## 3 Data
### Field data
#### 3.1.2 Vegetation structure variables  
Leaf area index (LAI) and the fraction of absorbed photosynthetically active radiation (fPAR) are two key variables of vegetation structure used as input variables to models that predict NPP over extensive terrestrial areas [5, 27, 37]. Either direct or indirect methods have been used to estimate _in situ_ LAI and fPAR. In the present study, LAI and fPAR were measured at 25 sample plots across the study area using gap fraction analysis of hemispherical photos. The gap fraction is an integrated canopy structural quantity. The vertical gap fraction corresponds directly to the complement to unity of the cover fraction and allows estimating both the LAI and fPAR of canopies with an assumption about the spatial organisation of the vegetation elements [38, 39]. Recent advances in instrumentation and the improvement of gap fraction inversion models have significantly increased the attractiveness of this technique [40].  
For hemispherical photography, a WinScanopy Image Acquisition instrument from \"Regent Instruments\" (http/www.regentinstruments.com) was used. Field survey was carried out at the peak of vegetation activity in June 2008. The plot size was chosen to correspond to an area observed by nine 30-m Landsat ETM\(+\) pixels. Plot locations and coordinates were determined using global positioning  
\begin{table}
\begin{tabular}{|l|l|c|c|c|c|} \hline \multirow{2}{*}{**Land cover**} & \multirow{2}{*}{**Dominate vegetation**} & \multicolumn{4}{c|}{**Carbon, g/m\({}^{2}\)**} \\ \cline{3-6}  & & **BGB** & \(AGB_{I}\) & **Litter** & **Total** \\ \hline Short grassland (8 sample plots) & _Convolvulus arrenisia_ & 38.1 & 54.2 & 80.5 & 172.8 \\ \cline{2-6}  & _sublessingiana_ & & & & \\ \hline Steppe grassland (6 sample plots) & _Festuca valesiaca,_ & 58.0 & 56.4 & 61.3 & 195.7 \\ \cline{2-6}  & _Stipa capillata, Cooleria cristata_ & & & & \\ \hline Average of 14 sample plots & & 48.0 & 61.6 & 70.9 & 179.5 \\ \hline \end{tabular}
\end{table}
Table 1: Description of field data used for the modelling (averaged by land cover type).  
system (GPS) and hemispherical photos were taken at each of the sub-plots. Each plot has a size of \(90\times 90\) m with multiple sub-plots over which measurements were averaged to produce a unique value per plot. The measurements were made in 30-m transect spacing within each plot. This spacing was selected on the basis of test trials conducted in reference plots and analysis of fine-scale vegetation patterns at Landsat ETM+ imagery. In order to take pictures underneath the canopy, the hemispherical camera was placed on ground surface on such manner that the objective surface was at the similar level with the ground surface. On such way, the portion of the light absorbing canopy, missed by the measurements, was minimal.  
The \"Can Eye\" software (INRA, France, http//www.avignon.inra.fr/can_eye/) was used for the processing of hemispherical photographs and derivation of LAI and fPAR values for each measurement site and than for each plot. \"Can Eye\" uses a look-up-table approach which is composed of gap fraction measurements in different view zenith angles and the corresponding LAI and fPAR parameters.  
The hemispherical measurements (non-contact method) were supported by calculation of LAI from harvesting biomass by destructive sampling (contact method) at the test sites described above in Section 3.1.1. A value of leaf area index for samples of contact measurements was calculated as:  
\[\text{LAI}=\text{AGB}\ \text{(gC/m^{2})*SLA(m^{2}/gC)} \tag{6}\]  
where AGB is aboveground biomass, and SLA is the specific leaf area. The SLA is an ecophysiological biome-dependent constant with values taken from [37]. The LAI calculated from contact measurements served as reference for LAI estimations by hemispherical photography. The study by [41] compared the LAI values from contact and non-contact measurements in the data set used in the present study. They found a high consistency of the LAI values from different sources.