Open PhD project: Tree-Ring Signatures of CO2 Fertilization and Altered Drought Resilience

International Max Planck Research School for Global Biogeochemical Cycles

In cooperation with Friedrich Schiller University Jena (FSU), the Max Planck Institute for Biogeochemistry (MPI-BGC) houses a unique and flexible research program that grants German and foreign students a broad selection of learning opportunities while still maintaining a research focus. The International Max Planck Research School for Global Biogeochemical Cycles (IMPRS-gBGC) offers a PhD program specializing in global biogeochemistry and related Earth system sciences.

Homepage: https://www.bgc-jena.mpg.de/en/imprs

Jena, Germany

Academic

Biogeosciences (BG)

Full time

Entry level

We offer scholarships for 4 years and full-time contracts for 3 years within an international and multidisciplinary working environment. The starting date is flexible.

Master

5 August 2025

3 July 2025

Project description
Tree rings serve as invaluable archives of climate history, recording forest responses to rising atmospheric CO₂ and climatic extremes while illuminating key physiological processes. Elevated CO₂ enrichment is expected to trigger enhanced photosynthetic productivity (the CO₂ fertilization effect). Concurrently, rising CO₂ also triggers stomatal closure dynamics—allowing trees to reduce water loss through transpiration while maintaining sufficient CO₂ uptake. This CO₂-response potentially enhances tree resilience under drought stress, suggesting a changing forest responses to aridity under elevated CO₂. Earth system models incorporate these mechanisms, projecting strong CO₂-driven feedbacks that modulate future climate trajectories; the magnitude of these effects remains uncertain, however, should leave a discernible imprint in tree-ring records.

This project leverages the rich temporal resolution of tree-ring data to address critical knowledge gaps in forest responses to rising CO₂. First, we will analyze tree-ring records—including isotopic signatures reflecting photosynthetic mechanisms—to identify distinct CO₂ signatures and quantify forest biomass responses. Using causal inference methods (e.g., Zhan et al., 2024), we will disentangle productivity and drought response dynamics from confounding factors to test theoretical expectations of CO₂ fertilization. Second, we will assess the temporal evolution of CO₂ sensitivity in trees, evaluating hypotheses regarding potential saturation of the fertilization effect. Third, we will integrate tree-ring data with complementary spatial datasets (e.g., FLUXNET, remote sensing) to investigate forest-climate interactions under rising CO₂. This analysis will ultimately provide data-driven insights that serve as critical constraints for Earth system models, refining projections of forest development and its role in the global carbon cycle.

Working group and planned collaborations
The successful PhD candidate will work in the Atmosphere-Biosphere Coupling, Climate and Causality group of the Department of Biogeochemical Integration at the Max Planck Institute for Biogeochemistry. The project is embedded in the MC3 4 Earth Max Planck Center – a collaboration between:

• Max Planck Institute of Biogeochemistry
• Max Planck Institute for Chemistry
• California Institute of Technology
• Carnegie Institution for Science (Department of Global Ecology)
• Columbia University.

Further, the PhD candidate will benefit from the European Lab for Learning and Intelligent Systems (ELLIS) and will work closely with the ELLIS Unit Jena.

Your profile
The ideal candidate has the following qualifications:

• Successfully completed scientific university studies (Master’s degree; or close to completion) in meteorology, ecology, environmental sciences, geosciences, computer science, informatics, bioinformatics, physics, or comparable fields.
• Basic understanding of terrestrial biogeochemical cycles, terrestrial ecology, biosphere-climate interactions.
• Practical experience in scientific programming and data processing, and ideally in the development and application of numerical models and/or machine learning models.
• Knowledge and experience in the use of numerical and statistical analysis using languages such as Julia, Python and/or similar programming languages.
• Experience in the use of HPC clusters, including detailed knowledge of scripting languages for process execution and automation, is desirable.
• Ability to work independently as well as in an interdisciplinary team
• Very good written and spoken English.

The Max Planck Society (MPS) strives for gender equality and diversity. The MPS aims to increase the proportion of women in areas where they are underrepresented. Women are therefore explicitly encouraged to apply. We welcome applications from all fields. The Max Planck Society has set itself the goal of employing more severely disabled people. Applications from severely disabled persons are expressly encouraged.

References
Zhan, C., Orth, R., Yang, H., Reichstein, M., Zaehle, S., De Kauwe, M.G., Rammig, A., Winkler, A.J., 2024. Estimating the CO2 Fertilization Effect on Extratropical Forest Productivity From Flux-Tower Observations. Journal of Geophysical Research: Biogeosciences 129, e2023JG007910. https://doi.org/10.1029/2023JG007910

Application deadline for the fully funded PhD positions is August 5th, 2025. Pre-interviews via web conference will be carried out and promising candidates will be invited to take part in our selection symposium (September 30th – October 1st, 2025).

Find out more and apply online: https://www.bgc-jena.mpg.de/en/imprs/career-application

The Max Planck Society is committed to increasing the number of individuals with disabilities in its workforce and therefore encourages applications from such qualified individuals. The Max Planck Society seeks to increase the number of women in those areas where they are underrepresented and therefore explicitly encourages women to apply.