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 15N/14N in plants and soils (termed as δ15Nplant and δ15Nsoil), as well as the difference between them (δ15Nsoil-to-plant = δ15Nplant−δ15Nsoil), 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 δ15Nplant (200 samples of top-dominant species) and δ15Nsoil (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 δ15Nsoil-to-plant. Our results showed that δ15Nplant, δ15Nsoil, and δ15Nsoil-to-plant were significantly different among the three zonal grassland types (analysis of differences with non-parametric Kruskal Test, P < 0.05), with the lowest values in meadows and the highest values in deserts. Regression analyses showed that the δ15Nplant, δ15Nsoil, and δ15Nsoil-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 δ15Nplant (56%), δ15Nsoil (62%), and δ15Nsoil-to-plant (35%). However, structural equation modeling performed better than multiple linear modeling in predicting δ15Nplant (76% vs. 66%) and worse in predicting δ15Nsoil (79% vs. 84%) and δ15Nsoil-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.

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

Tarolli P.;
2019

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 15N/14N in plants and soils (termed as δ15Nplant and δ15Nsoil), as well as the difference between them (δ15Nsoil-to-plant = δ15Nplant−δ15Nsoil), 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 δ15Nplant (200 samples of top-dominant species) and δ15Nsoil (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 δ15Nsoil-to-plant. Our results showed that δ15Nplant, δ15Nsoil, and δ15Nsoil-to-plant were significantly different among the three zonal grassland types (analysis of differences with non-parametric Kruskal Test, P < 0.05), with the lowest values in meadows and the highest values in deserts. Regression analyses showed that the δ15Nplant, δ15Nsoil, and δ15Nsoil-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 δ15Nplant (56%), δ15Nsoil (62%), and δ15Nsoil-to-plant (35%). However, structural equation modeling performed better than multiple linear modeling in predicting δ15Nplant (76% vs. 66%) and worse in predicting δ15Nsoil (79% vs. 84%) and δ15Nsoil-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.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3310538
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