Grazing enhances soil nutrient effects: Trade‐offs between aboveground and belowground biomass in alpine grasslands of the Tibetan Plateau

Abstract

Understanding the impact of grazing patterns on grassland production is of fundamental importance for grassland conservation and management. The objective of this study is to obtain an understanding of the trade‐offs between aboveground biomass and belowground biomass, which are influenced by environmental factors in free grazing (FG) and grazing exclusion (GE) alpine grasslands on the Tibetan Plateau. We explored the relationships between the trade‐off and environmental factors using correlation analysis, a generalized additive model and a structural equation model, and then found that the key factors that determine trade‐off showed differences in FG and GE grasslands and that the final structural equation modeling result explained that 96% (path coefficient = 0.96) and 65% (path coefficient = 0.65) of the variations in the trade‐off were due to FG or GE classifications, respectively. The results demonstrated that soil organic carbon, soil carbon/soil nitrogen, and soil available nitrogen affect the trade‐off between aboveground and belowground biomass in FG grasslands more obviously than in GE grasslands. However, the effects of growing season temperature on the trade‐off were insignificant, −0.218 and −0.181 in FG and GE grasslands, respectively. FG increased the soil bulk density, which resulted in an alteration in the soil pore size distribution and a greater resistance to root penetration. In addition, FG affected the level of soil nutrition, which will affect the nitrogen mineralization of decomposition and absorption, as well as the root biomass. Consequently, this study can provide guidance to improve the quality of grassland.

Water and heat availability are drivers of the aboveground plant carbon accumulation rate in alpine grasslands on the Tibetan Plateau

“…Correlation coefficients between environment factors and CAR greater than .10 were chose as the desirable variables that Structural equation modelling (SEM), a multivariate statistical technique, was applied in our study, which includes a synthesis of factor analysis, path analysis, and maximum likelihood analysis (Grace, 2002). To test the plausibility of a hypothetical model, SEM has been widely used for selecting the appropriate variables based on statistical criteria (Sun, Ma, et al, 2018). Additionally, SEM goes beyond the traditional multivariate analysis techniques (e.g., redundancy analysis).…”

“…was measured with the molybdate colorimetric test after perchloric acid digestion (Sommers & Nelson, 1972); and soil available nitrogen (SAN) and soil available phosphorus (SAP) were measured by the alkali-hydrolysed reduction-diffusion method and the Olsen method (Sun, Ma, & Lu, 2018), respectively.…”

Nitrogen addition stimulated compensatory growth responses to clipping defoliation in a Northern Tibetan alpine meadow

“…Differences in plant responses to herbivory are the result of different factors, such as the type of plant parts removed (e.g., leaves, buds and flowers), herbivory intensity, neighborhood effects and resource availability (Peters, Cleland, Mooney, & Field, 2006;Ren et al, 2016;Sun et al, 2018). Different functional groups may respond differently to these factors (Stevens & Gowing, 2014;van Staalduinen & Anten, 2005), and a clear understanding of how these factors interact is necessary for exploring the effects of herbivory on plant communities at the functional group level and for the sustainable development of grazed or clipped ecosystems.…”

The impact of grazing on land degradation: A common problem with many driving forces

“…Last contributions published were made by Jian Sun et al (–this issue), Artur Gil et al (—this issue), Tao Chen et al (—this issue), and Kajar Köster et al (—this issue). The first one (Sun et al, —this issue) studied the influence of grazing exclusion on the trade‐off between aboveground and belowground biomass.…”

“…Last contributions published were made by Jian Sun et al (–this issue), Artur Gil et al (—this issue), Tao Chen et al (—this issue), and Kajar Köster et al (—this issue). The first one (Sun et al, —this issue) studied the influence of grazing exclusion on the trade‐off between aboveground and belowground biomass. Artur Gil et al (—this issue) analysed changes in land cover and land use extension (expressed in ha) regarding to natural pastures from 1998 to 2013 in Pico Island (Azores, Portugal) using GIS‐based methods and providing a study case from Macaronesian bioregion to the Special Issue.…”