Pulsed resources and the coupling between life‐history strategies and exploration patterns in eastern chipmunks (<i><scp>T</scp>amias striatus</i>)
Bibliographic record
Abstract
Understanding the causes of animal personality (i.e. consistent behavioural differences) is a major aim of evolutionary studies. Recent theoretical work suggests that major personality traits may contribute to evolutionary trade-offs. However, such associations have only been investigated in a few study systems, and even less so in free ranging animal populations. Eastern chipmunks exhibit consistent individual differences in exploration, ranging from slow to fast. Birth cohorts also experience dramatic differences in age at first breeding opportunity due to annual differences in beech mast. Individuals may breed for the first time at 24, 33 or 50% of their average life span, depending on year of birth. Here, we used data from a long-term survey on a wild population to investigate the relationship between reproductive life history and consistent individual differences in exploration. We determined whether predictable differences in age at first breeding opportunity among birth cohorts were associated with exploration differences and favoured individuals with different exploration. Birth cohorts with a predictably earlier age at first breeding opportunity were faster explorers on average. Slower explorers displayed their highest fecundity (females) or highest fertilization success (males) later in their life compared with faster explorers. Overall, slow explorers attained a higher lifetime reproductive success than fast explorers when given an opportunity to reproduce later in their life. Our results suggest that the timing of mating seasons, associated with fluctuating food abundance, may favour individual variation in exploration and maintain population variation through its effects on reproductive life history. Together, our result shed light on how fluctuation in ecological conditions may maintain personality differences and on the nature of the relationships between animal personality and life history.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".