Escape from natural enemies depends on the enemies, the invader, and competition
Bibliographic record
Abstract
Abstract The enemy release hypothesis (ERH) attributes the success of some exotic plant species to reduced top‐down effects of natural enemies in the non‐native range relative to the native range. Many studies have tested this idea, but very few have considered the simultaneous effects of multiple kinds of enemies on more than one invasive species in both the native and non‐native ranges. Here, we examined the effects of two important groups of natural enemies–insect herbivores and soil biota–on the performance of Tanacetum vulgare (native to Europe but invasive in the USA) and Solidago canadensis (native to the USA but invasive in Europe) in their native and non‐native ranges, and in the presence and absence of competition. In the field, we replicated full‐factorial experiments that crossed insecticide, T. vulgare–S. canadensis competition, and biogeographic range (Europe vs. USA) treatments. In greenhouses, we replicated full‐factorial experiments that crossed soil sterilization, plant–soil feedback, and biogeographic range treatments. We evaluated the effects of experimental treatments on T. vulgare and S. canadensis biomass. The effects of natural enemies were idiosyncratic. In the non‐native range and relative to populations in the native range, T. vulgare escaped the negative effects of insect herbivores but not soil biota, depending upon the presence of S. canadensis; and S. canadensis escaped the negative effects of soil biota but not insect herbivores, regardless of competition. Thus, biogeographic escape from natural enemies depended upon the enemies, the invader, and competition. Synthesis: By explicitly testing the ERH in terms of more than one kind of enemy, more than one invader, and more than one continent, this study enhances our nuanced perspective of how natural enemies can influence the performance of invasive species in their native and non‐native ranges.
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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 | 0.001 | 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".