Assessment of soil health and identification of key soil health indicators for five long-term crop rotations with varying fertility management

Long-term agricultural management practices affect soil health, but identifying measurable soil properties that reflect soil health (soil health indicators – SHIs) is a challenge. Five long-term (>40 years) crop rotations with varying cropping frequency, crop diversity, fertility and lime treatments were sampled as part of the Soil Heath Institute's North American Project to Evaluate Soil Health Measurements (NAPESHM) at the University of Albert Breton Plots research site in 2019, and additional samples were collected in 2020 for additional indicator measurements. Many soil health frameworks such as the Cornell Assessment of Soil Health (CASH) generate soil health scores based on key SHIs identified from a large, multivariate database using principal component analysis (PCA). For our dataset, we adopted the PCA-based approach with the following questions in mind: 1) Were the key SHIs that explain a large portion of the total dataset variance also the key SHIs that were most sensitive to the rotation, fertilizer and lime management? 2) Were the key SHIs identified with PCA associated with soil health, soil fertility or inherent soil characteristics? We identified seven key SHIs with PCA that explained 86.8% of the database variance. Results of a permutational MANOVA suggested that crop rotation and fertilizer management significantly influenced the total variance of the identified key SHIs. Four of the seven identified key SHIs primarily reflected soil health and three SHIs primarily reflected soil fertility and/or inherent soil properties but were also positively associated with soil health at this site. Overall, the PCA-based approach used to develop the site-specific soil health score (SSpeSHS) proved to be a helpful screening tool for the identification of key SHIs that are sensitive to soil-health-promoting management practices from a large dataset.