Enzymatic and Microbial Indicators Contribute to the Sensitivity of Multidimensional Soil Health Indices Under Contrasting Land Uses in Subtropical Brazil

Enzymatic and microbial indicators are increasingly recognized as early diagnostics of soil functional changes, yet their contribution to composite soil health indices (SHIs) remains poorly quantified. This study tested whether five multidimensional SHIs consistently detect within-site management contrasts in Paraná, Brazil, and assessed the role of enzymatic and microbial parameters in index sensitivity. Twenty-five indicators - including four enzyme activities (β-glucosidase, arylsulfatase, acid phosphatase, urease), microbial biomass carbon, basal respiration, metabolic quotient, and Bradford-reactive soil compounds - were evaluated in the 0.00–0.10 m layer across seven sites each comprising two contrasting management units with nine node-level samples per unit (n = 126), under contrasting land uses. Indicators were standardized to unitless scores (0–1) and aggregated using five approaches differing in data selection and weighting. Index structure was described by variance partitioning and Random Forest regression, and management discrimination was assessed by rank-biserial effect sizes and a leave-one-site-out Random Forest classification. PCA-based indices (SHI3 and SHI4) showed the strongest discrimination among the evaluated within-site contrasts. Variance partitioning and Random Forest regression, which describe the internal structure of the indices, attributed the largest unique variance fraction (up to 50%) and share of importance (up to 63.1%) to biological indicators in the PCA-based indices. In an index-independent leave-one-site-out classification, the no-tillage vs. pasture contrast was predicted above chance (balanced accuracy 0.648; p = 0.009), and joint permutation of the biological indicators caused the largest loss of accuracy. Biological effect sizes (mean |r| = 0.70) exceeded physical (0.55) and chemical (0.56) ones. EE-BRSC, metabolic quotient, MBC, T-BRSC, and basal respiration exhibited the highest individual effect sizes among biological indicators. Within the evaluated index frameworks, enzymatic and microbial indicators contributed substantially to the detection of within-site management contrasts in subtropical soils. Pairing activity-based indicators with efficiency ratios such as the metabolic quotient is recommended to avoid misdiagnosis of disturbance-driven responses.