Linking Bacterial Rhizosphere Communities of Two Pioneer Species, Brachystegia boehmii and B. spiciformis, to the Ecological Processes of Miombo Woodlands
Bibliographic record
Abstract
Miombo is the most extensive ecosystem in southern Africa, being strongly driven by fire, climate, herbivory, and human activity. Soils are major regulating and supporting services, sequestering nearly 50% of the overall carbon and comprising a set of yet unexploited functions. In this study, we used next-generation Illumina sequencing to assess the patterns of bacterial soil diversity in two pioneer Miombo species, Brachystegia boehmii and Brachystegia spiciformis, along a fire gradient, in ferric lixisol and cambic arenosol soils. In total, 21 phyla, 51 classes, 98 orders, 193 families, and 520 genera were found, revealing a considerably high and multifunctional diversity with a strong potential for the production of bioactive compounds and nutrient mobilization. Four abundant genera characterized the core microbiome among plant species, type of soils, or fire regime: Streptomyces, Gaiella, Chthoniobacter, and Bacillus. Nevertheless, bacterial networks revealed a higher potential for mutualistic interactions and transmission of chemical signals among phylotypes from low fire frequency sites than those from high fire frequency sites. Ecological networks also revealed the negative effects of frequent fires on the complexity of microbial communities. Functional predictions revealed the core “house-keeping” metabolisms contributing to the high bacterial diversity found, suggesting its importance to the functionality of this ecosystem.
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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 | 0.000 |
| 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) | 0.000 | 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".