Long-term coal gangue dump regulates bacterial communities in different disturbance areas: Evidence mostly from diversity and network complexity
Bibliographic record
Abstract
In order to clarify the effects of long-term coal gangue(CG) dump on the surrounding soil bacterial community structure, we selected the CG dump formed during the mining of Tunlan coal mine in Gujiao city, Shanxi province in China as the study area to conduct a comprehensive study, the experimental design included six distinct zones: control soil area with no impaction (NC), undisturbed control sediment area (NL), atmospheric dry and wet deposition area (MC), upstream (MLS), midstream (MLZ) and downstream (MLX) in the leachate flow area (LFA), Using high-throughput sequencing technology and related software analysis, we obtained the following key findings: The heavy metal contents of Cr and Cd were different significantly in MC and NC (p < 0.05),Cr (90.18 mg·kg-1) in MC was higher than that in NC (65.29 mg·kg-1) (p < 0.05), while Cd (0.09 mg·kg-1) was lower than that in NC (0.14 mg·kg-1) (p < 0.05), and there was no significant differences in Cu, Zn, As and Pb between MC and NC (p > 0.05). All the heavy metal contents in MLS were highest significantly except Cd among NL and LFA. Shannon and Chao1 indices in NC were significantly higher than those in MC (p < 0.05), In LFA, Shannon and Chao1 indices of MLX were the highest, while MLS was significantly lower than NL (p < 0.05). The relative abundance of bacteria more than 40% in MC and NC was Actinomycetes (42.06%-42.38%), and while was Proteobacteria (40.66%-50.77%) in NL and LFA. Bacterial communities in different disturbed areas were significantly correlated with As, Pb, Cu, Cd, TP, SOC and EC in the soil, among which SOC contributed most about 40.1%. Molecular ecological network showed that the interactions among bacterial taxa in MC and LFA were mainly in a positive synergistic development, the bacteria with higher relative abundance may not be the key node in the bacterial molecular ecological network, while bacteria with the lower relative abundance might have been. The bacterial community structure of MC was more complex than NC because of fewer nodes and modules but more connections. The positive connection proportion and modules of bacteria in LFA was higher than that in NL, while the aggregation coefficient decreased. The average path distance (5.09) in MLS was the shortest, indicating the bacteria in MLS were most environmental sensitive to the external environment with rapid community response to disturbances. Our results revealed the changes in the bacterial community and the main environmental driving factors under disturbance of CG dump, this information provides a theoretical basis for ecological environment management.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".