School of Biological Sciences, University of Auckland, 3A Symonds Street, Auckland, 1010, New Zealand.
Manaaki Whenua-Landcare Research, Private Bag 3127, Hamilton, 3240, New Zealand.
Appl Microbiol Biotechnol. 2019 Aug;103(16):6407-6421. doi: 10.1007/s00253-019-09963-0. Epub 2019 Jun 26.
Microorganisms play fundamental roles in the diversity and functional stability of environments, including nutrient and energy cycling. However, microbial biodiversity loss and change because of global climate and land use change remain poorly understood. Many microbial taxa exhibit fast growth rates and are highly sensitive to environmental change. This suggests they have potential to be efficient biological indicators to assess and monitor the state of the habitats within which they occur. Here, we describe and illustrate a range of univariate and multivariate statistical approaches that can be used to identify effective microbial indicators of environmental perturbations and quantify changes in microbial communities. We show that the integration of multiple approaches, such as linear discriminant analysis effect size and indicator value analysis, is optimal for the quantification of the effects of perturbation on microbial communities. We demonstrate the most prevalent techniques using microbial community data derived from soils under different land uses. We discuss the limitations to the development and use of microbial bioindicators and identify future research directions, such as the creation of reliable, standardised reference databases to provide baseline metrics that are indicative of healthy microbial communities. If reliable and globally-relevant microbial indicators of environmental health can be developed, there is enormous potential for their use, both as a standalone monitoring tool and via their integration with existing physical, chemical and biological measures of environmental health.
微生物在环境的多样性和功能稳定性中发挥着基本作用,包括营养物质和能量循环。然而,由于全球气候和土地利用变化,微生物生物多样性的丧失和变化仍未得到很好的理解。许多微生物类群表现出快速的生长速度,对环境变化高度敏感。这表明它们有可能成为评估和监测其所处栖息地状态的有效生物指标。在这里,我们描述并说明了一系列单变量和多变量统计方法,可用于识别环境干扰的有效微生物指标并量化微生物群落的变化。我们表明,整合多种方法,如线性判别分析效应大小和指示值分析,对于量化干扰对微生物群落的影响是最优的。我们使用来自不同土地利用下的土壤中的微生物群落数据来演示最常见的技术。我们讨论了开发和使用微生物生物指标的局限性,并确定了未来的研究方向,例如创建可靠的、标准化的参考数据库,提供健康微生物群落的基准指标。如果能够开发出可靠的、具有全球相关性的环境健康微生物指标,那么它们的应用潜力巨大,无论是作为独立的监测工具,还是通过与现有的物理、化学和生物环境健康措施相结合。