PhD position (4 years): Can ecological systems remember? Information, ecological debt and evolution under climate extremes

PhD position (4 years): Can ecological systems remember? Information, ecological debt and evolution under climate extremes

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Climate extremes, such as heat waves and drought, can leave persistent imprints on biological systems, even after their apparent recovery. These ecological memories may be encoded in genetic changes, physiological responses, species interactions, community organization or environmental modifications. Yet we know surprisingly little about how ecological memories are generated, retained, transmitted or lost, and whether they help or hinder future ecological and evolutionary responses.

This PhD project will investigate a potentially transformative idea: ecological systems may retain and transmit information about environmental extremes, and this information could be critical for predicting their future persistence and adaptation. Using experimentally assembled soil food webs comprising bacteria, fungi, bacteriophages and springtails (Collembola), the researcher will explore three interconnected questions:
1. How do ecological systems acquire and store information? Investigate how environmental extremes generate ecological memories across different levels of biological organization.
2. How does ecological memory propagate? Explore whether information about past extremes can be transmitted between organisms, trophic groups and generations through ecological interactions and environmental modifications.
3. Can ecological memory predict persistence and adaptation? Examine whether retained information enhances resistance and recovery, facilitates evolutionary adaptation, or generates persistent ecological debts and vulnerabilities.

The project will combine controlled microcosm experiments, experimental evolution and quantitative modelling. Ecological systems will experience contrasting histories of climate extremes, followed by recovery periods and subsequent environmental challenges. The researcher will use a resistance - recovery framework to investigate ecological debts and test whether communities that appear to have recovered nevertheless retain hidden vulnerabilities or capacities for adaptation.

An innovative component will involve exploring information-theoretic approaches to understand ecological memory, distinguish it from other environmental legacies, and examine whether it improves forecasts of future ecological and evolutionary dynamics. The project offers substantial intellectual freedom to develop original hypotheses, experimental approaches and theoretical perspectives, supported by an interdisciplinary research environment.

We welcome applicants with a strong background in ecology, evolutionary biology, microbiology, systems biology or related disciplines. Experience with experimental research, quantitative analyses or programming (e.g., R or Python) would be advantageous. Above all, we value scientific curiosity, original thinking, critical reasoning and a willingness to challenge established assumptions. Applicants are not expected to have expertise in every discipline involved in the project.

The successful candidate will join the Terrestrial Ecology research group at the University of Bern, working in a collaborative environment that combines ecological experiments, evolutionary biology, climate-change research and quantitative approaches.

Collaborative environment and ambitious team

Strong research infrastructure and international network

Individual career support

International reputation

How to apply: Show us how you think!

We are taking a different approach to evaluating applications. We do not require a motivation letter. Instead, we would like to see how you think about scientific questions.
Please submit a single PDF containing the following three pages:
Page 1 - Concise CV (maximum one page)
Present your academic background, relevant skills and key achievements.
Optional: Briefly explain your most important academic or research contributions and what you personally accomplished.
Page 2 - Conceptual scientific figure (maximum one page)
Develop an original conceptual figure illustrating how you would approach one or more of the three research questions outlined above. Your figure should communicate a scientific idea, hypothesis or mechanism and illustrate how you might investigate it experimentally or quantitatively. You may include a short explanatory caption (maximum 150 words). We are not looking for a complete research proposal or an elaborate experimental design. We are interested in your scientific imagination, reasoning and ability to connect ideas. Hand-drawn figures, digitally created diagrams and AI-assisted illustrations are equally welcome. We will evaluate the originality, clarity, scientific reasoning and testability of your ideas, not the artistic quality of the figure.
Page 3 - Appendix: Use of AI tools (maximum 50 words)
The use of AI tools is welcome and encouraged. Briefly describe which AI tools you used and how they contributed to developing your ideas, scientific reasoning or conceptual figure. If no AI tools were used, please state this. All applicants should be able to explain and critically defend their scientific ideas.

April 2027 or later, by arrangement

Full-time

Temporary

Employee

A levels

madhav.thakur@unibe.ch