## Results
### Inter-Correlations among SOCD, SR, Q10 and TT
Specifically, SOCD significantly increased with LF proportion and EC (\(p<0.01\)). SR was significantly associated with EC (\(p<0.01\)) and TH (\(p<0.05\)). Q\({}_{10}\) value was negatively associated with LF proportion and EC (\(p<0.01\)). TT was related with LF proportion (\(p<0.01\)), Pinaceae proportion (\(p<0.05\)), conifer/broadleaf proportion (\(p<0.01\)) and EC (\(p<0.05\)). In other words, EC value was significantly related with all the four parameters, LF proportion had significant association with SOCD, Q\({}_{10}\) and TT, tree species proportion was only associated with SR and TT, and TH only had influence on SR (Table 3). Stepwise regression could explain 82.6-99.4% of variations of the 4 SOC-related parameters, and it also confirmed the findings in Pearson correlations (Table 4). Both EC and LF changes greatly affect the 4 SOC-related urban-rural patterns. With EC increases, increasing SOCD and SR, but decreasing Q\({}_{10}\) values, were observed. With increases in LF proportion in different urban-rural gradients, increasing SOCD, SR and TT were found (Table 4). Standardized coefficients showed the relative contributions of the parameters to SOC-related parameters. EC's contribution was 2-6-fold higher than that in pH, DBH, Betulaceae and Rosaceae proportion, and LF proportion was the second contribution to SOC-related parameters (Table 4). Figure 4: Correlations between (**A**) SOCD and SR; (**B**) SOCD and Q\({}_{10}\); (**C**) SOCD and TT; (**D**) SR and Q\({}_{10}\); (**E**) SR and TT and (**F**) Q\({}_{10}\) and TT, for Changchun city of China. Notes: SOCD, soil organic carbon density; SR, soil basal respiration rate; and TT, turnover time. \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline \multirow{2}{*}{**Items**} & \multirow{2}{*}{**Model**} & \multicolumn{3}{c}{**Unstandardized**} & \multicolumn{2}{c}{**Standardized**} & \multirow{2}{*}{**Seg.**} & \multirow{2}{*}{**\(R^{2}\)**} \\ \cline{3-3} \cline{5-8}  & & & **Coefficients** & & & & & \\ \cline{3-8}  & & & **B** & **Std. Error** & **Beta** & & & \\ \hline SOCD & \(1\) & (Constant) & \(1.879\) & \(0.387\) & & \(4.854\) & \(0.003\) & \(0.971\) \\  & & EC & \(0.024\) & \(0.003\) & \(0.740\) & \(7.693\) & \(0.000\) & \\  & & LF & \(2.433\) & \(0.589\) & \(0.387\) & \(4.128\) & \(0.006\) & \\  & & Rosaceae & \(1.680\) & \(0.594\) & \(0.190\) & \(2.557\) & \(0.043\) & \\ \hline SR & \(2\) & (Constant) & \(0.434\) & \(0.174\) & & \(2.500\) & \(0.041\) & \(0.826\) \\  & & EC & \(0.006\) & \(0.001\) & \(0.918\) & \(5.644\) & \(0.001\) & \\  & & Betulaceae & \(2.042\) & \(0.791\) & \(0.420\) & \(2.581\) & \(0.036\) & \\ \hline Q\({}_{10}\) & \(3\) & (Constant) & \(-2.437\) & \(0.549\) & & \(-4.435\) & \(0.007\) & \(0.994\) \\  & & EC & \(-0.007\) & \(0.000\) & \(-1.250\) & \(-16.736\) & \(0.000\) & \\  & & pH & \(0.546\) & \(0.068\) & \(0.540\) & \(8.015\) & \(0.000\) & \\  & & DBH & \(0.049\) & \(0.005\) & \(0.430\) & \(10.522\) & \(0.000\) & \\  & & LF & \(0.256\) & \(0.088\) & \(0.247\) & \(2.912\) & \(0.033\) & \\ \hline TT & \(4\) & (Constant) & \(13.446\) & \(0.750\) & & \(17.939\) & \(0.000\) & \(0.879\) \\  & & LF & \(9.759\) & \(1.621\) & \(0.803\) & \(6.021\) & \(0.001\) & \\  & & Betulaceae & \(-16.174\) & \(5.914\) & \(-0.365\) & \(-2.735\) & \(0.029\) & \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Stepwise regressions of SOCD, SR, Q\({}_{10}\), TT and forest types, tree species, soil properties as well as tree sizes. Note: The parameter was included in the model when \(p<0.05\), while deleted when \(p>0.10\). SOCD, soil organic carbon density; SR, soil basal respiration rate; TT, turnover time. EC, soil electrical conductivity; LF, landscape and relaxation forest; and DBH, tree diameter at breast height.