Effects of seed quality and abundance on the foraging behavior of deer mice
Bibliographic record
Abstract
Seeds are an important food resource for many rodents, but the decision to consume or cache seeds when they are encountered can be influenced by numerous factors such as their abundance, nutritional value, and plant secondary compound (PSC) contents. Although previous studies on rodent foraging behaviors have focused on the effects of specific seed characteristics, the combined impact of seed quality and abundance is unclear. Here, we used artificial food patches in the field to examine the foraging behaviors of deer mice (Peromyscus maniculatus) in response to varying abundances of high- and low-nutritional-quality conifer seeds. We also used a variant of giving-up densities to assess mouse perception of the quality of seeds in patches. Mice treated white spruce (Picea glauca) seeds as a high-quality food source in the field, whereas subalpine fir (Abies lasiocarpa) seeds were treated as low quality, corresponding to their nutrient and PSC contents. Observations of foraging behaviors showed a strong interaction between seed abundance and quality on foraging decisions. Caching, but not consumption, rates of spruce seeds varied with seed abundance, but abundance did not influence the frequency or nature of use of fir seeds, which were mostly ignored. High abundance did not confer any value to fir seeds, and even when exaggeratedly abundant relative to naturally available seed densities, mice almost completely disregarded these low-quality seeds as a valuable resource for both current and future use. Our results highlight the relative importance of seed quality in this foraging interaction.
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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) | 0.000 | 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".