There is limited knowledge on how the association of trees with different mycorrhizal types shapes soil microbial communities in the context of changing tree diversity levels. We used arbuscular (AM) and heterospecific tree species pairs (TSPs), which were established in plots of three tree diversity levels including monocultures, two-species mixtures and multi-tree species mixtures in a tree diversity experiment in subtropical China. We found that the tree mycorrhizal type had a significant effect on fungal but not bacterial alpha diversity. Furthermore, only EcM but not AM TSPs fungal alpha diversity increased with tree diversity, and the differences between AM and EcM TSPs disappeared in multi-species mixtures. Tree mycorrhizal type, tree diversity and their interaction had significant effects on fungal community composition. Neither fungi nor bacteria showed any significant compositional variation in TSPs located in multi-species mixtures. Accordingly, the most influential taxa driving the tree mycorrhizal differences at low tree diversity were not significant in multi-tree species mixtures. Collectively, our results indicate that tree mycorrhizal type is an important factor determining the diversity and community composition of soil microbes, and higher tree diversity levels promote convergence of the soil microbial communities.

This thesis is divided into a theoretical part, aimed at developing statements around the newly introduced concept of pattern morphisms, and a practical part, where we present use cases of pattern structures. A first insight of our work clarifies the facts on projections of pattern structures. We discovered that a projection of a pattern structure does not always lead again to a pattern structure. A solution to this problem, and one of the most important points of this thesis, is the introduction of pattern morphisms in Chapter4. Pattern morphisms make it possible to describe relationships between pattern structures, and thus enable a deeper understanding of pattern structures in general. They also provide the means to describe projections of pattern structures that lead to pattern structures again. In Chapter5 and Chapter6, we looked at the impact of morphisms between pattern structures on concept lattices and on their representations and thus clarified the theoretical background of existing research in this field. The application part reveals that random forests can be described through pattern structures, which constitutes another central achievement of our work. In order to demonstrate the practical relevance of our findings, we included a use case where this finding is used to build an algorithm that solves a real world classification problem of red wines. The prediction accuracy of the random forest is better, but the high interpretability makes our algorithm valuable. Another approach to the red wine classification problem is presented in Chapter 8, where, starting from an elementary pattern structure, we built a classification model that yielded good results.

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