To eat and not be eaten: diurnal mass gain and foraging strategies in wintering great tits
Bibliographic record
Abstract
Adaptive theory predicts that the fundamental trade-off between starvation and predation risk shapes diurnal patterns in foraging activity and mass gain in wintering passerine birds. Foragers mitigating both types of risk should exhibit a bimodal distribution (increased foraging and mass gain early and late in the day), whereas both foraging and mass gains early (versus late) during the day are expected when the risk of starvation (versus predation) is greatest. Finally, relatively constant rates of foraging and mass gain should occur when the starvation–predation risk trade-off is independent of body mass. Using automated feeders with integrated digital balances, we estimated diurnal patterns in foraging and body mass gain to test which ecological scenario was best supported in wintering great tits Parus major . Based on data of 40 consecutive winter days recording over 12 000 body masses of 28 individuals, we concluded that birds foraged and gained mass early during the day, as predicted by theory when the starvation–predation risk trade-off is mass-dependent and starvation risk outweighs predation risk. Slower explorers visited the feeders more often, and decreased their activity along the day more strongly, compared with faster explorers, thereby explaining a major portion of the individual differences in diurnal patterning of foraging activity detected using random regression analyses. Birds did not differ in body mass gain trajectories, implying both that individuals differed in the usage of feeders, and that unbiased conclusions regarding how birds resolve starvation–predation risk trade-off require the simultaneous recording of foraging activity and body mass gain trajectories. Our study thereby provides the first unambiguous demonstration that individual birds are capable of adjusting their diurnal foraging and mass gain trajectories in response to ecological predictors of starvation risk as predicted by starvation–predation risk trade-off theory.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".