Modelling Soil Organic Matter Dynamics – Global Challenges - Sustainable Management of Soil Organic Matter - page 47

using a dynamic simulation model linked to spatially explicit data, and
show results of carbon sequestration potential estimated with a simple
regression-based approach. We demonstrate the system in use for an area of
central Hungary.

Methods

Our case study area (24,804 km 2 ) in central Hungary and GIS data sets
have been described in detail elsewhere (Falloon et al ., 1998, 2000). Here,
we describe the use of the IGATE system (Fig 2.1.1; Falloon et al ., 2000)
to compare C sequestration estimates using the Roth-C (Coleman and
Jenkinson, 1996) and CENTURY (Parton et al ., 1988) models with
estimates using simple linear regressions (Smith et al ., 1997a,b, 1998,
2000a,b).
The CENTURY model was validated and calibrated using 17 data
sets from the GCTE-SOMNET database (Smith et al ., 1996) and the IBP
woodlands data set (DeAngelis et al ., 1981). To compare the models at the
regional scale, we initialized the models by running for 3000 years under
native vegetation (forest: Marton et al ., 1989) and then 500 years of current
land use. We then ran a demonstration scenario of afforestation of all
arable land to (i) show the maximum possible increase in SOC stocks; and
(ii) highlight the largest differences between model estimates. We used
the regressions of Smith et al . (1997a,b, 1998, 1999a,b) to estimate changes
in regional SOC stocks under the six scenarios given in Table 2.1.1, all
applied to all arable land. We calculated annual CO 2 emissions offsets
using 1990 national data from Marland et al . (1999), and scaled this to our

Fig. 2.1.1. IGATE system.