PhD position in Integrated Forest Risk Management

The Forest Resources Management (FORM) at ETH aims to maximise forest utilities for humans today and in the future. With this vision in mind our research is centred around the development of impact oriented new approaches to inventory our forest resources, decision support systems to manage our forests sustainably under risk, and translating our findings to policy and practice.

Project background

Forest ecosystems are increasingly exposed to risks. Climate extremes increase in frequency and severity and impact forest functions and ecosystem services. Accordingly, our forecasts of what to expect from forests when it comes to resources available for human consumption or the availability of forest ecosystem services need to consider these unknowns.

While select risks are considered in almost every attempt to forecast forest development today, three main shortcomings still exist: 1) reliance on past observations for probability-based assessments, 2) neglect of extreme events, and 3) a disregard for the complex interactions between risk factors.

Mathematical theories such as the Dragon King claim that extreme events may be generated by mechanisms such as positive feedback, tipping points, and phase transitions in nonlinear and complex systems, making them potentially predictable with a deep understanding of system dynamics. This project will improve the integration of risk into forest models by investigating the mechanisms underlying extreme events and cascading effects of natural disturbances in forests and exploring suitable approaches to effectively detect and consider them in forest management.

Job description

  • You will gain in-depth knowledge of the mechanisms underlying cascading effects and extreme events in forests, find suitable data to test your theories, and will drive the development of solutions that may change how we manage our forests.
  • You will explore how concepts such as the Dragon king theory offer potential solutions for improving the integration of risk into forest models.
  • You will publish your research findings in journal articles and present them at national and international conferences.
  • You will contribute to and participate in various FORM group activities, including related research and teaching activities.

Your profile

  • You hold a MSc in forestry, environmental science, geography, mathematics, stats or a similar field.
  • You enjoy programming and have experience with Python in data analysis and/or numerical modelling.
  • You are enthusiastic to learn about forest dynamics, natural disturbances, climate change, and the processes shaping patterns in forested landscapes.
  • You have good oral and written communication skills in English, German is an advantage.
  • You are highly committed, creative, and motivated to learn new skills.
  • You enjoy working in an open, diverse, and interdisciplinary team.

For more details and to apply:

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