1. MODELLING CARBON FLOWS IN CROP AND SOIL Krisztina R. Végh

2. Carbon and Nitrogen flows and storage Eckersten, 1994)

3. Dissolved organics Carbon flows in the CoupModel (Jansson, 2004) Organic residues: surface litter, rhizodeposition: 900-3000 kg C/ha C/N:20-80C/N:10-30

4.  Logistic growth:  Water use efficiency  Light use efficiency the potential growth is a function of time growth is estimated from WUE and simulated transpiration light use efficiency is used to estimate potential growth rate, limited by unfavorable temperature, water and N conditions. 3 approaches for the simulation of plant growth : C input: crop growth

5. Plant biomass is divided into compartments of carbon (C Leaf, C Stem, C Root, C grain C mobile ) Allocation of assimilated C to the different plant parts

6. Different response functions of C allocation to roots from above ground mass Options: linear function exponential independent Original parameters doubled: shoot mass, water stress, leaf C:N

7. Decomposition and mineralization – Soil organismsm are implicit When soil organisms are implicit, the soil profile includes maximum of three carbon pools with specific decomposition rates k l, k f, k h. The three rate constants are affected by response functions for soil moisture (f  ) and temperature (fT). Efficiency parameter f e determines the fraction of C that is not released from the soil as CO 2 The relative amounts of decomposition products The decomposition is substrate controlled and calculated as a first order rate process:

8. Organic carbon pools and carbon flows in the soil fraction of microbes located in the different pools subpools Estimated consumption rate of microbes with their efficiency explicitly taken into account + respiration of microbial biomass

9. Decomposition : Substrate dependence, CN ratio Decomposition : Substrate dependence, Carbon contentration S cons : substrate half rate concentration

10. The affects of parameters TemQ10 and TemQ10Bas affect the response function Q10 temp. response function with a threshold value

11. Simulation models help to understand the mechanistic relationships between SOC and soil – plant interactions C flows and OC pools are similarly conceptualized in several models. Simple switches to obtional pools, the possibility of the use of different allocation functions and several abiotic response functions help to describe the processes that interact simultaneously to control C dynamics in crop and soil. Conclusions