Diversity of the Vocal Signals of Concave-Eared Torrent Frogs (Odorrana tormota): Evidence for Individual Signatures
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.
Document Type: Research Article
Affiliations: 1: Department of Molecular and Integrative Physiology & Beckman Institute, University of Illinois, Urbana, IL, USA 2: Department of Biology, University of Utah, Salt Lake City, UT, USA 3: Department of Ecology and Evolutionary Biology, University of California, Los Angeles, CA, USA 4: State Key Laboratory of Brain and Cognitive Science, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China 5: Shanghai Institutes of Biological Sciences, Chinese Academy of Sciences, Beijing, China
Publication date: 2009-11-01