## 2 Material and Methods
### Eddy Covariance and Environmental Factors Measurements  
The CO\({}_{2}\) and H\({}_{2}\)O fluxes of two forest ecosystems were measured by the eddy covariance (EC) systems. The EC was composed of multiple sensors, including a three-dimensional sonic anemometer (CSAT-3, Campbell Scientific, Logan, UT, USA) with an open-path infrared H\({}_{2}\)O and CO\({}_{2}\) gas analyzer (LI-7500 DS, LI-COR, Lincoln, NE, USA). They combined to measure the CO\({}_{2}\) and H\({}_{2}\)O molar fractions and other relevant environmental factors in the air. The sensors were installed at a height of about 2.5 m in the forest canopy to measure the three components of wind velocity vectors (u, v, and w), and the sonic temperature. The CO\({}_{2}\) and H\({}_{2}\)O concentrations were collected at 10 Hz, recorded using the CR6 data logger (Campbell Scientific, Logan, UT, USA). At the same time, the main environmental factors were also measured by the EC systems, including air temperature (TA, \({}^{\circ}\)C), air relative humidity (RH, %), solar radiation (Rn, W\(\cdot\)m\({}^{-2}\)), four-component radiation (SWIN/SWOUT/LWIN/LWOUT, W\(\cdot\)m\({}^{-2}\)), photosynthetically active radiation (PAR, \(\mu\)mol\(\cdot\)m\({}^{-2}\).s\({}^{-1}\)), soil temperature (TS, \({}^{\circ}\)C), soil water content (SWC, %), atmospheric pressure (Pa, Pa), wind direction (\({}^{\circ}\)), and speed (m\(\cdot\)s\({}^{-1}\)). All of the above environmental factors were measured in a time step of 30 min by a data acquisition system (CR6, Campbell Scientific, Logan, UT, USA). More detailed information about the instruments and installations is described in Table S2. Vapor pressure deficit (VPD, KPa) was calculated using the 30 min average air temperature (TA, \({}^{\circ}\)C) and air relative humidity (RH, %) according to the following formula [49]:  
\[\mathrm{VPD}=0.611\times\mathrm{exp}\bigg{(}\frac{17.502\mathrm{TA}}{\mathrm{TA} +240.97}\bigg{)}\times\bigg{(}1-\frac{\mathrm{RH}}{100}\bigg{)} \tag{1}\]  
In this study, SWC and TS were measured at approximately 40 cm of soil layer (root zone), closely related to the vegetation growth and evapotranspiration [50]. Other meteorological data were collected at the top of the canopy. All the fluxes data and meteorological data collected by the EC system were integrated into the SmartFlux system (LI-COR, Lincoln, NE, USA), which included an Li-7500 DS, a built-in GPS module, and an embedded processor running EddyPro 7.0.6 (LI-COR, Lincoln, NE, USA). They were the software for calculating fluxes data [45; 50]. The SmartFlux system was an autonomous system that collected data from the LI-7500 DS and used the EddyPro program, which performed the spike detection, frequency response corrections, conversion of sonic temperature into actual temperature, coordinate rotation using planar fit method, and WPL density correction [51], and synchronization of variables from all instruments [50; 52]. Calculation, Quality Control, Gap Filling, and Component Partitioning of the H\({}_{2}\)O/CO\({}_{2}\) Fluxes  
The EC raw data were processed by SmartFlux system, including the eddy covariance, meteorological data, and data quality identification. Subsequently, the data quality control, gap filling, and component partitioning were further conducted with the Tovi 2.4.0 software (LI-COR, Lincoln, NE, USA) ([[https://www.licor.com/tovi/#pricing](https://www.licor.com/tovi/#pricing)]([https://www.licor.com/tovi/#pricing](https://www.licor.com/tovi/#pricing)) (accessed on 30 August 2020)) [53]. It mainly included the following steps: Firstly, it checked the quality of the eddy covariance and meteorology data. Secondly, it gap-filled meteorological data using the meteorological data from redundant or external datasets. Thirdly, it based the critical friction velocity (u*) threshold and excluded fluxes under calm wind conditions.