## 4 Discussion  
The results showed that the CV of Rs in plot 1 was the largest, and the CVs of soil properties and plant functional traits were greater than those in plot 2 and plot 3 (Table 2). The above results suggest that the biotic and abiotic factors in plot 1 had higher variability than those in plot 2 and plot 3, which might lead to stronger spatial variability of Rs by affecting plant and soil conditions [22; 30]. At different spatial scales, Rs exhibits high variability [62; 63; 64]. [PERSON] and [PERSON] [65] sampled a mature bir  
Figure 4: Variation partitioning for the effects of soil properties and plant traits on soil respiration. Figure 3: Relationship between soil respiration and plant traits (**a**–**f**) and soil properties (**g**–**m**) under different sampling scales. sampling line at 2-4 m intervals and found that the CV of Rs was between 16% and 45%. [PERSON] and [PERSON] [66] reported that when the sampling scale was greater than 1 m, the spatial variation of Rs increased with the increase of sampling spacing, but the increase was not significant. [PERSON] et al. [48] suggested that the CV of the Rs rate increased with the increase of spatial grain size (5 m \(\times\) 5 m, 10 m \(\times\) 10 m, and 50 m \(\times\) 50 m). However, there was no difference in the variation coefficient of Rs between the 5 m \(\times\) 5 m and 10 m \(\times\) 10 m scales. [PERSON] et al. [67] measured the variation coefficients of Rs at 20 m \(\times\) 20 m sampling scales of 1 hm\({}^{2}\) and 2 hm\({}^{2}\) and obtained CV values of 42.3%-43.7% and 39.6%-44.5%, respectively. In the present study, it was found that although Rs had obvious spatial variation, the variation coefficients of Rs in the same plot were consistent at two sampling scales (Figure 2 and Table 2). This indicates that relatively stable environmental factors at different sampling scales control the spatial variability of high or low Rs in the same plot [42; 68]. The spatial autocorrelation ranges of Rs at the 5 m \(\times\) 5 m and 10 m \(\times\) 10 m sampling scales were 11.65-16.3 m and 15.45-32.60 m, respectively, which were consistent with the results of [PERSON] et al. [48] (i.e., the spatial autocorrelation ranges of Rs were 7.9-14.1 m). These results indicate that it is important to evaluate the changes of Rs at different scales and analyze the key factors affecting the changes [19]. Rs includes autotrophic respiration (Ra) and heterotrophic respiration (Rh) [69]. Ra reflects carbon returned from roots and associated microbes to the atmosphere and regulates the distribution of photosynthetic carbon to underground tissues [29], namely root-derived respiration (i.e., root respiration and root exudates) [28]. Rh reflects the CO\({}_{2}\) released by the microbial decomposition of organic matter [69]. Therefore, Rs connects aboveground and underground carbon fractions [70] in terrestrial ecosystems and is significantly associated with a series of aboveground and underground plant traits and soil properties. However, it is difficult for researchers to obtain information on underground plant traits involving a certain spatial range. Because there is a strong correlation between changes in aboveground and underground traits [38], it is feasible to select easily measured aboveground functional traits to predict spatial variations in Rs [71]. The results showed that the key factors affecting Rs variability differed at different spatial scales. The effects of driving factors on Rs were significantly different, and plant functional traits could explain some variations in Rs (Table S2). This is because variations in aboveground plant traits can affect litter decomposition rates [72], soil microbial communities [73], and soil nutrient cycling [74; 75], and they can directly and indirectly affect spatial changes in Rs [76]. When spatial scales change, the controlling factors of Rs variation at small scales may be replaced by factors that have a stronger impact at the large scale [68].