PhD project offered by the IMPRS-gBGC in Jan 2025

The Role of Microbial Communities in Arctic Permafrost Ecosystems and the Relevance for Gas Exchange

Janina Rahlff, Mathias Goeckede, Christian Jogler, Judith Vogt

Project description

We invite expressions of interest from talented researchers to apply for a PhD project exploring the role of microbial and viral communities in biogeochemical processes within Arctic permafrost landscapes. The project focuses on microbial contributions to gas exchange processes at the interfaces of soils and thermokarst lakes. The project explores how microbial metabolic potential - including modulation by viruses - derived from metagenomic data, correlates with measured gas fluxes and environmental metadata. Soil and lake samples were collected during a 2024 field campaign in the Canadian Arctic, conducted in collaboration with Dr. Mathias Goeckede and Dr. Judith Vogt (Max Planck Institute for Biogeochemistry, Jena). Additional sampling opportunities may be available during the PhD funding period. We are particularly interested in candidates with a background in bioinformatics, microbial ecology, environmental microbiology, or related fields. Willingness to learn the analysis of high-throughput sequencing data and microbial functional profiling is essential. The project offers flexibility for the researcher to pursue their own scientific ideas within the broader framework of microbial-environment interactions and climate relevance.

Research program

Explore the microbial community composition (abundance and diversity) as well as the microbial and viral metabolic role in Arctic permafrost ecosystems in relation to typical environmental perturbations by using -omics approaches combined with cultivation of saprophytic gas producing key players in such habitats such as bacteria from the phylum Planctomycetota along with their phages. Changes in microbial communities and metabolic potential will be linked to gas exchange fluxes.

Working group

The successful PhD candidate will join the junior research group of Dr. Janina Rahlff embedded in the RNA Bioinformatics & High Throughput Analysis group of Prof. Dr. Manja Marz at the Friedrich-Schiller University of Jena. Associated molecular laboratories are accessible via the Fritz Lipmann Institute e.V. (FLI). Microbial laboratories are available in the Department of Microbial Interactions (FSU). The student will benefit from training and networking opportunities offered by the European Virus Bioinformatics Center. A close collaboration with the European Research Council Synergy Project Q-ARCTIC group, which is part of the Department of Biogeochemical Signals at the Max Planck Institute for Biogeochemistry, will be established.

Requirements

Applications to the IMPRS-gBGC are open to well-motivated and highly-qualified students from all countries. Prerequisites for this PhD project are:

a Master degree in bio(geo)chemistry, environmental science, bioinformatics, (geo-) ecology, biology, soil or aquatic science or other disciplines related to environmental sciences
openness to conduct field work in Arctic permafrost ecosystems (like the Canadian Arctic, North of Sweden):

microbiological sampling of soils and aquatic surface films from lakes to explore microbial consortia
employ gas chambers in soils and lakes to measure gas fluxes

Additional lab skills that would be advantageous

molecular techniques (RNA/DNA extraction)
micro-respiration experiments with natural microbial communities

Computational skills (essential or strong affinity)

skills to process and analyze metagenomic datasets and predict the metabolic potential of microbes and viruses (using BASH, R) are a strong asset
statistical analysis

Interest in combining microbiology and biogeochemistry data
Strong interest in handling large bioinformatic datasets (one of the main tasks in this PhD position)
Excellent oral and written communication skills in English are required, knowledge of German is an asset

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.

PhD project offered by the IMPRS-gBGC in Jan 2025

Improving soil-plant-atmosphere modeling under drought conditions via coupled processes and data integration

Shijie Jiang, Yijian Zeng, Sung-Ching Lee, Gregory Duveiller, Alexander Brenning, Markus Reichstein

Project description

Climate change has intensified droughts worldwide, putting ecosystems under increasing water stress and threatening their resilience. Understanding how ecosystems respond to water limitation is essential for predicting future impacts on carbon and water cycles. In particular, soil-plant-atmosphere interactions - such as root water uptake, plant hydraulic function, and canopy energy exchange - are key to understanding how ecosystems cope and adapt to drought. However, existing models often struggle to accurately capture these interactions under varying environmental conditions due to the complexity of coupling processes across soil, root, hydraulic, and canopy systems. This project seeks to address these gaps by applying and further developing a Soil-Plant-Atmosphere Continuum model (e.g., the STEMMUS-SCOPE model) that incorporates plant hydraulic dynamics (e.g., PSInet data). In addition, data-driven parameterization using machine learning will be considered to improve specific process representations to create a flexible and accurate hybrid model for simulating water-carbon dynamics under drought. Particularly, interpretable machine learning techniques will be used to deepen our understanding of key mechanisms and to complement existing mechanistic models.

The overarching goal of this PhD project is to improve our understanding and predictive ability of soil-plant-atmosphere interactions under drought conditions through the development of a coupled, data-integrated model. Using state-of-the-art data-driven approaches, the research aims to reveal hidden relationships and provide actionable insights into the complex non-linear dynamics linking soil moisture, plant hydraulics, and canopy fluxes, particularly in response to water stress and changing environmental conditions. Ultimately, these efforts aim to provide early warning indicators of ecosystem stress and insights for better ecosystem management under a changing climate. The prospective PhD student will be encouraged to explore their own innovative approaches within this integrated modeling framework, emphasizing both mechanistic understanding and data-driven improvements.

Working group

The successful candidate will work in the Department of Biogeochemical Integration at the Max Planck Institute for Biogeochemistry and will also be affiliated with the Friedrich Schiller University, Jena. The working group offers long-standing expertise and experience in the various fields relevant to this project. There will be a close collaboration with the Department of Water Resources of the University of Twente, the Netherlands. For further information, please contact Shijie Jiang.

Requirements

Applications to the IMPRS-gBGC are open to well-motivated and highly-qualified students from all countries. Prerequisites for this PhD project are:

Master's degree in ecohydrology, environmental science, earth system science, biogeosciences, climate science or related fields.
Strong background in eco(-/)hydrological modeling. Experience in data integration and machine learning (e.g., neural networks) for environmental applications is preferred but not required.
Proficiency in a modern programming language (e.g., Python, R, Julia).
Broad interest in soil-plant-atmosphere processes and water-carbon dynamics.
Fluency in spoken and written English.
Willingness to work in an interdisciplinary environment with geoscientists and computer scientists.

References

Wang, Y., et al. (2021). Integrated modeling of canopy photosynthesis, fluorescence, and the transfer of energy, mass, and momentum in the soil–plant–atmosphere continuum (STEMMUS–SCOPE v1. 0.0). Geoscientific Model Development, 14(3), 1379-1407.

Reichstein, M., et al. (2019). Deep learning and process understanding for data-driven Earth system science. Nature, 566(7743), 195-204.

Green, J. K. (2024). The intricacies of vegetation responses to changing moisture conditions. New Phytologist.