‘Beware, I am large and dangerous’ – human listeners can be deceived by dynamic manipulation of the indexical content of agonistic dog growls

Péter Pongrácz, Petra Dobos, Borbála Zsilák,Tamás Faragó, Bence Ferdinandy

Behavioral Ecology and Sociobiology(2024)

引用 0|浏览0
暂无评分
摘要
Dishonest vocal signals about body size are rarely encountered, however, dogs are capable of modifying indexical information in their growls. This apparent acoustic body-size manipulation could be affected by the level of threat experienced by the dog. We tested whether this natural size manipulation actually affects how listeners assess the size of the dog, thus whether it could be considered as a successful indexical information manipulation. We requested human participants to assess dog growls, originally recorded when dogs encountered various ‘threatening strangers’ (of different sex, stature). The participants heard several sets of growl pairs, where they had to guess, which growl belonged to the ‘larger dog’. In the Control condition, dog growls originated from two different dogs in a pair; in the Test condition, growls of the same dog were presented pair by pair, always recorded in the presence of different threatening humans. Human listeners reliably picked the larger dog from two differently sized animals based on their growls alone. In the Test condition, participants thought that the dog was ‘larger’ when it was threatened by a female experimenter, and when the dog was growling at a larger sized human. We found that while growl length modulation was the main factor behind size-choice decisions in the case of female strangers, formant dispersion difference contributed the most when listeners chose which dog was the larger in the case of male opponents. Our results provide firsthand evidence of dogs’ functionally deceptive vocalizations towards humans, a phenomenon which has not been shown before in any interspecific scenario.
更多
查看译文
关键词
Dog,Human,Indexical information,Vocalizations,Signal manipulation,Deception
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要