Matching scales of eddy covariance measurements and process-based modeling: assessing spatiotemporal dynamics of carbon and water fluxes in a mixed forest in Southern Germany

Eddy covariance (EC) measurements are a backbone of ecological research and have provided valuable insights into the variability of carbon and water fluxes in different ecosystems and under varying environmental conditions. Since these measurements are integrative and weighted over changing areas (footprint), species-specific information cannot be easily derived except for homogenous monocultures. However, EC sites are increasingly established in mixed forest stands which are considered to be more resilient under changing environmental conditions. This leads to the question of how species-specific responses can be determined, and whether the magnitude of fluxes derived from temporally varying flux footprint predictions (FFPs) can provide insight into these responses.

At a site in southwestern Germany's Black Forest, primarily composed of mature beech and Douglas fir trees, we investigate the dependence of EC flux measurements on different FFP areas and explore how species-specific contributions to gas exchange can be disentangled using a combined measurement and modeling framework. We applied an ecosystem model that has been calibrated from EC measurements at various sites with beech- and Douglas fir monocultures, and evaluated it with data of soil water content and soil respiration taken at homogeneous parts of the investigated mixed forest site. Then we compared hourly aggregated measurements of net carbon exchange (NEE) and evapotranspiration (ET) with model simulations under four configurations: (i) pure beech, (ii) pure Douglas fir, (iii) a static weighted average of both species, and (iv) a dynamic weighted average based on FFP variations.

The results show that weighted combinations of the two species generally provide a better match with hourly EC measurements than single-species simulations, while differences between static and dynamic weighting approaches remain relatively small. However, species-specific flux responses can be significantly different during transitional periods such as autumn and spring when physiological differences between Douglas fir and beeches are most pronounced. We demonstrate that accounting for seasonal differences is particularly important for gap-filling EC measurements in mixed forests and, consequently, for determining annual carbon and water budgets. Furthermore, EC measurements over mixed forests provide valuable information for detailed model evaluation, while species-specific modeling helps disentangle and attribute underlying ecosystem dynamics to individual species.