Soil Microbial Responses to Varying Environmental Conditions in a Copper Belt Region of Africa: Phytoremediation Perspectives
Bibliographic record
Abstract
The mining industry in the copper belt region of Africa was initiated in the early 1900s, with copper being the main ore extracted to date. The main objectives of the present study are (1) to characterize the microbial structure, abundance, and diversity in different ecological conditions in the cupriferous city of Lubumbashi and (2) to assess the metal phytoextraction potential of Leucaena leucocephala, a main plant species used in tailing. Four ecologically different sites were selected. They include a residential area (site 1), an agricultural dry field (site 2), and an agricultural wetland (site 3), all located within the vicinity of a copper/cobalt mining plant. A remediated tailing was also added as a highly stressed area (site 4). As expected, the highest levels of copper and cobalt among the sites studied were found at the remediated tailing, with 9447 mg/kg and 2228 mg/kg for copper and cobalt, respectively. The levels of these metals at the other sites were low, varying from 41 mg/kg to 579 mg/kg for copper and from 4 mg/kg to 110 mg/kg for cobalt. Interestingly, this study revealed that the Leucaena leucocephala grown on the remediated sites is a copper/cobalt excluder species as it accumulates soil bioavailable metals from the rhizosphere in its roots. Amplicon sequence analysis showed significant differences among the sites in bacterial and fungal composition and abundance. Site-specific genera were identified. Acidibacter was the most abundant bacterial genus in the residential and remediated tailing sites, with 11.1% and 4.4%, respectively. Bacillus was predominant in both dry (19.3%) and wet agricultural lands (4.8%). For fungi, Fusarium exhibited the highest proportion of the fungal genera at all the sites, with a relative abundance ranging from 15.6% to 20.3%. Shannon diversity entropy indices were high and similar, ranging from 8.3 to 9 for bacteria and 7.0 and 7.4 for fungi. Β diversity analysis confirmed the closeness of the four sites regardless of the environmental conditions. This lack of differences in the microbial community diversity and structures among the sites suggests microbial resilience and physiological adaptations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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; both teacher heads agree on what is shown here.
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".