Trait‐based aerial dispersal of arbuscular mycorrhizal fungi
Bibliographic record
Abstract
Dispersal is a key process driving local-scale community assembly and global-scale biogeography of plant symbiotic arbuscular mycorrhizal (AM) fungal communities. A trait-based approach could improve predictions regarding how AM fungal aerial dispersal varies by species. We conducted month-long collections of aerial AM fungi for 12 consecutive months in an urban mesic environment at heights of 20 m. We measured morphological functional traits of collected spores and assessed aerial AM fungal community structure both morphologically and with high-throughput sequencing. Large numbers of AM fungal spores were present in the air over the course of one year and these spores exhibited traits that facilitate aerial dispersal. Measured aerial spores were smaller than average for Glomeromycotinan fungi. Trait-based predictions indicate that nearly 1/3 of described species from diverse genera demonstrate the potential for aerial dispersal. Diversity of aerial AM fungi was relatively high (20 spore species and 17 virtual taxa) and both spore abundance and community structure shifted temporally. The prevalence of aerial dispersal in AM fungi is perhaps greater than previously indicated and a hypothesized model of AM fungal aerial dispersal mechanisms is presented. Anthropogenic soil impacts may liberate AM fungal propagules initiating the dispersal of ruderal species.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".