The ONSR is a karst park, containing many springs and caves. The “jewels” of the park are large springs, several of first magnitude, that contribute significantly to the flow and water quality of the Current River and its tributaries. Completion of 1:24,000-scale geologic mapping of the park and surrounding river basin, along with synthesis of published hydrologic data, allows us to examine the spatial relationships between the springs and the geologic framework to develop a conceptual model for genesis of these springs. Based on their similarity to mapped spring conduits, many of the caves in the ONSR are fossil conduit segments. Therefore, geologic control on the evolution of the springs also applies to speleogenesis in this part of the southern Missouri Ozarks.
Large springs occur in the ONSR area because: (1) the Ozark aquifer, from which they rise, is chiefly dolomite affected by solution via various processes over a long time period, (2) Paleozoic hypogenic fluid migration through these rocks exploited and enhanced flow-paths, (3) a consistent and low regional dip of the rocks off of the Salem Plateau (less than 2° to the southeast) allows integration of flow into large groundwater basins with a few discreet outlets, (4) the springs are located where the rivers have cut down into structural highs, allowing access to water from stratigraphic units deeper in the aquifer thus allowing development of springsheds that have volumetrically larger storage than smaller springs higher in the section, and (5) quartz sandstone and bedded chert in the carbonate stratigraphic succession that are locally to regionally continuous, serve as aquitards that locally confine groundwater up dip of the springs creating artesian conditions. This subhorizontal partitioning of the Ozark aquifer allows contributing areas for different springs to overlap, as evidenced by dye traces that cross adjacent groundwater basin boundaries, and possibly contributes to alternate flow routes under different groundwater flow regimes.
A better understanding of the 3-dimensional hydrogeologic framework for the large spring systems in the ONSR allows more precise mapping of the contributing areas for those springs, will guide future studies of groundwater flow paths, and inform development of groundwater resource management strategies for the park.
","largerWorkType":{"id":24,"text":"Conference Paper"},"conferenceTitle":"GSA Annual Meeting","conferenceDate":"2016","conferenceLocation":"Denver, CO ","language":"English","publisher":"Geological Society of America ","doi":"10.1130/abs/2016AM-282679","usgsCitation":"Weary, D.J., and Orndorff, R.C., 2016, Geologic context of large karst springs and caves in the Ozark National Scenic Riverways, Missouri, GSA Annual Meeting, Denver, CO , 2016, https://doi.org/10.1130/abs/2016AM-282679.","ipdsId":"IP-082624","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":336268,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58b548c1e4b01ccd54fddfbe","contributors":{"authors":[{"text":"Weary, David J. 0000-0002-6115-6397 dweary@usgs.gov","orcid":"https://orcid.org/0000-0002-6115-6397","contributorId":545,"corporation":false,"usgs":true,"family":"Weary","given":"David","email":"dweary@usgs.gov","middleInitial":"J.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":671702,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Orndorff, Randall C. 0000-0002-8956-5803 rorndorf@usgs.gov","orcid":"https://orcid.org/0000-0002-8956-5803","contributorId":2739,"corporation":false,"usgs":true,"family":"Orndorff","given":"Randall","email":"rorndorf@usgs.gov","middleInitial":"C.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":501,"text":"Office of Science Quality and Integrity","active":true,"usgs":true}],"preferred":true,"id":671703,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70187264,"text":"70187264 - 2016 - Predicting invasiveness of species in trade: Climate match, trophic guild and fecundity influence establishment and impact of non-native freshwater fishes","interactions":[],"lastModifiedDate":"2017-04-27T10:40:35","indexId":"70187264","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1399,"text":"Diversity and Distributions","active":true,"publicationSubtype":{"id":10}},"title":"Predicting invasiveness of species in trade: Climate match, trophic guild and fecundity influence establishment and impact of non-native freshwater fishes","docAbstract":"Aim
Impacts of non-native species have motivated development of risk assessment tools for identifying introduced species likely to become invasive. Here, we develop trait-based models for the establishment and impact stages of freshwater fish invasion, and use them to screen non-native species common in international trade. We also determine which species in the aquarium, biological supply, live bait, live food and water garden trades are likely to become invasive. Results are compared to historical patterns of non-native fish establishment to assess the relative importance over time of pathways in causing invasions.
Location
Laurentian Great Lakes region.
Methods
Trait-based classification trees for the establishment and impact stages of invasion were developed from data on freshwater fish species that established or failed to establish in the Great Lakes. Fishes in trade were determined from import data from Canadian and United States regulatory agencies, assigned to specific trades and screened through the developed models.
Results
Climate match between a species’ native range and the Great Lakes region predicted establishment success with 75–81% accuracy. Trophic guild and fecundity predicted potential harmful impacts of established non-native fishes with 75–83% accuracy. Screening outcomes suggest the water garden trade poses the greatest risk of introducing new invasive species, followed by the live food and aquarium trades. Analysis of historical patterns of introduction pathways demonstrates the increasing importance of these trades relative to other pathways. Comparisons among trades reveal that model predictions parallel historical patterns; all fishes previously introduced from the water garden trade have established. The live bait, biological supply, aquarium and live food trades have also contributed established non-native fishes.
Main conclusions
Our models predict invasion risk of potential fish invaders to the Great Lakes region and could help managers prioritize efforts among species and pathways to minimize such risk. Similar approaches could be applied to other taxonomic groups and geographic regions.
","language":"English","publisher":"Wiley","doi":"10.1111/ddi.12391","usgsCitation":"Howeth, J.G., Gantz, C.A., Angermeier, P.L., Frimpong, E.A., Hoff, M.H., Keller, R.P., Mandrak, N.E., Marchetti, M.P., Olden, J., Romagosa, C., and Lodge, D.M., 2016, Predicting invasiveness of species in trade: Climate match, trophic guild and fecundity influence establishment and impact of non-native freshwater fishes: Diversity and Distributions, v. 22, no. 2, p. 148-160, https://doi.org/10.1111/ddi.12391.","productDescription":"13 p.","startPage":"148","endPage":"160","ipdsId":"IP-060340","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":471374,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/ddi.12391","text":"Publisher Index Page"},{"id":340492,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"22","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2015-11-02","publicationStatus":"PW","scienceBaseUri":"59030326e4b0e862d230f727","contributors":{"authors":[{"text":"Howeth, Jennifer G.","contributorId":63319,"corporation":false,"usgs":true,"family":"Howeth","given":"Jennifer","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":693133,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gantz, Crysta A.","contributorId":105647,"corporation":false,"usgs":true,"family":"Gantz","given":"Crysta","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":693134,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Angermeier, Paul L. 0000-0003-2864-170X biota@usgs.gov","orcid":"https://orcid.org/0000-0003-2864-170X","contributorId":166679,"corporation":false,"usgs":true,"family":"Angermeier","given":"Paul","email":"biota@usgs.gov","middleInitial":"L.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":693122,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Frimpong, Emmanuel A.","contributorId":79372,"corporation":false,"usgs":true,"family":"Frimpong","given":"Emmanuel","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":693135,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hoff, Michael H.","contributorId":111519,"corporation":false,"usgs":true,"family":"Hoff","given":"Michael","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":693136,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Keller, Reuben P.","contributorId":98637,"corporation":false,"usgs":true,"family":"Keller","given":"Reuben","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":693137,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Mandrak, Nicholas E.","contributorId":177869,"corporation":false,"usgs":false,"family":"Mandrak","given":"Nicholas","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":693138,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Marchetti, Michael P.","contributorId":191469,"corporation":false,"usgs":false,"family":"Marchetti","given":"Michael","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":693139,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Olden, Julian D.","contributorId":66951,"corporation":false,"usgs":true,"family":"Olden","given":"Julian D.","affiliations":[],"preferred":false,"id":693140,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Romagosa, Christina M.","contributorId":39661,"corporation":false,"usgs":true,"family":"Romagosa","given":"Christina M.","affiliations":[],"preferred":false,"id":693141,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Lodge, David M.","contributorId":76622,"corporation":false,"usgs":false,"family":"Lodge","given":"David","email":"","middleInitial":"M.","affiliations":[{"id":16905,"text":"University of Notre Dame, Dept. of Biological Sciences, Notre Dame, IN, 46556, USA","active":true,"usgs":false}],"preferred":false,"id":693142,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70185995,"text":"70185995 - 2016 - A review of single-sample-based models and other approaches for radiocarbon dating of dissolved inorganic carbon in groundwater","interactions":[],"lastModifiedDate":"2017-03-30T11:21:50","indexId":"70185995","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1431,"text":"Earth-Science Reviews","active":true,"publicationSubtype":{"id":10}},"title":"A review of single-sample-based models and other approaches for radiocarbon dating of dissolved inorganic carbon in groundwater","docAbstract":"Numerous methods have been proposed to estimate the pre-nuclear-detonation 14C content of dissolved inorganic carbon (DIC) recharged to groundwater that has been corrected/adjusted for geochemical processes in the absence of radioactive decay (14C0) - a quantity that is essential for estimation of radiocarbon age of DIC in groundwater. The models/approaches most commonly used are grouped as follows: (1) single-sample-based models, (2) a statistical approach based on the observed (curved) relationship between 14C and δ13C data for the aquifer, and (3) the geochemical mass-balance approach that constructs adjustment models accounting for all the geochemical reactions known to occur along a groundwater flow path. This review discusses first the geochemical processes behind each of the single-sample-based models, followed by discussions of the statistical approach and the geochemical mass-balance approach. Finally, the applications, advantages and limitations of the three groups of models/approaches are discussed.
The single-sample-based models constitute the prevailing use of 14C data in hydrogeology and hydrological studies. This is in part because the models are applied to an individual water sample to estimate the 14C age, therefore the measurement data are easily available. These models have been shown to provide realistic radiocarbon ages in many studies. However, they usually are limited to simple carbonate aquifers and selection of model may have significant effects on 14C0 often resulting in a wide range of estimates of 14C ages.
Of the single-sample-based models, four are recommended for the estimation of 14C0 of DIC in groundwater: Pearson's model, (Ingerson and Pearson, 1964; Pearson and White, 1967), Han & Plummer's model (Han and Plummer, 2013), the IAEA model (Gonfiantini, 1972; Salem et al., 1980), and Oeschger's model (Geyh, 2000). These four models include all processes considered in single-sample-based models, and can be used in different ranges of 13C values.
In contrast to the single-sample-based models, the extended Gonfiantini & Zuppi model (Gonfiantini and Zuppi, 2003; Han et al., 2014) is a statistical approach. This approach can be used to estimate 14C ages when a curved relationship between the 14C and 13C values of the DIC data is observed. In addition to estimation of groundwater ages, the relationship between 14C and δ13C data can be used to interpret hydrogeological characteristics of the aquifer, e.g. estimating apparent rates of geochemical reactions and revealing the complexity of the geochemical environment, and identify samples that are not affected by the same set of reactions/processes as the rest of the dataset. The investigated water samples may have a wide range of ages, and for waters with very low values of 14C, the model based on statistics may give more reliable age estimates than those obtained from single-sample-based models. In the extended Gonfiantini & Zuppi model, a representative system-wide value of the initial 14C content is derived from the 14C and δ13C data of DIC and can differ from that used in single-sample-based models. Therefore, the extended Gonfiantini & Zuppi model usually avoids the effect of modern water components which might retain ‘bomb’ pulse signatures.
The geochemical mass-balance approach constructs an adjustment model that accounts for all the geochemical reactions known to occur along an aquifer flow path (Plummer et al., 1983; Wigley et al., 1978; Plummer et al., 1994; Plummer and Glynn, 2013), and includes, in addition to DIC, dissolved organic carbon (DOC) and methane (CH4). If sufficient chemical, mineralogical and isotopic data are available, the geochemical mass-balance method can yield the most accurate estimates of the adjusted radiocarbon age. The main limitation of this approach is that complete information is necessary on chemical, mineralogical and isotopic data and these data are often limited.
Failure to recognize the limitations and underlying assumptions on which the various models and approaches are based can result in a wide range of estimates of 14C0 and limit the usefulness of radiocarbon as a dating tool for groundwater. In each of the three generalized approaches (single-sample-based models, statistical approach, and geochemical mass-balance approach), successful application depends on scrutiny of the isotopic (14C and 13C) and chemical data to conceptualize the reactions and processes that affect the 14C content of DIC in aquifers. The recently developed graphical analysis method is shown to aid in determining which approach is most appropriate for the isotopic and chemical data from a groundwater system.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.earscirev.2015.11.004","usgsCitation":"Han, L.F., and Plummer, N., 2016, A review of single-sample-based models and other approaches for radiocarbon dating of dissolved inorganic carbon in groundwater: Earth-Science Reviews, v. 152, p. 119-142, https://doi.org/10.1016/j.earscirev.2015.11.004.","productDescription":"24 p.","startPage":"119","endPage":"142","ipdsId":"IP-068009","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":338803,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"152","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58de194fe4b02ff32c699ca7","contributors":{"authors":[{"text":"Han, L. F","contributorId":190101,"corporation":false,"usgs":false,"family":"Han","given":"L.","email":"","middleInitial":"F","affiliations":[],"preferred":false,"id":687282,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Plummer, Niel 0000-0002-4020-1013 nplummer@usgs.gov","orcid":"https://orcid.org/0000-0002-4020-1013","contributorId":190100,"corporation":false,"usgs":true,"family":"Plummer","given":"Niel","email":"nplummer@usgs.gov","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":687281,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70179689,"text":"70179689 - 2016 - Watershed-scale changes in terrestrial nitrogen cycling during a period of decreased atmospheric nitrate and sulfur deposition","interactions":[],"lastModifiedDate":"2018-03-30T12:49:09","indexId":"70179689","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":924,"text":"Atmospheric Environment","active":true,"publicationSubtype":{"id":10}},"title":"Watershed-scale changes in terrestrial nitrogen cycling during a period of decreased atmospheric nitrate and sulfur deposition","docAbstract":"Recent reports suggest that decreases in atmospheric nitrogen (N) deposition throughout Europe and North America may have resulted in declining nitrate export in surface waters in recent decades, yet it is unknown if and how terrestrial N cycling was affected. During a period of decreased atmospheric N deposition, we assessed changes in forest N cycling by evaluating trends in tree-ring δ15N values (between 1980 and 2010; n = 20 trees per watershed), stream nitrate yields (between 2000 and 2011), and retention of atmospherically-deposited N (between 2000 and 2011) in the North and South Tributaries (North and South, respectively) of Buck Creek in the Adirondack Mountains, USA. We hypothesized that tree-ring δ15N values would decline following decreases in atmospheric N deposition (after approximately 1995), and that trends in stream nitrate export and retention of atmospherically deposited N would mirror changes in tree-ring δ15N values. Three of the six sampled tree species and the majority of individual trees showed declining linear trends in δ15N for the period 1980–2010; only two individual trees showed increasing trends in δ15N values. From 1980 to 2010, trees in the watersheds of both tributaries displayed long-term declines in tree-ring δ15N values at the watershed scale (R = −0.35 and p = 0.001 in the North and R = −0.37 and p <0.001 in the South). The decreasing δ15N trend in the North was associated with declining stream nitrate concentrations (−0.009 mg N L−1 yr−1, p = 0.02), but no change in the retention of atmospherically deposited N was observed. In contrast, nitrate yields in the South did not exhibit a trend, and the watershed became less retentive of atmospherically deposited N (−7.3% yr−1, p < 0.001). Our δ15N results indicate a change in terrestrial N availability in both watersheds prior to decreases in atmospheric N deposition, suggesting that decreased atmospheric N deposition was not the sole driver of tree-ring δ15N values at these sites. Other factors, such as decreased sulfur deposition, disturbance, long-term successional trends, and/or increasing atmospheric CO2concentrations, may also influence trends in tree-ring δ15N values. Furthermore, declines in terrestrial N availability inferred from tree-ring δ15N values do not always correspond with decreased stream nitrate export or increased retention of atmospherically deposited N.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.atmosenv.2016.08.055","usgsCitation":"Sabo, R.D., Scanga, S.E., Lawrence, G.B., Nelson, D.M., Eshleman, K., Zabala, G.A., Alinea, A.A., and Schirmer, C.D., 2016, Watershed-scale changes in terrestrial nitrogen cycling during a period of decreased atmospheric nitrate and sulfur deposition: Atmospheric Environment, v. 146, p. 271-279, https://doi.org/10.1016/j.atmosenv.2016.08.055.","productDescription":"9 p.","startPage":"271","endPage":"279","ipdsId":"IP-073355","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":471363,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.atmosenv.2016.08.055","text":"Publisher Index Page"},{"id":352815,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"146","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afeea59e4b0da30c1bfc603","contributors":{"authors":[{"text":"Sabo, Robert D. 0000-0001-8713-7699","orcid":"https://orcid.org/0000-0001-8713-7699","contributorId":178226,"corporation":false,"usgs":false,"family":"Sabo","given":"Robert","email":"","middleInitial":"D.","affiliations":[{"id":13479,"text":"University of Maryland Center for Environmental Science, Appalachian Laboratory, 301 Braddock Road, Frostburg, Maryland","active":true,"usgs":false}],"preferred":false,"id":658251,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Scanga, Sara E. 0000-0003-4022-4167","orcid":"https://orcid.org/0000-0003-4022-4167","contributorId":178227,"corporation":false,"usgs":false,"family":"Scanga","given":"Sara","email":"","middleInitial":"E.","affiliations":[{"id":28019,"text":"Deptartment of Biology, Utica College","active":true,"usgs":false}],"preferred":false,"id":658252,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":658250,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nelson, David M.","contributorId":175098,"corporation":false,"usgs":false,"family":"Nelson","given":"David","email":"","middleInitial":"M.","affiliations":[{"id":13479,"text":"University of Maryland Center for Environmental Science, Appalachian Laboratory, 301 Braddock Road, Frostburg, Maryland","active":true,"usgs":false}],"preferred":false,"id":658253,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Eshleman, Keith N.","contributorId":178228,"corporation":false,"usgs":false,"family":"Eshleman","given":"Keith N.","affiliations":[{"id":13479,"text":"University of Maryland Center for Environmental Science, Appalachian Laboratory, 301 Braddock Road, Frostburg, Maryland","active":true,"usgs":false}],"preferred":false,"id":658254,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Zabala, Gabriel A.","contributorId":178229,"corporation":false,"usgs":false,"family":"Zabala","given":"Gabriel","email":"","middleInitial":"A.","affiliations":[{"id":28019,"text":"Deptartment of Biology, Utica College","active":true,"usgs":false}],"preferred":false,"id":658255,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Alinea, Alexandria A.","contributorId":178230,"corporation":false,"usgs":false,"family":"Alinea","given":"Alexandria","email":"","middleInitial":"A.","affiliations":[{"id":28019,"text":"Deptartment of Biology, Utica College","active":true,"usgs":false}],"preferred":false,"id":658256,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Schirmer, Charles D.","contributorId":178231,"corporation":false,"usgs":false,"family":"Schirmer","given":"Charles","email":"","middleInitial":"D.","affiliations":[{"id":27852,"text":"State University of New York, Syracuse","active":true,"usgs":false}],"preferred":false,"id":658257,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70187254,"text":"70187254 - 2016 - Effect of morphological fin curl on the swimming performance and station-holding ability of juvenile shovelnose sturgeon","interactions":[],"lastModifiedDate":"2017-04-27T11:23:47","indexId":"70187254","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Effect of morphological fin curl on the swimming performance and station-holding ability of juvenile shovelnose sturgeon","docAbstract":"We assessed the effect of fin-curl on the swimming and station-holding ability of juvenile shovelnose sturgeon Scaphirhynchus platorynchus (mean fork length = 17 cm; mean weight = 16 g; n = 21) using a critical swimming speed test performed in a small swim chamber (90 L) at 20°C. We quantified fin-curl severity using the pectoral fin index. Results showed a positive relationship between pectoral fin index and critical swimming speed indicative of reduced swimming performance displayed by fish afflicted with a pectoral fin index < 8%. Fin-curl severity, however, did not affect the station-holding ability of individual fish. Rather, fish affected with severe fin-curl were likely unable to use their pectoral fins to position their body adequately in the water column, which led to the early onset of fatigue. Results generated from this study should serve as an important consideration for future stocking practices.
","language":"English","publisher":"U.S. Fish and Wildlife Service","doi":"10.3996/092015-JFWM-087","usgsCitation":"Deslauriers, D., Johnston, R., and Chipps, S.R., 2016, Effect of morphological fin curl on the swimming performance and station-holding ability of juvenile shovelnose sturgeon: Journal of Fish and Wildlife Management, v. 7, no. 1, p. 198-204, https://doi.org/10.3996/092015-JFWM-087.","productDescription":"7 p.","startPage":"198","endPage":"204","ipdsId":"IP-064726","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":488616,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/092015-jfwm-087","text":"Publisher Index Page"},{"id":340501,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-03-01","publicationStatus":"PW","scienceBaseUri":"59030326e4b0e862d230f72d","contributors":{"authors":[{"text":"Deslauriers, David","contributorId":187586,"corporation":false,"usgs":false,"family":"Deslauriers","given":"David","email":"","affiliations":[],"preferred":false,"id":693112,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnston, Ryan","contributorId":191482,"corporation":false,"usgs":false,"family":"Johnston","given":"Ryan","email":"","affiliations":[],"preferred":false,"id":693189,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chipps, Steven R. 0000-0001-6511-7582 steve_chipps@usgs.gov","orcid":"https://orcid.org/0000-0001-6511-7582","contributorId":2243,"corporation":false,"usgs":true,"family":"Chipps","given":"Steven","email":"steve_chipps@usgs.gov","middleInitial":"R.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":693190,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70187253,"text":"70187253 - 2016 - Lethal thermal maxima for age-0 pallid and shovelnose sturgeon: Implications for shallow water habitat restoration","interactions":[],"lastModifiedDate":"2017-04-27T11:08:53","indexId":"70187253","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3301,"text":"River Research and Applications","active":true,"publicationSubtype":{"id":10}},"title":"Lethal thermal maxima for age-0 pallid and shovelnose sturgeon: Implications for shallow water habitat restoration","docAbstract":"We evaluated temperature tolerance in age-0 pallid and shovelnose sturgeon (Scaphirhynchus albus and Scaphirhynchus platorynchus), two species that occur sympatrically in the Missouri and Mississippi Rivers. Fish (0.04–18 g) were acclimated to water temperatures of 13, 18 or 24 °C to quantify temperatures associated with lethal thermal maxima (LTM). The results show that no difference in thermal tolerance existed between the two sturgeon species, but that LTM was significantly related to body mass and acclimation temperature. Multiple linear regression analysis was used to estimate LTM, and outputs from the model were compared with water temperatures measured in the shallow water habitat (SWH) of the Missouri River. Observed SWH temperatures were not found to yield LTM conditions. The model developed here is to serve as a general guideline in the development of future SWH.
","language":"English","publisher":"Wiley","doi":"10.1002/rra.3022","usgsCitation":"Deslauriers, D., Heironimus, L.B., and Chipps, S.R., 2016, Lethal thermal maxima for age-0 pallid and shovelnose sturgeon: Implications for shallow water habitat restoration: River Research and Applications, v. 32, no. 9, p. 1872-1878, https://doi.org/10.1002/rra.3022.","productDescription":"7 p.","startPage":"1872","endPage":"1878","ipdsId":"IP-066780","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":340497,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Mississippi river, Missouri river","volume":"32","issue":"9","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-04-13","publicationStatus":"PW","scienceBaseUri":"59030326e4b0e862d230f72f","contributors":{"authors":[{"text":"Deslauriers, David","contributorId":187586,"corporation":false,"usgs":false,"family":"Deslauriers","given":"David","email":"","affiliations":[],"preferred":false,"id":693111,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Heironimus, Laura B.","contributorId":187587,"corporation":false,"usgs":false,"family":"Heironimus","given":"Laura","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":693177,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chipps, Steven R. 0000-0001-6511-7582 steve_chipps@usgs.gov","orcid":"https://orcid.org/0000-0001-6511-7582","contributorId":2243,"corporation":false,"usgs":true,"family":"Chipps","given":"Steven","email":"steve_chipps@usgs.gov","middleInitial":"R.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":693178,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70189206,"text":"70189206 - 2016 - Implications of the methodological choices for hydrologic portrayals of climate change over the contiguous United States: Statistically downscaled forcing data and hydrologic models","interactions":[],"lastModifiedDate":"2017-07-05T16:25:03","indexId":"70189206","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2344,"text":"Journal of Hydrometeorology","active":true,"publicationSubtype":{"id":10}},"title":"Implications of the methodological choices for hydrologic portrayals of climate change over the contiguous United States: Statistically downscaled forcing data and hydrologic models","docAbstract":"Continental-domain assessments of climate change impacts on water resources typically rely on statistically downscaled climate model outputs to force hydrologic models at a finer spatial resolution. This study examines the effects of four statistical downscaling methods [bias-corrected constructed analog (BCCA), bias-corrected spatial disaggregation applied at daily (BCSDd) and monthly scales (BCSDm), and asynchronous regression (AR)] on retrospective hydrologic simulations using three hydrologic models with their default parameters (the Community Land Model, version 4.0; the Variable Infiltration Capacity model, version 4.1.2; and the Precipitation–Runoff Modeling System, version 3.0.4) over the contiguous United States (CONUS). Biases of hydrologic simulations forced by statistically downscaled climate data relative to the simulation with observation-based gridded data are presented. Each statistical downscaling method produces different meteorological portrayals including precipitation amount, wet-day frequency, and the energy input (i.e., shortwave radiation), and their interplay affects estimations of precipitation partitioning between evapotranspiration and runoff, extreme runoff, and hydrologic states (i.e., snow and soil moisture). The analyses show that BCCA underestimates annual precipitation by as much as −250 mm, leading to unreasonable hydrologic portrayals over the CONUS for all models. Although the other three statistical downscaling methods produce a comparable precipitation bias ranging from −10 to 8 mm across the CONUS, BCSDd severely overestimates the wet-day fraction by up to 0.25, leading to different precipitation partitioning compared to the simulations with other downscaled data. Overall, the choice of downscaling method contributes to less spread in runoff estimates (by a factor of 1.5–3) than the choice of hydrologic model with use of the default parameters if BCCA is excluded.
","language":"English","publisher":"American Meteorological Society","doi":"10.1175/JHM-D-14-0187.1","usgsCitation":"Mizukami, N., Clark, M.P., Gutmann, E.D., Mendoza, P.A., Newman, A.J., Nijssen, B., Livneh, B., Hay, L.E., Arnold, J.R., and Brekke, L.D., 2016, Implications of the methodological choices for hydrologic portrayals of climate change over the contiguous United States: Statistically downscaled forcing data and hydrologic models: Journal of Hydrometeorology, v. 17, p. 75-98, https://doi.org/10.1175/JHM-D-14-0187.1.","productDescription":"24 p.","startPage":"75","endPage":"98","ipdsId":"IP-064865","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":471387,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1175/jhm-d-14-0187.1","text":"Publisher Index Page"},{"id":343367,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"17","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-17","publicationStatus":"PW","scienceBaseUri":"595dfab0e4b0d1f9f056a763","contributors":{"authors":[{"text":"Mizukami, Naoki","contributorId":178120,"corporation":false,"usgs":false,"family":"Mizukami","given":"Naoki","email":"","affiliations":[],"preferred":false,"id":703484,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Clark, Martyn P.","contributorId":194183,"corporation":false,"usgs":false,"family":"Clark","given":"Martyn","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":703485,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gutmann, Ethan D.","contributorId":194227,"corporation":false,"usgs":false,"family":"Gutmann","given":"Ethan","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":703486,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mendoza, Pablo A.","contributorId":194228,"corporation":false,"usgs":false,"family":"Mendoza","given":"Pablo","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":703487,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Newman, Andrew J.","contributorId":194229,"corporation":false,"usgs":false,"family":"Newman","given":"Andrew","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":703488,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Nijssen, Bart","contributorId":178123,"corporation":false,"usgs":false,"family":"Nijssen","given":"Bart","email":"","affiliations":[],"preferred":false,"id":703490,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Livneh, Ben","contributorId":145804,"corporation":false,"usgs":false,"family":"Livneh","given":"Ben","email":"","affiliations":[{"id":12641,"text":"NOAA NMFS","active":true,"usgs":false}],"preferred":false,"id":703491,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Hay, Lauren E. 0000-0003-3763-4595 lhay@usgs.gov","orcid":"https://orcid.org/0000-0003-3763-4595","contributorId":1287,"corporation":false,"usgs":true,"family":"Hay","given":"Lauren","email":"lhay@usgs.gov","middleInitial":"E.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":703502,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Arnold, Jeffrey R.","contributorId":178125,"corporation":false,"usgs":false,"family":"Arnold","given":"Jeffrey","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":703492,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Brekke, Levi D.","contributorId":6776,"corporation":false,"usgs":true,"family":"Brekke","given":"Levi","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":703493,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70187148,"text":"70187148 - 2016 - An evaluation of methods for estimating decadal stream loads","interactions":[],"lastModifiedDate":"2018-03-15T10:26:32","indexId":"70187148","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"An evaluation of methods for estimating decadal stream loads","docAbstract":"Effective management of water resources requires accurate information on the mass, or load of water-quality constituents transported from upstream watersheds to downstream receiving waters. Despite this need, no single method has been shown to consistently provide accurate load estimates among different water-quality constituents, sampling sites, and sampling regimes. We evaluate the accuracy of several load estimation methods across a broad range of sampling and environmental conditions. This analysis uses random sub-samples drawn from temporally-dense data sets of total nitrogen, total phosphorus, nitrate, and suspended-sediment concentration, and includes measurements of specific conductance which was used as a surrogate for dissolved solids concentration. Methods considered include linear interpolation and ratio estimators, regression-based methods historically employed by the U.S. Geological Survey, and newer flexible techniques including Weighted Regressions on Time, Season, and Discharge (WRTDS) and a generalized non-linear additive model. No single method is identified to have the greatest accuracy across all constituents, sites, and sampling scenarios. Most methods provide accurate estimates of specific conductance (used as a surrogate for total dissolved solids or specific major ions) and total nitrogen – lower accuracy is observed for the estimation of nitrate, total phosphorus and suspended sediment loads. Methods that allow for flexibility in the relation between concentration and flow conditions, specifically Beale’s ratio estimator and WRTDS, exhibit greater estimation accuracy and lower bias. Evaluation of methods across simulated sampling scenarios indicate that (1) high-flow sampling is necessary to produce accurate load estimates, (2) extrapolation of sample data through time or across more extreme flow conditions reduces load estimate accuracy, and (3) WRTDS and methods that use a Kalman filter or smoothing to correct for departures between individual modeled and observed values benefit most from more frequent water-quality sampling.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2016.08.059","usgsCitation":"Lee, C.J., Hirsch, R.M., Schwarz, G., Holtschlag, D.J., Preston, S.D., Crawford, C.G., and Vecchia, A.V., 2016, An evaluation of methods for estimating decadal stream loads: Journal of Hydrology, v. 542, p. 185-203, https://doi.org/10.1016/j.jhydrol.2016.08.059.","productDescription":"19 p.","startPage":"185","endPage":"203","ipdsId":"IP-070870","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":471371,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jhydrol.2016.08.059","text":"Publisher Index Page"},{"id":340405,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"542","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59006063e4b0e85db3a5ddd9","contributors":{"authors":[{"text":"Lee, Casey J. 0000-0002-5753-2038 cjlee@usgs.gov","orcid":"https://orcid.org/0000-0002-5753-2038","contributorId":2627,"corporation":false,"usgs":true,"family":"Lee","given":"Casey","email":"cjlee@usgs.gov","middleInitial":"J.","affiliations":[{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":37786,"text":"WMA - 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Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":692775,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Crawford, Charles G. 0000-0003-1653-7841 cgcrawfo@usgs.gov","orcid":"https://orcid.org/0000-0003-1653-7841","contributorId":1064,"corporation":false,"usgs":true,"family":"Crawford","given":"Charles","email":"cgcrawfo@usgs.gov","middleInitial":"G.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":692776,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Vecchia, Aldo V. 0000-0002-2661-4401 avecchia@usgs.gov","orcid":"https://orcid.org/0000-0002-2661-4401","contributorId":1173,"corporation":false,"usgs":true,"family":"Vecchia","given":"Aldo","email":"avecchia@usgs.gov","middleInitial":"V.","affiliations":[{"id":478,"text":"North Dakota Water Science Center","active":true,"usgs":true},{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":692777,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70187207,"text":"70187207 - 2016 - Age, growth and fall diet of channel catfish in Cheat Lake, West Virginia","interactions":[],"lastModifiedDate":"2017-04-26T12:41:20","indexId":"70187207","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Age, growth and fall diet of channel catfish in Cheat Lake, West Virginia","docAbstract":"Acidification has historically impaired Cheat Lake's fish community, but recent mitigation efforts within the Cheat River watershed have improved water quality and species richness. Presently, channel catfish Ictalurus punctatus are abundant and attain desirable sizes for anglers. We evaluated the age, growth, and fall diet of the population. We collected a sample of 155 channel catfish from Cheat Lake from 5 August to 4 December 2014, a subset of which we aged (n = 148) using lapillus otoliths. We fit four growth models (von Bertalanffy, logistic, Gompertz, and power) to length-at-age data and compared models using an information theoretic approach. We collected fall diets from 55 fish sampled from 13 October to 4 December 2014. Total lengths of individuals in the sample ranged from 154 to 721 mm and ages ranged from 2 to 19 y. We AICc-selected the von Bertalanffy growth model as the best approximating model, and the power and Gompertz models also had considerable support. Diets were numerically dominated by Diptera larvae, specifically Chironomidae and Chaoboridae, while 39% of stomachs contained terrestrial food items. This study provides baseline data for management of Cheat Lake's channel catfish population. Further, this study fills a knowledge gap in the scientific literature on channel catfish, because few previously published studies have examined the population ecology of channel catfish in the Central Appalachian region.
","language":"English","publisher":"U.S. Fish and Wildlife Service","doi":"10.3996/092015-JFWM-091","usgsCitation":"Hilling, C., Welsh, S.A., and Smith, D.M., 2016, Age, growth and fall diet of channel catfish in Cheat Lake, West Virginia: Journal of Fish and Wildlife Management, v. 7, no. 2, p. 304-314, https://doi.org/10.3996/092015-JFWM-091.","productDescription":"11 p.","startPage":"304","endPage":"314","ipdsId":"IP-074154","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":471372,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/092015-jfwm-091","text":"Publisher Index Page"},{"id":340456,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"West Virginia","otherGeospatial":"Cheat Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": 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Stuart A. 0000-0003-0362-054X swelsh@usgs.gov","orcid":"https://orcid.org/0000-0003-0362-054X","contributorId":1483,"corporation":false,"usgs":true,"family":"Welsh","given":"Stuart","email":"swelsh@usgs.gov","middleInitial":"A.","affiliations":[{"id":205,"text":"Cooperative Research Units","active":false,"usgs":true}],"preferred":false,"id":693035,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, Dustin M.","contributorId":171829,"corporation":false,"usgs":false,"family":"Smith","given":"Dustin","email":"","middleInitial":"M.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":693036,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70187360,"text":"70187360 - 2016 - Fidelity and persistence of Ring-billed (Larus delawarensis) and Herring (Larus argentatus) gulls to wintering sites","interactions":[],"lastModifiedDate":"2017-05-01T13:09:34","indexId":"70187360","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3731,"text":"Waterbirds","onlineIssn":"19385390","printIssn":"15244695","active":true,"publicationSubtype":{"id":10}},"title":"Fidelity and persistence of Ring-billed (Larus delawarensis) and Herring (Larus argentatus) gulls to wintering sites","docAbstract":"While the breeding ecology of gulls (Laridae) has been well studied, their movements and spatial organization during the non-breeding season is poorly understood. The seasonal movements, winter-site fidelity, and site persistence of Ring-billed (Larus delawarensis) and Herring (L. argentatus) gulls to wintering areas were studied from 2008–2012. Satellite transmitters were deployed on Ring-billed Gulls (n = 21) and Herring Gulls (n = 14). Ten Ring-billed and six Herring gulls were tracked over multiple winters and > 300 wing-tagged Ring-billed Gulls were followed to determine winter-site fidelity and persistence. Home range overlap for individuals between years ranged between 0–1.0 (95% minimum convex polygon) and 0.31–0.79 (kernel utilization distributions). Ringbilled and Herring gulls remained at local wintering sites during the non-breeding season from 20–167 days and 74–161 days, respectively. The probability of a tagged Ring-billed Gull returning to the same site in subsequent winters was high; conversely, there was a low probability of a Ring-billed Gull returning to a different site. Ring-billed and Herring gulls exhibited high winter-site fidelity, but exhibited variable site persistence during the winter season, leading to a high probability of encountering the same individuals in subsequent winters.
","language":"English","publisher":"The Waterbird Society","doi":"10.1675/063.039.sp120","usgsCitation":"Clark, D.E., Koenen, K.K., Whitney, J.J., MacKenzie, K.G., and DeStefano, S., 2016, Fidelity and persistence of Ring-billed (Larus delawarensis) and Herring (Larus argentatus) gulls to wintering sites: Waterbirds, v. 39, no. SP1, p. 220-234, https://doi.org/10.1675/063.039.sp120.","productDescription":"15 p.","startPage":"220","endPage":"234","ipdsId":"IP-054563","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":340677,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"39","issue":"SP1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59084928e4b0fc4e448ffd54","contributors":{"authors":[{"text":"Clark, Daniel E.","contributorId":166686,"corporation":false,"usgs":false,"family":"Clark","given":"Daniel","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":693767,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Koenen, Kiana K. G.","contributorId":34313,"corporation":false,"usgs":true,"family":"Koenen","given":"Kiana","email":"","middleInitial":"K. G.","affiliations":[],"preferred":false,"id":693768,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Whitney, Jillian J.","contributorId":166687,"corporation":false,"usgs":false,"family":"Whitney","given":"Jillian","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":693769,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"MacKenzie, Kenneth G.","contributorId":166688,"corporation":false,"usgs":false,"family":"MacKenzie","given":"Kenneth","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":693770,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"DeStefano, Stephen 0000-0003-2472-8373 destef@usgs.gov","orcid":"https://orcid.org/0000-0003-2472-8373","contributorId":166706,"corporation":false,"usgs":true,"family":"DeStefano","given":"Stephen","email":"destef@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":693609,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70173765,"text":"70173765 - 2016 - Consequences of seasonal variation in reservoir water level for predatory fishes: linking visual foraging and prey densities","interactions":[],"lastModifiedDate":"2016-06-21T15:53:42","indexId":"70173765","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1169,"text":"Canadian Journal of Fisheries and Aquatic Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Consequences of seasonal variation in reservoir water level for predatory fishes: linking visual foraging and prey densities","docAbstract":"In reservoirs, seasonal drawdown can alter the physical environment and may influence predatory fish performance. We investigated the performance of lake trout (Salvelinus namaycush) in a western reservoir by coupling field measurements with visual foraging and bioenergetic models at four distinct states (early summer, mid-summer, late summer, and fall). The models suggested that lake trout prey, juvenile kokanee (Oncorhynchus nerka), are limited seasonally by suitable temperature and dissolved oxygen. Accordingly, prey densities were greatest in late summer when reservoir volume was lowest and fish were concentrated by stratification. Prey encounter rates (up to 68 fish·day−1) and predator consumption are also predicted to be greatest during late summer. However, our models suggested that turbidity negatively correlates with prey detection and consumption across reservoir states. Under the most turbid conditions, lake trout did not meet physiological demands; however, during less turbid periods, predator consumption reached maximum bioenergetic efficiency. Overall, our findings demonstrate that rapid reservoir fluctuations and associated abiotic conditions can influence predator–prey interactions, and our models describe the potential impacts of water level fluctuation on valuable sport fishes.
","language":"English","publisher":"NRC Press","doi":"10.1139/cjfas-2015-0008","usgsCitation":"Klobucar, S., and Budy, P., 2016, Consequences of seasonal variation in reservoir water level for predatory fishes: linking visual foraging and prey densities: Canadian Journal of Fisheries and Aquatic Sciences, v. 73, no. 1, p. 53-64, https://doi.org/10.1139/cjfas-2015-0008.","productDescription":"12 p.","startPage":"53","endPage":"64","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-058204","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":324165,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"73","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"576a6534e4b07657d1a11d44","contributors":{"authors":[{"text":"Klobucar, Stephen L.","contributorId":172291,"corporation":false,"usgs":false,"family":"Klobucar","given":"Stephen L.","affiliations":[],"preferred":false,"id":640155,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Budy, Phaedra E. 0000-0002-9918-1678 pbudy@usgs.gov","orcid":"https://orcid.org/0000-0002-9918-1678","contributorId":140028,"corporation":false,"usgs":true,"family":"Budy","given":"Phaedra","email":"pbudy@usgs.gov","middleInitial":"E.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":638095,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70187720,"text":"70187720 - 2016 - Rapid environmental change drives increased land use by an Arctic marine predator","interactions":[],"lastModifiedDate":"2017-05-18T10:32:17","indexId":"70187720","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Rapid environmental change drives increased land use by an Arctic marine predator","docAbstract":"In the Arctic Ocean’s southern Beaufort Sea (SB), the length of the sea ice melt season (i.e., period between the onset of sea ice break-up in summer and freeze-up in fall) has increased substantially since the late 1990s. Historically, polar bears (Ursus maritimus) of the SB have mostly remained on the sea ice year-round (except for those that came ashore to den), but recent changes in the extent and phenology of sea ice habitat have coincided with evidence that use of terrestrial habitat is increasing. We characterized the spatial behavior of polar bears spending summer and fall on land along Alaska’s north coast to better understand the nexus between rapid environmental change and increased use of terrestrial habitat. We found that the percentage of radiocollared adult females from the SB subpopulation coming ashore has tripled over 15 years. Moreover, we detected trends of earlier arrival on shore, increased length of stay, and later departure back to sea ice, all of which were related to declines in the availability of sea ice habitat over the continental shelf and changes to sea ice phenology. Since the late 1990s, the mean duration of the open-water season in the SB increased by 36 days, and the mean length of stay on shore increased by 31 days. While on shore, the distribution of polar bears was influenced by the availability of scavenge subsidies in the form of subsistence-harvested bowhead whale (Balaena mysticetus) remains aggregated at sites along the coast. The declining spatio-temporal availability of sea ice habitat and increased availability of human-provisioned resources are likely to result in increased use of land. Increased residency on land is cause for concern given that, while there, bears may be exposed to a greater array of risk factors including those associated with increased human activities.
","language":"English","publisher":"PLoS","doi":"10.1371/journal.pone.0155932","usgsCitation":"Atwood, T.C., Peacock, E.L., McKinney, M.A., Lillie, K., Wilson, R.H., Douglas, D.C., Miller, S., and Terletzky, P., 2016, Rapid environmental change drives increased land use by an Arctic marine predator: PLoS ONE, v. 6, no. 11, Article e0155932; 18 p., https://doi.org/10.1371/journal.pone.0155932.","productDescription":"Article e0155932; 18 p.","ipdsId":"IP-072257","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":471388,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0155932","text":"Publisher Index Page"},{"id":341326,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Alaska, Yukon","otherGeospatial":"Southern Beaufort Sea","volume":"6","issue":"11","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-06-01","publicationStatus":"PW","scienceBaseUri":"591abe37e4b0a7fdb43c8bf7","contributors":{"authors":[{"text":"Atwood, Todd C. 0000-0002-1971-3110 tatwood@usgs.gov","orcid":"https://orcid.org/0000-0002-1971-3110","contributorId":4368,"corporation":false,"usgs":true,"family":"Atwood","given":"Todd","email":"tatwood@usgs.gov","middleInitial":"C.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":695266,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Peacock, Elizabeth L. 0000-0001-7279-0329 lpeacock@usgs.gov","orcid":"https://orcid.org/0000-0001-7279-0329","contributorId":3361,"corporation":false,"usgs":true,"family":"Peacock","given":"Elizabeth","email":"lpeacock@usgs.gov","middleInitial":"L.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":false,"id":695552,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McKinney, Melissa A.","contributorId":11496,"corporation":false,"usgs":false,"family":"McKinney","given":"Melissa","email":"","middleInitial":"A.","affiliations":[{"id":6619,"text":"University of Connecticutt","active":true,"usgs":false}],"preferred":false,"id":695267,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lillie, Kate","contributorId":148213,"corporation":false,"usgs":false,"family":"Lillie","given":"Kate","affiliations":[{"id":17117,"text":"Department of Wildland Resources, Utah State University, Logan","active":true,"usgs":false}],"preferred":false,"id":695268,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wilson, Ryan H. 0000-0001-7740-7771","orcid":"https://orcid.org/0000-0001-7740-7771","contributorId":130989,"corporation":false,"usgs":false,"family":"Wilson","given":"Ryan","email":"","middleInitial":"H.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":695269,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Douglas, David C. 0000-0003-0186-1104 ddouglas@usgs.gov","orcid":"https://orcid.org/0000-0003-0186-1104","contributorId":2388,"corporation":false,"usgs":true,"family":"Douglas","given":"David","email":"ddouglas@usgs.gov","middleInitial":"C.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":695270,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Terletzky, Pat","contributorId":192063,"corporation":false,"usgs":false,"family":"Terletzky","given":"Pat","affiliations":[{"id":12682,"text":"Utah State University, Logan, UT","active":true,"usgs":false}],"preferred":false,"id":695272,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Miller, Susanne","contributorId":50955,"corporation":false,"usgs":false,"family":"Miller","given":"Susanne","email":"","affiliations":[{"id":13235,"text":"U.S. Fish and Wildlife Service, Marine Mammals Management","active":true,"usgs":false}],"preferred":false,"id":695271,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70169860,"text":"70169860 - 2016 - Status and trends in the Lake Superior fish community, 2015","interactions":[],"lastModifiedDate":"2018-03-28T13:37:53","indexId":"70169860","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":9,"text":"Other Report"},"title":"Status and trends in the Lake Superior fish community, 2015","docAbstract":"In 2015, the Lake Superior fish community was sampled with daytime bottom trawls at 76 nearshore and 33 offshore stations. Spring and summer water temperatures in 2015 were colder than average, but warmer than that observed in 2014. In the nearshore zone, a total of 11,882 individuals from 22 species or morphotypes were collected. Nearshore lakewide mean biomass was 1.8 kg/ha, which was near the lowest biomass on record for this survey since it began in 1978. In the offshore zone, a total 12,433 individuals from 8 species or morphotypes were collected lakewide. Offshore lakewide mean biomass was 5.9 kg/ha. The mean of the four previous years was 7.1 kg/ha. The abundance of age-1 Cisco was 14.3 fish/ha which was similar to that measured in 2009. We collected larval Coregonus in surface trawls at 94 locations and estimated a nearshore lakewide average density of 1,459 fish/ha which was nearly twice that measured in 2014.
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0000-0001-5256-9539 mvinson@usgs.gov","orcid":"https://orcid.org/0000-0001-5256-9539","contributorId":3800,"corporation":false,"usgs":true,"family":"Vinson","given":"Mark","email":"mvinson@usgs.gov","middleInitial":"R.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":625357,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Evrard, Lori M. 0000-0001-8582-5818 levrard@usgs.gov","orcid":"https://orcid.org/0000-0001-8582-5818","contributorId":2720,"corporation":false,"usgs":true,"family":"Evrard","given":"Lori","email":"levrard@usgs.gov","middleInitial":"M.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":625358,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gorman, Owen T. 0000-0003-0451-110X otgorman@usgs.gov","orcid":"https://orcid.org/0000-0003-0451-110X","contributorId":2888,"corporation":false,"usgs":true,"family":"Gorman","given":"Owen","email":"otgorman@usgs.gov","middleInitial":"T.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":625359,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Yule, Daniel L. dyule@usgs.gov","contributorId":139525,"corporation":false,"usgs":true,"family":"Yule","given":"Daniel","email":"dyule@usgs.gov","middleInitial":"L.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":false,"id":625360,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70173715,"text":"70173715 - 2016 - Hydrologic effects on diameter growth phenology for Celtis laevigata and Quercus lyrata in the floodplain of the lower White River, Arkansas","interactions":[],"lastModifiedDate":"2016-07-11T15:33:04","indexId":"70173715","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Hydrologic effects on diameter growth phenology for Celtis laevigata and Quercus lyrata in the floodplain of the lower White River, Arkansas","docAbstract":"Bottomland hardwood (BLH) forests represent an extensive wetland system in the Mississippi Alluvial Valley and southeastern USA, and it is currently undergoing widespread transition in species composition. One such transition involves increased establishment of sugarberry (Celtis laevigata), and decreased establishment of overcup oak (Quercus lyrata). The ecological mechanisms that control this transition are not well understood. We measured monthly diameter growth with dendrometer bands on 86 sugarberry and 42 overcup oak trees at eight sites in the floodplain of the White River (AR, USA) with differing hydrologic regimes. For both species, growth attenuated earlier at drier sites compared to wetter sites. Overcup oak grew slightly longer through late August, suggesting its growth period extends across both wet and dry periods. In contrast, sugarberry growth rate decreased substantially by mid-July. While these results did not necessarily indicate a mechanism for increased prominence of sugarberry, they suggest sugarberry growing season does not as much coincide with the typically drier period of late summer and may be less affected by these conditions. Overcup oak grows later into the dry season and water table conditions during this period may determine if overcup oak benefits from this relatively extended growth period.
","largerWorkTitle":"Proceedings of the 18th Biennial Southern Silvicultural Research Conference: USDA Forest Service General Technical Report SRS-212","conferenceTitle":"18th Biennial Southern Silvicultural Research Conference","conferenceDate":"March 2-5, 2015","conferenceLocation":"Knoxville, TN","language":"English","publisher":"USDA Forest Service","publisherLocation":"Asheville, NC","usgsCitation":"Allen, S.T., Cochran, W., Krauss, K.W., Keim, R., and King, S.L., 2016, Hydrologic effects on diameter growth phenology for Celtis laevigata and Quercus lyrata in the floodplain of the lower White River, Arkansas, in Proceedings of the 18th Biennial Southern Silvicultural Research Conference: USDA Forest Service General Technical Report SRS-212, Knoxville, TN, March 2-5, 2015, p. 273-279.","productDescription":"7 p.","startPage":"273","endPage":"279","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-065597","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":324096,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":324095,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.treesearch.fs.fed.us/pubs/50265"}],"publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"576a653ce4b07657d1a11dc0","contributors":{"editors":[{"text":"Schweitzer, Callie Jo","contributorId":172250,"corporation":false,"usgs":false,"family":"Schweitzer","given":"Callie","email":"","middleInitial":"Jo","affiliations":[],"preferred":false,"id":640026,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Clatterbuck, Wayne K.","contributorId":172251,"corporation":false,"usgs":false,"family":"Clatterbuck","given":"Wayne","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":640027,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Oswalt, Christopher M.","contributorId":172252,"corporation":false,"usgs":false,"family":"Oswalt","given":"Christopher","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":640028,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Allen, Scott T.","contributorId":168409,"corporation":false,"usgs":false,"family":"Allen","given":"Scott","email":"","middleInitial":"T.","affiliations":[{"id":25282,"text":"School of Renewable Natural Resources, Louisiana State University, Baton Rouge, LA","active":true,"usgs":false}],"preferred":false,"id":640022,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cochran, Wesley","contributorId":172249,"corporation":false,"usgs":false,"family":"Cochran","given":"Wesley","email":"","affiliations":[],"preferred":false,"id":640023,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Krauss, Ken W. 0000-0003-2195-0729 kraussk@usgs.gov","orcid":"https://orcid.org/0000-0003-2195-0729","contributorId":2017,"corporation":false,"usgs":true,"family":"Krauss","given":"Ken","email":"kraussk@usgs.gov","middleInitial":"W.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":640024,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Keim, Richard F.","contributorId":21858,"corporation":false,"usgs":true,"family":"Keim","given":"Richard F.","affiliations":[],"preferred":false,"id":640025,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"King, Sammy L. 0000-0002-5364-6361 sking@usgs.gov","orcid":"https://orcid.org/0000-0002-5364-6361","contributorId":557,"corporation":false,"usgs":true,"family":"King","given":"Sammy","email":"sking@usgs.gov","middleInitial":"L.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":637688,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70168574,"text":"70168574 - 2016 - A strategy for low cost development of incremental oil in legacy reservoirs","interactions":[],"lastModifiedDate":"2017-04-25T10:37:01","indexId":"70168574","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"A strategy for low cost development of incremental oil in legacy reservoirs","docAbstract":"The precipitous decline in oil prices during 2015 has forced operators to search for ways to develop low-cost and low-risk oil reserves. This study examines strategies to low cost development of legacy reservoirs, particularly those which have already implemented a carbon dioxide enhanced oil recovery (CO2 EOR) program. Initially the study examines the occurrence and nature of the distribution of the oil resources that are targets for miscible and near-miscible CO2 EOR programs. The analysis then examines determinants of technical recovery through the analysis of representative clastic and carbonate reservoirs. The economic analysis focusses on delineating the dominant components of investment and operational costs. The concluding sections describe options to maximize the value of assets that the operator of such a legacy reservoir may have that include incremental expansion within the same producing zone and to producing zones that are laterally or stratigraphically near main producing zones. The analysis identified the CO2 recycle plant as the dominant investment cost item and purchased CO2 and liquids management as a dominant operational cost items. Strategies to utilize recycle plants for processing CO2 from multiple producing zones and multiple reservoir units can significantly reduce costs. Industrial sources for CO2 should be investigated as a possibly less costly way of meeting EOR requirements. Implementation of tapered water alternating gas injection schemes can partially mitigate increases in fluid lifting costs.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the SPE/IAEE hydrocarbon economics and evaluation symposium 2016","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"SPE/IAEE Hydrocarbon Economics and Evaluation Symposium 2016","conferenceDate":"May 17-18, 2016","conferenceLocation":"Houston, TX","language":"English","publisher":"Society of Petroleum Engineers","publisherLocation":"Richardson, TX","doi":"10.2118/179997-MS","isbn":"9781510831292","usgsCitation":"Attanasi, E., 2016, A strategy for low cost development of incremental oil in legacy reservoirs, in Proceedings of the SPE/IAEE hydrocarbon economics and evaluation symposium 2016, Houston, TX, May 17-18, 2016, p. 636-652, https://doi.org/10.2118/179997-MS.","productDescription":"17 p.","startPage":"636","endPage":"652","ipdsId":"IP-073305","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":340145,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-10","publicationStatus":"PW","scienceBaseUri":"58ff0e9ee4b006455f2d61c6","contributors":{"authors":[{"text":"Attanasi, Emil 0000-0001-6845-7160 attanasi@usgs.gov","orcid":"https://orcid.org/0000-0001-6845-7160","contributorId":1809,"corporation":false,"usgs":true,"family":"Attanasi","given":"Emil","email":"attanasi@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":620942,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70194448,"text":"70194448 - 2016 - LakeMetabolizer: An R package for estimating lake metabolism from free-water oxygen using diverse statistical models","interactions":[],"lastModifiedDate":"2018-01-24T16:05:13","indexId":"70194448","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1999,"text":"Inland Waters","active":true,"publicationSubtype":{"id":10}},"title":"LakeMetabolizer: An R package for estimating lake metabolism from free-water oxygen using diverse statistical models","docAbstract":"Metabolism is a fundamental process in ecosystems that crosses multiple scales of organization from individual organisms to whole ecosystems. To improve sharing and reuse of published metabolism models, we developed LakeMetabolizer, an R package for estimating lake metabolism from in situ time series of dissolved oxygen, water temperature, and, optionally, additional environmental variables. LakeMetabolizer implements 5 different metabolism models with diverse statistical underpinnings: bookkeeping, ordinary least squares, maximum likelihood, Kalman filter, and Bayesian. Each of these 5 metabolism models can be combined with 1 of 7 models for computing the coefficient of gas exchange across the air–water interface (k). LakeMetabolizer also features a variety of supporting functions that compute conversions and implement calculations commonly applied to raw data prior to estimating metabolism (e.g., oxygen saturation and optical conversion models). These tools have been organized into an R package that contains example data, example use-cases, and function documentation. The release package version is available on the Comprehensive R Archive Network (CRAN), and the full open-source GPL-licensed code is freely available for examination and extension online. With this unified, open-source, and freely available package, we hope to improve access and facilitate the application of metabolism in studies and management of lentic ecosystems.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/IW-6.4.883","usgsCitation":"Winslow, L., Zwart, J., Batt, R., Dugan, H., Woolway, R., Corman, J., Hanson, P.C., and Read, J.S., 2016, LakeMetabolizer: An R package for estimating lake metabolism from free-water oxygen using diverse statistical models: Inland Waters, v. 6, no. 4, p. 622-636, https://doi.org/10.1080/IW-6.4.883.","productDescription":"15 p.","startPage":"622","endPage":"636","ipdsId":"IP-065534","costCenters":[{"id":160,"text":"Center for Integrated Data Analytics","active":false,"usgs":true}],"links":[{"id":349534,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","issue":"4","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-02","publicationStatus":"PW","scienceBaseUri":"5a60fd87e4b06e28e9c24fa5","contributors":{"authors":[{"text":"Winslow, Luke 0000-0002-8602-5510 lwinslow@usgs.gov","orcid":"https://orcid.org/0000-0002-8602-5510","contributorId":168947,"corporation":false,"usgs":true,"family":"Winslow","given":"Luke","email":"lwinslow@usgs.gov","affiliations":[{"id":160,"text":"Center for Integrated Data Analytics","active":false,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"preferred":true,"id":723877,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zwart, Jacob A.","contributorId":173345,"corporation":false,"usgs":false,"family":"Zwart","given":"Jacob A.","affiliations":[{"id":16905,"text":"University of Notre Dame, Dept. of Biological Sciences, Notre Dame, IN, 46556, USA","active":true,"usgs":false}],"preferred":false,"id":723878,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Batt, Ryan D.","contributorId":168948,"corporation":false,"usgs":false,"family":"Batt","given":"Ryan D.","affiliations":[{"id":25393,"text":"Department of Ecology, Evolution, and Natural Resources, Rutgers University, New Brunswick, New Jersey, USA 08901","active":true,"usgs":false}],"preferred":false,"id":723879,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dugan, Hilary A.","contributorId":150191,"corporation":false,"usgs":false,"family":"Dugan","given":"Hilary","middleInitial":"A.","affiliations":[{"id":17938,"text":"Center for Limnology University of Wisconsin, Madison, WI 53706, US","active":true,"usgs":false}],"preferred":false,"id":723880,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Woolway, R. Iestyn","contributorId":150345,"corporation":false,"usgs":false,"family":"Woolway","given":"R. Iestyn","affiliations":[{"id":18007,"text":"Lake Ecosystems Group, Centre for Ecology & Hydrology, Lancaster Environment Centre, Library Avenue, Bailrigg, Lancaster, LA1 4AP, UK.","active":true,"usgs":false}],"preferred":false,"id":723881,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Corman, Jessica","contributorId":194469,"corporation":false,"usgs":false,"family":"Corman","given":"Jessica","affiliations":[],"preferred":false,"id":723882,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hanson, Paul C.","contributorId":35634,"corporation":false,"usgs":false,"family":"Hanson","given":"Paul","email":"","middleInitial":"C.","affiliations":[{"id":12951,"text":"Center for Limnology, University of Wisconsin Madison","active":true,"usgs":false}],"preferred":false,"id":723883,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Read, Jordan S. 0000-0002-3888-6631 jread@usgs.gov","orcid":"https://orcid.org/0000-0002-3888-6631","contributorId":4453,"corporation":false,"usgs":true,"family":"Read","given":"Jordan","email":"jread@usgs.gov","middleInitial":"S.","affiliations":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true},{"id":160,"text":"Center for Integrated Data Analytics","active":false,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":723884,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70190182,"text":"70190182 - 2016 - Consistent and efficient processing of ADCP streamflow measurements","interactions":[],"lastModifiedDate":"2022-09-15T16:14:59.415624","indexId":"70190182","displayToPublicDate":"2016-01-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Consistent and efficient processing of ADCP streamflow measurements","docAbstract":"The use of Acoustic Doppler Current Profilers (ADCPs) from a moving boat is a commonly used method for measuring streamflow. Currently, the algorithms used to compute the average depth, compute edge discharge, identify invalid data, and estimate velocity and discharge for invalid data vary among manufacturers. These differences could result in different discharges being computed from identical data. Consistent computational algorithm, automated filtering, and quality assessment of ADCP streamflow measurements that are independent of the ADCP manufacturer are being developed in a software program that can process ADCP moving-boat discharge measurements independent of the ADCP used to collect the data.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"River Flow 2016: Proceedings of the international conference on fluvial hydraulics","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"River Flow 2016: The international conference on fluvial hydraulics","conferenceDate":"July 11-14, 2016","conferenceLocation":"St. Louis, MO","language":"English","publisher":"Taylor & Francis Group","publisherLocation":"Boca Raton, FL","isbn":"978-1-138-02913-2","usgsCitation":"Mueller, D.S., 2016, Consistent and efficient processing of ADCP streamflow measurements, in River Flow 2016: Proceedings of the international conference on fluvial hydraulics, St. Louis, MO, July 11-14, 2016, p. 655-663.","productDescription":"9 p.","startPage":"655","endPage":"663","ipdsId":"IP-071056","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":344917,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5996ab4de4b0b589267b3fca","contributors":{"editors":[{"text":"Constantinescu, George","contributorId":174167,"corporation":false,"usgs":false,"family":"Constantinescu","given":"George","email":"","affiliations":[{"id":7241,"text":"IIHR-Hydroscience and Engineering, Department of Civil and Environmental Engineering, The University of Iowa","active":true,"usgs":false}],"preferred":false,"id":707900,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Garcia, Marcelo H.","contributorId":74236,"corporation":false,"usgs":false,"family":"Garcia","given":"Marcelo H.","affiliations":[{"id":33106,"text":"University of Illinois at Urbana Champaign","active":true,"usgs":false}],"preferred":false,"id":707901,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Hanes, Dan","contributorId":174168,"corporation":false,"usgs":false,"family":"Hanes","given":"Dan","email":"","affiliations":[{"id":12995,"text":"Department of Earth and Atmospheric Sciences, Saint Louis University","active":true,"usgs":false}],"preferred":false,"id":707902,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Mueller, David S. dmueller@usgs.gov","contributorId":1499,"corporation":false,"usgs":true,"family":"Mueller","given":"David","email":"dmueller@usgs.gov","middleInitial":"S.","affiliations":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":true,"id":707850,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70191820,"text":"70191820 - 2016 - Water-quality effects on phytoplankton species and density and trophic state indices at Big Base and Little Base Lakes, Little Rock Air Force Base, Arkansas, June through August, 2015","interactions":[],"lastModifiedDate":"2017-10-25T14:30:19","indexId":"70191820","displayToPublicDate":"2015-12-31T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2531,"text":"Journal of the Arkansas Academy of Science","active":true,"publicationSubtype":{"id":10}},"title":"Water-quality effects on phytoplankton species and density and trophic state indices at Big Base and Little Base Lakes, Little Rock Air Force Base, Arkansas, June through August, 2015","docAbstract":"Big Base and Little Base Lakes are located on\r\nLittle Rock Air Force Base, Arkansas, and their close\r\nproximity to a dense residential population and an\r\nactive military/aircraft installation make the lakes\r\nvulnerable to water-quality degradation. The U.S.\r\nGeological Survey (USGS) conducted a study from\r\nJune through August 2015 to investigate the effects of\r\nwater quality on phytoplankton species and density and\r\ntrophic state in Big Base and Little Base Lakes, with\r\nparticular regard to nutrient concentrations. Nutrient\r\nconcentrations, trophic-state indices, and the large part\r\nof the phytoplankton biovolume composed of\r\ncyanobacteria, indicate eutrophic conditions were\r\nprevalent for Big Base and Little Base Lakes,\r\nparticularly in August 2015. Cyanobacteria densities\r\nand biovolumes measured in this study likely pose a\r\nlow to moderate risk of adverse algal toxicity, and the\r\nhigh proportion of filamentous cyanobacteria in the\r\nlakes, in relation to other algal groups, is important\r\nfrom a fisheries standpoint because these algae are a\r\npoor food source for many aquatic taxa. In both lakes,\r\ntotal nitrogen to total phosphorus (N:P) ratios declined\r\nover the sampling period as total phosphorus\r\nconcentrations increased relative to nitrogen\r\nconcentrations. The N:P ratios in the August samples\r\n(20:1 and 15:1 in Big Base and Little Base Lakes,\r\nrespectively) and other indications of eutrophic\r\nconditions are of concern and suggest that exposure of\r\nthe two lakes to additional nutrients could cause\r\nunfavorable dissolved-oxygen conditions and increase\r\nthe risk of cyanobacteria blooms and associated\r\ncyanotoxin issues.","language":"English","publisher":"Arkansas Academy of Science","usgsCitation":"Driver, L., and Justus, B., 2016, Water-quality effects on phytoplankton species and density and trophic state indices at Big Base and Little Base Lakes, Little Rock Air Force Base, Arkansas, June through August, 2015: Journal of the Arkansas Academy of Science, v. 70, no. 1, p. 88-95.","productDescription":"8 p.","startPage":"88","endPage":"95","ipdsId":"IP-074006","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":347379,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":346820,"type":{"id":15,"text":"Index Page"},"url":"https://scholarworks.uark.edu/jaas/vol70/iss1/16"}],"country":"United States","state":"Arkansas","otherGeospatial":"Big Base Lake, Little Base Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.17520713806152,\n 34.888395122782164\n ],\n [\n -92.1556806564331,\n 34.888395122782164\n ],\n [\n -92.1556806564331,\n 34.904375309375645\n ],\n [\n -92.17520713806152,\n 34.904375309375645\n ],\n [\n -92.17520713806152,\n 34.888395122782164\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"70","issue":"1","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59f1a2a8e4b0220bbd9d9f8d","contributors":{"authors":[{"text":"Driver, Lucas ldriver@usgs.gov","contributorId":197344,"corporation":false,"usgs":true,"family":"Driver","given":"Lucas","email":"ldriver@usgs.gov","affiliations":[],"preferred":true,"id":713230,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Justus, Billy bjustus@usgs.gov","contributorId":152446,"corporation":false,"usgs":true,"family":"Justus","given":"Billy","email":"bjustus@usgs.gov","affiliations":[{"id":129,"text":"Arkansas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":713229,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70168829,"text":"70168829 - 2016 - Water-quality response to a high-elevation wildfire in the Colorado Front Range","interactions":[],"lastModifiedDate":"2021-04-20T13:20:37.020538","indexId":"70168829","displayToPublicDate":"2015-12-29T15:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Water-quality response to a high-elevation wildfire in the Colorado Front Range","docAbstract":"Water quality of the Big Thompson River in the Front Range of Colorado was studied for 2 years following a high‐elevation wildfire that started in October 2012 and burned 15% of the watershed. A combination of fixed‐interval sampling and continuous water‐quality monitors was used to examine the timing and magnitude of water‐quality changes caused by the wildfire. Prefire water quality was well characterized because the site has been monitored at least monthly since the early 2000s. Major ions and nitrate showed the largest changes in concentrations; major ion increases were greatest in the first postfire snowmelt period, but nitrate increases were greatest in the second snowmelt period. The delay in nitrate release until the second snowmelt season likely reflected a combination of factors including fire timing, hydrologic regime, and rates of nitrogen transformations. Despite the small size of the fire, annual yields of dissolved constituents from the watershed increased 20–52% in the first 2 years following the fire. Turbidity data from the continuous sensor indicated high‐intensity summer rain storms had a much greater effect on sediment transport compared to snowmelt. High‐frequency sensor data also revealed that weekly sampling missed the concentration peak during snowmelt and short‐duration spikes during rain events, underscoring the challenge of characterizing postfire water‐quality response with fixed‐interval sampling.
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Hurricane Sandy made landfall during an investigation in Barnegat Bay-Little Egg Harbor estuary that included water quality monitoring, geomorphologic characterization, and numerical modeling; this provided an opportunity to characterize the storm response of the barrier island-estuary system. Barrier island morphologic response was characterized by significant changes in shoreline position, dune elevation, and beach volume; morphologic changes within the estuary were less dramatic with a net gain of only 200,000 m3 of sediment. When observed, estuarine deposition was adjacent to the back-barrier shoreline or collocated with maximum estuary depths. Estuarine sedimentologic changes correlated well with bed shear stresses derived from numerically simulated storm conditions, suggesting that change is linked to winnowing from elevated storm-related wave-current interactions rather than deposition. Rapid storm-related changes in estuarine water level, turbidity, and salinity were coincident with minima in island and estuarine widths, which may have influenced the location of two barrier island breaches. Barrier-estuary connectivity, or the transport of sediment from barrier island to estuary, was influenced by barrier island land use and width. Coupled assessments like this one provide critical information about storm-related coastal and estuarine sediment transport that may not be evident from investigations that consider only one component of the coastal system.
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hydrologic evidence","docAbstract":"Explosives used in construction have been implicated as sources of NO3– contamination in groundwater, but direct forensic evidence is limited. Identification of blasting-related NO3– can be complicated by other NO3– sources, including agriculture and wastewater disposal, and by hydrogeologic factors affecting NO3– transport and stability. Here we describe a study that used hydrogeology, chemistry, stable isotopes, and mass balance calculations to evaluate groundwater NO3– sources and transport in areas surrounding a highway construction site with documented blasting in New Hampshire. Results indicate various groundwater responses to contamination: (1) rapid breakthrough and flushing of synthetic NO3– (low δ15N, high δ18O) from dissolution of unexploded NH4NO3 blasting agents in oxic groundwater; (2) delayed and reduced breakthrough of synthetic NO3– subjected to partial denitrification (high δ15N, high δ18O); (3) relatively persistent concentrations of blasting-related biogenic NO3– derived from nitrification of NH4+ (low δ15N, low δ18O); and (4) stable but spatially variable biogenic NO3– concentrations, consistent with recharge from septic systems (high δ15N, low δ18O), variably affected by denitrification. Source characteristics of denitrified samples were reconstructed from dissolved-gas data (Ar, N2) and isotopic fractionation trends associated with denitrification (Δδ15N/Δδ18O ≈ 1.31). Methods and data from this study are expected to be applicable in studies of other aquifers affected by explosives used in construction.
","language":"English","publisher":"American Chemical Society","publisherLocation":"Easton, PA","doi":"10.1021/acs.est.5b03671","usgsCitation":"Degnan, J.R., Bohlke, J.K., Pelham, K., Langlais, D.M., and Walsh, G.J., 2016, Identification of groundwater nitrate contamination from explosives used in road construction: Isotopic, chemical, and hydrologic evidence: Environmental Science & Technology, v. 50, no. 2, p. 593-603, https://doi.org/10.1021/acs.est.5b03671.","productDescription":"11 p.","startPage":"593","endPage":"603","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-067263","costCenters":[{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":313910,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"50","issue":"2","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-28","publicationStatus":"PW","scienceBaseUri":"568e4912e4b0e7a44bc419dd","chorus":{"doi":"10.1021/acs.est.5b03671","url":"http://dx.doi.org/10.1021/acs.est.5b03671","publisher":"American Chemical Society (ACS)","authors":"Degnan James R., Böhlke J. 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The approach was applied at three sites spanning gradients in watershed size and land use in the Chesapeake Bay watershed. Results indicate that 58-73% of the annual nitrate load to the streams was groundwater-discharged nitrate. Average annual first order nitrate loss rate constants (k) were similar to those reported in both modelling and in-stream process-based studies, and were greater at the small streams (0.06 and 0.22 d-1) than at the large river (0.05 d-1), but 11% of the annual loads were retained/lost in the small streams, compared with 23% in the large river. Larger streambed area to water volume ratios in small streams result in greater loss rates, but shorter residence times in small streams result in a smaller fraction of nitrate loads being removed than in larger streams. A seasonal evaluation of k values suggests that nitrate was retained/lost at varying rates during the growing season. Consistent with previous studies, streamflow and nitrate concentration were inversely related to k. This new approach for interpreting high-frequency nitrate data and the associated findings furthers our ability to understand, predict, and mitigate nitrate impacts on streams and receiving waters by providing insights into temporal nitrate dynamics that would be difficult to obtain using traditional field-based studies.
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Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":588270,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pellerin, Brian A. bpeller@usgs.gov","contributorId":1451,"corporation":false,"usgs":true,"family":"Pellerin","given":"Brian","email":"bpeller@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":588271,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hyer, Kenneth E. kenhyer@usgs.gov","contributorId":152108,"corporation":false,"usgs":true,"family":"Hyer","given":"Kenneth E.","email":"kenhyer@usgs.gov","affiliations":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true}],"preferred":false,"id":588272,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"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":588273,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70155254,"text":"70155254 - 2016 - The East African monsoon system: Seasonal climatologies and recent variations: Chapter 10","interactions":[],"lastModifiedDate":"2017-04-17T15:14:20","indexId":"70155254","displayToPublicDate":"2015-12-26T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"The East African monsoon system: Seasonal climatologies and recent variations: Chapter 10","docAbstract":"This chapter briefly reviews the complex climatological cycle of the East African monsoon system, paying special attention to its connection to the larger Indo-Pacific-Asian monsoon cycle. We examine the seasonal monsoon cycle, and briefly explore recent circulation changes. The spatial footprint of our analysis corresponds with the “Greater Horn of Africa” (GHA) region, extending from Tanzania in the south to Yemen and Sudan in the north. During boreal winter, when northeast trade winds flow across the northwest Indian Ocean and the equatorial moisture transports over the Indian Ocean exhibit strong westerly mean flows over the equatorial Indian Ocean, East African precipitation is limited to a few highland areas. As the Indian monsoon circulation transitions during boreal spring, the trade winds over the northwest Indian Ocean reverse, and East African moisture convergence supports the “long” rains. In boreal summer, the southwesterly Somali Jet intensifies over eastern Africa. Subsidence forms along the westward flank of this jet, shutting down precipitation over eastern portions of East Africa. In boreal fall, the Jet subsides, but easterly moisture transports support rainfall in limited regions of the eastern Horn of Africa. We use regressions with the trend mode of global sea surface temperatures to explore potential changes in the seasonal monsoon circulations. Significant reductions in total precipitable water are indicated in Kenya, Tanzania, Rwanda, Burundi, Uganda, Ethiopia, South Sudan, Sudan, and Yemen, with moisture transports broadly responding in ways that reinforce the climatological moisture transports over the Indian Ocean. Over Kenya, southern Ethiopia and Somalia, regressions with velocity potential indicate increased convergence aloft. Near the surface, this convergence appears to manifest as a surface high pressure system that modifies moisture transports in these countries as well as Uganda, Tanzania, Rwanda, and Burundi. An analysis of rainfall changes indicates significant declines in parts of Tanzania, Rwanda, Burundi, Uganda, Kenya, Somalia, Ethiopia, and Yemen.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"The Monsoons and Climate Change","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","publisherLocation":"Cham","doi":"10.1007/978-3-319-21650-8_8","usgsCitation":"Funk, C.C., Hoell, A., Shukla, S., Husak, G.J., and Michaelsen, J., 2016, The East African monsoon system: Seasonal climatologies and recent variations: Chapter 10, chap. of The Monsoons and Climate Change, p. 163-185, https://doi.org/10.1007/978-3-319-21650-8_8.","productDescription":"13 p.","startPage":"163","endPage":"185","ipdsId":"IP-062072","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":339820,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-21","publicationStatus":"PW","scienceBaseUri":"58f5d440e4b0f2e20545e415","contributors":{"authors":[{"text":"Funk, Christopher C. 0000-0002-9254-6718 cfunk@usgs.gov","orcid":"https://orcid.org/0000-0002-9254-6718","contributorId":721,"corporation":false,"usgs":true,"family":"Funk","given":"Christopher","email":"cfunk@usgs.gov","middleInitial":"C.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":565381,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hoell, Andrew","contributorId":145803,"corporation":false,"usgs":false,"family":"Hoell","given":"Andrew","affiliations":[{"id":16236,"text":"UCSB Climate Hazards Group","active":true,"usgs":false}],"preferred":false,"id":565382,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shukla, Shraddhanand","contributorId":145802,"corporation":false,"usgs":false,"family":"Shukla","given":"Shraddhanand","affiliations":[{"id":16236,"text":"UCSB Climate Hazards Group","active":true,"usgs":false}],"preferred":false,"id":565383,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Husak, Gregory J.","contributorId":34435,"corporation":false,"usgs":true,"family":"Husak","given":"Gregory","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":565384,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Michaelsen, J.","contributorId":12288,"corporation":false,"usgs":true,"family":"Michaelsen","given":"J.","affiliations":[],"preferred":false,"id":565385,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70156787,"text":"70156787 - 2016 - Multi-scale predictions of massive conifer mortality due to chronic temperature rise","interactions":[],"lastModifiedDate":"2018-01-12T15:44:21","indexId":"70156787","displayToPublicDate":"2015-12-21T16:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2841,"text":"Nature Climate Change","onlineIssn":"1758-6798","printIssn":"1758-678X","active":true,"publicationSubtype":{"id":10}},"title":"Multi-scale predictions of massive conifer mortality due to chronic temperature rise","docAbstract":"Global temperature rise and extremes accompanying drought threaten forests and their associated climatic feedbacks. Our ability to accurately simulate drought-induced forest impacts remains highly uncertain in part owing to our failure to integrate physiological measurements, regional-scale models, and dynamic global vegetation models (DGVMs). Here we show consistent predictions of widespread mortality of needleleaf evergreen trees (NET) within Southwest USA by 2100 using state-of-the-art models evaluated against empirical data sets. Experimentally, dominant Southwest USA NET species died when they fell below predawn water potential (Ψpd) thresholds (April–August mean) beyond which photosynthesis, hydraulic and stomatal conductance, and carbohydrate availability approached zero. The evaluated regional models accurately predicted NET Ψpd, and 91% of predictions (10 out of 11) exceeded mortality thresholds within the twenty-first century due to temperature rise. The independent DGVMs predicted ≥50% loss of Northern Hemisphere NET by 2100, consistent with the NET findings for Southwest USA. Notably, the global models underestimated future mortality within Southwest USA, highlighting that predictions of future mortality within global models may be underestimates. Taken together, the validated regional predictions and the global simulations predict widespread conifer loss in coming decades under projected global warming.
","language":"English","publisher":"Nature Publishing Group","publisherLocation":"London, UK","doi":"10.1038/nclimate2873","usgsCitation":"McDowell, N., Williams, A., Xu, C., Pockman, W., Dickman, L., Sevanto, S., Pangle, R., Limousin, J., Plaut, J., Mackay, D., Ogee, J., Domec, J., Allen, C.D., Fisher, R.A., Jiang, X., Muss, J., Breshears, D., Rauscher, S.A., and Koven, C., 2016, Multi-scale predictions of massive conifer mortality due to chronic temperature rise: Nature Climate Change, v. 6, p. 295-300, https://doi.org/10.1038/nclimate2873.","productDescription":"6 p.","startPage":"295","endPage":"300","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-058464","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":471401,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.osti.gov/biblio/1492529","text":"External Repository"},{"id":312936,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2015-12-21","publicationStatus":"PW","scienceBaseUri":"56826b46e4b0a04ef4925b86","contributors":{"authors":[{"text":"McDowell, Nathan G.","contributorId":9176,"corporation":false,"usgs":true,"family":"McDowell","given":"Nathan G.","affiliations":[],"preferred":false,"id":583294,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Williams, A.P.","contributorId":70226,"corporation":false,"usgs":true,"family":"Williams","given":"A.P.","email":"","affiliations":[],"preferred":false,"id":583295,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Xu, C.","contributorId":9781,"corporation":false,"usgs":true,"family":"Xu","given":"C.","email":"","affiliations":[],"preferred":false,"id":583296,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pockman, W. T.","contributorId":57260,"corporation":false,"usgs":false,"family":"Pockman","given":"W. T.","affiliations":[{"id":7164,"text":"Department of Biology, University of New Mexico, Albuquerque, NM 87131 USA","active":true,"usgs":false}],"preferred":false,"id":583297,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dickman, L. T.","contributorId":150844,"corporation":false,"usgs":false,"family":"Dickman","given":"L. T.","affiliations":[],"preferred":false,"id":583298,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sevanto, Sanna","contributorId":150845,"corporation":false,"usgs":false,"family":"Sevanto","given":"Sanna","email":"","affiliations":[],"preferred":false,"id":583299,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pangle, R.","contributorId":150846,"corporation":false,"usgs":false,"family":"Pangle","given":"R.","email":"","affiliations":[],"preferred":false,"id":583300,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Limousin, J.","contributorId":150892,"corporation":false,"usgs":false,"family":"Limousin","given":"J.","affiliations":[],"preferred":false,"id":583491,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Plaut, J.J.","contributorId":6982,"corporation":false,"usgs":true,"family":"Plaut","given":"J.J.","email":"","affiliations":[],"preferred":false,"id":583302,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Mackay, D.S.","contributorId":150893,"corporation":false,"usgs":false,"family":"Mackay","given":"D.S.","email":"","affiliations":[],"preferred":false,"id":583492,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Ogee, J.","contributorId":150847,"corporation":false,"usgs":false,"family":"Ogee","given":"J.","affiliations":[],"preferred":false,"id":583301,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Domec, Jean-Christophe","contributorId":146460,"corporation":false,"usgs":false,"family":"Domec","given":"Jean-Christophe","email":"","affiliations":[],"preferred":false,"id":583305,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Allen, Craig D. 0000-0002-8777-5989 craig_allen@usgs.gov","orcid":"https://orcid.org/0000-0002-8777-5989","contributorId":2597,"corporation":false,"usgs":true,"family":"Allen","given":"Craig","email":"craig_allen@usgs.gov","middleInitial":"D.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":570546,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Fisher, Rosie A.","contributorId":147090,"corporation":false,"usgs":false,"family":"Fisher","given":"Rosie","email":"","middleInitial":"A.","affiliations":[{"id":16785,"text":"National Center for Atmospheric Research, Boulder, CO","active":true,"usgs":false}],"preferred":false,"id":583306,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Jiang, X.","contributorId":150848,"corporation":false,"usgs":false,"family":"Jiang","given":"X.","email":"","affiliations":[],"preferred":false,"id":583307,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Muss, J.D.","contributorId":31954,"corporation":false,"usgs":true,"family":"Muss","given":"J.D.","affiliations":[],"preferred":false,"id":583308,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Breshears, D.D.","contributorId":17952,"corporation":false,"usgs":false,"family":"Breshears","given":"D.D.","email":"","affiliations":[{"id":12625,"text":"School of Natural Resources and the Environment, University of Arizona, Tucson, AZ, 85721, USA","active":true,"usgs":false}],"preferred":false,"id":583309,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Rauscher, Sara A.","contributorId":47653,"corporation":false,"usgs":true,"family":"Rauscher","given":"Sara","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":583310,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Koven, C.","contributorId":39655,"corporation":false,"usgs":true,"family":"Koven","given":"C.","email":"","affiliations":[],"preferred":false,"id":583311,"contributorType":{"id":1,"text":"Authors"},"rank":19}]}} ,{"id":70160330,"text":"70160330 - 2016 - Structure and spatial patterns of macrobenthic community in Tai Lake, a large shallow lake, China","interactions":[],"lastModifiedDate":"2015-12-17T14:23:38","indexId":"70160330","displayToPublicDate":"2015-12-17T15:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Structure and spatial patterns of macrobenthic community in Tai Lake, a large shallow lake, China","docAbstract":"Tai Lake (Chinese: Taihu), the third-largest freshwater lake in China, suffers from harmful cyanobacteria blooms that are caused by economic development and population growth near the lake. Several studies have focused on phytoplankton in Tai Lake after a drinking water crisis in 2007; however, these studies primarily focused on microcystin bioaccumulation and toxicity to individual species without examining the effects of microcystin on macrobenthic community diversity. In this study, we conducted a survey of the lake to examine the effects of microcystine and other pollutants on marcobenthic community diversity. A totally of forty-nine species of macroinvertebrates were found in Tai Lake. Limnodrilus hoffmeisteri and Corbicula fluminea were the most abundant species. Cluster-analysis and one-way analysis of similarity (ANOSIM) identified three significantly different macrobenthic communities among the sample sites. More specifically, sites in the eastern bays, where aquatic macrophytes were abundant, had the highest diversity of macrobenthic communities, which were dominated by Bellamya aeruginosa, Bellamya purificata, L. hoffmeisteri, and Alocinma longicornis. Sites in Zhushan Bay contained relatively diverse communities, mainly composed of L. hoffmeisteri, C. fluminea, L. claparederanus, R. sinicus, and Cythura sp. Sites in the western region, Meiliang Bay and Wuli Bay had the lowest diversity, mainly composed ofL. hoffmeisteri, C. fluminea, Branchiura sowerbyi, and Rhyacodrilus sinicus. In addition, the relationships between macrobenthic metrics (Shannon–Wiener, Margalef, and Pielou) and environmental variables showed that community structure and spatial patterns of macrobenthos in Tai Lake were significantly influenced by chemical oxygen demand (CODCr), biochemical oxygen demand (BOD5), lead (Pb), and microcystin-LR (L for leucine and R for arginine). Our findings provide critical information that could help managers and policymakers assess and modify ecological restoration practices.
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