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RD 4 - Research Areas


In the research area Complex Systems networks of networks are our pivotal approach for the transdisciplinary study and modelling of heterogeneous climate impacts and interacting social systems.

The research area is structured into 3 flagship projects:

  • In the flagship project Complex Networks of Networks (NEONET), we pioneer this new direction, develop new tools for the reconstruction, characterization, design, control, and adaptation of network of networks, and analyse structure formation on evolving networks of networks such as collective behavior, clustering, synchronization, and especially stability.
  • Essential input for the complex networks studies are provided by the flagship project Time Series Analysis (TSA), where we develop and critically test new methods for the detection of causal relationships and coupling directions. We focus on making these applicable to challenging data sets such as extreme events data or data with time uncertainties or irregular sampling (e.g., palaeoclimate data from stalagmites).
  • The new joint flagship project with RD1, Coevolutionary Pathways (COPAN), uses NEONET methods and the results from the flagship METAB (see below) to study feedbacks, stable attractors, phase transitions, and sustainable pathways in the mid- and long-term coevolution of natural and social systems to identify emergent properties like the great acceleration or societal collapse.


In the research area Social Metabolism we study stocks and flows of energy and raw materials which support human societies (social metabolism) and explore intervention strategies to assist policies of sustainable socio-metabolic pathways. The dual role of the industrial metabolism in raising the standard of living while creating global environmental change has been amply demonstrated by sustainability science. Comparatively less is known about the complex structure of socio-metabolic network, their social regulation and feasible leverage points for their transformation.

This research area is structured into one flagship Project and one Governance Group

  • Adaptive Networks of social-metabolic Flows (METAB) focuses on new complex network methods to improve our understanding of the structure, evolution and potential vulnerability of socio-metabolic systems at global and urban scales and how these are structurally coupled to socio-economic dynamics.
  • The group Governance and Policy of socio-metabolic transformations develops innovative methods to exemplarily link the quantitative assessment of physical flows with the institutional, governance, and discourse structures with respect to societal transformations towards a low-carbon society.


Cross-Cutting Group

Computational Methods (COMET) is a cross cutting research activity with a clear focus on modelling, simulation and data analysis. By bringing together domain experts, developing and applying tools and languages for model specification, model quality assurance, visualization of climate data and visual analytics, COMET substantially supports PIK's modelling effort and contributes to the implementation of a PIK-wide modelling strategy.



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