Variable Breeding Strategies in a Fluctuating Environment: A Feeding Experiment in Eastern Chipmunks
Bibliographic record
Abstract
ABSTRACT Small mammals inhabiting pulsed‐resource environments, such as forests with intermittent seed masting of trees, often adjust their allocation to reproduction with the drastic fluctuations in food availability. They could, for instance, plastically allocate capital resources to reproduction when food availability is low or adopt an income breeding strategy when food availability is high. We investigated how eastern chipmunks (Tamias striatus), a food‐hoarding rodent strongly relying on the masting of beech trees (Fagus grandifolia), anticipate and respond to food pulses to reproduce. We supplemented a study site with sunflower seeds to buffer food availability for 2 years that were characterized by a non‐mast and a beech mast. We monitored chipmunks exploitation of the feeders, body mass, and reproductive activity. We tested if food‐supplemented females would reproduce in the absence of a beech mast. We compared those results with two control sites and 10 years of data on chipmunk reproduction. The probability of summer estrus significantly increased with the exploitation of feeders compared to the controls. Exploiting the feeders had a stronger effect than body mass on the probability of estrus. Still, beech masting had a broader effect on the probability of estrus across all sites than exploiting the feeders. Although most supplemented females showed oestrus during the non‐mast year, as opposed to non‐supplemented females, they did not fully reproduce despite their favorable body condition and the extensive hoard they accumulated. Those results suggest that summer reproduction in eastern chipmunks is not only financed by current food availability, revealing the complexity of plastic resource allocation in fluctuating environments.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 source (direct Gemma or distilled Codex), 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".