4.4 Article

Land-use types and slope topography affect the soil labile carbon fractions in the Loess hilly-gully area of Shaanxi, China

Journal

ARCHIVES OF AGRONOMY AND SOIL SCIENCE
Volume 66, Issue 5, Pages 638-650

Publisher

TAYLOR & FRANCIS LTD
DOI: 10.1080/03650340.2019.1630824

Keywords

Land-use change; soil erosion; soil organic carbon; slope position; vegetation restoration

Funding

  1. National Key Research and Development Program of China [2017YFC0504704]
  2. National Natural Science Foundation of China [41601092, 41601017, 41501091]
  3. National Geological Prospecting Special Project [DD20190504]
  4. Shaanxi Provincial Technology Innovation Guidance Project [2017CGZH-HJ-06]
  5. Shaanxi Province Innovation Talent Promotion Project Technology Innovation Team [2018TD-037]
  6. National Geological Prospecting special [DD20190504]

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This study evaluated the effects of vegetation restoration on soil organic carbon (SOC) and its fractions, by exploring the SOC, particulate organic C (POC), mineralizable organic C (MOC), and light fraction organic C (LFOC) of three sloping land-use types (sloping farmland, forestland and grassland) and at four locations along each hillslope (30, 60, 90 and 120 m from the hilltop). Soil Cs-137 was measured to calculate the soil erosion rate. The SOC, POC, MOC, and LFOC were significantly higher (p < 0.05) in the forestland and grassland than the sloping farmland. The SOC, LFOC, MOC, and POC of the grassland and forestland were higher in the lower than in the upper parts of the hillslope. The Cs-137 activity was associated with soil loss rate and related to the redistribution of soil carbon fractions along the hillslope. The distribution of the soil carbon fractions and soil erosion in the forestland and grassland showed opposing trends. The soil labile organic carbon distribution and erosion of sloping farmland displayed a consistent distribution trend. Land-use changes and erosion were the most important factors that governed soil labile organic carbon: accounting for 21.7% and 25.7% of the observed variances, respectively.

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