Enemy release from the effects of generalist granivores can facilitate <i>Bromus tectorum</i> invasion in the Great Basin Desert
Bibliographic record
Abstract
Abstract The enemy release hypothesis (ERH) of plant invasion asserts that natural enemies limit populations of invasive plants more strongly in native ranges than in non‐native ranges. Despite considerable empirical attention, few studies have directly tested this idea, especially with respect to generalist herbivores. This knowledge gap is important because escaping the effects of generalists is a critical aspect of the ERH that may help explain successful plant invasions. Here, we used consumer exclosures and seed addition experiments to contrast the effects of granivorous rodents (an important guild of generalists) on the establishment of cheatgrass (Bromus tectorum) in western Asia, where cheatgrass is native, versus the Great Basin Desert, USA, where cheatgrass is exotic and highly invasive. Consistent with the ERH, rodent foraging reduced cheatgrass establishment by nearly 60% in western Asia but had no effect in the Great Basin. This main result corresponded with a region‐specific foraging pattern: rodents in the Great Basin but not western Asia generally avoided seeds from cheatgrass relative to seeds from native competitors. Our results suggest that enemy release from the effects of an important guild of generalists may contribute to the explosive success of cheatgrass in the Great Basin. These findings corroborate classic theory on enemy release and expand our understanding of how generalists can influence the trajectory of exotic plant invasions.
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 | 0.001 |
| 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".