@phdthesis{Grimbs2009,
  author    = {Grimbs, Sergio},
  title     = {Towards structure and dynamics of metabolic networks},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-32397},
  school      = {Universit{\"a}t Potsdam},
  year      = {2009},
  abstract  = {This work presents mathematical and computational approaches to cover various aspects of metabolic network modelling, especially regarding the limited availability of detailed kinetic knowledge on reaction rates. It is shown that precise mathematical formulations of problems are needed i) to find appropriate and, if possible, efficient algorithms to solve them, and ii) to determine the quality of the found approximate solutions. Furthermore, some means are introduced to gain insights on dynamic properties of metabolic networks either directly from the network structure or by additionally incorporating steady-state information. Finally, an approach to identify key reactions in a metabolic networks is introduced, which helps to develop simple yet useful kinetic models. The rise of novel techniques renders genome sequencing increasingly fast and cheap. In the near future, this will allow to analyze biological networks not only for species but also for individuals. Hence, automatic reconstruction of metabolic networks provides itself as a means for evaluating this huge amount of experimental data. A mathematical formulation as an optimization problem is presented, taking into account existing knowledge and experimental data as well as the probabilistic predictions of various bioinformatical methods. The reconstructed networks are optimized for having large connected components of high accuracy, hence avoiding fragmentation into small isolated subnetworks. The usefulness of this formalism is exemplified on the reconstruction of the sucrose biosynthesis pathway in Chlamydomonas reinhardtii. The problem is shown to be computationally demanding and therefore necessitates efficient approximation algorithms. The problem of minimal nutrient requirements for genome-scale metabolic networks is analyzed. Given a metabolic network and a set of target metabolites, the inverse scope problem has as it objective determining a minimal set of metabolites that have to be provided in order to produce the target metabolites. These target metabolites might stem from experimental measurements and therefore are known to be produced by the metabolic network under study, or are given as the desired end-products of a biotechological application. The inverse scope problem is shown to be computationally hard to solve. However, I assume that the complexity strongly depends on the number of directed cycles within the metabolic network. This might guide the development of efficient approximation algorithms. Assuming mass-action kinetics, chemical reaction network theory (CRNT) allows for eliciting conclusions about multistability directly from the structure of metabolic networks. Although CRNT is based on mass-action kinetics originally, it is shown how to incorporate further reaction schemes by emulating molecular enzyme mechanisms. CRNT is used to compare several models of the Calvin cycle, which differ in size and level of abstraction. Definite results are obtained for small models, but the available set of theorems and algorithms provided by CRNT can not be applied to larger models due to the computational limitations of the currently available implementations of the provided algorithms. Given the stoichiometry of a metabolic network together with steady-state fluxes and concentrations, structural kinetic modelling allows to analyze the dynamic behavior of the metabolic network, even if the explicit rate equations are not known. In particular, this sampling approach is used to study the stabilizing effects of allosteric regulation in a model of human erythrocytes. Furthermore, the reactions of that model can be ranked according to their impact on stability of the steady state. The most important reactions in that respect are identified as hexokinase, phosphofructokinase and pyruvate kinase, which are known to be highly regulated and almost irreversible. Kinetic modelling approaches using standard rate equations are compared and evaluated against reference models for erythrocytes and hepatocytes. The results from this simplified kinetic models can simulate acceptably the temporal behavior for small changes around a given steady state, but fail to capture important characteristics for larger changes. The aforementioned approach to rank reactions according to their influence on stability is used to identify a small number of key reactions. These reactions are modelled in detail, including knowledge about allosteric regulation, while all other reactions were still described by simplified reaction rates. These so-called hybrid models can capture the characteristics of the reference models significantly better than the simplified models alone. The resulting hybrid models might serve as a good starting point for kinetic modelling of genome-scale metabolic networks, as they provide reasonable results in the absence of experimental data, regarding, for instance, allosteric regulations, for a vast majority of enzymatic reactions.},
  language  = {en}
}
@phdthesis{Huber2010,
  author    = {Huber, Veronika Emilie Charlotte},
  title     = {Climate impact on phytoplankton blooms in shallow lakes},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-42346},
  school      = {Universit{\"a}t Potsdam},
  year      = {2010},
  abstract  = {Lake ecosystems across the globe have responded to climate warming of recent decades. However, correctly attributing observed changes to altered climatic conditions is complicated by multiple anthropogenic influences on lakes. This thesis contributes to a better understanding of climate impacts on freshwater phytoplankton, which forms the basis of the food chain and decisively influences water quality. The analyses were, for the most part, based on a long-term data set of physical, chemical and biological variables of a shallow, polymictic lake in north-eastern Germany (M{\"u}ggelsee), which was subject to a simultaneous change in climate and trophic state during the past three decades. Data analysis included constructing a dynamic simulation model, implementing a genetic algorithm to parameterize models, and applying statistical techniques of classification tree and time-series analysis. Model results indicated that climatic factors and trophic state interactively determine the timing of the phytoplankton spring bloom (phenology) in shallow lakes. Under equally mild spring conditions, the phytoplankton spring bloom collapsed earlier under high than under low nutrient availability, due to a switch from a bottom-up driven to a top-down driven collapse. A novel approach to model phenology proved useful to assess the timings of population peaks in an artificially forced zooplankton-phytoplankton system. Mimicking climate warming by lengthening the growing period advanced algal blooms and consequently also peaks in zooplankton abundance. Investigating the reasons for the contrasting development of cyanobacteria during two recent summer heat wave events revealed that anomalously hot weather did not always, as often hypothesized, promote cyanobacteria in the nutrient-rich lake studied. The seasonal timing and duration of heat waves determined whether critical thresholds of thermal stratification, decisive for cyanobacterial bloom formation, were crossed. In addition, the temporal patterns of heat wave events influenced the summer abundance of some zooplankton species, which as predators may serve as a buffer by suppressing phytoplankton bloom formation. This thesis adds to the growing body of evidence that lake ecosystems have strongly responded to climatic changes of recent decades. It reaches beyond many previous studies of climate impacts on lakes by focusing on underlying mechanisms and explicitly considering multiple environmental changes. Key findings show that climate impacts are more severe in nutrient-rich than in nutrient-poor lakes. Hence, to develop lake management plans for the future, limnologists need to seek a comprehensive, mechanistic understanding of overlapping effects of the multi-faceted human footprint on aquatic ecosystems.},
  language  = {en}
}
@article{BecherGrimmThorbeketal.2014,
  author    = {Becher, Matthias A. and Grimm, Volker and Thorbek, Pernille and Horn, Juliane and Kennedy, Peter J. and Osborne, Juliet L.},
  title     = {BEEHAVE: a systems model of honeybee colony dynamics and foraging to explore multifactorial causes of colony failure},
  series = {Journal of applied ecology : an official journal of the British Ecological Society},
  volume    = {51},
  journal   = {Journal of applied ecology : an official journal of the British Ecological Society},
  number    = {2},
  publisher = {Wiley-Blackwell},
  address   = {Hoboken},
  issn      = {0021-8901},
  doi       = {10.1111/1365-2664.12222},
  pages     = {470 -- 482},
  year      = {2014},
  abstract  = {BEEHAVE offers a valuable tool for researchers to design and focus field experiments, for regulators to explore the relative importance of stressors to devise management and policy advice and for beekeepers to understand and predict varroa dynamics and effects of management interventions. We expect that scientists and stakeholders will find a variety of applications for BEEHAVE, stimulating further model development and the possible inclusion of other stressors of potential importance to honeybee colony dynamics.},
  language  = {en}
}
@misc{EldridgeŁangowskiStaceyetal.2016,
  author    = {Eldridge, Tilly and Łangowski, Łukasz and Stacey, Nicola and Jantzen, Friederike and Moubayidin, Laila and Sicard, Adrien and Southam, Paul and Kennaway, Richard and Lenhard, Michael and Coen, Enrico S. and {\O}stergaard, Lars},
  title     = {Fruit shape diversity in the Brassicaceae is generated by varying patterns of anisotropy},
  series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  journal   = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  number    = {986},
  issn      = {1866-8372},
  doi       = {10.25932/publishup-43804},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-438041},
  pages     = {3394 -- 3406},
  year      = {2016},
  abstract  = {Fruits exhibit a vast array of different 3D shapes, from simple spheres and cylinders to more complex curved forms; however, the mechanism by which growth is oriented and coordinated to generate this diversity of forms is unclear. Here, we compare the growth patterns and orientations for two very different fruit shapes in the Brassicaceae: the heart-shaped Capsella rubella silicle and the near-cylindrical Arabidopsis thaliana silique. We show, through a combination of clonal and morphological analyses, that the different shapes involve different patterns of anisotropic growth during three phases. These experimental data can be accounted for by a tissue level model in which specified growth rates vary in space and time and are oriented by a proximodistal polarity field. The resulting tissue conflicts lead to deformation of the tissue as it grows. The model allows us to identify tissue-specific and temporally specific activities required to obtain the individual shapes. One such activity may be provided by the valve-identity gene FRUITFULL, which we show through comparative mutant analysis to modulate fruit shape during post-fertilisation growth of both species. Simple modulations of the model presented here can also broadly account for the variety of shapes in other Brassicaceae species, thus providing a simplified framework for fruit development and shape diversity.},
  language  = {en}
}
@phdthesis{Fuhrmann2018,
  author    = {Fuhrmann, Saskia},
  title     = {Physiologically-based pharmacokinetic and mechanism-based pharmacodynamic modelling of monoclonal antibodies with a focus on tumour targeting},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-418861},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xvii, 171},
  year      = {2018},
  abstract  = {Monoclonal antibodies (mAbs) are an innovative group of drugs with increasing clinical importance in oncology, combining high specificity with generally low toxicity. There are, however, numerous challenges associated with the development of mAbs as therapeutics. Mechanistic understanding of factors that govern the pharmacokinetics (PK) of mAbs is critical for drug development and the optimisation of effective therapies; in particular, adequate dosing strategies can improve patient quality life and lower drug cost. Physiologically-based PK (PBPK) models offer a physiological and mechanistic framework, which is of advantage in the context of animal to human extrapolation. Unlike for small molecule drugs, however, there is no consensus on how to model mAb disposition in a PBPK context. Current PBPK models for mAb PK hugely vary in their representation of physiology and parameterisation. Their complexity poses a challenge for their applications, e.g., translating knowledge from animal species to humans. In this thesis, we developed and validated a consensus PBPK model for mAb disposition taking into account recent insights into mAb distribution (antibody biodistribution coefficients and interstitial immunoglobulin G (IgG) pharmacokinetics) to predict tissue PK across several pre-clinical species and humans based on plasma data only. The model allows to a priori predict target-independent (unspecific) mAb disposition processes as well as mAb disposition in concentration ranges, for which the unspecific clearance (CL) dominates target-mediated CL processes. This is often the case for mAb therapies at steady state dosing. The consensus PBPK model was then used and refined to address two important problems: 1) Immunodeficient mice are crucial models to evaluate mAb efficacy in cancer therapy. Protection from elimination by binding to the neonatal Fc receptor is known to be a major pathway influencing the unspecific CL of both, endogenous and therapeutic IgG. The concentration of endogenous IgG, however, is reduced in immunodeficient mouse models, and this effect on unspecific mAb CL is unknown, yet of great importance for the extrapolation to human in the context of mAb cancer therapy. 2) The distribution of mAbs into solid tumours is of great interest. To comprehensively investigate mAb distribution within tumour tissue and its implications for therapeutic efficacy, we extended the consensus PBPK model by a detailed tumour distribution model incorporating a cell-level model for mAb-target interaction. We studied the impact of variations in tumour microenvironment on therapeutic efficacy and explored the plausibility of different mechanisms of action in mAb cancer therapy. The mathematical findings and observed phenomena shed new light on therapeutic utility and dosing regimens in mAb cancer treatment.},
  language  = {en}
}
@phdthesis{Raatz2019,
  author    = {Raatz, Michael},
  title     = {Strategies within predator-prey interactions - from individuals to ecosystems},
  doi       = {10.25932/publishup-42658},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-426587},
  school      = {Universit{\"a}t Potsdam},
  pages     = {175},
  year      = {2019},
  abstract  = {Predator-prey interactions provide central links in food webs. These interaction are directly or indirectly impacted by a number of factors. These factors range from physiological characteristics of individual organisms, over specifics of their interaction to impacts of the environment. They may generate the potential for the application of different strategies by predators and prey. Within this thesis, I modelled predator-prey interactions and investigated a broad range of different factors driving the application of certain strategies, that affect the individuals or their populations. In doing so, I focused on phytoplankton-zooplankton systems as established model systems of predator-prey interactions. At the level of predator physiology I proposed, and partly confirmed, adaptations to fluctuating availability of co-limiting nutrients as beneficial strategies. These may allow to store ingested nutrients or to regulate the effort put into nutrient assimilation. We found that these two strategies are beneficial at different fluctuation frequencies of the nutrients, but may positively interact at intermediate frequencies. The corresponding experiments supported our model results. We found that the temporal structure of nutrient fluctuations indeed has strong effects on the juvenile somatic growth rate of {\itshape Daphnia}. Predator colimitation by energy and essential biochemical nutrients gave rise to another physiological strategy. High-quality prey species may render themselves indispensable in a scenario of predator-mediated coexistence by being the only source of essential biochemical nutrients, such as cholesterol. Thereby, the high-quality prey may even compensate for a lacking defense and ensure its persistence in competition with other more defended prey species. We found a similar effect in a model where algae and bacteria compete for nutrients. Now, being the only source of a compound that is required by the competitor (bacteria) prevented the competitive exclusion of the algae. In this case, the essential compounds were the organic carbon provided by the algae. Here again, being indispensable served as a prey strategy that ensured its coexistence. The latter scenario also gave rise to the application of the two metabolic strategies of autotrophy and heterotrophy by algae and bacteria, respectively. We found that their coexistence allowed the recycling of resources in a microbial loop that would otherwise be lost. Instead, these resources were made available to higher trophic levels, increasing the trophic transfer efficiency in food webs. The predation process comprises the next higher level of factors shaping the predator-prey interaction, besides these factors that originated from the functioning or composition of individuals. Here, I focused on defensive mechanisms and investigated multiple scenarios of static or adaptive combinations of prey defense and predator offense. I confirmed and extended earlier reports on the coexistence-promoting effects of partially lower palatability of the prey community. When bacteria and algae are coexisting, a higher palatability of bacteria may increase the average predator biomass, with the side effect of making the population dynamics more regular. This may facilitate experimental investigations and interpretations. If defense and offense are adaptive, this allows organisms to maximize their growth rate. Besides this fitness-enhancing effect, I found that co-adaptation may provide the predator-prey system with the flexibility to buffer external perturbations. On top of these rather internal factors, environmental drivers also affect predator-prey interactions. I showed that environmental nutrient fluctuations may create a spatio-temporal resource heterogeneity that selects for different predator strategies. I hypothesized that this might favour either storage or acclimation specialists, depending on the frequency of the environmental fluctuations. We found that many of these factors promote the coexistence of different strategies and may therefore support and sustain biodiversity. Thus, they might be relevant for the maintenance of crucial ecosystem functions that also affect us humans. Besides this, the richness of factors that impact predator-prey interactions might explain why so many species, especially in the planktonic regime, are able to coexist.},
  language  = {en}
}
@phdthesis{Kath2022,
  author    = {Kath, Nadja Jeanette},
  title     = {Functional traits determine biomass dynamics, coexistence and energetics in plankton food webs},
  doi       = {10.25932/publishup-55123},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-551239},
  school      = {Universit{\"a}t Potsdam},
  pages     = {197},
  year      = {2022},
  abstract  = {Plankton food webs are the basis of marine and limnetic ecosystems. Especially aquatic ecosystems of high biodiversity provide important ecosystem services for humankind as providers of food, coastal protection, climate regulation, and tourism. Understanding the dynamics of biomass and coexistence in these food webs is a first step to understanding the ecosystems. It also lays the foundation for the development of management strategies for the maintenance of the marine and freshwater biodiversity despite anthropogenic influences. Natural food webs are highly complex, and thus often equally complex methods are needed to analyse and understand them well. Models can help to do so as they depict simplified parts of reality. In the attempt to get a broader understanding of the complex food webs, diverse methods are used to investigate different questions. In my first project, we compared the energetics of a food chain in two versions of an allometric trophic network model. In particular, we solved the problem of unrealistically high trophic transfer efficiencies (up to 70\%) by accounting for both basal respiration and activity respiration, which decreased the trophic transfer efficiency to realistic values of ≤30\%. Next in my second project I turned to plankton food webs and especially phytoplankton traits. Investigating a long-term data set from Lake Constance we found evidence for a trade-off between defence and growth rate in this natural phytoplankton community. I continued working with this data set in my third project focusing on ciliates, the main grazer of phytoplankton in spring. Boosted regression trees revealed that temperature and predators have the highest influence on net growth rates of ciliates. We finally investigated in my fourth project a food web model inspired by ciliates to explore the coexistence of plastic competitors and to study the new concept of maladaptive switching, which revealed some drawbacks of plasticity: faster adaptation led to higher maladaptive switching towards undefended phenotypes which reduced autotroph biomass and coexistence and increased consumer biomass. It became obvious that even well-established models should be critically questioned as it is important not to forget reality on the way to a simplistic model. The results showed furthermore that long-term data sets are necessary as they can help to disentangle complex natural processes. Last, one should keep in mind that the interplay between models and experiments/ field data can deliver fruitful insights about our complex world.},
  language  = {en}
}