Girvan Martina S, Bullimore Juliet, Pretty Jules N, Osborn A Mark, Ball Andrew S
Department of Biological Sciences, University of Essex, Wivenhoe Park, Colchester CO4 3SQ, England, UK.
Appl Environ Microbiol. 2003 Mar;69(3):1800-9. doi: 10.1128/AEM.69.3.1800-1809.2003.
Degradation of agricultural land and the resulting loss of soil biodiversity and productivity are of great concern. Land-use management practices can be used to ameliorate such degradation. The soil bacterial communities at three separate arable farms in eastern England, with different farm management practices, were investigated by using a polyphasic approach combining traditional soil analyses, physiological analysis, and nucleic acid profiling. Organic farming did not necessarily result in elevated organic matter levels; instead, a strong association with increased nitrate availability was apparent. Ordination of the physiological (BIOLOG) data separated the soil bacterial communities into two clusters, determined by soil type. Denaturing gradient gel electrophoresis and terminal restriction fragment length polymorphism analyses of 16S ribosomal DNA identified three bacterial communities largely on the basis of soil type but with discrimination for pea cropping. Five fields from geographically distinct soils, with different cropping regimens, produced highly similar profiles. The active communities (16S rRNA) were further discriminated by farm location and, to some degree, by land-use practices. The results of this investigation indicated that soil type was the key factor determining bacterial community composition in these arable soils. Leguminous crops on particular soil types had a positive effect upon organic matter levels and resulted in small changes in the active bacterial population. The active population was therefore more indicative of short-term management changes.
农业用地退化以及随之而来的土壤生物多样性和生产力丧失令人深感担忧。土地利用管理措施可用于改善这种退化状况。采用多相方法,结合传统土壤分析、生理分析和核酸谱分析,对英格兰东部三个采用不同农场管理措施的独立耕地农场的土壤细菌群落进行了调查。有机耕作不一定会导致有机质水平升高;相反,与硝酸盐有效性增加存在明显的强关联。根据土壤类型,对生理(BIOLOG)数据进行排序可将土壤细菌群落分为两个簇。基于16S核糖体DNA的变性梯度凝胶电泳和末端限制性片段长度多态性分析,在很大程度上根据土壤类型确定了三个细菌群落,但对豌豆种植有区分作用。来自地理上不同土壤且种植方案不同的五块田地产生了高度相似的图谱。活跃群落(16S rRNA)进一步根据农场位置以及在一定程度上根据土地利用方式进行区分。这项调查结果表明,土壤类型是决定这些耕地土壤中细菌群落组成的关键因素。特定土壤类型上的豆科作物对有机质水平有积极影响,并导致活跃细菌种群发生微小变化。因此,活跃种群更能表明短期管理变化。