Evaluating the diversity and composition of bacterial communities associated with <i>Vachellia pachyceras</i> — the only existing native tree species in the Kuwait desert
Bibliographic record
Abstract
We investigated the diversity and composition of bacterial communities in rhizospheric and non-rhizospheric bulk soils as well as root nodule bacterial communities of Vachellia pachyceras - the only native tree species existing in the Kuwait desert. Community fingerprinting comparisons and 16S rDNA sequence identifications were used for characterization of the bacterial population using specific primers. The bacterial characterization of soil samples revealed four major phyla: Acidobacteria, Bacteroidetes, Firmicutes, and Proteobacteria. In situ (desert) samples of both rhizospheric and non-rhizospheric bulk soil were dominated by the bacterial phyla Firmicutes and Bacteroidetes, whereas the phylum Betaproteobacteria was present only in non-rhizospheric bulk soil. Ex situ (nursery growing condition) V. pachyceras resulted in restricted bacterial communities dominated by members of a single phylum, Bacteroidetes. Results indicated that the soil organic matter and rhizospheric environments might drive the bacterial community. Despite harsh climatic conditions, data demonstrated that V. pachyceras roots harbor endophytic bacterial populations. Our findings on bacterial community composition and structure have major significance for evaluating how Kuwait's extreme climatic conditions affect bacterial communities. The baseline data obtained in this study will be useful and assist in formulating strategies in ecological restoration programs, including the application of inoculation technologies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".