谷歌浏览器插件
订阅小程序
在清言上使用

Diversity of the Vocal Signals of Concave-Eared Torrent Frogs (odorrana Tormota): Evidence for Individual Signatures

Ethology(2009)

引用 63|浏览81
暂无评分
摘要
Male concave-eared torrent frogs (Odorrana tormota) have an unusually large call repertoire and have been shown to communicate ultrasonically. We investigated the individual specificity of male advertisement calls in order to explore the acoustic bases of individual recognition, which was demonstrated in an accompanying study. Vocalizations of 15 marked males were recorded in the field. A quantitative analysis of the signals revealed eight basic call-types. Two of them (the single- and multi-note long-calls) were investigated in more detail. Long-calls were characterized by pronounced and varying frequency modulation patterns, and abundant occurrence of nonlinear phenomena (NLP), i.e., frequency jumps, subharmonics, biphonations and deterministic chaos. The occurrence of NLP was predictable from the contour of the fundamental frequency in the harmonic segment preceding the onset of the NLP, and this prediction showed individual-specific patterns. Fifteen acoustic variables of the long calls were measured, all of which were significantly different among individuals, except biphonic segment duration. Discriminant function analysis (DFA) showed that 54.6% of the calls could be correctly assigned to individual frogs. The correct classification was above chance level, suggesting that individual specificity of calls underlie the ability of males to behaviorally discriminate the vocal signals of their neighbors from those of strangers, a remarkable feat for a frog species with a diverse vocal repertoire. The DFA classification results were lower than those for other anurans, however. We hypothesize that there is a tradeoff between an increase in the fundamental frequency of vocalizations to avoid masking by low-frequency ambient background noise, and a decrease in individual-specific vocal tract information extractable from the signal.
更多
查看译文
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