## 3 Results
### NBP Simulation Results and Validation  
#### 3.4.1 NBP Simulation Results for Ecological Nodes  
We used the parameterized Biome-BGC model to simulate the annual average NBP of vegetation ecosystems in 27 ecological nodes of the YRB during 2009-2018, with the complete results for 10 years presented in Table S2 and the results for only 2018 presented in Figure 11. On a temporal scale, the ecological nodes of the YRB were in a state of alternating carbon sources and sinks from 2009-2018. Some nodes were in a state of gradually increasing carbon sink intensity in recent years, such as Node 2. Node 2 represented the deciduous broadleaf forest located in Shandong, whose annual NBP was \(-4.2\) g\(\cdot\)C m\({}^{-2}\)\(\cdot\)year\({}^{-1}\) in 2014 and 5.6 g\(\cdot\)C m\({}^{-2}\)\(\cdot\)year\({}^{-1}\) in 2015. During this period, the NBP of Node 2 increased by about 233%, which means that Node 2 changed from a carbon source to a carbon sink in 2015. Between 2015 and 2018, Node 2's NBP increased from 5.6 g\(\cdot\)C m\({}^{-2}\)\(\cdot\)year\({}^{-1}\) to 43.7 g\(\cdot\)C m\({}^{-2}\)\(\cdot\)year\({}^{-1}\), an increase of about 680%. Similar to Node 2 was Node 17, whose annual NBP increased from 15.7 g\(\cdot\)C m\({}^{-2}\)\(\cdot\)year\({}^{-1}\) to 165 g\(\cdot\)C m\({}^{-2}\)\(\cdot\)year\({}^{-1}\) between 2015 and 2018, an increase of about 950%, which implied a significant increase in the carbon sequestration capacity of Node 17 during that period. Similarly, some nodes were in carbon sink status in recent years but converted to a carbon source in 2018, such as Node 27. Node 27 represented the temperate steppe in Qinghai, which was in carbon sink status in 2014 (NBP of Node 27 in 2014 was 0.6 g\(\cdot\)C m\({}^{-2}\)\(\cdot\)year\({}^{-1}\)) but converted to a carbon source in 2018 (NBP of Node 27 in 2018 was \(-2.6\) g\(\cdot\)C m\({}^{-2}\)\(\cdot\)year\({}^{-1}\)). The NBP of Node 27 in 2018 was 533% lower than in 2014. In addition, some nodes were carbon sources in recent years, such as Node 7. Node 7 was the deciduous broadleaf forest located in Henan, which was a carbon source between 2016 and 2018. The NBP of Node 7 increased by about 38.5% in 2018 compared to 2016. We speculate that the transformation of these vegetation nodes in the state of carbon sources or carbon sinks is the result of climate change, construction of national ecological projects, human management, and other factors.  
Figure 10: The result of community division of ecological nodes. The node size represents the clustering coefficient.  
In the 2018 NBP results, 17 ecological nodes were in carbon sink status and 10 ecological nodes were in carbon source status (Figure 11). The node with the largest carbon sink intensity was Node 17, with an annual NBP of 165 g-C m\({}^{-2}\)-year\({}^{-1}\). This node represented evergreen broadleaf forest located in Sichuan, which had the strongest net carbon sequestration capacity in the ecospatial network in 2018. The node with the largest carbon source intensity was Node 7 with an annual NBP of 28.8 g-C m\({}^{-2}\)-year\({}^{-1}\). Node 7 represented the deciduous broadleaf forest located in Henan, which was the node with the strongest net carbon emission capacity in the ecospatial network in 2018. In addition, some carbon source nodes (Node 24, 25, 26, and 27) had a small aggregation in the western region of Qinghai, which is the focus of future national ecological project construction in the context of carbon neutrality (Figure 11, far left). In terms of vegetation types of nodes, forest nodes had much higher intensity of net carbon sequestration or net carbon emission per unit time than grassland nodes. In addition, the total and mean values of NBP of carbon sink nodes in the YRB were much larger than those of carbon source nodes.