Abstract：
:Vocal individual identification has been demonstrated in many animals, with discriminant function analysis (DFA) and spectrographic cross-correlation (SPCC) being the two most frequent methods. Successful vocal individual identification requires high among-individual differences and within-individual stability over time for vocal features. Lack of vocal individual identification is common in songbirds with complex songs, and most vocal individual identification studies are made in bird species with simple vocalizations. Here, we applied vocal individual identification with the two methods on a songbird, green-backed flycatcher Ficedula elisae. We based its complex songs by division into first, second, and third phrases. DFA resulted in a correct distinction rate of 94.5 % between one first-phrase type and another. SPCC similarity was significantly higher within than among types for first and second phrases, respectively. For first-phrase types with recordings from different days during a breeding season, the correct DFA rate was 87.1 %. SPCC similarity within type changed significantly among days, but was still significantly higher than that among types. In conclusion, first phrases of the complex songs met the two requirements and could be effectively used for vocal individual identification in this species. This study filled a gap in vocal individual identification in birds with complex songs.
journal_name
Behav Processesjournal_title
Behavioural processesauthors
Chen G,Xia C,Zhang Ydoi
10.1016/j.beproc.2020.104063subject
Has Abstractpub_date
2020-04-01 00:00:00pages
104063eissn
0376-6357issn
1872-8308pii
S0376-6357(19)30458-9journal_volume
173pub_type
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