## 4 Materials and Methods
### Flux Observation  
This study directly utilized the shared data of ChinaFLUX ([[http://www.chinaflux.org/](http://www.chinaflux.org/)]([http://www.chinaflux.org/](http://www.chinaflux.org/)) (accessed on 1 March 2023)). Eddy covariance technique (EC) is generally utilized to measure the Net Ecosystem Exchange (NEE) between vegetation and the atmosphere [36]. In this study, the open-path Eddy covariance (OPEC) is adopted for flux observation. The system is composed of a three-dimensional ultrasonic anemometer (CAST3, Campbell Scientific Ltd., Logan, UT, USA) and a fast-response infrared CO\({}_{2}\)/H\({}_{2}\)O analyzer (Li-7500A, LiCor Inc., Lincoln, NE, USA). The data collector (CR5000, Campbell Scientific Ltd., Logan, UT, USA) collects data at a frequency of 10 Hz and the half-hourly average flux was computed and stored in real time. The net ecosystem carbon flux is calculated as:  
\[F_{c}=\overline{w^{\prime}\rho_{c}{}^{\prime}} \tag{1}\]  
Figure 7: Vegetation landscape of Qianyanzhou Station.  
where \(F_{c}\) is CO\({}_{2}\) flux derived from EC; \(w^{\prime}\) is the instantaneous vertical wind velocity fluctuation, and \(\rho_{c}{{}^{\prime}}\) is the CO\({}_{2}\) density fluctuation in the air. The upper horizontal line represents the covariance between the instantaneous fluctuation of vertical wind speed and the CO\({}_{2}\) density during a certain period (30 min).  
The standard procedure developed by ChinaFLUX was applied to the measured flux to carry out a series of correction and quality control and generate the half-hourly averaged flux data including coordinate rotation, WPL correction, frequency response correction and night data correction [37]. Consider the effect of the canopy, the storage flux was also estimated from the variation of CO\({}_{2}\) concentration, and net ecosystem exchange (NEE) was the sum of the measured \(F_{c}\) and the storage flux. After that, the spurious half-hourly CO\({}_{2}\) flux data were also detected and eliminated using both a flux threshold (1 NEE! 3.0 mg CO\({}_{2}\) m\({}^{-2}\) s\({}^{-1}\)) and the algorithms proposed by [PERSON] et al. [38]. The data under stable conditions was also excluded with a reasonable u\({}^{*}\) threshold which was helpful to reduce the effect of insufficient fetch and turbulence.  
For missing flux and meteorological observation data in a short period of time (less than 2 h), linear interpolation is used; For meteorological data that has been missing for a long time, use meteorological station observation data (excluding SWC and Rain) for interpolation; If the interpolation cannot be completed, use the average daily variation method to complete the data interpolation. For CO\({}_{2}\) flux data missing for a long time, non-linear regression method is used for interpolation, the Lloyd and Taylor equation is used for nighttime data interpolation, and rectangular hyperbola equation is used to fill the daytime missing data [39].  
The marginal distribution sampling method was applied for flux partitioning. Firstly, using the same regression equation as when imputing missing data, the coefficients in the ecosystem respiration equation are determined for nighttime observation data; Then, use this equation to calculate the ecosystem respiration (Reco) at night and during the day; Finally, complete and continuous ecosystem GPP observation data were obtained using daytime CO\({}_{2}\) flux data and calculated ecosystem respiration [39]. Consider the sign of NEE, negative NEE which indicating carbon absorption by ecosystem, GPP was calculated as,  
\[\text{GPP}=\text{R}_{\text{eco}}-\text{NEE} \tag{2}\]  
Further details for flux processing in this station were described in [PERSON] et al. [40].