Advertisement

Contemporary Problems of Ecology

, Volume 2, Issue 2, pp 97–102 | Cite as

Component diversity of the soil cover in the Chuya depression, Gorny Altai

  • E. N. Smolentseva
Article
  • 26 Downloads

Abstract

The high-mountain Chuya depression (Gorny Altai) was studied in 2006–2008. New data on the diversity of soil components of the soil cover in terms of the new Russian soil classification system have been obtained. Some relations of soil components to biotic and abiotic components of high-mountain steppe terrestrial ecosystems have been revealed.

Key words

soil formation soil classification arid soils halogenesi 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Soils of Gorno-Altaisk Autonomous Oblast (Nauka, Siberian Branch, Novosibirsk, 1973) [in Russian].Google Scholar
  2. 2.
    V. I. Volkovintser, Steppe Cryoarid Soils (Nauka, Siberian Branch, Novosibirsk, 1978) [in Russian].Google Scholar
  3. 3.
    V. A. Khmelev, in Genesis, Evolution, and Geography of West Siberian Soils (Nauka, Siberian Branch, Novosibirsk, 1978), pp. 193–204 [in Russian].Google Scholar
  4. 4.
    I. D. Zol’nikov and A. A. Mistryukov, Quaternary Deposits and Topography of Valleys of the Chuya and Katun Rivers (Parallel’, Novosibirsk, 2008) [in Russian].Google Scholar
  5. 5.
    Classification and Diagnostics of Soils of Russia (Oikumena, Smolensk, 2004) [in Russian].Google Scholar
  6. 6.
    Field Identification Guide of Soils in Russia (Dokuchaev Institute of Soil, Moscow, 2008) [in Russian].Google Scholar
  7. 7.
    L. A. Vorob’eva, Chemical Analysis of Soils (Mosk. Gos. Univ., Moscow, 1998) [in Russian].Google Scholar
  8. 8.
    M. I. Gerasimova, Soil Geography of the USSR (Vysshaya Shkola, Moscow, 1987) [in Russian].Google Scholar

Copyright information

© Pleiades Publishing, Ltd. 2009

Authors and Affiliations

  1. 1.Institute of Soil Science and Agrochemistry, Siberian BranchRussian Academy of SciencesNovosibirskRussia

Personalised recommendations