Fines, defined here as grains or particles, less than 75 μm in diameter, exist nearly ubiquitously in natural sediment, even those classified as coarse. Macroscopic sediment properties, such as compressibility, which relates applied effective stress to the resulting sediment deformation, depend on the fabric of fines. Unlike coarse grains, fines have sizes and masses small enough to be more strongly influenced by electrical interparticle forces than by gravity. These electrical forces acting through pore fluids are influenced by pore fluid chemistry changes. Macroscopic property dependence on pore fluid chemistry must be accounted for in sediment studies involving subsurface flow and sediment stability analyses, as well as in engineered flow situations such as groundwater pollutant remediation, hydrocarbon migration, or other energy resource extraction applications. This study demonstrates how the liquid limit‐based electrical sensitivity index can be used to predict sediment compressibility changes due to pore fluid chemistry changes. Laboratory tests of electrical sensitivity, sedimentation, and compressibility illustrate mechanisms linking microscale and macroscale processes for selected pure, end‐member fines. A specific application considered here is methane extraction via depressurization of gas hydrate‐bearing sediment, which causes a dramatic pore water salinity drop concurrent with sediment being compressed by the imposed effective stress increase.
Among the numerous models that have been suggested for the primary and predominant source of silica for chert, we suggest that eolian dust is worthy of further considerations. Such considerations are supported by the common association of Phanerozoic chert with evaporites, limestones, dolomites, or other strata that were deposited within or near arid paleoclimates. This association suggests a direct or indirect causal link between aridity and chert formation.
In addition, eolian processes export large quantities of quartz-rich dust from arid climate ergs or loess lands. The chemistry of abraded quartz particles derived therefrom is consistent with chert formation. Abrasion of quartz particles produces an amorphous surface layer and underlying lattice disorder. An inverse relation between particle size distribution (< 64 μm) and the enthalpy of solution of abraded quartz is indicative of the degree of lattice disorder; as particle size decreases, the enthalpy of solution increases. The amorphous surface layer and underlying lattice disorder enhance both the rate and amount of dissolution of quartz dust particles; the solubilized silica can then be reprecipitated and diagenetically altered to the various silica polymorphs that occur in chert. An eolian supply and the chemistry of eolian abraded quartz particles may account for chert formation in disparate depositional environments that encompass deep-sea chert, chert in epicontinental seas including shallow shelves, and chert that formed in continental eolinites, lakes, and soils (arid climate silcretes).
","language":"English","publisher":"SEPM Society for Sedimentary Geology","doi":"10.2110/jsr.2018.39","usgsCitation":"Cecil, C., Hemingway, B., and Dulong, F.T., 2018, The chemistry of eolian quartz dust and the origin of chert: Journal of Sedimentary Research, v. 88, no. 6, p. 743-752, https://doi.org/10.2110/jsr.2018.39.","productDescription":"10 p.","startPage":"743","endPage":"752","ipdsId":"IP-096590","costCenters":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":418401,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":418372,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9SA2M1L","text":"The chemistry of eolian quartz dust and the origin of chert"}],"volume":"88","issue":"6","noUsgsAuthors":false,"publicationDate":"2018-06-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Cecil, C. Blaine 0000-0002-9032-1689","orcid":"https://orcid.org/0000-0002-9032-1689","contributorId":311202,"corporation":false,"usgs":false,"family":"Cecil","given":"C. Blaine","affiliations":[{"id":67354,"text":"USGS Scientist Emeriti","active":true,"usgs":false}],"preferred":false,"id":876032,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hemingway, Bruce 0000-0002-4421-8605","orcid":"https://orcid.org/0000-0002-4421-8605","contributorId":311203,"corporation":false,"usgs":false,"family":"Hemingway","given":"Bruce","email":"","affiliations":[{"id":67354,"text":"USGS Scientist Emeriti","active":true,"usgs":false}],"preferred":false,"id":876033,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dulong, Frank T. 0000-0001-7388-647X fdulong@usgs.gov","orcid":"https://orcid.org/0000-0001-7388-647X","contributorId":650,"corporation":false,"usgs":true,"family":"Dulong","given":"Frank","email":"fdulong@usgs.gov","middleInitial":"T.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":876031,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70197916,"text":"70197916 - 2018 - Using stereo satellite imagery to account for ablation, entrainment, and compaction in volume calculations for rock avalanches on Glaciers: Application to the 2016 Lamplugh Rock Avalanche in Glacier Bay National Park, Alaska","interactions":[],"lastModifiedDate":"2018-06-26T14:06:50","indexId":"70197916","displayToPublicDate":"2018-06-26T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2314,"text":"Journal of Geophysical Research B: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"Using stereo satellite imagery to account for ablation, entrainment, and compaction in volume calculations for rock avalanches on Glaciers: Application to the 2016 Lamplugh Rock Avalanche in Glacier Bay National Park, Alaska","docAbstract":"The use of preevent and postevent digital elevation models (DEMs) to estimate the volume of rock avalanches on glaciers is complicated by ablation of ice before and after the rock avalanche, scour of material during rock avalanche emplacement, and postevent ablation and compaction of the rock avalanche deposit. We present a model to account for these processes in volume estimates of rock avalanches on glaciers. We applied our model by calculating the volume of the 28 June 2016 Lamplugh rock avalanche in Glacier Bay National Park, Alaska. We derived preevent and postevent 2‐m resolution DEMs from WorldView satellite stereo imagery. Using data from DEM differencing, we reconstructed the rock avalanche and adjacent surfaces at the time of occurrence by accounting for elevation changes due to ablation and scour of the ice surface, and postevent deposit changes. We accounted for uncertainties in our DEMs through precise coregistration and an assessment of relative elevation accuracy in bedrock control areas. The rock avalanche initially displaced 51.7 ± 1.5 Mm3 of intact rock and then scoured and entrained 13.2 ± 2.2 Mm3 of snow and ice during emplacement. We calculated the total deposit volume to be 69.9 ± 7.9 Mm3. Volume estimates that did not account for topographic changes due to ablation, scour, and compaction underestimated the deposit volume by 31.0–46.8 Mm3. Our model provides an improved framework for estimating uncertainties affecting rock avalanche volume measurements in glacial environments. These improvements can contribute to advances in the understanding of rock avalanche hazards and dynamics.","language":"English","publisher":"Wiley","doi":"10.1002/2017JF004512","usgsCitation":"Bessette-Kirton, E., Coe, J.A., and Zhou, W., 2018, Using stereo satellite imagery to account for ablation, entrainment, and compaction in volume calculations for rock avalanches on Glaciers: Application to the 2016 Lamplugh Rock Avalanche in Glacier Bay National Park, Alaska: Journal of Geophysical Research B: Solid Earth, v. 123, no. 4, p. 622-641, https://doi.org/10.1002/2017JF004512.","productDescription":"20 p.","startPage":"622","endPage":"641","ipdsId":"IP-094586","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":468630,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2017jf004512","text":"Publisher Index Page"},{"id":355368,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Glacier Bay National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -154.423828125,\n 50.3454604086048\n ],\n [\n -125.24414062499999,\n 50.3454604086048\n ],\n [\n -125.24414062499999,\n 64.62387720204688\n ],\n [\n -154.423828125,\n 64.62387720204688\n ],\n [\n -154.423828125,\n 50.3454604086048\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"123","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-04-06","publicationStatus":"PW","scienceBaseUri":"5b46e54ee4b060350a15d0b9","contributors":{"authors":[{"text":"Bessette-Kirton, Erin 0000-0002-2797-0694 ebessette-kirton@usgs.gov","orcid":"https://orcid.org/0000-0002-2797-0694","contributorId":177153,"corporation":false,"usgs":true,"family":"Bessette-Kirton","given":"Erin","email":"ebessette-kirton@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":739093,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coe, Jeffrey A. 0000-0002-0842-9608 jcoe@usgs.gov","orcid":"https://orcid.org/0000-0002-0842-9608","contributorId":1333,"corporation":false,"usgs":true,"family":"Coe","given":"Jeffrey","email":"jcoe@usgs.gov","middleInitial":"A.","affiliations":[{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":739094,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zhou, Wendy","contributorId":205989,"corporation":false,"usgs":false,"family":"Zhou","given":"Wendy","email":"","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":739095,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70197443,"text":"sir20185076 - 2018 - Nearshore sediment monitoring for the Stormwater Action Monitoring (SAM) Program, Puget Sound, western Washington","interactions":[],"lastModifiedDate":"2018-10-04T19:38:11","indexId":"sir20185076","displayToPublicDate":"2018-06-26T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-5076","title":"Nearshore sediment monitoring for the Stormwater Action Monitoring (SAM) Program, Puget Sound, western Washington","docAbstract":"Chemicals such as metals and organics (polychlorinated biphenyl [PCBs], polybrominated diphenyl ethers [PBDEs], polycyclic aromatic hydrocarbons [PAHs], and phthalates) continue to enter Puget Sound, western Washington, from point sources (such as industrial and municipal outfalls) and combined sewer outfalls and non-point sources (such as stormwater runoff). Runoff during storm events has been identified as a major source of contamination entering Puget Sound and has been implicated in the degradation of nearshore habitats and biota. Metals, organic chemicals, and other pollutants are known to accumulate in sediments such as those present along the shoreline of Puget Sound. In addition to chemical contaminants, small plastic particles (known as microplastics), found in marine waters of Puget Sound and suspected of being in aquatic sediments, are a potential concern because they can be ingested by animals and are suspected of transporting sorbed chemicals such as PCBs and metals.
The Stormwater Work Group of Puget Sound (SWG) (composed of State and municipal stormwater permittees, and other stakeholders) developed a strategy to address sediment conditions in the nearshore environment of Puget Sound. As part of this strategy, the SWG developed a regional stormwater monitoring strategy designed to inform monitoring requirements in National Pollutant Discharge Elimination System (NPDES) stormwater permits issued by the Washington State Department of Ecology (Ecology). The monitoring program is referred to as the Stormwater Action Monitoring (SAM).
The overall focus of the work described in this report is to address one of the goals of SAM, which is to characterize the status, spatial extent, and quality of Puget Sound sediment chemicals in the nearshore urban areas. The nearshore urban areas are defined as areas parallel to established Urban Growth Areas (UGAs) using a spatially balanced probabilistic Generalized Random Tessellation Stratified (GRTS) sampling design. One of the benefits of the GRTS sampling design used for this study is that it allows one to efficiently extrapolate from a relatively small number of sampled nearshore sites to the entire nearshore shoreline within the 2011 defined UGA boundaries of Puget Sound. In addition to characterizing nearshore sediment chemical concentrations, this study also characterized the abundance of microplastics in the nearshore sediment.
A total of 41 randomly selected sites were sampled throughout Puget Sound in summer and early autumn of 2016. All sampling sites were located at 6 feet below the Mean Lower Low Water line. The top 2–3 centimeters of sediment were collected using a boat-mounted, pre-cleaned stainless-steel box corer. All chemical samples were sieved to 2 millimeters and placed in appropriate containers for chemical analysis for PCBs, PBDEs, PAHs, phthalates, metals, total organic carbon, and grain size. Pre-sieved sediment samples were stored in glass containers for microplastic analysis. Nearshore sediment chemical concentrations were summarized using numerous statistical approaches to examine the minimum, mean, and maximum concentrations for each of the compounds analyzed and to compare the results to criteria and other nearshore and marine sediment studies.
The GRTS sampling design also allowed the authors to assess the percentage of the UGA nearshore environment that did not meet established standards or criteria for each chemical analyzed. Additionally, regression and machine learning statistical analyses were used to examine relations between measured chemical concentrations, and land cover and geologic features at multiple scales within the watersheds adjacent to sampling sites. The influence of marine hydrodynamic factors on nearshore sediment chemical concentrations was statistically evaluated with nonparametric methods by assigning each sampling site to one of five nearshore drift cell types based on its location. The Puget Sound shoreline can be divided into segments, referred to as drift cells, based on the movement of sediment along the shore by waves. Each drift cell type has a unique influence on nearshore sediment transport.
The nearshore sediment chemical concentrations for organics and metals generally were low, and in most cases less than Washington State criteria. The concentrations of some PAHs were greater than the criteria, but these exceedances were limited to one or two sites. The results of the probabilistic study design determined that, for the PAHs examined, 96 percent or more of the 1,344 km of shoreline represented by this study had concentrations less than any established criteria. For the remaining organics (PCBs and PBDEs), the probabilistic study design indicates that more than 98 percent of shoreline examined had concentrations less than criteria or proposed standards. For the metals, the results of the study indicate that 100 percent of the nearshore sediment had concentrations less than the criteria. The relations between sediment organic and metal concentrations, and adjacent watershed land cover and the particle size of the samples, were determined to be weakly related. Although weakly related, the particle size of the sediment in a sample typically explained more of the variation in metal concentrations than organics. While the measured watershed attributes adjacent to the sampling sites and sediment size of the samples were weakly related to chemical concentrations, they were significantly related to unique drift cells along the shoreline of Puget Sound known as drift cells. Each drift cell represents a long-term directional transport of sediment from its source to its depositional zone. Sediment chemical concentrations were significantly higher in drift cells with limited sediment movement compared to those with higher sediment transport energy.
Microplastics in the nearshore sediment ranged from 0.02 to 0.65 pieces per gram of sediment, with a mean of 0.19 pieces per gram of sediment, and were dominated by small fibers (355–1,000 micrometers). Like chemical concentrations, microplastics concentrations in the nearshore sediment were poorly related to watershed land cover. Although not significantly different, microplastics concentrations generally were higher in the low energy drift cells compared to the high energy drift cells.
The results of this study provide a statistically valid status assessment of current nearshore sediment chemical conditions throughout Puget Sound in those areas adjacent to defined UGAs. In addition to the study findings of relatively low concentrations of PCBs, PBDEs, PAHs, phthalates, and metals, the study design provides a statistically valid tool for evaluating changes in these compounds over time if future nearshore sediment assessments are done. Furthermore, the assessment of microplastic abundance represents the first study of its kind that can be used as a benchmark for future evaluations. The results of this study will help inform Ecology in the implementation of monitoring requirements as part of its NPDES stormwater permitting process.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185076","collaboration":"Prepared in cooperation with the Washington State Department of Ecology, Stormwater Action Monitoring (SAM) Program","usgsCitation":"Black, R.W., Barnes, A., Elliot, C., and Lanksbury, J., 2018, Nearshore sediment monitoring for the Stormwater Action Monitoring (SAM) Program, Puget Sound, western Washington: U.S. Geological Survey Scientific Investigations Report 2018-5076, 53 p., https://doi.org/10.3133/sir20185076.","productDescription":"Report: vii, 53 p.; Appendixes: 1-6","numberOfPages":"66","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-095908","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":355365,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5076/coverthb.jpg"},{"id":355367,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2018/5076/sir20184076_appendixes01-06.xlsx","text":"Appendixes 1–6","size":"73 KB xlsx","description":"SIR 2018-5076 Appendixes 01-06"},{"id":355366,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5076/sir20185076.pdf","text":"Report","size":"5.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5076"}],"country":"United States","state":"Washington","otherGeospatial":"Puget Sound","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -125.09033203124999,\n 46.51351558059737\n ],\n [\n -120.82763671875,\n 46.51351558059737\n ],\n [\n -120.82763671875,\n 49.993615462541136\n ],\n [\n -125.09033203124999,\n 49.993615462541136\n ],\n [\n -125.09033203124999,\n 46.51351558059737\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402
Local topographically driven processes – such as wind drifting, avalanching, and shading – are known to alter the relationship between the mass balance of small cirque glaciers and regional climate. Yet partitioning such local effects from regional climate influence has proven difficult, creating uncertainty in the climate representativeness of some glaciers. We address this problem for Sperry Glacier in Glacier National Park, USA, using field-measured surface mass balance, geodetic constraints on mass balance, and regional climate data recorded at a network of meteorological and snow stations. Geodetically derived mass changes during 1950–1960, 1960–2005, and 2005–2014 document average mass change rates during each period at −0.22 ± 0.12, −0.18 ± 0.05, and −0.10 ± 0.03 m w.e. yr−1, respectively. A correlation of field-measured mass balance and regional climate variables closely (i.e., within 0.08 m w.e. yr−1) predicts the geodetically measured mass loss from 2005 to 2014. However, this correlation overestimates glacier mass balance for 1950–1960 by +1.20 ± 0.95 m w.e. yr−1. Our analysis suggests that local effects, not represented in regional climate variables, have become a more dominant driver of the net mass balance as the glacier lost 0.50 km2 and retreated further into its cirque.
","language":"English","publisher":"European Geosciences Union","doi":"10.5194/tc-12-2109-2018","usgsCitation":"Florentine, C., Harper, J.T., Fagre, D.B., Moore, J., and Peitzsch, E.H., 2018, Local topography increasingly influences the mass balance of a retreating cirque glacier: The Cryosphere, v. 12, p. 2109-2122, https://doi.org/10.5194/tc-12-2109-2018.","productDescription":"14 p.","startPage":"2109","endPage":"2122","ipdsId":"IP-094543","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":468631,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/tc-12-2109-2018","text":"Publisher Index Page"},{"id":355348,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Northern Rocky Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.67,\n 48.1667\n ],\n [\n -113.33,\n 48.1667\n ],\n [\n -113.33,\n 48.9167\n ],\n [\n -114.67,\n 48.9167\n ],\n [\n -114.67,\n 48.1667\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"12","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-06-20","publicationStatus":"PW","scienceBaseUri":"5b46e54ee4b060350a15d0bd","contributors":{"authors":[{"text":"Florentine, Caitlyn 0000-0002-7028-0963","orcid":"https://orcid.org/0000-0002-7028-0963","contributorId":205964,"corporation":false,"usgs":true,"family":"Florentine","given":"Caitlyn","email":"","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":738982,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harper, Joel T.","contributorId":173392,"corporation":false,"usgs":false,"family":"Harper","given":"Joel","email":"","middleInitial":"T.","affiliations":[{"id":16951,"text":"Department of Geosciences, University of Montana, Missoula, MT 59812, USA","active":true,"usgs":false}],"preferred":false,"id":738983,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fagre, Daniel B. 0000-0001-8552-9461 dan_fagre@usgs.gov","orcid":"https://orcid.org/0000-0001-8552-9461","contributorId":2036,"corporation":false,"usgs":true,"family":"Fagre","given":"Daniel","email":"dan_fagre@usgs.gov","middleInitial":"B.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":738984,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Moore, Johnnie","contributorId":205965,"corporation":false,"usgs":false,"family":"Moore","given":"Johnnie","affiliations":[{"id":36523,"text":"University of Montana","active":true,"usgs":false}],"preferred":false,"id":738985,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Peitzsch, Erich H. 0000-0001-7624-0455 epeitzsch@usgs.gov","orcid":"https://orcid.org/0000-0001-7624-0455","contributorId":3786,"corporation":false,"usgs":true,"family":"Peitzsch","given":"Erich","email":"epeitzsch@usgs.gov","middleInitial":"H.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":738986,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70196224,"text":"sir20185049 - 2018 - Estimates of water use and trends in the Colorado River Basin, Southwestern United States, 1985–2010","interactions":[],"lastModifiedDate":"2018-06-27T08:36:36","indexId":"sir20185049","displayToPublicDate":"2018-06-26T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-5049","title":"Estimates of water use and trends in the Colorado River Basin, Southwestern United States, 1985–2010","docAbstract":"The Colorado River Basin (CRB) drains 246,000 square miles and includes parts of California, Colorado, Nevada, New Mexico, Utah, and Wyoming, and all of Arizona (Basin States). This report contains water-use estimates by category of use for drainage basins (Hydrologic Unit Code 8; HUC‑8) within the CRB from 1985 to 2010, at 5-year intervals. Estimates for public supply, domestic, commercial, industrial, irrigation, livestock, mining, aquaculture, hydroelectric and thermoelectric power, and wastewater returns are tabulated as (1) water withdrawals from groundwater or surface‑water sources of fresh or saline quality, (2) water delivered for domestic use, (3) wastewater returns and instream use (hydroelectric), and (4) consumptive use, or water that is consumed (USGS definition) and not available for immediate reuse. Water transported outside of the CRB (interbasin transfers) is not included as part of withdrawals and are not accounted for in any category of use within the CRB.
Total withdrawals in the CRB (excluding interbasin transfers) averaged about 17 million acre-feet (maf) from 1985 to 2010, peaked at about 17.76 maf in 2000, and reached their lowest levels of 16.43 maf in 1990. Interbasin transfers to serve mostly public-supply and irrigation needs outside of the CRB are reported for 2000, 2005, and 2010 only, and averaged 5.40 maf. More surface water was used in the CRB than groundwater, averaging about 78 percent of total withdrawals, and its use increased less than 2 percent from 1985 to 2010, while groundwater withdrawals decreased about 12 percent. From 1985 to 2010, surface water averaged 98 percent of withdrawals in the upper CRB, and about 59 percent in the lower CRB. Nearly all withdrawals were freshwater, but some saline groundwater was used for mining and self-supplied industrial.
Interbasin transfers have a large effect on flows in the Colorado River and are listed in this report separately with no explanation of how the water is used outside of the CRB. There are 34 interbasin transfers that conveyed an estimated 5.83, 5.20, and 5.18 maf out of the CRB in 2000, 2005, and 2010, respectively. The largest interbasin transfers are in the lower CRB and convey surface water (Colorado River water) to southern California; these accounted for 80 to 84 percent of total interbasin transfers in the CRB from 2000 to 2010. Intrabasin transfers are conveyances of surface water that cross drainage basin or State boundaries in the CRB, but the water does not leave the CRB. There are many intrabasin transfers in the CRB, but this report lists 11 that are mostly in the State of Colorado. The largest is the Central Arizona Project (CAP), through which more than 1.00 maf of water was provided to irrigate nearly 1 million acres in Maricopa, Pinal, and Pima Counties, as well as provide municipal water for Phoenix and Tucson, Arizona, during 2000, 2005, and 2010. In 2010, interbasin and intrabasin transfers accounted for 24 and 11 percent of the total water withdrawals in CRB, respectively, with the larger volumes being conveyed out of the lower CRB.
Total population in the CRB increased from 4.56 to 9.44 million people from 1985 to 2010. Most of those people were in the lower CRB, with 86 percent of the total in 1985, and 90 percent of the total in 2010. Total public-supply withdrawals in the CRB provided most people with their potable water, and averaged about 1.63 maf from 1985 to 2010, ranging from about 1.07 maf in 1985 to about 2.10 maf in 2010, when it peaked. Most of public-supply withdrawals occurred in the lower CRB, ranging from 87 to 91 percent of total public-supply withdrawals in the CRB over the 25 years. Total domestic use, comprised of public-supply deliveries and self-supply domestic withdrawals, increased more than 90 percent from 1985 to 2010, from about 0.80 maf to about 1.54 maf. Domestic daily per-capita use rates in the CRB ranged from about 144 (1985) to about 121 (2000) gallons (gal) per‑capita between 1985 and 2010. When comparing domestic daily per-capita rates for the upper and lower CRB, people in the lower CRB, on average, used less water for domestic purposes at 128 gal per-capita daily (1985–2010), while those in the upper CRB for the same time period averaged 133 gal per-capita daily. The trend in daily per-capita use rates for the entire CRB fluctuated between the reporting years, but decreased overall, indicating that more people used less water in 2010 than in 1985, likely due to improved infrastructure, conservation, and improvements to water using appliances in homes and businesses.
Irrigation accounted for most total withdrawals in the CRB, excluding instream use for hydroelectric power and interbasin transfers, averaging 85 percent from 1985 to 2010. Far more surface water than groundwater was used for irrigation in both the upper and lower CRB, but in the upper CRB, it accounted for an average of more than 98 percent of the total withdrawals (1985–2010), whereas in the lower CRB, surface-water withdrawals for irrigation averaged 61 percent of total withdrawals. On average, the upper CRB accounted for 56 percent of total irrigated acres, and the irrigation systems in the upper CRB trended towards more efficient sprinkler systems from 1985 to 2010. Long-term drought in the CRB substantially decreased the amount of streamflow available for irrigation. Increases in micro-irrigation acres, which can have efficiencies that exceed 90 percent and require 20–50 percent less water than sprinkler systems, likely contributed to reduced withdrawals in the lower CRB.
For thermoelectric power, total withdrawals, including the use of reclaimed wastewater, were greater in the upper CRB from 1985 through 2005. In 2010, the lower CRB exceeded the upper by only 11,000 acre-feet. On average, thermoelectric consumptive use accounted for about 80 percent of the total withdrawals; however, consumptive-use data in the upper CRB was incomplete. Surface water was the primary source in the upper CRB and groundwater was the primary source in the lower CRB. In the CRB overall, water withdrawals for thermoelectric generation has decreased since 2000, except for groundwater withdrawals in the lower CRB. Power generation at thermoelectric plants was greater in the upper CRB from 1985 to 2000, and after 2005 the difference in power generation was small; however, the upper CRB continued to have more power generation. In both the upper and lower CRB, power generation increased from 1985 to 2005.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185049","usgsCitation":"Maupin, M.A., Ivahnenko, T., and Bruce, B., 2018, Estimates of water use and trends in the Colorado River Basin, Southwestern United States, 1985–2010: U.S. Geological Survey Scientific Investigations Report 2018–5049, 61 p., https://doi.org/10.3133/sir20185049.","productDescription":"Report: ix, 61 p.; Data release","numberOfPages":"75","onlineOnly":"Y","ipdsId":"IP-074683","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":354013,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5049/sir20185049.pdf","text":"Report","size":"18.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5049"},{"id":354012,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5049/coverthb.jpg"},{"id":355338,"rank":3,"type":{"id":30,"text":"Data 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U.S. Geological Survey
230 Collins Road
Boise, Idaho 83702
The Cosumnes River watershed requires a 57–64 percent reduction in loads to meet the new Delta methylmercury (MeHg) total maximum daily load allocation, established by the Central Valley Regional Water Quality Control Board. Because there are no large point sources of MeHg in the watershed, the focus of MeHg load reductions will fall upon non-point sources, particularly the expansive wetlands considered to be a primary source of MeHg in the region. Few management practices have been implemented and tested in order to meet load reductions in managed wetlands, but recent efforts have shown promise. This project examines a treatment approach to reduce MeHg loads to the Sacramento-San Joaquin River Delta by creating open-water deep cells with a small footprint at the downstream end of wetlands to promote net demethylation of MeHg and to minimize MeHg and Hg loads exiting wetlands at the Cosumnes River Preserve. Specifically, the deep cells were were located immediately up gradient of the wetland’s outflow weir and were deep enough (75–91 centimeter depth) to be vegetation-free. The topographic and hydrologic structure of each treatment wetland was modified to include open-water deep cells so that the removal of aqueous MeHg might be enhanced through (1) particle settling, (2) photo-degradation, and (3) benthic microbial demethylation. These deep cells were, therefore, expected to clean MeHg from surface water prior to its discharge to the Cosumnes River and the downstream Delta.
Our goal was to test whether the implementation of the deep cells within wetlands would minimize MeHg and total Hg export. Further, we sought to test whether continuous flow-through hydrology, would lower MeHg concentrations in resident biota, compared to traditional wetland management operations. The dominant practice in seasonal wetlands management is the “fill-and-maintain” approach, in which wetlands are filled with water and the water levels maintained without substantial draining until drawdown. Our approach was to create and characterize replicate treatment wetland complexes, in conjunction with monitoring of hydrologic, biologic, and chemical indicators of MeHg exposure for two full annual cycles within winter-spring flooded seasonal wetlands. In addition to the creation of deep cells within treatment wetlands, hydrology was manipulated so that there was a constant flow-through of water, while the control wetlands utilized the fill-and-maintain approach. Specifically, the treatment wetlands were maintained in a flow-through manner, while the control wetlands were maintained in a fill-and-maintain manner from September through May, to test the hypothesis that the flow of water through the seasonal wetland can lower fish bioaccumulation through dilution of MeHg-concentrated water within the wetland by constant inflows of water into the wetland.
The major tasks of this study included: (1) field design and implementation, (2) water and wetland management, (3) hydrologic monitoring and water quality sampling, (4) MeHg export and load estimates, (5) caged fish experiments for examining MeHg bioaccumulation, (6) site and process characterization to improve understanding and transferability of results, (7) adaptive management, transferability, and outreach, and (8) reporting of results and conclusions. This report summarizes the key findings of this study, which focuses on MeHg load estimates from control and treatment wetlands, quantification of three MeHg removal mechanisms (particulate settling, benthic demethylation, and photo-demethylation) in the deep cells within the treatment wetlands, and MeHg bioaccumulation in wetland fishes.
Key findings include:
Hydro-Eco Interactions Branch
U.S. Geological Survey
345 Middlefield Road
Menlo Park, CA 94025
https://water.usgs.gov
Acetylene (IUPAC name: ethyne) is a colorless, gaseous hydrocarbon, composed of two triple bonded carbon atoms attached to hydrogens (C2H2). When microbiologists and biogeochemists think of acetylene, they immediately think of its use as an inhibitory compound of certain microbial processes and a tracer for nitrogen fixation. However, what is less widely known is that anaerobic and aerobic microorganisms can degrade acetylene, using it as a sole carbon and energy source and providing the basis of a microbial food web. Here, we review what is known about acetylene degrading organisms and introduce the term 'acetylenotrophs' to refer to the microorganisms that carry out this metabolic pathway. In addition, we review the known environmental sources of acetylene and postulate the presence of an hidden acetylene cycle. The abundance of bacteria capable of using acetylene and other alkynes as an energy and carbon source suggests that there are energy cycles present in the environment that are driven by acetylene and alkyne production and consumption that are isolated from atmospheric exchange. Acetylenotrophs may have developed to leverage the relatively high concentrations of acetylene in the pre-Cambrian atmosphere, evolving later to survive in specialized niches where acetylene and other alkynes were produced.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/femsec/fiy103","usgsCitation":"Akob, D.M., Sutton, J.M., Fierst, J.L., Haase, K.B., Baesman, S., Luther, G., Miller, L., and Oremland, R.S., 2018, Acetylenotrophy: A hidden but ubiquitous microbial metabolism?: FEMS Microbiology Ecology, v. 94, no. 8, p. 1-14, https://doi.org/10.1093/femsec/fiy103.","productDescription":"Article fiy103; 14 p.","startPage":"1","endPage":"14","ipdsId":"IP-096218","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":468632,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/femsec/fiy103","text":"Publisher Index Page"},{"id":355323,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"94","issue":"8","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-05-31","publicationStatus":"PW","scienceBaseUri":"5b46e54fe4b060350a15d0c5","contributors":{"authors":[{"text":"Akob, Denise M. 0000-0003-1534-3025 dakob@usgs.gov","orcid":"https://orcid.org/0000-0003-1534-3025","contributorId":4980,"corporation":false,"usgs":true,"family":"Akob","given":"Denise","email":"dakob@usgs.gov","middleInitial":"M.","affiliations":[{"id":5058,"text":"Office of the Chief Scientist for Water","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":738931,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sutton, John M.","contributorId":179294,"corporation":false,"usgs":false,"family":"Sutton","given":"John","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":738932,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fierst, Janna L.","contributorId":179295,"corporation":false,"usgs":false,"family":"Fierst","given":"Janna","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":738933,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Haase, Karl B. 0000-0002-6897-6494 khaase@usgs.gov","orcid":"https://orcid.org/0000-0002-6897-6494","contributorId":3405,"corporation":false,"usgs":true,"family":"Haase","given":"Karl","email":"khaase@usgs.gov","middleInitial":"B.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":738934,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Baesman, Shaun 0000-0003-0741-8269 sbaesman@usgs.gov","orcid":"https://orcid.org/0000-0003-0741-8269","contributorId":3478,"corporation":false,"usgs":true,"family":"Baesman","given":"Shaun","email":"sbaesman@usgs.gov","affiliations":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":738935,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Luther, George","contributorId":199947,"corporation":false,"usgs":false,"family":"Luther","given":"George","affiliations":[],"preferred":false,"id":738936,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Miller, Laurence G. 0000-0002-7807-3475 lgmiller@usgs.gov","orcid":"https://orcid.org/0000-0002-7807-3475","contributorId":2460,"corporation":false,"usgs":true,"family":"Miller","given":"Laurence G.","email":"lgmiller@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":738937,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Oremland, Ronald S. 0000-0001-7382-0147 roremlan@usgs.gov","orcid":"https://orcid.org/0000-0001-7382-0147","contributorId":931,"corporation":false,"usgs":true,"family":"Oremland","given":"Ronald","email":"roremlan@usgs.gov","middleInitial":"S.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":738938,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70197881,"text":"70197881 - 2018 - Environmentally relevant chemical mixtures of concern in waters of United States tributaries to the Great Lakes","interactions":[],"lastModifiedDate":"2018-06-25T10:56:09","indexId":"70197881","displayToPublicDate":"2018-06-25T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2006,"text":"Integrated Environmental Assessment and Management","active":true,"publicationSubtype":{"id":10}},"title":"Environmentally relevant chemical mixtures of concern in waters of United States tributaries to the Great Lakes","docAbstract":"The North American Great Lakes are a vital natural resource that provide fish and wildlife habitat, as well as drinking water and waste assimilation services for millions of people. Tributaries to the Great Lakes receive chemical inputs from various point and nonpoint sources, and thus are expected to have complex mixtures of chemicals. However, our understanding of the co‐occurrence of specific chemicals in complex mixtures is limited. To better understand the occurrence of specific chemical mixtures in the US Great Lakes Basin, surface water from 24 US tributaries to the Laurentian Great Lakes was collected and analyzed for diverse suites of organic chemicals, primarily focused on chemicals of concern (e.g., pharmaceuticals, personal care products, fragrances). A total of 181 samples and 21 chemical classes were assessed for mixture compositions. Basin wide, 1664 mixtures occurred in at least 25% of sites. The most complex mixtures identified comprised 9 chemical classes and occurred in 58% of sampled tributaries. Pharmaceuticals typically occurred in complex mixtures, reflecting pharmaceutical‐use patterns and wastewater facility outfall influences. Fewer mixtures were identified at lake or lake‐influenced sites than at riverine sites. As mixture complexity increased, the probability of a specific mixture occurring more often than by chance greatly increased, highlighting the importance of understanding source contributions to the environment. This empirically based analysis of mixture composition and occurrence may be used to focus future sampling efforts or mixture toxicity assessments.
","language":"English","publisher":"Society of Environmental Toxicology and Chemistry","doi":"10.1002/ieam.4041","usgsCitation":"Elliott, S.M., Brigham, M.E., Kiesling, R.L., Schoenfuss, H.L., and Jorgenson, Z.G., 2018, Environmentally relevant chemical mixtures of concern in waters of United States tributaries to the Great Lakes: Integrated Environmental Assessment and Management, v. 14, no. 4, p. 509-518, https://doi.org/10.1002/ieam.4041.","productDescription":"10 p.","startPage":"509","endPage":"518","ipdsId":"IP-087836","costCenters":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"links":[{"id":355324,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Great Lakes","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92,\n 40\n ],\n [\n -74,\n 40\n ],\n [\n -74,\n 49.5\n ],\n [\n -92,\n 49.5\n ],\n [\n -92,\n 40\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"14","issue":"4","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-08","publicationStatus":"PW","scienceBaseUri":"5b46e550e4b060350a15d0c7","contributors":{"authors":[{"text":"Elliott, Sarah M. 0000-0002-1414-3024 selliott@usgs.gov","orcid":"https://orcid.org/0000-0002-1414-3024","contributorId":1472,"corporation":false,"usgs":true,"family":"Elliott","given":"Sarah","email":"selliott@usgs.gov","middleInitial":"M.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":738926,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brigham, Mark E. 0000-0001-7412-6800 mbrigham@usgs.gov","orcid":"https://orcid.org/0000-0001-7412-6800","contributorId":1840,"corporation":false,"usgs":true,"family":"Brigham","given":"Mark","email":"mbrigham@usgs.gov","middleInitial":"E.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":738927,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kiesling, Richard L. 0000-0002-3017-1826 kiesling@usgs.gov","orcid":"https://orcid.org/0000-0002-3017-1826","contributorId":1837,"corporation":false,"usgs":true,"family":"Kiesling","given":"Richard","email":"kiesling@usgs.gov","middleInitial":"L.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":738928,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schoenfuss, Heiko L.","contributorId":76409,"corporation":false,"usgs":false,"family":"Schoenfuss","given":"Heiko","email":"","middleInitial":"L.","affiliations":[{"id":13317,"text":"Saint Cloud State University","active":true,"usgs":false}],"preferred":false,"id":738929,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jorgenson, Zachary G.","contributorId":69476,"corporation":false,"usgs":false,"family":"Jorgenson","given":"Zachary","email":"","middleInitial":"G.","affiliations":[{"id":13317,"text":"Saint Cloud State University","active":true,"usgs":false}],"preferred":false,"id":738930,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70197455,"text":"fs20183033 - 2018 - Assessment of undiscovered oil and gas resources in the Eagle Ford Group and associated Cenomanian–Turonian Strata, U.S. Gulf Coast, Texas, 2018","interactions":[],"lastModifiedDate":"2018-06-22T10:08:55","indexId":"fs20183033","displayToPublicDate":"2018-06-22T11:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-3033","title":"Assessment of undiscovered oil and gas resources in the Eagle Ford Group and associated Cenomanian–Turonian Strata, U.S. Gulf Coast, Texas, 2018","docAbstract":"Using a geology-based assessment methodology, the U.S. Geological Survey estimated undiscovered, technically recoverable mean resources of 8.5 billion barrels of oil and 66 trillion cubic feet of gas in continuous accumulations in the Upper Cretaceous Eagle Ford Group and associated Cenomanian–Turonian strata in onshore lands of the U.S. Gulf Coast region, Texas.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/fs20183033","usgsCitation":"Whidden, K.J., Pitman, J.K., Pearson, O.N., Paxton, S.T., Kinney, S.A., Gianoutsos, N.J., Schenk, C.J., Leathers-Miller, H.M., Birdwell, J.E., Brownfield, M.E., Burke, L.A., Dubiel, R.F., French, K.L., Gaswirth, S.B., Haines, S.S., Le, P.A., Marra, K.R., Mercier, T.J., Tennyson, M.E., and Woodall, C.A., 2018, Assessment of undiscovered oil and gas resources in the Eagle Ford Group and associated Cenomanian–Turonian strata, U.S. Gulf Coast, Texas, 2018: U.S. Geological Survey Fact Sheet 2018–3033, 4 p., https://doi.org/10.3133/fs20183033. ","productDescription":"4 p.","onlineOnly":"N","ipdsId":"IP-098113","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":437846,"rank":12,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9BH0ED5","text":"USGS data release","linkHelpText":"Estimated Ultimate Recoveries of Oil Wells in the Eagle Ford Group and Associated Cenomanian–Turonian Strata, U.S. Gulf Coast, Texas, 2018"},{"id":354803,"rank":9,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/fs20133013","text":"Fact Sheet 2013–3013:","linkHelpText":"Assessment of Undiscovered Oil Resources in the Bakken and Three Forks Formations, Williston Basin Province, Montana, North Dakota, and South Dakota, 2013"},{"id":354804,"rank":10,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/fs20123116","text":"Fact Sheet 2012–3116:","linkHelpText":"Assessment of Undiscovered Oil and Gas Resources of the Ordovician Utica Shale of the Appalachian Basin Province, 2012"},{"id":354805,"rank":11,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/fs20113092","text":"Fact Sheet 2011–3092:","linkHelpText":"Assessment of Undiscovered Oil and Gas Resources of the Devonian Marcellus Shale of the Appalachian Basin Province, 2011"},{"id":354801,"rank":7,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/fs20163030","text":"Fact Sheet 2016–3030:","linkHelpText":"Assessment of Continuous (Unconventional) Oil and Gas Resources in the Late Cretaceous Mancos Shale of the Piceance Basin, Uinta-Piceance Province, Colorado and Utah, 2016"},{"id":354798,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/fs20173015","text":"Fact Sheet 2017–3015:","linkHelpText":"Assessment of Undiscovered Oil and Gas Resources in the Bossier Formation, U.S. Gulf Coast, 2016"},{"id":354802,"rank":8,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/fs20153078","text":"Fact Sheet 2015–3078:","linkHelpText":"Assessment of Undiscovered Shale Gas and Shale Oil Resources in the Mississippian Barnett Shale, Bend Arch–Fort Worth Basin Province, North-Central Texas"},{"id":354797,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/fs20173016","text":"Fact Sheet 2017–3016:","linkHelpText":"Assessment of Undiscovered Oil and Gas Resources in the Haynesville Formation, U.S. Gulf Coast, 2016"},{"id":354800,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/fs20163092","text":"Fact Sheet 2016–3092:","linkHelpText":"Assessment of Undiscovered Continuous Oil Resources in the Wolfcamp Shale of the Midland Basin, Permian Basin Province, Texas, 2016"},{"id":354793,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2018/3033/coverthb.jpg"},{"id":354794,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2018/3033/fs20183033.pdf","text":"Report","size":"5.13 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2018-3033"},{"id":354796,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/fs20173029","text":"Fact Sheet 2017–3029:","linkHelpText":"Assessment of Undiscovered Oil and Gas Resources in the Spraberry Formation of the Midland Basin, Permian Basin Province, Texas, 2017"}],"country":"United States","state":"Louisiana, Texas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -101.3818359375,\n 25.16517336866393\n ],\n [\n -88.330078125,\n 25.16517336866393\n ],\n [\n -88.330078125,\n 32.175612478499325\n ],\n [\n -101.3818359375,\n 32.175612478499325\n ],\n [\n -101.3818359375,\n 25.16517336866393\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver, CO 80225-0046
Besides performing multiple ecosystem services individually and collectively, biocrust constituents may also create biological networks connecting spatially and temporally distinct processes. In the fungal loop hypothesis rainfall variability allows fungi to act as conduits and reservoirs, translocating resources between soils and host plants. To evaluate the extent to which biocrust species composition and nitrogen (N) form influence loops, we created a minor, localized rainfall event containing 15NH4+ and 15NO3−. We then measured the resulting δ15N in the surrounding dry cyanobacteria- and lichen-dominated crusts and grass, Achnatherum hymenoides, after 24 h. We also estimated the biomass of fungal constituents using quantitative PCR and characterized fungal communities by sequencing the 18S rRNA gene. We found evidence for the initiation of fungal loops in cyanobacteria-dominated crusts where 15N, from 15NH4+, moved 40 mm h−1 in biocrust soils with the δ15N of crusts decreasing as the radial distance from the water addition increased (linear mixed effects model (LMEM)): R2 = 0.67, F2,12 = 11, P = 0.002). In cyanobacteria crusts, δ15N, from 15NH4+, was diluted as Ascomycota biomass increased (LMEM: R2 = 0.63, F2,8 = 6.8, P = 0.02), Ascomycota accounted for 82 % (±2.8) of all fungal sequences, and one order, Pleosporales, comprised 66 % (±6.9) of Ascomycota. The seeming lack of loops in moss-dominated crusts may stem from the relatively large moss biomass effectively absorbing and holding N from our minor wet deposition event. The substantial movement of 15NH4+ may indicate a fungal preference for the reduced N form during amino acid transformation and translocation. We found a marginally significant enrichment of δ15N in A. hymenoides leaves but only in cyanobacteria biocrusts translocating 15N, offering evidence of links between biocrust constituents and higher plants. Our results suggest that minor rainfall events may initiate fungal loops potentially allowing constituents, like dark septate Pleosporales, to rapidly translocate N from NH4+ over NO3− through biocrust networks.
","language":"English","publisher":"Copernicus Publications","doi":"10.5194/bg-15-3831-2018","usgsCitation":"Aanderud, Z.T., Smart, T.B., Wu, N., Taylor, A.S., Zhang, Y., and Belnap, J., 2018, Fungal loop transfer of nitrogen depends on biocrust constituents and nitrogen form: Biogeosciences, v. 15, no. 12, p. 3831-3840, https://doi.org/10.5194/bg-15-3831-2018.","productDescription":"10 p.","startPage":"3831","endPage":"3840","ipdsId":"IP-091786","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":468633,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/bg-15-3831-2018","text":"Publisher Index Page"},{"id":356987,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"15","issue":"12","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-06-22","publicationStatus":"PW","scienceBaseUri":"5b98a2a3e4b0702d0e842fa8","contributors":{"authors":[{"text":"Aanderud, Zachary T.","contributorId":176977,"corporation":false,"usgs":false,"family":"Aanderud","given":"Zachary","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":743959,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smart, Trevor B.","contributorId":207495,"corporation":false,"usgs":false,"family":"Smart","given":"Trevor","email":"","middleInitial":"B.","affiliations":[{"id":37545,"text":"Department of Plant and Wildlife Sciences, Brigham Young University, Provo, UT 84602, USA","active":true,"usgs":false}],"preferred":false,"id":743960,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wu, Nan","contributorId":207496,"corporation":false,"usgs":false,"family":"Wu","given":"Nan","email":"","affiliations":[{"id":37546,"text":"Xinjiang Institute of Ecology and Geography, Key Laboratory of Biogeography and Bioresource in Arid Land, Chinese Academy of Sciences,","active":true,"usgs":false}],"preferred":false,"id":743961,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Taylor, Alexander S.","contributorId":207497,"corporation":false,"usgs":false,"family":"Taylor","given":"Alexander","email":"","middleInitial":"S.","affiliations":[{"id":37545,"text":"Department of Plant and Wildlife Sciences, Brigham Young University, Provo, UT 84602, USA","active":true,"usgs":false}],"preferred":false,"id":743963,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zhang, Yuanming","contributorId":173232,"corporation":false,"usgs":false,"family":"Zhang","given":"Yuanming","email":"","affiliations":[{"id":27200,"text":"Key Laboratory of Biogeography and Bioresource in Arid Land, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China","active":true,"usgs":false}],"preferred":false,"id":743962,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Belnap, Jayne 0000-0001-7471-2279 jayne_belnap@usgs.gov","orcid":"https://orcid.org/0000-0001-7471-2279","contributorId":1332,"corporation":false,"usgs":true,"family":"Belnap","given":"Jayne","email":"jayne_belnap@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":743958,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70196364,"text":"sir20185038 - 2018 - Extraction and development of inset models in support of groundwater age calculations for glacial aquifers","interactions":[],"lastModifiedDate":"2018-06-22T10:10:22","indexId":"sir20185038","displayToPublicDate":"2018-06-22T09:15:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-5038","title":"Extraction and development of inset models in support of groundwater age calculations for glacial aquifers","docAbstract":"The U.S. Geological Survey developed a regional model of Lake Michigan Basin (LMB). This report describes the construction of five MODFLOW inset models extracted from the LMB regional model and their application using the particle-tracking code MODPATH to simulate the groundwater age distribution of discharge to wells pumping from glacial deposits. The five study areas of the inset model correspond to 8-digit hydrologic unit code (HUC8) basins. Two of the basins are tributary to Lake Michigan from the east, two are tributary to the lake from the west, and one is just west of the western boundary of the Lake Michigan topographic basin. The inset models inherited many of the inputs to the parent LMB model, including the hydrostratigraphy and layering scheme, the hydraulic conductivity assigned to bedrock layers, recharge distribution, and water use in the form of pumping rates from glacial and bedrock wells. The construction of the inset models entailed modifying some inputs, most notably the grid spacing (reduced from cells 5,000 feet on a side in the parent LMB model to 500 feet on a side in the inset models). The refined grid spacing allowed for more precise location of pumped wells and more detailed simulation of groundwater/surface-water interactions. The glacial hydraulic conductivity values, the top bedrock surface elevation, and the surface-water network input to the inset models also were modified. The inset models are solved using the MODFLOW–NWT code, which allows for more robust handling of conditions in unconfined aquifers than previous versions of MODFLOW. Comparison of the MODFLOW inset models reveals that they incorporate a range of hydrogeologic conditions relative to the glacial part of the flow system, demonstrated by visualization and analysis of model inputs and outputs and reflected in the range of ages generated by MODPATH for existing and hypothetical glacial wells. Certain inputs and outputs are judged to be candidate predictors that, if treated statistically, may be capable of explaining much of the variance in the simulated age metrics. One example of a predictor that model results indicate strongly affects simulated age is the depth of the well open interval below the simulated water table. The strength of this example variable as an overall predictor of groundwater age and its relation to other predictors can be statistically tested through the metamodeling process. In this way the inset models are designed to serve as a training area for metamodels that estimate groundwater age in glacial wells, which in turn will contribute to ongoing studies, under the direction of the U.S. Geological Survey National Water Quality Assessment, of contaminant susceptibility of shallow groundwater across the glacial aquifer system.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185038","usgsCitation":"Feinstein, D.T., Kauffman, L.J., Haserodt, M.J., Clark, B.R., and Juckem, P.F., 2018, Extraction and development of inset models in support of groundwater age calculations for glacial aquifers: U.S. Geological Survey Scientific Investigations Report 2018–5038, 96 p., https://doi.org/10.3133/sir20185038.","productDescription":"Report: viii, 96 p.; Data release","numberOfPages":"108","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-081404","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":355245,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5038/sir20185038.pdf","text":"Report","size":"39.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5038"},{"id":355246,"rank":3,"type":{"id":30,"text":"Data Release"},"url":" https://doi.org/10.5066/F76D5R5V","text":"USGS data release","description":"USGS data release","linkHelpText":"MODFLOW-NWT inset models from the regional Lake Michigan Basin Model in support of groundwater age calculations for glacial aquifers"},{"id":355244,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5038/coverthb.jpg"}],"country":"United States","state":"Illinois, Indiana, Michigan, Wisconsin","otherGeospatial":"Lake Michigan Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.615234375,\n 40.413496049701955\n ],\n [\n -81.5185546875,\n 40.413496049701955\n ],\n [\n -81.5185546875,\n 46.830133640447386\n ],\n [\n -90.615234375,\n 46.830133640447386\n ],\n [\n -90.615234375,\n 40.413496049701955\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Midwest Water Science Center
8505 Research Way
Middleton, WI 53562
(608) 828–9901
We assessed hematozoa infection in Spectacled Eiders (Somateria fischeri) at two areas in Alaska. No Haemoproteus or Plasmodium species were detected. Leucocytozoon prevalence was 6.5% for adults across sites and 41.9% for juveniles sampled in the Arctic, providing evidence for local transmission. All Leucocytozoon haplotypes were previously detected in waterfowl.
","language":"English","publisher":"Wildlife Disease Association","doi":"10.7589/2018-01-012","usgsCitation":"Reed, J.A., Sexson, M.G., Smith, M.M., Schmutz, J.A., and Ramey, A.M., 2018, Evidence for haemosporidian parasite infections in Spectacled Eiders (Somateria fischeri) sampled in Alaska during the breeding season: Journal of Wildlife Diseases, v. 54, no. 4, p. 877-880, https://doi.org/10.7589/2018-01-012.","productDescription":"4 p.","startPage":"877","endPage":"880","ipdsId":"IP-094145","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":437847,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9CDBRDC","text":"USGS data release","linkHelpText":"Blood Parasite Infection Data from Spectacled Eiders (Somateria fischeri), Alaska (USA), 2008-2012"},{"id":355316,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","volume":"54","issue":"4","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b46e552e4b060350a15d0cf","contributors":{"authors":[{"text":"Reed, John A. 0000-0002-3239-6906 jareed@usgs.gov","orcid":"https://orcid.org/0000-0002-3239-6906","contributorId":127683,"corporation":false,"usgs":true,"family":"Reed","given":"John","email":"jareed@usgs.gov","middleInitial":"A.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":738844,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sexson, Matthew G. 0000-0002-1078-0835 msexson@usgs.gov","orcid":"https://orcid.org/0000-0002-1078-0835","contributorId":5544,"corporation":false,"usgs":true,"family":"Sexson","given":"Matthew","email":"msexson@usgs.gov","middleInitial":"G.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":false,"id":738845,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, Matthew M. 0000-0002-2259-5135 mmsmith@usgs.gov","orcid":"https://orcid.org/0000-0002-2259-5135","contributorId":5115,"corporation":false,"usgs":true,"family":"Smith","given":"Matthew","email":"mmsmith@usgs.gov","middleInitial":"M.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":738846,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schmutz, Joel A. 0000-0002-6516-0836 jschmutz@usgs.gov","orcid":"https://orcid.org/0000-0002-6516-0836","contributorId":1805,"corporation":false,"usgs":true,"family":"Schmutz","given":"Joel","email":"jschmutz@usgs.gov","middleInitial":"A.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":738847,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ramey, Andrew M. 0000-0002-3601-8400 aramey@usgs.gov","orcid":"https://orcid.org/0000-0002-3601-8400","contributorId":1872,"corporation":false,"usgs":true,"family":"Ramey","given":"Andrew","email":"aramey@usgs.gov","middleInitial":"M.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":738848,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70197874,"text":"70197874 - 2018 - Riparian spiders indicate the magnitude and sources of polychlorinated biphenyl (PCB) contamination at a large contaminated sediment site","interactions":[],"lastModifiedDate":"2018-08-31T10:53:08","indexId":"70197874","displayToPublicDate":"2018-06-22T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1571,"text":"Environmental Toxicology and Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Riparian spiders indicate the magnitude and sources of polychlorinated biphenyl (PCB) contamination at a large contaminated sediment site","docAbstract":"We investigated PCB contamination at the Ashtabula River Area of Concern (AOC) following remedial dredging using araneid and tetragnathid spiders. PCB concentrations remain elevated in the AOC compared to reference conditions. Patterns of contamination were strikingly similar between taxa, but were higher in tetragnathids at the most contaminated sites. Spider PCB homolog distributions identified two PCB sources to the AOC. Based on these findings, we recommend situations where these taxa can be used singularly, in concert, or combined into a composite “spider” sample to assess environmental contamination.
","language":"English","publisher":"Society of Environmental Toxicology and Chemistry","doi":"10.1002/etc.4216","usgsCitation":"Walters, D.M., Otter, R.R., Kraus, J.M., and Mills, M.A., 2018, Riparian spiders indicate the magnitude and sources of polychlorinated biphenyl (PCB) contamination at a large contaminated sediment site: Environmental Toxicology and Chemistry, v. 37, no. 9, p. 2467-2474, https://doi.org/10.1002/etc.4216.","productDescription":"8 p.","startPage":"2467","endPage":"2474","ipdsId":"IP-094555","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":437848,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9SX2FCX","text":"USGS data release","linkHelpText":"Polychlorinated biphenyl concentrations and lipid content in riparian spiders at the Ashtabula River Area of Concern, USA"},{"id":355317,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"37","issue":"9","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-06-21","publicationStatus":"PW","scienceBaseUri":"5b46e551e4b060350a15d0cd","contributors":{"authors":[{"text":"Walters, David M. 0000-0002-4237-2158 waltersd@usgs.gov","orcid":"https://orcid.org/0000-0002-4237-2158","contributorId":140992,"corporation":false,"usgs":true,"family":"Walters","given":"David","email":"waltersd@usgs.gov","middleInitial":"M.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":738849,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Otter, Ryan R.","contributorId":205916,"corporation":false,"usgs":false,"family":"Otter","given":"Ryan","email":"","middleInitial":"R.","affiliations":[{"id":37193,"text":"Middle Tennessee State University","active":true,"usgs":false}],"preferred":false,"id":738850,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kraus, Johanna M. 0000-0002-9513-4129 jkraus@usgs.gov","orcid":"https://orcid.org/0000-0002-9513-4129","contributorId":4834,"corporation":false,"usgs":true,"family":"Kraus","given":"Johanna","email":"jkraus@usgs.gov","middleInitial":"M.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":738851,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mills, Marc A.","contributorId":141085,"corporation":false,"usgs":false,"family":"Mills","given":"Marc","email":"","middleInitial":"A.","affiliations":[{"id":12772,"text":"USEPA","active":true,"usgs":false}],"preferred":false,"id":738852,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70197861,"text":"70197861 - 2018 - Tracing enhanced oil recovery signatures in casing gases from the Lost Hills oil field using noble gases","interactions":[],"lastModifiedDate":"2018-06-22T14:25:56","indexId":"70197861","displayToPublicDate":"2018-06-22T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1427,"text":"Earth and Planetary Science Letters","active":true,"publicationSubtype":{"id":10}},"title":"Tracing enhanced oil recovery signatures in casing gases from the Lost Hills oil field using noble gases","docAbstract":"Enhanced oil recovery (EOR) and hydraulic fracturing practices are commonly used methods to improve hydrocarbon extraction efficiency; however the environmental impacts of such practices remain poorly understood. EOR is particularly prevalent in oil fields throughout California where water resources are in high demand and disposal of high volumes of produced water may affect groundwater quality. Consequently, it is essential to better understand the fate of injected (EOR) fluids in California and other subsurface petroleum systems, as well as any potential effect on nearby aquifer systems. Noble gases can be used as tracers to understand hydrocarbon generation, migration, and storage conditions, as well as the relative proportions of oil and water present in the subsurface. In addition, a noble gas signature diagnostic of injected (EOR) fluids can be readily identified. We report noble gas isotope and concentration data in casing gases from oil production wells in the Lost Hills oil field, northwest of Bakersfield, California, and injectate gas data from the Fruitvale oil field, located within the city of Bakersfield. Casing and injectate gas data are used to: 1) establish pristine hydrocarbon noble-gas signatures and the processes controlling noble gas distributions, 2) characterize the noble gas signature of injectate fluids, 3) trace injectate fluids in the subsurface, and 4) construct a model to estimate EOR efficiency. Noble gas results range from pristine to significantly modified by EOR, and can be best explained using a solubility exchange model between oil and connate/formation fluids, followed by gas exsolution upon production. This model is sensitive to oil-water interaction during hydrocarbon expulsion, migration, and storage at reservoir conditions, as well as any subsequent modification by EOR.","language":"English","publisher":"Elsevier","doi":"10.1016/j.epsl.2018.05.028","usgsCitation":"Barry, P.H., Kulongoski, J.T., Landon, M.K., Tyne, R.L., Gillespie, J., Stephens, M.J., Hillegonds, D., Byrne, D., and Ballentine, C., 2018, Tracing enhanced oil recovery signatures in casing gases from the Lost Hills oil field using noble gases: Earth and Planetary Science Letters, v. 496, p. 57-67, https://doi.org/10.1016/j.epsl.2018.05.028.","productDescription":"11 p.","startPage":"57","endPage":"67","ipdsId":"IP-092040","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":468634,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://ora.ox.ac.uk/objects/uuid:5065b220-4d22-4bf9-9f89-b0cc7e00a948","text":"Publisher Index Page"},{"id":355310,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.88693237304688,\n 35.529152854619\n ],\n [\n -119.59236145019531,\n 35.529152854619\n ],\n [\n -119.59236145019531,\n 35.72170907899236\n ],\n [\n -119.88693237304688,\n 35.72170907899236\n ],\n [\n -119.88693237304688,\n 35.529152854619\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"496","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b46e553e4b060350a15d0d3","contributors":{"authors":[{"text":"Barry, Peter H. 0000-0002-6960-1555","orcid":"https://orcid.org/0000-0002-6960-1555","contributorId":205890,"corporation":false,"usgs":true,"family":"Barry","given":"Peter","email":"","middleInitial":"H.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":738788,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kulongoski, Justin T. 0000-0002-3498-4154 kulongos@usgs.gov","orcid":"https://orcid.org/0000-0002-3498-4154","contributorId":173457,"corporation":false,"usgs":true,"family":"Kulongoski","given":"Justin","email":"kulongos@usgs.gov","middleInitial":"T.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":738789,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Landon, Matthew K. 0000-0002-5766-0494 landon@usgs.gov","orcid":"https://orcid.org/0000-0002-5766-0494","contributorId":392,"corporation":false,"usgs":true,"family":"Landon","given":"Matthew","email":"landon@usgs.gov","middleInitial":"K.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":738790,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tyne, R. L.","contributorId":205891,"corporation":false,"usgs":false,"family":"Tyne","given":"R.","email":"","middleInitial":"L.","affiliations":[{"id":37187,"text":"Department of Earth Sciences, University of Oxford, Oxford, UK","active":true,"usgs":false}],"preferred":false,"id":738791,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gillespie, Janice M. 0000-0003-1667-3472","orcid":"https://orcid.org/0000-0003-1667-3472","contributorId":203915,"corporation":false,"usgs":true,"family":"Gillespie","given":"Janice M.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":738792,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stephens, Michael J. 0000-0001-8995-9928","orcid":"https://orcid.org/0000-0001-8995-9928","contributorId":205895,"corporation":false,"usgs":true,"family":"Stephens","given":"Michael","email":"","middleInitial":"J.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":738796,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hillegonds, D.J.","contributorId":205892,"corporation":false,"usgs":false,"family":"Hillegonds","given":"D.J.","email":"","affiliations":[{"id":37187,"text":"Department of Earth Sciences, University of Oxford, Oxford, UK","active":true,"usgs":false}],"preferred":false,"id":738793,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Byrne, D.J.","contributorId":205893,"corporation":false,"usgs":false,"family":"Byrne","given":"D.J.","email":"","affiliations":[{"id":37187,"text":"Department of Earth Sciences, University of Oxford, Oxford, UK","active":true,"usgs":false}],"preferred":false,"id":738794,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Ballentine, C.J.","contributorId":205894,"corporation":false,"usgs":false,"family":"Ballentine","given":"C.J.","email":"","affiliations":[{"id":37187,"text":"Department of Earth Sciences, University of Oxford, Oxford, UK","active":true,"usgs":false}],"preferred":false,"id":738795,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70197857,"text":"70197857 - 2018 - Arsenic geochemistry of alluvial sediments and pore waters affected by mine tailings along the Belle Fourche and Cheyenne River floodplains","interactions":[],"lastModifiedDate":"2018-06-22T09:56:46","indexId":"70197857","displayToPublicDate":"2018-06-22T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3728,"text":"Water, Air, & Soil Pollution","onlineIssn":"1573-2932","printIssn":"0049-6979","active":true,"publicationSubtype":{"id":10}},"title":"Arsenic geochemistry of alluvial sediments and pore waters affected by mine tailings along the Belle Fourche and Cheyenne River floodplains","docAbstract":"Gold mining operations in the northern Black Hills of South Dakota resulted in the discharge of arsenopyrite-bearing mine tailings into Whitewood Creek from 1876 to 1977. Those tailings were transported further downstream along the Belle Fourche River, the Cheyenne River, and the Missouri River. An estimated 110 million metric tons of tailings remain stored in alluvial deposits of the Belle Fourche and Cheyenne Rivers. Pore-water dialysis samplers were deployed in the channel and backwaters of the Belle Fourche and Cheyenne Rivers to determine temporal and seasonal changes in the geochemistry of groundwater in alluvial sediments. Alluvial sediment adjacent to the dialysis samplers were cored for geochemical analysis. In comparison to US Environmental Protection Agency drinking water standards and reference concentrations of alluvial sediment not containing mine tailings, the Belle Fourche River sites had elevated concentrations of arsenic in pore water (2570 μg/L compared to 10 μg/L) and sediment (1010 ppm compared to < 34 ppm), respectively. Pore water arsenic concentration was affected by dissolution of iron oxyhydroxides under reducing conditions. Sequential extraction of iron and arsenic from sediment cores indicates that substantial quantities of soluble metals were present. Dissolution of arsenic sorbed to alluvial sediment particles appears to be affected by changing groundwater levels that cause shifts in redox conditions. Bioreductive processes did not appear to be a substantial transport pathway but could affect speciation of arsenic, especially at the Cheyenne River sampling sites where microbial activity was determined to be greater than at Belle Fourche sampling sites.
","language":"English","publisher":"Springer","doi":"10.1007/s11270-018-3836-8","usgsCitation":"Pfeifle, B.D., Stamm, J.F., and Stone, J.J., 2018, Arsenic geochemistry of alluvial sediments and pore waters affected by mine tailings along the Belle Fourche and Cheyenne River floodplains: Water, Air, & Soil Pollution, v. 229, p. 1-18, https://doi.org/10.1007/s11270-018-3836-8.","productDescription":"Article 183; 18 p.","startPage":"1","endPage":"18","ipdsId":"IP-049076","costCenters":[{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":355291,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Belle Fourche River, Cheyenne River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106,\n 42.5\n ],\n [\n -101,\n 42.5\n ],\n [\n -101,\n 45\n ],\n [\n -106,\n 45\n ],\n [\n -106,\n 42.5\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"229","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2018-05-25","publicationStatus":"PW","scienceBaseUri":"5b46e553e4b060350a15d0d7","contributors":{"authors":[{"text":"Pfeifle, Bryce D.","contributorId":205879,"corporation":false,"usgs":false,"family":"Pfeifle","given":"Bryce","email":"","middleInitial":"D.","affiliations":[{"id":37185,"text":"South Dakota School of Mines and Technology","active":true,"usgs":false}],"preferred":false,"id":738774,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stamm, John F. 0000-0002-3404-2933 jstamm@usgs.gov","orcid":"https://orcid.org/0000-0002-3404-2933","contributorId":149144,"corporation":false,"usgs":true,"family":"Stamm","given":"John","email":"jstamm@usgs.gov","middleInitial":"F.","affiliations":[{"id":562,"text":"South Dakota Water Science Center","active":true,"usgs":true}],"preferred":false,"id":738773,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stone, James J.","contributorId":205880,"corporation":false,"usgs":false,"family":"Stone","given":"James","email":"","middleInitial":"J.","affiliations":[{"id":37185,"text":"South Dakota School of Mines and Technology","active":true,"usgs":false}],"preferred":false,"id":738775,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70197859,"text":"70197859 - 2018 - Sediment supply to San Francisco Bay, water years 1995 through 2016: Data, trends, and monitoring recommendations to support decisions about water quality, tidal wetlands, and resilience to sea level rise","interactions":[],"lastModifiedDate":"2018-06-22T10:42:50","indexId":"70197859","displayToPublicDate":"2018-06-22T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":9,"text":"Other Report"},"title":"Sediment supply to San Francisco Bay, water years 1995 through 2016: Data, trends, and monitoring recommendations to support decisions about water quality, tidal wetlands, and resilience to sea level rise","docAbstract":"Knowledge of the status and trends of sediment supply to San Francisco Bay is critically\nimportant for management decisions about dredging, marsh restoration, flood control,\ncontaminants, water clarity (in relation to primary production), and sea level rise. Several sitespecific\nstudies of sediment supply to San Francisco Bay have been conducted, but no synthesis\nof recent studies is available. The purpose of this report is to synthesize the best available data\nand knowledge to answer a few of the key study questions related to sediment supply to the Bay\n(listed below).\nThis synthesis report was prepared jointly by the Regional Monitoring Program for Water\nQuality in San Francisco Bay (RMP) and the U. S. Geological Survey (USGS) with funding\nfrom both organizations. The project is meant to be a step in the development of a more\ncomprehensive sediment management and monitoring strategy for the Bay.\n\nWhat are the magnitudes and sources of fine and coarse sediment transported to San Francisco Bay?\n\nNet sediment supply to San Francisco Bay from terrestrial sources during the most recent 22-\nyear period (water years [WY] 1995-2016) was 1.9+/-0.8 Mt/yr (1 Mt is one million metric\ntonnes or 1 billion kilograms). Sixty-three percent of the sediment supply was from small\ntributaries that drain directly to the Bay. Net supply from the Central Valley (measured at\nMallard Island) was 37% of the total supply. Bedload supply, after accounting for dredging,\nremovals, storage in flood control channels, and errors in measurements was indistinguishable\nfrom zero. For a 30-year “climate normal” reference period of WY 1981-2010 (a period assumed\nto be representative of current climatic conditions), we estimate the total sediment supply would\nbe 2.0 Mt/yr of which 70% would come from small tributaries. The delivery points are Mallard\nIsland for sediment from the Delta and the head of tide of each small tributary or outfall for\nsediment from the small tributaries.\nThe finding that, on average, small tributaries have supplied more sediment to the Bay than the\nDelta is important but not new (McKee et al., 2013). During the Gold Rush and perhaps through\nto the 1980s, 80% or more of the supply was estimated to be from the Central Valley\n(Porterfield, 1980). But land and water management have continued to evolve (Krone, 1996) and\nthe sediment wave associated with the Gold Rush has diminished (Schoellhamer, 2011). In\naddition, the coastal mountains of California and around the Bay are steep, tectonically active\nand composed of relatively erodible marine sedimentary and metasedimentary rocks, in contrast\nto the Central Valley watershed that is dominated by highly indurated granitic, metasedimentary,\nand metavolcanic rocks in the western-facing slopes of the Sierra Nevada Mountains\n(McKee et al., 2013). Also, water management is quite different between the Central Valley\nrivers and small tributaries. About 48% of the Central Valley watershed is upstream from dams\nthat are designed to capture, delay and diminish discharge from spring snowmelt and so\neliminate or damp many of the peak flows that are normally crucial for sediment transport.\nAnother factor contributing to the importance of small tributaries for sediment supply is the way\nthat they deliver sediment. Annual discharge from small tributaries is very small in comparison\nto the volume of the Bay (around one-fifth of a Bay volume on average), and the load that small\ntributaries supply is delivered through hundreds of channels and outfalls via wetland sloughs to\nthe mudflats on the margin of the Bay. Therefore, the majority of this sediment delivered from\nBay Area small tributaries is more likely to be trapped in these tidal channels or the margins of\nthe Bay. In contrast, supply from the Central Valley enters the Bay through one large river\nchannel at the head of the estuary (functionally adjacent to Mallard Island, near Pittsburg, CA)\nwith an average annual discharge volume that is more than twi","language":"English","publisher":"San Francisco Estuary Institute","usgsCitation":"Schoellhamer, D., McKee, L., Pearce, S., Kauhanen, P., Saloman, M., Dusterhoff, S., Grenier, J.L., Marineau, M.D., and Trowbridge, P., 2018, Sediment supply to San Francisco Bay, water years 1995 through 2016: Data, trends, and monitoring recommendations to support decisions about water quality, tidal wetlands, and resilience to sea level rise, xi, 80 p.","productDescription":"xi, 80 p.","ipdsId":"IP-091659","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":355288,"type":{"id":15,"text":"Index Page"},"url":"https://www.sfei.org/documents/sediment-supply-san-francisco-bay"},{"id":355292,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay-Delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.64862060546875,\n 37.391981943533544\n ],\n [\n -121.74362182617188,\n 37.391981943533544\n ],\n [\n -121.74362182617188,\n 38.238180119798635\n ],\n [\n -122.64862060546875,\n 38.238180119798635\n ],\n [\n -122.64862060546875,\n 37.391981943533544\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b46e553e4b060350a15d0d5","contributors":{"authors":[{"text":"Schoellhamer, David H. 0000-0001-9488-7340 dschoell@usgs.gov","orcid":"https://orcid.org/0000-0001-9488-7340","contributorId":631,"corporation":false,"usgs":true,"family":"Schoellhamer","given":"David H.","email":"dschoell@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":738777,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McKee, Lester","contributorId":205882,"corporation":false,"usgs":false,"family":"McKee","given":"Lester","email":"","affiliations":[{"id":37186,"text":"SFEI","active":true,"usgs":false}],"preferred":false,"id":738779,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pearce, Sarah","contributorId":205883,"corporation":false,"usgs":false,"family":"Pearce","given":"Sarah","email":"","affiliations":[{"id":37186,"text":"SFEI","active":true,"usgs":false}],"preferred":false,"id":738780,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kauhanen, Pete","contributorId":205884,"corporation":false,"usgs":false,"family":"Kauhanen","given":"Pete","email":"","affiliations":[{"id":37186,"text":"SFEI","active":true,"usgs":false}],"preferred":false,"id":738781,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Saloman, Micha","contributorId":205885,"corporation":false,"usgs":false,"family":"Saloman","given":"Micha","email":"","affiliations":[{"id":37186,"text":"SFEI","active":true,"usgs":false}],"preferred":false,"id":738782,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dusterhoff, Scott","contributorId":205886,"corporation":false,"usgs":false,"family":"Dusterhoff","given":"Scott","email":"","affiliations":[{"id":37186,"text":"SFEI","active":true,"usgs":false}],"preferred":false,"id":738783,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Grenier, J. Letitia","contributorId":205887,"corporation":false,"usgs":false,"family":"Grenier","given":"J.","email":"","middleInitial":"Letitia","affiliations":[{"id":37186,"text":"SFEI","active":true,"usgs":false}],"preferred":false,"id":738784,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Marineau, Mathieu D. 0000-0002-6568-0743 mmarineau@usgs.gov","orcid":"https://orcid.org/0000-0002-6568-0743","contributorId":4954,"corporation":false,"usgs":true,"family":"Marineau","given":"Mathieu","email":"mmarineau@usgs.gov","middleInitial":"D.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":738778,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Trowbridge, Philip","contributorId":205888,"corporation":false,"usgs":false,"family":"Trowbridge","given":"Philip","email":"","affiliations":[{"id":37186,"text":"SFEI","active":true,"usgs":false}],"preferred":false,"id":738785,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70197864,"text":"70197864 - 2018 - ShakeMap-based prediction of earthquake-induced mass movements in Switzerland calibrated on historical observations","interactions":[],"lastModifiedDate":"2018-06-22T14:41:46","indexId":"70197864","displayToPublicDate":"2018-06-22T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2822,"text":"Natural Hazards","active":true,"publicationSubtype":{"id":10}},"title":"ShakeMap-based prediction of earthquake-induced mass movements in Switzerland calibrated on historical observations","docAbstract":"In Switzerland, nearly all historical Mw ~ 6 earthquakes have induced damaging landslides, rockslides and snow avalanches that, in some cases, also resulted in damage to infrastructure and loss of lives. We describe the customisation to Swiss conditions of a globally calibrated statistical approach originally developed to rapidly assess earthquake-induced landslide likelihoods worldwide. The probability of occurrence of such earthquake-induced effects is modelled through a set of geospatial susceptibility proxies and peak ground acceleration. The predictive model is tuned to capture the observations from past events and optimised for near-real-time estimates based on USGS-style ShakeMaps routinely produced by the Swiss Seismological Service. Our emphasis is on the use of high-resolution geospatial datasets along with additional local information on ground failure susceptibility. Even if calibrated on historic events with moderate magnitudes, the methodology presented in this paper yields sensible results also for low-magnitude recent events. The model is integrated in the Swiss ShakeMap framework. This study has a high practical relevance to many Swiss ShakeMap stakeholders, especially those managing lifeline systems, and to other global users interested in conducting a similar customisation for their region of interest.
","language":"English","publisher":"Springer","doi":"10.1007/s11069-018-3248-5","usgsCitation":"Cauzzi, C., Fah, D., Wald, D.J., Clinton, J., Losey, S., and Wiemer, S., 2018, ShakeMap-based prediction of earthquake-induced mass movements in Switzerland calibrated on historical observations: Natural Hazards, v. 92, no. 2, p. 1211-1235, https://doi.org/10.1007/s11069-018-3248-5.","productDescription":"25 p.","startPage":"1211","endPage":"1235","ipdsId":"IP-095789","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":468635,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/20.500.11850/250020","text":"External Repository"},{"id":355312,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Switzerland","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 6,\n 45.75\n ],\n [\n 10.5,\n 45.75\n ],\n [\n 10.5,\n 47.75\n ],\n [\n 6,\n 47.75\n ],\n [\n 6,\n 45.75\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"92","issue":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-07","publicationStatus":"PW","scienceBaseUri":"5b46e552e4b060350a15d0d1","contributors":{"authors":[{"text":"Cauzzi, Carlo","contributorId":205898,"corporation":false,"usgs":false,"family":"Cauzzi","given":"Carlo","email":"","affiliations":[{"id":37189,"text":"Swiss Seismological Service at ETH Zurich","active":true,"usgs":false}],"preferred":false,"id":738801,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fah, Donat","contributorId":205899,"corporation":false,"usgs":false,"family":"Fah","given":"Donat","email":"","affiliations":[],"preferred":false,"id":738802,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wald, David J. 0000-0002-1454-4514 wald@usgs.gov","orcid":"https://orcid.org/0000-0002-1454-4514","contributorId":795,"corporation":false,"usgs":true,"family":"Wald","given":"David","email":"wald@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":738803,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Clinton, John","contributorId":205900,"corporation":false,"usgs":false,"family":"Clinton","given":"John","affiliations":[],"preferred":false,"id":738804,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Losey, Stephane","contributorId":205901,"corporation":false,"usgs":false,"family":"Losey","given":"Stephane","email":"","affiliations":[],"preferred":false,"id":738805,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wiemer, Stefan","contributorId":205902,"corporation":false,"usgs":false,"family":"Wiemer","given":"Stefan","email":"","affiliations":[],"preferred":false,"id":738806,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70227705,"text":"70227705 - 2018 - Experimental evidence of long-term reproductive costs in a colonial nesting seabird","interactions":[],"lastModifiedDate":"2022-01-27T14:30:59.155631","indexId":"70227705","displayToPublicDate":"2018-06-21T08:24:36","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2190,"text":"Journal of Avian Biology","active":true,"publicationSubtype":{"id":10}},"title":"Experimental evidence of long-term reproductive costs in a colonial nesting seabird","docAbstract":"Trade-offs between current and future reproduction are central to the evolution of life histories. Experiments that manipulate brood size provide an effective approach to investigating future costs of current reproduction. Most manipulative studies to date, however, have addressed only the short-term effects of brood size manipulation. Our goal was to determine whether survival or breeding costs of reproduction in a long-lived species manifest beyond the subsequent breeding season. To this end, we investigated long-term survival and breeding effects of a multi-year reproductive cost experiment conducted on black-legged kittiwakes Rissa tridactyla, a long-lived colonial nesting seabird. We used multi-state capture–recapture modeling to assess hypotheses regarding the role of experimentally reduced breeding effort and other factors, including climate phase and colony size and productivity, on future survival and breeding probabilities during the 16-yr period following the experiment. We found that forced nest failures had a positive effect on breeding probability over time, but had no effect on long-term survival. This apparent canalization of survival suggests that adult survival is the most important parameter influencing fitness in this long-lived species, and that adults should pay reproductive costs in ways that do not compromise this critical life history parameter. When declines in adult survival rate are observed, they may indicate populations of conservation concern.
","language":"English","publisher":"Wiley","doi":"10.1111/jav.01779","usgsCitation":"McKnight, A., Blomberg, E.J., Golet, G.H., Irons, D.B., Loftin, C., and McKinney, S.T., 2018, Experimental evidence of long-term reproductive costs in a colonial nesting seabird: Journal of Avian Biology, v. 49, no. 8, e01779, 14 p., https://doi.org/10.1111/jav.01779.","productDescription":"e01779, 14 p.","ipdsId":"IP-075525","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":394966,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Prince William Sound","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -148.86474609375,\n 59.77852198502987\n ],\n [\n -145.5,\n 59.77852198502987\n ],\n [\n -145.5,\n 61.29398784561188\n ],\n [\n -148.86474609375,\n 61.29398784561188\n ],\n [\n -148.86474609375,\n 59.77852198502987\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"49","issue":"8","noUsgsAuthors":false,"publicationDate":"2018-09-03","publicationStatus":"PW","contributors":{"authors":[{"text":"McKnight, Aly","contributorId":220818,"corporation":false,"usgs":false,"family":"McKnight","given":"Aly","email":"","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":831948,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Blomberg, Erik J.","contributorId":17543,"corporation":false,"usgs":false,"family":"Blomberg","given":"Erik","email":"","middleInitial":"J.","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":831949,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Golet, Gregory H.","contributorId":89844,"corporation":false,"usgs":false,"family":"Golet","given":"Gregory","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":831950,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Irons, David B.","contributorId":220820,"corporation":false,"usgs":false,"family":"Irons","given":"David","email":"","middleInitial":"B.","affiliations":[{"id":12428,"text":"U. S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":831951,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Loftin, Cyndy 0000-0001-9104-3724 cyndy_loftin@usgs.gov","orcid":"https://orcid.org/0000-0001-9104-3724","contributorId":146427,"corporation":false,"usgs":true,"family":"Loftin","given":"Cyndy","email":"cyndy_loftin@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":831842,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McKinney, Shawn T. smckinney@usgs.gov","contributorId":5175,"corporation":false,"usgs":true,"family":"McKinney","given":"Shawn","email":"smckinney@usgs.gov","middleInitial":"T.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":831952,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70197821,"text":"70197821 - 2018 - Use of Bank Swallow (Riparia riparia) burrows as shelter by Common Tern (Sterna hirundo) chicks","interactions":[],"lastModifiedDate":"2018-06-21T09:19:49","indexId":"70197821","displayToPublicDate":"2018-06-21T00:00:00","publicationYear":"2018","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}},"displayTitle":"Use of Bank Swallow (Riparia riparia) burrows as shelter by Common Tern (Sterna hirundo) chicks","title":"Use of Bank Swallow (Riparia riparia) burrows as shelter by Common Tern (Sterna hirundo) chicks","docAbstract":"The availability of shelter to avoid predation and ameliorate physiologically stressful conditions is often important to the survival of avian hatchlings. However, as changes in habitat availability force birds to nest in nontraditional locations, young must quickly adapt to using novel sources of shelter. Two Common Tern (Sterna hirundo) colonies (one vegetated and one barren) were observed during the 2017 breeding season on a remote island habitat restoration project during data collection for a larger associated study. While chicks within the vegetated colony sought shade under vegetation, those in the barren colony were frequently found under anthropogenically constructed chick shelters. The first reported instance of Common Tern chicks using Bank Swallow (Riparia riparia) burrows for shelter was also observed in the barren colony. This behavior, when paired with other similar reports, suggests that this species is able to recognize beneficial shelters, both natural and anthropogenic, and use them at a young age, an important ability if they are to successfully reproduce in atypical habitats","language":"English","publisher":"The Waterbird Society","doi":"10.1675/063.041.0210","usgsCitation":"McGowan, P.C., Reintsma, K., Sullivan, J.D., DeVoss, K.P., Wall, J.L., Zimnik, M.D., Callahan, C.R., Schultz, B., and Prosser, D.J., 2018, Use of Bank Swallow (Riparia riparia) burrows as shelter by Common Tern (Sterna hirundo) chicks: Waterbirds, v. 41, no. 2, p. 179-182, https://doi.org/10.1675/063.041.0210.","productDescription":"4 p.","startPage":"179","endPage":"182","ipdsId":"IP-089905","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":355240,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland","otherGeospatial":"Poplar Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.41883850097656,\n 38.73212548425921\n ],\n [\n -76.34193420410156,\n 38.73212548425921\n ],\n [\n -76.34193420410156,\n 38.79690830348427\n ],\n [\n -76.41883850097656,\n 38.79690830348427\n ],\n [\n -76.41883850097656,\n 38.73212548425921\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"41","issue":"2","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b46e554e4b060350a15d0df","contributors":{"authors":[{"text":"McGowan, Peter C.","contributorId":13867,"corporation":false,"usgs":false,"family":"McGowan","given":"Peter","email":"","middleInitial":"C.","affiliations":[{"id":6987,"text":"U.S. Fish and Wildlife Sevice","active":true,"usgs":false}],"preferred":false,"id":738656,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reintsma, Kaitlyn","contributorId":205843,"corporation":false,"usgs":true,"family":"Reintsma","given":"Kaitlyn","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":738655,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sullivan, Jeffery D.","contributorId":202910,"corporation":false,"usgs":false,"family":"Sullivan","given":"Jeffery","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":738657,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"DeVoss, Katie P.","contributorId":205844,"corporation":false,"usgs":false,"family":"DeVoss","given":"Katie","email":"","middleInitial":"P.","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":738658,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Wall, Jennifer L.","contributorId":205845,"corporation":false,"usgs":false,"family":"Wall","given":"Jennifer","email":"","middleInitial":"L.","affiliations":[{"id":7083,"text":"University of Maryland","active":true,"usgs":false}],"preferred":false,"id":738659,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Zimnik, Mia D.","contributorId":205846,"corporation":false,"usgs":false,"family":"Zimnik","given":"Mia","email":"","middleInitial":"D.","affiliations":[{"id":37175,"text":"Hood College","active":true,"usgs":false}],"preferred":false,"id":738660,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Callahan, Carl R.","contributorId":205289,"corporation":false,"usgs":false,"family":"Callahan","given":"Carl","email":"","middleInitial":"R.","affiliations":[{"id":37073,"text":"USFWS, Annapolis MD","active":true,"usgs":false}],"preferred":false,"id":738661,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Schultz, Bill","contributorId":205847,"corporation":false,"usgs":false,"family":"Schultz","given":"Bill","email":"","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":738662,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Prosser, Diann J. 0000-0002-5251-1799 dprosser@usgs.gov","orcid":"https://orcid.org/0000-0002-5251-1799","contributorId":2389,"corporation":false,"usgs":true,"family":"Prosser","given":"Diann","email":"dprosser@usgs.gov","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":738654,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70197845,"text":"70197845 - 2018 - High latitude Southern Hemisphere fire history during the mid-late Holocene (750- 6000 yr BP)","interactions":[],"lastModifiedDate":"2018-06-21T14:16:33","indexId":"70197845","displayToPublicDate":"2018-06-21T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1250,"text":"Climate of the Past","active":true,"publicationSubtype":{"id":10}},"title":"High latitude Southern Hemisphere fire history during the mid-late Holocene (750- 6000 yr BP)","docAbstract":"We determined the specific biomass burning biomarker levoglucosan in an ice core from the TALos Dome Ice CorE drilling project (TALDICE) during the mid- to late Holocene (6000–750 BP). The levoglucosan record is characterized by a long-term increase with higher rates starting at ∼ 4000 BP and peaks between 2500 and 1500 BP. The anomalous increase in levoglucosan centered at ∼ 2000 BP is consistent with other Antarctic biomass burning records. Multiple atmospheric phenomena affect the coastal Antarctic Talos Dome drilling site, where the Southern Annular Mode (SAM) is the most prominent as the Southern Annular Mode Index (SAMA) correlates with stable isotopes in precipitation throughout the most recent 1000 years of the ice core. If this connection remains throughout the mid- to late Holocene, then our results demonstrate that changes in biomass burning, rather than changes in atmospheric transport, are the major influence on the TALDICE levoglucosan record. Comparisons with charcoal syntheses help evaluate fire sources, showing a greater contribution from southern South American fires than from Australian biomass burning. The levoglucosan peak centered at ∼ 2000 BP occurs during a cool period throughout the Southern Hemisphere, yet during a time of increased fire activity in both northern and southern Patagonia. This peak in biomass burning is influenced by increased vegetation in southern South America from a preceding humid period, in which the vegetation desiccated during the following cool, dry period. The Talos Dome ice core record from 6000 to ∼ 750 BP currently does not provide clear evidence that the fire record may be strongly affected by anthropogenic activities during the mid- to late Holocene, although we cannot exclude at least a partial influence.","language":"English","doi":"10.5194/cp-14-871-2018","usgsCitation":"Battistel, D., Kehrwald, N.M., Zennaro, P., Pellegrino, G., Barbaro, E., Zangrando, R., Pedeli, X.X., Varin, C., Spolaor, A., Vallelonga, P.T., Gambaro, A., and Barbante, C., 2018, High latitude Southern Hemisphere fire history during the mid-late Holocene (750- 6000 yr BP): Climate of the Past, v. 14, p. 871-886, https://doi.org/10.5194/cp-14-871-2018.","productDescription":"16 p.","startPage":"871","endPage":"886","ipdsId":"IP-094682","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":468750,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/cp-14-871-2018","text":"Publisher Index Page"},{"id":355285,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-06-21","publicationStatus":"PW","scienceBaseUri":"5b46e553e4b060350a15d0d9","contributors":{"authors":[{"text":"Battistel, Dario","contributorId":205865,"corporation":false,"usgs":false,"family":"Battistel","given":"Dario","email":"","affiliations":[{"id":37181,"text":"Department of Environmental Science, Informatics and Statistics, Ca' Foscari University of Venice, Italy","active":true,"usgs":false}],"preferred":false,"id":738732,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kehrwald, Natalie M. 0000-0002-9160-2239 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Giuseppe","contributorId":205866,"corporation":false,"usgs":false,"family":"Pellegrino","given":"Giuseppe","email":"","affiliations":[{"id":37181,"text":"Department of Environmental Science, Informatics and Statistics, Ca' Foscari University of Venice, Italy","active":true,"usgs":false}],"preferred":false,"id":738734,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Barbaro, Elena","contributorId":205867,"corporation":false,"usgs":false,"family":"Barbaro","given":"Elena","email":"","affiliations":[{"id":37181,"text":"Department of Environmental Science, Informatics and Statistics, Ca' Foscari University of Venice, Italy","active":true,"usgs":false}],"preferred":false,"id":738735,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Zangrando, Roberta","contributorId":205868,"corporation":false,"usgs":false,"family":"Zangrando","given":"Roberta","email":"","affiliations":[{"id":37182,"text":"Institute for the Dynamics of Environmental Processes -- CNR, Venice, Italy","active":true,"usgs":false}],"preferred":false,"id":738736,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pedeli, Xanthi X.","contributorId":205869,"corporation":false,"usgs":false,"family":"Pedeli","given":"Xanthi","email":"","middleInitial":"X.","affiliations":[{"id":37181,"text":"Department of Environmental Science, Informatics and Statistics, Ca' Foscari University of Venice, Italy","active":true,"usgs":false}],"preferred":false,"id":738737,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Varin, Cristiano","contributorId":205870,"corporation":false,"usgs":false,"family":"Varin","given":"Cristiano","email":"","affiliations":[{"id":37183,"text":"Department of Environmental Sciences, Informatics and Statistics, Ca' Foscari University of Venice, Italy","active":true,"usgs":false}],"preferred":false,"id":738738,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Spolaor, Andrea","contributorId":205871,"corporation":false,"usgs":false,"family":"Spolaor","given":"Andrea","email":"","affiliations":[{"id":37182,"text":"Institute for the Dynamics of Environmental Processes -- CNR, Venice, Italy","active":true,"usgs":false}],"preferred":false,"id":738739,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Vallelonga, Paul T.","contributorId":205872,"corporation":false,"usgs":false,"family":"Vallelonga","given":"Paul","email":"","middleInitial":"T.","affiliations":[{"id":37184,"text":"Centre for Ice and Climate, Niels Bohr Institute, University of Copenhagen, Denmark","active":true,"usgs":false}],"preferred":false,"id":738740,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Gambaro, Andrea","contributorId":205873,"corporation":false,"usgs":false,"family":"Gambaro","given":"Andrea","email":"","affiliations":[{"id":37181,"text":"Department of Environmental Science, Informatics and Statistics, Ca' Foscari University of Venice, Italy","active":true,"usgs":false}],"preferred":false,"id":738741,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Barbante, Carlo","contributorId":202632,"corporation":false,"usgs":false,"family":"Barbante","given":"Carlo","email":"","affiliations":[{"id":36503,"text":"Department of Environmental Sciences, Infomatics, and Statistics, Ca'Foscari University of Venice, Via Torino 155, 30172 Mestre (VE), Italy","active":true,"usgs":false}],"preferred":false,"id":738742,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70197822,"text":"70197822 - 2018 - Stability of mercury concentration measurements in archived soil and peat samples","interactions":[],"lastModifiedDate":"2018-06-21T09:41:40","indexId":"70197822","displayToPublicDate":"2018-06-21T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1226,"text":"Chemosphere","active":true,"publicationSubtype":{"id":10}},"title":"Stability of mercury concentration measurements in archived soil and peat samples","docAbstract":"Archived soil samples can provide important information on the history of environmental contamination and by comparison with recently collected samples, temporal trends can be inferred. Little previous work has addressed whether mercury (Hg) concentrations in soil samples are stable with long-term storage under standard laboratory conditions. In this study, we have re-analyzed using cold vapor atomic adsorption spectroscopy a set of archived soil samples that ranged from relatively pristine mountainous sites to a polluted site near a non-ferrous metal smelter with a wide range of Hg concentrations (6 - 6485 µg kg-1). Samples included organic and mineral soils and peats with a carbon content that ranged from 0.2 to 47.7%. Soil samples were stored in polyethylene bags or bottles and held in laboratory rooms where temperature was not kept to a constant value. Mercury concentrations in four subsets of samples were originally measured in 2000, 2005, 2006 and 2007, and re-analyzed in 2017, i.e. after 17, 12, 11 and 10 years of storage. Statistical analyses of either separated or lumped data yielded no significant differences between the original and current Hg concentrations. Based on these analyses, we show that archived soil and peat samples can be used to evaluate historical soil mercury contamination.","language":"English","publisher":"Elsevier","doi":"10.1016/j.chemosphere.2018.06.033","usgsCitation":"Navratil, T., Burns, D., Novakova, T., Kana, J., Rohovec, J., Roll, M., and Ettler, V., 2018, Stability of mercury concentration measurements in archived soil and peat samples: Chemosphere, v. 208, p. 707-711, https://doi.org/10.1016/j.chemosphere.2018.06.033.","productDescription":"4 p.","startPage":"707","endPage":"711","ipdsId":"IP-092247","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":355241,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Czech Republic","volume":"208","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b46e554e4b060350a15d0dd","contributors":{"authors":[{"text":"Navratil, Tomas","contributorId":205848,"corporation":false,"usgs":false,"family":"Navratil","given":"Tomas","email":"","affiliations":[{"id":37176,"text":"Institute of Geology of the Czech Academy of Science","active":true,"usgs":false}],"preferred":false,"id":738664,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burns, Douglas A. 0000-0001-6516-2869","orcid":"https://orcid.org/0000-0001-6516-2869","contributorId":202943,"corporation":false,"usgs":true,"family":"Burns","given":"Douglas A.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":738663,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Novakova, Tereza","contributorId":205849,"corporation":false,"usgs":false,"family":"Novakova","given":"Tereza","email":"","affiliations":[{"id":37176,"text":"Institute of Geology of the Czech Academy of Science","active":true,"usgs":false}],"preferred":false,"id":738665,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kana, Jiri","contributorId":205850,"corporation":false,"usgs":false,"family":"Kana","given":"Jiri","email":"","affiliations":[{"id":37177,"text":"Biology Centre of the Czech Academy of Science","active":true,"usgs":false}],"preferred":false,"id":738666,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rohovec, Jan","contributorId":205851,"corporation":false,"usgs":false,"family":"Rohovec","given":"Jan","email":"","affiliations":[{"id":37176,"text":"Institute of Geology of the Czech Academy of Science","active":true,"usgs":false}],"preferred":false,"id":738667,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Roll, Michal","contributorId":205852,"corporation":false,"usgs":false,"family":"Roll","given":"Michal","email":"","affiliations":[{"id":37176,"text":"Institute of Geology of the Czech Academy of Science","active":true,"usgs":false}],"preferred":false,"id":738668,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ettler, Vojtech","contributorId":205853,"corporation":false,"usgs":false,"family":"Ettler","given":"Vojtech","email":"","affiliations":[{"id":37178,"text":"Charles University","active":true,"usgs":false}],"preferred":false,"id":738669,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70197825,"text":"70197825 - 2018 - Response of mercury in an Adirondack (NY, USA) forest stream to watershed lime application","interactions":[],"lastModifiedDate":"2018-06-21T09:39:47","indexId":"70197825","displayToPublicDate":"2018-06-21T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1566,"text":"Environmental Science: Processes and Impacts","active":true,"publicationSubtype":{"id":10}},"title":"Response of mercury in an Adirondack (NY, USA) forest stream to watershed lime application","docAbstract":"Surface waters in Europe and North America previously impacted by acid deposition are recovering in conjunction with declining precursor emissions since the 1980s. Lime has been applied to some impacted watersheds to accelerate recovery. The response to liming can be considered a proxy for future recovery from acid deposition. Increases in dissolved organic carbon concentrations have been observed in surface waters in response to increased pH associated with recovery from acid deposition. Although not previously described, recovery-related increases in dissolved organic carbon could drive increases in mercury concentrations and loads because of the affinity of mercury for dissolved organic matter. We used a before–after impact-response approach to describe the response of stream mercury cycling to the application of lime to the watershed of a small stream in the Adirondack Mountains of New York, USA. Dissolved organic carbon, total mercury and methylmercury concentrations increased\nsignificantly in streamwater within two weeks of treatment, to previously unobserved oncentrations. After six months, post-treatment before–after impact-control (BACI) tests indicate that mean dissolved organic carbon concentrations and total mercury to dissolved organic carbon ratios remained significantly higher and limed site fluxes of methylmercury were lower than those at the reference stream. This pattern suggests total mercury is leaching at elevated levels from the limed watershed, but limitations in production and transport to the stream channel likely resulted in increases in methylmercury concentration that were of limited duration.","language":"English","publisher":"The Royal Society of Chemistry","doi":"10.1039/c7em00520b","usgsCitation":"Millard, G.D., Driscoll, C.T., Burns, D., Montesdeoca, M., and Riva-Murray, K., 2018, Response of mercury in an Adirondack (NY, USA) forest stream to watershed lime application: Environmental Science: Processes and Impacts, v. 20, no. 4, p. 607-620, https://doi.org/10.1039/c7em00520b.","productDescription":"14 p.","startPage":"607","endPage":"620","ipdsId":"IP-080653","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":355239,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Honnedaga Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.89603042602539,\n 43.48543487611435\n ],\n [\n -74.7810173034668,\n 43.48543487611435\n ],\n [\n -74.7810173034668,\n 43.55252937447483\n ],\n [\n -74.89603042602539,\n 43.55252937447483\n ],\n [\n -74.89603042602539,\n 43.48543487611435\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"20","issue":"4","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b46e554e4b060350a15d0db","contributors":{"authors":[{"text":"Millard, Geoffrey D.","contributorId":205854,"corporation":false,"usgs":false,"family":"Millard","given":"Geoffrey","email":"","middleInitial":"D.","affiliations":[{"id":37179,"text":"Research Assistant, Dept of Civil & Environmental Engineeering, Syracuse University, NY","active":true,"usgs":false}],"preferred":false,"id":738674,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Driscoll, Charles T.","contributorId":167460,"corporation":false,"usgs":false,"family":"Driscoll","given":"Charles","email":"","middleInitial":"T.","affiliations":[{"id":5082,"text":"Syracuse University","active":true,"usgs":false}],"preferred":false,"id":738675,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Burns, Douglas A. 0000-0001-6516-2869","orcid":"https://orcid.org/0000-0001-6516-2869","contributorId":202943,"corporation":false,"usgs":true,"family":"Burns","given":"Douglas A.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":738673,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Montesdeoca, Mario R.","contributorId":198382,"corporation":false,"usgs":false,"family":"Montesdeoca","given":"Mario R.","affiliations":[{"id":5082,"text":"Syracuse University","active":true,"usgs":false}],"preferred":false,"id":738676,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Riva-Murray, Karen 0000-0001-6683-2238 krmurray@usgs.gov","orcid":"https://orcid.org/0000-0001-6683-2238","contributorId":168876,"corporation":false,"usgs":true,"family":"Riva-Murray","given":"Karen","email":"krmurray@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":738677,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70197401,"text":"ofr20181073 - 2018 - Regional spectral analysis of moderate earthquakes in northeastern North America—Final Report to the Nuclear Regulatory Commission, Project V6240, Task 3","interactions":[],"lastModifiedDate":"2018-06-22T09:44:35","indexId":"ofr20181073","displayToPublicDate":"2018-06-21T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-1073","title":"Regional spectral analysis of moderate earthquakes in northeastern North America—Final Report to the Nuclear Regulatory Commission, Project V6240, Task 3","docAbstract":"We analyze the Fourier spectra of S+Lg+surface wave groups from the horizontal and vertical components of broadband and accelerogram recordings of 120 small and moderate (2< Mw <6) earthquakes recorded by Canadian and American stations sited on rock at distances from 3 to 600 kilometers. There are seven Mw 4.0–4.5, six Mw 4.5–5.0, and three Mw ≥5 earthquakes in this event set. We test the regional spectral analysis by comparing the moment magnitudes with the moment magnitudes from the earthquake moment tensors determined by Bob Herrmann (St. Louis University) for 27 events, obtaining dMw=0.004±0.074. We determine the Lg attenuation in seven regions within northeastern North America: Charlevoix, lower St. Lawrence, Maine, Northern New York, lower Great Lakes, Ontario, and Nunavut. These attenuation estimates yield an average attenuation Q= (368±13)f (0.54±0.02) for the Appalachian region, a stronger attenuation Q= (317±16)f (0.54±0.03) for the Appalachian lowlands, and a weaker attenuation Q=(455±20)f (0.51±0.02) for Ontario and western Quebec. For events in Nunavut and northernmost Quebec, we estimate a similar attenuation for r <450 km, but a weaker attenuation Q= (773±70)f (0.27±0.06) for Lg propagation for 450< r <1700 kilometers. This far-regional attenuation allows us to analyze recordings of the 1989 Ungava and Payne Bay earthquakes obtained in Ontario and southern Quebec. We use these regional attenuations to determine the corner frequencies, stress drops, and radiated energies of the 120 earthquakes.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181073","usgsCitation":"Boatwright, J., 2018, Regional spectral analysis of moderate earthquakes in northeastern North America—Final report to the Nuclear Regulatory Commission, project V6240, task 3: U.S. Geological Survey Open-File Report 2018–1073, 39 p., https://doi.org/10.3133/ofr20181073.","productDescription":"Report: vi, 39 p.","numberOfPages":"39","onlineOnly":"Y","ipdsId":"IP-096269","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":355095,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1073/ofr20181073.pdf","text":"Report","size":"2.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1073"},{"id":355094,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1073/coverthb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -78.2666015625,\n 39.977120098439634\n ],\n [\n -49.0869140625,\n 39.977120098439634\n ],\n [\n -49.0869140625,\n 54.059387886623576\n ],\n [\n -78.2666015625,\n 54.059387886623576\n ],\n [\n -78.2666015625,\n 39.977120098439634\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Earthquake Science Center
U.S. Geological Survey
345 Middlefield Road, MS 977
Menlo Park, CA 94025