The interaction between poisonous plants and soil quality in response to grassland degradation in the alpine region of the Qinghai-Tibetan Plateau

Plant Ecology ◽  
2014 ◽  
Vol 215 (8) ◽  
pp. 809-819 ◽  
Author(s):  
Yuan-Yuan Li ◽  
Shi-Kui Dong ◽  
Shiliang Liu ◽  
Xuexia Wang ◽  
Lu Wen ◽  
...  
2012 ◽  
Vol 76 (6) ◽  
pp. 2256-2264 ◽  
Author(s):  
S. K. Dong ◽  
L. Wen ◽  
Y. Y. Li ◽  
X. X. Wang ◽  
L. Zhu ◽  
...  

2018 ◽  
Vol 10 (10) ◽  
pp. 3477 ◽  
Author(s):  
Fuqiang Dai ◽  
Zhiqiang Lv ◽  
Gangcai Liu

Ecologically fragile cropland soils and intensive agricultural production are characteristic of the valley area of the Tibetan Plateau. A systematic assessment of soil quality is necessary and important for improving sustainable cropland management in this area. This study aims to establish a minimum data set (MDS) for soil quality assessment and generate an integrated soil quality index for sustainable cropland management in the Tibetan Plateau. Soil samples were collected from the 0–20 cm depths of agricultural land in the middle and lower reaches of the Lhasa River. These samples were analyzed by routine laboratory methods. Significant differences were identified via statistical test between different soil types and land use types for each soil property. Principal component analysis was used to define a MDS of indicators that determine soil quality. Consequently, effective porosity, pH, total organic C, total N, available P, and catalase were identified as the final MDS. The soil quality index was obtained by the fuzzy-set membership function and the linear weighted additive method. The soil quality index differed significantly between the soil types and land use types. The soil quality can be ranked based on their indices in the following order: 1. Grain land with meadow soils, 2. Grain land with steppe soils, 3. Greenhouse vegetable land with fluvo-aquic soils, 4. Grain land with fluvo-aquic soils. The soils with higher soil quality indices exhibited better soil structure, higher nutrient contents, and superior resistance to water and nutrient loss. While the intensive tillage practices associated with vegetable production could reduce the values for effective porosity, pH and catalase, the application of appropriate fertilizers increased the values for total organic C, total N and available P. Therefore, the MDS method is an effective and useful tool to identify the key soil properties for assessing soil quality, and provides guidance on adaptive cropland management to a variety of soil types and land use types.


2010 ◽  
Vol 2 ◽  
pp. 1966-1969 ◽  
Author(s):  
L. Wen ◽  
S.K. Dong ◽  
L. Zhu ◽  
X.Y. Li ◽  
J.J. Shi ◽  
...  

2012 ◽  
Vol 49 ◽  
pp. 77-83 ◽  
Author(s):  
Yuan-yuan Li ◽  
Shi-kui Dong ◽  
Lu Wen ◽  
Xue-xia Wang ◽  
Yu Wu

PLoS ONE ◽  
2013 ◽  
Vol 8 (3) ◽  
pp. e58432 ◽  
Author(s):  
Lu Wen ◽  
Shikui Dong ◽  
Yuanyuan Li ◽  
Xiaoyan Li ◽  
Jianjun Shi ◽  
...  

2020 ◽  
Author(s):  
Wangya Han ◽  
Xukun Su ◽  
Guohua Liu

<p>Grassland degradation is a global ecological problem, and grassland on the Qinghai-Tibetan Plateau (QTP) is suffering serious and continuous degradation. Due to the vulnerability of grassland ecosystem on the QTP and its sensitivity to global climate change, alpine grassland degradation needs more attention. In this study, we extracted 7 visible vegetation indices by using an unmanned aerial vehicle (UAV) with visible light sensors. We used random forest model and stepwise multiple regression establishing the relationship between visible vegetation indices and filed degradation index to assess alpine meadow degradation. The result showed that ExG (Excess Green Index) was effective in the simulation with an R<sup>2</sup> value of 0.53. The degradation distributions of 50 field sites were obtained at 10cm spatial resolution. This study with visible vegetation indices by UAV provides an effective approach for monitoring grassland degradation at low altitude. The high resolution contributes to more refined grassland management.</p>


2020 ◽  
Author(s):  
Zuonan Cao ◽  
Peter Kühn ◽  
Thomas Scholten

<p>The Tibetan Plateau is the third-largest glaciated area of the world and is one of the most sensitive regions due to climate warming, such as fast-melting permafrost, dust blow and overgrazing in recent decades. In the past 50 years, the warming rate on the Tibetan Plateau is higher than the global average warming rate with 0.40 ± 0.05 °C per decade. The climate warming is most distinct in the northeastern Tibetan Plateau, implying increasing air and surface temperatures as well as duration and depth of thawing. The main ecological consequences are a disturbed vegetation cover of the surface and a depletion of nutrient-rich topsoils (Baumann et al., 2009, 2014) coupled with an increase of greenhouse gas emissions, mainly CO<sub>2</sub> (Bosch et al., 2017). Due to the extreme environmental conditions resulting from the intense and rapid tectonic uplift, highly adaptive and sensitive ecosystem have developed, and the Plateau is considered to be a key area for the environmental evolution of Earth on regional and global scales, which is particularly sensitive to global warming (Jin et al., 2007; Qiu, 2008). Climate warming and land-use change can reduce soil organic carbon (SOC) stocks as well as soil nitrogen (N) and phosphorus (P) contents and soil quality. Many species showed their distributions by climate-driven shifts towards higher elevation. In Tibetan Plateau, however, the elevational variations of the alpine grassland are rare (Huang et al., 2018) and it is largely unknown how the grass line will respond to global warming and whether soils play a major role. With this research, the hypothesis is tested that soil quality, given by SOC, N and P stocks and content, is a driving factor for the position and structure of the grass line and that soil quality is one of the major controls of biodiversity and biomass production in high-mountain grassland ecosystems.</p><p>A Fourier transformation near and mid-infrared spectroscopy (FT-NMIRS) should be used to measure soil P fractions rapid and for large numbers of soil samples, and analyze environmental factors, including temperature, precipitation, soil development, soil fertility, and the ability of plants to adapt to the environmental impact of climate using FT-NMIRS.</p><p>We explored first near-infrared spectroscopy (NIRS) in soils from grassland on the Tibetan Plateau, northwestern China and extracted P fractions of 196 samples from Haibei Alpine Meadow Ecosystem Research Station, Chinese Academy of Sciences, at four depths increments (0-10 cm 10-20 cm 20-40 cm and 40-70 cm) with different pre-nutrient additions of nitrogen (N) an P. The fractionation data were correlated with the corresponding NIRS soil spectra and showed significant differences for depth increments and fertilizer amendments. The R<sup>2</sup> of NIRS calibrations to predict P in traditional Hedley fractions ranged between 0.12 and 0.90. The model prediction quality was higher for organic than for inorganic P fractions and changed with depth and fertilizer amendment. The results indicate that using NIRS to predict the P fractions can be a promising approach compared with traditional Hedley fractionation for soils in alpine grasslands on the Tibetan Plateau.</p>


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