## 4 Conclusions  
Analyses of NPP trends, calculations of the coefficient of variation, and the second-order partial correlation coefficient were used to study the spatial and temporal changes and interpolate future trends of NPP. Climate factors as a driver of NPP are discussed. The following conclusions are drawn. First, the spatial distribution of NPP was consistent with that of precipitation and showed obvious spatial heterogeneity. The spatial distribution for which the NPP of the study area was 2008 g C/m\({}^{2}\) is consistent with an annual average precipitation of 400 mm. Grassland and farmland accounted for \(179.35\times 10^{4}\) km\({}^{2}\) (48.29%) and \(66.0\times 10^{4}\) km\({}^{2}\) (17.77%) of the study area. The average annual variation tendency of NPP was 20.57 g C/m\({}^{2}\)-a, indicating that the NPP in the study area had an overall upward trend from 2000 to 2015. The maximum rate of increase in NPP was 475.18 g C/m\({}^{2}\)-a, and the maximum rate of decrease was 306.39 g C/m\({}^{2}\)-a. The upward trend of NPP in the study area from 2000 to 2015 may be closely related to the large-scale implementation of the Grain for Green Program and the Three Northern Shelter Forest Programs that have been run by the Chinese government since 1999. The rapid development of agricultural technology may also have played a role in the upward trend of NPP. Figure 7: Future trend analysis of net primary productivity in the study area. Second, the second-order partial correlation coefficient of NPP and precipitation was between \(-0.96\) and \(0.95\). The areas with positive and negative correlations accounted for \(39.24\%\) and \(60.76\%\) of the total study area, respectively. The area for which the partial correlation coefficient passed the significance test (\(p<0.01\)) was \(11.13\times 10^{4}\) km\({}^{2}\), accounting for \(3.67\%\) of the total area. The partial correlation coefficient between NPP and LST was between \(-0.94\) and \(0.96\), and the areas with positive and negative correlations accounted for \(52.64\%\) and \(47.36\%\) of the total area, respectively. The area for which the partial correlation coefficient passed the significance test (\(p<0.01\)) was \(7.25\times 10^{4}\) km\({}^{2}\) (\(2.39\%\) of the total study area). On the whole, NPP in the study area shows a negative correlation with precipitation and a positive correlation with temperature, which may be because the study area contains a large portion of the Tibetan Plateau, which predominately has year-round cold, wet conditions. The perennial low temperature condition in the Tibetan Plateau is the limiting factor for crop growth, and the occurrence of precipitation events will increase the cloud and soil moisture, thus aggravating the negative effects of low temperatures. Finally, the persistence of NPP showed significant differences on different time and seasonal scales. The biggest persistence of NPP was observed for autumn (\(185.52\times 10^{4}\) km\({}^{2}\) or \(49.92\%\) of the study area), followed by spring and summer, accounting for \(25.67\%\) and \(13.40\%\) of the total area, respectively. The lowest persistence of NPP was in winter, in which only \(25.09\times 10^{4}\) km\({}^{2}\) (\(6.75\%\)) of the study area showed persistence of NPP. On an annual scale, the region with a Hurst index of \(>\)0.5 accounted for \(46\%\) of the total study area and was distributed in the eastern part of the study area. The NPP shows obvious anti-persistence characteristics on the annual scale, indicating that although NPP in the research area has increased over the past 20 years, NPP is likely to be degraded in the future due to the strong ecological vulnerability and the complex, changing climatic conditions. In this study, when analyzing the effect of climate factors on NPP change, only the temperature, precipitation, and evaporation that have the most obvious effect on NPP were introduced.