Fear of humans as apex predators has landscape‐scale impacts from mountain lions to mice
Why is this work in the frame?
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Full frame distilled prediction
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.
- Candidate categories
- Meta-epidemiology (narrow), Insufficient payload (model declined to judge)
- Consensus categories
- Insufficient payload (model declined to judge)
- Domain
- Candidate signal: noneConsensus signal: none
- Study design
- Candidate signal: ObservationalConsensus signal: none
- Genre
- Candidate signal: CommentaryConsensus signal: none
- Teacher disagreement score
- 0.463
- Threshold uncertainty score
- 1.000
- Validation status
machine_predicted_unvalidated·codex-gemma-dda1882f352a
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.009 |
Machine scores (provisional)
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
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.
- Teacher spread
- 0.201 · how far apart the two teachers sit on this one work
- Validation status
score_only:v0-immature-baseline· verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it
Abstract
Apex predators such as large carnivores can have cascading, landscape-scale impacts across wildlife communities, which could result largely from the fear they inspire, although this has yet to be experimentally demonstrated. Humans have supplanted large carnivores as apex predators in many systems, and similarly pervasive impacts may now result from fear of the human 'super predator'. We conducted a landscape-scale playback experiment demonstrating that the sound of humans speaking generates a landscape of fear with pervasive effects across wildlife communities. Large carnivores avoided human voices and moved more cautiously when hearing humans, while medium-sized carnivores became more elusive and reduced foraging. Small mammals evidently benefited, increasing habitat use and foraging. Thus, just the sound of a predator can have landscape-scale effects at multiple trophic levels. Our results indicate that many of the globally observed impacts on wildlife attributed to anthropogenic activity may be explained by fear of humans.
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.
The record
- Venue
- Ecology Letters
- Topic
- Wildlife Ecology and Conservation
- Field
- Environmental Science
- Canadian institutions
- Western University
- Funders
- Natural Sciences and Engineering Research Council of CanadaGordon and Betty Moore FoundationNational Science Foundation
- Keywords
- Apex predatorForagingPredationEcologyWildlifePredatorHabitatGeographyTrophic levelScale (ratio)Trophic cascadeBiologyCartography
- Has abstract in OpenAlex
- yes