Dataset of microbial community evolution in synthetic black-clay-based soils during ecological reconstruction

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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Publication Details

Journal
Data in Brief
Published
2026-02-18
DOI
https://doi.org/10.1016/j.dib.2026.112593
Primary Topic
Microbial Community Ecology and Physiology
Type
article
Field-Weighted Citation Impact
0.00

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article

Dataset of microbial community evolution in synthetic black-clay-based soils during ecological reconstruction

Fangzhou Li, Jie Li, María Laura Gigena, Meng Wang et al.
Data in Brief
Microbial Community Ecology and Physiology
article

Dataset of microbial community evolution in synthetic black-clay-based soils during ecological reconstruction

Fangzhou Li, Jie Li, María Laura Gigena, Meng Wang, Ruibiao Fu, Malone Ange Melina Toure, Pei Li, Dong Xiao
article en

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.

Data in BriefVol. 65
Fuyang Normal University (CN), Xuzhou Medical College (CN), China University of Mining and Technology (CN), Jiangsu Province Special Equipment Safety Supervision and Inspection Institute (CN), Universidad Católica de Salta (AR), Fuyang Maternity and Child Health Care Hospital (CN), Xuzhou Construction Machinery Group (China) (CN), Xuzhou No.1 People's Hospital (CN)
China University of Mining and Technology
Life in Land
Openalex Percentile: Top 57%
Microbial Community Ecology and Physiology
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