Fungal and Bacterial Microbiome Associated with the Rhizosphere of Native Plants from the Atacama Desert
Bibliographic record
Abstract
The rhizosphere microbiome is key in survival, development, and stress tolerance in plants. Salinity, drought, and extreme temperatures are frequent events in the Atacama Desert, considered the driest in the world. However, little information of the rhizosphere microbiome and its possible contribution to the adaptation and tolerance of plants that inhabit the desert is available. We used a high-throughput Illumina MiSeq sequencing approach to explore the composition, diversity, and functions of fungal and bacterial communities of the rhizosphere of Baccharis scandens and Solanum chilense native plants from the Atacama Desert. Our results showed that the fungal phyla Ascomycota and Basidiomycota and the bacterial phyla Actinobacteria and Proteobacteria were the dominant taxa in the rhizosphere of both plants. The linear discriminant analysis (LDA) effect size (LefSe) of the rhizosphere communities associated with B. scandens showed the genera Penicillium and Arthrobacter were the preferential taxa, whereas the genera Oidiodendron and Nitrospirae was the preferential taxa in S. chilense. Both plant showed similar diversity, richness, and abundance according to Shannon index, observed OTUs, and evenness. Our results indicate that there are no significant differences (p = 0.1) between the fungal and bacterial communities of both plants, however through LefSe, we find taxa associated with each plant species and the PCoA shows a separation between the samples of each species. This study provides knowledge to relate the assembly of the microbiome to the adaptability to drought stress in desert plants.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".