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February 21, 2026Data in Brief0 citationsOpen Access

Dataset of Microbial Community Evolution in Synthetic Black-Clay-Based Soils During Ecological Reconstruction

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JLJie LiDXDong XiaoMGMaría Laura Gigena

Key Points

  • The aim is to explore microbial community evolution in artificial black-clay soils used for mine dump restoration.
  • Collected soil samples from various restoration zones with different microbial inoculation regimes.
  • Used high-throughput sequencing for microbial community characterization of bacterial 16S rRNA gene.
  • Analyzed microbial diversity through taxonomic abundance tables and diversity metrics.
  • Generated network topology metrics for structural assessments of microbial associations.
  • Provided functional predictions using PICRUSt2 based on 16S rRNA gene data.
  • Diverse microbial communities were detected across different inoculation regimes and soil layers.
  • Alpha- and beta-diversity metrics revealed significant variations in microbial composition.
  • Functional predictions indicated a range of ecological pathways present in the microbial communities.
  • Network analysis highlighted distinct structural associations among microbial taxa.

Abstract

Ecological reconstruction of mine dump sites in cold-region environments is frequently constrained by limited availability of natural topsoil and harsh climatic conditions that hinder soil development and biological succession. In such settings, artificial soils derived from mineral substrates are increasingly used as alternatives to surface soil; however, their biological maturation relies strongly on microbial community establishment and evolution. This data article presents a microbial diversity dataset derived from black-clay–based artificial soils applied in a mine dump restoration system located in a cold and arid desert grassland. Soil samples were collected from restoration zones subjected to different microbial inoculation regimes, including full-process application of an ecological restoration bacteria consortium, single application, and untreated controls. To capture spatial and vertical heterogeneity, samples were obtained independently from upper aerobic layers and lower anaerobic layers across multiple sampling batches corresponding to different restoration stages. Microbial community composition was characterized using high-throughput sequencing of the bacterial 16S rRNA gene, generating raw sequence reads and a suite of processed datasets. These include taxonomic abundance tables, alpha- and beta-diversity metrics, distance matrices, hierarchical clustering outputs, shared operational taxonomic unit profiles, ecological niche breadth indices, beta-deviation measurements, and core community identification based on prevalence criteria. Network topology metrics derived from Zi–Pi analysis are also provided to support structural assessments of microbial associations. In addition, functional profiles were inferred from 16S rRNA gene data using PICRUSt2, producing pathway- and category-level functional prediction tables. All data files are organized with standardized metadata and fully documented analytical parameters to facilitate independent reuse. This dataset supports reanalysis of microbial community assembly, stratification, and temporal variation in artificial soil systems and can be applied in comparative studies, methodological benchmarking, and synthesis efforts related to mine-site restoration, artificial soil development, and microbial ecology in cold-region environments.

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Cite This Study

Li et al. (2026) studied this question.

synapsesocial.com/papers/69994bdd873532290d01fe60https://doi.org/10.1016/j.dib.2026.112593
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