## 3 Results
### Driving Analysis of Influencing Factors  
#### 3.3.1 Impact Analysis of Natural Factors on NEP  
From the results of single factor detection (Figure 8), the degree of influence of each natural factor on vegetation carbon sinks from 2000 to 2022 is as follows: DEM (0.174) > temperature (0.148) > precipitation (0.026) > slope (0.017) > slope aspect (0.003). The \(p\)-values of the models are all less than 0.01, i.e., the results are all significant at the 0.01 level. Among them, DEM has the strongest explanatory power for the spatial and temporal distribution characteristics of vegetation carbon sinks, followed by temperature and precipitation, and the least explanatory power for topographic slope aspect. Vegetation carbon sinks show great differences depending on the spatial distribution of vegetation, and DEM is an important factor that directly affects the spatial distribution of vegetation; therefore, DEM directly affects the habitat of vegetation and then affects the spatial distribution of vegetation carbon sinks. Suitable temperature and precipitation, on the other hand, are important bases for the survival and growth of vegetation. The q-value of precipitation is small, 0.026, and in combination with the climatic characteristics and vegetation type characteristics of the Taihang Mountainous Region, the climate in North China is drier, the average annual rainfall is smaller, and the vegetation in this region is also mainly dominated by grassland meadows and coniferous forests. In addition, the explanatory power of slope gradient and slope aspect on vegetation carbon sinks is weak. As the slope increases, the more difficult it is for water to collect, the higher the risk of erosion to the vegetation, and the stronger the erosion and scouring of the soil by the water flow, which will affect the coverage of the vegetation. Slope aspect mainly affects the soil texture by influencing the light time and then indirectly affects the growth of vegetation, which has a weaker effect compared with other factors. Figure 7: Spatial distribution of discrete coefficients for NEP. From the detection results of the interactions among natural factors, the explanatory power of natural factors on vegetation carbon sequestration is significantly stronger than that of single factors in both pairwise interactions. As shown in Figure 9, the NEP natural factor interactions basically show a non-linear enhancement relationship, i.e., the explanatory power of the pairwise interaction of influencing factors on NEP is greater than the sum of explanatory power of single factor effects. For example, the explanatory power of the non-linearly enhanced interaction of temperature and precipitation is 0.299 (Figure 10), which is greater than the sum of the explanatory powers of the single-factor effects of 0.148 and 0.026 (Figure 8). In addition, the interactions of the two sets of factors, DEM and air temperature and DEM and slope, show a bilateral enhancement relationship, i.e., the explanatory power of the pairwise interaction of influencing factors on NEP is greater than the explanatory power of each single factor. For example, the explanatory power of the bilaterally enhanced interaction of temperature and DEM is 0.217 (Figure 10), which is greater than the one-factor explanatory power of 0.148 and 0.174 for temperature and DEM. Combining Figures 8 and 10, it is found that the vegetation carbon sinks in the Tai-hang Mountains are influenced by a variety of natural factors and that this influence is not determined by a single factor alone but rather by the combined effects of multiple factors. The interaction between DEM and temperature and DEM and slope is a bilaterally enhancement relationship, indicating that when the regional DEM is supplemented with suitable temperature and slope, it will be more conducive to the positive growth of the vegetation carbon sink.