Marleen Pallandt, MSc.

Per 01.01.2024 I moved to Stockholm University. Please find my updated web page here: https://www.su.se/english/profiles/mapa7208-1.705205

Research Interests

• terrestrial C & water cycle
• process-based terrestrial biosphere models
• remote sensing of vegetation

About me

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.

PhD project

My PhD project focused on modelling the role of soil moisture and temperature on SOC decomposition. The thesis was submitted to Bayreuth University and is currently under review (updated April 2024).

Selected Publications:

• Pallandt, M., Schrumpf, M., Lange, H., Reichstein, M., Yu, L., and Ahrens, B.: Drought counteracts soil warming more strongly in the subsoil than in the topsoil according to a vertical microbial SOC model, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2024-186, 2024.
• 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. JGR: Biogeosciences 127, https://doi.org/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). Geosc. Mod. Dev. 12, https://doi.org/10.5194/gmd-12-4781-2019
  
• Vermeulen, M., Kruijt, B., Hickler, T., Kabat, P., 2015. Modelling short-term variability in carbon and water exchange in a temperate Scots pine forest. Earth Syst. Dynam., 6, https://doi.org/10.5194/esd-6-485-2015
• Mücher, C.A., Kooistra, L., Vermeulen, M., 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,  https://doi.org/10.1016/j.ecolind.2012.09.013