## 3 Results  
### Changes in Rs and Environmental Factors  
The mean Rs of plot 1 was the highest (5 m \(\times\) 5 m: 0.29 \(\pm\) 0.17 umol m\({}^{-2}\) s\({}^{-1}\); 10 m \(\times\) 10 m: 0.28 \(\pm\) 0.15 umol m\({}^{-2}\) s\({}^{-1}\)), and that of plot 3 was the lowest (5 m \(\times\) 5 m: 0.12 \(\pm\) 0.05 umol m\({}^{-2}\) s\({}^{-1}\); 10 m \(\times\) 10 m: 0.11 \(\pm\) 0.04 umol m\({}^{-2}\) s\({}^{-1}\)) (Figure 2a). Plot types had significant effects on Rs, but sampling scales and their interactions with plot types had no significant effects on Rs (\(p\) > 0.05, Table 1). At different sampling scales, ST, SWC, SSC, pH, TN, SOC, H\({}_{\text{max}}\), and LPC were not significantly different in the same plot (\(p\) > 0.05, Figure 2b-f), but were significantly different among the three plots (\(p\) < 0.05, Figure 2k,l,t). At the sampling scale of 5 m \(\times\) 5 m, the AN, NN, TP, and AP of plot 1 were significantly higher than those of plot 2 and plot 3 (\(p\) < 0.05, Figure 2g-j), while there was no significant difference in AN, NN, TP, and AP between plot 2 and plot 3 (\(p\) > 0.05). At the sampling scale of 10 m \(\times\) 10 m, except for AP and SLA, the variables showed significant differences among different plots (\(p\) < 0.05, Figure 2q). LW, LT, and LL were significantly different among different plots and sampling scales (\(p\) < 0.05, Figure 2m-o). In addition to ST and pH, Rs and its environmental factors exhibited moderate spatial variations (10% \(\leq\) CV \(\leq\) 100%). Among them, the CV of Rs and environmental factors at different scales were not significantly different in three plots, but were different among different plots, showing the order of plot 1 \(>\) plot 2 \(>\) plot 3 (Table 2). At the sampling scale of 5 m \(\times\) 5 m, Rs in plot 1, plot 2, and plot 3 had strong, medium, and weak spatial dependence, respectively. At the scale of 10 m \(\times\) 10 m, the spatial dependence of Rs in plot 1 and plot 2 was stronger, while that in plot 3 was weaker (Table 3). Multiple Regression Analysis of Rs and Environmental Factors in Specific Plot Types under Different Sampling Scales  
The variables with higher correlations (LW, LC, LN, TN, SSC, and SOC) were removed because of [PERSON]'s \(\rho\)2 > 0.7 (Figure S2), and all the other variables were entered into the final model. Under different sampling scales, the most significant environmental variables affecting the spatial variation of Rs in different plots could be explained by the multiple regression analysis model (Table S2). At the scale of 5 m \(\times\) 5 m, LL (0.02, \(p\) < 0.01), LDMC \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Source of Variation** & _df_ & **Sum Square** & **Mean Square** & **F Value** & \(p\) **Value** \\ \hline Plot type & 2 & 0.76 & 0.38 & 32.08 & \textless{}0.001 \\ Sampling scale & 1 & 0.03 & 0.03 & 2.87 & 0.09 \\ Plot type: Sampling scale & 2 & 0.03 & 0.01 & 1.17 & 0.31 \\ Residuals & 144 & 1.71 & 0.01 & - & - \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Two-factor analysis of variance (ANOVA) for the effects of plot type and sampling scale on soil respiration. (2.98, \(p<0.01\)), LPC (0.52, \(p<0.001\)), and AP (0.01, \(p<0.05\)) jointly explained 49% of Rs variation in plot 1. In plot 2, LPC had the most significant effect on Rs (0.12, \(p<0.05\)). As the most significant variables affecting the Rs in plot 3, LL (\(-0.06\), \(p<0.05\)), LT (\(-1.23\), \(p<0.05\)), and AN (0.07, \(p<0.01\)) jointly explained 42% of the total variation (\(p<0.005\)). At the scale of 10 m \(\times\) 10 m, LL (partial regression coefficient was 0.01, \(p<0.05\)), SWC (0.04, \(p<0.001\)), and pH (0.19, \(p<0.01\)) were the most important variables affecting the Rs in plot 1, which could explain 70% of the spatial variation of the Rs in this plot (\(p<0.001\)). The contribution of LPC, SWC, TP, and AN to the Rs in plot 2 was small but significant (\(-0.09\)-\(0.06\), \(p<0.05\)).