For a long time, water shortages and flooding have been challenges in many parts of China. Meanwhile, the Chinese government announced the change of water management from engineering-oriented approach towards integrated approach in the last decades. However, the announced changes in management approach does not necessarily lead to the wide implementation of institutions, infrastructures and practice. They can be confronted by a strong resistance from the existing management approach. In fact, the development of water resources management is a complex process. Such a complexity raise the following questions: did fundamental changes really take place in the structure of water supply and demand management and flood management in China? If yes, how? In order to answer this question, the author (1) developed conceptual frameworks to enable a detailed and precise analysis of regime development; (2)applied the elaborated conceptual frameworks to explore the development of the water resources management regime in China, at the example of three case studies. These three case studies were: •Flood Management (IFM) took place in the Dongting Lake Area in the middle Yangtze River, •Water allocation in the Yellow River Basin, •The experimentation period of Water Saving Society in China. With the support of the developed framework, the case studies show that fundamental changes, i.e. transitions, have taken place in flood management regime and water supply-demand regime in China, but transitions have not yet completed, due to, namely, the lack of reconfiguration of other regime components and other relevant regimes. In addition, the case studies also depict how the start of transitions were triggered and how informal learning processes influenced regime development. The thesis contributed to sustainability transitions research by developing an operational approach to analyze transitions of water resource management regime and by expanding the empirical basis for transitions research to natural resources management regime in emerging economies.

Grasslands cover 40% of the earth’s land area and provide numerous valuable ecosystem services. However, climate change, global land use change and increasing intensive anthropogenic interventions make grasslands to one of the most endangered ecosystem types in the world. Effective protection in the future requires a fundamental understanding of the dynamics of grasslands and their major drivers. Field experiments have been conducted for impact analyses, for example, with different management intensities, plant community composition and altered climatic conditions. Complementary, ecological models allow to extend the analysis to long-term effects of changes as well as to a deeper understanding of the underlying ecological processes. In this thesis, an individual-based grassland model and network science were applied to understand the community structure and dynamics emerging from individual plant interactions – in relation to plant traits, ecological processes, environmental and anthropogenic impacts, and the small-scale spatial distribution of plants. In the first study, an individual-based process-oriented grassland model was parameterized to simulate field data of a local biodiversity experiment using the concept of plant functional types. The influence of various functional plant traits and ecological processes on grassland productivity and functional composition were analyzed. Different functional plant traits showed partly contrasting effects on plant growth. With regard to the modeled ecological processes, competition for space between plants affected grassland productivity more than shading of plants. In the second study, the parameterized grassland model was used to analyze the impact of functional diversity, mowing frequency and air temperature on ecological processes that lead to changes in grassland productivity. The model reproduced the increase of biomass yields with functional diversity as observed in the field experiment. Modeled plant competition for space showed to be the dominant process and was responsible for an increase in biomass yields in more frequently mown grasslands. In the third study, an approach to generate a regionally transferable parameterization of the grassland model is presented. The impact of management, environment and climate change on productivity and functional composition of grasslands was analyzed within a German-wide scenario analysis. Management intensity had more influence on grassland productivity than environmental factors and correlations of productivity with environmental factors become stronger in less managed grasslands. Climate change showed to have only a minor influence on simulated vegetation attributes. In the fourth study, network science was applied to forest megaplots to quantify the spatial neighborhood structure of species-rich ecosystems. Networks at the individual-tree and tree-species levels revealed similar structures at three investigated forest sites. Tropical tree species coexisted in small-scale networks and only up to 51% of all possible connections between species pairs were realized. A null community analysis showed that details on the tree position and tree size have no major influence on the network structures identified. In summary, this thesis presents the development of advanced methods and analysis tools as well as their application to vegetation ecosystems with high diversity. Thereby, complex structures and dynamics of ecological systems could be systematically explored by combining ecological models with extensive field measurements.

Terrestrial environments are highly complex and dynamic. It consists of various types of soils which are constantly exposed to fluctuating conditions affecting their physical and biological properties. Moreover, soils are delivering several ecosystem services with high relevance for the human well-being such as water purification, nutrient cycling, or biodegradation. For many of those ecosystem services, microorganisms are the main drivers. In consequence, it is important to understand the functional response of microbial ecosystems to disturbances. Thus, identifying key factors for the functional stability of microbial ecosystems in terrestrial environments is of high interest. A powerful tool for analysing dynamics and underlying mechanisms of ecosystems are computational simulation models. Within this doctoral thesis, a spatiotemporally explicit bacterial simulation model was developed for assessing dynamics of biodegradation as a typical microbial ecosystem function under the influence of disturbances. Disturbances were introduced as lethal events for the bacteria within a certain, randomly picked disturbance area. The disturbance characteristics vary in the spatial configuration and frequency of the disturbance events. Functional stability was analysed in terms of the ability to recover the function after a single disturbance event, i.e. functional resilience, and the ability to maintain the function during recurrent disturbance events, i.e. functional resistance. Key factors for functional stability were assessed by systematically varying properties and processes of the microbial ecosystem and characteristics of the disturbance regime. Simulation results show a high influence of the disturbance characteristics, especially its spatial distribution pattern, on the stability of biodegradation. Functional resistance and resilience increase with fragmentation of the spatial pattern of the disturbances. The frequency of recurrent disturbance events proved also essential for the functional resistance: if the disturbances occur too often, the emergence of a functional collapse may not be preventable. However, if the fragmentation of the applied disturbance patterns increases, the function is also maintained under more frequent disturbances without a functional collapse. Ecological processes such as bacterial dispersal and growth are shown to enhance the biodegradation performance, but only under specific disturbance regimes, again depending on frequency and fragmentation of the disturbances. Dispersal networks are shown to increase the functional stability in many scenarios and, thus, may serve as a buffer mechanism against disturbances. Therefore, strategies facilitating these ecological processes, for instance stimulating fungi that act as dispersal networks for bacteria, or modulating the physical soil structure to alter the spatial configuration of disturbances are proposed to increase the functional stability of microbial ecosystems.

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