Population and community consequences of perceived risk from humans in wildlife
Bibliographic record
Abstract
Abstract Human activities catalyse risk avoidance behaviours in wildlife across taxa and systems. However, the broader ecological significance of human‐induced risk perception remains unclear, with a limited understanding of how phenotypic responses scale up to affect population or community dynamics. We present a framework informed by predator–prey ecology to predict the occurrence of non‐consumptive effects (NCE) and trait‐mediated indirect effects (TMIE) of anthropogenic disturbances. We report evidence from a comprehensive review of the different types of human‐induced behavioural and physiological phenotypic changes and their influence on vital rates and population parameters in wildlife. Evidence for human‐induced NCEs and TMIEs is mixed, with half of published studies finding a relationship between human activities, phenotypic change and population outcomes. The net effects of anthropogenic NCEs and TMIEs depend on the mismatch between the phenotypic response and the lethality of human activity. However, strong research biases in taxa, systems, human disturbance types and demographic measures prevent unified inference about the prevalence of population responses to human activities. Coexistence with and conservation of wildlife requires additional research linking human‐induced phenotypic change to population and community outcomes.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 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".