Quantitative evaluation of soil health based on a minimum dataset under various short-term crop rotations on the Canadian prairies

Abstract

Maintaining and improving soil health (SH) is essential for the long-term sustainability and productivity of agriculture, notably in the face of climate change. This study addressed the challenge of selecting appropriate soil indicators, scoring methods, and indexing approaches for SH evaluation under no-till crop rotations. This study aimed to develop minimum datasets (MDS) and assess SH in six crop rotations (denoted as conventional, diversified, high-risk and high-reward, market-driven, pulse-oilseed intensified, and soil health-enhanced rotations) at three sites on the Canadian prairies. Fourteen soil indicators in the total dataset (TDS) were examined, encompassing both chemical (0–7.5 cm depth) and physical (5–10 cm depth) properties. Principal component analysis (PCA) identified MDSs from the TDS. Two scoring [linear (L) and non-linear (NL)] and two SH indexing approaches [additive (A) and weighted additive (WA)] were used to calculate the SH index (SHI). One-way ANOVA evaluated the SHI among crop rotations. The PCA revealed variations in the number of indicators in the MDS across sites, with soil organic carbon, bulk density, macroporosity, and plant-available water capacity as the common indicators for MDS across sites. Other indicators such as particulate organic matter carbon, aggregate stability, field capacity, and microporosity were found to be important, depending on the site. The non-linear weighted additive SH indexing (SHI.NLWA) proved to be the most sensitive and effective for differentiating among crop rotations in the short-term across study sites (R2 = 0.89–0.94, P < 0.05). Crop rotations significantly influenced SHI, with the diversified and high-risk and high-reward rotations having the highest SHI at Lethbridge and Scott, respectively. Overall, the diversified rotation at Lethbridge and Swift Current, along with the high-risk and high-reward rotation at Scott, exhibited better soil function than other rotations. Monitoring SHI over time and selecting crop rotations that improve SH can collectively enhance soil functions and agroecosystem productivity.