Emissions of nitrous oxide (N2O) over croplands are a major source of greenhouse gases to the atmosphere. The precise accounting of sources of N2O is essential to national and global budgets, as well as the understanding of the spatial and temporal relationships with environmental variables such as rainfall, air and soil temperature, and soil moisture. The objective of this work was to investigate the temporal correlations of N2O fluxes with soil and air temperatures, as well as soil moisture. N2O fluxes were measured over four biofuel crops in Central Illinois during their establishment phase. Measurements were carried out from 2009 to 2011 using a trace gas analyzer (TGA) with tunable laser technology. Measurements of concentrations of N2O and CO2 were taken at the center of four plots of maize/soybean rotation, miscanthus (Miscanthus × giganteus), switchgrass (Panicum virgatum) and a mixture of native prairie plants. Cumulative fluxes indicate an average emission of nitrogen via N2O fluxes on the order of 1.5 kg N ha−1 year−1, in agreement with chamber measurements previously reported for the site. N2O fluxes were associated with peaks in soil and air temperature, and soil moisture, particularly during spring and winter thaws. Cross-wavelet analysis was used to investigate the correlation between N2O fluxes and those variables. Results indicate that N2O fluxes and meteorological variables have significant covariance in time scales ranging from 4 to 32 days. In addition, temporal delays of 1–8 days were found in those relationships. Cross-wavelet patterns were similar when relating N2O fluxes with soil temperature, air temperature and soil moisture. The temporal patterns of fluxes and environmental variables reported here support the modeling of emissions and highlight the importance of considering the timing of fluxes in relation to trends in meteorological variables.
CITATION STYLE
Zeri, M., Yang, W. H., Cunha-Zeri, G., Gibson, C. D., & Bernacchi, C. J. (2020). Nitrous oxide fluxes over establishing biofuel crops: Characterization of temporal variability using the cross-wavelet analysis. GCB Bioenergy, 12(9), 756–770. https://doi.org/10.1111/gcbb.12728
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