MODELLING CARBON FLOWS IN CROP AND SOIL Krisztina R. Végh

MODELLING CARBON MODELLING CARBON FLOWS IN CROP AND SOILFLOWS IN CROP AND SOIL

Krisztina R. VéghKrisztina R. Végh

Carbon and Nitrogen flows and storage

Eckersten, 1994)

Dissolved organics

Carbon flows in the CoupModel

(Jansson, 2004)

Organic residues: surface litter,

rhizodeposition: 900-3000 kg C/haC/N:20-80 C/N:10-30

Logistic growth:

Water use efficiency

Light use efficiency

(t))N/Ef(EcnC pl,pstptapaAtm

tawaAtm EC

plstptaleafaLaAtm )R/E)f(E)f(CNf(TεC

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

Plant biomass is divided into compartments of carbon (CLeaf, CStem, CRoot, Cgrain Cmobile)

Allocation of assimilated C to the different plant parts

Different response functions of C allocation to roots from above ground mass

Options: linear functionexponential independent

)/()/( tptawcwctpta EErrEEf 21

MrMcMc

McerrMf .)( 321

1Mcr1Mcr

Original parametersdoubled:

2Mcr3Mcr

1wcr2wcr

shoot mass, water stress,

leaf C:N

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 kl, kf, kh.The three rate constants are affected by response functions for soil moisture (f) and temperature (fT).

Efficiency parameter fe determines the fraction of C that is not released from the soil as CO2

The relative amounts of decomposition products

The decomposition is substrate controlled and calculated as a first order rate process:

litterdecomp Cf(T)fkC )(1

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

Decomposition :Substrate dependence,

CN ratio

Decomposition :

Substrate dependence,

Carbon contentration

Scons: substrate half rate concentration

The affects of parameters TemQ10 and

TemQ10Bas affect the response function Q10 temp. response function with a threshold value

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