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Institute
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Die Phyllosphäre
(2015)
Analysis and modeling of transient earthquake patterns and their dependence on local stress regimes
(2015)
Investigations in the field of earthquake triggering and associated interactions, which includes aftershock triggering as well as induced seismicity, is important for seismic hazard assessment due to earthquakes destructive power. One of the approaches to study earthquake triggering and their interactions is the use of statistical earthquake models, which are based on knowledge of the basic seismicity properties, in particular, the magnitude distribution and spatiotemporal properties of the triggered events.
In my PhD thesis I focus on some specific aspects of aftershock properties, namely, the relative seismic moment release of the aftershocks with respect to the mainshocks; the spatial correlation between aftershock occurrence and fault deformation; and on the influence of aseismic transients on the aftershock parameter estimation. For the analysis of aftershock sequences I choose a statistical approach, in particular, the well known Epidemic Type Aftershock Sequence (ETAS) model, which accounts for the input of background and triggered seismicity. For my specific purposes, I develop two ETAS model modifications in collaboration with Sebastian Hainzl. By means of this approach, I estimate the statistical aftershock parameters and performed simulations of aftershock sequences as well.
In the case of seismic moment release of aftershocks, I focus on the ratio of cumulative seismic moment release with respect to the mainshocks. Specifically, I investigate the ratio with respect to the focal mechanism of the mainshock and estimate an effective magnitude, which represents the cumulative aftershock energy (similar to Bath's law, which defines the average difference between mainshock and the largest aftershock magnitudes). Furthermore, I compare the observed seismic moment ratios with the results of the ETAS simulations. In particular, I test a restricted ETAS (RETAS) model which is based on results of a clock advanced model and static stress triggering.
To analyze spatial variations of triggering parameters I focus in my second approach on the aftershock occurrence triggered by large mainshocks and the study of the aftershock parameter distribution and their spatial correlation with the coseismic/postseismic slip and interseismic locking. To invert the aftershock parameters I improve the modified ETAS (m-ETAS) model, which is able to take the extension of the mainshock rupture into account. I compare the results obtained by the classical approach with the output of the m-ETAS model.
My third approach is concerned with the temporal clustering of seismicity, which might not only be related to earthquake-earthquake interactions, but also to a time-dependent background rate, potentially biasing the parameter estimations. Thus, my coauthors and I also applied a modification of the ETAS model, which is able to take into account time-dependent background activity. It can be applicable for two different cases: when an aftershock catalog has a temporal incompleteness or when the background seismicity rate changes with time, due to presence of aseismic forces.
An essential part of any research is the testing of the developed models using observational data sets, which are appropriate for the particular study case. Therefore, in the case of seismic moment release I use the global seismicity catalog. For the spatial distribution of triggering parameters I exploit two aftershock sequences of the Mw8.8 2010 Maule (Chile) and Mw 9.0 2011 Tohoku (Japan) mainshocks. In addition, I use published geodetic slip models of different authors. To test our ability to detect aseismic transients my coauthors and I use the data sets from Western Bohemia (Central Europe) and California.
Our results indicate that:
(1) the seismic moment of aftershocks with respect to mainshocks depends on the static stress changes and is maximal for the normal, intermediate for thrust and minimal for strike-slip stress regimes, where the RETAS model shows a good correspondence with the results;
(2) The spatial distribution of aftershock parameters, obtained by the m-ETAS model, shows anomalous values in areas of reactivated crustal fault systems. In addition, the aftershock density is found to be correlated with coseismic slip gradient, afterslip, interseismic coupling and b-values. Aftershock seismic moment is positively correlated with the areas of maximum coseismic slip and interseismically locked areas. These correlations might be related to the stress level or to material properties variations in space;
(3) Ignoring aseismic transient forcing or temporal catalog incompleteness can lead to the significant under- or overestimation of the underlying trigger parameters. In the case when a catalog is complete, this method helps to identify aseismic sources.
In many procedures of seismic risk mitigation, ground motion simulations are needed to test systems or improve their effectiveness. For example they may be used to estimate the level of ground shaking caused by future earthquakes. Good physical models for ground motion simulation are also thought to be important for hazard assessment, as they could close gaps in the existing datasets. Since the observed ground motion in nature shows a certain variability, part of which cannot be explained by macroscopic parameters such as magnitude or position of an earthquake, it would be desirable that a good physical model is not only able to produce one single seismogram, but also to reveal this natural variability.
In this thesis, I develop a method to model realistic ground motions in a way that is computationally simple to handle, permitting multiple scenario simulations. I focus on two aspects of ground motion modelling. First, I use deterministic wave propagation for the whole frequency range – from static deformation to approximately 10 Hz – but account for source variability by implementing self-similar slip distributions and rough fault interfaces. Second, I scale the source spectrum so that the modelled waveforms represent the correct radiated seismic energy. With this scaling I verify whether the energy magnitude is suitable as an explanatory variable, which characterises the amount of energy radiated at high frequencies – the advantage of the energy magnitude being that it can be deduced from observations, even in real-time.
Applications of the developed method for the 2008 Wenchuan (China) earthquake, the 2003 Tokachi-Oki (Japan) earthquake and the 1994 Northridge (California, USA) earthquake show that the fine source discretisations combined with the small scale source variability ensure that high frequencies are satisfactorily introduced, justifying the deterministic wave propagation approach even at high frequencies. I demonstrate that the energy magnitude can be used to calibrate the high-frequency content in ground motion simulations.
Because deterministic wave propagation is applied to the whole frequency range, the simulation method permits the quantification of the variability in ground motion due to parametric uncertainties in the source description. A large number of scenario simulations for an M=6 earthquake show that the roughness of the source as well as the distribution of fault dislocations have a minor effect on the simulated variability by diminishing directivity effects, while hypocenter location and rupture velocity more strongly influence the variability. The uncertainty in energy magnitude, however, leads to the largest differences of ground motion amplitude between different events, resulting in a variability which is larger than the one observed.
For the presented approach, this dissertation shows (i) the verification of the computational correctness of the code, (ii) the ability to reproduce observed ground motions and (iii) the validation of the simulated ground motion variability. Those three steps are essential to evaluate the suitability of the method for means of seismic risk mitigation.
Methicillin resistant Staphylococcus aureus (MRSA) is one of the most important antibiotic-resistant pathogens in hospitals and the community. Recently, a new generation of MRSA, the so called livestock associated (LA) MRSA, has emerged occupying food producing animals as a new niche. LA-MRSA can be regularly isolated from economically important live-stock species including corresponding meats. The present thesis takes a methodological approach to confirm the hypothesis that LA-MRSA are transmitted along the pork, poultry and beef production chain from animals at farm to meat on consumers` table. Therefore two new concepts were developed, adapted to differing data sets.
A mathematical model of the pig slaughter process was developed which simulates the change in MRSA carcass prevalence during slaughter with special emphasis on identifying critical process steps for MRSA transmission. Based on prevalences as sole input variables the model framework is able to estimate the average value range of both the MRSA elimination and contamination rate of each of the slaughter steps. These rates are then used to set up a Monte Carlo simulation of the slaughter process chain. The model concludes that regardless of the initial extent of MRSA contamination low outcome prevalences ranging between 0.15 and 1.15 % can be achieved among carcasses at the end of slaughter. Thus, the model demonstrates that the standard procedure of pig slaughtering in principle includes process steps with the capacity to limit MRSA cross contamination. Scalding and singeing were identified as critical process steps for a significant reduction of superficial MRSA contamination.
In the course of the German national monitoring program for zoonotic agents MRSA prevalence and typing data are regularly collected covering the key steps of different food production chains. A new statistical approach has been proposed for analyzing this cross sectional set of MRSA data with regard to show potential farm to fork transmission. For this purpose, chi squared statistics was combined with the calculation of the Czekanowski similarity index to compare the distributions of strain specific characteristics between the samples from farm, carcasses after slaughter and meat at retail. The method was implemented on the turkey and veal production chains and the consistently high degrees of similarity which have been revealed between all sample pairs indicate MRSA transmission along the chain.
As the proposed methods are not specific to process chains or pathogens they offer a broad field of application and extend the spectrum of methods for bacterial transmission assessment.
In den letzten Jahrzehnten ist der Trend der Verselbstständigung in vielen Kommunen zu beobachten. Ein Großteil der öffentlichen Leistungserbringer wird mittlerweile als privatrechtliche Gesellschaften in einem wettbewerbsorientierten Umfeld geführt. Während viele Forscher Ausgliederungen in Form von nachgeordneten Behörden auf Bundesebene untersuchen und diese Reformwelle als einen faktischen Autonomisierungsprozess beschreiben, gibt es nur einige wenige Studien, die sich explizit mit den Autonomisierungstendenzen auf Kommunalebene auseinandersetzen. Daher fehlt es an empirischen Erkenntnissen zur Steuerung der kommunalen Beteiligungen.
In dieser Arbeit werden die Steuerungsarrangements deutscher Großstädte erstmals aus Sicht der Gesteuerten beleuchtet. Das Untersuchungsziel der vorliegenden Forschungsarbeit besteht darin, Flexibilisierungstendenzen in mehrheitlich kommunalen Unternehmen zu identifizieren und hierfür Erklärungsfaktoren zu identifizieren. Die Forschungsfrage lautet: Welche instrumentellen und relationalen Faktoren beeinflussen die Managementautonomie in kommunalen Mehrheitsbeteiligungen?
Dabei interessiert insbesondere die Einflussnahme der Kommunen auf verschiedene Tätigkeitsbereiche ihrer Ausgliederungen. Über diese unternehmensspezifischen Sachverhalte ist in Deutschland fast nichts und international nur sehr wenig Empirisches bekannt. Zur Beantwortung der Forschungsfrage hat der Autor auf Basis der Transaktionskosten- und der Social-Exchange-Theorie einen Analyserahmen erstellt. Die aufgestellten Hypothesen wurden mit einer großflächigen Umfrage bei 243 Unternehmen in den 39 größten deutschen Städten empirisch getestet.
Im Ergebnis zeigen sich mehrere empirische Erkenntnisse: Erstens konnten mittels Faktorenanalyse vier unabhängige Faktoren von Managementautonomie in kommunalen Unternehmen identifiziert werden: Personalautonomie, Generelles Management, Preisautonomie und Strategische Fragen. Während die Kommunen ihren Beteiligungen einen hohen Grad an Personalautonomie zugestehen, unterliegen vor allem strategische Investitionsentscheidungen wie die finanzielle Beteiligung an Tochterfirmen, große Projektvorhaben, Diversifikationsentscheidungen oder Kreditautfnahmen einem starken politischen Einfluss.
Zweitens führt eine Rechtsformänderung und die Platzierung in einem Wettbewerbsumfeld (auch bekannt als Corporatisation) vor allem zu einer größeren Flexibilisierung der Personal- und Preispolitik, wirkt sich allerdings wenig auf die weiteren Faktoren der Managementautonomie, Generelles Management und Strategische Entscheidungen, aus. Somit behalten die Kommunen ihre Möglichkeit, auf wichtige Unternehmensfragen der Beteiligung Einfluss zu nehmen, auch im Fall einer Formalprivatisierung bei.
Letztlich können zur Erklärung der Autonomiefaktoren transaktionskostenbasierte und relationale Faktoren ergänzend herangezogen werden. In den Transaktionsspezifika wirken vor allem der wahrgenommene Wettbewerb in der Branche, die Messbarkeit der Leistung, Branchenvariablen, die Anzahl der Politiker im Aufsichtsrat und die eingesetzten Steuerungsmechanismen. In den relationalen Faktoren setzen sich die Variablen gegenseitiges Vertrauen, Effektivität der Aufsichtsräte, Informationsaustausch, Rollenkonflikte, Rollenambivalenzen und Geschäftsführererfahrung im Sektor durch.