Department Biogeochemical Signals

Department Biogeochemical Signals

Prof. Dr. Sönke Zaehle

Interactions between land eocsystems, atmosphere and the climate system.

The aim of the Biogeochemical Signals Department is to improve our understanding of the interactions between biogeochemical element cycles on land surface and the atmosphere on local, regional and global scales. In addition to the climate-relevant cycles of carbon and water, our research focuses on the essential  nutrients nitrogen (N) and phosphorus (P) and their importance for plant growth, soil dynamics and feedbacks between biospheric processes and climate.

We utilise atmospheric greenhouse gas observations and transport modelling and remote sensing data to to understand regional variations in the terrestrial greenhouse gas balance and identify underlying biospheric signals. We combine knowledge about eco-physiological processes with observations and modelling of biogeochemical cycles at different spatial scales to understand the underlying drivers of these biospheric signals.

We develop complex models to simulate terrestrial biogeochemical element cycles and their dependence on vegetation and soil properties as well as local climate. Based on detailed knowledge of physiological principles of ecosystem processes, we seek to improve these models and adapt them better to capture biological processes at climate relevant scales. We test the improved models with different ecosystem and atmospheric observations. Our new findings also feed into global models of the Earth system to estimate the impact of increasing human influence on terrestrial ecosystems.

 

Latest Key Results

Lacroix, F.,  Zaehle, S.,  Caldararu, S.,  Schaller, J.,  Stimmler, P.,  Holl, D.,  Kutzbach, L., &  Göckede, M. (2022). Mismatch of N release from the permafrost and vegetative uptake opens pathways of increasing nitrous oxide emissions in the high Arctic. Global Change Biology,  00,  1– 18. https://doi.org/10.1111/gcb.16345

Latest Publications

Damasceno, A. R.; Garcia, S.; Aleixo, I. F.; Menezes, J. C. G.; Pereira, I. S.; Kauwe, M. G. D.; Ferrer, V. R.; Fleischer, K.; Grams, T. E. E.; Guedes, A. V. et al.; Hartley, I. P.; Kruijt, B.; Lugli, L. F.; Martins, N. P.; Norby, R. J.; Pires-Santos, J. S.; Portela, B. T. T.; Rammig, A.; de Oliveira, L. R.; Santana, F. D.; Santos, Y. R.; de Souza, C. C. S.; Ushida, G.; Lapola, D. M.; Quesada, C. A. N.; Domingues, T. F.: In situ short‐term responses of Amazonian understory plants to elevated CO2 CO2. Plant, Cell and Environment (2024)
Jin, Y.; Keeling, R. F.; Stephens, B. B.; Chen, M.; Patrad, P. K.; Rödenbeck, C.; Morgan, E.; Kort, E. A.; Sweeney, C.: Improved atmospheric constraints on Southern Ocean CO2 exchange. Proceedings of the National Academy of Sciences of the United States of America 121 (6), 2309333121 (2024)
Schlutow, A.; Kraft, P.; Scheuschner, T.; Schlutow, M.; Schröder, W.: Bioindication for Ecosystem Regeneration towards Natural conditions: the BERN data base and BERN model. Environmental sciences Europe 36, 14 (2024)
Park, H.-J.; Baek, N.; Seo, B.-S.; Jeong, Y.-J.; Yang, H. I.; Lee, S.-I.; Yoon, K.-S.; Kim, H.-Y.; Choi, W.-J.: Estimation of the electrical conductivity of saturated paste from soil–water extracts of coastal saline paddy soils using random forest and multiple regression models. Journal of Soils and Sediments (2024)
Son, R.; Stacke, T.; Gayler, V.; Nabel, J. E. M. S.; Schnur, R.; Silva, L. A.; Requena Mesa, C.; Winkler, A.; Hantson, S.; Zaehle, S. et al.; Weber, U.; Carvalhais, N.: Integration of a deep-learning-based fire model into a global land surface model. Journal of Advances in Modeling Earth Systems 16 (1), e2023MS003710 (2024)

 

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