Soil health assessment under different soil and irrigation types in the agro-pastoral ecotone of northern China

Abstract

Soil health indexes (SHIs) are widely used methods on a regional or national scale to evaluate the status of soils. However, how to unbiasedly select appropriate indicators and score these indicators to obtain comprehensive SHI is still a big issue, due to the multiformity and complexity of soil. The goal of the study was to assess various cropland soil and irrigation types soil health using two scoring methods (linear and nonlinear scoring) and three indexes choosing methods (minimum data set MDS, revised minimum data set RMDS and total data set TDS) in loess plateau. Soil and irrigation types were Kastanozems soil and irrigation farming (KA-IL), Kastanozems soil and rainfed farming (KA-RL), Regosols soil and irrigation farming (RE-IL), Regosols soil and rainfed farming (RE-RL). Twenty-four soil indexes of soil chemical, physical and biological properties were determined from the top soil layer (0–20 cm). One-way ANOVA and PCA were used to select the MDS, RMDS and TDS. The finding results demonstrated that fifteen soil indicators were incorporated into TDS. In addition, the six soil indicators were selected to establish the RMDS (BD, EC, TN, MBC, LAP and ALP) and MDS (BD, SOC, TN, NO3--N, MBN and BG), respectively. The consistency in SHIs of the nonlinear scoring was better than that of the linear scoring method. The nonlinear scoring method with MDS was considered the optimal method to calculate the SHI due to its maximum values of CV, F and highest correlation coefficient with TDS. The SHI values of the different soil and irrigation types showed the following order: RE-IL > RE-RL > KA-IL > KA-RL. This study demonstrated that different soil and irrigation types noticeably affected the soil health in cropland of an agro-pastoral ecotone of northern China, and the SHI-NLM method was a sensitive and accurate model for quantitative assessment of soil health in this region.