Belowground biomass (BGB), contributing 80% of total biomass to grassland in Tibetan Plateau, plays an important role for grassland carbon cycling. Understanding the relationships between BGB and its environment factors is crucial for grassland resources management and predicting the future influence of climate change on Tibetan grassland ecosystem. Many previous studies have investigated the relationship between BGB and its environment in Tibetan grassland, however large uncertainties still exist, and some research results are even controversial due to limited ground samplings. This study overcomes the previous sampling problem, analyzes the relationship between belowground biomass and its environmental factors based on a large scale of field survey conducted in August 2010.
Total 32 field sampling plots were selected along two transects in Tibetan plateau: the North-South transect from the Huangyuan county (36.4°N, 100.96°E), Qinghai province, across 7 latitudes southward to Bomi county(29.64°N, 96.72°E), Tibet Autonomous Region, and the East-West transect mainly located in Xigaze area, Tibet Autonomous Region, along the Yajiang Valley, starting from Saga county(29.33°N, 85.38°E) across 7 longitudes eastward to Gongbujiada county(29.69°N, 92.27°E). Statistical methods were used to analyze the relationships between the observed BGB of grassland in Tibetan Plateau and the environmental factors including observed soil moisture, annual precipitation, annual mean temperature, soil organic carbon and soil nitrogen contents.
Research results show that soil moisture is the most critical controlling factor which influences the spatial distribution of grassland BGB in Tibetan Plateau. It is positively correlated with Tibetan grassland BGB, explaining 52.76% of total variation in Tibetan grassland BGB. For these two transects, the grassland BGB is more significantly correlated with soil moisture in the East-West transect (R²=0.6744, P<0.01) than in the North-South transect (R²=0.4081, P<0.01). The connection between grassland BGB and precipitation is complex. For all Tibetan grassland plots, only 7.95% (P<0.01) of the variance in BGB can be explained by precipitation. Grassland BGB increases with increasing precipitation (R²=0.1910, P<0.01) in the East-West transect, but the correlation between the two variables is insignificant in the North-South transect. Such discrepancy between the two transects is partially due to fluctuant topography in this region, causing large differences of evaporation and runoff over a large area, and thus significant differences in grassland BGB.
The relationship between grassland BGB and temperature is weak with no significant correlation between temperature and grassland BGB in the East-West transect. Along the North-South transect, the temperature is negatively correlated with grassland BGB, and explains only 11.86% (P=0.0397) of the variation in grassland BGB.
Tibetan grassland BGB is positively correlated with surface soil organic carbon (R²=0.3094, P<0.01) and total nitrogen content (R²=0.2081, P<0.01). The positive relationship may be explained by the fact that increased below-ground biomass is related to increased amount of root litter in the soil, thus increased organic carbon and total nitrogen content in the soil. Comparison of the relationships between grassland BGB and the soil organic carbon in the two transects indicates that the correlation coefficient (R²=0.6751) and the confidence level (P<0.01) in the East-West transect are higher and more significant than those (R²=0.1445, P=0.0222) in the North-South transect. The grassland BGB is also closely related to soil total Nitrogen with the R² and confidence level in the East-West transect 0.4593 and less than 0.01, respectively, much higher and more significant than those (0.1050 and 0.0539, respectively) in the North-South transect. The reason for more significant relationships in the East-West transect is still under investigation. Overall, this study demonstrates the strong relationships between BGB of grassland in Tibetan Plateau and its environmental factors, and these relationships vary significantly over large spatial scales.