A comparison of approaches for estimating the stable carbon isotopic composition of respired CO2 at the ecosystem scale

Background/Question/Methods

The partitioning of net ecosystem exchange of CO₂ (NEE) measured via the eddy covariance technique into gross photosynthesis (GPP) and ecosystem respiration (R_eco) can be challenging and is often associated with unknown amounts of uncertainty. In order to estimate GPP from NEE, typically nighttime measurements of R_eco are extrapolated to the day using a temperature function. Then R_eco is subtracted from NEE to obtain GPP (i.e., GPP = NEE - R_eco). However, recent evidence employing stable carbon isotopes of CO₂ has shown that this practice can strongly overestimate GPP and R_eco, from 10-100%. This is due to reduced leaf respiration during the day, aka the Kok effect. One key parameter for partitioning NEE using stable carbon isotopes is the isotopic composition of carbon respiration by the ecosystem, δ¹³C_r. δ¹³C_r is typically estimated using a Keeling plot with nighttime data either sampled via a profile method or single-inlet sampling where measurements are filtered by vertical wind velocity. In both techniques, nighttime measurements are assumed to contain information about the fractionated carbon sources from R_eco, including heterotrophic respiration and autotrophic respiration (roots, stems and leaves). We propose to compare the two Keeling plot techniques (profile vs single inlet sampling) with a modeling approach where δ¹³C_r is estimated using nighttime and daytime measurements of the δ¹³C of CO₂ emissions from leaves and profile measurements within the soil and at the soil surface. By sampling beneath the ground surface, isotopic measurements will be unaffected by wind patterns above ground thereby allowing more accurate measurements of the isotopic composition of soil respiration.

Results/Conclusions

Preliminary data comparing these approaches in an alfalfa field suggests that the δ¹³C_r can vary substantially at the daily to sub-daily time step. For example, using the Keeling plot approach with a single inlet, δ¹³C_r varied over the course of 2 weeks by 5 per mil. We are currently evaluating the modeling and profile techniques in a restored wetland. These data will help assess uncertainty associated with the δ¹³C_r parameter thereby improving our ability to accurately partition NEE into R_eco and GPP.