Complex Systems

Environmental Research

Dietary vs. chronological age

It is well known, that the intestinal microbiome is changing during the first years of life due to the change of diet. Commonly, a continuous transition starting from a diet comprising breast or formula milk towards a more complex nutritional regime, with solid food and without breast- or formula-feeding takes place. As the huge impact of diet on the composition of the intestinal microbiome has frequently been shown and the influence of the intestinal microbial community composition on early allergy onset has been postulated, we hypothesize that the “dietary age” of a child might be the more appropriate factor to account for than the actual biological age itself.

Prediction of Random Forrest Regression using samples with biological age <0.5 years from infants being exclusively breast fed (blue), breast fed with additions (light blue), formula fed (orange), or neither breast nor formula fed (red).

The obtained stratification according to dietary age can be used for subsequent analysis of host-microbe interactions and ecological factors.

Succession on the Island of Surtsey

The Island of Surtsey was formed during a volcanic eruption in the Vestmannaeyjar archipelago in the 1960s. From that date, the development of its flora and fauna has been systematically monitored. Longitudinal abundance data of the detected species allow us to apply our maturation method. By means of the resulting networks of information transfer, we can visualize the structural change of this system and find indications of the role of individual species. Significant properties of these networks suggest Surtsey's transition to a new vegetative period in the last decade. This transition is confirmed in literature about the island's development. In combination with biological background knowledge and the network-based information about the system's communication structure, we can find hints on possible reasons for the system's breakdown and reorganization.


Maturation of ectomycorrhizal communities under high stress factor

In course of the development and validation of plausibility of our maturation method, we are interested in real-life case studies investigating the development process of complex systems. Those systems facing perturbations are of particular interest to us as they can enable us to observe resistance strategies or a breakdown and reorganization process.
For this purpose, we are thankfully provided with data of the 'Kranzberg Forest Roof Experiment' (KROOF), a project carried out by forest scientists and biologists of the Technische Universität München and the Helmholtz Zentrum München. In this project, the effect of reduced water availability and tree mixture in a mature stand of European beech and Norway spruce is examined. Among others, the focus is on the impact of drought on the ectomycorrhizal communities, which play a crucial role in the exchange of water, carbon and mineral nutrients between plant and soil. Their adaptability, robustness and and effectiveness can be understood as a measure for the corresponding properties of the plant.
The experimental setup includes twelve plots, each of which can be divided into three zones: one in which spruce trees neighbour spruce trees, one in which beech trees neighbour beech trees and a mixed zone. Six of the plots are equipped with retractable roofs, which keep out throughfall from spring to autumn. Yearly abundance data of the fungal species identified in the mycorrhiza in the three zones of the plots are available.
By means of our method, we want to investigate the development of the myccorhizal communities challenging drought in the different zones. We try to explain their development taking into consideration the networks of information transfer resulting from our method. Thereby, we hope to confirm well-known facts and conclusions in corresponding publications and to develop new hypotheses.


Past Projects

Systemic analysis of plants

Systemic analysis of plants, in particular the study of plant systems within a dynamically changing environment is crucial for the understanding of future developments of the earth's environmental system. Combining data from various scales and sources, plant systems biology aims at unravelling central mechanisms of plant-environment interaction.

Methods from image analysis can be used to estimate crucial parameters for modelling and statistical analysis.

Color Based Classification

Machine learning and data-driven analysis further allow to identify common patterns and characteristics.