Biotic interactions experienced by a new invader: effects of its close relatives at the community scale
Bibliographic record
Abstract
The success of nonindigenous species may be influenced by biotic interactions during the initial stages of invasion. Here, we investigated whether a potential invader, Solidago virgaurea L., would experience more damage by natural enemies in communities dominated by close relatives than those without them; interactions with mutualistic mycorrhizae might partially counteract these effects. We monitored damage experienced by S. virgaurea planted into communities with native congeners and without close relatives. Community type was crossed with a vegetation removal treatment to assess the combined effects of herbivory and competition on survival. We also evaluated growth of S. virgaurea in a greenhouse experiment where seedlings were exposed to soil biota sampled from these communities and compared with sterile controls. Overall, community type did not affect levels of herbivory or plant survival. Removal of surrounding vegetation resulted in reduced damage and increased survival; these effects were largest in grass-dominated communities. Soil sterilization reduced root growth and tended to reduce shoot growth, especially when compared with plants inoculated with biota collected near congeners. Overall, our results suggest that the presence of close relatives is unlikely to make old-field communities more resistant to invasion by S. virgaurea; instead, soil biota might facilitate growth in communities dominated by close relatives.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".