## Discussion
### Uncertainties  
Carbon sinks in terrestrial ecosystems are usually influenced by land cover change and climate change. However, separating the effects of land cover change and climate change remains a challenge due to their complex interactions [84]. The vegetation carbon sink in the ARNWC is mainly affected by land cover change [14]. Therefore, our study explored this phenomenon by means of modeling scenarios. For example, to investigate the effects of land cover change, we only allowed land cover type, NDVI, and EVI to change during the model operation, while climate-related factors were kept at 2001 levels. However, it can be seen that the simulation results still represent the combined effect of land cover change and climate influences under stable climate conditions, even if the climate factors remain constant. In addition, to take the impact of natural vegetation growth into account, we allowed NDVI and EVI to vary in the stable category, but this was also potentially affected by climate simultaneously and introduced some uncertainty into the results. Nevertheless, our findings still provide knowledge regarding how land cover change affects the vegetation carbon sink in the ARNWC. Ultimately, we found that land cover change had an obvious positive impact on the vegetation carbon sink in ARNWC. In addition, we used a direct strategy to analyze the effects of land cover change, and the results are conservative in comparison with the indirect strategy (Supplementary Figure S1), which has a similar pattern to previous studies [9]. This further supports our results in another way because, even with some underestimation, our study still found that the effects of land cover change contributed to an increase in the vegetation carbon sink, regardless of whether it was considered in the overall study area or split by land cover types. Regarding the model, although we have partially improved the CASA model, there may also be differences in the results due to varying sources of input data. For example,by comparing ESA CCI and MCD12Q1 land cover products, we found that there are some differences in the classification of pixel units. Particularly in the hinterland of the Tuha Basin and the southern margin of the Tarim Basin, a large number of pixel units are classified as permanent snow and ice in MCD12Q1, which is not reasonable. In contrast, the CCI product provides the first detailed long-term time series of land cover change, and it also meets the input requirements of both surface and climate models [85]. Therefore, we chose the ESA CCI product as the input land cover dataset for the model in this study. In addition, it has been proposed that the estimation results derived by inputting MODIS NDVI are higher than those of GIMMS NDVI [52], and NDVI suffers from saturation effects, which may underestimate the value of high coverage areas [86]. Thus, it can be seen that the results of the vegetation carbon sink will be subject to some uncertainty. However, the results of our study still contribute to revealing the relative magnitude and direction of the vegetation carbon sink. Furthermore, given the uncertainty of the model itself, we need to improve our understanding of the formation mechanism and influencing factors for terrestrial ecosystem productivity and deepen our research on the mechanisms of physiological and ecological processes in the model in future studies. In addition, there is no doubt that model simulation results with high-spatial-resolution input data are more beneficial to our understanding of the response of terrestrial ecosystems to global climate change. However, fine representation of model results at large scales is often difficult to achieve due to the complexity of the model structure, the difficulty of applying high-resolution simulations regionally/globally, and long operation times.