Song Divergence in the Group of “Brownish” Chiffchaff Forms (Phylloscopus collybita sensu lato) View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2021-12-17

AUTHORS

I. Yu. Il’ina, I. M. Marova, P. V. Kvartalnov, V. V. Ivanitskii

ABSTRACT

Study of the geographic variability of bird song is important for understanding the evolution and taxonomic structure of polytypic species with extensive and complex distribution areas. The chiffchaff is among such species. Several allopatric and parapatric forms inhabit the space of its trans-Palaearctic range. They vary in body size and vocalization, and, in accordance with the plumage color, they can be divided into two groups: “greenish” and “brownish.” We made a comparative analysis of the song of three allopatric “brownish” forms (lorenzii, sindianus, and tristis), as well as one “greenish” form (caucasicus), which is sympatric with lorenzii (the only case of almost complete sympatry of different forms of chiffchaff). Significant differences were found in a number of phonetic and syntactic song parameters. Complete separation of the forms studied can be made according to the maximum frequency of the song and the speed of its performance (the number of notes per second). The sindianus form stands out for its relatively high-frequency and broadband song. The tristis form shows the lowest frequency song and the narrowest range. It is also the leader in the speed of performance of the song (up to 6–7 notes/s). The number of notes with a rising modulation is the maximum in tristis and the minimum in lorenzii; no such notes exist in caucasicus, like in other “greenish” chiffchaffs. The differences are discussed in light of the hypothesis of “acoustic adaptation” and in connection with the taxonomic relationships between the different forms of chiffchaff. More... »

PAGES

1067-1074

Identifiers

URI

http://scigraph.springernature.com/pub.10.1134/s1062359021070141

DOI

http://dx.doi.org/10.1134/s1062359021070141

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1143980484


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