Food storage in a changing world: implications of climate change for food-caching species
Bibliographic record
Abstract
Food caching is a behavioural strategy used by a wide range of animals to store food for future use. When food is stored, it is susceptible to environmental conditions that can lead to spoilage via microbial proliferation or physical and chemical processes. Given that the nutrition gained from consuming cached food will almost always be less than consuming it immediately upon capture, the degree of degradation will play a central role in determining the ecological threshold at which caching is no longer profitable. Our framework proposes that the degree of susceptibility among caching species is based primarily on the duration of storage, and the perishability of stored food. We first summarize the degree of susceptibility of 203 vertebrate caching species. Thirty-eight percent (38%) of these species are long-term cachers (>10 days) but only 2% are both long-term cachers and store highly perishable food. We then integrate insights from the fields of applied food science and plant biology to outline potential mechanisms by which climate change may influence food-caching species. Four climatic factors (temperature, number of freeze-thaw events, deep-freeze events and humidity) have been shown to affect the degradation of food consumed by humans and are also expected to influence the quality of perishable food cached in the wild. Temperature and moisture are likely important factors influencing seemingly nonperishable seeds. Although we are able to provide broad classifications for caching species at risk of climate change, an improved understanding of how environmental conditions affect the quality and persistence of cached food may allow us to better predict the impact of changing climatic conditions on the fitness of food-caching animals.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".