Mycorrhizae confer aluminum resistance to tulip-poplar seedlings
Bibliographic record
Abstract
Aluminum (Al) toxicity may limit the growth and nutrient acquisition of sensitive tree species in regions receiving acidic deposition. Symbioses between tree roots and mycorrhizal fungi may offset the negative impacts of Al in the root zone. Liriodendron tulipifera L. (tulip-poplar) is an important tree species in the Appalachian Mountains of the southeastern United States and may be at risk from the high levels of acidic deposition in that area. Mycorrhizal and non-mycorrhizal tulip-poplar seedlings were exposed to Al levels of 0, 50, 100, and 200 µM in sand culture for 6 weeks. Mycorrhizal plants accumulated two to seven times the shoot and root biomass of non-mycorrhizal plants and demonstrated no decreases in biomass with Al exposure. Non-mycorrhizal plants exhibited significant reductions in biomass at and above 100 µM Al. Aluminum toxicity in non-mycorrhizal plants appears to be the result of the disruption of P translocation to leaves and Ca, Mg, P, Cu, and Zn uptake in roots. Mycorrhizal plants accumulated 2 and 1.5 times the concentration of Al in shoots and roots, respectively, indicating that Al resistance was not associated with the exclusion of Al from the plant. Patterns of labile Al in solution, nutrients, and Al accumulation in tissues suggest that arbuscular mycorrhizal fungal ecotypes may alter the form or compartmentation of Al within the rhizosphere and plant, thus protecting seedlings from the effects of exposure to Al in the soil solution.
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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 | 0.000 | 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 | 0.001 |
| 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".