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Entomological Review

, Volume 92, Issue 3, pp 296–304 | Cite as

The fauna and ecology of butterflies (Lepidoptera, Rhopalocera) of the Kanin Peninsula and Kolguev Island

  • I. N. BolotovEmail author
Article

Abstract

A total of 29 butterfly species in the forest-tundra and 14 species in the hypoarctic tundra were recorded on the Kanin Peninsula. Six species of butterflies were identified on Kolguev Island. The data on the fauna and distribution of species in the forest-tundra of the Kanin Peninsula are generally typical of this natural zone (Chernov and Tatarinov, 2006). The faunas of the northern part of the Kanin Peninsula and the southern part of Kolguev Island comprise fewer species, including those of the Arctic complex. This phenomenon is related to the coastal position of the regions, the cool summer and strong winds. On Kolguev Island, seasonal migrants appear simultaneously with the local species or considerably later. The most abundant species in the forest-tundra of the Kanin Peninsula are Erebia disa, Oeneis norna, Clossiana freija, Pieris napi, and Vacciniina optilete. The dominant species in southern tundra localities are Erebia euryale, E. pandrose, and Boloria aquilonaris, which coincides with the result of the 1903 research (Poppius, 1906). Only the dewy ringlet Erebia pandrose was recorded regularly in the south of Kolguev Island in 2009. In spite of the impoverished fauna of Rhopalocera some butterfly species clearly prevail in abundance and inhabit a wide range of biotopes, which agrees with the concept of compensatory mechanisms (Chernov, 2005). A high abundance of E. pandrose is a specific feature of the northern part of the Kanin Peninsula and Kolguev Island, pointing to the connection of the biota of these territories with the Subarctic regions of Fennoscandia.

Keywords

Entomological Review Butterfly Species Dwarf Birch Southern Tundra Butterfly Fauna 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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© Pleiades Publishing, Ltd. 2012

Authors and Affiliations

  1. 1.Institute of Ecological Problems of the North, Ural DivisionRussian Academy of SciencesArkhangelskRussia

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