Differential response of soil CO2, CH4, and N2O emissions to edaphic properties and microbial attributes following afforestation in central China

Abstract Land use change specially affects greenhouse gas (GHG) emissions, and it can act as a sink/source of GHGs. Alterations in edaphic properties and microbial attributes induced by land use change can individually/interactively contribute to GHG emissions, but how they predictably affect soil CO 2 , CH 4 , and N 2 O emissions remain unclear. Here, we investigated the direct and indirect controls of edaphic properties (i.e., dissolved organic carbon [DOC], soil organic C, total nitrogen, C:N ratio, ‐N, ‐N, soil temperature [ST], soil moisture [SM], pH, and bulk density [BD]) and microbial attributes (i.e., total phospholipid fatty acids [PLFAs], 18:1ω7c, nitrifying genes [ammonia‐oxidizing archaea, ammonia‐oxidizing bacteria], and denitrifying genes [ nirS , nirK , and nosZ ]) over the annual soil CO 2 , CH 4 , and N 2 O emissions from the woodland, shrubland, and abandoned land in subtropical China. Soil CO 2 and N 2 O emissions were higher in the afforested lands (woodland and shrubland) than in the abandoned land, but the annual cumulative CH 4 uptake did not significantly differ among all land use types. The CO 2 emission was positively associated with microbial activities (e.g., total PLFAs), while the CH 4 uptake was tightly correlated with soil environments (i.e., ST and SM) and chemical properties (i.e., DOC, C:N ratio, and ‐N concentration), but not significantly related to the methanotrophic bacteria (i.e., 18:1ω7c). Whereas, soil N 2 O emission was positively associated with nitrifying genes, but negatively correlated with denitrifying genes especially nosZ . Overall, our results suggested that soil CO 2 and N 2 O emissions were directly dependent on microbial attributes, and soil CH 4 uptake was more directly related to edaphic properties rather than microbial attributes. Thus, different patterns of soil CO 2 , CH 4 , and N 2 O emissions and associated controls following land use change provided novel insights into predicting the effects of afforestation on climate change mitigation outcomes.