Outsized effect of predation: Wolves alter wetland creation and recolonization by killing ecosystem engineers
Bibliographic record
Abstract
Gray wolves are a premier example of how predators can transform ecosystems through trophic cascades. However, whether wolves change ecosystems as drastically as previously suggested has been increasingly questioned. We demonstrate how wolves alter wetland creation and recolonization by killing dispersing beavers. Beavers are ecosystem engineers that generate most wetland creation throughout boreal ecosystems. By studying beaver pond creation and recolonization patterns coupled with wolf predation on beavers, we determined that 84% of newly created and recolonized beaver ponds remained occupied until the fall, whereas 0% of newly created and recolonized ponds remained active after a wolf killed the dispersing beaver that colonized that pond. By affecting where and when beavers engineer ecosystems, wolves alter all of the ecological processes (e.g., water storage, nutrient cycling, and forest succession) that occur due to beaver-created impoundments. Our study demonstrates how predators have an outsized effect on ecosystems when they kill ecosystem engineers.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".