Managed pastures are strong sources for the greenhouse gas nitrous oxide (N2O) through various nitrogen (N) inputs. So far, chamber measurements have been used to quantify N2O emissions and emissions factors of specific emissions sources like grazing cattle excreta. This study presents a three-year dataset of N2O emissions from a grazed and fertilized pasture measured by eddy covariance (EC) in eastern Switzerland. N2O fluxes were gapfilled and disaggregated into the emission sources (flux partitioning) by using random forest. The excreta N deposition in the pasture was estimated based on a cattle nitrogen budget approach using observed milk yield, body weight and feed intake of the cattle herd. Furthermore, a driver analysis was performed to quantify the relationship between N2O emissions and predictor variables. The observed annual N2O emissions amounted to 5.3 ± 0.8, 3.1 ± 0.5 and 4.4 ± 0.7 kg N2O-N ha-1 yr-1 and were disaggregated into background, fertilizer and excreta related N2O emissions with contributions of 27–46 %, 15–40 % and 30–51 %, respectively. Combining the excreta N2O fluxes with the excreta N inputs resulted in an average emission factor (EF) for cattle excreta of 1.1 ± 0.5 %, that tends to be higher than the IPCC default value of 0.6 % for wet climates. While maximum N2O emissions usually were observed after fertilizer application and under optimum soil moisture conditions as expected, distinct N2O emission peaks also occurred during a longer drought period in summer and could be parametrised as a function of precipitation and previous grazing activity. Moreover, peak N2O emissions occurred during the cold season at low temperatures and should be considered in future studies. Overall, we suggest that EC measurements under pasture conditions with subsequent flux partitioning by random forest are suitable for quantifying pasture N2O emissions of different sources.
Barczyk L., Six J., Ammann C.
Partitioning and driver analysis of eddy covariance derived N2O emissions from a grazed and fertilized pasture.
Agricultural and Forest Meteorology, 359, 2024, Artikel 110278.
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ISSN Print: 0168-1923
ISSN Online: 1873-2240
Digital Object Identifier (DOI): https://doi.org/10.1016/j.agrformet.2024.110278
Publikations-ID (Webcode): 57713
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