Temporal Dynamics and Adaptive Mechanisms of Microbial Communities: Divergent Responses and Network Interactions

Microbial communities are vital to aquatic ecosystems, driving biogeochemical cycles, nutrient recycling, and overall ecosystem functioning. However, their instant feedback, particularly in response to environmental fluctuations, remain insufficiently understood. In this study, we investigated the interaction of prokaryotic and eukaryotic microbial communities in riverine ecosystems under temporal dynamics using high-throughput sequencing and co-occurrence network analysis. We observed distinct patterns, with eukaryotic communities showing a consistent increase in alpha diversity, while prokaryotic communities exhibited more variable and directional shifts over time. Two key phases were identified: a dynamic phase characterized by rapid changes in both alpha and beta diversity and a stabilization phase where community composition became more stable, with increased evenness. Co-occurrence network analysis revealed a transition from a modular structure in the dynamic phase to a more centralized and highly connected network in the stabilization phase. While modularity can enhance stability by localizing perturbations within distinct subnetworks, increased centralization and connectivity may weaken this stabilizing effect, potentially making the network less resilient to environmental fluctuations. Our findings provide new insights into the adaptive mechanisms that sustain microbial community stability and resilience in dynamic aquatic ecosystems, emphasizing the importance of diversity and network structure in maintaining ecological stability.

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Publication Details

Journal
Microbial Ecology
Published
2025-09-25
DOI
https://doi.org/10.1007/s00248-025-02596-z
Citations
5
Primary Topic
Microbial Community Ecology and Physiology
Type
article
Field-Weighted Citation Impact
8.58

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article

Temporal Dynamics and Adaptive Mechanisms of Microbial Communities: Divergent Responses and Network Interactions

Da Huo, Yingchun Gong, Zhiyi Qiao, Denis V. Tikhonenkov et al.
5 citations
Microbial Ecology
Microbial Community Ecology and Physiology
8.58
article

Temporal Dynamics and Adaptive Mechanisms of Microbial Communities: Divergent Responses and Network Interactions

Da Huo, Yingchun Gong, Zhiyi Qiao, Denis V. Tikhonenkov, Shengjie Sun, Hua Li, Renhui Li, Kexin Sun
article en
5 citations

Abstract

Microbial communities are vital to aquatic ecosystems, driving biogeochemical cycles, nutrient recycling, and overall ecosystem functioning. However, their instant feedback, particularly in response to environmental fluctuations, remain insufficiently understood. In this study, we investigated the interaction of prokaryotic and eukaryotic microbial communities in riverine ecosystems under temporal dynamics using high-throughput sequencing and co-occurrence network analysis. We observed distinct patterns, with eukaryotic communities showing a consistent increase in alpha diversity, while prokaryotic communities exhibited more variable and directional shifts over time. Two key phases were identified: a dynamic phase characterized by rapid changes in both alpha and beta diversity and a stabilization phase where community composition became more stable, with increased evenness. Co-occurrence network analysis revealed a transition from a modular structure in the dynamic phase to a more centralized and highly connected network in the stabilization phase. While modularity can enhance stability by localizing perturbations within distinct subnetworks, increased centralization and connectivity may weaken this stabilizing effect, potentially making the network less resilient to environmental fluctuations. Our findings provide new insights into the adaptive mechanisms that sustain microbial community stability and resilience in dynamic aquatic ecosystems, emphasizing the importance of diversity and network structure in maintaining ecological stability.

Microbial EcologyVol. 88(1)
Tianjin Agricultural University (CN), Chinese Academy of Sciences (CN), Wenzhou Medical University (CN), Institute of Hydrobiology (CN), Institute of Biology of Inland Waters named Ivan Dmitrievich Papanin (RU), Institute of Bioinformatics (IN)
National Natural Science Foundation of China, China Postdoctoral Science Foundation, Russian Science Foundation
Openalex Percentile: Top 2%
Microbial Community Ecology and Physiology
8.58
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