VARIATION IN PLANT RESPONSE TO NATIVE AND EXOTIC ARBUSCULAR MYCORRHIZAL FUNGI
Bibliographic record
Abstract
High variability in plant-growth response to the presence of different mycorrhizal fungi can be a major determinant of local plant species diversity. Multiple species of arbuscular mycorrhizal fungi can coexist in terrestrial ecosystems, and co-occurring plants can differ in their response to colonization by these different fungi. However, the range of mycorrhizal plant-growth responses that can occur within communities has not been determined. In the present study, I crossed a large number of plant and fungal species that co-occur to determine the range of responses that can exist within an ecosystem. I also crossed exotic fungal isolates vs. local plant isolates and local fungal isolates vs. exotic plant isolates to determine whether the range of plant growth responses differs when using foreign genotypes. The data indicate that plant growth responses to mycorrhizal inoculation within an ecosystem can range from highly parasitic to highly mutualistic. In this study, the direction and magnitude of the response depended on the combination of plant and fungal species. No plant did best with the same fungal isolate. The range of responses was greatest when using local plants and fungi. Whereas parasitic and mutualistic responses were also detected when using foreign plant or fungal genotypes, the range of responses was significantly reduced, as was the relative frequency of positive responses. Overall, this study suggests that, within ecosystems, arbuscular mycorrhizal fungi can function along a continuum from parasitism to mutualism, and that extreme responses are more common when using locally adapted plants and fungi. This high variation in plant growth response may be a large contributor to plant species coexistence and the structure of plant communities.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".