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Depth Distribution Pattern of Soil Organic Carbon in Forest from Taowan Basin of Funiu Mountain Area

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  • NING, Xifeng
  • SONG, Lina
  • TIAN, Yaowu

Abstract

[Objectives] By testing applicability of SOC depth distribution model in geographical and climatic conditions of Funiu Mountain area, SOC depth distribution model in the region was established and applied. The constructed model was used to estimate SOC mass density in other regions, thereby obtaining SOC abundance distribution chart at different depths. [Methods] 165 soil sampling sites were selected from Quercus variabilis forest, Pinus tabulaeformis forest, mixed forest, and shrub forest in Taowan basin of Funiu Mountain area, to determine SOC content at different depths, study SOC depth distribution pattern of forest in Taowan basin of Funiu Mountain area, and assess SOC reserve at different depths. [Results] Average SOC density of Q. variabilis forest, P. tabulaeformis forest, mixed forest, and shrub forest at the depth of 0-20 cm was 7.92, 8.42, 8.14 and 9.67 kg/m2, and there was significant difference in SOC density between shrub forest and Q. variabilis forest, P. tabulaeformis forest, mixed forest (P<0.05), and SOC density of four kinds of vegetation all abruptly declined with soil depth increased. At the depth of 0-20 cm, correlation between SOC density and vegetation type, canopy density, clay content and sand content was significant, and the correlation with altitude was insignificant. When carbon density at the depth of 0-100 cm was used to describe regional SOC reserve, the estimated value was lower. The established space model could predict SOC density of forest. [Conclusions] The estimation of deep-layer SOC by the established model needed further consideration, and estimation method for special areas needed to be further demonstrated.

Suggested Citation

  • NING, Xifeng & SONG, Lina & TIAN, Yaowu, 2019. "Depth Distribution Pattern of Soil Organic Carbon in Forest from Taowan Basin of Funiu Mountain Area," Asian Agricultural Research, USA-China Science and Culture Media Corporation, vol. 11(06), June.
  • Handle: RePEc:ags:asagre:298717
    DOI: 10.22004/ag.econ.298717
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    Keywords

    Agribusiness;

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