Ammonia-Oxidizing Bacteria Rather Than Archaea Dominantly Contribute to Nitrification in an Agricultural Soil Under Contrasting N Sources.

The first and often rate-limiting step of autotrophic nitrification is carried out by ammonia oxidizing bacteria (AOB) and ammonia oxidizing archaea (AOA).The response of AOA and AOB populations to organic and conventional N fertilization, and their relative contributions to nitrification activity were investigated in an agricultural soil planted to silage corn. Our goal is to determine the effects of conventional and organic N management on nitrification and ammonia oxidizers in this agricultural soil over multiple years. The effects of N source were compared using a randomized block design with 4 treatments, control (no additional N), ammonium sulfate (AS100 & 200 kg N ha^-1), and compost (200 kg total N ha^-1) over 3 years. Ammonia oxidizers were examined using DNA extracted from the soil and quantification of the gene (amoA) encoding one sub-unit of the ammonia monooxygenase enzyme. Quantification of amoA with real-time PCR revealed that ammonia oxidizing archaea (AOA) had similar abundance in the differently treated soils and were more abundant than ammonia oxidation bacteria (AOB). In contrast, the AOB populations were strongly affected by the different N treatments, and AOB amoA copy numbers significantly correlated with nitrification potential rates. Studies using specific inhibitors of ammonia oxidation further indicated that AOB dominated the nitrification potential activity in both AS and compost treated soils. The recovery of nitrification potential (RNP) after acetylene inactivation in the presence and absence of bacterial protein synthesis inhibitors suggests that AOB are responsible for approximately 69-76%of nitrifying activity in N treated soils. The soil slurry approach with or without 1-octyne also indicates that AOB contribute approximately 82-91% to nitrification potential in N treated soils. Understanding the differential response of the microbial community to N sources will inform our ability to manage N more efficiently in agricultural systems.