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A critical evaluation of ecological indices for the comparative analysis of microbial communities based on molecular datasets

机译:基于分子数据集的微生物社区比较分析的生态指标的关键评价

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摘要

In times of global change and intensified resource exploitation, advanced knowledge of ecophysiological processes in natural and engineered systems driven by complex microbial communities is crucial for both safeguarding environmental processes and optimising rational control of biotechnological processes. To gain such knowledge, high-throughput molecular techniques are routinely employed to investigate microbial community composition and dynamics within a wide range of natural or engineered environments. However, for molecular dataset analyses no consensus about a generally applicable alpha diversity concept and no appropriate benchmarking of corresponding statistical indices exist yet. To overcome this, we listed criteria for the appropriateness of an index for such analyses and systematically scrutinised commonly employed ecological indices describing diversity, evenness and richness based on artificial and real molecular datasets. We identified appropriate indices warranting interstudy comparability and intuitive interpretability. The unified diversity concept based on 'effective numbers of types' provides the mathematical framework for describing community composition. Additionally, the Bray-Curtis dissimilarity as a beta-diversity index was found to reflect compositional changes. The employed statistical procedure is presented comprising commented R-scripts and example datasets for user-friendly trial application.
机译:在全球变化和加强资源开发的时候,复杂微生物社区驱动的自然和工程系统中的生态学过程的先进知识对于保护环境过程和优化生物技术过程的合理控制至关重要。为了获得这些知识,常规使用高通量的分子技术来研究在各种天然或工程环境中的微生物群落组成和动力学。然而,对于分子数据集分析对普遍适用的alpha多样性概念没有共识,并且尚未存在相应的统计指标的适当基准。为了克服这一点,我们列出了这种分析指数的适当性的标准,并系统地审查了描述了基于人工和真实分子数据集的多样性,均匀度和丰富度的常用生态指标。我们确定了适当的指标,保证非可比性和直观的可解释性。基于“有效数量”的统一分集概念提供了用于描述社区组成的数学框架。另外,发现作为β-多样性指数的Bray-Curtis差异反映了组成变化。介绍了所采用的统计程序,包括注释的R脚本和示例数据集,用于用户友好的试用应用程序。

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