AUTHOR=Jiang Junjie , Hu Junguo , Xu Xiaojun , Li Yongfu , Sheng Jie TITLE=Effect of near-surface winds on the measurement of forest soil CO2 fluxes using closed air chambers JOURNAL=Frontiers in Ecology and Evolution VOLUME=11 YEAR=2023 URL=https://www.frontiersin.org/journals/ecology-and-evolution/articles/10.3389/fevo.2023.1163704 DOI=10.3389/fevo.2023.1163704 ISSN=2296-701X ABSTRACT=

Forest soil CO2 flux measurements are important for studying global climate change. Current monitoring methods are based on closed gas chambers, which block the wind pumping effect of near-surface winds in the measurements, resulting in biased values. Therefore, in this study, the effects of near-surface winds on chamber-monitored fluxes were investigated. The CO2 flux was quantified using a designed flux reference system with different CO2 concentrations, and the monitoring performance of the closed chamber was studied. Wavelet coherence was used to analyze the response relationship between near-surface winds and soil gas, and was combined with a flux calculation model to explore the relevant factors influencing gas chamber measurement-produced bias. The data indicate that at near-surface wind speeds greater than 0.8 m·s−1, gas transport enhancement was significant and further increased the deviation of the gas chamber-monitored CO2 fluxes. The monitoring error of the flow chamber (NSF) increased from 7% to 30% in soils with low carbon content, but did not vary significantly (3–7%) in soils with high CO2 concentrations. The flux measurement bias of the non-flow chamber (NSNF) was positively correlated with the soil carbon content, with the measurement error expanding by 16–24% with increasing soil CO2 concentrations. The measurement errors of the exponential and linear models in a windless environment were 9.8% (Exp) and 18.7% (Lin), respectively. The estimation errors of both models were positively correlated with both the time of a single monitoring event and the wind-induced coefficient Dw. Therefore, flux calculation models should be improved by considering environments with wind disturbances to reduce the effect of wind on measured values, which will help improve the accuracy of ecosystem carbon budgets.