Aspen-associated soil microbiomes reveal different strategies for nitrogen acquisition across ecosystems in Mexico and Canada
Bibliographic record
Abstract
Abstract Plant species shape soil microbiome composition through species-specific interactions. However, it is less clear how these interactions vary across populations that diverged a long time ago. In this study, we explore the influence of host genetic composition and edaphic factors on the soil microbiome of Populus tremuloides , one of North America’s most widespread tree species. Using 16S, 18S rRNA gene, and ITS2 region metabarcoding on soils from natural stands and potting mix, rhizosphere, and root samples from a greenhouse common garden, we examined prokaryotic and fungal communities in two aspen genetic groups. The Eastern Canada group represents boreal and cold temperate ecoregions, and the one from Northwestern Mexico represents warm temperate ecoregion. Variation in microbial community structure correlated with soil properties but results from common gardens indicated that the host genetic makeup may also play a role. The three ecoregions showed functional divergence: warm temperate sites hosted a higher abundance and diversity of nitrogen-fixing bacteria, while boreal stands exhibited stronger associations with ectomycorrhizal fungi. Our findings highlight how local adaptations to climate and soil conditions in aspen extend to their microbial partners, emphasizing the potential role of host-microbe interactions in shaping tree resilience and susceptibility to future climate changes.
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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".