Potential gross nitrogen mineralization and its linkage with microbial respiration along a forest transect in eastern China

Abstract

Nitrogen (N) mineralization in soils generally controls biological N availability in terrestrial ecosystems. As the pivotal first step in the overall N mineralization process, gross N mineralization (GNM, defined as the production of ammonium from microbial mineralization of organic N) is inherently coupled with microbial mineralization of soil organic carbon (C) which is commonly referred to as microbial respiration (MR), and that has often been used as a proxy of C availability. However, the pattern of GNM and its underlying mechanisms at a regional scale, and its linkage with MR remain unclear. By analyzing 100 soil samples collected across different forest types along a 3800 km long north-south transect in eastern China, we simultaneously measured the potential GNM using a 15N pool dilution method and MR using a dynamic CO2 trapping technique. We conducted a structural equation model (SEM) to examine the interactive effects of climate, soil pH, microbial substrate availability, and microbial biomass on potential GNM along the forest transect. Furthermore, we conducted a non-linear regression analysis between potential GNM and MR. We found that both potential GNM and MR varied largely, from 0.55 to 16.14 mg N kg−1 soil d−1 and from 3.64 to 24.30 mg C kg−1 soil d−1, respectively, but were not significantly affected by forest type. The SEM analysis showed that 51% of the variation in potential GNM was explained, with microbial substrate availability being the most important influencing factor. There was a positive non-linear relationship between potential GNM and MR (R2 = 0.52, P < 0.0001). Notably, MR alone exerted a comparable role in explaining the variation in potential GNM compared to the interactive effects between multiple factors used in the SEM. Our findings confirm the dominant control of C availability to microbes on potential GNM, and necessitate the incorporation of MR for better modeling GNM in forest soils.