## 2 Materials and Methods
### Eddy Covariance Measurements and Data Processing  
A closed-path eddy covariance (EC) system was installed in the east-central section of the orchard, with the sensors positioned at 8.0 m above the land surface. The system consisted of a fast-response three-dimensional sonic anemometer (CSAT3A, Campbell Scientific Inc., Logan, UT, USA), a closed path CO\({}_{2}\)/H\({}_{2}\)O gas analyzer (EC155, Campbell Scientific Inc., USA) capable of measuring the concentration of CO\({}_{2}\) (CCO\({}_{2}\)) and concentration of water vapor (CH\({}_{2}\)O), a temperature and humidity sensor (HMP45C), a data logger (CR6 Campbell Scientific Inc., UT, USA), an instrument calibration control system, and a power supply system. To alleviate aerodynamic interference, the three-dimensional sonic anemometer was mounted on a 3 m long arm, oriented perpendicular to the prevailing wind direction at the flux station.  
Data measured by the eddy covariance technique were processed using the Datalogger Support Software 4.4 (Campbell Scientific Inc., USA), following standard procedures to convert the origin 10 Hz data into 30 minute flux data. The processing methods include the following: (i) using quadratic rotation to eliminate the vertical (w) and lateral (v) velocity components over the 30 minute interval; (ii) using covariance maximization to correct the time delays caused by the distance between the sensor and the analyzer; (iii) correction for high-frequency losses due to the spacing between the ultrasonic instrument and the water vapor and CO\({}_{2}\) probes, and low-frequency losses due to inadequate averaging time; and (iv) WPL density correction (adjustment for air density fluctuations) for water vapor and CO\({}_{2}\) fluxes [34].  
The 30 min flux data were further screened based on the following criteria: (1) incomplete measurements or data measured within rain events were excluded; (2) data with  
Figure 1: (**a**) Geophysical location and (**b**) wind rose plot of the studied ecosystems in the Pujiang County of Chengdu Plain, southwest China.  
quality flags ranging from 7 to 9 were also excluded due to low measured quality [35]; (3) flux data were deemed accurate only under high turbulent conditions, indicated by the friction velocity u* > 0.15 m s\({}^{-1}\)[36; 37]. Based on these criteria for quality control, 27% of all data during 2018-2019 were rejected. For the data gaps less than 2 h, the data were filled with linear interpolation. For gaps exceeding two hours, daytime carbon flux data were interpolated using the following Michaelis-Menten equation [38]:  
\[\mathrm{NEE}=\mathrm{R_{d}}-\frac{\alpha\cdot\mathrm{PAR}\cdot\mathrm{P_{max} }}{\alpha\cdot\mathrm{PAR}+\mathrm{max_{max}}} \tag{1}\]  
where NEE is the measured net ecosystem exchange (mg CO\({}_{2}\) m\({}^{-2}\) s\({}^{-1}\)), \(\mathrm{R_{d}}\) is the daytime ecosystem respiration (mg CO\({}_{2}\) m\({}^{-2}\) s\({}^{-1}\)), PAR is photosynthetic active radiation (\(\mathrm{\mu mol}\) phon m\({}^{-2}\) s\({}^{-1}\)), \(\alpha\) is the apparent quantum output (mg CO\({}_{2}\)\(\mathrm{\mu mol}\) phon\({}^{-1}\)), and \(\mathrm{P_{max}}\) is maximum ecosystem photosynthetic rate.  
The missing nighttime carbon flux data was filled using the equation given by [39]:  
\[\mathrm{R_{e}}=\mathrm{R_{10}}\cdot\mathrm{exp}\left[\mathrm{E_{0}}\left( \frac{1}{\mathrm{T_{10}}-\mathrm{T_{0}}}\right)-\left(\frac{1}{\mathrm{T_{a}} -\mathrm{T_{0}}}\right)\right] \tag{2}\]  
where \(\mathrm{R_{e}}\) is ecosystem respiration, \(\mathrm{R_{10}}\) is ecosystem respiration at 10 \({}^{\circ}\)C (T\({}_{10}\)), \(\mathrm{E_{0}}\) is a temperature-sensitive parameter, \(\mathrm{T_{a}}\) is air temperature, and \(\mathrm{T_{0}}\) is a reference temperature (\(-\)46.02 \({}^{\circ}\)C).  
The gross primary productivity (GPP) is calculated from the following:  
\[\mathrm{GPP}=\mathrm{R_{e}}-\mathrm{NEE} \tag{3}\]