## 2 Study Site and Methodology
### Ecosystem Components of Carbon Metabolism  
Nighttime \(R_{\mathrm{E}}\) was modeled using (1) best-fit M(N)LR models with/without the forced inclusion of temporal variables (hour and month), and (2) ST-dependent \(R_{\mathrm{soil}}\) equations [Equations (1) and (2)] of  
\begin{table}
\begin{tabular}{l c c c c} \hline \hline \multicolumn{1}{c}{**Local hour**} & \multicolumn{1}{c}{**\(n\)**} & \multicolumn{1}{c}{**mean**} & \multicolumn{1}{c}{**SD**} & \multicolumn{1}{c}{**Comparison based on 95\% confidence intervals**} \\ \hline  
0.20 & 0.20 & 0.40 \\
24:00 & 54 & 0.267 & 0.266 & (*) \\ \hline
**Day _vs. night_** & \(n\) & mean & SD & (*) & (*) \\ \hline Daytime & 1030 & \(-0.111\) & 0.222 & +-.*-.+. RothC and CENTURY models with/without the forced addition of SWC. All the \(R_{\mathrm{E}}\) models were built with the intercept forced through zero as follows:  
\[ \begin{array}{l}R_{\mathrm{E}}\left(\mathrm{mg~{}CO_{2}~{}m^{-2}~{}s^{-1}} \right)=0.0004922~{}\mathrm{h}-0.02111~{}\mathrm{month}\pm 0.13747~{}T_{\mathrm{sonic}}-0.1496~{}T_{ \mathrm{a}}\pm 0.01119\\ \mathrm{ST}_{\mathrm{min}}\pm 0.0032329~{}\mathrm{SWC}\pm 0.5456~{}u^{\star}\pm 0.5201~{}U _{\mathrm{z}}-0.04903~{}\mathrm{WS}-0.00061~{}P_{\mathrm{a}}\pm 0.0021203~{}R_{ \mathrm{n}}\\ \hskip 142.26378 pt-0.0027481~{}H_{\mathrm{s}}\\ \hskip 142.26378 pt(R^{2}_{\mathrm{adj}}=73.8\%;\ \mathrm{SE}=0.0473;n=203;P<0.001) \end{array}  \tag{6}\]  
\[ \begin{array}{l}R_{\mathrm{E}}\left(\mathrm{mg~{}CO_{2}~{}m^{-2}~{}s^{-1}} \right)=0.005383~{}T_{\mathrm{sonic}}\pm 0.0026921~{}\mathrm{SWC}\pm 1.0846~{}u^{\star} \pm 0.0733~{}U_{\mathrm{z}}-0.09595\\ \hskip 142.26378 pt\mathrm{WS}\pm 0.0009581~{}H_{\mathrm{s}}-0.0003665~{} \mathrm{RH}\\ \hskip 142.26378 pt(R^{2}_{\mathrm{adj}}=70.8\%;\ \mathrm{SE}=0.0677;n=207;P<0.001) \end{array}  \tag{7}\]  
\[ \begin{array}{l}R_{\mathrm{E}}\left(\mathrm{mg~{}CO_{2}~{}m^{-2}~{}s^{-1}} \right)=0.33084~{}\mathrm{CENTURY}\\ \hskip 142.26378 pt(R^{2}_{\mathrm{adj}}=42.0\%;\ \mathrm{SE}=0.0708;n=207;P<0.001) \end{array}  \tag{8}\]  
\[ \begin{array}{l}R_{\mathrm{E}}\left(\mathrm{mg~{}CO_{2}~{}m^{-2}~{}s^{-1}} \right)=0.085842~{}\mathrm{RothC}\\ \hskip 142.26378 pt(R^{2}_{\mathrm{adj}}=44.3\%;\ \mathrm{SE}=0.0686;n=207;P<0.001) \end{array}  \tag{9}\]  
\[ \begin{array}{l}R_{\mathrm{E}}\left(\mathrm{mg~{}CO_{2}~{}m^{-2}~{}s^{-1}} \right)=0.071387~{}\mathrm{RothC}\pm 0.0005546~{}\mathrm{SWC}\\ \hskip 142.26378 pt(R^{2}_{\mathrm{adj}}=53.0\%;\ \mathrm{SE}=0.0684;n=207;P<0.001) \end{array}  \tag{10}\]  
\[ \begin{array}{l}R_{\mathrm{E}}\left(\mathrm{mg~{}CO_{2}~{}m^{-2}~{}s^{-1}} \right)=0.28185~{}\mathrm{CENTURY}\pm 0.0004839~{}\mathrm{SWC}\\ \hskip 142.26378 pt(R^{2}_{\mathrm{adj}}=53.3\%;\ \mathrm{SE}=0.0708;n=207;P<0.001) \end{array}  \tag{11}\]  
where \(T_{\mathrm{sonic}}\) is sonic temperature (\({}^{\circ}\)C), \(U_{\mathrm{z}}\) is vertical wind speed (m s\({}^{-1}\)), and \(P_{\mathrm{a}}\) is air pressure (kPa). Nighttime \(R_{\mathrm{E}}\) Equations (6) and (11) were used to estimate daytime RE values which in turn led to the estimation of \(-\)GPP component from Equation (3) as can be seen in Figures 8 and 9. Soil water content was also determined to play a significant role in controlling daytime \(R_{\rm E}\) from the Yenicaga peatland. As a function of SWC, quadratic regression models elucidated 39.2% and 68.7% of variation in daytime \(R_{\rm E}\) according to Equations (6) and (11), respectively (Figures 12 and 13). A significant relationship between estimated GPP and PAR values was found, yielding \(R^{2}{}_{\rm adj}\) values of 80.3% and 55% from Equations (6) and (11), respectively (Figures 14 and 15). The rate of NEE in the Yenicaga peatland for the study period was on average estimated at 0.11 mg CO\({}_{2}\) m\({}^{-2}\) s\({}^{-1}\) (26.5 kg C ha\({}^{-1}\) day\({}^{-1}\)) and ranged from \(-\)1.26 mg CO\({}_{2}\) m\({}^{-2}\) s\({}^{-1}\) (-297 kg C ha\({}^{-1}\) day\({}^{-1}\)) to 1.06 mg CO\({}_{2}\) m\({}^{-2}\) s\({}^{-1}\) (249 kg C ha\({}^{-1}\) day\({}^{-1}\)).