Abstract

Variations in soil microbial metabolism currently represent one of the greatest areas of uncertainty with regard to soil nutrient cycles and the control of terrestrial carbon (C) and nitrogen (N) loss and are poorly understood in agricultural ecosystems with intensive farming practices. In this study, extracellular enzymatic stoichiometry models and quantitative PCR techniques were used to examine microbial metabolic limitation and its relationship with N-cycling gene expression in semi-arid agricultural ecosystems considering four N fertilization levels (N 0, N 100, N 250, and N 400 kg N ha−1) and two agronomic strategies (film mulching and no mulching). Film mulching increased microbial C limitation (reflecting microbial C metabolism size; 0.189 of the total effects), while very small effects on microbial phosphorus (P) limitation were observed (-0.007 of the total effects). N fertilization increased the microbial demand for P (microbial P limitation; 0.504 of the total effects). Increased microbial C metabolism was mainly attributed to increased soil moisture content after film mulching, which enhanced microbial decomposition of organic C (high C-acquiring enzyme activities). Changes in nutrient stoichiometry and the increase in N availability due to N fertilization were largely responsible for increased microbial P limitation. Furthermore, microbial P limitation negatively affected the abundance of AOA amoA, AOB amoA (involved in nitrification), nirK, nirS, nosZ (involved in denitrification) genes, strongly inhibiting nitrification and denitrification potential (-0.743 and -0.761 of the total effects, respectively). The present results suggest that agricultural ecosystems with film mulching are conducive to organic residue decomposition, while appropriate P limitation under N fertilization could reduce the loss of N due to nitrification and denitrification in soil. This study highlights the importance of elemental stoichiometry-driven microbial metabolic variation in understanding soil nutrient cycles and optimizing agricultural practices.

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