Individual determinants of social foraging tactic use when resources are defendable: An experiment with zebra finches
Bibliographic record
Abstract
In a social foraging context where individuals can search either for food (i.e. produce) or for opportunities to join (i.e. scrounge), bold individuals, generally, tend to produce more than shy individuals. Yet, the underlying cause of this link remains poorly understood. In particular, bold individuals might rely more on the producer tactic because they have less chance to detect joining opportunities compared to shy individuals or because they prefer more risky and uncertain behavioural tactics. To assess the importance of both mechanisms, we conducted a laboratory experiment with zebra finches (Taenyopigia guttata) that were observed while searching for defendable food patches using either the producer or the scrounger tactic, when their arrival order on the grid was either free or imposed by the experimenter. As anticipated, we detected a strong effect of neophobia on producer-scrounger tactic use, but contrary to most previous experiments in which food patches were not defendable, shy individuals, in the present study, relied more on the producer tactic. In addition, we found that arrival order had no significant effect on foraging tactic use in bold and shy individuals. Thus, our results support the hypothesis that producer-scrounger tactic use would not be determined by the ability of individuals to detect scrounging opportunities, but rather by their tolerance to uncertainty and risk. Furthermore, our findings have important evolutionary implications as they suggest that temporal and/or spatial heterogeneity in resource distribution, through influencing the success of each behavioural type, would contribute in maintaining personality differences within populations.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".