## 3 Results and Discussion  
Suitability of the MODIS GPP Product to Estimate Annual GPP in Shrublands and Grasslands in Water Deficient Areas. Table 2 shows the values of GPPec, GPPm and precipitation aggregated on an annual basis for each site and year. It also shows the relative error in \(\%\) (E) for the estimation of GPP by using GPPm. All the variables in the annual dataset were normal according to the Kolmorogov-Smirnov test (\(\alpha=0.05\)), so the agreement between GPPec and GPPm was reported as the r\({}^{2}\) coefficient of adjustment and the SEE (Table 3). The results show that GPPm is highly correlated with GPPec for grassland and shrubland areas on an annual basis (r\({}^{2}=0.94\), SEE = 142.57), which agrees with the findings of [13] for three sites (r = 0.86) and [18] in an across-biome validation where 10 out of the 42 sites were in non-forested areas (r\({}^{2}=0.84\), n = 42). The better agreement obtained in our study might be due to the fact that grasslands/shrublands have been analysed separately from other biomes and they constituted a more homogeneous group. The results obtained when adding the forested site to the model support this argument (r\({}^{2}=0.93\), SEE: 142.57). On the other hand, when we only considered grasslands/shrublands in water-limited sites, the degree of agreement was lower (r\({}^{2}=0.77\), SEE: 143.36). The results showed that GPPm tended to overestimate annual GPP in non-forested areas (Table 2, Figure 2). For the two sites located in shrublands (USSO4 and UKSS2) water limitation might have played a role, since the overestimation was much larger for the site located in a water-limited area (USSO4) compared to non-water limited areas. This overestimation by GPPm could be attributed to the fact that the DAO meteorology used by the MOD17 algorithm underestimates local VPD in many water-limited sites during the summer, and therefore photosynthesis is not sufficiently constrained when calculating GPPm for dry periods in North America [13, 42]. This result agrees with [13], who found a similar overestimation of 67% for an open shrubland site in a dry area. However, [19] found that MODIS slightly underestimated GPP in two shrublands in water deficient areas. Some authors have suggested that these limitations in dry regions can be overcome with the inclusion of the variable SWC in the MOD17 algorithm [43]. \begin{table}
\begin{tabular}{c c c c c c} \hline Tower & **Year** & **GPPec** & **GPPm** & **E (\%)** & **Precip** \\ \hline \multirow{4}{*}{USAUD} & 2003 & 113.1 & 223.5 & 97.6 & 272.0 \\  & 2004 & 125.1 & 214.8 & 71.6 & 191.2 \\  & 2005 & 362.9 & 252.1 & \(-\)30.5 & 305.6 \\ \hline \multirow{4}{*}{USFP} & 2004 & 380.2 & 329.4 & \(-\)13.4 & 268.0 \\  & 2005 & 381.2 & 177.8 & \(-\)53.4 & 219.2 \\  & 2006 & 149.1 & 146.2 & \(-\)1.9 & 238.4 \\ \hline \multirow{4}{*}{USVAR} & 2004 & 635.1 & 875.7 & 37.9 & 399.2 \\  & 2005 & 1084.8 & 914.5 & \(-\)15.7 & 721.6 \\  & 2006 & 745.7 & 766.9 & 2.8 & 698.4 \\ \hline \multirow{2}{*}{USKS2} & 2005 & 1950.8 & 1997.1 & 2.4 & 1022.4 \\  & 2006 & 1438.4 & 1679.2 & 16.7 & 814.4 \\ \hline \multirow{4}{*}{USSO4} & 2004 & 227.2 & 431.7 & 90.0 & 410.4 \\  & 2005 & 498.1 & 626.3 & 25.7 & 668.8 \\  & 2006 & 173.5 & 314.4 & 81.2 & 184.0 \\ \hline \multirow{2}{*}{USME3} & 2004 & 985.9 & 1005.1 & 1.9 & 365.8 \\  & 2005 & 683.6 & 944.5 & 38.2 & 592.0 \\ \hline \end{tabular}
\end{table} 
Table 2: Annual values registered for each site. GPPec (g C\(\cdot\)m\({}^{-2}\cdot\)year\({}^{-1}\)): GPP derived from the EC tower, GPPm (g C\(\cdot\)m\({}^{-2}\cdot\)year\({}^{-1}\)): GPP obtained from the MODIS imagery, E (%): GPP relative error, Precip (mm): precipitation. Since the grasslands were located in water-limited areas and taking into account the limitation of the MOD17 algorithm in underestimating water stress, we expected the annual GPP to be overestimated [13] in these sites. However, the results showed that GPP was underestimated in these three sites in 2005 (Table 2).