## 4 Discussion  
### Uncertainty in the Calculation of the Human Activity Index  
The HAI index is calculated by using the variables ANPP, PNPP, and HNPP in this study. Numerous studies used only the difference between the PNPP and ANPP to assess the impact of human activities on terrestrial NPP [5; 16; 20]. However, the HNPP sometimes was ignored and should be considered as one part of the HAI [21; 22]. The HAI is a comparable indicator in different countries and regions, as shown in Table 2. According to our results, the HAI decreased from 75% to 47% from 2000 to 2017 in the grasslands, which is larger than that in different countries. Previous studies have suggested that the HAI in forest areas is low, as forest areas suffered less disturbance than other land cover types. In contrast, the HAI on cropland and grasslands sometimes is high. The high HNPP from the harvest of crops sometimes leads to a high HAI on cropland [43], and the low ANPP and high HNPP on grasslands resulting from grassland degradation and grazing sometimes lead to a large difference between the ANPP and PNPP and also a high HAI. Therefore, it is reasonable that the value of the HAI in our study is higher than that of other regions, especially with high forest coverage, and being close to the coastal areas of Jiangsu province in China, dominated by cropland [44]. In addition, in the city of Guangzhou, China, as well as the Yangtze River delta, the HAIs are also high, mainly due to the low ANPP and high PNPP in cities.  
Figure 8: Spatial distribution of grassland degradation in the year of 2017 in eastern Inner Mongolia.  
Although the HAI in this study is reasonable compared with previous studies, uncertainties still exist in our calculation and also in similar studies. For example, the difference between the ANPP and PNPP sometimes brings in errors by different model structures, i.e., the ANPP and PNPP are calculated by different kinds of models or NPP products. For example, [PERSON] et al. [46] used the Zhouguangsheng model and MOD17A3 production to obtain the PNPP and ANPP, respectively. In this study, although the input data are the same, however, principle differences between the BEPS model (process-based ecological model) and Miami model (light energy utilization model) still bring uncertainties to the calculated results.  
The annual mean ANPP of the grasslands in eastern Inner Mongolia from 2000 to 2017 ranges from 102.5 g C m\({}^{-2}\) yr\({}^{-1}\) to 292.4 g C m\({}^{-2}\) yr\({}^{-1}\), which is close to 281.3 g C m\({}^{-2}\) yr\({}^{-1}\), calculated by [PERSON] [50] in the same region. Meanwhile, the ANPP was validated with the FLUX data at the sites of NM and XLD (Table 3), summarized by [PERSON] [51]. We assumed that the NPP was half of the GPP, and PRE% in these two sites were only 17.76% and 8.13%, respectively. However, the PNPP is hard to verify using the flux data. We also assumed that the ANPP of the natural forest was equal to the PNPP [21], considering the natural forest is rarely affected by human activities in the Greater Khingan Mountains. For this reason, the PRE% of the PNPP in the flux site of HZ is only 4.76%. On the whole, our results are reasonable.