Reduction of bacterial integrity associated with dam construction: A quantitative assessment using an index of biotic integrity improved by stability analysis.
Reduction of bacterial integrity associated with dam construction: A quantitative assessment using an index of biotic integrity improved by stability analysis.
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DOI：
10.1016/j.jenvman.2018.09.071
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发表时间：
2019-01
影响因子：
8.7
通讯作者：
Nan Yang;Yi Li;Wenlong Zhang;Linqiong Wang;Yu Gao
中科院分区：
文献类型：
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作者：
Nan Yang;Yi Li;Wenlong Zhang;Linqiong Wang;Yu Gao
通过筑坝对河流进行了广泛的管理，但这种干扰对细菌群落的影响尚未得到定量评估。为了填补这一空白，我们利用从三峡水库及其上游采集的细菌群落数据，提出了一种基于细菌的生物完整性指数(BA-IBI)。基于细菌抗性(RS)和对外界干扰的恢复力(RL)进行了稳定性分析，以提高该指标的性能。经过范围、响应性和冗余性试验，选择了4个核心指标，即芽孢杆菌、拟杆菌和梭状芽胞杆菌与变形杆菌的比率(BBC/A)、草杆菌科细菌、甲烷营养菌和嗜热菌。与改进前相比，改进的BA-IBI在1.04~4.10的范围内更能区分有或没有直接大坝效应的地点。河道部位的指标值维持在较高水平，而水库的指标值有所下降，说明了大坝建设对细菌完整性的负面影响。根据评价结果，受筑坝影响较大、中等和较小的采样点分别占23.1%、46.2%和30.8%。对随机森林(RF)回归模型进行了训练和测试，提供了对输入的BA-IBI和环境参数的有效预测。敏感性分析表明，流速对预测过程性能有显著贡献，说明水动力条件对确定细菌群落空间变异性的重要性。本研究不仅为评价堤坝对细菌的响应提供了第一个定量的见解，而且为改进的指数在大坝整治和生态保护中的应用提供了指导。
Rivers are extensively regulated by damming, yet the effects of such interruption on bacterial communities have not been assessed quantitatively. To fill this gap, we proposed a bacteria-based index of biotic integrity (Ba-IBI) by using bacterial community dataset collected from the Three Gorges Reservoir and its upper reaches. Stability analysis based on bacterial resistance (RS) and resilience (RL) to external disturbance was conducted to improve the performance of the index. Four core metrics, i.e. the ratio of Bacilli, Bacteroidetes and Clostridia to Alphaproteobacteria (BBC/A), Oxalobacteraceae, Methanotrophs and Thermophiles were selected after range, responsive and redundancy tests. The improved Ba-IBI, ranging from 1.04 to 4.10, was better at distinguishing sites with or without direct dam effects compared with the unimproved one. The index values maintained high in the riverine sites while reducing in the reservoir, demonstrating the negative influence of dam construction on bacterial integrity. Based on the assessment results, 23.1%, 46.2% and 30.8% sampling sites were large, moderately and little affected by damming, respectively. A Random Forest (RF) regression model was trained and tested, offering a valid prediction of the input Ba-IBI and environmental parameters. Sensitivity analysis revealed the significant contributions of flow velocity towards the predicting process performance, indicating the importance of hydrodynamic conditions on determining the spatial variability of bacterial communities. This study provides not only a first quantitative insight for assessing bacterial response to damming, but also a guideline for applying the improved index in the dam regulation and ecological protection.