Rare rather than abundant microbial communities drive the effects of long-term greenhouse cultivation on ecosystem functions in subtropical agricultural soils

Abstract Long-term greenhouse cultivation has an adverse effect on ecosystem functions such as soil carbon (C) and nitrogen (N) pools and greenhouse gas (GHG) emissions, but the underlying microbial mechanisms still remain unclear. Here, different sites under long-term greenhouse cultivation in a subtropical agricultural ecosystem were selected to measure soil C and N contents, extractable organic C (EOC) and N (EON) contents, and potential GHG emissions. Metagenomic analysis and 16S rRNA high-throughput sequencing were used to measure microbial communities. The results showed that long-term greenhouse cultivation increased soil salinity, and significantly increased soil total C and N contents, EOC and EON contents, and N2O emission potentials, although it significantly decreased CO2 emission and CH4 oxidation potential compared with the ambient control. Changes in soil CH4 oxidation and N2O emission potential exhibited similar patterns in the corresponding key functional genes based on according to our metagenomic analysis. In addition, long-term greenhouse cultivation did not change microbial diversity, although it clearly affected soil microbial community composition. Soil microbial communities were further classified into rare and abundant microbial taxa. Rare rather than abundant microbial taxa could adequately explain the changes in ecosystem functions, except for CH4 oxidation potential across the treatments. To our knowledge, this is the first study to quantify the importance of microbial subcommunities to ecosystem functions on the basis of microbial co-occurrence network analysis under greenhouse cultivation in agricultural ecosystems. Overall, our results indicated that rare rather than abundant microbial taxa could act as indicators of variations in ecosystem functions under long-term greenhouse cultivation in subtropical agricultural soils, which might be useful for better management practices and improving crop yields in agricultural ecosystems.