Above‐ and belowground biomass allocation in Tibetan grasslands

Yang, Yuanhe; Fang, Jingyun; Ji, Chengjun; Han, Wenxuan

doi:10.1111/j.1654-1103.2009.05566.x

Cited by 278 publications

(289 citation statements)

References 20 publications

(60 reference statements)

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“…Aboveground and belowground biomass are different forms to fulfill the plant function as a whole (Mokany et al 2006), which make aboveground and belowground biomass allocation a central issue in plant ecology (Yang et al 2009). Former researchers used the R/S ratio to gain a greater understanding of the relationship between aboveground and belowground biomass.…”

Section: X) and The Vegetation Characteristics (Y)mentioning

confidence: 99%

“…The influence of grazing on the plant community lies in two ways, i.e., the direct impact through diet preference and trampling of livestock on plant's survival, growth, and fecundity and the indirect one by altering the intraspecific and interspecific interactions or the water and nutrient availability (Wan et al 2010). The response of the aboveground and belowground biomass allocation to grazing, however, is unclear, because the strategies of allocation in plant under grazing are very controversial (Yang et al 2009;Gao et al 2007;An and Li 2015), which led to observation results of decreased belowground biomass (Deng et al 2014a) and also increased ones (Gao et al 2007) related to grazing.…”

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confidence: 99%

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Soil properties and species composition under different grazing intensity in an alpine meadow on the eastern Tibetan Plateau, China

Yang

Xiong

et al. 2016

Environ Monit Assess

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As the main form of land use and human disturbance of grassland, livestock grazing has great influences on the soil resources and plant communities. This study observed the variation of soil properties and community characteristics of four treatments of different grazing intensity (no grazing, UG; light grazing, LG; moderate grazing, MG; and heavy grazing, HG) in an alpine meadow of Sichuan Province on the northeastern margin of the Tibetan Plateau. The results showed that grazing increased the pH, soil bulk density (BD), and contents of total carbon (TC) and total nitrogen (TN), and the BD increased while the others decreased with the grazing intensity. At the community level, with the increase of the grazing intensity, the vegetation coverage (R 2 = 0.61, P < 0.001), mean height of community (R 2 = 0.37, P < 0.001), aboveground biomass (R 2 = 0.54, P < 0.001), litter biomass (R 2 = 0.84, P < 0.001), and percentage of aboveground biomass of palatable grasses to total biomass (R 2 = 0.74, P < 0.001) significantly decreased, while the belowground biomass (R 2 = 0.72, P < 0.001) and the root/shoot (R/S) ratio (R 2 = 0.65, P < 0.001) increased. The species richness was the greatest at LG and the total biomass at UG. With grazing, the dominant species of the plant community shifted from palatable grasses (Gramineae and Cyperaceae) to unpalatable grasses (Compositae and Ranunculaceae). Based on the results, LG may be the optimal grassland management mode to be used in the long time in the alpine meadow of the Tibetan Plateau.

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Section: X) and The Vegetation Characteristics (Y)mentioning

confidence: 99%

mentioning

confidence: 99%

Soil properties and species composition under different grazing intensity in an alpine meadow on the eastern Tibetan Plateau, China

Yang

Xiong

et al. 2016

Environ Monit Assess

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“…Furthermore, the extremely low water availability in the study region may further limit the growth of soil microbes in high elevation regions (Li and Chen, 2004;Serna-Chavez et al, 2013). In addition, the extremely low temperature and precipitation also constrain the growth of plants which is critical to maintaining soil substrate availability to soil microbes (Yang et al, 2009;Zhang et al, 2013). In TRH, NPP is known to be remarkably low above 4000 m elevation (Song et al, 2011;Wei and Wang, 2014;) where higher plants are mostly absent (Baniya, 2010;Baniya et al, 2012).…”

Section: Relationships Between Soil Microbial Biomass and Elevation Imentioning

confidence: 99%

Spatial variability of soil microbial biomass and its relationships with edaphic, vegetational and climatic factors in the Three-River Headwaters region on Qinghai-Tibetan Plateau

Shen

et al. 2015

Applied Soil Ecology

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a b s t r a c tThis study aims to investigate the level of soil microbial biomass (MB) and analyze the relationships between soil MB and edaphic, vegetational and climatic factors at high elevation sites (>3000 m). We collected soil samples from 0 to 10 cm soil depth in 259 plots at 55 sites across 6 biomes in Three-River Headwaters (TRH) region at 3280-5127 m elevation. Soil microbial biomass carbon and nitrogen (MBC and MBN) were measured with the chloroform fumigation-extraction method. Multivariate stepwise regression analyses were used to analyze the combined effects of edaphic, vegetational and climatic factors on soil MB. We found: (1) soil MBC and MBN had an average of 30.95 mmol C/kg dry soil and 5.84 mmol N/kg dry soil in TRH, respectively, and their values were found to be negatively correlated with elevation; (2) soil MB was found to be significantly different among different biomes, and this spatial variation could be explained by the levels of soil organic carbon and belowground plant biomass. Our results indicate that the MB at high elevation region might be very low, and the increasing trend of soil microbial biomass with elevation could reverse at higher elevations.

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“…LSWI, selected by us as the model driver, is a more direct proxy for moisture than LST diff , which was used in RECO but had no significant relation with the temporal dynamics of RE in our study (R 2 < 0.2, p > 0.05); in addition, land surface moisture was found to have greater influence on RE than deep soil water [20,28], which is especially instrumental in northern China's grasslands with the large number of roots distributed in the soil surface [55]. Therefore, all these drivers appear to be chosen empirically but are based on the physiological dependencies of RE, thereby ensuring reliable estimates from our model.…”

Section: Model Parameterization and Validationmentioning

confidence: 86%

A Satellite-Based Model for Simulating Ecosystem Respiration in the Tibetan and Inner Mongolian Grasslands

Ren

et al. 2018

Remote Sensing

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Abstract:It is important to accurately evaluate ecosystem respiration (RE) in the alpine grasslands of the Tibetan Plateau and the temperate grasslands of the Inner Mongolian Plateau, as it serves as a sensitivity indicator of regional and global carbon cycles. Here, we combined flux measurements taken between 2003 and 2013 from 16 grassland sites across northern China and the corresponding MODIS land surface temperature (LST), enhanced vegetation index (EVI), and land surface water index (LSWI) to build a satellite-based model to estimate RE at a regional scale. First, the dependencies of both spatial and temporal variations of RE on these biotic and climatic factors were examined explicitly. We found that plant productivity and moisture, but not temperature, can best explain the spatial pattern of RE in northern China's grasslands; while temperature plays a major role in regulating the temporal variability of RE in the alpine grasslands, and moisture is equally as important as temperature in the temperate grasslands. However, the moisture effect on RE and the explicit representation of spatial variation process are often lacking in most of the existing satellite-based RE models. On this basis, we developed a model by comprehensively considering moisture, temperature, and productivity effects on both temporal and spatial processes of RE, and then, we evaluated the model performance. Our results showed that the model well explained the observed RE in both the alpine (R 2 = 0.79, RMSE = 0.77 g C m −2 day −1 ) and temperate grasslands (R 2 = 0.75, RMSE = 0.60 g C m −2 day −1 ). The inclusion of the LSWI as the water-limiting factor substantially improved the model performance in arid and semi-arid ecosystems, and the spatialized basal respiration rate as an indicator for spatial variation largely determined the regional pattern of RE. Finally, the model accurately reproduced the seasonal and inter-annual variations and spatial variability of RE, and it avoided overestimating RE in water-limited regions compared to the popular process-based model. These findings provide a better understanding of the biotic and climatic controls over spatiotemporal patterns of RE for two typical grasslands and a new alternative up-scaling method for large-scale RE evaluation in grassland ecosystems.

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Above‐ and belowground biomass allocation in Tibetan grasslands

Cited by 278 publications

References 20 publications

Soil properties and species composition under different grazing intensity in an alpine meadow on the eastern Tibetan Plateau, China

Soil properties and species composition under different grazing intensity in an alpine meadow on the eastern Tibetan Plateau, China

Spatial variability of soil microbial biomass and its relationships with edaphic, vegetational and climatic factors in the Three-River Headwaters region on Qinghai-Tibetan Plateau

A Satellite-Based Model for Simulating Ecosystem Respiration in the Tibetan and Inner Mongolian Grasslands

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