HERBIVORY LIMITS RECRUITMENT IN AN OLD-FIELD SEED ADDITION EXPERIMENT
Bibliographic record
Abstract
Environmental variability can promote coexistence by creating establishment sites for rare plants, but low diversity in anthropogenic grasslands suggests that this variability may be eliminated (homogenization hypothesis) or inaccessible (barrier hypothesis). We explore these alternatives on the northern Great Plains, where 11 million hectares have been transformed by multiple environmental changes, but the causes of species loss are unclear. In a degraded grassland, we increased environmental variability by manipulating competition and herbivory along gradients of fertility and disturbance, and we circumvented dispersal barriers by adding 1.2 million seeds of five functionally distinct species at varying densities. The experiment ended after 12 weeks due to the direct and indirect effects of unapparent small native herbivores, which were barriers to population establishment by the added species. The direct cause of recruitment failure was browsing. The indirect cause was associated with competition from invasive plants that appeared to be more tolerant or resistant to herbivory. Variability in fertility, disturbance, propagule pressure, and competition had relatively minor impacts on colonization by the added species because herbivores controlled recruitment in most environments. Recruitment outside the herbivore exclosures was mostly by unpalatable exotics, suggesting a possible link between invasion success and herbivore resistance for some introduced plants.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".