## 2 Materials and Methods
### Data Processing  
Sensible (H) and latent heat (LE) fluxes as well as carbon dioxide (CO\({}_{2}\)) fluxes were obtained using the eddy covariance (EC) technique. This procedure is based on the covariance between vertical wind speed and a scalar obtained from the experimental data at high frequency [33]. The high-frequency EC measurements were processed using the EddyPro Advanced Software, version 7.0.6 (LI-COR Inc., Lincoln, NE, USA), resulting in half-hour fluxes. Flux estimation involved several steps: raw data filtration using the methodology described by [PERSON] and [PERSON] [34]; turbulent fluctuation calculation on a per-block mean basis, with double rotation [35] and density effect correction [36]; high-frequency spectral correction based on the mathematical formulations to model the attenuations due to instrumental configuration [37]; and both high- and low-filter spectral corrections following the methods of [PERSON] et al. [38] and [PERSON] et al. [39], respectively.  
The net ecosystem carbon exchange (NEE) was obtained as the sum of the CO\({}_{2}\) flux and the storage term (S). S was calculated as follows:  
\[\mathrm{S}=\int_{0}^{\mathrm{h}}\frac{\mathrm{d}\mathrm{C}}{\mathrm{d}t} \mathrm{d}z \tag{1}\]  
where \(\frac{\mathrm{d}\mathrm{C}}{\mathrm{d}t}\) represents the variation in the CO\({}_{2}\) concentration (C) over a half-hour interval between the surface and the observation height (h).  
Half-hour fluxes were quality controlled to remove spurious values [40]. NEE, LE, and H values above 50 umol CO\({}_{2}\) m\({}^{-2}\) s\({}^{-1}\), 700 W m\({}^{-2}\), and 400 W m\({}^{-2}\) and below \(-50\) umol CO\({}_{2}\) m\({}^{-2}\) s\({}^{-1}\), \(-100\) W m\({}^{-2}\), and \(-100\) W m\({}^{-2}\), respectively, were removed. Subsequently, a filter was applied to eliminate the remaining spikes. This filter compares the fluxes every half hour (f\({}_{\mathrm{i}}\)) with the mean (f\({}_{\mathrm{m}}\)) and standard deviation (f\({}_{\mathrm{sd}}\)), using data from the same time as f\({}_{\mathrm{i}}\) in a 14-day moving window, according to the adapted equations [41]:  
\[\mathrm{f}_{\mathrm{m}}+(1.7\mathrm{f}_{\mathrm{sd}})<\mathrm{f}_{\mathrm{i}} <\mathrm{f}_{\mathrm{m}}-(1.7\mathrm{f}_{\mathrm{sd}}) \tag{2}\]  
The filter usually used in low-turbulence situations (i.e., the u\({}_{*}\) filter, where u\({}_{*}\) represents the friction velocity) was not applied to our data, as recommended by [PERSON] et al. [31]. These authors demonstrated, using the same dataset, that when turbulence is weak, CO\({}_{2}\) and other scalars accumulate inside the canopy due to a decoupling between the levels. When a more intense period of turbulence occurs, recoupling happens. Under these conditions, the CO\({}_{2}\) fluxes filtered with u\({}_{*}\) correction can overestimate ecosystem respiration rates. This tendency increases as the turbulent fluxes become more intermittent.  
The measurement system failed during the period from 7 February 2011 to 24 August 2011. Therefore, these data were discarded from the analysis; i.e., no gap-filling procedures were performed since it is a large window to be filled. After applying quality controls to the flux data, the total amount of failures was 44.8%, 43.8%, and 51.1% for H, LE, and NEE, respectively, at the 11 m height measurements and 39.5%, 45.9%, and 49.2% for H, LE, and NEE, respectively, at the 32 m height measurements, primarily due to lack of energy or sensor maintenance. This rate of failures is in accordance with the literature [42]. Gap filling was performed using a marginal distribution sampling (MDS) method following the procedure suggested by [PERSON] et al. [43], using the REddyProc package (version 1.2.2) (Max Planck Institute for Biogeochemistry at MPI-BGC, Jena, Germany) available in RStudio (version RStudio-2024.04.0-735) [44].