Results

Representativeness and Functional Homogeneity of the Ecosystem

To ensure that the measurements collected by the Kakubari Tower were representative of the system, a site homogeneity validation was performed. This step was important because eddy covariance measurements depend on a dynamically changing source area, which may influence the interpretation of ecosystem processes. Wind direction (north, south, east, and west), tower footprint modeling (short, medium, and long distance), and wind speed (low, medium, and high speed) were considered to identify the variability of fluxes such as Gross Primary Productivity, Net Ecosystem Exchange, and Latent Heat, as well as water use efficiencies. Speeds and distances were grouped using tertiles.

Validation by Wind Speed

Figure 13 shows the behavior of the analyzed variables under three different wind speed ranges. The results show stable values ​​for the variables corresponding to water use efficiency, while Net Ecosystem Exchange exhibits inherent variability at high speeds. The low sensitivity in water use efficiency suggests that the captured signal mainly reflects physiological processes of the forest, such as stomatal regulation (process where plants control the opening and closing of leaf pores to balance gas exchange). 

Validation by Wind Direction 

The box plots in Figure 14 show some variability for Net Ecosystem Exchange, Gross Primary Productivity, and Latent Heat Flux, while water use efficiency shows greater stability. The observed changes are not significant, except for Net Ecosystem Exchange, suggesting that the forest surrounding the tower is functionally uniform, ruling out biases due to the presence of heterogeneous vegetation patches. 

Footprint Distance Validation (X80) 

For the key variables presented in the box plots of Figure 15 (Gross Primary Productivity, Net Ecosystem Exchange, and Latent Heat Flux), the medians and ranges of dispersion show similar behavior across the three distance categories, indicating that the forest structure is equivalent along the selected buffer kilometer. Although the variables related to water use efficiency exhibit greater dispersion due to their mathematical sensitivity, the medians also maintain a similarity. 

The coefficient of variation (CV) of the box plots presented above is shown in Table 1. This variability matrix allows for easy distinction between the biological stability of the ecosystem and the physical dynamics of atmospheric transport. While low CV values ​​for productivity and water efficiency act as indicators of a structurally uniform canopy, the variations observed in net ecosystem exchange are interpreted under the intrinsic sensitivity of net fluxes and turbulent mixing. 

Carbon and energy flows do not show significant variations depending on the direction of wind or the extent of the operational footprint. This analysis suggests that the data obtained from the Kakubari station show functional homogeneity for ecosystem productivity, where the coefficient of variation for Gross Primary Productivity was used as a primary indicator of functionally uniform canopy. When grouping the values ​​by distance from which the data originated (footprint extent), the coefficient of variation was 3.75%, while when grouped by wind speed and direction, values ​​of 17.4% and 19.7% were obtained respectively (Table 1). However, it is not possible to attribute the variability observed when varying wind speed and direction solely to ecosystem properties, since these factors constantly change turbulence and carbon dioxide transport, increasing variability in the tower records.

Identification of Dominant Environmental Drivers 

Canonical correlation analysis was used to examine the association of environmental variables with the variability in ecosystem fluxes, using two sets of variables: environmental drivers (Photosynthetic Active Radiation, Vapor Pressure Deficit, Air temperature, NDVI, and EVI) and ecosystem responses (Gross Primary Productivity, Net Ecosystem Exchange, Latent Heat Flux, Intrinsic Water Use Efficiency, and Water Use Efficiency).  

The results reveal a strong level of shared variability between forest fluxes and environmental conditions, with a first correlation of Rc = 0.926 (Figure 16). This result suggest that environmental conditions and ecosystem fluxes are statistically associated.

For the loads obtained in CANCOR (Table 2), the Vapor Pressure Deficit appears as the main environmental driver (-0.97), followed by air temperature (-0.59). For Photosynthetic Active Radiation and vegetation indices, their contribution was very low, implying that on a daily scale, atmospheric water stress has greater control over forest metabolism, in contrast to light availability or forest greenness. Regarding the ecosystem response, the analysis highlights a close link between the atmospheric driver and water use (intrinsic water use efficiency = -0.9 and water use efficiency = -0.59). 

The fact that Vapor Pressure Deficit and Intrinsic Water Use Efficiency have the greatest contribution and the same sign suggests a biological response: the increase in evaporative demand is the main driver of water use efficiency in this forest. These results suggests that atmospheric water status is the primary regulator of this forest's dynamics.