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Additional file 1: Appendix 1. PBSA chemical and physical properties. Figure S1. Rarefaction curves of archaea (a), bacteria (b), and fungi (c). Figure S2. Links between soil pH and microbial richness: a) Soil pH values of initial soil, initial-N soil, control S, control SN, and soils in PS, and PSN treatment on 90 days. Correlations between soil pH and richness of archaea (b), bacteria (c) and fungi (d). Figure S3. Factors explain variations in microbial community composition: percent explainable variations of archaeal (a), bacterial (b), and fungal (c) communities explained by PBSA addition, N fertilization, soil pH, and combinations of these factors. Total variations of archaeal, bacterial, and fungal communities explained by PBSA addition, N fertilization, soil pH, and combinations of these factors are 13, 23 and 28%, respectively. Table S4. Comparisons between microbial community compositions of (i) PBSA and soil counterparts and (ii) soils of different treatments and (iii) control soils (Control S and Control SN) and PBSA (PS and PSN treatments) using analysis of similarities (ANOSIM) and non-parametric multivariate analysis of variance (NPMANOVA).

The relationship between biodiversity and ecosystem functioning (BEF) is a central issue in soil and microbial ecology. To date, most belowground BEF studies focus on the diversity of microbes analyzed by barcoding on total DNA, which targets both active and inactive microbes. This approach creates a bias as it mixes the part of the microbiome currently steering processes that provide actual ecosystem functions with the part not directly involved. Using experimental extensive grasslands under current and future climate, we used the bromodeoxyuridine (BrdU) immunocapture technique combined with pair-end Illumina sequencing to characterize both total and active microbiomes (including both bacteria and fungi) in the rhizosphere of Trifolium pratense. Rhizosphere function was assessed by measuring the activity of three microbial extracellular enzymes (β-glucosidase, N-acetyl-glucosaminidase, and acid phosphatase), which play central roles in the C, N, and P acquisition. We showed that the richness of overall and specific functional groups of active microbes in rhizosphere soil significantly correlated with the measured enzyme activities, while total microbial richness did not. Active microbes of the rhizosphere represented 42.8 and 32.1% of the total bacterial and fungal taxa, respectively, and were taxonomically and functionally diverse. Nitrogen fixing bacteria were highly active in this system with 71% of the total operational taxonomic units (OTUs) assigned to this group detected as active. We found the total and active microbiomes to display different responses to variations in soil physicochemical factors in the grassland, but with some degree of resistance to a manipulation mimicking future climate. Our findings provide critical insights into the role of active microbes in defining soil ecosystem functions in a grassland ecosystem. We demonstrate that the relationship between biodiversity-ecosystem functioning in soil may be stronger than previously thought.