摘要：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 sequestration. The aim of this work is to evaluate the potential advantages of using apparent electrical conductivity (EC a )‐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 EC a maps that showed two different soil conditions—the presence or absence (high‐salinity conditions) of a strong correlation between EC a 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 EC a 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 EC a maps of the no‐till site, which allowed a smaller minimum sample size. When stratification failed due to the effect of salinity on EC a , StSRS efficiency was similar to SRS. These results suggest that EC a –directed sampling, regardless of knowing the relationships between EC a and soil properties, 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 EC a –directed sampling where strong patterns not related to SOC could lead to inappropriate stratification or suboptimal sample allocation.
关键词：BD; bulk density; CONS; conservation agriculture; CONV; conventional agriculture; ECa; soil apparent electrical conductivity; F1; Farm 1; F2; Farm 2; SOC; soil organic carbon; SRS; simple random sampling; SRSfix; simple random sampling using the same number of samples for each stratum; SRSopt; simple random sampling using an optimal number of samples per stratum; StSRS; stratified simple random sampling; StSRSfix; stratified simple random sampling using the same number of samples for each stratum; StSRSopt; stratified simple random sampling using an optimal number of samples per stratum.
