Quantifying and reducing the differences in forest CO2-fluxes estimated by eddy covariance, biometric and chamber methods: A global synthesis
Carbon dioxide (CO2) fluxes between terrestrial ecosystems and the atmosphere are primarily measured with eddy covariance (EC), biometric, and chamber methods. However, it is unclear why the estimates of CO2-fluxes, when measured using these different methods, converge at some sites but diverge at others. We synthesized a novel global dataset of forest CO2-fluxes to evaluate the consistency between EC and biometric or chamber methods for quantifying CO2 budget in forests. The EC approach, comparing with the other two methods, tended to produce 25% higher estimate of net ecosystem production (NEP, 0.52Mg C ha-1 yr-1), mainly resulting from lower EC-estimated Re; 10% lower ecosystem respiration (Re, 1.39Mg C ha-1 yr-1); and 3% lower gross primary production (0.48 Mg C ha-1 yr-1) The discrepancies between EC and the other methods were higher at sites with complex topography and dense canopies versus those with flat topography and open canopies. Forest age also influenced the discrepancy through the change of leaf area index. The open-path EC system induced >50% of the discrepancy in NEP, presumably due to its surface heating effect. These results provided strong evidence that EC produces biased estimates of NEP and Re in forest ecosystems. A global extrapolation suggested that the discrepancies in CO2 fluxes between methods were consistent with a global underestimation of Re, and overestimation of NEP, by the EC method. Accounting for these discrepancies would substantially improve the our estimates of the terrestrial carbon budget .
- Research Organization:
- Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
- Sponsoring Organization:
- USDOE
- DOE Contract Number:
- AC05-76RL01830
- OSTI ID:
- 1416691
- Report Number(s):
- PNNL-SA-124998; KP1702010
- Journal Information:
- Agricultural and Forest Meteorology, Vol. 247, Issue 15 December 2017; Related Information: pages 93-103; ISSN 0168-1923
- Publisher:
- Elsevier
- Country of Publication:
- United States
- Language:
- English
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