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MODELLING CARBON FLOWS IN CROP AND SOIL

MODELLING CARBON FLOWS IN CROP AND SOIL. Krisztina R. Végh. Carbon and Nitrogen flows and storage. Eckersten, 1994). Carbon flows in the CoupModel. Organic residues: surface litter, rhizodeposition: 900-3000 kg C/ha. C/N:20-80. C/N:10-30. Dissolved organics. (Jansson, 2004).

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MODELLING CARBON FLOWS IN CROP AND SOIL

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

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

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

  4. C input: crop growth • Logistic growth: • Water use efficiency • Light use efficiency 3 approaches for the simulation of plant growth : 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.

  5. Allocation of assimilated C to the different plant parts Plant biomass is divided into compartments of carbon (CLeaf, CStem, CRoot, Cgrain Cmobile)

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

  7. Decomposition and mineralization – Soil organismsm are implicit The decomposition is substrate controlled and calculated as a first order rate process: When soil organisms are implicit, the soil profile includes maximum of three carbon pools with specific decomposition rates kl, kf, kh. The relative amounts of decomposition products The three rate constants are affected by response functions for soil moisture (f) and temperature (fT). Efficiency parameter fe determines the fraction of Cthat is not released from the soil as CO2

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

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

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

  11. Conclusions 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.

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