Increased spatial replication above heterogeneous agroforestry improves the representativity of eddy covariance measurements

Eddy covariance (EC) studies typically involve the use of one or maximum two measuring towers, which leads to a low level of spatial replication, compromising the statistical representativity of EC measurements, especially above highly heterogeneous ecosystems, such as agroforestry systems. Lower-cost eddy covariance setups (LC-EC) represent a potential solution to this problem, since their affordability allows for the installation of multiple EC towers to study heterogeneity at the landscape scale. In the last years, several LC-EC setups have been successfully validated against conventional EC setups (CON-EC), with the main difference being the use of slower gas analyzers. These introduce a higher uncertainty due to the enhanced high-frequency spectral attenuation in the turbulent energy spectrum.

In this study, we analyzed turbulent fluxes of CO₂ and H₂O and turbulence characteristics measured by three flux towers equipped with LC-EC setups above one agroforestry system located in Wendhausen, Germany. The agroforestry system was a Short Rotation Alley Cropping (SRAC) system, consisting of alternating rows of trees and crops. The three flux towers were installed at different North-South aligned tree stripes. Additionally, we compared the results of the three LC-EC setups above the SRAC with another LC-EC setup installed at an adjacent monocropping (MC) field.

The objectives of the study were: (i) to evaluate the spatial variability of EC fluxes from the three flux towers above the SRAC system; (ii) to compare the variability of fluxes within the SRAC to the variability of fluxes between SRAC and MC; (iii) to quantify whether the use of several LC-EC setups counteracts the higher uncertainty associated to LC-EC, due to the increased statistical robustness of the measurement network compared to the hypothetical use of just one EC station.

The highest spatial variability across the SRAC was measured for CO₂ fluxes, followed by latent heat (LE) flux, with coefficients of variation, calculated following Oren et al. (2006) (https://doi.org/10.1111/j.1365-2486.2006.01131.x), of 2.3 and 1.4 (dimensionless), respectively. The spatial variability in CO₂ and LE fluxes within the SRAC was similar to the variability between MC and SRAC, and was attributed to the different land cover types around the towers. On the other hand, the spatial variability in sensible heat flux (H), momentum flux and turbulence characteristics (such as friction velocity and variance of vertical wind speed), within the SRAC, was smaller than the variability between SRAC and MC, likely explained by the development of an internal boundary layer (IBL) above the SRAC.

Our results show that the heterogeneity of the SRAC, despite not affecting significantly the turbulence characteristics across the site, leads to a large spatial variation in CO₂ and LE fluxes. Therefore, a distributed network of several EC systems is necessary to properly quantify patterns and drivers of CO₂ and latent heat fluxes above such heterogeneous land-use systems.