Preliminary construction of a microecological evaluation model for uranium-contaminated soil

Area of Science:

• Environmental Science
• Microbiology
• Soil Science

Background:

• Nuclear energy development leads to increasing soil uranium contamination.
• Assessing uranium contamination effects on soil ecosystems requires robust evaluation systems.
• Understanding soil microhabitat responses to uranium is critical for environmental management.

Purpose of the Study:

• To investigate the impact of uranium contamination on soil microbial carbon source metabolism and community structure.
• To analyze the responses of soil biochemical properties to uranium exposure.
• To develop and optimize a microbiological evaluation model for uranium-contaminated soils.

Main Methods:

• Biolog microplate technology and high-throughput sequencing were employed to assess microbial communities.
• Soil biochemical properties were analyzed in response to uranium contamination.
• Machine learning algorithms including random forest (RF), Boruta, grey relational analysis (GRA), partial least squares regression (PLS), support vector regression (SVR), and improved particle algorithm (IPSO-SVR) were utilized for indicator screening and model development.

Main Results:

• Ten key biological indicators (arylsulfatase, biomass nitrogen, metabolic entropy, microbial entropy, Simpson, Shannon, McIntosh, Nocardioides, Lysobacter, and Mycoleptodisus) were identified as reliable input variables.
• The partial least squares regression (PLS) model demonstrated superior performance with a high R² (0.932) and low RMSE (0.214) for evaluating uranium contamination.
• Uranium contamination significantly affects soil microbial community structure and carbon source utilization capacity.

Conclusions:

• A novel and effective microbiological evaluation method for uranium-contaminated soils was established.
• The developed PLS model provides a reliable tool for assessing soil ecological effects based on biological indicators.
• This research contributes to better environmental monitoring and risk assessment strategies for nuclear contamination sites.