stream Quality Assessment","interactions":[],"lastModifiedDate":"2016-04-22T09:58:02","indexId":"fs20163021","displayToPublicDate":"2016-04-22T10:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-3021","title":"The Northeast Stream Quality Assessment","docAbstract":"In 2016, the U.S. Geological Survey (USGS) National Water-Quality Assessment (NAWQA) is assessing stream quality in the northeastern United States. The goal of the Northeast Stream Quality Assessment (NESQA) is to assess the quality of streams in the region by characterizing multiple water-quality factors that are stressors to aquatic life and evaluating the relation between these stressors and biological communities. The focus of NESQA in 2016 will be on the effects of urbanization and agriculture on stream quality in all or parts of eight states: Connecticut, Massachusetts, New Hampshire, New Jersey, New York, Pennsylvania, Rhode Island, and Vermont.
Findings will provide the public and policymakers with information about the most critical factors affecting stream quality, thus providing insights about possible approaches to protect the health of streams in the region. The NESQA study will be the fourth regional study conducted as part of NAWQA and will be of similar design and scope to the first three, in the Midwest in 2013, the Southeast in 2014, and the Pacific Northwest in 2015 (http://txpub.usgs.gov/RSQA/).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20163021","collaboration":"National Water-Quality Assessment","usgsCitation":"Van Metre, P.C., Riva-Murray, Karen, and Coles, J.F., 2016, The Northeast Stream Quality Assessment: U.S. Geological Survey Fact Sheet 2016–3021, 2 p., https://dx.doi.org/10.3133/fs20163021.","productDescription":"2 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-072939","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":320334,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2016/3021/fs20163021.pdf","text":"Report","size":"556 KB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2016-3021"},{"id":320333,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2016/3021/coverthb.jpg"}],"country":"United States","state":"Connecticut, Massachusetts, New Hampshire, New Jersey, New 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413 National Center
12201 Sunrise Valley Drive
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Email: gs-w_nawqa_whq@usgs.gov
http://water.usgs.gov/nawqa/
Data specific to the Harlem River, New York, have been summarized and are presented in this report. The data illustrate improvements in the quality of water for the past 65 years and emphasize the importance of a continuous water-quality record for establishing trends in environmental conditions. Although there is a paucity of sediment-quality data, the New York City Department of Environmental Protection (NYCDEP) Bureau of Wastewater Treatment has maintained a water-quality monitoring network in the Harlem River (and throughout the harbor of New York City) to which 61 combined sewer outfalls discharge effluent. In cooperation with the NYCDEP, the U.S. Geological Survey evaluated water-quality data collected by the NYCDEP dating back to 1945, which indicate trends in water quality and reveal improvement following the 1972 passage of the Clean Water Act. These improvements are indicated by the steady increase in median dissolved oxygen concentrations and an overall decrease in fecal indicator bacteria concentrations starting in the late 1970s. Further, the magnitude of the highest fecal indicator bacteria concentrations (that is, the 90th percentile) in samples collected from the Harlem River have decreased significantly over the past four decades. Other parameters of water quality used to gauge the health of a water body include total suspended solids and nutrient (inorganic forms of nitrogen and phosphorus) concentrations—mean concentrations for these indicators have also decreased in the past decades. The limited sediment data available for one sample in the Harlem River indicate concentrations of copper, zinc, and lead are above sediment-quality thresholds set by the New York State Department of Environmental Conservation. However, more data are needed to better understand the changes in both sediment and water quality in the Harlem River, both as the tide cycles and during precipitation events. As a partner in the Urban Waters Federal Partnership, the U.S. Geological Survey has worked to address the chronic water-quality concerns of the Harlem River by compiling relevant data and studies, which is an important component for understanding and rectifying water-quality problems within a watershed.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165044","collaboration":"Prepared in cooperation with the New York City Department of Environmental Protection","usgsCitation":"Fisher, S.C., 2016, Historical water-quality data from the Harlem River, New York: U.S. Geological Survey Scientific Investigations Report 2016–5044, 21 p., appendix, https://dx.doi.org/10.3133/sir20165044.","productDescription":"Report: viii, 19 p.; Water-quality data","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-055014","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":320361,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5044/sir20165044_appendix1.xlsx","text":"Water-quality data - Tables 1-1 through 1-9 ","size":"3.4 MB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2016-5044"},{"id":320327,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5044/coverthb.jpg"},{"id":320328,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5044/sir20165044.pdf","text":"Report","size":"1.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5044"}],"country":"United States","state":"New York","otherGeospatial":"Harlem River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.9657974243164,\n 40.76520144280567\n ],\n [\n -73.9657974243164,\n 40.883928811599326\n ],\n [\n -73.89335632324219,\n 40.883928811599326\n ],\n [\n -73.89335632324219,\n 40.76520144280567\n ],\n [\n -73.9657974243164,\n 40.76520144280567\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New York Water Science Center
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2045 Route 112, Building 4
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Eelgrass (Zostera marina) populations occupying coastal waters of Alaska are separated by a peninsula and island archipelago into two Large Marine Ecosystems (LMEs). From populations in both LMEs, we characterize genetic diversity, population structure, and polarity in gene flow using nuclear microsatellite fragment and chloroplast and nuclear sequence data. An inverse relationship between genetic diversity and latitude was observed (heterozygosity: R2 = 0.738, P < 0.001; allelic richness: R2 = 0.327, P = 0.047), as was significant genetic partitioning across most sampling sites (θ = 0.302, P < 0.0001). Variance in allele frequency was significantly partitioned by region only in cases when a population geographically in the Gulf of Alaska LME (Kinzarof Lagoon) was instead included with populations in the Eastern Bering Sea LME (θp = 0.128–0.172; P < 0.003), suggesting gene flow between the two LMEs in this region. Gene flow among locales was rarely symmetrical, with notable exceptions generally following net coastal ocean current direction. Genetic data failed to support recent proposals that multiple Zostera species (i.e. Z. japonica and Z. angustifolia) are codistributed with Z. marina in Alaska. Comparative analyses also failed to support the hypothesis that eelgrass populations in the North Atlantic derived from eelgrass retained in northeastern Pacific Last Glacial Maximum refugia. These data suggest northeastern Pacific populations are derived from populations expanding northward from temperate populations following climate amelioration at the terminus of the last Pleistocene glaciation.
","language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pone.0152701","usgsCitation":"Talbot, S.L., Sage, G.K., Rearick, J.R., Fowler, M., Muñiz-Salazar, R., Baibak, B., Wyllie-Echeverria, S., Cabello-Pasini, A., and Ward, D.H., 2016, The structure of genetic diversity in eelgrass (Zostera marina L.) along the North Pacific and Bering Sea coasts of Alaska: PLoS ONE, v. 11, no. 4, Article e0152701; 31 p., https://doi.org/10.1371/journal.pone.0152701.","productDescription":"Article e0152701; 31 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-061219","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":471053,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0152701","text":"Publisher Index Page"},{"id":438617,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7GQ6VTK","text":"USGS data 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sediment is one of the difficult practical problems commonly addressed by fluvial geomorphologists. This problem typically arises in three situations. In the first situation, geomorphologists are attempting to understand why a channel or class of channels has a certain general form; in a sense, this is the central goal of fluvial geomorphology. In the second situation, geomorphologists are trying to understand and explain how and why a specific channel will evolve or has evolved in response to altered or unusual sediment and water supplies to that channel. For example, this would include explaining the short-term response of a channel to an unusually large flood or predicting the response of a channel to long-term changes in flow or sediment supply due to various human activities such as damming or diversions. Finally, geomorphologists may be called upon to design or assess the design of proposed man-made channels that must carry a certain range of flows and sediment loads in a stable or at least quasi-stable manner. In each of these three situations, the problem is really the same: geomorphologists must understand and predict the interaction of the flow field in the channel, the sediment movement in the channel and the geometry of the channel bed and banks. In general, the flow field, the movement of sediment making up the bed and the morphology of the bed are intricately linked; the flow moves the sediment, the bed is altered by erosion and deposition of sediment and the shape of the bed is critically important for predicting the flow. This complex linkage is precisely what makes understanding channel form and process such a difficult and interesting challenge.
","language":"English","publisher":"Wiley","doi":"10.1002/9781118648551.ch18","usgsCitation":"Nelson, J.M., McDonald, R.R., Shimizu, Y., Kimura, I., Nabi, M., and Asahi, K., 2016, Modeling flow, sediment transport and morphodynamics in rivers, p. 412-441, https://doi.org/10.1002/9781118648551.ch18.","productDescription":"30 p.","startPage":"412","endPage":"441","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059573","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":328104,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-04-22","publicationStatus":"PW","scienceBaseUri":"57c7ffbbe4b0f2f0cebfc301","contributors":{"authors":[{"text":"Nelson, Jonathan M. 0000-0002-7632-8526 jmn@usgs.gov","orcid":"https://orcid.org/0000-0002-7632-8526","contributorId":2812,"corporation":false,"usgs":true,"family":"Nelson","given":"Jonathan","email":"jmn@usgs.gov","middleInitial":"M.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":645882,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McDonald, Richard R. 0000-0002-0703-0638 rmcd@usgs.gov","orcid":"https://orcid.org/0000-0002-0703-0638","contributorId":2428,"corporation":false,"usgs":true,"family":"McDonald","given":"Richard","email":"rmcd@usgs.gov","middleInitial":"R.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":645883,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shimizu, Yasuyuki","contributorId":173790,"corporation":false,"usgs":false,"family":"Shimizu","given":"Yasuyuki","email":"","affiliations":[{"id":17805,"text":"Hokkaido University, Sapporo, Japan","active":true,"usgs":false}],"preferred":false,"id":645884,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kimura, Ichiro","contributorId":173798,"corporation":false,"usgs":false,"family":"Kimura","given":"Ichiro","email":"","affiliations":[{"id":17805,"text":"Hokkaido University, Sapporo, Japan","active":true,"usgs":false}],"preferred":false,"id":645885,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nabi, Mohamed","contributorId":173800,"corporation":false,"usgs":false,"family":"Nabi","given":"Mohamed","affiliations":[{"id":17805,"text":"Hokkaido University, Sapporo, Japan","active":true,"usgs":false}],"preferred":false,"id":645886,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Asahi, Kazutake","contributorId":173792,"corporation":false,"usgs":false,"family":"Asahi","given":"Kazutake","email":"","affiliations":[{"id":27296,"text":"River Link Corporation, Tokyo, Japan","active":true,"usgs":false}],"preferred":false,"id":645887,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70169104,"text":"sir20165031 - 2016 - The source of groundwater and solutes to Many Devils Wash at a former uranium mill site in Shiprock, New Mexico","interactions":[],"lastModifiedDate":"2016-04-25T09:52:57","indexId":"sir20165031","displayToPublicDate":"2016-04-21T17:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-5031","title":"The source of groundwater and solutes to Many Devils Wash at a former uranium mill site in Shiprock, New Mexico","docAbstract":"The Shiprock Disposal Site is the location of the former Navajo Mill (Mill), a uranium ore-processing facility, located on a terrace overlooking the San Juan River in the town of Shiprock, New Mexico. Following the closure of the Mill, all tailings and associated materials were encapsulated in a disposal cell built on top of the former Mill and tailings piles. The milling operations, conducted at the site from 1954 to 1968, created radioactive tailings and process-related wastes that are now found in the groundwater. Elevated concentrations of constituents of concern—ammonium, manganese, nitrate, selenium, strontium, sulfate, and uranium—have also been measured in groundwater seeps in the nearby Many Devils Wash arroyo, leading to the inference that these constituents originated from the Mill. These constituents have also been reported in groundwater that is associated with Mancos Shale, the bedrock that underlies the site. The objective of this report is to increase understanding of the source of water and solutes to the groundwater beneath Many Devils Wash and to establish the background concentrations for groundwater that is in contact with the Mancos Shale at the site. This report presents evidence on three working hypotheses: (1) the water and solutes in Many Devils Wash originated from the operations at the former Mill, (2) groundwater in deep aquifers is upwelling under artesian pressure to recharge the shallow groundwater beneath Many Devils Wash, and (3) the groundwater beneath Many Devils Wash originates as precipitation that infiltrates into the shallow aquifer system and discharges to Many Devils Wash in a series of springs on the east side of the wash. The solute concentrations in the shallow groundwater of Many Devils Wash would result from the interaction of the water and the Mancos Shale if the source of water was upwelling from deep aquifers or precipitation.
In order to compare the groundwater from various wells to groundwater that has been affected by Mill activities, a classification system was developed to determine which wells were most likely to have been affected. Affects to groundwater by the Mill were determined by using the reported uranium alpha activity ratios measured in groundwater samples, along with the concentration of the uranium and the location of the wells relative to the Mill. Activity ratios of 1.2 or less were determined to be the most reliable indicator of Mill-affected groundwater. Wells with samples that had a reported activity ratio of 1.2 or less were classified as Mill affected. To compare groundwater with background water-quality, data from groundwater seeps and springs in the Upper Eagle Nest Arroyo and Salt Creek Wash, located north of the San Juan River, are also presented and analyzed.
Based on groundwater elevations and tritium concentrations measured in wells located between the disposal cell and Many Devils Wash, Mill water is not likely to reach Many Devils Wash. The tritium concentrations also indicate that groundwater from the Mill has not substantially affected Many Devils Wash in the past. Upwelling from deep aquifers was also determined to be an unlikely source, primarily by comparing the composition of the stable isotopes of water in the shallow groundwater with those reported in groundwater samples from the deeper aquifers. The stable-isotope compositions of the shallow groundwater around the site are enriched relative to the San Juan River and local meteoric lines, which suggests that most of the shallow groundwater has been influenced by evaporation and therefore was recharged at the surface. Several observations indicate that focused recharge is the likely source of groundwater in the area of Many Devils Wash. The visible erosional features in Many Devils Wash provide evidence of piping and groundwater sapping, and the distribution and type of vegetation in Many Devils Wash suggest that the focused recharge of precipitation is occurring. The estimated recharge from precipitation was calculated to be 0.0008 inches per year (in/yr) by using the mass-balance approach from reported seep discharge and 0.0011 in/yr using the chloride mass-balance approach.
A conceptual model of groundwater quality beneath Many Devils Wash is presented to explain the source of solutes in the groundwater beneath Many Devils Wash. The major-ion concentrations and geochemical evolution in the groundwater beneath Many Devils Wash and across the study area support the conceptual model that the underlying Mancos Shale is the source of solutes. Differences in the major-ion composition between groundwater samples collected around the site, result from the degree of weathering to the Mancos Shale. The cation distribution appears to be an indicator of effects from the Mill, with samples from the Mill-affected wells largely having a calcium/magnesium-sulfate composition that resembles the reported compositions of more weathered shale; however, that composition could change if the Mill-processed water flowed into areas where the Mancos Shale was less weathered. On the basis of the widespread presence of uranium in the Mancos Shale and the distribution of aqueous uranium in the analog sites and other sites in the region, it appears likely that uranium in the groundwater of Many Devils Wash is naturally sourced from the Mancos Shale.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165031","collaboration":"Prepared in cooperation with the Navajo Nation Environmental Protection Agency","usgsCitation":"Robertson, A.J., Ranalli, A.J., Austin, S.A., and Lawlis, B.R., 2016, The source of groundwater and solutes to Many Devils Wash at a former uranium mill site in Shiprock, New Mexico: U.S. Geological Survey Scientific Investigations Report 2016–5031, 54 p., https://dx.doi.org/10.3133/sir20165031.","productDescription":"x, 54 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-051391","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":320372,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5031/coverthb.jpg"},{"id":320373,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5031/sir20165031.pdf","text":"Report","size":"5.19 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5031"}],"country":"United States","state":"New Mexico","otherGeospatial":"Shiprock","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.74404907226562,\n 36.84775766525783\n ],\n [\n -108.74267578125,\n 36.70806354647625\n ],\n [\n -108.54766845703125,\n 36.71356812817935\n ],\n [\n -108.56552124023438,\n 36.869733528373395\n ],\n [\n -108.74542236328125,\n 36.87742358748459\n ],\n [\n -108.74404907226562,\n 36.84775766525783\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New Mexico Water Science Center
U.S. Geological Survey
5338 Montgomery Blvd. NE
Suite 400
Albuquerque, NM 87109
http://nm.water.usgs.gov/
Conifers are often used as an “air passive sampler”, but few studies have focused on the implication of broadleaf evergreens to monitor atmospheric semivolatile organic compounds such as polychlorinated biphenyls (PCBs). In this study, we used Rhododendron maximum (rhododendron) growing next to a contaminated stream to assess atmospheric PCB concentrations. The study area was located in a rural setting and approximately 2 km downstream of a former Sangamo-Weston (S-W) plant. Leaves from the same mature shrubs were collected in late fall 2010, and winter and spring 2011. PCBs were detected in the collected leaves suggesting that rhododendron can be used as air passive samplers in rural areas where active sampling is impractical. Estimated ΣPCB (47 congeners) concentrations in the atmosphere decreased from fall 2010 to spring 2011 with concentration means at 3990, 2850, and 931 pg m-3 in fall 2010, winter 2011, and spring 2011, respectively. These results indicate that the atmospheric concentrations at this location continue to be high despite termination of active discharge from the former S-W plant. Leaves had a consistent pattern of high concentrations of tetra- and penta-CBs similar to the congener distribution in polyethylene (PE) passive samplers deployed in the water column suggesting that volatilized PCBs from the stream were the primary source of contaminants in rhododendron leaves.
","language":"English","publisher":"Elsevier Science","doi":"10.1002/etc.3404","usgsCitation":"Dang, V.D., Walters, D., and Lee, C.M., 2016, Assessing atmospheric concentration of polychlorinated biphenyls (PCBs) by evergreen Rhododendron maximum next to a contaminated stream: Environmental Toxicology and Chemistry, v. 35, no. 9, p. 2192-2198, https://doi.org/10.1002/etc.3404.","productDescription":"7 p.","startPage":"2192","endPage":"2198","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068484","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":320339,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"South Carolina","city":"Pickens","otherGeospatial":"Town Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.73447513580322,\n 34.88663500030197\n ],\n [\n -82.73447513580322,\n 34.89346406486655\n ],\n [\n -82.71533489227295,\n 34.89346406486655\n ],\n [\n -82.71533489227295,\n 34.88663500030197\n ],\n [\n -82.73447513580322,\n 34.88663500030197\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"35","issue":"9","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-02-17","publicationStatus":"PW","scienceBaseUri":"57189a1ae4b0ef3b7caaf76f","contributors":{"authors":[{"text":"Dang, Viet D.","contributorId":168701,"corporation":false,"usgs":false,"family":"Dang","given":"Viet","email":"","middleInitial":"D.","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":627038,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Walters, David 0000-0002-4237-2158 waltersd@usgs.gov","orcid":"https://orcid.org/0000-0002-4237-2158","contributorId":147135,"corporation":false,"usgs":true,"family":"Walters","given":"David","email":"waltersd@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":627037,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lee, Cindy M.","contributorId":168702,"corporation":false,"usgs":false,"family":"Lee","given":"Cindy","email":"","middleInitial":"M.","affiliations":[{"id":7084,"text":"Clemson University","active":true,"usgs":false}],"preferred":false,"id":627039,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ]}