## 4 Discussion  
In our paper, the NPP simulated by the LPJ model and NDVI was used to monitor vegetation restoration or degradation. Similar results can be found in previous studies [41; 42]. For example, [PERSON] et al. [9] used a combination of the most recent NDVI and model-based NPP estimates for the period 1982-2012; 80% and 67% of the global land area showed positive NPP and NDVI values, respectively. However, on the temporal scale, both global NPP and NDVI showed a corresponding pattern of increase (decrease) for the duration except for a few years (e.g., 1990 and 1995-1998). [PERSON] et al. [43] compared \"space based\" MODIS satellite driven NPP vs terrestrial \"ground based\" productivity estimates. They reported that MODIS satellite driven annual NPP estimates provide a continuous productivity estimate across Austria and no significant differences between different daily climate input data sets were evident. The two methods will enhance the ability to generate forest productivity assessments across large forest areas. In this article, we studied that the forest NPP and NDVI generally presented decreasing trends from the southeast to northwest in the Yangtze River basin from 1982 to 2013. We concluded that the spatial and temporal distribution of forest NPP and NDVI would change under the influence of such climate changes as temperature and precipitation. This study illustrates that in the northwestern part of the Yangtze River basin, the positive impact of climate change on NPP offset the negative impact in the southeast region. Moreover, on a particular time scale, the annual average temperature was positively correlated with forest NPP in the Yangtze River basin during the period 1982-2013, whereas precipitation was not significantly correlated with the forest NPP and NDVI. Some other researchers have reached similar conclusions. For example, [PERSON] et al. [44] indicated that vegetation productivity could benefit from climate warming by lengthening growing seasons and enhancing photosynthesis. [PERSON] et al. [45] reported that climate change resulted in increased NPP in savannas, tropical forests, and temperate forests and decreased NPP in a cold desert between 1911 and 2000. [PERSON] et al. [46] considered that sunshine duration and annual average temperature presented a significantly positive association with annual NPP in the Karst area of northwest Guangxi during the period 2000-2013, whereas annual precipitation had no significant correlation with NPP. However, other studies have indicated that a warmer climate could increase plants' autotrophic respiration and potentially reduce NPP, especially in high-temperature regions [40]. [PERSON] et al. [47] discovered that the temperature variation has more significant impact on NDVI and NPP than the precipitation variation in the southwestern Karst region of China. [PERSON] et al. [48] investigated that the mean annual precipitation was strongly and positively correlated with the MODIS NPP across China's Xinjiang region from 2000 to 2010. Human activities could influence forest NPP as well. In this study, we demonstrated that in some areas of the mid-lower Yangtze, the acceleration of urbanization and other human activity factors affected the mean annual forest NPP. [PERSON] et al. [11] pointed out that on the basin or city scale in China, urbanization in the Pearl River Delta reduced the total NPP by 0.137 TgC from 2000 to 2010. [PERSON] et al. [7] revealed that the implementation of national restoration projects could increase the C stocks in the project regions, especially in north, south, and east China. [PERSON] et al. [22] pointed out that the ecological restoration programs in Xinjiang from 2001 to 2009 could increase the NPP. Moreover,