A new model of carbon and phosphorus transfers in arbuscular mycorrhizas
Bibliographic record
Abstract
Existing models of nutrient transfer in arbuscular mycorrhizal (AM) symbioses are inadequate as they do not explain the range of real responses seen experimentally. A computer simulation model was used to evaluate the novel hypotheses that mycorrhizal nutrient transfers were based solely on symbionts' internal needs, and that carbon and phosphorus transfers were quantitatively unlinked. To be plausible, simulated mycorrhizal plants would show a +/-50% variation in weight vs nonmycorrhizal controls, with a normal response distribution (mimicking a real data set). One plant and one arbuscular mycorrhizal fungus (AMF) growing in a soil volume were simulated, using C, P and nitrogen nutrient cycling and stoichiometry. C- and P-exchange rates were independent and could be varied at will. The model was tested at realistic nutrient concentrations and a full range of nutrient exchange rates. The model showed -20% to +55% range in mycorrhizal plant weight distributed close to normal, suggesting that the hypotheses were plausible. The model suggests that theoretical assumptions about mycorrhizas should be reassessed. The model worked only because the symbionts possessed incomplete information on their partner and environmental conditions. Conventional cost-benefit models do not work under these circumstances, but both mutualistic and parasitic interactions were successfully simulated.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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; 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".