Avian Mobbing Response is Restricted by Territory Boundaries: Experimental Evidence from Two Species of Forest Warblers
Bibliographic record
Abstract
Abstract Predator mobbing has been viewed as an adaptation to reduce the risk of predation, however, factors influencing mobbing behaviour are still debated. We report on the results of an experiment with Dendroica caerulescens and Dendroica virens designed to determine (1) whether mobbing response by forest songbirds during the breeding season is restricted by territory boundaries, (2) the distance songbirds will move in response to anti‐predator mobbing calls, and (3) whether reproductive status, age, and time of the breeding season determine the distance moved to mob. We did not detect an effect of reproductive status, age, or time of breeding season on the distance moved by birds to mob. All birds responded to the mobbing playback within their territory (defined by territorial defence in relation to specific song playbacks). The maximum distance moved within a territory to engage in mobbing ranged from 25 to 175 m ( = 72 ± 6 m). Three of 37 birds responded to playbacks outside their territory boundaries. In all three cases, maximum movement distances outside territories were short (25 m). Thus, for two species of warblers, mobbing is highly constrained by territory boundaries during the breeding season. This finding is congruent with arguments that mobbing is primarily a selfish behaviour, at least with respect to conspecifics. Our results also provide support for the ‘move‐on’ hypothesis.
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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 | 0.001 | 0.001 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".