Wavelet analysis of wintertime and spring thaw COd2 and Nd2O fluxes from agricultural fields

摘要

Fluxes of Nd2O and COd2 are not limited to the growing season; winter and spring thaw can represent a significant emission period. The objective of this study was to apply wavelet analysis to winter and spring thaw COd2 and Nd2O fluxes and soil temperatures, to yield additional information about underlying processes, examining temporal patterns and relationships among them. Fluxes used in this analysis were measured over 4 years using micrometeorological methods, in a study comparing two agricultural management practices, best management (BM) and conventional (CONV) practices. Cross-wavelet transform (XWT) and wavelet coherence (WCO) were applied to daily mean time series of Nd2O fluxes for BM and CONV replicates and treatments, COd2 vs. Nd2O fluxes, COd2 flux vs. air and soil temperatures, and Nd2O flux vs. air and soil temperatures. Nd2O fluxes for replicate plots had small differences in temporal variation while Nd2O fluxes from BM and CONV treatments showed a large difference in their time series. XWT and WCO analysis confirmed differences in Nd2O fluxes between management practices due to differences in temporal trends in the time series. Field emissions of Nd2O and COd2 fluxes showed times of common high fluxes, such as thaw events. Nitrous oxide and COd2 flux time series showed a strong coherence with surface (air) temperatures. The relationship between Nd2O fluxes and temperature decreased with depth but the relationship between COd2 flux and temperature was similar for surface and at depth. The strong coherence between emissions and surface conditions does not support the suggested mechanism of trapped gas release. A release of trapped gases from below the ice formation would have been indicated by a strong coherence from COd2 and Nd2O with temperatures at depth as the trapping ice barrier melted. This study demonstrates the effectiveness of wavelets as a tool to investigate temporal relationships in GHG emissions, which is a relatively new application for this type of analysis.