Soil apparent electrical conductivity-directed sampling design for advancing soil characterization in agricultural fields

Abstract

The “4 per 1,000” initiative calls for land management practices that increase soil organic C (SOC). Despite an imperative for accurate SOC measurement, several methodological issues may complicate the verification of C seques-tration. The aim of this work is to evaluate the potential advantages of using apparent electrical conductivity (ECa)-directed sampling to deep (0–90 cm) SOC stock assessment. We compared simple random sampling (SRS) and stratified random sampling (StSRS), with either a fixed or optimized number of samples, in fields managed under conservation agriculture and conventional tillage. The stratification in StSRS was built from ECa maps that showed two different soil conditions—the presence or absence (high-salinity conditions) of a strong correlation between ECa and soil properties. Treatment and sampling design effects on SOC estimates were tested through a mixed-model approach. Sampling efficiency was calculated by classical and bootstrap methods. Results suggested that when ECa has a strong relationship with soil properties, StSRS was more efficient than SRS, especially when using an optimal number of samples per stratum. Stratification was based on ECa maps of the no-till site, which allowed a smaller minimum sample size. When stratification failed due to the effect of salinity on ECa, StSRS efficiency was similar to SRS. These results suggest that ECa –directed sampling, regardless of knowing the relationships between ECa and soil proper-ties, is a win-win solution to advance soil characterization and SOC stock estimation in agricultural fields of the low Venetian plain. However, further research should investigate ECa –directed sampling where strong patterns not related to SOC could lead to inappropriate stratification or suboptimal sample allocation.