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  • 2015-2019  (375)
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  • 1
    Publication Date: 2019-09-18
    Description: Three species of Habrostroma dominate stromatoporoid faunas in the Lower Devonian (Lochkovian) of five areas in North America: New York, Virginia, Maine, Bathurst Island, and Ellesmere Island. In addition, they occur in what could be the upper Silurian (uppermost Pridoli) of Virginia, and possibly New York. Measurements of nine morphologies from 127 specimens of Habrostroma were subjected to an average linkage cluster analysis. Using average linkage between groups, three distinct clusters were revealed. Group assignments made from the cluster analysis were saved, and entered into a canonical discriminant analysis with the nine morphological variables. An overall Wilks’ lambda was calculated, and is statistically significant at alpha
    Print ISSN: 0022-3360
    Electronic ISSN: 1937-2337
    Topics: Geosciences
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  • 2
  • 3
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    Geological Society
    In:  In: Mesozoic Resource Potential in the Southern Permian Basin. , ed. by Kilhams, B., Kukla, P. A., Mazur, S., McKie, T., Mijnlieff, H. F. and van Ojikk, K. Geological Society Special Publication, 469 . Geological Society, London, Chapter 21.
    Publication Date: 2018-06-29
    Description: A high-resolution three-dimensional (3D) numerical basin model, incorporating the eastern part of the Lower Saxony Basin (LSB), the Gifhorn Trough and parts of the southern Pompeckj Block, was built to reconstruct the thermal and structural evolution of this area. The estimation and calculation of the unconventional oil and gas resource density within the Posidonia Shale source-rock unit was the main objective of this study. Incorporating organic–geochemical data for the Posidonia Shale source-rock units, such as compositional petroleum generation kinetics data, allowed a more accurate prediction of hydrocarbon potential compared to large-scale models of the area, as well as a better prediction of bulk adsorption capacity and adsorbed gas content. For the accurate calculation of oil and gas contents within the source-rock lithologies, mineralogy and physical properties of the rocks, such as compressibility, sorption capacity and porosity, are important as well as organic matter quantity, quality and thermal maturity. These properties in turn are strongly dependent on the vastly different burial/uplift histories within the LSB, Gifhorn Trough and the Pompeckj Block. The Gifhorn Trough, large parts of the Pompeckj Block and the flanks of the LSB are interesting concerning the unconventional oil potential, with current source-rock maturities between 0.65% and 1.2% vitrinite reflectance. Central parts of the LSB and small parts of the Pompeckj Block show inherent unconventional gas potential. Methane adsorption capacity is influenced by the burial/uplift history of the basin, which stresses the importance of structural and geochemical interlocking in understanding unconventional hydrocarbon systems.
    Type: Book chapter , NonPeerReviewed
    Format: text
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  • 4
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    PANGAEA
    In:  Supplement to: Stock, Andy (2015): Satellite mapping of Baltic Sea Secchi depth with multiple regression models. International Journal of Applied Earth Observation and Geoinformation, 40, 55-64, https://doi.org/10.1016/j.jag.2015.04.002
    Publication Date: 2018-09-27
    Description: Secchi depth is a measure of water transparency. In the Baltic Sea region, Secchi depth maps are used to assess eutrophication and as input for habitat models. Due to their spatial and temporal coverage, satellite data would be the most suitable data source for such maps. But the Baltic Sea's optical properties are so different from the open ocean that globally calibrated standard models suffer from large errors. Regional predictive models that take the Baltic Sea's special optical properties into account are thus needed. This paper tests how accurately generalized linear models (GLMs) and generalized additive models (GAMs) with MODIS/Aqua and auxiliary data as inputs can predict Secchi depth at a regional scale. It uses cross-validation to test the prediction accuracy of hundreds of GAMs and GLMs with up to 5 input variables. A GAM with 3 input variables (chlorophyll a, remote sensing reflectance at 678 nm, and long-term mean salinity) made the most accurate predictions. Tested against field observations not used for model selection and calibration, the best model's mean absolute error (MAE) for daily predictions was 1.07 m (22%), more than 50% lower than for other publicly available Baltic Sea Secchi depth maps. The MAE for predicting monthly averages was 0.86 m (15%). Thus, the proposed model selection process was able to find a regional model with good prediction accuracy. It could be useful to find predictive models for environmental variables other than Secchi depth, using data from other satellite sensors, and for other regions where non-standard remote sensing models are needed for prediction and mapping. Annual and monthly mean Secchi depth maps for 2003–2012 come with this paper as Supplementary materials.
    Type: Dataset
    Format: text/tab-separated-values, 33 data points
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  • 5
    Publication Date: 2015-03-26
    Description: The sea ice structure of the Arctic Ocean has changed measurably in the last decades. Sea ice decline and warming of the surface water layers may affect composition and diversity of protist communities living in the sea ice interface and the pelagic realm. Samples from different habitats were analyzed (1) to investigate the impact of sea ice on the protists and, (2) to elucidate cryo-pelagic coupling. Samples were collected from melt ponds, sea ice, under-ice water and water column during two RV Polarstern cruises to the Central Arctic Ocean in August - September 2011 & 2012. Automated ribosomal intergenic spacer analysis (ARISA) from 182 samples and Illumina-sequencing of 57 samples revealed a high heterogeneity between different melt pond and sea ice samples, whereas samples from the water column were more homogeneous. However, different sea ice habitats showed similar patterns in protist community structure at the same station, indicating intensive sea-ice-water-exchange during melting and freezing processes. These results illustrate that the high biodiversity in the Central Arctic is mainly governed by the sea ice origin compared to the oceanic currents.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Conference , NonPeerReviewed
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  • 6
    Publication Date: 2017-02-21
    Description: Sea ice is one of the main features influencing the Arctic marine protist community composition and diversity in sea ice and sea water. We analyzed protist communities within sea ice, melt pond water, under-ice water and deep-chlorophyll maximum water at eight sea ice stations sampled during summer of the 2012 record sea ice minimum year. Using Illumina sequencing, we identified characteristic communities associated with specific habitats and investigated protist exchange between these habitats. The highest abundance and diversity of unique taxa were found in sea ice, particularly in multi-year ice (MYI), highlighting the importance of sea ice as a unique habitat for sea ice protists. Melting of sea ice was associated with increased exchange of communities between sea ice and the underlying water column. In contrast, sea ice formation was associated with increased exchange between all four habitats, suggesting that brine rejection from the ice is an important factor for species redistribution in the Central Arctic. Ubiquitous taxa (e.g. Gymnodinium) that occurred in all habitats still had habitat-preferences. This demonstrates a limited ability to survive in adjacent but different environments. Our results suggest that the continued reduction of sea ice extent, and particularly of MYI, will likely lead to diminished protist exchange and subsequently, could reduce species diversity in all habitats of the Central Arctic Ocean. An important component of the unique sea ice protist community could be endangered because specialized taxa restricted to this habitat may not be able to adapt to rapid environmental changes.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , NonPeerReviewed
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  • 7
    Publication Date: 2017-05-09
    Description: Atmospheric chemical composition is crucial in determining a planet's atmospheric structure, stability, and evolution. Attaining a quantitative understanding of the essential chemical mechanisms governing atmospheric composition is nontrivial due to complex interactions between chemical species. Trace species, for example, can participate in catalytic cycles - affecting the abundance of major and other trace gas species. Specifically, for Mars, such cycles dictate the abundance of its primary atmospheric constituent, carbon dioxide (CO2), but also for one of its trace gases, ozone (O3). The identification of chemical pathways/cycles by hand is extremely demanding; hence, the application of numerical methods, such as the Pathway Analysis Program (PAP), is crucial to analyze and quantitatively exemplify chemical reaction networks. Here, we carry out the first automated quantitative chemical pathway analysis of Mars' atmosphere with respect to O3 . PAP was applied to JPL/Caltech's 1-D updated photochemical Mars model's output data. We determine all significant chemical pathways and their contribution to O3 production and consumption (up to 80 km) in order to investigate the mechanisms causing the characteristic shape of the O3 volume mixing ratio profile, i.e. a ground layer maximum and an ozone layer at ~50 km. These pathways explain why an O3 layer is present, why it is located at that particular altitude and what the different processes forming the near-surface and middle atmosphere O3 maxima are. Furthermore, we show that the Martian atmosphere can be divided into two chemically distinct regions according to the O(3P):O3 ratio. In the lower region (below approximately 24 km altitude) O3 is the most abundant Ox (= O3 + O(3P)) species. In the upper region (above approximately 24 km altitude), where the O3 layer is located, O(3P) is the most abundant Ox species. Earlier results concerning the formation of O3 on Mars can now be explained with the help of chemical pathways leading to a better understanding of the vertical O3 profile.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , NonPeerReviewed
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  • 8
    Publication Date: 2016-10-26
    Repository Name: EPIC Alfred Wegener Institut
    Type: Conference , NonPeerReviewed
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  • 9
    Publication Date: 2016-10-26
    Repository Name: EPIC Alfred Wegener Institut
    Type: Conference , NonPeerReviewed
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  • 10
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    Munich: Center for Economic Studies and Ifo Institute (CESifo)
    Publication Date: 2016-02-23
    Description: Least-squares estimates of the response of gasoline consumption to a change in the gasoline price are biased toward zero, given the endogeneity of gasoline prices. A seemingly natural solution to this problem is to instrument for gasoline prices using gasoline taxes, but this approach tends to yield implausibly large price elasticities. We demonstrate that anticipatory behavior provides an important explanation for this result. Gasoline buyers increase purchases before tax increases and delay purchases before tax decreases, rendering the tax instrument endogenous. Including suitable leads and lags in the regression restores the validity of the IV estimator, resulting in much lower elasticity estimates.
    Keywords: ddc:330 ; IV ; price elasticity of demand ; gasoline ; anticipation ; intertemporal substitution ; storage
    Repository Name: EconStor: OA server of the German National Library of Economics - Leibniz Information Centre for Economics
    Language: English
    Type: doc-type:workingPaper
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