CAS Key Laboratory of Urban Pollutant Conversion, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; Fujian Key Laboratory of Watershed Ecology, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; Water Pollution Research Department, National Research Centre, Giza 12622, Egypt.
CAS Key Laboratory of Urban Pollutant Conversion, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; Fujian Key Laboratory of Watershed Ecology, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; University of Chinese Academy of Sciences, Beijing 100049, China.
Sci Total Environ. 2024 Feb 1;910:168659. doi: 10.1016/j.scitotenv.2023.168659. Epub 2023 Nov 17.
This study represents the pioneering effort in employing 16S rRNA-bacteria and 18S rRNA-microeukaryotes to construct the microbial community-based index of biotic integrity (MC-IBI) for assessing the ecological health of riverine ecosystems. The MC-IBI was developed, validated, and implemented using water samples from the Changle River watershed, encompassing both wet and dry seasons. A total of 205 metrics, containing microbial diversity, composition, pollution tolerance/sensitivity, and functional categories, were selected as candidates for evaluation. Following a rigorous screening process, five core metrics were identified as key indicators, namely Pielou's evenness of microeukaryotes, %Cryptophyceae, %Proteobacteria, %Oxyphotobacteria, and % 16S rRNA gene-human pathogens. Moreover, redundancy analysis revealed three metrics (i.e., Pielou's evenness, % 16S rRNA gene-human pathogens, and % Proteobacteria) were positively correlated with impairment conditions. In contrast, two metrics (i.e., %Oxyphotobacteria and %Cryptophyceae) were associated positively with reference conditions. Notably, the developed MC-IBI demonstrates clear discrimination between reference and impaired sites and significantly correlates with environmental parameters and land use patterns. A path model analysis revealed that land use patterns (i.e., build-up land, cropland) negatively impacted the MC-IBI scores. The application of the MC-IBI method yielded an assessment of the ecological conditions at the 73 sampling locations within the Changle River watershed, assigning them into categories of "Very good" (4.1 %), "Good" (4.1 %), "Moderate" (5.5 %), "Poor" (21.9 %), and "Very poor" (64.4 %). This bioassessment framework presents an innovative approach toward the preservation, maintenance, and management of riverine ecosystems.
本研究率先利用 16S rRNA 细菌和 18S rRNA 微真核生物构建基于微生物群落的生物完整性指数 (MC-IBI),用于评估河流生态系统的生态健康状况。该 MC-IBI 是使用昌乐河流域的水样开发、验证和实施的,涵盖了干湿两季。共选择了 205 个指标,包括微生物多样性、组成、污染耐受/敏感性和功能类别,作为评估的候选指标。经过严格的筛选过程,确定了五个核心指标作为关键指标,即微真核生物的皮尔逊均匀度、隐藻%、变形菌%、光合细菌%和 16S rRNA 基因-人类病原体%。此外,冗余分析表明,有三个指标(即皮尔逊均匀度、16S rRNA 基因-人类病原体和变形菌%)与受损条件呈正相关。相比之下,有两个指标(即光合细菌%和隐藻%)与参照条件呈正相关。值得注意的是,所开发的 MC-IBI 能够清晰地区分参照和受损站点,并且与环境参数和土地利用模式显著相关。路径模型分析表明,土地利用模式(即建设用地、耕地)对 MC-IBI 得分有负面影响。该 MC-IBI 方法在昌乐河流域的 73 个采样点进行了应用,将这些采样点的生态条件评估结果分为“非常好”(4.1%)、“良好”(4.1%)、“中等”(5.5%)、“较差”(21.9%)和“非常差”(64.4%)。该生物评估框架为河流生态系统的保护、维护和管理提供了一种创新方法。