Leaf damage has weak effects on growth and fecundity of common ragweed (<i>Ambrosia artemisiifolia</i>)
Bibliographic record
Abstract
The Enemy Release Hypothesis predicts that exotic plants gain an advantage over native competitors by losing their natural enemies while invading new regions. However, this assumes that those enemies reduced the performance of these invaders in their native ranges, and this may not be true if an invader is highly tolerant of herbivory. We used a field experiment to test the herbivore tolerance of a North American annual, common ragweed (Ambrosia artemisiifolia L.), which is known to have lost insect herbivores while invading Europe. We clipped leaves to simulate damage by folivores and removed meristems to simulate apical mortality caused by stem borers, and measured the consequences for growth and reproduction. Stem biomass was only reduced by defoliation far in excess of native-range natural damage, while seed production was unaffected by our treatments. Severely damaged plants maintained seed production by allocating relatively more aboveground biomass to reproduction. These results suggest that for the most part, damage by natural enemies may have little impact on this highly tolerant plant; consequently, enemy release may not have provided a significant advantage to this species in Europe. As well, biological control by insect folivores is unlikely to succeed unless it results in very high levels of damage.
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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".