Integrating physiological, community, and evolutionary perspectives on the arbuscular mycorrhizal symbiosis
Bibliographic record
Abstract
Our knowledge of arbuscular mycorrhizal (AM) function is largely based on results from short-term studies in controlled environments. While these have provided many important insights into the potential effects of the symbiosis on the two symbionts and their communities, they may have also inadvertently led to faulty assumptions about the function of the symbiosis in natural settings. Here we highlight the consequences of failing to consider the AM symbiosis from the perspectives of community ecology and evolutionary biology. Also, we argue that by distinguishing between physiological and evolutionary viewpoints, we may be able to resolve controversies regarding the mutualistic vs. parasitic nature of the symbiosis. Further, while most AM research has emphasized resource transfers, primarily phosphate and carbohydrate, our perceptions of parasitism, cheating, bet-hedging, and partner choice would most likely change if we considered other services. Finally, to gain a fuller understanding of the role of the AM symbiosis in nature, we need to better integrate physiological processes of plants and their AM fungi with their naturally occurring temporal and spatial patterns. It is our hope that this article will generate some fruitful discussions and make a contribution toward this end.
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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 | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.004 | 0.009 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| 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".