{"pageNumber":"616","pageRowStart":"15375","pageSize":"25","recordCount":40828,"records":[{"id":70048762,"text":"70048762 - 2014 - A previously unrecognized path of early Holocene base flow and elevated discharge from Lake Minong to Lake Chippewa across eastern Upper Michigan","interactions":[],"lastModifiedDate":"2014-09-23T14:33:14","indexId":"70048762","displayToPublicDate":"2014-01-22T13:10:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1727,"text":"GSA Special Papers","active":true,"publicationSubtype":{"id":10}},"title":"A previously unrecognized path of early Holocene base flow and elevated discharge from Lake Minong to Lake Chippewa across eastern Upper Michigan","docAbstract":"It has long been hypothesized that flux of fresh meltwater from glacial Lake Minong in North America's Superior Basin to the North Atlantic Ocean triggered rapid climatic shifts during the early Holocene. The spatial context of recent support for this idea demands a reevaluation of the exit point of meltwater from the Superior Basin. We used ground penetrating radar (GPR), foundation borings from six highway bridges, a GIS model of surface topography, geologic maps, U.S. Department of Agriculture–Natural Resources Conservation Service soils maps, and well logs to investigate the possible linkage of Lake Minong with Lake Chippewa in the Lake Michigan Basin across eastern Upper Michigan. GPR suggests that a connecting channel lies buried beneath the present interlake divide at Danaher. A single optical age hints that the channel aggraded to 225 m as elevated receipt of Lake Agassiz meltwater in the Superior Basin began to wane <10.6 ka. The large supply of sediment required to accommodate aggradation was immediately available at the channel's edge in the littoral shelves of abandoned Lake Algonquin and in distal parts of post-Algonquin fans. As discharge decreased further, the aggraded channel floor was quickly breached and interbasin flow to Lake Chippewa was restored. Basal radiocarbon ages on wood from small lakes along the discharge path and a GIS model of Minong's shoreline are consistent with another transgression of Minong after ca. 9.5 ka. At the peak of the latter transgression, the southeastern rim of the Superior Basin (Nadoway Drift Barrier) failed, ending Lake Minong. Upon Minong's final drop, aggradational sediments were deposited at Danaher, infilling the prior breach.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"GSA Special Papers","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Geological Society of America","doi":"10.1130/2014.2508(01)","usgsCitation":"Loope, W.L., Jol, H.M., Fisher, T.G., Blewett, W.L., Loope, H.M., and Legg, R.J., 2014, A previously unrecognized path of early Holocene base flow and elevated discharge from Lake Minong to Lake Chippewa across eastern Upper Michigan: GSA Special Papers, v. 508, p. 1-13, https://doi.org/10.1130/2014.2508(01).","productDescription":"13 p.","startPage":"1","endPage":"13","ipdsId":"IP-051112","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":294371,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":294370,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1130/2014.2508(01)"}],"country":"United States","state":"Michigan","otherGeospatial":"Lake Superior","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -84.6753,46.4146 ], [ -84.6753,46.5054 ], [ -84.527,46.5054 ], [ -84.527,46.4146 ], [ -84.6753,46.4146 ] ] ] } } ] }","volume":"508","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5422bb09e4b08312ac7ceec9","contributors":{"authors":[{"text":"Loope, Walter L. wloope@usgs.gov","contributorId":4616,"corporation":false,"usgs":true,"family":"Loope","given":"Walter","email":"wloope@usgs.gov","middleInitial":"L.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":485585,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jol, Harry M.","contributorId":11571,"corporation":false,"usgs":true,"family":"Jol","given":"Harry","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":485586,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fisher, Timothy G.","contributorId":45659,"corporation":false,"usgs":true,"family":"Fisher","given":"Timothy","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":485588,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Blewett, William L.","contributorId":57031,"corporation":false,"usgs":true,"family":"Blewett","given":"William","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":485589,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Loope, Henry M.","contributorId":79381,"corporation":false,"usgs":true,"family":"Loope","given":"Henry","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":485590,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Legg, Robert J.","contributorId":30527,"corporation":false,"usgs":true,"family":"Legg","given":"Robert","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":485587,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}}
,{"id":70073494,"text":"70073494 - 2014 - Uncertainty, robustness, and the value of information in managing an expanding Arctic goose population","interactions":[],"lastModifiedDate":"2014-01-22T13:12:00","indexId":"70073494","displayToPublicDate":"2014-01-22T13:09:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"title":"Uncertainty, robustness, and the value of information in managing an expanding Arctic goose population","docAbstract":"We explored the application of dynamic-optimization methods to the problem of pink-footed goose (Anser brachyrhynchus) management in western Europe. We were especially concerned with the extent to which uncertainty in population dynamics influenced an optimal management strategy, the gain in management performance that could be expected if uncertainty could be eliminated or reduced, and whether an adaptive or robust management strategy might be most appropriate in the face of uncertainty. We combined three alternative survival models with three alternative reproductive models to form a set of nine annual-cycle models for pink-footed geese. These models represent a wide range of possibilities concerning the extent to which demographic rates are density dependent or independent, and the extent to which they are influenced by spring temperatures. We calculated state-dependent harvest strategies for these models using stochastic dynamic programming and an objective function that maximized sustainable harvest, subject to a constraint on desired population size. As expected, attaining the largest mean objective value (i.e., the relative measure of management performance) depended on the ability to match a model-dependent optimal strategy with its generating model of population dynamics. The nine models suggested widely varying objective values regardless of the harvest strategy, with the density-independent models generally producing higher objective values than models with density-dependent survival. In the face of uncertainty as to which of the nine models is most appropriate, the optimal strategy assuming that both survival and reproduction were a function of goose abundance and spring temperatures maximized the expected minimum objective value (i.e., maxi–min). In contrast, the optimal strategy assuming equal model weights minimized the expected maximum loss in objective value. The expected value of eliminating model uncertainty was an increase in objective value of only 3.0%. This value represents the difference between the best that could be expected if the most appropriate model were known and the best that could be expected in the face of model uncertainty. The value of eliminating uncertainty about the survival process was substantially higher than that associated with the reproductive process, which is consistent with evidence that variation in survival is more important than variation in reproduction in relatively long-lived avian species. Comparing the expected objective value if the most appropriate model were known with that of the maxi–min robust strategy, we found the value of eliminating uncertainty to be an expected increase of 6.2% in objective value. This result underscores the conservatism of the maxi–min rule and suggests that risk-neutral managers would prefer the optimal strategy that maximizes expected value, which is also the strategy that is expected to minimize the maximum loss (i.e., a strategy based on equal model weights). The low value of information calculated for pink-footed geese suggests that a robust strategy (i.e., one in which no learning is anticipated) could be as nearly effective as an adaptive one (i.e., a strategy in which the relative credibility of models is assessed through time). Of course, an alternative explanation for the low value of information is that the set of population models we considered was too narrow to represent key uncertainties in population dynamics. Yet we know that questions about the presence of density dependence must be central to the development of a sustainable harvest strategy. And while there are potentially many environmental covariates that could help explain variation in survival or reproduction, our admission of models in which vital rates are drawn randomly from reasonable distributions represents a worst-case scenario for management. We suspect that much of the value of the various harvest strategies we calculated is derived from the fact that they are state dependent, such that appropriate harvest rates depend on population abundance and weather conditions, as well as our focus on an infinite time horizon for sustainability.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ecological Modelling","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolmodel.2013.10.031","usgsCitation":"Johnson, F.A., Jensen, G., Madsen, J., and Williams, B.K., 2014, Uncertainty, robustness, and the value of information in managing an expanding Arctic goose population: Ecological Modelling, v. 273, p. 186-199, https://doi.org/10.1016/j.ecolmodel.2013.10.031.","productDescription":"14 p.","startPage":"186","endPage":"199","numberOfPages":"14","ipdsId":"IP-044497","costCenters":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"links":[{"id":473210,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolmodel.2013.10.031","text":"Publisher Index Page"},{"id":281382,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":281381,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.ecolmodel.2013.10.031"}],"volume":"273","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52e0e93ee4b0d0c3df9947bf","chorus":{"doi":"10.1016/j.ecolmodel.2013.10.031","url":"http://dx.doi.org/10.1016/j.ecolmodel.2013.10.031","publisher":"Elsevier BV","authors":"Johnson Fred A., Jensen Gitte H., Madsen Jesper, Williams Byron K.","journalName":"Ecological Modelling","publicationDate":"2/2014","auditedOn":"3/22/2016","publiclyAccessibleDate":"11/4/2013"},"contributors":{"authors":[{"text":"Johnson, Fred A. 0000-0002-5854-3695 fjohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-5854-3695","contributorId":2773,"corporation":false,"usgs":true,"family":"Johnson","given":"Fred","email":"fjohnson@usgs.gov","middleInitial":"A.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":488811,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jensen, Gitte H.","contributorId":74671,"corporation":false,"usgs":true,"family":"Jensen","given":"Gitte H.","affiliations":[],"preferred":false,"id":488813,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Madsen, Jesper","contributorId":9950,"corporation":false,"usgs":true,"family":"Madsen","given":"Jesper","affiliations":[],"preferred":false,"id":488812,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Williams, Byron K. 0000-0001-7644-1396","orcid":"https://orcid.org/0000-0001-7644-1396","contributorId":86616,"corporation":false,"usgs":true,"family":"Williams","given":"Byron","email":"","middleInitial":"K.","affiliations":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"preferred":false,"id":488814,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70072831,"text":"70072831 - 2014 - Thermal behavior and ice-table depth within the north polar erg of Mars","interactions":[],"lastModifiedDate":"2018-11-14T10:42:25","indexId":"70072831","displayToPublicDate":"2014-01-22T13:04:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1963,"text":"Icarus","active":true,"publicationSubtype":{"id":10}},"title":"Thermal behavior and ice-table depth within the north polar erg of Mars","docAbstract":"We fully resolve a long-standing thermal discrepancy concerning the north polar erg of Mars. Several recent studies have shown that the erg’s thermal properties are consistent with normal basaltic sand overlying shallow ground ice or ice-cemented sand. Our findings bolster that conclusion by thoroughly characterizing the thermal behavior of the erg, demonstrating that other likely forms of physical heterogeneity play only a minor role, and obviating the need to invoke exotic materials. Thermal inertia as calculated from orbital temperature observations of the dunes has previously been found to be more consistent with dust-sized materials than with sand. Since theory and laboratory data show that dunes will only form out of sand-sized particles, exotic sand-sized agglomerations of dust have been invoked to explain the low values of thermal inertia. However, the polar dunes exhibit the same darker appearance and color as that of dunes found elsewhere on the planet that have thermal inertia consistent with normal sand-sized basaltic grains, whereas Martian dust deposits are generally lighter and redder. The alternative explanation for the discrepancy as a thermal effect of a shallow ice table is supported by our analysis of observations from the Mars Global Surveyor Thermal Emission Spectrometer and the Mars Odyssey Thermal Emission Imaging System and by forward modeling of physical heterogeneity. In addition, our results exclude a uniform composition of dark dust-sized materials, and they show that the thermal effects of the dune slopes and bright interdune materials evident in high-resolution images cannot account for the erg’s thermal behavior.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Icarus","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.icarus.2013.07.010","usgsCitation":"Putzig, N.E., Mellon, M.T., Herkenhoff, K.E., Phillips, R.J., Davis, B.J., Ewer, K.J., and Bowers, L.M., 2014, Thermal behavior and ice-table depth within the north polar erg of Mars: Icarus, v. 230, p. 64-76, https://doi.org/10.1016/j.icarus.2013.07.010.","productDescription":"13 p.","startPage":"64","endPage":"76","numberOfPages":"13","ipdsId":"IP-043367","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":281377,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.icarus.2013.07.010"},{"id":281380,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Mars","volume":"230","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd78d1e4b0b2908510c6a3","contributors":{"authors":[{"text":"Putzig, Nathaniel E.","contributorId":100991,"corporation":false,"usgs":true,"family":"Putzig","given":"Nathaniel","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":488573,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mellon, Michael T.","contributorId":8603,"corporation":false,"usgs":false,"family":"Mellon","given":"Michael","email":"","middleInitial":"T.","affiliations":[{"id":7037,"text":"Southwest Research Institute, Boulder, Colorado","active":true,"usgs":false}],"preferred":false,"id":488568,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Herkenhoff, Kenneth E. 0000-0002-3153-6663 kherkenhoff@usgs.gov","orcid":"https://orcid.org/0000-0002-3153-6663","contributorId":2275,"corporation":false,"usgs":true,"family":"Herkenhoff","given":"Kenneth","email":"kherkenhoff@usgs.gov","middleInitial":"E.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":488567,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Phillips, Roger J.","contributorId":74495,"corporation":false,"usgs":false,"family":"Phillips","given":"Roger","email":"","middleInitial":"J.","affiliations":[{"id":24730,"text":"Department of Earth and Planetary Sciences, Washington University in St. Louis","active":true,"usgs":false}],"preferred":false,"id":488572,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Davis, Brian J.","contributorId":54333,"corporation":false,"usgs":true,"family":"Davis","given":"Brian","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":488571,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ewer, Kenneth J.","contributorId":44457,"corporation":false,"usgs":true,"family":"Ewer","given":"Kenneth","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":488570,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bowers, Lauren M.","contributorId":25457,"corporation":false,"usgs":true,"family":"Bowers","given":"Lauren","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":488569,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70217581,"text":"70217581 - 2014 - Late Devonian–Mississippian(?) Zn-Pb(-Ag-Au-Ba-F) deposits and related aluminous alteration zones in the Nome Complex, Seward Peninsula, Alaska","interactions":[],"lastModifiedDate":"2021-01-22T13:40:11.697389","indexId":"70217581","displayToPublicDate":"2014-01-22T07:34:24","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1727,"text":"GSA Special Papers","active":true,"publicationSubtype":{"id":10}},"title":"Late Devonian–Mississippian(?) Zn-Pb(-Ag-Au-Ba-F) deposits and related aluminous alteration zones in the Nome Complex, Seward Peninsula, Alaska","docAbstract":"<p>Stratabound base-metal sulfide deposits and occurrences are present in metasedimentary rocks of the Neoproterozoic and Paleozoic Nome Complex on south-central Seward Peninsula, Alaska. Stratabound and locally stratiform deposits including Aurora Creek (Zn-Au-Ba-F), Wheeler North (Pb-Zn-Ag-Au-F), and Nelson (Zn-Pb- Cu-Ag), consist of lenses typically 0.5–2.0 m thick containing disseminated to semimassive sulfides. Host strata of the Aurora Creek and Wheeler North deposits are variably calcareous and graphitic siliciclastic metasedimentary rocks of Middle Devonian or younger age based on detrital zircon geochronology; the Nelson deposit is within Ordovician–Devonian marble (Till et al., this volume, Chapter 4). Deformed veins such as Quarry (Zn-Pb-Ag-Ba-F) and Galena (Pb-Zn-Ag-F) occur in a unit composed mainly of marble and schist; fossil and detrital zircon data indicate that this unit contains rocks of Ordovician, Silurian, and Devonian age. None of these Zn- and Pbrich deposits or occurrences has spatially associated metavolcanic or intrusive rocks. All were deformed and metamorphosed to blueschist facies and then retrograded to greenschist facies during the Jurassic and Early Cretaceous Brookian orogeny. Disseminated Cu-rich deposits including Copper King (Cu-Bi-Sb-Pb-Ag-Au) and Wheeler South (Cu-Ag-Au) occur in silicified carbonate rocks and have textures that indicate a pre- to syn-metamorphic origin.</p><p>The Zn- and Pb-rich sulfide deposits and occurrences consist mainly of pyrite, sphalerite, and/or galena in a gangue of quartz and carbonate. Minor minerals include arsenopyrite, chalcopyrite, magnetite, pyrrhotite, tetrahedrite, barite, fluorite, and chlorite; gold and electrum are trace to minor constituents locally. Sphalerite is uniformly unzoned and commonly aligned in the dominant foliation. These textures, together with the presence of folded layers of barite at Aurora Creek and folded sulfi de layers at Wheeler North, indicate that mineralization in the stratabound deposits predated deformation and metamorphism. Electron microprobe (EMP) analyses of the carbonate gangue show three major compositions comprising siderite, ankerite, and lesser dolomite. The Cu-rich deposits differ in containing chalcopyrite and bornite in a quartzose matrix.</p><p>Altered wall rocks surrounding the Zn- and Pb-rich deposits and occurrences have aluminous assemblages composed of muscovite + chloritoid + siderite + chlorite + quartz ± tourmaline ± ilmenite ± apatite ± monazite. Muscovite within these assemblages and in sulfide-rich samples is phengitic and locally enriched in barium; chloritoid at Aurora Creek is enriched in zinc. Minor minerals including pyrite, sphalerite, galena, chalcopyrite, barite, and hyalophane occur as fine-grained disseminations. These altered rocks vary from small lenses a few meters thick to large zones tens of meters in thickness that extend along strike, discontinuously, for 4 km or more. Whole-rock geochemical analyses of the altered rocks from deposit-proximal and deposit-distal settings reveal generally lower SiO<sub>2</sub>/Al<sub>2</sub>O<sub>3</sub><span>&nbsp;</span>ratios and higher Fe<sub>2</sub>O<sub>3</sub><span>&nbsp;</span><sup>T</sup>/MgO ratios compared to those of unaltered clastic metasedimentary rocks of the Nome Complex and of average shale or graywacke. The deposit-proximal samples are also characterized by anomalously high Zn, Pb, Hg, and Sb, relative to the unaltered metasediments. These data, together with mass change calculations, suggest that the aluminous rocks formed as replacements of permeable graywacke in semi-conformable alteration zones, beneath the seafloor contemporaneously with Zn-and/or Pb-rich sulfide mineralization.</p><p>Exposures of all three stratabound Zn-Pb deposits show evidence of deformation and recrystallization that occurred in a largely brittle deformational regime. This evidence includes small faults and veins that cut foliation and localized zones of breccia. Sulfide minerals, fluorite, quartz, chlorite, and carbonate minerals crystallized within these structures, which probably formed during Cretaceous deformation of the Nome Complex.</p><p>Previous studies of the Zn-Pb(-Ag-Au-Ba-F) deposits and occurrences have invoked models of epigenetic veins, volcanogenic massive sulfides (VMS), or carbonate- replacement deposits (CRD). In contrast, our field and laboratory data (including sulfur isotopes; Shanks et al., this volume) suggest that these Zn- and/or Pb-rich deposits represent different levels of sediment-hosted, seafloor-hydrothermal systems, with stratabound and locally stratiform deposits such as Aurora Creek and Wheeler North having formed on the seafloor and/or in the shallow subsurface like many sedimentary-exhalative (SEDEX) deposits worldwide. The deformed veins such as Quarry and Galena are interpreted to have formed deep in the subsurface, possibly as feeders to overlying SEDEX deposits such as Aurora Creek. Formation of all of the Zn- and Pb-rich deposits and occurrences took place during episodic rifting of the continental margin between the Ordovician and Mississippian(?). Regional relationships are consistent with at least some of the deposits having formed in Late Devonian–Mississippian(?) time.</p>","language":"English","publisher":"Geological Society of America","doi":"10.1130/2014.2506(06)","usgsCitation":"Slack, J.F., Till, A., Belkin, H.E., and Shanks, W., 2014, Late Devonian–Mississippian(?) Zn-Pb(-Ag-Au-Ba-F) deposits and related aluminous alteration zones in the Nome Complex, Seward Peninsula, Alaska: GSA Special Papers, v. 506, p. 173-212, https://doi.org/10.1130/2014.2506(06).","productDescription":"40 p.","startPage":"173","endPage":"212","ipdsId":"IP-036872","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":382489,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Nome Complex","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n      \"type\": \"Feature\",\n      \"properties\": {},\n      \"geometry\": {\n        \"type\": \"Polygon\",\n        \"coordinates\": [\n          [\n            [\n              -168.1787109375,\n              64.35893097894457\n            ],\n            [\n              -160.576171875,\n              64.35893097894457\n            ],\n            [\n              -160.576171875,\n              66.60067571342496\n            ],\n            [\n              -168.1787109375,\n              66.60067571342496\n            ],\n            [\n              -168.1787109375,\n              64.35893097894457\n            ]\n          ]\n        ]\n      }\n    }\n  ]\n}","volume":"506","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Slack, John F. 0000-0001-6600-3130 jfslack@usgs.gov","orcid":"https://orcid.org/0000-0001-6600-3130","contributorId":1032,"corporation":false,"usgs":true,"family":"Slack","given":"John","email":"jfslack@usgs.gov","middleInitial":"F.","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":808734,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Till, Alison 0000-0002-6640-6877","orcid":"https://orcid.org/0000-0002-6640-6877","contributorId":247882,"corporation":false,"usgs":false,"family":"Till","given":"Alison","affiliations":[{"id":12545,"text":"USGS retired","active":true,"usgs":false}],"preferred":false,"id":808735,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Belkin, Harvey E. 0000-0001-7879-6529","orcid":"https://orcid.org/0000-0001-7879-6529","contributorId":190267,"corporation":false,"usgs":false,"family":"Belkin","given":"Harvey","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":808736,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Shanks, Wayne C.","contributorId":248280,"corporation":false,"usgs":false,"family":"Shanks","given":"Wayne C.","affiliations":[{"id":12545,"text":"USGS retired","active":true,"usgs":false}],"preferred":false,"id":808737,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70068449,"text":"ofr20141005 - 2014 - Bathymetric surveys and area/capacity tables of water-supply reservoirs for the city of Cameron, Missouri, July 2013","interactions":[],"lastModifiedDate":"2014-01-21T14:31:49","indexId":"ofr20141005","displayToPublicDate":"2014-01-21T14:16:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-1005","title":"Bathymetric surveys and area/capacity tables of water-supply reservoirs for the city of Cameron, Missouri, July 2013","docAbstract":"Years of sediment accumulation and dry conditions in recent years have led to the decline of water levels and capacities for many water-supply reservoirs in Missouri, and have caused renewed interest in modernizing outdated area/capacity tables for these reservoirs. The U.S. Geological Survey, in cooperation with the Missouri Department of Natural Resources, surveyed the bathymetry of the four water-supply reservoirs used by the city of Cameron, Missouri, in July 2013. The data were used to provide water managers with area/capacity tables and bathymetric maps of the reservoirs at the time of the surveys.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141005","collaboration":"Prepared in cooperation with the Missouri Department of Natural Resources","usgsCitation":"Huizinga, R.J., 2014, Bathymetric surveys and area/capacity tables of water-supply reservoirs for the city of Cameron, Missouri, July 2013: U.S. Geological Survey Open-File Report 2014-1005, iv, 15 p., https://doi.org/10.3133/ofr20141005.","productDescription":"iv, 15 p.","numberOfPages":"19","onlineOnly":"Y","ipdsId":"IP-052176","costCenters":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true}],"links":[{"id":281331,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1005/"},{"id":281335,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141005.jpg"},{"id":281334,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1005/pdf/of2014-1005.pdf"}],"scale":"100000","projection":"Universal Transverse Mercator projection","datum":"North American Datum of 1983","country":"United States","state":"Missouri","city":"Cameron","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -94.319842,39.724343 ], [ -94.319842,39.785227 ], [ -94.209326,39.785227 ], [ -94.209326,39.724343 ], [ -94.319842,39.724343 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd4ef1e4b0b290850f2660","contributors":{"authors":[{"text":"Huizinga, Richard J. 0000-0002-2940-2324 huizinga@usgs.gov","orcid":"https://orcid.org/0000-0002-2940-2324","contributorId":2089,"corporation":false,"usgs":true,"family":"Huizinga","given":"Richard","email":"huizinga@usgs.gov","middleInitial":"J.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":488011,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70073345,"text":"70073345 - 2014 - Evaluating the efficiency of environmental monitoring programs","interactions":[],"lastModifiedDate":"2014-01-28T08:37:06","indexId":"70073345","displayToPublicDate":"2014-01-21T10:51:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating the efficiency of environmental monitoring programs","docAbstract":"Statistical uncertainty analyses can be used to improve the efficiency of environmental monitoring, allowing sampling designs to maximize information gained relative to resources required for data collection and analysis. In this paper, we illustrate four methods of data analysis appropriate to four types of environmental monitoring designs. To analyze a long-term record from a single site, we applied a general linear model to weekly stream chemistry data at Biscuit Brook, NY, to simulate the effects of reducing sampling effort and to evaluate statistical confidence in the detection of change over time. To illustrate a detectable difference analysis, we analyzed a one-time survey of mercury concentrations in loon tissues in lakes in the Adirondack Park, NY, demonstrating the effects of sampling intensity on statistical power and the selection of a resampling interval. To illustrate a bootstrapping method, we analyzed the plot-level sampling intensity of forest inventory at the Hubbard Brook Experimental Forest, NH, to quantify the sampling regime needed to achieve a desired confidence interval. Finally, to analyze time-series data from multiple sites, we assessed the number of lakes and the number of samples per year needed to monitor change over time in Adirondack lake chemistry using a repeated-measures mixed-effects model. Evaluations of time series and synoptic long-term monitoring data can help determine whether sampling should be re-allocated in space or time to optimize the use of financial and human resources.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ecological Indicators","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2013.12.010","usgsCitation":"Levine, C.R., Yanai, R.D., Lampman, G.G., Burns, D.A., Driscoll, C.T., Lawrence, G.B., Lynch, J., and Schoch, N., 2014, Evaluating the efficiency of environmental monitoring programs: Ecological Indicators, v. 39, p. 94-101, https://doi.org/10.1016/j.ecolind.2013.12.010.","productDescription":"8 p.","startPage":"94","endPage":"101","numberOfPages":"8","ipdsId":"IP-050636","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":473212,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolind.2013.12.010","text":"Publisher Index Page"},{"id":281315,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.ecolind.2013.12.010"},{"id":281316,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"39","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52df97f8e4b0d7b3a14e1aa2","contributors":{"authors":[{"text":"Levine, Carrie R.","contributorId":106009,"corporation":false,"usgs":true,"family":"Levine","given":"Carrie","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":488618,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yanai, Ruth D.","contributorId":59720,"corporation":false,"usgs":true,"family":"Yanai","given":"Ruth","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":488615,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lampman, Gregory G.","contributorId":26970,"corporation":false,"usgs":true,"family":"Lampman","given":"Gregory","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":488613,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Burns, Douglas A. 0000-0001-6516-2869 daburns@usgs.gov","orcid":"https://orcid.org/0000-0001-6516-2869","contributorId":1237,"corporation":false,"usgs":true,"family":"Burns","given":"Douglas","email":"daburns@usgs.gov","middleInitial":"A.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":488612,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Driscoll, Charles T.","contributorId":35418,"corporation":false,"usgs":true,"family":"Driscoll","given":"Charles","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":488614,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lawrence, Gregory B. 0000-0002-8035-2350 glawrenc@usgs.gov","orcid":"https://orcid.org/0000-0002-8035-2350","contributorId":867,"corporation":false,"usgs":true,"family":"Lawrence","given":"Gregory","email":"glawrenc@usgs.gov","middleInitial":"B.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":488611,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lynch, Jason","contributorId":97001,"corporation":false,"usgs":true,"family":"Lynch","given":"Jason","affiliations":[],"preferred":false,"id":488616,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Schoch, Nina","contributorId":101988,"corporation":false,"usgs":true,"family":"Schoch","given":"Nina","email":"","affiliations":[],"preferred":false,"id":488617,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}}
,{"id":70072613,"text":"70072613 - 2014 - Complexity versus certainty in understanding species’ declines","interactions":[],"lastModifiedDate":"2017-06-10T11:37:06","indexId":"70072613","displayToPublicDate":"2014-01-21T09:46:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1399,"text":"Diversity and Distributions","active":true,"publicationSubtype":{"id":10}},"title":"Complexity versus certainty in understanding species’ declines","docAbstract":"Aim\nOur understanding of and ability to predict species declines is limited, despite decades of study. We sought to expand our understanding of species declines within a regional landscape by testing models using both traditional hypotheses and those derived from a complex adaptive systems approach.\n\nLocation\nOur study area was the dry mixed grassland of south-eastern Alberta, Canada, one of the largest remnants of native grassland in North America, and the adjacent grassland in Saskatchewan.\n\nMethods\nWe used the breeding birds of the grassland to test the relationship between species declines and a suite of traits associated with decline (such as size, specialization and rarity, as well as distance to edge of a discontinuity, and edge of geographic range) in a stepwise regression with AICc values and bootstrapping via model averaging, followed by a refit procedure to obtain model-averaged parameter estimates. We used both provincial government and Breeding Bird Survey (BBS) classifications of decline. We also modelled degree of decline in the Alberta and Saskatchewan grasslands, which differ in amount of habitat remaining, to test whether severity of decline was explained by the same traits as species decline/not- decline.\n\nResults\nWe found that the model for government-defined decline fulfilled government expectations that species' extinction risk is a function of being large, specialized, rare and carnivorous, whereas the model for BBS-defined decline suggested that the biological reality of decline is more complex, requiring the need to explicitly model scale-specific patterns. Furthermore, species decline/not- decline was explained by different traits than those that fit degree of decline, though complex systems- derived traits featured in both sets of models.\n\nMain conclusions\nTraditional approaches to predict species declines (e.g. government processes or IUCN Red Lists), may be too simplistic and may therefore misguide management and conservation. Using complex systems approaches that account for scale-specific patterns and processes have the potential to overcome these limitations.","language":"English","publisher":"Wiley","doi":"10.1111/ddi.12166","usgsCitation":"Sundstrom, S.M., and Allen, C.R., 2014, Complexity versus certainty in understanding species’ declines: Diversity and Distributions, v. 3, p. 344-355, https://doi.org/10.1111/ddi.12166.","productDescription":"12 p.","startPage":"344","endPage":"355","ipdsId":"IP-052551","costCenters":[],"links":[{"id":281307,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":281306,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/ddi.12166"}],"volume":"3","edition":"20","noUsgsAuthors":false,"publicationDate":"2014-01-03","publicationStatus":"PW","scienceBaseUri":"52df97f6e4b0d7b3a14e1a9b","contributors":{"authors":[{"text":"Sundstrom, Shana M.","contributorId":7159,"corporation":false,"usgs":true,"family":"Sundstrom","given":"Shana","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":488527,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Allen, Craig R. 0000-0001-8655-8272 allencr@usgs.gov","orcid":"https://orcid.org/0000-0001-8655-8272","contributorId":1979,"corporation":false,"usgs":true,"family":"Allen","given":"Craig","email":"allencr@usgs.gov","middleInitial":"R.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":488526,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70157143,"text":"70157143 - 2014 - Evaluating CO2 and CH4 dynamics of Alaskan ecosystems during the Holocene Thermal Maximum","interactions":[],"lastModifiedDate":"2022-11-08T11:57:24.879652","indexId":"70157143","displayToPublicDate":"2014-01-21T00:00:00","publicationYear":"2014","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}},"displayTitle":"Evaluating CO<sub>2</sub> and CH<sub>4</sub> dynamics of Alaskan ecosystems during the Holocene Thermal Maximum","title":"Evaluating CO2 and CH4 dynamics of Alaskan ecosystems during the Holocene Thermal Maximum","docAbstract":"<p><span>The Arctic has experienced much greater warming than the global average in recent decades due to polar amplification. Warming has induced ecological changes that have impacted climate carbon-cycle feedbacks, making it important to understand the climate and vegetation controls on carbon (C) dynamics. Here we used the Holocene Thermal Maximum (HTM, 11&ndash;9&nbsp;ka&nbsp;BP, 1&nbsp;ka&nbsp;BP&nbsp;=&nbsp;1000&nbsp;cal&nbsp;yr before present) in Alaska as a case study to examine how ecosystem Cdynamics responded to the past warming climate using an integrated approach of combining paleoecological reconstructions and ecosystem modeling. Our paleoecological synthesis showed expansion of deciduous broadleaf forest (dominated by&nbsp;</span><i>Populus</i><span>) into tundra and the establishment of boreal evergreen needleleaf and mixed forest during the second half of the HTM under a warmer- and wetter-than-before climate, coincident with the occurrence of the highest net primary productivity, cumulative net ecosystem productivity, soil C accumulation and CH</span><sub>4</sub><span>&nbsp;emissions. These series of ecological and biogeochemical shifts mirrored the solar insolation and subsequent temperature and precipitation patterns during HTM, indicating the importance of climate controls on C dynamics. Our simulated regional estimate of CH</span><sub>4</sub><span>&nbsp;emission rates from Alaska during the HTM ranged from 3.5 to 6.4&nbsp;Tg&nbsp;CH</span><sub>4</sub><span>&nbsp;yr</span><sup>&minus;1</sup><span>&nbsp;and highest annual NPP of 470&nbsp;Tg&nbsp;C&nbsp;yr</span><sup>&minus;1</sup><span>, significantly higher than previously reported modern estimates. Our results show that the differences in static vegetation distribution maps used in simulations of different time slices have greater influence on modeled C dynamics than climatic fields within each time slice, highlighting the importance of incorporating vegetation community dynamics and their responses to climatic conditions in long-term biogeochemical modeling.</span></p>","language":"English","publisher":"Elsevier","doi":"10.1016/j.quascirev.2013.12.019","usgsCitation":"He, Y., Jones, M.C., Zhuang, Q., Bochicchio, C., Felzer, B.S., Mason, E., and Yu, Z., 2014, Evaluating CO2 and CH4 dynamics of Alaskan ecosystems during the Holocene Thermal Maximum: Quaternary Science Reviews, v. 86, p. 63-77, https://doi.org/10.1016/j.quascirev.2013.12.019.","productDescription":"15 p.","startPage":"63","endPage":"77","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-053302","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science 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S.","contributorId":147519,"corporation":false,"usgs":false,"family":"Felzer","given":"B.","email":"","middleInitial":"S.","affiliations":[{"id":16857,"text":"Lehigh Univ.","active":true,"usgs":false}],"preferred":false,"id":571850,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mason, Erik","contributorId":147520,"corporation":false,"usgs":false,"family":"Mason","given":"Erik","email":"","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":571851,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Yu, Zicheng 0000-0003-2358-2712","orcid":"https://orcid.org/0000-0003-2358-2712","contributorId":147521,"corporation":false,"usgs":false,"family":"Yu","given":"Zicheng","email":"","affiliations":[{"id":16857,"text":"Lehigh Univ.","active":true,"usgs":false}],"preferred":false,"id":571852,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}}
,{"id":70179213,"text":"70179213 - 2014 - Lithologic influences on groundwater recharge through incised glacial till from profile to regional scales: Evidence from glaciated Eastern Nebraska","interactions":[],"lastModifiedDate":"2016-12-22T09:21:02","indexId":"70179213","displayToPublicDate":"2014-01-21T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Lithologic influences on groundwater recharge through incised glacial till from profile to regional scales: Evidence from glaciated Eastern Nebraska","docAbstract":"Variability in sediment hydraulic properties associated with landscape depositional and erosional features can influence groundwater recharge processes by affecting soil-water storage and transmission. This study considers recharge to aquifers underlying river-incised glaciated terrain where the distribution of clay-rich till is largely intact in upland locations but has been removed by alluvial erosion in stream valleys. In a stream-dissected glacial region in eastern Nebraska (Great Plains region of the United States), recharge estimates were developed for nested profile, aquifer, and regional scales using unsaturated zone profile measurements (matric potentials, Cl- and 3H), groundwater tracers (CFC-12 and SF6), and a remote sensing-assisted water balance model. Results show a consistent influence of till lithology on recharge rates across nested spatial scales despite substantial uncertainty in all recharge estimation methods, suggesting that minimal diffuse recharge occurs through upland glacial till lithology whereas diffuse recharge occurs in river valleys where till is locally absent. Diffuse recharge is estimated to account for a maximum of 61% of total recharge based on comparison of diffuse recharge estimated from the unsaturated zone (0-43 mm yr-1) and total recharge estimated from groundwater tracers (median 58 mm yr-1) and water balance modeling (median 56 mm yr-1). The results underscore the importance of lithologic controls on the distributions of both recharge rates and mechanisms.","language":"English","publisher":"American Geophysical Union","publisherLocation":"Washington, D.C.","doi":"10.1002/2013WR014073","usgsCitation":"Gates, J.B., Steele, G.V., Nasta, P., and Szilagyi, J., 2014, Lithologic influences on groundwater recharge through incised glacial till from profile to regional scales: Evidence from glaciated Eastern Nebraska: Water Resources Research, v. 50, no. 1, p. 466-481, https://doi.org/10.1002/2013WR014073.","productDescription":"16 p.","startPage":"466","endPage":"481","ipdsId":"IP-045391","costCenters":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"links":[{"id":332457,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nebraska","geographicExtents":"{\n  \"type\": \"FeatureCollection\",\n  \"features\": [\n    {\n    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Gregory V. gvsteele@usgs.gov","contributorId":783,"corporation":false,"usgs":true,"family":"Steele","given":"Gregory","email":"gvsteele@usgs.gov","middleInitial":"V.","affiliations":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"preferred":true,"id":656408,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nasta, Paolo","contributorId":177626,"corporation":false,"usgs":false,"family":"Nasta","given":"Paolo","email":"","affiliations":[],"preferred":false,"id":656410,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Szilagyi, Jozsef","contributorId":177627,"corporation":false,"usgs":false,"family":"Szilagyi","given":"Jozsef","email":"","affiliations":[],"preferred":false,"id":656434,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70074654,"text":"70074654 - 2014 - Seismicity within a propagating ice shelf rift: the relationship between icequake locations and ice shelf structure","interactions":[],"lastModifiedDate":"2018-07-07T18:00:36","indexId":"70074654","displayToPublicDate":"2014-01-20T10:12:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2318,"text":"Journal of Geophysical Research F: Earth Surface","active":true,"publicationSubtype":{"id":10}},"title":"Seismicity within a propagating ice shelf rift: the relationship between icequake locations and ice shelf structure","docAbstract":"Iceberg calving is a dominant mass loss mechanism for Antarctic ice shelves, second only to basal melting. An important known process involved in calving is the initiation and propagation of through-penetrating fractures called rifts; however, the mechanisms controlling rift propagation remain poorly understood. To investigate the mechanics of ice-shelf rifting, we analyzed seismicity associated with a propagating rift tip on the Amery Ice Shelf, using data collected during the Austral summers of 2004-2007. We investigated seismicity associated with fracture propagation using a suite of passive seismological techniques including icequake locations, back projection, and moment tensor inversion. We confirm previous results that show that seismicity is characterized by periods of relative quiescence punctuated by swarms of intense seismicity of one to three hours. However, even during periods of quiescence, we find significant seismic deformation around the rift tip. Moment tensors, calculated for a subset of the largest icequakes (M<sub>W</sub> > -2.0) located near the rift tip, show steeply dipping fault planes, horizontal or shallowly plunging stress orientations, and often have a significant volumetric component. They also reveal that much of the observed seismicity is limited to the upper 50 m of the ice shelf. This suggests a complex system of deformation that involves the propagating rift, the region behind the rift tip, and a system of rift-transverse crevasses. Small-scale variations in the mechanical structure of the ice shelf, especially rift-transverse crevasses and accreted marine ice, play an important role in modulating the rate and location of seismicity associated with propagating ice shelf rifts.","language":"English","publisher":"Wiley","doi":"10.1002/2013JF002849","usgsCitation":"Heeszel, D.S., Fricker, H., Bassis, J.N., O’Neel, S., and Walter, F., 2014, Seismicity within a propagating ice shelf rift: the relationship between icequake locations and ice shelf structure: Journal of Geophysical Research F: Earth Surface, v. 119, no. 4, p. 731-744, https://doi.org/10.1002/2013JF002849.","productDescription":"14 p.","startPage":"731","endPage":"744","numberOfPages":"14","ipdsId":"IP-045706","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":473213,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2013jf002849","text":"Publisher Index Page"},{"id":281801,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":281800,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/2013JF002849"}],"otherGeospatial":"Amery Ice Shelf, Antarctica","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 66.4,-72.04 ], [ 66.4,-68.02 ], [ 76.46,-68.02 ], [ 76.46,-72.04 ], [ 66.4,-72.04 ] ] ] } } ] }","volume":"119","issue":"4","noUsgsAuthors":false,"publicationDate":"2014-04-02","publicationStatus":"PW","scienceBaseUri":"5351705fe4b05569d805a398","contributors":{"authors":[{"text":"Heeszel, David S.","contributorId":14729,"corporation":false,"usgs":true,"family":"Heeszel","given":"David","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":489693,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fricker, Helen A.","contributorId":57337,"corporation":false,"usgs":true,"family":"Fricker","given":"Helen A.","affiliations":[],"preferred":false,"id":489696,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bassis, Jeremy N.","contributorId":49271,"corporation":false,"usgs":true,"family":"Bassis","given":"Jeremy","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":489695,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":107,"text":"Alaska Climate Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":true,"id":489697,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Walter, Fabian","contributorId":21431,"corporation":false,"usgs":true,"family":"Walter","given":"Fabian","email":"","affiliations":[],"preferred":false,"id":489694,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70156246,"text":"70156246 - 2014 - Inferences about population dynamics from count data using multi-state models: A comparison to capture-recapture approaches","interactions":[],"lastModifiedDate":"2022-11-10T16:40:39.588899","indexId":"70156246","displayToPublicDate":"2014-01-20T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Inferences about population dynamics from count data using multi-state models: A comparison to capture-recapture approaches","docAbstract":"<p><span>Wildlife populations consist of individuals that contribute disproportionately to growth and viability. Understanding a population's spatial and temporal dynamics requires estimates of abundance and demographic rates that account for this heterogeneity. Estimating these quantities can be difficult, requiring years of intensive data collection. Often, this is accomplished through the capture and recapture of individual animals, which is generally only feasible at a limited number of locations. In contrast, N-mixture models allow for the estimation of abundance, and spatial variation in abundance, from count data alone. We extend recently developed multistate, open population N-mixture models, which can additionally estimate demographic rates based on an organism's life history characteristics. In our extension, we develop an approach to account for the case where not all individuals can be assigned to a state during sampling. Using only state-specific count data, we show how our model can be used to estimate local population abundance, as well as density-dependent recruitment rates and state-specific survival. We apply our model to a population of black-throated blue warblers (</span><i>Setophaga caerulescens</i><span>) that have been surveyed for 25&nbsp;years on their breeding grounds at the Hubbard Brook Experimental Forest in New Hampshire, USA. The intensive data collection efforts allow us to compare our estimates to estimates derived from capture–recapture data. Our model performed well in estimating population abundance and density-dependent rates of annual recruitment/immigration. Estimates of local carrying capacity and per capita recruitment of yearlings were consistent with those published in other studies. However, our model moderately underestimated annual survival probability of yearling and adult females and severely underestimates survival probabilities for both of these male stages. The most accurate and precise estimates will necessarily require some amount of intensive data collection efforts (such as capture–recapture). Integrated population models that combine data from both intensive and extensive sources are likely to be the most efficient approach for estimating demographic rates at large spatial and temporal scales.</span></p>","language":"English","publisher":"Wiley","doi":"10.1002/ece3.942","usgsCitation":"Grant, E., Zipkin, E., Scott, S.T., Chandler, R., and Royle, J., 2014, Inferences about population dynamics from count data using multi-state models: A comparison to capture-recapture approaches: Ecology and Evolution, v. 4, no. 4, p. 417-426, https://doi.org/10.1002/ece3.942.","productDescription":"9 p.","startPage":"417","endPage":"426","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-062556","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true}],"links":[{"id":473214,"rank":0,"type":{"id":41,"text":"Open Access External Repository 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]\n}","volume":"4","issue":"4","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2014-01-20","publicationStatus":"PW","scienceBaseUri":"55d305b5e4b0518e35468d02","contributors":{"authors":[{"text":"Grant, Evan H. Campbell ehgrant@usgs.gov","contributorId":146545,"corporation":false,"usgs":true,"family":"Grant","given":"Evan H. Campbell","email":"ehgrant@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":568209,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zipkin, Elise ezipkin@usgs.gov","contributorId":470,"corporation":false,"usgs":true,"family":"Zipkin","given":"Elise","email":"ezipkin@usgs.gov","affiliations":[],"preferred":true,"id":568332,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Scott, Sillett T.","contributorId":30003,"corporation":false,"usgs":true,"family":"Scott","given":"Sillett","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":568333,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chandler, Richard rchandler@usgs.gov","contributorId":2511,"corporation":false,"usgs":true,"family":"Chandler","given":"Richard","email":"rchandler@usgs.gov","affiliations":[{"id":13266,"text":"Warnell School of Forestry and Natural Resources, The University of Georgia","active":true,"usgs":false}],"preferred":false,"id":568334,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Royle, J. Andrew aroyle@usgs.gov","contributorId":138860,"corporation":false,"usgs":true,"family":"Royle","given":"J. Andrew","email":"aroyle@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":568335,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70049011,"text":"ofr20131265 - 2014 - The United States Geological Survey Science Data Lifecycle Model","interactions":[],"lastModifiedDate":"2018-08-10T16:11:18","indexId":"ofr20131265","displayToPublicDate":"2014-01-17T11:49:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-1265","title":"The United States Geological Survey Science Data Lifecycle Model","docAbstract":"U.S. Geological Survey (USGS) data represent corporate assets with potential value beyond any immediate research use, and therefore need to be accounted for and properly managed throughout their lifecycle. Recognizing these motives, a USGS team developed a Science Data Lifecycle Model (SDLM) as a high-level view of data—from conception through preservation and sharing—to illustrate how data management activities relate to project workflows, and to assist with understanding the expectations of proper data management. In applying the Model to research activities, USGS scientists can ensure that data products will be well-described, preserved, accessible, and fit for re-use. The Model also serves as a structure to help the USGS evaluate and improve policies and practices for managing scientific data, and to identify areas in which new tools and standards are needed.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131265","issn":"2331-1258","usgsCitation":"Faundeen, J., Burley, T.E., Carlino, J., Govoni, D.L., Henkel, H., Holl, S.L., Hutchison, V., Martín, E., Montgomery, E., Ladino, C., Tessler, S., and Zolly, L., 2014, The United States Geological Survey Science Data Lifecycle Model: U.S. Geological Survey Open-File Report 2013-1265, iii, 4 p., https://doi.org/10.3133/ofr20131265.","productDescription":"iii, 4 p.","numberOfPages":"12","onlineOnly":"Y","ipdsId":"IP-045321","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":37226,"text":"Core Science Analytics, Synthesis, and 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Center","active":true,"usgs":true}],"preferred":true,"id":486004,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burley, Thomas E. 0000-0002-2235-8092 teburley@usgs.gov","orcid":"https://orcid.org/0000-0002-2235-8092","contributorId":3499,"corporation":false,"usgs":true,"family":"Burley","given":"Thomas","email":"teburley@usgs.gov","middleInitial":"E.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":486005,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Carlino, Jennifer A.","contributorId":72710,"corporation":false,"usgs":true,"family":"Carlino","given":"Jennifer A.","affiliations":[],"preferred":false,"id":486013,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Govoni, David L. dgovoni@usgs.gov","contributorId":5192,"corporation":false,"usgs":true,"family":"Govoni","given":"David","email":"dgovoni@usgs.gov","middleInitial":"L.","affiliations":[{"id":5071,"text":"Office of Administration","active":true,"usgs":true}],"preferred":true,"id":486010,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Henkel, Heather S. hhenkel@usgs.gov","contributorId":2869,"corporation":false,"usgs":true,"family":"Henkel","given":"Heather S.","email":"hhenkel@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":486003,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Holl, Sally L. sholl@usgs.gov","contributorId":4464,"corporation":false,"usgs":true,"family":"Holl","given":"Sally","email":"sholl@usgs.gov","middleInitial":"L.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":false,"id":486008,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hutchison, Vivian B. 0000-0001-5301-3698 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,{"id":70060093,"text":"ofr20141001 - 2014 - Emergency assessment of post-fire debris-flow hazards for the 2013 Springs Fire, Ventura County, California","interactions":[],"lastModifiedDate":"2014-01-15T16:26:17","indexId":"ofr20141001","displayToPublicDate":"2014-01-15T16:08:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-1001","title":"Emergency assessment of post-fire debris-flow hazards for the 2013 Springs Fire, Ventura County, California","docAbstract":"Wildfire can significantly alter the hydrologic response of a watershed to the extent that even modest rainstorms can produce dangerous flash floods and debris flows. In this report, empirical models are used to predict the probability and magnitude of debris-flow occurrence in response to a 10-year rainstorm for the 2013 Springs fire in Ventura County, California. Overall, the models predict a relatively high probability (60–80 percent) of debris flow for 9 of the 99 drainage basins in the burn area in response to a 10-year recurrence interval design storm. Predictions of debris-flow volume suggest that debris flows may entrain a significant volume of material, with 28 of the 99 basins identified as having potential debris-flow volumes greater than 10,000 cubic meters. These results of the relative combined hazard analysis suggest there is a moderate likelihood of significant debris-flow hazard within and downstream of the burn area for nearby populations, infrastructure, wildlife, and water resources. Given these findings, we recommend that residents, emergency managers, and public works departments pay close attention to weather forecasts and National Weather Service-issued Debris Flow and Flash Flood Outlooks, Watches, and Warnings, and that residents adhere to any evacuation orders.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141001","usgsCitation":"Staley, D.M., 2014, Emergency assessment of post-fire debris-flow hazards for the 2013 Springs Fire, Ventura County, California: U.S. Geological Survey Open-File Report 2014-1001, Report: iv, 10 p.; 3 Plates: 48 x 36 inches, https://doi.org/10.3133/ofr20141001.","productDescription":"Report: iv, 10 p.; 3 Plates: 48 x 36 inches","numberOfPages":"14","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-052864","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":281128,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141001.jpg"},{"id":281127,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1001/"},{"id":281129,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1001/pdf/of2014-1001.pdf"},{"id":281130,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2014/1001/pdf/Plate1_ProbabilityMap.pdf"},{"id":281131,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2014/1001/pdf/Plate2_VolumeMap.pdf"},{"id":281132,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2014/1001/pdf/Plate3_CombinedMap.pdf"}],"projection":"Universal Transverse Mercator","datum":"North American Datum of 1983","country":"United States","state":"California","county":"Ventura County","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -119.227066,33.997458 ], [ -119.227066,34.27651 ], [ -118.767014,34.27651 ], [ -118.767014,33.997458 ], [ -119.227066,33.997458 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52d7ade1e4b0f10664b99dc7","contributors":{"authors":[{"text":"Staley, Dennis M. 0000-0002-2239-3402 dstaley@usgs.gov","orcid":"https://orcid.org/0000-0002-2239-3402","contributorId":4134,"corporation":false,"usgs":true,"family":"Staley","given":"Dennis","email":"dstaley@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":487883,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70073397,"text":"70073397 - 2014 - Fluorescence-based classification of Caribbean coral reef organisms and substrates","interactions":[],"lastModifiedDate":"2014-01-20T09:34:00","indexId":"70073397","displayToPublicDate":"2014-01-15T09:30:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Fluorescence-based classification of Caribbean coral reef organisms and substrates","docAbstract":"A diverse group of coral reef organisms, representing several phyla, possess fluorescent pigments. We investigated the potential of using the characteristic fluorescence emission spectra of these pigments to enable unsupervised, optical classification of coral reef habitats. We compiled a library of characteristic fluorescence spectra through in situ and laboratory measurements from a variety of specimens throughout the Caribbean. Because fluorescent pigments are not species-specific, the spectral library is organized in terms of 15 functional groups. We investigated the spectral separability of the functional groups in terms of the number of wavebands required to distinguish between them, using the similarity measures Spectral Angle Mapper (SAM), Spectral Information Divergence (SID), SID-SAM mixed measure, and Mahalanobis distance. This set of measures represents geometric, stochastic, joint geometric-stochastic, and statistical approaches to classifying spectra. Our hyperspectral fluorescence data were used to generate sets of 4-, 6-, and 8-waveband spectra, including random variations in relative signal amplitude, spectral peak shifts, and water-column attenuation. Each set consisted of 2 different band definitions: ‘optimally-picked’ and ‘evenly-spaced.’ The optimally-picked wavebands were chosen to coincide with as many peaks as possible in the functional group spectra. Reference libraries were formed from half of the spectra in each set and used for training purposes. Average classification accuracies ranged from 76.3% for SAM with 4 evenly-spaced wavebands to 93.8% for Mahalanobis distance with 8 evenly-spaced wavebands. The Mahalanobis distance consistently outperformed the other measures. In a second test, empirically-measured spectra were classified using the same reference libraries and the Mahalanobis distance for just the 8 evenly-spaced waveband case. Average classification accuracies were 84% and 87%, corresponding to the extremes in modeled water-column attenuation. The classification results from both tests indicate that a high degree of separability among the 15 fluorescent-spectra functional groups is possible using only a modest number of spectral bands.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"PLoS ONE","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pone.0084570","usgsCitation":"Zawada, D., and Mazel, C.H., 2014, Fluorescence-based classification of Caribbean coral reef organisms and substrates: PLoS ONE, v. 9, no. 1, 13 p., https://doi.org/10.1371/journal.pone.0084570.","productDescription":"13 p.","numberOfPages":"13","onlineOnly":"Y","ipdsId":"IP-040535","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":473221,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0084570","text":"Publisher Index Page"},{"id":281274,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":281273,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1371/journal.pone.0084570"}],"volume":"9","issue":"1","noUsgsAuthors":false,"publicationDate":"2014-01-15","publicationStatus":"PW","scienceBaseUri":"53cd5a05e4b0b290850f9113","contributors":{"authors":[{"text":"Zawada, David G. 0000-0003-4547-4878 dzawada@usgs.gov","orcid":"https://orcid.org/0000-0003-4547-4878","contributorId":1898,"corporation":false,"usgs":true,"family":"Zawada","given":"David G.","email":"dzawada@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":488686,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mazel, Charles H.","contributorId":84266,"corporation":false,"usgs":true,"family":"Mazel","given":"Charles","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":488687,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70048953,"text":"sir20135125 - 2014 - Evaluation of toxicity to the amphipod, <i>Hyalella azteca</i>, and to the midge, <i>Chironomus dilutus</i>; and bioaccumulation by the oligochaete, <i>Lumbriculus variegatus</i>, with exposure to PCB-contaminated sediments from Anniston, Alabama","interactions":[],"lastModifiedDate":"2014-01-21T08:32:17","indexId":"sir20135125","displayToPublicDate":"2014-01-14T14:48:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-5125","title":"Evaluation of toxicity to the amphipod, <i>Hyalella azteca</i>, and to the midge, <i>Chironomus dilutus</i>; and bioaccumulation by the oligochaete, <i>Lumbriculus variegatus</i>, with exposure to PCB-contaminated sediments from Anniston, Alabama","docAbstract":"<p>The U.S. Environmental Protection Agency (USEPA) requested that as part of the remedial investigation for the Anniston, Alabama Polychlorinated Biphenyl (PCB) Site (Anniston PCB Site), that Pharmacia Corporation and Solutia Inc. (P/S) perform long-term reproduction toxicity tests with the amphipod, <i>Hyalella azteca</i>, and the midge, <i>Chironomus dilutus</i>, and bioaccumulation tests with the oligochaete, <i>Lumbriculus variegatus</i>, using sediment samples collected from reference locations and from Operable Unit 4 of the Anniston PCB Site. The sediment toxicity testing and sediment bioaccumulation results will be used by ARCADIS U.S., Inc. (ARCADIS) as part of a weight-of-evidence assessment to evaluate risks and establish sediment remediation goals for contaminants to sediment-dwelling organisms inhabiting the Anniston PCB Site.</p>\n<br/>\n<p>The goal of this study was to characterize relations between sediment chemistry and sediment toxicity and relations between sediment chemistry and sediment bioaccumulation in samples of sediments collected from the Anniston PCB Site. A total of 32 samples were evaluated from six test sites and one reference site to provide a wide range in concentrations of chemicals of potential concern (COPCs) including PCBs in samples of whole sediment. The goal of this study was not to determine the extent of sediment contamination across the Anniston PCB Site. Hence, the test sites or samples collected from within a test site were not selected to represent the spatial extent of sediment contamination across the Anniston PCB Site. Sediment chemistry, pore-water chemistry, and sediment toxicity data were generated for 26 sediment samples from the Anniston PCB Site. All of the samples were evaluated to determine if they qualified as reference sediment samples. Those samples that met the chemical selection criteria and biological selection criteria were identified as reference samples and used to develop the reference envelope for each toxicity test endpoint.</p>\n<br/>\n<p>Physical characterization of samples of whole sediment included analyses of grain size, TOC, and nutrients. Organic chemical characterization of samples of whole sediment included PCB homologs and select (13) PCB congeners, parent and alkylated polycyclic aromatic hydrocarbons (PAHs), organochlorine pesticides, and polychlorinated dibenzo-p-dioxins; and dibenzofurans. The PCB aroclors analyzed included 1016, 1221, 1232, 1242, 1248, 1254, 1260, 1262 and 1268. Analyses of whole sediment also included total metals, simultaneously extracted metals, and acid volatile sulfide. Chemical characterization of samples of pore water isolated from samples of whole sediment at the start of the sediment toxicity exposures or at the start of the sediment bioaccumulation exposures included metals, major cations, major anions, dissolved organic carbon, and additional water-quality characteristics. Concentrations of metals or PCBs in pore water during the sediment toxicity exposures or during sediment bioaccumulation exposures also were determined using peeper samples (for metals) or solid-phase microextraction (SPME) samplers (for PCBs).</p>\n<br/>\n<p>The bioavailability and bioaccumulation of PCBs in 14 sediment samples were investigated using SPME passive samplers and the 28-d L. variegatus whole-sediment bioaccumulation exposures In general the accumulation of PCBs consistently was predicted through the use of organic carbon normalization and equilibrium partitioning. In these sediments, PCB homologs were accumulated differently based on bioavailability and potential to accumulate in oligochaetes. As part of this assessment homolog specific biota sediment accumulation factor values were developed that could be applied across the larger site to predict tissue levels of PCBs.</p>\n<br/>\n<p>The whole-sediment toxicity tests done with <i>H. azteca</i> and <i>C. dilutus</i> met the established ASTM and USEPA test acceptability criteria. The most responsive <i>H. azteca</i> endpoints were day 42 survival normalized young per female and day 28 biomass and that the most responsive <i>C. dilutus</i> endpoints were adult biomass and percent adult emergence. Overall, between the two species, the most responsive endpoint assessed for these two species was <i>H. azteca</i> survival-normalized young per female (67 percent of the samples classified as toxic).</p>\n<br/>\n<p>Concentration-response models (CRMs) and site-specific sediment toxicity thresholds (TTs) were generated with matching sediment chemistry and sediment toxicity data. Sediment chemistry, pore-water chemistry, and sediment toxicity data were evaluated for as many as 26 sediment samples from the Anniston PCB Site. The reference-envelope approach was used to identify the sediment samples that were toxic to benthic invertebrates. This procedure involved identification of reference sediment samples, normalizing the toxicity data to reflect control responses, developing a reference envelope for each toxicity test endpoint, and designating each sediment sample as toxic or not toxic for each toxicity test endpoint, for each species, and for all species combined. These results demonstrated percent emergence of adult <i>C. dilutus</i>, biomass of adult <i>C. dilutus</i>, and reproduction of <i>H. azteca</i> normalized to percent survival were among the most responsive endpoints that were evaluated. Therefore, these endpoints were selected for CRM development.</p>\n<br/>\n<p>The site-specific TTs for whole sediment provide a reliable basis for identifying toxic and not toxic sediment samples in the Anniston PCB Site (that is, for correctly classifying the sediment samples used to derive the TTs as toxic or not toxic, for the endpoint used to derive the TTs). Among the 69 TTs for sediment, the TT<sub>LRs</sub> for total PCB homologs [499 to 1,870 micrograms per kilogram dry weight (μg/kg DW)] and for lead [(9.48 to 10.3 milligrams per kilogram (mg/kg) DW] based on reproduction of <i>H. azteca</i> or based on emergence or biomass of adult <i>C. dilutus</i>, were the most reliable. Such TTs had low rates of false negative errors (that is, only 0 to 11 percent of the samples below the TT were toxic to benthic invertebrates), low rates of false positive errors (only 0 to 6 percent of the samples greater than the TT were not toxic to benthic invertebrates), and high rates of correct classification (that is, 92 to 96 percent).</p>\n<br/>\n<p>The site-specific TTs for PCBs and other COPCs derived in this study also were compared to empirically based sediment quality guidelines (SQGs), to equilibrium-partitioning based SQGs, and to the results of spiked-sediment toxicity tests. The results of this evaluation indicated that the site-specific sediment TTs for PCBs were comparable to the consensus-based SQGs that were derived for PCBs. In addition, the site-specific sediment TTs for PCBs are well within the range of SQGs derived using the equilibrium partitioning approach. The site-specific sediment TTs for PCBs also are consistent with the results of chronic TTs that have been estimated for benthic invertebrates using the results of spiked-sediment toxicity tests. As the site-specific sediment TTs for PCBs are consistent with empirically based SQGs, equilibrium-partitioning based SQGs, and results of sediment-spiking studies, these site- specific sediment TTs likely represent the concentrations of PCBs that are sufficient to cause toxicity to benthic invertebrates (as opposed to simply being correlated with adverse effects on the survival, weight, or reproduction of benthic invertebrates). Importantly, such site-specific sediment TTs have been demonstrated to accurately classify sediment samples as toxic or not toxic to benthic invertebrates at the Anniston PCB Site. In contrast, the TTs for metals, PAHs, and organochlorine pesticides were generally lower than consensus-based SQGs (that is, probable effect concentrations), and LC<sub>50s</sub> (median lethal effect concentrations) generated in spiked-sediment toxicity tests, indicating that these COPCs are likely not the main contributors to the observed toxicity of the site sediments evaluated in this study. The reproduction endpoint for <i>H. azteca</i> provided lower TTs compared to the day 28 biomass endpoint for <i>H. azteca</i> and the emergence or biomass endpoints for adult <i>C. dilutus</i> provided lower TTs compared to the day 13 biomass endpoint for <i>C. dilutus</i>.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135125","issn":"2328-0328","usgsCitation":"Ingersoll, C.G., Steevens, J., MacDonald, D., Brumbaugh, W.G., Coady, M.R., Farrar, J.D., Lotufo, G.R., Kemble, N.E., Kunz, J.L., Stanley, J.K., and Sinclair, J., 2014, Evaluation of toxicity to the amphipod, <i>Hyalella azteca</i>, and to the midge, <i>Chironomus dilutus</i>; and bioaccumulation by the oligochaete, <i>Lumbriculus variegatus</i>, with exposure to PCB-contaminated sediments from Anniston, Alabama: U.S. Geological Survey Scientific Investigations Report 2013-5125, Report: ix, 122 p.; Downloads Directory, https://doi.org/10.3133/sir20135125.","productDescription":"Report: ix, 122 p.; Downloads Directory","numberOfPages":"136","onlineOnly":"Y","ipdsId":"IP-036311","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":281049,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135125.jpg"},{"id":281046,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5125/"},{"id":281048,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2013/5125/downloads/"},{"id":281047,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5125/pdf/sir2013-5125.pdf"}],"country":"United States","state":"Alabama","city":"Anniston","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -85.931236,33.599966 ], [ -85.931236,33.750917 ], [ -85.755367,33.750917 ], [ -85.755367,33.599966 ], [ -85.931236,33.599966 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52d65d72e4b0b566e996b34b","contributors":{"editors":[{"text":"Ingersoll, Christopher G. 0000-0003-4531-5949 cingersoll@usgs.gov","orcid":"https://orcid.org/0000-0003-4531-5949","contributorId":2071,"corporation":false,"usgs":true,"family":"Ingersoll","given":"Christopher","email":"cingersoll@usgs.gov","middleInitial":"G.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":509632,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Steevens, Jeffery A. 0000-0003-3946-1229","orcid":"https://orcid.org/0000-0003-3946-1229","contributorId":65415,"corporation":false,"usgs":true,"family":"Steevens","given":"Jeffery A.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":509634,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"MacDonald, Donald D.","contributorId":49911,"corporation":false,"usgs":true,"family":"MacDonald","given":"Donald D.","affiliations":[],"preferred":false,"id":509633,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Ingersoll, Christopher G. 0000-0003-4531-5949 cingersoll@usgs.gov","orcid":"https://orcid.org/0000-0003-4531-5949","contributorId":2071,"corporation":false,"usgs":true,"family":"Ingersoll","given":"Christopher","email":"cingersoll@usgs.gov","middleInitial":"G.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":485857,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Steevens, Jeffery A. 0000-0003-3946-1229","orcid":"https://orcid.org/0000-0003-3946-1229","contributorId":65415,"corporation":false,"usgs":true,"family":"Steevens","given":"Jeffery A.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":485864,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"MacDonald, Donald D.","contributorId":49911,"corporation":false,"usgs":true,"family":"MacDonald","given":"Donald D.","affiliations":[],"preferred":false,"id":485862,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brumbaugh, William G. 0000-0003-0081-375X bbrumbaugh@usgs.gov","orcid":"https://orcid.org/0000-0003-0081-375X","contributorId":493,"corporation":false,"usgs":true,"family":"Brumbaugh","given":"William","email":"bbrumbaugh@usgs.gov","middleInitial":"G.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":485856,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Coady, Matthew R.","contributorId":36055,"corporation":false,"usgs":true,"family":"Coady","given":"Matthew","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":485861,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Farrar, J. Daniel","contributorId":18272,"corporation":false,"usgs":true,"family":"Farrar","given":"J.","email":"","middleInitial":"Daniel","affiliations":[],"preferred":false,"id":485860,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lotufo, Guilherme R.","contributorId":64564,"corporation":false,"usgs":true,"family":"Lotufo","given":"Guilherme","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":485863,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kemble, Nile E. 0000-0002-3608-0538 nkemble@usgs.gov","orcid":"https://orcid.org/0000-0002-3608-0538","contributorId":2626,"corporation":false,"usgs":true,"family":"Kemble","given":"Nile","email":"nkemble@usgs.gov","middleInitial":"E.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":485858,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kunz, James L. 0000-0002-1027-158X jkunz@usgs.gov","orcid":"https://orcid.org/0000-0002-1027-158X","contributorId":3309,"corporation":false,"usgs":true,"family":"Kunz","given":"James","email":"jkunz@usgs.gov","middleInitial":"L.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":485859,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Stanley, Jacob K.","contributorId":96590,"corporation":false,"usgs":true,"family":"Stanley","given":"Jacob","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":485866,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Sinclair, Jesse A.","contributorId":66967,"corporation":false,"usgs":true,"family":"Sinclair","given":"Jesse A.","affiliations":[],"preferred":false,"id":485865,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}}
,{"id":70071870,"text":"70071870 - 2014 - Parameter estimation for the 4-parameter Asymmetric Exponential Power distribution by the method of L-moments using R","interactions":[],"lastModifiedDate":"2014-01-14T14:20:36","indexId":"70071870","displayToPublicDate":"2014-01-14T14:18:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1309,"text":"Computational Statistics and Data Analysis","active":true,"publicationSubtype":{"id":10}},"title":"Parameter estimation for the 4-parameter Asymmetric Exponential Power distribution by the method of L-moments using R","docAbstract":"The implementation characteristics of two method of L-moments (MLM) algorithms for parameter estimation of the 4-parameter Asymmetric Exponential Power (AEP4) distribution are studied using the R environment for statistical computing. The objective is to validate the algorithms for general application of the AEP4 using R. An algorithm was introduced in the original study of the L-moments for the AEP4. A second or alternative algorithm is shown to have a larger L-moment-parameter domain than the original. The alternative algorithm is shown to provide reliable parameter production and recovery of L-moments from fitted parameters. A proposal is made for AEP4 implementation in conjunction with the 4-parameter Kappa distribution to create a mixed-distribution framework encompassing the joint L-skew and L-kurtosis domains. The example application provides a demonstration of pertinent algorithms with L-moment statistics and two 4-parameter distributions (AEP4 and the Generalized Lambda) for MLM fitting to a modestly asymmetric and heavy-tailed dataset using R.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Computational Statistics and Data Analysis","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.csda.2012.12.013","usgsCitation":"Asquith, W.H., 2014, Parameter estimation for the 4-parameter Asymmetric Exponential Power distribution by the method of L-moments using R: Computational Statistics and Data Analysis, v. 71, p. 955-970, https://doi.org/10.1016/j.csda.2012.12.013.","productDescription":"15 p.","startPage":"955","endPage":"970","ipdsId":"IP-040542","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":281037,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":280982,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.csda.2012.12.013"}],"volume":"71","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52d65d79e4b0b566e996b35b","contributors":{"authors":[{"text":"Asquith, William H. 0000-0002-7400-1861 wasquith@usgs.gov","orcid":"https://orcid.org/0000-0002-7400-1861","contributorId":1007,"corporation":false,"usgs":true,"family":"Asquith","given":"William","email":"wasquith@usgs.gov","middleInitial":"H.","affiliations":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":488268,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70071871,"text":"70071871 - 2014 - Regression models of discharge and mean velocity associated with near-median streamflow conditions in Texas: utility of the U.S. Geological Survey discharge measurement database","interactions":[],"lastModifiedDate":"2014-01-14T14:16:00","indexId":"70071871","displayToPublicDate":"2014-01-14T14:04:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2341,"text":"Journal of Hydrologic Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Regression models of discharge and mean velocity associated with near-median streamflow conditions in Texas: utility of the U.S. Geological Survey discharge measurement database","docAbstract":"A database containing more than 16,300 discharge values and ancillary hydraulic attributes was assembled from summaries of discharge measurement records for 391 USGS streamflow-gauging stations (streamgauges) in Texas. Each discharge is between the 40th- and 60th-percentile daily mean streamflow as determined by period-of-record, streamgauge-specific, flow-duration curves. Each discharge therefore is assumed to represent a discharge measurement made for near-median streamflow conditions, and such conditions are conceptualized as representative of midrange to baseflow conditions in much of the state. The hydraulic attributes of each discharge measurement included concomitant cross-section flow area, water-surface top width, and reported mean velocity. Two regression equations are presented: (1) an expression for discharge and (2) an expression for mean velocity, both as functions of selected hydraulic attributes and watershed characteristics. Specifically, the discharge equation uses cross-sectional area, water-surface top width, contributing drainage area of the watershed, and mean annual precipitation of the location; the equation has an adjusted R-squared of approximately 0.95 and residual standard error of approximately 0.23 base-10 logarithm (cubic meters per second). The mean velocity equation uses discharge, water-surface top width, contributing drainage area, and mean annual precipitation; the equation has an adjusted R-squared of approximately 0.50 and residual standard error of approximately 0.087 third root (meters per second). Residual plots from both equations indicate that reliable estimates of discharge and mean velocity at ungauged stream sites are possible. Further, the relation between contributing drainage area and main-channel slope (a measure of whole-watershed slope) is depicted to aid analyst judgment of equation applicability for ungauged sites. Example applications and computations are provided and discussed within a real-world, discharge-measurement scenario, and an illustration of the development of a preliminary stage-discharge relation using the discharge equation is given.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Hydrologic Engineering","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Society of Civil Engineers","doi":"10.1061/(ASCE)HE.1943-5584.0000715","usgsCitation":"Asquith, W.H., 2014, Regression models of discharge and mean velocity associated with near-median streamflow conditions in Texas: utility of the U.S. Geological Survey discharge measurement database: Journal of Hydrologic Engineering, v. 19, no. 1, p. 108-122, https://doi.org/10.1061/(ASCE)HE.1943-5584.0000715.","productDescription":"15 p.","startPage":"108","endPage":"122","ipdsId":"IP-040546","costCenters":[],"links":[{"id":281036,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":281034,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1061/(ASCE)HE.1943-5584.0000715"},{"id":281035,"type":{"id":15,"text":"Index Page"},"url":"https://ascelibrary.org/doi/abs/10.1061/%28ASCE%29HE.1943-5584.0000715"}],"country":"United States","state":"Texas","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -102.69,28.17 ], [ -102.69,36.50 ], [ -93.52,36.50 ], [ -93.52,28.17 ], [ -102.69,28.17 ] ] ] } } ] }","volume":"19","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52d65d7ae4b0b566e996b35f","contributors":{"authors":[{"text":"Asquith, William H. 0000-0002-7400-1861 wasquith@usgs.gov","orcid":"https://orcid.org/0000-0002-7400-1861","contributorId":1007,"corporation":false,"usgs":true,"family":"Asquith","given":"William","email":"wasquith@usgs.gov","middleInitial":"H.","affiliations":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":488269,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70049003,"text":"sim3274 - 2014 - Flood-inundation maps for the East Fork White River near Bedford, Indiana","interactions":[],"lastModifiedDate":"2014-01-13T17:49:16","indexId":"sim3274","displayToPublicDate":"2014-01-13T17:05:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3274","title":"Flood-inundation maps for the East Fork White River near Bedford, Indiana","docAbstract":"Digital flood-inundation maps for an 1.8-mile reach of the East Fork White River near Bedford, Indiana (Ind.) were created by the U.S. Geological Survey (USGS) in cooperation with the Indiana Department of Transportation. The inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation/ depict estimates of the areal extent and depth of flooding corresponding to selectedwater levels (stages) at USGS streamgage 03371500, East Fork White River near Bedford, Ind. Current conditions for estimating near-real-time areas of inundation using USGS streamgage information may be obtained on the Internet at http://waterdata.usgs.gov/in/nwis/uv?site_no=03371500. In addition, information has been provided to the National Weather Service (NWS) for incorporation into their Advanced Hydrologic Prediction Service (AHPS) flood warning system (http://water.weather.gov/ahps/). The NWS forecasts flood hydrographs at many places that are often colocated with USGS streamgages, including the East Fork White River near Bedford, Ind. NWS-forecasted peak-stage information may be used in conjunction with the maps developed in this study to show predicted areas of flood inundation.\n\nFor this study, flood profiles were computed for the East Fork White River reach by means of a one-dimensional step-backwater model. The hydraulic model was calibrated by using the most current stage-discharge relations at USGS streamgage 03371500, East Fork White River near Bedford, Ind., and documented high-water marks from the flood of June 2008. The calibrated hydraulic model was then used to determine 20 water-surface profiles for flood stages at 1-foot intervals referenced to the streamgage datum and ranging from bankfull to the highest stage of the current stage-discharge rating curve. The simulated water-surface profiles were then combined with a geographic information system (GIS) digital elevation model (DEM, derived from Light Detection and Ranging (LiDAR) data having a 0.593-foot vertical accuracy) in order to delineate the area flooded at each water level.\n\nThe availability of these maps, along with Internet information regarding current stage from the USGS streamgage near Bedford, Ind., and forecasted stream stages from the NWS, provides emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures, as well as for postflood recovery eforts.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3274","issn":"2329-132X","collaboration":"Prepared in cooperation with the Indiana Department of Transportation","usgsCitation":"Fowler, K.K., 2014, Flood-inundation maps for the East Fork White River near Bedford, Indiana: U.S. Geological Survey Scientific Investigations Map 3274, Report: v, 8 p.; 20 Map Sheets; Downloads Directory, https://doi.org/10.3133/sim3274.","productDescription":"Report: v, 8 p.; 20 Map Sheets; Downloads Directory","numberOfPages":"18","onlineOnly":"Y","ipdsId":"IP-045036","costCenters":[{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":280947,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim3274.jpg"},{"id":280944,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sim/3274/pdf/mapsheets/"},{"id":280945,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sim/3274/images/mapsheets_jpg/"},{"id":280946,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sim/3274/Downloads"},{"id":280942,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3274/"},{"id":280943,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3274/pdf/sim3274.pdf"}],"datum":"North American Vertical Datum 1988","country":"United States","state":"Indiana","city":"Bedford","otherGeospatial":"East Fork White River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -86.533333,38.75 ], [ -86.533333,38.85 ], [ -86.383333,38.85 ], [ -86.383333,38.75 ], [ -86.533333,38.75 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52d50bcae4b0f19e63d9b376","contributors":{"authors":[{"text":"Fowler, Kathleen K. 0000-0002-0107-3848 kkfowler@usgs.gov","orcid":"https://orcid.org/0000-0002-0107-3848","contributorId":2439,"corporation":false,"usgs":true,"family":"Fowler","given":"Kathleen","email":"kkfowler@usgs.gov","middleInitial":"K.","affiliations":[{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true},{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":485983,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}}
,{"id":70068736,"text":"70068736 - 2014 - Differentiation of pre-existing trapped methane from thermogenic methane in an igneous-intruded coal by hydrous pyrolysis","interactions":[],"lastModifiedDate":"2014-01-13T11:12:11","indexId":"70068736","displayToPublicDate":"2014-01-13T11:04:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2958,"text":"Organic Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Differentiation of pre-existing trapped methane from thermogenic methane in an igneous-intruded coal by hydrous pyrolysis","docAbstract":"So as to better understand how the gas generation potential of coal changes with increasing rank, same-seam samples of bituminous coal from the Illinois Basin that were naturally matured to varying degrees by the intrusion of an igneous dike were subjected to hydrous pyrolysis (HP) conditions of 360 °C for 72 h. The accumulated methane in the reactor headspace was analyzed for δ<sup>13</sup>C and δ2H, and mol percent composition. Maximum methane production (9.7 mg/g TOC) occurred in the most immature samples (0.5 %R<sub>o</sub>), waning to minimal methane values at 2.44 %Ro (0.67 mg/g TOC), and rebounding to 3.6 mg/g TOC methane in the most mature sample (6.76 %R<sub>o</sub>). Methane from coal with the highest initial thermal maturity (6.76 %R<sub>o</sub>) shows no isotopic dependence on the reactor water and has a microbial δ<sup>13</sup>C value of −61‰. However, methane from coal of minimal initial thermal maturity (0.5 %R<sub>o</sub>) shows hydrogen isotopic dependence on the reaction water and has a δ<sup>13</sup>C value of −37‰. The gas released from coals under hydrous pyrolysis conditions represents a quantifiable mixture of ancient (270 Ma) methane (likely microbial) that was generated in situ and trapped within the rock during the rapid heating by the dike, and modern (laboratory) thermogenic methane that was generated from the indigenous organic matter due to thermal maturation induced by hydrous pyrolysis conditions. These findings provide an analytical framework for better assessment of natural gas sources and for differentiating generated gas from pre-existing trapped gas in coals of various ranks.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Organic Geochemistry","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.orggeochem.2013.11.010","usgsCitation":"Dias, R.F., Lewan, M., Birdwell, J.E., and Kotarba, M.J., 2014, Differentiation of pre-existing trapped methane from thermogenic methane in an igneous-intruded coal by hydrous pyrolysis: Organic Geochemistry, v. 67, p. 1-7, https://doi.org/10.1016/j.orggeochem.2013.11.010.","productDescription":"7 p.","startPage":"1","endPage":"7","ipdsId":"IP-043968","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":280861,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":280847,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.orggeochem.2013.11.010"}],"volume":"67","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52d50ae2e4b0f19e63d9b20c","contributors":{"authors":[{"text":"Dias, Robert F. rfdias@usgs.gov","contributorId":3746,"corporation":false,"usgs":true,"family":"Dias","given":"Robert","email":"rfdias@usgs.gov","middleInitial":"F.","affiliations":[],"preferred":true,"id":488086,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lewan, Michael D. mlewan@usgs.gov","contributorId":940,"corporation":false,"usgs":true,"family":"Lewan","given":"Michael D.","email":"mlewan@usgs.gov","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":488084,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Birdwell, Justin E. 0000-0001-8263-1452 jbirdwell@usgs.gov","orcid":"https://orcid.org/0000-0001-8263-1452","contributorId":3302,"corporation":false,"usgs":true,"family":"Birdwell","given":"Justin","email":"jbirdwell@usgs.gov","middleInitial":"E.","affiliations":[{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":488085,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kotarba, Maciej J.","contributorId":74665,"corporation":false,"usgs":true,"family":"Kotarba","given":"Maciej","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":488087,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70068633,"text":"ofr20131289 - 2014 - Three-dimensional ground-motion simulations of earthquakes for the Hanford area, Washington","interactions":[],"lastModifiedDate":"2018-03-23T14:12:36","indexId":"ofr20131289","displayToPublicDate":"2014-01-10T14:51:03","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-1289","title":"Three-dimensional ground-motion simulations of earthquakes for the Hanford area, Washington","docAbstract":"This report describes the results of ground-motion simulations of earthquakes using three-dimensional (3D) and one-dimensional (1D) crustal models conducted for the probabilistic seismic hazard assessment (PSHA) of the Hanford facility, Washington, under the Senior Seismic Hazard Analysis Committee (SSHAC) guidelines. The first portion of this report demonstrates that the 3D seismic velocity model for the area produces synthetic seismograms with characteristics (spectral response values, duration) that better match those of the observed recordings of local earthquakes, compared to a 1D model with horizontal layers. The second part of the report compares the response spectra of synthetics from 3D and 1D models for moment magnitude (M) 6.6–6.8 earthquakes on three nearby faults and for a dipping plane wave source meant to approximate regional S-waves from a Cascadia great earthquake. The 1D models are specific to each site used for the PSHA. The use of the 3D model produces spectral response accelerations at periods of 0.5–2.0 seconds as much as a factor of 4.5 greater than those from the 1D models for the crustal fault sources. The spectral accelerations of the 3D synthetics for the Cascadia plane-wave source are as much as a factor of 9 greater than those from the 1D models. The differences between the spectral accelerations for the 3D and 1D models are most pronounced for sites with thicker supra-basalt sediments and for stations with earthquakes on the Rattlesnake Hills fault and for the Cascadia plane-wave source.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131289","usgsCitation":"Frankel, A., Thorne, P., and Rohay, A., 2014, Three-dimensional ground-motion simulations of earthquakes for the Hanford area, Washington: U.S. Geological Survey Open-File Report 2013-1289, vi, 48 p., https://doi.org/10.3133/ofr20131289.","productDescription":"vi, 48 p.","numberOfPages":"54","onlineOnly":"Y","ipdsId":"IP-052201","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":280820,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131289.PNG"},{"id":280819,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1289/pdf/ofr2013-1289.pdf"},{"id":280818,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1289/"}],"country":"United States","state":"Washington","otherGeospatial":"Hanford Facility","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -119.4078,46.5637 ], [ -119.4078,46.6037 ], [ -119.3677,46.6037 ], [ -119.3677,46.5637 ], [ -119.4078,46.5637 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52d1176ae4b072eb3e0c4b88","contributors":{"authors":[{"text":"Frankel, Arthur","contributorId":103761,"corporation":false,"usgs":true,"family":"Frankel","given":"Arthur","affiliations":[],"preferred":false,"id":488028,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thorne, Paul","contributorId":13131,"corporation":false,"usgs":true,"family":"Thorne","given":"Paul","email":"","affiliations":[],"preferred":false,"id":488026,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rohay, Alan","contributorId":58934,"corporation":false,"usgs":true,"family":"Rohay","given":"Alan","affiliations":[],"preferred":false,"id":488027,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70059781,"text":"ofr20131308 - 2014 - Response of Global Navigation Satellite System receivers to known shaking between 0.2 and 20 Hertz","interactions":[],"lastModifiedDate":"2016-08-29T15:22:23","indexId":"ofr20131308","displayToPublicDate":"2014-01-10T08:12:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-1308","title":"Response of Global Navigation Satellite System receivers to known shaking between 0.2 and 20 Hertz","docAbstract":"<p>Over the past decade, several technological advances have allowed Global Navigation Satellite Systems (GNSS) receivers to have the capability to record displacements at high frequencies, with sampling rates approaching 100 samples per second (sps). In addition, communication and computer hardware and software have allowed various institutions, including the U.S. Geological Survey (USGS), to retrieve, process, and display position changes recorded by a network of GNSS sites with small, less than 1-s delays between the time that the GNSS receiver records signals from a constellation of satellites and the time that the position is estimated (a method known as &ldquo;real-time&rdquo;). These improvements in hardware and software have allowed the USGS to process GNSS (or a subset of the GNSS, the Global Positioning System, GPS) data in real-time at 1 sps with the goal of determining displacements from earthquakes and volcanoes in real-time. However, the current set of GNSS equipment can record at rates of 100 sps, which allows the possibility of using this equipment to record earthquake displacements over the full range of frequencies that typically are recorded by acceleration and velocity transducers. The advantage of using GNSS to record earthquakes is that the displacement, rather than acceleration or velocity, is recorded, and for large earthquakes, the GNSS sensor stays on scale and will not distort the observations due to clipping of the signal at its highest amplitude. The direct observation of displacement is advantageous in estimating the size and spatial extent of the earthquake rupture. Otherwise, when using velocity or acceleration sensors, the displacements are determined by numerical integration of the observations, which can introduce significant uncertainty in the estimated displacements. However, GNSS technology can, at best, resolve displacements of a few millimeters, and for most earthquakes, their displacements are less than 1 mm. Consequently, to be useful, GNSS data are only relevant for the large earthquakes with magnitudes (M) exceeding M5.5 at best.</p>\n<p>With the capability to record GNSS data at high-rate, at sampling rates typical for seismological applications, experiments are needed to quantify the response of GNSS to shaking from earthquakes. There have been a few studies that examine the response of GNSS to strong shaking. One of the first was Elosegui and others (2006), where they simulated surface waves from a distant earthquake and mechanically applied the shaking to a GPS antenna. They processed the 1 sps observations and compared the estimated displacements with the simulated displacements. They determined that the GPS could accurately track the simulated surface wave whose primary frequency spans from 0.01 to 0.1 Hertz (Hz), which spanned the frequency band of the simulation.</p>\n<p>To test GNSS equipment due to shaking from a large earthquake in the near-field, Wang and others (2012) used a mechanical simulator or shake table with 6 degrees of freedom and studied two different inputs to the simulator&mdash;(1) the accelerometer record from one station that was located near the 2010 M8.8 Maule, Chile earthquake, and (2) a 2-Hz sinusoid. Wang and others (2012) analyzed the 2-Hz data with spectral analysis and determined that the displacements observed by the GPS included higher harmonics along with the 2-Hz signal. In addition, the background spectral amplitude was greater during periods of 2-Hz shaking than when at rest. With the simulated M 8.8 earthquake, Wang and others (2012) observed decreased signal to noise for L1 and L2 carrier frequencies of the GPS signal, at times corresponding to high acceleration and jerk (first derivative of acceleration).</p>\n<p>One of the principal limitations of these experiments was that the displacements of the shake table itself could not be measured independently. Although with the 2-Hz sinusoidal measurements, the input displacements were purely translational, Wang and others (2012) analysis of the data showed that the shake table also included rotational motions which affect horizontal inertial sensors like accelerometers and seismometers at first order.</p>\n<p>More recently, Ebinuma and Kato (2012) used a GPS simulator to electronically test several GNSS receivers and obtain the receiver characteristics at three frequencies: 1, 2, and 5 Hz. The results showed that the amplitude of 5-Hz displacements recorded by the GPS was, depending on the receiver model, between 30 and 125 percent more than the displacement input to the simulator. At low frequencies, the GPS displacement was nearly equal to the input displacement. In addition, Ebinuma and Kato (2012) examined how each receiver model amplified an earthquake displacement record in the 2&ndash;8 Hz band. The simulated earthquake was the 2008 moment magnitude (Mw) 6.8 Iwate-Miyagi earthquake where, for the simulated record, acceleration peaked at 1 G.</p>\n<p>The study discussed here builds on the tests by Ebinuma and Kato (2012), but rather than using electronic simulation, the tests are setup outdoors and closer to actual field installations of GNSS equipment. We used a one-dimensional shake table capable of 400 mm of displacement and high acceleration; the shake table also is constrained by a precision linear slider to have very low tilt that would affect inertial sensors. In addition, the stage position can be accurately monitored independent of the GNSS hardware and, importantly, provides a reference to compare with the estimated displacements from the GNSS data. Our tests spanned a greater frequency range from 0.2 to 20 Hz and we used equipment from three different manufacturers covering five different combinations of receivers and antennas. In addition, we have been able to simulate the frequency response of the GNSS equipment using a simple, causal filter. The quality of the filter was tested using additional test data where a step function in displacement was applied to the shake table. The observed displacements from the GNSS data show an overshoot in displacement at the time of the step or transition of the stage. That overshoot was accurately predicted using the filter design derived from our sinusoidal displacement tests.</p>\n<p>Similar to Wang and others (2012), we also examined the GPS displacement records using standard spectral techniques. However, we extended their work by evaluating several models of GNSS receivers using a variety of input frequencies. Because our shake table was limited on acceleration and displacement, we did not attempt to duplicate the high shaking associated with high magnitude earthquakes. However, because our shake table could measure the table displacement, we could directly compare the measured GPS displacements with the true displacements.</p>","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131308","usgsCitation":"Langbein, J.O., Evans, J.R., Blume, F., and Johanson, I., 2014, Response of Global Navigation Satellite System receivers to known shaking between 0.2 and 20 Hertz: U.S. Geological Survey Open-File Report 2013-1308, iv, 28 p., https://doi.org/10.3133/ofr20131308.","productDescription":"iv, 28 p.","numberOfPages":"32","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-049015","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":379,"text":"Menlo Park Science Center","active":false,"usgs":true}],"links":[{"id":280804,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131308.PNG"},{"id":280801,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1308/"},{"id":280803,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1308/pdf/ofr2013-1308.pdf","text":"Report","size":"4.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52d11769e4b072eb3e0c4b81","contributors":{"authors":[{"text":"Langbein, John O.","contributorId":72438,"corporation":false,"usgs":true,"family":"Langbein","given":"John","middleInitial":"O.","affiliations":[],"preferred":false,"id":487818,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Evans, John R. jrevans@usgs.gov","contributorId":529,"corporation":false,"usgs":true,"family":"Evans","given":"John","email":"jrevans@usgs.gov","middleInitial":"R.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":487816,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Blume, Fredrick","contributorId":100283,"corporation":false,"usgs":true,"family":"Blume","given":"Fredrick","email":"","affiliations":[],"preferred":false,"id":487819,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Johanson, Ingrid","contributorId":54880,"corporation":false,"usgs":true,"family":"Johanson","given":"Ingrid","affiliations":[],"preferred":false,"id":487817,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
,{"id":70067810,"text":"70067810 - 2014 - <i>Graptemys pulchra</i> Baur 1893: Alabama Map Turtle","interactions":[],"lastModifiedDate":"2014-01-09T08:38:45","indexId":"70067810","displayToPublicDate":"2014-01-09T08:28:00","publicationYear":"2014","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"<i>Graptemys pulchra</i> Baur 1893: Alabama Map Turtle","docAbstract":"The Alabama Map Turtle, <i>Graptemys pulchra</i> (Family Emydidae), is a moderately large riverine species endemic to the Mobile Bay drainage system of Alabama, Georgia, and Mississippi. Sexual size dimorphism is pronounced, with adult females (carapace length [CL] to 273 mm) attaining more than twice the size of adult males (CL to 117 mm). The species is an inhabitant of relatively large, swift creeks and rivers, often with wide sandbars. Stream sections open to the sun and with abundant basking sites in the form of logs and brush are preferred. Six to seven clutches of 4–7 eggs are laid each year on river sandbars. Although the species is locally abundant, populations are threatened by habitat destruction, declines in their prey base, commercial collection, and vandalism. It is listed as a Species of Special Concern in Alabama.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Conservation biology of freshwater turtles and tortoises: a compilation project of the IUCN/SSC Tortoise and Freshwater Turtle Specialist Group","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"Chelonian Research Foundation","doi":"10.3854/crm.5.072.pulchra.v1.2014","usgsCitation":"Lovich, J.E., Godwin, J.C., and McCoy, C., 2014, <i>Graptemys pulchra</i> Baur 1893: Alabama Map Turtle, chap. <i>of</i> Conservation biology of freshwater turtles and tortoises: a compilation project of the IUCN/SSC Tortoise and Freshwater Turtle Specialist Group, p. 072.1-072.6, https://doi.org/10.3854/crm.5.072.pulchra.v1.2014.","productDescription":"6 p.","startPage":"072.1","endPage":"072.6","numberOfPages":"6","ipdsId":"IP-053336","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":473227,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3854/crm.5.072.pulchra.v1.2014","text":"Publisher Index Page"},{"id":280783,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":280781,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.3854/crm.5.072.pulchra.v1.2014"},{"id":280782,"type":{"id":15,"text":"Index Page"},"url":"https://www.iucn-tftsg.org/graptemys-pulchra-072/"}],"country":"United States","state":"Alabama;Georgia;Mississippi","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -92.36,28.98 ], [ -92.36,35.62 ], [ -79.98,35.62 ], [ -79.98,28.98 ], [ -92.36,28.98 ] ] ] } } ] }","noUsgsAuthors":false,"publicationDate":"2014-01-06","publicationStatus":"PW","scienceBaseUri":"52cfc4dfe4b07de2a9490917","contributors":{"editors":[{"text":"Rhodin, A. G. J.","contributorId":114192,"corporation":false,"usgs":true,"family":"Rhodin","given":"A.","email":"","middleInitial":"G. J.","affiliations":[],"preferred":false,"id":509672,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Pritchard, P. C. H.","contributorId":113118,"corporation":false,"usgs":true,"family":"Pritchard","given":"P.","email":"","middleInitial":"C. H.","affiliations":[],"preferred":false,"id":509670,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"van Dijk, P. P.","contributorId":113295,"corporation":false,"usgs":true,"family":"van Dijk","given":"P.","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":509671,"contributorType":{"id":2,"text":"Editors"},"rank":3},{"text":"Saumure, Raymond A.","contributorId":71375,"corporation":false,"usgs":false,"family":"Saumure","given":"Raymond","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":509668,"contributorType":{"id":2,"text":"Editors"},"rank":4},{"text":"Buhlmann, K.A.","contributorId":112229,"corporation":false,"usgs":true,"family":"Buhlmann","given":"K.A.","email":"","affiliations":[],"preferred":false,"id":509669,"contributorType":{"id":2,"text":"Editors"},"rank":5},{"text":"Iverson, J. B.","contributorId":16364,"corporation":false,"usgs":true,"family":"Iverson","given":"J.","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":509666,"contributorType":{"id":2,"text":"Editors"},"rank":6},{"text":"Mittermeier, R.A.","contributorId":37034,"corporation":false,"usgs":true,"family":"Mittermeier","given":"R.A.","email":"","affiliations":[],"preferred":false,"id":509667,"contributorType":{"id":2,"text":"Editors"},"rank":7}],"authors":[{"text":"Lovich, Jeffrey E. 0000-0002-7789-2831 jeffrey_lovich@usgs.gov","orcid":"https://orcid.org/0000-0002-7789-2831","contributorId":458,"corporation":false,"usgs":true,"family":"Lovich","given":"Jeffrey","email":"jeffrey_lovich@usgs.gov","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":488006,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Godwin, James C.","contributorId":55734,"corporation":false,"usgs":true,"family":"Godwin","given":"James","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":488007,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McCoy, C.J.","contributorId":89075,"corporation":false,"usgs":true,"family":"McCoy","given":"C.J.","email":"","affiliations":[],"preferred":false,"id":488008,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}}
,{"id":70048449,"text":"70048449 - 2014 - Forecasting conditional climate-change using a hybrid approach","interactions":[],"lastModifiedDate":"2014-01-08T16:18:32","indexId":"70048449","displayToPublicDate":"2014-01-08T16:12:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1551,"text":"Environmental Modelling and Software","active":true,"publicationSubtype":{"id":10}},"title":"Forecasting conditional climate-change using a hybrid approach","docAbstract":"A novel approach is proposed to forecast the likelihood of climate-change across spatial landscape gradients. This hybrid approach involves reconstructing past precipitation and temperature using the self-organizing map technique; determining quantile trends in the climate-change variables by quantile regression modeling; and computing conditional forecasts of climate-change variables based on self-similarity in quantile trends using the fractionally differenced auto-regressive integrated moving average technique. The proposed modeling approach is applied to states (Arizona, California, Colorado, Nevada, New Mexico, and Utah) in the southwestern U.S., where conditional forecasts of climate-change variables are evaluated against recent (2012) observations, evaluated at a future time period (2030), and evaluated as future trends (2009–2059). These results have broad economic, political, and social implications because they quantify uncertainty in climate-change forecasts affecting various sectors of society. Another benefit of the proposed hybrid approach is that it can be extended to any spatiotemporal scale providing self-similarity exists.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Environmental Modelling and Software","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.envsoft.2013.10.009","usgsCitation":"Esfahani, A.A., and Friedel, M.J., 2014, Forecasting conditional climate-change using a hybrid approach: Environmental Modelling and Software, v. 52, p. 83-97, https://doi.org/10.1016/j.envsoft.2013.10.009.","productDescription":"15 p.","startPage":"83","endPage":"97","numberOfPages":"15","ipdsId":"IP-044598","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":280780,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":280779,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.envsoft.2013.10.009"}],"country":"United States","state":"Arizona;California;Colorado;Nevada;New Mexico;Utah","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.41,31.25 ], [ -124.41,42.0 ], [ -102.0,42.0 ], [ -102.0,31.25 ], [ -124.41,31.25 ] ] ] } } ] }","volume":"52","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52ce747de4b073e0995b2dd3","contributors":{"authors":[{"text":"Esfahani, Akbar Akbari","contributorId":67795,"corporation":false,"usgs":true,"family":"Esfahani","given":"Akbar","email":"","middleInitial":"Akbari","affiliations":[],"preferred":false,"id":484681,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Friedel, Michael J. 0000-0002-5060-3999 mfriedel@usgs.gov","orcid":"https://orcid.org/0000-0002-5060-3999","contributorId":595,"corporation":false,"usgs":true,"family":"Friedel","given":"Michael","email":"mfriedel@usgs.gov","middleInitial":"J.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":484680,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}}
,{"id":70048979,"text":"ofr20131235 - 2014 - Lesser prairie-chicken nest site selection, microclimate, and nest survival in association with vegetation response to a grassland restoration program","interactions":[],"lastModifiedDate":"2014-01-08T13:58:10","indexId":"ofr20131235","displayToPublicDate":"2014-01-08T13:49:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-1235","title":"Lesser prairie-chicken nest site selection, microclimate, and nest survival in association with vegetation response to a grassland restoration program","docAbstract":"Climate models predict that the region of the Great Plains Landscape Conservation Cooperative (GPLCC) will experience increased maximum and minimum temperatures, reduced frequency but greater intensity of precipitation events, and earlier springs. These climate changes along with different landscape management techniques may influence the persistence of the lesser prairie-chicken (Tympanuchus pallidicinctus), a candidate for protection under the Endangered Species Act and a priority species under the GPLCC, in positive or negative ways. The objectives of this study were to conduct (1) a literature review of lesser prairie-chicken nesting phenology and ecology, (2) an analysis of thermal aspects of lesser prairie-chicken nest microclimate data, and (3) an analysis of nest site selection, nest survival, and vegetation response to 10 years of tebuthiuron and/or grazing treatments.\n\nWe found few reports in the literature containing useful data on the nesting phenology of lesser prairie-chickens; therefore, managers must rely on short-term observations and measurements of parameters that provide some predictive insight into climate impacts on nesting ecology. Our field studies showed that prairie-chickens on nests were able to maintain relatively consistent average nest temperature of 31 °C and nest humidities of 56.8 percent whereas average external temperatures (20.3–35.0 °C) and humidities (35.2–74.9 percent) varied widely throughout the 24 hour (hr) cycle. Grazing and herbicide treatments within our experimental areas were designed to be less intensive than in common practice. We determined nest locations by radio-tagging hen lesser prairie-chickens captured at leks, which are display grounds at which male lesser prairie-chickens aggregate and attempt to attract a female for mating. Because nest locations selected by hen lesser prairie-chicken are strongly associated with the lek at which they were captured, we assessed nesting habitat use on the basis of hens captured at individual leks, and then for all leks pooled. There was no clear pattern of selection for treatment type for nest placement among hens associated with individual leks; however, when hens from all leks were pooled, we found nesting lesser prairie-chickens selected control plots for nesting over plots that were grazed, treated with tebuthiuron, or were both grazed and treated with tebuthiuron. Overall, the probability of a nest surviving the incubation period was 0.57 for this study and did not vary significantly among treatment types. In contrast to nesting preference for untreated habitats, lek use exhibited no noticeable selection of treatment type. Over the 10 years of the habitat management study, there was 91 percent less sand shinnery oak (Quercus havardii) in treated areas than untreated areas. The removal of sand shinnery oak made environmental soil moisture more available for grasses and forbs to germinate and grow. Grasses increased by 149 percent and forbs increased by 257 percent in treated areas as compared to untreated areas throughout the study period. Our combined results, including our habitat selection analysis at the individual lek level, indicated that reduced rates of herbicide and short-duration grazing treatments were not detrimental to nesting lesser prairie-chickens and that populations of lesser prairie-chickens in shrub-dominated ecosystems may benefit from reduced rates of herbicide application and short duration of grazing that results in increased habitat heterogeneity.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131235","issn":"2331-1258","collaboration":"Prepared in cooperation with New Mexico Game and Fish and Texas Parks and Wildlife Department","usgsCitation":"Boal, C.W., Grisham, B.A., Haukos, D.A., Zavaleta, J.C., and Dixon, C., 2014, Lesser prairie-chicken nest site selection, microclimate, and nest survival in association with vegetation response to a grassland restoration program: U.S. Geological Survey Open-File Report 2013-1235, x, 35 p., https://doi.org/10.3133/ofr20131235.","productDescription":"x, 35 p.","numberOfPages":"48","onlineOnly":"Y","ipdsId":"IP-042288","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":280746,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131235.jpg"},{"id":280745,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1235/pdf/ofr2013-1235.pdf"},{"id":280744,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1235/"}],"country":"United States","state":"New Mexico;Texas","county":"Cochran County;Hockley County;Roosevelt County;Terry County;Yoakum County","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -103.9475,32.5586 ], [ -103.9475,34.6068 ], [ -101.0989,34.6068 ], [ -101.0989,32.5586 ], [ -103.9475,32.5586 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"52ce7482e4b073e0995b2de3","contributors":{"authors":[{"text":"Boal, Clint W. 0000-0001-6008-8911 cboal@usgs.gov","orcid":"https://orcid.org/0000-0001-6008-8911","contributorId":1909,"corporation":false,"usgs":true,"family":"Boal","given":"Clint","email":"cboal@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":485918,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grisham, Blake A.","contributorId":75419,"corporation":false,"usgs":true,"family":"Grisham","given":"Blake","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":485921,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haukos, David A. 0000-0001-5372-9960 dhaukos@usgs.gov","orcid":"https://orcid.org/0000-0001-5372-9960","contributorId":3664,"corporation":false,"usgs":true,"family":"Haukos","given":"David","email":"dhaukos@usgs.gov","middleInitial":"A.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":485919,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zavaleta, Jennifer C.","contributorId":102785,"corporation":false,"usgs":true,"family":"Zavaleta","given":"Jennifer","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":485922,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dixon, Charles","contributorId":68203,"corporation":false,"usgs":true,"family":"Dixon","given":"Charles","email":"","affiliations":[],"preferred":false,"id":485920,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}}
,{"id":70047737,"text":"70047737 - 2014 - Ground motion in the presence of complex topography: Earthquake and ambient noise sources","interactions":[],"lastModifiedDate":"2016-01-29T11:13:00","indexId":"70047737","displayToPublicDate":"2014-01-08T11:58:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Ground motion in the presence of complex topography: Earthquake and ambient noise sources","docAbstract":"<p>To study the influence of topography on ground motion, eight seismic recorders were deployed for a period of one year over Poverty Ridge on the east side of the San Francisco Bay Area, California. This location is desirable because of its proximity to local earthquake sources and the significant topographic relief of the array (439 m). Topographic amplification is evaluated as a function of frequency using a variety of methods, including reference‐site‐based spectral ratios and single‐station horizontal‐to‐vertical spectral ratios using both shear waves from earthquakes and ambient noise. Field observations are compared with the predicted ground motion from an accurate digital model of the topography and a 3D local velocity model. Amplification factors from the theoretical calculations are consistent with observations. The fundamental resonance of the ridge is prominently observed in the spectra of data and synthetics; however, higher‐frequency peaks are also seen primarily for sources in line with the major axis of the ridge, perhaps indicating higher resonant modes. Excitations of lateral ribs off of the main ridge are also seen at frequencies consistent with their dimensions. The favored directions of resonance are shown to be transverse to the major axes of the topographic features.</p>","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Bulletin of the Seismological Society of America","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Seismological Society of America","publisherLocation":"Stanford","doi":"10.1785/0120130088","usgsCitation":"Hartzell, S.H., Meremonte, M., Ramírez-Guzmán, L., and McNamara, D., 2014, Ground motion in the presence of complex topography: Earthquake and ambient noise sources: Bulletin of the Seismological Society of America, v. 104, no. 1, p. 451-466, https://doi.org/10.1785/0120130088.","productDescription":"16 p.","startPage":"451","endPage":"466","numberOfPages":"16","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-050721","costCenters":[{"id":218,"text":"Denver Federal Center","active":false,"usgs":true}],"links":[{"id":280770,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"Santa Clara Valley","otherGeospatial":"Diablo Mountains; Poverty Ridge","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.0,37.2 ], [ -122.0,37.6 ], [ -121.6,37.6 ], [ -121.6,37.2 ], [ -122.0,37.2 ] ] ] } } ] }","volume":"104","issue":"1","noUsgsAuthors":false,"publicationDate":"2013-11-19","publicationStatus":"PW","scienceBaseUri":"52ce747ee4b073e0995b2dd7","contributors":{"authors":[{"text":"Hartzell, Stephen H. 0000-0003-0858-9043 shartzell@usgs.gov","orcid":"https://orcid.org/0000-0003-0858-9043","contributorId":2594,"corporation":false,"usgs":true,"family":"Hartzell","given":"Stephen","email":"shartzell@usgs.gov","middleInitial":"H.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":482862,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Meremonte, Mark","contributorId":56968,"corporation":false,"usgs":true,"family":"Meremonte","given":"Mark","affiliations":[],"preferred":false,"id":482864,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ramírez-Guzmán, Leonardo","contributorId":45946,"corporation":false,"usgs":true,"family":"Ramírez-Guzmán","given":"Leonardo","affiliations":[],"preferred":false,"id":482863,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McNamara, Daniel","contributorId":103566,"corporation":false,"usgs":true,"family":"McNamara","given":"Daniel","affiliations":[],"preferred":false,"id":482865,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}}
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