Bacteria versus fungi for predicting anthropogenic pollution in subtropical coastal sediments: Assembly process and environmental response
文献类型：期刊论文
| 作者 | Zhao, Zelong; Li, Hongjun; Sun, Yi; Zhan, Aibin; Lan, Wenlu; Woo, Sau Pinn; Shau-Hwai, Aileen Tan; Fan, Jingfeng |
| 刊名 | ECOLOGICAL INDICATORS
 |
| 出版日期 | 2022-01 |
| 卷号 | 134期号:0页码:108484 |
| ISSN号 | 1470-160X |
| 关键词 | MICROBIAL COMMUNITY HEAVY-METALS BEIBU GULF DISPERSAL LIMITATION MARINE BACTERIAL GROWTH-RATES DIVERSITY WATER ESTUARINE CHINA |
| 英文摘要 | Coastal regions support the most threatened ecosystems on Earth, and anthropogenic activities have been significantly affecting both habitat structure and ecological quality. Understanding the dynamics of ecological response to multiple stresses is a precondition for management and restoration of largely disturbed coastal ecosystems. Among diverse taxa in coastal regions, benthic organisms are widely recognized as promising targets for assessing ecological causes and consequences of anthropogenic activity-derived stressors, such as environmental pollution. However, spatial and local environmental factors play important but different roles in shaping community structure of different benthic taxa, mainly owing to their distinct body size, mobility, and metabolic capacity. Here, we applied metabarcoding, coupled with physicochemical analyses, to determine the benthic microbial community composition in a typical subtropical coast area, Beibu Gulf in Southern China. Stochastic processes were found as the dominant ecological driver in shaping the community assembly of both bacteria and fungi. Moreover, environmental factors explained a considerable portion of variation in bacterial communities, while spatial factors were more influential in structuring larger body size and weak mobility fungal communities. Mantel tests and network analysis revealed significant relationships between several environmental variables and bacterial communities. More importantly, the concentrations of heavy metals, particularly Cr and Zn, could be predicted using the constructed random forest model based on bacterial communities. The results obtained here provide new insights into causes and consequences of various factors for influencing healthy coasts, thus further clearing the road to the integration of biological information into routine ecological monitoring of coastal ecosystems. |
| 源URL | [https://ir.rcees.ac.cn/handle/311016/47771]  |
| 专题 | 生态环境研究中心_中国科学院环境生物技术重点实验室 |
| 通讯作者 | Li, Hongjun |
| 作者单位 | 1.Marine Environm Monitoring Ctr Guangxi, Beihai 536000, Peoples R China 2.Univ Sains Malaysia USM, Ctr Marine & Coastal Studies, George Town 11800, Malaysia 3.Natl Marine Environm Monitoring Ctr, State Environm Protect Key Lab Coastal Ecosyst, Dalian 116023, Peoples R China 4.Chinese Acad Sci, Res Ctr Ecoenvironm Sci, 18 Shuangqing Rd, Beijing 100085, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zhao, Zelong,Li, Hongjun,Sun, Yi,et al. Bacteria versus fungi for predicting anthropogenic pollution in subtropical coastal sediments: Assembly process and environmental response[J]. ECOLOGICAL INDICATORS,2022,134(0):108484. |
| APA | Zhao, Zelong.,Li, Hongjun.,Sun, Yi.,Zhan, Aibin.,Lan, Wenlu.,...&Fan, Jingfeng.(2022).Bacteria versus fungi for predicting anthropogenic pollution in subtropical coastal sediments: Assembly process and environmental response.ECOLOGICAL INDICATORS,134(0),108484. |
| MLA | Zhao, Zelong,et al."Bacteria versus fungi for predicting anthropogenic pollution in subtropical coastal sediments: Assembly process and environmental response".ECOLOGICAL INDICATORS 134.0(2022):108484. |
入库方式： OAI收割
来源：生态环境研究中心
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