Integrating microbial biomass, composition and function to discern the level of anthropogenic activity in a river ecosystem
Integrating microbial biomass, composition and function to discern the level of anthropogenic activity in a river ecosystem
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整合微生物生物量、组成和功能来辨别河流生态系统中的人类活动水平
DOI：
10.1016/j.envint.2018.04.003
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发表时间：
2018-07-01
影响因子：
11.8
通讯作者：
Qu, Jiuhui
中科院分区：
文献类型：
--
作者：
Liao, Kailingli;Bai, Yaohui;Qu, Jiuhui
人为活动（例如，废水排放以及农药和化肥的使用）对自然水生生态系统的生物特性，特别是微生物群落和功能产生了相当大的影响。微生物可以对人类活动作出反应，因此是活动水平的潜在指标。一些报告记录了人类活动对微生物群落变化的影响，但直接使用微生物群落指数来辨别人类活动水平仍然有限。本研究采用流式细胞仪、16SrRNA测序和天然有机物代谢测定相结合的方法，对河流生态系统中受人为干扰沿着梯度分布的3个区域（少干扰山区、废水排放城区和农药化肥使用农业区）的微生物生物量、组成和功能进行了研究。采用多种统计方法探讨了环境因素变化与微生物变异之间的因果关系。结果表明，人类活动（例如，废水排放、农药和化肥的使用）促进了细菌的产生，影响了优势种的分布，并加速了微生物对天然有机物（NOM）的代谢速率。在筛选了可能影响微生物群落的因素后，我们确定蓝藻浓度可以作为营养水平的诊断指标。我们还开发了NOM代谢指数，以定量地反映营养素和外源性物质的整体影响。
Anthropogenic activities (e.g., wastewater discharge and pesticide and fertilizer use) have considerable impact on the biotic properties of natural aquatic ecosystems, especially the microbial community and function. Microbes can respond to anthropogenic activities and are thus potential indicators of activity levels. Several reports have documented the impacts of anthropogenic activities on the variations in the microbial community, but the direct use of microbial community indices to discern anthropogenic activity levels remains limited. Here, we integrated flow cytometry, 16S rRNA sequencing, and natural organic matter metabolism determination to investigate microbial biomass, composition, and function in three areas along a gradient of anthropogenic disturbance (less-disturbed mountainous area, wastewater-discharge urban area, and pesticide and fertilizer used agricultural area) in a river ecosystem. Multiple statistical methods were used to explore the causal relationships between changes in environmental factors and microbial variation. Results showed that anthropogenic activities (e.g., wastewater discharge, pesticide and fertilizer use) facilitated bacterial production, affected dominant species distribution, and accelerated natural organic matter (NOM) metabolic rate by microbes. After screening the possible factors influencing the microbial community, we determined that cyanobacterial concentration could be a diagnostic indicator of nutrient levels. We also developed a NOM metabolic index to quantitatively reflect the holistic influence of nutrients and xenobiotics.