Soil quality indices following long-term conservation pasture management practices

Monitoring long-term grazing management practices influence on soil quality (SQ) is essential to ensuring pasture sustainability, which is the largest land use in world agroecosystems. The aim of this study was to quantify SQ based on long-term (15-years) conservation pasture management and landscape position using the Soil Management Assessment Framework (SMAF). Treatments were setup in 15 watersheds (0.14 ha each, 8% slope) in a completely randomized design with five pasture management practices: continuously grazed (CG), hayed (H), rotationally grazed (R), rotationally grazed with an unfertilized buffer strip (RB), and rotationally grazed with an un-grazed, unfertilized, and fenced riparian strip (RBR). Each watershed was divided in three zones (A, B, and C), with the riparian buffer strip (RBS) corresponding to the RBR D zone. Selected soil chemical, physical, and biological properties were determined on soil samples collected in 2017 (0−15 cm depth) per zone. Total P, organic C, and total suspended solids (TSS) were measured in 2017 runoff samples. The SMAF SQ scores were evaluated individually and as an overall SQ index (SQI). Exponential models were used to investigate the relationship between SQI and total P, organic C runoff, and TSS loads. Continuously grazed watersheds had improved soil fertility, with greater nutrient concentration at the shoulder landscape position (zone A). Degradation of soil physical properties were not observed for this practice. After 15 years of continuous management, CG and R watersheds had the greatest SQI (7.07 and7.05, respectively), not differing from RBR (6.93), likely owing to cattle manure deposition for these treatments. Increased SQI in RBS (7.33) improved SQI for RBR watersheds. Differences in SQI were mostly driven by changes in pH, electrical conductivity, soil P and K concentrations. The exponential models indicated that 34 and 28 % of the variation in P and TOC runoff loads, respectively, can be explained by the SMAF SQI (p