The eastern oyster (Crassostrea virginica) and the reefs they create provide significant ecosystem services. This study measured their possible role in nutrient mitigation through bioassimilation, burial, and oyster-mediated sediment denitrification in near-shore shallow water (< 1 m water depth) and deep-water (> 1 m water depth) oyster reefs in Louisiana. Nitrogen (N) and carbon (C) in shell and tissue differed by oyster reproductive status, size, and habitat type. Changes in tissue percent N and C post-spawning combined with significant reductions in tissue dry weight from the release of gametes, resulted in 20 and 46% reductions in tissue N and C load (mg), respectively, for a 100-mm oyster. Oyster reefs did not enhance burial rates, with burial range rates estimated at 1.4–2.6 g N m−2 year−1, and 26.9–43.8 g C m−2 year−1. Closed-system ex situ incubations indicated net denitrification in all habitat types studied, with the highest rates exceeding 600 µmol N m−2 h−1 during the summer, but no enhancement attributable to oyster reefs specifically. Within the highly productive, organic-rich wetland complex systems of coastal Louisiana, oyster reefs were not associated with enhanced denitrification, likely due to the organic-rich setting, and redundant supplies of organic nitrogen and carbon from adjacent marshes. Context remains critical in determining ecosystem provision of habitats, and efforts to extrapolate and predict nitrogen removal across locations necessitates consideration of local conditions. Considering the large extent of reefs and oyster production across coastal Louisiana, oyster habitats may still contribute to N and C mitigation, but their unique contribution likely comes from bioassimilation, and removal of the oysters from the system.
","language":"English","publisher":"Springer Link","doi":"10.1007/s00227-018-3449-1","usgsCitation":"Westbrook, P., Heffner, L., and La Peyre, M., 2019, Measuring carbon and nitrogen bioassimilation, burial, and denitrification contributions of oyster reefs in Gulf coast estuaries: Marine Biology, v. 166, 4, 14 p., https://doi.org/10.1007/s00227-018-3449-1.","productDescription":"4, 14 p.","ipdsId":"IP-091640","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":395047,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.131591796875,\n 28.849485201023\n ],\n [\n -89.296875,\n 28.849485201023\n ],\n [\n -89.296875,\n 30.130875412002318\n ],\n [\n -91.131591796875,\n 30.130875412002318\n ],\n [\n -91.131591796875,\n 28.849485201023\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"166","noUsgsAuthors":false,"publicationDate":"2018-11-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Westbrook, P.","contributorId":272525,"corporation":false,"usgs":false,"family":"Westbrook","given":"P.","email":"","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":832045,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Heffner, L.","contributorId":272526,"corporation":false,"usgs":false,"family":"Heffner","given":"L.","email":"","affiliations":[{"id":38006,"text":"Western Alaska Landscape Conservation Cooperative","active":true,"usgs":false}],"preferred":false,"id":832046,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"La Peyre, Megan K. 0000-0001-9936-2252","orcid":"https://orcid.org/0000-0001-9936-2252","contributorId":264343,"corporation":false,"usgs":true,"family":"La Peyre","given":"Megan K.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":832047,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70204011,"text":"70204011 - 2019 - Radium accumulation in carbonate river sediments at oil and gas produced water discharges: Implications for beneficial use as disposal management","interactions":[],"lastModifiedDate":"2019-06-27T08:40:40","indexId":"70204011","displayToPublicDate":"2018-11-30T08:39:47","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5830,"text":"Environmental Science","active":true,"publicationSubtype":{"id":10}},"title":"Radium accumulation in carbonate river sediments at oil and gas produced water discharges: Implications for beneficial use as disposal management","docAbstract":"In the western U.S., produced water from oil and gas wells discharged to surface water augments downstream supplies used for irrigation and livestock watering. Here we investigate six permitted discharges on three neighboring tributary systems in Wyoming. During 2013-16, we evaluated radium activities of the permitted discharges and the potential for radium accumulation in associated stream sediments. Radium activities of the sediments at the points of discharge ranged from approximately 200-3600 Bq/kg with elevated activities above the background of 74 Bq/kg over 30 km downstream of one permitted discharge. Sediment as deep as 30 cm near the point of discharge had radium activities elevated above background. X-ray diffraction and targeted sequential extraction of radium in sediments indicate that radium is likely coprecipitated with carbonate, and to a lesser extent sulfate minerals. PHREEQC modeling predicts radium coprecipitation with aragonite and barite, but over-estimates the latter compared to observations of downstream sediment, where carbonate predominates. Mass-balance calculations indicate over 3 billion Bq of radium activity (226Ra+228Ra) is discharged each year from five of the discharges, combined, with only 5 percent of the annual load retained in stream sediments within 100m of the effluent discharges; the remaining 95 percent of the radium is transported farther downstream as sediment-associated and aqueous species","language":"English","publisher":"The Royal Society of Chemistry","doi":"10.1039/C8EM00336J","usgsCitation":"McDevitt, B., McLaughlin, M., Cravotta, C.A., Ajemigbitse, M.A., Van Sice, K.J., Blotevogel, J., Borch, T., and Warner, N.R., 2019, Radium accumulation in carbonate river sediments at oil and gas produced water discharges: Implications for beneficial use as disposal management: Environmental Science, v. 21, no. 2, p. 324-338, https://doi.org/10.1039/C8EM00336J.","productDescription":"15 p.","startPage":"324","endPage":"338","ipdsId":"IP-102035","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":365100,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":365097,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.rsc.org/en/content/articlehtml/2019/em/c8em00336j"}],"volume":"21","issue":"2","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"McDevitt, Bonnie","contributorId":211455,"corporation":false,"usgs":false,"family":"McDevitt","given":"Bonnie","affiliations":[{"id":38248,"text":"Civil and Environmental Engineering Department, The Pennsylvania State University,","active":true,"usgs":false}],"preferred":false,"id":765179,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McLaughlin, Molly","contributorId":216622,"corporation":false,"usgs":false,"family":"McLaughlin","given":"Molly","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":765180,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cravotta, Charles A. III 0000-0003-3116-4684","orcid":"https://orcid.org/0000-0003-3116-4684","contributorId":216591,"corporation":false,"usgs":true,"family":"Cravotta","given":"Charles","suffix":"III","email":"","middleInitial":"A.","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":765178,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ajemigbitse, Moses A","contributorId":216601,"corporation":false,"usgs":false,"family":"Ajemigbitse","given":"Moses","email":"","middleInitial":"A","affiliations":[{"id":6738,"text":"The Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":765181,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Van Sice, Katherine J.","contributorId":216623,"corporation":false,"usgs":false,"family":"Van Sice","given":"Katherine","email":"","middleInitial":"J.","affiliations":[{"id":36985,"text":"Penn State University","active":true,"usgs":false}],"preferred":false,"id":765182,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Blotevogel, Jens","contributorId":216624,"corporation":false,"usgs":false,"family":"Blotevogel","given":"Jens","email":"","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":765183,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Borch, Thomas","contributorId":195631,"corporation":false,"usgs":false,"family":"Borch","given":"Thomas","email":"","affiliations":[],"preferred":false,"id":765184,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Warner, Nathaniel R.","contributorId":211458,"corporation":false,"usgs":false,"family":"Warner","given":"Nathaniel","email":"","middleInitial":"R.","affiliations":[{"id":38248,"text":"Civil and Environmental Engineering Department, The Pennsylvania State University,","active":true,"usgs":false}],"preferred":false,"id":765185,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70206001,"text":"70206001 - 2019 - Chesapeake Bay impact structure—Development of \"brim\" sedimentation in a multilayered marine target","interactions":[],"lastModifiedDate":"2019-10-18T06:35:29","indexId":"70206001","displayToPublicDate":"2018-11-29T07:36:51","publicationYear":"2019","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Chesapeake Bay impact structure—Development of \"brim\" sedimentation in a multilayered marine target","docAbstract":"The late Eocene Chesapeake Bay impact structure was formed in a multilayered target of seawater underlain sequentially by a sediment layer and a rock layer in a continental-shelf environment. Impact effects in the “brim” (annular trough) surrounding and adjacent to the transient crater, between the transient crater rim and the outer margin, primarily were limited to the target-sediment layer. Analysis of published and new lithostratigraphic, biostratigraphic, sedimentologic, petrologic, and mineralogic studies of three core holes, and published studies of a fourth core hole, provided information for the interpretation of the impact processes, their interactions and relative timing, their resulting products, and sedimentation in the brim. Most studies of marine impact-crater materials have focused on those found in the central crater. There are relatively few large, complex marine craters, of which most display a wide brim around the central crater. However, most have been studied using minimal data sets. The large number of core holes and seismic profiles available for study of the Chesapeake Bay impact structure presents a special opportunity for research. The physical and chronologic records supplied by study of the sediment and rock cores of the Chesapeake Bay impact indicate that the effects of the initial, short-lived contact and compression and excavation stages of the impact event primarily were limited to the transient crater. Only secondary effects of these processes are evident in the brim. The preserved record of the brim was created primarily in the subsequent modification stage. In the brim, the records of early impact processes (e.g., outgoing tsunamis, overturned flap collapse) were modified or removed by later processes. Transported and rotated, large and small clasts of target sediments, and intervals of fluidized sands indicate that seismic shaking fractured and partially fluidized the Cretaceous and Paleogene target sediments, which led to their inward transport by collapse and lateral spreading toward the transient crater. The succeeding inward seawater-resurge flow quickly overtook and interacted with the lateral spreading, further facilitating sediment transport across the brim and into the transient crater. Variations in the cohesion and relative depth of the target sediments controlled their degree of disaggregation and redistribution during these events. Melt clasts and shocked and unshocked rock clasts in the resurge sediments indicate fallout from the ejecta curtain and plume. Basal parautochthonous remnant sections of target Cretaceous sediments in the brim thin toward the collapsed transient crater. Overlying seawater-resurge deposits consist primarily of diamictons that vary laterally in thickness, and vertically and laterally in maximum grain size. After cessation of resurge flow and re-establishment of pre-impact sea level, sandy sediment gravity flows moved from the margin to the center of the partially filled impact structure (shelf basin). The uppermost unit consists of stratified sediments deposited from suspension. Postimpact clayey silts cap the crater fill and record the return to shelf sedimentation at atypically large paleodepths within the shelf basin. An unresolved question involves a section of gravel and sand that overlies Neoproterozoic granite in the inner part of the brim in one core hole. This section may represent previously unrecognized, now parautochthonous Cretaceous sediments lying nonconformably above basement granite, or it may represent target sediments that were moved significant distances by lateral spreading above basement rocks or above a granite megaclast from the overturned flap. The Chesapeake Bay impact structure is perhaps the best documented example of the small group of multilayer, marine-target impacts formed in continental shelves or beneath epeiric seas.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Chesapeake Bay impact structure—Development of brim sedimentation in a multilayered marine target","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Geological Society of America","doi":"10.1130/2018.2537","usgsCitation":"Dypvik, H., Gohn, G., Edwards, L., Horton,, J., Powars, D., and Litwin, R., 2019, Chesapeake Bay impact structure—Development of \"brim\" sedimentation in a multilayered marine target, chap. of Chesapeake Bay impact structure—Development of brim sedimentation in a multilayered marine target, p. 1-68, https://doi.org/10.1130/2018.2537.","productDescription":"68 p.","startPage":"1","endPage":"68","ipdsId":"IP-080339","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":468046,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/2018.2537","text":"Publisher Index Page"},{"id":368360,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Chesapeake Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.38220214843749,\n 36.80048816579081\n ],\n [\n -75.5145263671875,\n 36.80048816579081\n ],\n [\n -75.5145263671875,\n 39.7240885773337\n ],\n [\n -77.38220214843749,\n 39.7240885773337\n ],\n [\n -77.38220214843749,\n 36.80048816579081\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Dypvik, Henning","contributorId":219821,"corporation":false,"usgs":false,"family":"Dypvik","given":"Henning","email":"","affiliations":[{"id":24717,"text":"University of Oslo, Norway","active":true,"usgs":false}],"preferred":false,"id":773256,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gohn, Gregory 0000-0003-2000-479X ggohn@usgs.gov","orcid":"https://orcid.org/0000-0003-2000-479X","contributorId":219822,"corporation":false,"usgs":true,"family":"Gohn","given":"Gregory","email":"ggohn@usgs.gov","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":773257,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Edwards, Lucy 0000-0003-4075-3317","orcid":"https://orcid.org/0000-0003-4075-3317","contributorId":219823,"corporation":false,"usgs":true,"family":"Edwards","given":"Lucy","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":false,"id":773258,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Horton,, J. Wright Jr. 0000-0001-6756-6365","orcid":"https://orcid.org/0000-0001-6756-6365","contributorId":219824,"corporation":false,"usgs":true,"family":"Horton,","given":"J. Wright","suffix":"Jr.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":773259,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Powars, David 0000-0002-6787-8964","orcid":"https://orcid.org/0000-0002-6787-8964","contributorId":219825,"corporation":false,"usgs":true,"family":"Powars","given":"David","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":false,"id":773260,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Litwin, Ronald","contributorId":219826,"corporation":false,"usgs":true,"family":"Litwin","given":"Ronald","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":false,"id":773261,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70216038,"text":"70216038 - 2019 - Modelling effects of invasive species and drought on crayfish extinction risk and population dynamics","interactions":[],"lastModifiedDate":"2020-11-04T00:09:04.544821","indexId":"70216038","displayToPublicDate":"2018-11-28T18:02:57","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":862,"text":"Aquatic Conservation: Marine and Freshwater Ecosystems","active":true,"publicationSubtype":{"id":10}},"title":"Modelling effects of invasive species and drought on crayfish extinction risk and population dynamics","docAbstract":"Imperfect detection and misclassification errors are often ignored in the context of invasive species management. Here we present an approach that combines spatially explicit models and an optimization technique to design optimal search and destroy strategies based on noisy monitoring observations. We focus on two invasive plants, melaleuca (Melaleuca quinquenervia) and Old World climbing fern (Lygodium microphyllum), which continue to cause important damages to the Everglades ecosystem. We present a methodological framework that combines Hidden Markov Random Field (HMRF, initially developed for image analysis) and linear programming to optimally search for invasive species. A benefit of this approach is that it accounts for the spatial structure of the system by using a spatially explicit modeling approach (i.e. HMRF), and does not require repeated visits to model the probability of occurrence of species. We found on simulated cases that our approach can lead to substantial improvements in control efficiency when compared to state of the art model-free approaches. For example, in the case of the old world fern, simulations showed that the optimal strategy would allow managers to control up to 34% more sites than with model-free approaches that ignored misclassification and imperfect detection. For melaleuca it was possible to control up to 20% more sites. The vast increase in imagery data obtained from different sources (e.g. unmanned aerial systems, and satellite) provides great opportunities to improve management of natural resources by applying modern computational methods such as the one we present. Our approach can substantially increases the efficiency of invasive species control by accounting for imperfect detection, misclassification error and the spatial structure of the system. Our approach is applicable to other systems and problems, for example it could be applied to the control of plant pathogens, or optimal extraction of resources (e.g. minerals or biological resources).
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolmodel.2018.11.012","usgsCitation":"Bonneau, M., Martin, J., Peyrard, N., Rodgers, L., Romagosa, C.M., and Johnson, F., 2019, Optimal spatial allocation of control effort to manage invasives in the face of imperfect detection and misclassification: Ecological Modelling, v. 392, p. 108-116, https://doi.org/10.1016/j.ecolmodel.2018.11.012.","productDescription":"9 p.","startPage":"108","endPage":"116","ipdsId":"IP-089846","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":468047,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolmodel.2018.11.012","text":"Publisher Index Page"},{"id":366875,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"392","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Bonneau, Mathieu","contributorId":150041,"corporation":false,"usgs":false,"family":"Bonneau","given":"Mathieu","email":"","affiliations":[{"id":12557,"text":"University of Florida, FLREC","active":true,"usgs":false}],"preferred":false,"id":769177,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Martin, Julien 0000-0002-7375-129X","orcid":"https://orcid.org/0000-0002-7375-129X","contributorId":214502,"corporation":false,"usgs":true,"family":"Martin","given":"Julien","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":769178,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Peyrard, Nathalie","contributorId":218403,"corporation":false,"usgs":false,"family":"Peyrard","given":"Nathalie","email":"","affiliations":[],"preferred":false,"id":769179,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rodgers, LeRoy","contributorId":217557,"corporation":false,"usgs":false,"family":"Rodgers","given":"LeRoy","email":"","affiliations":[{"id":7036,"text":"South Florida Water Management District","active":true,"usgs":false}],"preferred":false,"id":769180,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Romagosa, Christina M.","contributorId":200925,"corporation":false,"usgs":false,"family":"Romagosa","given":"Christina","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":769181,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Johnson, Fred A. 0000-0002-5854-3695","orcid":"https://orcid.org/0000-0002-5854-3695","contributorId":213877,"corporation":false,"usgs":true,"family":"Johnson","given":"Fred A.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":769182,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70207458,"text":"70207458 - 2019 - C–O stable isotope geochemistry and 40Ar/39Ar geochronology of the Bear Lodge carbonatite stockwork, Wyoming, USA","interactions":[],"lastModifiedDate":"2019-12-19T15:41:54","indexId":"70207458","displayToPublicDate":"2018-11-28T15:29:49","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2588,"text":"LITHOS","active":true,"publicationSubtype":{"id":10}},"displayTitle":"C–O stable isotope geochemistry and 40Ar/39Ar geochronology of the Bear Lodge carbonatite stockwork, Wyoming, USA","title":"C–O stable isotope geochemistry and 40Ar/39Ar geochronology of the Bear Lodge carbonatite stockwork, Wyoming, USA","docAbstract":"The carbonatite dike swarm and vein stockwork at the center of the Paleogene Bear Lodge alkaline complex (BLAC), Wyoming, USA, is host to diverse REE mineral assemblages that are largely a result of subsolidus modification and REE redistribution. Pseudomorphic replacement of primary burbankite by an assemblage of ancylite, strontianite, and barite is the result of interaction with late-stage hydrothermal fluids that added Sr, Ba, S, F, and REE, analogous to the replacement processes described for some carbonatite complexes of Russia's Kola Peninsula. Carbon and oxygen stable isotope ratios indicate that the primary carbonatite mineralogy experienced degassing/pneumatolysis and alteration by fluids of variable temperature, CO2/H2O ratios, and/or meteoric water content. Isotopic differences of matrix calcite between Group 1 carbonatites (avg. δ13C = −7.3‰; δ18O = 9.1‰) and Group 2 carbonatites (avg. δ13C = −9.9‰; δ18O = 10.2‰) are consistent with loss of CO2 during degassing. The open-system alteration of burbankite caused a pronounced positive δ18O-shift in bulk ancylite pseudomorphs (δ18O: 14.3–25.7‰) relative to matrix calcite (δ18O: 8.7–11.2‰). Oxygen isotope compositions of biotite (δ18O: 4.5–5.9‰) and K-feldspar (δ18O: 7.3–7.9‰) in unoxidized carbonatite are typical of primary magmatic silicates and suggest that fluids responsible for the burbankite-to-ancylite conversion remained predominantly magmatic (carbohydrothermal). Concomitant increases toward the surface in 13C and 18O, oxidation, matrix carbonate dissolution, and the replacement of REE carbonates (ancylite, carbocernaite, and burbankite) by Ca-REE fluorocarbonates (bastnäsite, parisite, synchysite) suggest interaction with late-stage, low temperature (<250 °C) fluids characterized by lower CO2/H2O ratios, and an increasing meteoric water component. The first 40Ar/39Ar ages from carbonatite-hosted biotite and K-feldspar at the BLAC are between 51.45 ± 0.08 and 51.89 ± 0.14 Ma. Although carbonatite is commonly observed as the final intrusive phase in alkaline igneous complexes, relative-age relationships and previously published geochronology for Bear Lodge rocks indicate that alkaline silicate magmatism both preceded and followed carbonatite emplacement.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.lithos.2018.11.030","usgsCitation":"Andersen, A.K., Larson, P.B., and Cosca, M.A., 2019, C–O stable isotope geochemistry and 40Ar/39Ar geochronology of the Bear Lodge carbonatite stockwork, Wyoming, USA: LITHOS, v. 324-324, p. 640-660, https://doi.org/10.1016/j.lithos.2018.11.030.","productDescription":"21 p.","startPage":"640","endPage":"660","ipdsId":"IP-097912 ","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":370516,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Bear Lodge alkaline complex","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -104.79721069335938,\n 44.40827836571936\n ],\n [\n -104.3975830078125,\n 44.40827836571936\n ],\n [\n -104.3975830078125,\n 44.71063416158254\n ],\n [\n -104.79721069335938,\n 44.71063416158254\n ],\n [\n -104.79721069335938,\n 44.40827836571936\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"324-324","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Andersen, Allen K. 0000-0002-6865-2561","orcid":"https://orcid.org/0000-0002-6865-2561","contributorId":217476,"corporation":false,"usgs":true,"family":"Andersen","given":"Allen","email":"","middleInitial":"K.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":778124,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Larson, Peter B.","contributorId":22645,"corporation":false,"usgs":true,"family":"Larson","given":"Peter","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":778125,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cosca, Michael A. 0000-0002-0600-7663 mcosca@usgs.gov","orcid":"https://orcid.org/0000-0002-0600-7663","contributorId":1000,"corporation":false,"usgs":true,"family":"Cosca","given":"Michael","email":"mcosca@usgs.gov","middleInitial":"A.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":778126,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70204970,"text":"70204970 - 2019 - Overview of spirit microscopic imager results","interactions":[],"lastModifiedDate":"2019-08-28T10:57:49","indexId":"70204970","displayToPublicDate":"2018-11-28T14:22:50","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2317,"text":"Journal of Geophysical Research E: Planets","active":true,"publicationSubtype":{"id":10}},"title":"Overview of spirit microscopic imager results","docAbstract":"This paper provides an overview of Mars Exploration Rover Spirit Microscopic Imager (MI) operations and the calibration, processing, and analysis of MI data. The focus of this overview is on the last five Earth years (2005–2010) of Spirit's mission in Gusev crater, supplementing the previous overview of the first 450 sols of the Spirit MI investigation. Updates to radiometric calibration using in‐flight data and improvements in high‐level processing are summarized. Released data products are described, and a table of MI observations, including target/feature names and associated data sets, is appended. The MI observed natural and disturbed exposures of rocks and soils as well as magnets and other rover hardware. These hand‐lens‐scale observations have provided key constraints on interpretations of the formation and geologic history of features, rocks, and soils examined by Spirit. MI images complement observations by other Spirit instruments, and together show that impact and volcanic processes have dominated the origin and evolution of the rocks in Gusev crater, with aqueous activity indicated by the presence of silica‐rich rocks and sulfate‐rich soils. The textures of some of the silica‐rich rocks are similar to terrestrial hot spring deposits, and observations of subsurface cemented layers indicate recent aqueous mobilization of sulfates in places. Wind action has recently modified soils and abraded many of the rocks imaged by the MI, as observed at other Mars landing sites.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2018JE005774","usgsCitation":"Herkenhoff, K., Squyres, S., Arvidson, R.E., Cole, S.B., Sullivan, R., Yingst, A., Cabrol, N., Lee, E., Richie, J., Sucharski, R.M., Calef, F.J., Bell, J., Chapman, M., Geissler, P., Edgar, L.A., Franklin, B., Hurowitz, J.A., Jensen, E., Johnson, J.R., Kirk, R.L., Lanagan, P., Mullins, K., Leff, C., Maki, J., Redding, B.L., Rice, M., Sims, M.H., Spanovich, N., Soderblom, L.A., Sunda, A., Springer, R., and Vaughan, A., 2019, Overview of spirit microscopic imager results: Journal of Geophysical Research E: Planets, v. 124, no. 2, p. 528-584, https://doi.org/10.1029/2018JE005774.","productDescription":"57 p.","startPage":"528","endPage":"584","ipdsId":"IP-087430","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":468048,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/10150/633773","text":"External Repository"},{"id":367004,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Gusev Crater, Mars","volume":"124","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-02-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Herkenhoff, Kenneth E. 0000-0002-3153-6663","orcid":"https://orcid.org/0000-0002-3153-6663","contributorId":206170,"corporation":false,"usgs":true,"family":"Herkenhoff","given":"Kenneth E.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":769327,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Squyres, Steve W","contributorId":218471,"corporation":false,"usgs":false,"family":"Squyres","given":"Steve W","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":769328,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Arvidson, Raymond E.","contributorId":106626,"corporation":false,"usgs":false,"family":"Arvidson","given":"Raymond","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":769334,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cole, Shoshanna B","contributorId":218473,"corporation":false,"usgs":false,"family":"Cole","given":"Shoshanna","email":"","middleInitial":"B","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":769335,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sullivan, Rob","contributorId":218474,"corporation":false,"usgs":false,"family":"Sullivan","given":"Rob","email":"","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":769336,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Yingst, Aileen","contributorId":172313,"corporation":false,"usgs":false,"family":"Yingst","given":"Aileen","email":"","affiliations":[{"id":13179,"text":"Planetary Science Institute","active":true,"usgs":false}],"preferred":false,"id":769337,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cabrol, Nathalie","contributorId":218475,"corporation":false,"usgs":false,"family":"Cabrol","given":"Nathalie","affiliations":[{"id":39853,"text":"NASA Ames Research Center/SETI Institute","active":true,"usgs":false}],"preferred":false,"id":769338,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lee, Ella 0000-0001-6144-7197 elee@usgs.gov","orcid":"https://orcid.org/0000-0001-6144-7197","contributorId":218476,"corporation":false,"usgs":true,"family":"Lee","given":"Ella","email":"elee@usgs.gov","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":769339,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Richie, Janet 0000-0003-4151-1010","orcid":"https://orcid.org/0000-0003-4151-1010","contributorId":206347,"corporation":false,"usgs":true,"family":"Richie","given":"Janet","email":"","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":769329,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Sucharski, Robert M. bsucharski@usgs.gov","contributorId":5051,"corporation":false,"usgs":true,"family":"Sucharski","given":"Robert","email":"bsucharski@usgs.gov","middleInitial":"M.","affiliations":[],"preferred":true,"id":769601,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Calef, Fred J.","contributorId":146331,"corporation":false,"usgs":false,"family":"Calef","given":"Fred","email":"","middleInitial":"J.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":769341,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Bell, James F. 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We built a population model using parameters (i.e. age-specific mortality, age at maturity, and size-specific fecundity) from literature and field studies to investigate the theoretical effects of harvest mortality on age structure. Because stock-recruitment relations are poorly characterized for this species, we explored the influence of both Beverton-Holt and Ricker recruitment processes. Our base model closely resembled the empirical age structures reported from three unfished lakes in Maine, with four percent of fish in the modeled spawning run being age-10 or older. We assessed the additive effects of harvest mortality on age structure using the full range of possible mortalities. As expected, increased harvest mortality in the model resulted in a decline and disappearance of older age-classes such that few fish greater than age-10 remained in the population under a realistic harvest mortality scenario. This age-truncation was qualitatively comparable to data from aggregate age distributions reported from three commercially harvested lakes in Maine. Because the loss of older fish may compromise population viability, this model is a valuable guidance tool for managers to craft regulation of this growing fishery.
","language":"English","publisher":"Taylor and Francis","doi":"10.1080/02705060.2018.1496951","usgsCitation":"Zydlewski, J.D., Begley, M., and Coghlan, S., 2019, Modeling White Sucker (Catostomus commersonii) populations to assess commercial harvest influence on age structure: Journal of Freshwater Ecology, v. 33, no. 1, p. 413-428, https://doi.org/10.1080/02705060.2018.1496951.","productDescription":"16 p.","startPage":"413","endPage":"428","ipdsId":"IP-084184","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":468049,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/02705060.2018.1496951","text":"Publisher Index Page"},{"id":365939,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"33","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-11-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Zydlewski, Joseph D. 0000-0002-2255-2303 jzydlewski@usgs.gov","orcid":"https://orcid.org/0000-0002-2255-2303","contributorId":2004,"corporation":false,"usgs":true,"family":"Zydlewski","given":"Joseph","email":"jzydlewski@usgs.gov","middleInitial":"D.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":false,"id":767018,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Begley, Meg","contributorId":217535,"corporation":false,"usgs":false,"family":"Begley","given":"Meg","email":"","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":767191,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Coghlan, Stephen","contributorId":199623,"corporation":false,"usgs":false,"family":"Coghlan","given":"Stephen","email":"","affiliations":[],"preferred":false,"id":767020,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70227741,"text":"70227741 - 2019 - Modelling effects of invasive species and drought on crayfish extinction risk and population dynamics","interactions":[],"lastModifiedDate":"2022-01-28T16:15:17.750707","indexId":"70227741","displayToPublicDate":"2018-11-28T10:07:19","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":862,"text":"Aquatic Conservation: Marine and Freshwater Ecosystems","active":true,"publicationSubtype":{"id":10}},"title":"Modelling effects of invasive species and drought on crayfish extinction risk and population dynamics","docAbstract":"The occurrence of plant species across the globe is largely constrained by climate. Ecologists use plant-climate relationships such as bioclimatic envelopes and related niche models to determine potential environmental conditions promoting probable species occurrence. Traditionally bioclimatic envelopes either exclude disturbance explicitly, or only include disturbance as infrequent and smaller scale processes, assuming that the net effect of climate parameters on key demographic processes predict longer-term equilibrial responses of biota. Due to increasing frequency and extent of extreme events associated with climate change, ecologists may need to increase focus on individual demographic events driven by environmental extremes such as widespread coral bleaching or large-scale tree die-off. An expanded focus on how extreme events catalyze individual demographic events would complement existing tools that predict long-term equilibrial biogeographic responses associated with long-term trends in climate. In many cases, extreme conditions (e.g. drought) are a necessary precursor for an abrupt demographic event (e.g. large-scale tree die-off) and the effects of extremes can be exacerbated by climatic trends (e.g. higher temperatures in combination with drought). Here, we highlight application of bioclimatic models for predicting individual demographic events. Defining the environmental conditions that precipitate demographic events such as widespread tree mortality is a necessary precursor for applying predictions to geographic space, and may require challenging biota with experiments that impose a combination of ecologically extreme conditions in one parameter and a shifting distribution in another (e.g. drought under higher temperatures). Currently data on conditions that drive individual demographic events associated with extremes are usually rare, aggregated across time, and/or correlative. We highlight this approach with a case study of drought-induced mortality in adult Pinus edulis trees that predicts a more than five-fold increase in frequency of die-off events under a global change scenario of high emissions. This general approach complements both traditional bioclimatic envelopes and more detailed physiological approaches currently being refined to address climate change challenges. Notably, this proposed approach could be developed for any climate condition or plant life stage, offering promise for improving predictions of individual demographic events that are rapidly altering ecosystems globally.
","language":"English","publisher":"University of Chicago Press","doi":"10.1086/700702","usgsCitation":"Law, D.J., Adams, H.D., Breshears, D.D., Cobb, N.S., Bradford, J.B., Zou, C.B., Field, J.P., Gardea, A.A., Williams, A.P., and Huxman, T.E., 2019, Bioclimatic envelopes for individual demographic events driven by extremes: Plant mortality from drought and warming: International Journal of Plant Sciences, v. 80, no. 1, p. 53-62, https://doi.org/10.1086/700702.","productDescription":"10 p.","startPage":"53","endPage":"62","ipdsId":"IP-066810","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":367246,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"80","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Law, Darin J.","contributorId":216390,"corporation":false,"usgs":false,"family":"Law","given":"Darin","email":"","middleInitial":"J.","affiliations":[{"id":39400,"text":"School of Natural Resources and the Environment, University of Arizona, Tucson, AZ, USA","active":true,"usgs":false}],"preferred":false,"id":770258,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Adams, Henry D.","contributorId":218785,"corporation":false,"usgs":false,"family":"Adams","given":"Henry","email":"","middleInitial":"D.","affiliations":[{"id":39910,"text":"Earth and Environmental Sciences Division, Los Alamos National Laboratory, Los Alamos, NM 87544, USA","active":true,"usgs":false}],"preferred":false,"id":770261,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Breshears, David D.","contributorId":51620,"corporation":false,"usgs":false,"family":"Breshears","given":"David","email":"","middleInitial":"D.","affiliations":[{"id":7042,"text":"University of Arizona","active":true,"usgs":false}],"preferred":false,"id":770260,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cobb, Neil S.","contributorId":200776,"corporation":false,"usgs":false,"family":"Cobb","given":"Neil","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":770262,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bradford, John B. 0000-0001-9257-6303 jbradford@usgs.gov","orcid":"https://orcid.org/0000-0001-9257-6303","contributorId":611,"corporation":false,"usgs":true,"family":"Bradford","given":"John","email":"jbradford@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":770257,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Zou, Chris B.","contributorId":218786,"corporation":false,"usgs":false,"family":"Zou","given":"Chris","email":"","middleInitial":"B.","affiliations":[{"id":39911,"text":"Oklahoma State University, Stillwater, OK 74074, USA","active":true,"usgs":false}],"preferred":false,"id":770263,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Field, Jason P.","contributorId":216389,"corporation":false,"usgs":false,"family":"Field","given":"Jason","email":"","middleInitial":"P.","affiliations":[{"id":39400,"text":"School of Natural Resources and the Environment, University of Arizona, Tucson, AZ, USA","active":true,"usgs":false}],"preferred":false,"id":770259,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Gardea, Alfonso A.","contributorId":218787,"corporation":false,"usgs":false,"family":"Gardea","given":"Alfonso","email":"","middleInitial":"A.","affiliations":[{"id":39912,"text":"Centro de Investigación en Alimentación y Desarrollo, A.C., Guaymas, Sonora, Mexico","active":true,"usgs":false}],"preferred":false,"id":770264,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Williams, A. Park","contributorId":200207,"corporation":false,"usgs":false,"family":"Williams","given":"A.","email":"","middleInitial":"Park","affiliations":[{"id":27369,"text":"Lamont-Doherty Earth Observatory at Columbia University","active":true,"usgs":false}],"preferred":false,"id":770265,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Huxman, Travis E.","contributorId":53898,"corporation":false,"usgs":false,"family":"Huxman","given":"Travis","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":770266,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70204991,"text":"70204991 - 2019 - The extreme space weather event in September 1909","interactions":[],"lastModifiedDate":"2019-08-28T12:17:09","indexId":"70204991","displayToPublicDate":"2018-11-27T12:12:44","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5624,"text":"Monthly Notices of the Royal Astronomical Society","active":true,"publicationSubtype":{"id":10}},"title":"The extreme space weather event in September 1909","docAbstract":"We evaluate worldwide low-latitude auroral activity associated with the great magnetic storm of September 1909 for which a minimum Dst value of −595 nT has recently been determined. From auroral observations, we calculate that the equatorward boundary of the auroral oval in the 1909 event was in the range from 31°–35° invariant latitude (assuming auroral height of 400 km) to 37°–38° (800 km). These locations compare with satellite-based observations of precipitating auroral electrons down to 40° magnetic latitude for the March 1989 storm with its comparable minimum Dst value of −589 nT. According to Japanese auroral records, bluish colour started to appear first, followed by reddish colour. The colour change can be attributed to the transition from sunlit aurora to the usual low-latitude reddish aurora. Telegraph communications were disrupted at mid/low latitudes, coincidently with the storm main phase and the early recovery phase. The telegraphic disturbances were caused by geomagnetically induced currents associated with the storm-time ring current and substorm current wedge. From the calculated CME energy ─ based on the 24.75 hr separation between the flare-associated magnetic crochet and the geomagnetic storm sudden commencement and interplanetary conditions inferred from geomagnetic data ─ and consideration of the ∼−40 nT crochet amplitude, we estimated that the soft X-ray class of the 24 September 1909 flare was ≥X10. As is the case for other extreme storms, strong/sharp excursions in the horizontal component of the magnetic field observed at low-latitude magnetic stations were coincident with the observation of low-latitude aurora.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/mnras/sty3196","usgsCitation":"Hayakawa, H., Ebihara, Y., Cliver, E.W., Hattori, K., Toriumi, S., Love, J.J., Umemura, N., Namekata, K., Sakaue, T., Takahashi, T., and Shibata, K., 2019, The extreme space weather event in September 1909: Monthly Notices of the Royal Astronomical Society, v. 484, no. 3, p. 4083-4099, https://doi.org/10.1093/mnras/sty3196.","productDescription":"17 p.","startPage":"4083","endPage":"4099","ipdsId":"IP-104047","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":313,"text":"Geomagnetism Program","active":false,"usgs":true}],"links":[{"id":468050,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://purl.org/net/epubs/work/44708484","text":"External Repository"},{"id":367012,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"484","issue":"3","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-11-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Hayakawa, Hisashi","contributorId":215231,"corporation":false,"usgs":false,"family":"Hayakawa","given":"Hisashi","email":"","affiliations":[{"id":39211,"text":"Graduate School of Letters, Osaka University; Science and Technology Facilities Council, RAL Space, Rutherford Appleton Laboratory, Harwell Campus","active":true,"usgs":false}],"preferred":false,"id":769466,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ebihara, Yusuke","contributorId":218518,"corporation":false,"usgs":false,"family":"Ebihara","given":"Yusuke","email":"","affiliations":[{"id":39859,"text":"Research Institute for Sustainable Humanosphere, Kyoto University, Uji; Unit of Synergetic Studies for Space, Kyoto University, Kyoto","active":true,"usgs":false}],"preferred":false,"id":769467,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cliver, Edward W.","contributorId":215232,"corporation":false,"usgs":false,"family":"Cliver","given":"Edward","email":"","middleInitial":"W.","affiliations":[{"id":39212,"text":"National Solar Observatory","active":true,"usgs":false}],"preferred":false,"id":769468,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hattori, Kentaro","contributorId":218519,"corporation":false,"usgs":false,"family":"Hattori","given":"Kentaro","email":"","affiliations":[{"id":39860,"text":"Graduate School of Science, Kyoto University, Kyoto","active":true,"usgs":false}],"preferred":false,"id":769469,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Toriumi, Shin","contributorId":218520,"corporation":false,"usgs":false,"family":"Toriumi","given":"Shin","email":"","affiliations":[{"id":39861,"text":"National Astronomical Observatory of Japan","active":true,"usgs":false}],"preferred":false,"id":769470,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Love, Jeffrey J. 0000-0002-3324-0348 jlove@usgs.gov","orcid":"https://orcid.org/0000-0002-3324-0348","contributorId":760,"corporation":false,"usgs":true,"family":"Love","given":"Jeffrey","email":"jlove@usgs.gov","middleInitial":"J.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":769471,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Umemura, Norio","contributorId":218521,"corporation":false,"usgs":false,"family":"Umemura","given":"Norio","email":"","affiliations":[{"id":39862,"text":"Institute for Space–Earth Environmental Research, Nagoya University","active":true,"usgs":false}],"preferred":false,"id":769472,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Namekata, Kosuke","contributorId":218522,"corporation":false,"usgs":false,"family":"Namekata","given":"Kosuke","email":"","affiliations":[{"id":39860,"text":"Graduate School of Science, Kyoto University, Kyoto","active":true,"usgs":false}],"preferred":false,"id":769473,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Sakaue, Takahito","contributorId":218523,"corporation":false,"usgs":false,"family":"Sakaue","given":"Takahito","email":"","affiliations":[{"id":39863,"text":"Graduate School of Science, Kyoto University, Kyoto; Kwasan Observatory, Kyoto University","active":true,"usgs":false}],"preferred":false,"id":769474,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Takahashi, Takuya","contributorId":218524,"corporation":false,"usgs":false,"family":"Takahashi","given":"Takuya","email":"","affiliations":[{"id":39863,"text":"Graduate School of Science, Kyoto University, Kyoto; Kwasan Observatory, Kyoto University","active":true,"usgs":false}],"preferred":false,"id":769475,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Shibata, Kazunari","contributorId":218525,"corporation":false,"usgs":false,"family":"Shibata","given":"Kazunari","email":"","affiliations":[{"id":39863,"text":"Graduate School of Science, Kyoto University, Kyoto; Kwasan Observatory, Kyoto University","active":true,"usgs":false}],"preferred":false,"id":769476,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70201074,"text":"70201074 - 2019 - Extreme value-based methods for modeling elk yearly movements","interactions":[],"lastModifiedDate":"2019-02-11T15:03:17","indexId":"70201074","displayToPublicDate":"2018-11-27T10:08:36","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2151,"text":"Journal of Agricultural, Biological, and Environmental Statistics","active":true,"publicationSubtype":{"id":10}},"title":"Extreme value-based methods for modeling elk yearly movements","docAbstract":"Species range shifts and the spread of diseases are both likely to be driven by extreme movements, but are difficult to statistically model due to their rarity. We propose a statistical approach for characterizing movement kernels that incorporate landscape covariates as well as the potential for heavy-tailed distributions. We used a spliced distribution for distance travelled paired with a resource selection function to model movements biased toward preferred habitats. As an example, we used data from 704 annual elk movements around the Greater Yellowstone Ecosystem from 2001 to 2015. Yearly elk movements were both heavy-tailed and biased away from high elevations during the winter months. We then used a simulation to illustrate how these habitat effects may alter the rate of disease spread using our estimated movement kernel relative to a more traditional approach that does not include landscape covariates. Supplementary materials accompanying this paper appear online.
","language":"English","publisher":"Springer","doi":"10.1007/s13253-018-00342-2","usgsCitation":"Wijeyakulasuriya, D.A., Hanks, E.M., Shaby, B.A., and Cross, P.C., 2019, Extreme value-based methods for modeling elk yearly movements: Journal of Agricultural, Biological, and Environmental Statistics, v. 24, no. 1, p. 73-91, https://doi.org/10.1007/s13253-018-00342-2.","productDescription":"19 p.","startPage":"73","endPage":"91","ipdsId":"IP-094523","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":359698,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"24","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-11-12","publicationStatus":"PW","scienceBaseUri":"5bfe65e0e4b0815414ca60f2","contributors":{"authors":[{"text":"Wijeyakulasuriya, Dhanushi A. 0000-0001-6244-6575","orcid":"https://orcid.org/0000-0001-6244-6575","contributorId":210839,"corporation":false,"usgs":false,"family":"Wijeyakulasuriya","given":"Dhanushi","email":"","middleInitial":"A.","affiliations":[{"id":36985,"text":"Penn State University","active":true,"usgs":false}],"preferred":false,"id":752266,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hanks, Ephraim M. 0000-0003-0345-7164","orcid":"https://orcid.org/0000-0003-0345-7164","contributorId":210840,"corporation":false,"usgs":false,"family":"Hanks","given":"Ephraim","email":"","middleInitial":"M.","affiliations":[{"id":36985,"text":"Penn State University","active":true,"usgs":false}],"preferred":false,"id":752267,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shaby, Benjamin A.","contributorId":210841,"corporation":false,"usgs":false,"family":"Shaby","given":"Benjamin","email":"","middleInitial":"A.","affiliations":[{"id":36985,"text":"Penn State University","active":true,"usgs":false}],"preferred":false,"id":752268,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cross, Paul C. 0000-0001-8045-5213 pcross@usgs.gov","orcid":"https://orcid.org/0000-0001-8045-5213","contributorId":2709,"corporation":false,"usgs":true,"family":"Cross","given":"Paul","email":"pcross@usgs.gov","middleInitial":"C.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":752265,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70228051,"text":"70228051 - 2019 - The future of recreational fisheries: Advances in science, monitoring, management, and practice","interactions":[],"lastModifiedDate":"2022-02-03T15:45:33.331121","indexId":"70228051","displayToPublicDate":"2018-11-27T09:40:24","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1661,"text":"Fisheries Research","active":true,"publicationSubtype":{"id":10}},"title":"The future of recreational fisheries: Advances in science, monitoring, management, and practice","docAbstract":"Recreational fisheries (RF) are complex social-ecological systems that play an important role in aquatic environments while generating significant social and economic benefits around the world. The nature of RF is diverse and rapidly evolving, including the participants, their priorities and behaviors, and the related ecological impacts and social and economic benefits. RF can lead to negative ecological impacts, particularly through overexploitation of fish populations and spread of non-native species and genotypes through stocking. Hence, careful management and monitoring of RF is essential to sustain these ecologically and socioeconomically important resources. This special issue on recreational fisheries contains diverse research, syntheses, and perspectives that highlight the advances being made in RF research, monitoring, management, and practice, which we summarize here. Co-management actions are rising, often involving diverse interest groups including government and non-government organizations; applying collaborative management practices can help balance social and economic benefits with conservation targets. Technological and methodological advances are improving the ability to monitor biological, social, and economic dynamics of RF, which underpin the ability to maximize RF benefits through management actions. To ensure RF sustainability, much research focuses on the ecological aspects of RF, as well as the development of management and angling practices that reduce negative impacts on fish populations. For example, angler behavior can be influenced to conform to conservation-minded angling practices through regulations, but is often best accomplished through growing bottom-up social change movements. Anglers can also play an important role in fisheries monitoring and conservation, including providing data on fish abundance and assemblages (i.e., citizen science). The increasing impacts that growing human populations are having on the global environment are threatening many of the natural resources and ecosystem services they provide, including valuable RF. However, with careful development of research initiatives, monitoring and management, sustainable RF can generate positive outcomes for both society and natural ecosystems and help solve allocation conflicts with commercial fisheries and conservation.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.fishres.2018.10.019","usgsCitation":"Brownscombe, J., Hyder, K., Potts, W.M., Wilson, K.V., Pope, K.L., Danylchuk, A., Cooke, S.J., Clarke, A., Arlinghaus, R., and Postel, J.R., 2019, The future of recreational fisheries: Advances in science, monitoring, management, and practice: Fisheries Research, v. 211, p. 247-255, https://doi.org/10.1016/j.fishres.2018.10.019.","productDescription":"9 p.","startPage":"247","endPage":"255","ipdsId":"IP-099929","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":468051,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://repository.publisso.de/resource/frl:6411884","text":"External Repository"},{"id":395354,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"211","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Brownscombe, J. W.","contributorId":274403,"corporation":false,"usgs":false,"family":"Brownscombe","given":"J. W.","affiliations":[{"id":17786,"text":"Carleton University","active":true,"usgs":false}],"preferred":false,"id":832966,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hyder, K.","contributorId":268277,"corporation":false,"usgs":false,"family":"Hyder","given":"K.","email":"","affiliations":[{"id":17786,"text":"Carleton University","active":true,"usgs":false}],"preferred":false,"id":832967,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Potts, W. M.","contributorId":268289,"corporation":false,"usgs":false,"family":"Potts","given":"W.","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":832968,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wilson, K. V.","contributorId":196488,"corporation":false,"usgs":false,"family":"Wilson","given":"K.","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":832969,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pope, Kevin L. 0000-0003-1876-1687","orcid":"https://orcid.org/0000-0003-1876-1687","contributorId":270762,"corporation":false,"usgs":true,"family":"Pope","given":"Kevin","email":"","middleInitial":"L.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"preferred":true,"id":832970,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Danylchuk, A. J.","contributorId":146536,"corporation":false,"usgs":false,"family":"Danylchuk","given":"A. J.","affiliations":[{"id":16720,"text":"Department of Environmental Conservation, University of Massachusetts, Amherst, MA 01003-9485, USA","active":true,"usgs":false}],"preferred":false,"id":832973,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Cooke, S. J.","contributorId":55645,"corporation":false,"usgs":false,"family":"Cooke","given":"S.","email":"","middleInitial":"J.","affiliations":[{"id":16718,"text":"Department of Biology, Carleton University, 1125 Colonel By Drive, Ottawa, Ontario K1S 5B6, Canada","active":true,"usgs":false}],"preferred":false,"id":832974,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Clarke, Adrian","contributorId":274507,"corporation":false,"usgs":false,"family":"Clarke","given":"Adrian","email":"","affiliations":[],"preferred":false,"id":833066,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Arlinghaus, R.","contributorId":268274,"corporation":false,"usgs":false,"family":"Arlinghaus","given":"R.","affiliations":[{"id":55610,"text":"IGB Leibniz-Institute of Freshwater Ecology and Inland Fisheries","active":true,"usgs":false}],"preferred":false,"id":832971,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Postel, J. R.","contributorId":152576,"corporation":false,"usgs":false,"family":"Postel","given":"J.","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":832972,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70215506,"text":"70215506 - 2019 - Early arc development recorded in Permian–Triassic plutons of the northern Mojave Desert region, California, USA","interactions":[],"lastModifiedDate":"2020-10-21T14:12:28.072247","indexId":"70215506","displayToPublicDate":"2018-11-27T09:09:56","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1786,"text":"Geological Society of America Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"Early arc development recorded in Permian–Triassic plutons of the northern Mojave Desert region, California, USA","docAbstract":"Permian–Middle Triassic plutons in the northern Mojave Desert, USA, are emplaced into the cryptic El Paso terrane, which is characterized by a northwest-striking belt of deep marine eugeoclinal strata juxtaposed against Proterozoic basement and its miogeoclinal cover. Fourteen new zircon U-Pb ages from the El Paso Mountains and Lane Mountain region of the Mojave Desert record nearly continuous magmatism occurring between ca. 275 and 240 Ma. These ages, which are taken to record the onset of subduction-related magmatism along the southwestern Laurentian margin, are older than the earliest arc plutons documented in the southern Sierra Nevada region to the north and in the Transverse Ranges to the south. They overlap, however, with Permian arc plutons documented in Sonora, Mexico. Dated plutons are compositionally variable, but can be characterized as intermediate to felsic, calcic to calc-alkalic, and having chemistries consistent with generation in an arc setting. Whole rock Sr-Nd isotopic compositions vary widely from relatively primitive (Sri = 0.7035, initial εNd = +3, initial εHf in zircon = +13) to moderately evolved (Sri = 0.708, initial εNd = –5, initial εHf in zircon = –3). Isotopic signatures differ considerably from partially coeval Triassic suites of the Transverse Ranges and central Mojave, which are more evolved and consistent with emplacement in Proterozoic continental crust of the Mojave province. They also differ considerably from those typical of intermediate plutons generated in intra-oceanic arcs, which are overall much more mantle-like. This suggests that the underpinnings of the El Paso terrane may be at least partly composed of continental crust and that magmas emplaced into the terrane may have been variably contaminated by crustal components. This is supported by the presence of Precambrian and early Paleozoic zircon inheritance recorded in some plutons. In all isotopic systems, values are the most evolved in the oldest plutons (ca. 275–270 Ma), becoming more juvenile in the Middle Triassic. These temporal trends, together with pluton fabrics and new estimates of Permian plate vectors, are interpreted to reflect generation of the earliest arc in a contractional setting that may have driven crustal thickening and a greater involvement of crustal materials in Permian magmas. This result supports a model of forced subduction initiation, which is favored by a change in plate motions along a previously weak margin, and predicts an initial compressive state in the upper plate. The uniformly primitive signatures of Triassic melts are taken to indicate a change to a transtensional upper-plate stress regime that promoted the development of more voluminous, primarily mantle-derived melts. Regional pluton age patterns suggest that arc magmatism initiated in restricted areas of the southwestern Laurentian margin (northern Mojave, Sonora) and then migrated north and south ultimately becoming a continuous arc by Jurassic time.
Aims
Understanding the conditions associated with dryland vegetation recovery after restoration treatments is challenging due to a lack of monitoring data and high environmental variability over time and space. Tracking recovery trajectories with satellite‐based vegetation indices can strengthen predictions of restoration outcomes across broad areas with varying environmental conditions.
Location
Southwestern United States.
Methods
We quantified the recovery trajectories of spring and summer soil‐adjusted total vegetation index (SATVI) for 5 to 10 year periods following post‐wildfire seeding or prescribed burns for 241 treatment sites, and related SATVI to ground‐based vegetation cover. We modeled SATVI based on time since treatment, yearly temperature and precipitation, weather extremes following treatment, soil available water capacity, invasive species presence, and treatment type. We also tested for the effects of environmental variables on trajectories, by examining interactions with years post‐treatment.
Results
Ground‐based vegetation cover and SATVI were highly correlated. Most treatment sites had positive recovery rates for spring (82%) and summer (85%) SATVI. Several environmental variables affected vegetation recovery trajectories as indicated by interactions with time since treatment. Yearly warm season precipitation had a positive effect on SATVI recovery that increased over time, whereas the positive effect of extreme high warm season precipitation following treatment decreased over time for both seasons of vegetation measurements. For spring SATVI, the positive effect of cool season yearly precipitation increased over time while the negative effect of extreme high temperatures following treatment became more negative over time. Invasive species presence led to higher spring, but not summer, SATVI.
Conclusions
Satellite‐based remote sensing is a promising tool to assess vegetation recovery following restoration treatments, particularly when it is combined with ground‐based monitoring. Our results suggest that weather extremes following restoration treatments can affect vegetation recovery trajectories and should be considered in decisions such as the timing of restoration treatments.
Early ocean survival of Chinook salmon, Oncorhynchus tshawytscha, varies greatly inter-annually and may be the period during which later spawning abundance and fishery recruitment are set. Therefore, identifying environmental drivers related to early survival may inform better models for management and sustainability of salmon in a variable environment. With this in mind, our main objectives were to (a) identify regions of high temporal variability in growth potential over a 23-year time series, (b) determine whether the spatial distribution of growth potential was correlated with observed oceanographic conditions, and (c) determine whether these spatial patterns in growth potential could be used to estimate juvenile salmon survival. We applied this method to the fall run of the Central Valley Chinook salmon population, focusing on the spring and summer period after emigration into central California coastal waters. For the period from 1988 to 2010, juvenile salmon growth potential on the central California continental shelf was described by three spatial patterns. These three patterns were most correlated with upwelling, detrended sea level anomalies, and the strength of onshore/offshore currents, respectively. Using the annual strength of these three patterns, as well as the overall growth potential throughout central California coastal waters, in a generalized linear model we explained 82% of the variation in juvenile salmon survival estimates. We attributed the relationship between growth potential and survival to variability in environmental conditions experienced by juvenile salmon during their first year at sea, as well as potential shifts in predation pressure following out-migration into coastal waters.
Jupiter's Moon Europa has one of the youngest geological surfaces in our solar system with an age of 40–90 Ma, implying an intense history of resurfacing. The surface of Europa indeed shows abundant evidence of tectonic deformation related to extension, strike-slip, and shortening. However, observed features related to shortening are scarce compared with pervasive extensive extensional features such as dilational bands, and do not suffice as the sole mechanism for recycling aging terranes. Recently, evidence for potential plate tectonics, associated with subduction zones, has been discovered on Europa; this could be responsible for recycling most of Europa's surface. However, basic physical parameters needed to initiate subduction on Europa, such as thickness of the brittle layer, deformation rates, and orientation of pre-existing zones of weakness at which subduction could start, are not well understood. Here, we aim to better understand the process and the conditions that could lead to initiation of subduction on Europa through physical experiments, using wax to simulate Europa's two-layered (i.e. convective) icy crust. By deforming the wax, strain on Europa's surface—possibly caused by diurnal tides or its nonsynchronous rotation—is simulated. Our results indicate that subduction could initiate over a broad range of surface thicknesses and deformation rates above a minimum conductive layer thickness, but is strongly dependent on the orientation of the pre-existing zones of weakness. Very thin conductive layer experiments, however, result in a previously undescribed process that we term ductile rolldown, which creates surface features similar to double ridges observed on Europa. Thus, subduction and ductile rolldown represent physically plausible mechanisms that could play a critical role in resurfacing Europa throughout its geologic history. These results could yield significant implications for Europa's thermal history and evolution, habitability, and future spacecraft missions.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.icarus.2018.11.005","usgsCitation":"Klasner, M.W., Gross, J., Tindall, S., Schlishe, R.W., and Potter, C.J., 2019, Europa’s ice tectonics: New insights from physical wax experiments with implications for subduction initiation and global resurfacing processes: Icarus, v. 321, p. 593-607, https://doi.org/10.1016/j.icarus.2018.11.005.","productDescription":"15 p.","startPage":"593","endPage":"607","ipdsId":"IP-098567","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":420904,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Europa, Jupiter","volume":"321","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Klasner, Michael W","contributorId":329765,"corporation":false,"usgs":false,"family":"Klasner","given":"Michael","email":"","middleInitial":"W","affiliations":[{"id":12727,"text":"Rutgers University","active":true,"usgs":false}],"preferred":false,"id":883238,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gross, Juliane 0000-0002-5288-0981","orcid":"https://orcid.org/0000-0002-5288-0981","contributorId":223401,"corporation":false,"usgs":false,"family":"Gross","given":"Juliane","email":"","affiliations":[{"id":40711,"text":"Rutgers State University of New Jersey","active":true,"usgs":false}],"preferred":false,"id":883239,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tindall, Sarah","contributorId":329766,"corporation":false,"usgs":false,"family":"Tindall","given":"Sarah","email":"","affiliations":[{"id":78714,"text":"Kutztown University","active":true,"usgs":false}],"preferred":false,"id":883240,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schlishe, Roy W.","contributorId":329767,"corporation":false,"usgs":false,"family":"Schlishe","given":"Roy","email":"","middleInitial":"W.","affiliations":[{"id":12727,"text":"Rutgers University","active":true,"usgs":false}],"preferred":false,"id":883241,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Potter, Christopher J. 0000-0002-2300-6670 cpotter@usgs.gov","orcid":"https://orcid.org/0000-0002-2300-6670","contributorId":1026,"corporation":false,"usgs":true,"family":"Potter","given":"Christopher","email":"cpotter@usgs.gov","middleInitial":"J.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":883242,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70207166,"text":"70207166 - 2019 - Interannual snow accumulation variability on glaciers derived from repeat spatially extensive ground-penetrating radar surveys","interactions":[],"lastModifiedDate":"2019-12-11T08:06:31","indexId":"70207166","displayToPublicDate":"2018-11-22T07:51:17","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3554,"text":"The Cryosphere","active":true,"publicationSubtype":{"id":10}},"title":"Interannual snow accumulation variability on glaciers derived from repeat spatially extensive ground-penetrating radar surveys","docAbstract":"There is significant uncertainty regarding the spatiotemporal distribution of seasonal snow on glaciers, despite being a fundamental component of glacier mass balance. To address this knowledge gap, we collected repeat, spatially extensive high-frequency ground-penetrating radar (GPR) observations on two glaciers in Alaska for five consecutive years. GPR measurements showed steep snow water equivalent (SWE) elevation gradients at both sites; continental Gulkana Glacier’s SWE gradient averaged 115 mm 100 m–1 and maritime Wolverine Glacier’s gradient averaged 440 mm 100 m–1 (over >1000 m). We extrapolated GPR point observations across the glacier surface using terrain parameters derived from digital elevation models as predictor variables in two statistical models (stepwise multivariable linear regression and regression trees). Elevation and proxies for wind redistribution had the greatest explanatory power, and exhibited relatively time-constant coefficients over the study period. Both statistical models yielded comparable estimates of glacier-wide average SWE (1 % average difference at Gulkana, 4 % average difference at Wolverine), although the spatial distributions produced by the models diverged in unsampled regions of the glacier, particularly at Wolverine. In total, six different methods for estimating the glacier-wide average agreed within ± 11 %. We assessed interannual variability in the spatial pattern of snow accumulation predicted by the statistical models using two quantitative metrics. Both glaciers exhibited a high degree of temporal stability, with ~85 % of the glacier area experiencing less than 25 % normalized absolute variability over this five-year interval. We found SWE at a sparse network (3 stakes per glacier) of long-term glaciological stake sites to be highly correlated with the GPR-derived glacier-wide average. We estimate that interannual variability in the spatial pattern of SWE is only a small component (4–10 % of glacier-wide average) of the total mass balance uncertainty and thus, our findings support the concept that sparse stake networks effectively measure interannual variability in winter balance on glaciers, rather than some spatially varying pattern of snow accumulation.","language":"English","publisher":"Copernicus Publications","doi":"10.5194/tc-12-3617-2018","usgsCitation":"McGrath, D.J., Sass, L., O’Neel, S., McNeil, C., Candela, S.G., Baker, E., and Marshall, H.P., 2019, Interannual snow accumulation variability on glaciers derived from repeat spatially extensive ground-penetrating radar surveys: The Cryosphere, v. 12, p. 3617-3633, https://doi.org/10.5194/tc-12-3617-2018.","productDescription":"17 p.","startPage":"3617","endPage":"3633","ipdsId":"IP-098923","costCenters":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"links":[{"id":468053,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/tc-12-3617-2018","text":"Publisher Index Page"},{"id":370143,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -153.80859375,\n 58.21702494960191\n ],\n [\n -140.888671875,\n 58.21702494960191\n ],\n [\n -140.888671875,\n 64.28275952823394\n ],\n [\n -153.80859375,\n 64.28275952823394\n ],\n [\n -153.80859375,\n 58.21702494960191\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"12","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2018-11-22","publicationStatus":"PW","contributors":{"authors":[{"text":"McGrath, Daniel J 0000-0002-9462-6842","orcid":"https://orcid.org/0000-0002-9462-6842","contributorId":221142,"corporation":false,"usgs":false,"family":"McGrath","given":"Daniel","email":"","middleInitial":"J","affiliations":[{"id":40333,"text":"Department of Geosciences, Colorado State University, Fort Collins, CO","active":true,"usgs":false}],"preferred":false,"id":777116,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sass, Louis 0000-0003-4677-029X lsass@usgs.gov","orcid":"https://orcid.org/0000-0003-4677-029X","contributorId":221141,"corporation":false,"usgs":true,"family":"Sass","given":"Louis","email":"lsass@usgs.gov","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":777115,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"O’Neel, Shad 0000-0002-9185-0144 soneel@usgs.gov","orcid":"https://orcid.org/0000-0002-9185-0144","contributorId":166740,"corporation":false,"usgs":true,"family":"O’Neel","given":"Shad","email":"soneel@usgs.gov","affiliations":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":107,"text":"Alaska Climate Science Center","active":true,"usgs":true},{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":777117,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McNeil, Christopher J. 0000-0003-4170-0428 cmcneil@usgs.gov","orcid":"https://orcid.org/0000-0003-4170-0428","contributorId":5803,"corporation":false,"usgs":true,"family":"McNeil","given":"Christopher J.","email":"cmcneil@usgs.gov","affiliations":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":777118,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Candela, Salvatore G 0000-0002-1605-4463","orcid":"https://orcid.org/0000-0002-1605-4463","contributorId":221143,"corporation":false,"usgs":false,"family":"Candela","given":"Salvatore","email":"","middleInitial":"G","affiliations":[{"id":40334,"text":"School of Earth Sciences and Byrd Polar Research Center, Ohio State University, Columbus, OH","active":true,"usgs":false}],"preferred":false,"id":777119,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Baker, Emily 0000-0002-0938-3496 ehbaker@usgs.gov","orcid":"https://orcid.org/0000-0002-0938-3496","contributorId":200570,"corporation":false,"usgs":true,"family":"Baker","given":"Emily","email":"ehbaker@usgs.gov","affiliations":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":777120,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Marshall, Hans P.","contributorId":172745,"corporation":false,"usgs":false,"family":"Marshall","given":"Hans","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":777121,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70202166,"text":"70202166 - 2019 - Uncertainty in quantitative analyses of topographic change: Error propagation and the role of thresholding","interactions":[],"lastModifiedDate":"2019-06-18T08:59:22","indexId":"70202166","displayToPublicDate":"2018-11-21T13:07:57","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1425,"text":"Earth Surface Processes and Landforms","active":true,"publicationSubtype":{"id":10}},"title":"Uncertainty in quantitative analyses of topographic change: Error propagation and the role of thresholding","docAbstract":"Topographic surveys inevitably contain error, introducing uncertainty into estimates of volumetric or mean change based on the differencing of repeated surveys. In the geomorphic community, uncertainty has often been framed as a problem of separating out real change from apparent change due purely to error, and addressed by removing measured change considered indistinguishable from random noise from analyses (thresholding). Thresholding is important when quantifying gross changes (i.e. total erosion or total deposition), which are systematically biased by random errors in stable parts of a landscape. However, net change estimates are not substantially influenced by those same random errors, and the use of thresholds results in inherently biased, and potentially misleading, estimates of net change and uncertainty. More generally, thresholding is unrelated to the important process of propagating uncertainty in order to place uncertainty bounds around final estimates. Error propagation methods for uncorrelated, correlated, and systematic errors are presented. Those equations demonstrate that uncertainties in modern net change analyses, as well as in gross change analyses using reasonable thresholds, are likely to be dominated by low‐magnitude but highly correlated or systematic errors, even after careful attempts to reduce those errors. In contrast, random errors with little to no correlation largely cancel to negligible levels when averaged or summed. Propagated uncertainty is then typically insensitive to the precision of individual measurements, and is instead defined by the relative mean error (accuracy) over the area of interest. Given that real‐world mean elevation changes in many landscape settings are often similar in magnitude to potential mean errors in repeat topographic analyses, reducing highly correlated or systematic errors will be central to obtaining accurate change estimates, while placing uncertainty bounds around those results provides essential context for their interpretation.
","language":"English","publisher":"Wiley","doi":"10.1002/esp.4551","usgsCitation":"Anderson, S.W., 2019, Uncertainty in quantitative analyses of topographic change: Error propagation and the role of thresholding: Earth Surface Processes and Landforms, v. 44, no. 5, p. 1015-1033, https://doi.org/10.1002/esp.4551.","productDescription":"19 p.","startPage":"1015","endPage":"1033","ipdsId":"IP-097288","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":361175,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"44","issue":"5","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2019-02-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Anderson, Scott W. 0000-0003-1678-5204 swanderson@usgs.gov","orcid":"https://orcid.org/0000-0003-1678-5204","contributorId":196687,"corporation":false,"usgs":true,"family":"Anderson","given":"Scott","email":"swanderson@usgs.gov","middleInitial":"W.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":757062,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70200978,"text":"70200978 - 2019 - Distance models as a tool for modelling detection probability and density of native bumblebees","interactions":[],"lastModifiedDate":"2019-03-15T12:42:58","indexId":"70200978","displayToPublicDate":"2018-11-20T10:58:40","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5782,"text":"Journal of Applied Entomology","active":true,"publicationSubtype":{"id":10}},"title":"Distance models as a tool for modelling detection probability and density of native bumblebees","docAbstract":"Effective monitoring of native bee populations requires accurate estimates of population size and relative abundance among habitats. Current bee survey methods, such as netting or pan trapping, may be adequate for a variety of study objectives but are limited by a failure to account for imperfect detection. Biases due to imperfect detection could result in inaccurate abundance estimates or erroneous insights about the response of bees to different environments. To gauge the potential biases of currently employed survey methods, we compared abundance estimates of bumblebees (Bombus spp.) derived from hierarchical distance sampling models (HDS) to bumblebee counts collected from fixed‐area net surveys (“net counts”) and fixed‐width transect counts (“transect counts”) at 47 early‐successional forest patches in Pennsylvania. Our HDS models indicated that detection probabilities of Bombus spp. were imperfect and varied with survey‐ and site‐covariates. Despite being conspicuous, Bombus spp. were not reliably detected beyond 5 m. Habitat associations of Bombus spp. density were similar across methods, but the strength of association with shrub cover differed between HDS and net counts. Additionally, net counts suggested sites with more grass hosted higher Bombusspp. densities whereas HDS suggested that grass cover was associated with higher detection probability but not Bombus spp. density. Density estimates generated from net counts and transect counts were 80%–89% lower than estimates generated from distance sampling. Our findings suggest that distance modelling provides a reliable method to assess Bombus spp. density and habitat associations, while accounting for imperfect detection caused by distance from observer, vegetation structure, and survey covariates. However, detection/non‐detection data collected via point‐counts, line‐transects and distance sampling for Bombus spp. are unlikely to yield species‐specific density estimates unless individuals can be identified by sight, without capture. Our results will be useful for informing the design of monitoring programs for Bombus spp.and other pollinators.
","language":"English","publisher":"Wiley","doi":"10.1111/jen.12583","usgsCitation":"McNeil, D.J., Otto, C., Moser, E.L., Urban-Mead, K.R., King, D.E., Rodewald, A.D., and Larkin, J.L., 2019, Distance models as a tool for modelling detection probability and density of native bumblebees: Journal of Applied Entomology, v. 143, no. 3, p. 225-235, https://doi.org/10.1111/jen.12583.","productDescription":"11 p.","startPage":"225","endPage":"235","ipdsId":"IP-096861","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":359602,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Pennsylvania","county":"Centre County, Clinton County","otherGeospatial":"Pennsylvania 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Jr.","contributorId":37620,"corporation":false,"usgs":false,"family":"McNeil","given":"Darin","suffix":"Jr.","email":"","middleInitial":"J.","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":751537,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Otto, Clint 0000-0002-7582-3525 cotto@usgs.gov","orcid":"https://orcid.org/0000-0002-7582-3525","contributorId":5426,"corporation":false,"usgs":true,"family":"Otto","given":"Clint","email":"cotto@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":751536,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Moser, Erin L.","contributorId":210723,"corporation":false,"usgs":false,"family":"Moser","given":"Erin","email":"","middleInitial":"L.","affiliations":[{"id":38138,"text":"Indiana University of Pennsylvania","active":true,"usgs":false}],"preferred":false,"id":751538,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Urban-Mead, Katherine R.","contributorId":210724,"corporation":false,"usgs":false,"family":"Urban-Mead","given":"Katherine","email":"","middleInitial":"R.","affiliations":[{"id":38139,"text":"Department of Entomology, Cornell University, Ithaca, NY 14850, US","active":true,"usgs":false}],"preferred":false,"id":751539,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"King, David E.","contributorId":210754,"corporation":false,"usgs":false,"family":"King","given":"David","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":751540,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rodewald, Amanda D.","contributorId":169748,"corporation":false,"usgs":false,"family":"Rodewald","given":"Amanda","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":751541,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Larkin, Jeffrey L.","contributorId":169747,"corporation":false,"usgs":false,"family":"Larkin","given":"Jeffrey","email":"","middleInitial":"L.","affiliations":[{"id":17929,"text":"American Bird Conservancy","active":true,"usgs":false},{"id":34542,"text":"Department of Biology. Indiana University of Pennsylvania","active":true,"usgs":false}],"preferred":false,"id":751542,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70202862,"text":"70202862 - 2019 - Keeping the crown of the continent connected: An interagency US2 connectivity workshop report","interactions":[],"lastModifiedDate":"2019-04-17T10:20:15","indexId":"70202862","displayToPublicDate":"2018-11-20T10:19:53","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Keeping the crown of the continent connected: An interagency US2 connectivity workshop report","docAbstract":"At over 2.5 million acres, Glacier National Park and the Bob Marshall Wilderness complex form one of the largest protected areas in the continental United States. Straddling the Continental Divide, these two areas form a vital linkage between vast areas of public land to the south towards Yellowstone, and contiguous protected areas north of the US-Canada border. However, US Highway 2 (US2) and the Burlington Northern-Santa Fe (BNSF) railroad separate Glacier National Park to the north from the Bob Marshall Wilderness complex to the south. While this narrow ribbon of development passes through primarily public land, it is bordered in some areas by narrow strips of private land. Many of these private parcels are developed as ranches, campgrounds, or seasonal and permanent home sites and businesses.
Currently, two of the defining characteristics of this portion of the US2 corridor are relatively low highway traffic volume, but relatively high railroad traffic volume. The highway had a 2017 annual average daily traffic volume (AADT) of 1859 vehicles, far less than other interstate highways around the region which often have AADTs well over 10,000. Conversely, the BNSF railroad line currently carries about 33 trains per day, making it one of the busier railroad lines in the northwestern US.
While wildlife movement patterns across this corridor have not been well studied, the existing data suggests that wildlife can still make frequent and successful crossings at current railroad and highway traffic levels. However, as the region’s human population grows, we expect that connectivity to diminish. Over the past decade (2000-2017), based on census data, Flathead County has grown by 10% and Glacier County has grown by 1.5%. A study on loss of open space found that Flathead County alone accounts for 15% of the new homes built in Montana since 2000 (https://headwaterseconomics.org/economicdevelopment/local-studies/montana-home construction/). Outdoor recreation and tourism have also been breaking participation records (source: GPI record passengers https://flatheadbeacon.com/2018/01/24/glacier-park-international-airport-sees-record-passengers-2017/, GNP record visitation https://www.usnews.com/news/best-states/montana/articles/2018-01 15/glaciernational-park-breaks-visitation-record-in-2017). This growth has been accompanied by a ~50% increase in highway traffic volume in the corridor over the past decade (Waller and Miller 2015). This increased traffic is decreasing the time available for wildlife to cross the highway and appears to be increasing the frequency of wildlife killed by vehicles (Fig. 1 and 2).
In addition, the Middle Fork of the Flathead River is a favored river for recreation, and this also appears to be growing. In the summer of 2017, researchers recorded 136 boats per day in July and 93 boats per day in August. Although the river does not extend along the entire highway, it extends along 31 miles of the highway corridor.
Accurate and precise analyses of oil and gas (O&G) wastewaters and solids (e.g., sediments and sludge) are important for the regulatory monitoring of O&G development and tracing potential O&G contamination in the environment. In this study, 15 laboratories participated in an inter-laboratory comparison on the chemical characterization of three O&G wastewaters from the Appalachian Basin and four solids impacted by O&G development, with the goal of evaluating the quality of data and the accuracy of measurements for various analytes of concern. Using a variety of different methods, analytes in the wastewaters with high concentrations (i.e., >5 mg L−1) were easily detectable with relatively high accuracy, often within ±10% of the most probable value (MPV). In contrast, often less than 7 of the 15 labs were able to report detectable trace metal(loid) concentrations (i.e., Cr, Ni, Cu, Zn, As, and Pb) with accuracies of approximately ±40%. Despite most labs using inductively coupled plasma mass spectrometry (ICP-MS) with low instrument detection capabilities for trace metal analyses, large dilution factors during sample preparation and low trace metal concentrations in the wastewaters limited the number of quantifiable determinations and likely influenced analytical accuracy. In contrast, all the labs measuring Ra in the wastewaters were able to report detectable concentrations using a variety of methods including gamma spectroscopy and wet chemical approaches following Environmental Protection Agency (EPA) standard methods. However, the reported radium activities were often greater than ±30% different to the MPV possibly due to calibration inconsistencies among labs, radon leakage, or failing to correct for self-attenuation. Reported radium activities in solid materials had less variability (±20% from MPV) but accuracy could likely be improved by using certified radium standards and accounting for self-attenuation that results from matrix interferences or a density difference between the calibration standard and the unknown sample. This inter-laboratory comparison illustrates that numerous methods can be used to measure major cation, minor cation, and anion concentrations in O&G wastewaters with relatively high accuracy while trace metal(loid) and radioactivity analyses in liquids may often be over ±20% different from the MPV.
","language":"English","publisher":"Royal Society of Chemistry","doi":"10.1039/c8em00359a","usgsCitation":"Tasker, T.L., Burgos, W.D., Ajemigbitse, M.A., Lauer, N.E., Gusa, A.V., Kuatbek, M., May, D., Landis, J.D., Alessi, D.S., Johnsen, A.M., Kaste, J.M., Headrick, K., Wilke, F.D., McNeal, M., Engle, M.A., Jubb, A., Vidic, R., Vengosh, A., and Warner, N.R., 2019, Accuracy of methods for reporting inorganic element concentrations and radioactivity in oil and gas wastewaters from the Appalachian Basin, U.S. based on an inter-laboratory comparison.: Environmental Science: Processes and Impacts, v. 21, no. 2, p. 224-241, https://doi.org/10.1039/c8em00359a.","productDescription":"18 p.","startPage":"224","endPage":"241","ipdsId":"IP-100644","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":365078,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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Pittsburg","active":true,"usgs":false}],"preferred":false,"id":765150,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Vengosh, Avner","contributorId":208460,"corporation":false,"usgs":false,"family":"Vengosh","given":"Avner","email":"","affiliations":[{"id":12643,"text":"Duke University","active":true,"usgs":false}],"preferred":false,"id":765151,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Warner, Nathaniel R.","contributorId":211458,"corporation":false,"usgs":false,"family":"Warner","given":"Nathaniel","email":"","middleInitial":"R.","affiliations":[{"id":38248,"text":"Civil and Environmental Engineering Department, The Pennsylvania State University,","active":true,"usgs":false}],"preferred":false,"id":765152,"contributorType":{"id":1,"text":"Authors"},"rank":19}]}} ,{"id":70216090,"text":"70216090 - 2019 - New approach to assessing age uncertainties – The 2300-year varve chronology from Eklutna Lake, Alaska (USA)","interactions":[],"lastModifiedDate":"2023-11-08T14:28:34.652988","indexId":"70216090","displayToPublicDate":"2018-11-19T10:49:08","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3219,"text":"Quaternary Science Reviews","active":true,"publicationSubtype":{"id":10}},"title":"New approach to assessing age uncertainties – The 2300-year varve chronology from Eklutna Lake, Alaska (USA)","docAbstract":"Developing robust chronological frameworks of lacustrine sediment is central to reconstructing past environmental changes. We present varve chronologies from five sites extending back 2300 years from Eklutna Lake, in the Chugach Mountains of south-central Alaska. The chronologies are built from image analysis of high-resolution photographs and CT scans of sediment cores. The age uncertainty of each record is tested by three methods. We first present varve chronologies from individual sites and reconcile the difference in varve delimitation from two observers. The varve chronologies from each site are then compared to each other using a series of marker beds that can be traced across the lake basin. Finally, using a new Bayesian probabilistic model, we develop age models that incorporate information regarding age uncertainty from the multiple-observer method and the age distribution of marker layers from multiple cores. To evaluate the accuracy of the Bayesian model output, we used seven radiocarbon ages from terrestrial macrofossils and four tephra layers traceable across the core sites. The major-element geochemistry of the tephra layers and their ages are presented here for the first time. The Bayesian age model offers a new approach to quantifying age uncertainty in inter-correlated cores of varved sediment.