Daily dynamics of greenhouse gas (GHG) emissions and cultivable bacterial populations have rarely been examined. The objectives were: (1) to investigate if dynamics of GHG emissions can be described by harmonics and are related to those of cultivable bacteria after soil disturbances in three grassland management systems; (2) to determine to which extent daily GHG emissions are related to environmental variables rather than disturbance events in two climate zones; and (3) to investigate differences in GHG emissions between organic and conventional tilled grassland versus no-till long-term grassland systems (OG, CG and LG, respectively). In replicated field experiments with OG, CG, and LG plots in the Netherlands and Russia, GHG (CO2, N2O and CH4) emissions and cultivable bacterial populations were measured daily during two one-month periods at each location. Tillage, fertilization, biomass incorporation and irrigation were considered disturbances. The dynamics were subjected to harmonics, cross-correlation, and canonical correspondence analyses (CCA). The dynamics of cultivable bacterial populations and GHG fluxes rarely reflected autonomous growth and death cycles of bacteria after a disturbance due to the overarching influences of environmental conditions, especially in spring. Thus, GHG emissions were influenced more by weather variables than by agronomic disturbances. This was confirmed by CCA. Cultivable bacterial populations were cross correlated with CO2 fluxes and sometimes N2O emissions, but generally not with CH4 fluxes. Average cultivable bacterial populations and CO2 emissions were highest in OG and lowest in LG; N2O emissions were mostly highest in CG and lowest in LG; and CH4 fluxes were frequently highest in OG and lowest in LG. Thus, although bacteria and GHG peaks were induced by disturbances, sometimes followed by autonomous oscillations due to growth and death cycles and associated cycles in nutrient and oxygen availability, the dynamics were mainly affected by environmental variables and long-term management, with the smallest GHG emissions from LG plots.
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