the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
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
Abstract. 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 extended monocultures. However, EC sites are increasingly established in mixed forest stands which are considered to be more resilient under changing environmental conditions. This imposes the question of how species-specific responses can be derived, and how the magnitude of fluxes originating from temporally varying flux footprints predictions (FFPs) might provide insights into species-specific responses.
At a site in the Black Forest (southwestern Germany), which mainly consists of a mix of mature beech and Douglas fir trees, we investigate how EC flux measurements depend on different FFP areas and how species-specific contributions to gas exchange can be disentangled. 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 footprint 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. Nevertheless, specific-species responses to the environment 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 considering these differences is particularly important for gap-filling EC measurements and thus for determining annual carbon and water budgets. We herewith demonstrate that EC measurements over mixed forests provide important model evaluation information and that species-specific modeling is essential for untangling and distributing the underlying species-specific ecosystem dynamics.
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Status: open (until 17 Nov 2025)
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RC1: 'Comment on egusphere-2025-4605', Anonymous Referee #1, 17 Oct 2025
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CC1: 'Reply on RC1', Rüdiger Grote, 24 Oct 2025
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We are happy and grateful for the positive evaluation of the manuscript and fully comply with any request and suggestion.
Regarding the relative high number of gaps, we admit that although the intake tube of the eddy covariance system is principally heated, this heating system was not working in autumn up until we exchanged the tube beginning of December 2024. Before this change, filters were often clogged after fog and rain events which was no problem anymore afterwards.
The reason why we used soil moisture and respiration for evaluation was the availability of separate measurements for Douglas fir and beech dominated plots, respectively. This should indicate that the model is representing fluxes species-specifically in order to be sure that lumped up NEE and ET from eddy covariance measurements are correctly represented for the right reasons. However, we suggest to add a figure with measurements and weighted simulations of NEE and ET in daily resolution throughout the year (see preliminary sketch attached).
We fully comply with the other suggestions, including adding that conventional approaches of gap filling can provide similar results than the applied model. We will address this issue in the final revision of the manuscript.
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CC1: 'Reply on RC1', Rüdiger Grote, 24 Oct 2025
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General remarks:
The authors present a well-designed single-site study regarding footprint classified EC flux measurements to address tree species specific carbon and water budgets on different temporal scales. Overall, I only suggest minor changes.
The C budgets based on non-gap-filled and gap-filled fluxes differ considerably maybe due to more frequent gaps or fluxes with flag2 during winter. This is somewhat surprising to me because the use of the enclosed LI-7200 should prevent frequent gaps (by the way: is the intake tube of the LI-7200 heated or not?).
Regarding model validation: Why only soil respiration and soil moisture were compared with in situ measurements? It would be nice to see the model performance also for NEE and ET.
The conclusions include the finding that the REddyProc gap-filling showed slightly higher correlation than process-based gap-filling approaches like LandscapeDNDC. So, the statement “the current analysis we could … demonstrate the suitability of process-based models for this task” should maybe complemented by the statement that the model doesn’t perform better than the usual gap-filling, im my point of view.
Some spelling mistakes in the detailed remarks below.
Detailed remarks:
L55: regarding footprint calculation references you should mention Kljun et al. already here:
Kljun, N., P. Calanca, M. W. Rotach, and H. P. Schmid. 2004. A simple parameterisation for flux footprint predictions. Boundary-Layer Meteorology, 112: 503-523.
L94: 7.8782°E instead of 7.8782°W
L180: European instead of Europe
Fig. 4: measured soil moisture instead of measured flux
Fig. 7:Regarding hourly resolution of NEE I would prefer the unit µmol m-2 s-1 instead of kgC ha-1 hr-1
Tab. 3: mm hr-1 instead of kgC ha-1 hr-1
Fig. S8: during the non-growing season instead of during the growing season