Global biogeography of the soil carbon/nitrogen imbalance in topsoil

The mismatch between microorganisms' soil carbon (C)-nitrogen (N) stoichiometry and the C/N resource imbalance plays an important role in global nutrient biogeochemistry. The biogeographic patterns of the soil C/N imbalance hold fundamental importance for unravelling the mechanisms underlying soil nutrient cycling. The data for this research came from 793 sampling locations across 13 major biomes. These sampling locations included data on dissolved organic C, dissolved organic N, microbial biomass C, and microbial biomass N in topsoil. To quantify the C/N imbalance, the stoichiometric ratios of resources were divided by the stoichiometric ratios of microbial biomass. The soil C/N imbalance exhibited significant biogeographic patterns across latitude and environmental gradients, including meteorological parameters, plant productivity, and edaphic properties, as confirmed by analyses with the Mantel test. At the biome level, tropical and subtropical forests showed the highest C/N imbalance at 7.2 ± 0.80 and 6.43 ± 0.23, respectively, while tundra and boreal forests showed the lowest C/N imbalance at 0.64 ± 0.19 and 0.9 ± 0.16, respectively. The generalised linear model, which incorporated meteorological parameters, plant productivity, and edaphic properties, constituted 77 % of the variation in the soil C/N imbalance. It identified the complex interplay of environmental factors as the most significant contributors to the soil C/N imbalance. Moreover, the soil C/N imbalance was mainly controlled by soil clay and sand content, soil organic C, total N, mean annual temperature, and net primary productivity, as confirmed by analyses with a structural equation model. Our findings enhance our understanding of the global distribution of the soil C/N imbalance, and facilitated the incorporation of C and N stoichiometry of microorganisms and their resources into earth system models. Furthermore, the estimates of the soil C/N imbalance both at the biome level and at the global level provide valuable data for parameterising and benchmarking models of soil nutrient cycling under a changing climate.