Composition of fungal soil communities varies with plant abundance and geographic origin
Bibliographic record
Abstract
Interactions of belowground fungal communities with exotic and native plant species may be important drivers of plant community structure in invaded grasslands. However, field surveys linking plant community structure with belowground fungal communities are missing. We investigated whether a selected number of abundant and relatively rare plants, either native or exotic, from an old-field site associate with different fungal communities. We also assessed whether these plants showed different symbiotic relationships with soil biota through their roots. We characterized the plant community and collected roots to investigate fungal communities using 454 pyrosequencing and assessed arbuscular mycorrhizal colonization and enemy-induced lesions. Differences in fungal communities were considered based on the assessment of α- and β diversity depending on plant 'abundance' and 'origin'. Plant abundance and origin determined the fungal community. Fungal richness was higher for native abundant as opposed to relatively rare native plant species. However, this was not observed for exotics of contrasting abundance. Regardless of their origin, β diversity was higher for rare than for abundant species. Abundant exotics in the community, which happen to be grasses, were the least mycorrhizal whereas rare natives were most susceptible to enemy attack. Our results suggest that compared with exotics, the relative abundance of remnant native plant species in our old-field site is still linked to the structure of belowground fungal communities. In contrast, exotic species may act as a disturbing agent contributing towards the homogenization of soil fungal communities, potentially changing feedback interactions.
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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) | 0.001 | 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".