Interpretation of data on the aggregate composition of typical chernozems under different land use by cluster and principal component analyses

Abstract

Cluster analysis and principal component analysis (PCA) have been used for the interpretation of dry sieving data. Chernozems from the treatments of long-term field experiments with different land-use patterns— annually mowed steppe, continuous potato culture, permanent black fallow, and untilled fallow since 1998 after permanent black fallow—have been used. Analysis of dry sieving data by PCA has shown that the treatments of untilled fallow after black fallow and annually mowed steppe differ most in the series considered; the content of dry aggregates of 10–7 mm makes the largest contribution to the distribution of objects along the first principal component. This fraction has been sieved in water and analyzed by PCA. In contrast to dry sieving data, the wet sieving data showed the closest mathematical distance between the treatment of untilled fallow after black fallow and the undisturbed treatment of annually mowed steppe, while the untilled fallow after black fallow and the permanent black fallow were the most distant treatments. Thus, it may be suggested that the water stability of structure is first restored after the removal of destructive anthropogenic load. However, the restoration of the distribution of structural separates to the parameters characteristic of native soils is a significantly longer process.

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Correspondence to V. A. Kholodov.

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Original Russian Text © V.A. Kholodov, N.V. Yaroslavtseva, V.I. Lazarev, A.S. Frid, 2016, published in Pochvovedenie, 2016, No. 9, pp. 1093–1100.

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Kholodov, V.A., Yaroslavtseva, N.V., Lazarev, V.I. et al. Interpretation of data on the aggregate composition of typical chernozems under different land use by cluster and principal component analyses. Eurasian Soil Sc. 49, 1026–1032 (2016). https://doi.org/10.1134/S1064229316090076

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Keywords

  • chernozems
  • air-dry aggregates
  • water-stable aggregates
  • soil structure
  • long-term field experiments
  • cluster analysis
  • principal component analysis (PCA)
  • Chernozems