| Literature DB >> 29723835 |
Yang Yang1, Yanxing Dou2, Shaoshan An3, Zhaolong Zhu2.
Abstract
Plant biomass and the root/shoot ratio (R/S) are key parameters for estimating terrestrial ecosystem carbon (C) stocks. However, how environmental driving factors (abiotic and biotic factors) modulate plant biomass and R/S has not been well investigated on the Loess Plateau. Here, we tested the impacts of abiotic and biotic driving factors on plant biomass and R/S and whether they are in accordance with optimal partitioning theory in natural grassland in this region. The results showed that above-ground biomass (AGB) and below-ground biomass (BGB) were 63.96 g·m-2 and 311.18 g·m-2, respectively, and that R/S ranged from 0.13 to 0.46, with high spatial heterogeneity. There was a strong positive linear relationship between AGB and BGB (p < 0.05) in accordance with optimal partitioning theory. A principal component analysis (PCA) indicated that the topographic properties (Slope position, Slope gradient and Altitude) were negatively correlated with the soil physical properties (Ec,Electric conductivity; BD, Bulk density; ST, Soil temperature; and SM, Soil moisture) and positively correlated with the soil chemical properties (SOC, Soil organic carbon; TN, Total nitrogen; SMBC, Soil microbial biomass carbon and SMBN, Soil microbial biomass nitrogen), while soil total phosphorus (TP) was not correlated with the soil physical properties (p > 0.05). Structural equation modeling (SEM) suggested that R/S is indirectly driven by plant properties (Height, Density, Coverage), which are determined by soil and topographic properties. However, only 5% of R/S was explained by the soil physical properties and topographic properties, suggesting that these factors had no significant effect on R/S. The data do, however, provide information for quantifying C stocks in natural grassland on the Loess Plateau. Further, ecologists should focus on mechanistic and fresh approaches to understanding the abiotic and biotic factors influencing plant biomass and R/S.Entities:
Keywords: Grassland; Loess Plateau; Plant biomass; Principal component analysis; Root/shoot ratio; Structural equation modeling
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Year: 2018 PMID: 29723835 DOI: 10.1016/j.scitotenv.2018.04.260
Source DB: PubMed Journal: Sci Total Environ ISSN: 0048-9697 Impact factor: 7.963