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

With the extensive development of nuclear energy, soil uranium contamination has become an increasingly prominent problem. The development of evaluation systems for various uranium contamination levels and soil microhabitats is critical. In this study, the effects of uranium contamination on the carbon source metabolic capacity and microbial community structure of soil microbial communities were investigated using Biolog microplate technology and high-throughput sequencing, and the responses of soil biochemical properties to uranium were also analyzed. Then, ten key biological indicators as reliable input variables, including arylsulfatase, biomass nitrogen, metabolic entropy, microbial entropy, Simpson, Shannon, McIntosh, Nocardioides, Lysobacter, and Mycoleptodisus, were screened by random forest (RF), Boruta, and grey relational analysis (GRA). The optimal uranium-contaminated soil microbiological evaluation model was obtained by comparing the performance of three evaluation methods: partial least squares regression (PLS), support vector regression (SVR), and improved particle algorithm (IPSO-SVR). Consequently, partial least squares regression (PLS) has a higher R 2 (0.932) and a lower RMSE value (0.214) compared to the other. This research provides a new evaluation method to describe the relationship between soil ecological effects and biological indicators under nuclear contamination.