Home Biogeochemical Integration | Prof. Reichstein Publications Theses Ongoing Theses Ongoing Theses Zavud Baghirov Deep learning-based, hybrid, uncertainty aware modelling of the coupled water and carbon cycle using Earth observations Vitus Benson Deep Learning for multi-modal characterization of spatio-temporal Earth system dynamics on multiple spatial scales Georgios Blougouras Interpretable machine learning for hydrological drought understanding Eleanor Butler Compound Extremes and Forest Disturbances Xiuzhi Chen Mohammed Ayoub Chettouh Ranit De Inter-annual variability in terrestrial ecosystem fluxes Kelley De Polt Impacts of extreme weather events across scales and domains Qiqi Deng Lucia Muriel Eder Effects of elevated CO2 on soil organic matter turnover and nutrient uptake, Institute for Geography, University of Jena Arvind Gauns Integrating Remote Sensing and Modeling approaches to Assess Carbon Dynamics of a Fertilized Tree-Grass Ecosystem Reda ElGhawi Hybrid machine-learning based modelling of biosphere-atmosphere interactions Naixin Fan Environmental controls of ecosystem turnover times Ulisse Gomarasca Understanding relationship between ecosystems multifunctionality with climate, vegetation properties and biodiversity Bayu Budi Hanggara Complex biogeochemical and biophysical properties of tree-grass coexistence at a Mediterranean savanna ecosystem Sebastian Hoffmann Yucong Hu Theertha Kariyathan Biogeochemical insights from multi-tracer atmospheric flask data Negin Katal Using Flora Incognita plant observation data and applying deep learning for phenological modeling Lara Kösters Deep learning species classification using morphological and genetic data Çağlar Küçük Ecohydrology from space Hoontaek Lee Carbon-water interactions across scales Na Li Internally-driven versus externally forced components of the global C cycle Suxun Li Laura Nadolski Revealing Carbon Dynamics in a Semi-Arid Savanna Ecosystem under Different Disturbances Nora Linscheid Ecological process understanding across time scales Franziska Müller Forest disturbance classification using deep learning approaches Sinikka Paulus Atmosphere interactions in seasonally dry systems using lysimeter data Jeran Poehls Downscaled Predictions of Climatic Extreme Events Moien Rangzan Harnessing computer vision and machine learning for a renewed cartography of human impact on landscapes Christian Requeña Deep learning approaches for analyzing spatio-temporal memory effects in Earth System data Claire Robin Machine learning method for vegetation forecasting Leo Roßdeutscher Combining process-based and deep learning models to understand soil processes better Melissa Ruiz Vásquez Exploring the potential of vegetation information for improving weather forecasts Deep Prakash Sarkar Data driven models of individual trees to better understand forest water use Myriam Terristi Dynamics of the terrestrial carbon and water cycles in response to record shattering eco-meteorological events Samuel Upton Machine-learning based estimation of ecosystem CO2 fluxes constrained by atmospheric and ecosystem observations Siyuan Wang Global Vegetation Dynamics Chenwei Xiao Land management for ecosystem resilience Xin Yu Memory effects of climate extremes on ecosystems Chunhui Zhan How do plant-physiological effects of increasing CO2 influence the land-atmosphere fluxes of carbon and water? Jinfeng Zhao Disentangle the individual effects of eCO2 on ET across vegetation types