Simulated fire and plant-soil feedback effects on mycorrhizal fungi and invasive plants
Bibliographic record
Abstract
Summary Climate change intensifies fires, raising questions about their impacts on plant invasions via changes in soil biota and plant-soil feedback (plants alter soil conditions, changing plant growth and vice-versa). We explored effects of plant-soil feedback and simulated fire (heat) on mutualistic arbuscular mycorrhizal (AM) fungal communities and invasive plant growth. Soils were collected from a dominant native grass (Chionochloa macra) and two invasive hawkweeds (Hieracium lepidulum, Pilosella officinarum) in a New Zealand grassland and then heated. In our experiment, both hawkweeds exhibited greater biomass in Pilosella soils, which also had the highest AM fungal richness. Heat had little effect on plant biomass or AM fungal community composition and richness. Hawkweeds altered AM fungal communities relative to the dominant native grass, and moderate soil heating increased Hieracium growth. Hieracium plants also grew better in Pilosella soils, suggesting the potential for soil-mediated invasional meltdown whereby one invasive species facilitates invasion by another.
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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) | 0.001 | 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".