## 6 Discussion and Conclusions  
Based on SPOT-VGT, _in situ_ measurements of carbon residing in the aboveground and underground vegetation and climate data, the values of gross primary production (GPP), net primary production (NPP), total respiration of ecosystem (\(R_{e}\)) and net ecosystem exchange (NEE) were calculated for a large grassland region in Central Kazakhstan. The presented study used the well-known [PERSON]'s approach, but the most important advantage of the model presented is the exclusive use of the variables obtained from field survey data for model's calibration and validation. The model is fixed in its regional scale with the spatial resolution of \(1\times 1\) km and temporal resolution of 10 days. Figure 5: Pixel-by-pixel relationship between MODIS GPP and the GPP modelled in this study. Points represent individual pixels (\(1\times 1\) km, n = 31500). The thin line represents 1:1 line, while the thick one is the regression line between the data sets. Our analysis showed that for the investigated year 2004 the short grassland was a net carbon sink, while the steppe grassland was a net carbon float. The average accumulation of carbon in the short grassland was 13.17 g C/m2; this resulted in 263,768 tons over the whole area of the short grassland. The steppe grassland was losing carbon with a low rate of -0.09 g C/m2. One of the reasons for the carbon loses by the steppe grassland was a higher rate of respiration and lower NPP modelled in this zone. Other reasons were not investigated in this study and are objective of an ongoing research. However, basing on the conclusions by [65], we can suggest that climate, particularly precipitation amount, should be the major driving force for dynamics of carbon flux. [65] concluded that globally about 44% of interannual variability in NEP resulted from precipitation, about 16% from temperature and about 12% from soil carbon. In general, the evaluation of the modelling results reveals a high reliability. On the one hand, the comparison of the results with directly measured field data suggested a strong relationship between the values of GPP derived by the model and the peak aboveground carbon amount at 14 test sites. No attempts have been made to quantify the uncertainty of the direct comparison, but as in all cases of evaluating coarse resolution satellite based primary production models by harvest measurements some uncertainty must be expected due to differences between the spatial unit size of the ground measurements and the coarse resolution of the satellite sensor [66, 67, 68, 69, 70, 71]. In the present study, the total size of the samples taken in each of the 14 test plots was only 256 m2 (four samples of 1 x 1 m per replicate and four replicates per plot). It encompasses 0.0256% of a MODIS pixel. Without doubt, the surface of an area covered by one MODIS pixel has more variations than the surface covered by one test site. Fortunately, the heterogeneity of surface for grassland is much less than it is for forested ecosystems. The study by [72] estimated magnitude of surface heterogeneity and its influence on the results of LAI modelling with MODIS data. They found that the surface heterogeneity in grassland of the Sahel within one MODIS pixel is low, and its influence can be neglected by direct comparison of MODIS data with field measurements. Taking some uncertainty related to scale differences between observed biomass and satellite data into account the model presented in this study performs well for the grassland of Central Kazakhstan. On the other hand, the model bears comparison with the global MODIS GPP dataset. This comparison reveals a general similarity in the spatial pattern of the MODIS GPP and GPP from this study, even though the first dataset includes a number of block artefacts and some data gaps at the level of individual pixels. The average value of GPP for the MODIS dataset was slightly underestimated (about 8%, considering mean values of the two data sets) in comparison to the dataset in this study.