A Modeling Approach to Investigate Drivers, Variability and Uncertainties in O2 Fluxes and the O2 : CO2 Exchange Ratios in a Temperate Forest
Abstract. The O2 : CO2 exchange ratio (ER) between terrestrial ecosystems and the atmosphere is a key parameter for partitioning global ocean and land carbon fluxes. The long-term terrestrial ER is considered to be close to 1.10 moles of O2 consumed per mole of CO2 produced. Due to the technical challenge in measuring directly the ER of entire terrestrial ecosystems (EReco), little is known about the variations in ER at the hourly and seasonal scales as well as how different components contribute to EReco. In this modeling study, we explore the variability and drivers of EReco and evaluate the hypothetical uncertainty in determining ecosystem O2 fluxes based on current instrument precision. We adapted the one-dimensional, multi-layer atmosphere-biosphere gas exchange model, CANVEG, to simulate hourly EReco from modeled O2 and CO2 fluxes in a temperate beech forest in Germany.
We found that the annual mean EReco ranged from 1.06 to 1.12 mol mol-1 within the five years’ study period. Hourly EReco showed strong variations over diel and seasonal cycles and within the vertical canopy profile. Determination of ER from O2 and CO2 mole fractions in air above and within the canopy (ERconc) varied between 1.115 and 1.15 mol mol-1. CANVEG simulations also indicated that ecosystem O2 fluxes could be derived using the flux-gradient method in combination with measurements of vertical scalar gradients and CO2, sensible heat or latent heat fluxes obtained with the eddy covariance technique. Owing to measurement uncertainties, however, the uncertainty in estimated O2 fluxes derived with the flux-gradient approach could be as high as 15 μmol m-2 s-1, which represented the 90 % quantile of the uncertainty in hourly data with a high-accuracy instrument. We also demonstrated that O2 fluxes can be used to partition net CO2 exchange fluxes into their component fluxes of photosynthesis and respiration, if EReco is known. The uncertainty of the partitioned gross assimilation ranged from 1.43 to 4.88 μmol m-2 s-1 assuming a measurement uncertainty of 0.1 or 2.5 μmol m-2 s-1 for net ecosystem CO2 exchange and from 0.1 to 15 μmol m-2 s-1 for net ecosystem O2 exchange, respectively. Our analysis suggests that O2 measurements at ecosystem scale have the potential for partitioning net CO2 fluxes into their component fluxes, but further improvement in instrument precision is needed.
Yuan Yan et al.
Status: open (until 13 Apr 2023)
RC1: 'Comment on bg-2023-30', Anonymous Referee #1, 07 Mar 2023
- AC1: 'Reply on RC1', Yuan Yan, 22 Mar 2023 reply
- CC1: 'Comment on bg-2023-30', Andrew Kowalski, 13 Mar 2023 reply
Yuan Yan et al.
Yuan Yan et al.
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The reviewed manuscript presents an interesting study that models the O2 and CO2 fluxes in and above a forest canopy, and aims to determine if the actual measurement of such fluxes will enable the partitioning of the CO2 fluxes into its components. This is a new and interesting modeling exercise, and the manuscript is generally well-written and clear.
I find the way the manuscript is structured somewhat confusing. In the method section, the effect of nitrate assimilation on the ER is ignored, and a fixed value for stem and soil ER is assumed, although the introduction mentioned a range found in field studies. That leaves the reader to wonder why these important variations are ignored. Then the results are detailed, based on the simplified assumption of a fixed ER, and only in the discussion, the variability in the sources ER is discussed in detail and a sensitivity test is performed. If the authors want to keep this structure, they should state clearly in the methods and the results sections, that the effect of variability in ER will be discussed and tested later. For me, it seems it will be even better if some of this discussion will be moved to the introduction and the sensitivity analysis will be included in the methods and results.
This issue has also important implications for the conclusions. If chamber studies at a given site show a constant and large difference between the respiration components, there is a much better chance to use the O2 approach for CO2 fluxes partitioning. Maybe this could be also demonstrated by a test run of the model.
Line 35: I guess there are much older references for this, or this can be just assumed as common knowledge.
Line 49: How important is this 0.05 Pg uncertainty compared to other uncertainties, like the effect of ocean warming on O2 solubility?
Line 707: As in the major comments above – is it worth showing some sensitivity test for this?