The evolutionary implications of exploitation in mycorrhizas
Bibliographic record
Abstract
Some views of mutualism, where the fitness of two symbiotic partners is higher in association than when apart, assume that they necessarily evolve towards greater benefit for the partners. Most mutualisms, however, seem prone to conflicts of interest that destabilize the partnership. These conflicts arise in part because mutualistic outcomes are conditional, depending upon complex interactions between environmental, developmental, and genotypic factors. Mutualisms are also subject to exploitation or cheating. Although various compensating mechanisms have been proposed to explain how mutualism can be maintained in the presence of exploiters, none of these mechanisms can eliminate exploitation. In this paper we explore various compensating mechanisms in mycorrhizas, examine the evidence for exploitation in mycorrhizas, and conclude that mycorrhizal mutualisms exhibit characteristics that are more consistent with a concept of reciprocal parasitism. We propose that researchers should not assume mycorrhizas are mutualistic based upon structural characteristics or limited functional studies showing bilateral exchange and should view mycorrhizas as occupying a wider range on the symbiotic continuum, including commensalism and antagonism. We recommend that comparative studies of mycorrhizas incorporate other types of root associations that have traditionally been considered antagonistic.Key words: mycorrhizas, mutualism, exploiters, compensating mechanisms, symbiotic continuum.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".