Ma Wai K, Farrell Richard E, Siciliano Steven D
Department of Soil Science, University of Saskatchewan Saskatoon, SK, Canada.
Front Microbiol. 2011 Jun 10;2:110. doi: 10.3389/fmicb.2011.00110. eCollection 2011.
Nitrous oxide (N(2)O) is a greenhouse gas with a global warming potential far exceeding that of CO(2). Soil N(2)O emissions are a product of two microbially mediated processes: nitrification and denitrification. Understanding the effects of landscape on microbial communities, and the subsequent influences of microbial abundance and composition on the processes of nitrification and denitrification are key to predicting future N(2)O emissions. The objective of this study was to examine microbial abundance and community composition in relation to N(2)O associated with nitrification and denitrification processes over the course of a growing season in soils from cultivated and uncultivated wetlands. The denitrifying enzyme assay and [Formula: see text] pool dilution methods were used to compare the rates of denitrification and nitrification and their associated N(2)O emissions. Functional gene composition was measured with restriction fragment length polymorphism profiles and abundance was measured with quantitative polymerase chain reaction. The change in denitrifier nitrous oxide reductase gene (nosZ) abundance and community composition was a good predictor of net soil N(2)O emission. However, neither ammonia oxidizing bacteria ammonia monooxygenase (bacterial amoA) gene abundance nor composition predicted nitrification-associated-N(2)O emissions. Alternative strategies might be necessary if bacterial amoA are to be used as predictive in situ indicators of nitrification rate and nitrification-associated-N(2)O emission.
一氧化二氮(N₂O)是一种温室气体,其全球变暖潜能值远超过二氧化碳。土壤N₂O排放是两个微生物介导过程的产物:硝化作用和反硝化作用。了解景观对微生物群落的影响,以及微生物丰度和组成对硝化作用和反硝化作用过程的后续影响,是预测未来N₂O排放的关键。本研究的目的是在一个生长季节内,研究耕种和未耕种湿地土壤中与硝化作用和反硝化作用相关的N₂O的微生物丰度和群落组成。采用反硝化酶测定法和[公式:见正文]库稀释法比较反硝化作用和硝化作用的速率及其相关的N₂O排放。用限制性片段长度多态性图谱测定功能基因组成,用定量聚合酶链反应测定丰度。反硝化亚硝酸盐还原酶基因(nosZ)丰度和群落组成的变化是土壤净N₂O排放的良好预测指标。然而,氨氧化细菌氨单加氧酶(细菌amoA)基因的丰度和组成均不能预测与硝化作用相关的N₂O排放。如果要将细菌amoA用作硝化速率和与硝化作用相关的N₂O排放的原位预测指标,可能需要其他策略。