Acquisition and evolution of enhanced mutualism—an underappreciated mechanism for invasive success?
Bibliographic record
Abstract
Soil biota can determine plant invasiveness, yet biogeographical comparisons of microbial community composition and function across ranges are rare. We compared interactions between Conyza canadensis, a global plant invader, and arbuscular mycorrhizal (AM) fungi in 17 plant populations in each native and non-native range spanning similar climate and soil fertility gradients. We then grew seedlings in the greenhouse inoculated with AM fungi from the native range. In the field, Conyza plants were larger, more fecund, and associated with a richer community of more closely related AM fungal taxa in the non-native range. Fungal taxa that were more abundant in the non-native range also correlated positively with plant biomass, whereas taxa that were more abundant in the native range appeared parasitic. These patterns persisted when populations from both ranges were grown together in a greenhouse; non-native populations cultured a richer and more diverse AM fungal community and selected AM fungi that appeared to be more mutualistic. Our results provide experimental support for evolution toward enhanced mutualism in non-native ranges. Such novel relationships and the rapid evolution of mutualisms may contribute to the disproportionate abundance and impact of some non-native plant species.
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 | 0.001 | 0.001 |
| 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 | 0.001 |
| 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".