@phdthesis{Arend2024,
  author    = {Arend, Marius},
  title     = {Comparing genome-scale models of protein-constrained metabolism in heterotrophic and photosynthetic microorganisms},
  doi       = {10.25932/publishup-65147},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-651470},
  school      = {Universit{\"a}t Potsdam},
  pages     = {150},
  year      = {2024},
  abstract  = {Genome-scale metabolic models are mathematical representations of all known reactions occurring in a cell. Combined with constraints based on physiological measurements, these models have been used to accurately predict metabolic fluxes and effects of perturbations (e.g. knock-outs) and to inform metabolic engineering strategies. Recently, protein-constrained models have been shown to increase predictive potential (especially in overflow metabolism), while alleviating the need for measurement of nutrient uptake rates. The resulting modelling frameworks quantify the upkeep cost of a certain metabolic flux as the minimum amount of enzyme required for catalysis. These improvements are based on the use of in vitro turnover numbers or in vivo apparent catalytic rates of enzymes for model parameterization. In this thesis several tools for the estimation and refinement of these parameters based on in vivo proteomics data of Escherichia coli, Saccharomyces cerevisiae, and Chlamydomonas reinhardtii have been developed and applied. The difference between in vitro and in vivo catalytic rate measures for the three microorganisms was systematically analyzed. The results for the facultatively heterotrophic microalga C. reinhardtii considerably expanded the apparent catalytic rate estimates for photosynthetic organisms. Our general finding pointed at a global reduction of enzyme efficiency in heterotrophy compared to other growth scenarios. Independent of the modelled organism, in vivo estimates were shown to improve accuracy of predictions of protein abundances compared to in vitro values for turnover numbers. To further improve the protein abundance predictions, machine learning models were trained that integrate features derived from protein-constrained modelling and codon usage. Combining the two types of features outperformed single feature models and yielded good prediction results without relying on experimental transcriptomic data. The presented work reports valuable advances in the prediction of enzyme allocation in unseen scenarios using protein constrained metabolic models. It marks the first successful application of this modelling framework in the biotechnological important taxon of green microalgae, substantially increasing our knowledge of the enzyme catalytic landscape of phototrophic microorganisms.},
  language  = {en}
}
@phdthesis{Aue2024,
  author    = {Aue, Lars},
  title     = {Cyclone impacts on sea ice in the Atlantic Arctic Ocean},
  doi       = {10.25932/publishup-63445},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-634458},
  school      = {Universit{\"a}t Potsdam},
  pages     = {VIII, 131},
  year      = {2024},
  abstract  = {The Arctic is the hot spot of the ongoing, global climate change. Over the last decades, near-surface temperatures in the Arctic have been rising almost four times faster than on global average. This amplified warming of the Arctic and the associated rapid changes of its environment are largely influenced by interactions between individual components of the Arctic climate system. On daily to weekly time scales, storms can have major impacts on the Arctic sea-ice cover and are thus an important part of these interactions within the Arctic climate. The sea-ice impacts of storms are related to high wind speeds, which enhance the drift and deformation of sea ice, as well as to changes in the surface energy budget in association with air mass advection, which impact the seasonal sea-ice growth and melt. The occurrence of storms in the Arctic is typically associated with the passage of transient cyclones. Even though the above described mechanisms how storms/cyclones impact the Arctic sea ice are in principal known, there is a lack of statistical quantification of these effects. In accordance with that, the overarching objective of this thesis is to statistically quantify cyclone impacts on sea-ice concentration (SIC) in the Atlantic Arctic Ocean over the last four decades. In order to further advance the understanding of the related mechanisms, an additional objective is to separate dynamic and thermodynamic cyclone impacts on sea ice and assess their relative importance. Finally, this thesis aims to quantify recent changes in cyclone impacts on SIC. These research objectives are tackled utilizing various data sets, including atmospheric and oceanic reanalysis data as well as a coupled model simulation and a cyclone tracking algorithm. Results from this thesis demonstrate that cyclones are significantly impacting SIC in the Atlantic Arctic Ocean from autumn to spring, while there are mostly no significant impacts in summer. The strength and the sign (SIC decreasing or SIC increasing) of the cyclone impacts strongly depends on the considered daily time scale and the region of the Atlantic Arctic Ocean. Specifically, an initial decrease in SIC (day -3 to day 0 relative to the cyclone) is found in the Greenland, Barents and Kara Seas, while SIC increases following cyclones (day 0 to day 5 relative to the cyclone) are mostly limited to the Barents and Kara Seas. For the cold season, this results in a pronounced regional difference between overall (day -3 to day 5 relative to the cyclone) SIC-decreasing cyclone impacts in the Greenland Sea and overall SIC-increasing cyclone impacts in the Barents and Kara Seas. A cyclone case study based on a coupled model simulation indicates that both dynamic and thermodynamic mechanisms contribute to cyclone impacts on sea ice in winter. A typical pattern consisting of an initial dominance of dynamic sea-ice changes followed by enhanced thermodynamic ice growth after the cyclone passage was found. This enhanced ice growth after the cyclone passage most likely also explains the (statistical) overall SIC-increasing effects of cyclones in the Barents and Kara Seas in the cold season. Significant changes in cyclone impacts on SIC over the last four decades have emerged throughout the year. These recent changes are strongly varying from region to region and month to month. The strongest trends in cyclone impacts on SIC are found in autumn in the Barents and Kara Seas. Here, the magnitude of destructive cyclone impacts on SIC has approximately doubled over the last four decades. The SIC-increasing effects following the cyclone passage have particularly weakened in the Barents Sea in autumn. As a consequence, previously existing overall SIC-increasing cyclone impacts in this region in autumn have recently disappeared. Generally, results from this thesis show that changes in the state of the sea-ice cover (decrease in mean sea-ice concentration and thickness) and near-surface air temperature are most important for changed cyclone impacts on SIC, while changes in cyclone properties (i.e. intensity) do not play a significant role.},
  language  = {en}
}
@article{Berkovich2024,
  author    = {Berkovich, Ilya},
  title     = {Jewish Mercenaries in Habsburg Service},
  series = {PaRDeS},
  journal   = {PaRDeS},
  number    = {29},
  publisher = {Universit{\"a}tsverlag Potsdam},
  address   = {Potsdam},
  isbn      = {978-3-86956-574-3},
  issn      = {1614-6492},
  doi       = {10.25932/publishup-65023},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-650239},
  pages     = {69 -- 79},
  year      = {2024},
  abstract  = {This article aims to demonstrate the exceptional potential of Habsburg military records for the study of Jewish history during Europe's Age of Revolution. We begin with the random discovery of six Jewish veterans of Freikorps Gr{\"u}n Loudon - a unit of mercenary freebooters - which fought for the Habsburgs during the first war against the French Republic (1792 - 97). A careful re-reading of the available archival evidence reveals that these men were the survivors of a much larger group numbering at least two dozen Jewish soldiers. While Jewish conscripts had been drafted into the Habsburg army since 1788, the fact that Jews could also serve - even volunteer - as professional soldiers in that period is completely new to us. When considered together, the personal circumstances and service experiences of the Jewish soldiers of Freikorps Gr{\"u}n Loudon enable us to make several observations about their motivation as well as their position vis-{\`a}-vis their non-Jewish comrades.},
  language  = {en}
}
@techreport{BorckMulder2024,
  type      = {Working Paper},
  author    = {Borck, Rainald and Mulder, Peter},
  title     = {Energy policies and pollution in two developing country cities},
  series = {CEPA Discussion Papers},
  journal   = {CEPA Discussion Papers},
  number    = {78},
  issn      = {2628-653X},
  doi       = {10.25932/publishup-63847},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-638472},
  pages     = {37},
  year      = {2024},
  abstract  = {We study the effect of energy and transport policies on pollution in two developing country cities. We use a quantitative equilibrium model with choice of housing, energy use, residential location, transport mode, and energy technology. Pollution comes from commuting and residential energy use. The model parameters are calibrated to replicate key variables for two developing country cities, Maputo, Mozambique, and Yogyakarta, Indonesia. In the counterfactual simulations, we study how various transport and energy policies affect equilibrium pollution. Policies may be induce rebound effects from increasing residential energy use or switching to high emission modes or locations. In general, these rebound effects tend to be largest for subsidies to public transport or modern residential energy technology.},
  language  = {en}
}
@techreport{BruttelEisenkopfNithammer2024,
  type      = {Working Paper},
  author    = {Bruttel, Lisa Verena and Eisenkopf, Gerald and Nithammer, Juri},
  title     = {Pre-election communication in public good games with endogenous leaders},
  series = {CEPA Discussion Papers},
  journal   = {CEPA Discussion Papers},
  number    = {73},
  issn      = {2628-653X},
  doi       = {10.25932/publishup-62395},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-623952},
  pages     = {28},
  year      = {2024},
  abstract  = {Leadership plays an important role for the efficient and fair solution of social dilemmas but the effectiveness of a leader can vary substantially. Two main factors of leadership impact are the ability to induce high contributions by all group members and the (expected) fair use of power. Participants in our experiment decide about contributions to a public good. After all contributions are made, the leader can choose how much of the joint earnings to assign to herself; the remainder is distributed equally among the followers. Using machine learning techniques, we study whether the content of initial open statements by the group members predicts their behavior as a leader and whether groups are able to identify such clues and endogenously appoint a "good" leader to solve the dilemma. We find that leaders who promise fairness are more likely to behave fairly, and that followers appoint as leaders those who write more explicitly about fairness and efficiency. However, in their contribution decision, followers focus on the leader's first-move contribution and place less importance on the content of the leader's statements.},
  language  = {en}
}
@phdthesis{Bryant2024,
  author    = {Bryant, Seth},
  title     = {Aggregation and disaggregation in flood risk models},
  doi       = {10.25932/publishup-65095},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-650952},
  school      = {Universit{\"a}t Potsdam},
  pages     = {ix, 116},
  year      = {2024},
  abstract  = {Floods continue to be the leading cause of economic damages and fatalities among natural disasters worldwide. As future climate and exposure changes are projected to intensify these damages, the need for more accurate and scalable flood risk models is rising. Over the past decade, macro-scale flood risk models have evolved from initial proof-of-concepts to indispensable tools for decision-making at global-, nationaland, increasingly, the local-level. This progress has been propelled by the advent of high-performance computing and the availability of global, space-based datasets. However, despite such advancements, these models are rarely validated and consistently fall short of the accuracy achieved by high-resolution local models. While capabilities have improved, significant gaps persist in understanding the behaviours of such macro-scale models, particularly their tendency to overestimate risk. This dissertation aims to address such gaps by examining the scale transfers inherent in the construction and application of coarse macroscale models. To achieve this, four studies are presented that, collectively, address exposure, hazard, and vulnerability components of risk affected by upscaling or downscaling. The first study focuses on a type of downscaling where coarse flood hazard inundation grids are enhanced to a finer resolution. While such inundation downscaling has been employed in numerous global model chains, ours is the first study to focus specifically on this component, providing an evaluation of the state of the art and a novel algorithm. Findings demonstrate that our novel algorithm is eight times faster than existing methods, offers a slight improvement in accuracy, and generates more physically coherent flood maps in hydraulically challenging regions. When applied to a case study, the algorithm generated a 4m resolution inundation map from 30m hydrodynamic model outputs in 33 s, a 60-fold improvement in runtime with a 25\% increase in RMSE compared with direct hydrodynamic modelling. All evaluated downscaling algorithms yielded better accuracy than the coarse hydrodynamic model when compared to observations, demonstrating similar limits of coarse hydrodynamic models reported by others. The substitution of downscaling into flood risk model chains, in place of high-resolution modelling, can drastically improve the lead time of impactbased forecasts and the efficiency of hazard map production. With downscaling, local regions could obtain high resolution local inundation maps by post-processing a global model without the need for expensive modelling or expertise. The second study focuses on hazard aggregation and its implications for exposure, investigating implicit aggregations commonly used to intersect hazard grids with coarse exposure models. This research introduces a novel spatial classification framework to understand the effects of rescaling flood hazard grids to a coarser resolution. The study derives closed-form analytical solutions for the location and direction of bias from flood grid aggregation, showing that bias will always be present in regions near the edge of inundation. For example, inundation area will be positively biased when water depth grids are aggregated, while volume will be negatively biased when water elevation grids are aggregated. Extending the analysis to effects of hazard aggregation on building exposure, this study shows that exposure in regions at the edge of inundation are an order of magnitude more sensitive to aggregation errors than hazard alone. Among the two aggregation routines considered, averaging water surface elevation grids better preserved flood depths at buildings than averaging of water depth grids. The study provides the first mathematical proof and generalizeable treatment of flood hazard grid aggregation, demonstrating important mechanisms to help flood risk modellers understand and control model behaviour. The final two studies focus on the aggregation of vulnerability models or flood damage functions, investigating the practice of applying per-asset functions to aggregate exposure models. Both studies extend Jensen's inequality, a well-known 1906 mathematical proof, to demonstrate how the aggregation of flood damage functions leads to bias. Applying Jensen's proof in this new context, results show that typically concave flood damage functions will introduce a positive bias (overestimation) when aggregated. This behaviour was further investigated with a simulation experiment including 2 million buildings in Germany, four global flood hazard simulations and three aggregation scenarios. The results show that positive aggregation bias is not distributed evenly in space, meaning some regions identified as "hot spots of risk" in assessments may in fact just be hot spots of aggregation bias. This study provides the first application of Jensen's inequality to explain the overestimates reported elsewhere and advice for modellers to minimize such artifacts. In total, this dissertation investigates the complex ways aggregation and disaggregation influence the behaviour of risk models, focusing on the scale-transfers underpinning macro-scale flood risk assessments. Extending a key finding of the flood hazard literature to the broader context of flood risk, this dissertation concludes that all else equal, coarse models overestimate risk. This dissertation goes beyond previous studies by providing mathematical proofs for how and where such bias emerges in aggregation routines, offering a mechanistic explanation for coarse model overestimates. It shows that this bias is spatially heterogeneous, necessitating a deep understanding of how rescaling may bias models to effectively reduce or communicate uncertainties. Further, the dissertation offers specific recommendations to help modellers minimize scale transfers in problematic regions. In conclusion, I argue that such aggregation errors are epistemic, stemming from choices in model structure, and therefore hold greater potential and impetus for study and mitigation. This deeper understanding of uncertainties is essential for improving macro-scale flood risk models and their effectiveness in equitable, holistic, and sustainable flood management.},
  language  = {en}
}
@article{CorbettSiegelThulin2024,
  author    = {Corbett, Tim and Siegel, Bj{\"o}rn and Thulin, Mirjam},
  title     = {Towards Pluricultural and Connected Histories},
  series = {PaRDeS},
  journal   = {PaRDeS},
  number    = {29},
  publisher = {Universit{\"a}tsverlag Potsdam},
  address   = {Potsdam},
  isbn      = {978-3-86956-574-3},
  issn      = {1614-6492},
  doi       = {10.25932/publishup-64598},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-645988},
  pages     = {15 -- 27},
  year      = {2024},
  language  = {en}
}
@article{Csaky2024,
  author    = {Cs{\´a}ky, Moritz},
  title     = {Habsburg Central Europe},
  series = {PaRDeS},
  journal   = {PaRDeS},
  number    = {29},
  publisher = {Universit{\"a}tsverlag Potsdam},
  address   = {Potsdam},
  isbn      = {978-3-86956-574-3},
  issn      = {1614-6492},
  doi       = {10.25932/publishup-64599},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-645995},
  pages     = {31 -- 37},
  year      = {2024},
  abstract  = {Central Europe is characterized by linguistic and cultural density as well as by endogenous and exogenous cultural influences. These constellations were especially visible in the former Habsburg Empire, where they influenced the formation of individual and collective identities. This led not only to continual crises and conflicts, but also to an equally enormous creative potential as became apparent in the culture of the fin-de-si{\`e}cle.},
  language  = {en}
}
@article{Czakai2024,
  author    = {Czakai, Johannes},
  title     = {Between Legibility, Emancipation, and Markers of "Otherness"},
  series = {PaRDeS},
  journal   = {PaRDeS},
  number    = {29},
  publisher = {Universit{\"a}tsverlag Potsdam},
  address   = {Potsdam},
  isbn      = {978-3-86956-574-3},
  issn      = {1614-6492},
  doi       = {10.25932/publishup-65024},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-650249},
  pages     = {81 -- 89},
  year      = {2024},
  abstract  = {The article analyzes the interdependences between the history of the Habsburg Empire and the names of its Jewish inhabitants. Until today, these names tell stories about this close relationship and they are an everlasting symbol of this era. By focusing on names, this paper shows how state policies towards Jews shifted over time, and how the perspective on names and name regulations can be a tool to connect and investigate both Habsburg and Jewish studies.},
  language  = {en}
}
@phdthesis{Damseaux2024,
  author    = {Damseaux, Adrien},
  title     = {Improving permafrost dynamics in land surface models: insights from dual sensitivity experiments},
  doi       = {10.25932/publishup-63945},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-639450},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xiii, 143},
  year      = {2024},
  abstract  = {The thawing of permafrost and the subsequent release of greenhouse gases constitute one of the most significant and uncertain positive feedback loops in the context of climate change, making predictions regarding changes in permafrost coverage of paramount importance. To address these critical questions, climate scientists have developed Land Surface Models (LSMs) that encompass a multitude of physical soil processes. This thesis is committed to advancing our understanding and refining precise representations of permafrost dynamics within LSMs, with a specific focus on the accurate modeling of heat fluxes, an essential component for simulating permafrost physics. The first research question overviews fundamental model prerequisites for the representation of permafrost soils within land surface modeling. It includes a first-of-its-kind comparison between LSMs in CMIP6 to reveal their differences and shortcomings in key permafrost physics parameters. Overall, each of these LSMs represents a unique approach to simulating soil processes and their interactions with the climate system. Choosing the most appropriate model for a particular application depends on factors such as the spatial and temporal scale of the simulation, the specific research question, and available computational resources. The second research question evaluates the performance of the state-of-the-art Community Land Model (CLM5) in simulating Arctic permafrost regions. Our approach overcomes traditional evaluation limitations by individually addressing depth, seasonality, and regional variations, providing a comprehensive assessment of permafrost and soil temperature dynamics. I compare CLM5's results with three extensive datasets: (1) soil temperatures from 295 borehole stations, (2) active layer thickness (ALT) data from the Circumpolar Active Layer Monitoring Network (CALM), and (3) soil temperatures, ALT, and permafrost extent from the ESA Climate Change Initiative (ESA-CCI). The results show that CLM5 aligns well with ESA-CCI and CALM for permafrost extent and ALT but reveals a significant global cold temperature bias, notably over Siberia. These results echo a persistent challenge identified in numerous studies: the existence of a systematic 'cold bias' in soil temperature over permafrost regions. To address this challenge, the following research questions propose dual sensitivity experiments. The third research question represents the first study to apply a Plant Functional Type (PFT)-based approach to derive soil texture and soil organic matter (SOM), departing from the conventional use of coarse-resolution global data in LSMs. This novel method results in a more uniform distribution of soil organic matter density (OMD) across the domain, characterized by reduced OMD values in most regions. However, changes in soil texture exhibit a more intricate spatial pattern. Comparing the results to observations reveals a significant reduction in the cold bias observed in the control run. This method shows noticeable improvements in permafrost extent, but at the cost of an overestimation in ALT. These findings emphasize the model's high sensitivity to variations in soil texture and SOM content, highlighting the crucial role of soil composition in governing heat transfer processes and shaping the seasonal variation of soil temperatures in permafrost regions. Expanding upon a site experiment conducted in Trail Valley Creek by \citet{dutch_impact_2022}, the fourth research question extends the application of the snow scheme proposed by \citet{sturm_thermal_1997} to cover the entire Arctic domain. By employing a snow scheme better suited to the snow density profile observed over permafrost regions, this thesis seeks to assess its influence on simulated soil temperatures. Comparing this method to observational datasets reveals a significant reduction in the cold bias that was present in the control run. In most regions, the Sturm run exhibits a substantial decrease in the cold bias. However, there is a distinctive overshoot with a warm bias observed in mountainous areas. The Sturm experiment effectively addressed the overestimation of permafrost extent in the control run, albeit resulting in a substantial reduction in permafrost extent over mountainous areas. ALT results remain relatively consistent compared to the control run. These outcomes align with our initial hypothesis, which anticipated that the reduced snow insulation in the Sturm run would lead to higher winter soil temperatures and a more accurate representation of permafrost physics. In summary, this thesis demonstrates significant advancements in understanding permafrost dynamics and its integration into LSMs. It has meticulously unraveled the intricacies involved in the interplay between heat transfer, soil properties, and snow dynamics in permafrost regions. These insights offer novel perspectives on model representation and performance.},
  language  = {en}
}