Profile summary

  • Complex systems theory
  • Resilience assessments
  • Non-linear dynamics
  • Network science
  • Information theory

Hannah Zoller's research focuses on non-linear dynamics of complex systems and the emergent phenomena that arise across a range of scales, from microbial communities to earth system processes

Zoller is currently focusing on an advanced understanding of the interactions between certain earth system processes in the planetary boundary framework. This project represents a natural extension of her data-driven work on the dynamic interaction patterns of general adaptive systems. In her work, she makes use of the abstract concept of distributed computation and the rich toolbox of information theory. A major aspect of her study of complex systems is their resilience, which she approaches via spectral graph theory. Together, those methods provide a holistic approach to the analysis of complex systems development, which has been applied to microbial, economic, as well as socio-ecological system.

Zoller holds a PhD in Mathematics from the Technical University of Munich (2016-2021). Being a mathematician by training, she developed a general quantification of Gunderson’s and Holling’s Adaptive Cycle Metaphor for her PhD at Helmholtz Munich, Department of Scientific Computing. Zoller worked as a postdoctoral researcher at the GFZ German Research Centre for Geosciences, Department of Geoinformation, before starting as a researcher at the Stockholm Resilience Centre in 2024.

Zoller is particularly interested in matchmaking theory and application, and in thereby helping bridge the gap between theoretical mathematics and life sciences.

Key publications

Schrenk, H., Magnússon, B., Sigurdsson, B. D., and zu Castell, W. 2022. Systemic analysis of a developing plant community on the island of Surtsey. Ecology and Society 27. https://ecologyandsociety.org/vol27/iss1/art35/

Schrenk, H., Garcia-Perez, C., Schreiber, N., and zu Castell, W. 2022. QtAC: an R-package for analyzing complex systems development in the framework of the adaptive cycle metaphor. Ecological Modelling 466:109860. https://www.sciencedirect.com/science/article/pii/S0304380021003987?via%3Dihub

zu Castell, W. and Schrenk, H. 2020. Computing the adaptive cycle. Scientific Reports 2020(10):18175. https://www.nature.com/articles/s41598-020-74888-y