Uncertainty about predation risk: a conceptual review
Bibliographic record
Abstract
Uncertainty has long been of interest to economists and psychologists and has more recently gained attention among ecologists. In the ecological world, animals must regularly make decisions related to finding resources and avoiding threats. Here, we describe uncertainty as a perceptual phenomenon of decision-makers, and we focus specifically on the functional ecology of such uncertainty regarding predation risk. Like all uncertainty, uncertainty about predation risk reflects informational limitations. When cues are available, they may be novel (i.e. unknown information), incomplete, unreliable, overly abundant and complex, or conflicting. We review recent studies that have used these informational limitations to induce uncertainty of predation risk. These studies have typically used either over-responses to novelty (i.e. neophobia) or memory attenuation as proxies for measuring uncertainty. Because changes in the environment, particularly unpredictable changes, drive informational limitations, we describe studies assessing unpredictable variance in spatio-temporal predation risk, intensity of predation risk, predator encounter rate, and predator diversity. We also highlight anthropogenic changes within habitats that are likely to have dramatic impacts on information availability and thus uncertainty in antipredator decisions in the modern world.
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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 | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.009 | 0.012 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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; both teacher heads agree on what is shown here.
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".