Land use conversion from flooded paddy fields to upland vegetable systems is becoming increasingly widespread, yet its ecological consequences for soil N2O emissions remain poorly understood. Here, we integrated the potential denitrification-derived N2O flux measurements, microbial community profiling, and network analyses to elucidate how paddy-to-vegetable land conversion reshapes soil microbial interactions and regulates N2O emission dynamics in the Yangtze River Delta region of China. Results showed that N2O emissions increased significantly following the conversion, with fluxes reaching approximately 0.43 and 0.0083 nmol N g-1 h-1 in soils under vegetable cultivation for 4 and 7 years, respectively. In contrast to the trend in N2O emissions, bacterial diversity decreased significantly following the conversion, whereas fungal diversity showed no significant change. Co-occurrence network analysis demonstrated a divergent response of bacterial and fungal communities to land use conversion. In vegetable soils, bacterial networks exhibited enhanced connectivity, with average degrees 1.23 and 1.17 times higher than those in paddy soils after 4 and 7 years of conversion, respectively. Conversely, fungal networks showed markedly reduced connectivity, with average degrees declining by 54.67 and 36.70%, respectively. The number of edges, positive connection edges, negative connection edges, the number of vertices, and average degree in the bacterial network were all significantly positively correlated with N2O emission rates, whereas fungal network connectivity showed opposite trends. Random forest modeling further identified bacterial network features were the most influential determinant of N2O emissions, outperforming traditional soil environmental variables. Altogether, our findings demonstrate that paddy-to-vegetable land conversion alters the architecture, stability, and modularity of soil microbial networks, which may play a pivotal role in enhanced N2O emissions. This study emphasizes the necessity of considering microbial network dynamics in greenhouse gas mitigation strategies.
Li et al. (Thu,) studied this question.