PLoS ONE (Jan 2019)

The spatio-temporal patterns of the topsoil organic carbon density and its influencing factors based on different estimation models in the grassland of Qinghai-Tibet Plateau.

  • Shiliang Liu,
  • Yongxiu Sun,
  • Yuhong Dong,
  • Haidi Zhao,
  • Shikui Dong,
  • Shuang Zhao,
  • Robert Beazley

DOI
https://doi.org/10.1371/journal.pone.0225952
Journal volume & issue
Vol. 14, no. 12
p. e0225952

Abstract

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The grassland soils of the Qinghai-Tibet Plateau (QTP) store a large amount of organic carbon because of the cold, humid climate, and topsoil organic carbon is quite sensitive to global climate changes. However, the spatio-temporal dynamics and factors that influence the soil organic carbon (SOC) on the QTP's grassland are not understood well. Moreover, there are few comparative analyses of different approaches to estimate the QTP' SOC. In this study, we estimated the storage and patterns of SOC density (SOCD) using several methods, including MODIS (moderate-resolution imaging spectroradiometer) retrieval, field data and previous empirical models (Models1-4, and soil organic matter (SOM)). And their relations with aboveground biomass, soil moisture, temperature, elevation, and soil conductivity were further explored. The results showed that SOC showed a similar variation trend in the different models, in which it decreased with increasing bulk density (BD) in the topsoil at 30 cm. For meadow and steppe grasslands, Models 1, 2, and 4 showed similar estimated values of SOCD, while Model3 had a lower value than them. SOC storage in the BD 3 and SOM methods had abnormal values, while the MODIS-NDVI, BD 1, 2, and 4 methods had similar SOC stock values for meadow and steppe grassland. Moreover, meadow grassland had a higher SOC storage than did steppe grassland, with means values of 397.9×1010 kg and 242.2×1010 kg, respectively. SOCD's spatial distribution using MODIS-NDVI method differed clearly from the empirical models, with a significant tendency for spatial variation that increased from the northwestern to southeastern regions on the QTP. Therefore, based on the values estimated and spatial variation features, the MODIS-NDVI method may be a more feasible and valid model to estimate SOC. Moreover, the mean annual SOCD values during 2000-2015 showed an increasing trend, with a higher mean value in meadow and a lower mean value in steppe. Further, SOCD was correlated significantly and positively with aboveground biomass and soil moisture, and negatively correlated with elevation and soil conductivity. Increasing temperature had negative effects on SOCD, which was consistent with the global trend. These results indicated that topsoil moisture plays a key role in SOCD spatial patterns. Our results provide valuable support for the long-term estimation of SOCD in future research on the QTP.