Distribution characteristics and prediction model of farmland soil organic carbon in eastern China

Abstract

Soil organic carbon (SOC) plays a key role in soil improvement, carbon sequestration, and increasing crop yield. In this study, the distribution characteristics and the influence of hydrothermal conditions on farmland SOC content in eastern China were studied. The results showed that the spatial heterogeneity of SOC content in eastern China was obvious. In the area with the mean average temperature (MAT) below 10.42 ℃, the SOC content was negatively correlated with MAT and ≥10 °C accumulated temperature, but positively correlated with the ratio of precipitation to temperature (P/T). In the area with the MAT between 10.42 ℃ and 20.75 ℃, the SOC content was negatively correlated with mean average precipitation (MAP), MAT, P/T and ≥10 °C accumulated temperature. In the area with the MAT above 20.75 ℃, the SOC content was negatively correlated with MAT and ≥10 °C accumulated temperature, but positively correlated with MAP and P/T. In the area with the MAP below 400 mm, the SOC content was negatively correlated with P/T, but positively correlated with MAP, MAT and ≥10 °C accumulated temperature. In the area with the MAP between 400 mm and 800 mm, the SOC content was negatively correlated with P/T, but positively correlated with MAT and ≥10 °C accumulated temperature. In the area with the MAP more than 800 mm, the SOC content was negatively correlated with MAP, MAT, P/T and ≥10 °C accumulated temperature. Based on the above results, a model for predicting SOC content was established. This is of great significance for the rapid estimation of SOC content on a regional large scale.

Mapping Soil Organic Carbon in Floodplain Farmland: Implications of Effective Range of Environmental Variables

“…This method fits the relationship between SOC and environmental variables and then applies this relationship to predict the SOC at the unsampled region. Soil types, climate, land use type, vegetation index, terrain, parent materials, and distance factors have been widely used in SOC mapping [11][12][13][14][15]. However, many soil properties, such as soil texture, nutrient content, and pH, are associated with the SOC content [16][17][18], but they are rarely used as covariates in SOC mapping due to the lack of spatial distribution maps.…”