Abstract
Vocal communication is often used to signal willingness to escalate into a physical fight during territorial conflicts. In songbirds, starting to sing when an opponent already sings (song overlapping) has been suggested to signal aggressive intent (willingness to escalate). We used a multiyear data set to test whether song overlapping predicts aggressiveness in great tits, Parus major. Territorial males were subjected twice to a simulated territorial intrusion when their mate was in the egg-laying phase, and twice when she was incubating. Males were presented with a taxidermic mount and a noninteractive playback of a conspecific song near their nestbox. The experiment was conducted over 3 consecutive years, resulting in repeated measures for males that bred across multiple years. The estimated minimum approach distance to the intruder, a repeatable and heritable trait that predicts the likelihood of physical attack, was used as a measure of aggression. We determined the duration of song overlapping by the focal male relative to values expected by chance. Against expectations, we found that birds that over -lapped were less (rather than more) aggressive. In addition, variance partitioning demonstrated that this link resulted from a within-individual effect: when birds became less aggressive from one observation to the next, they also overlapped more. There was no among-individual effect: individuals that were on average more aggressive did not, on average, overlap either more or less than others. Our results thus imply that song overlapping is linked to aggression but opposite to expectations, and not among in-dividuals. Furthermore, the majority of birds overlapped at or below chance levels. Overall, song over-lapping may not signal aggressive intent but rather 'nonengagement', or result from interference avoidance, allowing aggressive residents to better hear an intruder's acoustic output during territorial intrusions. (c) 2021 The Association for the Study of Animal Behaviour. Published by Elsevier Ltd. All rights reserved.
Dokumententyp: | Zeitschriftenartikel |
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Fakultät: | Mathematik, Informatik und Statistik |
Themengebiete: | 500 Naturwissenschaften und Mathematik > 510 Mathematik |
ISSN: | 0003-3472 |
Sprache: | Englisch |
Dokumenten ID: | 99154 |
Datum der Veröffentlichung auf Open Access LMU: | 05. Jun. 2023, 15:30 |
Letzte Änderungen: | 13. Aug. 2024, 11:46 |