Simple rules for the coexistence and competitive dominance of plants mediated by mycorrhizal fungi
Bibliographic record
Abstract
Abstract Mycorrhizal fungi have been demonstrated to be important in the makeup of plant communities. Likely, their most important role is in altering mineral nutrition of plants, which, in turn, is thought to be among the most important determinants of plant competitive ability. Using mathematical models we examine what role these fungi can play in determining the competitive outcome between two plants in competition for one mineral resource. Depending on different relationships between the benefit accrued to the plant and the fungi, the presence of mycorrhizal fungi can (i) have no impact on which plant wins in competition, (ii) change the order of competitive dominance or (iii) enable coexistence when compared with the system in the absence of mycorrhizal fungi. Furthermore, environmental conditions, such as light and nutrient levels, can determine if coexistence is possible. We describe the necessary biological trade‐offs for coexistence and experimental tests for these trade‐offs.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".