Plant identity and environmental filtering are the key drivers of bacterial community structure in four desert plant species from the Sahara Desert in Morocco
Bibliographic record
Abstract
BACKGROUND: Plant microbiome is a very wide research area playing a major role in agriculture and plant health. This study investigates the interactions between root-associated bacterial communities and soil physico-chemical characteristics of four Moroccan desert plant species: Lavandula coronopifolia Poir. (n = 20), Lycium intricatum Boiss. (n = 20), Nitraria retusa Asch. (n = 20) and Searsia tripartita (Ucria) Moffett. (n = 20). Soil samples were collected in the rhizosphere of each plant species, and root samples from four different sites, with five random samples per site. Elemental chemical composition of soil sample was analyzed using the X-Ray fluorescence spectrometry and soil carbon, i.e., organic carbon (SOC) and inorganic carbon (SIC) were measured using the Rock-Eval® Oxypure method. Roots were assessed for their microbial community, using the 16S rDNA metabarcoding analysis. RESULTS: Significant variation in soil parameters was observed across sites and among the four desert plant species. SOC and SIC contents were highest in soils associated with S. tripartita, N. retusa, and Ly. intricatum, while La. coronopifolia was associated with elevated levels of Si, Al, K, and Mn. Soil EC was highest in N. retusa and S. tripartita. Microbial analysis revealed that Pseudomonadota and Actinomycetota dominated the root-associated bacterial communities, comprising around 60% of total abundance. Alpha diversity (Shannon and Simpson indices) varied significantly across species and sites, especially in La. coronopifolia. Beta diversity analyzes confirmed that geographic location significantly influenced microbial community structure. Rhizosphere network complexity and composition varied by species, with N. retusa showing broad ecological tolerance, while S. tripartita communities were strongly shaped by SOC, SIC, K, Ca, Mn, and Fe. Mantel test results further highlighted that plant identity and environmental factors differentially influence root microbial composition across sites. CONCLUSION: Each plant species showed unique responses in terms of soil characteristics and microbial communities, highlighting the importance of adopting a species-specific approach.
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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) | 0.000 | 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 teacher head, 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".