## 4 Results
### Impacts of LUCC on GPP  
The temporal variations of GPP_ref over the study period were mainly controlled by LUCC, and the effects of meteorological variations had been largely minimized. Figure 9 illustrates the time series of the annual total GPP_ref and annual mean GPP_ref in the study area. The annual total GPP_ref showed a clear decreasing trend, with a decreasing rate of 1.02% per year (\(p<0.1\)). The annual mean GPP_ref fluctuated from year to year, showing a weak increasing trend (\(p=0.12\)). We analyzed the relationship between the interannual variation of total GPP_ref and that of the built-up, cropland, grassland, EBF, and DBF fractions, respectively. The interannual variation of total GPP_ref and annual mean GPP_ref fluctuated from year to year, showing a weak increasing trend (\(p=0.12\)). Figure 8: The map of land-use/cover in 2000 (a); the map of land cover changes from 2000 to 2013 in the study area (b). GPP_ref had a negative linear relationship with the interannual variation of built-up fraction (r = 0.70, \(p\) < 0.05). During 2001-2005, when the pace of urbanization was slow, the interannual variation of GPP_ref was related to the interannual variation of the cropland fraction (r = 0.66, \(p\) < 0.05). During 2006-2013, when the built-up areas increased rapidly, the interannual variation of GPP_ref was related to that of the cropland fraction (r = 0.48, \(p\) < 0.1) as well as the forest fraction (r = 0.48, \(p\) < 0.1). The combined effect of changes in cropland and forest fraction on the interannual variation of GPP_ref can be quantified by the multiple correlation coefficient (r = 0.68, \(p\) < 0.05), implying that interannual variations in cropland and forest fractions together explained 68% variance in the interannual variation of GPP_ref. We derived the transition matrix of the gain and the loss of annual GPP_ref associated with LUCC for each year in comparison with the annual GPP_ref of the previous year. The summary of the transition matrix over the 13 years is shown in Table 1. Besides the transition between cropland and bare land and the transition between cropland and water bodies, the maximum loss of GPP was associated with the conversion from cropland to built-up areas. The conversion from EBF and DBF to cropland and water bodies also contributed to a large amount of GPP loss. The substantial gain in GPP was due to the conversion from cropland to EBF and DBF. The transition between cropland and bare land may be caused by either crop rotation or urban expansion, with the net loss of 90.57 Gg C. The gain and loss of GPP that resulted from LUCC were not in balance. Approximately 309.95 Gg C in total was lost in the study area over the 13 years. Figure 10 shows the temporal variations of loss and gain of GPP that was associated with a specific form of LUCC. The loss of GPP associated with the conversion from cropland to built-up areas increased slightly from 2001 to 2009, but the loss of GPP was worse after 2009, when built-up areas expanded rapidly. The loss of GPP due to the conversion from forest to cropland fluctuated through the study period, but it showed a sharp decrease in 2007 and 2008. The gain of GPP due to the  
Figure 9: Time series of the total annual GPP_ref (Gg C year\({}^{-1}\)) (**a**) and mean annual GPP_ref (gC m\({}^{-2}\) year\({}^{-1}\)) (**b**) in the study area from 2000 to 2013. The dash lines represent the trends of the time series. The trend of the total annual GPP_ref was significant at \(p\) < 0.1; the trend of the mean annual GPP_ref was not significant (\(p\) = 0.12). conversion from cropland to forest was low during 2001-2009, but it increased dramatically from 2009 to 2013. The spatial patterns of GPP_ref in 2000 is shown in Figure 11a. Urban forests showed the highest GPP values, and cropland in the suburb also had high GPP values ranging from 600 gC m\({}^{-2}\) year\({}^{-1}\) to 800 gC m\({}^{-2}\) year\({}^{-1}\).