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Multiple factors drive imbalance in the global microbial assemblage in soil
Yueqi Hao1, Fubo Yu1, Xiangang Hu1
1Key Laboratory of Pollution Processes and Environmental Criteria (Ministry of Education), Tianjin Key Laboratory of Environmental Remediation and Pollution Control, College of Environmental Science and Engineering, Nankai University, 30080 Tianjin, China.
The Science of the Total Environment
|April 1, 2022
Summary
Global soil microbes are vital for ecosystems. This study uses machine learning to predict how climate change impacts bacterial and fungal hotspots, revealing critical shifts and risks to soil health.
Area of Science:
- Ecology
- Microbiology
- Computational Science
Background:
- Soil microbial communities are essential for biogeochemical cycles.
- Predicting microbial assemblage dynamics under global change is challenging.
- Current methods struggle to integrate multiple influencing factors.
Purpose of the Study:
- To develop a predictive model for soil microbial assemblages.
- To analyze the impact of multiple factors on microbial distribution.
- To forecast changes in bacterial and fungal hotspots under climate change scenarios.
Main Methods:
- Collected global soil microbial data.
- Applied a feature-explicable machine learning (FEML) approach.
- Utilized multi-factor and factor interaction network analysis.
Main Results:
- FEML predicted significant expansion of bacterial hotspots in South America and Africa (27% and 83% respectively) under RCP8.5 by 2100.
- FEML predicted significant decline of fungal hotspots in Asia and North America (34% and 62% respectively) under RCP8.5 by 2100.
- Bacterial-dominated communities alter nutrient cycling, food webs, and soil structure.
Conclusions:
- Climate change is projected to cause substantial geographical shifts in soil microbial hotspots.
- The predicted imbalance between bacteria and fungi poses risks to soil ecosystem functions.
- Mitigating climate change is crucial for maintaining soil microbial health and ecosystem stability.
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