PhD project offered by the IMPRS-gBGC in January 2022


Ecological forecasting of dryland vegetation dynamics in a changing world *

Sönke Zaehle , Shilong Piao , Nathasha MacBean

Project description

Drylands cover ~40% of global land area, are home to ~40% of the global population and harbor more than 20% of global biodiversity. Drylands face significant challenges from climate change (e.g. changes in temperature and precipitation patterns leading to extended drought) and intensified anthropogenic activities and disturbance (e.g. over-grazing) leading to land degradation and desertification. However, our ability to accurately assess and predict dryland vegetation dynamics remains limited, largely due to the lack of understanding of the biological and ecological mechanisms/processes driving the spatial-temporal dynamics of dryland vegetation under climate change and land-use changes.

In the framework of the highly collaborative and interdisciplinary DRYLANDS project between the Max Planck Institute for Biogeochemistry (MPI-BGC) and the Chinese Academy of Sciences Research Center for Eco-Environmental Sciences (CAS-RCEES), this PhD project aims to improve the predictive capacity of carbon and water cycle responses to seasonal and interannual varying drought in drylands. The project provides a unique opportunity and training to integrate available and newly-collected observations with a state-of-the-art biosphere model (QUINCY) and thereby contribute to the continuous development of this model. Specifically, the successful applicant will synthesize complementary streams of long-term monitoring observations (eddy covariance, soil moisture, remotely sensed vegetation indices) and observations from field and process studies carried out across a gradient of dryland ecosystems in the DRYLAND project using the QUINCY model. The data-constrained model will be used (i) to assess the predictive skill in forecasting seasonal to interannual responses of carbon and water fluxes to climate variability and extremes and (ii) to assess the impact of future scenarios of climate and land-use change on dryland carbon and water fluxes and potential climate feedbacks.

Working group & co-operations

The successful PhD candidate will be affiliated with the Terrestrial Biosphere Modelling group in the MPI-BGC Signals Department (Dr. Sönke Zaehle, land surface modelling, model-data synthesis), and will benefit from collaborations with the Institute of Tibetan Plateau Research (ITP) of the CAS (Prof. Shilong Piao, remote sensing, Eddy covariance fluxes) and the University of Indiana (Prof. Nathasha MacBean, land surface modelling and data assimilation). As part of the joint MPG-CAS research project, the PhD candidate also has the opportunity to collaborate with researchers from other MPI department and CAS institutions, spanning multiple disciplines (e.g. ecosystem observations and manipulations).


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's degree in environmental / Earth system science, environmental engineering, physics or a computational science or a similarly relevant discipline.
  • Very good programming skills in a modern script language (e.g. python, R, Julia), and/or programming language (e.g. FORTRAN, C++).
  • One or more of the following would be very advantageous:
    • Knowledge on global change ecology and dryland processes.
    • Experiences in process-based numerical ecosystem or land surface modelling
    • Experience with data-assimilation or ensemble simulation techniques.
  • Good English written and communication skills.
The Max Planck Society (MPS) strives for gender equality and diversity. The MPS seeks to increase the number of women in those areas where they are underrepresented and therefore explicitly encourages women to apply. The MPS is committed to increasing the number of individuals with disabilities in its workforce and therefore encourages applications from such qualified individuals.

>> more information about the IMPRS-gBGC + application