Life-History Strategies of Arbuscular Mycorrhizal Fungi in Relation to Their Successional Dynamics
Bibliographic record
Abstract
Arbuscular mycorrhizal fungi (AMF) are integral components of terrestrial ecosystems. Currently, it is difficult to predict the dynamics of AMF communities, mainly because little is known about AMF life-history strategies. This review provides a theoretical context for AMF community dynamics on a successional time scale, based on differences in AMF life-history strategies. While some studies have examined colonization and persistence behaviors among AMF, these traits have not been examined in the context of life-history strategies for AMF. We propose a model whereby differences in colonizing and persistence strategies among AMF are responsible for AMF succession over time. In our Driver/Passenger hypothesis, we describe two mechanisms for AMF and plant community changes over time. In the Driver hypothesis, interactions within AMF communities are responsible for changes in the plant community over time. In the Passenger hypothesis, AMF community dynamics are a by-product of changes within the plant community. To test these theories, it will be necessary to classify AMF in terms of life-history strategies. Once accomplished, this knowledge will allow landscape managers to have better predictive power when utilizing AMF for ecosystem management.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".