919 resultados para Geology--Germany--Maps


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We used hyperspectral imaging to study short-term effects of bioturbation by lugworms (Arenicola marina) on the surficial biomass of microphytobenthos (MPB) in permeable marine sediments. Within days to weeks after the addition of a lugworm to a homogenized and recomposed sediment, the average surficial MPB biomass and its spatial heterogeneity were, respectively, 150 - 250% and 280% higher than in sediments without lugworms. The surficial sediment area impacted by a single medium-sized lugworm (~4 g wet weight) over this time-scale was at least 340 cm**2. While sediment reworking was the primary cause of the increased spatial heterogeneity, experiments with lugworm-mimics together with modeling showed that bioadvective porewater transport from depth to the sediment surface, as induced by the lugworm ventilating its burrow, was the main cause of the increased surficial MPB biomass. Although direct measurements of nutrient fluxes are lacking, our present data show that enhanced advective supply of nutrients from deeper sediment layers induced by faunal ventilation is an important mechanism that fuels high primary productivity at the surface of permeable sediments even though these systems are generally characterized by low standing stocks of nutrients and organic material.

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"Classification, cataloging, and care of maps": p. 282-295; "Tentative map classification outline by subject": p. 297-308; "Map classification outline by areas": p. 309-311.

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Self-organizing maps (Kohonen 1997) is a type of artificial neural network developedto explore patterns in high-dimensional multivariate data. The conventional versionof the algorithm involves the use of Euclidean metric in the process of adaptation ofthe model vectors, thus rendering in theory a whole methodology incompatible withnon-Euclidean geometries.In this contribution we explore the two main aspects of the problem:1. Whether the conventional approach using Euclidean metric can shed valid resultswith compositional data.2. If a modification of the conventional approach replacing vectorial sum and scalarmultiplication by the canonical operators in the simplex (i.e. perturbation andpowering) can converge to an adequate solution.Preliminary tests showed that both methodologies can be used on compositional data.However, the modified version of the algorithm performs poorer than the conventionalversion, in particular, when the data is pathological. Moreover, the conventional ap-proach converges faster to a solution, when data is \well-behaved".Key words: Self Organizing Map; Artificial Neural networks; Compositional data

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Starting with logratio biplots for compositional data, which are based on the principle of subcompositional coherence, and then adding weights, as in correspondence analysis, we rediscover Lewi's spectral map and many connections to analyses of two-way tables of non-negative data. Thanks to the weighting, the method also achieves the property of distributional equivalence

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A high-resolution carbon and oxygen isotope analysis of Late Oxfordian-Early Kimmeridgian deep-shelf sediments of southern Germany is combined with investigation of nannofossil assemblage composition and sedimentological interpretations in order to evaluate the impact of regional palaeoenvironmental conditions on isotopic composition of carbonates. This study suggests that carbonate mud was essentially derived from the Jura shallow platform environments and also that the isotopic signature of carbonates deposited in the Swabian Alb deep shelf indirectly expresses the palaeoenvironmental evolution of the platform. Short-term fluctuations in delta(13) C and delta(18)O are probably controlled by changes in salinity (fresh-water input versus evaporation) in platform environments. Long-term fluctuations in carbon and oxygen isotope record throughout the Late Oxfordian-Early Kimmeridgian result from the interplay of increasing temperature and decreasing humidity, which both control the trophic level. Changes from mesotrophic to oligotrophic conditions in platform environments and in the deep-shelf surface waters are inferred. During the Late Oxfordian (Bimammatum Subzone to Planula Zone), the delta(13)C curve displays a positive shift of about 1 parts per thousand, which is comparable in intensity to global perturbations of the carbon cycle. This evident isotopic shift has not been documented yet in other basinal settings. It can be reasonably explained by local palaeoenvironmental changes on the Jura platform (salinity, temperature, and nutrient availability) that controlled platform carbonate production, and the geochemistry of overlying waters. However, increasing carbonate production on the Jura platform and related positive delta(13)C shifts recorded in the Swabian Alb deep shelf are the regional signatures of climatic changes affecting other palaeogeographical domains of Europe in which the carbonate production increased throughout the Late Oxfordian. (C) 2002 Elsevier Science B.V. All rights reserved.

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The purposes of this report are to delineate and describe aquifers in Cerro Gordo County, evaluate the availability and quality of water in the aquifers, supply data on ground-water utilization, and determine the rate of growth and the magnitude of the cone of drawdown in the Mason City area. It includes photos and fold-out maps

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Notice about the geologic and geomorphologic maps of Santa Coloma de Farners, at scale 1:10,000 published by Unitat de Geologia of the Universitat de Girona

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In 1978 University de Girona's Unity of Geodynamics started publishing geological maps, in several themes and scales, of various areas of the Province of Girona (fig. 1). So far, up to 38 maps, gathered in several collections, have been published

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The main task of this work has been to investigate the effects of anisotropy onto the propagation of seismic waves along the Upper Mantle below Germany and adjacent areas. Refraction- and reflexion seismic experiments proved the existence of Upper Mantle anisotropy and its influence onto the propagation of Pn-waves. By the 3D tomographic investigations that have been done here for the crust and the upper mantle, considering the influence of anisotropy, a gap for the investigations in Europe has been closed. These investigations have been done with the SSH-Inversionprogram of Prof. Dr. M. Koch, which is able to compute simultaneously the seismic structure and hypocenters. For the investigation, a dataset has been available with recordings between the years 1975 to 2003 with a total of 60249 P- and 54212 S-phase records of 10028 seismic events. At the beginning, a precise analysis of the residuals (RES, the difference between calculated and observed arrivaltime) has been done which confirmed the existence of anisotropy for Pn-phases. The recognized sinusoidal distribution has been compensated by an extension of the SSH-program by an ellipse with a slow and rectangular fast axis with azimuth to correct the Pn-velocities. The azimuth of the fast axis has been fixed by the application of the simultaneous inversion at 25° - 27° with a variation of the velocities at +- 2.5 about an average value at 8 km/s. This new value differs from the old one at 35°, recognized in the initial residual analysis. This depends on the new computed hypocenters together with the structure. The application of the elliptical correction has resulted in a better fit of the vertical layered 1D-Model, compared to the results of preceding seismological experiments and 1D and 2D investigations. The optimal result of the 1D-inversion has been used as initial starting model for the 3D-inversions to compute the three dimensional picture of the seismic structure of the Crust and Upper Mantle. The simultaneous inversion has showed an optimization of the relocalization of the hypocenters and the reconstruction of the seismic structure in comparison to the geology and tectonic, as described by other investigations. The investigations for the seismic structure and the relocalization have been confirmed by several different tests. First, synthetic traveltime data are computed with an anisotropic variation and inverted with and without anisotropic correction. Further, tests with randomly disturbed hypocenters and traveltime data have been proceeded to verify the influence of the initial values onto the relocalization accuracy and onto the seismic structure and to test for a further improvement by the application of the anisotropic correction. Finally, the results of the work have been applied onto the Waldkirch earthquake in 2004 to compare the isotropic and the anisotropic relocalization with the initial optimal one to verify whether there is some improvement.

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Starting with logratio biplots for compositional data, which are based on the principle of subcompositional coherence, and then adding weights, as in correspondence analysis, we rediscover Lewi's spectral map and many connections to analyses of two-way tables of non-negative data. Thanks to the weighting, the method also achieves the property of distributional equivalence

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Self-organizing maps (Kohonen 1997) is a type of artificial neural network developed to explore patterns in high-dimensional multivariate data. The conventional version of the algorithm involves the use of Euclidean metric in the process of adaptation of the model vectors, thus rendering in theory a whole methodology incompatible with non-Euclidean geometries. In this contribution we explore the two main aspects of the problem: 1. Whether the conventional approach using Euclidean metric can shed valid results with compositional data. 2. If a modification of the conventional approach replacing vectorial sum and scalar multiplication by the canonical operators in the simplex (i.e. perturbation and powering) can converge to an adequate solution. Preliminary tests showed that both methodologies can be used on compositional data. However, the modified version of the algorithm performs poorer than the conventional version, in particular, when the data is pathological. Moreover, the conventional ap- proach converges faster to a solution, when data is \well-behaved". Key words: Self Organizing Map; Artificial Neural networks; Compositional data