The hydrodynamics of a tidally forced semi‐enclosed coral reef atoll (North Scott) at the edge of the continental shelf of northwestern Australia were investigated by combining field observations and numerical modeling. The observations revealed that the spring tidal range outside the atoll reaches 4 m, and as the water level drops below mean sea level, the reef rim surrounding the shallow (~10–15 m) lagoon becomes exposed. During this time, the lagoon can only exchange with the open ocean through two narrow channels, resulting in highly asymmetric water levels and velocities that were most pronounced during spring tide. On average, the ebb tide duration was ~2 hr longer than the flood, with rapid flood velocities in the channel reaching 2 m/s. We applied an unstructured grid model Delft3D‐Flexible Mesh to simulate the atoll hydrodynamics and were able to replicate the asymmetric water levels and complex velocities in the lagoon. The results revealed that at higher tidal stages, a dominant momentum balance exists between the pressure gradient (established by the propagation of the tide on the shelf) and the local flow acceleration of water throughout the interior of the atoll. At lower tidal stages, which coincided with a reversal of the offshore tidal pressure gradient, the lagoon became isolated from offshore dynamics and all momentum terms were negligible. This resulted in a tidally averaged residual westward flow within the lagoon that drove an asymmetric flushing pattern within the atoll, which we propose would be a common flushing mechanism within other tide‐dominated atolls worldwide.
","language":"English","publisher":"AGU","doi":"10.1029/2018JC013946","usgsCitation":"Green, R.H., Lowe, R.J., and Buckley, M.L., 2018, Hydrodynamics of a tidally‐forced coral reef atoll: Journal of Geophysical Research C: Oceans, v. 123, no. 10, p. 7084-7101, https://doi.org/10.1029/2018JC013946.","productDescription":"18 p.","startPage":"7084","endPage":"7101","ipdsId":"IP-095615","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":468331,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2018jc013946","text":"Publisher Index Page"},{"id":358199,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 122,\n -14.05\n ],\n [\n 121.8,\n -14.05\n ],\n [\n 121.8,\n -13.9\n ],\n [\n 122,\n -13.9\n ],\n [\n 122,\n -14.05\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"123","issue":"10","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-10-08","publicationStatus":"PW","scienceBaseUri":"5bc02f77e4b0fc368eb53839","contributors":{"authors":[{"text":"Green, Rebecca H.","contributorId":208503,"corporation":false,"usgs":false,"family":"Green","given":"Rebecca","email":"","middleInitial":"H.","affiliations":[{"id":24588,"text":"The University of Western Australia","active":true,"usgs":false}],"preferred":false,"id":747469,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lowe, Ryan J.","contributorId":152265,"corporation":false,"usgs":false,"family":"Lowe","given":"Ryan","email":"","middleInitial":"J.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":747470,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Buckley, Mark L. 0000-0002-1909-4831","orcid":"https://orcid.org/0000-0002-1909-4831","contributorId":203481,"corporation":false,"usgs":true,"family":"Buckley","given":"Mark","email":"","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":747468,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70199954,"text":"70199954 - 2018 - Improving earthquake rupture forecasts using California as a guide","interactions":[],"lastModifiedDate":"2018-11-14T09:01:53","indexId":"70199954","displayToPublicDate":"2018-10-09T10:18:39","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Improving earthquake rupture forecasts using California as a guide","docAbstract":"This article discusses ways in which earthquake rupture forecast models might be improved. Because changes are most easily described in the context of specific models, the third Uniform California Earthquake Rupture Forecast (UCERF3) and its presumed successor, UCERF4, is used as a basis for discussion. Virtually all of the issues and possible improvements discussed are nevertheless general and should therefore be applicable to other regions as well. Two common themes are a need for better epistemic uncertainty representation and the potential utility of physics‐based simulators. Given the large number of possible improvements, coupled with challenges in defining the potential value of each, which will vary among uses, community feedback is invaluable in terms of setting priorities. We should also strive to define more objective valuation metrics.
","language":"English","publisher":"SSA","doi":"10.1785/0220180151","usgsCitation":"Field, E., and Working Group on California Earthquake Probabilities, 2018, Improving earthquake rupture forecasts using California as a guide: Seismological Research Letters, v. 89, no. 6, p. 2337-2346, https://doi.org/10.1785/0220180151.","productDescription":"10 p.","startPage":"2337","endPage":"2346","ipdsId":"IP-101307","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":358197,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"89","issue":"6","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-10-03","publicationStatus":"PW","scienceBaseUri":"5bc02f77e4b0fc368eb5383b","contributors":{"authors":[{"text":"Field, Edward H. 0000-0001-8172-7882 field@usgs.gov","orcid":"https://orcid.org/0000-0001-8172-7882","contributorId":1165,"corporation":false,"usgs":true,"family":"Field","given":"Edward H.","email":"field@usgs.gov","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":false,"id":747466,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Working Group on California Earthquake Probabilities","contributorId":128141,"corporation":true,"usgs":false,"organization":"Working Group on California Earthquake Probabilities","id":747523,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70199996,"text":"70199996 - 2018 - Downhole log evidence for the coexistence of structure II gas hydrate and free gas below the bottom simulating reflector in the South China Sea","interactions":[],"lastModifiedDate":"2018-10-10T10:06:27","indexId":"70199996","displayToPublicDate":"2018-10-09T10:03:02","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2682,"text":"Marine and Petroleum Geology","active":true,"publicationSubtype":{"id":10}},"title":"Downhole log evidence for the coexistence of structure II gas hydrate and free gas below the bottom simulating reflector in the South China Sea","docAbstract":"Stratigraphic layered pore-filling gas hydrates are identified above the bottom simulating reflector (BSR) using the well log and core data acquired at Sites W11 and W17 during the third gas hydrate drilling expedition conducted by China's Geological Survey/Guangzhou Marine Geological Survey (GMGS3) in the South China Sea. A seismic profile near Site W17, reveal the presence of two BSRs (i.e., double BSR), which we show to relate to zones of structure I gas hydrate (I-BSR) and structure II gas hydrate (II-BSR). Well log data from Site W17 between the “I-BSR” (projected depth of 250 mbsf) and “II-BSR” (projected depth of 330 mbsf) showed anomalous responses for gas hydrate-bearing sediments with high resistivity, high S-wave velocity, and alternating high and low P-wave velocities. Pressure core data support the interpretation that structure II gas hydrate occurs at a depth of 263 mbsf at Site W17. The cross-plot between log-derived neutron and density porosities reveals a free gas-bearing layer at a depth of 258–270 mbsf, suggesting gas hydrate coexists with free gas between the “I-BSR” and the “II-BSR.” Synthetic seismograms generated from the P-wave velocity and density logs further support the presence of free gas in this section. Based on the coexistence of hydrate, free gas and water, the simplified three-phase equation (STPE) was modified to simultaneously estimate free gas and hydrate saturations beneath the “I-BSR” from P-wave and S-wave velocity logs, assuming uniform or patchy distributions of free gas. The estimated free gas and hydrate saturations, together with gas compositions from pressure core samples, collectively indicate that structure II gas hydrate and free gas are interbedded and coexist below the “I-BSR” at Site W17. Our study of the coexistence of gas hydrate and free gas between the double BSR at Site W17 provides new insights into gas hydrate systems in nature that contain more complex gas chemistries.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.marpetgeo.2018.09.024","usgsCitation":"Qian, J., Wang, X., Collett, T.S., Guo, Y., Kang, D., and Jin, J., 2018, Downhole log evidence for the coexistence of structure II gas hydrate and free gas below the bottom simulating reflector in the South China Sea: Marine and Petroleum Geology, v. 98, p. 662-674, https://doi.org/10.1016/j.marpetgeo.2018.09.024.","productDescription":"13 p.","startPage":"662","endPage":"674","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":358236,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"China","otherGeospatial":"South China Sea","volume":"98","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5bc02f78e4b0fc368eb5383f","contributors":{"authors":[{"text":"Qian, Jin","contributorId":208554,"corporation":false,"usgs":false,"family":"Qian","given":"Jin","email":"","affiliations":[],"preferred":false,"id":747680,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wang, Xiujuan","contributorId":87071,"corporation":false,"usgs":true,"family":"Wang","given":"Xiujuan","affiliations":[],"preferred":false,"id":747681,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Collett, Timothy S. 0000-0002-7598-4708 tcollett@usgs.gov","orcid":"https://orcid.org/0000-0002-7598-4708","contributorId":1698,"corporation":false,"usgs":true,"family":"Collett","given":"Timothy","email":"tcollett@usgs.gov","middleInitial":"S.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":747682,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Guo, Yiqun","contributorId":195860,"corporation":false,"usgs":false,"family":"Guo","given":"Yiqun","email":"","affiliations":[],"preferred":false,"id":747683,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kang, Dongju","contributorId":208555,"corporation":false,"usgs":false,"family":"Kang","given":"Dongju","email":"","affiliations":[],"preferred":false,"id":747684,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jin, Jiapeng","contributorId":208556,"corporation":false,"usgs":false,"family":"Jin","given":"Jiapeng","email":"","affiliations":[],"preferred":false,"id":747685,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70226708,"text":"70226708 - 2018 - Igneous and detrital zircon U-Pb and Lu-Hf geochronology of the late Meso- to Neoproterozoic northwest Botswana rift: Maximum depositional age and provenance of the Ghanzi Group, Kalahari Copperbelt, Botswana and Namibia","interactions":[],"lastModifiedDate":"2021-12-07T12:17:51.532126","indexId":"70226708","displayToPublicDate":"2018-10-06T06:09:53","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3112,"text":"Precambrian Research","active":true,"publicationSubtype":{"id":10}},"title":"Igneous and detrital zircon U-Pb and Lu-Hf geochronology of the late Meso- to Neoproterozoic northwest Botswana rift: Maximum depositional age and provenance of the Ghanzi Group, Kalahari Copperbelt, Botswana and Namibia","docAbstract":"New igneous and detrital zircon laser ablation-inductively coupled plasma mass spectrometry (LA-ICPMS) U-Pb geochronology and Lu-Hf isotopic data are presented for the Mesoproterozoic Kgwebe Formation and the unconformably overlying Ghanzi Group in northwestern Botswana. The Makgabana Hills porphyritic rhyolite flow from the Ghanzi area yielded a U-Pb concordia age of 1085.5 ± 4.5 Ma and provides a new maximum depositional age for the unconformably overlying Ghanzi Group. Detrital zircon (n = 448) from the Ghanzi Group yielded a 207Pb/206Pb age distribution with a dominant (70 to 90%) Mesoproterozoic population (∼1450 to ∼1050 Ma), a smaller (5 to 20%) Paleoproterozoic (∼2200 to ∼1700 Ma) population, and a few (n = 4) older (∼3000 Ma to ∼2450 Ma) grains. A maximum depositional age constraint of ∼1060 to ∼1050 Ma was obtained for middle and upper Ghanzi Group based on the weighted-mean 207Pb/206Pb age of the youngest clusters of overlapping zircon ages for each sample.
Initial hafnium ratios (εHfi) and corresponding crustal residence model ages (TCDM) for the Paleoproterozoic zircon populations indicate either fractionation from a chondritic uniform reservoir (CHUR) or mixing between juvenile mantle and older crustal components. Mesoproterozoic zircon with εHfi values between −20 and +15 and TCDM model ages between 3000 and 1200 Ma suggest that the source terrane(s) contained magmatic rocks including both juvenile material and substantially reworked Paleoproterozoic and possibly Archean crust.
Comparison with a compilation of published U-Pb, Lu-Hf, and Sm-Nd data from the Kalahari Craton suggests that the predominant Mesoproterozoic zircon population was derived from the Namaqua Sector, Rehoboth Basement Inlier, Kwando Complex, and Choma-Kalomo Block; some zircon may have had distal sources in adjacent Rodinia landmasses. Both Archean cratonic components and juvenile ∼1200 to ∼1000 Ma magmatic rocks of the Natal Sector and the Maud and Mozambique belts on the eastern margin of the craton are unlikely sources for the detrital zircon based on isotopic composition. Sediment transported from the western margin of the Kalahari Craton entered the northwest Botswana rift and mixed with sediments from the Rehoboth Basement Inlier and Paleo- to Mesoproterozoic terranes that bound the northwest Botswana rift.
Insufficient food during early life could limit the population growth of endangered Pallid Sturgeon Scaphirhynchus albus in the lower Missouri River. Shallow‐water habitat restoration is intended to provide nursery benefits, including food, for young sturgeon, but the effect of shallow‐water habitat on their diet is unknown. Age‐0 Pallid Sturgeon are rare, providing little opportunity for direct evaluation; however, studying the closely related and abundant Shovelnose Sturgeon S. platorynchus may provide valuable information to guide habitat restoration efforts. We compared diet, body condition (lipid content), and change in body weight (24‐h bioenergetics simulation) for postdrift, age‐0 sturgeon among five reaches ranging widely in shallow‐water habitat availability. Lipid content of satiated and emaciated laboratory‐reared individuals were compared with that of wild‐caught fish. In general, shallow‐water habitat availability appeared to have little effect on the variables examined. Regardless of reach, wild‐caught fish primarily consumed chironomids, and empty stomachs were rare. Additionally, differences in prey weight, lipid content, or the modeled change in body weight did not usually correspond to differences in shallow‐water habitat availability. Instead, we found annual differences, as prey weight consumed and the percentage of fish with modeled weight gain was often higher in 2015 than 2014, while the opposite was true for the percentage of fish with lipid content values that were comparable with the emaciated laboratory standard. Overall, our findings complement recent suggestions that shallow‐water habitat restoration efforts, as previously implemented, may not benefit sturgeon populations. Our results coupled with previous research suggest that the lower Missouri River prey base can support a stable Shovelnose Sturgeon population; however, additional research is needed to determine whether this applies to Pallid Sturgeon.
","language":"English","publisher":"Wiley","doi":"10.1002/nafm.10236","usgsCitation":"Civiello, A.P., Gosch, N., Gemeinhardt, T., Miller, M., Bonneau, J., Chojnacki, K., Delonay, A.J., and Long, J.M., 2018, Diet and condition of age‐0 Scaphirhynchus Sturgeon: Implications for shallow‐water habitat restoration: North American Journal of Fisheries Management, v. 38, no. 6, p. 1324-1338, https://doi.org/10.1002/nafm.10236.","productDescription":"15 p.","startPage":"1324","endPage":"1338","ipdsId":"IP-090944","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":468332,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/nafm.10236","text":"Publisher Index Page"},{"id":379943,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Missouri","otherGeospatial":"Missouri River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.658203125,\n 38.151837403006766\n ],\n [\n -90.3076171875,\n 38.151837403006766\n ],\n [\n -90.3076171875,\n 39.57182223734374\n ],\n [\n -94.658203125,\n 39.57182223734374\n ],\n [\n -94.658203125,\n 38.151837403006766\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"38","issue":"6","noUsgsAuthors":false,"publicationDate":"2018-10-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Civiello, A. P.","contributorId":171493,"corporation":false,"usgs":false,"family":"Civiello","given":"A.","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":803389,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gosch, N. J. C.","contributorId":244139,"corporation":false,"usgs":false,"family":"Gosch","given":"N. J. C.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":803390,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gemeinhardt, T. R.","contributorId":171492,"corporation":false,"usgs":false,"family":"Gemeinhardt","given":"T. R.","affiliations":[],"preferred":false,"id":803391,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miller, M. L.","contributorId":244140,"corporation":false,"usgs":false,"family":"Miller","given":"M. L.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":803392,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bonneau, J. L.","contributorId":171494,"corporation":false,"usgs":false,"family":"Bonneau","given":"J. L.","affiliations":[],"preferred":false,"id":803393,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Chojnacki, Kimberly 0000-0001-6091-3977 kchojnacki@usgs.gov","orcid":"https://orcid.org/0000-0001-6091-3977","contributorId":221080,"corporation":false,"usgs":true,"family":"Chojnacki","given":"Kimberly","email":"kchojnacki@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":803394,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"DeLonay, Aaron J. 0000-0002-3752-2799 adelonay@usgs.gov","orcid":"https://orcid.org/0000-0002-3752-2799","contributorId":2725,"corporation":false,"usgs":true,"family":"DeLonay","given":"Aaron","email":"adelonay@usgs.gov","middleInitial":"J.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":803395,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Long, James M. 0000-0002-8658-9949 jmlong@usgs.gov","orcid":"https://orcid.org/0000-0002-8658-9949","contributorId":3453,"corporation":false,"usgs":true,"family":"Long","given":"James","email":"jmlong@usgs.gov","middleInitial":"M.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":803396,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70200354,"text":"70200354 - 2018 - Mount St. Helens retrospective: Lessons learned since 1980 and remaining challenges","interactions":[],"lastModifiedDate":"2018-10-15T15:05:06","indexId":"70200354","displayToPublicDate":"2018-10-05T15:05:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5232,"text":"Frontiers in Earth Science","onlineIssn":"2296-6463","active":true,"publicationSubtype":{"id":10}},"title":"Mount St. Helens retrospective: Lessons learned since 1980 and remaining challenges","docAbstract":"Since awakening from a 123-year repose in 1980, Mount St. Helens has provided an opportunity to study changes in crustal magma storage at an active arc volcano—a process of fundamental importance to eruption forecasting and hazards mitigation. There has been considerable progress, but important questions remain unanswered. Was the 1980 eruption triggered by an injection of magma into an upper crustal reservoir? If so, when? How did magma rise into the edifice without producing detectable seismicity deeper than ∼2.5 km or measurable surface deformation beyond the volcano’s north flank? Would precursory activity have been recognized earlier if current monitoring techniques had been available? Despite substantial improvements in monitoring capability, similar questions remain after the dome-forming eruption of 2004–2008. Did additional magma accumulate in the reservoir between the end of the 1980–1986 eruption and the start of the 2004–2008 eruption? If so, when? What is the significance of a relative lull in seismicity and surface deformation for several years prior to the 2004–2008 eruption onset? How did magma reach the surface without producing seismicity deeper than ∼2 km or measurable deformation more than a few hundred meters from the vent? Has the reservoir been replenished since the eruption ended, and is it now primed for the next eruption? What additional precursors, if any, should be expected? This paper addresses these questions, explores possible answers, and identifies unresolved issues in need of additional study. The 1980–1986 and 2004–2008 eruptions could have resulted from second boiling during crystallization of magma long-resident in an upper crustal reservoir, rather than from injection of fresh magma from below. If reservoir pressurization and magma ascent were slow enough, resulting strain might have been accommodated by viscoelastic deformation, without appreciable seismicity or surface deformation, until rising magma entered a brittle regime within 2–2.5 km of the surface. Given the remarkably gas-poor nature of the 2004–2008 dome lava, future eruptive activity might require a relatively long period of quiescence and reservoir pressurization or a large injection of fresh magma—an event that arguably has not occurred since the Kalama eruptive period (C.E. 1479–1720).
","language":"English","publisher":"Frontiers","doi":"10.3389/feart.2018.00142","usgsCitation":"Dzurisin, D., 2018, Mount St. Helens retrospective: Lessons learned since 1980 and remaining challenges: Frontiers in Earth Science, v. 6, p. 1-24, https://doi.org/10.3389/feart.2018.00142.","productDescription":"Article 142; 24 p.","startPage":"1","endPage":"24","ipdsId":"IP-098640","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":460833,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/feart.2018.00142","text":"Publisher Index Page"},{"id":358384,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Mount St. Helens","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.35,\n 46.0833\n ],\n [\n -122,\n 46.0833\n ],\n [\n -122,\n 46.3\n ],\n [\n -122.35,\n 46.3\n ],\n [\n -122.35,\n 46.0833\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"6","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-10-05","publicationStatus":"PW","scienceBaseUri":"5c10a92fe4b034bf6a7e5055","contributors":{"authors":[{"text":"Dzurisin, Daniel 0000-0002-0138-5067 dzurisin@usgs.gov","orcid":"https://orcid.org/0000-0002-0138-5067","contributorId":538,"corporation":false,"usgs":true,"family":"Dzurisin","given":"Daniel","email":"dzurisin@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":748479,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70199951,"text":"70199951 - 2018 - Thiamine deficiency in fishes: Causes, consequences, and potential solutions","interactions":[],"lastModifiedDate":"2018-11-14T09:08:20","indexId":"70199951","displayToPublicDate":"2018-10-05T14:47:59","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3278,"text":"Reviews in Fish Biology and Fisheries","active":true,"publicationSubtype":{"id":10}},"title":"Thiamine deficiency in fishes: Causes, consequences, and potential solutions","docAbstract":"Thiamine deficiency complex (TDC) is a disorder resulting from the inability to acquire or retain thiamine (vitamin B1) and has been documented in organisms in aquatic ecosystems ranging from the Baltic Sea to the Laurentian Great Lakes. The biological mechanisms leading to TDC emergence may vary among systems, but in fishes, one common outcome is high mortality among early life stages. Here, we review the causes and consequences of thiamine deficiency in fishes and identify potential solutions. First, we examine the biochemical and physiological roles of thiamine in vertebrates and find that thiamine deficiency consistently results in impaired neurological function across diverse taxa. Next, we review natural producers of thiamine, which include bacteria, fungi, and plants, and suggest that thiamine is not currently limiting for most animal species inhabiting natural aquatic environments. A survey of historic occurrences of thiamine deficiency identifies consumption of a thiamine-degrading enzyme, thiaminase, as the primary explanation for low levels of thiamine in individuals and subsequent onset of TDC. Lastly, we review conservation and management strategies for TDC mitigation ranging from evolutionary rescue to managing for a diverse forage base. As recent evidence suggests occurrences of thiamine deficiency may be increasing in frequency, increased awareness and a better mechanistic understanding of the underlying causes associated with thiamine deficiency may help prevent further population declines.
","language":"English","publisher":"Springer","doi":"10.1007/s11160-018-9538-x","usgsCitation":"Harder, A.M., Ardren, W.R., Evans, A.N., Futia, M.H., Kraft, C.E., Marsden, J., Richter, C.A., Rinchard, J., Tillitt, D.E., and Christie, M.R., 2018, Thiamine deficiency in fishes: Causes, consequences, and potential solutions: Reviews in Fish Biology and Fisheries, v. 28, no. 4, p. 865-886, https://doi.org/10.1007/s11160-018-9538-x.","productDescription":"12 p.","startPage":"865","endPage":"886","ipdsId":"IP-096509","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":358191,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"28","issue":"4","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2018-10-04","publicationStatus":"PW","scienceBaseUri":"5bc02f78e4b0fc368eb53841","contributors":{"editors":[{"text":"Christie, Mark R.","contributorId":191035,"corporation":false,"usgs":false,"family":"Christie","given":"Mark","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":747459,"contributorType":{"id":2,"text":"Editors"},"rank":10}],"authors":[{"text":"Harder, Avril M.","contributorId":208496,"corporation":false,"usgs":false,"family":"Harder","given":"Avril","email":"","middleInitial":"M.","affiliations":[{"id":37808,"text":"Department of Biological Sciences, Purdue University, 915 W. State St., West Lafayette, Indiana","active":true,"usgs":false}],"preferred":false,"id":747451,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ardren, William R.","contributorId":184180,"corporation":false,"usgs":false,"family":"Ardren","given":"William","email":"","middleInitial":"R.","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":747452,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Evans, Allison N.","contributorId":208497,"corporation":false,"usgs":false,"family":"Evans","given":"Allison","email":"","middleInitial":"N.","affiliations":[{"id":37809,"text":"Department of Fisheries and Wildlife, Oregon State University, 2820 SW Campus Way, Corvallis, OR","active":true,"usgs":false}],"preferred":false,"id":747453,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Futia, Matthew H.","contributorId":208498,"corporation":false,"usgs":false,"family":"Futia","given":"Matthew","email":"","middleInitial":"H.","affiliations":[{"id":37810,"text":"Department of Environmental Science and Ecology, The College at Brockport – State University of New York, 350 New Campus Drive, Brockport, New York","active":true,"usgs":false}],"preferred":false,"id":747454,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kraft, Clifford E.","contributorId":208499,"corporation":false,"usgs":false,"family":"Kraft","given":"Clifford","email":"","middleInitial":"E.","affiliations":[{"id":37811,"text":"Department of Natural Resources, Fernow Hall, Cornell University, Ithaca, NY","active":true,"usgs":false}],"preferred":false,"id":747455,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Marsden, J. Ellen","contributorId":190724,"corporation":false,"usgs":false,"family":"Marsden","given":"J. Ellen","affiliations":[],"preferred":false,"id":747456,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Richter, Catherine A. 0000-0001-7322-4206 crichter@usgs.gov","orcid":"https://orcid.org/0000-0001-7322-4206","contributorId":138994,"corporation":false,"usgs":true,"family":"Richter","given":"Catherine","email":"crichter@usgs.gov","middleInitial":"A.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":747450,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Rinchard, Jacques","contributorId":208500,"corporation":false,"usgs":false,"family":"Rinchard","given":"Jacques","affiliations":[{"id":37810,"text":"Department of Environmental Science and Ecology, The College at Brockport – State University of New York, 350 New Campus Drive, Brockport, New York","active":true,"usgs":false}],"preferred":false,"id":747457,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Tillitt, Donald E. 0000-0002-8278-3955 dtillitt@usgs.gov","orcid":"https://orcid.org/0000-0002-8278-3955","contributorId":1875,"corporation":false,"usgs":true,"family":"Tillitt","given":"Donald","email":"dtillitt@usgs.gov","middleInitial":"E.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":747458,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Christie, Mark R.","contributorId":191035,"corporation":false,"usgs":false,"family":"Christie","given":"Mark","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":747494,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70199953,"text":"70199953 - 2018 - Improving confidence by embracing uncertainty: A meta-analysis of U.S. hunting values for benefit transfer","interactions":[],"lastModifiedDate":"2018-10-05T14:42:19","indexId":"70199953","displayToPublicDate":"2018-10-05T14:42:16","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1477,"text":"Ecosystem Services","active":true,"publicationSubtype":{"id":10}},"title":"Improving confidence by embracing uncertainty: A meta-analysis of U.S. hunting values for benefit transfer","docAbstract":"Recreational hunting in the United States has traditional and cultural importance, and generates substantial economic benefits to individual hunters themselves. This paper conducts a meta-analysis of existing nonmarket valuation estimates for hunting in the United States to explore sources and implications of variation and uncertainty in these estimates. A multi-level meta-regression model is estimated to forecast point estimates for different hunting contexts, as well as to construct bounds of uncertainty around these estimates. The results and discussion provide insight to practitioners who need to conduct or understand benefit transfer, as well as those particularly interested in the value of hunting in the U.S.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecoser.2018.07.001","usgsCitation":"Huber, C., Meldrum, J., and Richardson, L., 2018, Improving confidence by embracing uncertainty: A meta-analysis of U.S. hunting values for benefit transfer: Ecosystem Services, v. 33, no. B, p. 225-236, https://doi.org/10.1016/j.ecoser.2018.07.001.","productDescription":"12 p.","startPage":"225","endPage":"236","ipdsId":"IP-091230","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":358189,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"33","issue":"B","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5bc02f78e4b0fc368eb53843","contributors":{"authors":[{"text":"Huber, Christopher 0000-0001-8446-8134 chuber@usgs.gov","orcid":"https://orcid.org/0000-0001-8446-8134","contributorId":127600,"corporation":false,"usgs":true,"family":"Huber","given":"Christopher","email":"chuber@usgs.gov","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":747463,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Meldrum, James R. 0000-0001-5250-3759 jmeldrum@usgs.gov","orcid":"https://orcid.org/0000-0001-5250-3759","contributorId":195484,"corporation":false,"usgs":true,"family":"Meldrum","given":"James","email":"jmeldrum@usgs.gov","middleInitial":"R.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":747464,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Richardson, Leslie","contributorId":197525,"corporation":false,"usgs":false,"family":"Richardson","given":"Leslie","affiliations":[],"preferred":false,"id":747465,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70199950,"text":"70199950 - 2018 - Machine learning for ecosystem services","interactions":[],"lastModifiedDate":"2018-10-05T14:40:59","indexId":"70199950","displayToPublicDate":"2018-10-05T14:40:55","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1477,"text":"Ecosystem Services","active":true,"publicationSubtype":{"id":10}},"title":"Machine learning for ecosystem services","docAbstract":"Recent developments in machine learning have expanded data-driven modelling (DDM) capabilities, allowing artificial intelligence to infer the behaviour of a system by computing and exploiting correlations between observed variables within it. Machine learning algorithms may enable the use of increasingly available ‘big data’ and assist applying ecosystem service models across scales, analysing and predicting the flows of these services to disaggregated beneficiaries. We use the Weka and ARIES software to produce two examples of DDM: firewood use in South Africa and biodiversity value in Sicily, respectively. Our South African example demonstrates that DDM (64–91% accuracy) can identify the areas where firewood use is within the top quartile with comparable accuracy as conventional modelling techniques (54–77% accuracy). The Sicilian example highlights how DDM can be made more accessible to decision makers, who show both capacity and willingness to engage with uncertainty information. Uncertainty estimates, produced as part of the DDM process, allow decision makers to determine what level of uncertainty is acceptable to them and to use their own expertise for potentially contentious decisions. We conclude that DDM has a clear role to play when modelling ecosystem services, helping produce interdisciplinary models and holistic solutions to complex socio-ecological issues.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecoser.2018.04.004","usgsCitation":"Willcock, S., Martinez-Lopez, J., Hooftman, D.A., Bagstad, K.J., Balbi, S., Marzo, A., Prato, C., Sciandrello, S., Signorello, G., Voigt, B., Villa, F., Bullock, J.M., and Athanasiadis, I., 2018, Machine learning for ecosystem services: Ecosystem Services, v. 33, no. Part B, p. 165-174, https://doi.org/10.1016/j.ecoser.2018.04.004.","productDescription":"10 p.","startPage":"165","endPage":"174","ipdsId":"IP-091205","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":468333,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecoser.2018.04.004","text":"Publisher Index Page"},{"id":358188,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"33","issue":"Part B","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5bc02f79e4b0fc368eb53845","contributors":{"authors":[{"text":"Willcock, Simon 0000-0001-9534-9114","orcid":"https://orcid.org/0000-0001-9534-9114","contributorId":201576,"corporation":false,"usgs":false,"family":"Willcock","given":"Simon","email":"","affiliations":[{"id":36207,"text":"Bangor University","active":true,"usgs":false}],"preferred":false,"id":747437,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Martinez-Lopez, Javier 0000-0003-4857-3396","orcid":"https://orcid.org/0000-0003-4857-3396","contributorId":208480,"corporation":false,"usgs":false,"family":"Martinez-Lopez","given":"Javier","email":"","affiliations":[{"id":32916,"text":"Basque Centre for Climate Change","active":true,"usgs":false}],"preferred":false,"id":747438,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hooftman, Danny A.P.","contributorId":208490,"corporation":false,"usgs":false,"family":"Hooftman","given":"Danny","email":"","middleInitial":"A.P.","affiliations":[{"id":37805,"text":"NERC Centre for Ecology and Hydrology","active":true,"usgs":false}],"preferred":false,"id":747439,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bagstad, Kenneth J. 0000-0001-8857-5615 kjbagstad@usgs.gov","orcid":"https://orcid.org/0000-0001-8857-5615","contributorId":3680,"corporation":false,"usgs":true,"family":"Bagstad","given":"Kenneth","email":"kjbagstad@usgs.gov","middleInitial":"J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":747436,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Balbi, Stefano 0000-0001-8190-5968","orcid":"https://orcid.org/0000-0001-8190-5968","contributorId":208481,"corporation":false,"usgs":false,"family":"Balbi","given":"Stefano","email":"","affiliations":[{"id":32916,"text":"Basque Centre for Climate Change","active":true,"usgs":false}],"preferred":false,"id":747440,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Marzo, Alessia","contributorId":208491,"corporation":false,"usgs":false,"family":"Marzo","given":"Alessia","email":"","affiliations":[{"id":37806,"text":"University of Catania","active":true,"usgs":false}],"preferred":false,"id":747441,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Prato, Carlo","contributorId":208492,"corporation":false,"usgs":false,"family":"Prato","given":"Carlo","email":"","affiliations":[{"id":37806,"text":"University of Catania","active":true,"usgs":false}],"preferred":false,"id":747442,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sciandrello, Saverio 0000-0003-1132-5698","orcid":"https://orcid.org/0000-0003-1132-5698","contributorId":208493,"corporation":false,"usgs":false,"family":"Sciandrello","given":"Saverio","email":"","affiliations":[{"id":37806,"text":"University of Catania","active":true,"usgs":false}],"preferred":false,"id":747443,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Signorello, Giovanni 0000-0002-5140-4975","orcid":"https://orcid.org/0000-0002-5140-4975","contributorId":208494,"corporation":false,"usgs":false,"family":"Signorello","given":"Giovanni","email":"","affiliations":[{"id":37807,"text":"University of Cataria","active":true,"usgs":false}],"preferred":false,"id":747444,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Voigt, Brian","contributorId":208483,"corporation":false,"usgs":false,"family":"Voigt","given":"Brian","email":"","affiliations":[{"id":13253,"text":"University of Vermont","active":true,"usgs":false}],"preferred":false,"id":747445,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Villa, Ferdinando 0000-0002-5114-3007","orcid":"https://orcid.org/0000-0002-5114-3007","contributorId":208486,"corporation":false,"usgs":false,"family":"Villa","given":"Ferdinando","email":"","affiliations":[{"id":32916,"text":"Basque Centre for Climate Change","active":true,"usgs":false}],"preferred":false,"id":747446,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Bullock, James M.","contributorId":208495,"corporation":false,"usgs":false,"family":"Bullock","given":"James","email":"","middleInitial":"M.","affiliations":[{"id":37805,"text":"NERC Centre for Ecology and Hydrology","active":true,"usgs":false}],"preferred":false,"id":747447,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Athanasiadis, Ioannis 0000-0003-2764-0078","orcid":"https://orcid.org/0000-0003-2764-0078","contributorId":208484,"corporation":false,"usgs":false,"family":"Athanasiadis","given":"Ioannis","email":"","affiliations":[{"id":37803,"text":"Wageningen University","active":true,"usgs":false}],"preferred":false,"id":747448,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70197900,"text":"sir20185085 - 2018 - Historical eruptions and hazards at Bogoslof volcano, Alaska","interactions":[],"lastModifiedDate":"2018-10-09T11:20:05","indexId":"sir20185085","displayToPublicDate":"2018-10-05T12:05:38","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":"2018-5085","title":"Historical eruptions and hazards at Bogoslof volcano, Alaska","docAbstract":"Bogoslof volcano is a submarine volcano in the southern
Bering Sea (53.9272°N, 168.0344°W), located 100 kilometers
(km) west of Dutch Harbor/Unalaska, and 40 km north
of Umnak Island. The volcano has a relatively long history of
scientific investigation and several of its historical eruptions
have been documented during brief visits to the area since the
late 1700s. The purpose of this report is to provide a modern
volcanological perspective on past eruptions of Bogoslof and
to readdress some of the eruptive phenomena described in
historical documents and reports. We also present for the first
time a brief analysis of the hazards posed by Bogoslof eruptions.
While this report was being prepared, Bogoslof volcano
was in an ongoing state of eruptive activity that began in
mid-December 2016. Detectable eruptive activity ended in late
August 2017 and the volcano has remained quiet since then.
Because we have not yet visited Bogoslof Island and have
only a few distal tephra samples from two eruptive events,
we will not discuss in detail the 2016–17 eruptive sequence,
but will provide some information for comparative purposes.
When more detailed data has been collected, a more extensive
review of the 2016–17 Bogoslof eruption should be the subject
of future reports.
Alaska Volcano Observatory
U.S. Geological Survey
4210 University Drive
Anchorage, AK 99508
Seafloor sediment flows (turbidity currents) are among the volumetrically most important yet least documented sediment transport processes on Earth. A scarcity of direct observations means that basic characteristics, such as whether flows are entirely dilute or driven by a dense basal layer, remain equivocal. Here we present the most detailed direct observations yet from oceanic turbidity currents. These powerful events in Monterey Canyon have frontal speeds of up to 7.2 m s−1, and carry heavy (800 kg) objects at speeds of ≥4 m s−1. We infer they consist of fast and dense near-bed layers, caused by remobilization of the seafloor, overlain by dilute clouds that outrun the dense layer. Seabed remobilization probably results from disturbance and liquefaction of loose-packed canyon-floor sand. Surprisingly, not all flows correlate with major perturbations such as storms, floods or earthquakes. We therefore provide a new view of sediment transport through submarine canyons into the deep-sea.
","language":"English","publisher":"Nature Publications","doi":"10.1038/s41467-018-06254-6","usgsCitation":"Paull, C.K., Talling, P., Maier, K.L., Parsons, D., Xu, J., Caress, D.W., Gwiazda, R., Lundsten, E., Anderson, K., Barry, J., Chaffey, M., O’Reilly, T., Rosenberger, K.J., Gales, J., Kieft, B., McGann, M., Simmons, S.E., McCann, M., Sumner, E., Clare, M.A., and Cartigny, M.J., 2018, Powerful turbidity currents driven by dense basal layers: Nature Communications, v. 9, no. 1, 4114, 9 p., https://doi.org/10.1038/s41467-018-06254-6.","productDescription":"4114, 9 p.","ipdsId":"IP-091840","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":468334,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41467-018-06254-6","text":"Publisher Index Page"},{"id":395259,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Monterey Canyon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.30804443359375,\n 36.50301312197295\n ],\n [\n -121.73950195312499,\n 36.50301312197295\n ],\n [\n -121.73950195312499,\n 37.070519031125826\n ],\n [\n -122.30804443359375,\n 37.070519031125826\n ],\n [\n -122.30804443359375,\n 36.50301312197295\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"9","issue":"1","noUsgsAuthors":false,"publicationDate":"2018-10-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Paull, C. 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Director,
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U.S. Geological Survey
520 N. Park Avenue
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Large-scale climatic forcing is impacting oceanic biogeochemical cycles and is expected to influence the water-column distribution of trace gases, including methane and nitrous oxide. Our ability as a scientific community to evaluate changes in the water-column inventories of methane and nitrous oxide depends largely on our capacity to obtain robust and accurate concentration measurements that can be validated across different laboratory groups. This study represents the first formal international intercomparison of oceanic methane and nitrous oxide measurements whereby participating laboratories received batches of seawater samples from the subtropical Pacific Ocean and the Baltic Sea. Additionally, compressed gas standards from the same calibration scale were distributed to the majority of participating laboratories to improve the analytical accuracy of the gas measurements. The computations used by each laboratory to derive the dissolved gas concentrations were also evaluated for inconsistencies (e.g., pressure and temperature corrections, solubility constants). The results from the intercomparison and intercalibration provided invaluable insights into methane and nitrous oxide measurements. It was observed that analyses of seawater samples with the lowest concentrations of methane and nitrous oxide had the lowest precisions. In comparison, while the analytical precision for samples with the highest concentrations of trace gases was better, the variability between the different laboratories was higher: 36 % for methane and 27 % for nitrous oxide. In addition, the comparison of different batches of seawater samples with methane and nitrous oxide concentrations that ranged over an order of magnitude revealed the ramifications of different calibration procedures for each trace gas. Finally, this study builds upon the intercomparison results to develop recommendations for improving oceanic methane and nitrous oxide measurements, with the aim of precluding future analytical discrepancies between laboratories.
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Mountains and East Humboldt Range, Nevada, USA: A tool for assessing high-elevation climatic variability","docAbstract":"Local conditions, including lake size, depth, bathymetric profile, watershed characteristics, and timing and extent of ice cover determine the characteristics of diatom floras, and how those assemblages respond to short and long-term changes in climate. The diatom assemblages from fourteen sediment samples collected from marginal and profundal zones of seven lakes in the Ruby Mountains and East Humboldt Range of northeastern Nevada are characterized in order to identify the factors affecting controlling species diversity, equitability, and assemblage structure. Principle component analysis delineates three depth-controlled diatom assemblages: shallow (~1), medium (~11 m), and deep (>12 m). The shallowest samples are characterized by a diverse benthic assemblage, the medium depth sample is dominated by small fragilarioid taxa, and, the deepest samples, while not dominated by planktonic species, show an increase in their abundance. In general, diatom assemblages in shallower samples exhibit higher diversity and greater equitability.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Nova Hedwigia","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Schweizerbart and Borntraeger Science Publishers","doi":"10.1127/nova-suppl/2018/024","usgsCitation":"Starratt, S.W., 2018, Diatom floras in lakes in the Ruby Mountains and East Humboldt Range, Nevada, USA: A tool for assessing high-elevation climatic variability, chap. of Nova Hedwigia, p. 319-358, https://doi.org/10.1127/nova-suppl/2018/024.","productDescription":"40 p.","startPage":"319","endPage":"358","ipdsId":"IP-060849","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":379027,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada","otherGeospatial":"Ruby Mountains, East Humboldt Range","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.8013916015625,\n 39.86758762451019\n ],\n [\n -115.09826660156251,\n 39.86758762451019\n ],\n [\n -115.09826660156251,\n 40.85537053192494\n ],\n [\n -115.8013916015625,\n 40.85537053192494\n ],\n [\n -115.8013916015625,\n 39.86758762451019\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Starratt, Scott W. 0000-0001-9405-1746 sstarrat@usgs.gov","orcid":"https://orcid.org/0000-0001-9405-1746","contributorId":2891,"corporation":false,"usgs":true,"family":"Starratt","given":"Scott","email":"sstarrat@usgs.gov","middleInitial":"W.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":800470,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70199887,"text":"ofr20181162 - 2018 - VS30 at three strong-motion recording stations in Napa and Solano Counties, California — Lovall Valley Road, Broadway Street and Sereno Drive in Vallejo, and Vallejo Fire Station — Calculations determined from S-wave refraction tomography and multichannel analysis of surface waves (Rayleigh and Love)","interactions":[],"lastModifiedDate":"2022-10-31T15:26:38.898926","indexId":"ofr20181162","displayToPublicDate":"2018-10-04T16:01:34","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":"2018-1162","displayTitle":"VS30 at three strong-motion recording stations in Napa and Solano Counties, California — Lovall Valley Road, Broadway Street and Sereno Drive in Vallejo, and Vallejo Fire Station — Calculations determined from S-wave refraction tomography and multichannel analysis of surface waves (Rayleigh and Love)","title":"VS30 at three strong-motion recording stations in Napa and Solano Counties, California — Lovall Valley Road, Broadway Street and Sereno Drive in Vallejo, and Vallejo Fire Station — Calculations determined from S-wave refraction tomography and multichannel analysis of surface waves (Rayleigh and Love)","docAbstract":"The August 24, 2014, moment magnitude (Mw) 6.0 South Napa earthquake caused an estimated $400 million in structural damage to the City of Napa, California. In 2015, we acquired high-resolution P- and S-wave seismic data near three strong-motion recording stations in Napa and Solano Counties where high peak ground accelerations (PGAs) were recorded during the South Napa earthquake. In this report, we present results from three sites—Lovall Valley Loop Road in Napa County (Northern California Seismic Network station, NCSN N019B) and Broadway Street and Sereno Drive (California Geological Survey station, CGS 68294) and Vallejo Fire Station (National Strong Motion Project station, NSMP 1759) in the City of Vallejo, California. To characterize the recording sites in terms of shallow-depth, shear-wave velocities (VS), we used both surface waves (Rayleigh and Love) and body waves (S-wave) to evaluate the time-averaged VS in the upper 30 meters of the subsurface (VS30). We used two-dimensional (2D) multichannel analysis of surface waves (MASW) to evaluate VS from surface waves, and a refraction tomography inversion algorithm, developed by Hole in 1992, to evaluate VS from the body waves. As determined by the tomography and MASW analysis for Love waves, we found VS30 near the strong-motion recording stations at Lovall Valley Loop Road, Broadway Street and Sereno Drive, and the Vallejo Fire Station to be from 711 meters per second (m/s) to 767 m/s, 455 to 673 m/s, and 490 to 583 m/s, respectively. We found that VS30 determined from Love waves were higher than those determined from Rayleigh waves at the Lovall Valley Loop Road recording site (221 m/s higher) and at the Vallejo Fire Station site (62 and 48 m/s higher); however, VS30 from Love waves was lower than those from Rayleigh waves at the Broadway Street and Sereno Drive site (78 m/s lower). We also found that VS30 varied depending on the number of shot points used in our MASW analysis for both Love and Rayleigh waves. Furthermore, VS30 values determined from S-wave refraction tomography are generally closer to those determined from MASW using Love waves than those determined using Rayleigh waves.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181162","usgsCitation":"Chan, J.H., Catchings, R.D., Goldman, M.R., and Criley, C.J., 2018, VS30 at three strong-motion recording stations in Napa and Solano Counties, California — Lovall Valley Road, Broadway Street and Sereno Drive in Vallejo, and Vallejo Fire Station — Calculations determined from S-wave refraction tomography and multichannel analysis of surface waves (Rayleigh and Love): U.S. Geological Survey Open-File Report 2018–1162, 62 p., https://doi.org/10.3133/ofr20181162.","productDescription":"Report: viii, 62 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-096908","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":358151,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9F4IAAL","text":"USGS data release","description":"USGS data release","linkHelpText":"2015 high resolution seismic data recorded at six strong motion seismograph sites in Napa and Solano counties, California"},{"id":358150,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20181161","text":"Open-File Report 2018-1161","linkHelpText":"- VS30 at Three Strong-Motion Recording Stations in Napa and Napa County, California—Main Street in Downtown Napa, Napa Fire Station Number 3, and Kreuzer Lane—Calculations Determined From S-wave Refraction Tomography and Multichannel Analysis of Surface Waves (Rayleigh and Love)"},{"id":358149,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1162/ofr20181162.pdf","text":"Report","size":"18 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Open-File Report 2018-1162"},{"id":358148,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1162/coverthb.jpg"}],"country":"United States","state":"California","county":"Napa County, Solano County","city":"Vallejo","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.41713722595051,\n 38.31876308218918\n ],\n [\n -122.41713722595051,\n 38.293376084062544\n ],\n [\n -122.3791235695102,\n 38.293376084062544\n ],\n [\n -122.3791235695102,\n 38.31876308218918\n ],\n [\n -122.41713722595051,\n 38.31876308218918\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.27260163802902,\n 38.14045873726971\n ],\n [\n -122.27260163802902,\n 38.09368883459186\n ],\n [\n -122.23175717738528,\n 38.09368883459186\n ],\n [\n -122.23175717738528,\n 38.14045873726971\n ],\n [\n -122.27260163802902,\n 38.14045873726971\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Contact Information,
Earthquake Science Center
U.S. Geological Survey
345 Middlefield Road, MS 977
Menlo Park, CA 94025
The August 24, 2014, moment magnitude (Mw) 6.0 South Napa earthquake caused an estimated $400 million in structural damage to the City of Napa, California. In 2015, we acquired high-resolution P- and S-wave seismic data near three strong-motion recording stations in Napa County where high peak ground accelerations (PGAs) were recorded during the South Napa earthquake. In this report, we present results from three sites—Main Street in Downtown Napa (Northern California Seismic Network station, NCSN N016), Napa Fire Station Number 3 (National Strong Motion Project station, NSMP 1765), and Kreuzer Lane (station KRE, temporary deployment). To characterize the recording sites in terms of shallow-depth shear-wave velocities (VS), we used both surface waves (Rayleigh and Love) and body waves (S-wave) to evaluate the time-averaged VS in the upper 30 meters of the subsurface (VS30). We used two-dimensional multichannel analysis of surface waves (MASW) to evaluate VS from the surface waves, and a refraction tomography inversion algorithm, developed by Hole in 1992, to evaluate VS from the body waves. As determined by the various methods, we found VS30 near the strong-motion recording stations on Main Street in Downtown Napa, Napa Fire Station Number 3, and on Kreuzer Lane to be from 281 meters per second (m/s) to 286 m/s, 297 to 371 m/s, and 885 to 916 m/s, respectively. The VS30 calculated from Love waves were slightly lower (10 m/s) than those calculated from Rayleigh waves at the Downtown Napa location and at Napa Fire Station Number 3 (4 m/s); however, VS30 calculated from Love waves was higher (190 m/s) than those calculated from Rayleigh waves at Kreuzer Lane. We also found that VS30 determined from MASW for both Love and Rayleigh waves varied depending on the number of shots along the profiles, and VS30 was not systematic based on the number of shots used in the analysis. Furthermore, VS30 calculated from S-wave refraction tomography are closer to those determined from MASW calculated from Love waves than from using Rayleigh waves.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181161","usgsCitation":"Chan, J.H., Catchings, R.D., Goldman, M.R., and Criley, C.J., 2018, VS30 at three strong-motion recording stations in Napa and Napa County, California — Main Street in downtown Napa, Napa fire station number 3, and Kreuzer Lane — Calculations determined from s-wave refraction tomography and multichannel analysis of surface waves (Rayleigh and Love): U.S. Geological Survey Open-File Report 2018–1161, 47 p., https://doi.org/10.3133/ofr20181161.","productDescription":"Report: vii, 47 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-091224","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":358146,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9F4IAAL","text":"USGS data release","description":"USGS data release","linkHelpText":"2015 high resolution seismic data recorded at six strong motion seismograph sites in Napa and Solano counties, California"},{"id":358144,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1161/ofr20181161.pdf","text":"Report","size":"13 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Open-File Report 2018-1161"},{"id":358143,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1161/coverthb.jpg"},{"id":358145,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20181162","text":"Open-File Report 2018-1162","linkHelpText":"- VS30 at three strong-motion recording stations in Napa and Solano Counties, California—Lovall Valley Road, Broadway Street and Sereno Drive in Vallejo, and Vallejo Fire Station—Calculations determined from S-wave refraction tomography and multichannel analysis of surface waves (Rayleigh and Love)"}],"country":"United States","state":"California","county":"Napa County","city":"Napa","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.33231191016716,\n 38.340761964883995\n ],\n [\n -122.33231191016716,\n 38.28175275852939\n ],\n [\n -122.22277030151793,\n 38.28175275852939\n ],\n [\n -122.22277030151793,\n 38.340761964883995\n ],\n [\n -122.33231191016716,\n 38.340761964883995\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Contact Information,
Earthquake Science Center
U.S. Geological Survey
345 Middlefield Road, MS 977
Menlo Park, CA 94025
Aquatic invasive species (AIS) have spread throughout the United States via major rivers and tributaries. Locks and dams positioned along affected waterways, specifically lock chambers, are being evaluated as potential management sites to prevent further expansion into new areas. Recent research has shown that infusion of chemicals (e.g., carbon dioxide) into water can block or kill several invasive organisms and could be a viable option at navigational structures such as lock chambers because chemical infusion would not interfere with vessel passage or lock operation. Chemical treatments near lock structures will require large-scale fluid-mechanic systems and significant energy. Mixing must extend to all stagnation regions within a lock structure to prevent the passage of an invasive fish. This work describes the performance of both wall- and floor-based CO2-infused-water to water injection manifolds targeted for lock structures in terms of mixing time, mixing homogeneity, injection efficiency, and operational power requirements. Both systems have strengths and weaknesses so selection recommendations are given for applications such as open systems and closed systems.
","language":"English","publisher":"ASME","doi":"10.1115/1.4041361","usgsCitation":"Zolper, T.J., Cupp, A.R., and Smith, D.L., 2018, Investigating the mixing efficiencies of liquid-to-liquid chemical injection manifolds for aquatic invasive species management: Journal of Fluids Engineering, v. 141, no. 3, p. 1-14, https://doi.org/10.1115/1.4041361.","productDescription":"Article 031302; 14 p.","startPage":"1","endPage":"14","ipdsId":"IP-091100","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":437722,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93J4EQ8","text":"USGS data release","linkHelpText":"Investigating the mixing efficiencies of liquid-to-liquid chemical injection manifolds for aquatic invasive species management:Data"},{"id":358968,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"141","issue":"3","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2018-10-04","publicationStatus":"PW","scienceBaseUri":"5c10a92fe4b034bf6a7e5059","contributors":{"authors":[{"text":"Zolper, Thomas J.","contributorId":210258,"corporation":false,"usgs":false,"family":"Zolper","given":"Thomas","email":"","middleInitial":"J.","affiliations":[{"id":38093,"text":"University of Wisconsin - Platteville","active":true,"usgs":false}],"preferred":false,"id":750289,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cupp, Aaron R. 0000-0001-5995-2100 acupp@usgs.gov","orcid":"https://orcid.org/0000-0001-5995-2100","contributorId":5162,"corporation":false,"usgs":true,"family":"Cupp","given":"Aaron","email":"acupp@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":750288,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, David L.","contributorId":192711,"corporation":false,"usgs":false,"family":"Smith","given":"David","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":750290,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70228093,"text":"70228093 - 2018 - Effects of large-scale wetland loss on network connectivity of the Rainwater Basin, Nebraska","interactions":[],"lastModifiedDate":"2022-02-04T17:49:38.98144","indexId":"70228093","displayToPublicDate":"2018-10-04T11:43:51","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2602,"text":"Landscape Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Effects of large-scale wetland loss on network connectivity of the Rainwater Basin, Nebraska","docAbstract":"Context
The Rainwater Basin region in south-central Nebraska supports a complex network of spatially-isolated wetlands that harbor diverse floral and faunal communities. Since European settlement, many wetlands have been lost from the network, which has increased distances among remaining wetlands. As a result, populations of wildlife species with limited dispersal capabilities may have become isolated and face greater local extinction risks.
Objectives
We compared the pre-European settlement and current extent of the Rainwater Basin network to assess the effects of wetland losses on network connectivity for a range of maximum dispersal distances.
Methods
We constructed network models for a range of maximum dispersal distances and calculated network metrics to assess changes in network connectivity and the relative importance of individual wetlands in regulating flow.
Results
Since European settlement, the number of wetlands in the Rainwater Basin has decreased by >90%. The average distance to the nearest neighboring wetland has increased by 150% to ~1.2 km, and the dispersal distance necessary to travel throughout the whole network has increased from 3.5 to 10.0 km. Last, relative importance of individual wetlands depended on the maximum dispersal distance. Which wetlands to preserve to maintain connectivity might therefore depend on the dispersal capabilities of the species or taxa of interest.
Conclusions
To preserve a broad range of biodiversity, conservation efforts should focus on preserving dense clusters of wetlands at fine spatial scales to maintain current levels of network connectivity, and restoring connections between clusters to facilitate long-range dispersal of species with limited dispersal capabilities.
","language":"English","publisher":"Springer","doi":"10.1007/s10980-018-0721-1","usgsCitation":"Verheijen, B., Varner, D.M., and Haukos, D.A., 2018, Effects of large-scale wetland loss on network connectivity of the Rainwater Basin, Nebraska: Landscape Ecology, v. 33, p. 1939-1951, https://doi.org/10.1007/s10980-018-0721-1.","productDescription":"13 p.","startPage":"1939","endPage":"1951","ipdsId":"IP-097520","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":395455,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nebraska","otherGeospatial":"Rainwater Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -99.77783203125,\n 40.04443758460856\n ],\n [\n -95.64697265625,\n 40.04443758460856\n ],\n [\n -95.64697265625,\n 41.376808565702355\n ],\n [\n -99.77783203125,\n 41.376808565702355\n ],\n [\n -99.77783203125,\n 40.04443758460856\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"33","noUsgsAuthors":false,"publicationDate":"2018-10-04","publicationStatus":"PW","contributors":{"authors":[{"text":"Verheijen, Bram H. F.","contributorId":274514,"corporation":false,"usgs":false,"family":"Verheijen","given":"Bram H. F.","affiliations":[{"id":48533,"text":"ksu","active":true,"usgs":false}],"preferred":false,"id":833103,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Varner, Dana M.","contributorId":271196,"corporation":false,"usgs":false,"family":"Varner","given":"Dana","email":"","middleInitial":"M.","affiliations":[{"id":40582,"text":"Rainwater Basin Joint Venture","active":true,"usgs":false}],"preferred":false,"id":833104,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haukos, David A. 0000-0001-5372-9960 dhaukos@usgs.gov","orcid":"https://orcid.org/0000-0001-5372-9960","contributorId":3664,"corporation":false,"usgs":true,"family":"Haukos","given":"David","email":"dhaukos@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":833105,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70199917,"text":"70199917 - 2018 - Artelle et al. (2018) miss the science underlying North American wildlife management","interactions":[],"lastModifiedDate":"2018-10-04T11:17:43","indexId":"70199917","displayToPublicDate":"2018-10-04T11:17:40","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5010,"text":"Science Advances","active":true,"publicationSubtype":{"id":10}},"title":"Artelle et al. (2018) miss the science underlying North American wildlife management","docAbstract":"Artelle et al. (2018) conclude that “hallmarks of science” are largely missing from North American wildlife management based on a desk review of selected hunting management plans and related documents found through Internet searches and email requests to state and provincial wildlife agencies. We highlight three fundamental problems that compromise the validity of the conclusions posited: missing information to support selection of “hallmarks of science,” confusion about the roles and nature of science and management, and failure to engage effectively with the scientists and managers actively managing wildlife populations in North America.
","language":"English","publisher":"Science Advances","doi":"10.1126/sciadv.aat8281","usgsCitation":"Mawdsley, J.R., Organ, J.F., Decker, D.J., Forstchen, A., Regan, R.J., Riley, S.J., Boyce, M.S., Mcdonald, J.E., Dwyer, C., and Mahoney, S.P., 2018, Artelle et al. (2018) miss the science underlying North American wildlife management: Science Advances, v. 4, no. 10, p. 1-2, https://doi.org/10.1126/sciadv.aat8281.","productDescription":"eaat8281; 2 p.","startPage":"1","endPage":"2","ipdsId":"IP-096267","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":468336,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1126/sciadv.aat8281","text":"Publisher Index Page"},{"id":358135,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"4","issue":"10","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5bc02f7ae4b0fc368eb5384f","contributors":{"authors":[{"text":"Mawdsley, Jonathan R.","contributorId":208479,"corporation":false,"usgs":false,"family":"Mawdsley","given":"Jonathan","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":747370,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Organ, John F. 0000-0002-0959-0639 jorgan@usgs.gov","orcid":"https://orcid.org/0000-0002-0959-0639","contributorId":189047,"corporation":false,"usgs":true,"family":"Organ","given":"John","email":"jorgan@usgs.gov","middleInitial":"F.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":747268,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Decker, Daniel J.","contributorId":166906,"corporation":false,"usgs":false,"family":"Decker","given":"Daniel","email":"","middleInitial":"J.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":747371,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Forstchen, Ann","contributorId":166904,"corporation":false,"usgs":false,"family":"Forstchen","given":"Ann","email":"","affiliations":[{"id":12556,"text":"Florida Fish and Wildlife Conservation Commission","active":true,"usgs":false}],"preferred":false,"id":747372,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Regan, Ronald J.","contributorId":113871,"corporation":false,"usgs":true,"family":"Regan","given":"Ronald","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":747373,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Riley, Shawn J.","contributorId":202177,"corporation":false,"usgs":false,"family":"Riley","given":"Shawn","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":747374,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Boyce, Mark S.","contributorId":113205,"corporation":false,"usgs":false,"family":"Boyce","given":"Mark","email":"","middleInitial":"S.","affiliations":[{"id":12980,"text":"Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada","active":true,"usgs":false}],"preferred":false,"id":747375,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Mcdonald, John E. Jr.","contributorId":171604,"corporation":false,"usgs":false,"family":"Mcdonald","given":"John","suffix":"Jr.","email":"","middleInitial":"E.","affiliations":[{"id":12428,"text":"U. S. 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Plague is a flea-borne zoonosis of rodents that often decimates prairie dog (Cynomys spp.) colonies in the western USA. Recently, an oral sylvatic plague vaccine (SPV) was developed to protect prairie dogs from plague and aid recovery of the endangered black-footed ferret (Mustela nigripes). Although oral vaccination programs are targeted toward specific species, field distribution of vaccine-laden baits can result in vaccine uptake by non-target animals and unintended indirect effects. We assessed the impact of SPV on non-target rodents at paired vaccine and placebo-treated prairie dog colonies in four US states from 2013 to 2015. Bait consumption by non-target rodents was high (70.8%, n = 3113), but anti-plague antibody development on vaccine plots was low (23.7%, n = 266). In addition, no significant differences were noted in combined deer mice (Peromyscus maniculatus) and western harvest mouse (Reithrodontomys megalotis) abundance or community evenness and richness of non-target rodents between vaccine-treated and placebo plots. In our 3-year field study, we could not detect a significant positive or negative effect of SPV application on non-target rodents.
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Treatments were administered by egg injection to compare embryonic effects of an environmentally relevant PCB congener mixture in the domestic chicken over a range of doses. Chicken eggs were injected with the PCB mixture with a profile similar to that found in avian eggs collected on the upper Hudson River, New York, USA, at doses that spanned 0 to 98 μg/g egg. Eggs were hatched in the laboratory to ascertain hatching success. In the domestic chicken, the median lethal dose was 0.3 μg/g. These data demonstrate adverse effects of an environmentally relevant PCB mixture and provide the basis for further work using in vitro and other models to characterize the potential risk to avian populations.
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We evaluated the chronic (28 days) toxicity of 4-nonylphenol (4-NP) to two commonly tested species of mussels: fatmucket (Lampsilis siliquoidea) and rainbow mussel (Villosa iris). By the end of the 28 days chronic exposures, mean survival was ≥93% in all treatments, but the mean dry weight and biomass of mussels at the highest exposure concentrations were significantly reduced relative to the control. The 20% effect concentrations were similar between the two species. When compared to all other tested species, fatmucket and rainbow mussels are among the top four most sensitive species to 4-NP. However, U.S. Environmental Protection Agency chronic water quality criterion of 6.6 μg 4-NP/L should protect the two mussel species.
","language":"English","publisher":"Springer","doi":"10.1007/s00128-018-2422-5","usgsCitation":"Ivey, C.D., Wang, N., Alvarez, D., Hammer, E.J., and Bauer, C.R., 2018, Chronic toxicity of 4-nonylphenol to two unionid mussels in water-only exposures: Bulletin of Environmental Contamination and Toxicology, v. 101, no. 4, p. 423-427, https://doi.org/10.1007/s00128-018-2422-5.","productDescription":"5 p.","startPage":"423","endPage":"427","ipdsId":"IP-098145","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":437723,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9R5MQJO","text":"USGS data release","linkHelpText":"Chronic toxicity of 4-Nonylphenol to two unionid mussels in water-only exposures-metadata"},{"id":358132,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"101","issue":"4","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2018-08-21","publicationStatus":"PW","scienceBaseUri":"5bc02f7be4b0fc368eb53855","contributors":{"authors":[{"text":"Ivey, Chris D. 0000-0002-0485-7242 civey@usgs.gov","orcid":"https://orcid.org/0000-0002-0485-7242","contributorId":3308,"corporation":false,"usgs":true,"family":"Ivey","given":"Chris","email":"civey@usgs.gov","middleInitial":"D.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":747310,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wang, Ning 0000-0002-2846-3352 nwang@usgs.gov","orcid":"https://orcid.org/0000-0002-2846-3352","contributorId":2818,"corporation":false,"usgs":true,"family":"Wang","given":"Ning","email":"nwang@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":747311,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Alvarez, David 0000-0002-6918-2709 dalvarez@usgs.gov","orcid":"https://orcid.org/0000-0002-6918-2709","contributorId":150499,"corporation":false,"usgs":true,"family":"Alvarez","given":"David","email":"dalvarez@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":747312,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hammer, Edward J.","contributorId":150723,"corporation":false,"usgs":false,"family":"Hammer","given":"Edward","email":"","middleInitial":"J.","affiliations":[{"id":18077,"text":"U. S. Environmental Protection Agency, Region 5, Water Quality Branch, Chicago, Illinois","active":true,"usgs":false}],"preferred":false,"id":747313,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bauer, Candice R.","contributorId":150724,"corporation":false,"usgs":false,"family":"Bauer","given":"Candice","email":"","middleInitial":"R.","affiliations":[{"id":18077,"text":"U. S. Environmental Protection Agency, Region 5, Water Quality Branch, Chicago, Illinois","active":true,"usgs":false}],"preferred":false,"id":747314,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70199925,"text":"70199925 - 2018 - High microscale variability in Raman thermal maturity estimates from shale organic matter","interactions":[],"lastModifiedDate":"2018-10-04T10:42:06","indexId":"70199925","displayToPublicDate":"2018-10-04T10:41:59","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2033,"text":"International Journal of Coal Geology","active":true,"publicationSubtype":{"id":10}},"title":"High microscale variability in Raman thermal maturity estimates from shale organic matter","docAbstract":"Raman spectroscopy has recently received attention as a means to estimate thermal maturity of organic matter in petroleum generating source rocks to complement more traditional approaches such as vitrinite reflectance and programmed pyrolysis. While many studies have observed positive correlations between source rock thermal maturity and Raman spectral parameters, little attention has been given to the degree of variation in the Raman response across individual organic grains, especially for shales or mudrocks with highly dispersed organic matter. Here the spatial variation in Raman estimates of thermal maturity within individual organic grains is assessed from shales from the Boquillas, Marcellus, Niobrara, and Woodford Formations. The thermal maturity parameters extracted from Raman spectra can vary widely across distances of ≤5 μm within the same organic grain. These results illustrate the high degree of chemical heterogeneity inherent to the organic matter within these source rocks. Additionally, the spatial pattern of the Raman parameters, as revealed by 2D Raman mapping, imply that organic matter structure is influenced by associations with mineral surfaces within the surrounding rock matrix. Chemical heterogeneity and matrix effects directly impact the Raman response from these types of materials and thus the extracted thermal maturity estimate. These findings highlight the care which must be adopted when making Raman measurements of organic matter within source rock matrices, especially for samples which feature highly dispersed, heterogeneous organic matter as found in petroliferous mudrocks.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.coal.2018.09.017","usgsCitation":"Jubb, A., Botterell, P., Birdwell, J.E., Burruss, R.C., Hackley, P.C., Valentine, B.J., Hatcherian, J.J., and Wilson, S., 2018, High microscale variability in Raman thermal maturity estimates from shale organic matter: International Journal of Coal Geology, v. 199, p. 1-9, https://doi.org/10.1016/j.coal.2018.09.017.","productDescription":"9 p.","startPage":"1","endPage":"9","ipdsId":"IP-099700","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":468337,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.coal.2018.09.017","text":"Publisher Index Page"},{"id":437724,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9D5ASO0","text":"USGS data release","linkHelpText":"High Microscale Variability in Raman Thermal Maturity Estimates from Shale Organic Matter - Data Release"},{"id":358129,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"199","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5bc02f7ce4b0fc368eb53857","contributors":{"authors":[{"text":"Jubb, Aaron M. 0000-0001-6875-1079","orcid":"https://orcid.org/0000-0001-6875-1079","contributorId":201978,"corporation":false,"usgs":true,"family":"Jubb","given":"Aaron M.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":747316,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Botterell, Palma J. 0000-0001-7140-0915","orcid":"https://orcid.org/0000-0001-7140-0915","contributorId":208476,"corporation":false,"usgs":false,"family":"Botterell","given":"Palma J.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":747317,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Birdwell, Justin E. 0000-0001-8263-1452 jbirdwell@usgs.gov","orcid":"https://orcid.org/0000-0001-8263-1452","contributorId":3302,"corporation":false,"usgs":true,"family":"Birdwell","given":"Justin","email":"jbirdwell@usgs.gov","middleInitial":"E.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":747318,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Burruss, Robert C. 0000-0001-6827-804X","orcid":"https://orcid.org/0000-0001-6827-804X","contributorId":203443,"corporation":false,"usgs":true,"family":"Burruss","given":"Robert","email":"","middleInitial":"C.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":747319,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hackley, Paul C. 0000-0002-5957-2551 phackley@usgs.gov","orcid":"https://orcid.org/0000-0002-5957-2551","contributorId":592,"corporation":false,"usgs":true,"family":"Hackley","given":"Paul","email":"phackley@usgs.gov","middleInitial":"C.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":747320,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Valentine, Brett J. 0000-0002-8678-2431 bvalentine@usgs.gov","orcid":"https://orcid.org/0000-0002-8678-2431","contributorId":3846,"corporation":false,"usgs":true,"family":"Valentine","given":"Brett","email":"bvalentine@usgs.gov","middleInitial":"J.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":747321,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hatcherian, Javin J. 0000-0001-9151-6798 jhatcherian@usgs.gov","orcid":"https://orcid.org/0000-0001-9151-6798","contributorId":195770,"corporation":false,"usgs":true,"family":"Hatcherian","given":"Javin","email":"jhatcherian@usgs.gov","middleInitial":"J.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":747322,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wilson, Stephen A. 0000-0002-9468-0005","orcid":"https://orcid.org/0000-0002-9468-0005","contributorId":208453,"corporation":false,"usgs":true,"family":"Wilson","given":"Stephen A.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":747323,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70199929,"text":"70199929 - 2018 - Wrangling distributed computing for high-throughput environmental science: An introduction to HTCondor","interactions":[],"lastModifiedDate":"2018-10-04T10:35:36","indexId":"70199929","displayToPublicDate":"2018-10-04T10:35:26","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5727,"text":"PLOS Computational Biology","active":true,"publicationSubtype":{"id":10}},"title":"Wrangling distributed computing for high-throughput environmental science: An introduction to HTCondor","docAbstract":"Biologists and environmental scientists now routinely solve computational problems that were unimaginable a generation ago. Examples include processing geospatial data, analyzing -omics data, and running large-scale simulations. Conventional desktop computing cannot handle these tasks when they are large, and high-performance computing is not always available nor the most appropriate solution for all computationally intense problems. High-throughput computing (HTC) is one method for handling computationally intense research. In contrast to high-performance computing, which uses a single \"supercomputer,\" HTC can distribute tasks over many computers (e.g., idle desktop computers, dedicated servers, or cloud-based resources). HTC facilities exist at many academic and government institutes and are relatively easy to create from commodity hardware. Additionally, consortia such as Open Science Grid facilitate HTC, and commercial entities sell cloud-based solutions for researchers who lack HTC at their institution. We provide an introduction to HTC for biologists and environmental scientists. Our examples from biology and the environmental sciences use HTCondor, an open source HTC system.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pcbi.1006468","usgsCitation":"Erickson, R.A., Fienen, M.N., McCalla, S.G., Weiser, E.L., Bower, M.L., Knudson, J.M., and Thain, G., 2018, Wrangling distributed computing for high-throughput environmental science: An introduction to HTCondor: PLOS Computational Biology, v. 14, no. 10, p. 1-8, https://doi.org/10.1371/journal.pcbi.1006468.","productDescription":"e1006468; 8 p.","startPage":"1","endPage":"8","ipdsId":"IP-087169","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":468338,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pcbi.1006468","text":"Publisher Index Page"},{"id":358128,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","issue":"10","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2018-10-03","publicationStatus":"PW","scienceBaseUri":"5bc02f7ce4b0fc368eb53859","contributors":{"authors":[{"text":"Erickson, Richard A. 0000-0003-4649-482X rerickson@usgs.gov","orcid":"https://orcid.org/0000-0003-4649-482X","contributorId":5455,"corporation":false,"usgs":true,"family":"Erickson","given":"Richard","email":"rerickson@usgs.gov","middleInitial":"A.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":747336,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fienen, Michael N. 0000-0002-7756-4651 mnfienen@usgs.gov","orcid":"https://orcid.org/0000-0002-7756-4651","contributorId":171511,"corporation":false,"usgs":true,"family":"Fienen","given":"Michael","email":"mnfienen@usgs.gov","middleInitial":"N.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":747337,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McCalla, S. Grace 0000-0003-4292-8694 smccalla@usgs.gov","orcid":"https://orcid.org/0000-0003-4292-8694","contributorId":168436,"corporation":false,"usgs":true,"family":"McCalla","given":"S.","email":"smccalla@usgs.gov","middleInitial":"Grace","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":747338,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Weiser, Emily L. 0000-0003-1598-659X","orcid":"https://orcid.org/0000-0003-1598-659X","contributorId":206605,"corporation":false,"usgs":true,"family":"Weiser","given":"Emily","email":"","middleInitial":"L.","affiliations":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"preferred":true,"id":747335,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bower, Melvin L. 0000-0002-4408-3771","orcid":"https://orcid.org/0000-0002-4408-3771","contributorId":208457,"corporation":false,"usgs":true,"family":"Bower","given":"Melvin","email":"","middleInitial":"L.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":747339,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Knudson, Jonathan M. 0000-0003-4985-988X","orcid":"https://orcid.org/0000-0003-4985-988X","contributorId":208458,"corporation":false,"usgs":true,"family":"Knudson","given":"Jonathan","email":"","middleInitial":"M.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":747340,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Thain, Greg","contributorId":208459,"corporation":false,"usgs":false,"family":"Thain","given":"Greg","email":"","affiliations":[{"id":16925,"text":"University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":747341,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70199930,"text":"70199930 - 2018 - Regional patterns in the geochemistry of oil-field water, southern San Joaquin Valley, California, USA","interactions":[],"lastModifiedDate":"2018-10-04T10:31:11","indexId":"70199930","displayToPublicDate":"2018-10-04T10:31:04","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":835,"text":"Applied Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Regional patterns in the geochemistry of oil-field water, southern San Joaquin Valley, California, USA","docAbstract":"Chemical and isotopic data for water co-extracted with hydrocarbons in oil and gas fields are commonly used to examine the source of the formation water and possible impacts on groundwater in areas of oil and gas development. Understanding the geochemical variability of oil-field water could help to evaluate its origin and delineate possible contamination of shallow aquifers in cases where oil-field water is released to the environment. Here we report geochemical and multiple isotope (H, C, O, Sr, Ra) data from 22 oil wells, three sources of produced water that are disposed of in injection wells, and two surface disposal ponds in four oil fields in the southern San Joaquin Valley, California (Fruitvale, Lost Hills, North and South Belridge). Correlations between Cl and δ18O, as well as other ions, and gradual increases in salinity with depth, indicate dilution of one or more saline end-members by meteoric water. The saline end-members, represented by deep samples (610 m–2621 m) in three oil-bearing zones, are characterized by NaCl composition, near-seawater Cl concentrations (median 20,000 mg/L), enriched δ18O
H2O (median 3.4‰), high ammonium(up to 460 mg-N/L), and relatively high radium activity (226Ra+228Ra = 12.3 Bq/L). The deepest sample has low Na/Cl (0.74), high Ca/Mg (5.0), and low 87Sr/86Sr (0.7063), whereas the shallower samples have higher Na/Cl (0.86–1.2), Ca/Mg near 1, and higher 87Sr/86Sr (∼0.7083). The data are consistent with an original seawater source being modified by various depth and lithology dependent diagenetic processes. Dilution by meteoric water occurs naturally on the east side of the valley, and in association with water-injectionactivities on the west side. Meteoric-water flushing, particularly on the east side, results in lower solute concentrations (minimum total dissolved solids 2730 mg/L) and total radium (minimum 0.27 Bq/L) in oil-field water, and promotes biodegradation of dissolved organic carbon and hydrocarbon gases like propane. Acetate concentrations and δ13C of dissolved inorganic carbon indicate biogenic methane production occurs in some shallow oil zones. Natural and human processes produce substantial variability in the geochemistry of oil-field water that should be considered when evaluating mixing between oil-field waters and groundwater. The variability could result in uncertainty as to detecting the potential source and impact of oil-field water on groundwater.