La microéconomie conventionnelle présente le concept de rationalité de manière univoque et étroite comme maximisation de l'utilité espérée. On sait les critiques qui ont été adressées à ce concept tant du point de vue de l'économie comportementale que de celui de la sociologie. Notre objectif est de proposer une lecture de certaines de ces critiques afin de montrer que, pour l'essentiel, elles mettent en évidence la diversité des modes de rationalité. Le problème est, dès lors, de savoir si le constat de cette diversité conduit nécessairement à la récusation du modèle standard. Cette thèse s'inscrit dans la double perspective de la théorie du choix rationnel et de la théorie des jeux. À partir des critiques de l'économie comportementale, nous soutenons que le principe de maximisation constitue un mode de raisonnement local et évaluable au regard du contexte d'action. Mais une telle régionalisation implique une profonde révision de la théorie des jeux standard. La récusation de l'équilibre général, fondé sur le présupposé de la maximisation de l'utilité espérée, comme modèle univoque appelle un nouveau type de formalisation. En ce sens, nous montrons que la modélisation multi-agents permet de penser, de manière contrefactuelle, des interactions entre agents économiques rationnels et situés. Cette méthode nous autorise ainsi à élaborer des scénarios rationalisants qui dessinent des mondes possibles sans trancher entre ces mondes. / Standard microeconomics displays the concept of rationality as the maximisation of expected utility i.e. in a narrow and unequivocal sense. The criticisms against this concept made by behavioural economics or sociology are well known. I aim at providing an analysis of some of them in order to emphasise the fact that they mainly highlight the diversity of reasoning modes. But the issue is to know whether the diversity of reasoning modes necessarily leads to reject the standard model. My intention falls into two fields : the theory of Rational Choice and the Game Theory. From the point of view of behavioural economics, I assume that the maximisation is nothing more than a local reasoning mode that can be assessed in relation to the context of action. But this assumption implies correcting the standard Game Theory as well. The fact that the general equilibrium, based on the maximisation of expected utility, cannot be used anymore as an unique model calls a new kind of formalisation. So, I point out that agent-based modelling allows us to conceive, in a counterfactual way, interactions between rational economic agents in their context. Therefore, in this respect, rational patterns of actions and interactions design possible worlds without having to choose between them.

La thématique de l'expansion du système agricole depuis l'Anatolie vers les Balkans est depuis longtemps un important sujet de recherche. Les approches archéologiques classiques ont permis de mieux comprendre le parcours et le temps de cette expansion, mais ils n'expliquent rien de ce qui n'est pas observable dans les traces archéologiques : notamment, la structure socio-économique d'une société agricole préhistorique. Dans cette thèse, un modèle de type multi-agents a été utilisé pour explorer ces éléments qui sont invisibles en archéologie. Ce modèle, appelé BEAN (Bridging European and Anatolian Neolithic), consiste en une adaptation du modèle OBRESOC (Un OBservatoire REtrospectif d'une SOCiété archéologique). OBRESOC avait été crée pour simuler l'expansion des agriculteurs rubanées en Europe Centrale, et a été modifié pour s'adapter au contexte archéologique balkanique. L'expansion des premiers agriculteurs Balkaniques est simulée en combinant des données archéologiques avec des inférences ethnohistoriques et paléodémographiques. Un environnement réaliste a été modélisé, où les zones d'optimum agricole sont déterminées par des estimations de la météorologie et de la fertilité des sols. Chaque agent correspond à un foyer domestique ; les agents interagissent dans cet environnement en suivant des modèles partiaux intermédiaires socioéconomiques qui déterminent les règles de leur comportement. Par exemple : maisons avec des familles nucléaires ; système agricole intensif sur des petits champs avec chasse et cueillette complémentaires ; expansion déterminée par le scalar stress villageois ; réseaux de solidarité entre apparentés ; disettes et famines causées par des événements météorologiques. De cette façon, le modèle simule le fonctionnement et l'expansion géographique d'une société agricole Néolithique. De nombreuses simulations ont été effectuées, en faisant varier les paramètres les plus importants, identifiés grâce à une analyse de sensibilité. L'adhérence entre les données archéologiques et les données simulées a été mesurée principalement avec des critères géographiques : la simulation qui produit le patron d'expansion simulé qui coïncide le mieux avec l'expansion archéologique est considérée la meilleure. De procédures spécifiques ont été crées pour manipuler la grande quantité de données simulées produites par le modèle. L'observation de ces données a permis l'exploration de certains aspects qui sont invisibles en archéologie ; par exemple, le modèle a aidé à questionner des croyances archéologiques basées sur des hypothèses qui n'étaient pas vérifiables autrement. Le modèle a permis aussi l'exploration d'autres sujets, comme la comparaison entre le front pionner de colonisation et les zones d'ancienne occupation, ainsi que l'influence de la météorologie sur l'expansion du système agricole. Le modèle a produit des patrons d'expansion qui adhèrent, géographiquement et chronologiquement, à l'expansion suggérée par les traces archéologiques. L'exploration des sorties socio-économiques a permis la formulation de nouvelles hypothèses qui ne pourraient pas être faites simplement sur la base de ce qui est trouvé dans les vestiges archéologiques. Même quand il y a un large écart entre ce qui est observé en archéologie et ce qui est produit par le modèle, cette approche de modélisation multi-agents ouvre à des nouvelles questions, en ajoutant de nouvelles idées et perspectives à la recherche actuelle. / A topic of great importance in archaeological research throughout the last decades concerns the expansion of the first farmers from Anatolia through the Balkans. The standard archaeological approaches allowed the understanding of the path and timing of this expansion; however, they lack explanation of what is unobservable in the archaeological record: in particular, the socio-economic structure of a prehistoric farming society. Throughout this thesis, an agent-based model was built in order to explore those elements which are hidden in archaeology. This model, called BEAN (Bridging European and Anatolian Neolithic), is an adaptation of the OBRESOC model (Un OBservatoire REtrospectif d'une SOCiété archéologique). OBRESOC was created to simulate the expansion of the LBK farmers in central Europe, and was adapted to the Balkan archaeological context. The expansion of the first Neolithic farmers in the Balkans was simulated by combining the archaeological records to ethnohistoric and paleodemographic inferences. A realistic environment has been modelled where the areas of optimum farming are determined by meteorology and soil fertility estimates. An agent corresponds to a household; agents interact on this landscape, following socioeconomic partial intermediate models. For instance: households composed of a nuclear family; intensive farming system on small plot completed by hunting-gathering; expansion determined by scalar stress at the hamlet scale; family clan solidarity; shortages and famines caused by meteorological events). Thus, the model simulates the functioning of the Neolithic farming society and its geographic expansion. Several simulations have been executed, testing different combinations of the key parameters, identified through a sensitivity analysis. The goodness of fit of simulated data to the archaeological data is measured mostly on geographic criteria : the best simulation is the one that produces the expansion pattern that better fits to the archaeological data. Specific procedures have been developed in order to process the large amount of data produced by the model. The observation of this data permitted to explore some aspects that are invisible in archaeological record : for example, the model helped to investigate some archaeological beliefs, based on assumptions that could not be verified. The model also permitted the exploration of other topics, such as the comparison between the pioneer front of colonization and the zones of previous occupation, as well as the effect of meteorology on the expansion of the farming system. The model produced an expansion pattern that corresponds geographically and chronologically to the expansion suggested by the archaeological evidence. The exploration of socio-economic outputs permitted the formulation of new hypothesis that could not be made using purely archaeological record. Even when there's a large gap between what is found in archaeology and what is produced by the model, this agent-based modelling approach helps to raise new questions, adding new ideas and perspective to the actual state of research.

This thesis describes and contextualises the Population & Cemetery Simulator (PCS), which represents agent-based demographic modelling software that can be used to model living populations based on archaeological and historical data as well as their cemeteries. The data used by the PCS are demographic in nature, e.g. age and sex data generated by osteoarchaeologists from excavated cemeteries or historical demographic data. This thesis seeks to provide a methodological foundation for modelling the demographics of archaeological populations. It focusses on case studies using data from early medieval Anglo-Saxon (South England) and Alamannic (South Germany) cemeteries, although excursions into neighbouring periods and regions are included as validation studies. The case studies show how the PCS can be used in archaeological research and the software is presented as a solution to various problems caused by the difference between the living population and the 'dead' cemetery data in archaeology.

Over the last decade a huge amount of experimental data on biological systems has been generated by modern high-throughput methods. Aided by bioinformatics, the '-omics' (genomics, transcriptomics, proteomics, metabolomics and interactomics) have listed, quantif ed and analyzed molecular components and interactions on all levels of cellular regulation. However, a comprehensive framework, that does not only list, but links all those components, is still largely missing. The biology-based but highly interdisciplinary field of systems biology aims at such a holistic understanding of complex biological systems covering the length scales from molecules to whole organisms. Spanning the length scales, it has to integrate the data from very different fields and to bring together scientists from those fields. For linking experiments and theory, hypothesis-driven research is an indispensable concept, formulating a cycle of experiment, modeling, model predictions for new experiments and, fi nally, their experimental validation as the start of the new iteration. On the hierarchy of length scales certain unique entities can be identi fied. At the nanometer scale such functional entities are molecules and at the micrometer level these are the cells. Cells can be studied in vitro as independent individuals isolated from an organism, but their interplay and communication in vivo is crucial for tissue function. Control over such regulation mechanisms is therefore a main goal of medical research. The requirements for understanding cellular interplay also illustrate the interdisciplinarity of systems biology, because chemical, physical and biological knowledge is needed simultaneously. Following the notion of cells as the basic units of life, the focus of this thesis are mathematical multi-scale models of multi-cellular systems employing the concept of individual (or agent) based modeling (IBM). This concept accounts for the entity cell and their individuality in function and space. Motivated by experimental observations, cells are represented as elastic and adhesive spheres. Their interaction is given by a model for elastic homogeneous spheres, which has been established for analysis of the elastic response of cells, plus an adhesion term. Cell movement is modeled by an equation of motion for each cell which is based on the balance of interaction, friction and active forces on the respective cell. As a fi rst step the model was carefully examined with regard to the model assumptions, namely, spherical shape, homogeneous isotropic elastic body and apriori undirected movement. The model examination included simulations of cell sorting and compression of multicellular spheroids. Cell sorting could not be achieved with only short range adhesion. However, it sorting completed with long range interactions for small cell numbers, but failed for larger aggregates. Compression dynamics of multi-cellular spheroids was apparently reproduced qualitatively by the model. But in a more detailed survey neither the time scales nor the rounding after compression could be reproduced. Based on these results, the applications consistent with the assumed simpli cations are discussed. One already established application is colony growth in two-dimensional cell cultures. In order to model cell growth and division, a two-phase model of the cell cycle was established. In a growth phase the cell doubles its volume by stochastic increments, and in a mitotic phase it divides into two daughter cells of equal volume. Additionally, control of the cell cycle by contact inhibition is included in the model. After examination of its applicability, the presented model is used for simulations of in vitro growth of mesenchymal stem cells (MSC) and subsequent cartilage formation in multi-cellular spheroids. A main factor for both processes is the oxygen concentration. Experimental results have shown, that i) MSC grow much better in vitro at low than at high oxygen concentrations and ii) the MSC progeny harvested from low oxygen culture produce higher amounts of the cartilage components aggrecan and collagen II in multicellular spheroids than the ones from high oxygen culture. In order to model these processes, IBM was extended by a stochastic model for cellular differentiation. In this model cellular differentiation is captured phenomenologically by two additional individual properties, the degree of differentiation and the lineage or cell type, which are subject to fl uctuations, that are state and environment dependent. After fitting the model parameters to the experimental results on MSC growth in monoclonal expansion cultures at low and high oxygen concentrations, the resulting simulated cell populations were used for initialization of the simulations of cartilage formation in multi-cellular spheroids. The model nicely reproduced the experimental results on growth dynamics and the observed number of functional cells in the spheroids and suggests the following explanation for the difference between the two expansion cultures: due to the stronger pre-differentiation found after expansion in high oxygen, the plasticity of these cells is smaller and less cell adopt the chondrogenic phenotype and start to produce cartilage. Moreover, the model predicts an optimal oxygen concentration for cartilage formation independent of expansion culture and a de-differentiating effect of low oxygen culture within 24h. Because all simulations comply with the concept of hypothesis-driven research and follow closely the experimental protocols, they can easily be tested and are currently used for optimization of a bioreactor for cartilage production. Cell populations are composed of individual cells and regulation of population properties is performed by individual cell, but knowledge about individual cell fates is largely missing due to the problem of single cell tracking. The IBM modeling approach used for modeling MSC growth and differentiation generically includes information of each individual cell and is therefore perfectly suited for tackling this question. Based on the validated parameter set, the model was used to generate predictions on plasticity of single cells and related population dynamics. Single cell plasticity was quantifi ed by calculating transition times into stem cell and differentiated cell states at high and low oxygen concentrations. At low oxygen the results predict a frequent exchange between all subpopulations, while at high oxygen a quasi-deterministic differentiation is found. After quantifying the plasticity of single cells at low and high oxygen concentration, the plasticity of a cell population is addressed in a simulation closely following a regeneration experiment of populations of hematopoietic progenitor cells. In the simulation the regeneration of the distribution of differentiation states in the population is monitored after selection of subpopulations of stem cells and differentiated cells. Simulated regeneration occurs on the time scales estimated from the single cell transition times except the unexpectedly fast regeneration from differentiated cells in the high oxygen environment, which favors differentiation. The latter case emphasizes the importance of single outlier cells in such system, which in this case repopulate less differentiated states with their progeny. In general, cell proliferation and regeneration behavior are in uenced by biomechanical and geometrical properties of the environment e.g. matrix stiffness or cell density. Because in the model cells are represented as physical objects, a variation of friction is linked to cell motility. The cultures of less motile cells become denser at the same size and the effects of contact inhibition of growth more pronounced. This variation of friction coe fficients allows the comparison of cultures with varying degrees of contact inhibition regarding their differentiation structure and the results suggest, that stalled proliferation is su fficient to explain the well-known differentiation effects in confl uent colonies. In addition, the composition of the simulated stem cell pool was analyzed regarding differentiation. In contrast to the established pedigree models, where stem cell can only be produced by asymmetric division, this model predicts that most of the cells in stem cell states descend from progenitor cells of intermediate differentiation states. A more detailed analysis of single cell derived clones revealed properties that could not be described by the model so far. First, a differentiation gradient was observed in larger colonies, that was the opposite of the one predicted by the model. Second, the proliferative activity turned out to depend not only on oxygen, but also to be a property of individual clones persisting over many generations. Because the relation slow growth/pre-differentiation also holds for single cell derived clones, the general model of differentiation is extended by another heritable individual property. Motivated by the decline of proliferation and differentiation in culture and the high metabolic and epigenetic activity during cell division, each division event is assumed to de-stabilize stem cell states. Consequently, in the model the cells age in terms of cell divisions determines the fl uctuations in stem cell states and the environment the mean fl uctuation strength. Including this novel concept, that links aging to growth and differentiation dynamics, into the model reproduces the experimental results regarding differentiation gradient and persistent clonal heterogeneity. The spatial differentiation pattern can largely be explained by the spatio-temporal growth pattern of the mono-clonal cell assembly: cells close to the border of the cell assembly have undergone more cell divisions than those in the interior and therefore their stem cell states are less stable. Heterogeneity of single-cell derived clones depends on the age of the first cell in the clone. When the stem cell fluctuations equal the mean fl uctuations strength, the proliferative activity passes a maximum at a certain age due to the destabilization of stem cell states. Thereafter the proliferative activity decreases, because more time is spent in non-proliferative differentiated states. Considering the number of divisions the cells have already undergone in vivo and after the initial expansion in vitro, it can be assumed that all cells have already passed this maximum. Interestingly, the model also predicts an optimal age for directed differentiation, when cells stably differentiate, but have not lost the required plasticity. According to the model, this clonal heterogeneity may be caused purely in vitro, but hypothetical simulation of in vivo aging yielded results consistent with experiments on MSC from rats of varying age. Finally, the detailed molecular regulation mechanisms in a multi-scale tissue model of liver zonation was studied, in which the key molecular components were explicitly modeled. Hence, this model resolved the intracellular regulation in higher resolution than the above considered differentiation models which had summarized the intracellular control and differentiation mechanisms by a few phenomenological, dynamical variables. The metabolic zonation of the liver is essential for many of the complex liver functions. One of the vitally important enzymes, glutamine synthetase, (GS) is only synthesized in a strictly defi ned pattern. Experimental evidence has shown that a particular pathway, the canonical wnt pathway, controls expression of the gene for GS. A model for transport, receptor dynamics and intracellular regulation mechanism has been set up for modeling the spatio-temporal formation of this pattern. It includes membrane-bound transport of the morphogen and an enzyme kinetics approach to fibeta-catenin-regulation in the interior of the cell. As an IBM this model reproduces the results of co-culture experiments in which two-dimensional arrangements of liver cells and an epithelial liver cell line give rise to different patterns of GS synthesis. The two main predictions of the model are: First, GS-synthesis requires a certain local cell number of wnt releasing cells. And second, a simple inversion of geometry explains the difference between the specifi c GS pattern found in the liver and in the co-culture experiments. Summarizing the results presented in this thesis, it can be concluded that properties such as the occurrence of memory effects and single cells pursuing fates far off the population average could be essential for biological function. Considering the role of single cells in many tissues, the use of individual based methods, that are able to take such effects into account, can be expected to be a very valuable tool for the problems of systems biology.

The effectiveness of land sharing and land sparing (LS/LS) approaches to conservation in the face of rising agricultural demands has been widely debated. While numerous studies have investigated the LS/LS framework from an ecological lens (yield-biodiversity relationship) the relevance of the framework to real life depends on broader considerations. Some of the key caveats include: i) limited knowledge regarding the feasibility of interventions given diverse stakeholders’ interests, ii) the social acceptability (uptake) of these contrasting strategies to direct land users, and iii) limited knowledge regarding their impacts on individuals’ livelihoods and food security. Without considering these social science dimensions proponents of the framework risk an incomplete picture that is not grounded in local realities and can paradoxically force into opposition the very conservation and development interests they seek to reconcile. Using a Companion Modelling approach, which comprises the development of a role-playing game (RPG) and an agent-based model (ABM), this thesis addressed these caveats. The research was based in the Nilgiris of Western Ghats India, a tropical agricultural system at the forest frontier. The main findings show that through engaging local stakeholders in a participatory process, plausible land use strategies that align with their objectives could be identified. Stakeholders proposed three land use interventions. Two of them resemble a form of land sparing (‘monofunctional’ landscapes) on the farms: sparing land for Wildflower Meadows or Tree Plantations while increasing yield on the remaining land. The third intervention asks farmers to accept yield penalties for Intercropping more trees on their farms, a form of land sharing (‘integrated’ landscapes). In terms of decision-making regarding the adoption of these three interventions by direct land users, the study reveals several findings. Firstly there are three main types of motivations that influence farmers’ decision to adopt interventions, in order of importance: monetary benefits, pro-environmental motivations and social norms. Secondly, land use, the type of management preferred on the farm and whether land users accept trees on the farm or not are factors that influence what type of interventions is socially acceptable on individual farms. These factors have been detected in the in-depth household survey and also validated by the RPG. When assessing the adoption of the three interventions, ex ante their implementation, using an ABM, there are some important differences observed between the interventions. Wildflower Meadows is the intervention adopted by the largest number of households, whereas Intercropping is adopted across the largest area of land. Forest Plantations is significantly more unpopular than the other two interventions. The third line of investigation, about the outcomes of adoption, has important policy implications. Adding a socioeconomic dimension to the ecological one adds a level of complexity and creates a less straightforward choice between the LS/LS strategies. None of the three interventions can provide optimal outcomes for production, aspects of biodiversity conservation, livelihoods and food security. Each intervention has indicators that score better compared to the other two interventions. The findings demonstrate that the ecological focus of the LS/LS framework is insufficient to deal with real-world complexities and lends itself to overly simplistic policy prescriptions. More meaningful policies could be achieved when bridging natural and social sciences to better understand the merits and limitations of the LS/LS approaches.

The following thesis presents a computational framework that can capture inherently non-linear and emergent biocomplex phenomena. The main motivation behind the investigations undertaken was the absence of a suitable platform that can simulate, both the continuous features as well as the discrete, interaction-based dynamics of a given biological system, or in short, dynamic reciprocity. In order to determine the most powerful approach to achieve this, the efficacy of two modelling paradigms, transport phenomena as well as agent-based, was evaluated and eventually combined. Computational Fluid Dynamics (CFD) was utilised to investigate optimal boundary conditions, in terms of meeting cellular glucose consumption requirements and exposure to physiologically relevant shear fields, that would support mesenchymal stem cell growth in a 3-dimensional culture maintained in a commercially available bioreactor. In addition to validating the default bioreactor configuration and operational parameter ranges as suitable towards sustaining stem cell growth, the investigation underscored the effectiveness of CFD as a design tool. However, due to the homogeneity assumption, an untenable assumption for most biological systems, CFD often encounters difficulties in simulating the interaction-reliant evolution of cellular systems. Therefore, the efficacy of the agent-based approach was evaluated by simulating a morphogenetic event: development of in vitro osteogenic nodule. The novel model replicated most aspects observed in vitro, which included: spatial arrangement of relevant players inside the nodule, interaction-based development of the osteogenic nodules, and the dependence of nodule growth on its size. The model was subsequently applied to interrogate the various competing hypotheses on this process and identify the one that best captures transformation of osteoblasts into osteocytes, a subject of great conjecture. The results from this investigation annulled one of the competing hypotheses, which purported the slow-down in the rate of matrix deposition by certain osteoblasts, and also suggested the acquisition of polarity to be a non-random event. The agent-based model, however, due to being inherently computationally expensive, cannot be recommended to model bulk phenomena. Therefore, the two approaches were integrated to create a modelling platform that was utilised to capture dynamic reciprocity in a bioreactor. As a part of this investigation, an amended definition of dynamic reciprocity and its computational analogue, dynamic assimilation, were proposed. The multi-paradigm platform was validated by conducting melanoma chemotaxis under foetal bovine serum gradient. Due to its CFD and agent-based modalities, the platform can be employed as both a design optimisation as well as hypothesis testing tool.

Le changement climatique continue d'affecter la dynamique des paysages forestiers à grande échelle. Cependant, il demeure incertain comment ces changements affecteront les forêts futures et en particulier les épidémies des insectes ravageurs forestiers. Le changement climatique affecte l’émergence des insectes, en perturbant notamment la synchronisation phénologique entre les insectes herbivores et leurs arbres hôtes. De telles perturbations peuvent avoir des conséquences importantes sur le moment de l’émergence, l'étendue et la gravité de l'épidémie. Cette étude vise à comprendre comment le changement climatique pourrait affecter la synchronie phénologique entre la tordeuse des bourgeons de l'épinette (Choristoneura fumiferana), un défoliateur indigène, et ses espèces hôtes (Abies balsamea et Picea mariana) et comment cela pourrait affecter l'étendue des épidémies de la tordeuse des bourgeons de l'épinette dans la région de la Côte-Nord au Québec, Canada. Nous avons exploré les effets de deux facteurs expérimentaux sur l'étendue des épidémies à l'aide d'un modèle de simulation stochastique spatialement explicite à base d’agents (MBA): (1) la température quotidienne représentée selon deux niveaux d'augmentation (+2°C et +4°C) relative à une base de référence 2016 et (2) la variation de la phénologie des arbres hôtes correspondant aux différents niveaux d'incertitude (SD) concernant le moment du débourrement des bourgeons. Nous avons évalué comment ces facteurs ont affecté la variation de l'étendue des épidémies de la tordeuse des bourgeons de l'épinette et la complexité spatiale du patch épidémique sur un horizon de simulation de 20 ans. Nos résultats de simulation indiquent que la synchronisation phénologique arbres hôtes-insectes est fortement affectée par les changements de température, mais de manière non linéaire. Une augmentation de 2°C a permis de réduire l'étendue de l'épidémie en raison de la faible survie des larves, tandis qu'une augmentation de 4°C a entraîné une survie plus élevée des insectes et des épidémies plus importantes. Notre modèle peut aider à prévoir la dynamique future des forêts et faciliter l'élaboration de meilleures stratégies de gestion pour réduire l'effet des épidémies sur les paysages forestiers. / Climate change continues to affect forest landscape dynamics at a global scale. However, it remains uncertain how these changes will affect future forests and in particular outbreaks of forest insect pests. Climate change can affect outbreaking insects by disrupting phenological synchrony between herbivorous insects and their host trees. Such disruptions can have important consequences for outbreak timing, extent, and severity. This study aims to understand how climate change could affect the phenological synchrony between the spruce budworm (Choristoneura fumiferana), a native outbreaking defoliator, and its host trees (Abies balsamea and Picea mariana), and how this might affect the extent of spruce budworm outbreaks in the Côte-Nord region in Quebec, Canada. We explored the effects of two experimental factors on outbreak extent using a spatially explicit stochastic agent-based simulation model (ABM): (1) daily temperature represented as two levels of increase (+2°C and +4 °C) relative to a 2016 baseline, and (2) variation in host phenology represented as four different levels of uncertainty (SD) around the timing of budburst. We assessed how these factors affected variation in spruce budworm outbreak extent and outbreak patch spatial complexity over a 20-year simulation horizon. Our simulation results indicate that host trees-insect phenological synchrony is strongly affected by temperature changes, but in a non-linear way. An increase of 2°C was found to reduce outbreak extent due to poor larval survival, while an increase of 4°C resulted in higher insect survival and larger outbreaks. Our model can help to forecast future forest dynamics and facilitate the development of better management strategies to reduce the effect of outbreaks on forest landscapes.

Les environnements arides végétalisés seront parmi les environnements les plus impactés par la désertification dans le cadre du changement climatique. Ces environnements légèrement végétalisés sont caractérisés par une balance précaire entre un état de résilience et de vulnérabilité qui est intrinsèquement menacé par la désertification pouvant potentiellement mener à une augmentation du transport des sédiments éolien et une dégradation des environnements. Le nombre d’interactions présentes entre la végétation, la pluie, le transport des sédiments et la présence d’herbivore en milieu aride, ainsi que leur nature non-linéaire rend difficile de représenter ces interactions à l’aide de modèle physique et mathématique. La modélisation complexe est mieux adaptée à la représentation des interactions complexes entre la végétation, la pluie, le transport des sédiments et la présence d’herbivores dans les systèmes arides. Un nombre considérable d’études ont utilisées les modèles complexes pour étudier l’effet de la végétation sur le transport des sédiments ou l’effet de la présence d’herbivore sur la végétation, mais peu d’études ont utilisées une approche intégrant ces trois composantes en un même modèle. Un nouveau modèle d’herbivorie basé sur l’agent (GrAM) est présenté sous forme d’extension du modèle ViSTA_M17 et permet une meilleure représentation de l’impact des régimes de pâturage en environnement aride végétalisé. Cet ajout ayant un modèle complexe de transport des sédiments et de végétation déjà établit vise présenter un modèle hybride pouvant représenter l’impact de l’herbivorie sur la composition végétale et le transport des sédiments en environnement aride à l’échelle du paysage. Le développement du nouveau module à l’intérieur de la structure du modèle ViSTA original a souligné certaines limites de ce dernier, notamment une sensitivité importante de la végétation et de la force de cisaillement du vent. Le modèle ViSTA_GrAM répond à certaines limites du modèle original par l’intégration d’un nouveau module d’herbivorie et présente une avancée vers une modélisation environnementale englobante permettant une meilleure compréhension des dynamiques spatiales et temporelles des environnements arides. L’approche englobante utilisée par le modèle ViSTA_GrAM est bénéfique à la prise de décision, puisqu’elle offre un outil permettant d’explorer les réponses des environnements arides à un changement de leur végétation, leur régime de pluie, leur régime de transport des sédiments ou leur régime d’herbivorie. Les modèles complexes et l’exploration de scénarios futurs des environnements arides peuvent permettre d’améliorer la gestion de ces mêmes environnements. / Vegetated arid environments will be among one of the most affected by desertification as a result of climate change. These sparsely vegetated regions exhibit a delicate balance of resilience and vulnerability that are profoundly challenged by desertification, potentially producing an important positive feedback leading to increased aeolian activity and therefore land degradation. The high level of interaction between rainfall, vegetation, sediment transport and grazing in these arid environments and the non-linear nature of these interactions make them difficult to predict by traditional mathematical modeling mean. Complex modeling, on the other hand, offer better representation of the intricate relation between vegetation, rainfall, sediment transport and grazing in an arid environment system. A sizable amount of studies has been conducted with complex models to explore the effect of vegetation on sediment transport or grazing effect on vegetation, but few have used a truly integrative approach where all tree components were represented in a complex model. This research present a novel agent-based model (GrAM) integrated as an extension to already complete sediment transport-vegetation complex model (ViSTA) allowing a more refined representation of grazer’s impact in vegetated arid environments. This addition to the ViSTA model is aimed to combine a land management and systematic approach in a coupled model, to represent, at a landscape level, the impact of grazing on the composition of vegetation and sediment movement in arid environments. The development of this new module within the original ViSTA model, has highlighted some limitations of this model, most notably concerning its sensitivity to vegetation and wind shear. The ViSTA_GrAM model addresses these limitations through integrating a new module of grazing as the next step toward an integrated modelling effort that permits models to effectively increase our spatial and temporal understanding of arid environments vegetation, sediment transport and grazing dynamics. Integrative approach, like the one provided by the ViSTA_GrAM model, is beneficial to decision making by providing tools to investigate the response of an arid environment to different state of their vegetation, rainfall regime, wind stress and grazing regime. By developing complex modeling in arid environment and exploring various future scenarios for arid environment, we hope to lead to better management plan of those same environment.

Mit den steigenden Anteilen der Wind- und Solarstromerzeugung als fluktuierenden erneuerbaren Energien (FEE) wurden in den vergangenen Jahren aus der Energiewirtschaft, der Wissenschaft und Politik Forderungen laut, die FEE im Interesse einer effizienteren Förderung „besser“ in die liberalisierten Strommärkte zu integrieren (sog. Marktintegration der EE). Gefordert wird u. a., dass die FEE in Zukunft ähnlich wie die thermischen Kraftwerke ihre Stromproduktion an den Preissignalen der Großhandels-Strommärkte ausrichten, um somit zum besseren Ausgleich von Angebot und Nachfrage beizutragen. In die Diskussion zur grundlegenden Reform des EEG 2014 wurde u. a. die Einführung einer fixen statt variablen Marktprämie, einer kapazitiven Vergütung sowie die wettbewerbliche Ausschreibung anstatt administrativer Förderhöhen eingebracht. Investitionen in FEE-Anlagen als kapitalintensive Technologien sehen sich jedoch bei verstärkter Marktintegration unter den heute vorherrschenden Marktbedingungen – die primär auf einen thermischen Kraftwerkspark ausgelegt sind - zunehmenden Investitions- und Betriebsrisiken ausgesetzt, die durch Risikoaufschläge bei Eigen- und Fremdkapital in die Investitionskosten eingepreist werden. Neben steigenden Preisrisiken durch stärkere Preisvolatilitäten bei höheren FEE-Anteilen ergeben sich in Abhängigkeit der Förderinstrumente jedoch auch neue Mengenrisiken, da mit der Einführung der FEE-Direktvermarktung diese bei entsprechend niedrigen Preisen marktgetrieben abgeregelt werden. Durch den bereits in der Vergangenheit nachgewiesenen Merit-Order-Effekt und den Marktwertverlust der FEE durch den sog. Gleichzeitigkeitseffekt, stellt sich damit die Frage, ob sich ein System mit hohen Anteilen an FEE zukünftig rein marktendogen auf Basis eines Grenzkostenmarktes refinanzieren lässt. Mit Hilfe des im Rahmen der Dissertation weiterentwickelten agentenbasierten Strommarktmodells AMIRIS wurden zur Beantwortung der Fragestellung unterschiedliche Szenarioanalysen durchgeführt und auf der Akteurs- und Systemebene ausgewertet. Die stündlich aufgelösten Simulationsläufe von 2015-2035 zur Entwicklung der Refinanzierungsbedingungen der FEE, der FEE-Marktwerte sowie der assoziierten Fördereffizienz zur Erreichung der FEE-Ziele bei Anwendung einer variablen oder fixen Markt- sowie Kapazitätsprämie kommen dabei zu dem Ergebnis, dass die Refinanzierung eines allein marktendogenen Ausbaus von FEE-Anlagen unter den Bedingungen eines grenzkostenbasierten Strommarktes nicht möglich ist. Dies liegt primär an den zunehmend marktgetrieben abgeregelten Strommengen sowie den Marktwertverlusten durch den Gleichzeitigkeitseffekt. Problem ist hierbei, dass keiner der Anlagenbetreiber zum Zeitpunkt der Investition realistisch abschätzen kann, welcher Anteil der meteorologisch erzeugbaren Strommenge sich letztendlich am Markt absetzen lässt. Denn die vermarktbaren Strommengen hängen nicht nur vom Förderinstrument, sondern vor allem von der zukünftigen Flexibilität im System ab. Hinzu kommt, dass sich im Referenzszenario mit keinem der diskutierten Instrumente auch nur annäherungsweise die EE-Ausbauziele bis 2035 erreichen lassen. Zusätzlich kommt es beim derzeit implementierten EE-Direktvermarktungssystem über die Strombörse mit Wettbewerb zwischen den dezentralen Direktvermarktern bei der variablen Marktprämie zu ineffizienten Abregelungsentscheidungen, da in diesem Förderregime der Anreiz besteht, die stromgestehungskostentechnisch günstigsten FEE-Anlagen als erstes abzuregeln. Mit zunehmendem Anteil der FEE-Einspeisung wird es zukünftig bei einem dezentralen Direktvermarktungssystem außerdem zu hohen Informationsasymmetrien und damit einer ineffizienten Preisbildung im Stromgroßhandel kommen. Dies liegt an der Unkenntnis anderer Marktteilnehmer über die dezentrale Entscheidung abzuregelnder FEE-Mengen. Ein zentrales Direktvermarktungssystem mit einem sog. ‚Single-Buyer‘-Konzept könnte hier Abhilfe schaffen. Entgegen der vorherrschenden ökonomischen Theorie erweist sich die variable Marktprämie jedoch in allen untersuchten Szenarien als dynamisch effizienter als eine fixe Marktprämie, die wiederum effizienter wirkt als eine variable und fixe Kapazitätsprämie. Den größten Einfluss auf die absoluten als auch relativen Marktwerte der FEE; haben neben den Förderinstrumenten in absteigender Reihenfolge vor allem neue Stromverbraucher (P2X), ein zentrales statt dezentrales Direktvermarktungssystem, ein gleichmäßigeres Ausbauverhältnis zwischen Wind- und PV-Anlagen, eine gleichmäßigere Verteilung der Windanlagen zwischen Nord- und Süddeutschland, der flexible Einsatz von Biomasseanlagen, der Einsatz von Strom-zu-Strom-Speichern und zu relativ kleinen Anteilen auch eine systemdienlichere Auslegung der Anlagen (Schwachwindanlagen). Bessere Anreize zur Hebung der Flexibilitätspotentiale und damit bessere Integrationsmöglichkeiten der FEE bietet die Integration über die Stromvertriebe statt über den Stromgroßhandel. / With the increasing shares of wind and solar power generation as variable renewable energies (VRE), demands have been made in recent years from the energy industry, science and politics to integrate the VRE 'better' into the liberalised electricity markets in the interest of more efficient promotion (so-called market integration of renewables). One of the demands is that the VRE, like thermal power plants, should in future align its electricity production with the price signals of the wholesale electricity markets in order to contribute to a better balance between supply and demand. The discussion on the fundamental reform of the EEG 2014 included the introduction of a fixed instead of a variable market premium, a capacitive remuneration and a competitive tendering procedure instead of administrative subsidy amounts. Investments in VRE plants as capital-intensive technologies, however, are exposed to increasing investment and operating risks under today's prevailing market conditions - which are primarily designed for a thermal power plant park - as a result of increased market integration. In addition to rising price risks due to greater price volatility in the case of higher VRE shares, there are also new volume risks, depending on the support instruments used, as the introduction of VRE direct-marketing means that the power can be curtailed on a market-driven basis at correspondingly low prices. The merit order effect already proven in the past and the loss in market value of VRE due to the so-called simultaneity effect raise the question of whether a system with a high shares of VRE can be refinanced purely marketendogenously on the basis of a marginal cost market in the future. With the help of the agent-based electricity market model AMIRIS, which was further developed within the framework of the dissertation, different scenario analyses were carried out to answer the question and evaluated at the actor and system level. The hourly resolved simulation runs of 2015-2035 for the development of the refinancing conditions of the VRE, the VRE market values as well as the associated support efficiency in order to achieve the VRE targets with the application of a variable or fixed market and capacity premium come to the conclusion that the refinancing of a market endogenous expansion of VRE plants is not possible under the conditions of a marginal cost based electricity market. This is primarily due to the increasingly market-driven curtailment of VRE electricity volumes and the loss of market value due to the simultaneity effect. The problem here is that none of the plant operators can realistically estimate at the time of the investment what share of the meteorologically producible quantity of electricity can ultimately be sold on the market. This is because the quantities of electricity that can be marketed depend not only on the funding instrument, but above all on the future flexibility of the system. In addition, none of the instruments discussed in the reference scenario can even come close to achieving the renewable energy expansion targets by 2035. In addition, the currently implemented direct marketing system for renewables via the power exchange with competition between the decentralised direct marketers leads to inefficient curtailment decisions with regard to the variable market premium, since in this support regime there is an incentive to curtail the VRE plants with the lowest levelized-cost of electricity (LCOE) first. As the share of VRE increases, a decentralised direct marketing system will in future also lead to high information asymmetries and thus inefficient pricing in electricity wholesale. This is due to the unawareness of other market participants about the decentralised decision to curtailment VRE volumes. A central direct marketing system with a so-called 'single buyer' concept could remedy this situation. Contrary to the prevailing economic theory, the variable market premium proves to be dynamically more efficient than a fixed market premium in all scenarios examined, which in turn is more efficient than a variable and fixed capacity premium. The greatest influence on the absolute as well as relative market values of the VRE is exerted in descending order by new electricity consumers (P2X), a central instead of decentralised direct marketing system, a more even expansion ratio between wind and PV plants, a more even distribution of wind plants between northern and southern Germany, the flexible use of biomass plants, the use of electricity to electricity storage units and to relatively small proportions also a more system-oriented design of the plants (weakwind turbines). Better incentives to increase the flexibility potentials and thus better integration possibilities of the VRE are offered by the integration via the electricity utilities instead of the wholesale market.

Over the last decade a huge amount of experimental data on biological systems has been generated by modern high-throughput methods. Aided by bioinformatics, the ''-omics'' (genomics, transcriptomics, proteomics, metabolomics and interactomics) have listed, quantif ed and analyzed molecular components and interactions on all levels of cellular regulation. However, a comprehensive framework, that does not only list, but links all those components, is still largely missing. The biology-based but highly interdisciplinary field of systems biology aims at such a holistic understanding of complex biological systems covering the length scales from molecules to whole organisms. Spanning the length scales, it has to integrate the data from very different fields and to bring together scientists from those fields. For linking experiments and theory, hypothesis-driven research is an indispensable concept, formulating a cycle of experiment, modeling, model predictions for new experiments and, fi nally, their experimental validation as the start of the new iteration. On the hierarchy of length scales certain unique entities can be identi fied. At the nanometer scale such functional entities are molecules and at the micrometer level these are the cells. Cells can be studied in vitro as independent individuals isolated from an organism, but their interplay and communication in vivo is crucial for tissue function. Control over such regulation mechanisms is therefore a main goal of medical research. The requirements for understanding cellular interplay also illustrate the interdisciplinarity of systems biology, because chemical, physical and biological knowledge is needed simultaneously. Following the notion of cells as the basic units of life, the focus of this thesis are mathematical multi-scale models of multi-cellular systems employing the concept of individual (or agent) based modeling (IBM). This concept accounts for the entity cell and their individuality in function and space. Motivated by experimental observations, cells are represented as elastic and adhesive spheres. Their interaction is given by a model for elastic homogeneous spheres, which has been established for analysis of the elastic response of cells, plus an adhesion term. Cell movement is modeled by an equation of motion for each cell which is based on the balance of interaction, friction and active forces on the respective cell. As a fi rst step the model was carefully examined with regard to the model assumptions, namely, spherical shape, homogeneous isotropic elastic body and apriori undirected movement. The model examination included simulations of cell sorting and compression of multicellular spheroids. Cell sorting could not be achieved with only short range adhesion. However, it sorting completed with long range interactions for small cell numbers, but failed for larger aggregates. Compression dynamics of multi-cellular spheroids was apparently reproduced qualitatively by the model. But in a more detailed survey neither the time scales nor the rounding after compression could be reproduced. Based on these results, the applications consistent with the assumed simpli cations are discussed. One already established application is colony growth in two-dimensional cell cultures. In order to model cell growth and division, a two-phase model of the cell cycle was established. In a growth phase the cell doubles its volume by stochastic increments, and in a mitotic phase it divides into two daughter cells of equal volume. Additionally, control of the cell cycle by contact inhibition is included in the model. After examination of its applicability, the presented model is used for simulations of in vitro growth of mesenchymal stem cells (MSC) and subsequent cartilage formation in multi-cellular spheroids. A main factor for both processes is the oxygen concentration. Experimental results have shown, that i) MSC grow much better in vitro at low than at high oxygen concentrations and ii) the MSC progeny harvested from low oxygen culture produce higher amounts of the cartilage components aggrecan and collagen II in multicellular spheroids than the ones from high oxygen culture. In order to model these processes, IBM was extended by a stochastic model for cellular differentiation. In this model cellular differentiation is captured phenomenologically by two additional individual properties, the degree of differentiation and the lineage or cell type, which are subject to fl uctuations, that are state and environment dependent. After fitting the model parameters to the experimental results on MSC growth in monoclonal expansion cultures at low and high oxygen concentrations, the resulting simulated cell populations were used for initialization of the simulations of cartilage formation in multi-cellular spheroids. The model nicely reproduced the experimental results on growth dynamics and the observed number of functional cells in the spheroids and suggests the following explanation for the difference between the two expansion cultures: due to the stronger pre-differentiation found after expansion in high oxygen, the plasticity of these cells is smaller and less cell adopt the chondrogenic phenotype and start to produce cartilage. Moreover, the model predicts an optimal oxygen concentration for cartilage formation independent of expansion culture and a de-differentiating effect of low oxygen culture within 24h. Because all simulations comply with the concept of hypothesis-driven research and follow closely the experimental protocols, they can easily be tested and are currently used for optimization of a bioreactor for cartilage production. Cell populations are composed of individual cells and regulation of population properties is performed by individual cell, but knowledge about individual cell fates is largely missing due to the problem of single cell tracking. The IBM modeling approach used for modeling MSC growth and differentiation generically includes information of each individual cell and is therefore perfectly suited for tackling this question. Based on the validated parameter set, the model was used to generate predictions on plasticity of single cells and related population dynamics. Single cell plasticity was quantifi ed by calculating transition times into stem cell and differentiated cell states at high and low oxygen concentrations. At low oxygen the results predict a frequent exchange between all subpopulations, while at high oxygen a quasi-deterministic differentiation is found. After quantifying the plasticity of single cells at low and high oxygen concentration, the plasticity of a cell population is addressed in a simulation closely following a regeneration experiment of populations of hematopoietic progenitor cells. In the simulation the regeneration of the distribution of differentiation states in the population is monitored after selection of subpopulations of stem cells and differentiated cells. Simulated regeneration occurs on the time scales estimated from the single cell transition times except the unexpectedly fast regeneration from differentiated cells in the high oxygen environment, which favors differentiation. The latter case emphasizes the importance of single outlier cells in such system, which in this case repopulate less differentiated states with their progeny. In general, cell proliferation and regeneration behavior are in uenced by biomechanical and geometrical properties of the environment e.g. matrix stiffness or cell density. Because in the model cells are represented as physical objects, a variation of friction is linked to cell motility. The cultures of less motile cells become denser at the same size and the effects of contact inhibition of growth more pronounced. This variation of friction coe fficients allows the comparison of cultures with varying degrees of contact inhibition regarding their differentiation structure and the results suggest, that stalled proliferation is su fficient to explain the well-known differentiation effects in confl uent colonies. In addition, the composition of the simulated stem cell pool was analyzed regarding differentiation. In contrast to the established pedigree models, where stem cell can only be produced by asymmetric division, this model predicts that most of the cells in stem cell states descend from progenitor cells of intermediate differentiation states. A more detailed analysis of single cell derived clones revealed properties that could not be described by the model so far. First, a differentiation gradient was observed in larger colonies, that was the opposite of the one predicted by the model. Second, the proliferative activity turned out to depend not only on oxygen, but also to be a property of individual clones persisting over many generations. Because the relation slow growth/pre-differentiation also holds for single cell derived clones, the general model of differentiation is extended by another heritable individual property. Motivated by the decline of proliferation and differentiation in culture and the high metabolic and epigenetic activity during cell division, each division event is assumed to de-stabilize stem cell states. Consequently, in the model the cells age in terms of cell divisions determines the fl uctuations in stem cell states and the environment the mean fl uctuation strength. Including this novel concept, that links aging to growth and differentiation dynamics, into the model reproduces the experimental results regarding differentiation gradient and persistent clonal heterogeneity. The spatial differentiation pattern can largely be explained by the spatio-temporal growth pattern of the mono-clonal cell assembly: cells close to the border of the cell assembly have undergone more cell divisions than those in the interior and therefore their stem cell states are less stable. Heterogeneity of single-cell derived clones depends on the age of the first cell in the clone. When the stem cell fluctuations equal the mean fl uctuations strength, the proliferative activity passes a maximum at a certain age due to the destabilization of stem cell states. Thereafter the proliferative activity decreases, because more time is spent in non-proliferative differentiated states. Considering the number of divisions the cells have already undergone in vivo and after the initial expansion in vitro, it can be assumed that all cells have already passed this maximum. Interestingly, the model also predicts an optimal age for directed differentiation, when cells stably differentiate, but have not lost the required plasticity. According to the model, this clonal heterogeneity may be caused purely in vitro, but hypothetical simulation of in vivo aging yielded results consistent with experiments on MSC from rats of varying age. Finally, the detailed molecular regulation mechanisms in a multi-scale tissue model of liver zonation was studied, in which the key molecular components were explicitly modeled. Hence, this model resolved the intracellular regulation in higher resolution than the above considered differentiation models which had summarized the intracellular control and differentiation mechanisms by a few phenomenological, dynamical variables. The metabolic zonation of the liver is essential for many of the complex liver functions. One of the vitally important enzymes, glutamine synthetase, (GS) is only synthesized in a strictly defi ned pattern. Experimental evidence has shown that a particular pathway, the canonical wnt pathway, controls expression of the gene for GS. A model for transport, receptor dynamics and intracellular regulation mechanism has been set up for modeling the spatio-temporal formation of this pattern. It includes membrane-bound transport of the morphogen and an enzyme kinetics approach to fibeta-catenin-regulation in the interior of the cell. As an IBM this model reproduces the results of co-culture experiments in which two-dimensional arrangements of liver cells and an epithelial liver cell line give rise to different patterns of GS synthesis. The two main predictions of the model are: First, GS-synthesis requires a certain local cell number of wnt releasing cells. And second, a simple inversion of geometry explains the difference between the specifi c GS pattern found in the liver and in the co-culture experiments. Summarizing the results presented in this thesis, it can be concluded that properties such as the occurrence of memory effects and single cells pursuing fates far off the population average could be essential for biological function. Considering the role of single cells in many tissues, the use of individual based methods, that are able to take such effects into account, can be expected to be a very valuable tool for the problems of systems biology.