期刊
ECOLOGICAL INDICATORS
卷 136, 期 -, 页码 -出版社
ELSEVIER
DOI: 10.1016/j.ecolind.2022.108695
关键词
Community stability; Seasonal variations; Microbial networks; Keystone taxa
资金
- National Natural Science Foundation of China [92051120]
- Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai) [SML2021SP203, 311021006]
This study used network analysis to investigate the seasonal stability of microbial communities in lake ecosystems. The results showed distinct differences in microbial networks among seasons, with the most complex network in autumn exhibiting the highest stability. Water temperature and pH were found to be significantly correlated with strong connecting structures among microbes, which impacted keystone taxa and destabilized microbial communities. Additionally, the presence of keystone taxa contributed to the stability of the networks, and their removal resulted in unstable networks. The specific composition of keystone taxa in different seasons was influenced by environmental filtering and interspecific interactions. These findings highlight the influence of seasonal variations in environmental factors on microbial networks and community stability.
Seasonal variations of environmental factors generally result in considerable changes in microbiomes, yet we still lack a clear understanding of how microbial communities maintain their ecological stability. Here, we analyze a long-term (nine years) high-throughput sequencing dataset by network analysis to illustrate how the microbial stability varies among seasons in lake ecosystems. The results showed that the microbial networks were distinctly different among seasons, and the most complex network in autumn exhibited the highest stability. We found that the strong connecting structures among microbes (large modules) were significantly (P < 0.05) correlated with water temperature and pH, which would negatively affect keystone taxa and destabilize microbial communities. The networks with more keystone taxa were generally stable and the removal of keystone taxa would result in unstable networks. Moreover, the keystone taxa were specific among seasons due to environmental filtering and relevant interspecific interactions. These results suggested that seasonal variations of environmental factors could influence microbial networks and community stability via the regulation of keystone taxa. Thus, the keystone taxa could be used as indicators to reflect the seasonal stability of microbial communities in lake ecosystems. These findings improve our understanding of the microbial seasonal co-occurrence patterns and reveal the mechanism how microbial communities maintain their seasonal stability in aquatic ecosystems.
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