# Characteristics of Carbon Fluxes and Their Environmental Control in Chenhu Wetland, China
## 3 Results and Discussion
### Relationships Between NEE and Some Environmental Parameters  
The CO\({}_{2}\) flux within wetland ecosystems is influenced by a range of environmental parameters. Tables 2 and 3 illustrate the relationships between the monthly average diurnal variation of NEE and several environmental factors, including T\({}_{\text{a}}\), T\({}_{\text{s}}\), PAR, VPD, SWC, and precipitation (P). During daylight hours, NEE exhibited the strongest correlation with PAR, followed by RH, T\({}_{\text{a}}\), and VPD. Conversely, during nighttime, NEE demonstrated a significant correlation with RH, VPD, and T\({}_{\text{a}}\). \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Study Site** & **Longitude/Latitude** & **Wetland** & **Dominant Plant** & **Measuring** & **Annual** & **References** \\ \hline Taihu wetland & 30.9278\({}^{\circ}\) N–5494\({}^{\circ}\) N, 119.8756\({}^{\circ}\) E–119.6028\({}^{\circ}\) E & Lake wetland & _Potamogeton maliaunts_, _Hydrilla verticillata_ & 2012–2017 & 25.25 & [37] \\ \hline Hongze Lake & 33.55\({}^{\circ}\) N, 118.53\({}^{\circ}\) E & Lake wetland & _Populus\(\times\) euramericana_ & & & \\  & & & cv. Nanlin-95, _Bidens_ & & & \\  & & & & _tripartita L., Setaria_ & & & \\  & & & _viridis_ (L.[PERSON]. & & & \\ \hline Beihai wetland & 25.1218\({}^{\circ}\) N, 98.5561\({}^{\circ}\) E & Alpine marsh & _Cyperus duclouzzi E.-G. [PERSON], Oberonia_ & & & \\  & & & _ciardifolia Roxb. [PERSON]_ & & & \\ \hline Chenhu wetland & 30.3270\({}^{\circ}\) N, 113.8617\({}^{\circ}\) E & Lake-marsh wetland & _Phragmites communis_, _Zizanicaaduflora Ass_ & 2022 & 21.20 & This study \\ \hline \hline \end{tabular}
\end{table} 
Table 1: _Cont._ \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Month** & **T\({}_{\text{a}}\)** & **PAR** & **T\({}_{\text{s}}\)** & **RH** & **VPD** & **SWC** & **P** \\ \hline
1 & \(-\)0.008 & 0.469 \({}^{\ast}\) & \(-\)0.156 & 0.051 & \(-\)0.054 & 0.143 & \(-\)0.120 \\
2 & \(-\)0.143 & \(-\)0.643 \({}^{\ast\ast}\) & 0.383 & 0.139 & \(-\)0.111 & 0.130 & \(-\)0.044 \\
3 & \(-\)0.279 & \(-\)0.903 \({}^{\ast\ast}\) & 0.837 \({}^{\ast\ast}\) & 0.342 & \(-\)0.267 & 0.212 & 0.273 \\
4 & \(-\)0.355 & \(-\)0.947 \({}^{\ast\ast}\) & 0.858 \({}^{\ast\ast}\) & 0.341 & \(-\)0.329 & 0.592 \({}^{\ast\ast}\) & 0.051 \\
5 & \(-\)0.463 \({}^{\ast}\) & \(-\)0.972 \({}^{\ast\ast}\) & \(-\)0.175 & 0.513 \({}^{\ast\ast}\) & \(-\)0.432 \({}^{\ast}\) & 0.435 \({}^{\ast}\) & 0.168 \\
6 & \(-\)0.500 \({}^{\ast\ast}\) & \(-\)0.939 \({}^{\ast\ast}\) & 0.070 & 0.575 \({}^{\ast\ast}\) & \(-\)0.521 \({}^{\ast\ast}\) & \(-\)0.112 & 0.404 \({}^{\ast}\) \\
7 & \(-\)0.529 \({}^{\ast\ast}\) & \(-\)0.949 \({}^{\ast\ast}\) & \(-\)0.297 & 0.657 \({}^{\ast\ast}\) & \(-\)0.611 \({}^{\ast\ast}\) & 0.088 & 0.239 \\
8 & \(-\)0.519 \({}^{\ast\ast}\) & \(-\)0.926 \({}^{\ast\ast}\) & \(-\)0.527 \({}^{\ast\ast}\) & 0.640 \({}^{\ast\ast}\) & \(-\)0.604 \({}^{\ast\ast}\) & 0.086 & 0.115 \\
9 & \(-\)0.501 \({}^{\ast\ast}\) & \(-\)0.914 \({}^{\ast\ast}\) & 0.134 & 0.548 \({}^{\ast\ast}\) & \(-\)0.492 \({}^{\ast}\) & 0.179 & 0.474 \({}^{\ast}\) \\
10 & \(-\)0.571 \({}^{\ast\ast}\) & \(-\)0.930 \({}^{\ast\ast}\) & 0.186 & 0.603 \({}^{\ast\ast}\) & \(-\)0.550 \({}^{\ast\ast}\) & 0.155 & 0.256 \\
11 & \(-\)0.560 \({}^{\ast\ast}\) & \(-\)0.913 \({}^{\ast\ast}\) & 0.191 & 0.549 \({}^{\ast\ast}\) & \(-\)0.541 \({}^{\ast\ast}\) & 0.101 & \(-\)0.103 \\
12 & \(-\)0.478 \({}^{\ast}\) & \(-\)0.453 \({}^{\ast}\) & \(-\)0.514 \({}^{\ast}\) & 0.573 \({}^{\ast\ast}\) & \(-\)0.529 \({}^{\ast}\) & \(-\)0.564 \({}^{\ast\ast}\) & \(-\)0.417 \\ \hline \hline \end{tabular} Note: \({}^{\ast}\) and \({}^{\ast\ast}\) are significantly correlated at 0.05 (bilateral) and 0.01 (bilateral) levels, respectively.  
\end{table} 
Table 2: Pearson correlation coefficients of the monthly mean daily variation of NEE and environmental parameters during daytime. Path analysis has been widely utilized to evaluate the significance of various environmental factors in relation to seasonal and interannual variations in carbon flux [47].