In April 2015 the official inauguration of the lysimeter station took place.
Key over with Dr. Mirco Migliavacca (Leader of the research group: Biosphere-Atmosphere Interactions and Experimentation, Max Planck Institute for Biogeochemistry) and Dr. Sascha Reth (managing director of UGT GmbH)
Project description by the Max Planck Institute for Biogeochemistry “Tree-grass” ecosystems. Mixed tree-grass systems are widely distributed (~16-35% of global land-surface) vegetation formations such as tropical and Mediterranean savannas, the “waldsteppe” in Eurasia and culturally influenced vegetation types such as agro-forestry systems or grazed open-forests in Europe (Hanan & Hill 2011). Semi-arid tree-grass systems are considered one of the major contributors to the interannual variability of the global carbon cycle (Poulter et al., 2014) Despite their wide distribution, Earth observation systems, and associated land-surface modeling development have been so far poorly adapted to the key structural and functional characteristics of tree-grass ecosystems. As consequence a significant uncertainty and bias in the assessments of energy, carbon, water and biogeochemical dynamics is often observed (Hanan & Hill 2011; Beringer et al. 2011). Nutrient (N, P) imbalance. Human induced CO2 and N fertilization leads to a stoichiometric imbalance, which confers an important role to P availability and leads to shifts in C-N-P ratios and balances (Peñuelas et al. 2012). N/P imbalances are particularly important in water-limited ecosystems (Sardans et al., 2012), where the synergistic effect of water and nutrient (N and P) availability/imbalance could impact ecosystem functioning, structure, allocation patterns and the nutrient and carbon cycling, and ultimately how the ecosystem will respond to extreme drought events. Hence it is important to study the effects of N and P imbalances under different water regimes, in particular in mixed tree-grass at ecosystem scale. MaNiP project offers an original experimental design integrating cutting-edge approaches (including eddy covariance, lysimiters and hyperspectral; remote sensing) to study the combined effect of nutrient and water limiting factors on fundamental ecosystem, plant and soil processes.