Trophic cascades: linking ungulates to shrub‐dependent birds and butterflies
Bibliographic record
Abstract
1. Studies demonstrating trophic cascades through the loss of top-down regulatory processes in productive and biologically diverse terrestrial ecosystems are limited. 2. Elk Island National Park, Alberta and surrounding protected areas have a wide range of ungulate density due to the functional loss of top predators, management for high ungulate numbers and variable hunting pressure. This provides an ideal setting for studying the effects of hyper-abundant ungulates on vegetation and shrub-dependent bird and butterfly species. 3. To examine the cascading effects of high ungulate density, we quantified vegetation characteristics and abundances of yellow warbler Dendroica petechia and Canadian tiger swallowtail Papilio canadensis under different ungulate density in and around Elk Island National Park. 4. Using Structural Equation Models we found that ungulate density was inversely related to shrub cover, whereas shrub cover was positively related to yellow warbler abundance. In addition, chokecherry Prunus virginiana abundance was inversely related to browse impact but positively related to P. canadensis abundance. 5. These results demonstrate a cascade resulting from hyper-abundant ungulates on yellow warblers and Canadian tiger swallowtails through reductions in shrub cover and larval host plant density. The combined effect of the functional loss of top predators and management strategies that maintain high ungulate numbers can decouple top-down regulation of productive temperate ecosystems.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".