@phdthesis{Khawaja2023, author = {Khawaja, Muhammad Asim}, title = {Improving earthquake forecast modeling and testing using the multi-resolution grids}, school = {Universit{\"a}t Potsdam}, pages = {107}, year = {2023}, language = {en} } @phdthesis{Ribacki2023, author = {Ribacki, Enrico}, title = {Intra-granitic pegmatites of the Las Chacras-Potrerillos batholith, Argentina}, school = {Universit{\"a}t Potsdam}, pages = {XVIII, 183}, year = {2023}, language = {en} } @phdthesis{DokhtDolatabadiEsfahani2022, author = {Dokht Dolatabadi Esfahani, Reza}, title = {Time-dependent monitoring of near-surface and ground motion modelling: developing new data processing approaches based on Music Information Retrieval (MIR) strategies}, doi = {10.25932/publishup-56767}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-567671}, school = {Universit{\"a}t Potsdam}, pages = {xiv, 107}, year = {2022}, abstract = {Seismology, like many scientific fields, e.g., music information retrieval and speech signal pro- cessing, is experiencing exponential growth in the amount of data acquired by modern seismo- logical networks. In this thesis, I take advantage of the opportunities offered by "big data" and by the methods developed in the areas of music information retrieval and machine learning to predict better the ground motion generated by earthquakes and to study the properties of the surface layers of the Earth. In order to better predict seismic ground motions, I propose two approaches based on unsupervised deep learning methods, an autoencoder network and Generative Adversarial Networks. The autoencoder technique explores a massive amount of ground motion data, evaluates the required parameters, and generates synthetic ground motion data in the Fourier amplitude spectra (FAS) domain. This method is tested on two synthetic datasets and one real dataset. The application on the real dataset shows that the substantial information contained within the FAS data can be encoded to a four to the five-dimensional manifold. Consequently, only a few independent parameters are required for efficient ground motion prediction. I also propose a method based on Conditional Generative Adversarial Networks (CGAN) for simulating ground motion records in the time-frequency and time domains. CGAN generates the time-frequency domains based on the parameters: magnitude, distance, and shear wave velocities to 30 m depth (VS30). After generating the amplitude of the time-frequency domains using the CGAN model, instead of classical conventional methods that assume the amplitude spectra with a random phase spectrum, the phase of the time-frequency domains is recovered by minimizing the observed and reconstructed spectrograms. In the second part of this dissertation, I propose two methods for the monitoring and characterization of near-surface materials and site effect analyses. I implement an autocorrelation function and an interferometry method to monitor the velocity changes of near-surface materials resulting from the Kumamoto earthquake sequence (Japan, 2016). The observed seismic velocity changes during the strong shaking are due to the non-linear response of the near-surface materials. The results show that the velocity changes lasted for about two months after the Kumamoto mainshock. Furthermore, I used the velocity changes to evaluate the in-situ strain-stress relationship. I also propose a method for assessing the site proxy "VS30" using non-invasive analysis. In the proposed method, a dispersion curve of surface waves is inverted to estimate the shear wave velocity of the subsurface. This method is based on the Dix-like linear operators, which relate the shear wave velocity to the phase velocity. The proposed method is fast, efficient, and stable. All of the methods presented in this work can be used for processing "big data" in seismology and for the analysis of weak and strong ground motion data, to predict ground shaking, and to analyze site responses by considering potential time dependencies and nonlinearities.}, language = {en} } @phdthesis{Schoenfeldt2022, author = {Sch{\"o}nfeldt, Elisabeth}, title = {Giant landslides in Patagonia, Argentina}, pages = {XXII, 156}, year = {2022}, language = {en} } @phdthesis{Zhao2021, author = {Zhao, Xueru}, title = {Palaeoclimate and palaeoenvironment evolution from the last glacial maximum into the early holocene (23-8 ka BP) derived from Lago Grande di Monticchio sediment record (S Italy)}, pages = {123}, year = {2021}, language = {en} } @phdthesis{Hebert2021, author = {H{\´e}bert, Raphaёl}, title = {Investigation of vegetation and terrestrial climate variablity during the holocene}, school = {Universit{\"a}t Potsdam}, pages = {201}, year = {2021}, language = {en} } @phdthesis{Liu2021, author = {Liu, Sisi}, title = {The history of plant diversity change and community assemply a high-altitude and high-latitude ecosystems inferred from sedimentary (ancient) DNA and pollen}, school = {Universit{\"a}t Potsdam}, year = {2021}, language = {en} } @phdthesis{Angelopoulos2020, author = {Angelopoulos, Michael}, title = {Mechanisms of sub-aquatic permafrost evolution in Arctic coastal environments}, school = {Universit{\"a}t Potsdam}, pages = {165}, year = {2020}, abstract = {Subsea permafrost is perennially cryotic earth material that lies offshore. Most submarine permafrost is relict terrestrial permafrost beneath the Arctic shelf seas, was inundated after the last glaciation, and has been warming and thawing ever since. It is a reservoir and confining layer for gas hydrates and has the potential to release greenhouse gases and affect global climate change. Furthermore, subsea permafrost thaw destabilizes coastal infrastructure. While numerous studies focus on its distribution and rate of thaw over glacial timescales, these studies have not been brought together and examined in their entirety to assess rates of thaw beneath the Arctic Ocean. In addition, there is still a large gap in our understanding of sub-aquatic permafrost processes on finer spatial and temporal scales. The degradation rate of subsea permafrost is influenced by the initial conditions upon submergence. Terrestrial permafrost that has already undergone warming, partial thawing or loss of ground ice may react differently to inundation by seawater compared to previously undisturbed ice-rich permafrost. Heat conduction models are sufficient to model the thaw of thick subsea permafrost from the bottom, but few studies have included salt diffusion for top-down chemical degradation in shallow waters characterized by mean annual cryotic conditions on the seabed. Simulating salt transport is critical for assessing degradation rates for recently inundated permafrost, which may accelerate in response to warming shelf waters, a lengthening open water season, and faster coastal erosion rates. In the nearshore zone, degradation rates are also controlled by seasonal processes like bedfast ice, brine injection, seasonal freezing under floating ice conditions and warm freshwater discharge from large rivers. The interplay of all these variables is complex and needs further research. To fill this knowledge gap, this thesis investigates sub-aquatic permafrost along the southern coast of the Bykovsky Peninsula in eastern Siberia. Sediment cores and ground temperature profiles were collected at a freshwater thermokarst lake and two thermokarst lagoons in 2017. At this site, the coastline is retreating, and seawater is inundating various types of permafrost: sections of ice-rich Pleistocene permafrost (Yedoma) cliffs at the coastline alternate with lagoons and lower elevation previously thawed and refrozen permafrost basins (Alases). Electrical resistivity surveys with floating electrodes were carried out to map ice-bearing permafrost and taliks (unfrozen zones in the permafrost, usually formed beneath lakes) along the diverse coastline and in the lagoons. Combined with the borehole data, the electrical resistivity results permit estimation of contemporary ice-bearing permafrost characteristics, distribution, and occasionally, thickness. To conceptualize possible geomorphological and marine evolutionary pathways to the formation of the observed layering, numerical models were applied. The developed model incorporates salt diffusion and seasonal dynamics at the seabed, including bedfast ice. Even along coastlines with mean annual non-cryotic boundary conditions like the Bykovsky Peninsula, the modelling results show that salt diffusion minimizes seasonal freezing of the seabed, leading to faster degradation rates compared to models without salt diffusion. Seasonal processes are also important for thermokarst lake to lagoon transitions because lagoons can generate cold hypersaline conditions underneath the ice cover. My research suggests that ice-bearing permafrost can form in a coastal lagoon environment, even under floating ice. Alas basins, however, may degrade more than twice as fast as Yedoma permafrost in the first several decades of inundation. In addition to a lower ice content compared to Yedoma permafrost, Alas basins may be pre-conditioned with salt from adjacent lagoons. Considering the widespread distribution of thermokarst in the Arctic, its integration into geophysical models and offshore surveys is important to quantify and understand subsea permafrost degradation and aggradation. Through numerical modelling, fieldwork, and a circum-Arctic review of subsea permafrost literature, this thesis provides new insights into sub-aquatic permafrost evolution in saline coastal environments.}, language = {en} } @phdthesis{MogrovejoArias2021, author = {Mogrovejo Arias, Diana Carolina}, title = {Assessment of the frequency and relevance of potentially pathogenic phenotypes in microbial isolates from Arctic environments}, school = {Universit{\"a}t Potsdam}, pages = {125}, year = {2021}, abstract = {The Arctic environments constitute rich and dynamic ecosystems, dominated by microorganisms extremely well adapted to survive and function under severe conditions. A range of physiological adaptations allow the microbiota in these habitats to withstand low temperatures, low water and nutrient availability, high levels of UV radiation, etc. In addition, other adaptations of clear competitive nature are directed at not only surviving but thriving in these environments, by disrupting the metabolism of neighboring cells and affecting intermicrobial communication. Since Arctic microbes are bioindicators which amplify climate alterations in the environment, the Arctic region presents the opportunity to study local microbiota and carry out research about interesting, potentially virulent phenotypes that could be dispersed into other habitats around the globe as a consequence of accelerating climate change. In this context, exploration of Arctic habitats as well as descriptions of the microbes inhabiting them are abundant but microbial competitive strategies commonly associated with virulence and pathogens are rarely reported. In this project, environmental samples from the Arctic region were collected and microorganisms (bacteria and fungi) were isolated. The clinical relevance of these microorganisms was assessed by observing the following virulence markers: ability to grow at a range of temperatures, expression of antimicrobial resistance and production of hemolysins. The aim of this project is to determine the frequency and relevance of these characteristics in an effort to understand microbial adaptations in habitats threatened by climate change. The isolates obtained and described here were able to grow at a range of temperatures, in some cases more than 30 °C higher than their original isolation temperature. A considerable number of them consistently expressed compounds capable of lysing sheep and bovine erythrocytes on blood agar at different incubation temperatures. Ethanolic extracts of these bacteria were able to cause rapid and complete lysis of erythrocyte suspensions and might even be hemolytic when assayed on human blood. In silico analyses showed a variety of resistance elements, some of them novel, against natural and synthetic antimicrobial compounds. In vitro experiments against a number of antimicrobial compounds showed resistance phenotypes belonging to wild-type populations and some non-wild type which clearly denote human influence in the acquisition of antimicrobial resistance. The results of this project demonstrate the presence of virulence-associated factors expressed by microorganisms of natural, non-clinical environments. This study contains some of the first reports, to the best of our knowledge, of hemolytic microbes isolated from the Arctic region. In addition, it provides additional information about the presence and expression of intrinsic and acquired antimicrobial resistance in environmental isolates, contributing to the understanding of the evolution of relevant pathogenic species and opportunistic pathogens. Finally, this study highlights some of the potential risks associated with changes in the polar regions (habitat melting and destruction, ecosystem transition and re-colonization) as important indirect consequences of global warming and altered climatic conditions around the planet.}, language = {en} } @phdthesis{Holm2020, author = {Holm, Stine}, title = {Methanogenic communities and metaplasmidome-encoded functions in permafrost environments exposed to thaw}, school = {Universit{\"a}t Potsdam}, pages = {VI, 243}, year = {2020}, abstract = {This thesis investigates how the permafrost microbiota responds to global warming. In detail, the constraints behind methane production in thawing permafrost were linked to methanogenic activity, abundance and composition. Furthermore, this thesis offers new insights into microbial adaptions to the changing environmental conditions during global warming. This was assesed by investigating the potential ecological relevant functions encoded by plasmid DNA within the permafrost microbiota. Permafrost of both interglacial and glacial origin spanning the Holocene to the late Pleistocene, including Eemian, were studied during long-term thaw incubations. Furthermore, several permafrost cores of different stratigraphy, soil type and vegetation cover were used to target the main constraints behind methane production during short-term thaw simulations. Short- and long-term incubations simulating thaw with and without the addition of substrate were combined with activity measurements, amplicon and metagenomic sequencing of permanently frozen and seasonally thawed active layer. Combined, it allowed to address the following questions. i) What constraints methane production when permafrost thaws and how is this linked to methanogenic activity, abundance and composition? ii) How does the methanogenic community composition change during long-term thawing conditions? iii) Which potential ecological relevant functions are encoded by plasmid DNA in active layer soils? The major outcomes of this thesis are as follows. i) Methane production from permafrost after long-term thaw simulation was found to be constrained mainly by the abundance of methanogens and the archaeal community composition. Deposits formed during periods of warmer temperatures and increased precipitation, (here represented by deposits from the Late Pleistocene of both interstadial and interglacial periods) were found to respond strongest to thawing conditions and to contain an archaeal community dominated by methanogenic archaea (40\% and 100\% of all detected archaea). Methanogenic population size and carbon density were identified as main predictors for potential methane production in thawing permafrost in short-term incubations when substrate was sufficiently available. ii) Besides determining the methanogenic activity after long-term thaw, the paleoenvironmental conditions were also found to influence the response of the methanogenic community composition. Substantial shifts within methanogenic community structure and a drop in diversity were observed in deposits formed during warmer periods, but not in deposits from stadials, when colder and drier conditions occurred. Overall, a shift towards a dominance of hydrogenotrophic methanogens was observed in all samples, except for the oldest interglacial deposits from the Eemian, which displayed a potential dominance of acetoclastic methanogens. The Eemian, which is discussed to serve as an analogue to current climate conditions, contained highly active methanogenic communities. However, all potential limitation of methane production after permafrost thaw, it means methanogenic community structure, methanogenic population size, and substrate pool might be overcome after permafrost had thawed on the long-term. iii) Enrichments with soil from the seasonally thawed active layer revealed that its plasmid DNA ('metaplasmidome') carries stress-response genes. In particular it encoded antibiotic resistance genes, heavy metal resistance genes, cold shock proteins and genes encoding UV-protection. Those are functions that are directly involved in the adaptation of microbial communities to stresses in polar environments. It was further found that metaplasmidomes from the Siberian active layer originate mainly from Gammaproteobacteria. By applying enrichment cultures followed by plasmid DNA extraction it was possible to obtain a higher average contigs length and significantly higher recovery of plasmid sequences than from extracting plasmid sequences from metagenomes. The approach of analyzing 'metaplasmidomes' established in this thesis is therefore suitable for studying the ecological role of plasmids in polar environments in general. This thesis emphasizes that including microbial community dynamics have the potential to improve permafrost-carbon projections. Microbially mediated methane release from permafrost environments may significantly impact future climate change. This thesis identified drivers of methanogenic composition, abundance and activity in thawing permafrost landscapes. Finally, this thesis underlines the importance to study how the current warming Arctic affects microbial communities in order to gain more insight into microbial response and adaptation strategies.}, language = {en} }