4.7 Article

Control of soil organic carbon under karst landforms: A case study of Guizhou Province, in southwest China

Journal

ECOLOGICAL INDICATORS
Volume 145, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.ecolind.2022.109624

Keywords

Soil organic carbon; Spatial variability; Karst landform; Determinants; Soil carbon sequestration

Funding

  1. China Post- doctoral Science Foundation [[2021] 302]
  2. Growth Project of Young Scientific and Technological Talents in Universities of Guizhou Province [2020M673582XB]

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This study analyzed the spatial heterogeneity of soil organic carbon (SOC) in Guizhou Province and found that the content of SOC decreased from west to east, with low-value areas mostly located in the south and north regions. Altitude, slope gradient, and rock exposure rate had significant impacts on SOC levels. The findings of this research are important for formulating carbon sink strategies.
Global karst landforms account for about 15 % of the land area. The development of karst landforms in southwest China accounts for>1/3 of the country's land area, and is considered to be an important carbon storage with considerable carbon sequestration potential to alleviate global warming. Clarifying the response mechanism of soil organic carbon (SOC) to different controlling factors is of great significance to formulate and implement regional carbon sink strategies. Based on 517 soil samples in Guizhou Province, this study used geostatistical methods to analyze the spatial heterogeneity of SOC in Guizhou Province. The effects of altitude, land use, soil type, slope direction, slope position, slope gradient and rock exposure rate on the spatial variability of SOC in karst areas were quantitatively compared by statistical analysis methods. The results showed that the mean value of SOC content in Guizhou Province was 19.59 g/kg, and the coefficient of variation was 69.11 %, showing moderate-intensity variation. Spatially, the SOC content in Guizhou Province showed a declining trend from west to east, with the low-value areas predominantly distributed in the south and north areas. The semi-variogram model showed that the nugget coefficient C-0/(C-0 + C) was < 25 %, and the SOC in the study area had a strong spatial autocorrelation. The artificial neural network analysis showed that the important coefficients of each independent variable on SOC level were as follows: altitude (0.355) > slope gradient (0.255) > rock exposure rate (0.166) > land use (0.08) > slope position (0.059) > slope direction (0.043) > soil type (0.041). This research suggests that the provincial government should pay attention to the control of rocky desertification and the development of modern low-carbon agriculture in the work of increasing soil carbon sequestration.

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