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Journal of Soils and Sediments

, Volume 19, Issue 10, pp 3427–3441 | Cite as

Soil organic carbon in semiarid alpine regions: the spatial distribution, stock estimation, and environmental controls

  • Meng Zhu
  • Qi FengEmail author
  • Mengxu Zhang
  • Wei Liu
  • Ravinesh C. Deo
  • Chengqi Zhang
  • Linshan Yang
Soils, Sec 1 • Soil Organic Matter Dynamics and Nutrient Cycling • Research Article
  • 164 Downloads

Abstract

Purpose

Soil organic carbon (SOC) in alpine regions is characterized by a strong local heterogeneity, which may contribute to relatively large uncertainties in regional SOC stock estimation. However, the patterns, stock, and environmental controls of SOC in semiarid alpine regions are still less understood. Therefore, the purpose of this study is to comprehensively quantify the stock and controls of SOC in semiarid alpine regions.

Materials and methods

Soils from 138 study sites across a typical semiarid alpine basin (1755–5051 m, ~1 × 104 km2) are sampled at 0–10, 10–20, 20–40, and 40–60 cm. SOC content, bulk density, soil texture, and soil pH are determined. Both a classical statistical model (i.e., a multiple linear regression, MLR) and a machine learning technique (i.e., a random forest, RF) are applied to estimate the SOC stock at a basin scale. The study further quantifies the environmental controls of SOC based on a general linear model (GLM) coupled with the structural equation modeling (SEM).

Results and discussion

SOC density varies significantly with topographic factors, with the highest values occurring at an elevation zone of ~3400 m. The results show that the SOC is more accurately estimated by the RF compared to the MLR model, with a total stock of 219.33 Tg C and an average density of 21.25 kg C m−2 at 0–60 cm across the study basin. The GLM approach reveals that the topography is seen to explain about 58.11% of the total variation in SOC density at 0–10 cm, of which the largest two proportions are attributable to the elevation (44.32%) and the aspect factor (11.25%). The SEM approach further indicates that, of the climatic, vegetative, and edaphic factors examined, the mean annual temperature, which is mainly shaped by topography, exerts the most significant control on SOC, mainly through its direct effect, and also, through indirect effect as delivered by vegetation type.

Conclusions

The results of this study highlight the presence of high stocks of organic carbon in soils of semiarid alpine regions, indicating a fundamental role played by topography in affecting the overall SOC, which is mainly attained through its effects on the mean annual temperature.

Keywords

Random forest Semiarid alpine regions Soil organic carbon Structural equation modeling Topography 

Notes

Funding information

This work was supported by the National Key R&D Program of China (No. 2017YFC0404305), the National Natural Science Fund of China (No. 41771252, 41801015), the Major Program of the Natural Science Foundation of Gansu province, China (No. 18JR4RA002), the Grants from the Key Project of the Chinese Academy of Sciences (No. QYZDJ-SSW-DQC031), the International Science and Technology Cooperation Project of Gansu province (No. 17YF1WA168), and the Foundation for Excellent Youth Scholars of NIEER, CAS (51Y851D61).

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Meng Zhu
    • 1
    • 2
  • Qi Feng
    • 1
    Email author
  • Mengxu Zhang
    • 2
  • Wei Liu
    • 1
  • Ravinesh C. Deo
    • 3
  • Chengqi Zhang
    • 1
  • Linshan Yang
    • 1
  1. 1.Key Laboratory of Ecohydrology of Inland River BasinNorthwest Institute of Eco-Environment and Resources, Chinese Academy of SciencesLanzhouChina
  2. 2.University of Chinese Academy of SciencesBeijingChina
  3. 3.School of Agricultural Computational and Environmental Sciences, Centre for Sustainable Agricultural Systems and Centre for Applied Climate SciencesUniversity of Southern QueenslandSpringfieldAustralia

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