What determines transfer of carbon from plants to mycorrhizal fungi?
Bibliographic record
Abstract
Biological Market Models are common evolutionary frameworks to understand the maintenance of mutualism in mycorrhizas. 'Surplus C' hypotheses provide an alternative framework where stoichiometry and source-sink dynamics govern mycorrhizal function. A critical difference between these frameworks is whether carbon transfer from plants is regulated by nutrient transfer from fungi or through source-sink dynamics. In this review, we: provide a historical perspective; summarize studies that asked whether plants transfer more carbon to fungi that transfer more nutrients; conduct a meta-analysis to assess whether mycorrhizal plant growth suppressions are related to carbon transfer; and review literature on cellular mechanisms for carbon transfer. In sum, current knowledge does not indicate that carbon transfer from plants is directly regulated by nutrient delivery from fungi. Further, mycorrhizal plant growth responses were linked to nutrient uptake rather than carbon transfer. These findings are more consistent with 'Surplus C' hypotheses than Biological Market Models. However, we also identify research gaps, and future research may uncover a mechanism directly linking carbon and nutrient transfer. Until then, we urge caution when applying economic terminology to describe mycorrhizas. We present a synthesis of ideas, consider knowledge gaps, and suggest experiments to advance the field.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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; both teacher heads agree on what is shown here.
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".