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首页> 外文期刊>Microbial Ecology: An International Journal >Spatial Variation in the Bacterial and Denitrifying Bacterial Community in a Biofilter Treating Subsurface Agricultural Drainage
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Spatial Variation in the Bacterial and Denitrifying Bacterial Community in a Biofilter Treating Subsurface Agricultural Drainage

机译:在处理地下农业排水的生物滤池中细菌和反硝化细菌群落的空间变化。

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Denitrifying biofilters can remove agricultural nitrates from subsurface drainage, reducing nitrate pollution that contributes to coastal hypoxic zones. The performance and reliability of natural and engineered systems dependent upon microbially mediated processes, such as the denitrifying biofilters, can be affected by the spatial structure of their microbial communities. Furthermore, our understanding of the relationship between microbial community composition and function is influenced by the spatial distribution of samples. In this study we characterized the spatial structure of bacterial communities in a denitrifying biofilter in central Illinois. Bacterial communities were assessed using automated ribosomal intergenic spacer analysis for bacteria and terminal restriction fragment length polymorphism of nosZ for denitrifying bacteria. Non-metric multidimensional scaling and analysis of similarity (ANOSIM) analyses indicated that bacteria showed statistically significant spatial structure by depth and transect, while denitrifying bacteria did not exhibit significant spatial structure. For determination of spatial patterns, we developed a package of automated functions for the R statistical environment that allows directional analysis of microbial community composition data using either ANOSIM or Mantel statistics. Applying this package to the biofilter data, the flow path correlation range for the bacterial community was 6.4 m at the shallower, periodically inundated depth and 10.7 m at the deeper, continually submerged depth. These spatial structures suggest a strong influence of hydrology on the microbial community composition in these denitrifying biofilters. Understanding such spatial structure can also guide optimal sample collection strategies for microbial community analyses.
机译:反硝化生物滤池可以从地下排水系统中去除农业硝酸盐,从而减少造成沿海低氧区的硝酸盐污染。取决于微生物介导过程(例如反硝化生物滤池)的自然和工程系统的性能和可靠性可能会受到其微生物群落空间结构的影响。此外,我们对微生物群落组成与功能之间关系的理解受到样品空间分布的影响。在这项研究中,我们表征了伊利诺伊州中部反硝化生物滤池中细菌群落的空间结构。使用自动核糖体基因间间隔区分析细菌来评估细菌群落,并使用nosZ的末端限制性片段长度多态性来反硝化细菌。非度量多维标度和相似度分析(ANOSIM)分析表明,按深度和横断面,细菌显示出统计学上显着的空间结构,而反硝化细菌则没有显示出显着的空间结构。为了确定空间格局,我们为R统计环境开发了一套自动化功能,该功能允许使用ANOSIM或Mantel统计信息对微生物群落组成数据进行定向分析。将该软件包应用于生物滤池数据,细菌群落的流径相关范围在较浅的,周期性淹没的深度为6.4 m,在较深的连续淹没的深度为10.7 m。这些空间结构表明水文学对这些反硝化生物滤池中微生物群落组成的强烈影响。了解这种空间结构还可以指导微生物群落分析的最佳样品收集策略。

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