Plant and soil’s δ15N are regulated by climate, soil nutrients, and species diversity in alpine grasslands on the northern Tibetan Plateau

Abstract Nitrogen (N) cycling is a critical pathway by which producer, consumer, and decomposer interact with each other and with environmental circumstances simultaneously. The natural abundance composition of 15 N/ 14 N in plants and soils (termed as δ 15 N plant and δ 15 N soil ), as well as the difference between them (δ 15 N soil-to-plant = δ 15 N plant  −δ 15 N soil ), is a useful tool for better understanding ecosystem N cycling. However, the drivers and mechanisms of ecosystem N cycling in alpine grasslands on the Tibetan Plateau are mostly unknown, especially across different grassland types at a regional scale. To fill this knowledge gap, we measured δ 15 N plant (200 samples of top-dominant species) and δ 15 N soil (85 samples of top-layer soils, 0–20 cm) at nine sites that represent zonal communities of alpine deserts, steppes, and meadows in North Tibet, and calculated the corresponding δ 15 N soil-to-plant . Our results showed that δ 15 N plant, δ 15 N soil, and δ 15 N soil-to-plant were significantly different among the three zonal grassland types (analysis of differences with non-parametric Kruskal Test, P 15 N plant , δ 15 N soil, and  δ 15 N soil-to-plant decreased with the increases of growing season precipitation (GSP) and habitat aridity index (Aridity), soil organic carbon (SOC) and soil total nitrogen (STN), plant species richness, Shannon diversity index, and plant community productivity, whereas increased with the increases of accumulated active temperature (AccT) and soil total phosphorus (STP) across alpine grassland types at the regional scale. Multiple linear models with analysis of covariance (ANCOVA) confirmed GSP to be the most critical driver, which alone explained most variances of δ 15 N plant (56%), δ 15 N soil (62%), and δ 15 N soil-to-plant (35%). However, structural equation modeling performed better than multiple linear modeling in predicting δ 15 N plant (76% vs. 66%) and worse in predicting δ 15 N soil (79% vs. 84%) and δ 15 N soil-to-plant (31% vs. 46%), likely due to the exclusion of collinear predictors and the removal of non-significant influencing paths. Overall, this study has highlighted the importance to uncover the complexity of climate, soil nutrients, and vegetation properties in networking to drive the different components of ecosystem N cycling in alpine grasslands on the Tibetan Plateau.