PhD student at the BGI department with Markus Reichstein | ![]() |
My background is a mix of vegetation ecology (BSc.degree), GIS & remote sensing (MSc. degree) and terrestrial biosphere modelling. Before joining the institute, I gained experience with ecophysiology and modelling the terrestrial carbon & water cycle by working with a global dynamic vegetation model (LPJ-GUESS) at Wageningen University for several years.
Within the TBM research group, the QUINCY model (Thum et al., 2019) was developed. QUINCY is a new general terrestrial biosphere model which addresses the multiway interactions of carbon, nitrogen, phosphorus and water cycles on a global scale. Its brand new soil model (JSM, Yu et al., 2020) is a vertically explicit, mechanistic microbial decomposition model. My PhD project focusses on modelling the interactions between the water cycle and soil organic matter decomposition. Within the framework of the MOCABORS project, a large part of my work will be aimed at modelling moisture dynamics and carbon sequestration in boreal soils.
Pallandt, M., Ahrens, B., Koirala, S., Lange, H., Reichstein, M., Schrumpf, M., Zaehle, S., (2022). Vertically divergent responses of SOC decomposition to soil moisture in a changing climate. Journal of Geophysical Research: Biogeosciences, 127, e2021JG006684, doi:10.1029/2021JG006684.
Thum, T., Caldararu, S., Engel, J., Kern, M., Pallandt, M., Schnur, R., Yu, L., and Zaehle, S. (2019). A new terrestrial biosphere model with coupled carbon, nitrogen, and phosphorus cycles (QUINCY v1.0; revision 1996), Geoscientific Model Development 12, 4781–4802, doi:10.5194/gmd-12-4781-2019.
Vermeulen, M.H., Kruijt, B.J., Hickler, T., Kabat, P., 2015. Modelling short-term variability in carbon and water exchange in a temperate Scots pine forest. Earth System Dynamics 6, 485-503, doi:10.5194/esd-6-485-2015.
Mücher, C.A., Kooistra, L., Vermeulen, M.H., Vanden Borre, J., Haest, B., Haveman, R., 2013. Quantifying structure of Natura 2000 heathland habitats using spectral mixture analysis and segmentation techniques on hyperspectral imagery. Ecological Indicators 33, 71-81, doi:10.1016/j.ecolind.2012.09.013.