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The Qualità Biologica del Suolo (QBS-ar) index provides a rapid, low-cost measure of soil biological quality by assigning arthropods in morphotaxonomic groups named biological forms. Although widely used, its low taxonomic resolution and reliance on expert-defined scores limits its sensitivity to subtle management effects. We therefore evaluated whether DNA metabarcoding can complement and refine QBS-based assessments by analysing soil microarthropod communities across seven agricultural treatments differing in tillage intensity and production system. Using COI metabarcoding, we compared α- and β-diversity patterns between molecular and QBS datasets, evaluated different QBS index variants in relation to DNA amplicon sequence variant (ASV) richness, and explored potential for a preliminary DNA-derived index based on QBS-like trait scoring. DNA metabarcoding resolved clear community separation among production systems and treatments that the QBS only partially detected and revealed indicator taxa characteristic of reduced-disturbance and organic management. The QBS indices distinguished major production systems but were less responsive to within-system variation. Correlations between ASV richness and QBS-ar varied among production systems, indicating context-dependent index performance. The experimental DNA-derived QBS index (QBS-DNA) retained a QBS-like trait signal, showing positive treatment-mean correlations with morphology-based QBS-ar and QBS-arBF, but it did not significantly distinguish treatments. These results support QBS-DNA as a proof-of-concept framework for translating trait-based soil-quality indicators into molecular biodiversity assessments. As molecular tools and trait databases expand, metabarcoding enables the development of next-generation soil biodiversity indicators based on explicit, species-level functional traits, moving beyond the constraints of classical QBS formulations while retaining their ecological intent.
Naglič et al. (2026) studied this question.