Parallel responses of gross nitrogen mineralization rate and related functional gene abundance along subalpine secondary succession

Abstract Understanding the soil nitrogen (N) cycling during vegetation succession is critical for effective ecosystem restoration and management. However, a comprehensive view of the dynamics of both the entire N‐cycling functional microbial community and gross N mineralization/nitrification rates during secondary succession remains a key knowledge gap, limiting the optimization of restoration strategies. We investigated N‐cycling functional gene profiles using metagenomics and gross N mineralization/nitrification rates by 15 N pool dilution techniques, along a complete secondary succession chronosequence (grassland‐shrubland‐secondary forest‐primary forest). The abundance of functional genes involved in N fixation, organic N synthesis, mineralization, nitrification, dissimilatory/assimilatory nitrate reduction to nitrite and denitrification increased by 27%–98% from grassland to shrubland, then declined by 13%–80% towards primary forest. The N‐cycling microbial community composition shifted significantly along the secondary succession. Functional genes were mainly distributed in Pseudomonadota , Acidobacteriota and Verrucomicrobiota phyla. The abundance of dominant phyla and the complexity of the functional gene co‐occurrence network were highest in the shrubland stage. The trend of the soil gross N mineralization rate was parallel to that of the mineralization functional gene abundance. Soil total carbon (C)/N pools exhibited greater effects on the N‐cycling microbial community and gross N mineralization rate than labile C/N fractions. Specifically, total C/N pools altered the gross N mineralization rate by changing the abundance of key mineralization genes, that is ure A / B / C and glsA . Synthesis and applications . These findings establish a microbial mediation framework for ecosystem recovery and suggest shrubland acts as a biogeochemical catalyst accelerating N cycling. By linking soil C/N pools to microbial N‐cycling potential and key N transformation rates, we provide a mechanistic basis for optimizing ecosystem restoration strategies.