NOVEL WEAPONS: INVASIVE PLANT SUPPRESSES FUNGAL MUTUALISTS IN AMERICA BUT NOT IN ITS NATIVE EUROPE
Bibliographic record
Abstract
Why some invasive plant species transmogrify from weak competitors at home to strong competitors abroad remains one of the most elusive questions in ecology. Some evidence suggests that disproportionately high densities of some invaders are due to the release of biochemicals that are novel, and therefore harmful, to naive organisms in their new range. So far, such evidence has been restricted to the direct phytotoxic effects of plants on other plants. Here we found that one of North America's most aggressive invaders of undisturbed forest understories, Alliaria petiolata (garlic mustard) and a plant that inhibits mycorrhizal fungal mutualists of North American native plants, has far stronger inhibitory effects on mycorrhizas in invaded North American soils than on mycorrhizas in European soils where A. petiolata is native. This antifungal effect appears to be due to specific flavonoid fractions in A. petiolata extracts. Furthermore, we found that suppression of North American mycorrhizal fungi by A. petiolata corresponds with severe inhibition of North American plant species that rely on these fungi, whereas congeneric European plants are weakly affected. These results indicate that phytochemicals, benign to resistant mycorrhizal symbionts in the home range, may be lethal to naïve native mutualists in the introduced range and indirectly suppress the plants that rely on them.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".