Spatial distribution characteristics and influencing factors of soil organic carbon based on the geographically weighted regression model

Environ Monit Assess. 2024 Oct 21;196(11):1083. doi: 10.1007/s10661-024-13279-6.

Abstract

Quantifying the effects of environmental factors on soil organic carbon and spatial distribution is fundamental to soil quality regulation, restoration, and response to climate change. The present study aims to explore the spatial distribution characteristics of the soil organic carbon (SOC) contents in Anhui Province, China, based on national soil data. In addition, we used the geographically weighted regression (GWR) model to quantify the influence degrees of environmental factors on the soil organic carbon density (SOCD). The results showed that the spatial distribution of SOCD in Anhui Province in both 1985 and 2018 was characterized by high in the south and low in the north. The GWR model prediction results of the 0-30 cm SOCD showed local coefficients of determination (local R2) ranging from 0.21 to 0.96 and 0.14 to 0.96 in 1985 and 2018, respectively. Therefore, the predicted results were effective in evaluating the overall spatial distribution of the SOCD in Anhui Province. The regression coefficients of the normalized difference vegetation index (NDVI) and air temperature ranged from - 0.39 to 5.67 and - 0.17 to 3.11, respectively, demonstrating their strong controlling effects on the spatiotemporal variations in the 0-30 cm SOCD in Anhui Province.

Keywords: Environmental factors; Geographically weighted regression; Local regression; Soil organic carbon; Spatial heterogeneity.

MeSH terms

  • Carbon* / analysis
  • China
  • Climate Change
  • Environmental Monitoring*
  • Soil* / chemistry
  • Spatial Regression

Substances

  • Soil
  • Carbon